Compendium of Crop Genome Designing for Nutraceuticals 9811941688, 9789811941689

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Chittaranjan Kole Editor

Compendium of Crop Genome Designing for Nutraceuticals

Compendium of Crop Genome Designing for Nutraceuticals

Chittaranjan Kole Editor

Compendium of Crop Genome Designing for Nutraceuticals With 153 Figures and 123 Tables

Editor Chittaranjan Kole Prof. Chittaranjan Kole Foundation for Science and Society Kolkata, India

ISBN 978-981-19-4168-9 ISBN 978-981-19-4169-6 (eBook) https://doi.org/10.1007/978-981-19-4169-6 © Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Paper in this product is recyclable.

Dedication

Dedicated to My parents, Late Bibhuti Bhushan Kole and Late Bhanumati Kole

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Acknowledgement

Special Acknowledgement to Phullara Kole For her outstanding assistance in editing this compendium

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Preface

The crop plants cater not only to our basic F5 (food, feed, fiber, fuel, and furniture) needs but also provide a number of nutraceuticals with potential nutritional, safety, and therapeutic attributes. Many crop plants provide an array of minerals, for example, Ca, Mg, K, Na, P, Cr, Cu, Fe, Mn, Mo, Ni, Se, and Zn; vitamins, for example, A, B-series, C, E and K; and antioxidant-rich bioactive phytochemicals, including Carotenoids, Phytosterols, Limonoids, Polyphenols, Glucosinolates, phytoestrogen, Terpenoids, Fibers, Polysachharides, and Saponins. Increasing incidences of chronic diseases such as cancer, diabetes and HIV, and malnutrition necessitate global attention to health and nutrition security with equal emphasis on food security. Stupendous amount of researches on biochemical, physiological, and genetic mechanisms underlying the biosynthesis of the health and nutrition related nutraceuticals and precise breeding strategies for augmentation of their content and amelioration of their quality in crop plants are underway all over the world under all commodity categories of crops including cereals and millets, oilseeds, grain legumes, fruits and nuts, and vegetables. This major review work entitled, “Compendium of Crop Genome Designing for Nutraceuticals,” comprises five sections dedicated to these five commodity groups and presents enumeration on the concepts, strategies, tools, and techniques of nutraceutomics. These sections include 50 chapters devoted to even number of major crop plants. These chapters present deliberations on the biochemistry and medicinal properties of the nutraceuticals contained; genetic variation of their contents; classical genetics of and breeding for their quantitative and qualitative improvement; tissue culture and genetic engineering for augmentation of productivity and quality; and sources of genes underlying their biosynthesis. They also include comprehensive enumeration on genetic mapping of the genes and QTLs controlling the contents and profile of the nutraceuticals and molecular breeding for their further improvement through marker assisted selection and backcross breeding tools. Prospects of post-genomic precise and targeted breeding strategies including genome-wide association mapping, genomic selection, allele mining and genome editing are also discussed. This compendium would fill the gap in academia, and research and development wings of the private sector industries and will also facilitate understanding of the policy making agencies and people in the socio-economic domain, and benefit students, teachers, scientists, policy makers and sponsoring agencies involved in an array of subjects relevant to ix

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Preface

crop sciences, specifically genetics, genomics, tissue culture, genetic engineering, molecular breeding, genomics-assisted breeding, gene editing, bioinformatics, biochemistry, physiology, pathology, entomology, pharmacognosy, and IPR. I express my thanks to the authors of the chapters of this compendium for their useful contributions and sincere cooperation. I am also grateful to the staff of the publisher for their assistance since inception till completion of editing this compendium. Kolkata, India November 2023

Chittaranjan Kole

Contents

Volume 1 Part I

Cereal Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Redesigning Rice as a Promising Nutraceutical Functional Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. M. Sundaram, D. Sanjeeva Rao, P. Sanghamitra, S. Gandhadmath Spoorti, J. Veerendra, N. Siromani, G. Niharika, R. Ananthan, J. Aravind Kumar, P. Raghuveer Rao, S. Malathi, S. K. Mangrauthia, M. Balram, J. Ali, and C. N. Neeraja Wheat Nutraceutomics: Breeding, Genomics, Biotechnology, and Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Velu Govindan, Om Prakash Gupta, Sunil Kumar, Chandra Nath Mishra, and Gyanendra Singh Maize Nutraceutomics: Genomics, Biotechnology, and Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deepti B. Sagare, Prashant Shetti, Shrikant Yankanchi, Sai Rekha Kadirimangalam, Rachana Baguda, Fan Xingming, Jun Fan, Shweta Singh, Rani Asaram Jadhav, M. A. Ashrutha, and Kumari Aditi Barley: From Molecular Basis of Quality to Advanced Genomics-Based Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Franca Finocchiaro, Valeria Terzi, and Stefano Delbono Oats: Nutritional Uniqueness and Breeding of a Healthy Superfood . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Caterina Morcia, Franca Finocchiaro, Stefano Delbono, Roberta Ghizzoni, Fabio Reggiani, Paola Carnevali, Giorgio Tumino, Ilaria Carrara, and Valeria Terzi Genetic Improvement of Sorghum: Crop Genome Designing for Nutraceuticals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. T. Labuschagne and L. Elkonin

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Contents

Breeding Efforts on Grain Micronutrient Enhancement in Pearl Millet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mahalingam Govindaraj and Mahesh Pujar Nutraceutomics of Foxtail Millet (Setaria italica L.): Insights . . . . . . . . Jyothish Madambikattil Sasi, Paramananda Barman, and Charu Lata

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Genetic and Genomic Resources for Harnessing the Health-Related Genes in Finger Millet . . . . . . . . . . . . . . . . . . . . . . . . . . S. Antony Ceasar and B. Kalyan Babu

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Proso Millet Nutraceutomics for Human Health and Nutritional Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Rituraj Khound, Ramesh Kanna Mathivanan, and Dipak K. Santra

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Part II

Oilseed Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Nutraceuticals in Soybean: Biosynthesis, Advanced Genetic Research, and Usage in Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maria Stefanie Dwiyanti and Maria D. P. T. Gunawan-Puteri

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Nutraceutical Potential of Rapeseed: Breeding and Biotechnological Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mehak Gupta and Gurpreet Kaur

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Nutragenomic Approaches in Sunflower: Genetic Improvement in Oil Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Manivannan Narayana and Ameena Premnath

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Next-Generation Breeding for Nutritional Traits in Peanut Priya Shah, Manish Pandey, Spurthi N. Nayak, Charles Chen, Sandip Bera, Chittaranjan Kole, and Naveen Puppala

Genomic Designing for Nutraceuticals in Brassica juncea: Advances and Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Aakanksha, Bal Govind Yadav, Shikha Mathur, Satish Kumar Yadava, and Nirala Ramchiary Nutraceutomics of the Ancient Oilseed Crop Sesame (Sesamum indicum L.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yinghui Duan, Hongmei Miao, Ming Ju, Chun Li, Hengchun Cao, and Haiyang Zhang Nutraceutical Usages and Nutrigenomics of Castor . . . . . . . . . . . . . . . . Jasminkumar Kheni and Rukam S. Tomar Genetic Enhancement of Nutraceuticals in Linseed: Breeding and Molecular Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Manimurugan, A. Zanwar, and M. Sujatha

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Increasing Nutraceutical and Pharmaceutical Applications of Safflower: Genetic and Genomic Approaches . . . . . . . . . . . . . . . . . . Megha Sharma, Varun Bhardwaj, Poulami Goswami, Anmol Kalra, Kadirvel Palchamy, Arun Jagannath, and Shailendra Goel Oil Palm: Genome Designing for Improved Nutritional Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Maizura Ithnin, Abrizah Othman, Noor Idayu Mhd Tahir, Kalyana Babu Banisetti, Mohd Amin Abd Halim, and M. K. Rajesh Part III

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Pulse Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Nutritional Traits of Beans (Phaseolus vulgaris): Nutraceutical Characterization and Genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. W. Blair, H. Li, L. Nekkalapudi, V. Becerra, and M. Paredes

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Genetic Improvement of Nutraceutical Traits in Chickpea (Cicer arietinum L.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Alok Das, Biswajit Mondol, Prateek Singh, and Shallu Thakur

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Nutrient-Dense Pea (Pisum sativum L.): Genetics and Genomics-Mediated Developments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. K. Parihar, G. P. Dixit, Amrit Lamichaney, Arpita Das, Kuldeep Tripathi, Neetu Singh, Aravind Konda, DebJyoti Sen Gupta, Surendra Barpete, Sanjeev Gupta, and Abhimanyu Sarker Breeding Cowpea: A Nutraceutical Option for Future Global Food and Nutritional Security . . . . . . . . . . . . . . . . . . . . . . . . . . Avi Raizada, Dhanasekar Punniyamoorthy, Souframanien Jegadeesan, Tesfaye Walle Mekonnen, and Penna Suprasanna Lentils (Lens culinaris Medik): Nutritional Profile and Biofortification Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Debjyoti Sen Gupta, Jitendra Kumar, Surendra Barpate, A. K. Parihar, Anup Chandra, Anirban Roy, and Ivica Djalovic Grain Micronutrients in Pigeonpea: Genetic Improvement Using Modern Breeding Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . Aloleca Mukherjee, Anjan Hazra, Dwaipayan Sinha, Prathyusha Cheguri, Shruthi H B, Sanatan Ghosh, Naresh Bomma, Rituparna Kundu Chaudhuri, Prakash I. Gangashetty, and Dipankar Chakraborti Nutrigenomics of Mungbean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Manu, Jayashree Ugalat, P. R. Saabale, Revanappa Biradar, Suma C. Mogali, and Shivanand Koti

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Contents

Rice Bean: A Neglected and Underutilized Food Crop Emerges as a Repertory of Micronutrients Essential for Sustainable Food and Nutritional Security . . . . . . . . . . . . . . . . . . . . . . Tanushri Kaul, Jyotsna Bharti, Rachana Verma, Puja Chakraborty, Arulprakash Thangaraj, Mamta Nehra, Sonia Khan Sony, Khaled Fathy, Rashmi Kaul, and Murugesh Easwaran

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Volume 2 Part IV

Fruit Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Improvement of Nutraceutical Traits of Banana: New Breeding Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jaindra Nath Tripathi, Valentine Otang Ntui, Mathiazhagan Malarvizhi, Samwel Muiruri, Kundapura V. Ravishankar, and Leena Tripathi

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Integrating Omic Tools to Design Nutraceutically Rich Citrus . . . . . . . Bidisha Mondal

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Watermelon: Advances in Genetics of Fruit Qualitative Traits . . . . . . . Sudip Kumar Dutta, Padma Nimmakayala, and Umesh K. Reddy

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Grapes: A Crop with High Nutraceuticals Genetic Diversity . . . . . . . . Javier Tello, Loredana Moffa, Yolanda Ferradás, Marica Gasparro, Walter Chitarra, Rosa Anna Milella, Luca Nerva, and Stefania Savoi

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Mango Nutrigenomics for Nutritional Security . . . . . . . . . . . . . . . . . . . Nimisha Sharma, Anil Kumar Dubey, and Ramya Ravishankar

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Apples: Role of Nutraceutical Compounds Schuyler S. Korban

Genetic Enhancement of Nutraceuticals in Papaya (Carica papaya L.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1001 C. Vasugi, K. V. Ravishankar, Ajay Kumar, and K. Poornima Avocado: Agricultural Importance and Nutraceutical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1033 A. Talavera, J. J. Gonzalez-Fernandez, A. Carrasco-Pancorbo, L. Olmo-García, and J. I. Hormaza Melon Nutraceutomics and Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . 1053 Prashant Kaushik Guava: A Nutraceutical-Rich Underutilized Fruit Crop . . . . . . . . . . . . 1069 Malarvizhi Mathiazhagan, Vasugi Chinnaiyan, and Kundapura V. Ravishankar

Contents

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Date Palm: Genomic Designing for Improved Nutritional Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1097 Joseph Kadanthottu Sebastian, Praveen Nagella, Epsita Mukherjee, Vijayalaxmi S. Dandin, Poornananda M. Naik, S. Mohan Jain, Jameel M. Al-Khayri, and Dennis V. Johnson Current Advances in Health-Related Compounds in Sweet Cherry (Prunus avium L.) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1161 Alejandro Calle, Ana Wünsch, Jose Quero-García, and Manuel Joaquín Serradilla Part V

Vegetable Crops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1181

Potato Nutraceuticals: Genomics and Biotechnology for Bio-fortification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1183 Teresa Docimo, Nunzia Scotti, Rachele Tamburino, Clizia Villano, Domenico Carputo, and Vincenzo D’Amelia Tomato: Genetics, Genomics, and Breeding of Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1217 Ibrahim Çelik, Nergiz Gürbüz Çolak, Sami Doğanlar, and Anne Frary Genome Designing for Nutritional Quality in Vegetable Brassicas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1269 Pritam Kalia, Shrawan Singh, Raman Selvakumar, Manisha Mangal, and T. K. Nagarathna Health-Enhancing Compounds in Carrots: Genetics, Genomics, and Molecular Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1365 Pablo F. Cavagnaro, Frank Dunemann, Raman Selvakumar, Massimo Iorizzo, and Philipp W. Simon Metabolomics and Cytoplasmic Genomics of Allium . . . . . . . . . . . . . . . 1437 Mostafa Abdelrahman, Rawan Rabie, Magdi El-sayed, and Masayoshi Shigyo Eggplant (Solanum melongena L.) Nutritional and Health Promoting Phytochemicals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1463 Partha Saha, Jugpreet Singh, N. Bhanushree, S. M. Harisha, Bhoopal Singh Tomar, and Bala Rathinasabapathi Genome Designing for Nutritional Quality in Amaranthus . . . . . . . . . . 1495 Isadora Louise Alves da Costa Ribeiro Quintans, Valesca Pandolfi, Thais Gaudencio do Rêgo, José Ribamar Costa Ferreira Neto, Thais A. R. Ramos, and Dinesh Adhikary Cucumber (Cucumis sativus L.): Genetic Improvement for Nutraceutical Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1527 Ashutosh Rai, Vishal Chugh, and Sudhakar Pandey

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Sweetpotato: Nutritional Constituents and Genetic Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1545 Guilherme Silva Pereira, Victor Acheampong Amankwaah, Mercy Ketavi, Bonny Michael Oloka, Aswathy G. H. Nair, Ana Paula da Mata, Carla Cristina da Silva, Iara Gonçalves dos Santos, João Ricardo Bachega Feijó Rosa, and Hugo Campos Designing Dioscorea Genomes for Improved Nutritional and Pharmaceutical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1589 Ranjana Bhattacharjee Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1609

About the Editor

Prof. Chittaranjan Kole is an internationally renowned academician with a spectacular professional career of about 40 years!. His pioneering scientific contributions, specifically in the fields of plant genomics and biotechnology, have been globally appreciated. Prof. Kole has developed a number of original concepts and strategies, which have contributed enormously to science and benefited the national as well as global society. His scholarly publications include 150-plus research articles and over 180 books with globallyreputed publishers. Prof. Kole’s academic contributions have been profusely appreciated by seven Nobel Laureates including Profs. Norman E. Borlaug, Arthur Kornberg, Werner Arber, Phillip A. Sharp, Günter Blobel, Leland H. Hartwell, and Roger D. Kornberg. His scientific achievements have been honored with several awards, fellowships and recognitions including the “Outstanding Crop Scientist Award” conferred by the International Crop Science Society in recognition of his “life-time and original contributions in the field of crop science.” Prof. Kole worked as a researcher, faculty member and administrator in a large number of premier institutions and universities in India and abroad. In India, he worked across all academic positions from an Assistant Professor to Vice Chancellor in three premier universities including Orissa University of Agriculture and Technology, Sam Higginbottom University of Agriculture, Technology and Sciences, and Bidhan Chandra Krishi Viswavidyalaya. He also worked in Indo-Russian Center for Biotechnology as its First

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About the Editor

Project Coordinator. In abroad, he worked in the USSR Academy of Sciences, erstwhile USSR, as a PostDoctorate Scholar; University of Wisconsin, USA as an Overseas Research Associate; The Pennsylvania State University, USA, and Clemson University, USA, as a Visiting Professor; and Institute of Nutraceutical Research at Clemson University as Director of Research. Prof. Kole is recognized as a visionary science leader in the global arena. He is the Founding President of three international organizations including the Genome India International, International Climate Resilient Crop Genomics Consortium, and International Phytomedomics and Nutriomics Consortium. In recognition of his international leadership quality, the Food and Agriculture Organization invited Prof. Kole to act as the Leader of the Climate Change theme for the FAO International Symposium on “The Role of Agricultural Biotechnologies in Sustainable Food Systems and Nutrition” in 2016. He organized and chaired many prestigious international workshops, chaired several technical sessions; and delivered innumerable invited plenary lectures and keynote addresses in many international scientific meetings. Prof. M. S. Swaminathan, World Food Prize Laureate, once wrote to Prof. Kole that “You are a role model for all of us.” while Nobel Laureate in Chemistry Prof. Roger D. Kornberg wrote to the Honorable Prime Minister of India about Prof. Kole that “your country will be increasingly benefitted by utilizing his comprehensive knowledge and visionary ideas on science, education and agriculture.” Above all, Nobel Laureate in Peace, Dr. Norman E. Borlaug, the Father of Green Revolution, wrote to Prof. Kole that “May all Ph.D.s, future scientists and students that are devoted to agriculture get an inspiration as it refers to your work.”

Contributors

Thais A. R. Ramos Universidade Federal da Paraíba, João Pessoa, Brazil Aakanksha Department of Genetics, University of Delhi South Campus, New Delhi, India Mohd Amin Abd Halim Malaysian Palm Oil Board, Persiaran Institusi, Bandar Baru Bangi, Kajang, Malaysia Mostafa Abdelrahman Aswan University Faculty of Science, Aswan, Egypt Dinesh Adhikary Department of Agricultural, Food & Nutritional Sciences, University of Alberta, Edmonton, AB, Canada Kumari Aditi Kansas State University, Manhattan, KS, USA J. Ali Professor Jayashankar Telangana State Agricultural University, Hyderabad, India Jameel M. Al-Khayri Department of Agricultural Biotechnology, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, Saudi Arabia Victor Acheampong Amankwaah Biotechnology, Seed and Post-Harvest Division, Crops Research Institute, Kumasi, Ghana R. Ananthan National Institute of Nutrition, Hyderabad, India J. Aravind Kumar ICAR-Indian Institute of Rice Research, Hyderabad, India M. A. Ashrutha Hytech seeds India Pvt. Ltd, Hyderabad, India Shruthi H B Pigeonpea Improvement Program, International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India B. Kalyan Babu ICAR-Indian Institute of Oil Palm Research, Pedavegi, Andhra Pradesh, India Rachana Baguda Professor Jayashankar Telangana State Agricultural University, Hyderabad, India M. Balram International Rice Research Institute, Los Banos, Philippines xix

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Contributors

Kalyana Babu Banisetti ICAR-Indian Institute of Oil Palm Research, Eluru, India Paramananda Barman Inclusive Health and Traditional Knowledge Studies Division, CSIR-National Institute of Science Communication and Policy Research, New Delhi, India Surendra Barpete Scientist, Food Legumes Research Platform (FLRP), International Centre for Agricultural Research in the Dry Areas (ICARDA), Sehore, Madhya Pradesh, India V. Becerra INIA - Instituto de Investigaciones Agropecuarias, Chillán, Chile Sandip Bera ICAR-Directorate of Groundnut Research, Junagadh, Gujarat, India N. Bhanushree Division of Vegetable Science, ICAR–Indian Agricultural Research Institute, New Delhi, India Varun Bhardwaj Department of Botany, University of Delhi, Delhi, India Jyotsna Bharti Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Ranjana Bhattacharjee International Institute of Tropical Agriculture, Ibadan, Nigeria Revanappa Biradar ICAR-Indian Institute of Pulses Research, Regional Station, Dharwad, Karnataka, India M. W. Blair TSU – Tennessee State University, Department of Agricultural and Environmental Sciences, Nashville, TN, USA Naresh Bomma Pigeonpea Improvement Program, International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India Alejandro Calle Plant and Environmental Sciences, Clemson University, Clemson, SC, USA Hugo Campos International Potato Center, Lima, Peru Hengchun Cao Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, China Henan Key Laboratory of Specific Oilseed Crops Genomics (Henan Sesame Research Center, Henan Academy of Agricultural Sciences), Zhengzhou, Henan, China Henan International Joint Laboratory of Specific Oilseed Crops Improvement, Zhengzhou, Henan, China Paola Carnevali Barilla S.p.A, Parma, PR, Italy Domenico Carputo Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy

Contributors

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Ilaria Carrara Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parma, PR, Italy A. Carrasco-Pancorbo Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Granada, Spain Pablo F. Cavagnaro National Scientific and Technical Research Council (CONICET), National Institute of Agricultural Technology (INTA) E.E.A. La Consulta, La Consulta CC8, San Carlos, Mendoza, Argentina S. Antony Ceasar Division of Plant Molecular Biology and Biotechnology, Department of Biosciences, Rajagiri College of Social Sciences, Kerala, Kochi, India Ibrahim Çelik Department of Agricultural and Livestock Production, Çal Vocational School of Higher Education, Pamukkale University, Denizli, Turkey Dipankar Chakraborti Department of Genetics, University of Calcutta, Kolkata, West Bengal, India Puja Chakraborty Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Anup Chandra ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Prathyusha Cheguri Pigeonpea Improvement Program, International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India Charles Chen Department of Crop, Soil, & Environmental Sciences, Auburn University, Auburn, AL, USA Vasugi Chinnaiyan Division of Fruit crops, ICAR–Indian Institute of Horticultural Research, Bengaluru, India Walter Chitarra Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Conegliano, Italy Institute for Sustainable Plant Protection, CNR, Torino, Italy Vishal Chugh College of Horticulture, Banda University of Agriculture and Technology, Banda, India Isadora Louise Alves da Costa Ribeiro Quintans Universidade Federal Rural do Semi-Árido, Mossoro, Brazil Ana Paula da Mata Department of Agronomy, Federal University of Viçosa, Viçosa, Brazil Carla Cristina da Silva Department of Agronomy, Federal University of Viçosa, Viçosa, Brazil

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Contributors

Vincenzo D’Amelia Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy Vijayalaxmi S. Dandin Department of Biology, JSS College, Dharwad, India Alok Das Division of Plant Biotechnology, ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Arpita Das Department of Genetics & Plant Breeding, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, Nadia, West Bengal, India Stefano Delbono Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy G. P. Dixit ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Ivica Djalovic Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Novi Sad, Serbia Teresa Docimo Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy Sami Doğanlar Plant Science and Technology Application and Research Center, Izmir Institute of Technology, Urla, Turkey Department of Molecular Biology and Genetics, Izmir Institute of Technology, Urla, Turkey Yinghui Duan Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, China Henan Key Laboratory of Specific Oilseed Crops Genomics (Henan Sesame Research Center, Henan Academy of Agricultural Sciences), Zhengzhou, Henan, China Henan International Joint Laboratory of Specific Oilseed Crops Improvement, Zhengzhou, Henan, China Anil Kumar Dubey Division of Fruits and Horticultural Technology, ICAR-Indian Agricultural Research Institute, New Delhi, India Frank Dunemann Julius Kühn-Institut (JKI), Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Horticultural Crops, Quedlinburg, Germany Sudip Kumar Dutta Gus R. Douglass Institute, Department of Biology, West Virginia State University, Institute, WV, USA ICAR RC NEH Region, Sikkim centre, Gangtok, Sikkim, India Maria Stefanie Dwiyanti Laboratory of Applied Plant Genome, Hokkaido University, Sapporo, Japan

Contributors

xxiii

Murugesh Easwaran Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India L. Elkonin Department of Biotechnology, Federal Centre of Agriculture Research of the South-East Region, Saratov, Russia Magdi El-sayed Faculty of Science, Galala University, Suze, Egypt Jun Fan Yunnan Academy of Agricultural Sciences, Kunming, China Khaled Fathy Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Yolanda Ferradás Instituto de Ciencias de la Vid y del Vino (ICVV), Consejo Superior de Investigaciones Científicas– Universidad de la Rioja – Gobierno de La Rioja, Logroño, Spain Faculty of Biology, University of Santiago de Compostela, Santiago de Compostela, Spain Franca Finocchiaro Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy Anne Frary Department of Molecular Biology and Genetics, Izmir Institute of Technology, Urla, Turkey Prakash I. Gangashetty Pigeonpea Improvement Program, International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India Marica Gasparro Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Turi, Italy Thais Gaudencio do Rêgo Universidade Federal da Paraíba, João Pessoa, Brazil Roberta Ghizzoni Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy Sanatan Ghosh Department of Genetics, University of Calcutta, Kolkata, West Bengal, India Shailendra Goel Department of Botany, University of Delhi, Delhi, India J. J. Gonzalez-Fernandez Instituto de Hortofruticultura Subtropical Mediterranea La Mayora (IHSM La Mayora-UMA-CSIC), Malaga, Spain

y

Poulami Goswami Department of Botany, University of Delhi, Delhi, India Velu Govindan International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico Mahalingam Govindaraj HarvestPlus Program, Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Cali, Colombia

xxiv

Contributors

Maria D. P. T. Gunawan-Puteri Department of Food Technology, Swiss German University, Tangerang, Indonesia DebJyoti Sen Gupta ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Mehak Gupta Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India Om Prakash Gupta ICAR-Indian Institute of Wheat and Barley Research, Karnal, India Sanjeev Gupta Assistant Director General, Oil seeds & Pulses, Indian Council of Agricultural Research, New Delhi, India Nergiz Gürbüz Çolak Plant Science and Technology Application and Research Center, Izmir Institute of Technology, Urla, Turkey S. M. Harisha Division of Vegetable Science, ICAR–Indian Agricultural Research Institute, New Delhi, India Anjan Hazra Department of Genetics, University of Calcutta, Kolkata, West Bengal, India J. I. Hormaza Instituto de Hortofruticultura Subtropical y Mediterranea La Mayora (IHSM La Mayora-UMA-CSIC), Malaga, Spain Massimo Iorizzo Plants for Human Health Institute and Department of Horticultural Sciences, North Carolina State University, Kannapolis, NC, USA Maizura Ithnin Malaysian Palm Oil Board, Persiaran Institusi, Bandar Baru Bangi, Kajang, Malaysia Rani Asaram Jadhav College of Agriculture, Nagpur, India Arun Jagannath Department of Botany, University of Delhi, Delhi, India S. Mohan Jain Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland Souframanien Jegadeesan Nuclear Agriculture & Biotechnology Division, Bhabha Atomic Research Centre, Trombay, Mumbai, India Dennis V. Johnson Agriculture Consultant, Middlebrook Ave, Cincinnati, OH, USA Ming Ju Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, China Henan Key Laboratory of Specific Oilseed Crops Genomics (Henan Sesame Research Center, Henan Academy of Agricultural Sciences), Zhengzhou, Henan, China Henan International Joint Laboratory of Specific Oilseed Crops Improvement, Zhengzhou, Henan, China

Contributors

xxv

Sai Rekha Kadirimangalam International Crop Research Institute for the SemiArid Tropics, Hyderabad, India Pritam Kalia Division of Vegetable Science, ICAR-Indian Agricultural Research Institute, New Delhi, India Anmol Kalra Department of Botany, University of Delhi, Delhi, India Rashmi Kaul Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Tanushri Kaul Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Gurpreet Kaur Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India Prashant Kaushik Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universitat Politècnica de València, Valencia, Spain Mercy Ketavi Research Technology Support Facility, Michigan State University, East Lansing, MI, USA Jasminkumar Kheni Department of Biotechnology, Junagadh Agricultural University, Junagadh, Gujarat, India Rituraj Khound Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Scottsbluff, NE, USA Chittaranjan Kole Institute of Nutraceutical Research, Clemson University, Clemson, SC, USA Aravind Konda ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Schuyler S. Korban Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana–Champaign, Urbana, IL, USA Shivanand Koti Department of Fruit Science College of Horticulture, UHSB Campus, Bangalore, India Ajay Kumar ICAR-Indian Institute of Horticultural Research, Bengaluru, India Jitendra Kumar ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Sunil Kumar ICAR-Indian Institute of Wheat and Barley Research, Karnal, India Rituparna Kundu Chaudhuri Department of Botany, Barasat Government College, Barasat, West Bengal, India M. T. Labuschagne Department of Plant Sciences, University of the Free State, Bloemfontein, South Africa

xxvi

Contributors

Amrit Lamichaney ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Charu Lata Inclusive Health and Traditional Knowledge Studies Division, CSIRNational Institute of Science Communication and Policy Research, New Delhi, India Chun Li Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, China Henan Key Laboratory of Specific Oilseed Crops Genomics (Henan Sesame Research Center, Henan Academy of Agricultural Sciences), Zhengzhou, Henan, China Henan International Joint Laboratory of Specific Oilseed Crops Improvement, Zhengzhou, Henan, China H. Li TSU – Tennessee State University, Department of Agricultural and Environmental Sciences, Nashville, TN, USA Mathiazhagan Malarvizhi Division of Biotechnology, ICAR Indian Institute of Horticultural Research, Bengaluru, India S. Malathi ICAR-Indian Institute of Rice Research, Hyderabad, India Manisha Mangal Division of Vegetable Science, ICAR-Indian Agricultural Research Institute, New Delhi, India S. K. Mangrauthia ICAR-Indian Institute of Rice Research, Hyderabad, India C. Manimurugan ICAR-Indian Institute of Oilseeds Research, Hyderabad, India B. Manu ICAR-Indian Institute of Pulses Research, Regional Station, Dharwad, Karnataka, India Malarvizhi Mathiazhagan Division of Biotechnology, ICAR–Indian Institute of Horticultural Research, Bengaluru, India Ramesh Kanna Mathivanan Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Scottsbluff, NE, USA Shikha Mathur Department of Genetics, University of Delhi South Campus, New Delhi, India Tesfaye Walle Mekonnen Department of Plant Sciences, University of the Free State, Bloemfontein, South Africa Hongmei Miao Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, China Henan Key Laboratory of Specific Oilseed Crops Genomics (Henan Sesame Research Center, Henan Academy of Agricultural Sciences), Zhengzhou, Henan, China Henan International Joint Laboratory of Specific Oilseed Crops Improvement, Zhengzhou, Henan, China

Contributors

xxvii

Rosa Anna Milella Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Turi, Italy Chandra Nath Mishra ICAR-Indian Institute of Wheat and Barley Research, Karnal, India Loredana Moffa Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Conegliano, Italy Suma C. Mogali AICRP-MULLaRP Scheme, University of Agricultural Sciences, Dharwad, Karnataka, India Bidisha Mondal Department of Genetics and Plant Breeding, The School of Agriculture and Allied Sciences, The Neotia University, Sarisha, West Bengal, India Biswajit Mondol Division of Plant Biotechnology, ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Caterina Morcia Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy Samwel Muiruri International Institute of Tropical Agriculture (IITA), Nairobi, Kenya Department of Plant Sciences, Kenyatta University, Nairobi, Kenya Aloleca Mukherjee Department of Genetics, University of Calcutta, Kolkata, West Bengal, India Epsita Mukherjee Amity Institute of Biotechnology, Amity University, Noida, India T. K. Nagarathna University of Agricultural Sciences, GKVK Campus, Bengaluru, Karnataka, India Praveen Nagella Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, India Poornananda M. Naik Department of Botany, Karnatak University, Dharwad, Karnataka, India Aswathy G. H. Nair Division of Crop Improvement, Central Tuber Crops Research Institute, Thiruvananthapuram, India Manivannan Narayana Centre of Excellence in Molecular Breeding, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, India, Spurthi N. Nayak Department of Biotechnology, University of Agricultural Sciences, Dharwad, India C. N. Neeraja ICAR-Indian Institute of Rice Research, Hyderabad, India

xxviii

Contributors

Mamta Nehra Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India L. Nekkalapudi TSU – Tennessee State University, Department of Agricultural and Environmental Sciences, Nashville, TN, USA Luca Nerva Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Conegliano, Italy Institute for Sustainable Plant Protection, CNR, Torino, Italy José Ribamar Costa Ferreira Neto Universidade Federal de Pernambuco, Recife, Brazil G. Niharika ICAR-Indian Institute of Rice Research, Hyderabad, India Padma Nimmakayala Gus R. Douglass Institute, Department of Biology, West Virginia State University, Institute, WV, USA Valentine Otang Ntui International Institute of Tropical Agriculture (IITA), Nairobi, Kenya L. Olmo-García Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Granada, Spain Bonny Michael Oloka Department of Horticultural Science, North Carolina State University, Raleigh, NC, USA Abrizah Othman Malaysian Palm Oil Board, Persiaran Institusi, Bandar Baru Bangi, Kajang, Malaysia Kadirvel Palchamy ICAR-Indian Institute of Oilseeds Research, Hyderabad, Telangana, India Manish Pandey International Crops Research Institute for the Semiarid Tropics, Hyderabad, Telangana, India Sudhakar Pandey ICAR-Indian Institute of Vegetable Research, Varanasi, India Valesca Pandolfi Universidade Federal de Pernambuco, Recife, Brazil M. Paredes INIA - Instituto de Investigaciones Agropecuarias, Chillán, Chile Univ Vina del Mar, Escuela de Ciencas Agricolas y veterinarias, Vina del Mar, Chile A. K. Parihar ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Guilherme Silva Pereira Department of Agronomy, Federal University of Viçosa, Viçosa, Brazil K. Poornima ICAR-Indian Institute of Horticultural Research, Bengaluru, India

Contributors

xxix

Ameena Premnath Department of Plant Biotechnology, Centre for Plant Molecular Biology and Biotechnology, Tamil Nadu Agricultural University, Coimbatore, India, Mahesh Pujar Crop Improvement Theme, Research Program-Asia, at ICRISAT, Hyderabad, India Dhanasekar Punniyamoorthy Nuclear Agriculture & Biotechnology Division, Bhabha Atomic Research Centre, Trombay, Mumbai, India Naveen Puppala Agricultural Science Center at Clovis, New Mexico State University, Clovis – New Mexico, USA Jose Quero-García UMR Biologie du Fruit et Pathologie, INRAE, Univ. Bordeaux, Villenave d’Ornon, France Rawan Rabie Faculty of Science, Galala University, Suze, Egypt P. Raghuveer Rao ICAR-Indian Institute of Rice Research, Hyderabad, India Ashutosh Rai College of Horticulture, Banda University of Agriculture and Technology, Banda, India Avi Raizada Nuclear Agriculture & Biotechnology Division, Bhabha Atomic Research Centre, Trombay, Mumbai, India M. K. Rajesh Division of Crop Improvement, ICAR-Central Plantation Crops Research Institute, Kasaragod, India Nirala Ramchiary School of Life Sciences, Jawaharlal Nehru University, New Delhi, India Bala Rathinasabapathi Horticultural Sciences Department, University of Florida, Gainesville, FL, USA K. V. Ravishankar ICAR-Indian Institute of Horticultural Research, Bengaluru, India Kundapura V. Ravishankar Division of Biotechnology, ICAR–Indian Institute of Horticultural Research, Bengaluru, India Ramya Ravishankar Sun Valley Family Care, Peoria, AZ, USA Umesh K. Reddy Gus R. Douglass Institute, Department of Biology, West Virginia State University, Institute, WV, USA Fabio Reggiani Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy João Ricardo Bachega Feijó Rosa Department of Agronomy, Federal University of Viçosa, Viçosa, Brazil Anirban Roy Ramakrishna Mission Vivekananda Educational and Research Institute, Kolkata, West Bengal, India

xxx

Contributors

P. R. Saabale ICAR-Indian Institute of Pulses Research, Regional Station, Dharwad, Karnataka, India Deepti B. Sagare Bayer Crop Science Ltd, Hyderabad, India Partha Saha Division of Vegetable Science, ICAR–Indian Agricultural Research Institute, New Delhi, India P. Sanghamitra ICAR-National Rice Research Institute, Cuttack, India D. Sanjeeva Rao ICAR-Indian Institute of Rice Research, Hyderabad, India Iara Gonçalves dos Santos Department of Agronomy, Federal University of Viçosa, Viçosa, Brazil Dipak K. Santra Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Scottsbluff, NE, USA Abhimanyu Sarker John Innes Centre, Norwich, UK Jyothish Madambikattil Sasi Inclusive Health and Traditional Knowledge Studies Division, CSIR-National Institute of Science Communication and Policy Research, New Delhi, India Stefania Savoi Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco, Italy Nunzia Scotti Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy Joseph Kadanthottu Sebastian Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, India Raman Selvakumar Centre for Protected Cultivation Technology, ICAR-Indian Agricultural Research Institute (IARI), New Delhi, India Debjyoti Sen Gupta ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Manuel Joaquín Serradilla Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), Instituto Tecnológico Agroalimentario de Extremadura (INTAEX), Badajoz, Spain Priya Shah International Crops Research Institute for the Semiarid Tropics, Hyderabad, Telangana, India Megha Sharma Department of Botany, University of Delhi, Delhi, India Nimisha Sharma Division of Fruits and Horticultural Technology, ICAR-Indian Agricultural Research Institute, New Delhi, India Prashant Shetti Banashankari Agro Agency, Nipani, India

Contributors

xxxi

Masayoshi Shigyo Laboratory of Vegetable Crop Science, College of Agriculture, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi, Japan Philipp W. Simon USDA Agricultural Research Service, Vegetable Crops Research Unit, Department of Horticulture, University of Wisconsin, Madison, WI, USA Gyanendra Singh ICAR-Indian Institute of Wheat and Barley Research, Karnal, India Jugpreet Singh LeafWorks Inc., Sebastopol, CA, USA Neetu Singh ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Prateek Singh Division of Plant Biotechnology, ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Shrawan Singh Division of Vegetable Science, ICAR-Indian Agricultural Research Institute, New Delhi, India Shweta Singh Indian Institute of Sugarcane Research, Lucknow, India Dwaipayan Sinha Department of Botany, Government General Degree College Mohanpur, Mohanpur, West Bengal, India N. Siromani ICAR-Indian Institute of Rice Research, Hyderabad, India Sonia Khan Sony Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India S. Gandhadmath Spoorti ICAR-Indian Institute of Rice Research, Hyderabad, India M. Sujatha ICAR-Indian Institute of Oilseeds Research, Hyderabad, India R. M. Sundaram ICAR-Indian Institute of Rice Research, Hyderabad, India Penna Suprasanna Amity Institute of Biotechnology, Amity University of Maharashtra (AUM), Mumbai, Maharashtra, India Noor Idayu Mhd Tahir Malaysian Palm Oil Board, Persiaran Institusi, Bandar Baru Bangi, Kajang, Malaysia A. Talavera Instituto de Hortofruticultura Subtropical y Mediterranea La Mayora (IHSM La Mayora-UMA-CSIC), Malaga, Spain Rachele Tamburino Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy Javier Tello Instituto de Ciencias de la Vid y del Vino (ICVV), Consejo Superior de Investigaciones Científicas– Universidad de la Rioja – Gobierno de La Rioja, Logroño, Spain

xxxii

Contributors

Valeria Terzi Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy Shallu Thakur Division of Plant Biotechnology, ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India Arulprakash Thangaraj Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Bhoopal Singh Tomar Division of Vegetable Science, ICAR–Indian Agricultural Research Institute, New Delhi, India Rukam S. Tomar Department of Biotechnology, Junagadh Agricultural University, Junagadh, Gujarat, India Jaindra Nath Tripathi International Institute of Tropical Agriculture (IITA), Nairobi, Kenya Kuldeep Tripathi Division of Germplasm Evaluation, ICAR-National Bureau of Plant Genetic Resources, New Delhi, India Leena Tripathi International Institute of Tropical Agriculture (IITA), Nairobi, Kenya Giorgio Tumino Plant Breeding, Wageningen University and Research, Wageningen, The Netherlands Jayashree Ugalat Department of Biotechnology and Crop Improvement College of Horticulture, UHSB Campus, Bangalore, India C. Vasugi ICAR-Indian Institute of Horticultural Research, Bengaluru, India J. Veerendra ICAR-Indian Institute of Rice Research, Hyderabad, India Rachana Verma Nutritional Improvement of Crops (NIC) Group, International Centre for Genetic Engineering and Biotechnology (ICGGEB), New Delhi, India Clizia Villano Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy Ana Wünsch Centro de Investigación y Tecnología Agroalimentaria de Aragón, Zaragoza, Spain Instituto Agroalimentario de Aragón-IA2 (CITA-Universidad de Zaragoza), Zaragoza, Spain Fan Xingming Yunnan Academy of Agricultural Sciences, Kunming, China Bal Govind Yadav International Centre for Genetic Engineering and Biotechnology, New Delhi, India Satish Kumar Yadava Centre for Genetic Manipulation of Crop Plants, University of Delhi South Campus, New Delhi, India

Contributors

xxxiii

Shrikant Yankanchi Indira Gandhi Krishi Vishwavidyalaya, Raipur, India A. Zanwar Interactive Research School for Health Affairs, Bharati Vidyapeeth (Deemed to be University), Pune, India Haiyang Zhang Henan Sesame Research Center, Henan Academy of Agricultural Sciences, Zhengzhou, Henan, China Henan Key Laboratory of Specific Oilseed Crops Genomics (Henan Sesame Research Center, Henan Academy of Agricultural Sciences), Zhengzhou, Henan, China Henan International Joint Laboratory of Specific Oilseed Crops Improvement, Zhengzhou, Henan, China

Part I Cereal Crops

Redesigning Rice as a Promising Nutraceutical Functional Food R. M. Sundaram, D. Sanjeeva Rao, P. Sanghamitra, S. Gandhadmath Spoorti, J. Veerendra, N. Siromani, G. Niharika, R. Ananthan, J. Aravind Kumar, P. Raghuveer Rao, S. Malathi, S. K. Mangrauthia, M. Balram, J. Ali, and C. N. Neeraja

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Rice: A Staple Food Across the World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Growing Importance of Rice in the Face of Chronic Diseases and Malnutrition . . . . . 1.3 Development of Biofortified Rice Varieties: Limitations of Conventional Breeding and Rationale for Next-Generation Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Nutritional Composition of the Rice Grain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Starch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Lipids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Other Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Iron (Fe) and Zinc (Zn) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Marker-Assisted Breeding for Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Germplasm Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 QTL Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Nutritional Improvement in Rice Quality Using a Genetic Engineering Approach . . . 4 Genomics-Aided Breeding for Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 GWAS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Sequencing/Resequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Wild Species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

4 4 5 7 9 11 13 15 17 21 23 24 28 30 36 36 37 37

R. M. Sundaram · D. Sanjeeva Rao · S. G. Spoorti · J. Veerendra · N. Siromani · G. Niharika · J. Aravind Kumar · P. Raghuveer Rao · S. Malathi · S. K. Mangrauthia · C. N. Neeraja (*) ICAR-Indian Institute of Rice Research, Hyderabad, India P. Sanghamitra ICAR-National Rice Research Institute, Cuttack, India R. Ananthan National Institute of Nutrition, Hyderabad, India M. Balram International Rice Research Institute, Los Banos, Philippines J. Ali Professor Jayashankar Telangana State Agricultural University, Hyderabad, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_1

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4

R. M. Sundaram et al.

4.4 3K Rice Panel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Genomic Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Functional Genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Bioinformatics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Whole-Genome Selection and Breeding Chips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 Genomics-Assisted Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Role of Genome Editing Technology in Rice Nutritional Quality Improvement . . . . . . . . . . . 6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

37 38 38 38 39 39 40 40 42

Abstract

Rice is a staple food for more than half of the world’s population and is grown in more than 100 countries in varied water regimes and ecological systems. In recent years, the perspective of rice has changed from staple food to its potential to be used as a functional food. Industrialization brought changes in lifestyle, leading to the consumption of milled rice, leaving aside the rice bran. Brown rice is a good source of energy, fats, vitamins, and minerals, and the colored rice grains have higher mineral content, antioxidants, and bioactive compounds; the polished rice is a poor source of nutrients. Challenges like climate change with elevated CO2, and drought and heat stress are also reducing the nutritional quality of rice. Enhancing the nutritive value of rice grain and promoting as a nutraceutical functional food could address nutrition security. Breeding interventions and the application of next-generation technologies can hasten the development of nutritive rice varieties with desired levels of the mineral, vitamin, and bioactive compounds and glycemic index. Landraces and wild species are the potential genetic donors aiding in the generation of the breeding material with the increased functionality of rice grain. The availability of enormous rice germplasm gives scope to identify new nutraceuticals and develop nutraceutical-rich varieties. Genomic regions and genes associated with nutritive function in grain are being identified by deploying sequencing, resequencing, genome-wide association, and biparental mapping. CRISPR-based genome editing appears to be the most potent tools for developing rice varieties with high grain nutrient levels. Keywords

Rice · Grain · Functional food · Nutritive composition · Bioactive compounds · Germplasm · Biofortification · Next-generation technologies

1

Introduction

1.1

Rice: A Staple Food Across the World

Rice is a major cereal crop and a staple food for half of the world’s population (Fukagawa and Ziska 2019). Globally, rice is cultivated in more than 100 countries, spanning an area of approximately 163 million hectares (FAO 2021). Rice has two cultivated species, Oryza sativa, which is predominant worldwide, and Oryza

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glaberrima, limited to a few parts of Western Africa (Khush 1997). Within O. sativa, two major subspecies have been identified: indica, cultivated in tropical Asia, and japonica, primarily found in Southern China, South East Asia, Indonesia, and outside Asia (Londo et al. 2006). Later, five distinct groups were made in O. sativa corresponding to indica, aus, aromatic, temperate japonica, and tropical japonica (Garris et al. 2005). Rice is cultivated worldwide in varied water regimes, ecology systems, and soil types. Nearly three-quarters world’s rice is produced from irrigated lowland systems with two to three crops per year (De Datta 1981). Around 20% of global rice production is from the rainfed lowland system, which is predominant in Southeast Asia and Africa. The upland condition accounts for approximately 4% of the world’s rice production. Deepwater, semi-deep water, and floating kinds of rice are cultivated in specific geographical regions in some South Asian countries (Khush 1987). Worldwide paddy production was around 0.8 billion tons in 2019, with an 8% contribution to global crop production (FAO 2021). China, India, and Indonesia are major rice-producing countries, accounting for 50% of rice production (www.fao. org). Other Asian countries like Bangladesh, Vietnam, Myanmar, Thailand, the Philippines, Japan, Pakistan, Cambodia, the Republic of Korea, Nepal, and Sri Lanka contribute to the remaining world’s total rice production. Brazil, the United States, Egypt, Madagascar, and Nigeria produce around 5% of global rice production (Muthayya et al. 2014). Nearly 490 million tons were reported to be global rice consumption in 2019. Daily rice consumption is also the highest in Bangladesh, the Lao People’s Democratic Republic, Cambodia, Vietnam, Myanmar, Thailand, Indonesia, and the Philippines among the Asian countries. Significant rice consumption is also indicated in South America, Latin America, the Caribbean, and Oceania, with China and India accounting for
50% of the world’s rice consumption. Interestingly, only 60% of the consumption in Africa is covered by local rice production, with the remaining rice being imported (www.africarice.org). Rice is reported to be the source of 20% of the world’s dietary energy, supplying more than 70% of calories in some Asian countries (GRiSP 2013). Rice production has significantly increased, more than doubling after the advent of the Green Revolution from yield levels of less than 2 t/ha during the 1950s. The development and broad adoption of semi-dwarf rice varieties responsive to increased inputs of fertilizers, irrigation, pesticides, and other resources considerably enhanced rice yield (Dalrymple 1986; Hedden 2003). Rice production was reported to be increased by 130% between the 1960s and 2000s (Muthayya et al. 2014). The next level of yield enhancement was made possible with the exploitation of heterosis by developing hybrid rice during the 1970s in China and other countries (Cheng et al. 2007a).

1.2

Growing Importance of Rice in the Face of Chronic Diseases and Malnutrition

Rice is the staple diet of more than 3.5 billion people (Xu et al. 2021a), mainly in Asian and African countries populated by people with poor purchasing power and access to nutritious food. The world’s population is projected to be 8.5 billion in

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2030, 9.7 billion in 2050, and 10.9 billion in 2100 (United Nations Department of Economic and Social Affairs 2019). Most of the population growth is expected in Southern Asia and Africa, which are already excessively dependent on rice. Thus, rice has become a crucial commodity in global food security, and around a 70% increase in food production is needed to meet the food demand in 2050 (FAO 2017). The anticipated increase in rice production could be possible from India, China, Vietnam, and Thailand as per projections by the OECD-FAO Agricultural Outlook, global rice production (OECD-FAO 2021). In addition to being targeted for the enhancement of its production for the future, rice is also being aimed for its nutraceutical quality improvement. People who subsist on polished rice are vulnerable to vitamin and mineral deficiencies. Increasing the nutritive value of rice grain can address nutrition security and food security, especially in countries where rice is the major source of calories/energy. More than 32% of women worldwide and 36.6% in Asia are reportedly anemic (FAO 2019; https://globalnutritionreport.org/reports/global-nutrition-report-2018/). The Global Nutrient Database of availability of macro- and micronutrients in 195 countries from 1980 to 2013 revealed higher consumption of carbohydrates in South Asia against the world’s consumption. It has also reported the poor availability of macroand micronutrients per day per person in South Asia, viz., 47 g fat (world: 72 g), 56 g protein (world: 71 g), 362 μg vitamin A (world: 705 μg), 19 g iron (Fe) (world: 18 mg), and 8 mg zinc (Zn) (world: 10 mg) (https://nutrition.healthdata.org/globalnutrient-database). Half of the world’s malnourished children reside in three countries of South Asia, viz., Bangladesh, India, and Pakistan (World Bank 2009). Concerning the Global Nutrient Database, the values of availability of energy (2500 to 25%) amylose (Juliano, 1971). Amylopectin is branched with α-D-(1-4) and α-D-(1-6) glycosidic bonds within the branches and branching points, respectively. The amylopectin proportion decreases with the increase in amylose content. Sugars are transported from the phloem of the seed coat to the maternal tissue, to the embryonic apoplast, and finally to the endosperm due to the osmotic gradient between the leaf and the growing seed. In the cytoplasm, ADP-glucose pyrophosphorylase (AGPase) activates glucose to ADP-glucose, which enters into the amyloplasts where granule-bound starch synthase I (GBSSI) uses ADP-glucose to synthesize amylose chains. In japonica rice, this enzyme (Wxb) is less efficient due to a transversion (G to T) mutation in the first intron. Three categories of enzymes coordinate amylopectin synthesis. Soluble starch synthases (SSI, SSIIa, and SSIIIa) elongate (add glucose), and starch branching enzymes (BEI, BEIIa, and BEIIb) create branching points. Debranching enzymes (isomerase and pullulanase)

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will enhance the granule compactness by removing some branching points. Involvement of multiple enzymes may accumulate similar amounts of starch; however, they can vary in chain length, branching density, compactness, etc. Regarding the medicinal/physiological properties and functions of starch concerning human health, in the gastrointestinal tract or gut, starch digestion in the mouth is negligible since the food is generally swallowed into the stomach. Pancreatic juice contains multiple enzymes. The α-amylase and maltase digest starch into maltose and glucose, respectively. SGLT1 and GLUT2 are hexose transporters in Caco-2 cells. GLUT2, a facilitated transporter, is on the apical side and gathers to the membrane at a high glucose concentration. It is the main transporter of glucose (Kamiloglu et al. 2015) into the blood, leading to its increase above normal level (140 mg/100 ml). In response, insulin hormone is secreted into blood from pancreatic β-cells. Insulin decreases the blood glucose to a normal level by either converting the extra glucose to glycogen in the liver and muscles or into fats and other molecules. During fasting or between the two meals, glucose can decrease by 10%) varieties – CR Dhan 310, CR Dhan 411, and CR Dhan 311 in milled rice – were released through the AICRIP biofortification trial and one BRRI Dhan 84 (9.7%) was released in Bangladesh. The average daily requirement of nitrogen is 0.83 g/kg body weight, and the average body weight is 65 kg for India, thus, 51.46–53.95 g protein (72 g for pregnant or breastfeeding women) is required. These high-protein varieties can

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Fig. 2 Amino acids (17) in brown (B) and polished (P) rice (unpublished data)

provide around 24–30 g of protein from 220 g of rice. As nitrogen fertilizer application decreases in the future, germplasm screening must be intensified to identify donors and promising markers to enhance protein.

2.3

Lipids

Lipids are present in the aleurone layer (marginally higher) and endosperm. Bran is a by-product while milling brown rice. Lipids extracted from bran are called bran oil, containing triglycerides, free fatty (bulky side chains) acids, and oryzanol. Rice contains

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Table 4 EAA (g/100 g) in raw rice (Longvah et al. 2017) and their role in human Amino acid Methionine (M)

Brown 2.39  0.26

Milled 2.60  0.34

Arginine (R)

7.69  0.37

7.72  0.55

Threonine (T) Tryptophan (W)

3.38  0.25 1.00  0.17

3.28  0.27 1.27  0.14

Valine (V)

6.72  0.36

6.06  0.02

Isoleucine (I)

4.08  0.51

4.29  0.23

Leucine (L)

8.40  0.55

8.09  0.40

Phenylalanine (F)

5.50  0.49

5.36  0.43

Histidine (H) Lysine (K)

2.36  0.18 3.63  0.29

2.45  0.30 3.70  0.39

Role Increases the antioxidant levels (glutathione). Reduce blood cholesterol level Precursor for nitric oxide, ornithine, polyamines, agmatine, proline, glutamate, creatine, and urea. Optimal growth and development of infants Prevents fatty buildup in liver Prevents fatty buildup in liver. Precursor of neurotransmitter serotonin (calming effect) Influences brain to uptake of tryptophan, phenylalanine, and tyrosine Formation of hemoglobin. Prevents muscle wasting in debilitated individuals Promotes healing of skin and broken bones. Reduces protein breakdown in the muscles Production of collagen. Precursor of tyrosine. Enhances learning, memory, mood, and alertness Production of RBC (anti-anemic) and WBC Inhibits viruses – herpes simplex virus. Lysine and vitamin C together form L-carnitine that enables muscle tissue to use oxygen more efficiently and delay muscle fatigue

higher levels of C16 and C18 fatty acids. Notably, the latter was at the highest level of the two essential fatty acids, linolenic and linoleic acids. Eventually, the proportion of unsaturated or polyunsaturated fatty acids (PUFA) is higher (Table 5). The growing fatty acid gains 2 carbons (acetyl CoA) during each condensation cycle, and it grows up to C16 in the cytoplasm. Further elongation as well as unsaturation (introduction of double bonds) occurs in the endoplasmic reticulum. Oryzanol was first isolated by Kaneko and Tsuchiya (1955). It is a mixture of sterol esters of ferulic acid. It contains cycloartenol, β-sitosterol, 24-methylenecycloartanol, cyclobranol (cycloartenol), and campesterol (4-desmethysterols) (Rogers et al. 1993), and composition varies among varieties. Regarding the medicinal/physiological properties and functions of lipids of rice concerning human health, triacylglycerols are emulsified by bile juice into micelles. Pancreatic lipase digests them into free fatty acids and glycerol, which enter into intestinal cells where they are resynthesized into triacylglycerols and packaged with cholesterol and specific proteins to form chylomicrons. Chylomicrons enter into the lymph and, through blood, reach various tissues to supply fatty acids and glycerol. The remnant chylomicrons reach the liver and are converted into very low-density (VLDL), low-density (LDL), or high-density (HDL) lipoproteins based on the availability of lipids.

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Table 5 Fatty acids in raw rice samples collected across the country (Longvah et al. 2017) S. No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Compound (mg/100 g) Systemic name Myristic Tetradecanoic acid Palmitic Hexadecenoic acid Stearic Octadecanoic acid Arachidic Eicosanoic acid Behenic Doeicosanoic acid Lignoceric Tetraeicosanoic acid Palmitoleic cis-9-Hexadecenoic Oleic cis-9-Octadecenoic Eicosenoic icos-11-enoic acid Nervonic Tetracos-15-enoic acid Linoleic all-cis-9,12-Octadecadienoic α-Linolenic all-cis-9,12-Octadecadienoic Total saturated fatty acids (SFA) Total mono-unsaturated fatty acids Total PUFA

Brown 30.42  3.15 273  14.9 33.01  4.34 3.09  0.21 1.98  0.21 2.49  0.38 2.77  0.46 197  15.4 1.89  0.25 0.89  0.22 490  33.2 16.10  0.92 346  20.3 203  15.7 506  33.6

Milled 13.19  3.00 143  28.0 14.50  3.27 1.46  0.40 1.98  1.49 1.14  0.35 1.49  0.47 109  21.2 1.54  0.44 0.75  0.36 234  45.8 9.51  1.09 184  8.9 117  6.6 253  13.2

In the liver, PUFA is converted into ketone bodies. While SFA is converted into LDL (Beynen and Katan 1985) and acetyl CoA, which is converted into cholesterol, this quantity is different from the one absorbed from the intestine where γ-oryzanol in food can inhibit cholesterol absorption. Rice contains more linolenic acid and will reduce LDL and simultaneously increase the HDL (Cicero and Gaddi 2001). Linolenic acid, the precursor of eicosanoids (C20) and docosahexaenoic acid (DHA; ω3, 22:6), is converted into eicosanoic acid (C20) that in turn form prostaglandins and thromboxanes (hormones) and into leukotrienes and lipoxins. Prostaglandins deal with inflammation and regulate blood coagulation and reproduction. Leukotrienes help in muscle contraction and chemotactic properties and are slow reactive substances of anaphylaxis (SRSA). DHA is required for brain and retina development. Thus, except for essential fatty acids, human metabolism is capable of synthesizing all other lipids from protein or carbohydrates.

2.4

Other Compounds

Rice also contains vitamins (Table 6), minerals, phytosterols, organic acids, etc. Some are more in the aleurone layer (Fe), and others are more in the endosperm. Highly pigmented brown rice is in red, purple, or black color (Table 7), and the various concentrations of cyanidin-3-O-glucoside equivalent (CGE) and catechin acid equivalent (CAE) are responsible for the variation in the color (Goufo and Trindade 2014). Generally, pigments (flavonoids) are glycosylated (aglycone), methylated or acylated forms of anthocyanidin (“Anthos” means flower, and “kyanos” is blue). Pigmented rice contains carotenoids, 159 and 16.87 μg/100 g in brown and milled rice, respectively.

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Table 6 Water-soluble vitamins in raw rice (Longvah et al. 2017) and their role in human Compound (mg/100 g) S. No Brown 1 Thiamine 0.27  0.023 (B1)

Milled 0.05  0.019

2

Riboflavin (B2)

0.06  0.011

0.05  0.006

3

Niacin (B3)

3.40  0.12

1.69  0.13

4

Pantothenic acid (B5)

0.61  0.04

0.57  0.05

5

Total pyridoxine (B6)

0.37  0.035

0.12  0.012

6

Biotin (B7) (μg)

1.38  0.21

0.60  0.12

7

Total folates (B9) (μg)

11.51  1.69

9.32  1.93

Functions Coenzyme in pyruvate, α-ketoglutarate, dehydrogenases, and transketolase; nerve conduction Coenzyme in redox reactions. Prosthetic group of flavoproteins

Coenzyme in redox reactions. Formation of NAD and NADP Functional part of CoA and ACP in fatty acid metabolism Coenzyme in transamination, decarboxylation, glycogen phosphorylase, and steroid hormone action Coenzyme in carboxylation, gluconeogenesis, and fatty acid synthesis Coenzyme in one carbon transfer

Deficiency symptom Beri-beri central nervous system lesions

Lesions of corner of mouth, lips, tongue; seborrheic dermatitis Pellagra

Huntington’s disease (HD)

Disorders of amino acid metabolism, convulsions

Impaired fat and carbohydrate metabolism, dermatitis Megaloblastic anemia

Table 7 Composition of colored rice Pericarp color Black Purple Red Brown

Anthocyanin (mg/100 g) 1884 2874 8.78 3.09

Proanthocyanidin (mg/100 g) 78 525.4 716.6 4.34

Phenylalanine is converted into 4-coumaroyl CoA to chalcone (committed step) in the presence of ATP, CoA, and three molecules of malonyl CoA (Fig. 3). Chalcone is converted into naringenin, which is oxidized to dihydrokaempferol. It, in turn, is hydroxylated at position 3 or 5 to dihydroflavonols, which are reduced to

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Fig. 3 Anthocyanin biosynthetic pathway (Mackon et al. 2021)

leucoanthocyanidin by NADPH and dihydroflavonol 4-reductase (DFR), which is another critical enzyme. The leucoanthocyanidin is oxidized to anthocyanidin and sequentially glycosylated and methylated to form anthocyanins (Mackon et al. 2021). The chalcones are isomerized to flavanones and converted into flavones by flavone synthases (FS I and II). FSII is a group of cytochrome P450 enzymes (CYP93G1) that desaturate naringenin to apigenin (Fig. 4), which is hydroxylated to luteolin followed by esterification to form chrysoeriaol, hydroxylation to form selgin, and final esterification to form tricin (Lam et al. 2015). Regarding the medicinal/physiological properties and functions of other compounds of rice concerning human health, the Ayurvedic treatise indicates the prevalence of medicinal rice varieties in India (Das and Qudhia 2001). Both Njavara and Jyothi are red rice; however, only Njavara is considered to have medicinal properties (circulatory, respiratory, and digestive systems). Antioxidant contents and capacities of pigmented rice were much higher than white rice (Pramai and Jiamyangyuen

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Fig. 4 Tricin biosynthesis pathway (Lam et al. 2015)

2016). Njavarakizhi is prepared by cooking Njavara rice in milk, with herbs, like Sidarectusa and Alpinia galanga, for the treatment of paralysis, arthritis, and neurological problems (Das and Qudhia 2001). Antioxidant, antiarthritic, antidiabetic, and antigastritis (peptic ulcers) activities were observed in Kavuni rice (Valarmathi et al. 2015). Karungkavuni is useful to cure elephantiasis and contains antioxidant, hypercholesteremic, hepatoprotective, anti-inflammatory, cancer-preventive, and antimicrobial compounds (Kalaivani et al. 2018). In black rice (Longjin), cyanidin-3,5-diglucoside is the major compound (Hou et al. 2013). Ethanol extract of black rice bran (EEBRB) contains 3.28  0.34 mg/

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100 g of anthocyanin content, which can regenerate pancreatic β-cells (Wahyuni et al. 2016), particularly cyanidin-3-glucoside (Tantipaiboonwong et al. 2017) which competes with glucose (having glucose moiety) to get absorbed through GLUT2 (Kroon et al. 2004) and inhibits glucose absorption (Kamiloglu et al. 2015). Despite the effector compound yet to be identified, extracts of black or red rice can inhibit the multiplication of breast cancer cells (Ghasemzadeh et al. 2018) by inhibiting cytochrome P450 or scavenging free radicals (Insuan et al. 2017). Similarly, purple rice extract was effective against hepatocarcinogenesis (Suwannakul et al. 2015). Tricin has been noted to have antioxidant, anticancer, anti-inflammatory, and cardiovascular properties (Lam et al. 2015). It inhibits cyclooxygenase I, which leads to the reduction of prostaglandin E2 (PGE2) and the inhibition of colorectal cancer cells. The vitamin E tocotrienols (0.08 mg/100 g) and tocopherols (1.09 mg/100 g) in nonpigmented rice (Longvah et al. 2017) are lesser than in pigmented rice (Irakli et al. 2016). The antioxidant activity of oryzanol is due to ferulic acid moiety. It inhibits cholesterol oxidation and lipid peroxidation in retinal homogenates under oxidative stress (Hiramitsu and Armstrong 1991) and can kill leukemia cells (Parrado et al. 2006). The scavenger receptor class B type I (SR-BI) on enterocytes, CD36 membrane protein at the border of duodenum and jejunum, and NPC1-like transporter 1 (NPC1L1) is a major sterol transporter in the intestine that help in the uptake of carotenoids, fat-soluble vitamins, long chain fatty acids, etc. (Reboul 2019). The ecological and climatic conditions were reported to influence the anthocyanin and bran oil content. Anthocyanin content was higher in two genotypes in the lowland and others in the highland. Similarly, antioxidant capacity was fourfold higher in lowland and other in highland (Rerkasem et al. 2015). Rice experiences high temperature during the grain filling stage of the dry season. In the AICRIP trial, high-temperature conditions (4–5  C higher than the control) were created, covering the treatment with a polythene sheet. In eight entries, bran oil content ranged from 10.5–12.5 and 5.8–13.0 g/100 g bran in control and high-temperature stress, respectively. The octanoic acid peak was higher while the palmitoleic acid peak was smaller under treatment in susceptible.

2.5

Iron (Fe) and Zinc (Zn)

Around 3.1% and 0.9% of 3177 germplasm showed Zn content 35 and 40 mg/ kg, respectively (Sanjeeva Rao et al. 2020). As the maximum Zn content in germplasm is four- to fivefold higher than the cultivars, high Zn varieties (24 mg/kg) were released (Table 8). For Fe, diversity in germplasm itself is narrow, and moreover, 70% is lost during milling. Hence, biotechnological tools were used to release 1 (the Philippines), 1 (Latin America), and 3 (Bangladesh) varieties having high Fe of 7–10 mg/kg in polished and 13–31 in brown rice.

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Table 8 List of high Zn (mg/kg) biofortified rice varieties released

3 4 5 6

Name of varieties DRR Dhan 45 Chhattisgarh Zn Rice 1 DRR Dhan 48 DRR Dhan 49 Surabhi GR-15

7

Surabhi

22.84

19

8

Zno Rice-MS

27.4

20

9

22–24

22

10

Chhattisgarh Zn Rice-2 DRR Dhan 63

24

23

11

CR Dhan 315

24.9

24

S. No Country 1 India 2

12

Philippines NSICRc460

Zn 22.3 22–24

Name of Sl. no. Country varieties 13 Bangladesh Binadhan 20 14 BRRI Dhan 62

Zn 26.5 19.6

20.91 26.13 22.84 21.58

15 16 17 18

25 24.2 27.6 21.8

19.6

Indonesia

LAC

BRRI Dhan 64 BRRI Dhan 74 BRRI Dhan 84 BU Aromatic Hybrid Dhan-1 BU Aromatic Dhan-2 INPARI 47 Nutri Zn INPARI IR Nutri Zn CENTA A-Nutremas CIAT BIO-44 +Zn Fedearroz BIO Zn 035

22 29.54 26 22.86 25 26

The recommended dietary allowance (RDA) of Fe and Zn for the human population (25–50 years of age) are 10–15 and 12–15 mg, respectively. In India, the average daily intake of rice is 220 g, and polished rice having 45.5–68.2 mg/kg Fe and 54.5–68.2 mg/kg Zn can only meet the RDA without considering the bioavailability (Sanjeeva Rao et al. 2014). As the maximum Zn in brown rice is 45 mg/kg, it may not be possible to get varieties >50 mg/kg through conventional breeding coupled with Zn-deficient soils. Strategies are to be chalked out to test rice’s actual genetic potential with sufficient Zn experimental fields. If the grain Zn content is still 80% in oil. These genes play a central role in metabolizing the oleic acid (monounsaturated fatty acid) into linoleic acid (polyunsaturated fatty acid) (Demorest et al. 2016). Recently, biofortified tomatoes enriched with vitamin D have been developed using genome editing. 7-Dehydrocholesterol reductase (Sl7-DR2) gene was knocked out using CRISPR/Cas9 for higher accumulation of provitamin D3 in genome-edited tomatoes. In rice also, increased resistant starch and low casein accumulation traits have been attempted by targeting SBEI, SBEIIb, and OsHAK-1 genes through CRISPR/ Cas9 approach. These genes regulate amylose content and calcium uptake phenotypes (Nagamine and Ezura 2022). The key regulatory genes regulating grain iron and zinc content in rice can be edited through various approaches of genome editing, including base editing and prime editing, to create superior alleles in popular rice cultivars. This approach can be instrumental in achieving the mission of nutritional security.

6

Conclusion

Rice, the paramount grain for ages, has shaped human civilization and played a critical role in food security. With the increasing population, the concomitant development and release of high-yielding rice cultivars played a significant role in feeding >7.98 billion people on this planet. The past two decades have brought revolutionary changes in breeding technologies. We have witnessed the wise and efficient use of marker-assisted breeding, genomics, transgenics, and genome editing to accelerate breeding efforts and make them more precise and targeted. Several cultivars with added traits of economic importance have been developed using these biotechnology-based breeding approaches. In particular, CRISPR/Cas9 genome

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editing technology can address many unsolved breeding questions and can be smartly used to breed new cultivars for present and future needs (Fig. 6). While food security will always remain a primary goal, nutrition security is equally essential, specifically in the developing world. Special programs by various governments have been implemented to minimize the adverse effects of malnutrition. However, it is still prevalent in places where rice constitutes the central portion of the diet. Therefore, enriching the rice grain with micronutrients and vitamins can address the severe issue of malnutrition. New genomics and genome modification approaches can be used to biofortify rice crops. In addition to discovering new genes and alleles, the known genes and natural genetic variations must be exploited through breeding and genetic engineering to develop biofortified rice varieties. The regulatory genes and transcription factors determining the loading of micronutrients in rice grain are primary targets for making the rice grain more nutritive. In addition, efforts should be made toward reducing the antinutritional factors such as phytate in rice grain. Targeted breeding programs and the introduction of nutritionrich rice in the food supply chain will play a key role in achieving the goals of “food and nutritional security.” To promote the cultivation of biofortified crops, incentives by the government and special prices for farmers’ produce will significantly impact the success of these programs. The goal of zero hidden hunger and starvation is achievable with the focused and coordinated efforts of researchers, funding agencies, policymakers, industries, and farmers.

Fig. 6 Genetic strategies toward the development of nutraceutical rice varieties

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Wheat Nutraceutomics: Breeding, Genomics, Biotechnology, and Nanotechnology Velu Govindan, Om Prakash Gupta, Sunil Kumar, Chandra Nath Mishra, and Gyanendra Singh

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 The Importance of Wheat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Wheat’s Importance in Times of Chronic Disease and Malnutrition . . . . . . . . . . . . . . . . . . 1.3 The Limitations of Conventional Breeding and Rational for Next-Generation Breeding: Nutritional Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Detailed Nutritional Composition of the Wheat Grain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Carbohydrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Dietary Fiber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Proteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Lipids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Tocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Minerals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Marker-Assisted Breeding for Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Germplasm Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Marker-Assisted Gene Introgression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Gene Pyramiding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Identification, Cloning, and Characterization of Health-Related Genes/QTLs . . . . . . . . . . . . . 5 Genomics-Aided Breeding for Heath-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Role of Nanotechnology for Nutritional Improvement of Wheat . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Role of Genome Editing Technology in Wheat Nutritional Quality Improvement . . . . . . . . . 8 Nutritional Improvement in Wheat Quality Using Genetic Engineering . . . . . . . . . . . . . . . . . . . . 9 Conclusion and Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

62 62 63 64 65 66 67 67 67 68 69 69 70 71 71 72 73 74 77 78 78 80 80

V. Govindan (*) International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico e-mail: [email protected] O. P. Gupta · S. Kumar · C. N. Mishra · G. Singh (*) ICAR-Indian Institute of Wheat and Barley Research, Karnal, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_2

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Abstract

Wheat is humanity’s second most important cereal crop, consumed widely in developed and developing countries and constituting a major source of protein and energy, especially in the developing world. Wheat grain, including the bran and endosperm, furnishes diverse macro-and micronutrients required for the normal physiological and biochemical functioning of the human body. Dietary deficiencies of micronutrients such as iron (Fe) and zinc (Zn) lead to severe health consequences in children below 5 years of age and in pregnant women and lactating mothers. Increasing the nutritional value of wheat grain can largely address micronutrient malnutrition for the world’s growing population. The recent availability of wheat genome sequence library in the public domain, together with the expanding horizon of next-generation sequencing, and genome editing technologies, holds great promise for trait-based molecular breeding to develop nutrient-rich wheat cultivars. Modern biofortification techniques, including conventional breeding, transgenics, and agronomic biofortification, have already increased wheat grain nutrient content and the nutrient-rich biofortified wheat cultivars grown over 2 million ha area in South Asia & Latim America. This chapter discusses the importance of wheat in the human diet, wheat grain’s nutritional composition, and advances in molecular and transgenic and genome editing approaches to develop health-related traits in wheat grain. Keywords

Micronutrients · Malnutrition · Genome editing · Genomic selection · QTLs · Genetic engineering

1

Introduction

1.1

The Importance of Wheat

Wheat, an annual herb belonging to the family Gramineae or Poaceae, is a food crop grown and consumed in nearly 100 countries and imported and consumed in many others where western-style diets are being adopted (Cummins and Roberts-Thomson 2009; Shewry 2009). Common hexaploid wheat (Triticum aestivum L., 2n ¼ 6x ¼ 42, AABBDD) is one of the most important staple crops in the world, serving as a key food source for 30% of the human population and contributing approximately 20% of its energy needs (calories) and 25% of its dietary protein (Borisjuk et al. 2019). Its grain is used in bread, supporting the baking industry, and popular foods such as chapatis, noodles, and cookies, to name just a few. Worldwide wheat cultivation ranges from 67 N in Scandinavia and Russia to 45 S in Argentina, including elevated regions in the tropics and sub-tropics (Feldman 1995; Shewry 2009). About 95% of wheat grown worldwide is hexaploid bread wheat (Triticum aestivum L.), with most of the rest being tetraploid durum wheat (T. turgidum var. durum), which

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is adapted to dry, Mediterranean climates and used in pasta. Minor amounts of primitive wheats are also grown mainly for specialty health foods, including einkorn (diploid Triticum monococcum), emmer (tetraploid T. turgidum var. dicoccon), and spelt (hexaploid T. aestivum var. spelta) in certain areas of Spain, Turkey, the Balkans, and the Indian subcontinent. The latter differs from bread wheat essentially in that the hull is not removed by threshing, resulting in a higher fiber content when consumed as whole grain (Brouns et al. 2013). Cultivation of wheat started about 10,000 years ago as part of the Neolithic Revolution, when humans switched from hunting and gathering to settled agriculture. The earliest cultivated forms were diploid (einkorn with genome AA) and tetraploid (emmer with genome AABB) wheats from southeastern Turkey (Brouns et al. 2013; Dubcovsky and Dvorak 2007). Hexaploid bread wheat (AABBDD) is believed to have emerged some 9000 years ago through spontaneous hybridization between a cultivated tetraploid (Triticum turgidum; AABB) and goat grass (Aegilops tauschii; DD) (Brouns et al. 2013; Feldman 2001). The earliest cultivated forms were landraces presumably selected from wild populations by ancient farmers, considering their superior yield and other agronomical important characteristics, a domestication that separated modern wheat genetically and phenotypically from its wild relatives and early forms. Wheat grain production amounted to over 780 million tons (t) harvested from more than 225 million hectares (ha) in 2019–2020 (http://www.fao.org/faostat); but wheat is still the third major food crop, lagging behind maize and rice both in yield and the application of genomic tools for crop improvement (Borisjuk et al. 2019; Uauy 2017). Average wheat yield worldwide increased nearly three-fold during the Green Revolution of the mid-to-late twentieth century, largely due to expanded irrigation, intensive fertilizer application, and advanced breeding methods (Evenson and Golin 2003a), but the current global average yield around 3 t/ha is far below the crop’s genetic potential (Langridge 2013), aside from yield gaps relating to crop management. As estimated by Langridge (2013) and Henry et al. (2016), to meet the wheat consumption demands (expected to rise 1.6% annually) of an estimated 9.5 billion world population by 2050, wheat yields should grow by over 60% to approximately 5 t/ha, coupled with maintaining or improving its nutritional characteristics and using currently available land. Facing this challenging scenario, which includes rising temperatures and alarming water scarcities, the emphasis must be on improved productivity and adapting to environmental challenges (Borisjuk et al. 2019).

1.2

Wheat’s Importance in Times of Chronic Disease and Malnutrition

Malnutrition can be classified as under-nutrition (hunger, micronutrient malnutrition/ hidden hunger) and over-nutrition (overweight/obesity). For malnourished children under 5 years of age, 149 million are stunted, 49.5 million are wasted, and 40 million are overweight (Development Initiatives 2020; Poole et al. 2021). About 45% of

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mortality among children aged five and below is associated with malnutrition, chiefly in low- and middle-income countries. In the early 2000s, more than 3 billion people were micronutrient malnourished (Šramková et al. 2009). More recently, some 528 million (29%) women of reproductive age are anemic from a lack of dietary iron, making iron deficiency the most widespread micronutrient deficiency in the world (Choge 2020). Dietary deficiencies of zinc, a critical micronutrient, are widespread, accounting for malnutrition-related developmental impediments across all age groups. Lethal effects amount to 800,000 child deaths annually, with vulnerability concentrated in sub-Saharan Africa and South Asia. Staple cereals such as wheat are significant sources of both minerals, contributing 44% of the daily intake of iron (15% in bread) and 25% of the daily intake of zinc (11% in bread) in the UK (Henderson et al. 2007; Shewry 2009). According to an estimate, almost 690 million people suffered from hunger in 2019, worsened by the worldwide COVID-19 health pandemic. The number of hungry people is expected to exceed 840 million by 2030 – almost 10% of the global population (Poole et al. 2021). While humankind is fighting malnutrition on one front, over-nutrition is increasing globally: nearly half of the world’s adult population is overweight or obese, and three-quarters of those persons live in low- and middle-income countries (Poole et al. 2021). Worldwide incidences of diabetes (44%), ischemic heart disease (23%), and certain cancers (7–41%) are linked to being overweight and obese. Child stunting often results from micronutrient malnutrition tied to imbalanced diets in children and mothers, especially among the poor. Food-based approaches to prevent malnutrition and which focus on micronutrients can help address “hidden hunger.” Cereal-based allergies and intolerance have also posed serious concerns. Major chronic diseases include obesity, heart ailments, cancer, and celiac disease, among others, taking a heavy toll on health and the world economy. In the current context of chronic diseases, wheat, its bioactives, and products assume relevance and need to be deliberated in a multifarious context.

1.3

The Limitations of Conventional Breeding and Rational for Next-Generation Breeding: Nutritional Perspectives

Wheat underwent hybridization and genome duplication to generate its hexaploid genome (2n ¼ 6x ¼ 42, AABBDD). Bread wheat possesses a sesquipedalian genome – 17 gigabases – which is over 5 times larger than the human genome and 40 times the size of the rice genome. Recent estimates document 107,891 highconfidence genes in bread wheat, with over 85% repetitive DNA sequences, representing a three-fold redundancy associated with being hexaploid. Every year, conventional commercial breeding produces a large number of new crop varieties to improve productivity and nutrition, strengthen food security, and increase consumer acceptability (Govindan et al. 2022). The conventional breeding process has evolved to provide an effective framework for improving crop performance while also assisting in the development of safe and nutritious foods. Conventional plant breeding entails identifying desirable parents in order to create favorable combinations in the next generation (Kaiser et al. 2020). This selection of a few individuals

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from a large population is an important component of the plant breeding process (Kaiser et al. 2020). Conventional breeding has made significant contributions to large-scale cultivation, yield potential, and the frequency of desirable traits in wheat; however, it has certain boundaries that should be considered under current conditions, and a new wheat breeding strategy is required (Borisjuk et al. 2019). Wheat’s hexaploid genome and associated functional gene redundancy make genetic advances to selecting a desired phenotype difficult, if not impossible, due to gene linkage or gene drag. Further advancement in wheat breeding is dependent on understanding of functional genomics. Grain yield and quality can be improved by identifying the most important key genes, as well as their structures, roles, and functions in wheat plant development. This functional genomics knowledge can then be used to change the structures and functions of selected key genes via genetic manipulation (Borisjuk et al. 2019), a broad term used here to describe molecular methods whose products fall outside the traditional definition of “genetically modified” (GM) such as RNA interference (RNAi) and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (CRISPR/Cas9) Borisjuk et al. 2019). Such approaches will be critical in determining the functions of wheat genes. By using cutting-edge technology like genome sequencing and targeted mutations using genome editing methods like CRSPR-Cas and RNAi, it is possible to increase the resilience of wheat while reducing environmental pollution (Gupta and Karkute 2021). However, the use of CRISPR/Cas systems depends on knowledge of the targeted gene’s sequence. Through homology directed repair (HDR), precise substitution of an existing allele has substantially benefited crop improvement with elite alleles in commercial types. Base editing, prime editing (PE), genome sequencing, genome-wide association study (GWAS), speed breeding, high-throughput genotype and phenotype profiling, and synthetic biology are a few examples of contemporary methods (Gupta et al. 2022). The ability to accurately replace one base with another by base editing, an alternative and powerful method for HDR-mediated gene replacement, has made it possible to accurately replace an allele with a single nucleotide polymorphism (SNP) (Komor et al. 2016). Many base substitutions (12 types) and minor insertions-deletions (indels) are made possible by prime editing (PE), which increases the reach and potential of precision genome editing. Recent studies have shown that RNAi, a frequent mechanism for controlling gene expression in eukaryotic cells, is a reliable tool for functional genomics and the engineering of novel phenotypes. The method relies on the expression of small interfering RNA (siRNA) molecules, such as antisense or hairpin RNAi constructs, to affect post transcriptional gene silencing in a sequence-specific manner (Borisjuk et al. 2019). RNAi applications in wheat.

2

Detailed Nutritional Composition of the Wheat Grain

Grain is the harvested and economically important part of the wheat plant, and its biochemical composition determines its nutritional and health properties (Shewry 2009). Table 1 details the generalized composition of various chemical constituents. On a dry weight basis, a wheat grain can be divided into three distinct parts: mealy

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Table 1 Contents and variations in chemical composition of wheat grains (dry weight) Parameter Carbohydrates (%) Starch (20–30% amylose and 70–80% amylopectin) Dietary fiber/non-starch/cell wall polysaccharides (%) Fats (%)

Range (%) 85 55–75

References Stone and Morell (2009) Borisjuk et al. (2019)

11.5–15.5

Andersson et al. (2013)

2.0–2.5

Gonzalez-Thuillier et al. (2015)

endosperm (80–85%), outer bran (13–17%), and germ (2–3%). (Belderok et al. 2000). The endosperm occupies the majority of the wheat grain, primarily consisting of starch and proteins with small amounts (2%) of fiber. The endosperm provides energy to the seed, making available carbohydrates and proteins during germination. The germ, the smallest segment of grain, contains lipids, sterols, antioxidants, vitamins (B, E), minerals, and enzymes, as well as nourishing the seed. The bran is a seed’s outer shell that contains fiber, vitamins, and trace minerals. The outer pericarp (3–5%) contains insoluble dietary fibers and bound phenolic acids (which act as antioxidants), whereas the aleurone layer (6–9%) contains dietary fibers, proteins, enzymes, phenolic compounds, vitamins (B-complex), minerals, and phytates. The testa (1% of the total) contains trace amounts of alkylresorcinols, sterols, and steryl ferulates. Wheat bran may typically contain dietary fiber (42.8%), other carbohydrates (21.7%), protein (15.6%), ash (5.8%), and lipids (4.3%). There is a need for suitable and efficient methods to test diverse wheat genotypes for various quality parameters, as documented in the updated listing by Gupta et al. (2022). Model-based methodologies are being developed to identify superior wheat lines in early generations of breeding cycles (Mohan et al. 2022).

2.1

Carbohydrates

Carbohydrates account for the majority of wheat grain (up to 85%) (Stone and Morell 2009). Starch accounts for the majority of stored carbohydrates, accounting for 55–75% of grain dry weight (Borisjuk et al. 2019). Fibers and low-molecularmass mono-, di-, and oligo-fructans are examples of others (Table 1). Wheat grain starch is found in either large lenticular granules of 25–40 m, which develop during the first 15 days after pollination, or small spherical granules of 5–10 m, which develop 10–30 days after pollination and account for approximately 88% of total grain starch granules (Belderok et al. 2000). Starch is a polymeric form of glucose that is chemically classified as amylose and amylopectin. Amylose has a molecular weight of around 250,000 and may contain nearly 1500 glucose units with wide variations. Amylose is thought to have a linear polymer structure, with -(1,4)glycosidic linking glucose moieties together and a degree of polymerization (DP) of 1000–5000 glucose units. The structure of this polymer was previously assumed

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to be primarily linear, but this appears to be true for only a portion of the amylose; the remainder is slightly branched. The branching in amylopectin is to a much greater extent than in amylose and the average unit chain of amylopectin has only 20–25 glucose molecules, with an average molecular weight of about 108. Amylopectin is a much larger polymer with a DP ranging from 105 to 106 glucose units tethered via α-(1,4)-linked glucose polymers, which are further connected by α-(1,6)-linkages (5–6%).

2.2

Dietary Fiber

Dietary fiber is defined as lignin plus plant polysaccharide components that are indigestible by human digestive enzymes. While soluble fiber (pectic substances, hydrocolloids, -glucans) is water soluble, insoluble fiber (cellulose, hemicellulose, lignin, arabinixylans) is not. Regular consumption of dietary fiber, which is primarily found in whole grains, protects against heart disease, hypertension, hyperlipidemia, type 2 diabetes, obesity, constipation prevention, diverticular disease, esophageal disease, and a variety of cancers (Poole et al. 2021; Weickert and Pfeiffer 2008). Soluble fiber such as β-glucan [(1!3,1!4)-β-D-glucan] effects glycemic index and appears to help prevent chronic diseases like diabetes and obesity and, possibly, negative effects associated with FODMAPS (fermentable oligo-, di-, monosaccharides and polyols) (Poole et al. 2021). Arabinoxylans (AX) and (1!3), (1!4)-β-glucans are housed primarily in wheat endosperm cell walls. Arabinoxylans yield short-chain fatty acids, particularly butyrate, in the colon. It is conjectured that high butyrate concentrations in the colon improves bowel health and lower cancer risk.

2.3

Proteins

Proteins are required for various body functions, ranging from enzymatic, structural to locomotory and many more. Protein content in wheat grain ranges from 10 to 15% (dry wt.) (Borisjuk et al. 2019). Wheat proteins are classified according to their extractability and solubility as per Osborne and have been highlighted in Table 2 In general, cereal proteins are low in the essential amino acids lysine (1.5–4.5% vs. 5.5% of WHO recommendation), tryptophan (Trp, 0.8–2.0% vs. 1.0%), and threonine (Thr, 2.7–3.9% vs. 4.0%).

2.4

Lipids

Lipids are present in small amounts (2–2.5%) in wheat but have a significant impact on food quality and texture because they can bind to proteins and starch to form inclusion complexes. The germ contains nearly 11% of total lipids, but significant amounts are also associated with the endosperm’s bran, starch, and proteins

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Table 2 Types of wheat proteins with their solubility and other features Protein name Albumins

Solubility Water soluble

Globulins

Insoluble in pure water; soluble in dilute NaCl solutions, but insoluble at high NaCl concentrations

Gliadins

Soluble in 70% ethyl alcohol

Glutenins

Soluble in dilute acid or sodium hydroxide solutions

% of Total protein Smallest in size (10%) Size more than albumins (10%)

Size more than above two (45%) Low- and highmolecularweight types (35%)

Features Most of physiologically active enzymes belong to these two; both proteins are present in the seed coat, the aleurone cells and the germ, with a lower concentration in the mealy endosperm; both make up 20–25% of total wheat proteins High-molecular-weight storage proteins for future use by the seedling located in the mealy endosperm; both constitute 75–80% of total wheat proteins; both are unique, being biologically active: though they have no enzyme activity, they function in dough formation through gas retention, producing spongy baked products

Source: Belderok et al. (2000), Borisjuk et al. (2019), Šramková et al. (2009)

(Poole et al. 2021). All fractions contain significant amounts of free fatty acids and triacylglycerols (Gonzalez-Thuillier et al. 2015). Phosphatidyl choline, phosphatidyl ethanolamine, and phosphatidyl serin are the most common bound lipids, followed by lysophosphatidyl derivates with one free hydroxyl group on the glycerol moiety. The main sterols were identified as -sitosterol, campesterol, and saturated sterols C28 and C29. Numerous studies have shown a high level of linoleate (C18:2) in both the total lipid and the triglycerides.

2.5

Vitamins

Over 3 billion people are currently micronutrient malnourished, which means their diets are deficient in micronutrients such as vitamins. Vitamins are a diverse group of food-based, essential, small organic substances that are synthesized by plants and microorganisms rather than the human body. They do not provide energy but are essential micronutrients for humans, acting as coenzymes or their precursors (niacin, thiamin, biotin, pantothenic acid, vitamin B6, vitamin B12, and folate) or in specialized functions such as vitamin A in vision and ascorbate in specific hydroxylation reactions. Vitamins play roles in human genetic regulation and genomic stability (folic acid, vitamin B12, vitamin B6, niacin, vitamin C, vitamin E, and vitamin D) as well as antioxidative defense systems (vitamins C and E and some carotenoids) (Poole et al. 2021). The vitamins in wheat and their range are presented in Table 3.

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Table 3 Vitamins, phenolics, minerals, and anti-nutritional factors composition in wheat grains Major component Vitamins

Minerals

Phenolics Anti-nutritional factors

2.6

Name Vitamin B1 (Thiamine) (mg/kg) Vitamin B2 (Riboflavin) (mg/kg) Vitamin B3 (Niacin) (mg/kg) Vitamin B5 (Pantothenic acid) (mg/kg) Vitamin B6 (Pyridoxine) (mg/kg) Vitamin B9 (Folates) (mg/kg) Magnesium (mg/kg) Iron (mg/kg) Zinc (mg/kg) Copper (mg/kg) Manganese (mg/kg) Phenolic acids (μg/g) Phytic acid (mg/g)

Range 5.53–13.55

References Shewry et al. (2011)

0.77–1.40 0.16–1.74 0.88–4.04 (Durum) 1.44–3.05 0.323–0.774 600–1400 18–40 21–63 1.8–6.2 24–37 326–1171 12–18

Tekin et al. (2018) Batifoulier et al. (2006) Piironen et al. (2008) Oury et al. (2006) Ram and Govindan (2020)

Tocols

The germ fraction of t einkorn accessions and some bread wheat seed showed the highest concentrations of -tocopherol and total tocols. The bran fraction had the highest levels of -tocotrienol, but significant amounts were also found in the flour.

2.7

Minerals

Table 3 summarizes the minerals that are available in wheat, as well as their generalized availability ranges. The topic of two vital minerals, iron and zinc, has been addressed here. Plants primarily store iron in the form of ferritin structures, which accumulate primarily in non-green plastids, etioplasts, and amyloplasts (Borisjuk et al. 2019). Iron has been found primarily in the aleurone layer (bran) of wheat grains, where it has complexed with phytate (myo-inositolphosphate 1,2,3,4,5,6-hexa-kisphosphate). These complexes are insoluble, limiting iron bioavailability in humans and livestock. Scientists are experimenting through breeding to express phytase enzymes in developing grain and thus increase mineral availability. The discovery of a heat-stable form of this enzyme would allow phytate complex hydrolysis to occur during food processing. Another option is to increase the concentration of Fe in grains. In 1994, Fe concentrations in a wheat variety grown at the CIMMYT research station in El Batán, Mexico, ranged from 28.8 to 56.5 mg/kg (mean ¼ 37.2 mg/kg). Peleg et al. (2008) reported new wild emmer wheat accessions with very high Fe (up to 88 mg/kg) and Zn (up to 139 mg/kg)

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Fig. 1 Localization of zinc in wheat grain with μXRF (left high zinc wheat ‘Zinc-shakti’, right CIMMYT control variety ‘Baj’)

concentrations, as well as high protein content (up to 380 g/kg) and tolerance to drought and Zn-deficient soils. Zn deficiency causes nearly 500,000 deaths in children under the age of five each year (Borisjuk et al. 2019). Micronutrient levels in modern elite wheat cultivars are typically suboptimal. Given the high concentrations of Zn and Fe in the outer husk, aleurone, and embryo, both micronutrients are lost during milling and polishing. Phytate, an anti-nutritional factor, reduces micronutrient availability in the human digestive tract. Zn deficiency affects nearly 33% of the world’s population, resulting in health complications such as stunted physical development, weakened immunity, and decreased learning ability, among other things. According to a variety of reports and survey studies, the average Zn concentration in whole wheat grain is from 21 to 63 mg/kg (Ram and Govindan 2020). Most of wheat grain Zn is in the embryo and aleurone layer, with a small portion in the endosperm (Fig. 1).

3

Marker-Assisted Breeding for Health-Related Traits

Genetic tools can accelerate genetic gains for yield and stress resilience by assisting in precise and accurate selection, saving time, money, and labor in crop improvement. Breeding approaches combine modern cutting-edge genomic tools and breeding tools to accelerate breeding progress. Molecular marker-assisted selection (MAS), backcross breeding (MABB), and recurrent selection (MARS) aid in the early identification of favorable alleles for economically important traits (Bonnett et al. 2005). It should also be noted that the requirements for selecting markers, as well as overestimation of marker effects with minor contributions, can limit the effectiveness of using molecular markers in MAS. In wheat, MAS aids in the improvement of agriculturally important traits by allowing efficient screening of

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difficult-to-estimate traits, the transfer of genomic regions from genetic stocks rich in desirable traits into better backgrounds, and the pyramiding of different polygenic characters. The discovery of numerous QTL-specific molecular markers for monogenic and polygenic traits in recent years has accelerated the deployment of molecular markers for regions associated with biotic and abiotic resistance, as well as other economically important traits. The cost of more precise genotyping, high-throughput genotyping and phenotyping, and the use of imaging and computational traits have all reduced the cost of biotechnological tools.

3.1

Germplasm Characterization

The high level of variability in nutritional traits found in wild relatives and land races of wheat allows for the development of high-yielding nutrient-rich wheat varieties (Cakmak 2008). The traits required for desirable processing and end-use quality, as well as nutritional traits, are being transferred from wild relatives of wheat, such as Aegilops tauschii, Triticum turgidum ssp. diccocoides, Triticum turgidum ssp. dicoccum, and Triticum aestivum ssp. spelta species, to high-yielding bread wheat lines that feature high yield and better adaptation (Guzmán et al. 2014). T. dicocconbased synthetic hexaploids, landraces from Iran, Spain, and Afghanistan, and T. dicoccoides from Israel and adjacent regions are being used to improve micronutrients. CIMMYT Mexico has a large collection of genetic resources in its germplasm bank near Mexico city. Screening for micronutrient variability has demonstrated that landraces and wild relatives of common wheat such as T. spelta and T. dicoccon have the ample amount of Zn and Fe. Contemporary breeding methods employ limited backcrossing procedure to introgress high-Zn/Fe genes from T. spelta, synthetic hexaploids, and landraces into better agronomy genotypes available with the breeders. Ae. peregrina accessions have more than double grain Fe and Zn concentrations than elite wheat cultivars. Some of the derivatives of fertile wheat x Ae. peregrina with bolder seeds, better harvest indexes comparable to those of elite wheat lines, and higher micronutrient concentrations demonstrated that Ae. peregrina possesses a separate genetic system for biofortification, similar to that of Ae. kotschyi. The fertile BC2F2 plants with one or more additional chromosomes from Ae. peregrina showed a 100–200% enhancement of grain Fe and Zn levels over those of normal, elite wheat lines. Further analysis showed that the two chromosome groups 7 and 4 of Ae. peregrina had genomic regions for micronutrient content in wheat.

3.2

Marker-Assisted Gene Introgression

The use of MAS can make conventional wheat breeding programs more costeffective and time-efficient (Gupta et al. 2010). It has primarily been used in wheat for foreground for carrier chromosome or segment selection and background selection for maximum genome recovery. It has recently been used successfully to

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Fig. 2 Trait augmentation program at CIMMYT, Mexico

introduce and pyramid major genes/QTL for desirable wheat characteristics of a major locus (Gpc-B1) on chromosome 6BS that was introgressed from wild emmer wheat (Triticum turgidum ssp. dicoccoides) has improved Fe (18%), Zn (12%), and protein (38%). A marker called Xuhw89, which is closely related to the (0.1 cM) Gpc-B1 locus (Distelfeld et al. 2006), has aided in the development of wheat varieties with high Fe, Zn, and protein concentrations. Many RFLP, SSR, and CAPS markers have been linked to this marker Xuhw89 (Distelfeld et al. 2004). With the cloning and characterization of Gpc B1 locus, a gene-specific marker and the locus has been introduced in wheat, improving GPC without a yield penalty (Kade et al. 2005). This has occurred mostly in many wheat growing regionssuch as India where it has transferred to elite cultivars. The wheat breeding program at CIMMYT recently embarked upon to introgress key agronomic, disease resistance and nutritional quality traits through its speed breeding pipeline (Fig. 2).

3.3

Gene Pyramiding

Functional markers are critical for gene stacking, genomic region transfer, and gene editing procedures. So far, 97 functional markers in bread wheat have been used to establish 30 loci from 93 alleles (Alotaibi et al. 2021). With the advancement of

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genomic studies, the number of alleles has increased, and approximately 157 markers for 100 loci for various traits of economic importance have been identified. Few genes, including VRN1 and Gpc-B1, have been successfully incorporated using the conventional positional cloning approach in wheat. Similarly, genes related to grains, such as TaGS5, TaGS3, and TaCwi-A1 related to grain size; the Psy1 (He et al. 2009) phytoene synthase gene and Zds1 related to zeta-carotene desaturase have been reported using competitive genomics methods.

4

Identification, Cloning, and Characterization of Health-Related Genes/QTLs

Micronutrient effectiveness has a complex nature that is influenced by the environment. It is critical for MAS and map-based cloning to identify the genes/QTLs that influence micronutrient content. Map-based cloning is a method for cloning the gene of interest without prior knowledge of its product. The basic requirement for map-based cloning is a population that has been systematically developed for the desired trait and is suitable for fine mapping. Precision genotyping and phenotyping for the trait aid in the generation of an accurate genetic map indicating the location of the gene. To determine the physical location, two nearby markers are used to screen BAC libraries. The candidate genes are discovered through chromosome walking and target interval sequencing. Significant progress has been made since cloning of the first gene. The gene Gpc-B1 has been positionally cloned in wheat; it is 7.4 kb (md) long and encodes for NAC transcription factors controlling senescence, protein content, and Zn and Fe content. A major QTL (18.3% phenotypic variation) in rice for Fe content on chromosome 8 of rice and shows synteny with chromosome 7 of wheat. Similarly, in a T. durum x T. dicoccoides cross combination, Peleg et al. (2008) discovered a major locus Fe content on chromosome 4 and two co-located loci on chromosome 7 for both Fe and Zn. Discovered major QTL on chromosome 7A for both micronutrients in a T. boeoticum and T. monococcum population. Xu et al. (2012) discovered 9 additive and 4 epistatic QTL on the 4B and 5A chromosomes, indicating a shared inherent basis for the three nutritional traits. Populations of diploid wheats, durum wheats, and wild Emmer wheat (Peleg et al. 2009), as well as synthetic wheats and T. spelta, were used to map QTLs for grain Zn and Fe concentration. In a separate report, Srinivasa et al. (2014) identified 10 QTLs (five each for Zn and Fe accumulation) that were widely distributed across 7 chromosomes. In a DH (doubled haloid) population, two QTLs for Zn content were found on chromosomes 1B and 2B. In addition, four genes governing the inheritance of grain Zn content were discovered in two mapping populations derived from a T. spelta x bread wheat combination (Srinivasa et al. 2014). Identified several QTLs on chromosome 7B accounting for 32.7% of total phenotypic variation for Zn concentration and a single QTL location on 4A accounting for 21.14% of total phenotypic variation for grain Fe content in two RIL populations derived from T. spelta L. and synthetic hexaploid wheat crosses. The majority of studies have found a statistically significant positive

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relationship between grain Zn and Fe concentrations in various environments where QTLs or similar genetic effects have regulated the Fe and Zn content in wheat. Co-localization of Fe and Zn concentrations has also been shown on chromosomes 2A, 2B, 4BS, and 5A (Xu et al. 2012) and 6B. This co-location of QTLs offers an opportunity to pursue a single marker-assisted program to enhance the concentrations of both Zn and Fe content. Table 4 provides a comprehensive list of major genes/QTLs identified in wheat for various quality traits.

5

Genomics-Aided Breeding for Heath-Related Traits

In wheat, genome-wide association studies (GWAS) have been widely used to investigate the genetics of quantitative traits. In comparison to traditional QTL mapping, GWAS provides better QTL resolution and wider allelic coverage, and it can be used on a larger population of genetic resources, landraces, varieties, or advance lines. Only a few studies in wheat have been conducted to better understand the genetic mechanism of quality characters. Nonetheless, improved genotyping facilities and access to the wheat genome reference sequence, RefSeq v.1.0, can speed up the identification and prediction of markers and their effects on trait. It would improve trait mapping, gene discovery. Detection of SNP markers that are distributed genome wide offers new avenues for genetic improvement of bread wheat for yield and traits of economic importance (Juliana et al. 2019). GWAS and interval mapping studies in wheat have resulted in the identification of hundreds of markers for improving Fe and Zn concentration, but only a few have been used in marker-assisted breeding for nutritional traits. The only example is the Gpc-B1 gene, which has been used to improve Fe, Zn, and Protein concentration in wheat using a MAS approach. Developed chromosome substitution lines in the variety ‘Langdon’ (LDN) and reported that a locus QGpc.ndsu-6B with a phenotypic variation of 66% is located on the 6B chromosome and contributes to high GPC. The wild allele at the locus accelerates leaf senescence and reduces grain size, resulting in yield reduction. Gpc-B1 regulates senescence and nutrient remobilization, according to studies. Normally, wheat cultivars carry a non-functional NAM-B1 allele, which is produced by a frame shift mutation in the wild allele, and this non-functional allele was preferred during wheat domestication. The presence of this allele on chromosome 6BS in wheat (Brevis and Dubcovsky 2010) allows for more time for grain development, which increases grain size and yield. In a study of 367 global bread wheat genotypes, only 5 Fennoscandian cultivars were found to have functional Gpc-B1 or NAM-B1 alleles, and these genotypes were only present for a short time in northern Europe. According to the wild-type/functional Gpc-B1 allele has been conserved during the process of domestication. The MAS to transfer the wild-type Gpc-B1 gene from Canadian to Australian varieties and found no yield penalty. Reported function loss caused by GPC1 and GPC2 mutations. GPC was found to be negatively associated with grain yield and influenced by genetic background in the majority of studies (Brevis and Dubcovsky 2010), and it is positively correlated with protein, iron, and zinc content with slight negative effect on yield. It is also suggested

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Table 4 QTLs for Fe, Zn, and Selenium content in the grain of wheat and wild species S. No 1. 2. 3. 4. 5. 6.

7. 8. 9. 10. 11. 12. 13.

14.

15.

16. 17. 18. 19.

20. 21. 22.

Cross/parents Triticum dicoccoides Triticum dicoccoides Hexaploid wheat (6x) W7984  Opata85 Hanxuan l0  Lumai 14 RAC875-2  Cascades RIL (Triticum boeoticum  Triticum monococcum) Tetraploid wheat (4x) Langdon  Accession #G18-16 RIL (Xiaoyan  54 Jing 411) Tabassi  Taifun Tetraploid wheat (4x) LDN  G18-16 Berkut 9  Krichauff SHW L1  Chuanmai32 & Chuanmai32  Chuannong16 RIL (PBW343  Kenya Swara)

Traits QTLs Fe & Zn GPC-B1 (6 7 BS) Fe & Zn TtNAM-B1

Fe

References

QFe.pau-7A, QFe.pau-2A

Fe & Zn QZn-5A, QFe-5A2, QGpc-5A1, QGpc-6A

Peleg et al. (2009) Xu et al. (2012)

Se

Fe, Zn & Se Zn

QGzncpk.cimmyt-1BS, QGzncpk.cimmyt-2Bc, QGzncpk.cimmyt-3AL RIL (T. spelta (H+ Fe & Zn QZn.bhu-2B, 26 (PI348449)  T. aestivum QZn.bhu-6A, cv. HUW 234) QFe.bhu-3B DH (Berkut  Krichauff) Fe & Zn QGfe.ada-2B, Hexaploid (Adana99  70.711) QGfe.ada-2B, QGZn.ada-2B, QGfe.ada-2B, QFe.bhu-2B T. spelta accession H + 26 (PI348449)  HUW 234 Hexaploid wheat (6x) Se SHW-L1  Chuanmai 32 Seri M82  SHW CWI76364 Tetraploid Fe & Zn QGfe.sar-5B& (Saricanak98  MM5/4) Qzneff.sar-6A, Qzneff.sar6B& QGzn.sar-1B, QGzn.sar6B, QGZn.sar-1B Saricanak98  MM5/4 (4  wheat) DH (Berkut  Krichauff) Zn QZn.bhu-1B, QZn.bhu-2 Hexaploid (Adana99  70.711) Zn QGzn.ada-6B, QGzn.ada-1D, QGzn.ada-7B

Pu et al. (2014)

Srinivasa et al. (2014)

Srinivasa et al. (2014) Pu et al. (2014)

Velu et al. (2017)

Velu et al. (2017)

(continued)

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Table 4 (continued) S. No 23. 24.

25.

26. 27. 28. 29. 30.

31. 32.

Cross/parents Traits QTLs Adana99  T. Sphaerococcum (70.711) RIL (Synthetic hexaploid Fe & Zn QGZn.cimmyt-7B_1P2, wheat  Triticum spelta) QGFe.cimmyt-4A_P2, QGZn.cimmyt-7B_1P2, QGZn.cimmyt-7B_1P1 Triticum dicoccon PI94624/ Fe & Zn QGFe.iari-2A, Aegilops squarrosa QGFe.iari-5A, [409]  BCN QGFe.iari-7A and QGFe.iari-7B, QGZn.iari-2A, QGZn.iari-4A, QGZn.iari-5A, QGZn. iari-7A and QGZn.iari-7B Bubo  Turtur Louries  Batelur Roelfs F 2007  Chinese Parental Line Hexaploid wheat (6x) Se Tianong18  Limmai6 WH542  synthetic derivative (Triticum dicoccon PI94624/ Aegilops tauschii [409]//BCN). RIL (163) Jingdong 8  Bainong AK58 Kachu  Zinc-Shakti

References Velu et al. (2017)

to transfer low phytic acid (LPA)-GPC in the cultivars for enhancing Fe and Zn concentration along with grain protein content without yield penalty. Several marker-trait associations (MTAs) for nutritional traits in wheat have been used. A total of 39 Zn MTAs were discovered in two studies, one involving 330 bread wheat genotypes and the other involving 320 genotypes from the Spring Wheat Reference Set (SWRS), with two large-effect QTL regions discovered on chromosomes 2 and 7. CIMMYT developed new biofortified varieties that are 20–40% superior in grain Zn content and agronomically on par with or better than popular South Asian wheat varieties. A GWAS study for grain Zn concentrations in 369 European wheat genotypes identified 40 MTAs on chromosomes 2A, 3A, 3B, 4A, 4D, 5A, 5B, 5D, 6D, 7A, 7B, and 7D, with the important and reliable MTAs having significant effects were localized on chromosomes 3B (723,504,241–723,611,488 bp) and 5A (462,763,758–466,582,184 bp). Reported an increase in the number of MTAs to 161 genomic regions, including recently identified candidate genes for Zn uptake and transport. A GBS study on a panel of 167 Ae. tauschii accessions revealed 5249 markers, as well as wide variability in micronutrient concentrations. Overall, 19 SNP MTAs were found on all 7 chromosomes, with positive associations found for 5 with grain Fe and 4 with Zn content. These associations were found to be associated with

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genes that code for transcription factor regulators, transporters, and phytosiderophore synthesis. With improved genomic prediction accuracy and lower genotyping costs, genomic selection in wheat breeding has gained traction (Juliana et al. 2019; Charmet et al. 2020). In the coming years, the ability of genomic selection to increase genetic gain for quality traits will further transform wheat improvement methodologies. Genomic selection would aid in the rapid selection of desired plant types by using widely distributed markers, estimating the effects of all loci, and accurate prediction of genomic estimated breeding values with precise genotypic and phenotypic data (GEBV). Linear prediction models such as G-BLUP and machine learning algorithms are used to recognize complex data patterns and draw appropriate conclusions, as well as to exploit GxE interactions. Using multi-trait and multi-environmental models improves prediction accuracy and performance in selected breeding. Overall, genomic selection improves selection accuracy while decreasing time and cost for varietal development, particularly for complex characters with low heritability that are difficult to improve using traditional plant breeding methods (Heffner et al. 2009). An efficient genomic selection approach optimizes the statistical prediction model for developing GEBVs based solely on genotyping data for an un-phenotyped population using a precisely genotyped and phenotyped “training” population. This reduces the breeding cycle and allows breeders to dispense with avoidable multi-location and multienvironmental testing of genotypes. When predicting the genotypic value of one panel based on another, prediction accuracy decreased. These findings are consistent with those of who demonstrated the high prediction accuracy in a germplasm set with high variation is used as training population as it has high genomic coverage. The use of efficient genomic selection models in conjunction with precision phenotyping on genetically variable populations will improve prediction accuracy, selection efficiency, and speed up the varietal development process. The addition of GWAS and genomic selection to MAS will undoubtedly shorten breeding cycles and improve the breeders’ equation. As a result, there is enormous potential for scaling up biotechnological approaches with traditional plant breeding for varietal development.

6

Role of Nanotechnology for Nutritional Improvement of Wheat

Nanotechnology has recently emerged as one of the outstanding technologies that can be gradually applied in agriculture for crop biofortification and can largely avoid the drawbacks associated with genetic and traditional agronomic biofortification. Nanomaterials have a variety of advantageous properties, including controlled and slow discharge at target sites, significantly higher absorption capacity, and a high volume to surface ratio for effective use in the production of nanofertilizers (NFs). Because nanofertilizers are used in minute quantities, they prevent the accumulation of residual by-products of chemical fertilizers in soil and thus have a lower environmental impact. Furthermore, nanofertilizers can be generated using biosensors based on soil status and crop nutritional demand.

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Furthermore, NFs have been shown to improve crop performance under various stresses by modulating carbohydrate and protein synthesis, seedling growth, nitrogen metabolism, photosynthesis, and nutrient mobilization from the rhizosphere to specific plant parts. Because of its target-bound slow delivery, even a trace amount of NFs can effectively improve micronutrient levels in grain without negatively impacting the environment. Wheat, as a major staple crop, has always been a driving force behind its use in various types of biofortification and fortification. As with other biofortification strategies, a number of greenhouse or small-scale field studies show that nanomaterials have a positive effect on wheat nutritional content. Largescale experiments in open and enclosed areas are required to assess the benefits and drawbacks of NF-based wheat nutrient enrichment. To increase the use of NFs in large-scale wheat biofortification programs, we must first understand how different nanomaterials, their combinations, and application strategies affect target nutrient levels in different wheat genotypes. Significant attention has recently been directed toward developing appropriate methodologies for applying nanoparticles, as this significantly affects the extent of micronutrient accumulation in wheat plants.

7

Role of Genome Editing Technology in Wheat Nutritional Quality Improvement

Gene editing technology has proven to be an effective tool for modifying desired traits in a variety of crop plants, including wheat. Modifying nutritional traits in crop plants provides several health benefits, particularly in staple crops like wheat. In this section, we will discuss the current progress made in the use of gene editing technology to improve the nutritional quality of wheat. Liang et al. (2017) demonstrated direct editing of the TaGASR7 and TaGW2 genes by introducing the CRISPR-Cas9 ribonucleoprotein complex into immature embryos of the wheat varieties Kenong 199 and YZ814. Created heritable mutations in the TaLpx-1, TaGW2, and TaMLO genes. They also demonstrated that the seed size and thousand grain weight were significantly larger (TGW). They also discovered that TaGW2 has a negative effect on grain size in wheat. In 2019, Jouanin and colleagues investigated the possibility of simultaneously editing multiple genes in the large – and – gliadin gene families.

8

Nutritional Improvement in Wheat Quality Using Genetic Engineering

Biotechnological crop improvement interventions have proven their worth for a variety of crops, including cereals, over the last 2–3 decades. Bt cotton, maize, and golden rice are a few examples. In the case of wheat, various genes determine traits such as starch composition, nutritional profile, and final end product formulation, all of which affect final grain quality. The cloning of the NAC gene Gpc-B1 for

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grain protein content from this accession’s chromosome arm 6BS encodes a transcription factor that accelerates senescence in plant vegetative parts, resulting in increased nutrient mobilization and mineral (iron and zinc) transfer to the grain (Shewry 2009). This could help in the fight against malnutrition. According to USDA World Wheat Collection research, the protein content of wheat grain can range from 7 to 22%, with 33% controlled by genomics and the rest by environmental factors, making breeding for this trait difficult (Vogel et al. 1978). This bottleneck can be circumvented by incorporating sources of variation from exotic bread wheat lines or related wild species, such as Atlas 50 and Atlas 66, which are derived from the South American line Frandoso. Both lines appeared to have multiple genes for high protein content in grain and have been extensively used in Nebraska breeding programs. Johnson et al. (1985) successfully inserted the Atlas 66 gene into the commercial variety Lancota (Johnson et al. 1985; Shewry 2009). Biotechnological interventions have been attempted to increase grain starch while also modulating its quality (Borisjuk et al. 2019). TaRSR1, a wheat homolog of Rice Starch Regulator (OsRSR1), is a transcription factor that negatively regulates the gene expression pattern of some starch synthesis-related enzymes in wheat grains. Downregulation of TaRSR1 resulted in a nearly 30% increase in starch content and a 20% increase in yield (Kang et al. 2013). Increased amylose in starch contributes to resistant starch (RS) in food, which can offer protection from health conditions such as diabetes, obesity, and cardiovascular diseases, many of which are chronic diseases (Borisjuk et al. 2019; Meenu and Xu 2019). A number of experiments focused on downregulation of starch branching enzymes SBEIIa and SBEIIb, leading to substantially elevated levels of amylose and resistant starch in wheat, which could benefit human health viz. obesity (Vetrani et al. 2018). The level of free amino acids in wheat was significantly altered when the GCN2-type protein kinase gene was overexpressed. In another experiment, the pA25-TaGW2-RNAi DNA construct was implanted into the immature embryos of the wheat variety ‘Shi 4185,’ resulting in TaGW2 gene suppression and increased grain weight and width. Using Pina-D1a and pinb-D1b genes, indicated the interaction of PINA with PINB to form friabilin which ultimately modulate the wheat grain texture. Aggarwal et al. (2018) created a TaIPK1:pMCG161 RNAi construct that was then mobilized into C306 wheat genotypes. The transgenic lines reduced phytate by 28–56%, increasing the molar ratios of iron: phytic acid and zinc: phytic acid. Similarly, demonstrated a reduction in phytate of 22–34% using the TaABCC13: pMCG161 RNAi construct. Furthermore, several genes for Fe and Zn homeostasis in wheat have been identified, which are associated with four key pathways: the methionine cycle, phytosirophore biosynthesis, the transport system, and the antioxidant system. These genes could be used for gene editing or genetic engineering to increase the amount of Fe and Zn in wheat grain and its bioavailability. In general, there is ample scope to improve wheat nutritional quality components using modern approaches to improve the quality standards of commercial wheat.

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Conclusion and Future Perspectives

Wheat grain contains various compounds which have potential nutraceutical functions. Wheat nutritional properties can be exploited in variousforms to prevent malnutrition and deadly diseases. For instance, wheat brans are the rich sources of flavonoids, phenolic acids, tocopherols, lignans, phytosterols, and carotenoids, which provide many health benefits. Wheat products contain a variety of highvalue compounds, mainly bioactive compounds with significant health benefits. They can be exploited as food ingredients, supplements, additives, or extracts that are high in functional molecules and micronutrients, such as zinc, iron, and manganese, phenolic compounds, novel carbohydrates, carotenoids, biopeptides, bioactive fatty acids, amino acids, prebiotics, vitamins, and mineral elements. Bioactive compounds derived from wheat can be used as antioxidants and preservatives, reducing lipid oxidation and microbial growth. Furthermore, processing technologies to improve nutritional characteristics and sensory features also been targeted to increase the functional food value, and nutrients bioavailability, while reducing the anti-nutritional factors of cereal by-products. In the near future, more studies are necessary on the nutraceutical properties of wheat including bioactive compounds for use as nutraceuticals or as ingredients in the development of functional products. Some of these traits can be integrated in the wheat breeding activities as it is a key set of characteristics for the trading and commercialization of the grain. Grain nutritional quality should be an integral part of the breeding process and considered within the variety development process to deliver new products with better nutritional properties to consumers.

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Maize Nutraceutomics: Genomics, Biotechnology, and Nanotechnology Deepti B. Sagare, Prashant Shetti, Shrikant Yankanchi, Sai Rekha Kadirimangalam, Rachana Baguda, Fan Xingming, Jun Fan, Shweta Singh, Rani Asaram Jadhav, M. A. Ashrutha, and Kumari Aditi

Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methods of Biofortification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic Resources for Nutritional Quality Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic Diversity Analysis for Nutritional Quality-Related Genes . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Morpho-Pheno-Biochemical Traits-Based Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . 4.2 Molecular Marker-Based Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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D. B. Sagare (*) Bayer Crop Science Ltd, Hyderabad, India P. Shetti Banashankari Agro Agency, Nipani, India S. Yankanchi Indira Gandhi Krishi Vishwavidyalaya, Raipur, India S. R. Kadirimangalam International Crop Research Institute for the Semi-Arid Tropics, Hyderabad, India R. Baguda Professor Jayashankar Telangana State Agricultural University, Hyderabad, India F. Xingming · J. Fan Yunnan Academy of Agricultural Sciences, Kunming, China S. Singh Indian Institute of Sugarcane Research, Lucknow, India R. A. Jadhav College of Agriculture, Nagpur, India M. A. Ashrutha Hytech seeds India Pvt. Ltd, Hyderabad, India K. Aditi Kansas State University, Manhattan, KS, USA © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_3

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5 Classical Genetics and Traditional Breeding for Nutritionally Rich Maize . . . . . . . . . . . . . . 5.1 Genetics of Nutritional Quality-Related Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Breeding Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Classical Breeding Achievements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Limitations of Traditional Breeding and Rationale for Molecular Breeding . . . . . . . 6 Mapping Grain Quality Genes and Quantitative Trait Loci (QTLs) . . . . . . . . . . . . . . . . . . . . . . 6.1 QTLs for Quality Protein Maize (QPM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 QTLs for Oil Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 QTLs for Starch Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 QTLs for Fe, Zn, and Provitamin A Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Association Mapping for Quality Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Marker-Assisted Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 MAB for Quality Protein Maize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 MAB for Oil Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 MAB for Starch Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 MAB for Provitamin A Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.5 Pyramiding Grain Quality Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Cloning of Grain Quality-Related Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Recent Concepts and Strategies Developed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1 Gene Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Genetic Engineering for Nutritional Quality Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 GE to Enhance Essential Amino Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 GE to Enhance Micronutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 GE to Enhance Carotenoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 GE to Increase Oil and Starch Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 GE to Increase Starch Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Role of Bioinformatics in Maize Metabolome Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Conclusion and Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Maize (Zea mays) is known as the queen of cereals because of its higher grain yield potential, wider adaptability, genetic diversity, use as food, feed, and industrial use among cereals. The growing population is a threat to nutritional security, and demand for a cost-effective and promising strategy for the food system. Every year around two billion of the world’s population is prone to malnutrition caused by essential micronutrients, proteins, and vitamins. Biofortification is one of the most promising approaches to enhance the nutritional quality of maize grains and reduce the risk of hidden hunger globally. Maize possesses several naturally existing mutants for nutritional quality traits and is considered as a model crop for biofortification. Effective utilization of recent advances in genomic, molecular tools, crop improvement techniques, machine learning, and artificial intelligence can pave the way in developing nutritionally rich maize. This chapter provides insight on the importance of maize in global nutritional food security, approaches for biofortification, genetic resources, and genetic diversity for nutritional quality traits, map-based gene cloning, trait mapping and finding major quantitative trait loci (QTLs), conventional and genomic-assisted breeding strategies for enhancing corn nutritional

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quality. Further this chapter emphasizes the genetic engineering approach, novel genome editing techniques, nanotechnology, and available bioinformatic databases to carry out omics research for designing nutritional rich maize. Keywords

Maize · Biofortification · Genomics · QTLs/genes · Molecular breeding · Maize genome database · Genetic engineering

1

Introduction

Corn, also called maize (Zea mays L.), is most prominent and versatile among cereals due to its adaptability, diversity, and use as food source for humans and animals, and wider industrial use. The literal meaning of maize is “that which sustains life.” Corn is the second most widely grown crop globally in temperate, tropics, and subtropical regions. There are different types of corn such as, field corn (sweet corn, baby corn, popcorn) and specialty corn (quality protein maize (QPM), high-oil maize, waxy maize etc). In 2021, a total of 1.2 billion metric tons of corn was produced globally and the United States was the largest producer of corn followed by China and Brazil (Statista.com). Globally, 61% of corn is used as feed, 17% as food and 22% for industrial (starch and biofuel) use, and therefore corn is considered as a driver for agricultural economy. Corn consists of 72% starch, 10% protein, 4% lipid, and various vitamins except for vitamin B12. Corn germ contains 80% of mineral content whereas, less than 1% resides in the endosperm. On a dry basis, maize provides approximately1400 Kcal/100 gm of energy to perform various physiological activities. Maize is a good source of fat, dietary fibers, essential amino acids, proteins, carbohydrates, starch, b-complex vitamins (histamine, folic acid, riboflavin, niacin, pantothenic acid), fat soluble vitamins (A, D, E, K), minerals and trace elements, organic acids, polyphenols, phytosterols (Table 1). Growing population is a threat to nutritional security, and there is a stealthy form of hunger called “micronutrient malnutrition” or “hidden hunger.” Every year around two billion of the world’s population is prone to malnutrition caused by key micronutrients Fe and Zn, and, provitamin A. Micronutrients play an important role to perform functions of the human body and inadequate consumption of micronutrients causes criticalities and several effects on biological A deficiency. Deficiency of protein causes marasmus, and kwashiorkor, fiber deficiency leads to diverticulitis, and constipation, whereas iron and vitamin A deficiency causes anemia and night blindness, respectively. Calf muscle pain and heart muscle weakening happen due to thiamine deficiency. Pyridoxine and niacin deficiency causes angular stomatitis and diarrhea, dermatitis, and dementia, respectively. The megaloblastic anemia is caused by folic acid deficiency, and, antioxidants deficiency decreases immunity. Thus, to minimize risk of malnutrition, foods rich in micronutrient content need to be included in the human diet. Fruits and vegetables are good sources of micronutrients. In developing countries where most of the population relies on staple cereal-based food diets either cannot have access or

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Table 1 Nutrient content of maize Nutrients Protein (g) Total fiber (g) Carbohydrates (g) Lysine (g) Tryptophan (g) Total starch (g) Thiamine (B1) (mg) Riboflavin (B2) (mg) Niacin (B3) (mg) Panthothenic acid (B5) (mg) Total B6 (mg) Biotin (B7) (mg) Total folates (B9) (mg) β-carotene (μg) Β- cryptoxanthin (μg) Total carotenoids (μg) α-tocopherol, vitamin-E (mg) Phylloquinones, Vitamin-K (μg) Oleic acid (C18:1) (mg) Linolenic acid (C18:2) (mg) Total saturated fatty acids (TSFA) (mg) Total monounsaturated fatty acids (TMUFA) (mg) Total polyunsaturated fatty acids (TPUFA) (mg) Calcium (Ca) (mg) Iron (Fe) (mg) Total oxalate (mg) Total polyphenols (mg)

Nutritive value (as per 100 gm of edible portion) 8.80
0.49 12.24
0.93 64.77
1.58 2.64
0.18 0.57
0.12 59.35
0.83 0.35
0.039 0.14
0.014 2.10
0.09 0.27
0.02 0.28
0.023 0.70
0.06 39.42
3.13 186
19.2 110
10.1 893
154 0.36
0.03 2.50
0.76 700
17.9 1565
18.2 413
5.6 706
17.4 1606
18.5 8.91
0.61 2.49
0.32 15.26
1.78 32.92
3.85

affordability of fruits and vegetables. Therefore, for nutrient security of cereals various approaches need to be adopted such as, supplementation, diversification, and fortification. Biofortification is the enhancement of micronutrients in the edible part of the crop and is a most promising approach to alleviate malnutrition. As there are several naturally existing mutant alleles for nutritionally important genes have been found in corn, it is considered a model crop for biofortification (Sagare et al. 2018).

2

Methods of Biofortification

Improvement of nutritional quality of a crop should be done by elevating the micronutrient content of the edible portion without compromising yield and yield attributing characters. For enhancing nutritional quality of food grains, three

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different biofortification methods are used, agronomic biofortification, transgenic biofortification and conventional biofortification. In conventional biofortification, the high yielding and popular varieties are a cross breed with nutritionally rich varieties, and then backcrossed to develop staple crops with higher nutrient content. In the genetic biofortification approach, a foreign gene (bacterial/plant) is introduced or manipulated genomic regions controlling nutritional related genes, to enhance micronutrient content in edible parts of the plant. In agronomic biofortification, application of micronutrient fertilizers, soil conditioning, or seed amendment is conducted to increase micronutrient content of dietary field crops. Soil amendment manages pH of the soil and makes micronutrients available in the root zone for plants to uptake. Soil amendment is done by application of lime, biochar, biosolids, elemental sulfur, gypsum, plant residues, animal manure, organic manure etc. Biofortification can also be done through nanotechnology, nanoparticles are incorporated into micronutrient fertilizers and exploited for their role in nutritional and yield enhancement. In corn, foliar application of zinc hydroxide nitrate (Zn5 (OH)8 (NO3)22H2O) led to accumulation of Zn content in endosperm (Ivanov et al. 2019). The conventional approaches are time consuming and are unable to fortify multiple micronutrients. In the recent past the genomic advances led to identifying various nutrition related genes and novel approaches such as, trait mapping, moleculargenomic breeding, genomic selection can accelerate breeding of staple food crops to enhance biofortification.

3

Genetic Resources for Nutritional Quality Improvement

Maize belongs to the family Poaceae and tribe Maydeae/Andropogonodae that comprises seven genera, viz. Coix (2n ¼ 10 or 20), Sclerachne (2n ¼ 20), Trilobachne (2n ¼ 20), Chionachne (2n ¼ 20) and Polytoca (2n ¼ 20) (Old World groups) and Zea and Tripsacum (New World groups). Two new world group genera, Zea and Tripsacum forms the genepool of maize, and comprises subtribe Tripsacinae, tribe Andropogoneae, and subfamily Panicoideae of family Poaceae (Barker et al. 2001). A gene pool categorization of cultivated crops was proposed based on the feasibility of gene flow/transfer from those species to cultivated crop species. The categories are, primary, secondary, and the tertiary gene pools. Biological species that have no gene exchange barrier fall under the primary gene pool that comprises wild and progenitors of cultivated crop species. Secondary gene pool comprises distantly related crop species and has crossability issues. Outer limits of potential genetic resources are considered as tertiary gene pools. Zea mays (ssp. mays) represents the primary genepool, other taxa in the genus Zea (teosintes) represents secondary genepool (subspecies parviglumis, mexicana, huehuetenangensis, and other zea species luxurians, nicaraguensis, diploperennis, perennis), and all the species in the genus Tripsacum, sister genus to Zea (new world perennial, polyploid grasses) represents tertiary genepool. About 9000 years ago maize (Zea mays ssp. mays) was domesticated from wild species ancestor, teosinte (Zea mays ssp. parviglumis).

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The wild relative serves as, great source genetic diversity and valuable resources of economically important genes viz., biotic and abiotic stress resistance, yield related genes and genes comprising higher nutrient content, and can be used in crop improvement. Wild relatives are a source of alleles for important traits such as insect resistance and gray leaf spot (GLS) resistance from Z. mays ssp. mexicana (Lennon et al. 2016), waterlogging resistance from Z. diploperennis and Z. nicaraguensis, resistance to the parasitic weed Striga from Z. diploperennis (Amusan et al. 2008), higher yield from Z. mays ssp. Parviglumis (Wang et al. 2008). Several nutritional quality-related mutant alleles were identified from cultivated wild relatives and landraces viz., waxy1 for high amylopectin, opaque2 for high quality protein, Y1 for high carotenoid content (Amusan et al. 2008). Maize lines rich in methionine, tryptophan and lysine were obtained by allelic introgression from Z. mays subsp. mexicana (Wang et al. 2008). Teosinte possesses several functional variations for nutritional quality traits, protein content, provitamin A carotenoids, Starch and oil content (Harjes et al. 2008; Karn et al. 2017), therefore, it could serve as a potential donor for maize biofortification.

4

Genetic Diversity Analysis for Nutritional Quality-Related Genes

Genetic diversity changes over time and space can be defined as the range of genetic characteristics presented within a crop or species (Swarup et al. 2021). Genetic diversity analysis plays a fundamental role in breeding, plant genetics, biological evolution, and biodiversity conservation. Understanding maize genetic difference and its distribution is particularly important for selecting diverse parental maize materials to improve maize quality. The analyses of genetic diversity can be classified as two categories: one is the phenotype-based diversity analysis which focuses on the observation of morphological traits such as height and color, while the other one is molecular-based analysis which focuses on the examination of DNA variations. The maize genetic diversity has strong relationships with its wild relatives, so conserving and utilizing wild relatives could help improve maize breeding. In addition, the distribution of maize genetic diversity shows obvious geographical characteristics (Mir et al. 2013).

4.1

Morpho-Pheno-Biochemical Traits-Based Diversity Analysis

Morpho-phenotype-based genetic diversity analysis refers to the use of analysis of phenotypic differences among plants to further infer genetic diversity, whereas, biochemical-diversity reveals the nutrient content of the seeds. It is widely used in new cultivar breeding, evaluation of genetic response to environment, and crop management such as biological pest control (Swarup et al. 2021). Diversity analysis based on kernel composition, and zein profiles in a diverse set of modern inbred lines, teosinte accessions, landraces, intermediate between inbred and teosinte, revealed

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in-spite of having smaller seed size teosinte possesses twice the protein content of landraces and inbred lines. The diversity analysis study based on morpho-phenotypic (plant height, kernel length, grain weight, kernel rows per cob, cob diameter etc.), biochemical/nutritional content (tryptophan) and kernel color (orange, white, yellow) traits in 1348 accessions of 13 maize populations belonging to stiff and non-stiff stalk heterotic groups, revealed variable relationships between and within total diversity among morpho-pheno-biochemical traits (Jaradat and Goldstein 2013). The diversity analysis study conducted in 51 accessions of maize landraces from north west Himalayas of India based on agro-morphological (grain yield per plant, plant height, ear height, kernel rows, kernels per row etc.) and nutritional quality (tryptophan content) traits, revealed significant differences among the accessions (Kumar et al. 2015). A total of 1279 accessions conserved in the Indonesian Agency for Agricultural Research and Development-Indonesian Center for Agricultural and Biotechnology and Genetic Resources Research and Development Gene Bank (IAARDICABIOGRAD Gene Bank) were assessed for their kernel characteristics (morphological- color, size, and shape) and a moderate-high genetic diversity among accessions was observed (Risliawati et al. 2022). Morpho-phenotype-based diversity analysis can detect unique traits or genotypes that can be used in breeding programs. A weakness of phenotype-based diversity analysis is that homozygotes and heterozygotes are not distinguishable. Also, as phenotype is affected not only by genes but also by environment, morpho-phenotype-based diversity analysis may need to be further validated by other methods such as molecular marker assistant analysis. Whereas, biochemical or nutritional content based genetic diversity is very much important to find out nutritionally rich germplasm and their subsequent utilization in breeding nutritionally rich crops.

4.2

Molecular Marker-Based Diversity Analysis

A molecular marker is a DNA sequence that reveals mutation or variation and can be located and identified in the genome. A number of metrics are used to evaluate genetic diversity such as the number of alleles, genetic differentiation index, observed or expected heterozygosity, percentage of polymorphic loci, genetic distance, and polymorphism information content. Moreover, hierarchical analysis of molecular variance and principal coordinate analysis are also widely used in genetic diversity analysis (Wu et al. 2021). Several studies have been taken up for molecular marker based genetic diversity for nutritional quality traits. Molecular diversity in 20 inbred lines with varied Kernel tryptophan, Lysine, provitamin A, Fe and Zn content, using 25 simple sequence repeat (SSR) markers, revealed high levels of polymorphisms, and the nutritionally contrasting could and genetically diverse lines can serve as potential sources for hybrid development program as well as for further studies on quantitative trait locus (QTL) analysis of kernel micronutrient traits (Jaiswal et al. 2019). A biochemical (α-tocopherol or vitamin E content) and molecular analysis (SSRs-based diversity) of set of 24 inbreds possessing favorable alleles of γ-tocopherol methyltransferase (ZmVTE4) identified set of potential cross

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combinations for developing high yielding vitamin E rich hybrids, and to map additional genes affecting accumulation of α-tocopherol (Das et al. 2019).

5

Classical Genetics and Traditional Breeding for Nutritionally Rich Maize

Classical genetics studies the mechanism of how certain characteristics are passed from parents to offspring without knowing the molecular details, and traditional breeding is based on the variations of observable traits. Breeders look for desired traits and use traditional methods such as mass selection, recurrent selection, hybridization, and synthetic variety development to create new cultivars.

5.1

Genetics of Nutritional Quality-Related Genes

Starch accounts for about 70% of maize kernel weight and is critical for grain yield and quality. In maize kernel sucrose is firstly converted to glucose and then further to starch, and starch is composed of amylopectin and amylose. Genetics studies reveal that starch production in maize is regulated by a wide range of genes such as sh1, sh2, bt2, wx1, ae1, and su1. These genes act in different pathways. For example, sh1 helps the formation of glucose, sh2 and bt2 help the conversion from UDP-glucose to ADP-glucose, ae1 and su1 aid to form amylopectin, and wx1 helps form amylose. About 10% of maize kernel weight is protein, made up of amino acids, and some of these are essential for human health. Proteins can be classified to two types: zein protein and non-zein protein. Zein protein accounts for about 70% of total protein in the maize kernel and is affected by abundant gene mutation. Some genes such as De-B30, mc, fl2, and fl4 encode zein protein, while others such as fl1 and o1 encode non-zein protein. Moreover, genes can also regulate endosperm metabolism enzymes (o5, o6) or transcription process (i.e., o2, fl3) and ultimately affect protein (Khan et al. 2019). Probably, the most widely studied gene is o2 which can be used to breed quality protein maize, as o2 can reduce alpha zein accumulation but increase lysine and tryptophan contents that are important for human health (Holding 2014). Oil is also a major component in maize seed and is rich in polyunsaturated fatty acids and energy. The quality of maize oil is determined by not only the oil content but also the composition ratios among fatty acids. Genetic studies have identified several main genes that control oil-related traits. For example, DGAT1-2 encodes diacylglycerol acyltransferase which catalyzes the final step of oil synthesis, fad2 encodes oleate desaturase that affects oleic acid composition, and ZmWRI1 encodes a transcription factor that can increase oil content.

5.2

Breeding Objectives

In maize breeding, selection is the main method used to eliminate or exhibit target characteristics, and it could be either natural selection or artificial selection or

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selective breeding. Selective breeding aims to produce offspring that have desirable traits which can be passed to future generations via genes. The selection of multiple traits simultaneously is conducted by developing a selection index to maximize genetic gains. From the selection objectives point of view, the selection could also be classified as positive selection and negative selection, which can be translated as keeping the favorable traits and eliminating detrimental traits, respectively. Breeding varieties with enhanced nutritional qualities such as high vitamin A content, highquality protein content, and high zinc content, while having stable yields under disease damage and/or environmental stress such as heat and drought, may be an ideal breeding objective to bred nutrition-rich maize. However, breeding objectives should also consider temporal and spatial conditions to address local specific challenges.

5.3

Classical Breeding Achievements

In the past decades, breeders have bred many nutritious maize varieties such as highamylose maize, high-oil maize, high-vitamin maize, sweet maize, waxy maize, and quality protein maize, using traditional methods. High-amylose maize is widely used in the food industry as the high-amylose starch in maize produces opaque gels that are good materials for confectionery and thickener. The high content of amylose in maize starch is mainly controlled by a recessive gene ae. Through hybridization, random mating, and mass selection, breeders managed to develop the SU amyloseextender maize cultivar with apparent amylose content ranging from 53.3% to 69% with an average of 61.7%. However, the yield of the amylose-extender maize was low (3–4 tons per ha) compared with normal maize hybrids. The Germplasm Enhancement of Maize project of the United States Department of Agriculture reported that the apparent amylose contents of their ae-inbred lines (H99ae, OH43ae, B89ae, and B84ae) were from 61.7% to 67.7% (Li et al. 2008). Another high-amylose maize germplasm was reported by Campbell et al. (2007) whose research showed that the apparent amylose starch content of GEMS-0067 inbred line was at least 70% and had good potential for future high-amylose maize breeding. Quality Protein Maize (QPM) is another achievement. QPM contains two enhanced amino acids: lysine and tryptophan which are essential for human and animal growth and development. The breeding of QPM started in the 1960s since scientists discovered some gene mutants such as o2 and fl2 could improve the contents of lysine and tryptophan (Prasanna et al. 2001). The International Maize and Wheat Improvement Center (CIMMYT) successfully developed a group of o2 based QPM gene pools (Table 2), using backcross recurrent selection. Later, by using CIMMYT’s germplasm, researchers around the world bred many local QPM hybrids or open-pollinated varieties to adapt local ecosystems such as HQ INTA-993 in Nicaragua, ICA in Colombia, INIA in Peru, FONAIAP in Venezuela, BR473 and Assum Preto in Brazil, H-553C and VS-538C in Mexico, Susuma in Mozambique, Obatampa in Bein and Guinea, Obangaina in Uganda, GH-132-28 in Ghana, QS-7705 in South Africa, BHQPY545 and AMH760Q in Ethiopia, Zhongdan

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Table 2 the QPM gene pools and their corresponding protein contents. (Source: Prasanna et al. 2001) Gene pool number Pool 15 Pool 17 Pool 18 Pool 23 Pool 24 Pool 25 Pool 26 Pool 27 Pool 29 Pool 31 Pool 32 Pool 33 Pool 34

Ecological adaptation Tropical Tropical Tropical Tropical Tropical Tropical Tropical Subtropical Subtropical Subtropical Subtropical Subtropical Subtropical

Maturity Early Early Early Late Late Late Late Early Early Medium Medium Medium Medium

Lysine content (%) 4.2 4.5 4.0 3.8 3.8 4.0 4.1 4.2 4.3 4.1 4.2 – 4.1

Tryptophan content (%) 0.94 1.04 0.93 1.03 0.92 0.94 0.90 1.05 1.06 0.96 1.04 1.05 1.10

Protein content (%) 9.1 8.9 9.9 9.1 9.4 9.8 9.5 9.5 9.2 10.2 8.9 9.3 9.1

9409 and Yunrui1 in China, Shaktiman in India, and HQ-2000 in Vietnam (Prasanna et al. 2001; Teklewold et al. 2015). Besides QPM, other amino acids enriched maize varieties are also reported. For example, high-methionine inbred lines derived from A632, B73 and Mo17 are registered in the United States. Breeding high-oil maize is challenging because oil content and grain yield has a negative relationship. With decades of effort, the University of Illinois selected two high-oil synthetics: Alexho Elite and UHO with oil contents accounting for 21.2% and 15%, respectively. By using this two high-oil germplasm, Lambert et al. (1998) managed to breed high-oil maize hybrids (oil content ranged from 7% to 9%) without grain yields decreasing. However, if the oil contents were increased to a range of 10–15%, the grain yield decreased. By incorporating CML171 (a tropical high-oil inbred line) and YML107 (an inbred line derived from Suwan1), the high-oil hybrid Yunrui8 is developed with oil content of 9% and yield of 9.8 ton per hectare. From 2005 to 2015, Yunrui8 has cultivated over 0.6 million hectares cumulatively in Yunnan and other Chinese provinces.

5.4

Limitations of Traditional Breeding and Rationale for Molecular Breeding

The general process of traditional breeding can be simply described as; setting breeding objectives, germplasm creation, crosses and selections, field trials and evaluations, and finally the release of new cultivars. If desirable traits do not appear, breeders need to create more mutations or introduce other germplasm and repeat the above process to obtain desirable varieties. Although traditional breeding has had many successes and contributed greatly to global food security, its limitations cannot

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be ignored such as (1) longer time required to breed pure lines that have stable and inheritable traits, (2) the offspring of hybrid F1 have inferior performance compared with F1 hybrids, causing farmers to buy F1 seeds annually, (3) the artificial selection narrows the gene pool, (4) the interested traits are not precisely transferred when plants are crossed, and (5) crosses can only be done between two maize plants that can be sexually mated, it is thus impossible to add useful traits or genes from other species to maize. Given the limitations of traditional breeding, molecular breeding can overcome some of these disadvantages. By using molecular tools to track within-genome variations, molecular breeding can monitor the recombination of specific genes or marker profiles in the breeding process.

6

Mapping Grain Quality Genes and Quantitative Trait Loci (QTLs)

Maize being an economically important cereal, attention has been paid to enhance maize grain quality (Protein, oil content, Fe, Zn, provitamin A, starch). Genetic studies have revealed that nutritional quality of maize kernels is possessed by quantitative traits. The recent advances in molecular and genomic research, and high throughput phenotypic techniques have accelerated genetic dissection of nutritional quality in maize by QTL mapping. Several nutritional quality-related quantitative trait loci (QTLs) in maize have been mapped using various DNA based markers viz., amplified fragment length polymorphisms (AFLPs), restriction fragment length polymorphisms (RFLPs), simple sequence repeats (SSRs), and single nucleotide polymorphisms (SNPs), and mapping populations F2, F2:3, DH (doubled haploids), BC (backcross), RILs (recombinant inbred lines), NILs (near isogenic line).

6.1

QTLs for Quality Protein Maize (QPM)

Maize kernels lack essential amino acids, lysine and tryptophan, and discovery of a spontaneous mutant with opaque and soft grains called opaque2 (o2) during 1940s led to the development of QPM. The homozygous recessive o2 allele was found to enhance lysine and tryptophan content (+69%) in maize grain endosperm. Several other mutants having different effects on lysine content in maize grain were identified viz., floury2 ( fl2), opaque7 (o7), opaque6 (o6), floury3 ( fl3), mucronate (Mc), defective endosperm (De-B30), opaque7749, opaque7455 (o11), and opaque16. In the early 90s a total of 22 loci associated with protein and two major QTLs involved in o2 modifications were reported. Recessive mutant opaque 16 on chromosome 8 from Robertson’s Mutator stock, and two SSRs umc1141 and umc1149 linked with the o16 mutant were reported in late 90s. Research at CIMMYT identified markers representing grain hardness (endosperm modifiers) and high amino acid contents (amino acid modifiers) in elite QPM  QPM crosses. Babu and Prasanna 2014 performed BSA (bulk segregant analysis) in phenotypically contrasting progenies of

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seven QPM  QPM populations using genome-wide SNP and found genomic regions associated with grain hardness and high tryptophan contents. Babu et al. (2015) mapped a total of five significant QTLs on chromosomes 5, 7, and 9 for tryptophan content in the F2:3 population from a cross between two isogenic QPM lines VQL2 and VQL8.

6.2

QTLs for Oil Content

Maize oil is high in polyunsaturated fatty acids and low in linolenic acid, making it a desirable vegetable oil (Lambert 2001). Improving the quantity and quality of maize kernel oil content is an important target for breeding. Number of QTL mapping studies for oil content in maize kernels have been conducted. More than 120 QTLs for oil content using different mapping populations and markers have been reported till date. A major QTL located on chromosome 6 was identified from different populations (F2, BC, RILs) and was consequently cloned. The oil content is influenced by a few QTLs with large effects, and epistasis is also crucial in the genetic basis of maize kernel oil content.

6.3

QTLs for Starch Content

Starch is the most important component of maize kernels, accounting for 70% of the kernel weight. It is used as a raw material in industries and in the production of other products like high fructose corn syrup, polymer-based fibers, and fuel ethanol. As a result, manipulating starch quality and quantity in maize kernels is a critical goal in maize breeding. QTLs for maize starch content are reported on all ten chromosomes. More than 50 QTLs for starch content has been reported so far. Recently, a major QTL Qsta9.1 for starch content in a 1.7 Mb interval on chromosome 9 in the RIL population has been reported by Lin et al. (2019).

6.4

QTLs for Fe, Zn, and Provitamin A Content

Micronutrient malnutrition, particularly zinc (Zn), iron (Fe), and vitamin-A deficiency in diets, has sparked global concern. The genetic dissection of these traits in major cereal grains is a prerequisite for a biofortified breeding program. A few QTL mappings have also been conducted on micronutrient content in maize. For Fe and Zn content several QTLs (>50) and metaQTLs were reported, in different populations viz., RIL population, F4 population, F2:3 populations. The two informative genomic regions, bins 2.07 and 2.08 are associated with higher Zn and Fe content QTLs. The dissimilar number and position of QTLs for Fe and Zn noticed in different studies indicated their complex nature and it also depends on genetic material and environment.

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Yellow kernel maize is grown and consumed globally but the provitamin A content is much less (~2ug/g), and efforts were taken up to identify QTLs/genes associated with higher provitamin A content of maize kernel. So far >120 QTLs are reported to be associated with provitaminA content in corn kernel, and major QTLs are co-localized with zeta-carotene desaturase (ZDS), y1, y9, phytoene synthase, carotene dioxygenase genes. The carotenoid biosynthesis pathway in maize is well studied, the significant allelic variations in two key genes of the pathway i.e., lycopene-ℇ-cyclase and β-carotene hydroxylase 1 controls accumulation of provitaminA carotenoids in maize endosperm (Harjes et al. 2008).

7

Association Mapping for Quality Traits

A genome-wide association study (GWAS) is a method used in genetic research to correlate specific genetic differences with specific traits. Due to the large coverage of historical recombination events prominent to the rapid decay of linkage disequilibrium (LD), GWAS analysis is the best approach to efficiently fine map QTL. Maize is the most suitable crop to perform GWAS due to abundant genetic variability, distinct subpopulations, plenty of SNP information, and rapid decay of LD. GWAS revealed a loci Zmfad2 responsible for the changes in oleic acid content. Similarly, a strong candidate gene DGAT1–2 controlling oil content on chromosome 6 was identified through GWAS. Genome-wide SNP scanning of contrasting lines for tryptophan content revealed many polymorphic regions, most notably 2.07, 5.03, and 10.03, which are associated with grain modifications and tryptophan contents. Cook et al. (2012) conducted Joint-linkage mapping (JLM) and GWAS in a nested association mapping population, and identified 21–26 QTLs through JLM for kernel oil, starch, and protein content; whereas from GWAS a gene Acyl-CoA: diacylglycerol acyltransferase1–2, controlling oil composition and quantity. Li et al. (2013) revealed 74 loci associated with kernel oil and folic acid composition in GWAS study using 1.03 million SNPs, further these loci were validated by expression QTL mapping and co-expression analysis. A coding region of the carotenoid biosynthetic genes zep1 and lut1, as well as previously associated lcyE and crtRB1 genes were identified by Owens et al. (2014) in a GWAS across 281 maize inbreds. A CrtRB1 gene on chromosome 10 related to β-carotene was identified from GWAS using CIMMYTs CAM panel of 380 diverse tropical and subtropical inbred lines (Suwarno et al. 2015). GWAS carried out by Liu et al. (2016) with a set of 263 maize inbred lines genotyped with the SNP50 BeadChip maize array, identified four QTLs and four genes within the 100-kb intervals and 77 candidate genes associated with starch synthesis; they further reported, Glucose-1-phosphate adenyltransferase (APS1; GRMZM2G163437) as a key controller of kernel starch content. GWAS using three RIL populations conducted by Deng et al. (2017) revealed 247 and 281 significant loci associated with grain protein controlling genes in two different environments, and reported that the O2 (GRMZM2G015534) gene is located approximately 98 Kb downstream of the lead SNP on chromosome

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7 and regulates endosperm storage protein genes such as 22 kD and zein. A significant association between several SNPs on chromosome 9 and amylose content was revealed in a GWAS analysis (Li et al. 2018). Association mapping using highdensity SNPs in 923 inbred maize lines was evaluated for Fe and Zn by Hindu et al. (2018), and a total of 20 and 26 SNPs were found to be significantly associated with Kernel Zn and Fe concentrations. The carotenoid biosynthesis genes crtRB1, lcyE, and ZEP1 were discovered in a GWAS performed using 130 diverse panels of yellow maize tropical inbred lines (Azmach et al. 2018). Furthermore, several transcription factors viz., RING zinc finger domain, and HLH DNA-binding domain superfamily proteins involved in the regulation of carotenoid biosynthesis were reported. A total of 49 SNPs significantly associated with five-grain quality traits, and three candidate genes for protein content, three for oil content, and three for starch content were identified using 83,057 SNPs in a GWAS with 248 diverse inbred lines (Zheng et al. 2021).

8

Marker-Assisted Breeding

Marker-assisted breeding (MAB) selects plants for inclusion in the breeding program at an early stage of development by using molecular markers associated with desirable traits. MAB uses molecular markers, molecular biotechnology, genomics and linkage mapping in conjunction with genotypic analyses to improve plant traits. Marker-assisted selection (MAS), marker-assisted backcrossing (MABC), markerassisted recurrent selection (MARS), genomic selection (GS), and genome-wide selection (GWS) are all synonyms for this term. MAB has been used successfully to improve the genetics of various nutritional traits in maize. The important QTLs/ genes to be utilized in molecular or genomic breeding, advanced tools and techniques to develop nutritional rich maize are depicted in Fig. 1.

8.1

MAB for Quality Protein Maize

The initiation of MAS for QPM development was accomplished with o2-specific SSR (Gupta et al. 2009; Shetti et al. 2020). Through MABB, the Institute of Crop Science and the Chinese Academy of Agricultural Sciences (CAAS) established several diverse QPM lines with different genetic backgrounds (Tian et al. 2004). The introgression of o2 allele into normal maize inbred lines has resulted in a 41% and 30% increase in tryptophan and lysine contents, when compared to non-QPM hybrids. The MAS-derived QPM version of “Vivek Hybrid 9” was designated as “Vivek QPM 9” possessing significantly improved amino acid profile (tryptophan increased by 41%, lysine increased by 30%, histidine increased by 23%, and methionine increased by 3.4%), and was released in India in 2008 (Gupta et al. 2009). Liu et al. (2016) identified q27 as a functional marker associated with endosperm modifications, which has opened up a new avenue for QPM breeding. Shetti et al. (2020) introgressed o2 allele into parental lines of popular maize hybrids

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Fig. 1 Genomic designing for nutritionally richmaize

and observed 20–40% higher tryptophan content in converted lines. Sarika et al. (2018) investigated F2 populations derived from crossing normal maize lines (CML533 and CML537) with a mutant o16 donor line (QCL3024) and observed that the o16o16 mutant combination results in genotypes with approximately two times the lysine and tryptophan content than of normal maize. Indian Agriculture Research institute (IARI) have developed several QPM hybrids such as “Pusa HM-4 Improved,” “Pusa HM-8 Improved,” and “Pusa HM-9 Improved,” and released for general cultivation in India in 2017 (Hossain et al. 2018). Four commercial QPM hybrids, HQPM-1, HQPM-4, HQPM-5, and HQPM-7 developed in India via o16 MABB introgression in their parental lines have 49–60% increase in lysine and tryptophan contents (Sarika et al. 2018). Through MABB, CIMMYT recently developed several QPM versions (CML244Q, CMl246Q, CML349Q, and CML354Q) of popular inbred lines (CML244Q, CMl246Q, CML349Q, and CML354Q). The performance of these QPM versions is comparable to that of their normal versions (Qureshi et al. 2019).

8.2

MAB for Oil Content

The DGAT1-2 gene has been majorly used in MAS for oil improvement of maize kernels. Hao et al. (2014) used MABC to transfer the DGAT1-2 from the high-oil inbred line (By804) into two parents of Zhengdan958 and effectively improved the oil content without changing grain weight. The major QTL qHO6 for enhancing oil content in maize grain located on chromosome 6 has also been extensively used in MABB (Hao et al. 2014) and developed high-oil populations and hybrids, namely Illinois 6021, 6052, 6001, and Burr white.

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MAB for Starch Content

The discovery of the ae (amylose-extender) mutant alleles led to development of high-amylose plants. Amylose content is significantly higher in maize endosperm with the ae recessive alleles. Chen et al. (2010) described the use of ae (amyloseextender) recessive mutant alleles to create high-amylose cultivars and able to detect ae alleles in a backcross and its second generation with this marker more efficiently (53.3 and 73.3%, respectively) than without marker selection.

8.4

MAB for Provitamin A Content

Naturally existing alleles of two key genes of carotenoid pathway were identified, Carotene hydroxylase1 (CrtRB1), and lycopene epsilon cyclase (LcyE) (Harjes et al. 2008). The favorable allele at CrtRB1 reduces hydroxylation of β-carotene into β-cryptoxanthin, whereas LcyE reduces flux into the α-branch of the pathway. Babu et al. (2013) validated the effects of 3 functional polymorphisms (LcyE50 TE, LcyE30 Indel and CrtRB1-30 TE) and observed around twofold to tenfold increase in β-carotene (BC) and total provitamin A (proA) content. The CrtRB1-30 TE allele have large, significant effect on enhancing BC and total ProA content, irrespective of genetic constitution for LcyE50 TE and genetic background (Babu et al. 2013; Sagare et al. 2019), and the favourableCrtRB1 allele is more effective in increasing PVA content than the favorable LcyE allele (Babu et al. 2013). Muthusamy et al. (2014) introgressed favorable allele of CrtRB-1 into seven elite inbreds and observed β-carotene concentration varied from 8.6 to 17.5 μg/g among the crtRB1introgressed inbreds which was 12.6-fold higher than original lines. Several inbred lines and hybrids have been developed in recent past possessing favorable alleles of CrtRB-1 and LcyE through molecular breeding to enhance provitamin A content (Babu et al. 2013; Azmach et al. 2013; Muthusamy et al. 2015; Yang et al. 2018; Maqbool et al. 2018; Sagare et al. 2019; Mehta et al. 2020; Natesan et al. 2020), and the increase in provitamin A content varied from 5 to 18 μg/g in introgressed lines and hybrids. Recently, Natesan et al. (2020) conducted MABC to transfer the β-carotene gene, crtRB1, into UMI1200 and UMI1230 using HP467-15 as the donor parent using one gene-specific marker (crtRB1 30 TE), and using the improved lines, five hybrid combinations were developed and ACM-M13-002 was identified as a superior hybrid with a 7.3-fold increase in β-carotene concentration.

8.5

Pyramiding Grain Quality Genes

Gene pyramiding is the process of combining desirable traits by stacking multiple genes into a single genotype. Via molecular breeding approaches several grain quality genes/ QTLs have been pyramided in maize (Table 3) without compromising grain yield. In India, QPM was introgressed with provitamin A, resulting in the provitamin A-enriched elite QPM inbreds CML161 and CML171, Pusa HQPM-5

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Table 3 Pyramiding nutritional quality traits in maize through molecular breeding Traits QPM and ProvitaminA QPM, ProvitaminA, Vitamin E QPM, ProvitaminA, Low phytate

Gene combination CrtRB1 in QPM inbreds CrtRB1, LcyE, and VTE4

lpa1-1, lpa2-1 in provitamin enriched QPM inbreds

QPM and ProvitaminA QPM and ProvitaminA

CrtRB1 in QPM inbreds

QPM and ProvitaminA

opaque2 in β-carotene riched lines

QPM and ProvitaminA

sh2, opaque2, lcyE and crtRB1 in parental lines of sweetcorn hybrid shrunken2, opaque2, lcyE and crtRB1 in sweetcorn hybrid waxy1 in white and yellow kernel maize inbreds waxy1 and opaque2 in inbreds

QPM, Provitamin A, kernel sweetness Low amylopectin QPM and low amylopectin

CrtRB1 in QPM inbreds

Nutritional trait value 5.25–8.14 μg/g provitaminA, 0.35% Lysine 16.8% μg/g α-tocopherol, 11.5 μg/g provitaminA, 0.367% Lysine, 0.085% Tryptophan 8.3–11.5 μg/g provitaminA, 0.081–0.087% Tryptophan, 0.323–0.372% Lysine, 30–40% reduction in phytic acid phosphorus 10.75 μg/g provitaminA, 0.080% Tryptophan, 0.303% Lysine 6.25–6.80 μg/g provitaminA, 0.080% Tryptophan, 0.334% Lysine 6.12–7.38 μg/g β-carotene, 0.073–0.081% Tryptophan, and 0.294–0.332% Lysine 18.98 μg/g Provitamin A, 0.39% Tryptophan, 0.10% Lysine, 17.04% brix 0.390% Lysine, 0.082% tryptophan, 21.14 ppm Provitamin A, 18.96% brix

Reference Liu et al. 2015 Hossain et al. 2018 Bhatt et al. 2018

Goswami et al. 2019 Sagare et al. 2019 Chandran et al. 2019 Mehta et al. 2020 Baveja et al. 2021

96.7% Amylopectin

Talukder et al. 2022

98.84% Amylopectin, 0.102% Tryptophan, and 0.384% Lysine

Talukder et al. 2022

improved, PVCBML6, PVCBML7, Pusa HQPM-7 improved, HKI1128Q, and Pusa Vivek QPM9 improved (Goswami et al. 2019; Liu et al. 2015; Muthusamy et al. 2014; Sagare et al. 2019). Hossain et al. (2018) reported the introgression of QPM with provitamin A and vitamin E, which resulted in the development of improved QPM and provitamin A-rich hybrids (HQPM-1-PV, HQPM-4-PV, HQPM-5-PV, and HQPM-7-PV) with higher α-tocopherol contents. Bhatt et al. (2018) attempted introgression of QPM, provitamin A content, and low phytate content which resulted in the development of improved versions of elite inbreds (HKI161-PV, HKI163-PV, HKI193-1- PV, and HKI193-2- PV) with higher protein quality, higher provitamin A content, and lower phytate content. Chandran et al. (2019) attempted o2 gene introgression (from HKI163 donor) to β-carotene-rich inbred lines (UMI1200β) and improved lines showed higher lysine (0.29–0.33%), tryptophan (0.07–0.08%), and β-carotene (6.12–7.38 μg/g) contents, along with improved agronomic performance. Parental lines of shrunken2 (sh2)-based sweet corn hybrids (ASKH-1 and ASKH-2) were subjected to crtRB1 and o2 gene introgression through use of

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MABB, and reconstituted hybrids with converted lines was found with higher levels of provitamin A (18.98 μg/g), lysine (0.39%), and tryptophan (0.10%), and on par yield as original hybrid (Mehta et al. 2020). Talukder et al. (2022) deployed GAB to pool recessive waxy1 (wx1) and o2 genes in the parental lines of four popular hybrids (HQPM1, HQPM4, HQPM5, and HQPM7) using the gene-based markers. The re-formed hybrids showed 1.4-fold increase in amylopectin and 14.3% and 14.6% increase in lysine and tryptophan respectively over the original hybrids (lysine- 0.336%, tryptophan- 0.089%). Three promising maize hybrids derived from MABB (improved Pusa Vivek Hybrid-27 – provitamin A), Pusa HQPM5 Improved – QPM and provitamin A, and Pusa HQPM7 Improved – QPM and provitamin A) have all been developed and approved for commercial cultivation in India in 2019 (Prasanna et al. 2020). MAS was used to introduce QPM with various nutritional traits such as provitamin A, vitamin E, and low phytate content.

9

Cloning of Grain Quality-Related Genes

The approach of determining the genetic basis of a mutant trait by exploring the linkage with markers whose physical location in the genome is known is referred as map-based cloning, also known as positional cloning. Because of the large amounts of repetitive DNA in maize, positional cloning was thought to be nearly impossible in the last century. However, now that maize physical maps and large number of available markers, and, most importantly, synteny conservation across cereal genomes, make it possible to consider a chromosome walk in less time than cloning by transposon tagging (Bortiri et al. 2006). The following factors pose significant challenges to gene discovery in maize: (1) large genome size, (2) variation in gene order and genome size, (3) a higher rate of multicopy genes, and (4) repetitive sequences and transposons. In maize, the genetic basis of various traits varies greatly. Positional cloning was done for different traits in maize such as diseaseresistant, male sterility, fertility restoration, plant architecture etc. But very less work of positional cloning is done on health-related/grain quality traits. Till date several genes related to maize nutritional quality have been cloned such as, opaque1 (o1), foury4 ( f4) and Mucronate (Mc) for protein quality, linoleic acid1 (ln1), Oleic acid content1 (olc1), fatty acid desaturation 2 ( fad2), and fad6 for oil content, and some of the starch content related genes – Shrunken1 (Sh1), Sh2 and Brittle2 (Bt2). Buckner et al. (1990) cloned the y1 locus of maize involved in the carotenoid biosynthesis. A maize cDNA encoding phytoene desaturase, an enzyme of the carotenoid biosynthetic pathway was characterized and cloned by Li et al. (1996). The key genes involved in the starch biosynthesis pathway have been cloned, including starch branching enzyme amylose-extender1 (Ae1), brittle2 (Bt2), Suc synthase shrunken1 (Sh1), large subunit of AGPase shrunken2 (Sh2), isoamylasetype DBE sugary1 (Su1), and granule-bound starch synthase waxy1 (Wx1). Zhang et al. (2019) found that wild-type Se1 is a gene Zm00001d007657 on chromosome 2 and deletion of this gene causes the sugary enhancer1 (se1) phenotype, which is actively involved in starch metabolism in maize endosperm. Recently, Li et al. (2022)

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isolated a novel gene from maize (ZmIRT2), which exhibited highly homologous to ZmIRT1. ZmIRT2 was expressed in roots and anther and was induced by Fe and zinc (Zn) deficiencies. ZmIRT2 overexpression in maize led to elevated Zn and Fe levels in roots, shoots, and seeds of transgenic plants. ZmIRT1 transcript levels were higher in the roots of ZmIRT2 transgenic plants. According to this study, ZmIRT2 may only work with ZmIRT1 to mediate Fe uptake in roots, and ZmIRT2 could also be used in fortification efforts to increase Zn and Fe levels in crop plants.

10

Recent Concepts and Strategies Developed

10.1

Gene Editing

Genome engineering technologies such as ZFNs (zinc finger nucleases), TALENs (transcription activator-like effector nucleases) and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats (CRISPR)-associated 9 (Cas9) endonucleases) along with tissue specific expression of functional genes have accelerated molecular/genomic breeding (Chilcoat et al. 2017) Maize has large number of commercialized transgenic events (Yadava et al. 2016), this demonstrates that maize improvement has always been taken prominently and genome engineering is powerful technology to pave the way for enhancing and stacking nutritional quality traits in maize. The phytate content in maize was reduced by blocking IPK1 gene encoding inositol-1,3,4,5,6-pentakisphosphate 2-kinase using ZFNs (Shukla et al. 2009). Three genes of phytate biosynthetic pathway, ZmIPK1A, ZmIPK, and ZmMRP4 were knocked out using CRISPR/Cas9 and TALENS (Liang et al. 2014). RNA interference (RNAi) and CRISPR/Cas9 knockout ZmMADS47 gene encoding a MADS-box protein, that interact with o2 to activate zein gene promoter, and the reduced zein content 16.8 and 12.5% were observed in the kernels of ZmMADS47 RNAi and MADS/CAS9-21 lines, respectively (Qi et al. 2016). Starch metabolism in maize was altered using CRIPSR/Cas9 to disrupt the waxy gene (Wx1), which encodes GBSS being responsible for synthesizing amylose in maize (Waltz 2016). Several nutritional quality traits such as, QPM (o2, o16), provitaminA (CrtRB1, LcyE), kernel sweetness (Shrunken2), low amylopectin (waxy1), etc have been well characterized and gene editing could serve as a powerful system for stacking these traits in agronomically superior and high yielding genetic backgrounds (Table 4).

10.2

Nanotechnology

Nanotechnology is a study of nanoparticles (NPs) with unique physical, chemical and biological properties, and in recent past use of nanotechnology in agriculture has been accelerated due to its wide range of applications in crop improvement. The major applications of nanotechnology in agriculture includes; improved seed

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Table 4 Potential targets for gene editing to improve nutritional quality in maize Trait Starch content

Oil content

Genes SBE1, SBE3, SBE4, AE1 SS1, SS2, SS3, SS4, SS5, SS6, SS7, Du1, Su2 Waxy1, GBSS1 GPM177 PEP1

Essential amino acid content

ACC1, ACC2, TIDP3607 LN1, DGATI2 OLE1, OLE3, OLE4 FAD2 KCS1, KCS16 VSP1, VSP2, BIP1, BIP2, BIP3 HNT1

Vitamin content

GOT1, GOT2, GOT3, GOT4 ASN3, ASN4 VP5 DXS1 DXR1, DXR2 NCED6, NCED8

Mineral content

HPT1 SXD1 DHFS1, DHFS2 FGP2, BM4 NAS1, NAS2, NAS3, NAS4, NAS6, NAS8, NAS9, NAS10 NAAT1, PCO115235C IDP871 MIPS2 PAP2, PAP22

Protein function Starch branching enzymes Starch synthase Granule bound starch synthase Protein targeting to starch Phosphoenolpyruvate carboxylase Acetyl-CoA carboxylase Diacylglycerol acyltransferase Delta-9 desaturase Delta-12 fatty acid desaturase Fatty acid elongase Storage protein

Gene editing strategy Knockout Overexpression Overexpression Overexpression Knockout Overexpression Overexpression Overexpression Knockout Knockout Overexpression

Homocysteine S-methyltransferase Aspartate aminotransferase

Overexpression

Asparagine synthetase Phytoene desaturase 1-deoxyxylulose 5-phosphate synthase Deoxy-D-xylulose 5-phosphate reductoisomerase Carotenoid cleavage dioxygenase Homogentisatephytyltransferase Tocopherol cyclase Dihydrofolate synthetase Folylpolyglutamate synthase Nicotianamine synthase

Overexpression Overexpression Overexpression

Nicotianamine aminotransferase Small GTPase Myo-inositol-1-phosphate synthase Phytase

Overexpression Overexpression Knockout

Overexpression

Overexpression Knockout Overexpression Overexpression Overexpression Overexpression Overexpression

Overexpression

germination using nanoformulations, nanofertilizers for nutrient use efficiency in crop that helps in accumulation of nutritional quality components in the edible portion, weed control using herbicides, disease and pest control using nanopesticides and nanosensors, nanopackaging for improving shelf life of produce, nanosensors for post-harvest quality analysis. Research on NPs for improving nutrition quality-

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related traits in cereals has gained attention in the recent past (Bajpai et al. 2020). In the agronomic biofortification approach, application of nanofertilizers to enhance nutrient use efficiency of crop and subsequently to improve nutritional quality of maize is an emerging approach. Surface-modified zeolite enhances phosphate and sulfate uptake (Li and Zhang 2010), Montmorillonite and Zeolite improves nitrogen uptake via xylem (Manikandan and Subramanian 2014), Nanocomposites containing organic polymer intercalated in the layers of kaolinite clays increases uptake of wide range of micronutrients. Recent developments in genetic engineering and engineered nanomaterials based targeted delivery of CRISPR/Cas mRNA, and sgRNA for the genetic modification of crops is a noteworthy scientific achievement and this will pave the way to enhance the nutritional content of major cereals like rice, corn, and wheat.

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Genetic Engineering for Nutritional Quality Traits

Biosynthetic and metabolic pathways of nutritional traits of maize are well studied. Genetic engineering (GE) approach provides opportunity to enhance nutrition content of maize via several approaches viz., transformation of single gene, transformation with multiple genes (encoding different nutrients) in a single cassette, overexpression of nutrient transporters, silencing of feedback inhibition enzymes of nutrient biosynthesis pathways, overexpression of major enzymes of pathways. Genetic engineering for enhancing nutrient content of crops by modifying biosynthesis pathways is called metabolic engineering.

11.1

GE to Enhance Essential Amino Acids

Zein are the major proteins in maize and deficit in essential amino acids lysine and tryptophan. T-DNA mediated mutations in 19- and 22-kD α-zeins in maize enhanced seed Lys and Trp content and reduced zein levels. A genetically engineered high lysine maize (0.360% vs. 0.255% in common maize kernel), LY038 was developed by transformation of the cordapA gene from Corynobacterium glutamicum, a soil bacterium, into the maize genome (Lucas et al. 2007). LY038 is the first genetically modified (GM) maize, approved for commercial use in countries like Colombia, Mexico, Canada, the Philippines, the USA, and Japan (EPA 2020). Tryptophan synthesis is feedback regulated by inhibiting Anthranilate synthase (AS), and 1.1to 50-fold increase in free amino acid content in maize transformed with feedback altered AS gene than in non-transformed maize is reported.

11.2

GE to Enhance Micronutrients

Phytic acid (phytate) is a chelator, reduces bioavailability of essential micronutrients such as Fe, Zn, Ca, Cu, Mn etc. The low phytic acid (lpa) mutant of

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maize viz., lpa1-1 and lpa2-1, lpa241 were found with 50–90% reduction in phytate, but have negative effect on seed germination and plant growth. Genetic modification of lpa1-1 maize by endosperm specific overexpression of soybean ferritin gene was resulted in more than twofold improvement in iron bioavailability, and transgenic lpa1-1 seeds were having higher germination rates and seedling vigor compared to non-transgenic seeds (Aluru et al. 2011). A significant enhancement in bioavailable Fe was observed in transgenic maize lines generated by endosperm specific co-expression of recombinant Soybean ferritin and Aspergillus Phytase genes.

11.3

GE to Enhance Carotenoids

Multiplex transgenic maize developed by transferring 5 carotenogenic genes, Zmpsy1 (Zea mays phytoene synthase 1), PacrtI (Pantoeaananatis phytoene desaturase), Gllycb (Gentiana lutea lycopene-cyclase), Glbch (Gentiana lutea carotene hydroxylase), and ParacrtW (Paracoccuscarotene ketolase) driven by different endosperm-specific promoters have resulted in 50- to 60-fold increase in total carotenoids. Carotenoid intermediates such as, keto-carotenoids, asthaxanthi, adonixanthin, 3-hydroxye chinenone, echinenone were engineered in transgenic maize. Genetic modification in maize by transferring ZmPSY1 cDNA (with LMW glutenin promoter from wheat), Crt1 gene from Pantoeaananatis (with barley Dhordein promoter), Osdhar gene (for ascorbate) and E. coli folE gene (for folate) were found to possess 169-fold higher β-carotene, 6-fold higher ascorbate, and double amount of folate than non-transformed maize (Naqvi et al. 2009). Transgenic maize produced by overexpression of Psygene and silencing LcyE gene resulted in diverting carotenoid biosynthesis pathway toward β-branch, and thus, with increasing high value astaxanthin carotenoid in the kernel (Farre et al. 2016). Overexpression of the IbOr gene in maize inbred lines under the control of maize seedspecific promoter globulin 1 (Glo1) resulted in 10.36- and 15.11-folds increase in total carotenoid and ß-carotene contents (Tran et al. 2017).

11.4

GE to Increase Oil and Starch Content

Maize transformed with Puroindoline genes (Pina and pinb) from wheat resulted in 25.23% increase in a total oil content (Zhang et al. 2010). Overexpression of ZmWRI1 (WRINKLED1) gene in maize resulted in enhancing oil content without affecting seed germination, plant growth and grain yield (Shen et al. 2010). The maize transformed with fungal diacylglycerol acyltransferase2 (DGAT2) genes from Umbelopsisramanniana and Neurospora crassa under the control of embryo enhanced promoter, showed 26% increase in kernel oil content compared to non-transgenic maize (Oakes et al. 2011).

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GE to Increase Starch Content

Genetic transformation of maize with Bt2 and Sh2 genes from wild maize under the control of endosperm specific promoter resulted in increased starch content in transformed lines (Li et al. 2008). Overexpression of Bt2, Sh2, Sh1 and GbssIIa genes, and silencing SbeI and SbeIIb by RNA interference to enhance activity of sucrose synthase, AGPase and granule-bound starch synthase, and to reduce the activity of starch branching enzyme in maize, resulted in 2.8–7.7% increase in kernel starch and 37.8–43.7% increase in amylose content (Jiang et al. 2013). The overexpression of the mutated ZmDA1 and ZmDAR1 genes driven by maize ubiquitin promoter resulted in improving the sugar imports into the sink organ and starch synthesis in maize kernels (Xie et al. 2018).

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Role of Bioinformatics in Maize Metabolome Improvement

Maizeis a model cereal crop in omics research programs across the world, and studies on maize using multi-omics datasets could help to understand more about domestication, selection, and evolution of maize over the period of time. In 2009 the first maize reference sequence B73 was released, further using high-density SNPs several maize lines and population were re-sequenced and mapped against B73 reference genome to expandnutritional related genomics such as oil and vitamin metabolism (Wang et al. 2018). Currently in maize genome database several additional maize genome sequences have been reported such as, PH207, Mexicana, Mo17, W22, HZS, and SK. For successful maize breeding and improvement programs timely utilization of multi-omics tools, datasets, and web-resources could be most imperative (Table 5) These genome sequences, datasets and omics platforms are playing crucial role in maize metabolome improvement, and assisting in diversified breeding purposes to bred varieties with high yield and nutritional quality

13

Conclusion and Future Perspectives

The early generation crop breeding approaches such as, phenotypic selection, cross breeding, mutation breeding have been developed several high yielding, biotic and abiotic stress-resistant varieties and hybrids. And, also identified diversity and resources for traits contributing nutritional quality. These conventional/ traditional breeding approaches are tedious and time consuming and creates difficulty in breeding quantitative traits. The recent advances in molecular tools, techniques, genome sequencing technologies, novel genomic tools such as trait mapping, identifying trait specific major QTLs and genes, haplotype-based allele mining, enriched bioinformatic databases, rapid generation advancement through speed breeding and

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Table 5 List of important maize databases and web-resource to obtain genomic information on nutritional quality Database/ Web-resource NCBI MaizeGDB SNPversity

Database/ Web-resource and Establish/Launch National Center for Biotechnology Information Maize Genetics and Genomics Database – Lawrence and colleagues, 2003 MaizeGDB team and

MaizeMine

MaizeGDB team and the Elsik lab at the University of Missouri

MaizeDIG

The Maize Database of Images and Genomes Carson M Andorf and team in 2019 Professor James Schnable from University of Nebraska-Lincoln MaizeGDB- PedigreeNet MaizeGDB team Zea mays Genome DB – PlantGDB Developed as a part of NSF-funded project “Cyberinfrastructure for (Comparative) Plant Genome Research Through PlantGDB” 2006 NSF-PGRP Maize Elite Inbred Line Ac/Ds Mutant database

qTeller PedigreeNet ZmGDB

Panzea MEILAM

Maize FLcDNA CSRDB ZEAMAP MaizeSNPDB PPIM Gramene

cropPAL

Full Length cDNA Project Cereal small RNAs Database Maize and its wild relative’s database MaizeSNP Database – Wen Yao, from College of Life Sciences, Henan Agricultural University Protein-Protein Interaction Database for maize Establishment and Maintenance – “Oregon State University, Cold Spring Harbor Laboratory and EMBL-EBI” The compendium of crop Proteins with Annotated Locations Initiated – Cornelia Hooper and Colleagues from The University of Western Australia, Crawley, Australia

Website https://www.ncbi.nlm.nih. gov/ https://www.maizegdb.org/ https://www.maizegdb.org/ snpversity https://maizemine.rnet. missouri.edu/maizemine/ begin.do https://maizedig.maizegdb. org/ https://qteller.maizegdb. org/ https://www.maizegdb.org/ breeders_toolbox https://www.plantgdb.org/ ZmGDB/

http://www.panzea.org http://www. maizetepolymorphism. com/AcDs/ http://www.maizecdna.org/ http://sundarlab.ucdavis. edu/smrnas/ http://www.zeamap.com/ https://venyao.xyz/ MaizeSNPDB/ http://comp-sysbio.org/ ppim/ https://www.gramene.org/

https://crop-pal.org/

double haploid, genomic selection, genome editing, nanotechnology, machine learning, and artificial intelligence has led to current generation crop breeding such as, biotech breeding and design breeding. The pathways of nutritional traits are well studies, the information on key enzymes, associated genes/QTLs, genetic diversity

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and resources is publicly available. The genome editing technologies and speed breeding approaches are assisting haplotype-based breeding/design breeding which can assist in developing tailor-made maize with higher nutrition.

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Barley: From Molecular Basis of Quality to Advanced Genomics-Based Breeding Franca Finocchiaro, Valeria Terzi, and Stefano Delbono

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Agricultural Importance of the Crop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 An Overview of Barley Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Importance of Barley in the Prevention of Chronic Diseases . . . . . . . . . . . . . . . . . . . . . . . . 2 Barley Bioactive Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 β-Glucans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Tocols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Simple Phenols and Polyphenols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Next-Generation Breeding for Phytochemicals and Nutrient Contents . . . . . . . . . . . . . . . . . . . . 3.1 Tools for Assessing Genetic Diversity in Genomic Era . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Connecting Genotype to Phenotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Genetic and Genomics Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Barley Gene Pools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion and Future Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Barley (Hordeum vulgare L.) is a cereal crop that belongs to the family of Poaceae (Gramineae) and tribe Triticeae. This cereal ranks fourth in the world production of cereals. Barley is one of the cereals having greater genetic diversity. It is largely used for animal feed and malting, with only a minor part used for human consumption. Barley can be considered an excellent cereal to produce functional foods, thanks above all to the presence of soluble fiber (β-glucans). In barley grains, it is possible to find a lot of bioactive compounds: from carbohydrate polymers (like β-glucan, arabinoxylan, and hemicellulose), to vitamin E (tocopherol and tocotrienols), to secondary metabolites like phenols. Over the F. Finocchiaro (*) · V. Terzi · S. Delbono Council for Agricultural Research and Economics (CREA), Research Centre for Genomics & Bioinformatics, Fiorenzuola d’Arda (PC), Italy e-mail: franca.fi[email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_4

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years, breeding programs have therefore been implemented to improve the content of bioactive compounds in barley. Genomics has developed very quickly in the last years, providing tools and technologies that help us to lend precision and efficiency to barley breeding programs for the development of new varieties with healthier properties and resilient to climate changes. Keywords

Barley · Hordeum vulgare · β-glucans · Polyphenols · Tocols · Breeding for HR molecules

1

Introduction

1.1

Agricultural Importance of the Crop

Barley (Hordeum vulgare L.) is a cereal crop that belongs to the family of Poaceae (Gramineae) and tribe Triticeae (Fig. 1). This cereal is the fourth in the world production of cereals, after wheat, maize, and rice. It is a crop that can grow under a wide environmental condition, stress tolerant, and, for these reasons, barley is particularly used in some developing countries that present arid climate condition, being the most important staple food resource. Currently, barley is grown on 48 million hectares in moderate, continental, and subtropical climates. It is mainly employed for animal feeding, to produce beer and

Fig. 1 Barley spike

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spirits, and to an ever-increasing extent, for human consumption. The barley world production was about 147.05 million metric tons in the 2021/2022 crop year, with a reduction of about 14.0 million metric tons compared to 2020/2021 (https://www. statista.com/statistics/271973/world-barley-production-since-2008/). Besides being an agronomically relevant crop, barley is considered a very good model for the Triticeae, especially bread, which possess very complex polyploid genomes. Barley is diploid with a genome size of about 5.3 Gb distributed over seven chromosomes. Barley was one of the first cereals being cultivated: archaeological finds have been found in areas corresponding to the Fertile Crescent and its domestication has been traced back to about 8000 years BC (Giraldo et al. 2019). Since its domestication, barley was a staple food, with considerable nutritional importance. At the time of the Romans, for example, it was used in the training diet of gladiators, a term that in Latin means Horderarii, literally “men of barley.” It has been the staple food especially in areas characterized by unfavorable environmental conditions and low productivity, as in the developing countries. It is still a staple food in some world areas, like North Africa and Near East regions and in the mountain region of Central Asia and South America. Something changed during the Middle Ages as wheat reached more significance in breadmaking, while barley almost disappeared from the diet of many countries, while its most important employment was for feed and, to a lesser extent, in alcohol beverages production (Giraldo et al. 2019). The cause can be found in the low gluten content, which determines less swelling of the loaf, and lower quality in general. Barley is one of the cereals having higher genetic diversity. According to the sowing period, there are winter, spring, or alternative types. According to the morphology of the spike, there are two- and six-rowed types. The grain is generally hulled (covered or dressed) with an outer structure around the grain, but hull-less (naked) grains, in which the outer hulls detach easily, as in wheat, also exist. Based on starch composition of the grain, normal, waxy, or high amylose barley type can be distinguished; high lysin, high β-glucan, and proanthocyanin-free varieties are also available. Two-rowed barley is the wild one that is grown in Europe, whereas the six-rowed is developed by gene mutation and has a triple crop yield. Both two-rowed and six-rowed barley genotypes have winter and spring types. Winter type is cultivated in fall (especially in Europe, the United States, and Canada), whereas spring cultivar is cultivated in spring or summer in the Mediterranean region (Farag et al. 2022). Most of the cultivated barley, about 65%, is employed for animal feed, about 33% is destined for malting production, while only 2% is used for human consumption as an ingredient of several food products (Farag et al. 2022). Historically, barley has been an important food source in many countries, including the Middle East, North Africa, and Northern and Eastern Europe (Farag et al. 2022). However, better product quality of food products prepared from wheat and rice compared to barley considerably decreased the use of barley as food, especially in the nineteenth and twentieth centuries. In the past, barley has received more attention from breeders and researchers thanks to the growing requests of healthy and more traditional food, which has led to the development of breeding programs aimed to obtain new barley varieties with a high level of healthy substances in the grain.

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The growing world population is causing a higher demand for food and puts high pressure on soil and production systems. The future of agriculture will have to take into account the improvement of the nutritional quality of its products, trying to mitigate the environmental impact.

1.2

An Overview of Barley Composition

Barley grain consists of about 65–68% starch, 10–17% protein, 4–9% β-glucan, 2–3% free lipids, and 1.5–2.5% minerals. β-Glucans, part of soluble fiber, constitute about 75% of the barley endosperm cell walls together with 20% arabinoxylans and protein. Genotype, environment, and crop management practices used during the crop-growing cycle determine grain composition and structure. β-Glucans, which represent normally about 5–10% of the caryopsis weight, have a very significant effect on technological and quality properties of barley. For example, both β-glucans and arabinoxylans are fundamental in malting quality as they are responsible for wort viscosity and beer filtration rates and block hydrolytic enzymes, which in turn break down starch and protein within the cell walls. Moreover, for malting quality and brewer production, the beer foam stability is linked to a minimal amount of β-glucans in the malt (Farag et al. 2022). Accordingly, low β-glucan content of grain and/or its breakdown during malting are critical issues in brewing and most barley breeding has produced barley cultivars that are normally low in β-glucans. Chemical and nutritional compounds of barley caryopsis can significantly vary due to genotype, agronomical practices, and environmental condition. The most abundant compounds of barley kernel are starch, fiber (including β-glucans), and proteins: varying the content of one of these substances will have a direct effect on the other two. Starch content is inversely correlated to protein and fiber. The starch is localized in the endosperm layer and is quite variable in composition, representing 54–75% of the grain weight. The starch of the normal or nonwaxy barleys has relatively high amylose (25%) and low amylopectin (75%), whereas waxy barleys have a low concentration of amylose (0–5%) and high amylopectin (100–95%). There are also high amylose barley mutants (up to 45% amylose fraction) (Farag et al. 2022). The nonstarch polysaccharides of barley caryopsis are structural molecules of the cell walls in hull, aleurone, and endosperm tissue. These polysaccharides are included in the total dietary fiber. In contrast to starch, they are not digested by human digestive system, but they are fermented by intestinal microbiota, producing several breakdown products, including short-chain fatty acids. The major nonstarch polysaccharides in barley are β-glucans, arabinoxylans, and cellulose. Cellulose is mainly located in the hull of the grain. Arabinoxylans are located mainly in the aleurone, where they consist about 71% of the fiber content; arabinoxylans are also present in the endosperm, where they account for 21% of the fiber content. Generally, arabinoxylan ranged from 3.8% to 6.0% based on genetic and environmental factors. Six-rowed genotypes contained higher levels of arabinoxylan than two-rowed varieties.

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β-Glucans are structural cell component that forms the cell wall in barley endosperm that accounts for 75% of the endosperm cell wall mass. The level of β-glucans in barley has a significant genetic variation, ranging from 3.0% to 15–17% (Farag et al. 2022). Waxy barley showed higher concentration of β-glucans. β-Glucan content is also affected by environmental factors: for example, the concentration increases under dry and hot conditions, while decreases under moist conditions. The level of protein in barley is highly variable: it is reported to vary from 8% to 30% as a percentage of total mass (Jaeger et al. 2021), although the level in typical barley is more commonly reported between 9% and 13%. The grain protein content is a valuable quality factor, defining barley grain end-use value: high protein grains would be desirable for feed, while a lower level (between 10% and 12%) is desirable for malting (Jaeger et al. 2021). The protein content is highly variable and can be affected by genotype, environmental conditions, and the use of fertilizers. Hordeins are the most abundant protein fraction: they belong to the prolamin class, namely storage proteins, characterized by a high content of glutamine and proline. These protein types are complex polymorphic mixtures of polypeptides. The other barley proteins are represented by a mixture of albumins, globulins, and glutenin (Jaeger et al. 2021). Prolamins are composed of high content of the amino acids glutamine, proline, and low level of essential amino acids such as lysine, threonine, and tryptophan. After hordeins, glutelin are the second most abundant storage proteins: they contain high levels of glutamine, proline, and glycine, and other hydrophobic amino acids (Jaeger et al. 2021). Albumin and globulin are minor protein forms in the aleurone grain and embryo (Farag et al. 2022). The protein in barely includes both essential (about 28%: leucine, valine, threonine, phenylalanine, isoleucine, lysine, histidine, methionine) and nonessential amino acids (72%: glutamic acid, aspartic acid, proline, tyrosine, glycine, and cytosine), potentially making barley a good source of protein in food supplements. Among the essential amino acids, barley is lacking in lysine (Farag et al. 2022).

1.3

Importance of Barley in the Prevention of Chronic Diseases

There is growing evidence that higher intakes of whole grains are associated with reduced incidence and mortality from several chronic diseases. Reynolds et al. (2019), in a recent systematic review and meta-analyses, showed that the data for whole grain consumption, from prospective studied and clinical trials, exhibit a reduction in all-cause mortality, coronary heart disease, cancer death, incidence of type 2 diabetes, and stroke mortality. The observed reductions in risk were high, typically around 20% with significant dose–response relationships. Among the bioactive components of whole grains, total fiber tended to explain the association to lower risk of CVD-related outcomes.

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Barley is a cereal with a high level of dietary fiber, particularly the soluble fiber β-glucans, which is mainly credited for barley’s health benefits, such as a reduction in cholesterol and glycemic response, the modulation of gut microbiota, the management of blood pressure, and a reduction in the incidence of metabolic syndrome (Murphy et al. 2020). In the scientific literature, there is a lot of evidence of the positive role of these compounds on physiological effects and the correlation between the consumption of β-glucans and blood cholesterol levels is now clarified. Several mechanisms have been proposed to elucidate the health effects of β-glucans and are still under study, but the factor thought to be the most responsible is the capability of soluble β-glucans to form viscous solution in the stomach and intestinal tract. The viscosity of β-glucan is related to its molecular weight, size, and its concentration in solution (Bai et al. 2019). Cultivar, growing conditions, processing, and food matrix affect the physicochemical and health properties, particularly molecular weight and solubility, of β-glucans. For these reasons, when clinical trials and new “functional foods” are developed, these aspects should be strongly considered. With consumers’ increasing awareness of the importance of nutrition and health, food is not only regarded as a medium for satiety but also as a means for disease prevention and control; such desire has created a rapidly increasing demand for “functional foods,” defined as foods that have an additional physiological benefit besides providing basic nutritional needs and opened markets for a broad range of processed foods, including beverages with specific health attributes (Shvachko et al. 2021). Barley can be considered an excellent cereal to produce functional foods, thanks above all to the presence of soluble fiber (β-glucans). The strong scientific evidence regarding the metabolic effects of the consumption of β-glucans has led the EFSA to authorize the use of specific nutritional and health claims, thus allowing and regulating the communication to the public of the benefits associated with the consumption of nutrients, provided they are present in the final product in adequate quantities and in a form that can be used by the body. Therefore, it has ordered the claim for barley and oat-based products so that it can be reported that consume 3 grams per day of β-glucans, or 0.75 g per serving in the four main meals, helps reduce plasma levels of total cholesterol and low-density lipoprotein (LDL) (ESFA 2011). In the past, thanks to the reported physiological properties of β-glucans, researchers have extensively studied the possibility to incorporate β-glucans in several food types with the aim to develop functional foods. Barley fractions enriched in β-glucans can be incorporated into wheat blends to make bakery good with improved nutritional properties. Finocchiaro et al. (2012) used two β-glucanenriched flour fractions, from two hull-less barley cultivars with normal starch type and a high-β-glucan waxy genotype, mixed with bread wheat flour. The two flour blends were used to make bread, and the postprandial glucose response was determined. The results showed that incorporation of high level of β-glucans (6% in the final blend) from the nonwaxy cultivar lower the GI significantly. Blandino et al. (2015) used pearling fractions obtained from naked barley to substitute conventional refined wheat flour for breadmaking. These fractions resulted in abundant insoluble

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and soluble dietary fiber (particularly β-glucans) and other bioactive compounds. The various healthy components present in barley kernel are not homogeneously distributed, and sequential pearling has shown to be an effective process to obtain fractions enriched in bioactive compounds (Blandino et al. 2015). Martínez-Subirà et al. (2020) obtained biscuits rich in β-glucans and antioxidants using barley flour from a purple hull-less cultivar. A single biscuit gives more than 0.75 g of β-glucans. In this way, it is easy to reach the target of EFSA recommendation and obtain the label lettering of “reduces blood cholesterol and risk of heart disease” (MartínezSubirà et al. 2020). Incorporation of β-glucan into pasta products revealed a lower glycemic response. A study on spaghetti enriched with barley β-glucans showed a β-glucan dosedependence reduction of GI, with a reduction of up to 54% of GI with the incorporation of 10% of barley β-glucans (Tosh and Bordenave 2021). Similarly, a reduced glycemic index was reported in β-glucan-enriched breakfast bars (Mejía et al. 2020). Diets and foods rich in β-glucans and with low glycemic index may have an effect on the prevention of important disease as coronary heart diseases and diabetes (Murphy et al. 2020). The simplest and most frequent use of β-glucan is their incorporation in cereal-based products, but their inclusion in beverages and dairy products has been also evaluated; it can also find some applications in the production of low-fat ice creams and yogurts (Mejía et al. 2020).

2

Barley Bioactive Compounds

In barley grains, it is possible to find a lot of bioactive compounds: from carbohydrate polymers (like β-glucan, arabinoxylan, and hemicellulose), to vitamin E (tocopherol and tocotrienols), to secondary metabolites like phenols, folates, and lignans. The focus of this section is to describe the bioactive phytochemicals that most characterize barley grain for its effects on human health: β-glucans, tocols, and phenol/polyphenol compounds.

2.1

β-Glucans

2.1.1 β-Glucans: Structure and Contents Mixed-linkage (1!3),(1!4) linear β-D-glucans (β-glucans) are major constituents of endosperm cell walls of cereals such as barley (Fig. 2), oat, and to a lesser extent wheat and rye. In barley, β-glucans account for 75% of the total cell wall polysaccharides, the remaining portion is made up of arabinoxylans, cellulose, glucamannans, and proteins. A unique feature of barley grain is that the β-glucan is uniformly distributed in the endosperm while it is concentrated in aleurone layers in oat grain, thus pearling or removal of the outer layers does not significantly affect the β-glucan content in barley (Murphy et al. 2020).

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Fig. 2 Barley β-glucan structure and localization in the grain

β-Glucans are complex nonstarchy polysaccharides consisting of D-glucose monomers linked through β-glycosidic bonds, which widely exist in plants and microorganisms. Different sources of β-glucans lead to different structures and physicochemical properties (Bai et al. 2019). Barley β-glucans are composed of linear homopolysaccharides of D-glucopyranosyl residues with β-(1!3) and β-(1!4) linkages. About 90% of glucose units are organized into blocks of cellotriose residues (three glucose molecules) and cellotetraose residues (four glucose molecules) joined by β-(1!3) bonds, while the rest are composed of segments longer cellulosics, composed of multiple glucose units (Bai et al. 2019). As already discussed earlier, the molecular characteristics of β-glucans seem to determine their physical properties, such as water solubility, dispersibility, viscosity, and gelation properties, as well as of their physiological function. The chemical composition of β-glucans determines their partial solubility in water. For example, β-glucans containing blocks of adjacent β-(1!4) linkages can show lower solubility thanks to interchain aggregation (Bai et al. 2019). Therefore, in addition to the physiological benefits of soluble dietary fiber, cereal β-glucans also show health

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properties typical of insoluble fiber, such as increased fecal bulk to reduce constipation and improve weight loss. Barley and oat are primary cereal sources for β-glucans. Total β-glucan content of barley grains ranges from 2.5% to 11.3% by kernel weight, but they most frequently fall between 4% and 7%. However, some genotypes demonstrate to accumulate up to 13–17% of total β-glucans (Farag et al. 2022). The variances in barley β-glucan concentration have been attributed to environmental growing conditions, although the genotype is the main factor in determining the final concentration of β-glucans in barley kernel. Naked barleys often have higher β-glucan contents (Farag et al. 2022) and are mainly used as human food thanks to easier processing after harvesting and consumption. Barley genotypes show also differences in the amylose/amylopectin ratio and genotypes with both waxy starch (with up to 100% amylopectin) and high amylose (over 35%) are available. Interestingly, these genotypes with different starch composition are also characterized by higher β-glucan concentration (Ferrari et al. 2009). Barley generally contains high molecular weight β-glucans that determine highviscosity solution and are responsible to enhance gut viscosity that is correlated to barley physiological activities (Murphy et al. 2020).

2.1.2 β-Glucans: Biochemical Pathway of Production β-(1!3),(1!4) at 4–5 days after pollination (DAP) and are uniformly distributed in the tissue by 10 DAP. β-(1!3),(1!4)-glucan content increases considerably within 16–36 DAP, coinciding with the grain filling and maturation stages (Garcia-Gimenez et al. 2019). The synthesis of β-glucans in barley is regulated by members of the cellulose synthase-like gene families, CslF and CslH. Seven CslF and one CslH (cellulose synthase-like genes) are responsible for β-glucan synthesis, and a UDP-glucose 4-epimerase (UGE) is also implicated. Among these, HvCslF6 is the most highly transcribed and is the most important gene for β-glucan synthesis in barley kernel. HvCslF6 was well characterized as a (1!3),(1! 4)-β-glucan synthase and it is expressed throughout grain development. This was confirmed in cslf6 mutant lines (called beta-glucanless or bgl) that have very low levels of mixed linkage β-glucan. During grain development, HvCslF6 and HvCslF9 are the predominant expressed genes, and a mutation in the HvCslF6 locus led to a loss of β-glucans accumulation. Burton et al. (2011) succeeded in overexpressing HvCslF4 and HvCslF6 in transgenic with extra copies of these genes, and the final result was an increase in grain β-glucan content of more than 50% and 80, respectively (Garcia-Gimenez et al. 2019). β-Glucan concentration is a quantitative trait, and there are several associated QTLs: for example, one QTL is located on chromosome 7H, within 5 cM of the Nud gene; this suggests a possible linkage effect. Many QTLs involved in β-glucan accumulation overlap with QTLs for amylose content probably due to co-localization or interaction between genes (Meints et al. 2021). In addition, several researchers suggested that variation in barley (1!3), (1!4)-β-glucan levels was also affected by polysaccharide remodeling and degradation pathways. Two barley genes, HvGlbI and HvGlbII, encoding for (1!3),

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(1!4)-β-glucan end hydrolases, have been reported to contribute to this trait, having an impact on modification on β-glucans during the malting process (Garcia-Gimenez et al. 2019).

β-glucans: Physiological Properties and Functions in Relation to Human Health β-Glucans play important roles, particularly in healthy foods and pharmaceutical products, due to their widely known beneficial effects, including immunomodulation, antitumor activity, serum cholesterol and glucose reduction, and obesity prevention (Bai et al. 2019). The degree and type of biological activity appear to be strictly correlated to β-glucans structural properties. 2.1.3

Physiological Properties of β-Glucans: Glycemic Control The reduction of the glycemic response after consumption of food (glycemic control) is among the most intensely studied and well-documented properties of barley β-glucans. This effect has been investigated in numerous animal and human studies using model food systems. There is evidence that increasing molar weight and/or viscosity of β-glucans improves the postprandial glucose regulation, indicating that this effect is based on the formation of a high-viscosity gel in the intestine. A proposed mechanism for these observations is that high viscosity of the intestinal content may slow down digestion of starch (by decelerating the diffusion of α-amylase toward its starch substrate) and the absorption of glucose (Tosh and Bordenave 2021). β-Glucan molecular weight should be an important trait in glycemic response, but to date, there are still contradicting results regarding the importance of this trait on glycemic response. Some researchers found that high molar mass and viscosity are essential parameters for healthy effects, such as glycemic control (Schmidt 2022). In contrast, recent studies reported no differences in the control of blood glucose and cholesterol lowering between hydrolyzed and native barley β-glucan in mice (Schmidt 2022). Physiological Properties of β-Glucans: Cholesterol Lowering Another well-studied health-promoting property of barley β-glucans is the ability to lower blood cholesterol levels. While high-density lipoprotein (HDL) cholesterol remains unaffected by β-glucans, the reduction in low-density lipoprotein (LDL) cholesterol, an important marker for the risk of cardiovascular diseases, is recognized (Schmidt 2022). The generally accepted mechanism behind this is based on the formation of a highly viscous gel inside the human intestine. The gel interacts with the bile acids present in the gastric system, preventing their readsorption and thus promotes the de novo synthesis of such acids. Since cholesterol is used for the bile acid synthesis, it is captured from blood and its concentration decreases (Schmidt 2022). Based on this data, the EFSA and FDA have concluded that the regular consumption of at least 3 g of β-glucans from oat and/or barley per day is required to achieve a substantial cholesterol-lowering effect (EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA) 2011; FDA_b-glucan health 2006).

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Physiological Properties of β-Glucans: Effects on Gut Microbiota The role of microbiota in maintaining good health is now clearly established, and whole-grain barley can support the growth and maintenance of gut microbiota (Tosh and Bordenave 2021). Fermentable fiber and β-glucan are a fundamental part of it and could actively impact the microbiota. β-Glucans perform their function of regulating blood cholesterol levels through the modulation of the microbiota, which is directly related to the metabolism of bile acids. β-Glucans are resistant to digestion, reach the small intestine, and are fermented by gut microbiota producing short-chain fatty acid (SCFA), limiting HMG-CoA activity, improving cholesterol catabolism (Murphy et al. 2020). Through dietary fiber fermentation, intestinal microbiota produces short-chain fatty acids (SCFA) (acetic, propionic, and butyric acids): butyric acid, in particular, plays an important role in promoting and maintaining colon health, while propionic acid, after supplementation of β-glucans, showed hypocholesterolemic properties. Furthermore, SCFA have been found to modulate the immune system (Murphy et al. 2020). β-Glucans are considered prebiotic as they improve indirectly gastrointestinal function by enhancing the intestinal microbiota (Murphy et al. 2020). They elicit the growth and activity of commensal bacteria in the colon. Both in vitro and in vivo models have confirmed that the growth of normal intestinal bacteria (Lactobacilli and Bifidobacteria species) is increased by β-glucans (Murphy et al. 2020). The intestinal microorganism can also influence hormone secretion. In particular, insulin sensitivity may be improved by the promotion of gut hormone secretion from enteroendocrine cells by SCFAs (Murphy et al. 2020).

2.1.4

Methods of Nutraceutical Improvement: Agronomic and Postharvesting Techniques β-Glucan content is a trait highly influenced by genotype, and this is a good point to develop new genotypes with the aim of functional food production. The environment and agronomic practices can also impact β-glucan levels. Supplementation of soil nitrogen can cause an increase in β-glucan levels, while increased irrigation has shown to lower β-glucan content (Choi et al. 2020). Dry and hot weather can also determine an increase in β-glucan concentration, while cooler, wetter conditions are generally correlated to a reduction in β-glucan content (Meints et al. 2021). Given the nutraceutical importance of β-glucans, over the years, methods have been developed to incorporate barley flours into baked products to make them functional foods. As β-glucans are water-soluble compounds, barley fractions enriched in β-glucans were obtained by extraction with aqueous solvents (Mejía et al. 2020). However, these procedures are highly energy-consuming and sometimes use dangerous solutions like sodium hydroxide or organic solvents, residues of which are forbidden in human foods. Otherwise, a way to increase β-glucan content is to mill and sieve barley flours to discriminate β-glucan-rich fraction (Mejía et al. 2020). The addition of barley flour, however, significantly worsens the quality characteristics of bakery products.

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Tocols

2.2.1 Tocols: Structure and Content Tocopherols (vitamin E) and tocotrienols, grouped as tocols, are a class of lipidsoluble antioxidants only synthesized by plants and other photosynthetic organisms. They are amphipathic molecules with a polar head group, the chroman ring, and a hydrophobic tail, which is either saturated (tocopherols) or contains three double bonds at positions 3, 7, and 11 (tocotrienols). Four homologs (α-, β-, γ-, δ-) exist for each tocol class, differing only in the number and position of methyl substitutions on the aromatic ring (Tiwari and Cummins 2009) (Fig. 3).

Fig. 3 Structure of barley tocols

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Oils from vegetable sources are the main forms of tocols, but also cereals, like barley, oats, wheat, rye, and rice are reported to be an excellent source of this class of compounds. The tocol composition of barley is unique as it includes all eight homologs (Obadi et al. 2021). In the barley grain, tocopherols and β-tocotrienol are mainly located in the germ, while hulls and endosperm have substantial tocotrienols concentration (Obadi et al. 2021) and accumulate during grain development (Obadi et al. 2021). Among cereals, barley is one of the best sources of tocopherols and tocotrienols due to a high level and favorable distribution of all eight biologically active homologs (Obadi et al. 2021). In whole-grain barley, α-tocotrienol is the most individual tocol homolog, contributing about 47.7% of the total tocol content, followed by α-tocopherol, γ-tocotrienol, γ-tocopherol, β-tocotrienol, and δ-tocotrienol (Idehen et al. 2017). The total tocotrienol level is markedly higher than the total tocopherol level (Idehen et al. 2017). There is a wide variation, influenced by genotypes and environment, in quantities of tocols in barley. Temelli et al. (2013) examined the total tocol content of wholegrain barley varieties, which ranged from 40 mg/kg to 151.1 mg/kg. Hulled barley has been shown to possess more tocols than hull-less barley (Idehen et al. 2017). Cavallero et al. (2004) also reported higher tocol and α-tocotrienol contents in hulled barley (53 and 61 mg/kg) than in hull-less barley (50.9 and 53.1 mg/kg). This was explained by the presence of tocols in the hull of barley.

2.2.2

Tocols: Physiological Properties and Functions in Relation to Human Health The presence of the phenolic hydroxyl group in tocopherol and tocotrienols is essential for the antioxidant activity of vitamin E due to the ability to donate a phenolic hydroxyl group of the chromanol ring to blocking peroxidation of lipids in cell membranes (Tiwari and Cummins 2009). α-Tocopherol content is important from a nutritional point of view as it is the tocol homolog with the highest vitamin E activity. The other homologs of tocols exhibit vitamin E activity in the following order: α-tocopherol > β-tocopherol > α-tocotrienol > γ-tocopherol > β-tocotrienol> δ-tocopherol (Gangopadhyay et al. 2015). Although α-tocopherol has the highest vitamin E activity, α-tocotrienol has been found to possess 40–60 times higher antioxidant activity than α-tocopherol (Gangopadhyay et al. 2015). In addition to antioxidant properties, studies have shown that tocotrienols have several beneficial functions. For example, thanks to the capacity of inhibition of cholesterol biosynthesis, they determine a protective effect by lowering LDL cholesterol (Tiwari and Cummins 2009). The hypocholesterolemic effect of α-tocotrienol is due to the suppression of hydroxyl-β-methylglutaryl co-enzyme A reductase, the key enzyme of cholesterol synthesis (Tiwari and Cummins 2009). Moreover, the tocol content of cereals can confer human health benefits, including modulating degenerative diseases like cancer and cardiovascular diseases (CVD) (Obadi et al. 2021). 2.2.3 Tocol Biosynthesis The biosynthesis of tocopherol occurs in plastids of plant cell, except for the first step of tocopherol biosynthesis (biosynthesis of chromanol head) that occurs in a plant’s cytoplasm (Fritsche et al. 2017).

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The biosynthesis starts through the formation of the chromanol ring, which is derived via the shikimate pathway from homogentisate. The polyprenyl side chain (phytyl diphosphate, phytyl PP/PDP) is suggested to originate from DOXP (1-deoxy-D-xylulose-5-phosphate) pathway, as well as from the recycling of free phytol derived from the chlorophyll degradation process (Fritsche et al. 2017). In tocopherols, the prenyl tail attached to the chromanol ring is derived from phytyl diphosphate (PDP). In tocotrienols, it originates from the condensation of HGA and phytyl diphosphate (PDP), which is catalyzed by the plastid-localized enzyme HGA phytyl transferase (HPT) (Yang et al. 2011). Plant tissues vary enormously in their tocol content and composition with photosynthetic tissues generally containing low levels of total tocols and a high percentage of α-tocopherol, whereas seeds contain 10–20 times this level of total tocols, but α-tocopherol is often a minor component (DellaPenna and Pogson 2006).

2.2.4

Methods of Nutraceutical Improvement: Agronomic and Postharvesting Technique Food processing significantly influences the level and stability of tocols (Tiwari and Cummins 2009). After harvesting, cereal grains undergo substantial changes in composition before being consumed; for example, tocol cereal content is influenced by pearling, milling, extrusion, cooking, malting, and baking (Tiwari and Cummins 2009). Pearling (which causes the removal of hull, aleurone, and germ) significantly decreased tocol concentration, if compared to the whole seed, suggesting that dehulled seed is not a rich source of tocols, whereas its by-product (the removed material during pearling) is rich in tocols (Farag et al. 2022). Tocol level was not affected by malting process, although brewers’ spent grains were enriched in tocols (Peterson 1994), becoming a good source of tocols. This attribute could make them valuable additions to food products, particularly as they will contain substances that have favorable effects on cholesterol levels and may offer remarkable economic and waste management opportunities. Storage is another factor that has an influence on the tocol content. Antioxidants and, among them, the tocols can be easily affected by light, water, and heat. Generally, after being harvested, barley will be stored for periods ranging from 4 to 18 months before processing. The storage may have an effect on vitamin E content and antioxidant capacity. Do et al. (2015) measured tocol content and antioxidant capacity in 25 barley cultivars before and after 4 months storage at 10  C. They observed that six homologs (α- T, α-T3, β-T, β-T3, γ-T, and γ-T3) were detected in barley genotypes after 4 months storage, but the amounts of δ-T and δ-T3 were minimal. The total vitamin E content changed from 6% to 30% after 4 months of storage. Liu and Moreau (2008), on the other hand, found the storage at 35  C with 75% relative humidity for 3 weeks caused no change in oil and tocopherols, but significant changes in tocotrienols. The changes were differential among T3 homologs, with α-tocotrienol decreasing and δ-tocotrienol increasing. The reduction in α-tocotrienol was accelerated in fractions characterized by a higher proportion of endosperm tissue. When the storage was prolonged for 6 months, the authors

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confirmed these findings. These results and practical information can help us to produce barley fractions enriched with functional lipids and maintain stability of their products.

2.3

Simple Phenols and Polyphenols

Phenolic compounds comprise a large heterogeneous class of secondary metabolites. Phenolics possess one or more aromatic rings with one or more hydroxyl groups and can be classified into different ways, based on their chemical structure, and distribution in nature. Barley is considered a good source of many classes of phenolic compounds, such as phenolic acids, proanthocyanins, quinones, flavanols, chalcones, flavones, and flavonones. These compounds may exist in free, conjugated, or bound forms. Due to the high level of phenolics in barley grains, this cereal can be considered a good dietary source of antioxidants, which have antiradical and antiproliferative capacity and are correlated to the potential prevention of several chronic disease and health well-being (Farag et al. 2022).

2.3.1 Phenolics Acids: Structure and Content Benzoic and cinnamic acid derivatives (grouped as phenolic acids, Fig. 4) are the dominant class of phenolics in barley and are in the outer layers of the kernel (Idehen et al. 2017). In barley, they are mainly present in the bound form, some are present in conjugated form, and only to a lesser extent are present in the free form. The free

Fig. 4 Structure of barley phenolic acids

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forms are concentrated in the outer layers of the pericarp, whereas the bound forms are esterified to cell wall constituents, such as lignin, cellulose, arabinoxylans, and other polysaccharides (Loskutov and Khlestkina 2021). Ferulic and p-coumaric acids are phenolic compounds abundantly found in whole grains of barley; they exist in free, bound, and soluble-conjugated forms. The composition of phenolic compounds depends upon the grain type, cultivars, and morphological fraction used for analysis. Deng et al. (2020) analyzed different hull-less barley genotypes for phenolic composition and content: bond ferulic acid resulted the predominant one, and the content varies from 50.16 to 54.65 mg/kg. In the study conducted by Šimić et al. (2019), ferulic acid content was found to have a wide range (4.5–102.7 mg/100 g dry weight) among different fractions of hull-less barley. They reported that ferulic acid was distributed mostly in the outer bran and has the lowest content in the endosperm. p-hydroxybenzoic (3.43–17.44 mg/kg), gallic (3.50–32.90 mg/kg), and vanillic (3.20–24.70 mg/kg) acids were the predominant phenolic acids present in the free form (Šimić et al. 2019). Martinez et al. (2018) observed a considerable variation in the content of total ferulic acid concentration, analyzing a set of barley genotypes, hulled and hull-less, with different origin. The content of some bound phenolic acids was related to the occurrence or lack of hull, with significantly higher levels of these compounds observed in the hulled genotypes compared to the hull-less samples.

2.3.2 Flavonoids: Structure and Content Flavonoids (Fig. 5) are a phenolic class with a C6–C3–C6 skeleton (two aromatic rings joined by a three-carbon link).

Fig. 5 Structure of barley flavonoids: flavonols and anthocyanins

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Clinical trials indicate that flavonoids may be the phytochemicals present in cereal grains correlated to the moderation of many diseases, like cancer and coronary heart diseases (Idehen et al. 2017). Flavonoids are a subclass of plant phenols and have been shown to have many health benefits, such as antioxidant, anticancer, antiallergic, and anti-inflammatory. Naringin (flavanone), catechin (flavonol), and quercetin (flavon) were reported to be the three predominant flavonoids in hull-less barleys with contents varied from 0.8 to 9.8, 0.1–20.5, and 1.4–8.7 mg/100 g (dry weight), respectively (Deng et al. 2020). Zhu et al. (2015) reported that total flavonoids (free and bound) in four hull-less barley varieties ranged between 145.5 and 247.4 mg catechin equivalents/100 g, dry weight basis, observing that it was higher than other grains like corn, wheat, oat, and rice (Zhu et al. 2015). Anthocyanins are water-soluble flavonoids, located in the vacuole, and they are mainly present in the pericarp or the aleurone layers of barley kernel, determining the purple or blue grain pigmentation, respectively. This class of flavonoid is normally present as glycoside in the grains. A range of anthocyanin compounds have been identified in barley kernels by various authors. Martinez et al. (2018) identified up to 27 anthocyanins in different barley genotypes. The most common anthocyanin in purple barley is cyanidin 3-glucosode, followed by peonidin 3-glucoside and pelargonidin 3-glucoside. Delphinidin 3-glucoside was found to be the main anthocyanin in blue and black barley varieties (Martínez et al. 2018) (Fig. 5). Martinez et al. (2018) found that purple and blue barleys contained higher average level of anthocyanins than the black barleys tested. This could be explained because the black pigmentation present in barley is linked to the presence of melanin-like pigment. So, it could be assumed that the color of the black barley genotypes is probably a result of co-pigmentation between anthocyanins and melanin-like pigments (Glagoleva et al. 2022). Proanthocyanidins (PAs), or condensed tannins, are a group of polyphenols that naturally occur in a wide range of plants, including barley (Fig. 6). PAs can be structurally distinguished by the different hydroxylation patterns of the basic flavan-3-ol units and by the nature of the bond among monomers. The common basic units are (epi)gallocatechins, (epi)catechins, and (epi)catechins, resulting in the formation of prodelphinidin, procyanidin, and propelargonidin structures, respectively. The units are commonly linked through B-type bonds (C4!C6or C4!C8 linkage), while an additional linkage (C2!O5 or C2!O7) contributes to the formation of A-type bonds (Zhu 2019). Different proanthocyanidin composition and concentration has been observed and linked to genetic diversity in barleys. For example, Verardo et al. (2015) found that PA concentrations in 14 barley genotypes ranged from 293 to 653 mg/kg. The HPLC-MS analysis revealed the presence of catechin/epicatechin monomers, procyanidin dimer, prodelphinidin dimer, procyanidin trimer (36.7–167 mg/g), prodelphinidin trimer I (monogalloylated), prodelphinidin trimer II (digalloylated), procyanidin tetramer, prodelphinidin tetramer, and procyanidin pentamer (Verardo et al. 2015).

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Fig. 6 Structure of proanthocyanidins found in barley

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Fig. 7 Structures of major lignans in barley

Lignans (Fig. 7) are natural polyphenols widely distributed in the plant kingdom and are recognized as natural defense compounds. They possess a phytoestrogens-like activity due to their structural and functional similarity to 17-β-estradiol. Lignans have been suggested to have a wide range of biological effects, such as antioxidant, antitumor, antimicrobial, antifungal, estrogenic, and antiestrogenic activities, and protect against coronary heart diseases. There is little information in the literature about the structure and concentration of lignans in barley. Smeds et al. (2007) analyzed lignan content in barley: the authors reported the presence of pinoresinol (71 mg/100 g), medioresinol (22 mg/100 g), syringaresinol (140 mg/100 g), lariciresinol (133 mg/100 g), cyclolariciresinol (28 mg/100 g), secoisolariciresinol (42 mg/100 g), secoisolariciresinol-sesquilignan (24 mg/100 g), matairesinol (42 mg/100 g), oxomatairesinol (28 mg/100 g), and 7-hydroxymatairesinol (541 mg/100 g) as major lignans and todolactol (127 mg/ 100 g), α-conidendrin acid (33 mg/100 g), nortrachelogenin (15 mg/100 g), and lariciresinol-sesquillgnan (6.6 mg/100 g) as minor lignans.

2.3.3

Simple Phenols and Polyphenols: Physiological Properties and Functions in Relation to Human Health Free radicals in human body can induce a series of diseases such as cancer diabetes, atherosclerosis, and reproductive endocrine dysfunction. Phenols, in this sense, can have an important function as they act as scavengers of free radicals and could play a major role in moderating cardiovascular diseases. Several in vitro experiments

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evidenced the bioactivities of barley phenols (Idehen et al. 2017). The most studied and reported bioactivity are the in vitro antioxidant capacity and free-radical-scavenging activity determined by different chemical tests, including DPPH, ORAC, FRAP, and ABTS (Obadi et al. 2021). Blue hull-less barley varieties evidenced higher antioxidant activities than regular barley varieties: these genotypes showed higher antioxidant than Canadian, Egyptian, and Tunisian barley (Yang et al. 2018). Li et al. (2019) demonstrated strong correlations between antioxidant capacities of barley grains and phenolic concentration, denoting that the phenolic compounds represent the main responsible for the antioxidant activity of whole naked barley flours. Abdel-Aal et al. 2012 selected Canadian and Egyptian barleys and investigated phenolic acid composition and antioxidant capacity against DPPH and ABTS radicals, and inhibition of oxidation of human low-density lipoprotein (LDL) cholesterol of whole grain flours and pearling fractions. The data showed significant variations among barley wholegrain flour and pearling/milling fractions in terms of phenolic acid composition and antioxidant capacity. Health benefits of barley phenols have also been reported in in vivo experiments using animal and clinical models. Mice that were fed with 600 mg/kg BW of polyphenol extract from black highland barley showed a significant reduction in total cholesterol (23.33%), LDL cholesterol (26.29%), and atherosclerosis index (38.70%), and an increase in high-density lipoprotein cholesterol (HDL, 17.80%) (Shen et al. 2016). Lee et al. (2015) also demonstrated that extracts from barley sprouts containing polyphenols regulated AMP-activated protein kinase, a cellular sensor of energy metabolism and a regulator for cholesterol metabolism. Oxidative stress, which has a key role in pathology like diabetes and obesity, can be reduced by phytochemicals present in barley, particularly phenolic compounds (Idehen et al. 2017). As previously reported, a large part of phenol compounds is bonded to cell wall constituents (i.e., cellulose, lignin, etc.), and therefore they are a part of dietary fiber. There is evidence that dietary fiber provides various beneficial health effects, among which are the decrease of the risk of cardiovascular disease, metabolic syndrome, diabetes, obesity, and cancers (Murphy et al. 2020); these health properties may be attributed to phytochemicals bound to or trapped within dietary fiber, especially phenolic compounds (Tosh and Bordenave 2021).

2.3.4 Simple Phenols and Polyphenols: Biosynthesis Barley grains accumulate a large amount and type of phenolic compounds, which are a product of secondary metabolism in plants. Moreover, different barley genotypes present different grain coloration: the most studied are yellow, purple, red, blue, and black. The yellow color is linked to the presence of proanthocyanidins synthesized in seed coat of the kernel; purple and red pigmented genotypes are characterized by the presence of anthocyanins, synthesized in pericarp and glumes; blue color is caused by anthocyanins synthesized in aleurone layer of the grain. In white barley grains, the pigments are not present (Shoeva et al. 2016).

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In barley, phenol biosynthesis metabolic pathway is well characterized: structural genes encoding enzymes of the pathway, as well as regulatory genes, have been described (Deng and Lu 2017) (Fig. 8). The fists step in phenylpropanoid biosynthetic pathway is the phenylalanine synthesis from the shikimate pathway. Phenylalanine ammonia lyase (PAL) catalyzes this first enzymatic step, which cause the deamination of phenylalanine to generate cinnamic acid, which in turn is hydroxylated to ρ-coumaric acid, catalyzed by cinnamate 4-hydroxylase (C4H). 4-Coumaroyl CoA ligase (4CL) is involved in the catalysis of the formation of ρ-coumaroyl-CoA from ρ-coumaroyl acid. The initial steps of the phenylpropanoid pathway are jointly known as the general phenylpropanoid pathway (GPP) (Deng and Lu 2017). After GPP, the pathway is branched leading to the synthesis of flavonoids, stilbenes, monolignols, phenolic acids, and coumarins. In the barley genome, the Chalcone synthase (CHS) characterize a gene family with at least seven copies. One of the Chs gene copies has been mapped to the short arm of chromosome 1H. Three nonoverlapping genetic markers for the Chs gene have been mapped to chromosomes 1HS, 1HL, and 6HS (Shoeva et al. 2016). The gene related to chalcone flavanone isomerase gene (Chi) has been identified and mapped to the long arm of chromosome 5H. Flavanone 3-hydroxylase gene (F3h) has been also characterized, and the gene has been localized to chromosome 2HL. Barley dihydroflavanol reductase gene (Dfr) has been mapped on the long arm of chromosome 3H. Other important genes coding for key enzyme have

Fig. 8 A schematic presentation of the flavonoid biosynthetic pathway in barley. The enzymes reported are CHS (chalcone synthase); CHI (chalcone-flavanone isomerase); F3H (flavanone 3-hydroxylase); FLS (flavonol synthase); FNS (flavone synthase); F30 H (flavonoid 30 -hydroxylase); F30 50 H (flavonoid 30 ,50 -hydroxylase); DFR (dihydroflavonol 4-reductase); ANS (anthocyanidin synthase); GT (glycosyltransferase); MT (methyltransferase), RT (rhamnosyltransferase); and LAR (leucoanthocyanidin reductase)

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been identified in barley: barley leucoanthocyanidin reductase (LAR) and gene for UDP glucose-flavonol 3-O-glucosyltransferase (UFGT), which mapping on the short arm of chromosome 7H. Flavonoid 3’-hydroxylase (F3’h) and anthocyanidin synthase (Ans) genes were identified and localized on chromosomes 1H and 5HL, respectively (Shoeva et al. 2016). In barley, anthocyanin pigmentation of the kernel pericarp is controlled by two complementary genes, Ant1 (MYB) and Ant2 (bHLH), which are located on chromosomes 7H and 2H, respectively (Glagoleva et al. 2020). They form, jointly with the transcription factor WD40, the MBW complex, which controls the anthocyanins biosynthetic pathway in a tissue-specific manner. Accumulation of blue anthocyanins in barley aleurone is controlled by HvMyc2 gene, a paralog of Ant2 (Strygina et al. 2017). Melanins are the product of enzymatic oxidation of phenolic precursors, such as tyrosine, cinnamic acid derivatives, and catechol, to quinones, which then undergo subsequent polymerization. Melanin biosynthesis in barley is under the monogenic control of Blp1 located on chromosome 1H (Long et al. 2019). Purple pigmentation (characterized by anthocyanins) and black pigmentation (characterized by phytomelanins) are under different genetic control, so these pigments can be both accumulated in the kernel combining genes controlling the two traits (Glagoleva et al. 2022).

2.3.5

Methods of Nutraceutical Improvement: Postharvesting Techniques Many authors have investigated the effects of grain type, genotype, and environment effect on the accumulation of phytochemical in barley grain. The most important goal of these studies is the possibility to select barley varieties, with improved nutritional characteristics. Several studies reported that pigmented barley genotypes accumulate a high concentration of different classes of polyphenols, like anthocyanins in blue or purple barley. This class of flavonoid had demonstrated important healthy properties. Moreover, there is a large variation in composition among the phytochemical composition in different cultivars, reflecting factors related to genetic diversity, indicating the need for proper selection of genetic material (Irakli et al. 2020). One of the most effective methods to improve nutritional value of seeds is germination. Several authors have demonstrated that germination can enhance the content of many phytochemicals, like phenolic compounds and other bioactive substances in grains, as well as remove antinutritional factors such as enzyme inhibitors. Tang et al. (2021) investigated the effect of germination on the polyphenol content, antioxidant capacity, and physicochemical properties of three different pigmented cultivars of hull-less barley. They observed that the germination determined an increase in the total phenolic and flavonoid content, as well as antioxidant properties. This could be due to the improved biosynthesis of polyphenols during germination.

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Also, malting process significantly affects the polyphenol content in grains. During the malting process, barley grains undergo different biochemical and physical changes: hydrolytic enzymes are released in the shoot or root developed during the malting process are removed physically (Sharma et al. 2022). Moreira et al. (2013) studied the antioxidant properties of brewer’s spent grain and reported that malt produced at lower temperature (light malt) had the higher total phenol content than raw barley. Fogarsi et al. (2015) observed that barley total phenols significantly increased after malting process. The germination and malting process increased the phenolic contents in barley due to the release of bound phenolic content by inherent enzymes (Sharma et al. 2022). Pearling, an important primary process in food-barley utilization, is a milling approach that gradually removes grain tissue by abrasive action and that, consequently, modulates the distribution of nutrients and phytochemicals in barley flour. Irakli et al. (2020) evidenced that bioactive components, including phenolic acids and flavonoids, exhibit a decreasing concentration from the external layers to the center part of barley grain among all barley cultivars tested, in contrast to what happens for β-glucans.

3

Next-Generation Breeding for Phytochemicals and Nutrient Contents

In recent years, scientists and the food industry developed and studied a wide range of new cereal products designed with healthy properties. Cereals, and among them barley, are a very rich source of several nutrients, micronutrients, and phytochemicals as already discussed in Sect. 2. Breeding techniques can help us to obtain new genetic materials with high a concentration of these cereal phytochemicals, and at the same time help to develop high-yielding genotypes, being able to combine the maximum level achievable for nutritional compounds and high-quality indicators, like yield, disease resistance, etc. (Loskutov and Khlestkina 2021). The genetic diversity existing among genotypes is at the base of all crop improvement programs. Diversity can be described as the degree of differentiation between or within species. The existence of genetic diversity within and between crop species permits the breeders to select superior genotypes to be used as parent in breeding programs. Wild species, related species, mutant lines, etc., represent the important source of genetic diversity and may provide new and favorable alleles (Bhandari et al. 2017). Thanks to the genetic diversity existing between the breeding parents, it is possible to obtain heterosis and transgressive segregants. Genetic diversity helps breeders to develop varieties for specific traits like quality improvement and tolerance to biotic and abiotic stresses. Another very important aspect, especially with respect to the continuous and recent climatic changes, is that genetic diversity is an aspect that helps crop plants to adapt to different environments and to variations in the environment itself (Bhandari et al. 2017).

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Tools for Assessing Genetic Diversity in Genomic Era

As genetic diversity is a fundamental aspect in breeding, the assessment of this diversity is crucial to ensure sufficient further genetic gain and make informed selection decisions. DNA-based methods are the most used for genetic diversity assessments. They can be divided into fragment analysis-based methods, in which DNA polymorphisms are determined by different sizes of DNA fragments; hybridization array-based methods, where DNA polymorphisms are detected by hybridizing the sample DNA to arrayed probes; and sequencing-based methods, where sequencing is used to detect polymorphisms. With these DNA-based methods, even thousands of polymorphisms may be assessed simultaneously in a lot of sample plants, making the analysis more cost-effective. Some of these can detect both coding and noncoding regions of the genome, which provides a broad view of genetic diversity and could potentially be employed to find genomic loci under selection. In recent years, DNA sequencing technologies have been subjected to considerable development, also allowing the analysis of complex genomes and the study of their genetic diversity (Loera-Sánchez et al. 2019). Thus, DNA-based molecular markers started to be used to examine the genetic basis of agronomic traits and improve crops through genome-based methods, including marker-assisted selection (MAS) and, in recent years, genomic selection. One of the disadvantages of traditional phenotype-based selection is the time needed to develop new varieties. Compared with traditional phenotype-based selection, genome-based breeding can directly find favorable alleles underlying the desired traits, and thus leads to precise selection that significantly reduces the time needed to develop new varieties (Liu et al. 2021). The fundamental characteristics of molecular markers are that they are correlated with phenotypic expression of a genomic trait, and that they are stable and detectable in all tissues despite of plant growth stage, and differentiation and status of the cell; moreover, environmental, pleiotropic, and epistatic effects do not influence them.

3.2

Connecting Genotype to Phenotype

3.2.1 Marker-Assisted Selection (MAS) As mentioned above, the development of molecular marker technology made plant breeding became more efficient by means of marker-assisted selection (MAS). Molecular markers are sequences of nucleotides and can be explored through the polymorphisms present between the nucleotide sequences of a given population. The polymorphism is highlighted through the identification of deletions, insertions, gene mutation, duplication, and translocation of a precise sequence, and they do not really influence the function of genes. There are five important considerations for the application of DNA markers in MAS: reliability (markers must be firmly connected to the target loci); quality and nature of required DNA; amount of DNA required; methodology for marker examination (high-throughput, straightforward techniques

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are required); cost-effectiveness; the level of polymorphism (ideally, the marker should be highly polymorphic in the breeding material): the suitability of a given molecular marker is dependent on its capacity to identify polymorphisms in the nucleotide sequences permitting segregation between the different alleles (Hasan et al. 2021). Different types of molecular markers have been used over the last few decades: restriction fragment length polymorphism (RFLP), random amplification of polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), microsatellite or simple sequence repeat (SSR), sequence characterized amplified region (SCARs), cleaved amplified polymorphic sequences (CAPS), single-nucleotide polymorphism (SNP), and diversity arrays technology (DArT) markers. Among these, SNP markers were the most widely used (Hasan et al. 2021). Molecular markers are powerful genomic tools for the assessment of genetic diversity within and between populations and offer the possibility to improve the performance of plant breeding program, especially in QTL identification, which help us to identify and locate genes on chromosomes. Moreover, if the identified marker is closely related to important agronomic traits, it can be used in MAS and thus increase the efficiency of selection, allowing acceleration of the total breeding process (Al-Abdallat et al. 2017). Marked-assisted selection combines information derived from mapping position of agronomical importance traits with and the linked molecular. The success of MAS depends on several factors, such as the number of individuals that can be analyzed, the genetic nature of the trait and the background in which the target gene must be transferred, and it is achieving increasing importance in breeding programs. Regarding the implications of barley breeding for nutrition quality traits, recent findings of regulatory features of anthocyanin biosynthesis in barley were useful for both MAS approach and genetic editing-based breeding strategies. Strygina et al. (2017) identified and characterized components of the anthocyanin synthesis regulatory network in the aleurone layer of barley. The genes identified and characterized included elements of the regulatory complex MBW, from which HvMyc2aMYC-encoding gene appeared to be the main factor determining variation of barley aleurone pigmentation. Gordeeva et al. (2019) applied a marker-assisted backcrossing approach evidencing its efficacy in creating barley genotype with favorable alleles of anthocyanin regulatory genes: they developed a set of near isogenic lines (NILs) and revealed specific features of the anthocyanin biosynthesis regulation in barley pericarp: the dominant alleles of both the Ant1 and Ant2 genes were required for anthocyanin accumulation in pericarp. The dominant allele of the two genes was upregulated in purple-pigmented line. The activity of these genes also influenced the expression of the F3’h and Ans structural genes. In addition, positive effect between Ant1 and Ant2 was detected. The results achieved in this work represent a strong basis for target manipulation to modulate the content of anthocyanins in barley grains. Since domestication, introgression breeding has been successfully used to improve barley, and it remains a key system for augmenting genetic diversity to deal with current and future challenges to crop production (Hernandez et al. 2020). Introgression essentially implies the transfer of a particularly and desirable trait from

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one plant species to another with the help of hybridization and frequent backcrossing. Introgression of favorable alleles using marker-assisted selection is now faster and more efficient due to the development of high-throughput tools and technologies. In the past century, breeding strategies were aimed to develop highly productive but uniform cultivars of cereals like wheat, barley, and other crops, leading to a constant decrease in genetic diversity. It is therefore necessary to find and improve strategies to increase the range of diversity especially in key quality traits. An important source of genes, alleles and genetic variation can be found in the ancestor of cultivated barley (H. vulgare subsp. spontaneum), landraces, and germplasm collections. Landraces have been used for the introgression of allele into adapted genotypes. Germplasm collections are excellent sources of genetic diversity. There are several germplasm collections in different part of the world, for example, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK, Germany), the Okayama University Barley and Wild Plant Resource Center (Japan), the International Center for Agricultural Research in the Dry Area (ICARDA), and the United States Department of Agriculture National Small Grains Collection (USDA-NSGC, the United States). All the collections from these institutions are an excellent source of generic diversity and were well characterized for gene and alleles linked to disease resistance, abiotic stress resistance, and yield performances (Hemshrot et al. 2019; Visioni et al. 2013; Monteagudo et al. 2019).

3.2.2 QTLs Genetic mapping of major genes and quantitative trait loci (QTLs) were widely used for many important agricultural traits and integrated with the conventional breeding process. A genome-wide association study (GWAS) has the same approach as the QTL mapping study, but using natural populations, landraces, cultivar collections released over years, and genotypes with little or no pedigree information. It is used to reveal the relationship between markers and phenotypic traits based on linkage disequilibrium (LD), considering that associated markers resulting from GWAS could be used in new MAS programs. GWAS approaches were used to identify novel QTLs for traits with practical implications on barley agronomical performances, quality, and disease-related traits. β-Glucan content is a quantitative trait with many associated QTLs found on chromosomes 1H, 2H, 5H, and 7H; they have been mapped in several populations, and candidate genes have been identified and validated. The QTL located on chromosome 7H and is within 5 cM of the Nud gene (Swanston and MiddlefellWilliams 2012), indicating a possible linkage effect. A pleiotropic effect between β-glucan and the recessive allele at the Waxy (WX) locus has been demonstrated (Meints et al. 2021). The Waxy gene codes for a granule-bound starch synthase I (GBSSI) (Li et al. 2021). Li et al. (2021) carried out a genome-wide association study (GWAS) and found several new QTLs that were related to starch content; these candidate genes and alleles can be used in future breeding programs focusing on amylose and amylopectin content. It has been also shown that mutations at the Lys3

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and Lys5 loci can modify β-glucan content, as well as other healthy compounds. Despite the shriveled endosperm, genotypes containing these mutations revealed higher amounts of β-glucans, fructans, arabinoxylans, and resistant starch (Meints et al. 2021). In the study of Steele et al. (2013), a breeding program for nutraceutical compounds in barley was developed using a large segregating population, developed from crosses between naked and hulled parents, selecting naked barley that were more than 65% genetically similar to UK hulled barley. With another approach, the authors obtained lines from a mapping population, with β-glucan contents ranging from 1.4% to 8.6% with transgressive segregation occurring in both directions; they also evidenced no significant association of β-glucan content with the nude gene (nud). A QTL describing about 30% of the β-glucan inheritance was found on chromosome arm 7HL, approximately 15 cM above nud, and CslF6 is the most probable candidate gene (Steele et al. 2013). If QTLs linked to β-glucan content and QTLS for yield components are combined, it is possible to develop new higher yielding functional food barley. The other quality barley trait of particular interest, related to the importance that antioxidant compounds have risen in recent years, is phenolic compound accumulation in the grain. To improve this quality trait, it is essential to identify genes and/or QTLs responsible for phenolic metabolism, but there are only a few studies on QTLs associated with phenolic compounds in barley. Han et al. (2018) determined total phenolic total flavonoid content and antioxidant capacity in grains of Tibetan barley, analyzing both wild and cultivated accessions. The results showed wild barley had higher content and broader genetic diversity of phenolic compounds than cultivated genotypes. The authors identified 20 unique QTLs associated with total phenolic compounds, total flavonoids, and antioxidant activity in Tibetan wild barley. Wild and cultivated barleys showed clearly different presence of QTLs linked to phenolic compounds, highlighting a significant genetic difference between the two different genetic materials and showing that Tibetan wild barley is suitable for barley breeding for phenolic compound content. The flavonoid class of compounds that characterized the pigmentation of barley pericarp are anthocyanins (Zhu 2018). Zhang et al. (2017) studied the genetic control of major anthocyanin compounds, peonidin-3-glucoside, P3G, and cyanidin-3-glucoside, C3G, which characterized the purple pericarp of barley using a segregating population suitable for QTL mapping. Both anthocyanin compounds were linked to two loci, one located on chromosome arm 2HL and the other on 7HS. The two different anthocyanins appear to be controlled by the different interactions of the two loci. The impact of the 7HS locus on P3G and C3G was not so clear if before the effect of the 2HL locus was removed. The biosynthesis of peonidin-3-glucoside needs at least one copy of 2HL alleles. This does not seem to be the case for the accumulation of cyanidin-3 glucoside that was produced regardless of the allele combinations between loci. The inheritance of purple pigmentation of the barley grains showed a typical maternal effect. The different anthocyanins present in pigmented barleys, their different concentrations, and their different genetic control

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suggest the development of breeding programs, and consequently food processing, directed to individual anthocyanins. Mohammadi et al. (2014) conducted an association mapping study on physicochemical properties of barley that play a role in its nutritional quality, like total phenolics, amylose, and β-glucan content. They used 3.069 breeding lines, including two-row and six-row spring barley, from US breeding programs, and 2.041 SNP markers for association mapping. For total phenolics, they identified three significant regions on 3H, 4H, and 5H chromosomes. Two regions on 2H and 7H were associated with β-glucan. They also identified several markers associated with amylose content on chromosome 7H. The future of breeding will be, at genomic level, the development of genotypes that contain the most favorable alleles for every gene for target compounds. Thanks to new genomic technologies, which allows the employment of genome-wide marker assays, accurate and high throughput, and in combination with new methods like gene editing and rapid generation turnover such as genomic selection (GS), have the capacity to accelerate the rate of genetic gains in crop breeding programs. Traits linked to quality and nutritional value of grains are the result of human selection in the relatively short period of 10,000 years since domestication began compared to other more complex traits like grain yield. As a result, many of these traits are relatively simple and controlled by one or a few major genes that have been selected by humans (Kumar Id et al. 2019). If we can use genomics to find and characterize these genes selected by humans, we can improve breeding strategies to obtain high-quality grains for breeding for grain quality.

3.2.3 Omic Technologies for Functional Food The application of omics technologies to crop breeding is strongly growing in interest. Foodomics include different omic technologies in relation to food and nutrition science, with the aim of improving human health and well-being. The omic topics comprise four major broad areas like genomics, transcriptomics, proteomics, and metabolomics. Genomics includes the sequencing of whole genomes, assembly and annotation of the sequences, identification and development of molecular markers and quantitative trait loci (QTLs) for target traits, genomics-assisted breeding, genomic selection, etc. (Nayak et al. 2021), and all these tools can be used for the improvement of the nutritional and functional quality of cereal species. The characterization of key genes involved in defining grain quality traits can be achieved by conventional genetic mapping techniques, but direct genomics approaches are helpful for the purpose. For example, genome resequencing of a large number of genotypes that differ for a specific trait can allow association with the quality trait. Transcriptomics refer to the study of how genes are expressed, changed, and interconnected in specific tissue at a particular stage. The differential gene expression can be studied and quantified by using different molecular biology techniques such as RNA sequencing, microarrays, Serial analysis of Gene Expression (SAGE), qRT-PCR, etc. While microarray, SAGE, and qRTPCR technologies are used for defined transcripts, the RNA sequencing has the advantage of high-throughput

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sequencing and captures all expressed genes (Nayak et al. 2021). Analysis of differential expression between genotypes that differ for specific traits is also a step to gene identification. RNA-seq analysis is now a well-established tool for analysis of differences in the transcriptome, which represent the sum of all RNA transcripts of a specific organism. The RNA-seq analysis of developing and mature grains can reveal the genetic determinants of grain composition and, as a consequence, grain quality. Chen et al. (2014) made a de novo transcriptome analysis of developing barley grains using two Tibetan hull-less barley landraces, focusing the attention on gene expression levels related to the biosynthesis of storage components (starch, protein, and β-glucan); the temporal and spatial patterns of these genes were deduced from the transcriptome data of cultivated barley Morex. The results of this study showed how the genes related to important nutritional traits changed the expression during germination and developing of the seed. Moreover, the characterization of these genes provides resources to identify genes that can help in nutritional quality improvement of hull-less barley. Proteomics can be effectively used to study protein structure, function, and interaction with other proteins or other bioactive compounds. Advanced techniques like matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) and liquid chromatography coupled to mass spectrometry (LC-MS) can detect and identify proteins differentially expressed (Nayak et al. 2021). Metabolomics is a systematic study of all the metabolites of organism, tissue, cell, and can be considered as a phenotyping tool. A typical and practical application of this omic science concerns the identification and quantification of specific metabolites present in a sample. Metabolomics can be used for quantification of biologically active compounds, food fingerprinting, and food profiling. Techniques like gas chromatography coupled to mass spectrometry (GC-MS), liquid chromatography coupled to mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR), have been largely used for the purpose of identification and quantification of metabolites (Nayak et al. 2021). Metabolomic analyses have been generally classified as targeted or untargeted. Targeted analyses focus on a specific group of compounds, requiring their identification and quantification. Targeted analyses are important for assessing the behavior of a certain class of metabolites in the sample under specific conditions. Moreover, targeted metabolomics usually requires higher level of purification and selective extraction protocols. In contrast, with untargeted metabolomics the attention is focused on the detection of as many groups of metabolites as possible to obtain patterns or fingerprints without necessarily identifying or quantifying all compounds. Untargeted analyses have been used for the fingerprints of biological events, such as plant diseases. The development of untargeted metabolic approaches was facilitated by the rapid advance in analytical techniques allowing the simultaneous detection of a wide range of compound classes. The techniques most commonly used for the characterization of compounds are mass spectrometry (MS) and NMR. Several omics technologies have been used for barley especially for the study of disease resistance and yield-related traits. However, there are only a few reports related to the functional compounds and quality properties in barley (Han et al. 2018; Chen et al. 2014).

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Liang et al. (2022) employed an untargeted metabolomics approach using UPLCMS/MS to investigate the metabolic differences of five hull-less barley with different grain colors. The authors annotated more than 600 metabolites, including flavonoids, amino acids, and phenolic acids. Colored hull-less barley cultivars were rich in flavonoids and possessed specific metabolite profiles that differ from the white hullless barley, and these flavonoids also vary between the different colored cultivars. These results improve the understanding of the metabolic pathways and health value associated with different barley pericarp colors. Plant metabolomics is a powerful tool to explore the metabolic and molecular regulatory mechanisms of plant growth, stress responses, and the improvement of crop productivity and quality. Thanks to next-generation sequencing technologies, metabolome-based GWAS (mGWAS) has been used to study genetic pathway that determines metabolic diversity and their associations with complex traits in plants (Scossa et al. 2016). Metabolomics combined with other omics could be a key issue of agronomic performance that was not resolved previously. Besides the chemical information, plant metabolomics can provide data on correlation among the different metabolites and agronomic important traits. Even more promising is the possibility of studying the relationship between metabolite modification and the resulting phenotype (Scossa et al. 2016; Zeng et al. 2020). This approach has accelerated to elucidate flavonoid pathways in cereals, including barley. Zeng et al. (2020) conducted comprehensive metabolic profiling and a metabolite-based genomewide association study (mGWAS) in the grain and leaf of 196 hull-less and hulled barley accessions. They identified a total of 90 loci associated to metabolites from different branches of the phenylpropanoid pathway, which are also involved in UV-B protection; some alleles related to high-level metabolite trait were found to be significantly enriched in naked barley, suggesting co-selection of various phenylpropanoids. They also identified some genetic determinants regulating natural variation of phenylpropanoid content, including three novel proteins, a flavone C-pentosyltransferase, a tyramine hydroxycinnamoyl acyltransferase, and a MYB transcription factor. Besides these omics approaches, genome-editing tools like RNAi, CRISPR/Cas9, TALENs, and ZFNs can be utilized to improve the crop plants. Use of computational and bioinformatics tools is essential and indispensable while using all these technologies (Nayak et al. 2021). Genome editing (also called gene editing) is one of the most powerful tools to study the function of genes and an approach by which it is possible to obtain desirable traits in crops. It consists of cutting the genome with a nuclease and then introducing new mutations through DNA repair pathways. Three genome-editing systems, ZFN (zinc-finger nucleases), TALEN (transcription activator-like effector nucleases), and CRISPR-Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein), have been well developed and reported for plants (Nadakuduti and Enciso-Rodríguez 2021). CRISPR-Cas9 is, so far, the most promising and versatile genome-editing technology and has been applied in barley to manipulate grain quality traits (Garcia-Gimenez and Jobling 2022).

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Genetic and Genomics Resources

Several genomic resources have been developed to study partial or total genomic sequences and the related gene function in barley. High-quality barley genetic maps have been developed, based on mutant phenotypes, and these results updated and complemented with genome-wide genetic maps generated from molecular markers. The open accessibility of barley sequencing data allowed us to understand the genetic and regulatory functions of genes related to agronomically important phenotypes. The haploid genome of barley is about 5.3 Gb in size distributed across seven chromosomes. In 2012, the International Barley Genome Sequencing Consortium published the first reference genome derived from the cultivar Morex (Mayer et al. 2016); this reference genome has been then improved in sequence depth, genome assembly, and annotation (Monat et al. 2019; Mascher et al. 2017) and can be accessed at http://barleysequence.org/. With the release of the barley genome sequence and the open availability of data, barley breeding is now in the “genomic” era, while barley research is in the postgenomic era. A number of genomic databases for barley have been produced, most of them freely available, and they are being used in different ways to identify or map the specific genes or genomic regions (Riaz et al. 2021) (Table 1).

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Barley Gene Pools

Wide genetic variability can be found inside the three barley gene pools, characterized by different levels of fertility with cultivated barley (Wendler 2018). The primary gene pool includes barley itself (Hordeum vulgare spp. L), collecting landraces, obsolete, and modern varieties, and H. spontaneum. The accessions belonging to this gene pool can easily produce hybrids and are therefore the basis of barley improvement. H. bulbosum is the only member within the secondary gene pool. A relatively large set of hybrids, substitution, and introgression lines between barley and H. bulbosum have been obtained and characterized via genotyping-by-sequencing and Exome Capture to unlock these genetic resources. The tertiary gene pool, including more than 31 wild species, has severe barrier to fertility respect to cultivated barley and its role in breeding programs is limited. An exception is represented by Tritordeum, an amphiploid derived from the cross between the wild barley Hordeum chilense and durum wheat. Tritordeum, from a nutritional point of view, has some peculiarities in comparison with the parentals, that is, the high carotenoid content and very low gluten content. The success of this new species underlines the importance of genetic resources for the development of new innovative products for agriculture and industry, as reviewed by Avila et al. (2021). The three gene pools are the building block to obtain the species pan-genome and genus super-pangenome. A key tool for the study of the barley pangenetic diversity

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Table 1 Barley genomic resources (Riaz et al. 2021; Jayakodi et al. 2020; Tan et al. 2020; König et al. 2020) Database/Website URL EnsemblPlants http://www.ensemblgenomes.org Gramene http://www.gramene.org

Nord-Gen https://www.nordgen.org/en/ BARLEX http://barlex.barleysequence.org

MorexGenes https://ics.hutton.ac.uk/ morexGenes/

GrainGenes https://wheat.pw.usda.gov.GG3/ barley_blvd HvGDB http://www.plantgdb.org/ HvGDB/

Bex-DB https://barleyflc.dna.affrc.go.jp/ bexdb/index.html Barley DB http://earth.nig.ac.jp/~dclust/cgibin/index.cgi?lang¼en

BarleyVarDB

Application Web database that acquires the genomic and proteomic data of different plant species, including barley Provides an overview of comparative maps of cereals including available updated molecular markers and maps of barley International database for genetic stock and mutant data collection in Nordic countries Presents the first linearly ordered barley sequence; provides physical and genetic maps of molecular markers and genes using different version of assembly and gene set, with expression profiling data of 16 developmental stages, as well as exome capture data Offers access to gene expression levels from RNA-seq data of the barley cv. Morex, which are assembled from whole-genome shotgun sequences of Morex Genetic database primarily containing data on barley and wheat (genetic markers, gene expression, QTLs) Barley database provided by plant genome DataBase; it offers comparative genomics by using genomic data integration and analysis It contains advanced tools for comparative genomics, to analyze syntenic relationships among grass genomes Database developed with the availability of full-length cDNA libraries of a two-rowed malting barley, Haruna Nijo Includes material on barley germplasms and genome resources, as well as BLAST and extra tools, which enables the creation of graphical figures of BLAST query results Database that provides data related to barley’s genomic variations in the form of three datasets – SNPs, InDels, and whole-genome sequences of wild and cultivated barley genomes

Tools Ve!P BLAST BLAST

BLAST

BLAST

BLAST CMAP BLAST GeneSeqer GenomeThreader

BLAST

CMAP BLAST BLASTscope GenomePaint BLAST Primer3

(continued)

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Table 1 (continued) Database/Website URL HarvEST https://harvest.ucr.edu/

BRIDGE https://bridge.ipk-gatersleben.de/ #start

Application HarvEST originated as EST databaseviewing software in support of gene function analyses and oligonucleotide design, then grew to support activities including microarray content design, SNP identification, genotyping platform design, comparative genomics, and the coupling of physical and genetic maps Visual analytics web Tool for barley Genebank Genomics

Tools BLAST

and its exploitation for crop improvement is in fact the genome sequence. However, a single reference genome cannot capture the full complement of barley sequence diversity. The genomes of 20 barley accessions belonging to primary gene pool, including landraces, varieties, and one Hordeum spontaneum, have been sequenced. From the assembly of multiple high-quality sequences, the so-called barley pan-genome has been obtained that can be considered a genomic infrastructure able to capture the full complement of sequence diversity of a crop species (Jayakodi et al. 2020). The use of structural variants individuated has been investigated in 300 GenBank accessions. The authors concluded: “This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding.” At an even higher level of complexity, it is assumed that the so-called super-pangenome can also be developed for crops, including barley. The superpangenome is the assembly of the pangenomes of different species, able to capture the genomic diversity at the genus level. Pangenomics of wild relatives belonging to the different gene pools can complete gene repertoire of a genus (Khan et al. 2020).

5

Conclusion and Future Perspective

Providing safe, nutritious, and accessible food continues to be a major challenge for agriculture. Barley is characterized by the presence of a large set of phytochemicals with the potential, and sometimes already demonstrated, impact on human health, so they are expected to play an ever-growing role in food industries, which are always looking for new healthy food for the general population. Consequently, plant breeders were driven to develop new breeding programs aimed to obtain cereal crop cultivars with higher contents of bioactive components in the grain (Loskutov and Khlestkina 2021). The progresses in genomics provide new modern tools for make breeding programs more efficient. Especially, the assembly of the first barley reference genome offered great opportunities for the application of genomics in plant breeding. Genomic information in combination with sequencing, resequencing, and genotyping

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datasets is being utilized to study important agricultural traits and their linked genes (Riaz et al. 2021). Moreover, the integration of genomics with other omics approaches in barley science aims to provide a nutritionally rich and safe cereal (Nayak et al. 2021). Another important aspect is that genomic tools will have a primary role to understand the impact of several environmental factors such as heat, drought, and plant diseases on crop quality, and this will become essential in adapting to a changing climate. Acknowledgments The authors acknowledge the financial support of the Joint Call Cofund FACCE ERA-GAS (grant no. 696356), Connect Farms project Italian MIPAAF project ID 79.

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Oats: Nutritional Uniqueness and Breeding of a Healthy Superfood Caterina Morcia, Franca Finocchiaro, Stefano Delbono, Roberta Ghizzoni, Fabio Reggiani, Paola Carnevali, Giorgio Tumino, Ilaria Carrara, and Valeria Terzi

Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nutritional Composition of Oat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Growing Importance in Chronic Diseases and Malnutrition Prevention . . . . . . . . . . . . . . . . . . Health-Related Molecules Unique to Oat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 β-D-Glucans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Avenanthramides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Genetic Resources of Health-Related (HR) Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Oat Breeding for Quality and Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Genetics of FHB Resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Breeding for Grain Size, Milling, and Naked Grains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Breeding for β-Glucans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Breeding for Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Breeding for Avenanthramides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Breeding for Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Are Oats Genetically Modified Crop? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 The Oat Genomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Conclusions and Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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C. Morcia · F. Finocchiaro · S. Delbono · R. Ghizzoni · F. Reggiani · V. Terzi (*) Council for Agricultural Research and Economics (CREA), Research centre for Genomics & Bioinformatics, Fiorenzuolad’Arda, PC, Italy e-mail: [email protected] P. Carnevali Barilla S.p.A, Parma, PR, Italy G. Tumino Plant Breeding, Wageningen University and Research, Wageningen, The Netherlands I. Carrara Dipartimento di Scienze degli Alimenti e del Farmaco, Università degli Studi di Parma, Parma, PR, Italy © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_5

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Abstract

Oat, of Poaceae grass family, is an important multipurpose cereal, cultivated for grain, food, feed, fodder, and straw, alone, in mixture, or as a dual-purpose crop. This cereal ranks sixth in world production statistics, following wheat, maize, rice, barley, and sorghum. Recently, an increased interest in oat arose due to its unique health-related properties. This cereal produces valuable and unique macro-, micro-, and phytonutrients, is rich in soluble fibers (mainly β-glucan), polyphenols, galactolipids, and contains a relatively high quantity of protein. In addition, oat is an important source of phenolic acids being the only cereal that contains avenanthramides, a group of phenolic alkaloids with beneficial effects on cardiovascular diseases and colon cancer prevention. Moreover, oat bran is an excellent source of B complex vitamins (B1, B2, B3, and B6) and tocopherol (vitamin E). The lipidic amount of whole-grain oats is doubled compared with other cereals and mainly consists of unsaturated fatty acids such as linoleic, oleic, and linolenic acids. Considerable genetic resources exist with large collections of landraces, wild relatives, and cultivars; therefore, sources of genetic variation are available for breeding purposes. The traditional breeding has been directed to improve yield and agronomical traits, such as abiotic and biotic stress resistance, lodging resistance, growth habit, together with a few quality-related traits, namely protein and starch content. During the last years, oats turned out to be a very interesting source of dietary and curative compounds. This newly found interest shifted the breeding paradigm from agronomic to health-related purposes. New breeding programs are aiming to develop “specialized” genotypes with high levels of bioactive compounds, vitamins, dietary fibers, and oils. Keywords

Avena sativa · Oats · Beta-glucans · Avenanthramides · Breeding for HR molecules

1

Introduction

Oat is a cereal grain from the Poaceae grass family that originated in the Mediterranean area, also named “brome” and “wild wheat” (Tang et al. 2022). It is an important multipurpose cereal, cultivated for grain, food, feed, fodder, and straw, alone, in mixture, or as a dual-purpose crop. Oats are primarily used as livestock feed that accounts for more than 70% of the total world’s usage. Recently, an increased interest in oats arose due to the unique properties of the grain and the nonfoodrelated applications. In parallel, an increased oat consumption as food has been vastly observed, reaching, in some countries (e.g., the United Kingdom), up to 70% of total oat grain usage. Several products containing oats became of daily use such as breakfast cereals (oatmeal and biscuits), beverages (oat raw or fermented milk), bread, and infant foods.

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This cereal plays a key role both in production and sustainable agricultural systems due to its importance in crop rotation and its economic benefits compared to barley production. It is, in fact, a low-input cereal growing relatively well on marginal land or in unsuitable conditions for wheat, barley, or maize production. Oats are mostly cultivated between 35
and 60
latitude, which correspond to cool and moist climate. Spring-sown oats are the most cultivated in cold environments, while autumn-sown oats (winter oats) are grown mostly in mild climates, such as the United Kingdom, Southern Europe, and the Mediterranean areas. Winter oats have high yields, deep roots, long growth cycle, and early maturity; on the other hand, they lack winter hardiness, making them unfit to be cultivated in very cold areas. In addition, in southern areas, winter sowing allows oats to partially avoid harsh late summer temperatures, even though drought and diseases are still the major causes of yield instability. In spite of this, thanks to new, high-yielding and stressresistant cultivars, it is gaining popularity also in southern subtropical regions (Sánchez-Martín et al. 2014). Oat ranks sixth in world cereal production statistics, following wheat, maize, rice, barley, and sorghum (Ahmad et al. 2020).The numbers of total world production in the last years are the following: cultivation area of 9.5 million hectares, yield of 2.4 metric tons per hectare, and production of 23.5 million metric tons. The global oats market amounted to 4.90 billion dollars in 2018 and is estimated to grow by 5.5% over the next 5 years (Kouřimská et al. 2021). During the marketing year 2020/21, approximately 4.72 million metric tons of oats have been yielded in Russia, the world’s leading producer, followed by Canada, Spain, Australia, Poland, and China (Fig. 1). Despite the yield increase of the last 50 years, obtained through new varieties and agronomic practices improvement, the share of minor cereals, that is, oats, rye, and triticale, decreased worldwide. For instance, the total cereal area in Europe downsized from 30% to 18% between 1961 and 2010 (http://faostat.fao.org/), while that of

Fig. 1 Leading oats producer countries (Meenu et al. 2021)

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the major cereals increased. This proliferation of maize and wheat monocultures means a greater dependence on these crops and consequently higher social and economic vulnerability to risks of soil-borne disease buildup and weed problems. Crop diversification is, therefore, supported, and oats, as low-input crops with higher nutritive efficiency and lower pesticide requirements, are highly appropriate for sustainable cropping systems and of great relevance to agricultural policies development. On the other hand, oats yield is stagnant since the 1980s; therefore, improved oat lines with higher yield and of better quality are urgently required to ensure competitiveness in modern agriculture.

2

Nutritional Composition of Oat

Oat contains valuable and unique macro-, micro-, and phytonutrients. The grains are rich in soluble fibers (mainly β-glucan), polyphenols, galactolipids, and are relatively high in protein content (15–20%) (Kumar et al. 2021), which is quite different when compared with that of other main cereals. It is mainly composed of globulins, prolamins, albumins, and glutelins, which have a superior amino acid profile rich in lysine and threonine. For this reason, oats-based products could be considered ideal plant-derived protein sources for both animals and humans. In addition, oat is an important source of phenolic acids being the only cereal that contains avenanthramides, a group of phenolic alkaloids with beneficial effects on cardiovascular diseases and colon cancer prevention (Dimberg et al., 1993; Soycan et al. 2019). The presence of polyphenols combined with other antioxidant compounds is reported to exert beneficial effects on the human health (Ryan et al. 2011). Oat carbohydrates content is 99% polysaccharides plus a low fermentable fraction of mono- and oligosaccharides (Bouchard et al. 2022). Starch and fiber (soluble and nonsoluble) are the principal polysaccharides found in oats. Regarding the on-starchy fraction, β-glucan is the most promising water-soluble dietary fiber. Moreover, oat bran is an excellent source of B complex vitamins (B1, B2, B3, and B6) and tocopherol (vitamin E). The lipidic amount of whole-grain oats is doubled compared with other cereals and mainly consists of unsaturated fatty acids (65%) such as linoleic, oleic, and linolenic acids. In the light of the above information, we can assume that the peculiar oat grains composition (Table 1), a bran rich in minerals, vitamins, antioxidant, soluble dietary fibers, and an endosperm and aleurone layer rich in proteins, are eligible features to consider oat among the healthiest cereals. To give a general overview: • Oats are a good source of proteins, with favorable amino acid contents, high in starch, fats, and vitamins, making them of high nutritional value. Oats have in fact the highest oils (6–12%) and protein (12–20%) contents in de-hulled grains among cereals. • Oats are rich in beta-glucans: The presence of these polysaccharides resulted in the approval of a health-related claim from the EFSA and the FDA given their

49.6–443 mg/ kg 180–576 mg/ 100 g

Saponin

35–68.2 mg/ 100 g

0.5–71.85 mg/ 100 g 6.25–7.5 g/ 100 g

15–20%

Phytosterols

Avenanthramides

Protein

Amino acid

Fatty acids

n.a.

Flavonoids

Phenolics

Total content 10–15.4 g/ 100 g

Nutrients Fiber

Unsaturated (65%): linoleic acid, oleic acid, linolenic acids Saturated: myristic acid, palmitic acid, stearic acids Globulins (50–80%), prolamins (avenins 4–15%), albumins (1–12%), glutelins (10%) Lysine (675 mg /100 g), threonine

AVA 2p, AVA 2f, AVA 2c (65–70%)

Principal compounds Nonsoluble: lignins, cellulose, hemicellulose Soluble: β-glucan (1.73–5.7 g/100 g) Avenacins, avenacosides A (37.7–60.6%) and B (13.8–55.2%) Alkaloid A/p-coumaric acid, alkaloid B/caffeic acids, alkaloid C/ferulic acid (max 149.36 mg/ 100 g) lignans Quercetin (max 8.9 mg/100 g in husked oats) Rutin (max 0.47 mg/100 g) β-Sitosterol (59.1–64.9%), campesterol (7.6–9.1%) Anti-inflammatory, antioxidant, anticancer, preventive and therapeutic for hypertension and coronary heart disease Antiproliferative, anti-inflammatory, antioxidant, antiatherogenic Cardiovascular protection, antiperoxidation of fat

Antioxidant, lowering cholesterol, affecting immune systems

Properties Antidiabetic, antibacterial, cardiovascular protection

Table 1 Main oat grain nutrients, their variation ranges, and properties, as inferred from recent literature

Tang et al. (2022) (continued)

Boukid (2021), Kumar et al. (2021)

Raguindin et al. (2021), Soycan et al. (2019), Liu and Wise (2021) Chen et al. (2021), Bouchard et al. (2022), Kim et al. (2021a, b)

Raguindin et al. (2021)

Raguindin et al. (2021)

References Raguindin et al. (2021), Zhang et al. (2021), Chen et al. (2021), Bouchard et al. (2022) Shi et al. (2004), Yang et al. (2016), Raguindin et al. (2021) Zhang et al. (2021), Raguindin et al. (2021), Soycan et al. (2019)

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Element and minerals in trace

Nutrients Vitamins

Total content

Table 1 (continued)

Principal compounds B1/thiamine (0.73 mg/100 g), B2/riboflavin (0.13 mg/100 g), B3/niacin (0.88 mg/100 g), B6 (0.1–0.22 mg/100 g), E/α-tocopherol (0.45–1.2 mg/100 g) Calcium (45–58 mg /100 g), phosphorus (325–734 mg/100 g), iron (3.5–5.41 mg /100 g), zinc (3.11–3.64 mg/100 g), manganese (3.63–5.63 mg/100 g), chromium

Properties Antioxidant

Chen et al. (2021)

References Chen et al. (2021), Bouchard et al. (2022)

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cholesterol-lowering effects. Several other claims, specific to oats and related to reducing the impact of chronic diseases (such as type 2 diabetes, obesity, hypertension, immune-related diseases), are under development. Moreover, oats display higher percentages of soluble beta-glucans in comparison with barley and contain other dietary fibers, notably arabinoxylans. • Recent investigations on health implications demonstrated that oats’ nutritional benefits to human diets go well beyond those currently recognized. Key molecules in this research include polar lipids, antioxidants, and minor bioactive compounds such as avenanthramides. Because of the grain composition, an increase in oats use for human nutrition has been observed, especially in Europe and North America. The expanding knowledge of the grain composition and its potential end uses are leading to the proliferation of oat-derived products. Table 1 reports the main oat grain nutrients and their ranges of variation depending on cultivation environment, genotypes, and their interaction.

3

Growing Importance in Chronic Diseases and Malnutrition Prevention

Increasing evidence suggests that dietary improvements are important strategies to prevent chronic diseases. Oats possess a variety of health benefits and pharmacological properties. They, potentially, exert antioxidant, anti-inflammatory, antidiabetic, and anticholesterolemic effects. These features could be exploited in functional ingredients production and innovation of traditional foods. Oat product intake is associated with a reduction in serum cholesterol levels, hence modulation of cardiovascular disease risk (Joyce et al. 2019; Sun et al. 2019). Flavonoids, from whole-grain oat, improve serum lipid profile and decrease lipid deposition contrasting hyperlipidemia (Ren et al. 2021). Studies demonstrated that oat consumption can significantly reduce insulin response, fasting blood glucose levels, and postprandial hyperglycemia incidence. Beta-glucans’ health benefits have been clearly demonstrated. Epidemiological investigations constantly denoted that diets rich in whole-grain products and fibers are associated with a decreased risk of chronic disorders such as type II diabetes, cardiovascular diseases, and cancer. Furthermore, oats contain plenty of primary and secondary metabolites, ranging from proteins (glutamine in particular) to microelements (copper, iron, selenium, zinc) and polyphenols. These components, together with beta-glucans, exert an immunomodulating role, that is, are able to stimulate the innate and adaptive immune system’s response and can inhibit the growth of various bacteria, viruses, fungi, and parasites. Moreover, oats wield a positive effect on gut’s microbiota and related metabolites (Chen et al. 2021) thanks to their dietary structure, resulting in amelioration of chronic problems and improved quality of life. Oat increases Bifidobacteria and Lactobacillus growth, which exert an antitumoral effect due to short-chain fatty

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acids formation, such as butyrate, an important metabolite for intestinal microbial fermentation of carbohydrates (Ren et al. 2021). Oats consumption can regulate intestinal transit times and increase butyrate production and/or other fecal short-chain fatty acids synthesized by the gut microflora. Patients suffering from inflammatory bowel disease, ulcerative colitis, colorectal adenoma, or cancer can, therefore, benefit from a regular dietary intake of oats. Of great interest are the different oil fractions and components, for example, polar lipids. Such polar lipids can be used to produce liposomes, which have been demonstrated useful to increase satiety and improve intestinal health (Härröd and Larsson 2011). The studies of Ohlsson et al. (2014) and Hossain et al. (2021) showed that polar lipids regulate hormones involved in human appetite. In the frame of Scan Oats consortium (www.scanoats.se), the combined consumption of lipids and β-glucans has been studied, finding that these two classes of molecules can lower the glucose response, but no synergistic effects have been demonstrated (Cloetends 2022). Thanks to their fibers and lipids content, oats effectively reduce obesity and are efficient indexes of serum lipid levels and liver function. Oats and oat products-positive effects are attributed to their fiber amount (especially β-glucan), but also to protein content, balanced amino acids profile, and bioactive substances such as starch, polyphenols, saponins, avenanthramides, and flavonoids. Ingredients derived from oat protein isolates and concentrates could be an added value in foodstuff, especially if considered in combination with the unique functional properties of this cereal (Kumar et al. 2021). Oats are rich in selenium, involved in DNA repair, and associated with a reduced risk for cancer, especially colon cancer. Several European countries, the United States, and Canada currently permit oats to be included as an ingredient in gluten-free diets, provided that the gluten contamination is below 20 ppm. Very recently, the proposal to remove oats as priority allergen in Codex Alimentarius has been submitted to FAO/WHO (Tye-Din 2022). Multiple studies reported in fact that oats’ prolamin storage proteins or “avenins” do not contain any of the known coeliac disease epitopes from gluten of wheat, barley, and rye (Gilissen et al. 2016; Smulders et al. 2018). Others found that oats have a very low or null immunogenicity, depending on the different cultivar (Comino et al. 2015; Kosová et al. 2020). Recent genomic studies suggested that A. sativa has low copy number of genes encoding celiac disease epitopes, low occurrence of highly immunogenic proteins, and low proportion of avenins within total oat proteins (Tye-Din 2022; Kamal et al. 2022). Long-term studies confirmed the safety of oats for celiac disease patients and the positive health effects of oat products in a glutenfree diet. Controlled avenin feeding studies concluded that protracted oat ingestion should not be harmful, even if a small sensitive subset of patients are likely to exist (Tye-Din 2022). Inclusion of oats in a gluten-free diet might be valuable due to their nutritional and health benefits, provided that no contamination from other small grain cereals can be guaranteed in the supply chain (Comino et al. 2015). Wheat, barley, or rye contamination is in fact a major problem in oats’ conventional production chains.

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Oat is different from other cereal grains as the whole de-hulled kernel is used. Many food products are available, for example, porridge or oatmeal, hot cereals, bread, biscuits, infant food, muesli, or granola bars and dairy substitutes, such as oat milk, yogurt, and ice cream. The technological processes applied to the production of different oat-based food can impact nutritional properties. For example, the three thermal treatments coupled to a starvation step used for the preparation of traditionally oat-based Chinese food impact the β-glucan and protein MW and on GI (Hu 2022). Starting from the numerous positive effects on human health, the consumption of oats and derived products can be encouraged. The diffusion of these products should be based on informative campaigns toward consumers, backed by robust scientific results. This will provide new markets for higher added value products and higher profitability in the oat-related agrofood sector.

4

Health-Related Molecules Unique to Oat

Oats gained a great deal of interest as a healthy and highly nutritive food, rich in secondary metabolites of great functional value. Two classes of HR compounds’ characteristics of oats are beta-glucans and avenanthramides (AVNs). β-Glucans have hypocholesterolemic, hypoglycemic, antitumor, immunomodulatory, antioxidant, and anti-inflammatory activities (Kim et al. 2021a, b). AVNs have strong and widely demonstrated anti-inflammatory activities. Tranilast, a commercially available antiallergic drug similar to AVN, has been demonstrated to potentially prevent exacerbation of COVID-19 by affecting different pathways such as NLRP3 inflammasome, signaling pathways, cytokines and chemokines, and cell adhesion molecules (Saeedi-Boroujeni et al. 2021).

4.1

β-D-Glucans

(1 ! 3), (1 ! 4) β-D-glucans (Fig. 2) are nonstarchy polysaccharides found in aleurone, subaleurone, and starchy endosperm cell walls. They represent the major component of the soluble fiber in oats. They are composed of glucose monomers in long linear glucose polymers, linked by β (1 ! 4) (70%) and β (1 ! 3) (30%) glycosidic bonds (Bouchard et al. 2022). The difference between soluble and insoluble β-D-glucans is based on the ratio of the two bonds. In fact, the presence of β (1 ! 3) gives greater flexibility to the molecule; consequently, more solubility and viscosity. Bonds formation is influenced by genotype and growing environment (Redaelli et al. 2013). Moreover, about 90% of glucose units are organized in trimers and tetramers joined by β (1 ! 3) bonds; their ratio influences structural variability and consequently the differences in some physical properties. The ratio between cellotriose and cellotetraose is characteristic of every different cereal with a smaller value for oats (1.9–2.4), a higher percentage of cellotetraose makes the molecule less soluble (Bouchard et al. 2022; Bai et al. 2019; Wang and Ellis 2014). Higher molecular

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Fig. 2 Chemical structure of (1 ! 3), (1 ! 4) β-D-glucans

weight and lower cellotriose/cellotetraose ratio β-glucans tend to have higher viscosities than those with lower molecular weight and higher cellotriose/cellotetraose ratio (Bouchard et al. 2022). The biosynthesis of (1 ! 3), (1 ! 4) β-D-glucans depends on an enzymatic complex consisting of a cellulose-synthase-like enzyme (Csl gene), which leads to the formation of cellobiose, units of cellodextrin, and a glycosyl-transferase enzyme, which adds another glycosyl residue to form cellotriose and higher odd-numbered chains units (Izydorczyk and Dexter 2008). CslF6 is the major gene responsible for the biosynthesis of (1,3; 1,4) -β-d-glucans. It is highly expressed in different tissues, especially in the developing endosperm, and produced in the Golgi apparatus, then is channeled through the secretory pathway to the plasma membrane. Changes in the CslF6 gene, of even a single amino acid, can alter the fine structure of the (1,3;1,4)-β-D-glucans (Chang et al. 2021). Oat is rich in both soluble, particularly β-glucan, and insoluble fiber, particularly cellulose, lignin, and hemicellulose. A diet high in fiber is known to be beneficial in the prevention of many diseases.

4.1.1 Reduction of Cholesterol and Postprandial Glucose in the Blood Soluble β-glucan can increase the viscosity of the food bolus by delaying stomach emptying, improving intestinal filling, and slower absorption of nutrients. More voluminous stools accelerate intestinal motility by reducing the time of exposure of the intestinal wall to irritants and carcinogens present (Singh et al. 2013). The increase in gastrointestinal viscosity also causes cholesterol and bile acids to be trapped, reducing their absorption; consequently, the bile acids necessary for digestion must be synthesized from cholesterol by reducing their concentration. β-Glucans have been shown capable of reducing the total and LDL-cholesterol level, in the blood of normo- or hypercholesterolemic subjects, reducing the risk of heart disease. The physiological response depends on solubility, concentration, molar mass of β-glucan, and molecular weight, all contributing to increase viscosity (Singh et al. 2013; Zhang et al. 2021).

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β-Glucan solutions’ high viscosity is able to reduce postprandial glucose by interfering with the transfer of released glucose to enterocytes. Another pathway is oat β-glucans consumption by the intestinal microbiota in the colon; hence, they are not digested in the upper gastric tract. Fermentation produces short-chain fatty acids, such as propionic, butyric, and acetic acid, which can regulate the expression of insulin-sensitive glucose transporter type 4 (GLUT-4) imputed to maintaining glucose concentration gradient across cell membranes and allowing the transport of glucose (Zhang et al. 2021). The reduction of postprandial glucose and therefore of inflammation caused by glucose is consequently reducing the general inflammatory state (Chen et al. 2021). The hypoglycemic function of β-glucans is influenced by its molecular weight, a higher value is associated with a greater decrease in fasting blood glucose levels and better control of blood glucose levels after meals. β-Glucan can lower the glycemic index (GI) of foods by delaying digestion and absorption of starch as a result of amylase activity reduction, thus obtaining a hypoglycemic effect, and the GI value is decreased with increasing molecular weight and viscosity of β-glucan (Tang et al. 2022). Scientific evidence about these beneficial effects of oats and its β-glucans led to the authorization of specific health claims that can be reported on labels of foodstuff constituted of oats and barley in order to clearly communicate benefits and limitations associated with consumption to the consumer. The European Food Safety Authority (EFSA) authorized the claim that β-glucan contributes to the maintenance of normal cholesterol levels in the blood and the beneficial effect is obtained with a daily intake of 3 g of beta-glucans from oat or oat bran, barley, or barley bran or mixtures of these (EFSA 2009; Commission Regulation EU 2012). In a subsequent opinion, EFSA established that a reduction in cholesterol can diminish the risk of (coronary) heart disease and the amount of β-glucan to be taken throughout the day must be part of a balanced diet (EFSA 2010). The use of the claim has also been approved by the Food and Drug Administration (FDA) in the United States, indicating that soluble fiber, 3 g or more per day of β-glucan from either whole oats or barley, or a combination of whole oats and barley, can reduce the risk of coronary heart disease through the intermediate link of blood cholesterol or total LDL cholesterol in the blood (Code of Federal Regulations, 21CFR101.81), recognized also by Health Canada and Food Standards Australia New Zealand. Another claim approved by EFSA and based on scientific evidence is that the consumption of β-glucan from oats or barley as part of a meal contributes to the reduction of high blood glucose after a meal. The claim can be used only for food containing at least 4 g of β-glucan from oats or barley for every 30 g of carbohydrates available in a quantified portion as part of the meal (EFSA 2011).

4.1.2

Effect on the Immune System, Cancer Prevention, and Antimicrobial Activity Oats β-glucans improve immunity and anticancer activity, and moreover, can kill the malignant cancer cells, sarcoma cells, and melanocytes. The inhibition exerted on

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different types of intestinal, liver, and breast carcinomas is similar to anticancer drugs but without any side effects (Tang et al. 2022). β-Glucans have an immunostimulant effect altering the microflora of the colon with the production of short-chain fatty acids (Singh et al. 2013). The fermentation of soluble fiber with the production of short-chain fatty acids, in particular butyric acid, favors the development and colonization of probiotics. Shortchain fatty acids improve cell proliferation of the colon mucosa, reducing the risk of cancer (Singh et al. 2013). Short-chain fatty acids (SCFA), bacterial metabolites of dietary fibers, stimulate the production of mucus and antimicrobial peptides, increase the expression of tight junction proteins, and modulate immune system (Chen et al. 2021). Multiprotein junctional complex plays a key role in osmose balance maintenance and transcellular transport of specific molecules. Fermentable fibers can reduce the amount of mucin used during fermentation; mucin acts as a barrier against pathogenic microorganisms, and fiber contributes to intestinal microbiota maintenance by reducing the chance of opportunistic pathogens to prevail (Chen et al. 2021). β-Glucan concentration has a positively proportional antibacterial effect. Low molecular weight β-glucan entering microbial cells would cause their lysis and death (Tang et al. 2022).

4.1.3 Blood Pressure Reduction β-Glucans can reduce blood pressure, likely due to their viscosity. Insulin resistance, an important indicator of hypertension, has been linked to β-glucans viscosity. The intake of viscous fibers influences renal sodium absorption and transmembrane ion transport, causing a reduction in blood pressure (Bai et al. 2019). 4.1.4 Antioxidant and Anti-inflammatory Activity Low molecular weight β-glucans transfer hydrogen from molecules that can act as free radical quenchers under physiological conditions (Bai et al. 2019). They have free radical “scavenger” activity and the ability to relieve inflammatory conditions.

4.2

Avenanthramides

Oats are rich in phenolic compounds that are interesting for their high antioxidant capacity and the potential health benefits (Boz 2015). Phenolic compounds consist of aromatic rings with one or more hydroxyl groups (Bouchard et al. 2022). Oats contain mainly simple phenols such as phenolic acids, flavonoids, and avenanthramides compounds (Tang et al. 2022). Avenanthramides were originally identified as phytoalexins produced by the plant when exposed to pathogens (Perrelli et al. 2018). The avenanthramides (AVAs) are a group of phenolic alkaloids typical of oats (Fig. 3); they are low molecular weight-soluble phenolic compounds (Boz 2015)

Oats: Nutritional Uniqueness and Breeding of a Healthy Superfood OH

OH

165

HO

O

CH3

OH

O

HN

O

HO

O

HN

O

O

HN O

HO

HO OH Avenanthramid 2p

OH Avenanthramid 2c

OH Avenanthramid 2f

Fig. 3 Chemical structure of avenanthramides

consisting of anthranilic acid and hydroanthranilic acid linked to hydroxycinnamic acids by amide bonds (Singh et al. 2013). Oats contain approximately 40 different types of AVAs, the predominant are esters of 5-hydroxyanthranilic acid with p-coumaric (AVA-A or 2p), ferulic (AVA-B or 2f), and caffeic (AVA-C or 2c) (Boz 2015). Among cereals, only oats contain AVAs; they can be found in almost all fractions of the kernel but particularly in bran (Bouchard et al. 2022) and aleurone layers (Tang et al. 2022). While the mechanisms of biosynthesis of the main avenanthramides in oats AVA-A, AVA-B, and AVA-C are not yet fully understood, studies identified three different types of genes that encode 4-coumarate-CoA ligase (4CL), hydroxycinnamoyl-CoA, hydroxyanthranilate N-hydroxycinnamoyl transferase (HHT), and caffeoyl-CoA O-methyltransferase (CCoAOMT) enzymes, all involved in the biosynthesis process of avenanthramides. 4CL oats appear to convert p-coumaric, caffeic, and ferulic acids in their CoA thioesters, while oats’ HHT are responsible for biosynthesis of AVA-A and AVA-C by the condensation process of hydroxyanthranilic acid, acyl acceptor, with pcumaroyl-CoA and caffeoyl-CoA, acyl donor. AVA-B is synthesized by methylation of the hydroxyl group at position 3 of the aroyl group in AVA-C by the CCoAOMT enzyme (Li et al. 2019).

4.2.1 Antioxidant, Anti-inflammatory, and Antiatherogenic Activity Avenanthramides showed antioxidant potential significantly higher than other simple phenols. Antioxidants protect cells from the oxidative damage and help prevent several chronic diseases caused by reactive oxygen species (ROS) generation. Antioxidant activity was found to be in AVA-C> AVA-B> AVA-A. AVAs inhibit calcium-induced low-density lipoprotein (LDL) oxidation in a dose-dependent manner and are shown to act synergistically with vitamin C and other antioxidant compounds. During physical activity, taking avenanthramides decreases ROS

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production and related lipid peroxidation. The antioxidant potential of AVAs could be related to an effect on antioxidant enzymes, such as superoxide dismutase (SOD) and glutathione (GSH) peroxidase (Tripathi et al. 2018). AVAs are bioavailable, and their antioxidant effect on LDL reduces the risk of cardiovascular diseases (Singh et al. 2013). AVAs also inhibit inflammatory processes that play a significant role in many diseases. AVAs’ anti-inflammatory activity was detected in endothelial human aortic cells with an evident reduction of various types of molecules involved in the attachment of monocytes (blood immune cells) to the arterial walls, responsible for inflammation and stiffening, first step in the development of atherosclerosis (Singh et al. 2013). AVAs reduce production of pro-inflammatory cytokines (interleukin IL-6, IL-8, and monocyte chemoattractant protein (MCP-1)) that carry the immune cells at the stimulation site and inhibit vascular endothelial cell expression of adhesion molecules, including ICAM-1 (intracellular adhesion molecule-1), VCAM-1 (vascular adhesion molecule-1), and E-selectin (Tripathi et al. 2018; Singh et al. 2013). Colloidal oat flour has been found to be effective as an anti-inflammatory and anti-itch in dermatitis treatment, with avenanthramides responsible for these beneficial effects. The anti-inflammatory effects of AVAs have been demonstrated in human keratinocytes. AVAs reduce the IL-8 production, and the anti-inflammatory action occurs through the NF-κB pathway. NF-κB is one of the very crucial regulatory transcription factors (Tripathi et al. 2018).

4.2.2

Antiproliferative Activity and Postprandial Glycemic Response Control AVAs, including AVA-C and its methylated derivative, can inhibit the proliferation of colon, breast, and smooth muscle vascular cancer cells. They cause cell cycle blockage in the G1 phase by upregulating the p53-p21cip1 pathway and inhibiting the retinoblastoma protein (pRB) phosphorylation with the possible activation of an apoptosis process (Perrelli et al. 2018). Glucose uptake can be mediated in humans by intestinal solute carriers SGLT1 and GLUT2. In a proof-of-concept study, Joseph (2022) showed that AVAs can inhibit glucose uptake in a dose-dependent manner in CaCo2 cell system.

5

Genetic Resources of Health-Related (HR) Genes

The genus Avena includes up to 30 recognized species, with different ploidy levels that includes diploids (2n ¼ 14), tetraploids (2n ¼ 28), and hexaploids (2n ¼ 42). As reviewed by Loskutov (2005, 2008), the genus comprises the two sections of Aristulatae and Avenae, including both wild and cultivated species (Table 2). Among cultivated, A. strigosa is a diploid with 2n ¼ 14 (genome As), whereas A. abissinica is a tetraploid that carries the two A and B genomes (2n ¼ 24).The most cultivated A. sativa and marginally cultivated A. abyssinica are hexaploids with 42 chromosomes, presenting three different sets of nuclear genomes A, C, and D.

Oats: Nutritional Uniqueness and Breeding of a Healthy Superfood Table 2 Main oat species according to Loskutov (2005)

Section Aristulatae

Avenae

Wild species A. claudia A. prostrata A. damascena A. longiglumis A. wiestii A. hirtula A. barbata A. vaviloviana A. fatua A. occidentalis A. ventricosa A. bruhnsualis A. canariensis A. magna A. murphyi A. canariensis A. insularis A. sterilis A. ludoviciana

167 Cultivated species A. strigosa A. abyssinica

A. byzantina A. sativa

Three gene pools can be recognized inside the genus, classified as primary, secondary, and tertiary depending on the interfertility with cultivated hexaploid oat, as reviewed by Ociepa (2019). The primary gene pool (GP-1) collects accessions, including landraces, breeding lines, modern and obsolete cultivars, belonging to the same species as the cultivated oat. The secondary gene pool (GP-2) includes species that are still crossable with cultivated oats, even if a limited number of fertile hybrids are produced. The tertiary gene pool (GP-3) includes relatives that are so distant that the crossing would require very specialized techniques such as embryo rescue, bridge crosses, and induced polyploidy. The primary gene pool is wide and collects wild and cultivated hexaploid species, interfertile and without any recombination restrictions. New genes from wild species have been introduced in cultivated forms mainly to improve agronomic traits. A. sterilis has been an interesting donor of resistance genes against fungal diseases such as powdery mildew, crown rust, and stem rust. A. sterilis contributes even to the improvement of winter hardiness, grain yield, drought tolerance, and green mass. This same species, A. sterilis, is a potential donor of desirable quality-related traits, such as large grains, high protein content, balanced amino acid composition, and high oil and beta-glucan contents. A. fatua has also been included in oat-breeding programs as genes donor for reduced plant height, abiotic stress resistance, stem and crown rust resistance, smuts, and viroses. A. fatua and A. ludoviciana are useful sources of resistance to crown rust. Aside from agronomic traits, these two species are considered donors of important genes for health-related characters, such as high protein and oil content.

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Exploitation of A. sterilis in breeding programs gave cultivated varieties, for example, Starter (characterized by high-protein content), Ozark (cold resistant), and Jay (resistant to crown rust). The secondary gene pool includes the tetraploids A. murphyi, A. maroccana, and A. insularis. The crosses between A. sativa and these species give partially fertile hybrids, whose fertility level can be increased by backcrossing. A. murphyi could be a potential source of resistance to powdery mildew and crown rust, but also donor of high protein content and high groat oil content. A. magna can contribute to both quality-related traits (grain size, high contents of protein, lysine, and oil) and biotic stress resistance (powdery mildew and crown rust). Crosses with A. maroccana resulted in varieties such as Amagalon, resistant to crown rust, and CDC Bell for green feed or oat hay production. In the tertiary gene pool are included all diploid and tetraploids species. Resistance to crown and stem rust, Septoria, powdery mildew, together with high oleic acid and fiber contents, are interesting features of several diploid and tetraploid wild species. However, cross-incompatibility complicates the gene transfer from diploids and tetraploids to hexaploids. This problem can be mitigated using backcrosses, mutants, and genetic intermediates. The varieties Hinoat, Gemini, and Foothill, all resistant to crown rust, have been obtained by crossing A. sativa with the diploid, marginally cultivated, A. strigosa. Considerable genetic resources exist with large collections of landraces, wild relatives, and cultivars. According to De Carvalho et al. (2013), currently, 116 major GeneBanks conserve oats’ genetic resources. The major collections of oat landraces are located in Canada (Plant Gene Resources of Canada (PGRC)) at the Saskatoon Research and Development Centre (Saskatoon, Saskatchewan), Russian Federation (Federal Research Center N. I. Vavilov All-Russian Institute of Plant Genetic Resources, VIR), the United States (NSGC), and Germany (Leibniz Institute of Plant Genetics and Crop Plant Research, IPK, Gatersleben). The collections include adapted cultivars, old landraces, marginally cultivated oats such as Avena strigosa, Avena abyssinica, Avena brevis, and Avena nuda, crop wild relatives, and genetic stocks bearing defined traits. Different Gene Bank information systems have been developed (e.g., GRIN-CA/GRIN-Global-CA, GRIN-USA, EURISCO) that allow national and international clients and the public to inspect and access to the GeneBank holdings. Significant sources of genetic variation for oat breeding are therefore mainly available in European and American GeneBanks and breeding programs, coherently with the spreading areas of this crop. Cultivated A. sativa was most likely first domesticated in Europe ca. 2000–3000 BC (Zohary et al. 2012) and then spread from the East to Central– North Europe in the late Bronze Age. In the western part of the Mediterranean region originated A. byzantine, the main cultivated form in North Africa and Spain. In the sixteenth century, the two A. sativa and A. byzantina species were introduced to North America. A. sativa, more suited to spring sowing, was mainly spread in the northern regions, whereas A. byzantina was used for autumn sowing in the Southern United States. In the twentieth century, new breeding programs

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built on the crosses between the two species and gave many varieties currently cultivated in these environments.

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Oat Breeding for Quality and Health-Related Traits

In the review of Loskutov and Khlestkina (2021), it is clearly reported how the oats’ breeding paradigm has been recently switched from agronomic objectives to healthrelated ones. The traditional breeding has been directed to improve yield and agronomical traits, such as abiotic and biotic stress resistance, lodging resistance, and growth habit, together with a few quality-related traits, namely protein and starch content. During the last years, oats turned out to be a very interesting source of dietary and curative compounds. New breeding programs are aiming to develop “specialized” genotypes with high levels of bioactive compounds, vitamins, dietary fibers, oils, etc. This is in line with the Rome Declaration on Nutrition, in which integrated strategies are indicated to eradicate all forms of malnutrition, that is, not only undernutrition, but even micronutrient deficiencies, and obesity. One of the strategies is optimizing the nutritional value of crop and derived raw materials. Starting from the prominent role of small grain cereals in human nutrition, the importance of new biofortified cereal varieties, improved in essential amino acids, fatty acids, vitamins, minerals, etc., is undeniable (Shelenga et al. 2021). Traditional breeding approach to biofortification involves crosses between genotypes high in target compounds and varieties with superior adaptability and agronomic performances (Fig. 4). This approach requires to find interesting genotypes by

Fig. 4 Scoring oat plants in traditional breeding program

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evaluating the existing variability not only in accessions belonging to primary gene pool, but even in wild relatives. The breeding can then be accelerated combining traditional techniques with marker-assisted selection, next-generation breeding, and improved phenotyping strategies for specialized compound identification and quantification. In traditional breeding programs, the evaluation of phenotypes is classically done in several environments; selection and recombination are based on the resulting data plus pedigree information, when available. Conventional crossbreeding in oats has been, up to now, based on relatively narrow genetic diversity (He and Bjørnstad 2012; Tinker et al. 2009). However, opportunities to significantly enhance genetic gain in crop breeding by combining phenotypic selection with precise molecular breeding approaches are rising. The other pillar is the exploitation of wider germplasm available in GeneBanks: genetic resources belonging to the different gene pools host interesting traits for crop improvement in various farming systems and under changing environmental scenarios. Table 3 summarizes the main targets for oat improvement. The main task of traditional breeding has been the yield increase. However, at the beginning of the twenty-first century the yield increase obtained with the new oat varieties was just over a third of the increases recorded in other small grain cereals (Menon et al. 2016). Moreover, even smaller breeding efforts have been invested in naked oats, despite their potential both from economic and nutritional point of view. There is therefore a large genetic gain margin to improve not only the yield, but also the nutritional characteristics to utilize oat as an ingredient in functional food. The improvement of such polygenic traits can be supported by molecular breeding strategies, such as molecular-assisted selection (MAS) and mutagenesis (TILLING), supported by QTL mapping and genome-wide association studies (GWAS). The identification of superior genotypes can be speeded up using molecular markers linked to the trait of interest, but to unravel the genetic basis of complex traits it is necessary to associate genotypic information with the corresponding phenotypic data. Association strategies are based on three main pillars: the phenotyping, the genotyping strategy, and the genetic population used (IsidroSánchez et al. 2020b). The first linkage-based QTL map was developed by O’Donoughue et al. (1995), using 71 recombinant inbred lines from a cross between Avena byzantina cv. Kanota and A. sativa cv. Ogle and restriction fragment length polymorphisms (RFLP) as molecular marker. Several other maps, at increasing density, have been developed since then. Different mapping populations were developed in combination with several classes of molecular markers such as RAPDs, ISSRs, IRAPs, SCARs, DArTs, and SNPs (Gorash et al. 2017). The first doubled haploid linkage map for cultivated oats was created in 2008 (Tanhuanpää et al. 2008), whereas Oliver et al. (2013) developed and published the first physically anchored hexaploid oat linkage map. Tinker et al. (2014) developed the first SNP genotyping array for hexaploid oat and a linkage map of naked oats was constructed by Song et al. (2015).

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Table 3 Main objectives of oat breeding. Some of the target traits have been already considered by traditional breeding, some others – mainly related to quality – are new ones Objective Competitiveness in cereal farming systems and supply chains

Host plant resistance to pathogens

Adaptation to stressful environments

Grain quality

Input-use efficiency and mitigating climate change Healthy food Livestock feed

Target trait(s) Yield potential and stability Various end user demands: food, feed, other derived products Plant architecture: dwarfing types to avoid lodging Crown rust Fusarium head blight (and minimizing mycotoxins in grains) Oat mosaic virus Powdery mildew Cold tolerance Drought tolerance Deep root systems Competing ability against weeds High kernel content Ease of dehulling Low proportion of screenings High specific weight Minimum grain blackening High protein and high essential amino acids High oil and high essential fatty acids High total and soluble fiber: β-glucan and arabinoxylan High bioactive phytochemicals: phenolics and terpenoids Nitrogen use efficiency Water use efficiency Increased β-glucan content Increased antioxidants High metabolizable energy by increasing oil content Low lignin husk High yield, protein and oil in naked oats (for ruminants) Low trichome density in naked oats (for facilitating harvest and grain handling)

The first linkage maps have been built on bi-parental populations; however, such materials can have some limits in genetic and phenotypic variation. Other kinds of populations, showing wider variation, are under development, including multiparent advanced generation intercross (MAGIC) and nested association mapping (NAM) populations. These kinds of populations can avoid biasing the selection of marker loci toward those that are polymorphic only between specific mapping parents. Moreover, an increased mapping resolution can be reached thanks to the numerous generations of intercrossing of the original parent plants and their ability to capture a wide range of genetic and phenotypic diversity in a breeding population. Such populations form the perfect basis for quantitative trait locus mapping and MAS in multiple genetic backgrounds.

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This strategy has been used to map QTL involved in β-glucan concentration (Newell et al. 2011; Asoro et al. 2013), disease resistance (Gnanesh et al. 2015; Montilla-Bascón et al. 2015), spikelet number (Pellizzaro et al. 2016), heading date (Klos et al. 2016), and frost and lodging tolerance and heading date (Tumino et al. 2016). The marker development in oat evolved from low-throughput to high-throughput markers. An international consortium of oat researchers partnered with Diversity Arrays Technology P/L (Canberra, Australia) to develop a high-throughput DArT marker platform for oat (Tinker et al. 2009). This collaborative effort successfully developed >2700 DArT markers, of which 1295 were unique and polymorphic in a diverse set of global oat germplasm. This work has more than doubled the number of available oats markers and provided the first high-throughput marker platform in oat; it can be applied in parallel and is based on a rapid and cost-effective commercial service. A further evolution was reached with single-nucleotide polymorphisms (SNPs) markers, as they are suitable for automation, easy to exchange among laboratories, and to score. Next-generation sequencing (NGS) approach has been addressed in a collaboration of North American and European oat researchers, resulting in the first SNP oat genotyping platform – an Illumina ® 6K oat chip containing highly informative SNP markers (Tinker et al. 2014) – which is now available to oat breeders and is the first physically anchored integrated map of the complex oat genome (Oliver et al. 2013) for further use in genetic analyses. This work has reversed the declining trends in oat research by infusing the research community with the genetic resources necessary to develop new and innovative cultivars. The SNP array has been used to evaluate the genetic diversity and population structures of American and European germplasm, whose genetic base is different (Tinker et al. 2009), and also for linkage and association mapping, thereby advancing genetic analysis and breeding. A problem in identifying informative SNPs in allohexaploid oat can be the occurrence of homeologs from the A, C, and D genomes. A number of bioinformatics tools have been developed to successfully detect and remove sequences with redundant and ambiguous polymorphism allowing efficient discovery and application of SNP markers in oats (Barker and Edwards 2009; Oliver et al. 2011). Moreover, Tumino et al. (2016) proposed to utilize SNP hybridization intensity ratios as continuous variables to better represent the allele frequencies at accession level (bulk). Using intensity ratios, SNP signals were not interpreted as discrete genotype classes but as continuous. The bulk allele frequencies can be statistically associated with phenotypes measured in bulks in GWAS. The same approach has been adopted by Montilla-Bascòn et al. (2015) in a GWAS for crown rust and powdery mildew. The main reasons supporting this strategy are the reduction of genotyping costs and the lowered risk of useful information loss given that SNP probes in allopolyploid species may or may not be subgenome-specific and therefore the genotype calling can be a challenging, time-consuming, and error-prone task. GWAS exploits natural large genetic resources collections for the identification of genomic regions that are in linkage disequilibrium (LD) with the QTL influencing

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traits of interest. This method takes advantage of ancestral recombination events and can provide higher resolution compared to traditional QTL mapping using biparental populations. Association genetics uses, therefore, large experimental populations with densely mapped genotype data and phenotypic data from multilocational field trials. An example of such populations is the Collaborative Oat Research Enterprise (CORE) panel, which consists of 635 single-panicle-derived lines representative of elite germplasm deemed important by 16 active oat breeding programs in Australia, Canada, the United Kingdom, and the United States. A further example is the AVEQ panel, developed to evaluate oat genetic resources for proteins, oils, minerals, βglucans, antioxidants, and phenolic compounds, as well as for resistance to Fusarium infections and cold tolerance, assembling 600 accessions and cultivars from 25 gene banks and 31 breeding programs from 14 European countries. The analysis is based on the nonindependence of alleles in a population called linkage disequilibrium (LD), defined as the nonrandom association of alleles at two loci. Association between marker alleles and causal alleles arises not from experimental crossing but from historical drift and mutation events. In such studies, associations between genotype and phenotype depend on historical LD broken down by many generations of recombination. For this reason, in GWAS a larger number of markers are required to assure LD between markers and causative alleles throughout the genome, thus enabling finescale mapping. This allows us to map causal loci more accurately than with traditional linkage analysis. The genetic distance over which LD is maintained in a population determines the resolution of mapping that is possible, and the marker density required for association analyses. A key point is the population structure deriving from admixture, mating system, genetic drift, artificial or natural selection during evolution, domestication, and breeding. Population structure can be responsible for false associations between polymorphic markers and phenotypic trait variations. Several statistical approaches are therefore available to describe population structures and genetic relatedness of the lines in the association panel. A lot of studies showed that population structure in oats is weak (Montilla-Bascón et al. 2015; Newell et al. 2012; Tumino et al. 2017; Winkler et al. 2016) in comparison with other cereals (Hamblin et al. 2010) probably due to admixtures and spring and winter types interbred species (Newell et al. 2012). Consequently, numerous GWAS for oats have been successfully concluded (Asoro et al. 2013; Klos et al., 2016; Foresman et al. 2016; Montilla-Bascón et al. 2015; Newell et al. 2012; Tumino et al. 2016, 2017; Winkler et al. 2016). NGS combined with the reduction in genome complexity enables genotyping-bysequencing (GBS) approaches (Bekele et al. 2020). This combines marker discovery and genotyping to produce high-density markers at a relatively low sample cost (Poland and Rife 2012). The development of such tools would enable genomic selection (GS) to be used in oats (Mellers et al. 2020). This has recently been proposed to overcome the limitations of current MAS approaches for complex traits governed by many genes. Instead of analyzing markers individually for their association with a phenotype, GS analyzes all the markers jointly to explain the total genetic variance by summation of all marker effects. These are then used to predict

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the breeding value of individuals. The development of high-density SNP maps and of high-throughput genotyping platforms makes GS a practical proposition for oat breeding (Asoro et al. 2011), as already established in other cereals (Poland and Rife 2012). A very high number of different molecular maps both for hexaploidy and diploid oats have been developed (Blake et al. 2019), and several of these can be found in GrainGenes database (https://wheat.pw.usda.gov/GG3/). The same database hosts reference genomes of hexaploidy oat and of A. insularis, A. longiglumis, A. atlantica, and A. eriantha. Chip-based SNP assays and GBS approaches are ideal genotyping platforms for GWAS and GS, but breeders often require screening large numbers of plants with small numbers of mapped markers associated with key traits of interest. KASPar SNP genotyping answer to this need as it is a flexible and cost-effective system able to discriminate SNPs even in hexaploidy species. KASPar assays can also identify heterozygous individuals, and this can be important in breeding and backcrossing programs, where marker-assisted selection often requires the resolution of heterozygous from homozygous classes. To map populations and germplasm collections, TILLING (targeting-induced local lesions in genomes) populations, obtained with an advanced mutation breeding method, can be employed. This nongenetically modified technology combines the traditional mutagenesis with high-resolution mutation screening and allows to expand the genetic variability and detect point mutations in individual plants (Parry et al. 2009). In oats, TILLING was applied by Chawade et al. (2010) to obtain mutant seed lines that have been used to study key genes in the lignin and βglucan biosynthetic pathways. Vivekanand et al. (2014) studied the lignin-level variability inside this same population and in Belinda variety, from which population was obtained, with the aim to identify more digestible mutants. Finally, González-Barrios et al. (2021) demonstrated how speed breeding and early panicle harvest can accelerate oat breeding cycles. By modulating growth temperatures and photoperiod, a significant acceleration in flowering time has been obtained and acceptable germination levels are present 21 days after flowering. Breeding programs where single-seed descent are used can be therefore greatly accelerated.

6.1

Genetics of FHB Resistance

Mycotoxins are secondary metabolites produced by different types of fungi such as Aspergillus, Penicillium, Alternaria, and Fusarium. These toxins can enter the food chain through contaminated crops used in food and feed production. The mycotoxigenic molds can invade both agricultural crops in the field and agricultural raw materials during storage and processing (Mielniczuk and Skwaryło-Bednarz 2020). Oat contamination by mycotoxin is of great concern for human and animal health (Perrone et al. 2020). Several mycotoxins can be detected in oats, but the ones considered most important are deoxynivalenol (DON, vomitoxin), zearalenone

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(ZON or ZEN), HT-2 toxin (HT2), and T-2 toxin (T2). DON and ZON are produced by several Fusarium species, the dominant being F. graminearum. HT2 and T2 are produced by several other Fusarium species, the dominant being F. langsethiae (Edwards et al. 2012). The Fusarium species invade the plant at flowering stage causing Fusarium Head Blight (FHB). Legislative limits for the mycotoxins DON and ZON for unprocessed cereals, intermediate products (e.g., flour), and finished products for human consumption have been fixed in several countries. Screening for sources of resistance to FHB is of key importance for the development of new oat cultivars. However, resistance to FHB is a quantitative trait (He et al. 2013; Bjørnstad et al. 2017), controlled by genes that are still largely unknown. Resistance can be divided into several different components, as reviewed by Hautsalo et al. (2018), resistance against initial infection and spreading of infection (respectively known as type I and II), mycotoxin (type III), kernel infection (type IV), and tolerance (type V). In addition, disease escape mechanisms exist, and are based on morphological features, such as plant height, degree of anther extrusion (Tekle et al. 2020), or physiological characteristics (flowering time). Moreover, mycotoxin accumulation is strictly linked to the fungal species, and infection success is strictly linked to agronomic practices and weather conditions (Hautsalo et al. 2020). Oat genetic resources have been screened to identify the potential source of resistance (Bjørnstad et al. 2017; Loskutov et al. 2017; Hautsalo et al. 2020; Gavrilova et al. 2021). Screening procedure itself has been demonstrated to be a nontrivial point to obtain reliable indication about resistance (Tekle et al. 2018). A ranking of oat cultivars with respect to the content of DON can be informative when repeated several years in a specific environment, as reported by Tekle et al. (2018) and Yan et al. (2010). Haikka et al. (2020) evaluated North European germplasms and breeding lines for DON and agronomic traits and compared two strategies, GWAS and genomic prediction, for their potentialities of application. Genomic prediction was identified as a promising method applicable in oat breeding programs for FHB resistance. Of particular concern in oat is the asymptomatic infection caused by Fusarium langsethiae, a pathogen able to produce the highly toxic T-2 and HT-2 mycotoxins. Isidro-Sánchez et al. (2020a) inoculated 190 spring oat varieties with a mixture of three isolates of the pathogen. Varieties were genotyped using 16,863 genotyping by sequencing markers. GWA identified a single QTL in the linkage group Mr06 associated with T-2 + HT-2 mycotoxin accumulation. In the QTL, the locus avgbs_6K_95238.1encodes lipase precursor that is associated with resistance to fungi. Lipid-derived secondary metabolites produced by the plants are known to play a crucial role in host–pathogen communication. The authors concluded that Mr06 linkage group plays an important role in F. langsethiae resistance. Willforss et al. (2020) carried out the first proteogenomic study to understand the molecular response of oat when exposed to FHB. The proteomes of resistant and susceptible cultivars were compared, and candidate proteins of interest were identified and linked to protein sequence variants.

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Breeding for Grain Size, Milling, and Naked Grains

Some traits are relevant for processing efficacy and determine quality perception in oat raw materials. A lot of characteristics, such as groat to hull ratio, ease of dehulling, uniformity of groat size, uniformity of mature kernels from top to bottom of the panicle, overall groat size in the medium to large range, few trichomes, husk content, test weight, grain size and weight, and milling yield, are not strictly definable nutritionally important characteristics but from an agronomic and industrial point of view are crucial. Grain yield and kernel size, shape, and morphology have been targets of traditional breeding programs (Fig. 5). Such traits can be positively or negatively linked with health-related characteristics. Negative correlations have been shown among water binding capacity, ß-glucans, intensity of odor, toasted odor, and flavor (Lapveteläinen et al. 2001). High oil concentration was associated with low groat weight and with long and slim seeds (Peterson and Wood 1997). In A. sterilis, negative correlations have been found between protein vs. groat size and oil (Rezai and Frey 1988). Selection for high yield and seed weight during oat breeding may have caused a loss of valuable characters health-wise and taste-wise (Lapveteläinen et al. 2001); all the traits can be made available from less developed materials.

Fig. 5 Oat seed biodiversity

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Recently, 57 QTLs, influencing one or more of 6 key milling traits, were identified by Klos et al. (2021) in a genome-wide association study involving 501 accessions from the Collaborative Oat Research Enterprise (CORE) panel. The Qkernel QTL was identified as the prominent one, influencing several milling traits. The comparison of QTLs associated with kernel morphology, grain yield, test weight, and chemical groat composition, with those affecting quality-related traits can be important for MAS (Groh et al. 2001). In breeding programs where selection is based on markers linked to specific QTLs, the potential negative associations among characteristics can be a serious limit, suggesting that it is important to have a deeper knowledge of the epistatic impact of specific QTLs. Naked oats are very interesting materials in the frame of human nutrition; however, few naked cultivars have been developed in comparison to covered types. For example, the naked oats varieties registered in European catalog are one-tenth compared to covered oats. The modern naked varieties are not fully naked but have a percentage of covered kernels, depending on the environment and on the genotype. The genetics of hulless character is in fact complex. N-1 locus has been identified as the major gene controlling naked trait in oats (Ubert et al. 2017); however, it is incompletely dominant, and the phenotype is the result of the interaction among N-1 gene with modifying genes N-2, N-3, and N-4. Different level of nakedness is observed depending on the alleles present at each of the four loci. Even the environment can influence this character. The naked character is in fact under genetic control but can be influenced by temperature and humidity. The yield of naked oats has been traditionally considered lower in comparison to covered varieties. Several explanations have been proposed, for example, the flower morphology (Valentine 1995; Burrows et al. 2001). A high number of varieties was taken into account in the study of Buerstmayr et al. (2007), demonstrating that the yield of covered lines was significantly higher than that of naked lines. Other studies deny the association between naked seeds and lower productivity. Peltonen-Sainio (1997) studied three naked and two covered lines at varying nitrogen fertilization and seeding rates in Finland and found that, under northern growing conditions, groat yield of naked oats was already similar to that of covered oats. Burrows et al. (2001) compared near-isogenic naked and covered lines and showed there was no significant difference in groat yield between the covered and naked isolines. Doehlert et al. (2001) found that the naked oat cultivar Paul produced more than covered oat cultivars over 12 environments during 3 years in the United States. Similar results were obtained by Moudrý et al. (2004), whereas Maunsell et al. (2004) found no significant difference between covered and naked lines for groat production during 2001–2002 in the United Kingdom. To summarize, naked oats have some disadvantages, such as the lower grain yield and the reduced level of germination, that have limited the use of these cultivars, but have unique end-use advantages, suggesting that specific breeding programs are a crucial step to identify the suitable naked oat genotypes to produce foods of high nutritional value (Redaelli et al. 2015).

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Breeding for β-Glucans

The AVEQ project (Avena Genetic Resources for Quality in Human Nutrition) confirmed the existence of variability for beta-glucan content in a panel of European oats varieties and wild relatives (Redaelli et al. 2013). Although there is genetic variability for β-glucan content and the interest from a nutritional point for this trait, the development of varieties with improved content of β-glucans has been, until now, very slow. Three main reasons slowed down the breeding for this trait: (i) the limits in phenotyping for β-glucan content; (ii) the poorly understood genetics of this complex trait; and (iii) the influence of environment. From a genetic point of view, the β-glucan content is controlled by many loci with additive effects and is also influenced by the environment. The broad sense heritability of this trait has been found ranging from 0.27 to 0.58 (Holthaus et al. 1996; Humphreys and Mather 1996; Kibite and Edney, 1998). β-Glucan content is therefore influenced by the environment, but the genotype has a major impact on the expression of this trait (Dvončová et al., 2010). Moreover, genotype–environment interactions have been evaluated, obtaining contrasting indications. The selection for beta-glucan content is expensive: the most common method for their determination is enzymatic, based on the specific enzymatic degradation of the carbohydrate followed by quantification of the products. In addition, other chemical and physical approaches have been developed, together with fast method of screening, mainly based on NIR. Because of the complex genetics and the expensive phenotyping, this trait is an ideal candidate for its molecular quantitative trait dissection and selection assisted by molecular markers in breeding programs. Kianian et al. (2000) suggested that, because of the complexity of the character, a mapping population with a large number of individuals is needed to detect small phenotypic effects. In their work, two recombinant inbred populations with the common parent Kanota were evaluated for beta-glucan content in multiple US environments and two genomic regions hosting the markers Xcdo665B and Xcdo400 were identified able to explain more than 20% of the phenotypic variance of the character in both populations. Several other studies were focused on the molecular mapping for β-glucan content in oats. De Koeyer et al. (2004), in a mapping population derived from a hulless spring oat found in North America, detected five QTLs influencing β-glucan content and explaining 23% of the phenotypic variance. Marker cdo484a was identified as associated with the most consistent region. In the double haploid oat mapping population “Aslak”  “Matilda” (AM), four relevant QTLs were found as responsible for more than one-third of the phenotypic variation for β-glucan content (Tanhuanpää et al. 2012). Two of these QTLs were environment-specific, and two of them are coincident with those identified by Kianian et al. (2000). Herrmann et al. (2014) identified three loci influencing β-glucan content in two mapping populations grown at three sites in Germany over a 3-year period. The QTL

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with the largest effect was QBg1.jki.A-1. This QTL is flanked by the markers E36M55_1 and E36M52_3, explains 31% of the phenotypic variance, and is located on a linkage group putatively homologous to KO_6 of the KO map. GWA mapping studies have also been published. Newell et al. (2012), using an oat panel composed of 431 genotypes, identified three markers associated with β-glucan content. One of the markers had high sequence homology to rice chromosome 7 in a region adjacent to CslF gene family members. Studying 446 oat lines genotyped with 1005 diversity array technology (DArT) markers, Asoro et al. (2013) identified 37 markers explaining β-glucan content. These authors compared efficiency of genomic, marker-assisted, and best linear unbiased prediction (BLUP) for selection for β-glucans concentration and concluded that, despite genomic method being more efficient in improving β-glucan concentration, it also leads to faster loss of genetic diversity. Zimmer et al. (2020) evaluated in multiyear trial the beta-glucan content of 413 accessions belonging to the UFRGS Oat Panel, characterized by a weak population structure. The beta-glucan content was associated to seven QTLs located in genomic regions synthenic with barley. In summary, despite several studies, the genetics underlying the beta-glucan synthesis and regulation in oats is still largely unknown. Important candidate genes for enzymes involved in the beta-glucan synthesis belong to the CLS (cellulose synthase like) gene family. Fogarty et al. (2020), in a genome-wide association study (GWAS) on three panels of elite accessions (spring, winter, world diversity) of oat grown in multiple North American locations, identified 58 significantly associated markers. The homology among the QTLs identified suggested that multiple copies of β-glucan biosynthesis genes are present in the three sub-genomes of oats and contribute to the overall phenotype. In particular, the high expression level of AsCslF6_A and AsCslF6_D genes, located respectively on A and C sub-genomes, is shared by high beta-glucan varieties.

6.4

Breeding for Oil

Oats are richer in oil (~6–10%) than any other cereal, and recurrent selection breeding resulted in lines with up to 18% oil. The oils are mainly concentrated in bran and endosperm and not in the germ, such as other cereals, for example, maize. The localization of the majority of oat grain oil to the endosperm suggests that there is a great potential to increase the oil content of this crop since this storage tissue is the major part of a cereal grain. Oat grains are rich in linoleic acid (Leonova et al. 2008; Leonova, 2013), polar lipids, and peculiar galactolipids with esterified hydroxyl fatty acids (Moreau et al. 2008). Cultivars with high- or low-oil content have different uses in human and animal nutrition and are both necessary, depending on the destination and on the different technological treatments. For example, low-oil cultivars are generally preferred for rolled oats to simplify the milling procedure and in general are for low-fat foods. On

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the contrary, high-oil oats are preferred for feed because more energetic, as well as to produce “oat milk” for human consumption due to the higher nutrition value. Breeding efforts, therefore, must be directed both to the selection of high- and low-oil content oats and even to oats enriched in beneficial PUFA. Oil content has a high heritability due to additive gene action (Bjørnstad et al. 1994). Negative correlation has been identified between fat and starch contents. Contrasting results have been obtained studying the correlation among fat level, βglucan, and protein content. It was, in fact, found that the protein concentration increases with nitrogen fertilization and the oil decreases, but there are even cultivars with high protein and oil levels. An interesting point is the beneficial PUFA 18:2 (linoleic acid) and 18:3 (linolenic acid) content of oats. Leonova et al. (2013) reported that the cultivated oats are richer in such molecules in comparison with wild relatives, even if these last have the highest total oil content. This observation has been confirmed by Dhanda (2011) in an extensive study on 917 oat accessions. The cultivated hexaploidy oats confirmed the elevated levels of linoleic and linolenic acids in different cultivation environments. The environmental impact on the total oil content has been observed, but its influence is still controversial on the oil composition, as reviewed by Stewart and McDougall (2014). Carlson et al. (2019) used multivariate GWAS methods for identifying genetic associations with metabolites that share lipid biosynthetic pathway. The authors analyzed ten fatty acids simultaneously with multi-trait GWAS methods and found a panel of SNPs that were not detected by traditional, univariate GWAS. They suggested how such multivariate GWAS may increase analysis sensitivity and be advantageous for oat, where the effect of a single locus may be buffered by the activity of its homeologs. Campbell et al. (2021) developed a trait-specific genomic relationship matrices (TGRMs) model as a prediction tool for the oil content in oats. This model is based on the relationships between individuals using genome-wide markers (SNPs) and place greater emphasis on markers relevant to the trait. In the first step of their work, nine fatty acids were quantified in a panel of 336 genotyped oat lines and the markers effects were used to construct TGRMs. In the second step of the study, the model was validated to predict total seed lipid content in an independent panel of 210 oat lines. The results obtained sustain the utility of using TGRM and improve genomic prediction for a conventional agronomic trait. The oat oil content is linked with lipase level. Oat lipases are a postharvest problem, which negatively impact on the seed storage, because of the transformation of oils into free fatty acids and the rancid flavor development. In the frame of CropTaylor project, 900 EMS mutation lines were screened for lipase content with the final aim to select low-lipase oat lines (Marmon 2022). Alternatively, or additionally, oat-based antioxidative extracts have been evaluated to prolong oat oil stability. AVA-rich extracts were found to inhibit lipase action and protect toward oxidation. Such natural extracts have therefore the potentialities to be used in oat-based food preservation (Tullberg 2022).

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Breeding for Avenanthramides

Avenanthramides (AVNs) have not been yet a direct target in oat breeding; however, varietal differences in a range from 40 to 132 mg/kg have been found (Dimberg et al., 1993). Moreover, their abundance has been found modulated by the environment (Redaelli et al. 2016). AVN concentration is a heritable trait, as demonstrated by Michels et al. (2020). These authors quantified AVNs in 100 at accessions in a multilocation and multiyear trial, finding that, despite environmental influence, genotype has the largest impact on all three AVN major types of production. In the review by Shelenga et al. (2021) are reported several screening works in which AVN concentration was measured in several accessions of different origin and species grown in European, Asiatic, and American environments. The highest range of variation for AVN was reported in the study of Leonova et al. (2020), who analyzed the AVN content and composition in 32 wild and 120 cultivated oat accessions, finding a great variability for this trait, with AVN ranging from 4 to 1825 mg kg1. Brzozowski et al. (2022), in an oat germplasm screening, found, in modern varieties, a reduced genetic variation for these molecules in comparison with obsolete cultivars and landraces. Modern varieties show that the abundance of these molecules increases with the seed size. Moreover, GWAS and TWAS analyses indicate that the enzymes preceding committed biosynthetic steps seem to have a key role in avenanthramide content. Hernandez-Hernandez et al. (2021) proposed mutagenesis coupled with highprecision biochemical selection as useful method to develop stable lines with a high concentration of total and/or individual AVNs in the oat seed grain.

6.6

Breeding for Protein

Oats are interesting from the point of view of protein content: it is in fact a low-cost protein source and has a higher level of protein in comparison with other grains, including cereals, legumes, and oil seeds. Higher protein is a desirable characteristic of oats used for both food and feed purposes. Moreover, a diet rich in plant protein is gaining attention as it is perceived as healthier for the consumer and more sustainable for the planet in comparison with animal proteins (Kumar et al. 2021). Proteins in oats are mainly localized in the germ and the bran and less in the endosperm (Boukid 2021). They differ in structural and distributional properties from other cereals that are rich in prolamins and poor in lysine. Globulins are the primary storage protein in oats; they also contain higher concentration of lysine and other essential amino acids, thus making them a superior protein source (Valentine and Cowan 2004). To improve protein concentration, emphasis has been given to breeding and selections. Sunilkumar et al. (2017) identified, in a mutagenized population, 15 oat

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lines with a protein content ranging from 17% to 24%. Such lines, increased in globulin-like proteins, are stable for this character and can be the starting point for the development of a high-quality, high-protein oat variety, both for food and feed. Batalova et al. (2019) worked on naked oats to obtain the high-protein Vitovet cultivar.

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Are Oats Genetically Modified Crop?

Oats are not genetically engineered crop. No genetically modified oat variety is present on the market. Several reasons are behind this: the complex oat genome is one, but the most important is the almost nonexistent demand to justify the expensive research that goes into developing genetically modified seeds. Genetically modified oat plants have been obtained with the unique aim to identify suitable protocols for transformation or to study specific gene functions. Oats can be transformed, and to this aim some protocols have been developed for a long time. In the pioneering work of Somers et al. (1992), friable, embryogenic oat callus cultures were obtained following microprojectile bombardment with a plasmid encoding the Streptomyces hygroscopicus bar gene and the Escherichia coli uidA gene. Pawlowski and Somers (1998) proposed a mechanism of transgenes integration in oat genome at multiple clustered DNA replication forks to explain the observation that all transgenic lines analyzed exhibited genomic interspersion of multiple clustered transgenes. Zhang et al. (1999) transformed shoot meristematic cultures derived from seedlings of commercial varieties.

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The Oat Genomes

A. sativa is allohexaploid (2n ¼ 6x ¼ 42) with a large and complex genome (> 12 Gb), composed of the three AACCDD subgenomes, highly repetitive and characterized by duplications and intra- and intergenomic rearrangements. All these features made full genome assembly a difficult task to reach. An oat reference genome has been therefore missing for decades. Common oat is thought to have been domesticated from wild-weedy A. sterilis L. (Zhou et al. 1999), an allotetraploid carrying CCDD subgenomes and an AsAs diploid (Yan et al. 2016). Several diploids carrying A genome variants (Ac, Ad, Al, Ap, and As) (Loskutov and Rines, 2011) are known to be potential source of genes relevant for qualitative trait, for example, improving soluble fiber and protein (Welch et al. 2000). The C-subgenome carries a putative CSlF6c locus that likely has a negative effect on seed soluble fiber content (Coon 2012; Jellen et al. 1994). Maughan et al. 2019 produced the first, reference-quality, whole-genome reference assemblies for As- and Cp-genomes, using A. atlantica and A. eriantha as plant materials and a hybrid approach for sequencing, involving PacBio long reads, Illumina short reads, and both in vitro and in vivo chromatin-contact mapping.

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All these genomic data, together with genetic, germplasm, and phenotypic datasets for oats, are available in GrainGenes (https://wheat.pw.usda.gov or https:// graingenes.org), the international centralized repository for curated, peer-reviewed datasets of small grain cereals, including oat. Since 1992, GrainGenes has been a useful source of data and information for oat geneticists and breeders in both public and private sectors worldwide (Blake et al. 2019). Very recently, the challenge of obtaining a reference genome for Avena sativa was also met. PepsiCo announced in 2021 to have completed, in the frame of a public– private collaborative work, the 21 chromosome DNA assembly of the North American oat variety OT3098 using the long-read PacBio technology. The assembly has been made publicly available via the GrainGenes website: the data are hosted on the USDA Agricultural Research Service’s GrainGenes website at https://wheat.pw. usda.gov/jb/?data¼/ggds/oat-ot3098-pepsico and the datasets can be downloaded at https://wheat.pw.usda.gov/GG3/graingenes_downloads/oat-ot3098-pepsico. In 2022, Kamal et al. (2022) presented the high-quality reference genome of A. sativa and of its diploid progenitor A. longiglumis and A. insularis. The mosaic structure of the oat genome was revealed, characterized by large-scale genomic reorganization during the polyploidization process. The availability of the highquality reference genome was exploited to clarify some genetic features of healthrelated traits. For example, the high content and quality of β-glucans are driven in oat by allelic variation and are modulated by transcription factors. Such studies are the starting point for the future challenge of obtaining oat’s pangenome (Mascher 2022). The international PanOat consortium is working on this, with the aim to produce a pan genome deriving from the sequence assemblies of 20 carefully selected oats.

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Conclusions and Future Prospects

The value of oats in human health is indisputable and therefore is more than rational to focus on this crop through various improvement and enhancement actions. This means new opportunities for using oats through advanced fractionation and the development of innovative nutritious food products. Moreover, oat is a low-input cereal, and its adoption also increases environmental and economic sustainability of cereal-based rotations. From a policy perspective, the sustainable production of resilient cereal-based crop systems must be combined with systems capable of adapting (to) and mitigating climate change as well as protecting our soils and water courses and maintaining or enhancing biodiversity. To expand oat cultivation and increase its use, future oat production will need to meet the challenges posed by climate change and the demands of various end users by identifying cultivars with higher and more stable yield, enhanced grain quality, and reduced environmental impacts. This will be complemented by the identification and development of new markets for improved and innovative food, products from oats. Powerful enabling technologies for the identification of specific genes and markers

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Fig. 6 Interactions aimed at oats valorization for food chains

and accessing genetic diversity will drive the development of breeder-friendly tools accelerating the production of more prolific and resilient oat cultivars. This approach, depicted in Fig. 6, will rely on the use of oat genetic resources, thus enhancing their conservation through plant breeding and deployment of newly bred cultivars with desired traits. An integrated approach is required to bring together academic researchers and applied R&D teams to maximize the translation of research outputs into impact through commercial practice. An example of such interaction is the Scan Oat consortium, whose activities are based on six pillars, ranging from genetics and agronomy to technology and industrial applications, and aimed to “develop food industry using oat as fundamental ingredients” (L. Bülow, https://scanoats.se).

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Genetic Improvement of Sorghum: Crop Genome Designing for Nutraceuticals M. T. Labuschagne and L. Elkonin

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Sorghum Grain Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Phenolic Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Carotenoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Lipids and Vitamin E . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Amines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Carbohydrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Fibers, Vitamins, and Minerals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.7 Sorghum Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 Other Proteins in Sorghum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genetic Improvement of Sorghum Nutraceutical Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Genetic Resources for Genetic Improvement of Nutraceuticals and Nutritional Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Subset Collections as Sources for Marker-Assisted Breeding . . . . . . . . . . . . . . . . . . . . . . . 3.3 Sorghum Linkage and Association Mapping Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 The Sorghum Mutant Library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Genetic Engineering Approaches for Improving Nutritional Composition of Sorghum Grain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Sorghum is an ancient cereal crop grown widely in the dry regions of Africa and Asia, mainly by subsistence farmers. It is inherently adapted to drought and heat stress and has significant potential as a global food security crop in changing M. T. Labuschagne (*) Department of Plant Sciences, University of the Free State, Bloemfontein, South Africa e-mail: [email protected] L. Elkonin Department of Biotechnology, Federal Centre of Agriculture Research of the South-East Region, Saratov, Russia © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_6

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climatic conditions. The nutritional profile of sorghum is comparable with that of other cereals, but is unique in that it has various bioactive compounds such as phenolic acids, procyanidins, flavonoids, and anthocyanins. The protein (kafirin) of sorghum is, however, poorly digestible, and genetic improvement of protein digestibility has remained a challenge. Large genetic variability has been shown for almost all the bioactive compounds in tested sorghum accessions, but there is a large gap in the knowledge of the genetics underlying their expression. There are a number of sorghum germplasm collections, reference genome sequences, association panels, and mutant populations available in the world, which could be used to screen for genetic variation and determine genetic architecture, in order to improve sorghum nutraceutical content. Genetic engineering techniques have been applied to improve kafirin digestibility and carotenoid content, and have significant potential for improving nutraceutical content in the future. Information on the genes linked to nutraceuticals and the gene action involved in their expression will allow improvement of nutraceutical content through conventional breeding and by use of molecular markers, genomics, and genetic engineering. All available information on grain nutraceuticals and other nutritional components in sorghum should be integrated as a resource to be used by the sorghum community for sorghum improvement and genetic studies of nutraceuticals. Keywords

Sorghum · Phenolic compounds · Kafirin · Genetic resources · Genomics · Genetic engineering

1

Introduction

Sorghum [Sorghum bicolor (L.) Moench] is a stress-tolerant C4 plant, which belongs to the Poaceae family, which is well adapted to arid growing conditions. It is a versatile ancient cereal grown mainly by subsistence farmers. This annual crop is mostly photoperiod insensitive and completes its life cycle in 4 months. It is seen as a potential food security crop highly suited to climate change conditions. Maize, rice, and wheat are the most important cereals in the world, with sorghum ranking fifth in terms of importance. It is a staple food to more than 500 million people in Africa and Asia (Xin et al. 2021). The annual sorghum production is over 57 million tons (FAOSTAT 2019). In developed countries, it is mainly used for animal feed, biofuel production, and bioproducts, but it is a staple food in many developing countries (Xin et al. 2021). Nutraceuticals are, by definition, bioactive compounds, which are biologically active, and are found in food. Various phytochemical substances are regarded as bioactive compounds, including the polyphenols. Dietary fiber, polyunsaturated fatty acids, micro- and macronutrients, vitamins, oligosaccharides, lactic acid bacteria, choline, and lecithin are all bioactive compounds (Chaudhari et al. 2017). Biopeptides, which are biologically active peptides, are also nutraceuticals.

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Nutraceuticals have possible antioxidant properties and various other effects on the human body. Protein is a natural source of biopeptides, including antioxidant biopeptides (Hu et al. 2021). Certain amino acids, peptides, and proteins are also possible bioactive compounds (Szerszunowicz and Kłobukowski 2020). Reactive oxygen species (ROS) is important in metabolism and aging of humans, and some nutraceuticals contribute to decreasing the levels of ROS formed in the body through antioxidant activity (Li et al. 2021a). Human consumption of foods containing nutraceuticals have many therapeutic advantages. These compounds contribute to longevity, delaying aging, and preventing the development chronic diseases such as diabetes and hypertension, among others (Szerszunowicz and Kłobukowski 2020). Nutraceuticals can contribute to the prevention and management of viral infections (Li et al. 2021a). Different kinds of biological properties and activities have been ascribed to bioactive compounds, including antioxidant, anti-inflammatory, and antimicrobial properties, which can contribute to protection against human disease (Omrani et al. 2020). Sorghum grains consist of carbohydrates, kafirin (protein), fiber, polyunsaturated fatty acids, and resistant starch (Khalid et al. 2022). Sorghum has a nutritional profile comparable with other cereals, but is unique to other cereals in that it contains different bioactive compounds such as anthocyanins, flavonoids, phenolic acids, and procyanidins (Ofosu et al. 2021). The extensive biological activities of sorghum grains have been shown in a number of in vitro and in vivo studies. Sorghum bioactive compounds have been shown to inhibit oxidative stress, cardiovascular disease, high lipid levels, and hypertension. It has anticancer and antidiabetic properties and could lower cholesterol index and obesity through antioxidant and anti-inflammatory mechanisms (Li et al. 2021a). The phenolic compounds having bioactive properties include phenolic acid, flavonoids, stilbenes, and tannins. Sorghum grain also contains B-complex vitamins, fat-soluble vitamins A, D, E, and K, as well as minerals, including magnesium, potassium, phosphorus, and zinc. Some sorghum polyphenols, including tannin (proanthocyanidin) and 3-deoxyanthocyanidin, have the potential to protect individuals against inflammation, diabetes, and oxidative stress. Flavonoids are also known as antioxidants, which could positively influence inflammatory and neurodegenerative diseases, as well as cancer and diabetes. Sorghum grain also have a high fiber content, which can reduce blood cholesterol and glucose levels (Khalid et al. 2022). As sorghum is a good source of B vitamins, minerals, carbohydrates, and is also gluten free, it has significant potential as a source of food and beverages and gluten-containing replacement diets for people with celiac disease (Bouargalne et al. 2022). Although sorghum is known for various phytochemicals, which contribute to human health, it is often not valued for these attributes due to the poor digestibility of its proteins (Duressa et al. 2018). Extensive research has been done by various research groups on sorghum protein digestibility. There have been sustained (although limited) global research efforts focusing on unraveling the biochemical and genetic basis of low protein digestibility and the improvement of kafirin bioavailability. The sequencing of the sorghum genome has supported these efforts, leading to a better scientific understanding of kafirin chemical properties, the

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genetics underlying kafirins, and its protein body structure. Despite this, there have been several challenges in the genetic improvement of protein digestibility, as increased protein digestibility is linked to agronomically undesirable traits such as the opaque (soft) endosperm phenotype. It is technically possible to develop highprotein digestible sorghum with hard endosperm, as was the case with quality protein maize, especially with the help of marker-assisted breeding (Duressa et al. 2018). Li et al. (2021a) stated that kafirins are some of the best nutraceutical sources. Significant genetic variability has been reported for almost all the bioactive compounds in numerous sorghum accessions, indicating the possibility for genetic improvement through selection. Despite this, very limited research has been done on the genetic basis of bioactive compounds in sorghum and its possible improvement through conventional breeding, the use of DNA markers, genomics, or genetic engineering. To improve sorghum, it is critical to use the available genetic variation. These genetic resources should be screened for valuable genes underlying the synthesis of nutraceutical compounds (Bouargalne et al. 2022). In the world, there are a number of sorghum germplasm collections, reference genome sequences of good quality, and association panels, which can be used for genome-wide association studies for food and quality related traits. There are also mutant populations, which are useful to discover genes, which can be applied for sorghum improvement, as well as information on gene expression. Genetic engineering is becoming increasingly important in sorghum nutritional content research, and the technology has developed significantly in recent years. The aim of this chapter was to determine the current status of sorghum as a source of nutraceuticals, to assess current genetic resources in sorghum for possible genetic manipulation and improvement of nutraceutical content, and the use of new technologies such as genomics and genetic engineering to improve sorghum as a source of nutraceuticals in the human diet.

2

Sorghum Grain Chemical Composition

Sorghum grain composition is similar to that of maize and millet. It consists of starch, lipids, protein, as well as non-starch polysaccharides. It also contains B vitamins and vitamins D, E, and K (fat-soluble), as well as minerals (Przybylska et al. 2019). Sorghum seed was reported to consist of protein (4.4–21.1%), fat (2.1–7.6%), crude fiber (1.0–3.4%), total carbohydrate (57.0–80.6%), starch (55.6–75.2%), and total minerals as ash (1.3–3.5%) (Cabrera et al. 2020). In contrast to other cereals, sorghum is also a rich source of phenolic compounds.

2.1

Phenolic Compounds

Sorghum has the highest amount of phenolic compounds of all cereals. A variety of phenolic compounds are present in sorghum grains, including phenolic acids, flavonols, 3-deoxyanthocyanidins, flavanones, flavones, and condensed tannins

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(Shen et al. 2018). The outer layer of the grain (bran) has a high concentration of most of these compounds, which is unfortunately often removed during milling by decortication, which leads to significant reduction of sorghum health benefits. Therefore, the consumption of whole grain sorghum has many key health benefits, such as free radical scavenging activity (Kumari et al. 2021). Two main categories of phenolic compounds have been identified, namely soluble and insoluble. The soluble compounds like flavonoids, quinones, and phenylpropanoids are found in the vacuole of plant cells, while the insoluble compounds like lignins, condensed tannins, and hydroxycinnamic acid are attached to the cell wall (Gharaati 2019). The phenolic compounds are important secondary metabolites and are major contributors to the antioxidant properties of sorghum, having significant physiological benefits for humans. For this reason, the consumption of sorghum-based foods with high levels of polyphenolic substances can contribute to the prevention and reduction of the risk of chronic diseases, including some cancers and diabetes. The sorghum variety or genotype, the grain pericarp color, and the testa pigmentation all influence the phenolic compound profiles in sorghum. There are four classes of pericarp color in sorghum, which are white, yellow, red, and black. Genetically, black sorghums are actually red, as sunlight during the maturation process causes the red color to turn black. The white sorghums, also known as food-type sorghum, have very low levels of total extractable phenol and usually have no tannins or anthocyanins. Red sorghum is caused by a red pericarp and contains significant levels of extractable phenols, although they have no tannins. Black pericarps lead to black sorghums, which have very high levels of anthocyanins, while the brown sorghums have varying levels of phenolic compounds and pigmented pericarps (Khalid et al. 2022). The presence of total phenolic compounds in most sorghum whole grain is 0.46 ~ 20 mg gallic acid equivalent (GAE) per gram. The highest total phenolic compound content of almost 48 mg GAE/g was reported in whole grain red sorghum. Total phenolic content in sorghum bran varies even more than in seed. The total phenolic content of red sorghum bran was 20-fold that of white sorghum bran and 8.9fold that of yellow sorghum bran, while that in black sorghum bran extracts was 7.5fold that of white sorghum bran and 3.3-fold that of yellow sorghum bran extract (Burdette et al. 2010). It must be kept in mind that the variations in the quantities of total phenolic compounds reported in different studies could have been influenced by different extraction procedures and the solvents used, the specific genotypes tested, and environmental conditions in which plants were grown (Li et al. 2021a). Free and bound forms of phenolic compounds are found in sorghum, but 70–95% of phenolic acids are in a bound form. Despite this, far more research has been done on the identification and biological activity of free phenolic compounds in sorghum than on the bound compounds (Li et al. 2021b). Bound phenolics bind to structural compounds of the cell wall, thereby reducing bioavailability. It is therefore important to find novel ways to promote the release of bound phenolic compounds in order to increase their bioavailability. The molecular bonding can be severed by creating an acidic or basic environment and by elevating the temperature, which can cause release (Li et al. 2021a; Espitia-Hernández et al. 2022).

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Phenolic compounds can act as natural antioxidants by decreasing the oxidative damage of biomolecules, which reduces the effects of reactive oxidants. Phenolic extracts from sorghum were shown to decrease and inhibit the growth of cancer cells in organs such as the colon, liver, and esophagus (Kadri et al. 2017). Phenolic compounds vary significantly between sorghum seeds of different colors (black, brown, red, and white). The amount of phenolic compounds is highly correlated with antioxidant properties. Due to their phenolic compound content, sorghum grains are important as an ingestible form of antioxidants in the diet. The development of sorghum varieties with high levels of antioxidants can increase its nutritional value and health benefits. Sorghum tannins also have medicinal properties (Choi et al. 2019).

2.1.1 Phenolic Acids and Flavonoids Various studies have reported different types and numbers of phenolic acids, but the most frequently reported phenolic acids isolated from sorghum were caffeic acid and ferulic acid, 3-deoxyanthocyanidins (luteolinidin and apigeninidin), flavanones (naringenin), flavones (luteolin and apigenin), and dihydroflavonol (taxifolin) (Wu et al. 2017). Caffeic acid, p-coumaric acid, sinapic acid, gallic acid, protocatechuic acid, and p-hydroxybenzoic acid have also been reported quite frequently. Ferulic acid is the predominant phenolic acid, especially in red and brown sorghum, and is uncountable for about 90% of the combined phenolic acids. In red sorghum, ferulic acid was the predominant phenolic acid, and p-coumaric, caffeic, and 3,4-dihydroxybenzoic acids were also identified, but there was a large genotype influence on phenolic acids (Li et al. 2021b). Red and brown sorghum grains had the most luteolinidin and apigeninidin, followed by black grains, while white pericarp varieties had very low amounts of these compounds. Many phenolic acids have been assayed, and of these, ferulic, p-coumaric, and protocatechuic acids were seen in the highest concentrations in both red and white sorghum grain (Przybylska-Balcerek et al. 2018). The outer layers of the grain contain most of the flavonoids, which contribute to the coloring of the pericarp. Sorghum grains have been found to contain many flavonoids. As in the case of phenolic acids, a large genotype effect was seen (Li et al. 2021b). Both the color and thickness of the pericarp influence flavonoid concentrations and profiles. Flavonoids have antioxidant properties, and the daily consumption of foods with significant amounts of flavonoids can help to reduce the risk of cancers of the breast, colon, and pancreas. The main flavonoids in sorghum are anthocyanins, which are a group of anthocyanidin glycosides (Wu et al. 2017). Anthocyanin content in sorghum bran was three to four times higher than that of the flour. The highest anthocyanin content was reported in black sorghum bran (Kumari et al. 2021). The most frequently reported flavones in sorghum grains are luteolin, apigenin, and naringenin. The widest known flavonols in sorghum grain are kaempferol and quercetin, and the most researched flavanol is iscatechin, and for dihydroflavonol, it is taxifolin (Luo et al. 2020). Ofosu et al. (2021) were the first to report the presence of formononetin, glycitein, and ononin in sorghum. High concentrations of flavanones were identified in yellow-pigmented sorghum genotypes, and those with colored testas had a higher content of condensed tannins (Szerszunowicz and

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Kłobukowski 2020). A high concentration of flavones was reported in red-brown sorghum bran (576.47 μg/g) and lower amounts in yellow sorghum flour (15.3 μg/g). The flavanone concentrations were higher in yellow bran (1773.47 μg/g) and lower in brown sorghum flour (4.29 μg/g). Flavanone concentrations were consistently higher in bran than in flour (Kumari et al. 2021). Some of the sorghum flavones had estrogenic effects, as well as anticancer effects in vitro (Cox et al. 2019). Of all the cereals, only sorghum is a dietary source of 3-deoxyanthocyanidins (3-DXAs). These occur mainly as luteolinidin and apigeninidin, which are mostly water-soluble pigments (Luo et al. 2020). They produce yellow (apigeninidin) and orange (luteolinidin) colors in acidic solvents. They are effective natural colorants and have good antioxidant properties, which are beneficial for human health. Li et al. (2021a) reported that luteolinidin was the predominant 3-DXA, with its total content accounting for 40.55–78.36% of the total 3-DX. The concentration of 3-DXA was three to four times higher in black testa seeds than red or brown testa seeds (Shen et al. 2018). Kumari et al. (2021) reported that red-brown sorghum bran had the highest 3-DXA (4479.16 μg/g), while yellow sorghum flour had low 3-DXA levels (14.14 μg/g). Results from in vitro tests in sorghum showed that 3-DXA had both anticancer and antioxidant properties (Cox et al. 2019). The main antidiabetic substances in sorghum flavonoids have likewise been ascribed to condensed tannins and 3-DXAs (Li et al. 2021a).

2.1.2 Stilbenoids Stilbenoids are a group of phenolic compounds, and they have a number of benefits for human health. Sorghum can produce stilbenoid metabolites, but very limited research has been done on this. The total stilbenoid content is related to grain color. One study reported 0.4–1 mg/kg of trans-piceid in white sorghum and up to 0.2 mg/ kg trans-resveratrol in red sorghum grains (Bröhan et al. 2011). 2.1.3 Tannins The growing knowledge on the health benefits of tannins have led to tannins receiving more attention in the last years. They are heterogeneous polyphenolic polymers. Tannins in sorghum occur mainly in the pericarp and are polymerized products of flavan-3, 4-diols, and/or flavan-3-ols. Tannin content in sorghum bran is higher than in the flour. Bran from brown and red-brown sorghum varieties had significantly higher tannin content than bran of red and yellow varieties (Kumari et al. 2021). Tannins have many health benefits as they have antioxidant properties and are radical scavengers. They were also reported to improve immunity and have anticancer and anti-inflammatory properties. They are cardioprotective, are vasodilators and have antithrombotic effects (Queiroz et al. 2018). Sorghum is an excellent source of tannins compared to other cereals. Seyoum et al. (2016) reported tannin concentration ranging from 0.2 to 48.0 mg/g in sorghum, with grain with a black testa having the highest tannin level. A significant growing season effect was evident on the tannin content and activity in sorghum. Sorghum with a high tannin content generally has good resistance to birds, insects, and molds.

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Tannins, unfortunately, also have anti-nutritional effects, as they form complexes with protein and iron. This impairs the digestibility of the protein and reduces iron absorption (Iyabo et al. 2018). Apart from their interaction with protein, tannins also affect carbohydrates, especially starch, hemicellulose, cellulose, and pectin, reducing their digestibility. Based on their biological and chemical characteristics, tannins have been grouped into hydrolyzable and condensed (known as proanthocyanidins) tannins. Hydrolyzable tannins are complex polymeric compounds classified as gallotannins, when derived from gallic acid, and ellagitannins, when derived from ellagic acid, which is a dimer of gallic acid. Many and varied hydrolyzable tannins have been isolated from edible and inedible plants. They have anticancer, antidiabetic, and antibiotic effects. Condensed tannins are the main polyphenolic substances in sorghum (De Oliveira et al. 2017). Condensed tannins are especially common in sorghum seeds with pigmented testas. The testa is a structure present between the pericarp and the endosperm of the grain of only some varieties. Sorghum varieties with a brown testa generally have more procyanidins than that of other seed colors. The presence of condensed tannins is one of the reasons why sorghum has higher levels of antioxidants than any other cereal (De Oliveira et al. 2017). Proanthocyanidins in sorghum grains have antioxidant, antitumor, and lipid-lowering activities, and they play a role in the prevention of cardiovascular diseases. They are powerful radical scavengers (Yu et al. 2018). The most basic unit of composition of condensed tannins is catechin, gallocatechin, allocatechin gallate, and afzelechin (Jiang et al. 2020). Testa color is used a means to classify sorghum grains into three categories where type I is tannin-free sorghum without pigmented testa, type II sorghum has a pigmented testa layer (condensed tannins), and type III contain tannins in the testa and pericarp. The proanthocyanidins in sorghum form complexes and precipitate with proteins, probably causing both acidity and a bitter taste, which contribute to them being bird repellents (Li et al. 2021a). Procyanidins concentrations of between 10.6 and 40.0 mg/g have been reported in sorghum, depending on the genotype. This is higher than that of blueberries, known for their high procyanidin content (Yu et al. 2018). Sorghum grain extracts rich in tannin polyphenolics were shown to have in vitro and in vivo inhibitory effects against α-amylase and α-glucosidase enzymes. This could decrease hyperglycemia in diabetics (Links et al. 2015).

2.2

Carotenoids

Carotenoids have many beneficial effects on human health. The most researched carotenoids in sorghum include lutein and zeaxanthin, which are the xanthophylls, which are also the major carotenoids in sorghum, and β-carotene. Varied concentrations of carotenoids have been reported in different studies. This may be due to a genotype effect and different extraction and detection methods. In one study, the total carotenoid content in a hundred sorghum genotypes varied from 2.12 to 85.46 μg/100 g. Nine genes were reported to be involved in carotenoid synthesis or degradation, which is a contributing factor to the variability of levels of carotenoids in the grains of sorghum (Cardoso et al. 2015).

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Lipids and Vitamin E

Sorghum grain has low lipid content, though higher than most other cereal grains, and its lipid profile is similar to that of maize. The oil from sorghum grain have higher levels of oleic and stearic acids and lower levels of linoleic, myristic, and palmitoleic acids, making it less saturated than maize grain oil. The fact that oil from sorghum grain is high in unsaturated fatty acids may provide the health benefit of lipid-lowering properties (Khalid et al. 2022). Sorghum grain fatty acids are considered as bioactive compounds with health benefits, especially the phytosterols and policosanols. These fatty acids occur in the lipid fraction of the grain as the lipid group of triacylglycerols with a high linoleic, oleic, and palmitic fatty acid content. Phytosterols are steroids that originate from plants, and β-sitosterol is the main phytosterol that was found in sorghum. Campesterol and stigmasterol were also isolated. The concentration of phytosterols is largely influenced by the environment, genotype, and extraction methods. Policosanols (a class of high-molecular-weight aliphatic alcohols) also have different types of bioactivity. Different policosanols (C28, C30, and C32) were isolated from sorghum, of which C28 policosanol was the predominant one (Wongwaiwech et al. 2020). The vitamin E contents in sorghum were reported to vary significantly, between 280.7 and 2962.4 μg/100 g (wet basis). The α-, β-, γ-, and δ-tocopherols are the most studied in sorghum, with γ-tocopherol being the tocochromanol most frequently found, followed by α-tocopherol. The genotype and the growing environment both have a significant influence on the vitamin E content in sorghum grains (Cardoso et al. 2015).

2.4

Amines

There are two classes of amines, which are the biogenic amines and polyamines, and they represent a class of low-molecular-mass nitrogenous bases. The polyamines represent 60–100% of the total amines. Amines are considered to be bioactive compounds, and sorghum was reported to be a main source of polyamines. Spermine and spermidine are the most prevalent amines, followed by putrescine and cadaverine (Paiva et al. 2015).

2.5

Carbohydrates

The major carbohydrate in sorghum grain is starch, present in a granular form in the endosperm. Starch consists of two polysaccharides, amylose and amylopectin, and can be classified as waxy and non-waxy. Sorghum starch classified as non-waxy is composed of amylose (25%) and amylopectin (75%), while waxy sorghum consists almost entirely of amylopectin. Waxy sorghum is highly digestible by enzymes, while non-waxy starch exhibits resistance to enzymatic digestion. Proteins, tannins, and starch granules interact in the sorghum grains, forming complexes, leading to very poor starch digestibility. Sorghum has the poorest starch digestibility of all cereals. Sorghum genotypes with high phenolic and tannin content were found to be

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associated with enzyme inhibition and starch molecule interaction. This impairs the starch digestibility, which increases the resistance of starch, which leads to a lower glycemic index of foods in which the starch is included (Moraes et al. 2018).

2.6

Fibers, Vitamins, and Minerals

Dietary fibers are mainly non-starch polysaccharides, which have numerous health benefits, such as positive effects on diabetes, tumors, and atherosclerosis. The whole grain of sorghum consists 10–25% of bran, of which 35–48% is insoluble dietary fiber (Miafo et al. 2019). Sorghum, being a fiber-rich food, has a low glycemic index, causing a slower and lower rise in blood glucose level (Moraes et al. 2018). Sorghum grains contain many and various types of vitamins and minerals. Minerals include Ca, Fe, K, Mg, P, and Zn (Motlhaodi et al. 2018). The most prevalent vitamins are of the B-complex such as pyridoxine (vitamin B6), riboflavin (vitamin B2), and thiamine (vitamin B1), and the fat-soluble vitamins such as A, D, E, and K (Przybylska et al. 2019).

2.7

Sorghum Protein

Cereal grains generally contain up to 20% proteins, but unlike animal protein, they have a low essential amino acid content. However, cereals are widely available and are a staple in many regions throughout the world, making them an attractive protein source and a source from which peptide nutraceuticals can be released, which could eliminate reactive oxygen (Szerszunowicz and Kłobukowski 2020). A wide range of protein content in sorghum grains have been reported (6–18%), of which the biggest percentage is storage protein, or prolamins. Sorghum prolamins are called kafirins and are located in the protein bodies of the endosperm. Sorghum kafirins make up a large portion of the total protein in whole kernels (48–70%) and an even higher portion (up to 80%) in decorticated kernels, while the rest consists of the albumins and globulins (Espinosa-Ramirez and Serna-Saldivar 2016. Discrete kafirin protein bodies are formed, and in mature endosperm, these bodies form a tight matrix with starch granules. These matrices affect the processing quality of sorghum and contribute to grain hardness and digestibility. Sorghum storage proteins are classified according to solubility, structure, amino acid composition, and molecular mass. They consist mainly of albumins (water extractable fraction), globulins (dilute salt extractable fraction), and kafirins or prolamins (alkali soluble fraction) (Wong et al. 2009). Kafirins are hydrophobic proteins and are divided into three groups based on their molecular weight: α-kafirin (23–27 kDa), β-kafirin (16, 18, and 20 kDa), and γ-kafirin (28 kDa) (Espinosa-Ramirez and Serna-Saldivar 2016). The most dominant kafirin proteins are the α-kafirins, accounting for 70–80% of total storage proteins in sorghum grain (66–71% in opaque endosperm). They occur mostly in outer layers of grain and a reduction of α-kafirins is associated with a loss of vitreous endosperm texture (Wu et al. 2013). Sodium dodecyl sulfate polyacrylamide gel electrophoresis

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(SDS-PAGE) has been used frequently in the past to separate the kafirins. With this technique, the α-kafirins resolve into two distinct bands with a molecular weight of 23 and 25 kDa, although these molecular weights can range from 22 to 27 kDa depending on different laboratory protocols and conditions (Cremer et al. 2014). The second largest group of kafirins is the γ-kafirins. They make up a large part of the total kafirins in opaque endosperm (19–21%) and a smaller part (9–12%) in vitreous endosperm. They have a molecular weight of about 20 kDa. The β-kafirin comprises about 7–8% of total kafirins in vitreous endosperm (10–13% in opaque endosperm). The outside layers of the protein bodies contain most of the β- and γ-kafirins, where cross-links are formed between proteins via disulfide bonds (Oria et al. 2000). The very minor δ-kafirins (Mr ¼ 15 kDa) form the fourth group, accounting for less than 1% of the mature grain total seed storage protein. Sorghum protein is poorly digestible, and the improvement of protein digestibility is still a major research goal in the sorghum fraternity. Protein digestibility is strongly related with the overall grain α- and γ-kafirin content (Wu et al. 2013; Elkonin et al. 2016). Dense, spherically shaped protein bodies are formed in the seed endosperm during grain development from the accumulation of the different kafirin groups. Kafirin protein bodies are quite compact, and on the periphery of these bodies, cross-links are formed. This probably causes the structural barriers preventing enzymatic access, which reduce the digestibility of these proteins (Oria et al. 2000). Amino acids in grains are largely obtained from storage proteins, so this is a major factor determining the nutritional quality of the grain as a source of food for humans and animals. Both maize and sorghum proteins are deficient in the essential amino acids lysine and tryptophan, reducing the nutritional value of these cereals, which is an even bigger problem in sorghum than maize. Sorghum grain has low amount of essential amino acids like methionine, lysine, and isoleucine. The main amino acids in sorghum protein are histidine, leucine, phenylalanine, tyrosine, threonine, tryptophan, and valine (Mohapatra et al. 2019). The γ-kafirins are rich in proline, cysteine, and histidine. The β-kafirins are rich in cysteine. As the δ-kafirin fractions are so small, it could be inconsequential in influencing sorghum grain quality traits. However, it is rich in the essential amino acid methionine, which is often deficient in cereal proteins, along with lysine, threonine, and tryptophan. If the δ-kafirin fraction can be increased, it could enhance the nutritional quality of sorghum proteins (Laidlaw et al. 2010).

2.8

Other Proteins in Sorghum

Various antifungal proteins have been identified in sorghum, including chitinase, glucanase, thionin, defensin, protease inhibitor, and ribosome-inactivating proteins. There are also several bioactive proteins in sorghum such as amylase and protease inhibitors, as well as glycine-rich RNA-binding proteins, protein kinases, and glutathione S-transferase isoenzymes. Proteins involved in lysine catabolism were also isolated from sorghum, which included lysine 2-oxoglutarate reductase and saccharopine dehydrogenase (Lin et al. 2013).

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Genetic Improvement of Sorghum Nutraceutical Content

The nutraceutical content of sorghum can be improved in breeding programs if sufficient genetic variability is available to select for higher content. Natural genetic variation can be exploited, or genetic variability can be introduced from wild and close relatives, many of which are available from conserved genetic resources. Molecular techniques such as linkage and association mapping, and more recently, genome-wide association studies, can be used to understand the underlying genetic architecture of nutraceutical content. Sorghum mutant libraries are also proving very useful to use reverse genetics to determine traits that are useful for sorghum improvement, which could include nutraceutical content. Genetic engineering and genome editing techniques can now be applied to improve important traits, which already include some nutraceuticals.

3.1

Genetic Resources for Genetic Improvement of Nutraceuticals and Nutritional Value

The sorghum genus consists of Sorghum bicolor. This belongs to the subgenera of Eu Sorghum, within which there are three species: Sorghum bicolor, Sorghum halepense (Johnson grass), and Sorghum propinquum. The S. bicolor species consists of three subspecies: bicolor, verticilliflorum, and drummondii (Sudan grass). The bicolor subspecies has 5 races (bicolor, caudatum, durra, guinea, and kafir) and 10 intermediate races (Ananda et al. 2020). There are numerous global genetic resources of conserved sorghum worldwide and over 240,000 accessions are conserved in ex-situ gene banks. Most of these are cultivated accessions (98.3%) and a small percentage are wild weedy relatives (1.7%) (Upadhyaya et al. 2016), although there may be duplicates which yet have to be identified and managed. There are at least 20 sorghum gene banks in the world. The International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in India have a collection of 37,949 accessions from 92 countries (ICRISAT 2021). The United States Department of Agriculture (USDA) National Plant Germplasm System (NPGS) at the Plant Genetic Resources Conservation Unit in Griffin, GA, maintains a collection of over 45,000 accessions (USDA 2021). The Institute of Crop Science, Chinese Academy of Agricultural Sciences (ICS-CAAS), China, holds a collection of 18,263 accessions, and the National Bureau of Plant Genetic Resources (NBPGR) of India conserves 20,221 accessions (NBPGR 2021). Wild relatives are widely used in cereal breeding programs and likewise has potential in sorghum breeding to enhance yield potential and genetic diversity.

3.2

Subset Collections as Sources for Marker-Assisted Breeding

Significant research has been done on accessions collected from Ethiopia. Usually a high number of accessions is screened in different growing environments, and then a subset of this is genotyped using a genotyping by sequencing (GBS) approach. A

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core subset is then identified which best represents the genetic diversity present in the whole germplasm collection. A subset of 374 accessions followed by another subset of 1425 Ethiopian landrace accessions were analyzed (Girma et al. 2019). After that, another subset of 387 Ethiopian germplasm accessions were comprehensively phenotyped and genomic characterization was done (Girma et al. 2020). The natural variation and genetic structure of these populations were determined. Single nucleotide sequence polymorphisms (SNP) associated with important traits can be used as molecular markers in breeding programs (Girma et al. 2019, 2020).

3.3

Sorghum Linkage and Association Mapping Resources

Natural variation in populations has been shaped by natural and artificial selection, and a combination of the two. Variation is probably linked to specific agronomic adaptive traits that have ecophysiological relevance. Ecogeographical and historical information also largely determine natural variation, and analysis of this variation can shed light on the evolutionary processes that led to the genetic variation patterns. Sorghum germplasm is known to have high levels of natural variation (Boyles et al. 2019) and is very suited for genetic analysis. In linkage mapping, recombination is generated by crossing parents, while in association mapping, historical recombination events are used. Linkage and association mapping are widely used to characterize the genetic architecture of traits. This includes information of how many loci are involved and how they are distributed, the gene action determining the traits, and linkage and allele frequency. With this knowledge, scientists can hypothesize on the genes that underlie variation in studied traits.

3.3.1 Linkage Mapping Resources Many genetic traits in sorghum have been investigated through linkage mapping in the past 25 years, such as plant and flowering traits, pigmentation, drought and cold tolerance, and disease resistance (Xin et al. 2021). Almost no research has been reported on seed composition, including nutraceutical content, with the exception of kafirins. 3.3.2 Association Mapping Resources There has been significant developments in the methods that can be used to generate high-density genome-wide markers. This has caused a shift towards genome-wide association studies (GWAS) from linkage mapping and gene association. The sorghum association panel is currently the most widely used sorghum GWAS resource. This panel was designed to capture and represent global plant diversity, and plant function and end uses. This association panel has genotyping by sequencing (GBS) marker data (Hu et al. 2019) and is available from the Germplasm Resources Information Network (GRIN). All the sorghum association panel accessions flower in temperate latitudes. This panel has been used for GWAS studies of many traits (Mural et al. 2020). There is also a bioenergy association panel, which is another global diversity panel that is available from GRIN, where the majority of the

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accessions are tropical and photoperiod-sensitive. Although this panel consists mainly of tropical accessions, sweet and forage sorghums are also included. The bioenergy association panel has associated SNP data from GBS and whole-genome resequencing (Bellis et al. 2020; Lozano et al. 2021). A sorghum collection has been made available for phenotyping and association studies, consisting of 2000 georeferenced accessions, which were genotyped with GBS. Most of these accessions are also available from GRIN (Bellis et al. 2020). A large number of landrace accessions have been collected from Africa, for which GBS SNP data are available. There are entire GRIN collections from Niger, Nigeria, Senegal, Ethiopia, and Sudan, and for sweet sorghum.

3.3.3 Multi-parent Mapping Resources Techniques such as linkage mapping are powerful and sensitive, while association mapping has the strength of power and sensitivity, which created an interest to combine the best of these techniques in different genetic approaches. This has led to the use of multi-parent mapping approaches, which include nested association mapping (NAM), backcross NAM, and multi-parent advanced generation intercross (MAGIC), all which have been applied in sorghum research (Boyles et al. 2019). The NAM approach is based on that which was developed for maize and now applied in many crops where multiple recombinant inbred line (RIL) families are developed that have diverse founders but share a common parent (Gage et al. 2020). RTx430 was selected as the common founder line for the global grain sorghum NAM resource (primarily because it has for decades been the most important public pollinator line), together with 10 diverse global founders (all part of the sorghum association panel), from which a total of more than 2200 RILs in 10 families were developed. The common germplasm between the association panel and the NAM allows the validation and comparison of the data from these two sources (Olatoye et al. 2020). In the past, mainly biparental linkage families were used in research, but the aim of the MAGIC approach is to increase allelic diversity and at the same time to increase the power and specificity of quantitative trait loci (QTL) detection relative to GWAS. All founder lines contribute equally to the MAGIC in order to balance allele frequencies. One sorghum MAGIC resource has been developed and is currently available from the developers (Ongom and Ejeta 2018). There is also a backcross NAM (BCNAM) approach, where backcrosses are made and selection done to recover the common elite parent phenotype, which may have more of a breeding advantage (Jordan et al. 2011).

3.4

The Sorghum Mutant Library

Xin et al. (2008) developed a pedigreed mutant library for functional genomic studies by using a systematic approach in such a way that all mutations are captured and preserved. Individual seeds from an elite inbred line, BTx623 (used to generate the first sorghum reference genome), were treated with the chemical mutagen ethyl

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methane sulfonate (EMS). Seeds were soaked in various concentrations of EMS to optimize the chances to obtain desirable mutations. This mutant library is a permanent resource, which can be used by scientists to test mutants under different growing conditions, to enhance breeding efforts. Currently, 6400 independent seed pools are available in this library to breeders and scientists. These are an excellent resource for sorghum breeding, as mutants with potentially useful traits can be selected for sorghum improvement programs (Xin et al. 2021). Purdue University has followed a similar approach to generate approximately 10,000 pedigreed seed pools (Addo-Quaye et al. 2018). A wide range of phenotypes that could be used for sorghum improvement have been identified and selected within this pedigreed mutant library. The traits and phenotypes identified in this mutant library have the potential to be used in sorghum breeding programs and in genomic studies. Both forward and reverse genetic resources have been developed that can be used to explore the mutant library traits (Wang et al. 2021). Next-generation sequencing techniques have been developing rapidly, providing large numbers of DNA markers, which are also financially affordable. The output of high-quality DNA sequences has been increasing, and next-generation sequencing has become much cheaper. Whole genome sequencing of pedigreed mutants has become a resource for reverse genetics by searching gene mutations online. Nextgeneration sequencing has been used to annotate SNP markers. Mutant phenotypes of interest can be studied to map and identify causal mutations through mapping-bysequencing or next-generation mapping (Hartwig et al. 2012). Addo-Quaye et al. (2018) introduced mutations with EMS and then sequenced 586 mutants, where they identified 1,275,872 homozygous and 477,531 heterozygous mutations. In the sorghum genome, as is the case in other crops, the mutations often have deleterious effects. The sequenced data of the mutant collections can be a very useful resource for reverse genetics. These collections can be used together with other methods, such as genome-wide association and biparental mapping of QTLs of important agronomic traits, to validate candidate genes (Xin et al. 2021). Although very limited research has been done on the genetics of nutraceuticals so far (with the exception of kafirins) compared to the adaptive and yield-related traits, the resources are there, and they should be used to generate data for genetic improvement.

3.5

Genetic Engineering Approaches for Improving Nutritional Composition of Sorghum Grain

Recent years have been marked by significant progress in sorghum genetic transformation technologies that have made it feasible to use genetic engineering and genome editing methods to improve the nutritional properties of sorghum grain. Such progress is based on improved technologies of plant regeneration in sorghum tissue culture, in particular, the use of nutrient media containing increased concentrations of phosphate, proline, and asparagine, which reduces the release of phenolic pigments characteristic of cultivated sorghum tissues and increase embryogenic potential (Elkonin and Pakhomova 2000), as well as elevated levels of copper

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ions, which improve the development of the root system of regenerants. Efficient media for plant regeneration allowed substantial improvement of genetic transformation methods of sorghum either through biolistic DNA delivery (Belide et al. 2017) or Agrobacterium-mediated genetic transformation (Do et al. 2016). In the latter case, significant improvements are due to the use of “hypervirulent” A. tumefaciens strain NTL4 or another Agrobacterium strain containing specially designed Ti-plasmids with additional copies of vir-genes (“superbinary” vectors) or containing “helper” plasmids with additional vir-genes that enhance the transfer of T-DNA from Agrobacterium cells to sorghum cells. An important factor that also contributed to the increase in the efficiency of Agrobacterium-mediated genetic transformation in sorghum was the obtaining of an auxotrophic mutant LBA4404 Thy – incapable of growth on a media without thymidine, the use of which made it possible to significantly simplify the transformation procedure. The creation of binary vectors carrying the genes of morphogenetic regulators BABY BOOM and WUSCHEL, which promote the direct development of embryoids from scutellum cells of immature embryos, and thereby increase the number of regenerants and the frequency of transgenic plants, also had a significant effect (Che et al. 2022). The main goals of genetic engineering approaches for improving nutritional value of sorghum grain are improvement of the digestibility of sorghum storage proteins, modification of starch content, enrichment of sorghum grain with essential amino acids and carotene, and decreasing the level of phytate that reduces bioavailability of minerals and phosphate. Some of these goals are being successfully realized currently, while the achievement of other goals is the task of future research.

3.5.1 Improvement of Kafirin Digestibility Kafirins are resistant to proteolytic digestion, which is one of the main causes of reduced nutritional value of sorghum grain. This resistance to proteolytic digestion not only reduces their digestibility by animals and humans but also reduces the digestibility of grain starch, since undigested kafirins prevent the amylolytic cleavage of starch granules (Duressa et al. 2018). Significant research has been devoted to the study of the factors that cause protein indigestibility. The reasons for kafirin resistance to protease digestion are multifactorial. It is assumed that kafirin resistance to protease digestion is caused by the chemical structure of kafirins, which are abundant with sulfur-containing amino acids capable to form S–S bonds that result in the formation of kafirin olygo- and polimers resistant to protease digestion; interactions of kafirins with non-kafirin proteins and nonprotein components such as polyphenols and polysaccharides; and the organization of different kafirins in the protein bodies, with the β- and γ-kafirin located at the periphery of the protein body, while the most abundant α-kafirin is located within the protein body. Such a spatial arrangement of kafirins in the protein bodies of sorghum, apparently, is a consequence of the prolamin synthesis pattern in the process of kernel development. In maize, it was found that starting from 4 to 5 days after fertilization, protein bodies accumulate γ- and β-prolamins, while later on, intensively accumulating α-prolamins moved γ- and β-prolamins to the periphery of the protein body. Due to the peripheral occurrence of γ-kafirin (which is

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considered as the most stable to protease digestion) in the protein body, it is generally accepted that it reduces digestibility of α-kafirin, which comprises up to 80% of total endosperm kafirins (Duressa et al. 2018). In addition, γ-kafirin effectively forms oligo- or polymers of high molecular weight, which has high resistance to protease digestion. This hypothesis was confirmed by the study of a mutant, P721Q, with a high level of lysine and improved digestibility of kafirins, obtained by chemical mutagenesis. In this mutant, the protein bodies had irregular shape, having deep invaginations, while normally they have a round shape. The γ-kafirin is located only in the bottom of these invaginations and does not form a continuous layer, which prevents digestion of α-kafirin in normal sorghum. It was suggested that such a structure of the protein bodies determines the high digestibility of proteins in the P721Q mutant and lines derived from it (Oria et al. 2000). Floury type endosperm grains are formed due to this mutation and lysine content is increased. It was therefore denoted with the symbol hdhl (high digestibility high lysine). Further investigation of this mutation using two-dimensional gel electrophoresis and mass spectrometry showed an increase of non-kafirin proteins (such as cytoskeleton and chaperone proteins, and the proteins involved in amino acids and carbohydrates synthesis) and a decrease in kafirin content in hdhl endosperm. The overexpression of chaperone proteins, which are probably involved in the repair of protein misfolding that was caused by the mutation, is in part responsible for increased lysine content of the P721-opaque sorghum (Benmoussa et al. 2015). Studies have been undertaken on the chromosome localization of this mutation. In the research of Winn et al. (2009), with the analysis of a hybrid population obtained by crossing highly digestible line P850029 (derived from P721Q) and the wild type line Sureno, two QTLs were identified. These QTLs (both from the highdigestibility parent) were located on chromosome 1 in genomic regions within 20 cM from each other. They were in repulsion phase, meaning one QTL (locus 1 from the HD parent) unfavorably affects digestibility and one QTL (locus 2 from the HD parent) favorably affects digestibility. Protein digestibility can be increased if this linkage in repulsion is broken, which will allow the recombination of favorable alleles. It is noteworthy that another research group found that the proteinase inhibitor gene is located on chromosome 1 (Duressa et al. 2018). Perhaps QTLs identified by Winn et al. (2009) are linked to this gene. In another investigation of chromosome localization of the hdhl mutation, one major QTL was identified on chromosome 5, in the 58 Mb region that overlaps with the genomic loci of the 17-kafirin gene cluster. In this research, the F2 population generated from a cross between a normal line (BTx623) and a high-digestible mutant, P721Q was used (Massafaro et al. 2016). The F2 plants with highly digestible protein displayed the unique protein body structure of P721Q. The results of this investigation confirms the data obtained by Wu et al. (2013) which showed that the hdhl phenotype in the P721Q mutant and lines derived from it is a consequence of a point mutation in one of the genes from the k1C family located on chromosome 5, encoding the 22 kDa α-kafirin. Sequencing revealed a point mutation in the nucleotide sequence that encodes the signal polypeptide responsible

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for the packaging of α-kafirin inside the protein body (substitution at position 61 G!A) (Wu et al. 2013). This mutation resulted in the formation of a missense codon at the last amino acid of the signal sequence. Despite the fact that the mutation was found in only one of the genes of this cluster, its presence was sufficient to cause significant changes in the structure of protein bodies and the digestibility of kafirins. It was hypothesized that this mutation decreases the accumulation of α-kafirin in protein bodies that leads to a change in their ultrastructure and increases their sensitivity to the action of proteases (Wu et al. 2013). In addition, a comparative analysis of the nucleotide sequences of all 27 kafirin genes in sorghum samples with high and low digestibility revealed four α-kafirin alleles localized on chromosome 5, which are closely associated with digestibility. Three alleles were associated with high digestibility (Sobic.005G185600, Sobic.005G188800, and Sobic.005G189000) and one with low digestibility (Sobic.005G192801). In silico predictive analysis showed the variants cause missense change in the amino acid sequences of the corresponding proteins (Duressa et al. 2020).

3.5.2 RNA Interference Technology The use of biotechnology methods, in particular, RNA interference technology, opens up much broader prospects for obtaining mutants with improved digestibility of kafirins. This technology has been widely used for a long time to modify the synthesis of storage proteins as well as starch and other nutrients of endosperm in a number of cereals (Elkonin et al. 2016). A number of research groups have been doing studies on the induction of RNA silencing of kafirin genes (Da Silva et al. 2011a, b; Kumar et al. 2012; Grootboom et al. 2014). RNA silencing was induced by genetic constructs carrying inverted repeats of several kafirin genes (α1, δ2, γ1, and γ2) separated by the ADH1 gene intron sequence. mRNA transcribed from this construct forms a double-stranded hairpin and underwent enzymatic degradation. The constructs were driven by the 19-kDa maize α-zein promoter (Da Silva et al. 2011a, b). In another study (Kumar et al. 2012), the genetic construct used to induce γ-kafirin silencing consisted of the complete γ-KAFIRIN gene sequence under the control of its own promoter. As a terminator, the sequence of the tobacco mosaic virus ribozyme gene was used. The expression of this gene should destroy γ-kafirin mRNA. In another construct, to induce α-kafirin silencing, α-kafirin inverted repeats separated by the intron sequence of the Arabidopsis gene encoding the D1 spliceosome protein were used; this construct was driven by the α-kafirin promoter (Kumar et al. 2012). Later, another complex construct consisting of inverted fragments of γ1-, γ2-, and δ-kafirin genes was used to obtain transgenic sorghum plants with silencing of kafirins (Grootboom et al. 2014). The transgenic plants obtained in these experiments had a modified protein body structure which resembled that of the P721Q mutant, and an increased digestibility of kafirins, which was observed when both raw and cooked sorghum flour was treated with pepsin. One such example is the transgenic plants of Tx430, carrying a genetic construct for silencing α- and γ-kafirin. They were identified as having

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improved in vitro protein digestibility (78% and 61% for the raw and cooked flour, respectively), while in the non-transgenic control, the digestibility varied in the ranges of 40–50% and 34–40%, respectively (Da Silva et al. 2011a). The genetic construct to suppress only δ- and γ-kafirins also improved the digestibility of raw flour but did not affect the digestibility of cooked flour. In the experiments of Kumar et al. (2012), the cooked flour from transgenic kernels carrying a genetic construct for γ-kafirin suppression did not differ from the non-transgenic control, while α-kafirin suppression improved the digestibility of such flour. Based on the hypothesis that the surface location of γ-kafirin in protein bodies is the reason for the low digestibility of sorghum protein bodies, a genetic construct (NRKAFSIL) was created that should prevent the accumulation of the γ-kafirin without affecting the accumulation of other kafirins (Elkonin et al. 2016). This construct contained the fragment of the nucleotide sequence of γ-kafirin gene (GenBank Accession No: M73688) in direct and inverted orientation, separated by the maize ubiquitin intron sequence. The construct was driven by the 35S promoter. Using Agrobacterium-mediated genetic transformation, this construct was introduced into two sorghum cultivars: Zheltozernoe 10 (Zh10) and Avans. Electrophoretic spectra of endosperm proteins were compared before and after pepsin digestion, showing that in the transgenic plant, the amount of undigested kafirin monomers and total undigested protein was significantly lower than in the original non-transgenic line (by 1.7–1.9 times) when quantitative SDS-PAGE analysis was done. The level of digestibility reached 85–92%, while in the original line, this value was about 60%. The effect of increased digestibility of kafirins was traced to the T4 generation; however, in some cases, it disappeared, possibly due to the instability of the introduced genetic construct or due to its silencing. It should be noted that RNAi silencing of the γ-kafirin gene also caused a decrease in the content of α-kafirins. This phenomenon was especially pronounced in the Avans-1/18 transgenic line (Elkonin et al. 2021). At the same time, the functioning of the construct for the γ-kafirin gene silencing did not lead to a significant decrease of the total protein content of the grain compared to the original non-transgenic cultivar (14.3% vs. 15.5%). This fact, apparently, is a consequence of the balancing of protein synthesis in the kernels. Another feature of transgenic sorghum lines with silencing of γ- and α-kafirins is the modification of the endosperm texture, in particular, the reduction of vitreous endosperm layer and formation of kernels containing floury endosperm characteristic to the P721Q mutant (Da Silva et al. 2011b; Kumar et al. 2012; Grootboom et al. 2014). Apparently, expression of RNAi genetic constructs also affects the formation of the protein-carbohydrate matrix, which caused formation of the vitreous endosperm layer. In experiments with the genetic construct for γ-kafirin gene silencing in variety Zh10, transgenic plants were obtained that had kernels with different endosperm types (Fig. 1). Normal endosperm with a thick or thin vitreous layer, floury endosperm, or a modified type of endosperm in which the vitreous layer developed as sectors or spots surrounded by floury endosperm were seen (Elkonin et al. 2016). In these experiments, the kernels of some transgenic plants that exhibited a thick vitreous

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Fig. 1 Cross sections of kernels of transgenic sorghum plants with genetic construct for silencing of the γ-kafirin gene (Elkonin et al. 2016). (a) Kernel with floury endosperm set on the plant from Т3 generation; (b) kernel of original non-transgenic line Zh10 with thick vitreous endosperm (marked by arrows); (c–e) modified endosperm type with blurs and sectors of vitreous endosperm observed in kernels of different T1 and T2 plants; and (f–h) irregularly developed vitreous endosperm developed in kernels of T2 and T3 plants. Bar ¼ 1 mm (© 2017 Elkonin LA, Italyanskaya JV, Panin VM, Selivanov NYu. Originally published in “Plant Engineering”, InTech, Zagreb (Chroatia) under CC BY 3.0 license. Available from: https://doi.org/10.5772/intechopen.69973)

endosperm had a digestibility level as high as 92%, while the amount of undigested monomers was reduced by 17.5 times, and the amount of total undigested protein was 4.7 times less compared to the original lines. Previously, transgenic plants with similar endosperm texture were also observed in the Tx430 transgenic line with a construct for silencing α- and γ-kafirins.

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It seems that the different types of endosperm that form are due to the particular expression of genetic constructs in the genome of the recipient line. In transgenic line Avans-1/18, in the T1 generation, a revertant with vitreous endosperm and significantly reduced digestibility of kafirins was found (Elkonin et al. 2021). This revertant contained part of the NRKAFSIL genetic construct determining resistance to the selective agent (bar gene). At the same time, this revertant has a deletion in the ubi1 intron, which is a part of the construct for silencing of the γ-KAFIRIN gene, that, apparently, caused inefficiency of silencing and loss of characteristic features of mutation. These data indicate that the 588 bp ubi1 intron sequence can be used as a molecular marker in the screening of plants with high protein digestibility during hybridization of the Avans-1/18 mutant with various sorghum varieties. The well-known correlation between the high digestibility of kafirins and floury endosperm was confirmed by these findings (Duressa et al. 2018). Such a correlation could hardly be explained by impaired synthesis of γ-prolamines (γ-kafirin), which are believed to play an important role in the interaction of protein bodies with starch granules, since mutants with impaired synthesis of α-kafirins also have a floury endosperm type (Da Silva et al. 2011b; Kumar et al. 2012; Grootboom et al. 2014). This correlation is possibly due to a violation of the formation of non-kafirin proteins in mutants with suppressed synthesis of α- or γ-kafirins, which form a protein matrix characteristic of vitreous endosperm. In mutants where kafirins are silenced, an increase in essential amino acid contents of lysine and threonine is seen, which appears to be due to increased synthesis of other proteins, including those with a higher content of essential amino acids. Thus, a significant increase of lysine content (an increase of 1.2 g/100 g protein compared to the non-transgenic control) was found in transgenic sorghum plants where α-, γ-, δ-kafirin genes were silenced due to the presence of complex genetic constructs for RNAi silencing and the presence of the lysine ketoglutarate reductase gene (which controls catabolism of free lysine) (Da Silva 2012). In the transgenic plants of variety Zh10 containing the genetic construct for γ-kafirin silencing, the proportion of lysine increased 1.6–1.7 times (Elkonin et al. 2016); in the Avans-1/18 line, the increase was 75%, from 0.36% in the original line to 0.63%. It seems that the increase was caused by a decrease in amount of α-kafirins, which are poor in lysine and threonine, while the synthesis of other proteins was not affected. This caused an increase in the relative proportions of lysine and threonine. The suppression of γ-kafirin synthesis probably has no effect on the synthesis of proteins that are rich in lysine and threonine, but it prevents the accumulation of α-kafirins. The use of RNA-interference technology, however, has a number of significant limitations: the genetic construct for silencing may undergo partial or complete destruction in the recipient genome (Elkonin et al. 2021), or its expression itself can undergo silencing. In addition, the functioning of the RNA silencing mechanism is an epigenetic process, and epigenetic processes in plants largely depend on environmental conditions (such as temperature, soil, and air humidity) (von Born et al. 2018). In the transgenic line Zh10, carrying the genetic construct for silencing

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γ-kafirin, the level of digestibility of kafirins in plants grown in a field plot under natural moisture conditions was lower than in plants grown in outdoor vessels (Elkonin and Italyanskaya 2017). In some cases, off-target, nontarget, and unintended effects of genetic constructs for RNAi were observed (Christiaens et al. 2018). Besides these scientific problems, public concerns on using transgenic plants are a serious problem, which limits widespread use of sorghum lines carrying genetic constructs for RNA silencing for food and feed purposes.

3.5.3 Genome Editing Technologies Site-directed mutagenesis using genetic constructs carrying the CRISPR/Cas system is one of the most effective technologies that are actively used to solve a variety of problems in genetics and plant breeding (Zhu et al. 2020). This approach allows the changing of the structure of the genes of plants, therefore, without introducing foreign genetic information, to change the plant metabolism in the necessary direction (Song et al. 2016). At the same time, in the offspring of mutants, due to recombination, it is possible to select plants that carry the induced mutation but are free from the genetic construct that induced it. As a result, the resulting mutants practically do not carry foreign genetic information; therefore, they are not transgenic organisms. The CRISPR/Cas9 system includes Cas9 endonuclease and guide RNA (gRNA), which directs Cas9 endonuclease to the target nucleotide sequence (Song et al. 2016). The classical variant of the Cas9 nuclease recognizes the NGG-30 Protospacer Adjacent Motif (PAM) sequence adjacent to the target (protospacer), which thus serves as the identification mark of the target in the edited genomic DNA. Cas9 endonuclease produces double-strand breaks in the target DNA located three nucleotides upstream of the PAM sequence. These breaks result in insertions or deletions at the target site, which can lead to frameshifts and null mutations. The CRISPR-Cas system was successfully used to induce mutations in the nucleotide sequence of the 22 kDa signal polypeptide of α-kafirin (Li et al. 2018). Mutations were deletions ranging in size from 1 to 33 nucleotides, and, more rarely, insertions ranging in size from 1 to 16 nucleotides. In the kernels of T1 and T2 plants, a reduced level of α-kafirin and an altered structure of protein bodies were observed; some T2 plants had higher protein digestibility and increased lysine levels. These results indicate the promise of using genome editing techniques to improve the nutritional value of sorghum grain. Edited sorghum plants with mutations in the nucleotide sequences of the β- and γ-kafirin gene have also been reported (Massel et al. 2022). In this study, high efficiency of endogenous U6 promoters (in particular, SbU62.3 promoter) was shown to improve gene editing efficiency in sorghum of up to 90% of experimental plants. A series of binary vectors (pC1-pC4) were created for site-directed mutagenesis of genes encoding α- and γ-kafirins (Gerashchenkov et al. 2021). These vectors contain the Cas9 endonuclease gene under the control of the ubi1 promoter and gRNA nucleotide sequences that are complementary to target sites encoding signal polypeptides of α- and γ-kafirins (the k1C5 and gKAF1 genes, respectively). Using Agrobacterium-mediated genetic transformation, the constructs for site-directed mutagenesis of these genes were introduced into the genome of cv. Avans. Using

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Fig. 2 Cross sections of kernels set on the panicle of the sorghum plant carrying a genetic construct for α-KAFIRIN (k1C5) gene editing target ((b), (c), (d)); ((a) – kernel of original cv. Avans). Вar 1 mm (Amer J Plant Sci, 2021, 12: 1276–1287, with permission)

the pC2 vector (to induce mutations in the k1C5 gene), regenerants (T0) with kernels with modified endosperm texture were obtained, in which a significant reduction in the vitreous endosperm was observed (Fig. 2). This demonstrates the efficiency of genome editing approaches for improvement of nutritional value of sorghum grain. The successful results obtained in these studies demonstrate the validity of the choice of kafirin signaling polypeptides as targets for improving the nutritional value of sorghum grain. However, it is likely that this approach is only one of the ways to use the CRISPR/Cas method to improve the nutritional value of sorghum grain, and other approaches will be used to solve this problem in future experiments.

3.5.4 Synthetic Biology Approaches With the help of synthetic biology approaches, transgenic lines with increased protein digestibility and increased protein content were obtained that contain an artificially synthesized β-kafirin gene (Liu et al. 2019). This gene encoded modified β-kafirin protein with additional proteolytic cleavage sites that should improve its digestibility. Some of the resulting transgenic lines had higher protein content in the seeds (by 11–37%) and a higher digestibility of kafirins (by 11–21%) compared to the non-transgenic original variety. The protein bodies had an irregular shape with invaginations characteristic for highly digestible sorghum lines.

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In order to increase the content of lysine in the grain, transgenic sorghum lines carrying the gene encoding the high-lysine protein of barley, gordotinin, were obtained. Agrobacterium-mediated genetic transformation was used to introduce the gene encoding the high lysine analog (HTl2 protein) of the Hordeum vulgare α-hordothionin protein under the control of the 27 kDa maize γ-zein promoter and terminator into the genome of two sorghum lines, P898012 and PHI391. The A. tumefaciens strain LBA4404 contained a “super-binary” vector with two unlinked T-DNA cassettes. The one cassette contained the lysine-rich HTl2 gene with the second cassette containing a herbicide-resistant bar gene as a selectable marker. The two different T-DNA cassettes in the co-transformation vector allows the segregation of the marker and trait genes in the progeny of the primary transformants. This also allows the elimination of the marker gene and consequently marker-free transgenic plants are obtained. Three high levels of the HTl2 protein were expressed in the grain of the five independent transgenic events that were co-transformed with both genes, with a 40–60% increase of lysine. Provitamin A is very important to human health, but sorghum grain has low levels of β-carotene or provitamin A. In order to increase β-carotene content in sorghum grain, the genetic construct encoding a number of enzymes involved in the carotenoid biosynthesis pathway has been introduced into the genome of sorghum line Tx430 (Che et al. 2016). These enzymes are: 1-deoxyxylulose 5-phosphate synthase, the precursor for carotenoid biosynthesis, Zea mays phytoene synthase 1, and the Pantoea ananatis carotene desaturase, involved in synthesis of phytoene and lycopene, respectively, which are the β-carotene precursors. This introduction resulted in an increase ofβ-carotene levels in mature seeds of transgenic plants of up to 9.1 μg/g (compared to 0.5 μg/g in non-transgenic control seeds). The β-carotene in plants can degrade during storage due to oxidation. To counter this effect, the barley HGGT gene encoding homogentisate geranylgeranyl transferase was introduced into the same genetic construct. Homogentisate geranylgeranyl transferase is involved in synthesis of vitamin E, and this vitamin has strong antioxidant effects. It was found that co-expression of the HGGT gene stacked with carotenoid biosynthesis genes, enhanced all-trans-β-carotene accumulation, and reduced β-carotene oxidative degradation. This led to stable provitamin A levels in sorghum seeds. Field trials of transgenic plants with increased carotene content showed that the all-trans-β-carotene levels were increased by about 20-fold in transgenic lines compared to the non-transgenic controls (Che et al. 2019). This is an example of how effective genetic engineering can be for modifying plant metabolism to meet human needs. Thus, development of genetic transformation techniques allowed the development of sorghum lines with significantly improved protein digestibility, increased content of lysine and other essential amino acids, and β-carotene. However, there still remains a number of unsolved problems. Future research should focus on the development of lines with reduced phytate content, which lowers bioavailability of Fe, Zn, and phosphate, as well as lines which have high protein digestibility of seed storage proteins, and vitreous endosperm. Starch digestibility is also an important question because improving the caloric value of staple food is of great importance. Identification of the naturally occurring allele of pullulanase (SbPUL-RA) – starch

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debranching enzyme – that confers significantly higher in vitro starch digestibility (Gilding et al. 2013) shows that this trait may be improved using a genome editing approach. These innovations, coupled with development of genomics of nutritive traits, will significantly improve the gene pool of existing varieties and hybrids of sorghum and make this important crop more in demand in world agricultural production.

4

Conclusion

Sorghum is an underutilized cereal, well adapted to changing climatic conditions, which are causing increased temperatures and an increased frequency of drought spells. The inclusion of especially whole grain sorghum in the diet may help avoid chronic lifestyle illnesses. The inclusion of sorghum grain as a regular part of the human diet has the potential to reduce the risk of cardiovascular diseases, some types of cancer, and type II diabetes. Sorghum has highly resistant starch, a high fiber content, high levels of bioactive compounds, and kafirin protein with potential benefits. The bioactivity of sorghum grain is influenced by phenolic compounds such as phenolic acid, flavonoids, stilbenes, and tannins, and it is rich in procyanidins (condensed tannins) and 3-deoxyantocyanidins. Sorghum tannins, also called proanthocyanidins, have shown anti-inflammation and anticancer properties. Sorghum also contains B-complex vitamins, fat-soluble A, D, E, and K vitamins, and minerals such as potassium, phosphorus, magnesium, and zinc. The generally high antioxidant activity of sorghum grain could contribute towards combating diseases associated with oxidative stress. Sorghum grain also has cholesterollowering and antimicrobial properties. It also was shown to improve glucose metabolism, which could positively affect diabetes. Sorghum is gluten-free with a high fiber content, which could benefit celiac disease patients. Sorghum could therefore be included in functional foods as a source of bioactive ingredients. Of the bioactive compounds in sorghum, phenolic compounds have been the main focus for research, so there is still a lot that is not known about the other compounds. With developing technology, new bioactive compounds may also be detected. All the studies reported so far found significant natural genetic variation for measured bioactive compounds, although the growing environment also consistently had a large influence on the expression of compounds. As was reported above, there are many untapped genetic resources available in the form of germplasm collections, which can be screened for naturally high occurrence of bioactive compounds. Significant research has been done on the genetics of kafirin protein indigestibility and to a lesser extent on compounds like carotenoids. There is, however, a large gap in the knowledge of the genetics underlying the expression of other bioactive compounds in sorghum. Linkage and association mapping, GWAS and mutant libraries have been used to research the genetic architecture of especially adaptive traits, and yield and related traits, and genetic engineering has been applied to contribute to improved protein indigestibility and carotene levels in sorghum. There is, however, scant data on the genetics of seed composition, bioactive compounds, and traits linked to the

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nutritional value of sorghum grain in general. When more is known about the genes linked to nutraceuticals and the gene action involved in expression of nutraceuticals, conventional breeding can be used to select and cross parents with good nutraceutical content, markers can be developed for marker-assisted selection, and genomics and genetic engineering could be used to improve nutraceutical content. Sorghum research is lagging behind that of other commercial crops such as maize, rice, and wheat. Likewise, research on the nutritional value of grains is lagging behind research on yield and yield-related traits, adaptive traits, and disease resistance. Databases should be generated to integrate all available information on seed nutraceutical and other nutritional components, which can be used by the sorghum community for sorghum improvement and genetic studies.

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Breeding Efforts on Grain Micronutrient Enhancement in Pearl Millet Mahalingam Govindaraj and Mahesh Pujar

Contents 1 2 3 4 5 6

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pearl Millet and Selected Nutrition Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pearl Millet Nutrition Profile at a Glance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Pearl Millet Breeding at ICRISAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genesis of Targeted Breeding for Nutrition Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Requirement for Nutrition Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Genetic Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Phenotyping for Grain Nutrition Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Nutrition Trait Genetics and Relationship with Agronomic Traits . . . . . . . . . . . . . . . . . 6.4 Pearl Millet Breeding Priority and Product Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Status of Biofortified Hybrids and Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 NARS Breeding Lines and Hybrids Characterized for Fe/Zn Content . . . . . . . . . . . . . . . . . . . 8.1 Commercial/Released Hybrids/OPVs Characterized for Fe/Zn Content . . . . . . . . . . . 8.2 Elite Breeding Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 G
E Effect on Grain Micronutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The increasing population growth essentially requires more diverse food in the future. Pearl millet is a major source of diets that provides energy and nutrition for millions of people living in India and sub-Saharan Africa (SSA). Malnutrition prevalence is estimated at 2 billion people globally affected. Malnutrition is highly prevalent in India and SSA, and progress in addressing them through M. Govindaraj (*) HarvestPlus Program, Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Cali, Colombia e-mail: [email protected] M. Pujar Crop Improvement Theme, Research Program-Asia, at ICRISAT, Hyderabad, India © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_7

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various recurrent costing interventions is slow. Biofortification is a nutritiondefined cost-competitive and sustainable approach for combating malnutrition among resource-poor households in low- and middle-income countries. Enhancing grain iron (Fe) and zinc (Zn) contents is prioritized for major staples including pearl millet as these two micronutrients are predominately deficient in human populations. HarvestPlus-supported biofortification pearl millet breeding globally accomplished significantly higher levels for Fe (80 mg kg1) and Zn (60 mg kg1) in germplasm, breeding populations, and hybrid parents using conventional breeding approaches. To date, 12 biofortified hybrids are released and are benefiting more than 120,000 households. Genetic gain for Fe and Zn is gradually increased (42 mg kg1 to >75 mg kg1 Fe; 30 mg kg1 to 50 mg kg1 Zn) and is higher than yield. Average levels of Fe (42 mg kg1) and Zn (31 mg kg1) in commercial hybrids and increased climate variability for pearl millet-growing areas will affect nutrition levels besides diminishing yield potential. Therefore, breeding for yield and nutrition should go hand in hand with mainstreaming nutrition. The use of biofortified cytoplasmic male sterile (CMS) lines and restorers, breeding pipelines in crossing, and application of improved breeding methods through precision phenotyping, genomic selection, and speed breeding options can expedite mainstreaming progress in pearl millet. Bioavailability studies confirm the improved human health significance of biofortified varieties and hybrids. Accelerated public-private partnership is essential in achieving higher nutrition in competitively yielding hybrids. Consumer preferences for nutritious millet grains have increased, thus prospecting nutrient-dense varieties for improved human nutrition in India and SSA. Keywords

Biofortification · Micronutrients · Iron · Zinc · Genomics · Mainstreaming

1

Introduction

Over 2 billion people globally are affected by at least one or more micronutrient deficiencies, which means that one-third of the global population is at risk of essential micronutrient deficiency (WHO 2019). The increasing population growth essentially requires nutrition-rich food besides energy in the future for their health and higher productivity. Pearl millet is a major source of diet that provided energy and nutrition for millions of people in India and sub-Saharan Africa (SSA) (Serba et al. 2020). Pearl millet is generally considered a nutrition-rich crop, but facts are rapidly changing owing to pearl millet breeding entirely focused on yield improvement in the last 30 years – will have a nutrient loss like other cereals. Malnutrition is preventable since it is the consequence of daily dietary nutrition deficiency. About 40% of Indian children under 5 are stunted, and 50% of women of reproductive age are anemic (NFHS, 2015–2016), whereas 24.1% of the population is malnourished in SSA (https://www.actionagainsthunger.org/africa-hunger-relief-facts-charity-aid).

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Biofortification refers to a process of breeding staple food crops with higher micronutrient content in edible parts and is proven as an essential strategy in addressing malnutrition that is sustainable and cost-effective (Bouis et al. 2011). HarvestPlus program of the CGIAR supported many CGIAR and NARS centers for biofortification breeding targeting iron, vitamin A, and zinc with the main crops being beans, sweet potato, cassava, maize, rice, banana, wheat, and pearl millet (Lowe et al., 2022). The HarvestPlus-supported targeted biofortification breeding projects at ICRSIAT explored germplasm screening and investigated the feasibility of biofortification in pearl millet and aimed to support mainstreaming breeding and its goals with novel traits (Rai et al. 2014). ICRISAT pearl millet breeding program investigated the genetic variability of various grain quality traits (iron, zinc, ß-carotene) during the inception of biofortification projects. Preliminary research results revealed inadequate variability to undertake genetic improvements for ß-carotene; thus, focus was directed to Fe and Zn improvement (Rai et al. 2012b). The justification for the pearl millet biofortification initiative was very clear on millet consumer health and appropriate for additional resource mobilization for more nutrient-specific germplasm development and supporting variety/hybrid parent research in India and Africa. The major reasons for pearl millet biofortification investment are as follows: (i) more than 60% of the population in arid and semiarid tropics is malnourished, (ii) inadequate micronutrient levels among commercially grown pearl millet hybrids, and (iii) adequate genetic variation for micronutrients in breeding population and germplasm accessions. Pearl millet is cultivated close to 30 million ha globally covering five continents, viz., Asia, Africa, North America, South America, and Australia. Despite the fact that India (8 million ha) and Africa (about 18 million ha) contribute the majority of crop area (Yadav and Rai 2013). With 8.61 million tonnes, India is the world’s largest producer of pearl millet (Directorate of Millets Development 2020). The major breeding goal of the ICRISAT pearl millet program is to (i) provide trait-specific germplasm and improved breeding lines and parents to NARS and other stakeholders; (ii) cultivate inter-institutional collaboration integrated conventional, participatory, and genomics-assisted breeding methods to develop widely adapted varieties and hybrid parents; and (iii) provide need-based capacity building on advanced tools and techniques. Although ICRISAT pearl millet breeding was established in the 1980s and the national program in the Indian Council of Agricultural Research (ICAR) in 1965 in India, no serious efforts were made to improve grain nutrition in pearl millet, while just a few attempts were made for screening germplasm before its inception of CGIAR biofortification program in 2005. Screening efforts found highly significant and larger genetic variation among breeding populations (30–70 mg kg1), hybrid parents (25–90 mg kg1), and germplasm (28–120 mg kg1) at ICRISAT and NARS. On the other hand, negative correlations reported between micronutrient content and grain yield hindered the commercial breeding prospects. These studies’ materials are highly selected for yield traits and not bred for micronutrients; therefore, there is no surprise in the observed trend. Some studies indicated that nonsignificant correlations bring hope for concurrent genetic improvement. In addition, a significant positive association between

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Fe/Zn and grain yield has been reported suggesting the feasibility of breeding competitive biofortified varieties and hybrids in the future. Therefore, a biofortified cultivar with improved mineral content is easily accepted by consumers as it does not require a change in dietary habits. Biofortification programs in general target to improve the micronutrient content of those cultivars which have preferred agronomic and consumption traits like grain yield. HarvestPlus has initiated the development and promotion of many biofortified cultivars with improved micronutrient content across different food crops including pearl millet (Yadav et al. 2017). Systematic deliberation with ICAR, focusing on nutritional improvement besides yield improvement, was also mandatory in pearl millet. This landmark decision was taken by the pearl millet researchers to include iron and zinc concentrations as one of the promotion criteria for promoting entries in the national coordinated trials during the 52nd Annual Group Meeting of ICAR-AICRP on Pearl Millet at PAU, Ludhiana, on April 28, 2017 (Satyavathi et al. 2021). To date, 12 biofortified pearl millet cultivars have been released in India and West Africa (Govindaraj et al. 2019) and reached more than 120,000 households (https://www.cgiar.org/innovations/highiron-pearl-millet-for-better-health/).

2

Pearl Millet and Selected Nutrition Traits

Pearl millet has significant potential as food, feed, and fodder crop in subsistence farming in the semiarid tropics. It can produce grains with high nutritive value even under hot, dry conditions on infertile soils of low water-holding capacity, where other cereal crops fail (Khairwal and Yadav 2005). The energy value of pearl millet grain is relatively higher compared to maize, wheat, or sorghum (Hill and Hanna 1990). Globally, pearl millet is cultivated on about 27 m ha of this, and India annually cultivates 9.3 m ha and produces about 9.5 m t. Pearl millet genetic improvement in India and SSA is critical for contributing to food production in semiarid tropic regions. There are many significant milestones achieved over the five decades. For instance, grain yield significantly surpassed from 4.5 kg/ha/yr (pre-green revolution [GR] era) to 31.1 kg/ha/yr (post-GR era) that accounts for a 188% increase in productivity since the green revolution (the 1970s) in India (Yadav et al. 2019). Crop improvement efforts in enhancing further grain and fodder with biotic and abiotic tolerances are being the topmost priority in both public and private sector breeding programs. The expansion of pearl millet uses to forage and dry fodders in drylands captivated the improvement in forage and fodder quantity per unit area. This supports food for humans and fodder for livestock in subsistence farming practices. Therefore, it is very clear that smallholder farming is dominant in semiarid regions and continues to be overwhelmed by numerous issues including poverty and malnutrition (Ryan and Spencer 2001; Sharma et al. 1996: Dar 2011). In semiarid tropic regions, household income and food expenditure play a significant role in determining family nutritional status (Padmaja et al. 2019). Addressing malnutrition in semiarid tropics where poverty and malnutrition persist together is not a supreme task of crop improvement history. The inception of biofortification

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initiatives demonstrated the nutrition breeding feasibility and sustainability of nutrition supply to rural remote households. Biofortification breeding in pearl millet is a recent development and was led by ICRISAT in partnership with NARS in India and SSA. In the search for nutritional functional properties from pearl millet grains, many traits are randomly reported in the past. However, their lower levels, less relevance to predominant nutrient deficiency among populations and nonsignificant genetic variations within crop genetic resources, diverted the breeding focus of Fe and Zn and some extent to proteins (Govindaraj et al. 2022). Pearl millet has an average of 11–12% proteins with moderately balanced amino acids (Shobana et al. 2013). The contribution of pearl millet to the total nutrient intake (Fe and Zn) from all foods widely varied across rural India; however, in some parts of rural India (Rajasthan, Maharashtra, and Gujarat), contribution of pearl millet to micronutrient (Fe and Zn) intake is higher. For instance, in these regions, pearl millet contributes 19–63% of the total Fe intake and 16–56% of the total Zn intake (Parthasarathy Rao et al. 2006). Therefore, it would be highly rewarding in providing additional Fe to their regular diet. Moreover, as the micronutrient requirements in human and plant nutrition are similar, genetic enhancement for grain minerals could improve human nutrition as well as farm productivity (Ma 2007). Today, addressing malnutrition is one of the priorities of the government of India, and pearl millet is one of the target crops in its NutriFarm initiative. Furthermore, a recent clinical study reveals that the bioavailability of both Fe and Zn from biofortified pearl millet is more than adequate to meet the physiological requirements for these micronutrients for children under 2 years old and young women (Kodkany et al. 2013; Cercamondi et al. 2013). Therefore, those farmers who grow biofortified pearl millet will have easy access to nutritious foods with minimal investments for their family’s well-being, and surplus productions can be marketed for greater impact in millet-consuming communities. Therefore, to meet the daily energy and nutrition requirements, dietary diversity and pearl millet biofortification are very much closer and could prove to be an essential strategy for combating micronutrient malnutrition in India and SSA in the future.

3

Pearl Millet Nutrition Profile at a Glance

Overall mineral nutrition of pearl millet is generally higher than that of other major cereals such as rice, wheat, and maize (Adeola and Orban 1995). Deep looking into the differences among the commercial and breeding lines of pearl millet collection will be much higher and may exceed two- to three fold variation for most nutrition traits. A national collection of pearl millet varieties, hybrids, and key germplasm under ICAR-All India Coordinated Research Project on Pearl Millet (AICRP-PM) screened for major nutrition recently (Goswami et al. 2022). This collection consisted of 87 genotypes (mixture of varieties, hybrids, and germplasm). The starch content ranged from 50 to 63 g/100 g. Amylose content varied from 19 to 28 g/100 g; glucose and sucrose content varied in very narrow variation ( P > Mg > Ca > Fe > Zn > Na > Mn. The results also revealed that the variability of P, K, Ca, Mg, Fe, Zn, Mn, and Na in parents/inbred trials was particularly larger than those found in the hybrids suggesting scope for improvement in commercial hybrids in the future otherwise underutilized this nutrition potential in presently grown pearl millet varieties and hybrids (Govindaraj et al. 2022). Therefore, untapped commercial feasibility prospects for genetic enhancement of these grain minerals in pearl millet along with productivity traits would greatly enhance pearl millet as the cheapest source of nutrition supply in drylands.

4

Pearl Millet Breeding at ICRISAT

Pearl millet remains one of the important staple crops in India after rice and wheat. The breeding program at ICRISAT generally develops open-pollinated varieties (OPVs) and hybrid parents (inbred lines) to produce hybrids which are the predominant cultivar type in India that covers about 5–6 m ha spread across three pearl millet cultivation zones (A, A1, and B) of India. All these three zones are differentiated by a range of factors including plant types and environmental variables such as soil type, rainfall, and farm inputs. For example, zone A has >400 mm annual rainfall, rainy season cultivation, and sandy loam soil; zone A1 has 0.98; Fig. 2) between ICP and XRF values, both for Fe and Zn content (Rai et al. 2012b; Paltridge et al. 2012; Govindaraj et al. 2016b). Setting up this small machine requires less space, with no recurring expenditure, and it provides nondestructive analysis of 250–300 samples per day at the cost of 98% homozygosity before multi-year yield assessment at multiple sites. The desirable 100% homozygosity can be achieved in a much shorter time by implementing doubled haploid technology (Khound et al. 2013; Santra et al. 2019). Only a few

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reports on successful tissue regeneration have been reported in proso millet. In 1982, Heyser and Nobors reported successful callus induction and shoot regeneration from a variety of explants by manipulating auxin levels in Linsmaier and Skoog (L and S) medium (Heyser and Nabors 1982). Bobkov and Suvorova (2012) studied the efficiency of anther culture technique in proso millet for embryogenic callus induction and regeneration. Heat (32  C) and cold (4  C) were observed to successfully induce callus formation and regeneration of the explants (Bobkov and Suvorova 2012). For several decades, genetic engineering has been used to introduce foreign genes expressing novel traits into a host genome or to knock out genes with deleterious effects. Genetic improvement of crops through genetic engineering relies on the development of an efficient regeneration method and a robust transformation system (Kumar et al. 2016). There has been no report on the generation of transgenic proso millet via genetic transformation so far. The DH and genetic engineering technologies can be used for developing proso millet varieties enriched with health-promoting bioactive compounds and no or minimum antinutrients. Therefore, more studies on efficient tissue culture and transformation systems are warranted for facilitating genetic engineering-assisted genetic improvement of proso millet.

7

Omics for Improving Grain Nutritional Quality

Biology works as a “system” rather than as an individual part separately. All the parts of biology work together in harmony to manifest overall biological functions. Many biochemical compounds are involved in this intrinsic process. Similarly, all the nutrients and antinutrients in food work together in harmony to manifest their effect on human health and nutrition. Therefore, it is very important to study proso millet seed nutrients quality and quantity, genes, biosynthesis pathways, regulation, and interactions together rather than separately. That means all aspects of proso millet seed nutraceuticals must be studied following the “omics” approach. The term “neutrocetomics” is used to indicate the combined study of nutraceuticals and omics. Proso millet being a minor crop, its “omics” areas of research are not as rich as other major crops such as corn, wheat, rice, and soybean. However, in recent years a lot of omics research has been done in proso millet, and more is being conducted due to its increasing importance for human health. Details of proso millet “omics” research were published in a recent comprehensive review paper (Khound and Santra 2020). The following section summarizes various fields of “omics” in proso millet and their relevance to its “nutraceutomics” (Fig. 3).

7.1

Genomics

Genomics is the branch of omics that tackles large-scale studies on the structural and functional aspects of the genome to understand the genetic and molecular underpinning of various biological processes. Initial genomic studies were primarily focused on genome size and physical as well as genetic mapping of organisms. Next-

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Fig. 3 Schematic representation of the applications of traditional breeding methods and tools, as well as omics-based and post-genomic breeding strategies to the genetic improvement of proso millet

generation sequencing (NGS) marked a new era of genomics by enabling researchers to sequence, assemble, and analyze the genomes of important crops at lower costs and in a shorter time (Khound and Santra 2020).

7.1.1 Molecular Markers Molecular markers are important genomic resources that have been widely used in genetic mapping, genetic diversity, and taxonomic and population genetic studies of crops. A limited number of molecular markers were developed in proso millet as this crop is grossly under-researched. The molecular markers identified in proso millet so far include amplified fragment length polymorphism (AFLP), random amplified polymorphic DNA (RAPD), inter-simple sequence repeat (ISSR), cleaved amplified polymorphic DNA (CAP), simple sequence repeat (SSR), and single nucleotide polymorphism (SNP) markers. These molecular markers were primarily used for evaluating the genetic diversity of the proso millet germplasm (Santra et al. 2019). SSRs are preferable for genetic studies as they are abundant, evenly distributed, multi-allelic, codominant, highly polymorphic, easy to score, and highly reproducible (Khound and Santra 2020). The earliest SSR-based genetic studies were conducted using SSRs from other species such as rice, wheat, oat, barley, and switchgrass. The first proso millet-specific SSRs were identified by Cho and coworkers (Cho et al. 2010). Twenty-five polymorphic SSRs were developed from the genomic DNA of 50 diverse proso millet genotypes. These SSRs were used to evaluate the genetic diversity of Chinese proso millet accessions (Liu et al. 2016).

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SNP markers are ideal for genetic studies, genetic map constriction, and genomic selection as they occur abundantly in the genome (Khound and Santra 2020). These markers are especially well suited for constructing linkage maps as they are costeffective, high-throughput, and more efficient compared to other DNA markers (Rajput et al. 2016). Several reports on SNP identification in proso millet have been published. Rajput et al. identified 833 high-quality biallelic genotype-bysequencing (GBS)-SNPs from genotyping of 93 recombinant inbred lines (RILs). These GBS-SNPs were used for constructing the first proso millet linkage map (details later in the quantitative trait locus (QTL) mapping section) (Rajput et al. 2016). Wang and her coworkers evaluated the allelic diversity of two waxy genes, viz., Wx-L and Wx-S, in 132 proso millet accessions from 12 provinces of China. In their study, Wang et al. (2018) identified six SNPs at the Wx-L locus after sequencing the PCR amplicons of all the accessions. Johnson and his team used GBS to generate 1882 filtered SNPs to conduct genome-wide population genetic studies in proso millet. The SNP markers were found to accurately represent genetic variation within the population (Johnson et al. 2019). In 2021, Boukail et al. (2021) developed 2412 SNPs from 88 proso millet accessions with RAD-seq. The identified SNPs were used for conducting GWAS to detect marker-trait associations for several agronomic and seed morphology traits (more details are covered in Sect. 8) (Boukail et al. 2021). In another recently published report, 126,822 filtered SNPs were identified using specific-locus amplified fragment sequencing (SLAF-seq) of 106 accessions (Li et al. 2021). More recently, Khound et al. (2022) developed 972,863 highquality biallelic SNPs from low-pass genome sequencing of 85diverse proso millet genotypes of the USDA gene bank. They employed those SNPs to study the population structure and phylogenetic relationships among the genotypes (Khound et al. 2022).

7.1.2 QTL Mapping Quantitative trait locus (QTL) mapping is routinely used in many crops for detecting quantitative trait loci (QTLs) associated with key traits due to the abundance of versatile DNA markers and statistical models and methods. QTLs for a wide array of traits have been reported in many major and minor crops including wheat, rice, maize, sorghum, millet, amaranth, quinoa, oat, and rye (Yabe and Iwata 2020). Among millets, pearl millet and foxtail millet have the major share of published reports on QTL mapping. In proso millet, very little research has been done on genetic mapping of QTLs compared to major crops such as rice, wheat, maize, soybean, and sorghum. This is possibly because of the minor crop status and inadequate resources available to proso millet geneticists. The first-ever genetic linkage map of proso millet was published in 2016 by Rajput et al. They used 833 GBS-SNPs and 93 RILs. Several QTLs and linked SNP markers for a few morpho-agronomic traits were identified (Rajput et al. 2016). However, no QTLs for proso millet seed components such as starch, protein, minerals, vitamins, and other bioactive compounds have been identified in proso millet to date.

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7.1.3 Whole-Genome Assembly Developing a whole-genome assembly (WGA) is a crucial step in genome-wide molecular studies as this creates opportunities for exploring complex molecular structures and functions in an organism. Information on genome assembly is an invaluable resource for genomic-assisted breeding for crop improvement. Proso millet was the fourth millet to have a published whole-genome assembly after foxtail millet, pearl millet, and finger millet (Khound and Santra 2020). In 2019, Zou et al. developed the complete proso millet genome sequence using various NGS tools. They also identified 55,930 protein-coding and 339 microRNA genes (Zou et al. 2019). In the same year, Shi et al. reported a near-complete assembly of the proso millet genome. The authors generated 18 super scaffolds covering approximately 96% of the estimated genome. Moreover, they were able to annotate 63,671 proteincoding genes in the proso millet genome (Shi et al. 2019). 7.1.4 TILLING Another modern approach that could be applied for improving grain nutritional quality of proso millet is the TILLING (targeted induced local lesions in genomes) method. This is an advanced method of detecting beneficial mutations or alleles that allows rapid identification of induced gene mutations within a mutagenized population via heteroduplex analysis. The initial step of TILLING involves creating a mutagenized population, which is subsequently assessed for detecting useful gene mutations that could be linked to important phenotypes. The mutations within the mutagenized population are usually detected by one of the three methods, viz., LI-COR method (uses CEL 1 enzyme), high-resolution melting (HRM) method, and NGS method. TILLING has been used for detecting useful mutations in a wide array of crops including wheat, rice, sorghum, and maize (Irshad et al. 2020). Tilling has been successfully employed to identify mutations in genes associated with starch synthesis, plant architecture, and disease resistance in several crop species. Another related method, namely, EcoTILLING, is used to detect naturally occurring polymorphisms within a population. The polymorphisms identified could be used to study the phylogenetic diversity within the population. This technique can also be used to detect novel allelic variations that can be exploited for genetic improvement. EcoTILLING has been utilized in different crops including Arabidopsis, chickpea (seed weight), wheat (disease susceptibility), rice (drought tolerance, starch synthesis), and soybean (seed protein) (Irshad et al. 2020). 7.1.5 Allele Mining A large number of beneficial alleles are present in plant genetic resources, which remain unutilized as they were abandoned during evolution and domestication. Introgression of these natural genetic variations has the potential to improve the performance of available cultivars. The recent surge of genomic data accelerated the discovery and annotation of novel genes and loci linked to essential agronomic traits in many crop species. The idea of identifying alleles in the annotated genes led to the concept of allele mining in plants. Allele mining refers to the approach of dissecting

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naturally occurring variations at candidate genes or loci associated with major agronomic traits with the help of modern genomic tools (Kumar et al. 2010). Two primary approaches for identifying alleles are EcoTILLING and sequence-based allele mining. As discussed in the previous section, EcoTILLING is used to identify naturally occurring allelic variants present in the primary and secondary gene pools. In a sequence-based approach, alleles of diverse genotypes are amplified by PCR and subsequently sequenced. Allele mining was used in identifying alleles for important seed quality traits including Amy32b(α-amylase gene) and Gpc-B1 (gene for grain protein content) in barley, wx locus (waxy gene) in rice, and Wx-A1 (waxy gene) in wheat (Kumar et al. 2010). The prospect of using allele mining for detecting novel alleles of genes is relatively unexplored in millets. The availability of wholegenome assemblies, high-quality molecular markers, and the gradually reducing cost of sequencing is expected to result in more studies for identifying novel genes and loci. That would encourage more efforts for the mining of candidate genes for some key agronomic and grain quality traits leading to the detection of useful alleles for application in molecular breeding.

7.2

Transcriptomics

A handful of reports on transcriptome studies investigating biological processes have been published in proso millet. Yue et al. (2016) used Illumina sequence reads from two proso millet accessions, viz., Yumi No.2 and Yumi No.3, to assemble a proso genome transcriptome. From the 113,643 unigenes assembled, 62,543 contigs were assigned to 315 gene ontology (GO) categories. Additionally, 15,514 unigenes could be mapped into 202 Kyoto Encyclopedia of Genes and Genomes (KEGG) clusters, and 51,020 unigenes were mapped to 25 clusters of orthologous groups (COG) categories. The most represented KEGG pathways included metabolic pathways (25.65%), biosynthesis of secondary metabolites (10.71%), and biosynthesis of amino acids (3.57%) (Yue et al. 2016). In 2017, Hou et al. developed a transcriptome assembly using Illumina sequence reads from a single genotype of proso millet named Neimenggu-Y1. They were able to identify 25,341 unigenes out of which 5170 (20.4%) could be mapped to 146 KEGG pathways. GO annotation with 2936 tissue-specific genes resulted in three subcategories- biological processes, molecular functions, and cellular components (Hou et al. 2017). Zhang et al. (2019) published a comparative analysis of transcriptome associated with drought tolerance in two genotypes, viz., Neimi 5 and Jinshu 6. Drought stress resulted in 833 and 2166 DEGs in Jinshu 6 and Neimi 5, respectively. Some of the DEGs could be mapped to some key KEGG pathways including carbon metabolism, phenylpropanoid biosynthesis, and amino acid biosynthesis (Zhang et al. 2019). The unigenes that were mapped to the key KEGG pathways in the above reports should be explored further to identify their roles in those pathways. This information could be useful in targeting specific genes for enriching proso millet with useful nutraceuticals or inhibiting the biosynthesis of antinutrients.

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Proteomics

There is an abundance of reports on proteomics research for the major crops including rice, corn, soybean, wheat, and potato. However, like other omics disciplines, the number of published reports pertaining to proteomics in proso millet and other millet is very meager (Khound and Santra 2020). Perhaps the first proteomics analysis in proso millet was done on a 2500-year-old starch food in China. Comparative proteomics analysis between the ancient sour dough bread and a few other reference cereals identified proso millet and barley as the ingredients of the ancient bread (Shevchenko et al. 2014). In 2017, Roy and co-workers reported the seed protein analysis of four Korean proso millet varieties using two-dimensional (2-D) electrophoresis and mass fingerprinting to map the seed proteins and determine their functional properties. They detected 1152 differentially expressed proteins, out of which 26 reproducible proteins were further analyzed using matrix-assisted laser desorption/ionization time-of-flight/time-offlight mass spectrometry (MALDI-TOF-TOF/MS). Two of the 26 proteins were found to be upregulated in all the cultivars, while 13 were upregulated and 11 were downregulated in 2 proso millet cultivars. The authors opined that the differential expression of the proteins in the four proso millet cultivars was possibly varietyspecific (Roy et al. 2017).

7.4

Metabolomics

There are only a couple of available reports on the metabolomics of proso millet. The first published study on proso millet metabolomics used gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) to evaluate gain quality. Kim et al. (2013) studied the primary metabolites and phenolic acids of the matured grains of three Korean proso millet varieties, viz., ‘Joongback’, ‘Joongjuk’, and ‘Hwangguem’. They were able to identify 48 metabolites from the grains, which included 43 primary metabolites and 5 phenolic acids. The mature grains of the variety ‘Joongjuk’ contained significantly higher levels of phenolic acids than the other two varieties. This makes this variety a suitable candidate for further evaluations and genetic improvement as a nutraceutical (Kim et al. 2013). In a relatively recent publication, 172 metabolites and 3 cooking quality traits were compared between conventionally and organically grown seeds of two proso millet varieties. There was no difference in the metabolite profiles between the conventionally and organically grown gains, except in the levels of some carbohydrates such as glucose and fructose, which were higher in the organically grown grain. The variations observed in the metabolite content could be primarily attributed to the variety (Liang et al. 2018a). These findings emphasize the importance of variety selection for developing proso millet varieties for nutraceutical use.

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Phenomics

A phenome can be described as the complete set of phenotypic traits expressed by a cell, tissue, or organism, and the field of studies on the phenome is known as phenomics. Establishing the relationship between the genotypes and phenotypes is a major breeding objective of any crop improvement program. Traditional phenotyping approaches are usually laborious, time-consuming, expensive, and mostly destructive (Santra et al. 2019). It is important to determine more phenotype-to-genotype relationships to develop reliable predictive models for predicting a full array of phenotypes of a genotype (Gustin and Settles 2015). In recent years, high-throughput phenotyping techniques and tools including high-resolution imaging, spectroscopy, robotics, and powerful algorithms have been developed to push plant phenotyping to the next level. Different high-throughput phenotyping approaches have been used to study a variety of phenotypic traits such as plant growth, biomass, leaf morphology, maturity, and nutrient status (Santra et al. 2019). To the best of our knowledge, the first-ever report on highthroughput phenotyping in proso millet was reported by Zhao et al. who used UAV-based imaging for heading percentage detection in proso millet (Zhao et al. 2022). A more niche area of phenomics, for example, “seed phenomics,” could be developed in proso millet to specifically study various seed characteristics (Gustin and Settles 2015). This will require the integration of various imaging technologies, spectroscopy, and multiple omics such as genomics, transcriptomics, proteomics, and metabolomics. Various imaging techniques and rapid, nondestructive spectroscopic techniques, such as near-infrared (NIR) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy, are routinely used to determine various seed traits such as shape, size, color, and chemical composition. To the best of our knowledge, there is no report or ongoing research on proso millet seed phenome, which is very important for genetic improvement of nutraceuticals values in proso millet.

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Post-Genomic Approaches for Improving Seed Nutritional Quality

The following sections summarize the current status of proso millet “omics” resources available to the scientists working in the field of proso millet nutraceutomics. The following sections address post-genomic omics approaches for genetic manipulation of proso millet seed nutraceuticals.

8.1

Genome-Wide Association Studies (GWAS)

Genome-wide association study (GWAS) or association mapping (AM) involves the detection of an association between DNA marker(s) and a trait of interest based on the principle of linkage disequilibrium (LD). This is achieved through

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large-scale genotyping of germplasm panels or breeding populations exhibiting contrasting phenotypes across different environments. Several GWAS have been conducted in millets to uncover the marker-trait association for some important traits. However, only a few reports of GWAS for seed nutritional traits are available. The only available report on GWAS in proso millet to date was published in 2021 by Boukail et al. They used a global collection of 88 varieties and landraces to identify marker trait associations (MTAs) for seed morphological traits. They identified 2412 high-quality SNPs using restriction site-associated DNA sequencing (RAD-seq). These SNPs were used for GWAS for seed traits, such as seed length (SL), seed width (SW), seed perimeter (SP), and seed color (RGB) as well as agronomical traits. They identified MTAs for the seed and agronomic traits (Boukail et al. 2021). The SNPs that were found to have a strong association with the agronomic and seed traits could be strong candidates for marker-assisted selection (MAS) in proso millet breeding programs. Having said that, no report on GWAS for nutraceutical traits is available in proso millet yet. This warrants the initiation of genome-scale studies to identify MTAs for some key seed quality traits to accelerate the development of proso millet varieties with impeccable agronomic qualities and healthy seed components.

8.2

Genomic Selection (GS)

Genomic selection (GS) is the breeding approach of using genome-wide highdensity markers to facilitate rapid selection of suitable candidates for breeding (Srivastava et al. 2020). GS is still in the nascent stage in millets as very few GS studies have been conducted so far due to the limited availability of genomic resources. Varshney et al. (2017) utilized whole-genome resequencing (WGRS) data for performing GS to predict the grain yield of pearl millet under four different stress scenarios across environments. They used to analyze the grain yield of 64 hybrids with 302,110 SNPs to identify promising hybrid combinations for hybrid production (Varshney et al. 2017). In another study, Liang and his coauthors (2018b) evaluated four genomic selection schemes using two genotyping strategies, namely, RAD-seq and tunable genotyping by sequencing (tGBS) in pearl millet. The authors observed that for traits with significant mid-parent heterosis, the inbred phenotypic data moderately improved genomic predication of the hybrid genomic estimated breeding values when the trait values of the inbred and hybrid lines were scored relative to the mean trait values of the corresponding populations (Liang et al. 2018b). Similar GS studies can be conducted in proso millet for major morphoagronomic and seed quality traits to accelerate genetic improvement of breeding populations in a time-efficient and cost-effective manner.

8.3

Genome Editing

Genome editing is a relatively newer technique adopted by plant breeders to develop new and improved varieties of crops. Rather than introducing transgene(s)

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randomly into the host genome, genome editing used sequence-specific nucleases (SSNs) to induce targeted and precise nucleotide sequence changes to the genome (Santra et al. 2019). Genome editing tools have been successfully used to introduce genes into major cereals including rice, wheat, and maize (Ceasar 2022). The most commonly used genome editing tools are clustered regularly interspersed short palindromic repeats-CRISPR-associated nucleases (CRISPR-Cas) system, transcription activator-like effector nucleases (TALENs), and zinc-finger nucleases (ZFNs) (Santra et al. 2019; Ceasar 2022). There are numerous reports on genome editing in major cereals, especially rice, wheat, maize, and barley. However, genome editing is still a relatively unexplored territory in millets. One example of the successful use of genome editing tools in improving grain quality is the knock-out of three key genes associated with phytic acid (PA) biosynthesis in maize. PA naturally occurs in the grains of many cereal crops, including proso millet. It is considered an antinutrient as it is largely indigestible and may cause environmental pollution. TALEN and CRISPR-Cas9 systems were used to induce mutations in the genes, viz., ZmIPK, ZmIPK1A, and ZmMRP4, encoding enzymes that catalyze three steps in PA biosynthesis (Liang et al. 2014). There are only two reports on successful CRISPR-Cas9-mediated genome modification in foxtail millet (Ceasar 2022). Similar strategies can be implemented in proso millet for improving grain quality by reducing the levels of antinutrients and enriching with health-promoting compounds such as carotenoids. However, reliable, reproducible, and robust micropropagation and transformation systems need to be developed for this crop in order to accomplish this.

9

Conclusion and Future Prospects

Compared to the major crops such as rice, wheat, corn, and soybean, there is a dearth of genomic resources available for the genetic improvement of proso millet. Especially, little to no progress has been made in exploring genes or QTLs linked to grain nutraceutical traits. Therefore, there is a need for devising strategies for developing and harnessing genomic resources in the identification of genes and QTLs associated with seed components in proso millet. This will facilitate omics-assisted breeding of this ancient crop thereby enabling rapid and precise genetic improvement for various agronomic and seed quality traits. Therefore, the global millet researchers must work together to take advantage of such technological advancement in the “omics” research to advance the field of “nutraceutomics” in proso millet. Interdisciplinary research, extension, and promotion are essential for using proso millet in the human food market. The future prospects of proso millet along with other climate-resilient millets are vast for the food and nutritional security of the global population in the current century and future. The global climate is deteriorating exponentially with the acute pressure of population increase and farmland reduction. All seven millets have great

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potential to address the mammoth global challenge. A strong collaboration among the millet geneticists and breeders across the globe will be mandatory for the successful implementation of the “omics” in proso millet “nutraceutomics” research and applications for human health and nutritional security in the changing climate, especially in the climate-fragile countries in the world. Conflict of Interest The authors declare that they have no conflict of interest. Funding Acknowledgment The project was supported by “Research State Aided” internal funds: 21-6243-1001.

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Part II Oilseed Crops

Nutraceuticals in Soybean: Biosynthesis, Advanced Genetic Research, and Usage in Food Maria Stefanie Dwiyanti and Maria D. P. T. Gunawan-Puteri

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Nutritional Components: Biosynthesis and Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Oil and Fatty Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Protein . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Isoflavones . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Saponins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Tocopherols (Vitamin E) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genetic Marker Resources and Genotyping Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 RFLP, AFLP, and RAPD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Simple Sequence Repeats . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Single-Nucleotide Polymorphism (SNP) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Insertion-Deletion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 QTL Mapping, GWAS, and Genomic Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 QTL Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Genome-Wide Association Mapping (GWAS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Genomic Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Genomic Resources and Other Bioinformatics Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Genome Assemblies and Reference Genomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Pangenomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Databases and Resources for Genetic Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Soy-Based Food . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Vegetable Soybean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Tempeh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Natto . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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M. S. Dwiyanti (*) Laboratory of Applied Plant Genome, Hokkaido University, Sapporo, Japan e-mail: [email protected] M. D. P. T. Gunawan-Puteri Department of Food Technology, Swiss German University, Tangerang, Indonesia e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_12

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6.4 Miso . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Third-Generation Product from Soy Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Soybean is a major protein feed and vegetable oil worldwide. Historically, soybean has been consumed in East and Southeast Asia, either as processed or fermented foods. Soybean also contains secondary metabolites such as isoflavones, saponins, and tocopherols (vitamin E) that are beneficial for human health. Studies have been conducted to understand the genetic basis of their biosynthesis and accumulation. Content and composition of most compounds change as response to environmental conditions during the plant growth and seed filling. This chapter will describe findings on oil, protein, isoflavones, saponins, and tocopherol biosynthesis and accumulation in soybean seeds. The availability of next-generation sequencing technologies has changed the way genetic analysis is done, and have accelerated the elucidation of genetic basis of the nutritional components. Moreover, the NGS affordability has provided us with reference genomes, large-scale sequencing data, and transcriptome data that are publicly available. Researchers can access and utilize this data to complement their findings. Lastly, this chapter will describe soy-based foods, the processing and nutritional values, and their potential as nutritional source and health component resources. Keywords

Fatty acid · Functional food · Isoflavones · Protein · Saponin · Soybean · Tocopherols · Vitamin E · Wild soybean

1

Introduction

Seeds of soybean (Glycine max (L.) Merrill) contain oil (20% of seed weight), protein (40% of seed weight), and secondary metabolites (isoflavones, saponins, and tocopherols). Having high protein and oil content, soybean became one of the major sources of protein and oil. During 2020/2021, soybean protein meal consumption as feed was 243.6 million metric tons, which contributed to 71% of the total protein meal consumed worldwide (Soystats 2022). Soybean oils contributed to 29% (58.7 million metric tons) of world oil consumption (Soystats 2022). Traditionally, soybean has been consumed in East Asia and Southeast Asia as various foods, which can be categorized into two, fermented and nonfermented foods. Nonfermented foods examples are tofu, bean sprout, soymilk, and yuba. Examples of fermented foods are natto, tempeh, miso, jang, and soy sauce. The fermentation process changes the nutritional components of soybean foods, reducing antinutrient components and increasing nutritional compounds. Natto and tempeh contain high vitamin K2 and B12, which are not detected in raw soybean seeds. The fermentation process also adds flavor through the catabolism of protein to amino acids and

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reduces antinutritional components such as lipoxygenases, trypsin inhibitors, and phytic acid (Nout and Kiers 2005). In addition to traditional food, recent interest in plant-based diets also increased the attention to soy-based food. Furthermore, the potential of soybean as nutritious food for children, a new protein source in Africa and Europe, and the use of by-products as a new source of nutrients is being explored. The domestication of soybean occurred about 6000–9000 years ago in Yellow River, Central China (Kofsky et al. 2018). The wild ancestor of soybean is G. soja (Siebold &Zucc.). Wild soybean naturally grows in diverse habitats in East Russia, Japan, China, and Korea (Kofsky et al. 2018). Wild soybean plants form vines, giving it the Japanese name “tsurumame,” which means “bean (plants) with vines.” The seeds are small and black. Soybean and wild soybean outcrossing produce fertile progenies. According to Kofsky et al. (2018), wild soybean has larger genetic diversity compared to soybean. Moreover, wild soybean possesses unique genes not available in soybean (Kofsky et al. 2018). Thus, wild soybean provides a huge genetic reservoir for current soybean cultivars’ improvement. To tap this potential, screening natural variants of metabolites content and resequencing projects also include wild soybean in the analysis.

2

Nutritional Components: Biosynthesis and Regulation

2.1

Oil and Fatty Acids

Soybean oils contribute to 29% (58.7 million metric tons) of world oil consumption (Soystats 2022). Oil content per seed dry weight of soybean seeds is approximately 20%. It varies depending on varieties, as well as growth conditions (Clemente and Cahoon 2009). Soybean oil is composed by mainly five fatty acids, palmitic acid (C16: 0), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and linolenic acid (C18:3) (Clemente and Cahoon 2009). Generally, linoleic acid is the most abundant fatty acid in soybean oil, about 55% of the total fatty acid content (Clemente and Cahoon 2009). Among five fatty acids, oleic acid, linoleic acid, and linolenic acid are categorized as unsaturated fatty acids, because they have double bonds in their carbon chains. The other two, palmitic acid and stearic acid, are saturated fatty acids, having no double bonds in their carbon chains. Carbon chain length and the level of unsaturation are shown as numbers after “C.” For example, oleic acid is described as C18:1, meaning it has 18 carbons and one double bond. Unsaturated fatty acids are more easily oxidized compared to saturated fatty acids, and if the fatty acids have higher number of double bonds, they are less stable. Therefore, linolenic acid is the most easily oxidized, followed by linoleic acid, and oleic acid. Oxidation makes oil becomes rancid and reduces its shelf life. Partial hydrogenation reduces the proportion of unsaturated fatty acids and creates trans-fatty acids, which are linked to cardiovascular diseases (Clemente and Cahoon 2009). Linoleic (C18:2) and linolenic acids (C18:3) are essential dietary elements for humans and higher animals. They are also able to decrease the risk of coronary heart

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diseases (Clemente and Cahoon 2009). Since human body cannot produce linoleic acid and linolenic acid, breeding cultivars with the optimum composition of unsaturated fatty acid and saturated fatty acid is one of the soybean breeding objectives. Quantitative trait locus (QTL) and genome-wide association study (GWAS) analyses have identified numerous quantitative trait loci (QTLs) associated with oil and fatty acid content in soybean seeds (Patil et al. 2017, 2018). Some of the oil content QTLs shared position with protein content but with contrasting effect.

2.1.1 Fatty Acids Biosynthesis and Its Regulation Fatty acids are synthesized from acetyl-CoA in the plastid. Acetyl-CoA is carboxylated to produce malonyl-CoA. Fatty acid transferase adds two carbon atoms to the acyl chain on acyl carrier protein (ACP) repeatedly to create 16 carbon acyl-ACP (C16:0-ACP). Reduction, dehydration, and reduction processes also occur along with the elongation process. C16:0-ACP can be elongated further by ketoacyl-ACP synthase II (KASII) to produce C18:0-ACP. Stearoyl-ACP desaturase desaturases C18:0-ACP to produce C18:1-ACP. Free fatty acids (C16:0, C18:0, and C18:1) are released from ACP and transported to the endoplasmic reticulum (ER). In ER, C18:1 is further desaturated by fatty acid desaturases to C18:2, and lastly to C18:3. Fatty acids in soybean seeds are stored in the form of triacylglycerol (TAG). Free fatty acids from ER and plastid are incorporated into glycerol-3-phosphate and undergo a series of conversions to create diacylglycerol (DAG). DAG is converted to triacylglycerol (TAG) by acyl-CoA:DAG acyltransferase (DGAT). TAG in soybean seeds is mostly stored in oil bodies (oleosomes), within membranes containing phospholipids and oleosins. Fatty acid desaturase-2 (FAD2) desaturases oleic acid (C18:1) to linoleic acid (C18:2). There are five FAD2 genes in soybean. Mutations at either GmFAD2-1A or GmFAD2-1B increased oleic acid content to 80% and decreased linoleic acid content to 30% (Anai et al. 2008). Double mutations of GmFAD2-1A or GmFAD2-1B produced lines having 80% oleic acid whereas linoleic acid was reduced to less than 5% (Pham et al. 2012). Desaturation of linoleic acid (C18:2) to linolenic acid (C18:3) is catalyzed by FAD3. There are three genes encoding FAD3, namely GmFAD3A, GmFAD3B, and GmFAD3C (Pham et al. 2012). Combination of GmFAD3A-GmFAD3B or GmFAD3A-GmFAD3C mutations produced lines having linolenic acid about 3% of total oil content, whereas triple mutations of GmFAD3 genes resulted in lines having 1% linolenic acid content (Pham et al. 2012). Pham et al. (2012) further combined GmFAD2-1 double mutants with one GmFAD3 mutant, producing mutants having less than 2% linolenic acid. Interestingly, growing locations affected the linolenic acid content of the mutants (Pham et al. 2012). Lines having triple mutants (FAD2-1aabb FAD3aaCC or FAD2-1aabb FAD3AAcc) had linolenic acid content less than 3% when they were grown in Portageville, Missouri, but quadruple mutants (FAD2-1aabb FAD3aacc) type is needed to achieve the same level of linolenic acid content for growing in Columbia (Missouri) which is located north of Portageville (Pham et al. 2012). Demorest et al. (2016) used transcription activator–like effector nucleases (TALEN), a gene editing method, to mutate

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GmFAD3A in fad2-1a- fad2-1b mutants and produced lines with low linolenic acid (2.5%) and high oleic acid (82.2%).

2.2

Protein

Protein contributes to about 40% of seed dry weight in commercial cultivars, and varies based on genotype or growth environment. Multiple genes regulate protein content. More than 160 QTLs distributed across 20 chromosomes have been identified from 35 independent studies (Patil et al. 2017). Of these, QTLs located on chromosome 15 and 20 are strongly correlated with protein content. The result was also confirmed in large-scale GWAS analysis conducted on 12,000 soybean accessions (Bandillo et al. 2015). Candidate gene analysis on chromosome 15 and 20 both identified three candidate genes each, which need further investigation for their roles in protein content regulation (Bandillo et al. 2015). Both QTLs also regulated oil content (Bandillo et al. 2015), but total protein content is negatively correlated with oil content (Patil et al. 2017). Therefore, it is challenging to breed a soybean cultivar having both high protein and oil content. While genetic breeding remains focused on seed yield and soybean oil remains as the major consumption of global soybean production, there might be a very few cultivars developed for its ultrahigh protein content though soybean accessions with >50% protein content were reported (Patil et al. 2017). Protein composition is also important for soybean nutritional value. About 70% of total storage proteins in soybean is composed by glycinin (11S globulin) and β-conglycinin (7S globulin) (Takahashi et al. 2003). β-conglycinin (7S globulin) is a heterotrimeric protein, and has three subunits: α, α0 , and β-subunit. β-subunit has 420 amino acids (AA) that are shared with α and α0 -subunit. The α and α0 -subunits have additional 125 AA and 141 AA in the N-terminal, respectively. Glycinin (11S globulin) is a heterohexameric protein, consisting of five subunits A1aB1b, A1bB2, A2B1a, A3B4, and A5A4B3 (Adachi et al. 2003). Between two storage proteins, the amount of methionine and cysteine per unit protein is higher in 11S globulin (Kitamura 1995). Methionine is an essential amino acid that cannot be synthesized in human body but it is important to build proteins and molecules in human body. Sufficient intake of methionine is important for the proper function of cells. Moreover, high 11S to 7S globulin is preferred in tofu processing, as it forms harder curd in tofu production (Kitamura 1995). Several breeding programs have aimed to increase the ratio of 11S globulin to 7S globulin using natural mutants in germplasm or mutants gained by γ-ray irradiation (Kitamura 1995). For example, ‘Kebuli’ lacking α’-subunit and ‘Moshidou Gong 503’ having low levels of α- and β-subunits have been used to breed lines with low α, β-subunits, and null α’-subunit (Kitamura 1995). The 7S-low lines had 50% lower 7S globulin and the 11S globulin was 15% higher compared to normal varieties without change in total protein content (Kitamura 1995). Gamma-ray irrradiation of ‘Karikei 434’ produced a mutant line lacking both α- and β-subunits and low level of α’-subunit without decrease in total protein content or defect in plant development

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(Takahashi et al. 1994). The reduced 11S globulin content in soybean were compensated by increase in 7S globulin (Yang et al. 2016). Takahashi et al. (2003) produced a mutant line lacking both 7S and 11S globulin without any defect in growth and production by crossing a line lacking 7S globulin with a line lacking 11S globulin. Protein bodies in cotyledons of the mutant is underdeveloped but the nitrogen content did not change compared to wild-type cultivars (Takahashi et al. 2003). Interestingly, free amino acids (arginine, asparagine, glutamic acid, and histidine) increased in the mutant, contributing to 4.5–8% of seed nitrogen content, whereas the proportion in wild-type varieties is between 0.3% and 0.8% (Takahashi et al. 2003). Soybean also has proteins which are allergens (Wilson et al. 2005). Subunits of 7S globulin also generate antibody response in mice fed with soy protein (Wilson et al. 2005). There are about 20 proteins identified as allergen in soybean. Three known major soybean allergens are Gly m Bd 60 K (α-subunit of β-conglycinin), Gly m Bd 30 K, and Gly m Bd 28 K (vicilin-like glycoprotein), respectively. P34 (Gly m Bd 30 K) shares 70% homology with peanut main allergen (Wilson et al. 2005). Due to this, most patients having allergy to peanuts also showed allergy to soybean (Wilson et al. 2005). Fermentation process hydrolyzes proteins and as the result, fermented soybean products such as miso, natto, tempeh, and soy sauce are potentially less allergenic than raw soybeans. For example, Gly m Bd 28 K content is reduced in fermented soybean products compared to raw soybean and nonfermented soy products (Ogawa et al. 2000; Bando et al. 1998). Another example of reducing soybean allergens is through breeding, such as low-P34 varieties having reduced P34 (Gly m Bd 30 K) content (Bilyeu et al. 2009). Analysis of soybean germplasm identified natural mutants such as PI 567476 and PI 603570A, which contain four base pairs insertion at P34 start codon resulting in translation initiation frameshift of the protein (Bilyeu et al. 2009). Molecular markers were developed to recognize this mutation and were used in marker-assisted selection for low P34 soybean cultivars (Watanabe et al. 2017).

2.3

Isoflavones

Isoflavones are metabolites derived from phenylalanine pathway. They are mainly found in legumes (Dhaubhadel et al. 2003, 2007). Soybean isoflavones can be categorized to three types based on their aglycone structure, daidzein, genistein, and glycitein. The aglycone forms are biologically active and are absorbed in the human intestine. Isoflavones have many human benefits, including reducing hormonedependent cancers and cardiovascular disease risk alleviating postmenopausal symptoms, and preventing osteoporosis. In plants, it induces phytoalexin production as a response to pathogen attack, induces the expression of nodulation genes, and regulates the formation of nodules in soybean roots (Dhaubhadel et al. 2003). Two major of soybean isoflavones are exist as malonylglycoside and glycoside forms (Tsukamoto et al. 1995). Isoflavones are synthesized starting at an early development stage and the accumulation rapidly increases at later stages of seed

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development (Dhaubhadel et al. 2003, 2007). Seed isoflavone content is affected by the environment, particularly the temperature during plant growth and seed maturation (Chennupati et al. 2011). Seven soybean varieties were grown in Kyushu and six varieties were grown in Tsukuba in three sowing times: April, May, and June 1991 (Tsukamoto et al. 1995). Average temperatures in Tsukuba and Kyushu differed by 4  C in July–August 1991, but the average temperatures differed only 1  C in October 1991 (Tsukamoto et al. 1995). Four varieties (‘Koganedaizu’, ‘Shirosaya I’, ‘Higomusume’, and ‘Kairyoshirome’) belonged to the early maturity group (Group I and II) and were known as low isoflavone varieties, and the other three varieties grown as control belonged to maturity group IVand VI (Tsukamoto et al. 1995). Interestingly, regardless of the varieties, malonyldaidzin and malonylgenistin contents were higher in whole seeds of the plants sown in July 1991 compared to seeds of plants from earlier sowing dates (Kyushu only). Harvest dates of the early maturity group sown in July 1991 were late September 1991, when the average temperature was 24.7  C, the maximum was 29.5  C, and the minimum was 19.8  C (Tsukamoto et al. 1995), which was lower compared to an average of 27.2  C in August 1991 (Tsukamoto et al. 1995). Chennupati et al. (2011) also investigated the effect of high temperature on the isoflavone content of two cultivars, ‘AC Proteina’ (high isoflavone) and ‘OAC Champion’ (low isoflavone). Stress condition of 33  C/25  C (day/night temperature) and control condition of 23  C/15  C (day/night temperature) were imposed during all developmental stages, pre-emergence, vegetative stage, early seed filling (R1-R4 stages), and late seed filling stage (R5-R8 stages) (Chennupati et al. 2011). Both cultivars showed a reduction in total isoflavone content when stress was imposed during all development stages and late seed filling stages (Chennupati et al. 2011), which coincided with the rapid isoflavone accumulation during late seed filling stages.

2.3.1 Isoflavone Biosynthesis and Its Regulation Isoflavone biosynthesis is a part of the phenylpropanoid pathway, which is also a precursor pathway for anthocyanins and lignin biosynthesis (Fig. 1). Phenylalanine ammonia lyase (PAL) catalyzes deamination of phenylalanine to cinnamic acid as the first enzyme of isoflavone biosynthesis process. Cinnamic acid is converted to p-coumaryol CoA through two steps catalyzed by cinnamate 4-hydroxylase (C4H) and 4-coumarate CoA ligase (4CL). P-coumaryol CoA and its precursor, p-coumaric acid, are a substrate for lignin biosynthesis. The next step is catalyzed by chalcone synthase (CHS). CHS converts p-coumaryol CoA to naringenin chalcone, and together with chalcone reductase converts p-coumaryol CoA to isoliquiritigenin. Naringenin chalcone and isoliquiritigenin are further converted to naringenin and liquiritigenin, respectively. This step is catalyzed by chalcone isomerase. Naringenin is converted to genistein by isoflavone synthase (IFS). IFS also catalyzes the conversion of liquiritigenin to daidzein. Glycitein is produced from liquiritigenin by a series of conversions involving flavonoid 6-hydroxylase (F6H) and IFS. Genistein, daidzein, and glycitein are further converted to their glucosides from (genistin, daidzin, and glycitin) by isoflavone 7-O-glucosyltransferase (IF7GT). Lastly, the malonylglucosides are synthesized from isoflavone glucosides, and the reaction is catalyzed by isoflavone 7-O-glucoside 6”-O-malonyltransferase

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Fig. 1 Isoflavones biosynthesis pathway. Abbreviations for enzymes: PAL phenylalanine ammonia lyase, C4H cinnamate 4-hydroxylase, C4L 4-coumarate CoA ligase, CHS chalcone synthase, CHR chalcone reductase, CHI chalcone isomerase, and IFS isoflavone synthase

(IF7MaT) (Fig. 1). CHS and IFS are the most studied among enzymes in the isoflavone biosynthesis pathway. Soybean contains multiple genes encoding for CHS. Dhaubhadel et al. (2007) performed transcriptome array analysis on two soybean cultivars, ‘Harovinton’ (low isoflavone) and ‘RCAT Angora’ (high isoflavone), to determine genes involved in isoflavone biosynthesis. The transcriptome analysis was conducted on five stages of seed development (Dhaubhadel et al. 2007). Compared to other copies, CHS7 and CHS8 are expressed in seeds and the expression level increased toward seed maturity (Dhaubhadel et al. 2007). The expression increases also coincided with the accumulation of seed isoflavones (Dhaubhadel et al. 2007). There are two gene copies for IFS: IFS1 and IFS2. Both copies are involved in isoflavone biosynthesis, but their transcription is regulated differently (Dhaubhadel et al. 2003). The genes are very similar, only IFS1 is expressed in all tissues, but its expression is the highest in root and seed coats (Dhaubhadel et al. 2003). IFS2 expression is low in stems, leaves, pods, and seed coats (Dhaubhadel et al. 2003). Its expression is high in embryos, developing seeds, and late-stage pods (Dhaubhadel et al. 2003). Interestingly, the expression level of IFS2 in developing seeds increases toward maturity, whereas the IFS1 expression is constant (Dhaubhadel et al. 2003). On the other hand, IFS2 plays role in response to pathogen attack since its expression increased in hypocotyls and roots after pathogen attacks (Dhaubhadel et al. 2003; Subramanian et al. 2004).

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Transcription levels of isoflavone biosynthesis genes are regulated by numerous transcription factors (TFs) such as MYB, bHLH, bZIP, WRKY, and MADS-boxand WD40 (Yi et al. 2010). There are more than 5000 genes putatively encoding TFs, and MYB TFs comprise about 14% of TFs. Based on the number of MYB domains, MYBs are classified into 1R, 2R (R2R3-type), 3R, and 4R MYBs. GmMYB176 encoding R1-type MYB was identified as a regulator for CHS8 (Yi et al. 2010). Cotransfection assay showed that GmMYB176 transactivated the CHS8 promoter (Yi et al. 2010). Hairy roots RNAi-mediated gene silencing of GmMYB176 reduced isoflavone content, but the overexpression did not increase the transcript level of CHS8 (Yi et al. 2010). R2R3-type MYB TFs such as GmMYB100, GmMYB39, and GmMYB29 were also identified as potential regulators for isoflavone biosynthesis (reviewed in Sohn et al. 2021). Although genes encoding biosynthesis genes and transcription factors regulating isoflavone content have been identified, the regulation in natural germplasm is much more complex, since genotype  environment interaction effect is large, and flavonoids are also involved in biotic stress response. More than 200 QTLs distributed in 20 chromosomes have been reported from a GWAS and QTL analyses using 200 soybean cultivars and 150 RILs identified several SNPs and QTLs associated with isoflavone content (Wu et al. 2020).

2.4

Saponins

Soyasaponins are triterpenoid glycosides (Sundaramoorthy et al. 2018). In soybeans, there are two major types of saponins, group A saponins and DDMP saponins (Sundaramoorthy et al. 2018). Group A saponins are the major form of saponin in hypocotyl, whereas DDMP saponins is a predominant form in cotyledon (Sundaramoorthy et al. 2018). Group A saponins cause bitter and astringent taste in soy food products (Tsukamoto et al. 1995). On the other hand, DDMP saponin showed health benefits such as inhibition of HIV infection and activation of EpsteinBarr virus early antigen (Tsukamoto et al. 1995). Therefore, decreasing the amount of group A saponins and increasing DDMP saponins would contribute to the improvement of soy-based foods’ quality (Tsukamoto et al. 1995). Group A saponins and DDMP saponins differ in the C-21 position of their soyasapogenol structure. Group A saponins have a hydroxy group (-OH) at the C-21 position (Fig. 2). The aglycones are called soyasapogenol A orsoyasapogenol B (Fig. 3). DDMP saponins have a 2,3-dihydro-2,5-dihydroxy-6-methyl-4H-pyran4-one (DDMP) moiety attached to the C-22 position of the soyasapogenol B (Fig. 3). During food processing, DDMP saponins are degraded to B saponin and E saponin (Fig. 3, Krishnamurthy and Min 2014). In addition, there are one or two sugar moieties attached to the C-3 position (R1), and acetylxylose or acetylglucose attached to the C-22 position (R2) resulting in saponin variations (Fig. 2). Saponins are derived from β-amyrin, which is a product of the mevalonate pathway (Sundaramoorthy et al. 2018). Genes involved in soybean saponin biosynthesis

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Fig. 2 Group A saponin and DDMP saponin structure. R1 is either galactose (Gal), arabinose (Ara), combinations of glucose-galactose (Glc-Gal), rhamnose-galactose (Rha-Gal), Glc-Ara, or Rha-Ara. R2 is either acetylglucose or acetylxylose

Fig. 3 Saponin biosynthesis pathway

pathway has not yet been fully elucidated, but several mutants having altered saponin composition have been identified (Fig. 3). Two mutants, Sg-1aand Sg-1b, showed a mutation in Glyma.07G254600, encoding a glycosyltransferase (Sayama et al. 2012). The significant difference between them is the amino acid number 138; Sg-1a and Sg-1b proteins have serine and glycine, respectively (Sayama et al. 2012). This resulted in a difference in their

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function. Sg-1a adds xylose whereas Sg-1badds glucose to the aglycone (Sayama et al. 2012). Accessions with the Sg-1aallele have acetylxylose, and accessions with the Sg-1b allele have acetylglucose as the third sugar group at the C-22 position. Mutants having loss-of-function allele sg-10 accumulated saponin A0-αg lacking acetylated terminal sugar at the C-22 position (Sayama et al. 2012). The sg-10 mutant has been used to breed ‘Kinusayaka’, which has a less bitter taste and astringent flavor. The variety is suitable for soymilk and tofu production (Kato et al. 2007). Sg-3 locus contains a glucosyltransferase UGT91H4 (Glyma.10G104700). The enzyme adds glucose as a third sugar at the C-3 position of group A saponin or DDMP saponin. Sg-4 locus contains a glycosyltransferase UGT73P10 (Glyma.01G046300). Homozygous recessive sg-4 mutants lacked saponins that have arabinose as the second sugar group at the C-3 position (Takagi et al. 2018). Sg-5 (Glyma.15g243300) encodes a cytochrome P450 enzyme (Yano et al. 2017). The natural sg-5 mutant was first identified in wild soybean, and the mutant did not accumulate group A saponin but showed a high level of DDMP saponin (Yano et al. 2017). This mutant had a premature stop codon in Glyma.15g243300 (Yano et al. 2017). Since high DDMP-low group A saponin is desirable for food production, the sg-5 allele has been introduced to ‘Tohoku 152’ (Yano et al. 2017). ‘Tohoku 152’ has low amount of group A saponins both in hypocotyl and cotyledon. Compared to cultivars carrying Sg-5, ‘Tohoku 152’ has higher DDMP saponin in the hypocotyl (Yano et al. 2017).

2.5

Tocopherols (Vitamin E)

Tocopherols are known as vitamin E. Tocopherol is consisted of a chromanol head and a saturated phytyl side chain. The number and position of the methyl groups on the chromanol head determine the isoforms as α-, β-, γ-, and δ- tocopherol (Fig. 4). Among four isoforms, α-tocopherol has high affinity with tocopherol transfer protein in the human liver, and kept at a high level in blood plasma. Thus, the vitamin E activity of α-tocopherol is the highest among four isoforms. The vitamin E activities of β-, γ-, and δ-tocopherol are 0.5, 0.1, and 0.03 when compared to vitamin E activity of α-tocopherol (equal to 1), respectively (Van Eenennaam et al. 2003). Total tocopherol content of soybean seed oil is higher than other oils from canola, sunflower, or palm. The major isoform in seeds is γ-tocopherol (60–70%), followed by δ-tocopherol (20–30%), whereas α-tocopherol content is less than 10%. Increasing α-tocopherol content in soybean seeds may improve the vitamin E status of soybean. On the other hand, γ-tocopherol and its derivative showed an anti-inflammatory effect, which is a specific function that was not observed in α-tocopherol (Jiang et al. 2001). Altering the ratio of γ-tocopherol and α-tocopherol may be preferred instead of increasing only the α-tocopherol content. Seed tocopherol content diversity of soybean germplasm has been surveyed in Japan (Ujiie et al. 2005; Dwiyanti et al. 2016), India (Rani et al. 2007), and Brazil (Carrão-Panizzi and Erhan 2007). From the screening of more than 1000 soybean and wild soybean accessions, three accessions containing high α-tocopherol

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Fig. 4 Tocopherol structure and isoforms

(more than 20% of total tocopherol content) were identified: ‘Keszthelyi Aproszemu Sarga’, ‘Dobrogeance’, and ‘Dobrudza 14 Pancevo’ (Ujiie et al. 2005). The α-tocopherol content ranged from 58 μg/g oil to 794 μg/g oil (Rani et al. 2007). The highest α-tocopherol percentage (27%) was observed in the variety ‘Ankur’ (Rani et al. 2007). The α-tocopherol content 89 Brazil soybean accessions varied between 11 ppm (‘Davis’) and 191 ppm (‘IPB-T’) (CarrãoPanizzi and Erhan 2007). ‘IPB-T’ also showed high total tocopherol content (1386.29 ppm) (Carrão-Panizzi and Erhan 2007). Tocopherols accumulate during the later stage of soybean seed development (R5–R8 stages). High temperature (28  C) and mild drought during these stages increased seed α-tocopherol content approximately twofold compared to those grown at 23  C (Britz and Kremer 2002). When the high temperature was imposed in different developmental stages, high temperature during whole growth stages or seed filling (R5–R8 stage) gave the largest effect on the increase in α-tocopherol content (Chennupati et al. 2011). In high temperatures, δ-tocopherol content decreased (Britz and Kremer 2002; Chennupati et al. 2011). Total tocopherol content and γ-tocopherol content change varied depending on studies and varieties (Britz and Kremer 2002; Chennupati et al. 2011).

2.5.1 Tocopherol Biosynthesis and Its Regulation The tocopherol biosynthesis pathway in higher plants is already elucidated (Fig. 5). The first component in the tocopherol biosynthesis pathway is 2-methyl-6-phytyl1,4-benzoquinone (MPBQ) which is synthesized by combining homogentisic acid (HGA) and phytyl-diphosphate (PDP). HGA is produced from the shikimate pathway, whereas PDP is produced from the MEP pathway or chlorophyll degradation

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Fig. 5 Tocopherol biosynthesis and chlorophyll degradation/phytol recycling pathway. MEP: methylerythritol phosphate. Abbreviations for substrates: GGDP, geranylgeranyl diphosphate; PDP, phytyl diphosphate; MPBQ, methylphytylbenzoquinol; DMPBQ, dimethylphytylbenzoquinol; Toc, tocopherol. Abbreviations for enzymes: GGDR, geranylgeranyl diphosphate reductase; PPK, phytyl phosphate kinase; PK, phytyl kinase; Chl synthase, chlorophyll synthase; PPH, pheophytin pheophorbide hydrolase; TAT, tyrosine aminotransferase; HPPD, hydroxyphenylpyruvate dioxygenase; HPT, homogentisatephytyl transferase; MPBQ-MT, MPBQ methyltransferase; TC, tocopherol cyclase; γ-TMT, γ-tocopherol methyltransferase

pathway. MPBQ is subsequently methylated by MPBQ- methyltransferase enzyme (MPBQ-MT) and is converted to 2,3-dimethyl-5- phytyl-1,4-benzoquinone (DMPBQ). The δ-tocopherol and γ-tocopherol are produced from cyclization of the chromanol heads of MPBQ and DMPBQ, respectively. Tocopherol cyclase is involved in this process. Gamma-tocopherol methyltransferase (γ-TMT) adds a methyl group to the chromanol head of δ-tocopherol and γ-tocopherol, converting them to β-tocopherol and α-tocopherol, respectively. Most tocopherol biosynthesis genes were first identified in Arabidopsis. The names of the corresponding Arabidopsis genes (VTE genes) are annotated in Fig. 5. MPBQ-MT and γ-TMT enzymes play important role in determining tocopherol composition in soybean seeds (Van Eenennaam et al. 2003). Overexpression of Arabidopsis VTE4 gene expressing γ-TMT (Van Eenennaam et al. 2003) could increase seed α-tocopherol percentage up to 50–75% of total tocopherol content, and reduced δ-tocopherol and γ-tocopherol percentage. Overexpression of Arabidopsis VTE3 gene encoding the MPBQ-MT reduced δ-tocopherol and β-tocopherol, and increased γ-tocopherol and α-tocopherol 10% compared to wild type. Coexpression of both VTE3 and VTE4 expressing MPBQ-MT and γ-TMT further improved α-tocopherol up to 60.4–91%

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of total tocopherol content, eliminated most of δ-tocopherol and β-tocopherol, and reduced γ-tocopherol (Van Eenennaam et al. 2003). Overexpression of the Arabidopsis VTE2 gene expressing homogentisate phytyltransferase (HPT) resulted in slight increase of total tocopherol content (Karunanandaa et al. 2005). Seed-specific overexpression of four genes encoding Arabidopsis HPPD, VTE2, GGDP dehydrogenase (GGH), and Erwinia herbicola prephenate dehydrogenase (Eh-TYRA) was conducted (Karunanandaa et al. 2005). TYRA catalyzes the synthesis of p-hydroxyphenylpyruvate, homogentisic acid precursor. The overexpression of four genes increased tocochromanols up to 15-fold in the best transgenic event (Karunanandaa et al. 2005). Surprisingly, up to 94% of tocochromanols in transgenic seeds were tocotrienols instead of tocopherols (Karunanandaa et al. 2005). How the combination of four genes led to conversion to tocotrienols is still unknown. Based on the Williams82 gene annotation, soybean has multiple gene copies of each enzyme in tocopherol biosynthesis. The copies may show differentiation in function and response to the growth environment. For example, there are three gene copies for γ-TMT: Glyma.12G014200 (γ-TMT1), Glyma.12G014300 (γ-TMT2), and Glyma.09G222800 (γ-TMT3) (Dwiyanti et al. 2011). Based on public transcriptomics data, the three copies are expressed in leaves, flowers, and early-stage pods (Severin et al. 2010; Le et al. 2007). Since tocopherol also plays role as antioxidant in photosynthetic organs, the gene expression observed in leaves, flowers, and pods may relate to its function. Interestingly, in developing seeds, the difference in expression pattern was observed. The γ-TMT1 is expressed higher in early stage of developing seeds and gradually decreased toward maturation. On the other hand, the seed γ-TMT2 and γ-TMT3 expression level increases toward seed maturation. Among three copies, only γ-TMT2 expression level is elevated at high temperature, whereas γ-TMT1 and γ-TMT3 did not increase (Park et al. 2019). Glyma.09G222800 (γ-TMT3) was identified as a candidate gene responsible for high α-tocopherol content in KAS. The candidate gene was identified based on QTL analysis on an F5 population derived from ‘Ichihime’  ‘KAS’ cross (Dwiyanti et al. 2011). Further confirmation using GUS-reporter assay in leaves of transgenic Arabidopsis transformed with ‘KAS’ γ-TMT3 promoter-intron GUS and with ‘Ichihime’ γ-TMT3 promoter-intron GUS showed that ‘KAS’ γ-TMT3 promoter activity was higher than that of ‘Ichihime’ (Dwiyanti et al. 2011). Another QTL analysis using recombinant inbred lines (RILs) population derived from a Hokkaido cultivar ‘TK780’ and high α-Toc wild soybean (‘B04009’) identified several QTLs, including a QTL containing γ-TMT3 and a QTL containing γ-TMT1 and γ-TMT2 (Park et al. 2019). Interestingly, both studies found γ-TMT3 as the candidate gene and same single-nucleotide polymorphisms (SNPs) differentiating between high and low varieties (Dwiyanti et al. 2011; Park et al. 2019). One of these was located within CAAT-box, which is located 74-bp upstream the translation start codon (Dwiyanti et al. 2011). Compared to ‘TK780’ and ‘Ichihime’, the γ-TMT3 expression level was elevated in ‘KAS’ and ‘B04009’, during seed maturation. This correlated to difference in α-tocopherol content (Dwiyanti et al. 2011; Park et al. 2019).

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3

Genetic Marker Resources and Genotyping Technologies

3.1

RFLP, AFLP, and RAPD

Restriction fragment length polymorphism (RFLP) is a marker based on DNA variations within restriction enzyme sites. Restriction enzymes (REs) recognize RE sites and cut the DNA. If DNA variation occurs at the RE sites, RE cannot cut the DNA. RE then can be used to digest DNA, and the differences in fragment length are the source of RFLP markers. RFLP is a codominant marker and does not need reference genome information, therefore it is suitable for soybean genotyping before the whole genome sequence was available. The first soybean genetic linkage map consisted of 26 linkage groups and was constructed from 150 RFLP markers based on a F2 population derived from a cross between a soybean cultivar A81-356022 and a wild soybean accession PI468916 (Song et al. 2004). After that several RFLPbased linkage maps were constructed (Song et al. 2004). However, RFLP has disadvantages: large amount of DNA needed for digestion and radioactive probe usage to detect polymorphism. In soybean, the polymorphism rate of RFLP markers is low. Also, since soybean is an ancient polyploid, RFLP probes map to more than one position in the genome, makes it difficult to compare the genotyping results across different studies. Amplified fragment length polymorphism (AFLP) also utilizes variations within RE sites. The difference from RFLP is that, after the genomic DNA digestion with RE, the DNA fragments are ligated to adaptors that ligate to the restriction enzyme site. Primers complementary to adaptor sequences amplify a subset of ligated fragments. The amplified fragments are then electrophoresed, and the presence/ absence of the fragments are visualized as variations for individuals. The advantage of AFLP is that it requires less amount of DNA compared to RFLP, and does not require radioactive probes. However, it is a dominant marker, so it is difficult to use as a marker in QTL analysis using segregating populations with a high rate of heterozygosity such as F2 generation. Random amplified polymorphic DNA (RAPD) markers are developed based on PCR amplification of random segments of genomic DNA with a single primer of the arbitrary nucleotide sequence. A disadvantage of RAPD markers is that it is a dominant marker, thus it cannot distinguish whether a locus is heterozygous or homozygous. Another disadvantage is that the amplification reproducibility is low because the amplification uses arbitrary primers that are not locus specific and the PCR result depends on genome DNA quality and PCR conditions.

3.2

Simple Sequence Repeats

Simple sequence repeats (SSR) markers or microsatellites are based on tandemly repeated 2–5 nucleotides, such as (CA)n, (AT)n, (ATT)n, and (ATG)n. Primers for SSR markers are designed using the conserved DNA sequences flanking these repeats. SSR is easy to use since it only requires PCR using the designated primers

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to detect the repeat number variations between varieties. Repeat number variations can be observed as differences in fragment length using gel electrophoresis performed after PCR. SSR markers are abundant and easy to use, therefore they were the main markers used for QTL mapping prior to next-generation sequencing. Even now, SSR markers are still used to fill in the gaps in linkage maps produced from SNP genotyping, and it is useful for labs with limited budget and sometimes the genotyping using SSR is much faster and easy than SNP genotyping for a smallscale project or for fine-mapping a certain QTL locus. A number of SSR markers for soybean has been developed since 1990s (Song et al. 2004). Song et al. (2004) evaluated the possibility of expressed sequence tag (EST) sequences as resource for SSR markers. The team screened 136,800 ESTs available in the GenBank to identify sequences containing SSRs. EST, however, contains low number of potential SSR markers having only low number of dinucleotide repeats of ten or more, and trinucleotide repeats of eight or more. Therefore, instead of EST, Song et al. (2004) looked into genomic libraries of ‘Williams’ soybean and bacterial artificial chromosome (BAC) clones. The number of SSR markers from genomic libraries and BAC clones was higher than that from EST. A total of 420 SSR markers developed: 24 from EST, and the remaining 396 markers were from BAC clones or genomic libraries. The SSR markers then were used to develop a genetic linkage map containing 20 linkage groups, with the number of markers per group varied between 12 and 29. After the release of Williams82 reference genome Glyma1, more than 210,000 potential SSR markers were identified from the reference genome (Song et al. 2010). After screening for locus specificity and perfect motif repeats, a BARCSOYSSR_01 database consisting of 21,206 SSR markers was published (Song et al. 2010). The database contains information on SSR marker ID, position in the chromosome, repeat motif, the physical position of flanking primers, estimated PCR product size, as well as the flanking primer sequences (Song et al. 2010).

3.3

Single-Nucleotide Polymorphism (SNP)

Single-nucleotide polymorphism (SNP) markers are abundant, biallelic, and their positions in the genome are known. In the GmHapMap dataset consisting of 1007 diverse accessions of soybean and wild soybean (Torkamaneh et al. 2021), there were 12.1 million SNPs across 1.1 Gb-length genomes. Biallelic means that at any SNP locus there will be only two nucleotides of four possible types (A, C, G, and T). The occurrence of the third allele is rare. The biallelic nature of SNPs also led to the development of automated and large-scale genotyping systems such as SNP chips or flexible array systems (Thomson 2014). Lastly, since the SNP position in the genome is known, it is possible to develop markers using primers based on the flanking sequences. These markers then can be used to compare genotyping results across different studies or populations and help the development of SNP databases compiled from different studies. In addition, the known position of SNPs makes it possible to predict the effect of SNPs on the phenotype. For example, SNPs located

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in the exon may lead to an early stop codon, missense mutation, or induction of splicing variants. SNPs located in the promoter region may add or reduce cis-elements regulating the gene expression. There are two types of SNP genotyping methods, fixed and flexible platforms (Thomson 2014). One example of a soybean fixed SNP genotyping platform is SoySNP50K BeadChip, which was developed based on DNA sequence analysis of six soybeans and two wild soybean accessions (Song et al. 2013). Initially, more than 200,000 SNPs were identified. After filtering for the distance between SNPs, unique flanking sequences indicating mapping to one locus, low rate of missing data, number of reads supporting each allele, and Illumina manufacturing phase, 52,041 SNPs distributed to 20 chromosomes were chosen as SoySNP50K content (Song et al. 2013). Genotype data of 12,116 soybean accessions has been used for genomewide association mapping for oil and protein content (Bandillo et al. 2015). The GWAS study identified SNPs linked to oil and protein content on chromosomes 20 and 15, respectively (Bandillo et al. 2015). The advantages of a fixed SNP genotyping platform are high call rates because the SNPs included in the array already passed initial call rate filtering, fast turnaround time, cost-effectiveness per data point, the easiness to compare datasets resulting from different studies since the same set of SNPs are genotyped across samples, and, as a result, it is easier to create an SNP fingerprinting database (Thomson 2014). The main disadvantage of the SNP chip is the high cost to design a new SNP array. Therefore, a high-density SNP array is usually developed by company or institutions that are sure to use SNP array for a large number of samples. If the SNP array can be used as a “universal” array, meaning it can be used for genotyping a large number of samples, then the SNP chip will be cost-effective (Thomson 2014). On the other hand, flexible SNP array platform examples are Douglas Array Tape, Fluidigm Dynamic Array, TaqMan, and KASP (Thomson 2014). The main characteristic of flexible array platforms is that these enable users to select markers for genotyping. Douglas Array Tape is a high-throughput platform having capacity to genotype more than 76,000 reactions per fun. Fluidigm Dynamic Array has less freedom in choosing number of markers and samples per run since it provides option either to genotype 96 SNPs  96 samples or 24 SNPs  192 samples. TaqMan and KASP can be run on a real-time PCR machine or fluorescence plate readers, thus the number of samples  markers in each run can be customized to fit in the 96-well or 384-well plate used in those machines. Region flanking target SNP is amplified using PCR and the SNP allele is detected using fluorescence tag attached to marker primers. If fixed array is more suitable for QTL mapping, GWAS, or genetic diversity analysis, flexible array is more suitable for marker-assisted selection (Thomson 2014). Another type of a flexible SNP genotyping method is restriction enzyme (RE) sequence–based genotyping method. This method provides SNP data across the whole genome, thus it is suitable for QTL mapping or GWAS. There are several methods such as restriction site–associated DNA sequence (RAD-seq), double-digest RAD-seq (ddRAD-seq), and genotyping by sequencing (GBS). RE-sequence-based genotyping method does not require initial effort to develop SNP array but does require users to create barcoded adaptors to be linked to sample DNA fragments. In

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addition, the sequencing cost is lower than normal deep whole genome sequencing because it combines multiple samples in one sequencing lane. Moreover, genomic library preparation can be performed in most labs equipped with molecular biology facilities. Therefore, users who do not have access to labs can do RE-sequence-based genotyping when they do not have SNP array. Disadvantages of RE-sequence-based genotyping is that it requires more computational resources for data analysis than fixed SNP array, the number and position of SNPs from genotyping can differ depending on the type of REs used in genomic library preparation, the SNP analysis pipeline. As an example, GBS protocol will be described. The first step of the GBS protocol is the digestion of genomic DNA using two restriction enzymes (REs), a commoncutter RE and a rare-cutter RE (Poland et al. 2012). The digested DNA is ligated to adapters containing unique 4–6 bp nucleotides serving as a barcode sequence. A unique barcode sequence enables mixing samples between 96 and 384 samples into one sequencing tube (Poland et al. 2012). The sample mix is then sequenced using next-generation sequencing (NGS) machines. The resulting reads are then separated per sample based on barcode information, mapped to the reference genome, and called the variants. The tedious part of GBS is sequence read processing and data analysis, which needs computational skill for big data processing (Thomson 2014). Also, since multiple samples are mixed and sequenced in one sequencing reaction, the sequencing depth of each sample is shallow, which may produce a high missing rate in samples. Several bioinformatics tools are available for GBS data analysis and to impute (predict and filling-in) the missing SNP data, for example, TASSEL-GBS, IGST, Fast-GBS, UNEAK, or Stacks. The number of SNPs and accuracy of SNP calling can vary depending on the pipeline and parameters used.

3.4

Insertion-Deletion

Insertion-deletion (InDel) markers are developed based on small insertion-deletion (between 5 and 50 bp) when comparing two genome sequences. InDel can be detected using pipelines for SNP variant calling. Compared to SNP which is biallelic, insertiondeletion length can vary among individuals in diverse populations. Therefore, InDel marker genotype scoring cannot be easily automated and the markers are not commonly used for genome-wide association mapping. Nevertheless, the InDel marker is still useful in genotyping biparental segregating populations. In addition, InDel markers genotyping can be done in house, target fragments can be amplified by PCR, and variant detection can be done by gel electrophoresis – gel visualization.

4

QTL Mapping, GWAS, and Genomic Selection

4.1

QTL Mapping

Quantitative trait loci (QTL) analysis is a method to identify genomic regions associated with a quantitative trait by investigating phenotype-genotype association in a biparental segregating populations. Three types of populations are commonly

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used in QTL mapping: F2, recombinant inbred lines (RILs), and backcross inbred line (BIL) populations. F2 population is derived from selfing the F1 hybrid produced by crossing two parental lines having contrasting phenotype of target trait. The genome of F2 lines is mostly heterozygous, therefore the F2 population is suitable for identifying major QTLs. RILs are developed by selfing F2 individuals for 5–6 cycles, resulting in homozygous lines. Large number of seeds having identical genome composition can be produced from each RIL, therefore the RIL population is suitable for multi-years, multi-locations QTL analysis (Collard et al. 2005). Another type of population is BIL. BIL is developed by crossing back F1 hybrids to one parental line (recurrent parent) for several cycles, followed by selfing until the genomes are fixed. BILs will have most of their genomes from the recurrent parent, and only a small part comes from the other parent. Since the genome is fixed, BILs can be used for multi-years and multi-locations studies. In addition, since the majority of the genome is from a recurrent parent, which is usually an improved line, promising BILs can be directly used in breeding programs. The first step of QTL mapping is genotyping the population and constructing a linkage map or recombination bin map. Linkage map is constructed by calculating recombination frequency between markers, and the recombination frequency is translated to distance between markers (centiMorgan). One centiMorgan (cM) is defined as 1% chance of recombination between two markers. It means in a population of 100 individuals, there will be one recombination between two markers with 1 cM distance. In most of QTL analyses, marker distance calculation will involve more than two markers. There are two functions for marker distance calculation: Haldane mapping function, which assumes no interference between crossover, and Kosambi mapping function, which considers influence of recombination events to the adjacent recombination events (Collard et al. 2005). Recombination bin map approach is commonly used when genotyping is performed using GBS, RAD-seq, or SNP-chip. These genotyping methods produce high-density SNP map containing SNP markers that often are within the same haplotype, meaning they are closely located and segregated together. Using all SNPs in QTL mapping will require more computational resources and give redundant information. To reduce computational time and cost, only one SNP per bin is used in QTL mapping. This is already sufficient to represent the entire whole genome sequence (Patil et al. 2018). Representative SNPs are then used to create linkage map. For QTL analysis, genotype, phenotype, and linkage map data are needed. There are several QTL mapping methods that are commonly used, such as single-marker analysis, interval mapping, or composite interval mapping (Collard et al. 2005). Single-marker analysis or single-marker association is finding association between one marker with phenotype. Single-marker analysis does not require linkage map data. Analysis of variance (ANOVA), linear regression, or t-tests are statistical methods used for single-marker analysis (Collard et al. 2005). Single-marker analysis can be performed without special QTL mapping software. However, QTL detection power will be less if the QTL is located far from the marker, due to recombination occurred between marker and QTL (Collard et al. 2005). Interval mapping incorporates marker distance information in QTL detection. While singlemarker analysis only estimates correlation between QTL and one marker, interval

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mapping can estimate QTL location between two markers (Collard et al. 2005). Composite interval mapping (CIM) is interval mapping method with linear regression and incorporates a subset of markers as covariates. By including covariates, the QTL analysis can account for linked QTLs and residual variation (Collard et al. 2005). CIM can detect QTLs with higher resolution but it requires more computational time. After QTL is determined, the next step is fine mapping and candidate gene identification. This process largely changed after reference genomes and highdensity SNP genotyping are available. First, the physical positions (position on genome) of flanking markers are determined. If the markers are generated by GBS or SNP chip, the marker physical position are already determined. Possible candidate genes are obtained by looking into reference genome sequence, for genes annotated within region between the flanking markers. Further selection can be done by checking whether the genes are expressed and the location or time of expression.

4.2

Genome-Wide Association Mapping (GWAS)

Genome-wide association mapping or genome-wide association studies (GWAS) utilize allelic diversity and recombination events in diverse populations to find genomic regions associated with certain trait (Chaudhary et al. 2015). One advantage of GWAS over QTL mapping is reduced time to create segregating populations needed for analysis. However, GWAS detection power relies on the frequency of minor allele in population and correct population structure (Chaudhary et al. 2015). Genotype data used for GWAS is usually filtered by removing SNPs having minor allele frequency less than 5% to avoid false positive, detect rare alleles (Chaudhary et al. 2015). GWAS studies have been conducted in soybean to identify SNPs associated with protein, oil, amino acid content, tocopherol, and isoflavones (Chaudhary et al. 2015; Wu et al. 2020; Bandillo et al. 2015; Sui et al. 2020). The challenge for GWAS analysis for nutritional components in soybean is the effect of environmental factors to the nutritional content. Diverse germplasm used in GWAS analysis may have different flowering time, thus temperature during seed filling period will differ for each accession. This may affect the phenotype and subsequently GWAS result.

4.3

Genomic Selection

Oil, protein, and isoflavone content are regulated by multiple and minor QTLs that interact with each other. Marker-assisted selection used a subset of markers linked to QTLs, therefore it may not correctly evaluate promising lines in breeding programs. Genomic selection term was introduced by Meuwissen et al. (2001). It utilizes all markers across the genome to predict phenotype, and this method is more affordable and efficient after the availability of NGS-based genotyping methods (StewartBrown et al. 2019). Genomic selection requires two populations, a training

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population and test population. The training population will be genotyped and phenotyped, and both data are used to build a prediction model. Test population will be genotyped, and the genomic estimated breeding values (GEBV) will be estimated using prediction model built with training population. Possibility of using genomic selection in soybean was tested in Stewart-Brown et al. (2019), the protein and oil content were predicted using 483 elite breeding lines genotyped using BARCSoySNP6K iSelect BeadChips. The predictive ability for protein and oil was quite high, 0.81 and 0.71, respectively, compared with predictive ability for yield (0.26).

5

Genomic Resources and Other Bioinformatics Resources

5.1

Genome Assemblies and Reference Genomes

The estimated soybean genome size is 1.1-Gb, divided into 20 chromosomes (Schmutz et al. 2010). Approximately, 59 and 13 million years ago, genome duplications occurred twice, followed by several gene diversification and loss, as well as chromosome rearrangements (Schmutz et al. 2010). As a result, about 75% of soybean genes exist as multiple copies (Schmutz et al. 2010). The first reference soybean genome was developed based on the Williams82 sequence (Schmutz et al. 2010), which was released as the Glyma1 version. The assembly was developed based on the whole-genome shotgun-sequencing method and it was one of the largest genomes to be assembled at that time (Schmutz et al. 2010). The assembly resulted in a total 950 Mbp length, grouped into 20 chromosomes and additional 1148 unanchored sequence scaffolds (Schmutz et al. 2010). The number of predicted protein-coding genes was 46,430 genes (Schmutz et al. 2010). About 78% of predicted genes were located in chromosome ends, where most all genetic recombination occurred (Schmutz et al. 2010). Genome sequence around centromeres is rich in repeats resulting in low recombination is this region (Schmutz et al. 2010). The subsequent version (Wm82.a2.v1) replaced Glyma1 assembly by integrating a dense genetic linkage map produced from the RIL population of ‘Williams 82’  wild soybean ‘PI479752’ and RIL population of ‘Essex’  ‘Williams82’ (Song et al. 2016). This produced a genome assembly with a length of 949.2 Mbp for 20 pseudomolecules related to 20 chromosomes and additional 1170 unanchored scaffolds (Song et al. 2016), and 56,044 protein-coding genes (based on gene annotation file available in Phytozome.org). A major change in the Wm82.a2.v1 version is the change in the gene model name (Phytozome.org). Since some studies were conducted before the release of version 2.1, to know the relation between gene model in version 1 and version2.1, Soybase.org released a tool called Gene Model Correspondence Lookup where users can post the gene model either in version1 or version 2.1 and vice versa. As of June 2022, the current genome assembly of Williams82 has been improved to version Wm82.a4.v1. Wm82.a4.v1 was improved by incorporating the synteny of two other Glycine assemblies (Lee and Soja), and

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also information based on PACBIO long reads. It has 961 Mbp of 20 pseudomolecules and 17 Mbp in unanchored scaffolds resulting in a total length of 282 scaffolds of 978.4 Mbp and the number of protein-coding genes is 52,872 genes (Valliyodan et al. 2019). The availability of multiple reference genomes for soybean will help identify genomic regions unique to certain varieties/species/regions.

5.2

Pangenomes

Pangenome represents the entire set of genes within a species, consisting of sequences that are shared among individuals or varieties in the species. The term pangenome was first defined in microbes (Tettelin et al. 2005). Core pangenome is entire genes shared by all strains within a clade (Tettelin et al. 2005). Shell pangenome is a gene set shared by several strains within a clade, whereas cloud pangenome is a gene set owned specifically by a strain within a clade. If the terms are translated to soybean, core pangenome can be defined as all genes shared by all varieties within soybean and wild soybean. Gene sets shared by several varieties in shell pangenome once were thought of as dispensable genes. However, recently it is thought that these genes may contribute to species diversity, encoding enzymes for a supplementary biochemical pathway that is not essential for growth but helps the species adaptation. Pangenome is getting attention instead of reference genome from one cultivar or variety because it can capture diversity present in the species. The first pangenome study was published in 2014 (Li et al. 2014). Li et al. (2014) assembled de novo sequences of seven wild soybean accessions from Yellow River region, North and South China, Japan, Korea, Russia, and accession from the predicted domestication center in the China’s northeast region. The de novo assemblies were compared to soybean reference genome Williams82 and identified 48.6% of the gene families as core genes (28,716 genes) (Li et al. 2014). The second pangenome study included nine soybean landraces, 14 soybean, and three wild soybean accessions representing the diversity of 2898 deeply sequenced soybean and wild soybean accessions (Liu et al. 2020). De novo assembly of the 26 accessions produced genome assemblies with lengths varied from 992.3 Mb to 1059.8 Mb with average of 1011.6 Mb (Liu et al. 2020). The assemblies were then combined with Zhonghuang 13 as the primary reference genome into a graph-based pangenome (Liu et al. 2020). Orthologs analysis classified all genes from the 27 genomes into 57,492 families (Liu et al. 2020). Of these, 20,623 gene families were categorized as core genes since they were present in all 27 accessions (Liu et al. 2020). An addition of 8163 families were present in more than 90% of the collection (softcore genes), and the remaining 28,679 families were shell pangenome (Liu et al. 2020). The third pangenome study (PanSoy) was published in 2021, involving de novo assemblies of 204 soybean accessions (Torkamaneh et al. 2021). The 204 accessions were selected as representative of the phylogenetic and geographical diversity of 1007 accessions from the GmHapMap dataset (Torkamaneh et al. 2021). PanSoy, sequence-based pangenome, was constructed by comparing each of 204 assemblies

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to the ‘Williams82’ reference genome (Wm82.a4.v1; Valliyodan et al. 2019). PanSoy detected 54,531 gene families in the 204 accessions, 90.6% of which (49,431 genes) were identified as core genes (Torkamaneh et al. 2021). The PanSoy genome coverage was evaluated using ‘Lee’ reference genome (Valliyodan et al. 2019). About 99.9% of ‘Lee’ genome sequence could be mapped to the PanSoy genome, in comparison to 92% of the ‘Lee’ genome mapped to the Williams82 reference genome only (Torkamaneh et al. 2021). The fourth pangenome study was based on resequencing data of 1110 accessions from the USDA Soybean Germplasm Collection (Bayer et al. 2021). The analysis produced a pangenome with 1213 Mbp length and 51,414 predicted gene families (Bayer et al. 2021). Of more than 50,000 gene families, 86.8% of genes are core genes (Bayer et al. 2021).

5.3

Databases and Resources for Genetic Research

Online databases for reference genome sequences, gene annotation, resequencing data, SNPs, transposable elements, biosynthesis pathway, transcriptome, proteome, metabolomics, cyst nematode proteins, functional network, functional genomics, and root phenotype have been developed for soybean. These databases contain data that can help other researchers in furthering their research, however, unfortunately, many of these databases were not accessible anymore or were not easy to be found. Two databases, Soybase (www.soybase.org, last accessed April 5th, 2023) and Phytozome (www.phytozome.org, last accessed April 5th, 2023), will be introduced here. Soybase (Grant et al. 2009) was developed by USDA-ARS. It provides a comprehensive repository of professionally curated genetics, genomics, and other related data for soybean analysis (Grant et al. 2009). Currently, it houses a large variety of data, from genetic marker data, genetic map, a compilation of QTLs and GWAS peaks identified in past, transcriptome data, SNP data from resequencing projects, whole-genome sequence data, and pangenomes to gene ontology, and tutorials on soybean development, disease, and pests. Transcriptome datasets from Severin et al. (2010) and Le et al. (2007) are also provided here. Severin et al. (2010) provided transcriptome data from 14 soybean tissues (leaf, flower, one M-pod, 10 days after flowering (DAF), and 14-DAF pods, root, nodule, and seven stages of developing seeds). The data is in Glyma1, thus users need to convert the gene IDs to Wm82.a2.v1 version and vice versa. On the other hand, Gene Networks in Seed Development project (Le et al. 2007) is based on transcriptome profiling of soybean seed regions (seed coat, endosperm, and embryo subregions). It is also known as Goldberg/Harada dataset. It used laser capture microdissection (LCM) to isolate these subregions. A total of 40 soybean seed sections were analyzed. Detailed analysis using seed sections was performed at the following stages: globular stage, heart stage, cotyledon stage, and early maturation stage. In addition, data from the mid-maturation stage, late-maturation stage, dry seeds, trifoliate leaves, roots, stems, floral buds, and seedlings 6 days after imbibition are also provided to represent the soybean life cycle. The datasets provide

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knowledge of genes active in different seed parts during development, transcription factors localized at specific seed regions and subregions, and biological processes important for seed differentiation. The dataset can be accessed from http:// seedgenenetwork.net (last accessed July 7th, 2022) and from the Soybase Expression Explorer Database. There are also transcriptome datasets grouped by experiments and are provided under NCBI GEO Expression data. Phytozome (Goodstein et al. 2012) is developed and is maintained by the Department of Energy, Joint Genome Institute. It serves as a plant comparative genome portal and the current version (Phytozome v13) houses 304 assembled and annotated genomes (last accessed 4th April 2023). Phytozome v13 hosts three soybean reference genomes, Williams82, Lee, Fiskeby III, and one wild soybean reference genome PI 483463. Users can perform BLAST analysis, search genes using keywords or gene ID, or retrieve sequences based on genomic position. For soybean and wild soybean, users can obtain the gene genomic sequence, transcript, coding sequence, and peptide sequence. Information about its function, organs where it is expressed, KEGG pathway annotation, gene homologs, and similarity to the homologs in other species are also available. Users can also perform gene comparative analysis across different species. Registered users can download wholegenome sequence (all softmasked, hardmasked, and repeat masked), transcript data, and gene annotation.

6

Soy-Based Food

Soy-based food has played an important contribution to the health, culture, and economy of Asian countries, especially China, Japan, Korea, and Indonesia. It is a high-protein food and contains essential fatty acids such as linoleic acid and linolenic acid. Soybean is known as “meat in the field” since it supplies high level of protein. It also provides nutritional components that provide health benefits beyond nutrients and other non-nutritional components with physiological function. There are currently three groups of Food for Specified Health Uses (FOSHU) soy-based products: cholesterol lowering, intestinal function regulation, and bone health (Yamamoto 2005). The versatility of soy for human consumption is shown in the rich varieties of soy-based food products. The protein and oil in soybeans are the components that are mostly made use of. The protein content in soybeans is an important aspect to know because they are often the ones that will experience the most changes when being processed. During fermentation of several traditional soy-based products, such as tempeh and miso, the protein content is metabolized to amino acids which will result in higher nutritional value and also enhance its texture and taste (Handoyo and Morita 2006). Notable amino acids are the umami-inducing glutamate and arginine. Soybean and products made of soybeans with high glutamic acid content often tastes better and is more preferred. When the soybean is further processed, like in tempeh, for example, the glutamic acid content increases as fermentation progresses (Gunawan-Puteri et al. 2015). The glutamic acid content gives tempeh its umami taste. Arginine on the other

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hand has an important function in metabolism reactions like, for example, in the urea cycle (Morris 2002). It helps in synthesis of larger protein molecules in the body. In the further processing of soybeans, arginine is one of the primary amino acids that could be used, for example, in fermentation. Soybean is also a very promising ingredient for functional food products. Soybean contains significant amounts of bioactive components, mainly phenolic compounds like flavonoids and isoflavones, that have antioxidant activities which are found to be enhanced in soybean products. Alongside protein and other nutrients in soybean, the bioactive components give soybean its functional properties such as antidiabetic, anticancer, anti-inflammatory, estrogenic, and anti-hypercholesterolemic function. Soy anti-nutrients, such as phytic acid, are eliminated with fermentation and soaking in processed soy foods such as tempeh, soy sauce, and tauco (Hui et al. 2004). Soybean could be processed using fermentation or without the fermentation process. Some of the soybean products that are fermented using Lactobacillus bulgaricus and Mucor sufu are soy yogurt and soy cheese, respectively. Wellknown fermented products in Indonesia are tempeh, soy sauce, and tauco. Tempeh is fermented using a mould starter of Rhizopus oligosporus, soy sauce is made by inoculating with Aspergillus sojae mould, while miso is fermented using Aspergillus oryzae mould. Natto is another soybean fermented food with Bacillus subtilis. Examples of soy-based foods that do not undergo fermentation process are tofu or soymilk. Soymilk can be further processed into tofu. Nonfermented soy products processed with modern methods include oil, soy flour, and soy protein isolate. Soy protein could also be used as an ingredient to produce synthetic meat (TVP/textured vegetable protein). Learning about the soybean ingredient requirement for each food product might become the future in soybean cultivation development.

6.1

Vegetable Soybean

Vegetable soybeans are defined as those that are harvested after the R6, the immature green state, but before the R7, the beginning of maturity stage when pods located at the main stem start to change into brown or tanned color. Vegetable soybean has different names: edamame (Japan), poot kong (Korea), maodou (China), and tuarae (Thailand). Edamame – green pods attached to the stem – is a popular snack in Japan. It is generally sold in the pods as fresh or frozen beans, attached or detached from the stem, though canned and frozen shelled beans are also available in the market. For consumption, edamame is boiled for 5–7 min in highly salted water. However, it can also be shelled, removed from the pods for boiling, baking, steaming, or toasting over fire for making soup, salad, or vegetable dishes. And while it is logical that vegetable soybeans that have 9–10 times moisture content than the mature bean have lower other nutrient components, surprisingly vegetable soybeans are recorded to have higher vitamin A, vitamin C, sodium, and comparable niacin content. In the dry weight composition, vegetable soybean also contains more calcium, folate, and comparable protein, fat, ash, carbohydrate, and fiber content compared to the mature soybean seed.

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The sensory quality of vegetable soybean owes to its sweetness and umami tastes along with the texture and aroma quality. Vegetable soybeans contain 1.28–7.12 g of sucrose, 0.37–1.51 aspartic acid, 0.64–2.82 glutamic acid, 0.17–0.72 glycine, and 0.11–0.51 g alanin per 100 g of bean (Kumar et al. 2011). The sodium content of vegetable soybean is higher than mature soybean (15 and 2 mg/100 bean), explaining the higher salty umami interaction of the sodium with umami inducing amino acid. It has significantly higher moisture content (67.5%) compared to mature soybean (8.54%) and was valued to have higher flavor quality compared to its mature soybean. The morphological characteristics expected for a good quality vegetable soybean include pod size, number of beans per pod, and pod color (Shanmugasundaram and Yan 2010). Preferable traits for vegetable soybean are large seeds (>30 g per 100 g dry seeds), with two or more beans per pod, subsequently pod size (should be 5.0 cm and 1.4 cm) as well as number of pods (should be 175 pods per 500 g frozen pod packet) become a quality parameter in vegetable soybean. The preferable pod and bean color for vegetable soybean is dark green, however, the mature seed color can be diverse from yellow, green, brown/red, or black.

6.2

Tempeh

Soy tempeh is defined as a compact white cake that is prepared from dehulled, boiled, and acidified soybeans through solid-state fermentation with Rhizopus spp., originated from Indonesia. Tempeh uses the whole bean of mature soybean and thus creates a hearty and firm, meaty texture from mycelium with a grizzle of soft bean texture. It has savory, nutty, earthy, and mushroom flavors. Tempeh is unique among major traditional soy foods because it did not originate from China or Japan. Variation occurs among tempeh artisans in the dehulling, boiling, and acidification processes prior tempeh starters inoculation. The acidification process can be conducted naturally by overnight soaking or chemically by soaking the bean in food-grade acidulants. Once the acidified soybean is inoculated with the mold, it is common to directly pack them into porous plastic bags or banana leaves and leave them to begin the solid-state fermentation. Tempeh can be consumed as it is, but the most popular preparation is to fry, stir-fry, or boil them with salt and spices and/or flour. The popularity of tempeh within the nation was never in question, as this relatively inexpensive meat replacement for protein source has been consumed by millions of Indonesian daily. Tempeh has high socioeconomic importance in Indonesia as there are more than 115,000 micro-, small, and medium enterprises (MSMEs), which employ 285,000 workers and generate about 57 million EUR per year. The soybean tempeh industry alone absorbs more than 1.2 million tons of soybeans per year (Central of Indonesian Agricultural Data and Information System 2013), which is more than 70% of soybean consumption within the country. The importance of the tempeh industry in Indonesia has affected domestic soybean development as it also put importance on

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the tempeh requirement such as the seed size, in addition to the yield, harvest time, and resistance to abiotic stress. According to the standard quality of setup by National Standardization Agency of Indonesia, soy tempeh contains minimum 15% protein and 7% fat (National Standardization Agency of Indonesia 2015), while the USDA National Nutrient Database recorded that tempeh has approximately 20% protein and 10% fat. Several studies recorded that Indonesian domestic soybean in general is having higher protein and lower fat content compared to imported soybean, especially those from the USA. The main reason is that soybean is used in the USA for soybean oil production. Therefore, the soybean demand is more a derivative of animal product consumption rather than for direct human consumption, such as tempeh and tofu in Indonesia. The first step in tempeh production is soybean hydration by soaking or boiling in water. This process also aims to loosen up the hull and facilitate the wet dehulling process. Traditionally, wet dehulling processes in tempeh are done manually by human feet as the workers get into the large pool of soybean and step on them. Nowadays, due to hygiene reasons and technological availability, dehulling machines have been employed for the process, and some more advanced tempeh industries are even employing dry dehulling techniques prior to water hydration. As tropical countries with high humidity and room temperature, microorganisms are naturally attracted during soaking which leads to natural lactic acid bacteria (LAB) acidification. The acidification is an important step in ensuring the success of mould inoculation as it wipes out other competitor microorganisms and provides an ideal condition for Rhizopus moulds to start the solid-state fermentation. In temperate countries where the humidity and temperature are much less, chemical acidification is often added to support this process. After the acidification process, the bean is boiled, drained, and cooled prior to Rhizopus mold inoculation. Traditionally, the mold is introduced by mixing small amounts of tempeh from previous fermentation, but nowadays ready-to-use and optimized tempeh starters have been commercially available. Following the tempeh starter inoculation, the inoculated beans are wrapped with clean banana leaves or porous plastic bags and allowed to sit at room temperature for at least 24 h. By this time, mycelium hold the beans together, though the white mycelium might not be visually available yet. Tempeh producers usually have this stage of tempeh (tempepera) during distribution, allowing more fermentation to happen before it reaches the customers. The fresh ripe tempeh covered with white mycelium is usually consumed within 2 days, otherwise it goes into the next stage of overripe tempeh. While fresh ripe tempeh is often consumed as a whole meal, overripe tempeh has much stronger taste and aroma and is often used more as condiment. Tempeh is a traditional Indonesian fermented food known for its high nutrients and superior digestibility (Hermana and Karyadi 1997). Tempeh fermentation increases sodium content that may contribute to salty taste and umami interaction with free amino acids. Tempeh also has a higher composition of manganese, niacin, and vitamin B-6 compared to soybean. Interestingly, tempeh contains vitamin B12 that commonly came from animal source food and was not available in raw mature soybean.

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The protein and fat content per 100 g dry weight of tempeh is higher than per 100 g dry weight of soybean. Tempeh fermentation increases protein digestibility and free amino acid content, and the availability of other macronutrients through hydrolysis and reduction anti-nutrient such as phytate, saponin, and protease inhibitors, making it an even better plant-based protein source than soybean. The nutrient content and availability in the originated soybean remain important as it will support the microbial growth. Tempeh consumption is associated with cholesterol reduction in blood and helps prevent cardiovascular diseases (Kris-Etherton et al. 1999; Mangkuwidjojo et al. 1985). It also shows diarrhea prevention effect, which improves its role in food safety area (Kiers et al. 2003). Tempeh has also found its way in the global market with the increasing findings of its benefits and the growing lifestyle toward plantbased food. At the current time, tempeh has been produced commercially in Japan, India, the USA, Canada, European countries, Australia, and New Zealand.

6.3

Natto

Natto is produced through fermentation of soybean by Bacillus subtilis. It originates and an important commodity in Japan. Natto is not the only soy-based Bacillus fermented product. In other countries, Bacillus fermented soy food has also been traditionally integrated into their national culture, such as chongkukjang in Korea, kinema in India, and thuanao in Thailand. Natto has a dark color, pungent but pleasant aroma, and sticky viscous coating with cheese texture. It can be served as it is or used as a seasoning agent with raw or cooked seafood, meat, and vegetables. Natto contains higher vitamin C content than soybean seed and has approximately 43, 24, 12, and 10% dry weight of protein, fat, fiber, and sugar content, which is a higher proportion compared to soybean. The proportion (but not the content) of several minerals, such as calcium, iron, sodium, zinc, manganese, and selenium, in natto are also higher than those in soybean. The peptide, free amino acids, ammonia, saccharide hydrolysis products, and minerals produced during fermentation constitute the characteristic flavor of natto. The sticky substances covering the well-fermented natto are composed of polyglutamic acid and levan (fructan) (Claus 1986). The B. subtilis fermentation also produces proteases and amylase that help with other food digestion processes inside the human body (Ferrari et al. 1993). Serine protease of subtilisin is shown to degrade Gly m Bd 28K (Ogawa 2000). Serine protease is also recorded to show fibrinolytic activity (Sumi et al. 1990), the formation of blood clots from platelets and blood-derived proteins (fibrin), which prevents extended bleeding and promote healing. Both catalase and subtilisin produced during natto fermentation exhibit a growth-promoting effect on fecal microflora (Terada et al. 1999), which adds more to its hypoallergenic character (Kalliomaki et al. 2001), as well as providing positive impact to gut health (Hosoi et al. 2000) and immune function (Pelto et al. 1998). The natto quality is affected by the soybean quality and B. subtilis (natto) strains. Japanese domestic soybeans such as ‘Suzuhime’, ‘Suzumaru’, ‘Kosuzu’,

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and ‘Natto-shoryu’ are preferred for natto production because of their small seeds (5.5–7.3 mm) or extra small (< 5.5 mm) in size, although there are natto produced from midsize or large-seeded soybeans. The seed size was reported to affect negatively with the activities of subtilisin alkaline protease that play roles in protein degradation and intensity of the taste and smell of natto. Therefore, natto made from larger seed soybean have weaker smell while those from extra small seed may have excess fermentation and stronger taste (Takahashi et al. 1996). Natto producers prefer soybean with yellow seed due to unappetizing appearance and lack of aroma character of brown and black soybean. It is just recently that black soybean natto is being on the shelf with highlights on the higher content of polyphenols. Other than its morphological characters, the soybean contents also play an important role in producing high-quality natto. Higher sugar content is associated with better taste and flavor production as it also has a positive correlation with the bacteria growth as B. subtilis natto strain can utilize di- and oligosaccharides but not starch and fiber. Smaller seed size soybean varieties are also associated with higher sugar content and therefore preferable for natto production. The protein content and profile of the originated soybean also affect the natto quality as B. subtilis natto strain utilize protein, peptides, and amino acids for their growth. Soybeans with high protein content are preferred. Among Japanese domestic soybean used for natto production, ‘Suzuhime’ and ‘Zizuka’ cultivars are highly regarded starting ingredient as they have high protein content, bright color, and polished appearance (Hosoi and Kiuchi 2003). In natto processing, soybeans are washed, soaked, and steamed prior to the B. subtilis (natto) spore inoculation. The inoculated beans are then packed and left for solid-state fermentation. Overnight soaking in cold water and steaming of the beans facilitates water hydration, bean swelling, and denature undesirable protein. Steaming also removes contaminant and pathogenic bacteria. Right after steaming, while the beans are still hot, B. subtilis (natto) spore suspension is sprayed onto the bean. The fermentation is set on 40  C with 85–90% humidity whereas the humidity is reduced to 75 and 55% in the following 6 and 16 h after fermentation started. Traditionally the inoculated beans were packed in rice straw to maintain warmth and absorb emitted carbon dioxide during the initial stage of fermentation.

6.4

Miso

Miso is a traditional Japanese fermented soy paste with thick texture, salty taste, savory flavor and aroma, and white, red, or brown color. It has high protein and low-fat content. Miso is often used as a soup base though it may also be used for meat and seafood seasoning prior cooking, or as condiment in many traditional Japanese dishes. There are two steps in miso production. First is koji production. In this process, Aspergillus fungi is inoculated to growth materials. The most common growth material is rice, although koji can also be produced using barley, or soybeans (Shurtleff and Aoyagi 2018). Second is the fermentation of boiled soybean by salt

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and koji. In this step, koji interacts with salt and moisture to induce the yeast and bacteria growth of miso. Miso fermentation period is 1 week to 3 years, and the color and flavor intensity increase with longer fermentation time (Ogasawara et al. 2006). According to the amount of salt and length of fermentation, miso can be classified into white, red, or dark miso (Katz 2012). White miso uses more koji, less salt, and applies shorter fermentation time, while dark miso is the opposite, and red miso is in between the arrangement of white and dark miso. Traditionally, miso was a homemade but commercial production is a major form since 1980. About 90% of miso produced in Japan came from factories (Shurtleff and Aoyagi 2018). The commercial miso production was boosted by mechanization, the availability and usage of commercial strains, standardization of processing methods, and the improvement of packaging and sterilization process (Shurtleff and Aoyagi 2018). Not all soybean can meet the quality parameters of soybean suitable for miso production. And of them that are suitable, most of them are Japanese domestic soybeans. The requirements for soybean to be selected for miso production include white hilum color, light yellow color of cotyledon, a high water-absorbing capacity during soaking, softness, sucrose content, and protein content. Though the color requirements might slightly change due to the popularity of high polyphenol of the darker color soybean, in general light yellow soybeans were assumed to give a more appetizing end product in the miso production. As miso end product is in the form of paste, the soft structure and the high water absorbing capacity is important to ensure targeted tenderness after soybean cooking. The water absorbing capacity also correlates with higher carbohydrates that gives even more free sugars. Other than influencing the taste of the end product, free sugars along with free amino acids availability prior inoculation are known to support the microbial growth during miso fermentation. Soy-fermented products similar to miso include tauco from Indonesia and also gochujang and doenjang from Korea. The tauco production differs from miso in terms of soybean form and the mold employed. The soybean preparation is similar without the mashing process. The soaked and cooked bean is fermented with salt and tempeh starter or combination of Rhizopus oligosporus, R. oryzae, and A. oryzae. Both gochujang and doenjang are fermented soybean paste that employ Aspergillus mold and brine fermentation. The soybean preparation is similar to miso with an additional process of square forming the mashed cooked soybean and drying them into large bricks. Inoculation of Aspergillus is done directly to the dried soybeans for 20–90 days resulting in fermented soybean bricks, called meju. Meju is the intermediate product that will be processed into either gochujang, or ganjang and doenjang, the trinity of Korean traditional condiments (Patra et al. 2016). In traditional production, Meju is broken down into small pieces and put into onggi, Korean traditional earthenware for storage or fermentation. To create gochujang, the meju is mixed with red chili powder, glutinous rice powder, salt, garlic, and onion, and then sweetened with a little sugar syrup and aged in onggi, a type of Korean earthenware (Song et al. 2021). To create ganjang and doenjang, brine is added to the broken meju and salt fermentation inside the onggi was performed for about 2 months creating the liquid part (kanjang) and the solid part (doenjang) (Patra et al. 2016).

Nutraceuticals in Soybean: Biosynthesis, Advanced Genetic Research,. . .

6.5

347

Third-Generation Product from Soy Processing

In the first generation of soy processing, whole soybean is being used, for example, in the production of tempeh and natto. The second-generation soy products refer to those coming from part of the soybean such as soybean oil, soy milk, and soy sauce. The third-generation products are targeted compounds that are isolated or fractionated from soy. The third-generation products are commonly components with high benefits for specific health uses which are required in higher amounts than those that can be acquired by only consumption. The production commercially of thirdgeneration products require solid scientific evidence of the component benefit, as well as advance investment in technology and therefore the products are commonly having a high economic value. Up to this book is being written the following thirdgeneration products from soy processing have been commercialized either as supplement or food ingredients: isolate soy protein, soy peptides, soy isoflavone/ phytoestrogen, soy lecithin, soy fiber, soy phytosterol, and soy oligosaccharides. Protein and bioactive peptide contents of soybean contribute to its potential to prevent lifestyle-related diseases (Yoshikawa and Tsuruki 2005). Soy peptides have been reported to have hypocholesterolemic (Sugano et al. 1988), hypotriglyceridemic, hypotensive, anticancer, and immunomodulating activities while also having an impact on the regulation of food intake. While the roles of dietary peptide in nutrition have been well established, soy peptides have been used in the formulation of functional foods (Takamatsu 2005) to relieve sports fatigue and stress, overcoming obesity, lowering blood cholesterol, hypoallergenic food, and seemed to have a future in alleviating stress and improvement of brain function. Hypocholesterolemic nature of soy protein comes from its hydrophobic highmolecular-weight peptides left after digestion that binds to bile acids (Carroll 1991). The bile acid–binding ability of soy peptide increased fecal excretion of bile acids and reduced cholesterol level in serum and liver. Soy peptide was also reported to stimulate fat metabolism and suppress fatty acid synthesis, leading to its hypotriglyceridemic activity.

7

Conclusion

Numerous studies have been conducted on nutritional content and physiological benefits beyond nutrition of soybean seeds as well as the regulation of biosynthesis of these components. Knowledge on nutritional values and bioactive content of soybean seeds can be utilized to increase their content in current soybean varieties through breeding. The availability of next-generation sequencing technologies, high-density genotyping platforms, and soybean reference genomes have accelerated the elucidation of genetic basic of the biosynthesis of these compounds. The knowledge of genetic basis of these traits enables breeders to select potential breeding lines efficiently using DNA markers. The breeding lines then can be utilized to produce soybean-based food products that are not only nutritious but also meet the diverse needs of consumers and the food industry.

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Nutraceutical Potential of Rapeseed: Breeding and Biotechnological Approaches Mehak Gupta and Gurpreet Kaur

Contents 1 The Crop Rapeseed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Nutraceutical Profile of Rapeseed Oil and Meal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Rapeseed Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Rapeseed Meal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Growing Importance of Rapeseed Nutraceuticals in Face of Chronic Diseases and Malnutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Attempts to Enhance Seed Oil Content in Rapeseed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Mapping for Oil Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Characterization of Genes Involved in Oil Biosynthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Improvement in Fatty Acid Composition of Rapeseed Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Reduction in Erucic Acid (EA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Progress to Increase Oleic acid (OA) or/and Reduce Linolenic Acid (LiA) in Rapeseed: HOLL (High Oleic and Low Linolenic) Varieties . . . . . . . . . . . . . . . . . . . . . 5.3 Increase in Eicosapentaenoic Acid (EPA) and Docosahexaenoic Fatty Acid Levels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Minor Oil Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Phytosterols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Tocopherols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Progress to Improve Rapeseed Meal Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Reduction of GSLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Reduction of Other Antinutritive Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Seed Storage Protein (SSP) Content and Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Rapeseed (Brassica napus L.) is a prime oil crop of the world that also provides proteins for the livestock feeding. This crop has achieved remarkable success over the past few decades by development of canola types with low erucic acid M. Gupta · G. Kaur (*) Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_13

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and glucosinolate contents. Considerable progress has also been made to enhance the oleic acid content of seed oil. In contrary, little attention has been paid to improve other health-promoting constituents such as phytosterols and tocopherols of the oil. Following oil extraction, rapeseed meal is an excellent source of vitamins, minerals, and high-quality proteins that can help to mitigate human malnutrition. However, poor digestibility, dark color, and bitter taste of rapeseed meal due to anti-nutritional factors like phenolics, phytates, and crude fiber make the meal unacceptable for human consumption. It is crucial to further improve the nutraceutical and commercial value of rapeseed by increasing the content of health-benefitting components while simultaneously minimizing the antinutritive components to the acceptable amounts. To achieve the objective, it is imperative to understand the consolidated genetic architecture of oil and meal quality traits in connection to each other. Recent advances in next-generation sequencing technologies, availability of pan-genome of B. napus together with improved bioinformatic and genome editing methodologies would be very useful to reveal the genetic networks and identify high-resolution sequence-based markers for marker-assisted breeding for quality traits in rapeseed. Keywords

Rapeseed · Nutraceutical · Marker-assisted selection · Erucic acid · Glucosinolates

1

The Crop Rapeseed

Brassica napus L. (AACC, 2n ¼ 38) is one of the six species comprising the wellknown U’s Triangle of Brassica, a genus that belongs to the plant family Brassicaceae. It is an allopolyploid crop species that possesses the full chromosome complements of two diploid species, known to be B. rapa and B. oleracea (Chalhoub et al. 2014). A few interspecific hybridization events followed by genome duplication are believed to occur in the recent past (26%). However, in addition to genetic factors, environmental conditions also play a major role in the variation of protein content. Besides, enrichment of grain micronutrient status, the bioavailability of nutrients needs to be increased through conventional breeding by reducing antinutritional elements and escalating compounds that encourage iron assimilation. For example, phytate declines the bioavailability of micro-nutrients; therefore, the reduction in phytate level is the utmost tactic toward the biofortification of pea. The biochemical pathway of phytate was modified by mutagenesis followed by conventional breeding. In pea, two low phytate mutants, viz., 1-150-81 and 1-2347-144 were developed employing chemical mutagenesis in base parent CDC Bronco (Warkentin et al. 2012). To understand the effects of environmental conditions on phytate level, multilocation testing was performed and results revealed that inorganic phosphorus, phytate phosphorus, and level of iron were significantly changed over the locations (Warkentin et al. 2012). In another study, it has been found that the reduced phytate in pea is operated through a recessive single gene (Rehman et al. 2012). The carotenoid enriched peas seeds are part of a biofortification approach and recently reported that the green-colored cotyledon pea cultivar possesses twice the total carotenoids as yellow cotyledon cultivar. Notably, the genotypic effect influences carotenoid content to a greater extent than the environment. The association analysis revealed that iron content has a positive correlation with iron bioavailability, while phytate content has a negative correlation with iron bioavailability. In addition, lutein content has a positive correlation with iron bioavailability.

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The conventional breeding approach has been well accepted as it is cost effective, free of synthetic inputs, eco-friendly, and sustainable practice. In spite of the several benefits of employing traditional breeding to bio fortify foods, certain limitations are also there; the first one is dependency on the existing genetic diversity for the trait of interest in targeted crop gene pools, i.e., primary, secondary, tertiary. If substantial diversity is not available then biofortification through conventional breeding in the targeted crop is not possible. For instance, biofortification in oilseed could be possible only through transgenic approach owing to its narrow genetic base, low heritability, and linkage drag with targeted traits. Furthermore, nutritional profiling of contemporary crops and crop wild relatives (CWR) has demonstrated that some of the crops are poor in nutritional worth than their wild colleagues. Though, the exploitation of CWR in biofortification could be a difficult task in owing to their cross incompatibility, tight linkage with undesirable traits with targeted traits and least representation of CWR in world gene bank. Another important drawback of conventional breeding is that it takes years to develop a cultivar because incorporation of a trait into an elite cultivar has to go through an exhaustive selection procedure at least till sixth generation. Conversely, many approaches are there like high-throughput phenomics platforms, seed chipping technology, molecular markers, genomic selection, genome editing, and speed breeding that can hasten the varietal improvement process. Of which, some of the methods are expensive than traditional breeding methods, therefore, not used extensively in public breeding institutes albeit they are more efficient. Last but not least, in conventional breeding before releasing, the cultivar must be tested in different environments because genotype-by-environment relationship can considerably affect cultivars phenotypic and nutritional performance. Consequently, a biofortified variety may lose its improved nutritive trait owing to the genetic-by-environment interactions. Laborious and time-consuming nature of conventional breeding and availability of genomic tools prompted plant breeders to go for marker assisted selection. Biotechnological approaches have played an instrumental role in crop improvement and could be helpful in designing food crops with targeted nutritional profile. The amalgamation of conventional breeding with biotechnological intervention has resultant improved cultivars with high nutritional profile. The most important activity for the detection and development of molecular markers associated with micronutrient is précised phenotyping of available germplasm accessions and successive discovery of contrast genotypes for trait of interest, which will be used to develop appropriate experimental populations. Mapping populations will be exploited to identify molecular markers related with the trait of interest. Ultimately, the identified genetic variants accountable for an amplified level of the targeted nutrient should be introgressed in targeted genotype to emanate the nutrient rich cultivar, either by traditional breeding or by current biotechnological tools. Genomic resources let breeders to take advantage of the existing genetic variability more precisely; hence, duration and expenses could be reduced significantly. In traditional plant breeding, the selection is carried out just considering phenotype, however, by applying genetic and genomic apparatus, allelic variants can be allied with phenotypic variation, which allow early selection of the plant. In the recent past, efforts

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were dedicated in pea towards development of genomic resources (Krajewski et al., 2012). Unlike other legume crops, in pea genomic resources have not been exploited judiciously in order to identify genes or quantitative trait loci (QTLs) for nutritional traits. However, some of the researchers revealed the genetic mechanism of iron content in seeds and successfully obtained markers and quantitative trait loci to facilitate breeding programmes (Gali et al. 2018). Most recently, SNPs markers associated with iron and zinc were identified using a group of genotypes of pea (Diapari et al. 2015). On a similar note, SNPs marker allied with Ca, Mg, carbohydrates, and inositol were found in pea (Cheng et al. 2015). Besides, QTLs were also identified on LG3, LG4, and LG7 for Fe status in a RIL population derivative of Carrera/CDC Striker. By employing genome wide association approach in a recombinant inbred line (RIL) population of Kiflica/ Aragorn, many QTLs have been discovered for seed weight and mineral concentration (Ma et al. 2017). Biotechnological approaches have been utilized to support breeding programs, such as marker-assisted selection (MAS) which dramatically accelerated the achievement of breeding for biofortification program. Unfortunately, pea being oldest domesticated crop is still lagging behind in the case of genomic resources. To accelerate genomics enabled biofortification there is urgent need of creation of more genomic resources and their judicious utilization towards identification of genes/QTLs that will be an important asset in MAS. The brief description of markers and molecular mapping of nutrient related genes and QTLs is presented in Sect. 6 of this chapter. If genetic variability is inadequate for trait of interest then the desired variability may be created by adopting induced mutagenesis or modern techniques like genome editing (i.e., clustered regularly interspaced short palindromic repeats (CRISPR) – associated system (CRISPR/Cas). The beauty of genetic engineering is that it can utilize indefinite group of genes for the targeted transfer and expression of desirable characters from one organism to another without any taxonomic constraints. Besides, if a targeted nutrient is not synthesized in a particular crop, to biofortify such crops for that specific nutrient transgenic is the best option. Using transgenic approach genes were integrated in the genome of the targeted crop to manufacture the micronutrient, for instance, golden rice. Initially, transgenic technique involves considerable duration, labor, and expense, but in a long term, it is lucrative and sustainable unlike other biofortification approaches. On this line biofortification efforts are underway in several crops including pea and brief account of transgenic and genome editing is elaborated in respective section of this chapter.

4

Pea Genetic Resources

4.1

Current Germplasm Holding

Pea is considered as the world’s oldest domesticated crop and is cultivated globally in temperate climates. It has been cultivated from Neolithic period as a food and vegetable crop. Pea is the fourth largest pulse crop cultivated mainly for a pulse,

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fodder, and vegetable. As per the information in the GENESYS portal, total collections of pea amounted to 33,023 accessions, conserved in different genebanks in the various parts of the world (Genesys portal, accessed on August 30, 2022). United Kingdom has the highest holding of germplasm collections followed by Australia, India, and Lebanon. The list of major genebanks holding pea germplasms are given in Table 2.

Table 2 Holdings of pea collections in different genebanks Holding Institute S. No Gene bank code 1 GBR247 GBR165 GBR016 GBR017 GBR006 2 AUS165 3 VIR 4 USDA 5 NBPGRa 6 LBN002 7 ITA436 ITA394 8 UKR001 9 SWE054 10 BGR001

Total collections 3360 3298 2110 132 02 7325 6790 5400 4680 4596 1716 1225 2704 1749 1570

Country of holding institute United Kingdom

Total collections 8902b

Australia Germany United States of America India Lebanon Italy

7325b 6790c 5400d 4680a 4596b 2941b

Ukraine Sweden Bulgaria

2704b 1749b 1570b

GBR247-Germplasm Resources Unit, John Innes Centre. Norwich Research Park – NR4 7UH, Norwich, United Kingdom GBR165-EURISCO (European Search Catalogue for Plant Genetic Resources) – https://www.sasa. gov.uk/ GBR016-EURISCO (European Search Catalogue for Plant Genetic Resources) – https://www. igergu.ibers.aber.ac.uk/ GBR017-EURISCO European Search Catalogue for Plant Genetic Resources https://www. gardenorganic.org.uk/ GBR006-EURISCO European Search Catalogue for Plant Genetic Resources http://www2. warwick.ac.uk/fac/sci/lifesci/acrc/gru AUS165-Australian GrainsGenebank, Agriculture Victoria, Australia LBN002-International Centre for Agricultural Research in Dry Areas ITA436-Consiglio NazionaledelleRicerche – Dipartimento di Scienze Bio-Agroalimentari, Italy UKR001-Institute of Plant Production n.a. V.Y. Yurjev of UAAS, Ukraine SWE054-Nordic Genetic Resources Centre (NordGen). Växthusvägen 24–23,456, Alnarp, Sweden BGR001-Institute of Plant Genetic Resources “KonstantinMalkov”. StrDrujba 2–4122, Sadovo, Plovdiv district, Bulgaria a NBPGR- National Bureau of Plant Genetic Resources, New Delhi, India-http://www.nbpgr.ernet. in/Research_Projects/Base_Collection_in_NGB.aspx-. Accessed on August 30, 2022 b Source: https://www.genesys-pgr.org/-. Accessed on August 30, 2022 c VIR-N.I. Vavilov Research Institute of Plant Industry, St. Petersburg, Germany d USDA-Plant Germplasm Introduction and Testing Research Station, Pullman, United States of America

Nutrient-Dense Pea (Pisum sativum L.): Genetics. . .

4.2

673

Primary Genepool

The genepool concept was given by Harlan and De wet to categorize the hybridization relationship of a species with other species and grouped into three categories, primary, secondary, and tertiary genepool. However, advancement in plant genomics has led to another set of category defined by Hammer and Gepts and Papa as a fourth genepool (quaternary genepool), and it could include any synthetic strain revealed in nucleic acid sequence, DNA or RNA that do not exist in nature. According to this concept, the species which are in the primary genepool of a crop can be easily crossable and develop fertile progenies during hybridization. It includes plants of the same species or closely related species wherein genes tradeoff can be done between the species by simple crosses, and it is considered as the précised material in term breeding importance. It is believed that P. sativum was domesticated in the Near East about 11,000 years ago, likely from P humile (also known as Pisum sativum subsp. elatius). In the Pisum genus, the species which are in the primary genepool are Pisum sativum subsp. elatius, Pisum sativum subsp. elatius var. brevipedunculatum, Pisum sativum subsp. elatius var. elatius, Pisum sativum subsp. elatius var. pumilio.

4.3

Secondary Genepool

The species in the secondary genepool results partial fertile hybrids on crossing with primary genepool. It includes plants related to the species. The introgression of gene from such material to primary genepool is feasible but difficult. The Pisum species which comes under this category are Pisum abyssinicum and Pisum fulvum.

4.4

Tertiary Genepool

The species in this category will lead to the synthesis of sterile hybrids on crossing with primary genepool, and the transfer of genes between the species is possible only with the help of exceptional techniques like bridge crossing, genetic recombination, etc. The species of peas which are under tertiary genepool are Vavilovia formosa.

4.5

Sources of Donor Genes

The proper utilization of genetic resources in any breeding program mainly relies on a valorization of genetic resources for targeted traits. In case of evaluation of existing germplasm, accessions for quality traits pea is still lagging behind other legume crops. During last 3–4 decades, concerted efforts have been made to characterize the pea germplasm for various nutritional traits, i.e., protein, iron, zinc, RFOs, and antinutritional traits (Tzitzikas et al. 2006; Tosh and Yada 2010; Harmankaya et al. 2010; Dahl et al. 2012; Demirbas 2018). Most importantly, the landraces and CWR could serve as arsenal of genetic resources to breed new crop varieties suitable for

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changing environmental and demographic conditions. Legume crop holds an exceptional status in world agriculture being protein rich and inbuilt ability of environmental nitrogen fixation, but bioavailability of protein is a major concern, because, the protease inhibitors decreases protein digestibility and are operated by two genes (TI1 and TI2) in pea. Recently, a wild pea (P. elatius) accession got mutated within the aforesaid both genes and considerably decreased the scale of protease inhibitor activity improving the bioavailability of amino acid (Clemente et al. 2015). Gawłowska et al. (2017) evaluated about 248 accessions belonging to P. abyssinicum, P. elatius, P. fulvum, P. syriacum, P. sativum subsp. asiaticum, P. sativum subsp. transcaucasicum, P. sativum subsp. sativum convar. Axiphium, convar. Medullosaccharatum and medullare, convar. Vulgare and convar. Speciosum for RFOs. The results revealed that highest content of total soluble carbohydrates and total RFOs were noticed in accessions with wrinkled seeds and the lowest content in the wild species P. fulvum. Therefore, P. fulvum could be used as valuable source in conventional breeding to further decrease RFOs. Most recently, in another study Ethiopian pea (Pisum sativum var. abyssinicum) landraces were examined to estimate the nutritional composition, and results demonstrated abundant variation for nutrients and mineral content. The protein content varied from 21.63% to 28.13%. Furthermore, all the landraces had high potassium (41.43–74.21 μg/g) and low sodium (0.93–27.65 μg/g) content (Gebreegziabher and Tsegay 2020). These finding clearly indicated that Ethiopian pea is an excellent source of protein, and other minerals and could be utilized in regular breeding to develop cultivars with enhanced nutritional status. In addition, P. fulvum, P. sativum subsp. elatius var. pumilio, P. abyssinicum, and P. sativum subsp. elatius also provide resistance against many biotic and abiotic stresses like rust, pea weevil, powdery mildew, ascochyta blight, broomrape and bruchid, bacterial blight, frost tolerance. P. sativum subsp. sativum var. arvense has potential to be utilized as feed and fodder for livestock. The given genotypes could be used in conventional and molecular breeding to develop high yielding and nutritionally enriched cultivars, experimental populations and established marker trait association to identify genes/QTLs. Henceforth, intensive efforts should be made toward the evaluation of available germplasm accessions for various nutritionally important traits, which could be used in breeding program to develop nutrient dense cultivars that would be helpful in the improvement of the overall health status of resource poor and vegetarian population of developed and developing countries.

5

Genetic Mechanism of Nutritionally Important Traits

Pea protein is complicated genetically because of various multigenes families encrypting protein composition and content. Pea seed protein composition is operated genetically; however, environmental factors and postharvest processing circumstances also influences protein magnitude (Bourgeois et al. 2009; Bourgeois et al. 2011). An earlier report identified that three QTLs accounting for 45% of the total variation of protein (Tar’an et al. 2004). On a similar note, 14 QTLs were identified

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across the environment affecting the development of genes controlling pea seed protein concentration (Burstin et al. 2007). Another report in which a RIL population was used and detected significant QTLs on linkage group V for total protein content (Irzykowska and Wolko 2004). Similarly, in two populations synthesized by hybridization between a small-seeded and protein rich line and two diverse large-seeded and high-yield potential cultivars detected QTLs for seed protein content located on LG V (Krajewski et al. 2012). Recently, a QTL on LG VI was detected that demonstrated 45% of the seed protein content variation. In addition, singlenucleotide polymorphism (SNP) within O2like gene in pea was identified having a significant consequence on seed protein content. O2like genes in pea have resemblance to Opaque2 (O2) of maize, a bZIP transcription regulating factor that influences starch and protein content (Jha et al. 2015b). The pea seed protein largely comprises of globulins legumin and vicilin storage proteins, where its synthesis is operated by at least 40 genes and 10 different genetic loci (Casey et al. 2001). Nevertheless, as mentioned above pea seed protein content as quantitative trait, therefore, single gene mutations may be less efficient to influence total protein concentration if not the mutation is at a locus which encrypt substantial part of phenotypic variation (Bourgeois et al. 2009; Rayner et al. 2018). For legumin biosynthesis up to four genes which are defined by distinct loci have been reported and approximately there are 10–15 genes which produce protein (Casey et al. 2001). Interestingly, the loci control starch synthesis can also influence the legumin synthesis due to mutant alleles at loci (r and rb controlling starch synthesis and synthesis of large subunit of ADP-glucose pyrophosphorylase, respectively) influence the expression of legumin genes and ultimately manipulates the ratio of legumin/vicilin in the overall seed protein (Casey et al. 2001). Another important storage protein is vicilin that is a poor source of sulphurcontaining amino acids in comparison to legumins. Consequently, these amino acids designated as negative factor in pea, and increment in their level is considered as a prime objective toward the nutritional upgrading. In cotyledon, vicilin produces amyloids which are protein aggregates having unique physiochemical attribute like resistance to alimentary tract digestion (Antonets et al. 2020). Using proteomics technique, 24 genes were found controlling vicilin synthesis in pea and also develop a reference map of pea seed proteome (Bourgeois et al. 2009). Interestingly, Domoney et al. (2013) demonstrated how the fast-neutron mutagenesis at single loci knocks out multiple genes which could influence synthesis of vicilin and some other proteins. On a similar note, a mutant allele at Vc-2 position influenced the manufacture of vicilin polypeptides and that subsequently impacted seed protein concentration (Chinoy et al. 2011). In a QTL analysis, genes operating legumin, convicilin and vicilin have been identified (Bourgeois et al. 2011). In another investigation, wherein characterize loss of function of abi5 mutant in pea and noticed that vicilin content reduces in mutant, and genes encrypting other major protein were upregulated (Le Signor et al. 2017). The gel permeation chromatography demonstrated the proportion of legumin and vicilin in total protein predominantly remains under genetic control, however, agronomic components also influences (Mertens et al. 2012). Most recently, reference genome of pea has been available which offer great opportunity for seed protein

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annotation. The genome assembly was explored, and DNA sequences programming proteins counting legumin, vicilin, and convicilin have been recognized. In the pea reference genome alleged RY motifs (CATGCATG) up regulated three storage protein genes by regulating their expression (Kreplak et al. 2019). There are two proteins, i.e., lectin and albumin which are undesirable due to poor digestibility and allergic effects (Le Gall et al. 2007). In earlier reports it is mentioned that, the lectin is determined by LecA gene that control symbiotic interactions of roots with rhizobium (Díaz et al. 1989). Most recent study illustrated the nodulation competence of the LecA mutant and observed that it is similar to that of wildtype pea, advocating that absence of lectin is not affecting the symbiotic interaction (Rayner et al. 2018). For pea albumin 2 (PA2) and PA1 coding nine and eight gene sequences, respectively, could identify using the reference genome (Kreplak et al. 2019). In another study, the null mutant for PA2 was hybridized with cultivar (Birte), and a RIL population was synthesized. The examination of RIL exhibited that the lines deficient to PA2 were higher in seed nitrogen content probably owing to a surprising upsurge in the production of other seed proteins (Vigeolas et al. 2008). Backcrossing with cv. Birte has also revealed the PA2 function in plant growth and response to stresses (Vigeolas et al. 2008). This was further validated in a report wherein it is explained that the polyamine and spermine can unite to the homolog of PA2 in grasspea (Gaur et al. 2010). Two major Lipoxygenases (LOX) polypeptides are present in pea seeds, viz., LOX-2 and LOX-3, of which, one catalyze the creation of compounds which are not preferred by customers (Forster et al. 1999). Both polypeptides are programmed by two or three genes at the lox locus situated on LG IV (North et al. 1989). However, a null mutant for LOX2 has been identified from P. fulvum collection at the John Innes Centre. Further analysis of this locus in this particular accession portrayed that the decrease in LOX-2 mRNA was not the outcome of a loss of LOX genes, but it happened owing to the one or multiple insertions, deletions, or substitutions into the LOX-2 promoter of the null mutant (Forster et al. 1999). Being rich in sulphurcontaining amino acids, pea albumins are vital component for human, and questions are often raised over low level of these amino acids in legumes. Hence, pea albumins can offer a nutritional advantage in respect to amino acid configuration, notwithstanding, apprehension are also there regarding its allergic properties and resistance to ingestion of these proteins in human guts. Starch, being a most dominating storage carbohydrate in pea seeds accounts for about 50% of dry seed weight. It is composed of various segments considering their configuration and digestibility (Lockyer and Nugent 2017). In his experiment Mendel used seven external characteristics of pea, including variation in mature seed shape, i.e., round or wrinkled to established laws of inheritance (Bateson 1901). Initially, this trait or locus was named as rugosus (gene symbol “r”) by white (1917) derived from Latin for wrinkled or shriveled shape and is located on chromosome 7 (Bhattacharyya et al. 1990). Later on, another locus named rb produces wrinkled shape seeds was recognized (Kooistra 1962). The r locus conferred a prominent visible effect on seed appearance that resulted due to the dominant effect of this locus on the configuration of pea seed. There is an unambiguous variation in starch

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metastasis of round and wrinkled seeds of peas (Bhattacharyya et al. 1993). In addition, round seeded pea contain more starch than wrinkled seeded and elevated proportions of amylopectin to amylase. The rr seeds possess greater concentration of free sucrose than round seeded, which leads to the higher osmotic pressure and water content and bigger cell size of wrinkled seeds (Wang et al. 1987). The rr seeds lose a greater part of their volume in the course of seed development, and because the testa does not contract along with the cotyledons, it shrinks to produce the wrinkled appearance (Casey and Davies 1993). Later on the wrinkled phenotypes were also reported to occur due to mutation at other loci counting rb and rug 1, 2, 3 (Wang and Hedley 1991). Notably, all the mutant, viz., r, rb, and rug have analogous exterior appearance, however, r mutants can be discriminate based on the starch granule morphology (Bhattacharyya et al. 1990). Starch granules are build up of two types of starch polymers, i.e., amylase and amylopectin. The proportion of amylose in the wrinkled seeds is around twofold of round seeds (Bhattacharyya et al. 1990). Indeed, the wrinkled seeds developed due to mutation in the gene that governs starchbranching enzyme isoform I (SBE1) by inclusion of a transposon-like component into the coding arrangement. Two isoforms of starch-branching enzyme, viz., SBE1 and SBEII are expressed in the initial and later phase, respectively, of embryo development. SBEI accounted about 1/3 of the amylopectin in matured pea embryos and create a less soluble polymer in comparison to the polymer generated by SBEII which may be more effective in catalysis of short chain production (Burton et al. 1995). The mutations of SBEI significantly reduce the scale of starch and fraction of amylopectin in the wrinkled genotypes than round (Bhattacharyya et al. 1993). The reduction in starch synthesis and failure of amylase to amylopectin conversion mainly happened due to the loss of SBEI enzyme activities. The metabolic proof and decreased SBE activity clearly designated this enzyme as an imperative determinant in starch content of rr embryos (Bhattacharyya et al. 1993). The SBEI play essential role in the construction of usual starch granules that cannot be replaced by other isoforms. In addition, r mutant seeds also demonstrated pleiotropic effects and intricate metabolic instabilities, for example, elevated scale of free sucrose, extra lipid, less legumin, and subsidize seed longevity (Bhattacharyya et al. 1990). In SBEII, gene mutation has not been recognized by the examination of wrinkled seeds which advocated that the mutation of SBEII does not have any role in wrinkled phenotype, and this could be due to minor involvement of SBEII in amylopectin synthesis and subsequent activity in the course of embryo development (Bhattacharyya et al. 1993). Starch debranching enzymes (DBEs) hydrolyze the α-1,6-glucan branches of amylopectin, this step is essential for the regular synthesis of amylopectin by pruning extra branches (Wang et al. 2014). In fact, two categories of debranching enzyme are there, viz., isoamylase (ISA) and pullulanase (PUL) with different amino acid sequences. Both DBEs are present in peas and have important role in starch metastasis during the development of embryo and in starch breakdown in the course of germination (Zhu et al. 1998). During last decade, three genes coding the diverse isoforms of ISA (Psisa1, Psisa2, and Psisa3) have been identified in peas and these are capable to bind to glucan substrate, although Psisa2 deprived of catalytic skill (Hussain and Martin 2009).

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At the end of the twentieth century, four other loci were recognized which influences starch metastasis: lam, rug3, rug4, and rug5. Mutant of rug4 locus causes loss of sucrose synthase (Susy) activity during the development of pea embryo. The rug4 mutant develops wrinkled seed and reduced the starch level in the embryo by affecting the supply for starch biosynthesis (Craig et al. 1998). Another locus rug5 control starch synthase II, and mutation results into modification of starch granule morphological appearance and the configuration of amylopectin (Craig et al. 1998). The lam mutation also influences starch synthase enzyme (starch synthase I) and develop starch with low amylose and high amylopectin (Tahir et al. 2011). Genes governing three isoforms of Susy (SuSy1, SuSy2, and SuSy3) were identified in peas. The starch scale of the SuSy1 embryo is reduced by 30%, whereas the cellulose level remains constant. The SuSy1 isoforms in embryos is essential for starch biosynthesis but not required for synthesis of cellulose (Weber et al. 1998). In pea, rug3 locus is responsible for a plastidial phosphoglucomutase (PGM) enzyme that catalyzes the interconversion of glucose-6-poshpate (Glc-1-P) and Glc-6-P in the cytosol and plastids. Further, five pea mutants at the rug3 locus developed wrinkled seeds with low amylose and starch content. In pea embryos, Glc-6-P is ingress from the cytosol into the amyloplast where it is reconverted to Glc-1-P by the plastidial isoform of PGM by supplying the substrate for starch synthesis (Harrison et al. 1998). The damage of plastidial phosphorylase (Pho1) enzyme causes substantial decline in the starch magnitude and its configuration (Satoh et al. 2008). Other two Pho isoforms, i.e., Pho1 and Pho2 were identified in pea cotyledon, of which Pho2 plays a vital role in starch granule development (Van Berkel et al. 1991). Recent literature reported auxin to play an imperative role in regulating starch accrual in pea seeds (McAdam et al. 2017). The auxin deprived mutant tar2 (tryptophan aminotransferase related 2) develop small and wrinkled seeds with low starch level. The activity of different starch synthesis enzymes and expression of the corresponding genes are condensed in mutants indicative of vital role of auxin in starch accumulation in peas (Meitzel et al. 2021). The above given facts witnesses the magnitude and composition of starch as polygenic traits, and their overall expressions are environment sensitive. Genetic mechanisms of starch metastasis are well explained in cereal crops, while there is little information in case of legumes. Recently, 132 SNPs were detected within the genes involved in carbohydrate metabolism, of which, 4 SNPs were associated with genes AGPase_L1,GBSSI, and SBEII operating amylose concentration, and 10 SNPs were associated with genes SBEII, SuSy2, and Sps (Jha et al. 2015b). Partial sequences of 25 candidate genes which represent 16 enzymes concerned to starch metastasis were characterized using a group of 92 pea accessions, which revealed 3 candidate genes (r, UGPase, AGPS2) to be associated with amylopectin chain length distribution (CLD), while amylose level has association with the r locus (Carpenter et al. 2017). Most recently, a linkage map has been developed for starch scale using two RIL populations and detected QTL for starch magnitude on LG2b and LG4a in one population, while QTL for starch content on different linkage groups, viz., LG1a, LG3b, LG3c, and LG7a in other population (Gali et al. 2018). The GWAS has been performed for seed starch content in a panel of 135 pea

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accessions and subsequently identified 9 SNP markers positioned on LG2, LG3, LG5, and LG7, and one scaffold was associated with starch level (Gali et al. 2019). Genes encrypting raffinose (rfs) and stachyose synthases (sts) were aligned to LG III and V, respectively (Ellis et al. 2018). Gali et al. (2018) explored three RILs and identified two QTLs for acid detergent fibre (ADF) positioned on LG 4 and two QTLs on LGVII. In another population, QTLs for ADF have been detected on LG IV and LG VIIa. For neutral detergent fibre (NDF), QTLs on LG Va, Ia, IV, and VIIa have been detected. Similarly, in another study five SNPs associated with level of ADF have been identified on chromosomes 5, 6, and 7, and eight on chromosomes 2, 3, 5, 6, and 7, of which, two markers linked with both type of fibre were positioned on chromosomes 6 and 7 (Gali et al. 2019). Further analysis of identified QTLs and discovery of new QTL could pave the way towards improved discerning of the genetic machinery operating the starch metabolism in pea seeds. Genes associated with starch synthesis are thoroughly examined in pea, consequently offers worthy opportunities for the manipulation and modification of pea starch magnitude and configuration considering further scope. In addition, it has been noticed that the total starch level reduces in peas having high protein, and high amylose level increases resistance to ingestion of the starch (Shen et al. 2016). Number of attempt has been made to decipher the genetic foundation of seed iron level and consequently detected various molecular marker and QTLs to facilitate breeding programme. Most recently, five QTLs have been detected which are linked with seed iron content in pea localized on LG VII and II (Ma et al. 2017). Of them, three QTLs appeared in close vicinity to markers earlier associated to iron concentration in a study wherein a set of 94 accessions was used (Diapari et al. 2015). QTLs for seed iron content were also reported in three RILs which were derived by hybridization among European and Canadian cultivars (Gali et al. 2018). QTLs for iron concentration in seed were identified on LG IIIb, however, on linkage group VII none of the QTLs for iron content were noticed (Diapari et al. 2015; Ma et al. 2017). This might be owing to the diverse parents used in mapping population or the derived material was evaluated under multilocation testing (Gali et al. 2018). For rest of the essential micronutrients like zinc and selenium very limited efforts were dedicated to understand genetic foundation of their concentrations in pea seeds. However, two SNPs were identified to be linked with high zinc concentration on LGIII (Diapari et al. 2015). Similarly, one more study also reported a QTL on LG III which elucidating maximum magnitude of phenotypic variance for zinc content in seeds (Ma et al. 2017); nevertheless, the SNPs identified by Diapari et al. (2015) were not in adjacent to the QTL located on LG III. A recently conducted study identified four QTLs concerning to zinc level in seeds along with a noteworthy locus on LG III (Gali et al. 2018). Overall, the above narrated finding suggested that the pea genomic region on LG III have huge potential towards the escalation of zinc content in seeds and identification of the core genes/genomic regions that would be helpful for accelerating biofortification programmes in pea. On a similar note, selenium content in seeds was examined in three RILs and of which, in two populations several QTLs located on LG VII, IV, and Vb were detected and strong environmental effect was also observed (Gali et al. 2018). The chemical

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resemblances between selenium and sulphur demonstrated that the QTLs recognized in this report may be loci that encrypt sulphate transporters (White 2016).

6

Molecular Mapping of Health-Related (HR) Genes and QTLs

Understanding the genes and genomic location governing valuable trait requires the comprehensive study of whole-genome sequence data. Pea genome consists of seven pairs of chromosomes with a huge genome size of 4.45 Gb (Gali et al. 2018), mostly comprised of transposons and other mobile elements of Ty3/gypsy family (Macas et al. 2007). The generation and accessibility of genomic tools have been slowed down in pea owing to the late availability of reference genome in public database. With the advancement of cutting-edge tools and cost effectiveness of Next Generation Sequencing Techniques (NGS), momentum jump has been achieved towards marker development and subsequent molecular breeding efforts for enriching pea genomic resources. Pea researchers walked a long way with the partnership of International-National consortium for making available the complete pea genome sequencing platform and paved the way from conventional to molecular breeding era (Madoui et al. 2015). A molecular marker is a segment of DNA linked to a particular locus in the genome. Molecular markers facilitate to perform MAS for the trait of interest at early growth stage and accelerate genetic progress, thus expedite genetic mapping and QTL analysis. Development of first and second-generation markers like RFLP, RAPD, AFLP, SSR, and CAPS aided for diversity studies and pea genetic improvement towards gene tagging and introgression (Aubert et al. 2006; Burstin et al. 2007; Bourgeois et al. 2011; Ma et al. 2017). With the availability of high throughput SNPs, genotyping has become more efficient, thanks to technological improvements in sequencing and generating genotyping platforms over the past 10 years in pea. Presently SSRs and SNPs markers are the prime choice of the plant breeders owing to their reliability, robustness, and wide distribution throughout the genome. Several SNP arrays have been generated by deploying genotyping-by sequencing (GBS) approach and transcriptome data of diverse pea germplasm set (Kaur et al. 2012; Tayeh et al. 2015a; Alves-Carvalho et al. 2015). Genetic map construction in pea dated back early in 1925 through development of six linkage group, however markers development in relation to HR genes were scarce (Table 3). Mapping efforts concerning seed protein quality was initiated to detect the QTL (Tar’an et al. 2004; Bourgeois et al. 2011; Tayeh et al. 2015b). Three QTLs were detected that was associated with seed nitrogen/protein content (Tar’an et al. 2004). Among these, two QTLs were mapped on LG-III and VI and can explain 45% of the total variation in seed protein and likely to be associated with seed storage protein albumin. Another study detected a total of 14 QTLs explaining 9–46% variation, positioned at 160 cM and 170 cM on LG V, thus highlighted the presence of two QTLs with opposite effects (Burstin et al. 2007). Except for the fabatin-like genes on linkage group VII, none of the QTLs were directly linked to seed protein gene loci. Irzykowska and

Vicilin

Trait Protein

114 plants of F2 generation from a cross between Wt10245  Wt11238

139 RILs between Térèse’ and K586 F2 generations derived from Wt11238  Wt3557 Wt10245  Wt11238 RIL population from the following crosses: VavD265  Ballet (211 individuals) Cameor  Melrose (120 individuals) Kazar  Cameor (84 individuals) Kazar  Melrose (118 individuals) 157 RIL population between ‘Cameor’, ‘VavD265’, and ‘Ballet’

5 QTLs (LG-II, V, VII)

14 QTLs (LG-I, III, IV, V, VI, VII)) 77 QTLs (LG-V) and 11 LGs

7 LGs

7 QTLs (VicB, Vc-2-5 (LG II, III, V)

Mapping Population 88 RILs between ‘Carneval’  ‘MP1401’

QTL /LGs 03 QTLs (LG-VI))

Table 3 Consensus mapping strategies concerning HR genes in Pea

Seed protein markers

282 morphological, isozyme, AFLP, ISSR, STS, CAPS, and RAPD markers SNPs, SSRs, RAPDs, RFLPs AFLPs, etc. 6188 8503 7013 3917

Marker system 193 AFLPs 13 RAPDs 01 STS (sequence tagged site) marker 204 markers morphological, isozyme, AFLP, ISSR (Inter Simple Sequence Repeat), STS, CAPS and RAPD markers 249 SSRs

Bourgeois et al. (2011)

–

(continued)

Tayeh et al. (2015a)

Burstin et al. (2007) Krajewski et al. (2012)

Irzykowska and Wolko (2004)

References Taran et al. (2003)

794.9

853

1113

2416

Map distance (cM) 1274

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Phytic acid and phosphorus content

82 QTLs

Seed mineral content Dietary fibre, seed protein, minerals, and phytate acid

16 QTLs (LG-Ib and LG4a: Seed protein) (LG-IV, VII and VIIa: acid detergent fibre) (LG-Ia, IV, Va, and VIIa: neutral detergent fibre (LG-IIb and LG-IVa, LG-Ia, LG-IIIb, LG-IIIc, and LG-VIIb: seed starch content) (LG-IIIb: seed Fe content) (LG-VII, LG-IV, and LG-Vb: seed Se content 4 QTLs for seed Zn content (two on LG-VI; one each on LG-Ia and LG-IIIb) (LG-IIIa, LG-V, and LG-VIa: seed phytate content) 7 LGs

QTL /LGs 7 LGs

Trait Starch metabolism

Table 3 (continued)

RIL population with 94 individuals derived from cross between 1–2347-144  CDC Meadowe

Mapping Population Térèse  K586 (Pop1, 139 F7 RILs) Térèse  Champagne (Pop2, 164 F8 RILs) RIL population (F6) derived from ‘Kiflica’ and ‘Aragorn’ RIL population developed from PR-02 (Orb  CDC Striker), PR-07 (Carerra x CDC Striker), and PR-15 (1–2347144  CDC Meadow)

341 SNPs

2066, 3023, and 3444 SNPs for three different population

114 SSRs and 1608 SNPs

Marker system 63 SNPs and 15 Indels markers, CAPs, and RAPDs

771.6

951.9, 1008.8 and 914.2 cM for three different populations

1310.1

Map distance (cM) 1458

Sindhu et al. (2014)

Ma et al. (2017) Gali et al. (2018)

References Aubert et al. (2006)

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Wolko (2004) deployed a RIL population between large- and small-seeded parents (Wt10245  Wt11238) and reported five substantial QTLs for total protein content accounting for 18.3–25.5% of variation. Among these, three (prot-2, prot-3, and prot-4) were located in LG-V with high LOD values (4.4–5.3), whereas the two other QTLs, viz., prot-1 in LG-II and prot-5 in LG-VII revealed lower LOD (2.2 and 2.4). Afterwards, mapping populations were developed by crossing three pea cultivars with differential protein content, viz., Cameor, VavD265, and Ballet. In Cameor  VavD265, 7 LGs were detected with 6952 markers with a map length of 752.6 cM, whereas, in cross between VavD265  Ballet, 850.1 cM map distance was covered with 6188 markers (Bourgeois et al. 2011; Tayeh et al. 2015b). Globulins are the main kind of seed storage protein in peas which is further classified in to 11 S legumins and 7 S vicilins/convicilins. The distribution of these two classes of protein is influenced by genotype and the growing environments (Casey et al. 2001). Genetic analysis and DNA hybridization as well as sequence characterization of DNA and protein in pea detected four classes of legumin and five classes of 7 S protein genes and their respective QTLs (Newbigin et al. 1990). For fine characterization of globulin protein genes in pea, integrating two-dimensional electrophoresis (2D)-based proteomic and QTL mapping strategy was deployed involving 157 RIL population developed from three contrasting parents (Cameor, VavD265, and Ballet) with differential protein level by the Composite Interval Mapping (CIM) procedure. It was detected that 40 multigene families were involved in regulation of pea storage proteins where four gene classes were uncovered which are responsible for legumin biosynthesis in pea (Casey et al. 2001). The framework of three sets of legumin genes were well characterized by utilizing F2 and F6 individuals from selected crosses exploring RFLPs. They were mapped on chromosome 7 close to r, while the other maps to a locus near a on chromosome 1. The third class of legumin gene was likewise connected to a, according to the findings of one of the tested crosses (Domoney et al. 1986). The mRNA from developing pea seeds was used for construction of cDNA plasmid bank for characterization of vicilin coding genes, which further unveiled two different classes of vicilin genes that were initially synthesized as provicilin with subsequent processing at C-terminal peptide as well as post translational endo-proteolytic cleavage. The accumulation of convicilin was chiefly regulated by cis-regulatory regions whereas; both cis- and trans-regulatory regions were governing vicilins and legumins accumulation in pea. In vitro protein digestibility and protein composition appear to be significantly regulated by LG-IIa (Bourgeois et al. 2011). Recently, genome sequence information of the reference genome of cv. Cameor annotated 12 genes for legumin; 9 genes for vicilin and 2 genes for convicilin along with RY motifs (CATGCATG) associated with seed specific transcriptional regulation in pea (Kreplak et al., 2019). LecA gene was discovered which is the key gene governing lectin content in pea as well as associated with symbiotic N2 fixation with Rhizobium in pea nodules (Domoney et al. 2013). Lectin is considered as an antinutritional factor due to poor digestibility. A knockout mutant was detected in pea with loss of function of LecA gene without any compensation regarding symbiotic N2 fixation (Rayner et al. 2018). Similarly, PA2 gene is governing another undesirable protein fraction albumin in pea seed.

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Reference genome of cv. Cameor detected all together nine genes governing PA2 and eight genes coding for another major albumin, PA1 (Kreplak et al. 2019). However, in recent investigation it was detected that pea albumin having adequate sulphur containing amino acids which are essential for human being. Lipoxygenases (LOX), a subclass of seed storage proteins that controls the production of hydroperoxides from fatty acids, were found in pea. In pea seeds, there are two major LOX polypeptides (LOX-2 and LOX-3), and two or three genes at the lox locus positioned on LG IV encode these polypeptides (North et al. 1989). In recent years, attempt has been made to tag the genomic regions related with carbohydrate metabolism and seed storage protein accumulation in pea and to detect the SNP variation related with various HR genes (amylose, total starch, and crude protein concentration) for future marker assisted breeding programme (Jha et al. 2015b). High density linkage map with less confidence interval is useful for QTL detection of major agronomic and economic traits in many crops including pea. GBS approach with simultaneous SNP detection has been extended for construction of high-resolution maps in pea to unveil the QTLs for seed mineral content (Ma et al. 2017). The study detected 6, 37, and 46 QTLs for seed weight, seed mineral content, and seed mineral concentration respectively, which explained phenotypic variation (PV) ranging from 2.4% to 43.3%. Another study by Gali et al. (2018) also deployed GBS approach for simultaneous detection of genome wide SNPs and QTLs associated with dietary fibre, seed protein, and mineral concentration using three RILs namely, PR-02, PR-07, PR-15 derived by cross of Orb  CDC Striker, Carrera  CDC Striker, and 1–2347-144  CDC Meadow, respectively, at Crop Development Centre (CDC), University of Saskatchewan, Canada, employing single seed descent method. QTL mapping was executed employing CIM through QTL cartographer. Seed protein concentration QTLs have been detected on LG-Ib and LG-IVa of PR-02 with maximum LOD values of 5.0 and 3.4, respectively, and accounted up to 15.9 and 10.3% of the PV. Notably, QTLs were also detected for different fractions of dietary fibers. Four linkage groups were found for acid detergent fibre (ADF), including two QTLs on LG VII that individually accounted for 28.0% and 26.2% of the PV in the PR-02 population. Significant QTLs for ADF were discovered on LG IV and VIIa for the PR-07 population. With regard to neutral detergent fibre (NDF), in the PR-02 population, identified QTLs on LG-Va, and in the PR-07 RIL population, identified QTLs on LG Ia, IV, and VIIa, accounting for up to 44% of phenotypic variance. On LG-IIb and LG-IVa of PR-02, LG-Ia, LG-IIIb, LG-IIIc, and LG-VIIb of PR-07, numerous QTLs for seed starch content were found. The largest LOD value represented by LG-VIIa was 8.4, and 20.1% of the phenotypic variance was elucidated by this QTL. QTLs for seed iron (Fe) concentration were found over four LGs of PR-02, and the QTL on LG-IIIb was highly significant with LOD values of 7.6 and 6.3. Based on two phenotypic experiments, three linkage groups of the PR-02 population were shown to have QTLs for seed selenium (Se) content. Of these, LG-VII embodied QTLs within the same linkage group region in both trials and demonstrated a phenotypic variance up to 15.0%. In two of the six trials for seed Se content in the PR-7 population, QTLs on LG-IV and LG-Vb were found. For seed zinc (Zn) concentration, four QTLs were found: two on LG-VI of PR-02 and one

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each on LG-Ia and LG-IIIb. With a LOD value of 13.7 and a PV of 25.8%, the QTL on LG-IIIb was highly significant. QTLs for seed phytate content were mapped in PR-15 population. Three linkage groups, viz., LG-IIIa, LG-V, and LG-Via were shown to include QTLs for this characteristic, with the LG-V QTL being found in all four trials evaluated in two sites (Gali et al. 2018). The recognized QTLs linked with HR genes in pea are valuable treasure for marker assisted breeding programme for improving seed quality traits in pea.

7

Map-Based Cloning of HR Genes/QTLs

An innovative method that pinpoints the underlying origin of a genetic variation is map-based cloning (MBC). Without prior knowledge of specific genes, MBC can access a practically infinite resource of induced and natural genetic variation. Therefore, scientists are attempting to use this method in model plants to clone the orthologues genes in related plant species. Medicago truncatula and Lotus japonicus are considered as model legumes as these are diploid with eight and six chromosomes, respectively, and having relatively small genome size of around 500 Mb (Cannon et al. 2009). These model legume species facilitate to transfer the genomic resources into target legume crops for better understanding of development as well as evolutionary biology. High degree of synteny between model species and pea facilitate to deploy cross species gene-based markers for unveiling the homologous genome segments. A comparison of the genomes of pea (P. sativum) and alfalfa (M. truncatula) has been done through comparing linkage maps of both the species to understand the co-linearity between the linkage groups and the presence of conserved and orthologues genes using gene-based RFLP and PCR markers (Kalo et al. 2004). Considering the model legume M. truncatula, it was discovered that the ABI5 transcription factor is a key factor in determining the accumulation of seed globulins. This study also characterized loss-of-function abi5 mutants in pea, showing that the mutants had higher levels of other important seed proteins and lower vicilin concentrations (Le Signor et al. 2017). Further, SNP variation was detected in O2like gene in pea that is similar to opaque2 in maize, a bZIP transcription regulating factor with having significant role in management of protein content (Jha et al. 2015b). Starch or amylum is the most abundant form of storage carbohydrate in pea seeds composed of amylose and highly branched amylopectin. Attempt has been made to characterize the key genes for getting better insight about the starch biosynthetic pathways through generating array of mutants with differential starch concentration. Various mutant forms (Iam, r, rb, rug3, rug4, and rug5) have been generated targeting the key enzymes like granule bound starch synthase Ia (GBSSIa) (Dry et al. 1992), starch branching enzyme I (SBEI) (Burton et al. 1995;), ADP-glucose pyrophosphorylase (AGPase) (Burgess et al. 1997), phosphoglucomutase [Plastidial] (PGM) (Harrison et al. 1998), sucrose synthase (SuSy1) (Barratt et al. 2001), and starch synthase II (SSII) (Craig et al. 1998). The generated mutant in pea with altered or absence of the targeted genes also exhibited pleotropic effects on the seed shape

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changed from round to wrinkled with a 50% reduction of starch content and an increase in lipid and sucrose content. Large and stable genomic clones for crops with complex genome are frequently created and stored using bacterial artificial chromosomes (BACs), which are employed as a genomic library. The first BAC library in pea consisting of partially HindIII-digested DNA fragments with a mean size of 105 kb was developed considering pea cv. PI269818 for isolation of disease resistance genes and genes governing economic traits (Coyne et al. 2007). A sequence-based physical mapping technique called whole genome profiling (WGP) makes use of sequence tags produced by NGS. A recent study by Gali et al. (2019) utilized pea cv. ‘Cameor’ for construction of BAC library for localization of the gene through physical mapping for further structural and functional annotation followed by genome sequencing as well as positional cloning of the mined genes having economic importance.

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Omics Approaches in Relation to HR Genes

In recent decades, the newly emerging omics-based approaches facilitate towards locating genes/QTLs governing the traits of interest and further make available the robust markers platform for marker assisted breeding programme. Microarray or RNA sequencing technology as well as the recent cutting edge NGS based transcriptome assembly can generate valuable genomic resources and markers that can be assembled for construction of highly saturated genome maps, improve genotyping technologies (sequencing and resequencing), and identification of additional markers like SNPs and EST-SSRs (Kaur et al. 2012). Pea had relatively meagre genomic resources compared to the model legume until the first pea reference genome assembly (Kreplak et al. 2019) became available. This offered pea genomics-assisted breeding a new momentum. The estimated pea genome is 3.92 Gb in size, spanning 88% of the reported genome assembly. This reference genome assembly has offered several contigs, transcripts, markers, and GBS platforms for their further annotation. The creation of integrated linkage maps and the comparison of markers across various studies have been made easier by the alignment of sequence reads to a common reference genome sequence. In pea, the transcriptome analysis has been mostly carried out to unveil the host pathogen interaction and pathogenesis related proteins (Winter et al. 2016), genes, and transcripts related with the mechanism underlying abiotic stress resistance (Chen et al. 2013; Bahrman et al. 2019), and there is scantiness regarding transcriptome analysis in relation to HR genes. However, the gene expression atlas developed in pea using the variety “Little Marvel” (Franssen et al. 2011) or by using another two cultivars (Kaspa and Parafeld) by Sudheesh et al. (2015) and Alves-Carvalho et al. (2015) generated valuable transcripts atlas that will further boost up reverse genetic studies, fine mapping, allele mining, and identification of candidate genes. In another study, eight diverse accessions of pea and five RIL populations were deployed to generate genome wide transcriptome-based SNP arrays using Illumina

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Golden Gate assay (Sindhu et al. 2014). A total of 1536 polymorphic SNP loci were found, and by combining them with previously discovered anchor markers, the first high-density pea SNP map was created, delineating all seven linkage groups. This breakthrough can expedite tagging and mapping the QTLs related with agronomic and HR genes for boosting up seed quality for betterment of human nutrition. Using 12 RIL populations, GenoPea 13.2 K SNP Array has been developed in pea with construction of collinear map of 3918–8503 SNPs and a total of 12,802 transcript-derived SNP markers were available for future genomic study (Tayeh et al. 2015a). The high resolution and high-density consensus map developed with 15,079-marker will further facilitate the identification of ohnologue-rich regions within the pea genome thus strengthen pea genomic resources. Proteomics and Metabolomics are new emerging arena to study the function of novel proteins associated with various physiological and biological events. Proteomics defined as the high-throughput study of proteins has assumed a leading role in plant biological research and stress responses owing to availability of plant genome sequence information in public database. Moreover, with the advancement of various high throughput approaches like mass spectrometry (MS), Tandem mass spectrometry and other quantitative assay coupled with bioinformatics approaches have offered easy characterization, quantification, and further validation of array of functional proteins from any crop species (Ramalingam et al. 2015). In addition to proteomics, metabolomics is a crucial tool of functional genomics that links cellular metabolic activity with phenotypes through the identification and quantification of metabolomes, a collection of metabolites or small molecules, within a cell, tissue, or organism (Weckwerth 2003). Like transcriptome assembly in pea, most of the proteomics and metabolomics study has been carried out in relation to characterization of proteins and metabolites underlying stress responses (Ranjbar Sistani et al. 2017) with meagre information that can uncover novel HR proteins and metabolites in pea. Improving vicilin concentration in pea is the need of the hour as vicilin having lower concentration of sulphur containing amino acid in comparison to legumin. Proteomic study by Bourgeois et al. (2009) was the first pea mature seed proteome reference map, detected 156 novel proteins including 24 different genes controlling vicilin in pea. This study provided the diversity in relation to seed storage proteins and their plasticity during plant developmental stages. Later on, integrating proteomic and QTL mapping approaches, Bourgeois et al. (2011) developed proteomic atlas from the RIL population developed from three pea genotypes Cameor, VavD265 and Ballet and unveiled the genetic architecture regarding the seed proteome variability. Protein quantity loci (PQL) were hunted for 525 spots noticed on 2-D gels and interestingly, most PQL were mapped in clusters. This demonstrated how a few numbers of loci were responsible for accumulating the major store protein families. Previous study also reported how fast-neutron mutagenesis may be used to disrupt many genes at a single locus, affecting the accumulation of vicilin and other proteins (Domoney et al. 2013). It has been demonstrated that a mutant allele at the Vc-2 gene affects seed nitrogen contents and major vicilin polypeptide synthesis (Chinoy et al. 2011).

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Genomics-Aided Breeding for HR Traits

Seed quality traits including protein, carbohydrate, and mineral concentration are mostly complex and quantitative in nature. Multiple genes, environment, and genotype  environment interaction create ambiguities towards expression of these HR genes related with seed quality. Besides biparental linkage mapping, genome wide association mapping (GWAS) is nowadays used to understand these complex traits. Association mapping based on the principle of linkage disequilibrium can capture greater number of alleles originated during the course of evolution. The first GWAS was applied to understand the allelic variation regarding starch metabolic pathway that can affect the chain length distribution (CLD) and starch structure in a set of 92 diverse pea accessions (Carpenter et al. 2017). Associations for polymorphisms in seven potential genes and the Mendel’s r locus were discovered that govern round versus wrinkled seed phenotype. Amongst seven significant candidate genes, three genes, viz., r (rugosus allele), UGPase (UDP-glucose pyrophosphorylase), and AGPS2 (ADP-glucose pyrophosphorylase S2 subunit) portrayed a significant relationship with CLD, and the amylose content was linked with the r locus. Another GWAS was performed to track the loci related with agronomic, seed morphology, and seed quality traits (protein, carbohydrate, and fiber content) using 135 diverse accessions of pea from 23 different pea growing countries. GBS approach was also integrated for detection of 16,877 high quality SNP arrays. Five SNPs were recognized that were being linked with ADF concentration (positioned on chromosomes 5, 6, and 7), whereas, eight SNPs were detected with NDF content (chromosomes 2, 3, 5, 6 and 7). Four markers (Chr1LG6_176606388, Chr2LG1_457185, Chr3LG5_234519042, and Chr7LG7_8229439), located on chromosomes1, 2, 3, and 7, were connected with seed starch content, and one marker (Chr3LG5_194530376) identified was linked with seed protein concentration (Gali et al. 2019). Dissanayaka et al. (2020) used a panel of 135 diverse pea accessions for identification of trait associated SNP arrays for an association study concerning seed mineral content. Out of the 16,877 SNP markers deployed for association analysis, five each were recognized for relationship with Fe and Zn content in pea seeds. Markers detected in the present study related with Fe (Chr5LG3_204123886) and Zn (Chr5LG3_1921113554, Chr5LG3_197808492, and Sc4026_15361) would be useful for MAS programme in pea for rapid generation of cultivar with good seed quality traits. With the expansion of pea genomic resources in recent years, particularly the reference genome sequence, which makes it easier to comprehend the allelic variation underlying the important traits and facilitate towards development of better pea cultivars opting various genomics assisted breeding programme like haplotypebased breeding, genome editing, and genomic selection (GS). Plant breeders are quickly adopting GS, a potent breeding technique, especially for traits that are challenging to detect. In the next 10 years, breeding for increased pea productivity and quality is anticipated to benefit from the use of GS in conjunction with highthroughput SNP genotyping platform. In order to maximize genomic prediction for complex traits, GS models depend on training and testing populations and enumerate the Genomic Estimated Breeding Values (GEBV). Comparatively to conventional

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marker-assisted selection, GS enables the simultaneous selection of several attributes. GS programme initiated in pea with the easily observable agronomic traits characterized by high heritability like seed weight, days to flowering, pods per plant, Ascochyta blight resistance, etc., with prediction accuracy of 0.19–0.84% (Tayeh et al. 2015b). These research findings offer “proof of concept” for the idea that selecting pea breeding lines for HR traits in various environments can be made more effective in the future by combining superior training and test population sets and integrating robust and reliable prediction models and high-density marker system.

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Other Approaches and Future Strategies for Modulating HR Genes in Pea

Like other legume, pea seeds are also fantastic treasury of dietary protein. Although they consist of numerous protein classes that resist proteolysis to varying grades and are adversely correlated with quality and animal health. Protease inhibitors, specifically trypsin/chymotrypsin inhibitors (TI), present in the pea seeds are regarded as antinutritional components that usually require additional heat-treatment or other processing for use as feed for cattle and poultry (Patto et al. 2015). Pea seed TI are mostly of the Bowman-Birk inhibitor (BBI) category, with wide genetic variation exists regarding inhibitory activity (Domoney and Welham 1992). Two closely related genes, TI1 and TI2, have been found to encode the two primary BBI isoforms that are expressed in pea seeds and mostly inhibit both trypsin and chymotrypsin (Domoney et al. 2002). Exploitation of a Targeted Induced Local Lesions IN Genomes (TILLING) population in pea facilitated to detect novel genetic variants regarding various classes of inhibitor proteins, which can provide deeper insight regarding the structure-function and relationships within the protease inhibitors. Moreover, targeted screening within TI1 gene of pea enabled to detect natural variant devoid of inhibitory activity class of seed protein. A total of 13 nucleotide changes have been detected including seven changes were in noncoding regions and six alterations influencing the coding sequence that generated missense mutations. It was validated from the finding that the substitution of C77Y in the mature mutant inhibitor completely eliminated inhibitor activity. A P. elatius accession as a double null mutant for the two closely linked genes TI1 and TI2 was detected with extremely low seed protease inhibitory activity, and introgression of the mutant into cultivated germplasm has been achieved (Clemente et al. 2015). In pea, attempt has been made to introduce antisense construct for genetic manipulation of the inhibitor genes. The promoter from TI gene has been isolated, characterized, and reintroduced within pea by Agrobacterium-mediated genetic transformation, as a TI promoter-bglucuronidase (GUS) gene fusion. A second gene construct uses the TI1 gene promoter for direct exhibition of an antisense TI gene. Seed TI activities in some transformed pea lines with this construct were tested, and it was detected that the activity of inhibitor genes was reduced significantly (Welham and Domoney 2000). Attempt was also being made to understand the structural relationship of multiple genes responsible for governing legumin

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biosynthesis in developing pea seeds by Casey et al. (2001). Earlier report confirmed that in pea seeds legumin biosynthesis was usually modified due to the nature of the r loci governing the structural gene for starch-branching enzyme isoform I (SBE I) or rb responsible for synthesis of ADP-glucose pyrophosphorylase. This ultimately led to changes in the ratio of legumin: vicilin within the total seed protein in pea. It was detected that the double mutants (rrb) showed a significant drop in the quantity of legumin without altering the concentration of vicilin. Further expression of cloned legumin cDNA construct of pea in transgenic wheat seeds able to synthesize an array of paracrystalline legumins. This evidence validated that, in spite of the presence of multiple genes with structural heterogeneity, the pea legumin comprises of a single type of subunit. In pea, there is no successful report of genome editing due to the calcitrant nature of this legume. However, the most recent approaches, such as de novo meristem induction by and DNA transfer in mature plants enabled by nanomaterial offered great promise towards the development of genome-edited pea plants with advantageous features. With the advent of affordable genomic tools, access to pea genomic resources will increase in the near future. This will help to close knowledge gaps regarding allelic variation and the genetic mechanisms governing the metabolism of various HR genes and will hasten the creation of novel pea cultivars through genomic assisted breeding programme with refine HR genes for the benefit of mankind.

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Future Prospects and Conclusion

Malnutrition has become a serious problem owing to the insufficient supply of nutritionally balanced diets to the resource-poor folks of under developed/developing countries in the prevailing changing climate. Unfortunately, hidden hunger is steadily increasing due to the reliance of the increasing population on cereal based carbohydrate rich diet which is deprived of vitamins and essential micronutrients. Various strategies such as dietary supplementation, fortification of foods, and agrofortification are being used to upsurge the disposal of an essential nutrient in the daily diet, but these are not accessible to the resource-poor population. Thus, genetic biofortification of edible crops through conventional and modern breeding approaches is considered as most effective, economic, and sustainable approach for the entire stakeholders. In the case of peas, very limited systematic efforts have been made to assess the extent of variability for nutritionally important traits such as protein, iron, zinc, folate, vitamins, phenolic compound, and selenium. In addition, the variability so far observed could not be exploited judiciously in the regular breeding programme toward genetic biofortification. Therefore, it is the need of the hour that large-scale high-throughput phenotyping should be done to unveil the genetic variability that exists in peas. Unfortunately, unlike other legume crops, restricted efforts have been made to explore the magnitude of variability that exists

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for nutritionally important traits in landraces and crop wild relatives. Thus, proper phenotyping of landraces and CWR needs to be done and subsequently, the identified sources must be embraced in a regular breeding programme to develop nutrientenriched pea. Indeed, conventional breeding approaches have been well accepted by the public as being cost-effective, free of synthetic inputs, and eco-friendly and sustainable practices, but their laborious and time-consuming nature prompted plant breeders to opt for genomics-assisted breeding. Genomic resources facilitate breeders in the exploitation of existing genetic variability more precisely with minimum duration and expenses. Unlike other legume crops, in pea, the genomic resources have not been developed and exploited to identify genes/QTL for nutritional traits. Therefore, the recently emerged omics-based approaches need to be embraced to facilitate the identification of genes/QTLs and further make available the robust markers platform for a marker-assisted breeding programme in pea. Microarray or RNA sequencing technology and NGS-based transcriptome assembly could be used to generate valuable genomic resources and markers that can be assembled for the construction of highly saturated genome maps, improve genotyping technologies (sequencing and resequencing), and identification of additional markers like SNPs and EST-SSRs. Notably, the pea reference genome assembly offered several contigs, transcripts, markers, and GBS platforms for their further annotation. The transcriptomics, proteomics, and metabolomics analysis have been mostly carried out in pea to unveil the mechanism underlying abiotic and biotic stress resistance, and there is insufficiency regarding analysis of nutrition-related genes, which must be accelerated. However, most recently few valuable transcripts atlas has been generated that will further boost reverse genetic studies, fine mapping, allele mining, and identification of candidate genes. In case genetic variability is inadequate for traits of interest then the desired variability may be created by adopting induced mutagenesis or modern techniques like genome editing (i.e., clustered regularly interspaced short palindromic repeats (CRISPR)- associated system (CRISPR/Cas). However, to date, there is no successful report of genome editing due to the recalcitrant nature of this legume. In addition, exploitation of a Targeted Induced Local Lesions IN Genomes (TILLING) population in peas would facilitate the detection of novel genetic variants regarding various classes of inhibitor proteins which can provide deeper insight into the structure-function and relationships within the protease inhibitors. Another powerful tool is a genetic transformation or transgenic, which possess many advantages including its long-term sustainability. In addition to protein, peas also consist of numerous antinutritional components specifically trypsin/chymotrypsin inhibitors (TI) and phytic acid. Therefore, gene silencing approaches should be used to down-regulate genes encoding antinutritional compounds without affecting other pathways and processes involved in plant growth and development. The advent of affordable genomic tools and access to reference genome will help to reduce the knowledge gaps regarding allelic variation and the genetic mechanisms governing the metabolism of various nutrition-related genes and will hasten the creation of novel pea cultivars with refined HR genes for the benefit of mankind.

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Breeding Cowpea: A Nutraceutical Option for Future Global Food and Nutritional Security Avi Raizada, Dhanasekar Punniyamoorthy, Souframanien Jegadeesan, Tesfaye Walle Mekonnen, and Penna Suprasanna

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Genetic Resources and Genetic Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Nutritional and Nutraceutical Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Protein Profile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Minerals and Vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Lipids and Fatty Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Carbohydrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Health-Promoting and Health-Protective Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Protein Hydrolysates and Peptides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Phenolics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Resistant Starch and Fiber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Anti-nutritional Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conventional and Molecular Approaches for Enhancing Nutritional Potential . . . . . . . . . . . 6 Genomics of Nutritional Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Future Perspectives and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Nutritional security has become the prime concern for world agriculture through improving the nutritional quality of crop plants and fostering nutri-rich crops. Malnutrition in the developing countries and increased occurrence of several A. Raizada · D. Punniyamoorthy · S. Jegadeesan (*) Nuclear Agriculture & Biotechnology Division, Bhabha Atomic Research Centre, Trombay, Mumbai, India e-mail: [email protected] T. W. Mekonnen Department of Plant Sciences, University of the Free State, Bloemfontein, South Africa P. Suprasanna (*) Amity Institute of Biotechnology, Amity University of Maharashtra (AUM), Mumbai, Maharashtra, India © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_26

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health problems are now the major global challenges. Cowpea is a prime pulse legume grown predominantly in the tropical and subtropical regions of Asia, Africa, Latin America, and southern Europe. Compared to other legumes, cowpea is more resilient to climate change and exhibits wider adaptability in different agro-ecologies. Cowpea is a rich source of protein, carbohydrates, minerals, and vitamins with a low lipid content. Besides being nutritious, its health-promoting and health-protective effects are based on resistant starch, dietary fiber, phenolics, and peptides. Major health beneficial features of cowpea include anti-cancer, antidiabetic, anti-inflammatory activities, and controlling blood lipid content. Germplasm evaluation is paving way for the identification of lines with high protein content and minerals (Cu, Fe, Zn, Mg, Ca, and K) which could be used in breeding for new biofortified cowpea cultivars. Development of databases such as “EDITS-Cowpea” for enabling exploration of cowpea traits, especially those related to grain quality-related traits and “Cowpea Genomics Initiative” for applying modern molecular genetic tools for gene discovery will foster research aimed at cowpea improvement. This chapter examines the nutritive value of cowpea with more emphasis on the remarkable nutraceutical properties of cowpea and suggests taking cowpea forward as a future smart crop for tackling global food and nutritional security. Keywords

Pulses · Cowpea · Nutritional security · Nutraceuticals · Human health

1

Introduction

Food security for the increasing world population has become a main concern for agricultural scientists and plant breeders, and it is estimated that food production will have to be enhanced by 70% by 2050 (Fróna et al. 2019). The problem is also compounded by the nutritional deficiencies and malnutrition among the world population (FAO 2017). This necessitates that the food will have to be produced in abundance and of good nutritional quality to ensure health of the future generations. Plant breeding over the past several decades has made a significant contribution to the development of high yielding and good quality varieties of cereals, pulses, and oil seeds besides other economically important plants to meet food and nutritional security (Mir et al. 2021). Cowpea (Vigna unguiculata), also known as China bean, black-eyed bean, blackeyed pea, and southern pea, is an annual bean plant and member of the family Fabaceaeor Leguminosae (Oyewale and Bamaiyi 2013). It is widely cultivated in the tropical regions of the world such as Southeast Asia, Africa, Southern United States, and Latin America due to its ability to tolerate climate change. Cowpea is majorly produced and consumed in Sudano–Sahelian zone of sub-Saharan Africa (Boukar

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Nigeria Burkina Faso Tanzania Kenya Myanmar

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Niger Ghana Cameroon Mali Sudan

Fig. 1 Global cowpea production (FAOStat 2020)

et al. 2019). According to FAOSTAT report, worldwide production estimates over 8.9 million metric tons of dry cowpeas in 2020, of which 86% is contributed by Western Africa, mainly Nigeria and Niger with 6.3 million tons (FAOSTAT 2020) (Fig. 1). At the global level, cowpea production and yield have been increased by 88% and 35%, respectively (Nedumaran et al. 2015). Most of the cowpea plant parts are edible and consumed such as juvenile leaves, growing points, raw/immature pods, green seeds, and dried/desiccated seeds (Gerrano et al. 2019). It is grown for its high nutritious value, and recently there has been focus on the nutraceutical properties and as fodder for livestock. Moreover, due to its nutritious leaves, cowpea is placed in class of the chief vegetables in Africa and Asia (Mohammed et al. 2021). The American Pulse Association declared “pulses” as the most versatile and multifaceted food source in the world (American Pulse Association 2020). It is often referred to as a multi-potential crop for the future (Fig. 2). Cowpea is reported to have originated from Africa (Lazaridi et al. 2016). A recent study in 2020 (Herniter et al. 2020) based on genetic, textual, and archeobotanical data proposed a likely spread of cowpea from the two centres of domestication, West Africa and East Africa. From West Africa cowpea was spread by the Bantu migrations south to the equatorial rainforest and then to the areas of modern Sudan, South Sudan, and Ethiopia followed by diversion into three branches. First branch leads to Southern Africa, which joined the East African domestication. Second branch directed toward north up to the Nile and Egypt and remained there up to 2500 BCE. Later on, by 400 BCE, this branch had entrenched itself as a key food crop in the Mediterranean basin and moved to Spain’s colonial holdings in the New World, including the modern south-western United States. The third branch makes its way to the west coast of India by 1500 BCE through the “Sabaean lane” in modern Yemen and then spreads to Southeast Asia. Vigna unguiculata ssp. unguiculata var. spontanea is assumed to be the wild ancestor of cultivated cowpea that is grown in sub-Saharan Africa (Pasquet et al. 2021).

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Nutrient-rich (Proteins, minerals and vitamins): Alleviang Malnutrion

Nutraceucal (Phenolics and resistant starch): Health promong and protecve effects

Livestock husbandry: Leaves and vines

Nutrious leaves,

Nitrogen fixaon and Enhancing soil ferlity

pods, flowers Revenue for smallholder farmers

Nitrogen fixaon in soil Climate resilient and Adaptability to less ferle soil

Fig. 2 Multifaceted potentials of cowpea

2

Genetic Resources and Genetic Diversity

Crop genetic resources including germplasm collections are essential for national and global agricultural security. Genetic diversity of crops is important for sustainable development and food security because this gene reservoir will aid in the future in further improvements in the elite cultivars with regard to better performance and well-adaptedness (Pathirana and Carimi 2022). To date several genetic resources have been developed in cowpea to aid in breeding elite varieties. The different forms of these developed genetic resources include physical and genetic linkage maps, genome sequences, databases, microarrays, molecular markers, etc. Few examples of different genetic resources in cowpea are genotyping assays and genetic maps based on single nucleotide polymorphism (SNP), physical maps, mapped quantitative trait loci (QTLs) traits, consensus genetic maps of cowpea (González et al. 2016), reference genome sequence of cowpea (Lonardi et al. 2019), cDNA sequences, unigenes, genic-SSR markers (Mahalakshmi et al. 2007), and linkage maps for cowpea developed using molecular markers and their further refinements through advanced markers (Muchero et al. 2009). Several genetic diversity studies have been conducted to investigate the evolutionary relationships among different genotypes, relationships with wild accessions, origin, taxonomy, domestication, and evolutionary pattern in cowpea. Initially studies were performed using conventional parameters such as allozymes and seed storage proteins that was followed by

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different marker systems such as chloroplast DNA polymorphism, restriction fragment length polymorphism (RFLP), amplified fragment length polymorphisms (AFLP), DNA amplification fingerprinting (DAF) simple sequence repeats (SSRs), cross species SSRs from Medicago, inter-simple sequence repeats, sequence tagged microsatellite sites (STMS), and single-nucleotide polymorphism (SNP) markers. The largest collection of cowpea consisting of 16,569 cultivated accessions from 100 countries and around 1500 wild accessions of vigna is maintained by the International Institute of Tropical Agricultural (IITA). Based on geographical, agronomical, and botanical descriptors, a central group of 2120 accessions and a minor collection of 376 accessions have been established at IITA (Boukar et al. 2019). Other major collections with overlapped data include the US Department of Agriculture–Agricultural Research Service (USDA-ARS) (Griffin, Georgia, USA) with 8379 accessions, the National Bureau of Plant Genetic Resources (NBPGR, New Delhi, India) holding 4003 accessions, and the University of California, Riverside (UCR, California, USA) harboring 5000 accessions and a mini core of 368 accessions. These cowpea accessions exhibited variations among each other with context to several morphological and agronomical traits such as plant pigmentation, plant kind, plant height, leaf type, growth habit, photosensitivity or insensitivity, maturity, nitrogen fixation, fodder grade, tolerance to high temperature and water deficit, root architecture, pod features, seed traits, grain quality and reaction/ response to diseases, root-knot nematodes, insect pests (aphids, bruchid, thrips), and parasitic weeds (Boukar et al. 2020). Large gene bank collections include those of IITA (Nigeria), USDA (Southern Regional Plant Introduction Station, Georgia), World Vegetable Centre (Taiwan), and the N.I. Vavilov Research Institute of Plant Industry (Russia). Padhi et al. (2022) explored 120 diverse cowpea germplasm lines to search for nutri-dense genotypes using biochemical traits and observed broad variability for protein content (19.4 to 27.9%), starch (27.5 to 42.7 g 100 g 1), amylose (9.65 to 21.7 g 100 g 1), TDF (13.7 to 21.1 g 100 g 1), and TSS (1.30 to 8.73 g 100 g 1). The study suggested that the collection showed some nutrient-dense lines having more than a single trait with high nutritional potential.

3

Nutritional and Nutraceutical Profile

The world is facing major critical situations of malnutrition in downtrodden population of developing countries and prevalence of chronic diseases in well-off people in developed countries. Protein energy malnutrition (PEM) is a very serious public health issue in many less developed nations (Bessada et al. 2019). Globally, one-third of all child deaths were estimated to be due to malnutrition, of which 54% occurred in underdeveloped countries (Bain et al. 2013). Thus, there is an urgent need to identify foods that are both nutritious and have nutraceutical properties and to introduce these food types into our regular diet so that their healthprotective and health-promoting effects will help in controlling frequent cases of several chronic diseases.

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Fig. 3 Major nutritional composition of cowpea seeds (based on the data from Gonçalves et al. 2016)

Legumes are well-known for their protein-richness, of which cowpea has gained more attention due to its remarkable nutritional profile and nutraceutical properties that make it unique among other pulses (Dhanasekar et al. 2021) (Fig. 3). Cowpea is known as “the poor man’s meat” because of its protein-rich nature complemented by its less expensive and affordable access to rural poor people (Dugje et al. 2022), and also because the protein content is approximately equal to certain meat types (18–25%). It also has digestible and non-digestible carbohydrates, potassium, and very low lipid and sodium content. The composition of different nutritional components in grains is given in Fig. 4. Cowpea leaves are rich in micronutrients, nutraceuticals, antioxidants (alpha tocopherols, flavonoids, lycopene), and anti-proliferating compounds (Owade et al. 2020). Dakora and Belane (2019) suggested that cowpea leaves could meet the suggested day-today dietary intake requirement of the micronutrients Fe and Zn by consuming 4 mg and 76 mg of leaf on a dry matter basis. Cowpea leaves are a nutritious food source, with an abundance of protein and minerals, digestible and non-digestible carbohydrates, and potassium but low lipids and sodium (Kamara et al. 2010). Leaves show higher nutritional content than grains (Fig. 5).

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Fig. 4 General nutritional profile per 100 g of raw cowpea seeds. (Source: USDA nutrient database)

13 9 60

5.8 14

Moisture Ash

65.2 43

33

Protein Lipid Fibre

4.1 35.9

3.9

carbohydrate

32

Fig. 5 Proximate and fiber composition (%) of leaves and grain (adopted from Mekonnen et al. 2022)

3.1

Protein Profile

Cowpea is consumed as a high-quality plant-based protein source (Jayathilake et al. 2018) with a protein content of 27 to 43% in leaves and 21 to 33% in dry grains (Gerrano et al. 2019). Cowpea protein fraction includes globulins (legumin and

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Table 1 Amino acid composition of cowpea grain and leaves (adopted from Mekonnen et al. 2022) Amino acid Arginine Aspartic acid Alanine Cysteine Glutamic acid Glycine Histidine Isoleucine Leucine

Leaves (g/100 g protein) 7.4–17.3 10.8–26.7

Grain (g/100 g protein) 5.0–10.8 6.0–13

Amino acid Lysine Methionine

Leaves (g/100 g protein) 3.0–16.3 1.0–4.5

Grain (g/100 g protein) 3.5–8.0 0.9–3.5

4.2–9.8 0.5–2.9 17.2–45.3

3.4–5.1 0.3–2.4 8.5–19

Phenylalanine Proline Serine

4.6–14.4 4.0–15.9 3.0–11.6

4.4–9.9 3.1–8.9 3.8–5.8

3.8–12.6 1.8–8.6 4.1–11.1 7.4–19.6

3.1–4.8 2.0–4.41 2.8–5.4 5.7–11.3

Threonine Tryptophan Tyrosine Valine

3.2–10.8 1.3–4.1 3.0–9.3 5.0–12.8

3.0–5.9 0.9–1.5 2.6–4.5 3.4–6.2

vicilin/β-vignin), albumins, glutelins, and prolamins (Santos et al. 2012). Because of this, cowpea has been highly promoted in economically backward regions to control protein malnutrition (Iqbal et al. 2006). Cowpea leaves and grains show a rich profile of different amino acids including essential amino acids like valine, leucine, phenylalanine, lysine, and tryptophan. The amino acid profile of leaves and grains is presented in Table 1.

3.2

Minerals and Vitamins

Cowpea seeds, leaves, and beans are enriched with vital minerals of both macronutrients (Ca, K, Mg, P and S) and micronutrients (Cu, Fe, Mn, Zn, Na, Al, Se, B) that are required for proper functioning of human body (Owade et al. 2020). Cowpea is a source of different vitamins, of which most prevalent are vitamin A, C, and B complex (thiamine, riboflavin, pantothenic acid, pyridoxine, and folic/folate acid) and gamma tocopherol. Cowpea leaves have more vitamin C and minerals compared to grains (Mekonnen et al. 2022). The major and micro-mineral profiles of leaves, immature pods, and grains are presented in Table 2.

3.3

Lipids and Fatty Acids

Cowpea is a low lipid grain crop compared to other legumes (chickpea, lentil, green gram, and lupin) (Belane and Dakora 2011) with 0.5% to 3.9% lipid in grain and 1.3 to 4.3% in leaves. The lipid profile of cowpea is composed of triglycerides (41.2%), phospholipids (25.1%), monoglycerides (10.6%), free fatty acids (7.9%), diglycerides (7.8%), sterols (5.5%), hydrocarbons, and sterol esters (2.6%)

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Table 2 Mineral composition of cowpea grains, immature pods, and leaves (adopted from Mekonnen et al. 2022) Grains Minerals Mean range Macro-minerals (mg/100 g dry matter) Phosphorus 2.3–6.10 Potassium 9.30–35.60 Magnesium 4.3–8.4 Sulfur 153.3–200.0 Micro-minerals (mg/100 g dry matter) Copper 0.15–2.2 Iron 26.76–182.33 Manganese 10.57–204 Sodium 11.59–43.95 Zinc 2.78–22.3 Aluminum Boron 3.14–5.01 Selenium

Immature pods Mean range

Leaves Mean range

383.43–537.53 170.74–240.78 297.97–426.20

2.1–592.4 9.57–1445.2 1.3–227.4 120.0–147.3

0.48–0.95 6.01–9.78 2.11–4.77 13.70–32.93 1.42–5.63 1.84–7.86 2.13–4.03 2.5–3.4

0.5–2.2 3.4–10.6 1.38–4.3 8.4–79.81 2.4–5.11 1.47–2.14

(Kapravelou et al. 2015). Among fatty acids, palmitic and linoleic acids and, within sterols, stigmasterol (42.1 to 43.3%) are predominant (Antova et al. 2014).

3.4

Carbohydrates

Cowpea is also rich in carbohydrates containing 30.39 to 31.11% in leaves and 50 to 60% in grains. Popova and Mihaylova (2019) suggested that the good fraction of carbohydrates consists of sucrose, glucose, fructose, galactose, and maltose, whereas anti-nutrient components of carbohydrates are mostly raffinose, stachyose, and verbascose.

4

Health-Promoting and Health-Protective Properties

Besides above-specified nutritional value, cowpea exerts several health benefits due to presence of soluble and insoluble dietary fibers, phenol-derived compounds, other functional agents, anthocyanins, and carotenoids (de Silva et al. 2021). Epidemiological evidences showed the nutraceutical aspects, i.e., health-promoting and disease-preventing effects of cowpea such as protection against many incurable and immedicable health situations such as cardiovascular diseases, hypercholesterolemia, and obesity (Frota et al. 2015), anti-diabetic (Barnes et al. 2015), anti-cancer (de Silva et al. 2021), anti-inflammatory (Awika and Duodu 2017), antihypertensive and hypocholesterolemia (Tadele 2019), reducing plasma low-density lipoprotein (Talabi et al. 2022), gastrointestinal disorders (Khalid II and Elharadallou 2012),

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weight loss (Perera et al. 2016), and improving assimilation and strengthening blood flow (Trehan et al. 2015). The nutraceutical aspects of cowpea were reviewed (Jayathilake et al. 2018) and credited with plant-derived compounds, resistant starch, dietary fiber, less fat, and good unsaturated fatty acids. Interestingly, upon germination, the nutritive profile of cowpea seeds is enhanced as observed by increase in antioxidant capacity, vitamin C (Doblado et al. 2007), β-carotene, phenolics (hydroxycinnamic acid, syringic acid, vanillaldehyde, ferulic acid, sinapic acid, p-coumaric acid, benzoic acid, ellagic acid, and cinnamic acid), and flavonoid content.

4.1

Protein Hydrolysates and Peptides

The protein lysates of cowpea vegetate shows a low lysine/arginine proportion like soybean, thus making it a potential functional ingredient for reducing cholesterol (Kanetro 2015). Cowpea bioactive compounds such as peptides that are products of enzymatic hydrolysis or fermentation are reported to create favorable physiological conditions for proper functioning of the human body (Marques et al. 2015). These peptides function by acting as antihypertensive (Boonla et al. 2015), antidyslipidemic (Udenigwe and Rouvinen-Watt 2015), antioxidative (Marques et al. 2015), anti-carcinogenic and antimicrobial (Felicio et al. 2017), and anti-diabetic (Barnes et al. 2015). Cowpea peptides are known to prevent the occurrence of diabetes mellitus by imitating the activity of insulin and inhibiting dipeptidyl peptidase IV activity (Barnes et al. 2015). The antioxidative properties of cowpea peptides were attributed to the hydrophobic and aromatic amino acids like leucine, isoleucine, tyrosine, phenylalanine, tryptophan, and the sulfur-bearing amino acid cysteine due to their proton giving property to free radicals (Xiong et al. 2013). Similarly cowpea proteins and peptides showed antihypertensive by inhibiting angiotensin-converting enzyme (ACE) (de Leon et al. 2013) and hypocholesterolemic effects occur in several ways such as bile acid-binding, disruption of cholesterol micelles, changing hepatic and adipocytic enzyme actions, and gene expression of lipogenic proteins, as well as by inhibiting HMG-CoA reductase activity (Marques et al. 2018).

4.2

Phenolics

Cowpea predominantly contains phenolics (70% free phenolics and 30% bound phenolics), flavonoids (flavonols and flavan-3-ols), coumaric acid and ferulic acid (seed), gallic acid, protocatechuic acid, and p-hydroxybenzoic acid (seed coat) and thus is supposed to exert high antioxidant activity (Gutierrez-Uribe et al. 2011). Anthocyanins found in cowpea are delphinidin-3-O-glucoside, cyanidin-3-O-glucoside, delphinidin-3-O-galactoside, cyanidin-3-O-galactoside, petunidin-3-O-glucoside, peonidin-3-O-glucoside, and malvidin-3-O-glucoside (Ha et al. 2010). Many studies have reported the phenolic composition and their functioning mechanisms in different cowpea varieties (Liyanage et al. 2014). Phenolic compounds have

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hypocholesterolemic activity because of inhibition of oxidation of lipids, lowering of blood triglycerides, total cholesterol, LDL, and surge of blood HDL (Hachibamba et al. 2013), anti-inflammatory by downregulating pro-inflammatory gene expression (Ojwang et al. 2015), and having an anticancer effect as antioxidants shields DNA from oxidation and suppress cancerous cell division (Hachibamba et al. 2013).

4.3

Resistant Starch and Fiber

Coming to the other health benefits, cowpea contains high amount of resistant starch up to 12.65 gm per 100 gm (Eshwarage et al. 2017; Chen et al. 2010) which makes it a low glycemic index food. As mentioned earlier, resistant starch and dietary fiber have antidiabetic effect due to slow release of glucose (Onyeka 2007) and hypocholesterolemic effect due to diminution of bile acids from the circulation, abatement of converting cholesterol to supplemental bile acids, and augmenting expulsion of fecal fat (Perera et al. 2016). The two major health benefits of resistant starch are that firstly, it slows the rate of digestion, thus slowing release of glucose into the body followed by less uptake of glucose by the intestinal cells and secondly, due to their incomplete digestion by human digestive enzymes, they act as a substrate for colonic microbes (including probiotics) resulting in production of short-chain fatty acids (butyrate) that aid in proper lipid function and cancer prevention. Cowpea also has low calorific value and thus helps with glucose regulation in diabetic patients and better weight control for the obese (Oboh and Agu 2010). Cowpea has both soluble and insoluble high fiber content and hence has associated health advantages (Eshwarage et al. 2017). Soluble fiber helps in regulating blood cholesterol and glucose levels, while insoluble fiber due to its water/moisture retention property helps in smooth passage of waste materials through intestine and colon, thereby preventing haemorrhoids, constipation, many other digestive difficulties, colon cancer, diabetes, obesity, cardiovascular diseases, and numerous other long-term health complications (Eshwarage et al. 2017). Some additional health benefits of cowpea include eliminating urination problems such as uneasiness or obstructions, managing leucorrhea, or abnormal vaginal discharge (Alfa et al. 2020).

4.4

Anti-nutritional Factors

Although numerous studies claim cowpea is highly nutritious and a good nutraceutical food, its consumption is still limited due to presence of several anti-nutritional factors, poor digestibility, and lack of sulfur-containing amino acids. These anti-nutrients include some phenolic compounds, such as proanthocyanidins (Ojwang et al. 2013), phytic acid, tanins (Lattanzio et al. 2005), hemagglutinins (Aguilera et al. 2013), cyanogenic glucosides, oxalic acid, dihydroxyphenylalanine and saponins, and enzyme inhibitors (protease inhibitors, phytocystatins) (Monteiro et al. 2017). Phenolic compounds bind proteins and chelate divalent metal ions (Ojwang et al. 2013). Phytic acid (PA), an anti-nutritional factor, is known to conjugate phosphorus and

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other essential elements like iron and make it unavailable to organisms that feed on seeds rich in PA. Mutations affecting PA content have been identified, and low PA mutants have been isolated in pulses including cowpea (Dhanasekar and Reddy 2017). These mutants are being exploited in varietal development program so as to reduce the PA content to reasonable levels without affecting the physiological balance as they are further involved in responses to biotic and abiotic stresses (Dhole and Reddy 2016; Dhanasekar and Reddy 2017). Another important anti-nutritional factor in cowpea is the raffinose family oligosaccharides (RFOs) known to cause flatulence in organisms ingesting cowpea seeds. The RFOs are highly recalcitrant to various processing methods, and genetic means of reducing the content is the only amenable method. Therefore, it becomes imperative to identify genotypes with low RFOs content. Mutants with low RFOs have been identified in cowpea (Dhanasekar and Reddy 2015) that could be potential donors for developing varieties with low RFOs. Nevertheless, appropriate processing techniques can be used to lower many of the antinutritional compounds and enhance their bioavailability levels. Knowledge of nutritional, nutraceutical, and anti-nutritional aspects of cowpea will help in designing appropriate dietary plans/guidelines as per ethnic groups and geographic regions. Besides being in high demand due to its nutritious and nutraceutical values, cowpea cultivation is also supported because of the desirable agronomic attributes such as ease of cultivation, less necessity for fertile soils, their adaptability, and steadiness across all continents, even in drought-afflicted regions (de Silva et al. 2021).

5

Conventional and Molecular Approaches for Enhancing Nutritional Potential

Different processing methods, depending on geographical regions, are widely adopted by respective natives to reduce anti-nutrients present in cowpea and to enhance nutritional profile and also for the ease of intake. These methods include boiling, sprouting, steaming, frying, soaking, de-hulling, and grinding, which result in the alteration of the properties and bioavailability of some nutrients, increase in protein and mineral content (Fabbri and Crosby 2016), increase in phenolics and flavonoids (Laila and Murtaza 2014), and protein quality and digestibility (Deol and Bains 2010). Fermented cowpea flour showed improved antioxidant and hypolipidemic effects on rat (Kapravelou et al. 2015). Extensive efforts through molecular tools have been made for breeding cowpea varieties resistant to biotic and abiotic stresses, to enhance yield and productivity, but reports on improving nutritional profile through molecular approaches are scarce. However, research on enhancing cowpea nutritional aspects has been conducted for evaluating biochemical properties of cowpea germplasm. Considerable data has been generated on estimation of the protein and minerals content of cowpea germplasm with the objective to identify appropriate parents for breeding nutrient-dense improved varieties (Fig. 3). For example, evaluation of cowpea germplasm lines for protein and minerals (Cu, Fe, Zn, Mg, Ca, and K) content (Gerrano et al. 2019) and analysis of cowpea cultivars for proteins and minerals under rain-fed conditions in

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Petrolina, Brazil (Santos and Boiteux 2013), suggested the identification of high protein and mineral content genotypes which could be used in breeding for new biofortified cowpea cultivars. Reports on cowpea genetics for biofortification with crucial minerals are still lacking, of which one study provided genetic factors for enhancing minerals in cowpea seeds. This study claimed the least number of genes controlling the augmentation of minerals ranging from 2 (K) to 11 (P) with transgressive segregation pattern and either oligogenic or polygenic control for all minerals analyzed (Fernandes et al. 2015). Composite interval mapping detected two QTLs for total soluble solid in pods using the population derived from the cross between yardlong bean (accession JP81610) and a wild cowpea (V. unguiculata ssp. unguiculata var. spontanea) (accession JP89083) (Kongjaimun et al. 2013). Recently in a genotype-by-environment interaction study, the expression of nutritional properties (protein and minerals concentrations) in cowpea leaves was assessed in different agro-ecologies of South Africa and typical agronomical practices of smallholder farmers (Gerrano et al. 2022). This study showed genetic variations among selected genotypes for all four analyzed traits and also influence of climate on expression of these traits. This study suggested that nutritional profile of legume plants is a function of local soil properties and soil health (Gerrano et al. 2022). Mutation breeding is generally adopted to introduce desired simply inherited trait in elite cultivars. The International Atomic Energy Agency (IAEA) in association with the Food and Agriculture Organization (FAO) encourages the deployment of mutation-inducing technologies in plants for its member states. So far, there have been 22 mutant varieties developed using physical and chemical mutagens in cowpea. Few reports are available in cowpea cultivar development for biotic and abiotic stress tolerance using induced mutations (Horn et al. 2017), of which one study showed increase in the protein content in grains of some mutants by up to 13.3% (mutant from IT84E-124) and 13.64% (mutant from Vita 7) upon treatment with 1.0 mM NaN3 (Odeigah et al. 1998). Raina et al. (2022) reported that there was a concurrent increase in yield and nutrient density (Protein, Fe, Zn, and Cu) in M4 mutant lines in cowpea. Seven cowpea cultivars developed through mutation breeding exhibiting high seed productivity, earliness, large grain size, resistance to yellow mosaic virus, or augmented fodder production were released between 1981 and 2007 in India (Punniyamoorthy et al. 2007). One of the mutant varieties, the multifaceted cowpea mutant variety “TC-901,” has desirable attributes like high grain yield, fodder yield, high seed protein content (28%), resistance to cowpea mosaic virus, and amenable for summer cultivation. The progress in enhancing nutritional profile of cowpea is underway through evaluation of germplasm lines for identifying appropriate parents for breeding elite, nutri-rich cultivars.

6

Genomics of Nutritional Quality

Information on genomics of the crop nutrition profile has laid a starting point for the implementation of advanced molecular breeding and genetic engineering methods for crop improvement and also helps in switching from time-consuming

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labor-intensive conventional breeding. Nutritive value of a crop can be enhanced either by upregulating genes/QTLs associated with nutritive traits or by suppressing genes involved in anti-nutrient biosynthesis for which knowledge of target genes is required. Efforts have been made to explore and understand the genomics behind nutritional features in crops like cereals, pulses, oil seeds, legumes, millets, and vegetables in the form of evaluation of crop germplasm, development of genetic resources through introduction of new genotypes/novel genes, mapping and characterization of genes through quantitative trait locus (QTL) interval mapping and sequencing, association mapping such as genome-wide association study (GWAS), and marker-assisted breeding as discussed as follows. For example, development of sorghum with low cyanogenic potential suitable for cattle feed generated by downregulating an important enzyme of dhurrin biosynthesis pathway through antisense strategy (Pandey et al. 2019) provides opportunities for fine-tuning nutritional quality in grain crops. Interestingly in mung bean which is close to cowpea, 43 noteworthy marker trait associations (MTAs) for seed calcium, iron, potassium, manganese, phosphorous, sulfur, or zinc concentrations were discovered through genotyping by sequencing (GBS) approach (Wu et al. 2020). Coming to the crop improvement through genome engineering, the technique has been successfully applied to few crops including soybean for reducing linolenic acid (silencing of the ω-3 fad3 gene) (Flores et al. 2008) and increasing oleic acid (suppressing fad2-1 gene) (Christou et al. 1990). A database for cowpea, “EDITS-Cowpea,” has all the required information on the cowpea traits especially related to grain quality-related traits which can be useful to breeders for crop improvement (EDITS-Cowpea 2022). A search conducted for nutritional quality as trait and zinc content as the specific search item showed that the cowpea varieties (240) in the database have a range of zinc content (34.5–46 mg/g). A remarkable initiative is taken by the Kirkhouse Trust, a UK-based charitable organization through Cowpea Genomics Initiative (CGI) project (http:// cowpeagenomics.med.virginia.edu/CGKB/) to help cowpea research community. CGI project is aimed at leveraging advanced molecular tools for gene study and bettering cowpea. This project attempts omics studies including transcriptome, proteome, and metabolome analyses to get comprehensive knowledge on the fundamental biology of host and important agronomic characteristics and also sequencing and annotation of the gene space (gene-rich region of the cowpea genome) (Chen et al. 2007). Muñoz-Amatriaín et al. (2017) developed genome resources for the analysis of an African cultivar IT97K-499-35 which included whole-genome shotgun assembly, a bacterial artificial chromosome physical map, and assembled sequences for use in linkage mapping, synteny analysis, and germplasm characterization. In a further study, Lonardi et al. (2019) developed a genomic assembly with the help of single-molecule real-time sequencing complemented with optical and genetic mapping tolls to categorize repetitive elements, genes, and gene families. Noteworthy advanced genome editing technology, CRISPR-Cas9 system, has been successfully applied first time in cowpea which involved the inactivation of symbiosis receptor-like kinase gene via Agrobacterium-mediated hairy root transformation method (Ji et al. 2019). Such

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project initiatives and implementation of genomics techniques may help in promoting cowpea research for improvement in nutritional quality in related crops through genomics-based trait introgression.

7

Future Perspectives and Conclusions

Increased food production and management of malnutrition always remain major challenges for the underdeveloped and developing countries, whereas in the developed world, increase in the occurrence of several chronic diseases and occupationrelated hazards are a priority. The situation is getting worrisome due to the continuously increasing population and climate changes that directly affect agriculture sector. Cultivation of important staple crops in all ecological conditions and climate change scenarios is not possible. In this regard, crops with wider adaptability can help in ensuring food and nutritional safety. Cowpea is a drought-tolerant, climateadaptable crop amenable to diverse cropping systems. Cowpea is an excellent nutrient-rich food source belonging to orphan crop category that remains to be extensively cultivated since, besides being highly nutritious, it also possesses many health-promoting and health-protective effects. Cowpea nutraceutical properties are attributed to bioactive or functional chemicals like peptides, resistant starch, digestible fiber, plant-derived compounds, antioxidants, vitamins, etc. that get better depending on processing methods. Cowpea has been shown to better the lipid profile, blood glucose content, blood pressure, cancer prevention, anti-inflammatory, anti-diabetic, etc. It is a multipurpose legume crop used for both human consumption and livestock fodder. In the current scenario, though cowpea is a nutrient dense food with several health benefits, it is a neglected crop because of huge losses in its production due to biotic and abiotic stresses, cultural beliefs, and limited research priority. Modern breeding technological interventions will have to be accelerated for cowpea breeding. Also, intensive clinical research on the anti-inflammatory and anticancer activity of cowpea is required to realize the nutraceutical aspects of cowpea for better acceptability. Breeding for biofortification in cowpea is in the budding stage, and hence the adoption of molecular tools and advanced genomic strategies is needed to accelerate the progress of development of nutrient-dense and nutraceutical-rich varieties. This could be achieved through mining available genetic resources for target and novel genes/traits in association with chance breeding (targeted mutation, hybridization, backcrossing, pedigree, and recurrent selection), modern breeding methods (space breeding, speed breeding, genomic selection, and gene/ genome editing), innovative techniques (mutagenesis breeding), transgenic development, demand-led breeding, and multi-omics analysis studies. Cowpeas can become a super crop for alleviating nutrient deficiency and health problems. With further research on its nutraceutical aspects, its acceptance will also be on the rise. Being the cheapest protein source and climate change-resilient crop, nextgeneration cowpea could be promoted for achieving future food and nutritional security at the global level.

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Lentils (Lens culinaris Medik): Nutritional Profile and Biofortification Prospects Debjyoti Sen Gupta, Jitendra Kumar, Surendra Barpate, A. K. Parihar, Anup Chandra, Anirban Roy, and Ivica Djalovic

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Description on Nutritional Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Traits Required for Development of Biofortified Lentil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic Resources of Health-Related (HR) Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic Variability for Biofortification Traits in Lens Gene Pool . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Primary Gene Pool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Secondary or Tertiary Gene Pool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Classical Genetics and Traditional Breeding of HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Genetics of HR Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Site-Specific Breeding for Biofortification Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Breeding for Biofortified Lentil Cultivars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Genetic Analysis of Agronomic Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Brief Account of Molecular Mapping of HR Genes and QTLs . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Genetic Engineering for HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Traits of Interest and Foreign Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Achievements of Transgenics in Lentil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Prospects of Cisgenics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Future Prospects and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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D. Sen Gupta (*) · J. Kumar · A. K. Parihar · A. Chandra ICAR-Indian Institute of Pulses Research, Kanpur, Uttar Pradesh, India e-mail: [email protected] S. Barpate Scientist, Food Legumes Research Platform (FLRP), International Centre for Agricultural Research in the Dry Areas (ICARDA), Sehore, Madhya Pradesh, India A. Roy Ramakrishna Mission Vivekananda Educational and Research Institute, Kolkata, West Bengal, India I. Djalovic Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Novi Sad, Serbia © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_27

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Abstract

Lentil is a highly consumed pulse crop in India, Bangladesh, Nepal, and many other countries. This crop is rich in nutrients which are easy to digest and palatable. In the form of a whole food source of nutrition, it can minimize the effect of malnutrition which is prevalent worldwide. Biofortification as a tool provides us great opportunity to further enhance nutrient content biologically. A few studies showed considerable genetic variability for nutrients including iron, zinc, calcium, magnesium, selenium, prebiotic carbohydrates, and folate concentration in lentil, which may be further improved. While breeding for nutrients, the role of environmental effects should be taken into consideration to provide a widely adapted plant variety. A number of genomic regions have been mapped using molecular markers; however, the intensity and coverage of the experiments were low, and this area needs more efforts to make marker-assisted breeding a reality in lentil breeding for nutritional traits. Lentil also has anti-nutrients like phytic acid, which influences the bioavailability of nutrients. In addition to traditional breeding approaches, efforts are underway to make use of cis- or transgenic technologies to enhance nutritional quality in many crops; the same may be adopted based on need in the case of lentil. Biofortified lentil varieties recently released which are rich in iron and zinc concentration; however, more varieties are required to cover different agroclimatic regions or niches. In short, more focused efforts are required to identify high-yielding, biotic and abiotic stress-tolerant, and nutrient-rich new-generation lentil varieties that will definitely boost health status among the consumers, especially from today’s perspective when plant-based protein or other nutrients are gaining huge popularity. Keywords

Lens culinaris · Micronutrient · Biofortification · Bioavailability · Anti-nutrients · Iron · Zinc

1

Introduction

Malnutrition is caused by unavailability of sufficient quantity of nutrients like proteins, carbohydrates, micronutrients, and vitamins. Higher quantity of anti-nutrients in our everyday meals is also detrimental to our health. This situation is present in both developed and developing countries. Consumption of carbohydrate-rich diets throughout the world aggravated the situation further since these are deficient in highly essential micronutrients, causing long-lasting disorders or diseases among the people (Stewart et al. 2010; Bouis et al. 2011). Thus, “hidden hunger” shows its effects on the well-being of the micronutrient-starved population, though in many cases have sufficient calorie intake. Implication of such long exposure to low or less than recommended requirement of micronutrients or vitamins causes serious health issues including lower birth weight, anemic condition, impaired learning ability,

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high mortality and morbidity, reduced working ability, and increased treatment costs (Batra and Seth 2002; Welch and Graham 1999). Deficiencies of iron (Fe), zinc (Zn), selenium (Se), and iodine (I) are not uncommon in South and South-East Asian countries along with Indian subcontinent. According to an estimate, nearly 60% of the global population is usually facing deficit of Fe (Yang et al. 2007) whereas 33% of Zn (Hotz et al. 2004) and almost 15% of Se (FAOSTAT 2007). About one-fourth of the people globally complain of anemia (WHO 2008), whereas 17.3% people are devoid of sufficient Zn intake (Wessells and Brown 2012), causing 433,000 deaths annually of children below age 5 (WHO 2009). About 20% children morbidity of age less than 5 years were due to the inadequate intake of vitamins like vitamin A, Zn, Fe, and/or I (Prentice et al. 2008). In preschool children and pregnant and lactating women, deficiencies of essential micronutrients especially Zn and Fe are observed more common (Welch and Graham 1999; White and Broadley 2009; WHO 2012). About one billion people suffered with Keshan (cardiomyopathy) and Kashin–Beck (osteoarthropathy) diseases caused by Se deficiency (Reilly 1996). Countries like Australia, New Zealand, Africa, the UK, Thailand, Finland, Central Siberia, Denmark, Turkey, Northeast to South-Central China, parts of India, Bangladesh, and Nepal have low levels of soil Se which is bioavailable (100–2000 μg kg
1), and due to this, crops grown in these countries have low concentration of Se in them, creating a perfect ground for Se deficiencyrelated health issues (Fordyce 2005; Lyons et al. 2005; Spallholz et al. 2004, 2008). Besides the role of a typical micronutrient, Se prevents cytotoxic effect of arsenic (Biswas et al. 1999); arsenic toxicity exists in many crop ecologies in South Asia, as Se and As detoxify each other’s effect (Holmberg Jr and Ferm 1969; Levander 1977). Similarly, deficiency of folate prevails worldwide over millions and leads to serious health problems, including birth defects and health risks both for the mother and child (Gupta et al. 2013). To combat the global malnutrition-related issues, several mitigations have been adopted by governments, nongovernmental organizations, and the United Nation. Food fortification through supplements is effective to bolster health in many communities from both developed and developing world. In fact, for many processed or polished food grains or products, food fortification is mandatory in many countries. However, food fortification causes price of the fortified food to move upward beyond the capacity of common consumers in target communities who are poor or have other priorities than to spend higher for fortified food purchase for consumption. Here comes the role of another very unique and successful strategy to develop biofortified crop varieties, which usually requires one-time investment (Bouis et al. 2011). Food crops can be biofortified in two ways: one of the popular method is to increase the concentration of target micronutrient by the external application of such micronutrient over the plant part for their ready absorption followed by translocation within the plant system and ultimately in the grain or any other plant part which is consumed. Crop rotations and intercropping including soil microbes may also be the components in agronomic biofortification helping in transport of target micronutrient in the soil (White and Broadley 2009). There are many success stories available for agronomic biofortification like Se can be achieved by its spraying in lentil

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(Thavarajah et al. 2015) and so in crops like potato tubers, field pea seeds, and tea leaves (Smrkolj et al. 2006; Turakainen 2007). Increase in production cost, particularly in developing countries, agronomic biofortification is not always feasible among the growers particularly for the smaller-land holdings (Graham and Rengel 1993). Complexity in the application of perfect crop growth stages as this method is vulnerable to both external and internal crop growing conditions (Terry et al. 2000). Application concentration of micronutrients and any allied inorganic nutrients should be standardized in many crops, thereby reducing the chances of any induced phytotoxicity. Secondly, genetic biofortification is a plant breeding-based technique wherein nutritionally rich high yielding food crop varieties are achieved by manipulating the genetic buildup of cultivars using either classical plant breeding tools or modern genomic approaches. This approach offers an one-time investment and costeffective method of delivering essential micronutrients and, thereby, does not require repeated efforts to fortify during food processing; therefore, biofortified seeds can be supplied to the target community who can easily grow, produce, and maintain the seed chain for a long period (Graham et al. 2007; White and Broadley 2009). It is a tool for food crop improvement, and sustenance which have been discussed by Miller and Welch (2013) and Saltzman et al. (2013). Several workers have discussed approaches to enhance zinc, selenium, and iron (Hawkesford and Zhao 2007; Velu et al. 2014) and deployment of genomics for biofortification of Fe and Zn in wheat (Borrill et al. 2014) and in common bean (Blair 2013; Petry et al. 2015). Genetic potential for high Fe and Zn concentrations and low anti-nutrients like PA in various food crops such as maize (Zea mays L.), rice (Oryza sativa L.), wheat (Triticum sativum L.), common bean (Phaseolus vulgaris L.), and field pea had been reviewed in recent years (Frossard et al. 2000; Gomez-Galera et al. 2010; Amarakoon et al. 2012). This chapter will provide information on the genetic potential of lentil as a whole food biofortified crop and recent achievements made in this direction.

2

Description on Nutritional Components

Lentil (Lens culinaris subsp. culinaris Medikus) is a nutritious food legume crop. It is cultivated in more than 50 countries but majorly grown in India (36%), western Canada (18%), south-eastern Turkey (15%), and Australia (4%) (FAOSTAT 2011). Like other pulses, it is rich in proteins, zinc, iron, folate, selenium, vitamins, and carotenoids (Thavarajah et al. 2011a, b; Johnson et al. 2013a, b; Gupta et al. 2013) (Table 1). Serving 100 g of lentil grain can fulfill the recommended daily allowance (RDA) – Fe: 41–113%; Zn: 40–68%; and Se 77–122% (Table 1). The pulse is rich in ß-carotene (2–12 μg/g) but contains less phytic acid phosphorous (0.7–1.2 mg/g). The amount of phytic acid has been found relatively lower than cereal and pulse crops with low PA (rice: 2.23 mg/g; soybean: 4.86 mg/g; wheat: 2.51 mg/g; maize: 3.7 mg/g; and common bean: 1.38 mg/g). As a whole food, lentil can be cooked within 10 min which is a great time and energy saver (Thavarajah et al. 2011a). Therefore, lentil is a natural candidate for biofortification efforts to develop a nutritionally rich, high protein, high iron and zinc containing pulse crop which if

Lentils (Lens culinaris Medik): Nutritional Profile. . . Table 1 Nutritional value of lentil seeds

Protein Carbohydrate Fat Ca Fe Zn Se Folate

723 20–25% 50–60% 0.7–0.8% 60–70 mg/100 g 7–9 mg/100 g 4–5 mg/100 g 42–67 μg/100 g 261–290 μg/100 g

Source: Adapted from Kumar et al. (2016a)

eaten with cereals can fulfill both calorific as well as micronutrient requirements. This will further help to fight global malnutrition problem among poor populations or communities. The various nutritional/antinutritional compounds estimated in lentil grain are given in Table 1.

3

Traits Required for Development of Biofortified Lentil

Modern breeding approaches along with conventional tools were found to be highly suitable for the breeding of nutrient-dense crop cultivars with high bioavailability of phytonutrients (Nestel et al. 2006). To achieve it, first targets should be fixed with respect to the status of nutrients and anti-nutrients present in the grain or seed. After knowing this information, breeder can plan to improve the bioavailability of a nutrient either by increasing its concentration or by reducing the concentration anti-nutrients present. Main objective of major biofortification efforts in cereals and pulses involves high iron and zinc concentration as target for breeding. Beside this, an anti-nutrient (phytic acid), which reduces the bioavailability of iron and zinc, is also targeted for reduction of their concentration by introgressing the genes or quantitative trait loci (QTLs) that produce anti-nutritional phytochemicals in lower concentration in plants. These potential biofortification-related traits are presented in Table 2.

4

Genetic Resources of Health-Related (HR) Genes

A number of genebanks store cultivated and wild lentils in their repository (Table 3). The largest Lens collection (31,970) is Genesys followed by ICARDA genebank which conserved 13,958 Lens accessions in Morocco (Dikshit et al. 2022). Australia, Iran, the USA, Russian Federation, and India have 1000–6000 accessions in their respective genebanks (Table 3). Canada has 1139 Lens accessions in their genebank. Variable numbers of lentils (678–1095) are collected by Turkey Syria, Hungary, Egypt, China, Pakistan, Bangladesh, and Ethiopia for conservation in respective genebanks. Core and mini-core sets from local collection have been developed by many research groups which are valuable genetic resources for their use in breeding

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Table 2 Potential areas for biofortification in lentil Traits Nutritional traits Protein Starch Dietary fibers Fatty acids Micronutrients Iron Zinc Sorbitol Mannitol Galactinol Sucrose Raffinose + stachyose Verbascose Nystose Anti-nutritional traits Phenolics Flavonoids Condensed tannin content Phytoestrogens Phytate Saponins Protease inhibitor α-amylase inhibitor Lectins Vicilin protein

Range 15.9–32% 34.7–65.0% 5.1–26.6% 0.3–3.5 g/100 g 73–90 mg/kg 44–54 mg/kg 1250–1824 mg/100 g 57–132 mg/100 g 46–89 mg/100 g 1750–2355 mg/100 g 3314–4802 mg/100 g 1907–2453 mg/100 g 8–450 mg/100 g 6.24–27.73 mg GAE/g defatted sample 1.15–4.94 mg CE/g defatted sample 3.14–12.97 mg CE/g defatted sample 8.9–12.3 μg/100 g dry matter 3.9–11.9 mg/g 0.07–0.13 g/100 g 25–55 TIA/mg of protein – – –

Source: Modified from Kumar et al. (2016b) GAE gallic acid equivalent, CE Catechin equivalent, TIA trypsin inhibitor activity

programs (Tripathi et al. 2022). However, there is a need in lentil for evaluation of these core or mini-core sets for nutrition-related traits. ICARDA Lens accessions around 76% have been characterized for morphological and phenological attributes (Kumar et al. 2016c). Apart from this, under the AGILE project that is led by Canadian Scientists, 324 accessions of lentil diversity panel were phenotyped for phenological traits (different nine diverse locations for two seasons) around the world (Wright et al. 2021). This set has also been genotyped using an exome capture array and seeds from 321 lines have been deposited in the ICARDA genebank (Ogutcen et al. 2018). Lentil is dense with protein contents and an affordable pulse crop that is an ancient crop and has a long domestication history. The lentil or Lens species belongs to the family Fabaceae and its crop wild relatives (CWR) are naturally and widely distributed in Mediterranean regions and Southwest Asia (Guerra-García et al. 2021). The genus Lens (2n ¼ 2x ¼ 14) phylogenetically belongs to the tribe Vicieae.

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Table 3 Prominent genebanks and their holding size in lentil

Country Global

Name of center/genebank Genesys

Total Lens accessions including CWR conserved in different global genebanks 31,970

Morocco

ICARDA

13,958

Australia

Australia Temperate Field Crops Collection Seed and Plant Improvement Institute USDA N.I. Vavilov All-Russian Scientific Research Institute of Plant Industry Inst de Inv. Agropecuaries, Centro Regional de Investigation Carillanca PGRC General Commission for Scientific Agricultural Research National Gene Bank Plant Genetic Resources Institute BARI Centro de Recuros Fitogenetico, INIA Biodiversity Conservation and Research Institute NBPGR, New Delhi Research Center for Agrobotany Institute of Crop Germplasm Resources Plant Genetic Resources Department, Aegean Agricultural Research Inst.

5254

Iran USA Russian Federation Chile

Canada Syria

Egypt Pakistan Bangladesh Spain Ethiopia India Hungary China Turkey

3000

References https://www. genesys-pgr. org Dikshit et al. 2022 Singh et al. 2017; Dikshit et al. 2022

2875 2556

1345

1139 1072

875 805 798 703 678 2285 1061 855 1095

The tribe contained cool season legume crops which are members of the family Fabaceae (Ladizinsky 1979). Presently, the Lens genus contained seven closely related species mainly Lens culinaris, L. orientalis, L. tomentosus, L. lamottei, L. odemensis, L. ervoides, and L. nigricans (Table 4). The studied taxonomic relationships on the basis of morphology, hybridization behavior, cytogenetics, and molecular markers do not accept classification at the level of species and

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Table 4 Lens gene pool and species S. No 1

2

Gene pool Primary

Secondary

3

Tertiary

4

Quaternary

Species name Lens culinaris Lens orientalis Lens tomentosus Lens odemensis Lens lamottei Lens ervoides Lens nigricans

Type Domesticated

References Ladizinsky 1979; Wong et al. 2015; Guerra-García et al. 2021

Wild Wild Wild Wild Wild Wild

subspecies. Although, researchers commonly agree that L. culinaris ssp. orientalis is the wild progenitor of L. culinaris ssp. culinaris whereas L. nigricans is distantly related. Apart from this, Lens culinaris subsp. culinaris is subdivided into two types: the microsperma cultivars having small-sized seeds and another with reddish cotyledons which is believed to be originated from near East and Central Asia region and the macrosperma cultivars having large seeded red, yellow, and green cotyledon are native to Mediterranean region. Based on a study (Schreier et al. 2012), genotyping data-based analysis of all the individuals like L. culinaris/L. orientalis/L. tomentosus and L. ervoides/L. nigricans each belong to one cluster whereas L. lamottei and L. odemensis exhibited diversified ancestry with L. ervoides/L. nigricans cluster in major proportion. The Chinese group of researchers (Wong et al. 2015) also categorized Lens in seven different taxa in four separate gene pool: as primary (L. culinaris), secondary (L. orientalis), tertiary (L. tomentosus and L. lamottei), and quaternary (L. ervoides and L. nigricans). However, crossing incompatibility for hybridization in the genus Lens among the gene pools reported by Cubero et al. (2009). Many studies reported the crossability of L. odemensis and L. orientalis with L. culinaris (Fratini and Ruiz 2006; Muehlbauer et al. 2006). Whereas, some of the studies showed hybrid embryo abortion, albino seedlings, and hybrid sterility are major restrictions in the wide hybridization among Lens species. Gupta and Sharma (2006) stated that hybrid embryos abort while crossing the parents from the tertiary gene pool with L. culinaris. These hybridization barriers can be overcome through tissue culturebased embryo rescue methods (Tullu et al. 2013). Apart from this, application of GA3 (gibberellic acid) also impacted positively and produced successful crosses of L. culinaris with L. ervoides, L. odemensis, and L. nigricans (Fratini and Ruiz 2006). In due course of lentil domestication process, uninterrupted selection reduced genetic variation/allelic diversity of members of primary gene pool in comparison to secondary, tertiary gene pool or wild progenitor. In the Lens primary gene pool,

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reduced allelic variation during domestication is the major hindrance for enhancing productivity and other useful agronomical traits. Because of the impact of climate change and unpredictable weather condition during growing season, effective adaptation strategies to combat with biotic and abiotic stresses are required. Therefore, crop wild relatives (CWRs) have remarkable potential and reservoir of economically important genes/alleles to enhance crop productivity as well as the tolerance against the biotic and abiotic stresses. Hence, CWRs are required for lentil improvement as potential sources of useful gene(s) for the deployment in cultivars. Thus, wild relatives act as most important donors for added genetic variability in cultivated crops.

5

Genetic Variability for Biofortification Traits in Lens Gene Pool

5.1

Primary Gene Pool

Since the inception of the HarvestPlus program, for many crops, identification of natural variants with high concentrations of iron and zinc in the cultivated gene pool has been a principal approach for the development of biofortified crop cultivars. As the natural variants are identified, if they are of less agronomic value, then such nutritional traits are transferred to agronomic bases by either hybridization or other techniques. As discussed by Kumar et al. (2016a), screening for high iron and zinc concentration in lentil was conducted in many countries, including India, Turkey, Syria, Canada, and Pakistan (Table 5). In these studies, folate, iron, and zinc concentrations have been targeted. In a study involving 19 lentil genotypes pertaining to the concentration of Fe and Zn from various markets of Canada, narrow range of genetic variability was observed. Fe concentration was found ranging between 73 and 90 mg of Fe kg
1 whereas Zn concentration between 44 and 54 mg of Zn kg
1 in these genotypes (Thavarajah et al. 2009a). This was followed by a large-scale experiment conducted by the International Center for Agricultural Research in the Dry Areas (ICARDA) under the HarvestPlus Challenge program in which they have screened iron (42–132 ppm) and zinc (23–78 ppm) concentration in a large collection of more than 1500 lentil accessions from cultivated gene pool (Sarker et al. 2007; HarvestPlus 2014). In a multiyear and multilocation study with respect to concentration of folate, significant genetic variability was observed which ranged between 216 and 290 μg/100 g in 10 lentil cultivars of the USA. Compared to other pulses like chickpea, yellow field pea, and green field pea, lentil was having more folate concentration than other pulses (Gupta et al. 2013). Geographical areas with limited zinc availability in soils, including India, Pakistan, China, Iran, and Turkey, are also countries where human Zn deficiency is most prevalent (Hotz et al. 2004; Khan et al. 2008). Eyüpoğlu et al. found that more than 50% of the land (14 Mha) in Turkey is Zn deficient. The high prevalence of Zn-deficient soils in Turkey has been suggested as a major cause of Zn deficiency and to be indirectly related to deficiencies of other micronutrients. Turkish landraces of lentil also

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Table 5 Genetic variability for biofortification traits in lentil Compound with No. of range of Type of genetic material accessions concentration Landraces, wild types, 1600 Fe: 43–132 and breeding lines Zn: 22–78 Lentil germplasm

Country ICARDA, Syria do

References Sarker et al. 2007 Baum et al. 2008

Fe: 41–109 Zn: 22–78 Fe: 73–90

Canada

Thavarajah et al. 2008, 2009a

Zn: 44–54 Se: 425–673 Fe: 49–81

Turkey

Karakoy et al. 2012

Zn: 26–65

India

Kumar et al. 2018a

19

Se: 240–630 Fe: 73–90

Canada

Thavarajah et al. 2009a

The USA

Elite breeding lines

41

Zn: 44–54 mg Folate: 216–290 μg/ 100 g Fe: 50.85–136.9 mg

Gupta et al. 2013 Kumar et al. 2014a

Varieties

7

Zn: 40.26–81.5 Se: 74–965 μg kg
1

Bangladesh

Varieties

23

Fe: 43–92 ppm

Canada

Germplasm line

–

Varieties

9

Cultivars and breeding lines

192

Breeding lines, 900 germplasm, and modern high-yielding genotypes

Landraces and cultivars 46

Landraces and breeding 96 material

Exotic lines Varieties

Varieties

Zn: 42–73 Fe: 37–157

PA: 3.8–15.9 mol/g Beta-carotene: 2–12 μg/g Prebiotic carbohydrate Se: 6–254 μg/kg
1

India

The USA

Rahman et al. 2013 DellaValle et al. 2013

Thavarajah et al. 2011b The USA Johnson et al. 2013b Syria, Nepal, Thavarajah Morocco, the USA, et al. 2011b Australia, and Turkey

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exhibited a range of genetic diversity not only for different micronutrients (Karakoy et al. 2012). In India, in a study, 41 elite lentil lines were tested for stability of grain Fe and Zn concentration across multiple locations. Pooled analysis of variance over locations detected significant differences between genotypes, locations, and genotype  location interaction. The average grain Fe concentration over the locations was obtained for L 4704 (137 mg/kg grain), while the grain Zn concentration was highest for VL 141 (82 mg/kg grain). Although both micronutrients were affected by the environment, iron concentration exhibited more G  E interaction compared to Zn concentration (Kumar et al. 2014a). Lentil seeds are also a very good source of organic Se (selenomethionine) (Thavarajah et al. 2007, 2008), and it was also reported that cooking had limited modifying effects on selenomethionine concentration (Thavarajah et al. 2008). In case of Se, significant genetic variability was noted in the genotypes from various countries (Thavarajah et al. 2011b; Rahman et al. 2013). In Bangladesh, total Se concentration was estimated in soil and lentil seeds received from both farmers’ fields and yield trials. Average of Se concentration in farmers’ fields was 163 and 312 μg kg
1, for soil and lentil seed, respectively. It was further calculated that 50 g of lentil consumption contributes 28% of the recommended daily allowance of Se (55 μg per person per day). Relative bioavailability of Fe was estimated through in vitro digestion/Caco-2 cell model in 23 genotypes of cultivated gene pool of lentil, wherein significant genetic variability reported for Fe and relative iron bioavailability and phytic acid (PA) concentration (DellaValle et al. 2013). The pulse is also a great source of beta-carotene where significant genetic variability (2–12 μg/g) was reported in the USA (Thavarajah et al. 2011b). Prebiotic carbohydrates are important to maintain gut microflora, and significant genetic variation exits in lentil for this complex biochemical trait (Tahir et al. 2011; Wang et al. 2009). Johnson et al. (2013b) reported the genetic variability in prebiotic carbohydrates such as raffinose-family oligosaccharides, sugar alcohols, fructooligosaccharides, and resistant starches in 10 commercially grown lentil varieties of the USA from cultivated genepool, which may be further elevated through the approach of breeding by utilizing more number of germplasm or varieties under screening. Significant environmental effect on this type of traits demands sitespecific breeding (Johnson et al. 2013b).

5.2

Secondary or Tertiary Gene Pool

Wild gene pool or alien gene pool or secondary and tertiary gene pool always are sources of lost useful genes or alleles, which were lost from the cultivated species in due course of evolution (Doyle 1988; Tanksley and McCouch 1997). The breeding history of a crop species has a bearing on the extent, type, and size of such wild sources of alleles. Being the most abundant curator of genetic resources in lentil,

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ICARDA in Lebanon holds more than 500 wild lentil accessions, representing 6 wild Lens species from 26 countries. Many species of wild Lens genepool have expressed their cross compatibility with cultivated species (Fratini et al. 2004; Fratini and Ruiz 2006; Muehlbauer et al. 2006) after employing modifications in tissue culturemediated hybridization procedures (embryo rescue) or by using different doses of plant growth regulators. Accessions from wild genepool have been identified as donors for high concentration of micronutrients in many crops (Cakmak et al. 2000; Ortiz-Monasterio et al. 2007). Seed micronutrient concentration of cultivated and wild lentils is not much known. Sen Gupta et al. (2016) estimated micronutrients in the seeds of 26 lentil genotypes, representing 4 species and 3 subspecies of Lens. Concentrations of Fe, Zn, Ca, Cu, and Mg in seeds varied from 26 to 92, 17–51, 97–536, 3–12, and 272–892 mg kg
1, respectively, among the Lens culinaris genotypes. Mineral concentrations for L. lamottei (Fe ¼ 64–80, Zn ¼ 26–40, Ca ¼ 311–434, Cu ¼ 2–6, and Mg ¼ 754–839 mg kg
1), L. nigricans (60–70, 33–39, 508–590, 3–4, and 445–738 mg kg
1), and L. ervoides (65, 37, 339, 6, and 638 mg kg
1) were similar to Lens culinaris genotypes. More number of germplasm should be tested in future to identify higher genetic variation in lentil for these micronutrients. Kumar et al. (2018b) evaluated a core set of 96 wild accessions extracted from 405 global wild annual collections comprising different wild Lens species for micronutrients. Significant genetic variation was observed for different micronutrients including Na (30–318), K (138.29–1578), P (37.50–593.75), Ca (4.74–188.75), Mg (15–159), Fe (2.82–14.12), Zn (1.29–12.62), Cu (0.5–7.12), Mn (1.22–9.99), Mo (1.02–11.89), Ni (0.16–3.49), Pb (0.01–0.58), Cd (0–0.03), Co (0–0.63), and As (0–0.02) (mg/100 g). Significant positive correlations among micronutrients were also observed. It is noteworthy to mention that accessions representation from Turkey and Syria had maximum variability for different micronutrients. Hence, wild gene pool can be used to transfer favorable alleles controlling higher micronutrient concentrations in lentil.

6

Classical Genetics and Traditional Breeding of HR Traits

6.1

Genetics of HR Genes

Traits like iron and zinc concentration and folate concentration are quantitatively inherited. In cereals, it was reported long ago that these kinds of traits are controlled by several genes with individually smaller effects on the trait mean. In wheat, generation mean analysis was conducted to find out the genetics of iron and zinc concentration (Amiri et al. 2020). Due to the role of fixable gene effects and high heritability for grain iron concentration, selection for this trait could be effective in early generations. Grain zinc concentration was having nonadditive gene effects and low heritability; hence selection should be practiced during advanced generations. Both kind of heterosis at both crosses for iron and zinc concentration were significantly negative. Response to selection varied over locations for iron and zinc concentrations.

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Site-Specific Breeding for Biofortification Traits

Environmental conditions during crop growth including soil pH, soil temperature, photoperiod, rainfall, soil organic matter, and texture affect the rate of accumulation of micronutrients into seeds (Cakmak 2008; Joshi et al. 2010). Hence, knowledge of such an optimal environment for growing facilitates the sink deposition of iron and zinc in seed, which is the key to the success of any biofortification research program. Here comes the role of genotype  environment interactions, which is usually very high for traits involving secondary metabolism. It is important to encourage breeders to develop crop cultivars that are site-specific and not look for wider adaptation, as that will be contrary to the overall breeding behavior of these traits. In lentil, iron, zinc, and phytic acid concentrations vary over locations, soil conditions, and weather parameters (Thavarajah et al. 2009a, b; Kumar et al. 2018a). It was further observed that samples from one geographical region varied from another (Thavarajah et al. 2011a). For example, Fe concentration was higher in samples of Syria (63 mg/kg), Turkey (60 mg/kg), and the USA (56 mg/kg). Likewise, Zn concentration was higher in the seeds from Syria (36 mg/kg), Turkey (32 mg/kg), and the USA (28 mg/kg). Se was high in the seeds from Nepal (180 μg/kg) and Australia (148 μg/kg) to Syria (22 μg/kg), Morocco (28 μg/kg), and Turkey (47 μg/kg) (Thavarajah et al. 2011a). Calcium was high in samples from Turkey (0.48–1.28 g/kg), while lentils grown in India have high Fe (37–156 mg/kg) and Zn (26–65 mg/kg) concentrations (Karakoy et al. 2012; Kumar et al. 2016a). A significant year  location interaction has been observed for total folate concentration in 10 lentil cultivars from the USA in a study conducted over 2 years (Gupta et al. 2013). It was observed that temperature influences the concentration of iron (Fe), phytic acid (PA), and zinc (Zn) in lentil genotypes on growing under different temperature regimes: Saskatoon, Canada (decreasing temperatures) and Lucknow, India (increasing temperatures). In lentil seeds, concentrations of Fe, PA, and Zn were significantly higher in the regime with a rising temperature than in the regime with a decreasing temperature. Microclimatic factors control the iron, zinc, and phytic acid concentrations in lentil, which show a quite similar trend as compared to other candidate crops (Gupta et al. 2013). Under changing climatic conditions, fluctuating temperature regimes (particularly warm night temperature) may affect the anti-nutrients like phytic acid biosynthesis in a negative way, further complicating the biofortified varietal improvement in this crop species.

6.3

Breeding for Biofortified Lentil Cultivars

Initially, through the HarvestPlus program, several already released varieties were tested for iron and zinc concentration (i.e., Ethiopia, Bangladesh, Morocco, Turkey, Syria, and Nepal). Many of these varieties which were identified as high yielding as well as having high iron and zinc concentration are listed in Table 3. A few of these lines are promoted by the national partners to reach to lentil growers rapidly. In

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Bangladesh, high iron and zinc containing varieties such as Barimasur 4 and Barimasur 5 are promoted to all corners of the country. HarvestPlus (2014) reported that several released varieties of lentil that possess high iron and zinc concentrations and high yield potential have been identified in Nepal; they are: Sisir (98 ppm Fe and 64 ppm Zn), Khajurah-2 (100.7 ppm Fe and 59 ppm Zn), Khajurah-1 (58 ppm Zn), Sital (59 ppm Zn), Shekhar (83.4 ppm Fe), and Simal (81.6 ppm Fe). In Nepal, another lentil variety, ILL 7723 (Khajura-4), was released for general cultivation in Nepal (Darai et al. 2020) with high iron and zinc concentration. This is a selection in materials from ICARDA, Morocco (Sel89503). In India, two biofortified lentil varieties, Pusa Ageti Masoor (Fe 65 ppm) and IPL 220 with high Fe (73–114 ppm) and Zn (51–65 ppm) concentrations, have been released so far and both of these became very popular among the lentil growers. Pusa Ageti Masoor is covering the central part and IPL 220 covers the northeastern plain zone of the country.

7

Genetic Analysis of Agronomic Traits

The Lens gene pool, especially Lens culinaris (lentil), and its wild progenitor are successfully cultivated in areas of low rainfall (less than 250 mm/year) on marginal and poor soil. Available germplasm in the primary gene pool demonstrated poor water extraction capacity and a lower growth rate as compared with secondary and tertiary gene pool. It is well known that the most prominent abiotic stress is drought. The drought tolerance capacity has been identified and reported in L. ervoides, L. nigricans, and L. odemensis (Gupta and Sharma 2006). The L. culinaris. spp. orientalis provides valuable sources of drought tolerance gene for low rainfall environments like Syria, Jordan, Azerbaijan, Turkmenistan, and Tajikistan. Moreover, it is reported that interspecific offsprings are capable of drought tolerance that is associated with relative leaf water content, pubescent leaves, cell membrane stability, higher root-shoot ratio, higher transpiration, decreased wilting, and reduced canopy temperature (Omar et al. 2019). Recombinant inbred lines (RILs) developed from crosses of L. culinaris with L. odemensis and L. orientalis were evaluated by Sanderson et al. (2019). They found that tolerance to stress is associated with delayed flowering, reduced transpiration, and profound root system in the studied Lens species. Accessions of L. orientalis and L. odemensis with extensive roots showed tolerance to drought, whereas late flowering caused root extension deeper into the soil. The previous study emphasized that L. tomentosus showed a reduced transpiration rate, and L. culinaris ssp. orientalis and L. lamottei accession showed cold tolerance capacities that may be good candidates for lentil improvement breeding programs (Hamdi and Erskine 1996; Gorim and Vandenberg 2017). Kumar et al. (2011, 2013) and Singh et al. (2013) identified variation of yield attributes and suitable donor for crop duration, biological yield, secondary branches, seed size, pod numbers, and yield in various Lens species. The accession ILWL 118 from L. culinaris ssp. orientalis is an excellent source of earliness that is critical for rice fallows and rainfed condition in Eastern and Central India, respectively. For

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improvement in growth habit, biomass production, and seed traits, utilization of L. ervoidis as a donor source is reported (Tullu et al. 2013). L. culinaris ssp. orientalis and L. lamottei are the potential sources of genes pertaining to size of seed and seed and pod number (Ferguson et al. 1998; Gupta and Sharma 2006). Singh et al. (2014, 2020) evaluated and found significant variation for agronomical important traits like yield variation and resistance against multiple diseases in L. ervoidis and L. nigricans of Lens wild species. L. culinaris accessions JL 1, IPL 98/193, and DPL 53 showed excellent root parameters; therefore, these genotypes survive and sustain in drought conditions (Kumar et al. 2012). Malhotra et al. (2004) has reported that some lentil genotypes have strong mechanism to drought escape, namely ILL7618, ILL7981, ILL9922, ILL9830, ILL9844, ILL9920, ILL6024, ILL7504, ILL8095, ILL8138, and ILL8621 when research was performed in the ICARDA (Mediterranean environment). Lens crop wild relatives have developed rich genetic diversities and adapted a broad range of environments for drought tolerances (Hamdi and Erskine 1996). The primary approaches for combating drought stress are avoidance, escape, and tolerance in the evaluated Lens species (L. culinaris Eston, L. odemensis acc. IG 72623, L. lamottei acc. IG 110813, and L. orientalis acc. PI 572376, PI 572376) that are capable of tolerance to drought stress (Fang and Xiong 2015; Gorim and Vandenberg 2017). Recently studied by Rajendran et al. (2021), they marked the accession ILL 7835 as a considerably good source for stable tolerance against the combined stress of heat and drought under various environmental conditions in Morocco. Major biotic stress donors for Lens species, i.e., Fusarium wilt, Stemphylium blight, Ascochyta blight, anthracnose, rust, powdery mildew, Sitona weevil, bruchids, and Orobanche, have been identified and utilized for improving cultivated lentil spp. (Meena et al. 2017). Moreover, 248 accessions of CWRs germplasm from ICARDA were evaluated for Ascochyta blight resistance by Bayaa et al. (1994). They found suitable donor in 3 accessions (L. culinaris ssp. odemensis), 12 accessions (L. culinaris ssp. orientalis), and 36 accessions (L. nigricans) for Ascochyta blight resistance. Fernández-Aparicio et al. (2009) evaluated wild Lens accessions and identified resistance to broom rape in Lens ervoides, Lens odemensis, and Lens orientalis.

8

Brief Account of Molecular Mapping of HR Genes and QTLs

A few molecular mapping studies have been reported in lentil for nutritional traits (Table 6). In this section, we will be discussing them one by one. In a recent study, a set of 96 diverse lentil germplasm lines were evaluated at 3 different locations in India for iron and zinc concentrations, and the entire panel was genotypes with SSR markers (Singh et al. 2017). Association mapping found three simple sequence repeats (SSRs) (PBALC 13, PBALC 206, and GLLC 563) linked with grain Fe concentration (9–11% of phenotypic variation) and four SSRs (PBALC 353, SSR 317–1, PLC 62, and PBALC 217) were associated with grain Zn concentration (14–21% of phenotypic variation). These identified SSRs were found to be

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Table 6 Molecular mapping of nutritional traits in lentil Trait Iron concentration

Zinc concentration

Selenium concentration Manganese concentration

QTLs 3 MTAs

Phenotypic variance (%) 9–11%

3 MTAs

6–13%

2 MTAs

9–21%

2 MTAs

6–17%

4 MTAs

14–21%

SeQTL2.1, SeQTL5.2, SeQTL5.1, SeQTL5.3

6–17%

MnQTL1.1, MnQTL1.2, MnQTL3.1, MnQTL3.2, MnQTL3.3, MnQTL7.1

15–24%

References Singh et al. 2017 Kumar et al. 2019 Khazaei et al. 2017 Kumar et al. 2019 Singh et al. 2017 Ates et al. 2016 Ates et al. 2018

stable across locations. These candidate SSRs can be used in marker-assisted lentil breeding for iron and zinc concentration. In another study utilizing a similar approach using the linkage disequilibrium (LD) analysis with a mixed linear model (MLM), two SSR markers, GLLC 106 and GLLC 108, were associated with grain Fe concentration, explaining 17% and 6% phenotypic variation, respectively, and three SSR markers (PBALC 364, PBALC 92, and GLLC592) were associated with grain Zn concentration, explaining 6%, 8%, and 13% phenotypic variation, respectively (Kumar et al. 2019). Khazaei et al. (2017) used SNP genotyping of a set of 138 cultivated lentil accessions from 34 countries. The entire set was also phenotyped for iron and zinc concentration over four environments. The marker–trait association analysis detected two SNP markers tightly linked to seed Fe and one linked to seed Zn concentration(
log10 P  4.36). A few putative candidate genes were also detected for iron and zinc concentration. Ates et al. (2016) studied a panel of 96 recombinant inbred lines (RILs) developed from the cross “PI 320937”  “Eston” grown in three environments for 2 years. Se concentrations in seed varied between 119 and 883 μg/kg. Genotyping with 4 SSRs and 1780 SNPs and further statistical analysis marked 4 QTL regions and 36 putative QTL markers with seed Se concentration, explaining 6–17% of the total phenotypic variation. In another similar study, Ates et al. (2018) phenotyped a RIL population (120) (CDC Redberry  ILL7502) for manganese concentration. Genotyping with 5385 markers and further linkage analysis found a total of 6 QTL for Mn concentration that were identified using composite interval mapping (CIM). All QTL were statistically significant and explained 15–24% of the total phenotypic variation. Our group at IIPR, India, also identified molecular markers linked with genomic regions in lentil controlling high iron and zinc concentrations; very soon, this information will be in the public domain. It is imperative to mention that in most of the cases, the percent variation explained by linked markers at 0.05 or 0.01 level of significance is lower than their utilization in marker-assisted breeding. Hence, significantly linked SNPs

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can be converted to PCR-based KASP (Kompetitive allele specific PCR) markers for routine use in these traits. Khazaei et al. (2017) reported that Fe and Zn concentrations were positively correlated; however, no common molecular marker could be found; hence, implementation of any marker-assisted selection would require independent selections.

9

Genetic Engineering for HR Traits

9.1

Traits of Interest and Foreign Genes

Genetic engineering methods are available today to incorporate alien genes which are usually not possible to be introgressed into cultivars due to hybridization barriers or incompatibility. With the interventions of molecular biology or genetic engineering today, alien gene coding for foreign proteins that improves the nutritional quality of a particular crop cultivar can be introduced, or already existing genes’ expression may be enhanced or reduced, as in the case of anti-nutritional factors like phytic acid.

9.1.1 Iron Biofortification Multiple methods to develop transgenic plants have been studied to enhance the iron concentration in different model species and cereal crops. However, we will be restricting our discussion on food legumes or pulses as far as possible. Iron-Binding Protein Gene (Ferritin Gene) Pea ferritin was found to be degraded in the case of exposure to gastric pH treatment, and the released iron was transported into the Caco-2 cells by DMT-1 (divalent metal transporter-1). It was further observed that inhibitors of DMT-1 and nonheme iron absorption reduced iron uptake by 26–40%. On the contrary, in the absence of gastric pH treatment, the iron uptake by pea ferritin was normal and unaffected by the inhibitors. Chlorpromazine (clathrin-mediated endocytosis inhibitor) has a negative impact on pea ferritin content; in the case of exposure to chlorpromazine, iron uptake can be reduced by 30%, which further indicates that Fe is transported into cells via a clathrin-mediated endocytic pathway. In addition, 60% less ROS production could be found in pea ferritin as compared to FeSO4. Few workers also reported that endosperm-specific expression of wheat and soybean ferritin in wheat led to several fold (1.5-fold for pea and 1.9-fold for soybean) increases in iron content, respectively (Borg et al. 2012; Xiaoyan et al. 2012). A few years back, in lentil, Sen Gupta et al. (2017) developed molecular markers for Ferritin-1, BHLH-1 (basic helix loop helix), or FER-like transcription factor protein and IRT-1 (iron-related transporter) genes utilizing genome synteny with barrel medic (Medicago truncatula). Significant expression of Ferritin-1 and IRT-1 was observed under excess iron conditions. More efforts are required for full-length cloning and functional validation of lentil ferritin gene for use in genetic engineering-mediated biofortification experiments in lentil.

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Iron-Chelator Gene Nicotianamine (NA) is involved in chelation of iron and regulate Fe homeostasis within the plant system (Curie et al. 2009). NA is the founding molecule of phytosiderophores, which are produced exclusively by the grass family, helping in the transport of Fe within plant system (Curie et al. 2009). Iron Reductase Gene Iron reductase genes reduce ferric ions to ferrous form. This reduction step is required for phytosiderophores-mediated uptake of iron (Schröder et al. 2003). Overexpressing iron reductase gene can help in increased uptake in iron from soil (Douchkov et al. 2005). Pea (brz and dgl) and Arabidopsis (frd3/man1) mutants expressing iron reductase accumulate higher concentration of Fe. In fact, among these mutants, high nicotianamine levels were also observed (Rogers and Guerinot 2002). Insertion of Transporter Gene Iron is transported via different plant transporters through root-soil interface and get stored in apoplasm (Morrissey and Guerinot 2009). The metal transporters of lentil may be studied on this aspect based on the clues established in model species and cereals (Kim et al. 2006; Connorton et al. 2017). Sen Gupta et al. (2017) developed molecular marker specific to IRT-1 (iron-related transporter) transporter gene and also observed genotypic variability in gene expression analysis for this gene; fulllength cloning and functional analysis are required for this and other heavy metal transporter gene families. Decreasing Anti-nutrient Phytic acid is known to be an anti-nutrient which impairs the iron and zinc absorption or bioavailability after consumption. Transgenic wheat plants show an almost fourfold increase in phytase activity (Brinch-Pedersen et al. 2000). In another study, transgenic soybean expressed 2.5-fold higher activity of phytase (Gao et al. 2007). Synthetic phytase gene construct accumulated a higher quantity of proteins than the native ones (Kohli et al. 2006). Increasing Enhancers for Increased Fe Absorption Some dietary components have been known to increase iron absorption. These include vitamins such as β-carotene, ascorbic acid, α-tocopherol, and amino acids, which are released from proteins during digestion. Ascorbic acid and citric acid are known to reduce Fe to a ferrous state and improve absorption in the small intestine. Therefore, transgenic approaches can be used to overexpress ascorbic acid in combination with ferritin (Gropper et al. 2006). An increased cysteine content has also been shown to have a good effect on Fe absorption (Layrisse et al. 1984).

9.1.2 Zinc Biofortification Zinc uptake, transport, and accumulation are similar to iron metabolism; however, more efforts are required to understand the zinc-specific transporter gene families (Zimmermann and Hurrell 2002). It is prevalent worldwide due to widespread soil

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deficiency. Hence, there is a strong demand to increase zinc concentration in staple crops. Improving bioavailability is important in this case as this can make use of even lower uptake (Lonnerdal 2003). Overexpression of NAS Gene Family Nicotianamine (NA) is a ubiquitous chelator of transition metals which transports iron and zinc within plant system. NA synthase (NAS) enzyme is involved in the synthesis of NA from S-adenosylmethionine (Takahashi et al. 2003). Increasing NA concentration in a plant through transgenics by the overexpression of NAS genes showed optimistic results in many cereals. Overexpression of NAC Gene Family NAC transcription factors have a critical role in mobilizing iron and zinc during senescence. By increasing the transcription factors activity, the iron and zinc mobilization may be improved, as was observed in transgenics that showed increased accumulation of zinc (Connorton et al. 2017). In the dicot plant lentil, the importance of these transcription factors has to be studied in detail.

9.2

Achievements of Transgenics in Lentil

Transgenics or genetic engineering technologies are providing opportunity to improve agronomical traits as well as micronutrient concentration in legumes. Agrobacteriummediated genetic transformation has been considered the most common and successful method for trait improvement in grain legumes like pea and soybean (Schroeder et al. 1993). Protoplasts cannot be transformed with Agrobacterium, but they can be cloned, whereas single-event transformants takes a long time to regenerate into plants. However, gene gun (particle bombardment) is efficient method to any plant tissue, but has the unpredictability of gene integration and high risks. Also, Agrobacterium-mediated transformation in many legumes are difficult due to their susceptibility to Agrobacterium infection and very low transformation efficiency (0.03–5.1%) (Yan et al. 2000). The efficiency of explant tissues (cotyledonary, embryo with single cotyledonary disc and node, and decapitated embryo) towards transformation through GUS (β-glucuronidase) found to express the GUS gene following histochemical assay. The explants showed inconsistent nature of GUS expression. In the case of lentil, explants showed much greater areas with GUS expression while some studied samples showed a small portion of the wounded cells competent for transformation (Warkentin and McHughen 1992). However, genetic transformation (Agrobacterium-mediated) is also influenced by several factors (Hashem 2007), including bacterial strain, duration of cocultivation time, explant type, etc. Warkentin and McHughen (1992) reported that inoculation of lentil epicotyl explants for 10–15 min found to be suitable for GUS-positive putative explants. Whereas, many researchers reported that longer coculture period is capable of enhancing the GUS-infected area in lentil explants (Hashem 2007). The virulence

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of the bacterial strain on lentil shoot apices explants differs significantly (Warkentin and McHughen 1992).

9.3

Prospects of Cisgenics

Biotechnological approaches based plant improvement is a continuous process that alters heritability of the trait and induces variation. Therefore, cisgenesis and intragenesis are utilized to create genetic variation in cultivated or existing germplasm for improving their quality and quantity. The advancement of sequencing technologies and genome information facilitates the isolation of intact Cis-genes with associated promoter/terminator from wild or cultivated species, which are utilized to insert into the genome of closely related and crossable species. In the case of intragenesis, different coding and regulatory sequences are assembled either in sense or in antisense orientation. The applications and future prospects of cisgenesis and intragenesis in the improvement of many crops have been studied (Singh et al. 2018b). Disease-resistant cultivar like late blight-resistant potato (gene Rpi-sto1, Rpi-vnt1.1) and scab-resistant apple has been developed. Thus, cisgenesis as a powerful approach to transfer gene of interest without linkage drag. Cisgenic- and intragenic-derived genetically modified plants (GMP) are eco-friendly as classical breeding plants and also exempted from GMP legislation. Dudziak et al. (2019) suggested that application of novel scientific approaches is of major importance for improving the crop plants. However, these most efficient strategies based on genetic modification are still very controversial issues. Opponents of GMO crops do not agree with the use of genetic engineering in crop improvement and the production of new varieties suited for organic agriculture. Cisgenesis suffers many a times from the random insertion in the genome causing variation in gene expression (Cardi 2016). Also, the random insertion may cause silencing of other genes. Random cisgene integration is similar to transgenic varieties, natural transposons, and induced translocations (Schmidt 2002). Another issue is the copy number and presence of vector sequence while transferred into a recipient genome. Schouten et al. (2006) reported that cisgenic transformation through Agrobacterium may also transfer small T-DNA borders. Approximately 80% of plants regenerated from cisgenic transformation experiments with vector backbone sequences. Projects for increasing iron and zinc in crops such as lentil are at varied stages of development (Saltzman et al. 2013). Cisgenesis has a long way to go in lentil improvement since, on the issue of safety, regulators could treat cisgenic plants the same as conventionally bred plants (Schouten et al. 2006).

10

Future Prospects and Conclusion

Lentil is a highly nutritional crop species having a tremendous opportunity as a biofortification crop. Already worldwide biofortified lentil varieties are being grown by the growers. However, there is still scope to better understand metabolism of

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biofortification-related traits in lentil. Only two traits, iron and zinc concentration, have been addressed so far; other important traits, such as folate concentration, Se concentration, and other micronutrients, can be investigated. Profiling of wild or related species as new sources of biofortification related traits is required. Moreover, more studies are required to map the biofortification traits in the lentil genome for their use in breeding programs. New tools like haplotype breeding using nextgeneration sequencing platforms have a great potential for use in this crop species. As far as transgenic or cisgenic research is concerned, functional analysis of genes related to biofortification related traits is a priority area. Lastly, the human nutrition component needs to be included in lentil biofortification research to address the malnutrition in a more holistic way.

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Welch MR, Graham DR (1999) A new paradigm for world agriculture: meeting human needs productive sustainable nutritious. Field Crops Res 60:1–10 Wessells KR, Brown KH (2012) Estimating the global prevalence of zinc deficiency: results based on zinc availability in national food supplies and the prevalence of stunting. PLoS One 7(11): e505–e568 White PJ, Broadley MR (2009) Biofortification of crops with seven mineral elements often lacking in human diets -iron, zinc, copper, calcium, magnesium, selenium and iodine. New Phytol 182(1):49–84 WHO (2008) The world health report. World Health Organization, Geneva WHO (2009) The world health report. World Health Organization, Geneva WHO (2012) The world health report. World Health Organization, Geneva Wong MML, Gujaria-Verma N, Ramsay L, Yuan HY, Caron C, Diapari M et al (2015) Classification and characterization of species within the genus lens using genotyping-by-sequencing (GBS). PLoS One 10(3):e0122025. https://doi.org/10.1371/journal.pone.0122025 Wright DM, Neupane S, Heidecker T, Haile TA, Chan C, Coyne CJ, McGee RJ, Udupa S, Henkrar F, Barilli E, Rubiales D (2021) Understanding photothermal interactions will help expand production range and increase genetic diversity of lentil (Lens culinaris Medik.). Plants, People, Planet 3(2):171–81 Xiaoyan S, Yan Z, Shubin W (2012) Improvement Fe content of wheat (Triticum aestivum) grain by soybean ferritin expression cassette without vector backbone sequence. J Agric Food Biochem 20:766–773. Available online at: https://www.semanticscholar.org/paper/Improvement-FeContent-of-Wheat(Triticum-aestivum)-Xiao/74c0480abe93478866cc155188e64407f1ff68e6 Yan B, Srinivasa Reddy MS, Collins GB, Dinkins RD (2000) Agrobacterium tumefaciens–mediated transformation of soybean [Glycine max (L.) Merrill.] using immature zygotic cotyledon explants. Plant Cell Reports 19:1090–7 Yang XE, Chen WR, Feng Y (2007) Improving human micronutrient nutrition through biofortification in the soil plant system: China as a case study. Environ Geochem Health 29: 413–428 Zimmermann MB, Hurrell RF (2002) Improving iron, zinc and vitamin A nutrition through plant biotechnology. Current Opinion in Biotechnology 13(2):142–5

Grain Micronutrients in Pigeonpea: Genetic Improvement Using Modern Breeding Approaches Aloleca Mukherjee, Anjan Hazra, Dwaipayan Sinha, Prathyusha Cheguri, Shruthi H B, Sanatan Ghosh, Naresh Bomma, Rituparna Kundu Chaudhuri, Prakash I. Gangashetty, and Dipankar Chakraborti Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Limitations in Conventional Breeding and Rationale of Nutritional Genomics . . . . . . . . . 3 Medicinal Properties of Pigeonpea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Ethnomedicinal Uses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Active Principles of Pigeonpea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Pharmacological Uses of Pigeonpea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Genetic Resources of Health-Related (HR) Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Classical Genetics and Traditional Breeding for HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Genetic Diversity with Regard to HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Molecular Mapping of HR Genes and QTLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Marker-Assisted Breeding for HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Map-Based Cloning of HR Genes/QTLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Genomics-Aided Breeding for HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Transgenic Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Transgenic Pigeonpea Development for Biofortification . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Biofortification Resources of Pigeonpea Used in Other Transgenic Crops . . . . . . . 12 Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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A. Mukherjee · A. Hazra · S. Ghosh · D. Chakraborti (*) Department of Genetics, University of Calcutta, Kolkata, West Bengal, India e-mail: [email protected] D. Sinha Department of Botany, Government General Degree College Mohanpur, Mohanpur, West Bengal, India P. Cheguri · S. H. B · N. Bomma · P. I. Gangashetty (*) Pigeonpea Improvement Program, International Crops Research Institute for Semi-Arid Tropics (ICRISAT), Patancheru, Telangana, India e-mail: [email protected] R. Kundu Chaudhuri Department of Botany, Barasat Government College, Barasat, West Bengal, India © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_28

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Abstract

The green revolution increased crop productivity and significantly reduced starvation and protein malnutrition. However, this caused micronutrient depleted soil, thereby responsible for widespread deficiencies of plant nutrients. Legumes are the important constituents of traditional healthy diets worldwide and second in agricultural importance after cereals. On a worldwide scale, pigeonpea ranks sixth among all legume crops and is India’s second most important legume. Biofortification is the process of enhancing the nutrient value of crops using conventional selective breeding and agronomic approaches or via genetically modifying them. In many Indian states, the seeds of pigeonpea serve as a protein-rich pulse and are consumed in many forms including grain, vegetable and fodder. A variety of nutrients are present in the seeds, including carbohydrates, fats, protein, vitamins, minerals, and also some secondary metabolites. Pigeonpea exhibited various ethnomedicinal and pharmacological properties, and it has a long history of ethnobotanical use. Conventional breeding programs are utilized to develop nutritionally improved cultivars, although the success of such a program is very slow due to restricted gene pool and linkage drag. The exploitation of breeding-based approaches along with supportive interdisciplinary research and development have been utilized for biofortified pigeonpea development. Some transgenic approaches were also undertaken for nutritional improvement and antibody production. Further improvement in those approaches and genomic technologies will enhance the nutritional quality of pigeonpea. Keywords

Genomics-assisted breeding · Health related traits · Molecular markers · Nutraceuticals · Quantitative trait loci · Whole genome sequence

1

Introduction

Pulses hold a salient position in Indian Agriculture. India tops the list for being the largest producer and consumer of pulses in the world, contributing about 25% to the global pulse or grain legumes production (Saxena et al. 2019). One such important grain legume, which has originated from the Indian subcontinent, is the pigeonpea (Cajanus cajan (L.) Millspaugh). Predominantly grown in rain-fed conditions, pigeonpea is a considerable source of protein to rural and urban households in Asia and Africa. It augments and enhances the soil through symbiotic nitrogen fixation and revitalizes the soil by recycling of soil nutrients, releasing soil-bound phosphorus, and addition of organic matter (Pahwa et al. 2013). Moreover, it is a great source for additional nitrogen supply to the subsequent crops. According to studies, pigeonpea releases roughly 40 kg/ha of residual nitrogen in the crop fields. All these properties cooperatively make pigeonpea a supreme crop for sustainable agriculture, around the equatorial regions of India. About three-fourths of the total

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Indian production of pigeonpea is derived from Gujarat, Karnataka, Maharashtra, Madhya Pradesh, Andhra Pradesh, and Uttar Pradesh. In Barbados, pigeons were fed with these pigeonpea seeds grown on barren lands; this justifies the name. Being a short-day plant, it has a longevity of 3–4 years. Plough pan is formed below the normal ploughing zone and is a compact soil layer, which reduces the productivity of the land. The long tap roots of pigeonpea are prominently known as “biological plough” because of their ability to break plough pan. The pigeonpea seeds consist of three structural features – cotyledons, seed coat, and embryo. The embryo is rich in albumin, globulin, and the cotyledons have high carbohydrate content, along with calcium and iron (Figs. 1 and 2). The albumin has affluent number of amino acids rich in sulphur; which encompasses methionine and cystine. Other amino acids like glycine, lysine, alanine, and aspartic acid are also present. Methionine is a limiting essential amino acid and hence, it is a beneficial factor under nutrition. The pigeonpea seed coat majorly contains amino acids like serine, proline, threonine, and glycine (Saxena et al. 2019). The pigeonpea seeds are an integral part of Indian diet. The dry seeds are dehusked and split into cotyledons which are commonly cooked as “dal.” In many Indian states, the green seeds serve as a protein-rich vegetable. To garner highest seed yield and utmost nutritional quality, the green pods must be harvested at an appropriate stage. An inverse relationship was observed between the starch content and the sugar-protein contents. In the developing seeds, there is a drop in the sugar and protein content and a rapid elevation in the starch content whereas, iron, zinc, calcium, magnesium, and copper contents were found to be more or less unchanged during seed development in pigeonpea. Pigeonpea also holds certain antinutritional factors. Polyphenols such as tannins and phenols, oligosaccharides, lectins, enzyme inhibitors like chymotrypsin and trypsin are some of the above mentioned factors (Toklu et al. 2021). Trypsin and chymotrypsin inhibitors are expressed only in the seeds. Whole seeds without dehulling are also consumed in many countries. Cooking of pigeonpea also plays a significant role which affects its nutritional features. The seeds are large in size, absorb more water, and have high nitrogen content, which makes it a quick cooking dal. Cooking not only enhances the bioavailability of certain nutrients, it also destroys certain antinutritional components. For instance, starch digestibility is improved by cooking whereas there is a drop in the measure of oligosaccharides. Heat destroys thiamine and riboflavin, but niacin content remains unchanged during roasting and cooking of pigeonpea seeds. Methionine and lysine content decreases upon roasting, whereas there are reports on increased methionine upon boiling. Pigeonpea possesses many herbal properties which are essentially described in folk medicine and used to treat numerous human illnesses (Salehi et al. 2019). Pneumonia, bronchitis, coughs can be cured using floral extracts of pigeonpea. It can also be employed to treat respiratory infections, menstrual distress, and dysentery. Dried seeds have the ability to ease difficulties like headache and vertigo, whereas fresh seeds help to diminish urinary incontinence, as well as other kidney disorders. The seed extracts aid in curing sickle cell anemia, by impeding the

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Fig. 1 Overall nutrient composition and their distribution in pigeonpea. (a) Nutrients in mature pigeonpea. (b) Major amino acids in mature pigeonpea. (c) Vitamins in mature pigeonpea. (d) Minerals and trace elements. (e) Protein fractions in dry pigeonpea seeds (Saxena et al. 2002)

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Fig. 1 (continued)

sickling of erythrocytes. According to some reports, dried pigeonpea roots could be used as anthelmintic, sedative, vulnerary, expectorant, and alexiteric.

2

Limitations in Conventional Breeding and Rationale of Nutritional Genomics

Improving the yield quantity, nutritional quality, and maintenance of genotype stability are the primary approaches to fulfil the demands of the population. Conventional breeding practices coupled with genomics-based selection approaches need to be employed to fight the threats offered by climate change and increasing population (Singh et al. 2020).

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Fig. 2 Detailed nutrient composition of pigeonpea. (a) Amino acid composition (Ade-Omowaye et al. 2015). (b) Carbohydrate profile (Apata 2008). (c) Fatty acid profile (Ade-Omowaye et al. 2015)

Traditional plant breeding methods include the recognition and development of improved parental lines that has quality nutrient content, hybridization with elite genotypes, followed by selection of hybrids over a number of generations to get commercially established cultivars showing required nutritional properties. Additional considerations include quantitative trait complexity and the difficulty of selection of desirable trait because of low heritability. As a result, traditional methods take longer to grow a new and improved variety. Advancement in omics techniques in combination with breeding programs have a lot of potential to contribute for nutritional quality improvement in pigeonpea (Singh et al. 2020). Some of the constraints related to nutritional improvement of pigeonpea are detailed in the next few paragraphs. Limited diversity within the basic pool of genes was revealed by a polymorphism study of sampled Cajanus accessions. Breeders have no choice but to use species and sub-species from secondary, tertiary, and quaternary gene pools through conventional and marker assisted selection techniques. Despite of vast genetic diversity of wild relatives, there is limitation of incorporation of them in breeding program because of lack of accurate information on the availability of desirable features and the necessity for extensive research whenever they are used. Poor agronomic traits in combination with partial characterization of relatively few wild relatives are responsible for lag in genetic improvement of pigeonpea (Saxena et al. 2014).

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Pigeonpea is a short-day plant (Vales et al. 2012). A pivotal regulator of flower induction is the interaction of the photoperiod with day and night temperature. Hence, beyond 30
northern and southern latitudes, the cultivation of pigeonpea is restricted. (Saxena 2008). There is an inverse correlation between earliness and photosensitivity which confirms limited success of breeding programs in photoinsensitive and late maturing cultivars. Low-temperature in combination with photoperiod and sensitivity limit the cultivation of this crop in higher altitudes and latitudes (Vales et al. 2012). This is restricting the use of pigeonpea in alternative cropping systems (Vales et al. 2012). The transfer of the genes of interest into the elite cultivar is highly interfered by the association of unwanted phenotypes with certain nutritional traits. As an example, transferring the genes involved in high protein accumulation was tried from C. scarabaeoides and C. albicans to the cultivars of pigeonpea. The selection of the desired genotype, high in productivity and protein yield, was obtained only after some 12–14 generations (Saxena and Sawargaonkar 2015).

3

Medicinal Properties of Pigeonpea

Pigeonpea had been used extensively in traditional medicine. In addition, the plant has also exhibited a wide array of pharmacological properties. This section will describe the various ethnomedicinal and pharmacological properties of pigeonpea along with a brief illustration about the selected chemical constituents present in the plant.

3.1

Ethnomedicinal Uses

The Garo tribal community of Netrakona district of Bangladesh uses pigeonpea as a remedy for diabetes. The seed paste of this plant is used as a stimulant while the leaf juice is used for the treatment of diabetes (Rahmatullah et al. 2009). In Trinidad and Tobago, the plant is used to treat food poisoning and is considered as colic. It is also used to treat constipation (Lans 2007). In Cote D’Ivoire, extraction from the leaves and stem are utilized for the treating of anemia, skin disease, and wounds (Koné et al. 2011). In Benin, the similar preparation is used for the treatment of candidiasis (Fanou et al. 2020). The local communities of south western Uganda use the juice of the leaves for the treatment of ear disease (Gumisiriza et al. 2019). In south west Nigeria, the leaves of the plants are used for treating malaria (Olorunnisola et al. 2013).

3.2

Active Principles of Pigeonpea

Chemical analysis revealed high quantities of flavonoids and stilbenes in the leaves of pigeonpea. Saponins, a significant quantity of tannins, and modest amounts of reducing sugars, resin, and terpenoids were also reported from the plant (Pal et al. 2011). Pigeonpea flavonoids can be found in a variety of plant organs. There are 27 flavonoids

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present. Among them flavones, isoflavones, and flavonols have been noticed in six, eight, and four numbers respectively. Besides them two anthocyanins and several flavanones, isoflavanones are also recorded, along with a solitary chalcone (Nix et al. 2015). Table 1 illustrates the selected flavonoids present in the plant. Apart from these, the plant contains stilbenes in the form of longistylene A (Wu et al. 2020) and longistylene C (Wang et al. 2011). Cajanus lactone and cajaninstilbene acid (Wu et al. 2009) along with pinostrobin have also been reported from the leaves of the plant (Patel and Bhutani 2014).

3.3

Pharmacological Uses of Pigeonpea

Since ancient times, different portions of pigeonpea have been used for their biological activity, and some of them have experimental grounds for acceptability. Aside from their use in traditional medicine, there have been various studies on pigeonpea’s biological and pharmacological properties (Table 2).

3.3.1 Antibacterial Activity The antibacterial activity of pigeonpea has been explored in a number of studies. In one experiment it was shown that the ethyl acetate leaf extraction contains naringenin that inhibited growth of Salmonella typhi and Staphylococcus aureus indicating its potential in the treatment of typhoid (Agus et al. 2017). It was shown that organic solvents extractions and water extracts were inhibiting Escherichia coli, Staphylococcus aureus growth, whereas Klebsiella pneumonae was inhibited by the extracts of organic solvents only. In addition, the minimum concentration of extract to inhibit E. coli was recorded as 0.125–0.25 mg/ml; to inhibit S. aureus it was found to be 0.125 mg/ml and that of Salmonella typhi was to be 0.0325–0.0625 mg/ml (Okigbo and Omodamiro 2007). 3.3.2 Antifungal Activity Antifungal activity of the plant was evaluated using ethanolic extract of leaf and root. It was observed that extracts inhibited growth of Candida albicans and Candida tropicalis. Tannins, flavonoids, and alkaloids in extracts from both organs was discovered to have clinically significant antifungal activity (Brito et al. 2012). 3.3.3 Antiviral Activity One study looked at the activity of water and ethanolic extracts against the measles virus as well as its toxic effect to embryonated chicken eggs. The in vivo assay using stem extraction in water provided a Log(2) titre of 0.1, and when the assay was done in vitro, a 100% suppression of cytopathic effect was observed in cell lines of Hep-2. Hemagglutination titration revealed a decrease in viral content ( p ¼ 0.05) at all concentrations of the extracts (Nwodo et al. 2011).

Chalcone

Isoflavanone

Flavanones

Flavonols

Isoflavones

Types Flavones

Name Apigenin Luteolin Vitexin Isovitexin Orientin Biochanin A Cajanin Genistein 20 -Hydroxygenistein Quercetin Isoquercitrin Isorhamnetin Naringenin Pinostrobin Cajanol Cajanone Pinostrobin

20 ,60 -Dihydroxy-40 -methoxychalcone

IUPAC name 5,7,40 -trihydroxyflavone 5,7, 30 ,40 -tetrahydroxyflavone Apigenin 8-C-glucoside Apigenin 6-C-glucoside Luteolin 8-C-glucoside 5,7-Dihydroxy-40 -methoxyisoflavone 5, 20 ,40 -Trihydroxy-7-methoxyisoflavone 5,7,40 -Trihydroxyisoflavone 5,7,20 ,40 -Tetrahydroxyisoflavone 3,5,7,30 ,40 -Pentahydroxyflavone Quercetin 3-β-D-glucoside 30 -Methoxyquercetin 5,7,40 -Trihydroxyflavanone 5-Hydroxy-7-methoxyflavanone 5,40 -Dihydroxy-7,20 -dimethoxyisoflavanone

Table 1 Selected flavonoids isolated from pigeonpea Source plant organ Leaves Leaves Leaves Leaves Leaves Leaves and roots Seed and etiolated stems Roots/root, bark, and etiolated stems Roots/root, bark, and etiolated stems Leaves Pod surface Leaves Leaves Leaves Roots Roots Leaves

Wei et al. 2013 Duker-Eshun et al. 2004 Dahiya 1987 Duker-Eshun et al. 2004 Duker-Eshun et al. 2004 Zu et al. 2006 Green et al. 2003 Zu et al. 2006 Wei et al. 2013 Wei et al. 2013 Luo et al. 2010 Dahiya 1991 Patel and Bhutani 2014

Fu et al. 2007

References Fu et al. 2008

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10.

Leaf

Leaf

9.

Hypocholesterolemic effect Hypolipidemic effect

Leaf

8.

Root

Antidiabetic activity

7.

Antimalarial activity

5.

Root

Antiviral activity

4.

6.

Leaf Root Leaf Stem Root Leaf

Antifungal activity

3.

Parts Leaf

Leaf

Pharmacological activity Antibacterial activity

2.

S. no. 1.

Ethanolic extract followed by extraction with hexane and dichloro ethane Methanolic extract

Methnolic extract

Methanolic extract of roots

Methanol extract Column chromatographic technique with organic solvent systems used to isolate compound Ethanolic extract of roots

Hot water and ethanol extract of leaf, stem, and root

Petroleum ether, ethanol, and chloroform/ methanol mixture extracts (organic) Aqueous extract Ethanolic extract of leaf and root

Form used Ethyl acetate fraction of leaf extract

Table 2 Pharmacological activities of pigeonpea

Cajanin, Longistylin C, and Longistylin A

Longistylin A and C, and betulinic acid

Cajachalcone

Active principle involved Naringenin

Akinloye and Solanke 2011

Duker-Eshun et al. 2004 Nahar et al. 2014 Ezike et al. 2010 Luo et al. 2008

Ajaiyeoba et al. 2013

Nwodo et al. 2011

References Agus et al. 2017 Okigbo and Omodamiro 2007 Brito et al. 2012

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Antihelminthic activity

Hepatoprotective

Anti-inflammatory activity Anti-inflammatory and antinociceptive activities

12.

13.

14.

Anticancer activity

Antioxidant activity

16. 17. 18.

19.

15.

Neuractive activity

11.

Root Root Stem, roots Leaf

Seed

Root

Leaf

Leaf

Leaf

Aqueous extract Ethanol extract Petroleum ether extract Ethyl acetate fraction n-Butanol fraction

Pure compound Pure compound Aqueous extract

Hexane extracts

Hot water and ethanolic extract extract

Ethanolic extract followed by partitioning and column chromatography using organic solvents Extraction with petroleum ether, ethyl acetate, ethanol, and water Ethanolic extract

Cajaninstilbene acid Pinostrobin Vitexin Orientin

Quercetin-3-O-β-D-glucopyranoside, Orientin, Vitexin, Quercetin, Luteolin, Apigenin, Isorhamnetin Cajanol Cajanin

Pinostrobin

Luo et al. 2010 Fu et al. 2015 Teixeira et al. 2021 Wu et al. 2009

Hassan et al. 2016

Khan et al. 2015 Iweala et al. 2019 Vo et al. 2020

Nicholson et al. 2010

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3.3.4 Antimalarial Activity Antimalarial activity of the plant was determined in vitro utilizing Plasmodium falciparum (K1) which is a multiresistant strain. This variant was used in the parasite lactate dehydrogenase assay employing bioassay-fractionation of the pigeonpea leaf extraction in methanol. Various chromatographic techniques were used to isolate the compound, and spectroscopy was used to determine its structure. The physiologically active ingredient from the ethyl acetate fraction was identified as a cajachalcone also known as 20 ,60 -dihydroxy-4-methoxy chalcone. The IC50 of cajachalcone was 2.0 μg/ml (7.4 μM). Plasmodium falciparum was inhibited by the extracts containing active principle (Ajaiyeoba et al. 2013). In another study, it was observed that in vitro assays performed with the Plasmodium falciparum strain 3D7 that shows chloroquine-sensitivity was moderately strong for various compounds like betulinic acid, longistylin A and C, stilbenes (Duker-Eshun et al. 2004). 3.3.5 Antidiabetic Activity The antidiabetic activity of the methanolic root extract was monitored using alloxan-applied mice with diabetes for 5 days. This indicated that upon oral ingestion of extracts of plant at various doses of body weight (200–400 mg/kg), there was a significant reduction in serum fasting glucose in diabetic mice induced with alloxan (Nahar et al. 2014). Some studies demonstrated that when alloxan applied mice, showing diabetes, were administered with 400–600 mg/kg of methanolic extract, the fasting blood sugar reduced with maximum effect between 4 and 6 h (Ezike et al. 2010). 3.3.6 Hypocholesterolemic Effect Hypocholesterolemic effect of the leaf extraction of pigeonpea was evaluated on diet-induced hypercholesterolemic mice. Excessive levels of serum and cholesterol from liver were significantly lessened by the 200 mg/kg plant extract after 4 weeks pretreatment, comparing to the model, by nearly 31% and 23% ( p ¼ 0.01), respectively. The proportions of serum and liver triglycerides were also minimized by 23% and 14%, respectively. During this time, LDL cholesterol from serum reduced by almost 53% ( p ¼ 0.01), whereas superoxide dismutase activity from serum rose by nearly 21%. The body weight and atherogenic index were both significantly lowered. mRNA transcript accumulation of HMG-CoA reductase, LDL-receptor, and CYP7A1were dramatically increased in mice given 200 mg/kg/ day of plant extract, but the hypercholesterolemic diet repressed those expressions (Luo et al. 2008). 3.3.7 Hypolipidemic Effect Methanolic extraction from leaves of the plant was tested for its hypolipidemic effect. The result showed a significant ( p ¼ 0.05) reduction in cholesterol, serum triglyceride, HDL, LDL, cholesterol, and blood glucose. The extract also reduced the functionality of aspartate transaminase and alanine transaminase along with reduction in levels of creatinine, urea and malondialdehyde levels in alloxan induced hyperglycemic mice (Akinloye and Solanke 2011).

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3.3.8 Neuroactive Activity Pinostrobin, from pigeonpea, was studied in vitro for its neuroactive characteristics and was found to inhibit voltage-gated sodium channels (IC50 ¼ 23 μM). This study was based on the previously known background about pinostrobin, which has the capacity to reduce the depolarization effects of a certain selective activator of sodium channels called veratridine, in the brain synaptonemal complex of mice. This compound had nil effect on synaptoneurosomes resting membrane-potential. Pinostrobin’s pharmacological profile is similar to that of depressive medications that block sodium channels (Nicholson et al. 2010). 3.3.9 Anthelminthic Activity Antihelminthic activity was assessed using the ethanolic and aqueous extract of the pigeonpea. The results suggest that, aqueous extraction has anthelmintic action for paralyzing and killing Indian earthworm Pheritima posthuma for a long period at 5 mg concentration, whereas the ethanolic extract has paralysis and death in a short time at the same dosage (Khan et al. 2015). 3.3.10 Hepatoprotective Activity The hepatoprotective activity of the plant was studied with respect to hepatotoxicity in male wistar rats. N-Nitrosodiethylamine (NDEA) induced hepatotoxicity which was reversed by the ethanolic extract of the leaf of the plant. The results indicated that pigeonpea-treated groups had considerably ( p ¼ 0.05) lower alanine and aspartate aminotransferases levels and significantly ( p ¼ 0.05) higher glutathione S-transferase, superoxide dismutase, glutathione, albumin, and catalase levels (Iweala et al. 2019). 3.3.11 Anti-inflammatory Activity The anti-inflammatory activity of pigeonpea was evaluated in an in vitro experiment using RAW 264.7 cells. The results confirmed that 95% ethanolic extract of the roots dramatically reduced intracellular reactive oxygen species and increased superoxide dismutase and catalase activity. EECR95 induced nuclear factor (NF) erythroid 2-related factor 2/antioxidant protein heme oxygenase-1 and hindered nuclear factor kappa B (NF-B) signaling pathways, resulting in antioxidant and anti-inflammatory properties, according to mechanism studies (Vo et al. 2020). In another experiment, albino rats were used as experimentation models to study the anti-inflammatory and antinociceptive activities of the plant seeds. The results indicated that in hexane extract of seeds, twenty-one unsaponifiable chemicals (including various phytols, stigmasterol, 2,6-di-(t-butyl)-4-hydroxy-4-methyl-2,5-cyclohexadiene-1-one, campesterol, and sitosterol) as well as fatty acids described mostly as palmitic acids and 9,12-octadecadienoic, almost 12 in numbers were found. Quercetin, Orientin, Luteolin, Quercetin-3-O-D-Glucopyranoside, Vitexin, Apigenin, and Isorhamnetin are all found in the n-butanolic extraction part. Three hours after carrageenan challenge, the hexane extract (200 and 400 mg/kg) reduced carrageenan induced inflammatory effects by a significant 85% and 95%, respectively. This was associated by a reduction in TNF- and IL-6 levels of 11% and 20%, 8% and 13%, respectively, as well as a significant reduction in IgG serum quantity. In

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addition, hexane fraction (200 and 400 mg/kg) reduced writings by 61 and 83%, respectively (Hassan et al. 2016).

3.3.12 Anticancer Activity The anticancer activity of cajanol, an isoflavanone derived from pigeonpea roots, was noted in a study using breast cancer cell lines from human (MCF-7). Cajanol suppressed MCF-7 cell growth depending upon dose- and time-specificity. After 24 h of treatment, the IC50 value was 83.42 μM, reached 58.32 μM after 48 h, and reduced to 54.05 μM after 72 h. Cajanol used a ROS-mediated mitochondria-dependent route to inhibit the cell cycle in the G2 and M stage and cause programmed cell death. Cajanol blocked the expression of Bcl-2 expression and elevated expression of the Bax gene, which led to the rupture of the outer mitochondrial membrane and resulted in cytochrome c liberation, as experimented through Western blot. The induction of the caspase-9 and caspase-3 cascades was linked to mitochondrial cytochrome c release, while active-caspase-3 was engaged in PARP cleavage (Luo et al. 2010). Another research showed cajanin stilbene acid obtained from the plant were investigated for its anticancer properties. Cajanin caused apoptosis and G2/M inhibition in a concentration-specified manner. Matrix Metalloproteinases was degraded, Bax level was increased, Bcl-2 was decreased, and caspase-3 was induced. BRCA-specific DNA impairment responsive pathways as well as cell cyclecontrolling chromosome replicative pathways were both impacted by cajanin stilbene acid, according to microarray profiling (Fu et al. 2015). Other study indicated that the fractions of stem and root extracts inhibited melanoma proteases and generated cellular toxicity in SK-MEL-28 cells, cultured in vitro (Teixeira et al. 2021). 3.3.13 Antioxidant Activity In a study, the antioxidative nature of pigeonpea from aqueous and ethanolic leaf extracts, as well as ethyl acetate, n-butanol, petroleum ether, and water fractions, as well as the four main compounds separated from the ethanol extract, namely pinostrobin, cajaninstilbene acid, orientin, and vitexin were investigated by a DPPH radical-scavenging assay. An IC50 value of 194.98 μg/ml, the ethyl acetate fraction had the highest scavenging power among the four fractions. Pinostrobin and vitexin were shown to have less effective radical-scavenging powers than cajaninstilbene acid (302.12 μg/ml) and orientin (316.21 μg/ml). The inhibition ratio (%) of the ethyl acetate fraction (94.13%  3.41%) was found to be the greatest in the beta-carotenelinoleic acid test, practically matching the inhibitory capability of the positive control BHT (93.89%  1.45%) at 4 mg/ml. When compared, cajaninstilbene (321.53 μg/ml) and orientin (444.61 μg/ml) had moderate antioxidant effects, while pinostrobin and vitexin both exhibited antioxidant activities at greater than 500 μg/ml (Wu et al. 2009).

4

Genetic Resources of Health-Related (HR) Genes

A large number of genetic resource accumulations, including genetic maps, molecular markers, whole-genome resequencing (WGRS) data, transcriptome assemblies, a reference genome sequence (Fig. 3) (Varshney et al. 2012) from multiple cultivars,

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Fig. 3 Timeline of major genomic approaches adopted in pigeonpea

have become available in pigeonpea (Kumar et al. 2016; Varshney et al. 2017). These resources have aided in the creation of high-resolution genetic maps as well as efficient and expeditious genetic analysis of quantitative trait loci (QTLs) and genes regulating important nutritional traits in pigeonpea (Saxena et al. 2012). Pigeonpea is an essential food source with amino acid rich plant protein for more than a billion people worldwide. However, genetic improvement for seed protein content (SPC) in the crop has acquired little concern in the past. The use of genomicsassisted breeding could aid in the acceleration of SPC genetic gain. Four genotypes of pigeonpea were taken for whole-genome resequencing data to recognize sequencebased markers and associated possible SPC genes (Obala et al. 2019). One hundred and eight sequence variations obtained from 57 genes were recognized by combining a common variant sieving methodology on already procured WGRS data with the gene functioning data concerning SPC. Subsequently, 17 of the 30 sequence variants when transformed into CAPS/dCAPS markers showed significant polymorphic traits between genotypes of low and high SPC. A significant ( p ¼ 0.05) co-segregation of 4 of the CAPS/dCAPS markers was observed with SPC when 16 polymorphic CAPS/dCAPS markers were tested on F2 generation which is a cross of ICP 5529 and ICP 11605, former with high SCP and the latter with low SCP. In summary, mutations in four gene sequences gave rise to four markers and were suggested to be helpful in pigeonpea crop improvement programmes for enhancing/regulating SPC (Obala et al. 2019).

5

Classical Genetics and Traditional Breeding for HR Traits

Over the last two decades, many attempts have been made to create high-yielding cultivars by traditional breeding methods and advancements in biotechnology. These investigations have given information and understanding for creating superior pigeonpea varieties with many agronomically important quality characters and show great yield potential even in challenging agro-climatic settings. New cultivars with better nutritional content and boosting production potential have already been created using traditional plant-breeding techniques. To develop genotypes with the required nutritionally rich and agronomically superior features, classical plant breeding requires identifying and developing parental lines showing enhanced nutritionrich content, crossing the latter with elite germplasm, and selection of the

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segregating population for some generations (Pfeiffer and McClafferty 2007). Thus, it pertains to a much-extended time to procure a novel or better variety. The complications at genetic level of quantitative traits and low heritability are some bottlenecks that pose challenges for selecting superiors. Due to a number of specific features, breeding of pigeonpea has proven to be more difficult than breeding other edible legumes. Pigeonpea is often crosspollinated crop. Insect-aided natural outcrossing rates of 20–70% in pigeonpea, have restricted the application of effective selection and mating methods are available in self-pollinating species (Saxena and Sharma 1990). This crop’s yield potential has gradually increased due to the employment of extensive hybridization, pure line breeding, population breeding along with mutation breeding hence create new pigeonpea varieties. Two genetic male-sterility (GMS) systems were found in pigeonpea to help with this bottleneck (Reddy et al. 1979). The GMS-based hybrids had a yield which was 30% more than that of nonhybrids but did not prove to be commercially viable because of its exorbitant production cost. The alternative and more effective cytoplasmic-genetic male-sterility (CGMS) approach was created in response to the yield-jump seen in the GMS hybrids (Saxena and Kumar 2003). In 2004, India had its first cytoplasmic male sterility (CMS)-based hybrid GTH-1 available from ICRISAT’s hybrid development programme in partnership with its partners. Furthermore, another CMS-based pigeonpea hybrid, ICPH 2671, was created in 2005 at ICRISAT utilizing C. cajanifolius (A4 cytoplasm) and has since been commercially available by Pravardhan Seeds under the name “Pushkal” for cultivation in various Indian states, including Maharashtra, Madhya Pradesh, Karnataka, and Andhra Pradesh. The expanded area cultivating pigeonpea hybrids is projected to result in higher crop yield and satisfying returns for farmers and pigeonpea production in a sustainable manner was possible. This will again be made feasible by ongoing attempts to breed resistance to biotic and abiotic challenges. Besides breeding for yield, breeding for nutrition has always been the focus of pigeonpea breeders. Despite pigeonpea being the household dal, consuming every single day, the average protein requirement of an Indian adult is not met. Hence, a breeding programme was initiated back in 1982 at ICRISAT. ICRISAT’s genebank houses 13,632 germplasm which has a protein range from 9% to 30% (Varshney et al. 2012). Protein content in pigeonpea is controlled by additive genetic action. Based on available information from the genebank, wild progenitors C. scarabaeoids (28.4%), C. sericeous (29.4%), and C. albicans (30.5%) were utilized to develop new protein lines. Accordingly, newly bred lines, called high protein lines (HPL) reported protein content up to 32%. These lines are in preliminary yield testing stage and serve as a donor for high protein trait in a breeding program. This twenty-first century has greater innovation in terms of protein. Protein based markets are worth USD 38 billion (2019) and is expected to grow at a rate of 9.1% from 2020 to 2027. Increasing traction towards plant-based protein (either as protein isolate or protein concentrates) is a greater opportunity for paradigm shift in nutritional breeding. Utilization of indigenous crops for protein source has been the current focus in Indian protein market. “Smart Protein” is a budding concept, pulses including pigeonpea is a part of this initiative. Harnessing the protein content of indigenous crops to be used as alternative protein

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source without burdening the environment is the aim. With nonmeat, vegan, dairyfree, vegetarian, and ethical food systems in rise “smart protein” will be the future. Next nutritive trait is Fe and Zn. The recommended daily allowance (R.D.A.) of Fe for a child and an adult in India is 13 and 17 mg per-day, respectively. Whereas the R.D.A. of per-day Zn for a child and an adult is 7 and 12 mg. Nevertheless, a food proportion of 7 g a day per person in India, imparts a daily per capita iron intake of 14.93 mg, which is much lesser than R.D.A. With this backdrop, a baseline study of genetic variability was taken for Fe and Zn content in pigeonpea at ICRISAT. Accordingly, a range of 24.91–44.65 mg/kg seed for Fe content and 26.08–47.80 mg/kg seed for Zn content was noted. Both wet methods, as well as Energy-dispersive X-ray fluorescence technique, were used to calibrate and estimate whole seed Fe and Zn content. A breeding programme is halfway in fortifying for Zn and Fe in pigeonpea. Marker-assisted backcrossing is effectively carried out for forwarding the generation. Recent development of early and photo-insensitive pigeonpea lines coupled with rapid-generation turnover methods has helped in fast-forwarding the generation. Interestingly, early genotypes are high in nutritional traits and is a win-win situation for introgression and generation advancement. Unlike the 1990s, three cropping seasons with year-round breeding can now be done. Conventional breeding coupled with genomic selections has increased the selection efficiency. Reduction in time taken for completion of a cropping season has increased the genetic gains in pigeonpea.

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Genetic Diversity with Regard to HR Traits

Molecular markers play a pivotal role in genetic improvement program of any crop. These are used both in the genetic diversity assessments as well as trait-specific molecular mapping. Various kinds of molecular markers have been adopted in pigeonpea also including first generation restriction fragment length polymorphism (RFLP), and subsequently, random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR), and latest single-nucleotide polymorphism (SNP) (Saxena et al. 2014; Pazhamala et al. 2015) markers. Amongst these, SNP markers stand for ideal DNA marker owing to their higher abundance throughout the genome and high throughput estimation procedure, apart from other advantages of a codominant marker. WGRS was given about 292 accessions to track the genetic diversity of pigeonpea. This included wild species, landraces, and breeding lines, yielding a total count of 17.2 million variations (Varshney et al. 2017). To discover how several candidate genes were related to agronomically significant variables, a GWAS was conducted. Sequence similarities exist between the genes functionally described in other plants for flowering time control, seed development, and pod dehiscence and the candidate genes for these features in pigeonpea. These polymorphic locations will help create high-density SNP arrays, genotyping of various mapping populations to create genetic maps, and identify the genomic areas underlying significant agronomic features. A total of 932 markers were used to create a condensed intraspecific pigeonpea linkage map, covering an overall adjusted map

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length of 1411.83 cM to enhance chromosomal anchoring and to map the genes linked to useful agricultural traits. It contains 65 SSR marker loci, 319 RAD-SNPs, and 547 bead-array SNPs (Arora et al. 2017). The genetic advancement of pigeonpea could be sped up with the help of this information. Recently, two high-density Affymetrix Axiom genotyping chips have been created in pigeonpea to accelerate the genetic gain. A 56 K Cajanus SNP chip has been created to study the genetic variation across 103 pigeonpea lines (Saxena et al. 2018).

7

Molecular Mapping of HR Genes and QTLs

High-throughput genotyping applications have caused drastic improvements in the density of markers which were used to generate genetic maps of pigeonpea. These have been adopted in pigeonpea, too, for the last two decades. Several genotyping programs targeting the F2 populations have resulted in high-density genomic maps to date (Arora et al. 2017; Saxena et al. 2017; Yadav et al. 2019). Such genetic resources were crucial to dissect the genomic design of agronomic traits in pigeonpea, including its nutritional appearances. Fine mapping of QTLs responsible for nutritive properties of pigeonpea is essentially required to generate superior cultivars/genotypes with potential well-being properties (Fig. 4).

Fig. 4 Overview of concurrent genomic technologies for designing biofortification of pigeonpea

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Marker-Assisted Breeding for HR Traits

In recent times, the availability of convenient library preparation methods and greater multiplexing capacity has facilitated the genotyping-by-sequencing (GBS) approach as a promising tool for the simultaneous discovery and characterization of numerous SNPs (Saxena et al. 2017). Whole-genome resequencing (WGRS) has become the latest high-throughput option for determining genetic variation and trait-linked marker discovery. Accordingly, an SNP array has been developed by resequencing diverse germplasm of pigeonpea with as many as 56,512 unique informative sequence variations (Saxena et al. 2018). Furthermore, identifying key agronomic traits associated with 1554 SNPs and 385 insertion/deletion (InDel) markers potentially enriched the genomic resource in pigeonpea toward markerassisted selection. The WGRS-based first-generation HapMap of pigeonpea unveiled 5.5 million genome-wide variants (4.6 million SNPs and 0.7 million InDels) (Kumar et al. 2016). Using a different whole-genome resequencing method, candidate gene sequence-based markers in relation to seed protein content were recognized, using four pigeonpea genotypes (Obala et al. 2019). The firstgeneration HapMap in Cajanus spp. was created using the whole-genome resequencing (WGRS) method to develop genetic resources. In a panel comprising of 20 Cajanus spp., including 2 wild and 18 cultivated species, there are 5,465,676 genome-wide variants, comprising 4,686,422 SNPs and 779,254 InDels. These sequence variations make mapping the genomic areas underlying fundamental features possible.

9

Map-Based Cloning of HR Genes/QTLs

Pigeonpeas have a protein level of about 21%. However, because they contain less lysine than other legumes, they have poor nutritional value. Dihydrodipicolinate Synthase, or DHDPS, is a crucial regulator of lysine biosynthesis. The DHDPS genes is inactivated by even trace amounts of lysine via a feedback mechanism, as a result pigeonpea exhibits low levels of lysine. Hence, the pigeonpea was transformed with the mutant DHDPS gene (dhdps-r1 from Nicotiana sylvestris), since it is no longer responsive to the feedback inhibition by lysine. DHDPS activity was two to six times higher in transgenic pigeonpea, resulting in an 8.5-fold increase in the amount of free lysine in the seeds (Thu et al. 2007). Additionally, pigeonpea has been utilized in the creation of edible vaccinations. With a transformation efficiency of roughly 67%, the Rinderpest virus’s haemagglutinin protein antigen was successfully produced in pigeonpea (Satyavathi et al. 2003). An Indian isolate of the Peste des Petits Ruminants (PPR) virus’s hemagglutinin-neuraminidase gene (HN) has also been successfully converted and expressed in transgenic pigeonpea. Neuraminidase activity showed that HN protein was physiologically active in transgenic pigeonpea (Prasad et al. 2004).

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Genomics-Aided Breeding for HR Traits

Conventionally identified QTLs controlling key agronomic traits in pigeonpea available so far (Bohra et al. 2019; Varshney et al. 2013) are inconvenient due to time challenges, cost, and labor faced by those low-throughput marker systems. The pitfalls of conventional marker systems can be overcome by employing high-density genome-wide marker systems. Genome-wide association study (GWAS) is one of the approaches that address the concern of low precision conventional QTL mapping. Instead, being independent of the biparental mapping population helps better understand the genomic background underlying complex phenotypic traits with higher resolution (Huang and Han 2014; Liu and Yan 2019). Accordingly, association mapping of diverse genotypes came out with the significant number of SSRs and SNPs throughout pigeonpea genome governing multiple traits of interest (Mir et al. 2014; Patil et al. 2017). The breakthrough GWAS of 286 resequenced pigeonpea accessions pinpointed numerous marker trait associations related to domestication and with prospects to breeding (Varshney et al. 2017). Nonetheless, more rigorous genotyping of potential accessions/cultivars and simultaneous highresolution marker-trait association studies would still be required for the efficient next-generation genomics-assisted breeding programs in pigeonpea.

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Transgenic Studies

Owing to properties such as rapid growth, lofty protein content, capacity to tolerate drought conditions, and a deep root system, pigeonpea is an economically essential crop. There is a huge breach created between the demand and supply of pigeonpea. This has been caused due to the explosion of population and the interplay of biotic and abiotic stresses affecting the growth of the crop. Biotic factors include certain insect pests, like Helicoverpa armigera; and some fungal diseases like Fusarium wilt. Abiotic stresses which lead to a drop in productivity include salinity and water logging. Other factor like extensive use of pesticides and herbicides which decreases soil fertility also effects the production of pigeonpea (Negi et al. 2021). Crop breeding has been the most traditional and well-established method of crop improvement. Plant breeding in pigeonpea is a laborious and time-consuming process. One of its main drawbacks is the restricted genetic diversity that results from gene loss during artificial selection. In order to resolve the issues and increase the pigeonpea production, several biotechnological approaches have been used. One of the most triumphant biotechnological approaches has been transgenic technology which removes the major breeding barriers. The development of transgenic technology has demonstrated remarkable success in pulse crop protection. It has also long-term supported research on the inclusion of agronomically advantageous traits, which improves crops and increases the world’s population’s access to high nutritious food (Saxena et al. 2016). The effective integration of many foreign genes using recombinant DNA technology has opened up new possibilities for the creation of tolerant pigeonpea cultivars with built-in resilience to survive biotic stress factors (Ghosh et al. 2014a).

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The availability of several transformation techniques has facilitated the production of effective transgenic crops in many crop species. Of them, Agrobacterium tumefaciensmediated genetic transformation is the most practical and widely applied method on a variety of plants. Researchers employed genetic transformation technology to improve more than 15 cultivars of the pigeonpea by enhancing nutritional quality or by including resilience against various environmental factors. Transgenic pigeonpea has been developed by incorporating a variety of genes, including cowpea protease inhibitor (CPI), Bacillus thuringiensis endotoxins cry1A(b), cry1Ab, cry1Aabc, cry1AcF, cry1Ac, cry2Aa, and cry1 E-C, etc. This has elevated the toxicity against the lepidopteran insects (Nandini et al. 2022). The antibiotic selection based in vitro tissue culture approaches showed numerous drawbacks despite extensive use, such as after successful transformation, small percentage of totipotent cells were able to survive, the selection pressure lowering the explants’ overall capacity for regeneration, and inadequate rooting responses (Ghosh et al. 2014b). In 2008, Ramu et al. first introduced in planta transformation method which fully skipped the in vitro co-cultivation and selection process and produce a large number of transgenics. Ghosh et al. (2017) developed a unique shoot grafting technique to develop Cry1Ac and Cry2Aa transgenic pigeonpea lines with steady DNA integration up to the T2 generation. Furthermore tissue culture independent technique was introduced by Ganguly et al. (2018) as plumular meristem transformation method with increasing transformation frequency and PCR based screening process.

11.1

Transgenic Pigeonpea Development for Biofortification

Various agronomically important genes has been discovered in well-characterized systems like Arabidopsis, tobacco, rice, pea, carrot, and other plants, and scientists were working to create transgenic pigeonpea plants that were resistant to biotic, abiotic stresses, and with good agronomic traits. (Banu et al. 2014). The ability to fix nitrogen in the roots is one of the most significant crop-specific characteristics of pigeonpea. This attribute improves and increases soil fertility. However, due to its high fixation in soil and low mobility, availability of phosphorous is constrained. As an adaptive strategy, plants vary the number of lateral roots, develop excessively root hair, and exude organic acids, particularly citrate to alter the rhizosphere (Shen et al. 2005). In order to refine and upgrade P uptake, Transgenic pigeonpea was created by overexpressing Daucus carota citrate synthase (DcCs) gene from carrot (Daucus carota), under a constitutive and root specific promoter. In both P deficient and P available situations, transgenic pigeonpea lines overexpressing the DcCs gene demonstrated higher level citrate synthase production and enhanced root growth (Hussain et al. 2016). Pigeonpea serves as an important source of protein, often high lysine content and complements the protein in cereals. Although during agricultural processing, lysine and tryptophan are lost in large amounts (Singh and Eggum 1984). Additionally, Dihydrodipicolinate synthase (DHDPS), the main enzyme of lysine biosynthesis pathway is also feedback-inhibited by lysine. Under the control of a phaseolin seed-

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specific promoter, a mutant dhdps-r1 gene from Nicotiana sylvestris that expresses a lysine insensitive enzyme was inserted into the pigeonpea genome by Thu et al. (2007) through particle bombardment and Agrobacterium mediated transformation. They examined 11 lines which showed two- to sixfold increase in DHDPS activity compared to wild type in immature seeds at a late stage of development. In comparison to control lines, the dhdps-r1 overexpression increased the free lysine concentration in pigeonpea seeds by 1.6–8.5 times. Proline is an important amino acid in plants functions as an osmoprotectant and is crucial for maintaining osmotic balance, safeguarding enzymes and subcellular structures, and raising cellular osmolarity, which provides the turgor required for cell expansion under stressful circumstances. The rate-limiting enzyme in the production of proline, 1-pyrroline-5-carboxylate synthetase (P5CS), is also inhibited by proline through feedback inhibition. Surekha et al. (2014) inserted a mutated version of P5CS named P5CSF129A from Vigna aconitifolia into pigeonpea genome. This mutated P5CSF129A gene is indifferent of feedback control. T0 transgenic generation showed higher proline accumulation than control plants. A significant improvement was seen in chlorophyll content and growth performance in T1 lines alongside decreased levels of lipid peroxidation. The relative water content under high salinity also showed improvement. Render pest virus (RPVH) and peste des petits ruminants’ virus (PPRV-HN) both are the causal agents of devastating diseases in cattle animals with very high mortality rate such as cattle plague and Peste des Petits Ruminants respectively. New vaccination methods were developed using pigeonpea transformation to strengthen the immune systems of sheep, goats, and bovids against those viruses as the existing live attenuated vaccines are heat labile. Satyavathi et al. (2003) developed pigeonpea line that express Rinderpest virus’s hemagglutinin protein. T1 Pigeonpea leaves had the highest expression of the hemagglutinin protein at 0.49% of the total soluble protein. The transgene was expressed in the offspring of the fertile transgenic plants. Prasad et al. (2004) successfully generated transgenic pigeonpea lines by inserting two PPRV surface glycoproteins, hemagglutinin-neuraminidase, and fusion protein using pBI121 binary vector. T1 plants showed transgene’s inheritance. Extracellular enzymes, especially those that cause the proteolytic breakdown of proteins in host plants are secreted by many phytopathogenic bacteria and some insects and crucial for pathogenesis. Plants have many inhibitors that work against these proteolytic enzymes as a key line of defense against these diseases. One such inhibitor named cowpea protease inhibitor (CPI), isolated from cowpea was inserted into pigeonpea genome through Agrobacterium mediated transformation. Transgenic pigeonpea lines showed higher level of defense against the lepidopteran insects (Lawrence and Koundal 2001).

11.2

Biofortification Resources of Pigeonpea Used in Other Transgenic Crops

In pigeonpea, under biotic and abiotic stress conditions, complex signaling pathways were found to be activated, causing changes in gene expression, necessary for plants

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to adapt and acclimate. One such gene named Pigeonpea hybrid-proline-rich protein encoding gene (CcHyPRP) was used to develop transgenic tolerance lines in rice by Mellacheruvu et al. (2016). CcHyPRP was cloned under an inducible rd29A promoter and a constitutive CaMV35S promoter. Four independent homozygous T4 lines for each rd29ACcHyPRP and CaMV35SCcHyPRP were developed, which revealed very high accumulation of proline and endochitinase. In comparison to the control lines, the CcHyPRP transgenics showed greater resistance to rice blast disease causing fungus Magnaporthe grisea. Transgenic rice was shown to have more bZIP and endochitinase transcripts and endochitinase activity than control plants. These T4 lines also demonstrated excellent levels of tolerance to the main abiotic stimuli, including heat, salinity, and drought, as demonstrated by enhanced chlorophyll content, survival rate, biomass, root, and shoot growth, in comparison to the untransformed lines. Additionally, under various biotic and abiotic stress situations, transgenic rice lines had larger panicles and more grains in comparison. In comparison to the control, the CcHyPRP transgenics showed increased catalase and superoxide dismutase (SOD) enzyme activity as well as decreased malondialdehyde (MDA) levels.

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Future Prospects

In the post-green revolution period, improving the nutritional value of pigeonpea has become crucial for reducing malnutrition issues in developing nations. Establishing desired genotypes will be aided by in-depth knowledge of the genes and QTLs related to nutritional quality and seed quality (Singh et al. 2020). In order to develop molecular techniques aiming at enhancing seed quality and other nutritionally related qualities in pigeonpea, it will be essential to identify the genes/QTLs controlling the quality traits. To define quality features, attention should be paid to locate genetically varied and nutritionally improved pigeonpea lines (Singh et al. 2020). In order to measure various phenotypic features, it is crucial to design a highthroughput phenotyping platform. Examples of techniques that will be impactful for high throughput phenotyping include picture-based computer vision phenotyping, image processing, and data extraction tools. All integrated approaches will improve the understanding of systems biology by providing information on gene function, genomic architecture, organization, biological pathways, and metabolic and regulatory networks (Fig. 4). The world’s problems with malnutrition can be addressed in a new way by utilizing and combining cutting-edge NGS “omics” technology to sequence vast populations, uncover the genetic basis of agronomically essential traits, and anticipate breeding value. Breeders will be aided to gather information on specific alleles of known genes involved in nutritional grain quality attributes to achieve this goal through the availability of gene-based markers and cutting-edge techniques. Genomic regions/genes can be found that are expected to influence seed quality and nutritional qualities of interest by genotyping and phenotyping for those traits utilizing associations and machine learning models, drawing on the collection and

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use of numerous unrelated lines. When omics technologies are used in conjunction with breeding programmes, it is anticipated that the nutritional quality of pigeonpea will improve.

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Nutrigenomics of Mungbean B. Manu, Jayashree Ugalat, P. R. Saabale, Revanappa Biradar, Suma C. Mogali, and Shivanand Koti

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Nutritional Profile of Mungbean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Approaches of Biofortification Through Omics Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Nutritional Genomics and Epigenomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Important Traits and Breeding Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Genome Size and Genomic Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Molecular Mapping and Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Metabolomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Nutritional Transcriptomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 EcoTILLING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 System Biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Genetic Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Genetic Engineering of Relevant Biosynthetic Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Ionomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Conclusion and Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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B. Manu (*) · P. R. Saabale · R. Biradar ICAR-Indian Institute of Pulses Research, Regional Station, Dharwad, Karnataka, India e-mail: [email protected] J. Ugalat Department of Biotechnology and Crop Improvement College of Horticulture, UHSB Campus, Bangalore, India S. C. Mogali AICRP-MULLaRP Scheme, University of Agricultural Sciences, Dharwad, Karnataka, India S. Koti Department of Fruit Science College of Horticulture, UHSB Campus, Bangalore, India © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_29

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Abstract

Mungbean (Vigna radiata (L.) Wilczek), one of the important leguminous crops, contains balanced nutrients protein, dietary fiber, minerals, vitamins, and good amounts of bioactive compounds such as phenolic acids, flavonoids, and tannins. The discipline of nutriomics or nutrigenomics explains the reciprocal interaction of nutrients and genes at the molecular level. Nutrigenomics can be helpful for better perceptiveness of nutrient-gene interactions and the development of “personalized nutrition” for good health and disease prevention. Considering the worldwide importance of mungbean, there is a scope for improving its nutritional value. Crop improvement focuses on enhancing protein and starch content and quality, the content of minerals like iron, zinc, and also in removing the antinutritional compounds like phytic acid. The mungbean whole-genome sequence data helps in the advancement of genomics research in Vigna species and speed up the mungbean breeding programs. Genotyping has enabled marker-assisted selection (MAS) and identified SNPs, serve as important resources to facilitate MAS for nutritional improvement. 8Sα globulin or vicilin is the major storage protein of mungbean and was engineered using site-directed mutagenesis. Transcriptomic, metabolomic, and ionomics analyses reveal the molecular mechanisms of nutrient accumulation, nutritional/nutraceutical value and health-promoting properties, and bioavailable minerals. Keywords

Nutrition · Nutrigenomics · Transcriptomics · Metabolomics · Ionomics · Disease · Health

1

Introduction

Mungbean (Vigna radiata (L.) Wilczek) is a low-input, short-season, important grain legume of tropical countries and is also known as greengram and moong. This crop is grown in various climatic conditions, locations, and seasons due to its inherent intrinsic tolerance mechanisms. It is grown over seven million hectares in South and Southeast Asia, Australia, Africa, and South America. It is cultivated as an intercrop or subsistence monocrop predominantly by small and marginal farmers; it is consumed as whole seed or split cooking, flour, or as sprouts; and it is a cheap source of vegetable protein, minerals, vitamins, and dietary fiber for the vegetarian population. The crop has valuable nutritional and health benefits, where malnutrition is a key concern. It has the ability to improve the soil health by fixing atmospheric nitrogen through a symbiotic association with Rhizobium, thus enhancing the yield of the subsequent crops. Other major benefits of this crop to farmers are its high nutritional and monetary value, as it fits into intensive wheat, rice, and summer cereal rotation systems, short duration, photo-thermo insensitivity, low input requirement, and heat and drought stress tolerance. Development of extra-early and yellow mosaic-resistant varieties paved the way for extensive cultivation

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of the crop in several parts of India into different cropping systems (rice-fallow, rice-rice, rice-wheat, and rice-maize) and for cultivation in different parts of the world including South America and sub-Saharan African regions (Moghadam et al. 2011). The yield potential of mungbean is 2.5–3.0 t/ha; however, the global productivity of mungbean is only 0.5 tons per hectare, impacted due to traditional low input farming system, nonavailability of quality seeds of improved varieties to farmers, and biotic and abiotic stress factors. The major biotic factors include insect pests, diseases, and weeds (Pandey et al. 2018; Nair et al. 2019). Insect pests cause direct damage by feeding the crop and indirect damage by transmitting viral diseases. Abiotic stresses, waterlogging, salinity, heat, and drought stress are key concerns in mungbean production (Hanumantha Rao et al. 2016). During the eighteenth century, the “analytical chemistry era” Lavoisier discovered how carbon dioxide, water, and energy were generated after food digestion in the body (Vasconcelo 2010). In the “biological era” around the nineteenth century, where important discoveries in metabolism and chemistry were done, helping the science of nutrition to prevent metabolic disorders (Cruz et al. 2003). Dietary components/nutritional attributes are environmental factors that can interact with the genome which determines the health condition of individuals (Ronteltap et al. 2008). With the advancement of science, the discipline of nutriomics or nutrigenomics was introduced to get insights regarding how could food bioactive molecules and genes influence the health of an individual positively and negatively (C. Kole and AG Abbott 2011 for ICPN at PAG 2011; Dauncey 2014; Cozzolino and Cominetti 2013). Nutrigenomics is an area of nutrition that corresponds to the use of physiology, biochemistry, genomics, metabolomics, proteomics, transcriptomics, nutrition, and epigenomics to explain the reciprocal interaction of nutrients and genes at the molecular level (Dauncey 2014; Cozzolino and Cominetti 2013). The study of nutrigenomics has progressed considerably in recent times, nutrigenomics aims at understanding the impact of nutritional factors in protecting the genome. Studies on folate metabolism proved that folic acid is a nutrient, ensures the genetic integrity of an individual, and acts as a cofactor for the biosynthesis of nucleotides and thymidylate (Liu and Qian 2011; Cozzolino and Cominetti 2013). Bioactive molecules contained in the diet act as cofactors/substrates in DNA metabolism and repair. Studies showed that vitamins A, D, and fatty acids activate nuclear receptors by direct action and induce gene transcription, and some of the bioactive compounds influence molecular signaling pathways (Fialho et al. 2008; Cozzolino and Cominetti 2013).

2

Nutritional Profile of Mungbean

Mungbean (Vigna radiata L.), an important pulse crop consumed across the world, especially in Asian continents, has a long history of usage in traditional medicine. Mungbean is consumed as a food for centuries. Mungbean contains balanced nutrients, importantly protein, minerals, dietary fiber, vitamins, and enough amounts of bioactive compounds (Gan et al. 2017). For those individuals who are vegan or cannot

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afford animal proteins, the mungbean is a relatively low-cost and has a good amount of protein. Furthermore, this protein is easily digestible in comparison protein of other legumes (Mubarak 2005; Yi-Shen et al. 2018), that is the how, it is becoming as a popular functional food in promoting good health (Tables 1, 2, and 3). The mungbean is a rich source of polyphenolics. The important phenolic contents in the mungbean are phenolic acids, tannins, and flavonoids (Lee et al. 2011; Shi et al. 2016; Singh et al. 2017a). The seed coats and cotyledons of mungbeans contain phenolics; however, most are present in the coats of seed. The most abundant secondary metabolite in the mungbean is flavonoids. The five subclasses of Table 1 Macronutrient composition of mungbean (Dahiya et al. 2015a) Macronutrient Moisture (g/100 g) Crude protein content (g/100 g dm) Crude fat (g/100 g dm) Crude fiber (g/100 gdm) Ash (g/100 gdm) Total carbohydrate (g/100 g dm) Energy yield (kcal/100 g dm) a

Averagea 9.80 23.8 1.22 4.57 3.51 61.0 344

Minimum 4.10 14.6 0.71 3.8 0.17 53.3 338

Maximum 15.20 32.6 1.85 6.15 5.87 67.1 347

Average of the values quoted by several authors

Table 2 Content of amino acids in mungbean protein isolates (Yi-Shen et al. 2018)

Amino acids Total amino acids content Total essential amino acids content Total aromatic amino acids content Total sulfur containing amino acids Phenylalanine+tyrosine Leucine Lysine Valine Isoleucine Histidine Threonine Methionine+cysteine Tryptophan Glutamic acid/glutamine Aspartic acid/asparagine Arginine Serine Alanine Glycine Proline

MBPI (mgg
1) 800.2 348.2 (43.51%)a 96.7 (12.08%)a 13.0 (1.63%)a 90.3 74 62.4 46.3 39.1 27.9 28.4 13 6.4 125.4 85.3 64.4 38.5 36.6 32.2 30

MBPI mungbean protein isolates Percent amino acids relative to total amino acids in MBPI

a

Nutrigenomics of Mungbean Table 3 Mungbean mineral nutrients content (Habibullah et al. 2007)

779 Mineral Na K Ca Mg P Fe Zn Cu Mn Pb

Content (mg/100 g) 22 mg/100 g 1443 mg/100 g 216 mg/100 g 204 mg/100 g 374 mg/100 g 11.34 mg/100 g 1.88 mg/100 g 1.92 mg/100 g 1.49 mg/100 g 2.64 mg/100 g

flavonoids in the mungbean are, i.e., flavonols, flavones, isoflavonoids, flavanols, and anthocyanins. Flavones (isovitexin, vitexin, isovitexin-600 -O-α-l-glucoside, and luteolin) and flavonols (myricetin, quercetin, and kaempferol) are the most occurring flavonoids found in the mungbean. Isovitexin and vitexin were considered to be the two major flavonoids in the seed of mungbean; their contents in the seed coat are attributed to 95.6% and 96.8% of the total vitexin and isovitexin, correspondingly (Cao et al. 2011; Peng et al. 2008). Quantification by chemical analysis indicated that the contents of isovitexin and vitexin in the seed coat were high, 37.43 mg/g and 47.18 mg/g, correspondingly. Legumes constitute the most abundant and least expensive protein source for human and animal diets; however, their utilization is limited largely because of the anti-nutritional/anti-physiological compounds (Liener 1994) present in these. Those are protease inhibitors (trypsin), amylase inhibitors, lectins, polyphenols, tannins (TN), phytic acid (PA), flatulence factors, and allergens (Liener and Kakade 1980; Liener 1995). These factors downgrade the nutritive value of beans through direct and indirect reactions, inhibit protein and carbohydrate digestibility, induce pathological conditions in the intestine and liver tissue, and finally affect metabolism, inhibit enzymes, and bind to nutrients, making them unavailable (Bressani et al. 1989; Bressani 1993). Anti-nutritional factors: trypsin inhibitor (TIUA; trypsin inhibitor units /mg protein) is 15.8, hemagglutinin activity (HUB; hemagglutinin units/g) is 2670, tannins (mg/g) 3.30, and phytic acid (mg/gm) is 5.80.

3

Approaches of Biofortification Through Omics Methods

3.1

Nutritional Genomics and Epigenomics

Nutrigenomics is the study of the gene-nutrient interaction, and it shows that some nutrients, called bioactive compounds, can shape the genetic expression or change the nucleotide sequence. To analyze the interaction between genes and nutrients, the term “nutrigenomics” was proposed. Hence, nutrigenomics makes use of biochemistry, physiology, nutrition, genomics, proteomics, metabolomics, transcriptomics,

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and epigenomics to get and explain the interactions between genes and nutrients at a chemical level. Nutrigenomics can be helpful for better perceptiveness of nutrient-gene connections and the development of “personalized nutrition” for good health and disease prevention (Di Renzo et al. 2019).

3.2

Important Traits and Breeding Goals

Mungbean is having a considerably good amount of protein, carbohydrates, and minerals such as zinc and Iron. Considering its worldwide importance, the crop is having a scope for improving its nutritional value with the available germplasm (Singh 2013). Studies must be conducted to understand the diversity at the level of nutrients in the mungbean germplasms. The increasing need for plant-based protein foods is a scope to study the functional properties of mungbean protein and starch (Shrestha et al. 2022). The mungbean breeding program should expand research to nutritional and food processing properties. Studies have to be conducted on several factors including the variety used, the region where the crop is grown, agronomic practices that have been adopted, and the storage environment. Further, studies have to be undertaken on the postharvest processes such as sprouting, dehulling, soaking, boiling, autoclaving, and microwave cooking to analyze their effect on the composition of nutritional and anti-nutritional contents of mungbean. Crop improvement in mungbean should further focus on enhancing protein and starch content and quality, the content of minerals like iron and zinc, and also in removing the anti-nutritional compounds like phytic acid (Samtiya et al. 2020). Micronutrients such as iron and zinc should be biofortified, for which identification of suitable parents, improvement of populations, and identification of quantitative trait loci (QTLs) for marker-assisted selection (MAS) are essential.

3.3

Genome Size and Genomic Resources

Mungbean is a member of the subgenus Ceratotropis of the genus Vigna, which also includes several agriculturally significant legumes, including rice bean, black gram, adzuki bean, and moth bean. While the majority of Vigna species are diploid (Egawa and Tomooka 1994), Vigna reflexo-pilosa (2n ¼ 4x ¼ 44) is a tetraploid species. The genomic sizes of the Vigna species range from 416 to 1394 Mb (Parida et al. 1990; Lakhanpaul and Babu 1991). A consortium of 12 universities, led by Suk-Ha-Lee of Seoul National University in Korea, completed the draft genome sequencing of the cultivated mungbean (V. radiata var. radiata VC1973A), using two next-generation sequencing platforms HiSeq2000 and GS FLX+ were employed to sequence and assemble the information into 11 pseudo chromosomes. For a thorough understanding of genus Vigna’s polyploidization, speciation, and domestication processes, whole-genome sequences of a wild relative mungbean (V. radiata var. sublobata) and a tetraploid relative of mungbean (V. reflexo-pilosa var. glabra), similarly transcriptome sequences of 22 Vigna accessions of 18 species were deciphered. The scientists also constructed a genetic map based on F6 population of 190 recombinant inbred lines (RIL) using genotyping by sequencing

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Table 4 List of genomics databases/resources S. No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Name of database Next Gen Seek Kevin’s GATTACA World In Between Lines of Code Next-Gen Sequencing CoreGenomics RNA-Seq Blog Next Generation Technologist Blog @ Illumina Bits of DNA Journal of Next Generation Sequencing& Applications Omics! Omics! PlantGDB LIS – Legume Information System Phytozome 10.2 Legume Information System Mungbean Genome Jbrowse Adzuki bean Genome Jbrowse PlantGDB Lotus japonicus genome assembly build 2.5 PlantGDB Phytozome 10.2

Source link/URL http://nextgenseek.com http://kevin-gattaca.blogspot.com http://flxlexblog.wordpress.com http://nextgenseq.blogspot.com http://core-genomics.blogspot.com http://www.rna-seqblog.com http://www.yuzuki.org http://blog.illumina.com http://liorpachter.wordpress.com/seq http://www.omicsonline.org/ nextgenerationsequencing-applications.php http://omicsomics.blogspot.com www.plantgdb.org/MtGDB/ http://legumeinfo.org/gbrowsecajca1.0 http://phytozome.jgi.doe.gov/commonbean http://cicar.comparative-legumes.org/ http://plantgenomics.snu.ac.kr/ http://plantgenomics.snu.ac.kr/ http://www.kazusa.or.jp/lotus/ www.plantgdb.org/MtGDB/ http://phytozome.jgi.doe.gov/soybean

(GBS) strategy. The work of Kang et al. (2014) provided a deeper understanding of the evolutionary history of Vigna spp. (particularly subgenus Ceratotropis) based on comparative genomics strategy, with the 421 Mb (80%) assembled genome coupled with sequence information of related Vigna species. Vigna species may be utilized as model legume plants in genetic studies to shed light on crop domestication and species divergence due to their short life cycle and small genome size. The mungbean wholegenome sequence data will help in the advancement of genomics research in Vigna species and speed up mungbean breeding programs, which could serve as a model for future efforts to resequence the Vigna germplasm. Scientists have also developed webserver/repositories (Table 4) containing the genomics and related information of selected Vigna species, like Vigna Genome Server (Vig GS) which incorporates annotated exon-intron structures, along with evidence for transcripts and proteins, visualized in GBrowse (Sakai et al. 2016).

3.4

Molecular Mapping and Breeding

DNA-based marker systems have become available over the past three decades. These include restriction fragment length polymorphisms (RFLPs), SSRs or microsatellites,

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random amplified polymorphic DNA (RAPD), amplified fragment length polymorphisms (AFLPs), single nucleotide polymorphisms (SNPs), and diversity array technology (DArT). Among these markers, RAPD, AFLP, and RFLP are frequently utilized for marker-trait association and analysis of pulse diversity. However, plant breeders do not prefer their use for MAS because of the difficulty in handling, low reproducibility, and use of radioactive elements for generating these markers (Gupta et al. 2010). Only PCR (polymerase chain reaction)-based SSR and SNP are preferred by breeders, as these markers can easily be employed in genotyping of large populations. Also, more reproducibility and ease in usage make them preferential to conventional plant breeders for MAS (Gupta et al. 2010). These have been extensively utilized (Kumar et al. 2011) in many crops; however, their use is still inadequate in pulses (Varshney et al. 2009; Saxena et al. 2010). Therefore, greater focus is being put to develop more markers for pulses, which are considered orphan legumes (Hamwieh et al. 2009; Varshney et al. 2009). Close phylogenetic similarity has spurred researchers to transfer SSR markers from one pulse crop to another to lower the cost of developing these markers (Datta et al. 2010; Reddy et al. 2010.) Different types of markers such as RFLPs, RAPDs, AFLPs, SSRs, and ISSRs have been used in discerning genetic diversity and developing linkage maps in these crops. In mungbean, eight genetic linkage maps have been developed so far but no map contained enough markers to resolve all the 11 linkage groups. Scientists are also working on genome-wide identification of SNP and association mapping of seed mineral concentration in mungbean (Vigna radiata L.). To assess the diversity of mungbeans available to breeders in the United States and to execute a genome-wide association study (GWAS), Wu et al. (2020) used genotyping by sequencing (GBS) tool. This study identified high-quality single nucleotide polymorphisms (SNPs) a total of 6486 from the GBS dataset and found marker x trait associations (MTAs) with calcium, iron, manganese, potassium phosphorous, zinc, or sulfur contents in mungbean grain. The 43 MTAs spread across 35 genomic regions elucidating an average of 22% of the variation for each seed nutrient. SNPs identified will serve as important resources of marker-assisted selection (MAS) for nutritional value in the mungbean.

4

Metabolomics

Plants produce wide numbers of nutrients that impart synergistic relations among the different combinations of nutrients. Therefore, inclusive nutrient profiling is required to evaluate the nutritional/nutraceutical value and health-promoting properties of crops. To acquire such datasets of mungbean, which is well known as a medicinal crop with heat-alleviating character, metabolites profiling is essential. Metabolomic and proteomic analysis of four genotypes from China, Thailand, and Myanmar has indicated a total of 449 proteins and 210 metabolic compounds in the seed coat. The first complete dataset of mungbean for nutraceutical values has indicated 480 proteins, and 217 metabolic factors in seed flesh. Whereas, gel-free/label-free proteomic analysis and metabolomic analysis in combination and pathway reconstruction

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detected that amino acid metabolism is more predominant in flesh. Compared to flesh coat contains a wider variety of lipids and phenolic acids/flavonoids. Among the compounds detected in the coat, sphingolipids, arachidonic acid, and prostaglandin E2 are related to defense response induction. Furthermore, the identification of prostaglandin F2α added support to the empirical validity of the usage of mungbean. The abundance of bioactive compounds such as naringenin, which can be metabolized into vitexin, varied among genotypes. Lipids together with flavonoids may be possibly responsible compounds for the biological activity of mungbean coat and flesh (Hashiguchi et al. 2017).

5

Nutritional Transcriptomics

The recent availability of genome sequence information of several legume crops has led to boosting genomics research. Study of the transcriptome at a global level can provide insights into the gene space, gene function, transcriptional programs, and molecular basis of various cellular events, even in the absence of genome sequence (Garg and Jain 2013). Transcriptome analysis has been shown as an indispensable step for basic and applied research in any living system. High-quality sequence reads of cDNA obtained using sequencing technology, Illumina paired-end sequences, were assembled into unigenes (48,693) with a length of 874 bp, on an average. Among these unigenes, 25,820 (53.0%) and 23,235 (47.7%) indicated significant similarity to nonredundant protein and nucleotide sequence databases in the NCBI, respectively. A set of unigenes, 19,242 (39.5%), were classified into gene ontology categories, whereas 18,316 (37.6%) were classified into Swiss-Prot categories and 10,918 (22.4%) into KOG database categories (E-value 71 g/day) by a group of Finnish women resulted in 43% reduction in coronary mortality compared to those who have not consumed apples. On the other hand, the reduction of risk of coronary mortality is 19% in a group of men consuming apples (>54 g/day) compared to those who have not consumed apples (reviewed by Hyson 2011). Furthermore, it has been demonstrated that there is an association of quercetin and apple consumption with

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cerebrovascular disease (Boyer and Liu 2004). In other studies, it has been demonstrated that catechin and epicatechin, both readily bioavailable in apples, are highly inversely associated with death from coronary heart disease (Boyer and Liu 2004). In recent studies, there has been an increased interest in identifying biomarkers associated with cardiovascular risk, particularly focusing on oxidation and lipid metabolism (Hyson 2011). It is known that overexposure to oxidants in the body can contribute to cellular damage, and such oxidative damage may likely disrupt DNA, protein, lipids, and other cellular components via ROS, thus serving to initiate several chronic diseases, such as cardiovascular disease (Hyson 2011). It is reported that dietary antioxidants contribute to the endogenous potential of the body to scavenge ROS and nitrogen-free radicals, thereby directly counteracting lipid peroxidation reactions (Hyson 2011). There are reports demonstrating that apple consumption increases total antioxidant activity in plasma by 64% within a few hours (3 and 6 h) following consumption compared to control (water) treatment (Maffei et al. 2007). Furthermore, it is reported that apple lowers ROS generated by exposure to hydrogen peroxide in lymphocytes isolated from participants in the study. In fact, it is observed that apple significantly protects against DNA damage (highest at 3 h, but this gradually drops by 24 h) in cultured lymphocytes isolated from participants following apple consumption (Maffei et al. 2007). There are several other reports, using animal feeding experiments and in vitro studies, that further demonstrate the role of phenolic compounds in apple and apple products in eliciting antioxidant activities, by inhibiting ROS-induced production of radicals, as well as in modulating lipids and lipid-related processes (Hyson 2011).

5.3

The Influence of Apple Nutraceutical Components on Asthma and Pulmonary Function

Exposure to high and steady levels of oxygen contributes to oxidative damage in lung tissues (Devereux and Seaton 2005). Such oxidant stress activates mediators of pulmonary inflammation that induce asthma (Devereux and Seaton 2005). In particular, oxidative stress can result in various deleterious effects on airway function, such as airway smooth muscle contraction, induction of bronchial hyper-responsiveness (BHR), mucus hypersecretion, epithelial shedding, and vascular exudation (Bowler 2004). Moreover, ROS can activate the transcription factor NF-κB, thus resulting in a cascade of events involving upregulation of transcription of several inflammatory cytokine genes, such as interleukin-6 (IL-6) and leading to influx and degranulation of airway neutrophils (Wood and Gibson 2009). There are a number of studies conducted in different countries that have demonstrated that apple consumption is inversely linked to asthma and it is positively associated with overall pulmonary health (Boyer and Liu 2004; Romieu et al. 2006; Hyson 2011). This reduced incidence of asthma is mostly attributed to apple flavonoids (Romieu et al. 2006). In one study, it is reported that apple and pear intake is positively associated with pulmonary function and negatively associated with chronic obstructive pulmonary disease and that it is catechin that is involved in these observed responses (Hyson 2011).

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The Influence of Apple Nutraceuticals on Anti-inflammatory Responses

Oleanolic acid plays a potential role in treating drug-induced hepatic steatosis via its interaction with liver X receptor alpha and pregnane X receptor, thus reducing ligandinduced lipogenesis (Chen and Lim 2018). Furthermore, it is well known that different triterpene acids from various natural sources have anti-inflammatory effects. For instance, recent studies have reported that maslinic acid has a significant effect on inflammation, and this is partially due to its inactivation of NF-κB (Yap and Lim 2015; Fukumitsu et al. 2016). Furthermore, such anti-inflammatory and anti-arthritic effects of both maslinic and pomolic acids are also attributed to their inactivation of NF-κB (Yap and Lim 2015). Ancient Italian apple cultivars in the Friuli Venezia Giulia region are reported to be important sources of such compounds; thus, further investigations should be conducted to assess the potential of these compounds in having antiinflammatory and glycemic control effects (Sut et al. 2019).

5.5

The Role of Apple Nutraceuticals on Diabetes and Weight Loss

Based on a meta-analysis of various observational studies, it is reported that consumption of apple significantly decreases risk of type 2 diabetes mellitus and body mass index (BMI), in addition to reduced risk of cerebrovascular disease and cardiovascular death (Gayer et al. 2019). Recently, Bondonno et al. (2021) have reported that there is evidence of an inverse association between higher intake of apples and type 2 diabetes for apples, as well as for other fruits including bananas, orange, and other citrus fruits. It is proposed that the beneficial effects of apple consumption (and of other fruits) on glucose regulation and diabetes risk are attributed to multiple factors. These factors include the fruit’s low energy intake, low glycemic load, high fiber content, phytochemicals, vitamins, and minerals (Bazzano et al. 2003; Bondonno et al. 2021). Among the phytochemicals in apples, the high content of flavonoids is reported to enhance sensitivity to insulin, thereby decreasing apoptosis, promoting proliferation of pancreatic β cells, as well as reducing muscular inflammation and oxidative stress (Vinayagam and Xu 2015; Kawser Hossain et al. 2016). Furthermore, apple intake may indirectly influence type 2 diabetes risk by either preventing or managing excess adiposity, likely via their higher dietary fiber that contributes to satiety (Guyenet 2019).

5.6

Effects of Apple Nutraceuticals on Various Other Health Diseases

Apple polyphenolic compounds have been reported to inhibit in vitro human low-density lipoprotein (LDL) cholesterol oxidation (Thilakarathna et al. 2013), attenuate Alzheimer’s disease (Chan and Shea 2009), and protect against cigarette

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smoke-induced acute lung injury (Bao et al. 2013), among other health benefits (Francini and Sebastiani 2013). Koutsos et al. (2020) have reported that apple consumption lowers serum cholesterol and improves cardiometabolic biomarkers in mildly hypercholesterolemic adults. In a recent study, Ichwan et al. (2021) have found that flavonoids, such as quercetin, and 3,5-dihydroxybenzoic acid (not related to flavonoids) are pro-neurogenic, as they activate precursor cell proliferation and promote cell cycle exit, cellular survival, and neuronal differentiation in brains of test animals. Thereby, it is proposed that these compounds are likely involved in promoting adult hippocampal neurogenesis, in particular these compounds are likely involved in brain plasticity. As functional neurons are generated throughout life, these are integrated into existing circuitry; therefore, these compounds are involved in mediating some forms of learning and memory (Ichwan et al. 2021). However, it is important to keep in mind that bioavailability of apple polyphenolic compounds is a critical factor in their efficacy as disease preventive agents.

5.7

Genetic Diversity of Phytochemical Contents in Apples

Various studies have been undertaken to evaluate the phytochemical contents in different apple cultivars used for the fresh market, as well as for processing – juice, cider, and applesauce, among others (Boyer and Liu 2004; van der Sluis et al. 2001; Escarpa and Gonzalez 1998; Guyot et al. 2002, 2003; Wojdyło and Oszmiański 2020). Studies have reported on the observed variations in total phenolic and total flavonoid contents among different apple cultivars. For example, among ten apple cultivars commonly used for fresh eating, ‘Fuji’ had the highest total phenolic and total flavonoid contents, while ‘Empire’ had the lowest (Boyer and Liu 2004). Moreover, among four apple cultivars used for applesauce, namely, ‘Rome Beauty’, ‘Idared’, ‘Golden Delicious’, and ‘Cortland’, ‘Rome Beauty’ had the highest phenolic and flavonoid contents, while ‘Cortland’ had the lowest (Boyer and Liu 2004). On the other hand, ‘Idared’ had the highest levels of anthocyanins than any of the other cultivars (Boyer and Liu 2004). van der Sluis et al. (2001) reported that among four apple cultivars analyzed, namely, ‘Jonagold’, ‘Golden Delicious’, ‘Cox’s Orange’, and ‘Elstar’, ‘Jonagold’ had the highest contents of quercetin glycosides, catechins, and chlorogenic acid, followed by ‘Golden Delicious’. Escarpa and Gonzalez (1998) reported that among four cultivars analyzed, namely, ‘Red Delicious’, ‘Granny Smith’, ‘Golden Delicious’, and ‘Reinata’, ‘Golden Delicious’ had the lowest levels of various flavonoid compounds, while ‘Reinata’ had the highest level of flavonoids along with ‘Granny Smith’ and ‘Red Delicious’. In addition, Hammerstone et al. (2000) reported that ‘Red Delicious’ and ‘Granny Smith’ had the highest content of procyanidins, while ‘Golden Delicious’ and ‘McIntosh’ had the lowest. Stushnoff et al. (2003) assessed the total phenolic content and the antioxidant capacity of a core germplasm collection of the USDA Plant Genetic Resources at Geneva, NY, also maintained at Excelsior (MN), consisting of over 300 Malus species, selections, and cultivars. It was found that this collection has a wide

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variation for total phenolic content, ranging from 14 to 7181 mg l1, gallic acid equivalents. In particular, it was observed that the total phenolic content of the commercial cultivars clustered together generally in a narrow and low range, 15–210 mg l1, the central Asian species M. sieversii collection ranged from 100 to 731 mg l1, and the red-fruited taxa ranged from 151 to 5355 mg l1. Moreover, 25 taxa representing 10 different Malus species and various other genetic backgrounds had the highest total phenolic contents, ranging between 1000 and 7181 mg l1. Using a large collection of 80 cultivated apples (M.
domestica) and 13 accessions of M. sieversii, Volz and McGhie (2011) determined levels of flavan-3-ols (catechin + epicatechin); oligomeric procyanidins; flavonols (quercetin 3-rutinoside, quercetin 3-galactoside, quercetin 3-glucoside, quercetin 3-xyloside, quercetin 3-arabinofuranoside, quercetin 3-arabinopyranoside, and quercetin 3-rhamnoside); chlorogenic acid; dihydrochalcones (phloridzin + phloridzin-2-xyloside); anthocyanin [cyanidin 3-O-galactoside (Cy3 gal)]; and total polyphenols in peel and flesh fruit tissues of these 93 apple genotypes for at least 1 year (between 2003 and 2005), grown at a single site in New Zealand. It was reported that genotypic differences for these phenolic compounds accounted for 46–97% of the total variation observed in levels of total polyphenols and for each of the individual phenol groups in both flesh and peel tissues in this germplasm pool. Moreover, it was observed that there were minimal effects for “year” and for “genotype
year” for all phenolic compounds, except for peel flavonols in the cultivated apple, M.
domestica, and for flesh flavonols in both M.
domestica and M. sieversii, wherein genotypic differences for flavonols accounted for less than 30% of the total variation, which was less than that observed for “genotype
year” interactions. Moreover, levels of total polyphenolic compounds among genotypes ranged between seven- and nine-fold in the flesh and four- and three-fold in peel of M. sieversii and M.
domestica, respectively. In addition, levels of individual polyphenol groups in flesh and peel tissues within each of M. sieversii and M.
domestica ranged between 2- and over a 500-fold. Overall, M. sieversii, all accessions originating from Kazakhstan, had higher levels of polyphenolic compounds than those in M.
domestica. Furthermore, it was found that among all M.
domestica cultivars and breeding selections originating in New Zealand (since 1990, except for two older cultivars) had lower mean total polyphenols and chlorogenic acid in both flesh and peel tissues than those cultivars originating from other countries, including the USA, UK, France, Germany, Spain, Czech Republic, Netherlands, and Canada.

5.8

Influence of Various Growth and Environmental Factors on Phytochemical Content in Apple

It is important to point out that profiles of phenolic compounds in apple cultivars are highly influenced not only by genetic control but also by growth season, growth period, and geographical location (Wojdyło and Oszmiański 2020). For instance, levels of hydroxycinnamic acids and catechins are high in early developing fruits,

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but these levels decrease during fruit growth (Mosel and Herrmann 1974). Similarly, accumulation of flavonoids including flavan-3-ols, dihydrochalcones, and flavonols occurs during early fruiting, and then this drops during fruit growth and maturation (Renard et al. 2007). Likewise, levels of quercetin glycosides, phloridzin, catechins, and chlorogenic acid in ‘Jonagold’ and ‘Elstar’ are found to be highest early in the growing season, and these decrease to steady levels during maturation and ripening (Awad et al. 2001a). Furthermore, levels of anthocyanins in both ‘Elstar’ and ‘Jonagold’ are high early in the growing season, drop in mid-season, and rapidly increase prior to fruit maturation. Interestingly, such increased levels in anthocyanin content are detected in fruit hanging along the outer periphery of the tree canopy, but not within the inner areas of the tree canopy. Similarly, levels of quercetin glycosides in both ‘Jonagold’ and ‘Elstar’ are also found to be higher in fruit hanging along the outer periphery of the tree canopy (Awad et al. 2001b). Thus, sun-exposed fruits of both cultivars have higher levels of both quercetin glycosides and anthocyanins than those of shaded fruits, thereby indicating that exposure to sun light influence increased accumulation of these two phenolic compounds in apple. However, levels of phloridzen, catechin, and chlorogenic acid are not influenced by sunlight. Therefore, it is proposed that light exposure of apple fruit may enhance synthesis and accumulation of particular phytochemicals (Awad et al. 2001b). Among other factors influencing phytochemical contents in apples is that of cultural management practices such as fertilization. Awad and de Jager (2002a) have reported that application of nitrogen fertilization is associated with drop in levels of anthocyanins, catechins, and total flavonoids in fruit and contributes to lower percentage of blush in peel of fruit of cv. Elstar. On the other hand, calcium fertilization is associated with increased levels in anthocyanins and total flavonoids in fruit of apple cv. Elstar. Furthermore, application of various growth regulators in apple orchards can also influence accumulation of flavonoids and chlorogenic acid as observed on apple cv. Jonagold (Awad and de Jager 2002b). It is reported that application of ethephon highly elevates levels of anthocyanin accumulation, but not of other flavonoid compounds and chlorogenic acid in peel of ‘Jonagold’, while application of ABG and gibberellic acid (GA3) significantly delayed accumulation of anthocyanin, but not that of other flavonoid compounds and of chlorogenic acid (Awad and de Jager 2002b).

5.9

Effects of Apple Fruit Storage and Processing on Phytochemical Content

It has been reported that phytochemical content in apples is not significantly affected by storage (Boyer and Liu 2004). In an early study, van der Sluis et al. (2001) have observed that levels of quercetin glycosides, phloridzin, and anthocyanin in ‘Golden Delicious’, ‘Jonagold’, ‘Elstar’, ‘Red Delicious’, and ‘Cox’s Orange Pippin’ do not change following controlled atmosphere (CA) storage for a period of 52 weeks. However, levels of both total catechins and chlorogenic acid slightly decrease in ‘Jonagold’, while levels of chlorogenic acid remain stable and those of total catechin

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slightly decrease in ‘Golden Delicious’. On the other hand, under standard cold storage conditions (0  C), there is no decrease in levels of chlorogenic acid in all cultivars analyzed, while levels of catechin slightly drop in ‘Elstar’, ‘Cox’s Orange Pippin’, and ‘Golden Delicious’ following 25 weeks of storage (van der Sluis et al. 2001). Interestingly, both forms of storage have no effects on antioxidant activity in any of these tested apple cultivars (van der Sluis et al. 2001). As apple processing is a major industry, studies have evaluated the influence of processing on phytochemical content. For instance, apple juice from ‘Jonagold’, using straight pressing and pulping, is found to have only 10% of the antioxidant activity of fresh apples. On the other hand, juice resulting from pulp enzyming has only 3% antioxidant activity, and this juice has 58% less catechin, 44% less chlorogenic acid, and 31% less phloridzin, as most of the phenolic compounds are retained in the apple pomace (van der Sluis et al. 2002). It is reported that apple phenolics, especially procyanidins, are found to bind with plant cell wall, which leads to these reduced levels of polyphenol compounds detected in apple juice (Renard et al. 2001). As apple peel contains higher levels of phenolic compounds than that of the flesh, apple peel of ‘Rome Beauty’ is turned into freeze-dried samples, and it is found that these samples have the highest levels of total phenolic and flavonoid contents, even higher than those in fresh peels (Boyer and Liu 2004; Wolfe and Liu 2003). Furthermore, apple peel powder is found to have a strong antioxidant activity and inhibits cell proliferation (Wolfe and Liu 2003). Therefore, apple peel powder may serve as a value-added product in various food products to increase their phytochemical content and antioxidant activity (Boyer and Liu 2004). In recent studies, it has been found that genotype, tissue type, and cold storage have strong effects on bioactive compound contents in different apple cultivars. It is observed that total phenol content is greatly reduced in flesh (50%) and peel (20%) following cold storage (1  C for 3 months) in apple cv. Braeburn (clone Hillwell), but not in apple cvs. Golden Delicious (clone B) and Fuji (clone Kiku8) (Carbone et al. 2011). Moreover, phenolic content is found to decrease slightly over storage period (1  C for 60 days) in commercial apple cvs. Topaz, Pinova, and Pink Lady, as well as in three local (Bosnia and Herzegovina) apple cultivars, namely, ‘Ruzmarinka’, ‘Ljepocvjetka’, and ‘Paradija’ (Begić-Akagić et al. 2011).

5.10

Influence of Applications of Growth Regulator Compounds and Fruit Drying Protocols on Apple Phytochemical Content

Boyer and Liu (2004) evaluated the effects of applying various chemical compounds, used as growth regulators on apple fruit ripening and red color development, as well as the phytochemical content in these fruits. It was observed that ethephon increased anthocyanin production, but it did not increase chlorogenic acid content or the levels of any of other phytochemicals. Moreover, applications of gibberellins and (S)-trans2-amino-4-(2-aminoethoxy)-3-butenoic acid hydrochloride (ABG-3168) decreased anthocyanin production in apple fruit, but these did not influence levels of other phytochemical compounds. Furthermore, application of other chemicals, such as

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cycocel, seniphos, shikimic acid, plantacur-E, and galactose, did not have effects on contents of any of the phytochemical contents in apple (Boyer and Liu 2004). Kidoń and Grabowska (2021) investigated the effects of three fruit drying methods, including convective drying, vacuum-microwave pretreatment with convective drying, and freeze-drying, on the content of phytochemicals, antioxidant activity, color, and sensory attributes of cut cubes of red-fleshed apples, M. purpurea or M. pumila var. Niedzwetzkyana. Fruits of M. purpurea are known to have high contents of anthocyanins both in skin and flesh tissues, rendering the entire apple either red or pink in color, as well as of various phenolic compounds, including chlorogenic acid, catechin, phlorizin, procyanidins, and quercetin derivatives. On average, levels of these phytochemical compounds are threefold higher than those found in standard apple cultivars (Rupasinghe et al. 2010; Wang et al. 2015). Kidoń and Grabowska (2021) observed that following drying, the highest levels of phenolics were detected in freeze-dried apples. In particular, chlorogenic acid was the major phenolic compound, accounting for 60% of all phenolics in both fresh and dried red-fleshed apples, while cyanidin-3-galactoside was the major anthocyanin. However, levels of anthocyanins were markedly lower in these apples following drying.

5.11

Correlations Between Apple Phytochemical Content and Antioxidant Activity

It is important to point out that variations in phytochemical contents among different apple cultivars also influence antioxidant activities. In particular, it has been reported that there is a correlation between levels of phenolic compounds and antioxidant activity (Boyer and Liu 2004). Wojdyło et al. (2008) have determined the composition of phenolic compounds in 67 apple “new” and “old” cultivars along with their antioxidant activities. It is reported that using liquid chromatography-mass spectrometry (LC-MS) analysis for phenolic contents (up to 18 compounds) in this large group of apple cultivars, including those of flavanols (catechin, procyanidin), flavonols, anthocyanins, hydroxycinnamates, and dihydrochalcones, a mean content of total polyphenols ranged between 523 and 2724 mg/100 g dry weight, depending on the apple cultivar. Moreover, it is found that flavanols (catechin and oligomeric procyanidins) account for 80% of polyphenols, followed by hydroxycinnamic acids (1–31%), flavonols (2–10%), dihydrochalcones (0.5–5%), and, in red apples, anthocyanins (1%). Furthermore, it is reported that the highest correlation (r) of total polyphenols and antioxidant activity, based on assays of free-radical scavenging ability, is detected with the 2,20 -azino-bis-3-ethylbenzothiazoline-6-sulphonic acid (ABTS) method (r ¼ 0.87), followed by that for the ferric reducing/antioxidant power (FRAP) (r ¼ 0.84), and 2,2-diphenyl-1-picrylhydrazyl (DPPH) (r ¼ 0.80) methods. Levels of bioactive compounds in this large group of cultivars indicated that these levels are either equal or higher in new (e.g., ‘Ozark Gold’, ‘Julyred’, and ‘Jester’) versus old (e.g., ‘Golden Delicious’, ‘Idared’, and ‘Jonagold’) cultivars, and concentration of procyanidins/flavan-3-ols is the most important contributor to the in vitro antioxidant activity (Wojdyło et al. 2008).

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As mentioned above, Stushnoff et al. (2003) evaluated the total phenolic content and the antioxidant activity using the ABTS method of a large collection of Malus germplasm. It was reported that the antioxidant activity of a subset of that collection, 103 taxa, correlated well with the total phenolic content (r ¼ 0.7779 for juice and r ¼ 0.7181 for freeze-dried fruit). Recently, Mignard et al. (2021) analyzed apple fruit quality and levels of biochemical compounds (peeled fruit, i.e., flesh tissue), including total phenolics content, total flavonoids, vitamin C (ascorbic acid-AsA), and relative antioxidant capacity (using the DPPH method) of 155 accessions, consisting of 99 local (commercial cultivars and traditional landraces) and 56 foreign accessions, grown at the germplasm bank in Spain over a period of 5 years. It was found that total phenolics content widely varied among these accessions and over the years, ranging from 3.3 (‘Poma de San Juan’, in 2018) to 116.7 (‘Camuesa Fina de Aragón’, in 2015) mg gallic acid equivalents/100 g fresh weight. On the other hand, the total flavonoid content ranged from 0.7 (‘Poma de San Juan’, in 2018) to 142.1 (‘Camuesa Fina de Aragón’, in 2014) mg catechin equivalents/100 g fresh weight. Moreover, levels of vitamin C ranged from 0.4 (‘Delgared infel’, in 2016) to 13.2 (‘Transparente’, in 2014) mg AsA/100 g fresh weight. As for the relative antioxidant capacity, this varied from 1.7 (‘Poma de San Juan’, in 2018) to 44.6 (‘Les_1 – MRF 73’, in 2014) mg trolox/100 g fresh weight. Over the period of 5 years, mean values of total phenolics content varied from 15.2 (‘Biscarri_1 – M 107’) to 98.1 (‘Camuesa Fina de Aragón’) mg gallic acid equivalents/ 100 g FW, total flavonoid content ranged from 6.0 (‘Biscarri_1 – M 107’) to 89.0 (‘Camuesa Fina de Aragón’) mg catechin equivalents/100 g FW, whereas, vitamin C ranged from 1.4 (‘Delgared infel’) to 5.9 (‘Reguard_1 – MRF 53) mg AsA/100 g fresh weight. Finally, mean values of relative antioxidant capacity varied from 5.9 (’Delgared infel’) to 30.8 (‘Les_1 – MRF 73’). Furthermore, Mignard et al. (2021) have reported that all levels of bioactive compounds and relative antioxidant capacity demonstrated significant differences between local and foreign accessions. Indeed, for all parameters analyzed, foreign cultivars such as ‘Deljeni’, ‘Delorgue Festival’, ‘Akane’, and ‘Reineta Gris’, among others, had lower values than those of local accessions such as ‘Peruco de Caparroso’, ‘Prau Riu_5’, ‘Camuesa Fina de Aragón’, and ‘Les_1 – MRF 73’, among others. Using Pearson’s correlation, Mignard et al. (2021) found that relative antioxidant capacity was highly and positively correlated with each of total phenolics content and total flavonoid content, r ¼ 0.901 and r ¼ 0.865, respectively. Moreover, total phenolics content was significantly and highly positively correlated with total flavonoid content, r ¼ 0.963. Interestingly, vitamin C showed a significant and moderate positive correlation with total phenolics content, r ¼ 0.415. In addition, significant moderate positive correlations were found between titratable acid and each of total phenolics content and flavonoid content, r ¼ 0.450 and r ¼ 0.464, respectively. Using a cluster analysis, Mignard et al. (2021) revealed that foreign cultivars (those not originating from Spain) were concentrated in two groups, while local accessions could not be segregated and had very different profiles. Furthermore, it

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was observed that levels of bioactive compounds tended to decrease with higher temperatures, while these levels increased with higher solar radiation; thus, it was concluded that genotypes and climate are major factors influencing variability in metabolite profiles. Interestingly, Kidoń and Grabowska (2021) used the ABTS assay to assess the antioxidant activity in dried apple fruit cubes of red-fleshed apples (as described in the above section), and they found that apple cubes subjected to convective drying had the highest antioxidant activity, while the vacuum-microwave pretreatment with convective drying samples had the lowest antioxidant activity.

5.12

Genetic Mapping of Phytochemical Content Components in Apple

Efforts to uncover the complex genetic controls of the phenolic compound content of apples have been underway for quite some time, but these efforts have intensified in recent years. Early genetic mapping efforts of some of metabolites in apple fruits have been undertaken with particular interest in volatile compounds that contribute to aroma. Dunemann et al. (2009) constructed a set of two parental genetic maps for apple cultivars ‘Discovery’ and ‘Prima’ using dominant amplified fragment length polymorphism (AFLP) and resistance gene analog (RGA) markers along with a set of 90 multi-allelic simple sequence repeats (SSRs), selected based on their known positions within the Malus genome. A total of 18 linkage groups (LGs) was constructed for ‘Discovery’, while the ‘Prima’ map consisted of 19 LGs. Hence, 17 homologous LGs corresponding to the basic chromosome number in apple (n ¼ 17) were assigned in both parents and aligned with co-dominant SSRs and with segregating AFLPs. A total of 20 volatiles, including various esters, alcohols, terpene α-farnesene, and norisoprenoid β-damascenone, measured using gas chromatography–mass spectroscopy (GC/MS) over a period of 3 years, were analyzed for levels of variability in ‘Discovery’ and ‘Prima’. It was observed that approximately 50 putative quantitative trait loci (QTLs) for a total of 27 different apple fruit volatile compounds were detected via interval mapping by using genotypic data of 150 F1 seedlings of the mapping population of ‘Discovery’
‘Prima’ along with phenotypic data obtained by head-space solid phase microextraction gas chromatography. It was reported that QTLs for volatile compounds likely involved in apple aroma were detected on 12 out of 17 apple chromosomes, but these were not evenly distributed. In particular, QTLs were clustered primarily on LGs 2, 3, and 9. A lipoxygenase (LOX) candidate gene, likely involved in volatile metabolism, was mapped on LG 9 and genetically associated with a cluster of QTLs for ester-type volatiles. With availability of various analytical tools for large-scale analysis of metabolites in an organism, the field of metabolomics has emerged as a powerful tool for pursuing functional genomics studies in various crops, including that of apple (Brizzolara et al. 2021; Han and Korban 2021). Khan et al. (2012a) investigated

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the genetic basis of quantitative variations of phenolic compounds in apple fruit. They used a large segregating F1 population of ‘Prima’
‘Fiesta’ to map metabolite quantitative trait loci (mQTLs). They conducted untargeted metabolic profiling of peel and flesh tissues of ripe apple fruits using liquid chromatography–mass spectrometry (LC-MS) and detected 418 metabolites in peel and 254 metabolites in flesh tissues (Khan et al. 2012a). Furthermore, using the mapping software MetaNetwork, enabling simultaneous genome-wide screening of numerous traits, they were able to detect and map 669 significant mQTLs, 488 in peel and 181 in flesh tissues. Of particular interest, they identified four linkage groups, namely, LG1, LG8, LG13, and LG16, that contained mQTL hotspots, primarily involved in regulating metabolites belonging to the phenylpropanoid pathway. Subsequently, they used the MapQTL ® software to construct an integrated map of both parents, ‘Prima’ and ‘Fiesta’, and this map, containing 801 markers and spanning 1348 cM, was used for analysis of annotated metabolites to elucidate the genetics of these annotated metabolites (Khan et al. 2012a). It was observed that a number of quercetin conjugates had mQTLs on either LG1 or LG13. However, an mQTL hotspot with the largest number of metabolites was detected on LG16, wherein mQTLs for 33 peel-related and 17 flesh-related phenolic compounds were located. Furthermore, structural genes of the phenylpropanoid biosynthetic pathway were located by aligning positions of orthologous genes on all 17 chromosomes of apple to DNA sequences of structural genes of Arabidopsis thaliana using the genome sequence of apple cv. Golden Delicious (Velasco et al. 2010). Various metabolites that mapped onto an mQTL hotspot on LG16 locus included procyanidins (flavan-3-ols and their polymers), phenolic esters, and flavonol and dihydrochalcone derivatives, among others. All these compounds belong to the phenylpropanoids; thus, it was presumed that this mQTL was controlled by a biosynthetic gene from the phenylpropanoid pathway, or by a transcription factor controlling this pathway. In addition, an apple structural gene coding for leucoanthocyanidin reductase (LAR1), MdLAR1, was identified in the mQTL hotspot on LG16, as well as seven transcription factor (TF) genes. In a subsequent study, Khan et al. (2012b) investigated expression profiles of structural and putative transcription factor genes of the phenylpropanoid and flavonoid pathways during various stages of fruit development in progeny. It was observed that it was only the structural gene MdLAR1, located on LG16, demonstrated highly significant correlation between transcript abundance and content of metabolites mapped onto the mQTL hotspot. Furthermore, it was observed that seedling progeny of ‘Prima’
‘Fiesta’, divided into two groups based on “procyanidin dimer II” levels of either high of low content, inheriting either one or two copies of dominant MdLAR1 alleles (Mm, MM) had 4.4- and 11.8-fold higher levels of expression, respectively, than progeny inheriting the recessive alleles, mm (Khan et al. 2012b). In addition, this observed higher level of expression was associated with a fourfold increase of procyanidin dimer II as a representative metabolite that mapped within the mQTL hotspot. Although expression levels of several other structural genes correlated with expression of various structural genes and with some bHLH and MYB transcription factor genes, it was only expression of MdLAR1 that correlated with metabolites mapped within the mQTL hotspot (Khan

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et al. 2012b). Therefore, it was proposed that MdLAR1 was the only candidate gene that could explain the mQTL for procyanidins and flavan-3-ols. However, mQTLs for other phenylpropanoids such as phenolic esters, flavonols, and dihydrochalcones that were detected at the same locus on this map have not been deemed to be dependent on LAR, as their biosynthesis did not involve LAR activity (Khan et al. 2012b). Thus, the dominant allele of MdLAR1, promoting increased content of metabolites of potential health benefit, was proposed to be useful in marker-assisted selection in current apple breeding programs, as well as for pursuing cisgenesis (Khan et al. 2012b). Chagné et al. (2012) analyzed fruits from a population of ‘Royal Gala’
‘Braeburn’ segregating for phenolic compounds using ultra-high performance liquid chromatography (UHPLC) of extracts derived from fruit peel and flesh. A total of 23 phenolic compounds with varying levels were quantified in apple peel and flesh in 2 separate years. Furthermore, using single nucleotide polymorphic (SNP) markers to genotype individuals in this segregating population, and subsets of these SNPs were used to construct genetic maps for the two parents, ‘Royal Gala’ and ‘Braeburn’. These genetic maps and segregating population were used to detect 79 QTLs for 17 fruit polyphenolic compounds. Of these QTLs, seven QTL clusters were found to be stable across two fruit harvest years, and these included QTLs for content of flavanols, flavonols, hydroxycinnamic acids, and anthocyanins. Following alignment of parental genetic maps with the whole genome sequence of apple cv. Golden Delicious (Velasco et al. 2010), this allowed for screening of candidate genes, coding for enzymes in the polyphenolic biosynthetic pathway, that were co-segregating with these QTLs. As observed by Khan et al. (2012a), the largest cluster of QTLs was located at the top of LG16. Using bioinformatic tools, candidate genes predicted on the basis of their involvement in the polyphenolic biosynthetic pathway were located on the whole genome sequence of cv. Golden Delicious using BLASTN analysis. Furthermore, this co-location was confirmed by genetic mapping of markers derived from gene sequences. It was found that LAR1 co-located with a QTL cluster for fruit flavanols catechin, epicatechin, and procyanidin dimer, and five unknown procyanidin oligomers identified near the top of linkage group LG 16, while HYDROXY CINNAMATE/QUINATE TRANSFERASE (HCT/HQT) co-located with a QTL for chlorogenic acid that mapped near the bottom of LG 17. Interestingly, it was hypothesized that the mutation that drove this signal on chromosome 16 was present in the promoter region of LAR1 and located within a site recognized by transcription factors involved in gene regulation. Furthermore, this mutation did not result in a complete loss of function of LAR1 (Chagné et al. 2012). It was concluded that LAR1 and HCT/HQT must have likely influenced levels of these phenolic compounds in apple fruit. Therefore, it was proposed that LAR1 and HCT/ HQT would serve as useful allele-specific markers for marker-assisted selection of fruit-bearing trees with high content of these phenolic compounds. Verdu et al. (2014) have capitalized on marker-assisted selection to identify and select new apple cultivars with specific phenolic compounds influencing the taste of cider. Fruit and juice of individuals from a segregating population of a cross between two hybrids X5210 (derived from ‘Kermerrien’, a well-known French

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cider apple cultivar) and X8402 (a desert apple derived from ‘Florina’
‘Prima’) have been analyzed for various phenolic compounds using a liquid chromatography system. The phenolic compounds including (+)-catechin, (2)-epicatechin, procyanidins B1 and B2, avicularin, hyperin, quercitrin, 5-caffeoylquinic acid, 4-p-coumaroylquinic acid, and phloridzin have been quantified in each 2 years in both fruit and juice. Other compounds (procyanidins B5 and C1, 4-caffeoylquinic acid, isoquercitrin, reynoutrin, ideain, rutin, and phloretin xyloglucoside) have been quantified in some experiments. QTLs have been detected on LG1 for flavanols, LG5 for dihydrochalcones, LG15 for flavonols, and LG16 for mean polymerization degree (DPn) of these phenolic compounds. These QTLs have demonstrated high stability between years and for apple products, fruit, and juice, with high proportion of explained phenotypic variation. Candidate genes under these QTLs for phenolic content were identified in silico from the apple genome sequence, and their co-localizations were confirmed by genetic mapping. For example, they identified and mapped four genes homologous to shikimate/ quinate O-hydroxycinnamoyl transferase (HCT/HQT) under the QTL confidence interval for the 5-caffeoylquinic acid on the LG17. Likewise, a gene homologous to flavonoid 30 -hydroxylase (F30 H), responsible for the hydroxylation on the third position of the B ring of flavonols, dihydroflavonols, and flavanones, was identified and mapped under the quercetin glycoside cluster. Moreover, a homologue of UDP-glucose 3-glucosyltransferase (UFGT) gene was identified under QTLs for flavanols on LG1. This gene is described to catalyze the formation of anthocyanidins-3-O-β-D-glucoside from anthocyanidins and UDP-D-glucose (Verdu et al. 2014). Verdu et al. (2014) have confirmed the importance of two regions involved in the biosynthesis of hydroxycinnamic acids on LG14 and LG17. Moreover, other regions of interest include those detected on LG1, LG5, and LG15 for flavanols, dihydrochalcones, and flavonols, respectively. These QTLs are of interest in applebreeding programs. Furthermore, identification of candidate genes in silico has revealed interesting targets for future studies to better understand the biosynthesis of phenolic compounds. This study not only highlighted QTLs responsible for variability of major phenolic compounds involved in cider organoleptic characteristics but also those for mean polymerization degree of procyanidins. It is reported that these QTLs would aid in understanding the mechanism of procyanidin biosynthesis, which appears to be independent from the synthesis of flavanols. In another study, a number of major QTLs regulating apple fruit mean L-ascorbate (l-AA), or vitamin C, and total l-AA levels on parental genetic linkage maps of apple cvs. Telamon and Braeburn have been detected (Davey et al. 2006). Moreover, common QTLs were localized to the same region of LGs 6, 10, and 11, accounting for up to 60% of the total observed variation in the segregating seedling population of ‘Telamon’
‘Braeburn’. It was proposed that molecular markers for some of these QTL alleles could be used to select for high mean and total contents of l-AA/total l-AA contents. Moreover, a major and highly significant QTL for flesh total l-AA content on LG 17 of the ‘Telamon’ map was detected that co-localized not only with a QTL for dehydroascorbate (DHA) content but also

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with strong QTLs for flesh browning. It is proposed that this QTL on LG 17 may be involved in regulating the redox status of fruit flesh l-AA pool, likely via the activity of polyphenol oxidases (PPOs) or peroxidases (Davey et al. 2006). Fang et al. (2017) determined the ascorbic acid (AsA) content in mature fruits in a large collection of 30 Malus species and 457 accessions, consisting of worldwide cultivars. It was found that AsA concentration ranged from 10.48 to 278.48 μg/g fresh weight, with an average of 46.43 μg/g fresh weight, corresponding to more than 26-fold variation in AsA concentration among all accessions analyzed. Ascorbic acid content ranged from 22.07 to 278.48 μg/g fresh weight in fruits of wild species compared to 10.48 to 131.52 μg/g fresh weight in fruits of apple cultivars. Thereby, this suggested that fruits of wild species had wider variations in ascorbic acid content than fruits of cultivated apples. Furthermore, it was observed that ascorbic acid accumulation in fruit of cultivated apples is rapid during early fruit development, but this markedly decreases during fruit expansion, followed by a slight decline during the mature stage. In an earlier genetic analysis study, Mellidou et al. (2012) reported that four regions on chromosomes 10, 11, 16, and 17 contained stable fruit AsA-QTL clusters, and when AsA metabolic genes were mapped, it was found that within this QTL clusters, these genes co-located with orthologs of GDPL-galactose phosphorylase (GGP), dehydroascorbate reductase (DHAR), and nucleobase-ascorbate transporter (NAT). Following additional analysis, it was delineated that AsA content in mature apple fruit was mainly controlled by a set of four genes, including two encoding the galactose biosynthetic pathway enzyme genes MdGGP1 and MdGGP3; an ascorbic acid recycling pathway enzyme encoding gene, MdDHAR3-3; and a nucleobase ascorbate transporter gene, MdNAT7-2. When Fang et al. (2017) evaluated expression of these four genes throughout apple fruit development, it was observed that all four genes were highly expressed in fruits at stages of fruit expansion (highest levels) and maturity stages compared to early fruitlet development at the juvenile stage. Moreover, levels of expression of three genes, MdGGP1, MdDHAR3-3, and MdNAT7-2, were significantly and negatively correlated with AsA contents in fruits throughout different stages of fruit development. This suggested that low levels of ascorbic acid may induce expression of these three genes during fruit expansion and maturity via a feedback mechanism. However, in young fruitlets, expression of all analyzed genes demonstrated a positive correlation with ascorbic acid content, thereby suggesting that unusual high levels of ascorbic acid detected in early developing fruit was likely due to coordinated contribution of ascorbic acid synthesis and regeneration, as well as of ascorbic acid translocation from leaves (Fang et al. 2017). A major locus for anthocyanin content in apple flesh has been mapped to linkage group LG 9 (Chagné et al. 2007). Expression studies have determined that this locus is controlled by MYB10 (Espley et al. 2009). An allelic gene, MYB1, also located on LG 9, controls fruit skin color (Zhu et al. 2011). Subsequently, a major QTL controlling red skin coloration on LG 9, found using four segregating New Zealand populations, was screened using an apple 8-K single-nucleotide polymorphism (SNP) array, and a significant SNP marker, ss475879531, was identified (Chagné et al. 2016). This SNP marker was transformed into a marker suitable for use in a real-time PCR assay for the

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red skin phenotype (Chagné et al. 2016). It was found that this marker could efficiently predict red skin coloration and it would be useful in marker-assisted selection.

5.13

Genome-Wide Association Studies and Candidate Gene Predictions

McClure et al. (2019) investigated the genetic architecture of polyphenols by combining high performance liquid chromatography (HPLC) data with ~100,000 SNPs using two apple populations, consisting of 136 cultivars evaluated in 2014 and 85 cultivars (from the larger population) evaluated again in 2016, planted in two different randomized blocks. They observed that polyphenol compound contents in fruit, of both peel and flesh, varied widely, up to two orders of magnitude across cultivars, and that much of this variation was both heritable and predicable using genetic markers. Moreover, it was observed that this wide variation was often controlled by a small number of genetic loci with large effects. Using genome-wide association study (GWAS), McClure et al. (2019) have detected significant genotype-phenotype associations, and the proportion of the phenotypic variance (R2) explained by the top SNPs ranges from 0.31 to 0.63. Although this relatively high effect size estimates are attributed in part to small sample size, it is suggested that expression of several polyphenolic compounds in apple is under relatively simple genetic control. Furthermore, it is reported that identified markers are in strong linkage disequilibrium (LD) with causal genetic variation that underlies expression of polyphenol compounds. Based on GWAS, it was observed that there was a clear trend for flavan-3-ols and pro-anthocyanidins, wherein there was a large peak on chromosome 16 for catechin, epicatechin, and procyanidin B1, B2, and C1. Interestingly, a highly significant SNP accounted for up to 50% of the observed phenotypic variance. As noted in the above genetic linkage mapping studies of biparental populations, this region on chromosome 16 was identified as a QTL hotspot for catechin, epicatechin, and proanthocyanidins (Khan et al. 2012a, b; Chagné et al. 2012). Although McClure et al. (2019) have detected some slight differences in the location of this most significant SNP across phenotypes, these were within the boundaries of the aforementioned QTL hotspot. Again, as LAR1 has been identified earlier as a putative candidate gene for this hotspot, it is proposed to catalyze conversion of leucocyanidin to catechin. Moreover, this region is found to also contain several transcription factors of different classes, including MYB, bHLH, bZIP, and AP2 that could also influence levels of phenolic compounds in apple fruit. McClure et al. (2019) have found GWAS peaks for various other phenolic compounds including those for flavonol and quercitrin, on chromosome 1. Earlier studies have detected hits for flavonols on chromosome 1 and have proposed that a uridine diphosphate-dependent glycosyltransferase (UGT) gene and a flavonoid 30 -hydroxylase (F30 H ) gene are potential candidate genes underlying this signal (Verdu et al. 2014; Khan et al. 2012a). McClure et al. (2019) have detected a SNP that strongly associated with quercitrin ~44 kb upstream of an apple UGT gene

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(MD01G1148700). As UGTs mediate glycosylation of flavonoids, and quercitrin is produced via glycosylation of the flavonoid quercetin, such glycosylation of secondary metabolites increases both solubility and stabilization of flavonoid compounds; moreover, specific UGTs have been identified that glycosylate flavonoids into potent antioxidants, such as phloridzin (Jugdé et al. 2008; Zhou et al. 2017; Kim et al. 2013). Nevertheless, no specific UGT has been associated with the formation of quercitrin in apples; thus, it is hypothesized that the GWAS signal detected on chromosome 1 is due to variation in a specific apple UGT gene (MD01G1148700) that regulates levels of quercitrin and glycosylation of quercetin (McClure et al. 2019). Further studies will assess whether or not quercetin is in fact associated with this UGT gene. Thus, it is anticipated that markers at this locus would be exploited for marker-assisted breeding to enhance the content of quercetin in apple or that genetic variation of antioxidant content will be introduced into new cultivars via gene editing. McClure et al. (2019) have exploited GWAS for chlorogenic acid, and two significant hits on apple chromosomes 5 and 15 have been detected, thereby suggesting that variation for this trait is controlled by two independent loci. Within this scope of these loci, three promising candidate genes have been identified at these loci including cinnamyl alcohol dehydrogenase (CAD; MD05G1089900), caffeoylCoA O-methyltransferase (CCOAMT; MD05G1083900), and 3-dehydroquinate synthase (DHQS; MD15G1242600). It is known that both CAD and CCOAMT are enzymes associated with biosynthesis of hydroxycinnamic acids via the phenylpropanoid pathway that also supplies intermediates for synthesis of flavonoids, tannins, and phytoalexins (Hoffmann et al. 2004). As CAD converts cinnamyl alcohol to cinnamaldehyde, it was found that a CAD gene was highly expressed in ripening receptacle tissues in strawberry; however, thus far no such CAD gene has been characterized in apple (McClure et al. 2019). While CCOAMT is not directly involved in the final step of chlorogenic acid biosynthesis, it is active upstream in its production via conversion of caffeoyl-CoA to feruloyl-CoA, and it has been associated with accumulation of chlorogenic acid accumulation in coffee (Clifford et al. 2017; Hoffmann et al. 2004). As for DHQS, it is reported to be involved in catalyzing key substrates for chlorogenic acid biosynthesis via the shikimate pathway (Maeda and Dudareva 2012). Therefore, it is proposed that all three genes, namely, CAD, CCOAMT, and DHQS, are likely candidates involved in chlorogenic acid production (McClure et al. 2019). As Khan et al. (2012a) and Chagné et al. (2012) have proposed that HCT/HQT on chromosome 17 are potential candidate genes for chlorogenic acid, McClure et al. (2019) have not identified SNPs on chromosome 17 that are significantly associated with chlorogenic acid. However, a suggestive GWAS signal is identified on chromosome 17 for chlorogenic acid, and a HCT/HQT gene (MD17G122510) is found within the suggestive peak on chromosome 17. Yet another hydroxycinnamic compound, 4-O-caffeoylquinic acid, produced significant GWAS hits on chromosomes 3 and 14 (McClure et al. 2019). Although candidate genes for flavonoid 30 -hydroxylase (F30 H ) or flavonoid 30 ,50 -hydroxylase (F30 50 H ) were proposed, these genes were not located on chromosome 14.

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As phenylalanine is converted to p-coumaroyl-CoA, with cinnamic acid and pcoumaric acid acting as intermediates, it is sequentially catalyzed by phenylalanine ammonia lyase (PAL), cinnamate 4-hydroxylase (C4H), and 4-cinnamoyl-CoA ligase (4CL). McClure et al. (2019) have identified an association signal for 4-Ocaffeoylquinic acid on chromosome 3; it is proposed that phenylalanine ammonialyase (PAL; MD03G1121500) may be a candidate gene for this detected signal. PAL, the first enzyme in the phenylpropanoid pathway, is an enzyme that catalyzes the production of cinnamic acid, a precursor to hydroxycinnamic compounds. PAL plays a critical role in controlling the biosynthesis of acyl-quinic acids (Clifford et al. 2017). In addition, a strong GWAS peak is detected for cyanidin-3-galactoside on chromosome 9, and a strongly associated SNP at this locus is also the most significantly associated SNP with total anthocyanin content in apple (McClure et al. 2019). It is reported that these associations are expected as cyanidin-3-galactoside is the most predominant anthocyanin in apples (Tsao et al. 2003), and several studies have identified a QTL for skin color that is found to co-locate to this genomic region (Zhang et al. 2019b; Amyotte et al. 2017; Chagné et al. 2016). It is reported that a SNP (ss475879531; chr9:33001375) on chromosome 9, useful in predicting skin color in apple breeding programs, is located 666 kb upstream from the most significant SNP identified by McClure et al. (2019). Moreover, Zhang et al. (2019b) have identified a retrotransposon insertion 1 kb upstream of the transcription factor MYB1 gene (chr9:35,541,127–35,541,721) that likely elicits the red-skinned phenotype. Although this putatively causal allele is located 1.8 Mb downstream from the top GWAS hit, it is found to overlap with a broad GWAS peak detected for both cyanidin-3-galactoside and total anthocyanins. Therefore, McClure et al. (2019) have identified several SNPs that are deemed as strong candidates for use in marker-assisted breeding. Moreover, it is reported that polyphenol compounds lacking significant GWAS are deemed as predictable using genome-wide SNPs; thus, these may be amenable for breeding using genomic selection (McClure et al. 2019). This study has demonstrated that quite often it is a relatively simple genetic architecture that underlies such observed wide variations in levels of key polyphenolic compounds in apple. These findings offer opportunities for breeding efforts in improving the nutritional value of apples using either markerassisted breeding or gene editing.

5.14

Transcriptome Expression Profiling of Genes Involved in the Phenylpropanoid Pathway

Busatto et al. (2019) conducted a large transcriptome analysis of 16 genes involved in key steps of the phenolic biosynthetic pathway, beginning with phenylalanine all the way through anthocyanins. These genes included Phenylalanine ammonia lyase (MdPAL), Chalcone synthase (MdCHS), Chalcone-flavone isomerase (MdCHI), Flavonoid 3-hydroxylase (MdF3H), Dihydroflavonol 4-reductase (MdDFR), Anthocyanin synthase (MdANS), and Anthocyanidin 3-O-glucosyltransferase (MdUFGT).

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Moreover, they investigated transcriptomes of genes involved in the synthesis of procyanidins including leucoanthocyanidin reductase (MdLAR) and anthocyanidin reductase (MdANR), as well as expression of those major genes involved in the synthesis of flavonols and phoridzin, including flavonol synthase (MdFLS), UDPdependent glycosyltransferase (MdUGT), and enoyl reductase (MdENLR), respectively. Furthermore, expression of three different MdUGT genes, including MdUGT88F1/4, MdMdUGT71K1s, and MdUGT71A15, along with MdENLR3/5, that are likely to be involved in the biosynthetic pathway of phloridzin, via glycosylation of phloretin into phloridzin (Zhou et al. 2017), was also investigated. In addition, expression of genes involved in the biochemical pathway of chlorogenic acid and its accumulation and oxidation were also investigated including p-Coumaroyl ester 3-hydroxylase (MdC3H) and the Polyphenol oxidase (MdPPO), respectively. This large transcriptome analysis study demonstrated that all these genes were expressed at higher levels in skin tissues than in flesh tissues, collected during early fruit development (74 days after full bloom) and at fruit maturity (harvest time, depending on the genotype), of seven apple genotypes including two wild Malus species, M. baccata and M. sieversii, and five apple cultivars, ‘Tyroler Spitzlederer’, two clones of ‘Golden Delicious’ (a smooth skin and a russeted skin clones), ‘Cripps Pink’, and ‘Braeburn’. However, there were some interesting findings wherein, during early fruit development, six genes, namely, MdCHI, MdF3H, MdDFR, MdANS, MdUFGT, and MdANR, had the highest levels of expression in the wild species M. baccata, but with no differences in levels of expression between the two tissues (skin and pulp), except for MdUFGT, whose expression was much higher in the flesh. On the other hand, transcriptome profiles of M. sieversii demonstrated higher levels of gene expression for MdCHS, MdFLS, MdLAR, and MdENLR3/5. Moreover, while MdCHS was expressed at higher levels in the fresh tissue, MdFLS showed higher transcript accumulation in the skin tissue (Busatto et al. 2019). Transcriptome profiles in cultivated apples demonstrated that MdPAL, MdF3H, and McCHI were highly expressed in skin of the russeted cultivar ‘Tyroler Spitzlederer’. Furthermore, the russeted ‘Golden Delicious’ clone (‘Rugiada’) demonstrated the highest level of expression of MdUGT88F1/4 in the skin tissue. These findings supported the role of russeting in the pattern of phenolic compound accumulation in these genotypes due to higher induction of expression of genes in the phenolic biosynthesis pathway of secondary metabolites (Busatto et al. 2019). Furthermore, the majority of genes involved in the phenolic biosynthesis pathway were highly expressed in skin tissues of fruit collected at harvest time in the different genotypes investigated (Busatto et al. 2019). However, at harvest time, transcriptome profiles of all 16 genes were higher in cultivated apples compared to the 2 wild Malus species, although MdCHS gene in M. sieversii was highly expressed. Furthermore, transcriptome profiles of nine genes, namely, MdPAL, MdCHI, MdF3H, MdANR, MdFLS, MdENLR3/5, MdANS, MdC3H, and MdUGT88F1/4, at harvest were significantly higher than during early fruit development, with a 3.8-fold (for MdUGTF88F1/a) to 58 (for MdFLS). This could be attributed to increased fruit size and skin russeting (Busatto et al. 2019).

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Enhancing Polyphenolic Contents in Red-Fleshed Apples

As noted above, interests in increasing contents of phenolic compounds and their bioavailability have prompted efforts for breeding for red-fleshed apple cultivars. It has been established that the red flesh trait has long been identified in the apple germplasm, particularly in Malus species, such as M. pumila var. Niedzwetzkyana (van Nocker et al. 2012; Wang et al. 2018). Several studies have reported that a MYB TF, MdMYB10, has been identified as a key factor responsible for increased accumulation of anthocyanin in several plant tissues and organs, including fruit, via its activation of anthocyanin pathway genes (Espley et al. 2007, 2009, 2013). In particular, owing to the higher anthocyanin contents in red-fleshed apples, compared to white-fleshed ones, particularly with higher levels of cyanidin, along with availability of molecular markers useful for marker-assisted selection for this trait, efforts have been underway to develop red-fleshed apples for its nutraceutical value (Wang et al. 2018). Busatto et al. (2019) evaluated the phenolic contents of seven white-fleshed apple accessions (described above) along with three red-fleshed apple accessions. As with white-fleshed apples, red-fleshed apple accessions had varying fruit sizes, wherein fruits of cultivated apple (M.
domestica) and M. pumila var. Niedzwetzkyana had an average weight of 80.8 and 75.1 g along with fruit diameter of 6 and 5.8 cm, respectively, while fruit of M. sylvestris had an average weight of 17.7 g and fruit diameter of 3.1 cm. All 15 phenolic compound contents, except for anthocyanins, were found in both white- and red-fleshed apples, including neochlorogenic acid, chlorogenic acid, trans-piceide, cis-piceide, catechin, epicatechin, procyanidin B1, procyanidin B2 + B4, quercetin-3-Rha, kampferol-3-rutinoside, quercetin-3-galactoside + glucoside, isorhamnetin-3-glucoside, rutin, arbutin, and phloridzin. Moreover, levels of chlorogenic acid, epicatechin, and procyanidin B2 + B4 in red-fleshed M. sylvestris were significantly higher (90.2, 133, and 16.9 mg/kg fresh weight, respectively), ranging from 1.3- to 4.5-fold, compared to these levels in the two red-fleshed accessions, cultivated apple and M. pumila var. Niedzwetzkyana. Comparing the metabolite profiles of white- versus red-fleshed apples, it was observed that the content of phenolic compounds was significantly higher in white-fleshed ones. However, red-fleshed apples had significantly higher anthocyanin contents than white-fleshed ones, although white-fleshed apples had higher contents of all other polyphenols. Furthermore, polyphenolic accumulation in the flesh of whitefleshed domesticated and red-fleshed accessions revealed a fold-change of 17.5, 12.7, and 26.2, respectively, for procyanidins B1 and B2 + B4 and quercetin-3-Rha, and this accumulation pattern is attributed to the fact that the red color is induced by MdMYB10 TF that activates anthocyanin-related genes in red-fleshed apples (van Nocker et al. 2012; Espley et al. 2007). It is worth pointing out that low levels of phenolic compounds, except for anthocyanins in red-fleshed apples, are noted both in skin and flesh tissues (Busatto et al. 2019). Although it has been widely reported that anthocyanins play important roles as an antioxidants, they have lower levels of bioavailability in comparison to other flavonoids, as they have been found to either degrade rather quickly or are rapidly absorbed and excreted in humans (McGhie and Walton 2007; Fernandes et al. 2014).

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Structural and Regulatory Genes Controlling Critical Nutraceutical Biosynthesis Pathways

5.16.1 The Phenylpropanoid Pathway The phenylpropanoid biosynthesis involves several structural genes, including those coding for phenylalanine ammonia-lyase (PAL), cinnamate-4-hydroxamate (C4H), and 4-coumarate–CoA ligase (4CL) (Fig. 2; Liu et al. 2021). This is followed by early biosynthesis genes (EBGs) of the flavonoid biosynthesis, including chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), flavanone 30 -hydroxylase (F30 H), and flavonoid 30 50 -hydroxylase (F30 50 H) (Henry-Kirk et al. 2012; Davies et al. 2020). This is followed by late biosynthesis genes (LBGs) of the flavonoid biosynthesis pathway including dihydroflavonol 4-reductase (DFR), anthocyanidin synthase (ANS)/leucoanthocyanidin dioxygenase (LDOX), UDP-glucose flavonoid 3-O-glucosyl transferase (UFGT), flavonol synthase (FLS), leucoanthocyanidin reductase (LAR1/LAR2), anthocyanidin reductase (ANR), glycosyltransferases (GT1/GT2), quinate hydroxycinnamoyl (HQT)/hydroxycinnamoyl CoA shikimate (HCT), and p-coumarate 3-hydroxylase (C3H), along with other modifying genes, such as methyltransferase (MT), O-methyltransferase (OMT), and anthocyanin transferase (AT) (Han et al. 2007, 2012; Henry-Kirk et al. 2012; Davies et al. 2020; Liu et al. 2021). In addition, there are four structural genes, namely, transparent testa 10 (tt10), transparent testa 12 (tt12), transparent testa 13 (tt13), and transparent testa 19 (tt19), encoding polyphenol oxidase (PPO), a secondary transport factor of the MATE (multidrug and toxic compound extrusion) family, H (+)-ATPase, and glutathione S-transferase (GST), respectively. These proteins play significant roles in modification, transport, and oxidation of anthocyanidins (Liu et al. 2021). 5.16.2 The Flavonoid Biosynthesis Pathway The flavonoid biosynthesis pathway has been extensively investigated in several plant species (Brueggemann et al. 2010; Liu et al. 2021). It is reported that regulation of this pathway occurs mostly at the transcriptional level of those structural genes encoding enzymes. It has been found that two major groups of transcription factors (TFs) are found to be involved in all investigated plant species, and these include the basic helix-loop-helix (bHLH) and R2R3 myeloblastosis (MYB) family proteins. BHLH proteins can typically regulate target genes in multiple branches of the flavonoid biosynthesis pathway (Brueggemann et al. 2010), while specificity for regulation of a single branch is conferred by MYB factors (Brueggemann et al. 2010). Although transcriptional control of the flavonoid pathway occurs mainly with these two major groups of TFs, additional regulators are required for proper expression of structural genes (Fig. 3). As reported above by Khan et al. (2012b) and Chagné et al. (2012), an LAR gene within a major QTL is deemed as a strong candidate controlling the accumulation of both flavanols and procyanidins. However, Brueggemann et al. (2010) have observed that an apple WD40-repeat gene (MdTTG1), a homolog of Arabidopsis TRANSPARENT TESTA GLABRA1 (TTG1), activated a promoter of the

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Fig. 3 A simplified schematic diagram of some of the key regulatory factors involved in the phenylpropanoid biosynthesis pathway. BBX B-box, bHLH basic-helix-loop-helix, ERF ethylene response factor, HY5 ELONGATED HYPOCOTYL 5, MYB v-myb avian myeloblastosis viral oncogene homolog, WD40 WD repeat protein, WRKY WRKYGQK domain, MBW MYB-bHLHWD40

Arabidopsis BANYULS gene, AtBAN, along with Arabidopsis TT2 and TT8 in A. thaliana protoplasts. This suggests that proanthocyanidin (PA) accumulation in apple is likely regulated at the transcriptional level although no TFs in apple have been yet identified to be involved in regulation of PA biosynthesis. Earlier, Han et al. (2012) investigated the functionality of the anthocyanidin reductase (ANR) gene family in apple, consisting of a single MdANR1 gene on chromosome 10 and two allelic MdANR2 genes, MdANR2a and MdANR2b, on chromosome 5. Liao et al. (2015) reported on the role of LAR genes in proanthocyanidins (PA), also referred to as condensed tannins, biosynthesis in apple. Expression profiles of both LAR and ANR genes were investigated in fruit skin of a single cultivated apple and three crabapples. Transcript levels of LAR1 and ANR2 genes were significantly correlated with contents of catechin and epicatechin, respectively, thus suggesting that these genes played active roles in PA synthesis. However, unexpectedly, transcript levels for both LAR1 and LAR2 genes were almost undetectable in two crabapples accumulating both flavan-3-ols and PAs. This finding contradicted an earlier finding that LAR1 gene was a strong candidate involved in regulation of metabolite accumulation of epicatechin and PAs in apple. Moreover, ectopic expression of the apple MdLAR1 gene in tobacco was found to

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suppress expression of the late genes in the anthocyanin biosynthesis pathway, thereby leading to resulting loss of anthocyanin in flowers. Furthermore, a decline in PA biosynthesis was also observed in flowers of transgenic tobacco plants overexpressing the MdLAR1 gene, which was likely attributed to reduced levels of expression of both tobacco genes NtANR1 and NtANR2 genes. This study confirmed the in vivo function of the apple LAR1 gene (Liao et al. 2015).

5.16.3 The Anthocyanin Biosynthesis Pathway As for anthocyanin biosynthesis, the role of regulatory genes is of critical importance. Many genes involved in regulation of the anthocyanin biosynthetic pathway consist of groups of TFs, including those of the MYB family, the bHLH family, and the tryptophan-aspartic acid repeat (WDR) family (Fig. 3) (Tian et al. 2017; Liu et al. 2021). Often, members of these three families of regulatory genes are dependent on the MYB-bHLH-WD40 (MBW) complex to elicit their roles (Hichri et al. 2010; Liu et al. 2021; Li et al. 2022). Those regulatory genes involved in upregulation of the anthocyanin pathway are members of a subclade that includes the PRODUCTION OF ANTHOCYANIN PIGMENT1 (PAP1) gene, and when overexpressed in Arabidopsis, this results in accumulation of anthocyanins (Borevitz et al. 2000). Anthocyanin-regulating MYBs have been isolated from various plant species, including apple, among other fruit crops in the Rosaceae family (Lin-Wang et al. 2010; Vimolmangkang et al. 2013; Chagné et al. 2013; Han et al. 2010). It is observed that proanthocyanidins are synthesized from epicatechin, which in turn is catalyzed by anthocyanidin reductase (ANR), transported, and polymerized (Tian et al. 2017). Anthocyanins are synthesized on the cytoplasmic surface of the endoplasmic reticulum, and stable anthocyanins are formed via different modifications, including glycosylation, methylation, and acylation, and then transported into the vacuole where they accumulate (Tian et al. 2017; Liu et al. 2021). Plunkett et al. (2019) have reported that accumulation of anthocyanins in plants seems to be linked to biotic and abiotic stress, with levels of anthocyanin increasing in response to these stresses. Studies on regulation of anthocyanin production have identified both biosynthetic pathways genes and major regulating TFs, comprising the MYB-bHLH-WD40 (MBW) complex (Baudry et al. 2004; Henry-Kirk et al. 2012; Albert et al. 2014). This complex binds promoter regions of anthocyanin biosynthetic genes and MYB10 to enhance transcription, as demonstrated in various plant species including apple (Espley et al. 2009; Chagné et al. 2013; Plunkett et al. 2019). Those MYBs regulating accumulation of anthocyanin in apple have been well investigated (Allan et al. 2008; Ban et al. 2007; Espley et al. 2009; Takos et al. 2006). It is found that the alleles MYBA and MYB1 are identical, sharing 98% sequence homology with MYB10, differing by three amino acids in the open reading frame (Ban et al. 2007). Furthermore, the R2R3 binding region of these genes and anthocyanin-related MYBs in other plant species is found to be highly conserved (Ban et al. 2007). It has been observed that MYB10, bHLH3/33, and a WD40 protein TTG1 in apple form an MBW complex that regulates anthocyanin levels in other plant systems (Allan et al. 2008; An et al. 2012).

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It is also important to point out that repressor genes also play an important role in the regulation of anthocyanin production, and these repressors have been identified in various plant species, such as Arabidopsis, petunia, strawberry, and apple, among others (Plunkett et al. 2019). For instance, two repressors have been reported in petunia: MYB27 (R2R3-MYB), a R2R3-type MYB that interferes with the MBW complex by preventing formation or incorporation and converting the complex into a repression complex, and MYBx (R3-MYB), an R3-type MYB that competes for interaction with the bHLH component of the MBW complex (Albert et al. 2014). MYB27 contains an ethylene-responsive element binding factor [ERF]-associated amphiphilic repression domain (EAR) and a repression TLLLFR motif, both involved in conferring the capability of anthocyanin repression (Albert et al. 2014). Lin-Wang et al. (2011) have identified a family of MYB repressors of anthocyanin in apple, belonging to the R2R3 MYB family, following heat treatment, and these repressors are characterized by an EAR motif. As Lin-Wang et al. (2011) have demonstrated that heat reduces MYB10 expression in apple skin, Xie et al. (2012) have demonstrated that low temperature induces binding of bHLH3 to MdMYB1 and to upregulating promoters of MdDFR and MdUFGT genes of the anthocyanin biosynthesis pathway (Fig. 3). Thus, it is clear that genes controlling the phenylpropanoid biosynthetic, flavonoid, and anthocyanin pathways in plants are mainly regulated by transcriptional changes (Plunkett et al. 2019; Liu et al. 2021). As mentioned above, anthocyanins are important secondary metabolites, belonging to flavonoids (polyphenols) (Liu et al. 2021). Thus far, over 20 anthocyanins have been identified in nature, and these are derived from the six most common anthocyanins, namely, cyanidin (Cy), peonidin (Pn), pelargonidin (Pg), malvidin (Mv), delphinidin (Dp), and petunidin (Pt). Anthocyanins are present along with various monosaccharides, including glucose, rhamnose, galactose, and xylose, as well as with disaccharides consisting of rhamnose, gentian disaccharide, and sophora disaccharide to form glycosides. Furthermore, anthocyanins consist of α-phenylbenzopyran cations, and these are primarily composed of C6(A)-C3 (C)C6(B) carbon skeleton structures. Depending on presence of hydroxyl groups at the 30 and 50 of the B-ring carbon structure, along with methoxylation, this is used to distinguish among the six anthocyanins. Thus, methylation and hydroxylation modifications at different positions of the B-ring of the molecule contribute to the development of different colors of anthocyanins. In addition to the roles of heat and cold temperatures in regulating anthocyanin accumulation, light conditions are also required for anthocyanin accumulation in many apple cultivars, particularly following exposure to ultraviolet-B (UV-B) irradiation (Ban et al. 2007; Jakopic et al. 2009; Vimolmangkang et al. 2014; Bai et al. 2014). R2R3-MYB TFs play critical roles in the regulation of the anthocyanin biosynthesis pathway as these can directly regulate expression of related genes, thereby contributing to tissue-specific anthocyanin accumulation (Liu et al. 2021). It has been well documented that BHLH TFs are necessary for activities of R2R3-MYBs, primarily for stabilizing the MYB complex or for promoting its transcription (Liu et al. 2021). As an

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example, some MYB TFs, such as MdMYB1, MdMYB9, MdMYB10, and MdMYB114, can promote apple fruit color development via interactions with bHLH3 and WD40 (Ban et al. 2007; Jiang et al. 2021). MdMYB1 is initially found in apple fruit skin, and its product participates in photoinduction by activating the transcription activity of promoters of the structural genes MdDFR and MdUFGT (Xie et al. 2012). It has been well documented that transcript levels of MdMYB1 are positively correlated with anthocyanin accumulation and expression of structural genes as promoters of MdDFR and MdUFGT have light-response elements, such as ACGTs and MRE or MRE-like sequences (Takos et al. 2006; Hartmann et al. 2005). Zhang et al. (2022) have reported that mdm-mir858, an miRNA with multiple functions in plant development, negatively regulates proanthocyanidin accumulation by targeting MdMYB9/11/12 in the peel of apple fruit. Members of the WD40 protein family have 4–10 random WD repeat domains, consisting of 40 amino acid sequences ending with tryptophan (W) and aspartic acid (D). Among the first WD40 proteins isolated from apple is MdTTG1, and this can interact with MdbHLH3 and MdMYB9 to control expression of downstream structural genes (Brueggemann et al. 2010). Some TFs such as apple MYB16 can negatively regulate anthocyanin biosynthesis by hindering formation of the MBW complex (Xu et al. 2017). Although many TFs have been found to be involved in the regulation of anthocyanin biosynthesis, the role of light in regulating anthocyanin biosynthesis is still under study. Various investigations of specific members of the BBX (B-BOX) protein gene family, belonging to the zinc-finger transcription factors, in apple have revealed that UV-B light in particular upregulates MdCOL11/BBX33 expression in a temperature-dependent manner (Liu et al. 2021). MdBBX33 is a close homolog of AtBBX22/LZF1 (LIGHT-REGULATED ZING FINGER PROTEIN 1), also known as STH3 (Salt Tolerance Homolog 3) and DBB3 (Double B-Box zinc finger 3) (Bai et al. 2014). Furthermore, overexpression of apple BBX33 in transgenic Arabidopsis lines resulted in increased anthocyanin accumulation and revealed that expression profiles of both BBX33 and MYB10 are related during different temperature and light regimes (Bai et al. 2014). It is demonstrated that BBX33 upregulates the MYB10 promoter, thus suggesting that BBX33 functions downstream of ELONGATED HYPOCOTYL 5 (HY5) and upstream of MYB10 as a component in the environmental sensing pathway, thereby resulting in anthocyanin production in apple (Fig. 3; Bai et al. 2014; Liu et al. 2021). Liu et al. (2018) assessed the roles of 23 apple BBX genes in anthocyanin regulation. Several BBX genes, including Arabidopsis CONSTANS (CO), CONSTANS-LIKE1 (COL1), and COL2, are reported to undergo diurnal patterns of gene expression. Furthermore, several studies investigated diurnal expression patterns in both candidate apple BBX genes and anthocyanin structural genes, along with expression profiles of anthocyanin biosynthetic genes and the MYB regulator, MYB1/MYB10 (An et al. 2019, 2020; Liu et al. 2019). A group of BBX proteins has been evaluated for their ability to activate the promoter of MYB1/MYB10 (Plunkett et al. 2019). The anthocyanin biosynthesis pathway is influenced by several parameters, including environmental factors (light, temperature, water, and sugar), phytohormones,

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transcription factors, as well as epigenetic modifications (Wang and Chen 2021). For instance, it is reported that light negatively regulates anthocyanin biosynthesis in apple primarily by inhibiting expression of MdBBX37, as MdBBX reduces expression of MdHY5 by directly targeting its promoter (Liu et al. 2019). In contrast, the transcription factors MdWRKY72 and MdWRKY11 bind to the W-box cis-element of MdHY5 to activate its regulation of anthocyanin biosynthesis (Liu et al. 2019; Hu et al. 2020). Therefore, it is apparent that BBX proteins function in response to light-induced anthocyanin accumulation and requiring HY5 participation. Furthermore, MdHY5, a bZIP TF and positive regulator of light signaling, can enhance anthocyanin biosynthesis via direct activation of MdMYB1/10 expression (An et al. 2019). Nevertheless, MdBBX37 hinders binding of MdMYB1 and MdMYB9 to their respective target genes, thereby reducing accumulation of anthocyanin (Ban et al. 2007; Takos et al. 2006; Liu et al. 2021). Phytohormones such as abscisic acid (ABA), jasmonic acid (JA), auxin, and ethylene are critical for plant and development, and they play important roles in anthocyanin biosynthesis (Wang and Chen 2021). An et al. (2021) have reported that ABI5 promotes ABA-induced anthocyanin biosynthesis by regulating the MYB1bHLH3 complex in apple. On the other hand, JA induces degradation of JAZ (jasmonate ZIM-domain) proteins in apple via direct interaction of MdJAZ with MdbHLH3, thereby interfering with the recruitment of MdbHLH3 to the promoter of MdMYB9 resulting in repressed transcription of the MBW complexes which leads to reduction in anthocyanin biosynthesis. As it has been observed that ethylene inhibits anthocyanin biosynthesis in red pears by downregulating expression of R2R3MYBs (including PpMYB10 and PpMYB114) and LBGs (late biosynthetic genes), and as ethylene signal transduction takes place via ethylene response factors (ERFs) and ethylene-insensitive 3 (EIN3)/EIN3-like (EIL), it has been reported that MdERF1B binds to promoters of MdMYB9 and MdMYB11 in regulating accumulation of both anthocyanin and proanthocyanidin (Zhang et al. 2018). Furthermore, elevated auxin levels can inhibit anthocyanin biosynthesis by suppressing structural and regulatory genes, while gibberellic acid (GA) signaling interrupts anthocyanin biosynthesis via DELLA proteins, essential for GA’s role in regulating anthocyanin biosynthesis (Liu et al. 2021). Expression of structural genes during anthocyanin biosynthesis is directly under the control of the MYB-bHLH-WDR complex, and R2R3-MYB TFs are highly involved in the regulatory anthocyanin pathway as these directly regulate expression of related genes, thereby resulting in tissue-specific accumulation of anthocyanin accumulation (Liu et al. 2021). Furthermore, BHLH TFs are critical for the activity of R2R3-MYBs, by either stabilizing the MYB complex or promoting its transcription (Liu et al. 2021). For instance, some MYB TFs, such as MdMYB1, MdMYB9, MdMYB10, and MdMYB114, can promote red color development in apple fruit via their interactions with bHLH3 and WD40 (Ban et al. 2007; Jiang et al. 2021). The MdMYB1 is detected in the skin tissue of apple, and its product participates in photoinduction by activating transcription activities of promoters of MdDFR and MdUFGT. It has been observed that MdMYB1 transcript levels are positively correlated with anthocyanin, as well as in accumulation and expression

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of structural genes as promoters of both MdDFR and MdUFG have light-response elements, such as ACGTs and MRE or MRE-like sequences (Hartmann et al. 2005; Takos et al. 2006). As members of the WD40 protein family have 4–10 random WD repeat domains, consisting of 40 amino acid sequences ending in tryptophan (W) and aspartic acid (D), MdTTG1 was the first WD40 protein isolated from apple and found to interact with both MdbHLH3 and MdMYB9 in controlling expression of downstream structural genes (Brueggemann et al. 2010). As it has been observed that some MYB TFs, such as apple MYB16, negatively regulate anthocyanin biosynthesis (Xu et al. 2017; Liu et al. 2021; Li et al. 2022), interactions of such MYBs with bHLH would hinder formation of the MBW complex, as well as competing in their interactions with subunits of bHLH and MYB/bHLH (Liu et al. 2021; Li et al. 2022). As TFs of members of the same family play different roles in the regulation of anthocyanin biosynthesis, functional elucidation of these TFs remains in progress. In addition to the above TF factors, other regulatory factors such as methylation and demethylation of DNA are also involved in the regulation of anthocyanin biosynthesis. For instance, the DNA methylation inhibitor 5-azacytidine can induce red color pigmentation in apple (Liu et al. 2021). Furthermore, microRNAs can play critical roles in anthocyanin biosynthesis. Zhang et al. (2020) have reported that expression of mdm-miR828 only increases during late red color development in the skin of apple fruit and that this miRNA is involved in a feedback regulatory mechanism associated with anthocyanin accumulation in apple. Moreover, mdm-miR828 is reported to inhibit accumulation of anthocyanin in response to high temperature (Zhang et al. 2020).

5.17

Future Opportunities and Challenges of Apple Nutraceutomics

In the past decade, there here has been a significant interest in enhancing the phytochemical content of apple fruit, particularly of various secondary metabolites involved in the phenylpropanoid, flavonoid, and anthocyanin biosynthesis pathways, as well as of vitamin C and fiber content. With availability of various biochemical analysis and metabolomic platforms and tools, as well as of molecular, genomic, transcriptomic, and bioinformatic tools and platforms, there are ongoing concerted and focused efforts in the evolving field of nutraceutomics. Nutraceuticals have been gaining more considerable interest due to their demonstrated safe, health benefit, and therapeutic effects. Many studies have focused on apple nutraceuticals, primarily of those secondary metabolites involved in the flavonoid biosynthesis pathway such as phloridzin, phloretin, and phenolic acids as they have demonstrated not only high antioxidant defense activities, as well as their critical roles in cell proliferation and gene expression, but they are also more readily bioavailable than those of other phytochemicals, particularly of anthocyanins. Therefore, nutraceuticals offer opportunities for improving human health, preventing chronic diseases, and alleviating various ailments and diseases, such as cancer, diabetes, cardiovascular diseases, asthma, pulmonary

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diseases, gastrointestinal disorders, and neurological disorders, among others. The most critical role of these apple nutraceuticals is to protect against oxidative damage, as humans live in a highly oxidative environment and various metabolic processes may result in production of higher levels of oxidants. As oxidative damage accumulates, it becomes more important to protect against oxidative damage early on. When compared to other fruits consumed in the USA, apples demonstrate the second highest level of antioxidant activity, after cranberry (Boyer and Liu 2003– 2004). Apples rank second for total content of phenolic compounds. When compared to other fruits, apples have the highest proportion of free phenolics; thus, these phenolics are likely to be more bioavailable, for eventual absorption into the bloodstream. As noted above, several of the antioxidant compounds in apples have been well investigated such as quercetin, catechin, epicatechin, procyanidin, chlorogenic acid, and phloridzin. Nutraceutomics offers new opportunities for pursuing enhancement of nutraceutical content of apple fruit in advanced breeding lines via integration of metabolome profiles, antioxidant activity, environment, and gene expression during pursuit of a genomic selection scheme(s) in an apple breeding program. Therefore, it is important that considerations of environmental influences, such as temperature and irradiation, as well as of fruit developmental factors are accounted for in gene expression analysis and in metabolic responses of these selections, as these present challenges in achieving rapid advances in nutraceutomics. Moreover, epigenetic modifications via DNA methylation can play important roles in structural and regulatory gene expression of “nutraceutical” profile(s). However, the key factor in continued successful advances in the field of apple nutraceutomics is to develop a set of priorities of those metabolites that are likely to be highly expressed in apple fruits under varying environmental conditions, particularly in light of current conditions of climate change, and also to demonstrate high efficacies of bioavailability. This should be followed by genetic enhancement and breeding efforts via various breeding schemes and strategies. These strategies could be pursued using either marker-assisted selection, genomic selection, rapid-cycling breeding, or gene editing, among others.

6

Conclusions

Plant secondary metabolites in apple fruit have been documented to be involved in alleviating various human health diseases and conditions, and therefore there has been increased interest in enhancing levels of these nutraceutical compounds in both skin and flesh tissues of apple fruits, as well as their bioavailability and antioxidant activities (Busatto et al. 2019; Nezbedova et al. 2021; Koh et al. 2019). Various studies have assessed contents of these nutraceutical compounds in different cultivars, genotypes, and accessions, and although contents of these compounds are higher in wild versus cultivated apples, there are various opportunities to enhance accumulation of these compounds in the cultivated apple (Busatto et al. 2019). Genetic studies have been undertaken to identify and map genes and

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QTLs associated with these compounds, particularly of phytochemical compounds involved in the phenylpropanoid pathway, including polyphenolic compounds consisting of phenolic acids and flavonoids (McClure et al. 2019; Brizzolara et al. 2021; Kim et al. 2020a). As marker-assisted selection efforts have become integrated in modern breeding programs, availability of molecular markers associated with various polyphenolic compounds has become highly critical in selecting genotypes with enhanced levels of these different compounds (Teh et al. 2021). Furthermore, owing to the availability of tools of apple genomics, transcriptomics, metabolomics, and other omics technologies, the field of apple nutraceutomics is a new frontier that is gaining stronger interest by apple geneticists, nutritionists, and health professionals (Korban 2021; Kidoń and Grabowska 2021; Li et al. 2020; Nasir et al. 2020).

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Integrating Omic Tools to Design Nutraceutically Rich Citrus Bidisha Mondal

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Mechanism of Nutraceutical Production in Citrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chemistry of Major Bioactive Compounds Present in Citrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Flavonoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Carotenoids and Apocarotenoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Terpenes and Limonoids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Phenolic Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Coumarin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Citrus Genome and Phylogeny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Omics Understanding of Nutraceutical Production in Citrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Nutragenomics of Citrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Nutra-transcriptomics of Citrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Nutra-metabolomics of Citrus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Citrus Genome Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Nutraceutical Breeding for Designer Food Development in Citrus . . . . . . . . . . . . . . . . . . . . . . . . 8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The world is facing a bipartite problem of malnutrition covering under-nutrition as well as over-nutrition. This situation is an outcome of imbalance in financial capability and inequality in food distribution. The intake of diverse nutraceutical compounds could assist in overcoming the health problems and may provide additional protection to the human communities through generation of substantial antimicrobial and antioxidant properties. The tropical and subtropical fruits and vegetables are rich source of multiple bioactive compounds and are regarded as therapeutic storehouse. In majority of the countries, the fruit by-products and B. Mondal (*) Department of Genetics and Plant Breeding, The School of Agriculture and Allied Sciences, The Neotia University, Sarisha, West Bengal, India e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_35

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wastes lead to a complication of agro-waste disposal and management. The fruits, as a whole, are fascinating in production of bioactive elements. Citrus is a representative fruit having marked significance in food and fragrance sector. The nonedible parts, including peel, seed, fiber, and leaves, are potent source of health-promoting elements. The sequencing of the Citrus genome and available omics information could distinctly aid in the development of a nutraceutical database. In this chapter, the contemporary account on Citrus omics, encompassing genomics, transcriptomics, and metabolomics are critically evaluated for development of an array of sub-foods pertinent to food-omics division. The Citrus germplasm recourse and exploitable breeding strategies available till date could build a designer Neutri-Citrus appropriate for the prospering nutraceutical sector. This futuristic strategy of utilization of Citrus fruit waste and by-products in phyto-pharmaceutical industry may simultaneously encourage global agro-waste reduction and emerge as a new model contributing to circular economy. Keywords

Citrus · Omics-tools · Nutraceutical · Germplasm · Designer food · Agro-waste · Circular economy

1

Introduction

Nutraceuticals are natural dietary components found in food having health benefit and disease-fighting property. Nutraceuticals exhibit a boundary between food and drug and could be exploited to ameliorate health, slow down senescence, and maintain proper functioning of human body. A broad functional classification of nutraceuticals includes two types: potential nutraceutical and established nutraceutical. A prospective sub-food could be considered as a potential nutraceutical and could be elevated to an established designer food subject to qualifying certain clinical trials. In current time, GRAS (generally recognized as safe) status of nutraceuticals is essential for the quality assurance of products. The common food sources used as nutraceuticals are covered under multiple categories. The dietary fiber, probiotics, and prebiotics contain elements for improvement of gut health. Polyunsaturated fatty acids (PUFAs), polyphenols, antioxidants, vitamins, and spices form a category with capacity of fighting free radical led damages (Das et al. 2012). Plants harbor bioactive compounds with health benefits beyond the basic nutritional values in the form of secondary metabolites. On the basis of chemical structure and function, the common secondary metabolites available in foods could be grouped as phytosterols, phytoestrogen, carnitine, and choline with direct cellular and tissuespecific activities. Carotenoids, dithiolthiones, flavonoids, polyphenols, glucosinolates, and taurine are equally potent modulators of physiological processes (RodríguezCasado 2014). Fruits and vegetables with diverse colors are quintessential source of an array of nutraceuticals. The classical examples are grape (Vitis vinifera), watermelon

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(Citrullus lanatus), and banana (Musa spp.). Fruits like bael (Aegle marmelos), pomegranate (Punica granatum), amla-Indian gooseberry (Phyllanthus emblica), cranberry (Vaccinium spp.), orange (Citrus sinensis), and lemon (Citrus limon) are wellestablished sources of nutraceuticals (Dutta et al. 2017). Citrus fruits including orange, bergamots (Citrus bergamia), lemon, and grapefruit (Citrus x paradisi) are rich in bioactive compounds. The tropical and subtropical fruits are considered as therapeutic storehouse. The pharmaceutical and nutraceutical components present in fruits protect human from several diseases, increases life expectancy and reduces stress. The fruit peel, seeds, and by-products from food processing units serve as potential source of multiple bioactive compounds. These waste products could be utilized for extraction and valorization of nutraceuticals that strengthen the field of circular economy and aid in environmental waste mitigation (Fig. 1). The phytochemistry of Citrus fruits and their by-products has gained importance in nutraceutical industry due to its impact on human health and contribution toward nutragenomics. The human gene expression, transcriptomic modulation, and protein turn-over could be regulated by Citrus bioactive compounds. In specific instances, the expression of COX2, microsomal cytochrome P450 A1, and NF-kB genes were guided by hesperidin, naringenin, and hesperetin, nutraceuticals that are present in Citrus. Evidence reveals that Citrus flavonoids have a regulatory effect on gene expression by coding of low-density lipoprotein receptors (LDLR). Citrus essential oil is also well known for food preservation with substantial antimicrobial, flavoring, and antioxidant properties (Mahato et al. 2018). The Citrus peel powder possesses free radical scavenging activity and could replace synthetic preservatives in the market in near future (Khan et al. 2021).

Fig. 1 Citrus fruits collected from Manipur, India (C. latipes, C. medica, C aurantifolia)

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Mechanism of Nutraceutical Production in Citrus

The qualitative and quantitative variation in bioactive compounds produced in vegetatively grown plants bears epigenetic regulation. The plant genome controls production of the expected phyto-constituents, but epigenomic events change the ultimate phenotypic imagery of the genotype. Parental imprinting and epi-alleles could affect developmental switches leading to gene silencing or over-expression in some natural ecotypes, producing variants. In clonally propagated plants, the recovery of somaclones is possible due to reprogramming of the somatic embryos, carrying similar genetic architecture as sib-plants. The movement of diffusible epigenetic signals through plasmodesmata and vascular systems as well as parasites from one part to another conceivably regulates the fitness of a plant. The season, ecology, and light intensity might regulate clonally propagated plant to a larger extent than its sexually grown complements (Pikaard and Scheid 2014). Several exogenous as well as endogenous stimuli determine the survival and nutraceutical production of various genotypes (Fig. 2). The by-products of the Citrus industry are of immense economic value. The red orange of Sicily (known as blood orange) is a reservoir of significant amount of biologically active compounds (limonoids and flavonoids). The decanted pulps were the most abundant source of highest amount of flavonoids (130 g/kg) and a high amount of limonoids (5.5 g/kg) earning the protected geographic indication (PGI) for the cultivar. In Citrus, seeds are the best source of limonoids with about 10 g/kg of expression. Low amount of anthocyanins were found only in coarse pulps and waste water of red oranges (Russo et al. 2021). Bergamot (Citrus bergamia Risso) contains limonoids in abundance in seeds and peels (70% and 80% of the total, respectively), while limonoid glucosides are more abundant in juices and pulps

Fig. 2 Major bioactive components present in Citrus peel essential oil

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(61% and 76% of the total, respectively). The limonoids are related to microbial disintegration and free radical scavenging activity (Russo et al. 2016). C. sinensis commonly called ‘Ovale Calabrese’ grows profusely in the south of Italy (Calabria region). Due to the richness of flavonoids and limonoids and high content of phenolic compounds, in particular hesperidin in the pastazzo, the fruits could be utilized for the valorization of the by-product for the development of a novel functional ingredient (Celano et al. 2019). The lemon leaf essential oil (EO) is rich in oxygenated monoterpenes, accounting over 48% of the extracted oil. The most abundant constituent of the oil is a terpenoid identified as neryl acetate (15.3%). Geranyl acetate is a monoterpenoid and its alcohol nerol and geraniol are involved in the generation of the characteristic lemon aroma. The sesquiterpene hydrocarbons fraction in the EO was represented by β-caryophyllene representing the second most quantitatively important chemical class of compounds. Traces of β-bisabolene and bicyclogermacrene were detected in lemon EO. Principle monoterpene hydrocarbons limonene and β-pinene along with spathulenol and caryophyllene oxide, the oxygenated sesquiterpenes were found to be a possible contributor in the lemon EO. The essential oil composition of lemon leaves exhibits great variability in onto-genetics. Leaves of lemon specimens from the Mediterranean region were mainly rich in limonene with the aldehydes and acetic esters of both nerol and geraniol (Vekiari et al. 2002), while the composition of Indian lemon leaf EO exhibits the presence of (Z)-sabinene hydrate, geraniol, with a trace of α-pinene (Pal et al. 2016). The Iranian lemon oil is predominated by linalool, followed by a substantial representation of geraniol, α-terpineol, as well as linalyl acetate (Hojjati and Barzegar 2017). The geographical origin of the genotypes plays an instrumental role in the composition of the essential oil (EO) extracted from the Citrus peel. The orange leaf essential oil was mainly dominated by oxygenated monoterpenes. The most prevalent component for this class was linalool. The acetic ester of linalool, α-terpineol, geranyl, and neryl acetate was associated with the signature aroma of the fruit. Myrcene, β-ocimene, and β-pinene belonging to monoterpene hydrocarbons were another related chemical class of volatiles found in orange fruits. The metabolic profile of oranges expresses differential outcomes subject to growth conditions and nurturing. The essential oil profile of different Citrus accessions under orange is consistent with the literature report presented earlier (Sanmartin et al. 2019). The leaf essential oil of endemic species of Australia reveals significant variation in oil content. While C. australasica produced oil is predominated by bicyclogermacrene, germacrene-D, δ-elemene, and limonene, the other promising species, C. australis oil shows major share of α-pinene. The oil from another species, C. garrawayi, shows two distinct components, α-pinene and β-caryophyllene, belonging to monoterpene group. C. glauca contains α and β-pinene in contrast to C gracilis with γ-terpinene as major contributor. Another species, C. inogora, contains germacrene D as principal constituent. The wide variation of component availability is a comprehensible reflection of disparate epigenetic control of the same pathway (Brophy et al. 2001). C. aurantifolia leaf and peel essential oil was characterized by 49 constituents (93.6% of the total oil), in which the dominant components were the monoterpene hydrocarbon limonene, β-pinene, γ-terpinene, and β-myrcene. C. aurantium

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essential oil displays 15 components, with limonene as the major monoterpene hydrocarbon with successors β-myrcene and α-pinene. The oil has minor fractions of linalool and linalyl acetate, representing the oxygenated monoterpenes (Tundis et al. 2012). The oil profile of both the above-mentioned species could be utilized as natural anti-oxidants and could prevent an array of neurodegenerative diseases and aging. Bioactive compounds naturally occur in our surrounding plants, but in trace quantities. Epidemiological studies indicate that intake of bioactive food increases gastrointestinal ecology, immunity, reduces risk of cancer, diabetes, heart diseases, Alzheimer’s disease, stroke, cataract, cytotoxicity, and even age-induced senescence (Saini et al. 2022). Additionally, energy boosting, wound recovery, and beauty retention are also ensured by nutraceuticals (Table 1). Limonoids exhibit antimicrobial and anticancer activities and is a recognized human health promoter with manifold pharmacological properties and potential (Brito et al. 2014).

3

Chemistry of Major Bioactive Compounds Present in Citrus

3.1

Flavonoids

Flavonoids are found in all parts of plants and form a class of polyphenolic secondary metabolites. Flavonoids contain a 15-carbon framework (C6-C3-C6). Two hexa-carbon phenyl rings form a heterocyclic ring with embedded oxygen. A variety of modifications in the heterocyclic ring of flavonoid generates several subgroups. The naringin, eriocitrin, hesperidin, and narirutin constitute flavanone group, while flavones were categorized into rhoifolin, vitexin, and diosmin. Polymethoxylated flavones with natural antioxidant property cover nobiletin, tangeritin, and 5-demethyl nobiletin. Flavonols, the colorless secondary metabolites housing kaempferol, quercetin, and rutin, are recognized developmental regulators and signaling receptors. The colorful pigment anthocyanin present inside vacuolar compartments provides numerous health benefits to humans. The anthocyanin covers the cyanidin and peonidin glucosides (Testai and Calderone 2017; Saini et al. 2022). Plant defense, cell signaling, and repair from UV associated damages were mainly regulated by the flavonoid group of bioactives.

3.2

Carotenoids and Apocarotenoids

Carotenoids are a universal accessory isoprenoid pigments involved in carbon fixation and signaling pathways. Pigment carotenoid produces two subgroups: carotenes and xanthophylls. The hydrocarbon carotenoids α-carotene, β-carotene, and lycopene act as immune-activator. While xanthophylls, the oxygenated derivatives of hydrocarbon carotenoids represented by neoxanthin, violaxanthin, lutein, and β-cryptoxanthin, were accepted as anti-phototoxic agents (Saini and Keum 2018). Apocarotenoid is

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Table 1 Health benefit related to consumption of diverse Citrus fruit species S. No 1.

Plant part Peels

Species Citrus maxima

Medical application Diabetes, hypertension

2. 3.

Citrus sinensis Citrus limetta

Lung cancer Wound healing

Citrus paradisi Citrus aurantifolia Citrus latifolia

Anti-inflammatory Diabetes mellitus

6.

Rind Sweet lime Peel Fruit extract Peel, pulp

7. 8.

Pulp Peel oil

Citrus grandis Citrus jambhiri

9. 10. 11.

Peel Peel, pulp Peel

12.

Plant extract Fruit

Citrus unshui Citrus medica Citrus aurantium Citrus limon

Colorectal, breast cancer Anti-ulcer, antinociceptive Edema, capillary leakage Anticatarrhal, analgesic Cellulite reduction

4. 5.

13. 14. 15.

Rind extract Leaf oil

16.

Fruit

17. 18. 19.

Leaf oil Fruit oil Leaf oil

20.

Leaf oil

21.

Rind oil

22.

Seed

Citrus latipes Citrus hystrix Citrus limonimedica Citrus clementina Citrus reshni Citrus bergamia Citrus australasica Citrus glauca Citrus ichangensis Citrus junos

Antibacterial activity

Pneumonia, skin disorder Antioxidant, UV absorber Alzheimer’s disease

Reference Oboh and Ademosun (2011) Xiao et al. (2009) Harsha und Aarti (2015) Eneke et al. (2021) Silalahi (2002) Medina-Torres et al. (2019) Tocmo et al. (2020) Babarinde et al. (2021) Tsitsagi et al. (2018) Chhikara et al. (2018) Jabri and Marzouk (2013) Shaikh et al. (2022) Rao et al. (2021) Siti et al. (2022)

Anticancer

Lota et al. (1999)

Antidiabetic, antioxidant

Loizzo et al. (2018)

Anti-inflammatory Urinary tract infection Anticancer, foot skin disorder Antibacterial, antileukemic Anticholesterol, anticancer Antitumor

Hamdan et al. (2013) Navarra et al. (2015) Wang et al. (2019) Scora and Ahmed (1995) Herman et al. (1989) Shon and Park (2006)

another category of pigment detected in Citrus with distinctive role in signaling and growth regulation. The origin of apocarotenoids is subject to cleavage of dioxygenase. The eco-nutritional variation of apocarotenoid is an important factor for its acceptance as a functional food. In Citrus, both β-cryptoxanthin and zeaxanthin could be the probable progenitor of β-citraurin, and the process witnesses an asymmetric cleavage of the progenitor (Luan et al. 2020).

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Terpenes and Limonoids

The monoterpene hydrocarbons consist of two isoprene components and cover several subtypes. The oxygenated monoterpenes (nonanal, geranial, and neral) are known as fragrant. Terpene alcohols are olfactory markers segregated into linalool, verbenol, geraniol, carveol, and α-terpineol. Sesquiterpenes with 15 carbon and 3 isoprene units are the major chemical constituents of the volatile fractions of Citrus essential oil (Raspo et al. 2020). The total terpenoids expressed in mandarin, tangerine, grapefruit, orange, citron, and lemon essential oil were preferentially dominated by a monoterpene D-limonene. An interesting study reveals that green mandarin contains fourfold higher limonin, a tetracyclic triterpenoidin much higher amount than its yellow and red complements. Montenegrin mandarin, essential oil has γ-terpinene as a major fraction with the minor presence of citronellol, an acyclic monoterpenoid, and terpene alcohol (Rossi et al. 2020). This sparse presence of these trace signatory components favored the antioxidant activity with a property of significant decrease of cytotoxicity inside colorectal cancer HT-29 cells.

3.4

Phenolic Acids

In a study involving kinnow mandarin clearly stated the percentage of solvent in determination of final recovery of the peel extracts or peel essential oil. Among the phenolic compounds, ferulic acid and hydroxycinnamic acid were recovered with remarkable antiaging properties. Hesperidin, a flavone glycoside, was also abundant in kinnow mandarin peel extracts. A tri-hydroxybenzoic acid, gallic acid, and catechin, a poly-phenol compounds were found to remain present in high concentration in kinnow type mandarin. Trace quantities of caffeic acid, a methylxanthine, and naringenin, a flavanone, were recovered from the peel extract with anti-carcinogenic and immune-stimulant activity (Safdar et al. 2017).

3.5

Coumarin

Five coumarins and 21 fucocoumarin compounds are widely present in Citrus species. The compounds are rich in dimethylallylated and/or geranylated compounds such as bergamottin, aurapten, or imperatorin. The coumarin compounds exhibit multiple applications in skin diseases with antiviral and anticancer properties. Citrus roots are storehouse of some novel coumarins. Peroxytamarin, with antibacterial property along with cis-casegravol having antiproliferative properties were detected as major constituents. Lignan glycoside, citrusarin-A, and citrusarinB were present in root of Citrus plants. These polycyclic compounds possess organoleptic properties with prominence as satisfactory odor and flavor agents (Ito et al. 1991).

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Citrus Genome and Phylogeny

Citrus is a diploid genus with 18 chromosomes and a genome size ranging from 265 to 407 Mb. In Citrus spp., a spectrum of research has been done on germplasm characterization and management. The Sino-Indian border area is regarded as a unique germplasm conservation center of Citrus. Citrus group contains multiple species qualifying as scions (commercial varieties) and several rootstocks (wild types). The novel Citrus fruit types of South Asia displays diverse species, including C. reticulata, C. sinensis, C. aurantifolia, Citrus indica, Citrus limon, C. aurantium, C. maxima, C. medica, C. limetta, C. latipes, C. jambhiri, and C. hystrix (Mondal 2021). These huge ecotypic resources could act as reservoir for a number of important bioactive compounds that could play a crucial role in Indian nutraceuticals industry. The North Eastern hilly region evinces C. indica, C. assamensis, C. macroptera, C. latipes, C. ichangensis, C. micrantha, C. medica, Fortunella margarita, F. crassifolia, F. japonica, and Poncirus trifoliata. The analysis of the pulp, peel, and seed of this gigantic germplasm reservoir, predominantly the wild types, could manufacture unique compounds with prospects in the medicinal and pharmaceutical sectors. In Chinese wild mandarin Mangshanju (Citrus reticulata Blanco), a total of 81 compounds were identified, including flavonoid glycosides, acylated flavonoid glycosides, flavones, polymethoxylated flavonoids, and limonoids, as well as four other compounds. The Citrus wild germplasm reserves are the automatic store house of nutraceuticals, and a thorough characterization of the constituents could yield an optimum product for the industry. The wild plant produces 22 polymethoxylated flavones and 10 polymethoxylated flavanones/chalcones in excess in comparison to its commercially propagated counterpart (Zhao et al. 2018). Ancient Indian Citrus species, pummelo (Citrus grandis L. Osbeck) harbors naringin as the predominant flavonoids irrespective of genotypes. Some selections are particularly high in naringin, and others seem promising for lycopene and phenols. Other phenolics quantified in the juice included caffeic, epicatechin, benzoic acid, neoeriocitrin, hesperidin, and narirutin. The examples cited above present the importance of germplasm characterization. The proper characterization of the wide and rich gene-pool with a nutraceutical inventory of elite cultivars could possibly assist Citrus nutraceuticals breeding program (Nishad et al. 2018).

5

Omics Understanding of Nutraceutical Production in Citrus

The omics tapestry of living organisms presents the most mysterious and interesting field of molecular research. The response of a plant genome to external stresses and the successive cellular homoeostasis are regulated by the genic and inter-genic territories of the genome. In metabolic discovery, the natural variation within the species provides significant insight into nutraceuticals production. The multiple genomic identities of Citrus, including the wild and cultivated types, influence a

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range of traits covering plant defense and commercially important attributes. Due to simultaneous occurrence of natural hybridization and vegetative propagation in citrus, the mode of inheritance of metabolite production becomes complex. Most of the biosynthetic pathways leading to identification of numerous bioactive compounds mainly follow non-Mendelian inheritance. The mQTL mapping technique unravels novel genes with intense epigenetic and environmental influence in synthesis of diverse end-products. The analysis and integration of various omics tools will assist in achieving futuristic goals in Citrus nutra-omics.

5.1

Nutragenomics of Citrus

In Citrus, the multidrug and toxic compound extrusion (MATE) gene plays a valuable role in flavonoids and citrate metabolism in fruits and is involved in numerous allied physiological processes. The MATE proteins are a class of secondary active multidrug transporters. In Citrus clementina, a total of 69 MATE transporters were classified on the basis of phylogeny. Tandem and segmental duplication events were the main causes of the Citrus MATE family expansion. RNA sequencing and qRT-PCR operations in different fruit developmental stages revealed that CitMATE gene expression is regulated by tissue diversity and a specific developmental stage. CitMATE43 and CitMATE66 are involved in the transport process of flavonoids and citrate in Citrus fruit, and additionally CitERF32 and CitERF33 are related to activation of CitMATE43 promoter (Liu et al. 2022a). In a research involving the large family of plant polyphenolic secondary metabolites, it has been expressed that transgenic plants could be developed with a high production capacity for bioactive compounds. A model transgenic tomato developed with structural flavonoid genes (encoding stilbene synthase, chalcone synthase, chalcone reductase, chalcone isomerase, and flavone synthase) from different plant sources was able to produce novel nutraceuticals. Biochemical analysis showed that the tomato peel contained high levels of stilbenes (resveratrol and piceid), deoxychalcones (butein and isoliquiritigenin), flavones (luteolin-7-glucoside and luteolin aglycon), and flavonols (quercetin glycosides and kaempferol glycosides). The study involving genetic engineering of flavonoids in tomato fruit demonstrated the prospects of developing tailor-made Citrus crops with high level of plant nutrients (Abeynayake et al. 2012). In a research involving the identification of major limonoid-producing gene in Citrus, P450s (CYP450s), MYB, and CiOSC genes were found to play a ubiquitous role in limonoid biosynthesis. The leaves, phloem, and seeds of pummelo (Citrus grandis L. Osbeck) express variations in limonoids’ contents at different development stages. Digital gene expression profiling identified 382 putative genes from 3 conjunctive groups related to the biosynthesis of limonoids. Repetitive correlation analysis with the samples from different genotypes involving different developing tissues of the Citrus confirmed 15 candidate genes with high correlation with the contents of limonoids. The cytochrome P450s (CYP450s) and transcriptional factor MYB demonstrated significantly high correlation coefficients, validating the

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importance of those genes for the biosynthesis of limonoids. CiOSC gene encoding the critical enzyme oxidosqualene cyclase (OSC) for biosynthesis of the precursor of tri-terpene scaffolds was responsible for limonoids production in seeds. Suppressing the expression of CiOSC with VIGS (Virus-induced gene silencing) demonstrated that the level of gene silencing was significantly correlated to the reduction of limonoids contents (Wang et al. 2017). In Citrus cultivars, two vacuolar P-ATPase homologs, CitPH1 and CitPH5, are strongly induced in highly acidic species such as lime and lemon fruits. The level of expression of these two genes is significantly reduced in acidless mutants. The cellular pH gradient is maintained by vacuolar ATPases with an array of genes: CitPH1, CitPH5, PH3 (WRKY), PH4 (MYB), and basic helix-loop-helix (bHLH). Citrus Noemi (CitAN1) transcription factors were less expressed or reduced in the mutants (Butelli et al. 2019). Homologs of PH4, which is a MYB transcription factor, have been reported to activate the promoter of the proton pumps (PH1 and PH5) in Citrus. A pleiotropic gene Noemi (CitAN1) regulates both acidless phenotypes and loss of proanthocyanidin and anthocyanin in sweet lime, citron, sweet orange, lemon, and limetta accessions. A variation in the core promoter region of the Noemi gene in two limetta accessions reduces gene expression and increases the pH of the juice, indicating Noemi as a vital gene contributing to fruit acidity. Recent studies showed that a specific mutation in CitAN1 is responsible for the reduced expression of CitPH1 and CitPH5 in acidless lemon and other acidless Citrus fruits (Strazzer et al. 2019). A complex formed of WD40-repeat proteins, MYB, bHLH, and WRKY transcription factors known as WMBW in short plays a significant role in the operation of three anthocyanin pathways. Ruby2 and Ruby1 genes belonging to a cluster function as anthocyanin activators, but Ruby2 operates in tender leaves and Ruby1 functions preferentially in fruits. The reduction or loss of anthocyanins may be due to the hitchhiking effect of fruit acidity selection in some domesticated types. A mutant gene, AN1, is a common regulator for both citric acid and anthocyanin metabolism, playing a regulatory role in fruit acidity and pigment production (Rao et al. 2021). The National Centre for Biotechnology Information (NCBI) reveals enormous data on Citrus, categorized under 20 databases. The Citrus literature is covered under 42 bookshelves with 6 NML catalog, 2407 Pubmed, 17,780 Pubmed central information (Table 2). The data available in NCBI exhibits 110,766 terpinene, 382 limonoid, 259 alcohol dehydrogenase, 162 flavonoid, 32 limonene, 22 γ-terpinene, 67 coumarin, 60 chalcone synthase, 48 geraniol, 28 carotenoid, 8 citronellol, 7 citral, 7 quercetin, 6 trans-citral, 5 cis-citral, 5 naringenin, 3 anthocyanin gene, and 2 kaempferol associated genes in Citrus genera (NCBI 1988). These potential candidate genes could be utilized for qualitative as well as quantitative improvement of bioactive accumulation in pulp, peel, and seeds of Citrus.

5.2

Nutra-transcriptomics of Citrus

The accurate comprehension of the biosynthetic pathway is essential for commercial metabolite production. Transcriptomic data-mining is an efficient tool for

910 Table 2 Citrusomics and related databases present in NCBI platform

B. Mondal

Citrus (taxonomy ID: 2706) Name of the database Domain: genome Genome Assembly Taxonomy Nucleotide Bio-collection SRA Domain: gene Gene Geo-data set Pop-set Domain: protein Protein Protein family model Conserved domains Identical protein groups Structure Domain: pathways Pathways Substances Bioassays Compounds Domain: clinical Clinical trials.gov dbGaP MedGen OMIM

Reported information 28 76 1 1,230,115 3 13,928 110,766 2316 2365 1,299,325 13 11 352,797 59 1320 360 640 14 191 5 2 1

identification of gene families involved in certain metabolite production. In non-model plant species, a transcriptomic approach could accelerate genomic investigation. Transcriptomic analysis could efficiently identify the genetic and epigenetic factors underlying the expression of diverse bioactive compounds present in various plant species and the interplay of gene and environment influencing distinct pathways. A study involving the transcriptomic profiling of two varieties of Citrus reticulata expressed differences in the storage of bioactive compounds. Transcriptomic profiling of Citrus reticulata ‘Huajuhong’ (HJH) and C. reticulata ‘Sanhuhongju’ (SHHJ) reveals differences in the distinct level of bioactive ingredients in fruit peels. The total flavonoid in HJH peels was significantly higher than that in SHHJ. Messenger RNA (m-RNA) sequencing identified 203 differentially accumulated metabolites (DAMs) and 3517 differentially expressed genes (DEGs). Among the DAMs, the major components were flavonoids (104, 51.2%), followed by phenolic acids (30, 14.7%). KEGG enrichment analysis indicated the over-

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expression of the flavonoid pathway. Ten glucosyl transferase genes regulated the accumulation of seven of the top ten flavonoid glycosides in HJH (Yu et al. 2022). Collectively, the higher content of flavonoid glycosides in HJH peels than SHHJ might contribute to the distinct health-promoting effect of the former and confirms its possible selection for integration in nutraceutical extraction. In a similar transcriptomics study conducted by a group of scientists involving blood orange (Citrus sinensis cv. ‘Tarocco’) showed significant effects of diverse exogenous treatments in regulation of internal qualities of the fruit. Bagging has been widely used in fruit crops to improve fruit quality, but the result showed that bagging treatment has a significant effect on fruit quality. The treatment led to increase in total flavonoid (TFL) and total anthocyanin (TAN) concentrations, while total soluble solids (TSS), total phenolics (TPH), ascorbic acid (AsA) concentrations, and titratable acidity (TA) decreased in response to the bagging treatment. The high-throughput tag-sequencing (Tag-seq) analysis detected over 21
106 clean reads per library. Approximately 53.7–71.7% genic and 3.1–6.4% of intergenic clean reads were mapped onto Citrus genomic regions, respectively. About 25.2–39.9% of the clean reads failed to align with the Citrus genome. Overall, bagging treatment resulted in an increase in transcripts involved in a range of metabolic pathways rather than anabolic pathways. The tricarboxylic acid (TCA) cycle, sucrose and starch metabolism, ascorbate metabolism, and the phenylpropanoid pathway got affected through the treatment. Competition for limited amounts of substrates for the flavonoid, phenolics, and anthocyanin pathways may have led to an increase in total anthocyanins (TAN) and total flavonoid (TFL) concentrations under a variety of stresses on fruits. The gene, bHLH is involved in anthocyanin biosynthesis in blood orange fruit and was identified as a key player in controlling the genetic mechanisms operating in Citrus fruit in response to a bagging treatment (Sun et al. 2014). In another, transcriptomic study on cold-induced response of Citrus paradisie confirms that low temperature exposure induces the elevation in the anthocyanin levels in the orange flesh. This enhancement being modulated by the transcriptional stimulation of the genes involved in the anthocyanin biosynthesis. The RNA profiling and subsequent construction of expressed sequence tag (EST) collection revealed NAC family of gene plays a vital role in the abiotic stress response. An EST, encoding the BRD4 bromodomain, a DNA-binding protein belonging to an extensive family of evolutionarily conserved protein originally remain associated with chromatin activity. This BRD4 plays a pivotal role in chromatin remodeling and transcriptional activation. Similarly, another gene, glutathione transferase (Tau2), previously identified in the leaves of blood oranges, ensures ROS scavenging activity. The storage temperature as well as the exposure tenure turned out to be critical for pigment development in flesh tissue. Though prolonged cold storage for more than 3 months, negatively influences the sensory quality of oranges due to the increase of the malodorous substance vinylphenol, whereas the standard fruit quality parameters (total soluble solids (TSS), total acidity (TA), and maturity index TSS/TA) remained unchanged between cold treated and control samples (Crifò et al. 2011).

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In accessions of citron, limetta, sweet lime, lemon, and sweet orange, the acid-less phenotype is associated with large deletions or insertions of retro-transposons in the Noemi gene. In two accessions of limetta, a change in the core promoter region of Noemi is associated with reduced expression and increased pH of juice, indicating that Noemi is a major determinant of fruit acidity. Noemi in turn encodes a basic helix-loophelix (bHLH) transcription factor and which controls flavonoid production as well as fruit acidity. A parallel research with 33 Citrus varieties completely unable to produce anthocyanins further reveals that acidless varieties containing functional alleles of Ruby, a key regulatory MYB gene, is essential for anthocyanin production. The two previous investigation show that both bHLH and Ruby are required for anthocyanins production. Mutation in any of the genes may affect pigmentation. Noemi encodes the bHLH protein that interacts with Ruby to control anthocyanin production in Citrus. Noemi and Ruby are both pleiotropic genes and play a regulatory role in anthocyanin production and fruit acidity (Butelli et al. 2019). The biologists are searching for natural resistance in plants that could be a significant defense weapon for controlling biotic stresses in an environmental sustainable manner. A functional genomics approach employing cDNA microarrays with pathogen-infested flavedo tissue of Citrus fruits detected upregulation of few genes. The most highly induced genes were related to the phenylpropanoid pathway, engrossing 29 most up-regulated genes in the flavedo. Out of the 20 genes, 13 were involved in either phenylpropanoid metabolism or coumarin biosynthesis, including 7 different O-methyltransferases, isoflavone reductase, hydroxycinnamoyl transferase, 2 leucoanthocyanidin dioxygenases, and 2 SRG1 proteins. Genes related to methionine and ethylene biosynthetic processes, such as 1-aminocyclopropane-1carboxylic acid oxidase (ACO) and proteins related to defense and response to stress were also induced in the flavedo. EFE and CsACO genes were over-expressed in tissues with direct affinity to ethylene production (Ballester et al. 2011). The multiple examples presented in previous paragraphs unravels that transcriptome sequencing in plant is an efficient way of mining of functional genes, development of genomic markers, detection of discriminatory secondary metabolites, and analysis of related pathways (Guo et al. 2020). The advantage of RNA sequencing is that it provides distinctly different results owing to diverse developmental stages and tissues. Moreover, differential expression of genetic and epigenetic factors may be precisely estimated to provide information on diverse nutraceuticals production in Citrus and its valorization for industrial utilization (Table 3).

5.3

Nutra-metabolomics of Citrus

The quality of the Citrus fruit is directly related to the metabolic profile expressed by the plant. The primary and secondary metabolite deposition regulates the quality, taste, color, texture, flavor, appearance, and most importantly, the disease prevention property of the fruit. The color differences between Citrus varieties were associated with the carotenoid content. The Citrus color Index (CCI) value shows a significant positive correlation with the carotenoid content. Carotenoids are indispensable

S. No 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.

LOC102630581 LOC102608560 LOC112098231 LOC112100835 LOC102607309 Cstps1 LOC112101189 LOC102625110 CtgOMT1 LOC102578043 LOC18044720 LOC102578043 LOC102617171

Gene ID LOC102619013

Gene AN1 (bHLH), AN2 (MYB), and AN11 (WD-repeat) CsMADS6 Limonoid UDP-glucosyltransferase F-box protein SKIP23-like Zeta-carotene desaturase Flavonoid 30 ,50 -hydroxylase-like Chalcone synthase Sesquiterpene synthase Coumarin 8-geranyltransferase 1b Solanesyl diphosphate synthase 3 O-methyltransferase (OMT) Citrus sucrose transporter 1 Squamosa promoter-binding-like protein 2 Citrus sucrose transporter 1 Fluoride export protein 2

Table 3 Important genes regulating nutraceutical production in Citrus Nutraceutical Anthocyanin Carotenoid Limonoid Ascorbic acid Carotene development Flavonoid Flavonoid Citral Coumarin Limonene Polymethoxyflavones Tangeritin Clementine Kutenone Camphor

Source Blood orange Sweet orange Sweet orange Sweet orange Clementine Clementine Sweet orange Sweet orange Clementine Clementine Citrus grandis Sweet orange Citrus clementina Sweet orange Sweet orange

Reference Butelli et al. (2012) Lu et al. (2018) Jia et al. (2019) Pillitteri et al. 2004 Terol et al. 2019 Itoh et al. 2016 Wan et al. 2022 Sharon-Asa et al. 2003 Zhu et al. 2022 Liu et al. 2020 Xian et al. 2022 Rooprai et al. 2021 Zeng et al. 2019 Hussain et al. 2020 Li et al. 2021

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molecules, providing protection against free radicals and oxidative stress (Zheng et al. 2019). Among organic acids, citric acid was the main organic acid found in Citrus flesh, followed by malic acid, acetic acid, and vitamin C. In a study of Korean Citrus varieties, significant variation was noticed among the local fruits (Hussain et al. 2017) with respect to acid content. Jeramon citrus showed the highest citric acid (482 mg/g DM) and malic acid content (60 mg/g DM), which were more or less 7–17 times and 2–9 times higher, respectively, than the other Korean varieties. Jeramon variety was developed from the nucellar embryo of a lemon plant, which excessively accumulates citric acid during fruit development. Kanpei (28 mg/g DM) and Natsumi (15 mg/g DM) had the lowest citric acid contents, while the lowest malic acid content was observed in Satsuma mandarin, Navel orange, Kanpei, and Setoka (approximately 6–8 mg/g DM). Setoka and Kanpei had the highest acetic acid content (about 6 mg/g DM), and the acetic acid content of the other varieties was approximately 2–4.8 mg/g DM. In particular, a high content of vitamin C, which has the strongest antioxidant activity in Citrus, was observed in Setoka (5.1 mg/g DM) and Jeramon (4.3 mg/g DM). These phenotypic and biochemical examinations provide a ground data for selection of germplasms and incorporation of the same for genomic and transcriptomic analysis, leading to the tracking of relevant biochemical pathways (Kim et al. 2021). The ratio of sugar content and organic acids is the main determinant of the maturity and core taste parameters in Citrus fruits. The sugar content and organic acid show a negative correlation, and the acid content declines during fruit development, resulting in a sweet taste in Citrus fruits (Smirnoff 2018). A very interesting study elucidated the relationships between Citrus genotypes, diet, and health requirements of human subjects. Urinary metabolomic profile for volunteers identified proline betaine and flavanone glucuronides as known biomarkers, irrespective of Citrus genotypes. The study by the French research group revealed two strong discriminates identified as limonene 531 8,9-diol glucuronide and nootkatone 13,14-diol glucuronide belonging to terpene metabolite family in addition to standard markers (Pujos-Guillot et al. 2013). The unique study involving human subjects has thrown light on the recovery of nutritional biomarkers for accurate dietary assessment. Metabolome profiling could be a method to detect adulteration in fruit processing industry. The maintenance of the authenticity of food products is essential for export business. The compliance of end-products of our food industry with the international standard may lead to economic gain for the overall agro-business sector. Targeted and untargeted metabolomics could be applied for qualitative classification of authentic and adulterated samples. According to the European Commission (2009), the addition of non-sweet orange (Citrus sinensis) to sweet orange juice is not allowed in the European Union countries. Codex Alimentarius guidelines state that up to 10% orange (Citrus reticulata) juice may be permitted in Citrus sinensis juice (Codex Alimentarius Commission 1992), while the Food and Drug Administration (FDA) permits the addition of 10% Citrus sinensis to pasteurized and canned orange juice, and up to 5% of Citrus aurantium to frozen concentrated orange juice. In proper operation of fruit industries, the assessment of adulteration is an important parameter. In this context, a scientific study led by the Indian food processing sector deserves mentioning.

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Kinnow mandarin (Citrus nobilis
Citrus deliciosa), Jaffa, Mosambi orange (Citrus sinensis), and red blush grapefruit (Citrus paradisi) were collected from the Indian Agriculture Research Institute (IARI) for assessment of the authenticity of randomly collected samples with the authentic collection. Untargeted methods of ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry were applied to identify characteristic markers that could potentially be used to control Citrus fruit authenticity. The most influential markers identified were: didymin, rhoifolin, isorhoifolin, neohesperidin, hesperidin, naringin, narirutin, limonin glucoside, and vicenin-2. A targeted liquid chromatography-tandem mass spectrometry method was then optimized for the application of the identified markers. Diverse ratios among the identified phyto-chemicals act as potential biomarker for the Citrus juice industry. The tested biomarkers were proved authentic, with a proven record of reduction in adultery down to 2%. The study prescribed an untargeted qualitative approach with Principal Component Analysis (PCA) as a validation method for possible discrimination between authentic and adulterated samples (Jandrić et al. 2017). These integrative omics studies could accelerate the growth of nutraceutical industry and authentic biomarking of the Citrus sub-foods. The peel and seed waste of Citrus could lead to the development of a new industry with a simultaneous reduction in the global load of agro-waste.

6

Citrus Genome Database

The draft genome sequences of some Citrus species were available in the genomic databases of the Citrus Annotation Project (CAP) 3 and Phytozome. The bulk data of reference genomes from Citrus re-sequencing projects were available for application in population genetics, including genome-wide association studies (GWAS), evolutionary studies, and comparative genomics (Table 4). The genomic variation assists in the discovery of key quantitative trait loci (QTLs), molecular genetic markers, and genes relevant to important traits and contributes to the understanding of the origin and evolutionary relationships in Citrus. CitGVD (http://citgvd.cric.cn/home), a comprehensive database of Citrus genomic variations that provides a publicly available and free data service for scientific studies includes large sets of data on genomic variations (SNPs and INDELs) compiled from two released reference genomes for Citrus clementina and Citrus grandis, including 84 phenotypes, gene functional annotations, and informative literature. CitGVD also provides in-depth analysis, including CitTRAIT for phenotypic data statistics, CitGWAS for GWASs based on built-in data, CitEVOL for genetic evolution analysis, PCR primer design, and Gbrowse for variations and genes (Li et al. 2020). Another Citrus Genome Database, known as CGD, is a USDA and NSF-funded resource that enables basic, translational, and applied research in Citrus (Dorrie and Sook 2018). It houses genomics, genetics, and breeding data for Citrus species. It is an open-source, generic database constructed on Tripal platform. The Citrus genome database contains 10 species: C. clementina, C. ichangensis, C. sinensis, C. reticulata, C. medica, C. Maxima, C. limon, C. trifoliate, Atalantia buxifolia,

Name Ploidy Chromosome number Genome size (Mb) Available marker Available map Available QTL Available MTL Available trait Available genome

C. sinensis Diploid 18 380 2191 3 673 0 229 –

C. reticulata Diploid 18 370 607 5 673 0 229 1

C. limon Diploid 18 312 7 0 673 0 229 1

Table 4 Brief genomic information of commercial Citrus species C. clementina Diploid 18 370 1968 3 673 0 229 1

C. ichangensis Diploid 18 391 0 0 673 0 229 –

C. maxima Diploid 18 380 8009 9 673 0 229 –

C. grandis Diploid 18 407 34 0 673 0 229 1

Poncirus Trifoliate Diploid 18 265 782 8 673 0 229 –

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Fig. 3 Canopy structure of Citrus reticulata plant taken in the orchards of Darjeeling, West Bengal, India

Fortunella hindsii, and three species of Ca. Liberibacter (Fig. 3). It contains 366,169 genes and 649,803 mRNAs, 25 genome assemblies, 2255 germplasm, 85 maps, 60,407 markers, 16,971 phenotypic measurements, 75 trait descriptors, 6997 publications, and 673 QTLs for 153 agronomic traits. Seven tools are available such as BLAST, CitrusCyc, JBrowse, BIMS, Map Viewer, Synteny Viewer, and Expression Heatmap in the database for in-depth study of citrus genomes. Another contemporary platform, CitSATdb (http://bioinfo.usu.edu/citSATdb/), mostly focuses on molecular markers mined from six Citrus species. The database is most useful for marker assisted selection and cisgenic improvement of Citrus. Recently, an updated genome information of Citrus sinensis (Wan et al. 2022) and 12 new sequenced genomes were integrated to provide an all-in-one database. The published Citrus genomes including Clementine, mandarin, pummelo, Mangshan wild mandarin, citron, Ichang papeda, kumquat, Trifoliate orange, and Chinese box orange were amalgamated to construct a more comprehensive database named the Citrus Pan-genome to Breeding Database (CPBD). CPBD presents large-scale datasets of Citrus transcriptomes, genome variations, and DNA methylomes as well as practical tools for Citrus breeding. In addition to omic data tool, some new datasets for CRISPR, KEGG/GO Enrichment, and GWAS are available in the CPBD platform (Liu et al. 2022b).

7

Nutraceutical Breeding for Designer Food Development in Citrus

In Citrus, several internal genetic complexities along with environment create hindrance in the improvement of different traits through breeding. The occurrence of heterozygosity, sexual reproduction, apomixis, polyploidy, juvenility, as well as recalcitrant seeds makes the breeding effort less productive. The majority of the Citrus plants are vegetatively propagated with preferential selection of the polyploid

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types for larger fruit size with smooth rind. The traditional Citrus breeding mostly depended on selection of new cultivars from wild germplasm reserve and their domestication and cultivation. In Citrus, most of the agriculturally important traits are polygenic in nature, and conventional breeding has developed very few cultivars and rootstocks till date (Fig. 4). The scarcity of monogenic traits in Citrus is responsible for the lack of improvement of commercial traits. It has been noticed that a product of hybridization is only producing apomictic seeds, often diluting the effect of hybridization. Traditional breeding sometimes produces a hybrid with weak zygotic embryo as a result of inbreeding depression through mating of near-isogenic parents. The vast juvenile stage of the plants makes Citrus breeding a more timeintensive, resource draining, and land-occupying venture. In Citrus, conventional breeding were applied in dichotomous way for the improvement of both scions and rootstocks. In selected cases, the application of mutation breeding is noticed with gamma rays and other chemical mutagens. In scion breeding, the new cultivars are developed through controlled crosses, and later the superior selections were grafted to compatible rootstocks. Natural hybridization, chance mutation, and Somaclonal variation have played major roles in cultivar development in Citrus. ‘Satsuma’ and ‘Clementine’ mandarins are outcomes of bud sport mutation. In grapefruit, a commercially acceptable cultivar, ‘Star Ruby’, was developed from ‘Hudson’ through irradiation. In Citrus, the long juvenile period was effectively utilized with a significant synergistic effect in the production of

Fig. 4 Multiple breeding techniques employed for improvement of Citrus Industry

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irradiated cultivars from growing scions. In sweet orange, lemon, and mandarin new varieties, ‘Zhongyu No 7’ (seedless), ‘Kutdiken lemon’ (resistant to mal secco), and ‘Tango’ (seedless) were developed respectively through the application of chemical mutagen in the juvenile stage of some scions. In scion breeding, there is a preference for monoembryonic species, inversely the rootstock propagation mostly depends on polyembryonic species, securing recovery of huge number of uniform plant-types. Root-stocks developed through inter-specific hybridization are found effective in disease resistance. Carrizo, Troyer Citranges, and Swingle Citrumelo were found to show resistance toward Phytophthora and nematode. Inter-specific hybrids between two species were found very effective for a third species. A hybrid between Citrus reticulata and Poncirus trifoliata was found exceptionally useful for Citrus sinensis. US-852, X639 are important representative of successful grafts involving three species. US early pride, UF Glow, Tango, Sugar belle, Roe tangerine, RBB7-34, Mandalate, Gold nugget, and Bingo, 950, 914 are commercially available varieties developed by the NVDMC, Citrus Research & Development Foundation (Gmitter et al. 2009). NRCC Mandarin Seedless-4, NRCC Acid Lime-7, NRCC Pummelo-5, NRCC Grapefruit-6, Cutter Valencia, Flame Grapefruit, US Pummelo-145, and Alemow were released by the Central Citrus Research Center, Nagpur, India, from the 552 indigenous and 62 core collections (Vi QRT Report-CCRI, 2018). In agriculture, molecular marker-assisted breeding plays an effective role in improvement of crop quality and productivity. The mainstream agriculture has provided food security to the majority of global population. In the present era, a metabolomics-driven breeding could pave a way for the development of customized designer Citrus using system biology tools. The cross-talk among different biochemical pathways could produce varied nutrient elements. Application of several stress situations alters the production of nutrients in plants utilizing the same pathway. The previous discussion illuminated the differential role of multiple putative genes and transcription factors in the production of the consumer-friendly end products. Though nutraceutical breeding is an emerging technique, but few examples are available that exhibit equivalence to this futuristic breeding approach. A study conducted on the influence of the rootstock in the production of bioactive compounds in the peels of a Mediterranean Citrus tree showed significant variation in the deposition of secondary compounds with respect to rootstock germplasm. Different rootstocks (Cleopatra mandarin and Troyer citrange) influenced the variable deposition of hesperidin and narirutin flavonoids. Flavanone glycosides, β-cryptoxanthin and violaxanthin, and limonene were the most abundant flavonoid, carotenoid, and limonoid identified in the peel essential oil of the grafted plants. The distinct difference in the content of bioactive compounds for the different groups of Citrus was in agreement with the taxonomic distinction of the rootstocks. The research highlighted that both mandarin and other hybrid orange varieties showed influence of the rootstocks in the deposition of a sizable amount of bioactive constituents, but the quantitative accumulation of individual nutrients were determined by the scion. This study concluded that different breeding programs with new rootstocks could yield conclusive outcomes for enhancement and production of desired nutraceutical according to the needs of the industry (Cano and Bermejo 2011).

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In another study, examining the influence of Citrus rootstocks (Carrizo citrange, C-35 citrange, and F-5) in bioactive compound production on Clementine scion revealed a complex interaction between the rootstock in critical production of bioactive compounds. The species reflects a particular flavanone glycoside pattern. Six flavonoids are detected in clementines cv. ‘Clemenrubí’ and ‘Orogrós’. The interaction between Orogrós cv and FA-5 rootstock presented the highest amounts of Api-6,8-di-C-glc, Nar-7-O-rut, and Hes-7-O-r flavonoids. Scion variety C-35 with citrange rootstock produced the heaviest and larger fruits, while the rootstock FA-5 produced the final reap with the major flavonoid content. This interesting study presents a special provision of integration of several desired agronomic and bio-chemical traits in a single plant by customized grafting techniques (Legua et al. 2017). The genealogy research in Citrus has proven very successful in the identification of suitable breeding parents. In a study involving tropical Citrus plants, some germplasm were identified as a potential reservoir of bioactive compounds (Fig. 5). Citrus maxima, Citrus grandis L. (Pomelo), Citrus paradisi Macfad (Grapefruit), Citrus sinensis (Orange), Citrus macroptera (Wild Orange), Citrus reticulata (Mandarin), Citrus limon (Lemon), and Citrus medica L. (Citron) exhibit a varied morpho-metabolomic profile. Additionally, analysis of Melicoccus bijugatus Jacq. (Spanish Lime) fruit peels presented pharmacological potential and novel therapeutic proficiency. The research recommended the natural cultivation of the non-commercial Citrus for foodomics and sustainable agroforestry (Chel-Guerrero et al. 2022).

Fig. 5 Late maturing type Mandarin of Lower Mirik region of Darjeeling, West Bengal, India

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The wild and endemic Citrus found in different parts of the globe may contribute toward the improvement of Citrus nutraceutical research. The gas chromatography– olfactometry (GC-O) analysis of volatiles of a wild mandarin, Mangshanyegan (Citrus nobilis Lauriro), and subsequent comparison with volatile profile of four Citrus species, Kaopan pummelo (Citrus grandis), Eureka lemon (Citrus limon), Huangyanbendizao tangerine (Citrus reticulata), and Seike navel orange (Citrus sinensis) exhibits significant distinctions. Monoterpene hydrocarbons d-limonene (85.75%) and β-myrcene (10.89%) pre-dominated the total volatile fraction. The flavor dilution factors (FD) detected eight oxygenated compounds, including (Z)and (E)-linalool oxides specific to Mangshanyegan. The combined results of GC-O, quantitative analysis, odor activity values (OAVs), and omission tests confirms the balsamic and floral aroma of Mangshanyegan is controlled by β-myrcene and (Z)and (E)-linalool oxides (Liu et al. 2012). These results are in consistence with the prospect of Citrus waste in the aroma and flavor industry. A striking discovery of a new wild Citrus species native to the Ryukyu island increases the prospect of nutraceutical research in Citrus. This new species collection with eight wild Okinawan accessions forms a separate cluster, disowning their association with all previously sequenced species of Citrus. The accessions include ‘tanibuta’ type Citrus that is genetically distinct from tachibana and shiikuwasha described by Tanaka. Among their differences, C. ryukyuensis is a sexual species that produces monoembryonic seeds, while tachibana and shiikuwasha, both produces polyembryonic (apomictic) seeds. The identification of C. ryukyuensis as a pure species (a distinct sexually reproducing population without admixture) with low genome-wide heterozygosity (0.2–0.3%) with zygotic (sexual) reproduction forms a promising separate accession suitable as a breeding parent (Wu et al. 2021). In a very recent study conducted in Manipur, India, confirms the origin of Citrus indica in the Indo-Burma border region. A wild orange morphologically resembling C. indica was characterized using morpho-taxonomic identifiers of Citrus. Additionally, plant barcoding using three chloroplast regions (trnL-F, psbK-I, matK50 trnK spacer) and one nuclear (ITS) region established the identity of the Manipuri wild Citrus species as Citrus indica. The Dailong Village of Manipur, inhabited by the Rongmei tribes, were associated with the natural conservation and maintenance of wild Citrus known as ‘Garuan-thai’. C. indica is known for its poor regeneration and less adaptability to new habitats. A distinct hilly microclimate is essential for its survival and existence (Fig. 6). The identification of ‘Garuan-thai’ in North Eastern India unveils the prospect of discovering potent genotypes for nutraceutical exploitation (Devi et al. 2022). In recent years, several attractive breeding strategies were applied for improvement of Citrus orchard and fruit production strategies. Normally, Citrus seedlings go through a very long juvenile phase (about 3–20 years), which hinders the breeding and improvement of Citrus. Research on minimizing the juvenile phase and promotion of early flowering in Citrus was done by adoption of a transgenic breeding method. APETALA1 (AP1) and LEAFY (LFY) genes were introduced into citrange (P. trifoliata L. Raf.
hybrid of C. sinensis L. Osbeck) from Arabidopsis. Transgenic citrange plants over-expressing the AP1 and LFY genes flowered early and

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Fig. 6 Molecular Profile of some elite clones of mandarin (Citrus reticulata) orange collected from North Eastern Himalayan Region of Indian Subcontinent

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produced fertile and normal flowers (Pillitteri et al. 2004). Fruits were obtained from first-year transgenic plants that were only 2–20 months old and bore their first flowers, significantly reducing the juvenile phase to less than 5 years in transgenic citrange compared with control plants (Peña et al. 2001). Zygotic seedlings obtained by crossing AP1 and LFY-transgenic citrange also showed early flowering with normal fruit setting in the first spring, validating provisions for novel research (Rao et al. 2021). The Citrus genetic resource in conjecture with model and non-model plants could produce unique nutraceutical cultivar in Citrus. The gene co-suppression, feedback inhibition regulates metabolic inheritance in Citrus and transcriptomic tool could encourage anabolic biosynthesis of desired components. In new generation Citrus breeding, a novel approach of genomic-assisted breeding (GAB) plays an important role. This GAB method could solve the main three constraints of Citrus improvement, meeting the commercial demand, disease resistance, and fast breeding. The GAB technique is an integration of genome wide association studies (GWAS), and genome selection (GS) is expected to increase the prediction accuracy of conventional MAS. In this method, the parents of multiple Citrus cultivars mainly natural hybrids will be confirmed. The genomic pedigree will be beneficial for selection of some unfamiliar cultivar for hybridization to assimilate novel traits in hybrid by reduction in unwanted traits. A research conducted by NARO released the current cultivars ‘Aurastar’, Nou No. 7, ‘Nou No. 8’, secondgeneration Trifoliate orange from a cross of ‘TF Flying Dragon’ and a local cultivar ‘Hassaku’, followed by subsequent crossing with ‘Kiyomi’, for transfer of Citrus tristeza resistance trait from the Banpeiyu pummelo genotype (Goto et al. 2018). The genealogy study of the cultivars is a productive approach that could accelerate the breeding pace. Several Japanese cultivars Satsuma, Hassaku, Sudachi, and Kabosu having unique traits were selected within a single cross. Elite hybrids were selected from the crossing of ‘Kaikoukan’ and ‘tachibana’ within a single generation. Screening of thousands and tens of thousands of offspring combining GAB techniques was assumed to be the new savior of dwindling orchards and the Citrus industry (Shimizu 2022).

8

Conclusion

In current times, the global nutrition sector is facing a dichotomous constraint: one is the nutritional deficit and malnutrition, and the other is anomalous nutrition associated with luxuriance in food habits. The malnutrition of children due to lack of healthy diet in developing and some developed nations is recognized as a global problem, the other condition of anomalous nutrition promotes obesity, diabetes, and coronary heart diseases in developed countries with abundance availability of highcalorie food. The imbalance in nutritional requirement could be compensated by the intake of functional foods. In tropical and subtropical countries, the fruits and vegetables are loaded with diverse nutraceuticals. A vast majority of economically

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backward countries are blessed with rich biodiversity reserves. This rich plant genepool is a robust weapon for the countries to alleviate poverty by creation of domestic and global agri-business. In real life, these germplasm biomass produces a sizable agro-waste that becomes a concern for the under-privileged nations. Through an intelligent approach, these agro-wastes could be utilized in alleviation of nutritional inconsistencies. Citrus is one of the prominent fruit crop with immense potential to be included as raw material in the emerging nutraceutical sector. This fruit crop has a long history of cultivation and has conserved a vast wild gene reserve in tropical and sub-tropical regions of the world. The appropriate utilization of the omic tool could lead to metabolic flux of the nutritive and pharmaceutically valuable plant bio-actives. Genotype-driven measurable phenotypic changes with consequent understanding of the biochemical mechanism and pathway dynamics may assist in food-omics research. The cutting-edge technologies of new omic era could increase the metabolite heritability, leading to development of designer Citrus cultivar. Omicguided novel designer citrus may accelerate the pace of emerging nutraceutical industry and ensure intelligent agro-waste management.

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Watermelon: Advances in Genetics of Fruit Qualitative Traits Sudip Kumar Dutta, Padma Nimmakayala, and Umesh K. Reddy

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Organic Acids and Sugar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Amino Acid Compositions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Fruit Bitterness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Fruit Shape and Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Flesh Color . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Rind Pattern . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Flesh Firmness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Rind Thickness and Toughness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Ethylene and Ripening in Watermelon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Watermelon (Citrullus lanatus) belongs to the family Cucurbitaceae. The crop is grown commercially in regions with extended warm, frost-free months. Watermelon is cultivated for its colorful, tender, juicy, and sweet fruit. They are generally consumed fresh and make an excellent and delicious dessert, particularly during the summer months. Because of its smaller genome and large number of gene mutations, watermelon is a suitable crop species for genetic research. Watermelon’s genome has 424 million base pairs. DNA sequencing found significant conservation, which is relevant for comparative genomics within Cucurbitaceae and other species. S. K. Dutta (*) Gus R. Douglass Institute, Department of Biology, West Virginia State University, Institute, WV, USA ICAR RC NEH Region, Sikkim centre, Gangtok, Sikkim, India P. Nimmakayala · U. K. Reddy Gus R. Douglass Institute, Department of Biology, West Virginia State University, Institute, WV, USA e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_36

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There exists a huge genetic variability in the fruit quality characteristics of watermelon with respect to seed traits, fruit shape, fruit size, skin color, skin pattern, flesh color and sugar/acid composition, fruit bitterness, and many more. This chapter serves as a guide to show the prospects and advances made in the genetics of fruit qualitative traits in watermelon breeding programs depending on profitability and consumer preferences. Keywords

Watermelon · Fruit · Genomics · Quality · Flesh color · Rind pattern

1

Introduction

Watermelon (Citrullus lanatus [Thunb.] Matsum. and Nakai var. lanatus; 2n ¼ 2x ¼ 22) belonging to the family Cucurbitaceae is primarily cultivated for its fresh and nutritious fruit. Citrullus lanatus var. citroides, C. naudinianus, C. mucosospermus, C. rehmii, C. ecirrhosus, and C. colocynthis are the species of the genus Citrullus (Chomicki and Renner 2015). Most Citrullus species have their origins and genetic diversity in continental Africa (Dane and Lang 2004). One theory claims that it came from a species of Citrullus lanatus that is a common wild plant in central Africa, while another believes that it was domesticated from the perennial Citrullus colocynthis that is a common plant in ancient sites. Watermelons have been grown in Africa for over 4000 years. Watermelons were commonly planted in the Nile valley region prior to 2000 BCE, according to seeds and plant pieces found in Egyptian tombs. They were transported from Africa to India in the year 800 CE and to China in the year 900 CE, after which they expanded to other continents in the year 1500s. Annual watermelon plants have lobed leaves, long, angular vines that trail, branching tendrils, and solitary male and female flowers. Watermelon of various shapes like round, oval, or elongated can weigh anywhere between 1.5 kg and 15 kg. The rind varies in color from light to dark green and has different striped patterns. Despite the fact that the flesh may be white, green, yellow, orange, or red, customers favor inner qualities like sweetness and texture and colors like deep red, pink, or dazzling yellow. Fruit types and cultivars differ widely in size and form, and the outside skin is smooth, sutured, or netted, with a white, green, or yellow tone. Normal colors for the flesh (mesocarp) are green or orange; however, pink and white are also found. Fig. 1 is a panel displaying the variety in morphology of watermelon fruits. A small genetic background of sweet watermelon has resulted from modern breeding practices that have mostly focused on fruit quality characteristics including sugar content, flesh color, and rind pattern (Levi et al. 2017). It is uncertain how phenotypic alterations brought about by human and natural choices affected the watermelon genome. For the creation and marketing of new products, sweet watermelon fruit characteristics are essential. The pharmaceutical industry, the processing industry, and the fresh market will all profit from the novel and value-added genotypes. Pickles, jam, fruit puree, popsicles, and watermelon juice are a few examples of items with added value that are made from recently created cultivars with superior qualities. The new cultivars ought to have a range of bioactive

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Fig. 1 A panel showing watermelon fruit morphological diversity

substances that are both nutritive and therapeutic in nature (Mashilo et al. 2022). A viable and alternate method for hastening the creation and release of watermelon varieties with sufficient agronomic and quality traits to meet the crop’s value chains is nonconventional breeding using gene-editing technology. For instance, changing watermelon genes associated with agronomic traits using clustered regularly interspaced short palindromic repeats (CRISPR/Cas9) allowed the development of novel cultivars (Wang et al. 2021). The development of superior cultivars with higher nutritional contents, market-preferred traits, and a longer shelf life will be aided by the information on the genetic control of fruit qualities in watermelons that will be possible by gene-editing and related technologies. The goal of this chapter is to illustrate the prospects and developments made in the genetic study of fruit quality characteristics in watermelon as a guide for quality breeding based on economic and end-user qualities, taking into account the aforementioned context.

2

Organic Acids and Sugar

Sugars and organic acids have a substantial influence on organoleptic fruit quality and are key components in fruit flavor development. Contrary to staple food crops, where production is the ultimate breeding goal, watermelon places greater emphasis on flavor

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and aroma, both of which are influenced by the metabolite composition of the fruit. During development, watermelon fruits go through a variety of biochemical changes, including as adjustments to sugar metabolism, an increase in organic acid and color, fruit softening, flavor, and volatile aromatic compounds (Zhu et al. 2017). In one study, researchers examined the coexpression patterns of gene networks linked to sugar and organic acid metabolism using transcriptome profiles. They found three gene networks or modules comprising 2443 genes that were substantially associated with organic acids and carbohydrates. Seven more genes involved in the metabolism of organic acids and carbohydrates were found. SWEET, EDR6, and STP were recognized as sugar transporters (Cla97C01G000640, Cla97C05G087120, and Cla97C01G018840, r 2 ¼ 0.83 with glucose content), while Cla97C03G064990 (Cla97C03G064990, r 2 ¼ 0.92 with sucrose concentration) was identified as a sucrose synthase. Cla97C07G128420, Cla97C03G068240, and Cla97C01G008870 were identified as malate and citrate transporters, respectively, since they displayed strong associations with malic acid (r 2 ¼ 0.75) and citric acid (r 2 ¼ 0.85) (ALMT7, CS, and ICDH) (Umer et al. 2020a). The two enzymes that regulate sugar metabolism in watermelon most crucially are sucrose synthase and sucrose phosphate synthase (Guo et al. 2015). The expression of gene clusters involved in sugar biosynthesis, including a-galactosidase, invertase, and urease diphosphate (UDP)-galactose/glucose pyrophosphorylase (UDP-Gal/Glc PPase), rises as the watermelon fruit ripens. The Cla013902 gene reportedly affects how sugar is metabolized in watermelons (Guo et al. 2015). There are nine a-galactosidase genes in the watermelon genome. The nine genes are reportedly involved in the hydrolysis of stachyose and raffinose, according to studies (Guo et al. 2013). Additionally, the buildup of sugar in watermelon is influenced by five genes for insoluble acid invertase (IAI) (Guo et al. 2015). The watermelon fruit’s extracellular sucrose degeneration, which permits fructose and glucose transfer and intercellular sugar accumulation, is linked to the IAI gene Cla020872 (Guo et al. 2015). Recent research has identified ClAGA2, an alkaline a-galactosidase gene expressed in the vascular bundle, as a critical regulator of the hydrolysis of stachyose and raffinose in watermelon. ClAGA2 controls fruit raffinose hydrolysis and reduces the amount of sugar in fully grown watermelon fruits (Ren et al. 2021). Tonoplast sugar transporter (ClTST2) and sugar transporter 3 (ClSWEET3) genes control sugar storage and transfer in watermelon fruit cell vacuoles (Ren et al. 2021). Several important genes involved in sugar production and translocation that are up- or downregulated throughout developmental processes have been found by several researches. Differentially expressed genes such NAD-dependent malate dehydrogenase (NAD-cyt MDH), aluminum-activated malate transporter (ALMT), and citrate synthase (CS) affect the accumulation of organic acids in watermelon (Gao et al. 2018). The reversible conversion of malate to oxaloacetate is catalyzed by the NAD-dependent malate dehydrogenase (NAD-cyt MDH) gene (OAA) (Yao et al. 2011), whereas citrate synthase (CS) gene controls citric acid production. Malate dehydrogenase genes and aluminum-triggered malate transporters control the regulation and breakdown of malates (Umer et al. 2020a). It is believed that the genes for citrate synthase (Cla97C03G068240) and isocitrate dehydrogenase (Cla97C01G008870) are involved in the generation and breakdown, respectively, of citric acid (Umer et al. 2020b). Malic and citric acid accumulation are linked to higher

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expression of the genes for malate dehydrogenases (Cla008235 and Cla011268) and citrate synthases (Cla013500) (Gao et al. 2018). From the sweet and sweet-andsour genotypes, Cla97C01G000640 (SWEET), Cla97C05G087120 (EDR6), and Cla97C01G018840 were shown to control glucose biosynthesis, whereas Cla97C03G064990 controls sucrose production in watermelon (Umer et al. 2020b). ClVST1, a gene for a vacuolar sugar transporter, was shown to be highly expressed during the ripening of watermelon fruit and was connected to the accumulation of sucrose (Ren et al. 2021).

3

Amino Acid Compositions

The amino acid citrulline is the most abundant in ripe watermelon fruit (Joshi et al. 2019). Citrulline is a nonessential amino acid which is generated throughout the urea cycle as a metabolic intermediate (Bahri et al. 2013). This amino acid serves as a precursor to arginine, another essential amino acid contained in watermelon fruit (Joshi et al. 2019). Watermelon has many genes that are involved in citrulline metabolism. Citrulline biosynthesis in watermelon is associated with ornithine carbamoyltransferase (OTC; ClCG05G018820), N-acetylornithine aminotransferase (N-AOA; ClCG09G003180), N-acetylornithine-glutamate acetyltransferase (N-AOGA), CPS-1 (ClCG11G013120) and CPS-2 (ClCG09G021680), N-acetylornithine deacetylase (AOD-1), N-acetylornithine deacetylase (AOD-3), and nitricoxide synthase gene (ClCG01G004960) (Joshi et al. 2019). Citrulline catabolism is also connected to ASS, 1,2,3-argininosuccinate synthase; ASL, 1,2-argininosuccinate lyase; ARG, arginase; ODC, ornithine decarboxylase; and ADC, arginine decarboxylase (Joshi et al. 2019). Citrulline biosynthesis is mediated by the genes argininosuccinate lyase, N-acetylglutamate kinase, and ornithine decarboxylase, whereas arginine biosynthesis and accumulation is mediated by the genes ornithine carbamoyltransferase (Fall et al. 2019).

4

Fruit Bitterness

Watermelons in the wild create bitter cucurbitacin molecules, a kind of highly oxygenated tetracyclic triterpene that repels pests. Cucurbitacin B (CuB), cucurbitacin C (CuC), cucurbitacin E (CuE), and cucurbitacin E-2-O-glucoside are all found in Citrullus fruits, leaves, roots, and stems (CuE-Glu) (Kim et al. 2018). The principal bitter ingredient in Citrullus fruit is CuE, commonly known as elaterinide (Matsuo et al. 1999). Despite the fact that these protective chemicals evolved in plants millions of years ago, humans have bred them to make them more appealing to our taste buds. In domesticated varieties of watermelon, a single point mutation in a transcription factor results in a faulty protein and diminished bitter compounds (Everts 2016). The genetic basis of two watermelon fruit traits were studied in a backcross generation arising from the hybridization of an interspecific F, hybrid of Citrullus lanatus and C. colocynthis with the domesticated parent Citrullus

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lanatus. Bitterness of the fruit, which distinguishes wild C. colocynthis, was revealed to be governed by a single dominant gene (Bi) that was linked to the isozyme marker Pgm-1 at a distance of 11.3 cm (Navot et al. 1990). In one study, it was shown that Cla011508 (located on chromosome 1) regulates the bitterness of watermelon fruit, and the crucial mutation locus in this gene provided molecular insights for markerassisted breeding of target characteristic (Gong et al. 2022). The dominant Bi gene regulates cucurbitacin production, which is responsible for bitterness in Citrullus fruits, whereas the recessive su (bitterness suppressor) gene regulates the presence or absence of bitterness in watermelon fruit. The Bi gene has been identified as an oxidosqualene cyclase (OSC; Cla007080) gene on watermelon chromosome 6 (Chambliss et al. 1968; Robinson et al. 1976; Navot et al. 1990; Lu et al. 2016). Furthermore, one watermelon fruit bitterness gene on chromosome 1 was found; the significant locus with the highest LOD score (58.361) was designated qbt-c1-1, and it explained 82.927% of phenotypic variation with a negative additive effect of 0.465 (Li et al. 2018). Watermelon breeders looking to improve their carotenoid profiles should hunt for progenies with genes that condition the carotenoid synthesis pathway.

5

Fruit Shape and Size

Fruit form and size are important horticultural sector traits that exhibit a large range of phenotypic variation, emphasizing their importance in breeding programs. The shape of watermelon fruits was assumed to be controlled by an incompletely dominant gene, resulting in elongate (OO), oval (Oo), and spherical (oo) fruits (Guner and Wehner 2004). It was also shown that a single gene regulates both spherical (Os) and oval (O+) watermelon fruits, exhibiting partial dominance when a spherical fruit inbred line crosses with an oval fruit inbred line (Tanaka et al. 1995). The similar pattern of inheritance was seen in F2 populations of ‘Peerless’, ‘Baby Delight’, ‘Northern Sweet’, and ‘Dove’ (Poole and Grimball 1945). For the dominant elongate fruit, allele ObE was proposed; for the recessive oblong fruit, allele Ob; and for the round fruit, allele ObR (not the same as the o gene for round) (Lou and Wehner 2016). Segregation analysis in F2 and BC1 populations derived from a cross between two inbred lines ‘Duan125’ (elongate fruit) and ‘Zhengzhouzigua’ (spherical fruit) revealed that watermelon fruit shape is controlled by a single locus and that elongate fruit (OO) is only partially dominant to spherical fruit (oo), with the heterozygote (Oo) being oval fruit and a 159 bp deletion (Dou et al. 2018). The SUN gene, a member of the IQ domain (IQD) family, has long been recognized to influence tomato fruit elongation early in fruit development, following pollination and fertilization (Van Der Knaap and Tanksley 2001). Several QTLs linked with FD (and fruit weight) and FL (fruit length) have been found in diverse genetic backgrounds; however, the genes underlying these QTLs remain unknown.

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Flesh Color

There are many different fruit flesh colors in watermelons (Fig. 1); fruit flesh color is a key feature that influences nutritional value, customer choice, and breeder selection. The composition of chlorophyll and carotenoids in the flesh determines its color. Watermelon flesh colors have been classified as scarlet red, red, pink, orange, canary yellow, pale yellow, and white based on carotenoid levels. Watermelons with red flesh (including flaming red and pink) are high in lycopene (Sun et al. 2018). Prolycopene and carotene concentrations are considerably higher in watermelons with orange flesh (Branham et al. 2017). Watermelons with yellow flesh (canary yellow and light yellow) contain a high concentration of neoxanthin, followed by neochrome and violaxanthin (Fang et al. 2020). Watermelons with white flesh have very little violaxanthin and lutein in them (Lv et al. 2015). The idea of genetic variability in the color of watermelon fruit flesh is supported by the existence of separate mechanisms regulating carotenoid metabolism. Understanding the process of carotenoid inheritance enables for the development of cultivars with improved phytochemical component compositions. The genetics of skin color are extremely complex, with numerous genes and quantitative trait loci (QTLs) influencing carotenoid production. Genes involved in the carotenoid biosynthesis and metabolism pathway’s genome-wide comparative expression study showed complex gene expression and regulatory networks that led to the accumulation of different carotenoids in watermelon fruit (Fang et al. 2020; Mashilo et al. 2022). Based on genotyping data, two Kompetitive Allele-Specific PCR (KASP) markers were created for the candidate gene Cla97C10G185970, which was annotated as plastid lipid-associated protein and showed a strong connection between pale green and non-pale green meat fruits (Pei et al. 2021). During fruit ripening, the carotenoid profiles of four watermelon cultivars – red-fleshed ‘CN66’, pink-fleshed ‘CN62’, yellow-fleshed ‘ZXG381’, and white-fleshed ‘ZXG507’ – were examined. It was revealed that the amounts of violaxanthin and lutein in yellow fruit were positively correlated with CHYB and ZEP transcription levels (Lv et al. 2015). ClPAPs, Cla006670, Cla010946, Cla008831, Cla014416, Cla021506, Cla003468, and Cla003198 are plastid lipid-associated genes that are thought to be involved in the development of plastoglobules and globular and crystalloid chromoplasts (Fang et al. 2020).

7

Rind Pattern

The most common rind (or skin) colors in watermelon are solid green (dark, medium, and light), striped (narrow, medium, and large dark green stripes on a light green background), and grey. Gray is also written grey, although the names of watermelons have been standardized to the grey spelling. The expression of genes responsible for rind color and pattern does not appear to be uniform across different

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genetic backgrounds. Furthermore, the inheritance of gray or medium green rind colors has not been recorded, despite the fact that they have been two of the most prevalent rind colors in watermelon breeding during the previous century. ClCG08G017810 (ClCGMenG), a protein encoding a 2-phytyl-1,4-betanaphthoquinone methyltransferase, is linked to the production of dark green rind vs light green rind in watermelon (Li et al. 2018). For the ‘0901’, ‘10909’, ‘109905’, and ‘90509’ rind trait-segregating F2 populations, genotyping analyses were done using subsets of 188, 273, 287, and 113 probes, respectively. For the ‘0901’, ‘10909’, ‘109905’, and ‘90509’ populations, 26, 34, 30, and 15 linkage groups containing 175, 254, 269, and 79 probes were created, respectively. The genetic order of the probes is mainly collinear with the physical order on the reference genome, with a few exceptions on chromosomes 1, 3, and 11. S, D, and Dgo, together with chr4 150/chr4 249 on chromosome 4 and chr6 25767 on chromosome 6, were identified nearby (Park et al. 2016). As a consequence of genetic investigations, a team of researchers found three unique genes in watermelon. In comparison to Angeleno Black Seeded, the type line for the hue of watermelon red flesh, scarlet red flesh (Scr) gave more vivid red color in Dixielee and Red-N-Sweet. They suggest calling the original red skin color coral red in order to distinguish it from scarlet red. As a single dominant gene, Scr is inherited. A single dominant gene called Yellow Belly (Yb) was identified as the cause of Black Diamond’s ground spot’s transition from creamy white to dark yellow. A single recessive gene called intermittent stripes (ins), with the dominant allele, was found to be responsible for the difference between continuous and intermittent stripes on the rind of Navajo Sweet (Gusmini and Wehner 2006).

8

Flesh Firmness

The firmness of the flesh determines the texture and quality of watermelon fruit. Multigenes control flesh firmness as a qualitative attribute. For watermelon genetic breeding, it is crucial to identify the regulatory elements that most significantly affect the firmness of the fruit’s flesh. According to localization interval transcriptome analysis, Cla012507 (MADS-box transcription factor) may be involved in the control of fruit ripening and affect the hardness of watermelon fruit. Cla016033 (DUF579 family member), which may impact the cell wall component contents to alter the flesh firmness in watermelon fruit, was distinct in W1-1 and PI186490 (Sun et al. 2020). The hardness of watermelon flesh is controlled by phytohormone levels, particularly ABA (Wang et al. 2017). Cla009779 (NCED), Cla005404 (NCED), Cla020673 (CYP707A), Cla006655 (UGT), and Cla020180 (SnRK2) are implicated in ABA biosynthesis in watermelon (Wang et al. 2017). Cla009779, Cla005404, and Cla005457 were the most effective at increasing ABA accumulation. On chromosome 6 of the watermelon genome here is a significant QTL (Qffi6.1) for flesh firmness from C. amarus (Gao et al. 2016). The putative candidate gene for Qffi6.1 is Cla018816, a xyloglucan endotransglucosylase/hydrolase (XTH) gene that is variably expressed across firmand soft-bodied near-isogenic lines (Anees et al. 2021). Another XTH gene

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(Cla006648), cellulose synthase (Cla012351), galactosyltransferase (Cla006648), pectinesterase gene (Cla004251), ethylene response element transcription factor 1 (Cla004120), and ethylene response element transcription factor 2a (Cla007092) all played important roles in watermelon flesh firmness, according to transcriptome analysis (Anees et al. 2021).

9

Rind Thickness and Toughness

Watermelon fruit rind breaking not only facilitates disease invasion and reduces yield, but it also degrades the fruit’s exterior aesthetic value. One of the simplest methods for gauging consumer acceptance during commercial purchases is the rind of a watermelon. After crossing 97103 and PI296341, a biparental F2 population was produced. Using RAPD and SSR markers, QTL analysis showed that there were a total of two rind thickness QTLs and three fruit weight QTLs (Fan et al. 2000). Additionally, a watermelon backcross (BC) generation was developed for measuring rind hardness, and a QTL location controlling rind hardness was found on chromosome 4 (Hashizume et al. 2003). Watermelon rind hardness is correlated with the ethylene clerf4 transcription factor genes, according to the genotyping of 349-F2 individuals from 32 germplasm. The genotyping indicated a significant ascending allelic pattern of aa (hard) bb (soft) and substantial QTL region on chromosome 10 (Liao et al. 2020). Another recent study combined the hard-fleshed and soft-fleshed watermelon lines ‘PI186490’ and ‘W1–1’, and preliminary mapping in 175-F2 individuals identified the key genes on chromosomes 2 and 8 controlling central flesh hardness using BSAseq and CAPS marker-based QTL analysis (Sun et al. 2020). Using a combinatory genomic map and bulk segregant analysis, it was possible to link variations in rind hardness to the ethylene-responsive transcription factor 4 (ClERF4) (BSA). The ClERF4 gene on chromosome 10 also has an 11-bp InDel and a neighboring SNP, which confers cracking resistance in F2 populations with different rind hardness (Liao et al. 2020). A transcriptome study demonstrated the molecular pathways involved in the enhancement of fruit attributes including greater rind toughness by watermelon and bottle gourd grafting (Garcia-Lozano et al. 2019).

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Ethylene and Ripening in Watermelon

A microarray and quantitative real-time PCR-based investigation was conducted to better understand the sequence of events linked to fruit growth and ripening in watermelon (Citrullus lanatus [Thunb.] Matsum. and Nakai var. lanatus). This study found several of the ESTs with potential roles in the growth and ripening of watermelon fruits, particularly those involving the vascular system and ethylene (Wechter et al. 2008). The researchers noted differential expression of homologs of genes involved in ethylene biosynthesis (ACC oxidase) and signal transduction (ethylene receptor Cm-ETR1, ethylene insensitive [EIN3/EIL]-like transcription factor, ethyleneresponsive binding protein [EREBP], and ethylene response factor [ERF]) in the same

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study. Fruit rind plays a major role in reducing moisture loss and disease, as well as cracking resistance, ease of transport, and storage stability quality of watermelon; an ethylene-responsive transcription factor 4 (ClERF4) linked with variation in rind hardness was discovered using a combinatory genetic map and bulk segregant analysis (BSA) (Liao et al. 2020). The ethylene biosynthesis and signaling pathway genes, such as ACC oxidase, ethylene receptor, and ethylene-responsive factor, showed highly ripening-associated expression patterns in the watermelon, a non-climacteric fruit, according to a comparative transcriptome profiling analysis of the cultivated watermelon 97103 and wild watermelon PI296341-FR. This suggests that ethylene may play a role in the development and ripening of the fruit (Guo et al. 2015). XTH gene (Cla006648), cellulose synthase (Cla012351), galactosyltransferase (Cla006648), pectinesterase gene (Cla004251), ethylene response element transcription factor 1 (Cla004120), and ethylene response element transcription factor 2a (Cla007092) all played important roles in watermelon flesh firmness, according to transcriptome analysis (Anees et al. 2021).

11

Conclusion

Watermelon fruit qualitative characters like seed color, seed size, fruit shape, skin color, rind pattern, flesh color and sugar/acid composition, fruit bitterness, and many more exhibit significant genetic diversity. With the advancement of genomics and availability of watermelon genome sequences, it has become possible to identify genes critical to valuable fruit quality traits. As the knowledge of the molecular mechanisms behind these characteristics improves, more effective and focused selection will enhance the efficiency of breeding of this important crop.

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Grapes: A Crop with High Nutraceuticals Genetic Diversity Javier Tello, Loredana Moffa, Yolanda Ferrada´s, Marica Gasparro, Walter Chitarra, Rosa Anna Milella, Luca Nerva, and Stefania Savoi

Contents 1 Introduction to Worldwide Wine and Table Grape Production . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Grape as a Source of Nutraceutical Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Polyphenolic Compounds in Grapes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Phenolic Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Stilbenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Flavonols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Flavanols . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Anthocyanins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Terpenoid Compounds in Grapes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Monoterpenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Sesquiterpenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Tetraterpenes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Javier Tello and Loredana Moffa contributed equally with all other contributors. J. Tello Instituto de Ciencias de la Vid y del Vino (ICVV), Consejo Superior de Investigaciones Científicas – Universidad de la Rioja – Gobierno de La Rioja, Logroño, Spain e-mail: [email protected] L. Moffa Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Conegliano, Italy e-mail: [email protected] Y. Ferradás Instituto de Ciencias de la Vid y del Vino (ICVV), Consejo Superior de Investigaciones Científicas – Universidad de la Rioja – Gobierno de La Rioja, Logroño, Spain Faculty of Biology, University of Santiago de Compostela, Santiago de Compostela, Spain e-mail: [email protected] M. Gasparro · R. A. Milella Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Turi, Italy e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_37

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5 Vitamins and Other Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Genetic Resources and Extent of Genetic Diversity for Health-Related Compounds in Grapes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Diversity in the Muscadinia Subgenre . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Diversity Among Grape Vitis Species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Diversity Among Wild and Cultivated Vitis vinifera Grapes . . . . . . . . . . . . . . . . . . . . . . . 7 Molecular Mapping Studies for Health-Related Compounds Content in Grapes . . . . . . . . 7.1 Anthocyanins Biosynthesis: The Berry Color Locus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Flavonols and Flavanols Biosynthesis: The Role of VviMYBF1, VviMybPA1, and VviMybPA2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Monoterpenes Biosynthesis: The 1-Deoxy-D-xylulose 5-Phosphate Synthase (DXS1) Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Carotenoids Biosynthesis: What Gene Is Prominent? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Grape miRNAs and Their Likely Impact on Human Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Applicability of Breeding Techniques in Grapevine Improvement . . . . . . . . . . . . . . . . . . . . . . . 9.1 Conventional Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 The Potential of New Plant Breeding Techniques (NPBTs) . . . . . . . . . . . . . . . . . . . . . . . . 10 Conclusion and Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Grapevine is considered the most important fruit crop cultivated in temperate regions and is acknowledged as a model species for non-climacteric fleshy fruits. From a nutritional perspective, grapes are fruits with a high content of carbohydrates, a good nutritional source of minerals and vitamins, and most importantly, they are one of the richest fruits in polyphenols and other compounds with antioxidant properties. In particular, this chapter focuses on nutraceutical compounds such as phenolic acids, stilbenes, flavonols, flavanols, tannins, anthocyanidins, monoterpenes, sesquiterpenes, carotenoids, C13-norisoprenoids, and some vitamins. Their chemical structures and biosynthetic pathways are revised, and the content and diversity of these secondary metabolites in genetic resources of the genus Vitis (including Muscadinia and Vitis species, focusing on V. vinifera cultivars) are shown. In addition, QTL and association studies exploring the genetic basis of the biosynthesis of different health-related compounds in V. vinifera grape berries were asserted. Finally, a survey on the peculiarities and limits of traditional breeding compared to the innovative plant breeding techniques (cisgenesis and genome editing) applied to grapevine is provided. We

W. Chitarra · L. Nerva (*) Council for Agricultural Research and Economics (CREA) – Research Centre for Viticulture and Enology, Conegliano, Italy Institute for Sustainable Plant Protection, CNR, Torino, Italy e-mail: [email protected]; [email protected] S. Savoi (*) Department of Agricultural, Forest and Food Sciences, University of Turin, Grugliasco, Italy e-mail: [email protected]

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conclude with the potential role of grape miRNA on human health as likely candidates for dietary therapy approaches due to their cross-kingdom abilities and regulation activity of gene expression and cellular processes in humans through dietary intake. Keywords

Vitis vinifera · Stilbenes · Anthocyanins · Monoterpenes · Carotenoids · miRNA · Cisgenesis · Genome editing

1

Introduction to Worldwide Wine and Table Grape Production

Grapevines are one of the most valuable horticulture crops, typically cultivated in regions with mild climate conditions, sufficient heat accumulation, and moderate winter low temperatures for proper fruit development and growth. The primary grape production areas are located between latitudes 30
–50
and 30
–40
in the Northern and Southern Hemispheres, respectively. These areas include some world-renowned winemaking regions, like Bordeaux and Burgundy in France, La Rioja in Spain, Tuscany in Italy, the Napa Valley in the USA, the Barossa Valley in Australia, or the Stellenbosch region in South Africa, to cite a few. It also embraces major table grape and raisin producers, including China, Turkey, India, the USA, and Chile (OIV 2019). In 2020, the total vineyard surface for wine grape and table grape production was estimated at 7.3 million hectares (OIV 2019). Mediterranean Sea countries, where grapevines have been cultivated for centuries, are some of the most important worldwide leading grape growers, including Spain (13.1% of the vineyard surface in 2020), France (10.9%), Italy (9.8%) and Turkey (5.9%). Outside these traditional grape-growing regions, it is worth highlighting other major grape-producing countries like China (10.7%), the USA (5.5%), Argentina (2.9%), and Chile (2.8%). These “New World” regions accounted for some of the largest vineyard surface and gross grape production increases over the last decades (OIV 2019). Worldwide grape production is estimated at 77–78 million tons per year. About 57% of this annual yield mainly aims to sustain worldwide wine production. In contrast, fresh grape and dried grape (raisins) markets account for 36% and 7% of the total annual grape production, respectively (OIV 2019). In addition, some of these grapes are processed into jam, grape juice, vinegar, jelly, and grape seed extracts and oils, which diversify the use of grapes. Although some muscadine grapes (from Vitis rotundifolia cultivars and interspecific hybrids) have local relevance in the Southeastern USA (Yuzuak and Xie 2022), worldwide grape production is majorly sustained by the cultivation of V. vinifera cultivars. Despite the vast number of cultivars available for this species (Wolkovich et al. 2018), grape production focuses on cultivating a few genotypes (Morales-Castilla et al. 2020). In this light, only 13 grape cultivars (‘Kyoho’, ‘Cabernet Sauvignon’, ‘Sultanina’, ‘Merlot’, ‘Tempranillo’, ‘Airén’, ‘Chardonnay’, ‘Syrah’, ‘Red Globe’, ‘Garnacha Tinta’, ‘Sauvignon Blanc’, ‘Pinot Noir’,

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Fig. 1 Grape clusters at maturity of ‘Kyoho’ (left), ‘Carbernet Sauvignon’ (middle), and ‘Sultanina’ (right). (Photos were downloaded from the Vitis International Variety Catalogue (VIVC), www.vivc.de – (accessed April 2022). Source: Ursula Brühl, Julius Kühn-Institut (JKI), Federal Research Centre for Cultivated Plants, Institute for Grapevine Breeding Geilweilerhof – 76,833 Siebeldingen, Germany)

and ‘Trebbiano Toscano’ (syn. ‘Ugni Blanc’)) account for more than one-third of global vineyard surface, and 33 cultivars for one half of it (Alston and Sambucci 2019). Attending to this list, the most widely cultivated genotype is ‘Kyoho’ (a blackberried table grape cultivar bred by Yasushi Ohinoue in 1935 in the Oinoue Institute for Agronomical and Biological Science, Japan), followed by ‘Cabernet Sauvignon’ (a black-berried wine grape cultivar), and ‘Sultanina’ (a seedless white-berried multipurpose cultivar also known as ‘Thompson Seedless’) (Fig. 1). Collectively, these three cultivars accounted for almost one million hectares in 2015 (Alston and Sambucci 2019). Global table grape production has increased gradually in the last decades to reach ca. 27 million tons in 2018, with four countries producing more than 50% of world production: China (9.5 million tons), Turkey (1.9), India (1.9), and Iran (1.7) (OIV 2019). Besides dominating table grape production, these countries also lead table grape consumption rates, likely due to the perishable nature of grape fruits, which tend to be consumed close to where they are grown. World raisins production and consumption have stayed relatively constant in the last decades, reaching a total production of 1.3 million tons in 2018 (OIV 2019). The two principal raisin producers worldwide are Turkey and the USA, with 381 and 263 thousand tons of gross production in 2018, respectively (OIV 2019). In contrast to table grapes, raisins can be easily transported, so they are majorly exported to other countries. In fact, although European countries are only minor producers of raisins, they account for one-third of global consumption (FAO and OIV 2016). As a result, raisins are considered valuable agricultural commodities for producing countries. Table grape production is based on cultivating a series of high-yielding cultivars with good sensory attributes and optimum commercial characteristics for packaging and

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transport. On the other hand, raisin production is based on growing cultivars with berries with a good attitude towards dehydration and easy detachment from the stalk. For both uses, seedless cultivars are preferred. Some of the most cultivated cultivars for table grapes and raisins production are ‘Alphonse Lavallée’, ‘Crimson Seedless’, ‘Dattier de Beyrouth’ (syn. ‘Afus Ali’), ‘Flame Seedless’, ‘Kyoho’, ‘Muscat Hamburg’, ‘Italia’, ‘Muscat of Alexandria’, ‘Red Globe’, ‘Sugraone’, ‘Sultanina’, and ‘Victoria’ (FAO and OIV 2016). As observed, modern table grape and raisins production is based on the combined cultivation of traditional cultivars (e.g., ‘Sultanina’, ‘Muscat of Alexandria’) with others obtained in more recent breeding programs aimed to achieve novel grapes with better features that fit consumers and producers’ needs (e.g., ‘Kyoho’, ‘Red Globe’).

2

Grape as a Source of Nutraceutical Compounds

Grapes and raisins are grown on all inhabited continents, so they are commonly included in worldwide diets. Therefore, grapes result as one of the most regularly consumed fruits worldwide. It has been estimated that the average world consumption of grapes per year is 4.0 kg per capita (FAO and OIV 2016), although some differences between regions exist. For example, Turkey and China’s annual grape consumption is much higher, estimated at 23 and 7 kg per capita, respectively (FAO and OIV 2016). Grapes are known to be one of the fruits with higher content of carbohydrates, mostly simple sugars (18.1 g per 100 g of grapes). As observed in Table 1, grapes are a good dietary source of calcium, manganese, phosphorous, Table 1 Nutritional facts of grapes, raisins, and other relevant fruit crops. Nutritional data is referred to as 100 g servings. Information is taken from the USDA-Agricultural Research Service, FoodData Central (https://fdc.nal.usda.gov/, access: April 2022) Energy (kcal) Carbohydrates (g) Proteins (g) Lipids (g) Fiber (total, g) Calcium (% DRV)a Magnesium (% DRV) 1 Manganese (% DRV) 1 Phosphorous (% DRV) 1 Potassium (% DRV) 1 Vitamin B1 (% DRV) 1 Vitamin B6 (% DRV) 1 Vitamin C (% DRV) 1 Vitamin E (% DRV) 1

Apple 52 13.8 0.26 0.17 2.4 0.6 1.4 1.2 2.0 3.1 1.8 2.4 4.2 1.4

Banana 89 22.8 1.09 0.33 2.6 0.5 7.7 9.0 4.0 10.2 2.7 21.8 7.9 0.8

Cherry 63 16 1.06 0.2 2.1 1.4 3.1 2.3 3.8 6.3 2.7 2.9 6.4 0.5

Grape 69 18.1 0.7 0.2 0.9 1.1 2.0 2.4 3.6 5.5 6.4 5.3 2.9 1.5

Pear 57 15.2 0.36 0.14 3.1 0.9 2.0 1.6 2.2 3.3 0.9 1.8 3.9 0.0

Raisin 296 78.5 2.52 0.54 6.8 2.9 8.6 8.9 13.6 23.6 10.0 11.2 4.9 n.a.

a Dietary Reference Values (DRVs) were taken from EFSA, considering a 40-year-old man. n.a.: not available

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potassium, and vitamins B1, B6, and E compared to other relevant fruit crops. However, grapes stand out as one of the fruits richest in polyphenols and other compounds with antioxidant properties. In this line, multiple bioactive compounds with antioxidant potential have been discovered in grapes, including, but not limited to, phenolic acids, stilbenes, anthocyanins, flavonols, and flavanols (Teixeira et al. 2013; Pinasseau et al. 2017). Nowadays, there is a growing interest in consuming food products naturally rich in antioxidants (like grapes), as they may reduce the incidence of some chronic diseases. The interest in uncovering the connection between grape consumption and its beneficial effects on human health started in the early 1990s when the so-called “French Paradox” was proposed. This concept refers to the unusually low rate of coronary heart disease observed in French people, regardless of consuming a diet rich in high saturated fats, which was initially correlated with moderate red wine intake (Renaud and de Lorgeril 1992). Later on, this phenomenon was linked to the presence of resveratrol in the skin of colored grapes and then to multiple dietary factors and life conditions that characterize Mediterranean and French lifestyles (Ndlovu et al. 2019). These findings boosted numerous research studies aimed at identifying and quantifying the most important health-related metabolites present in grapes and their derived products and analyzing their consumption’s effect on human health (Catalgol et al. 2012). Numerous epidemiological, in vivo, and in vitro studies have indicated a relationship between polyphenol grape consumption and the lower incidence of some diseases and health disorders, information that has been collected in numerous reviews (Catalgol et al. 2012; Yang and Xiao 2013; Wightman and Heuberger 2014; Singh et al. 2015; Rasines-Perea and Teissedre 2017; Herman et al. 2018; Nash et al. 2018; Ko and Kim 2020). On the contrary, very few in vivo studies have considered the effects of fresh table grape intake on human health. As an example, Ammollo and colleagues reported an anticoagulant and profibrinolytic effect in healthy subjects after a 3-week table grape-rich diet (Ammollo et al. 2017). This protective role was further linked to an effect on the modulation of a series of genes implicated in critical processes like immune response, DNA and protein repair, autophagy, and mitochondrial biogenesis (Milella et al. 2020). Another study has suggested a link between the intake of fresh table grapes and a series of microRNA involved in fighting cancer development (Tutino et al. 2021). Grape polyphenols have been linked to a lower risk of cardiovascular diseases, one of most industrialized countries’ dominant causes of death. Among other cardioprotective effects, grape flavonoids (like anthocyanins, flavanols, and flavonols) are known to (i) inhibit platelet aggregation, (ii) decrease blood levels of triglycerides and high-density lipoprotein cholesterol, (iii) increase blood levels of low-density lipoprotein cholesterol, (iv) reduce oxidative stress, and (v) improve endothelial function (Wightman and Heuberger 2014). Besides, grape consumption may have a beneficial effect on type-2 diabetes, as they have one of the lowest glycemic index and glycemic load values among fruit crops (FAO and OIV 2016), and they are rich in phenolic compounds with some capability to reduce blood glycemic levels after food intake (Yang and Xiao 2013). On the other hand, grape berries are rich in resveratrol. Besides its protective effect against cardiovascular

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diseases, resveratrol has been suggested to have chemopreventive and chemotherapeutic effects on different cancer types (Catalgol et al. 2012). In addition, the estrogenic activity of resveratrol has been associated with the prevention of some metabolic disorders in post-menopausal women, including the loss of bone mineral density and some alterations of the lipid metabolism pathways that might lead to the development of insulin resistance, abdominal adiposity, and dyslipidemia (Ko and Kim 2020). Lastly, grape polyphenols have been associated with some preventive effects toward developing neurodegenerative disorders, like Alzheimer’s and Parkinson’s diseases, and chronic traumatic encephalopathy (Herman et al. 2018). Delphinidin 3-O-glucoside is one of the predominant plant bioactive compounds of anthocyanins, linked to protecting against thrombosis and cardiovascular diseases, inhibiting platelet activation, and attenuating arterial and venous thrombus formation and development (Yang et al. 2012). Flavonoids can scavenge free radicals; therefore, they play a role in protecting against UV light damage. These compounds, accumulated preferentially in the skin and seeds of ripened grape berries can fulfill these functions thanks to the flavonoid scaffolds modification, which ameliorates the antioxidant capacity among other properties such as stability, solubility, and bioavailability of the resulting derivative. Grape seeds are especially rich in proanthocyanidins, also known as condensed tannins or tannins. Given their redox potential and capability to bind target proteins and regulate cell signaling pathways, proanthocyanidins are known to have beneficial effects against different diseases (Unusan 2020). For example, in vivo and in vitro experiments have indicated that seed proanthocyanidin can inhibit metastatic processes, positively affecting the progression of lung, breast, colon, prostate, liver, pancreas, and skin cancers (Unusan 2020). In fact, proanthocyanidins have been suggested as powerful candidate drugs for cancer prevention and treatment therapy. In addition, grape seed proanthocyanidins have shown some preventive effects against cardiovascular diseases, obesity, type-2 diabetes, inflammatory bowel disease, neurodegenerative disorders, asthma, eye diseases, and osteoarthritis (Unusan 2020). Because of these potential beneficial effects on human health, grape seed oils rich in proanthocyanidins and other antioxidants have been recommended as suitable dietary supplements to prevent certain diseases (Gupta et al. 2020). Nevertheless, detailed safety analyses are needed to set the conditions of use and consumption of grape-derived ingredients in humans, especially for subjects under specific medical conditions (Singh et al. 2015). Lastly, grapevine leaves have a long history as a traditional food in some regions, being considered a healthy food item with multiple nutritional benefits. In addition, they are often mentioned in folk medicine to treat some medical conditions, like high blood pressure, diabetes, and several circulatory system and inflammatory disorders (Pintać et al. 2019). Analyses of their chemical composition have indicated that they are rich in carotenoids (like β-carotene, lutein, and zeaxanthin) and essential minerals like calcium, potassium, iron, and zinc (Maia et al. 2021). In addition, they show a high content of flavonoids and hydroxycinnamic acid derivatives, which confer antioxidant protective activities (Pintać et al. 2019; Banjanin et al. 2020). In this regard, preliminary in vitro studies suggested that grapevine leaf extracts might

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exert some promising anti-proliferative effects in human cancer cell lines due to their phenolic composition (Ferhi et al. 2019). However, further research is needed to suggest a chemopreventive and/or chemotherapeutic effect of grapevine leaf extracts, as well as before their use as ingredients in functional foods. Biomarkers of food intake provide accurate information on the consumption of certain foods in the diet. Indeed, several protocols for identifying and confirming food candidate biomarkers have been established within the Food Biomarker Alliance (FoodBAll) Project funded by the Initiative “A Healthy Diet for a Healthy Life” (JPI-HDHL). It was developed to cover the food intake in different European populations to identify more straightforward sampling techniques for metabolomics analysis and discover dietary biomarkers. In particular, resveratrol and tartaric acid were found as candidate biomarkers for grapes intake. However, considering the putative biomarkers for berries in general (i.e., including strawberry, blueberry, blackberry, cranberry, raspberry, and blackcurrant), it was possible to identify that anthocyanins and ellagitannins are the main drivers in berries (Ulaszewska et al. 2020).

3

Polyphenolic Compounds in Grapes

Phenolic compounds significantly impact fruit and wine quality. Their biosynthetic pathways are tightly controlled by many transcription factors that modulate their expression and accumulation as a natural defense to various biotic and abiotic stresses (Kobayashi et al. 2004; Bogs et al. 2007; Terrier et al. 2009; Czemmel et al. 2009; Höll et al. 2013). In grapevine, phenolic compounds are conventionally separated into two classes: (i) non-flavonoid (phenolic acids and stilbenes) and (ii) flavonoid compounds (flavonols, flavanols, and anthocyanins).

3.1

Phenolic Acids

Polyphenol biosynthesis begins with phenylalanine. This amino acid can exert carbon competition phenomena between primary and secondary metabolites linking the shikimate pathway with the non-oxidative branch of the pentose phosphate pathway. The biosynthesis is divided into the phenylpropanoid and flavonoid/stilbene pathways. The phenylpropanoid ends with p-coumaryl-CoA in three reactions carried out by the phenylalanine ammonia-lyase, the cinnamate4-hydroxylase, and the 4-coumarateCoA ligase activities (PAL, C4H, 4CL, respectively). p-coumaryl-CoA is a branching compound of the phenylpropanoid pathway, and it can set up the flavonoid (with the enzymes chalcone synthase, CHS) or stilbene (with the enzyme stilbene synthase, STS) biosynthesis pathways (Teixeira et al. 2013; Falchi et al. 2019). Phenolic acids (coumaric, caffeic, and ferulic) can be synthesized via phenylpropanoid products. When esterified with tartaric acid, they are known as trans-caftaric, trans-coutaric, and trans-fertaric acids, respectively (Fig. 2). They are synthesized in the berry flesh before véraison (beginning of grape ripening). Another significant phenolic acid in grapes is gallic acid (Fig. 2). It is formed from an

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Fig. 2 Chemical structures of the primary phenolic acids in grapes. (Drawn by the authors with ChemSketch (ACD/Labs))

intermediate compound in the upstream reactions of the shikimate pathway, thanks to the activity of a dehydroshikimate dehydrogenase (Bontpart et al. 2016). Gallic acid participates in several reactions, such as the galloylation of flavanols.

3.2

Stilbenes

Stilbenes are phytoalexins, small lipophilic compounds with well-known benefits for human health. They are naturally formed by the stilbene synthases in berries from véraison onwards. Stilbenes content and composition in grape berries present differences among cultivars. In addition, an enhancement of their synthesis happens concurrently with biotic and abiotic stresses (Gatto et al. 2008). Genomics analysis in V. vinifera indicates a remarkable expansion of the stilbene synthase gene family compared to other crops and plant model species, likely through segmental and tandem gene duplication events. In fact, up to 45 stilbene synthases have been described, with 33 coding for functional proteins (Vannozzi et al. 2012). The major stilbenes in Vitis are trans-resveratrol and its isomer cis-resveratrol, although the latter is less stable. Modifications of resveratrol give rise to other stilbenes present in grapes, such as the glycosylated trans-piceid, the methoxylated pterostilbene, or the hydroxylated piceatannol, which, if further glycosylated, become astringin. Moreover, oligomerization processes can produce the resveratrol dimer pallidol or a series of viniferins (α-, β-, γ-, δ-, ε-) with different stilbene units (Fig. 3). The genetic and metabolic mechanisms involved in such modifications are mainly unknown, except for a resveratrol O-methyltransferase and a resveratrol glucosyl transferase responsible for the production of pterostilbene and piceid, respectively (Hall and De Luca 2007; Schmidlin et al. 2008).

3.3

Flavonols

The flavonoid pathway leads to flavanols, and anthocyanins. First, chalcone synthases and chalcone hydroxylated at diverse positions

three major polyphenolic classes: flavonols, naringenin is produced through the activity of isomerases (CHS, CHI). Then, naringenin is (3, 30 or 30 50 ) thanks to different flavanone

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Fig. 3 Chemical structures of the major stilbenes in grapes. (Drawn by the authors with ChemSketch (ACD/Labs))

hydroxylases (F3H, F30 H, F30 50 H). These reactions form dihydroquercetin, dihydrokämpferol, or dihydromyricetin, respectively. Flavonol synthases (FLS) trigger flavonols’ production by converting the previous dihydro-forms into kämpferol, quercetin, and myricetin. In addition to these three major compounds, grapes have isorhamnetin (the quercetin O-methylated form), laricitrin, and syringetin (the myricetin O-methylated forms carrying one or two methyl groups, respectively). Glycosylated flavonols are the majority metabolites found in grapes, and they can be linked to a glucoside, a galactoside, a rhamnoside, a rutinoside, or a glucuronide. In black-berried cultivars, flavonols can associate with anthocyanins, strengthening red wine color stability. In white-berried grapes, the primary flavonols are kämpferol (mono-hydroxylated), quercetin, and isorhamnetin (di-hydroxylated). In addition, myricetin, laricitrin, and syringetin (tri-hydroxylated) have been

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Fig. 4 Chemical structures of the noteworthy flavanols in grapes. (Drawn by the authors with ChemSketch (ACD/Labs))

detected in black-berried grapes (Mattivi et al. 2006) (Fig. 4). Synthetized prevalently in grape berries skins, they are suggested to have a protective effect against UV radiation.

3.4

Flavanols

Flavanols, synthesized during the first growth phase of the berry, are derived from dihydroflavonols in two ways. They can be formed (i) in three steps via the dihydroflavonol 4-reductase, the leucoanthocyanidin dioxygenases, and the anthocyanidin reductase passing by anthocyanidins (DFR, LDOX, ANR) or (ii) in two steps via the dihydroflavonol 4-reductase and leucoanthocyanidin reductase (DFR, LAR) (Falchi et al. 2019). The most abundant monomeric flavanols found in Vitis are catechin and gallocatechin, their enantiomers epicatechin and epigallocatechin, and the gallate ester epicatechin-3-O-gallate (Fig. 5). Their difference lies in their chemical modification (hydroxylation, acylation) and stereochemistry. Proanthocyanidins are the major polymeric phenolics, which differ in the number and selection of monomeric flavanols (polymerization degree) and the galloylation level (Mattivi et al. 2009). Tannins can be hydrolyzed under favorable pH conditions in gallic acid (from the gallotannins) or in ellagic acid (from the ellagitannins) (Teixeira et al. 2013).

3.5

Anthocyanins

Anthocyanins are a series of pigmented metabolites present in black-berried grapes, which are synthesized in the skin and stored in the vacuole during the second phase of berry growth. The UDP-glucose:flavonoid-3-O-glucosyltransferase (UFGT) is in

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Fig. 5 Chemical structures of the main flavanols in grapes. (Drawn by the authors with ChemSketch (ACD/Labs)) Fig. 6 Chemical structures of the most important glucosylated anthocyanins in grapes. (Drawn by the authors with ChemSketch (ACD/Labs))

charge of their stabilization by glycosylation. The main grapevine anthocyanins are the cyanidin-3-O-glucoside and peonidin-3-O-glucoside (di-hydroxylated forms), and the delphinidin-3-O-glucoside, petunidin-3-O-glucoside, and malvidin-3-O-glucoside (tri-hydroxylated forms). In addition, peonidin, petunidin, and malvidin can further be methylated, increasing their stability and promptly influencing the berry color, (Fig. 6).

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Terpenoid Compounds in Grapes

Terpenoid compounds can be obtained from two unrelated pathways: the plastid MEP (methyl-erythritol-4-phosphate) pathway or the cytosolic MVA (mevalonate) pathway. In any case, both pathways end with the synthesis of isopentenyl pyrophosphate (C5), which represents the building block of all terpenes, whose synthesis happens via specific prenyltransferases. Monoterpenes (C10) and tetraterpenes (C40) are produced in the plastid by geranyl pyrophosphate synthase and geranylgeranyl pyrophosphate synthase, while sesquiterpenes (C15) are formed in the cytosol by the farnesyl pyrophosphate synthase.

4.1

Monoterpenes

Up to 60 putatively terpene synthases (TPS) have been identified in the vinifera genome, some of them already functionally characterized (Martin et al. 2010). For more information, readers are referred to a recent review by Lin et al. (2019). Monoterpenes (C10) are compounds recognized as being involved in grape aroma, providing flower and fruity notes. The most aromatic monoterpenes in grapes are linalool (and its oxides, furanoid and pyranoid), geraniol (and its isomer nerol), citronellol, ho-trienol, α-terpineol and terpinen-4-ol, and cis-rose oxide (Mateo and Jiménez 2000) (Fig. 7). Monoterpenes diversity in grape berries arises from the linalool oxidative metabolism (Ilc et al. 2016), although the enzymes involved in this process have not yet been identified. In fact, geraniol can be converted to nerol or reduced to citronellol by an unknown isomerase and reductase, respectively. Moreover, hydroxylation and cyclization of citronellol can form cis and trans-rose oxide (Luan et al. 2005). The majority of monoterpenes are glycosylated in grapevine. Up to now, only three genes encoding for glycosyltransferases have been indicated to participate in this process (Bönisch et al. 2014a,b; Li et al. 2017). In their glycosylated forms, molecules are bound to sugar moiety and are not perceived, therefore, named as the nonvolatile fraction. Several hydrolysis mechanisms (acid or enzymatic) can free these bound terpenes during must fermentation or wine aging.

4.2

Sesquiterpenes

Sesquiterpenes (C15) are suggested to play a less important role in grape aroma, as they are generally found in concentrations lower than the olfactory perception threshold. Rotundone has been highly investigated in recent years (Fig. 7) due to the peppery character it confers to some black-berried (e.g., ‘Cabernet Sauvignon’, ‘Syrah’) and white-berried (e.g., ‘Grüner Veltliner’, ‘Riesling) grape cultivars, and derived wines (Siebert et al. 2008; Caputi et al. 2011). Interestingly, the rotundone biosynthesis has been indicated to be linked to a specific terpene synthase coding for α-guaiene, the rotundone precursor (Drew et al. 2015).

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Fig. 7 Chemical structures of the major monoterpenes and sesquiterpenes in grapes. (Drawn by the authors with ChemSketch (ACD/Labs))

4.3

Tetraterpenes

Tetraterpenes in grapes are represented by carotenoids (C40), a group of pigments commonly found in different flowers and fruits. They participate in light absorption processes and, due to their antioxidant properties, shield the photosystems from photooxidative degradation. The grapevine carotenoid metabolic pathway has been characterized by a comparative genomics approach (Young et al. 2012). Following this work, phytoene is formed by joining two molecules of geranylgeranyl pyrophosphate by phytoene synthase (PSY). In this regard, this first step is suggested to be the rate-limiting reaction of carotenoid biosynthesis. Then, phytoene is modified by four consecutive desaturation reactions by a phytoene desaturase, a carotene isomerase, a carotene desaturase, and a carotenoid isomerase (PDS/PDH, ZISO, ZDS, CISO), that end with the production of lycopene. Then, lycopene cyclases (LBCY) form α- and β-carotene, which triggers the formation of a series of carotenoid compounds, such as lutein and zeaxanthin, antheraxanthin and violaxanthin through different hydroxylation reactions (Fig. 8). The conversion of violaxanthin into neoxanthin represents the last reaction in the core carotenoid biosynthetic pathway, which is done by a neoxanthin synthase (NSY). The process of metabolite

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Fig. 8 Chemical structures of the major carotenoids in grapes. (Drawn by the authors with ChemSketch (ACD/Labs)) Fig. 9 Chemical structures of the representative C13norisoprenoids in grapes. (Drawn by the authors with ChemSketch (ACD/Labs))

interconversion between zeaxanthin and violaxanthin and between lutein and lutein 5,6-epoxide, named the xanthophyll cycle, is known to be involved in plant photoprotection processes. Thus, this conversion helps dissipate the excess of light energy in plant photosystems, shielding the photosynthetic apparatus. Carotenoid levels generally are higher during the first phase of berry growth, decreasing during berry ripening. Interestingly, only two carotenoids (zeaxanthin and antheraxanthin) have been reported to increase during berry ripening, reaching their maximum accumulation at harvest time. Further modifications can occur to the end-products of the carotenoid pathway (neoxanthin and violaxanthin), which end up synthesizing compounds like abscisic acid, strigolactone, or flavor and aroma-related compounds like C13-norisoprenoids (Lashbrooke et al. 2013). Within them, there are β-ionone and β-damascenone (Fig. 9), suggested to contribute to the grape floral and fruity aroma. In this regard, β-ionone is the direct cleavage metabolite of β-carotene, while 3-hydroxy-β-ionone

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(a β-ionone derivative) represents the one of zeaxanthin and lutein. On the contrary, β-damascenone results from a multistep reaction starting with the dioxygenase cleavage of neoxanthin, producing the precursor ketodiol, which undergoes several acid-catalyze conversions (Sefton et al. 2011).

5

Vitamins and Other Compounds

Vitamins are of utmost importance because of their impact on human health and, above all, because we cannot synthesize them. Consequently, the only source for the human being is via dietary intake. Vitamins showing strong antioxidant potential are both water-soluble vitamins (such as vitamin C) and lipid-soluble (such as vitamin E). Ascorbic acid, or vitamin C (Fig. 10), is a major soluble antioxidant agent, supplying renewing protection against the damages inflicted by reactive oxygen species (ROS). In grapes, the content of vitamin C is relatively low compared to other fruits, like citrus. In this regard, it is known that grapevines use ascorbic acid as a precursor of tartaric acid, which belongs to the primary organic acids synthesized in grapes (together with malic acid), and the end-product of the irreversible ascorbic acid catabolism (Burbidge et al. 2021). The biosynthesis of ascorbate in mitochondria can follow different pathways. The most studied one is the Smirnoff-Wheeler pathway (known as the D-mannose/L-galactose pathway), which in grapes is highly active in immature green berries. It converts D-glucose6-phosphate into GDP-D-mannose, then into GDP-L-galactose and L-galactono1,4-lactone, to ultimately produce ascorbic acid. The alternative biosynthetic pathway originates from methyl-galacturonate, a pectin degradation product, that is converted into L-galactonate, re-joining the Smirnoff-Wheeler pathway intermediate L-galactono-1,4-lactone. This alternative route is suggested to be the most common one in grape berries after veraison (Melino et al. 2009). Tocochromanols (comprised tocotrienols and tocopherols, collectively termed vitamin E) are a group of antioxidants known for preventing lipid oxidation (Fig. E). The structure of vitamin E holds a polar chromanol head group derived from the shikimate pathway and a hydrocarbon tail of isoprenoid origin. In this regard, tocotrienols and tocopherols are differentiated by containing a phytyl or a geranylgeranyl chain, respectively. Within each group of tocochromanols, molecules can be additionally distinguished in α-, β-, γ-, and δ- molecules based on the number and position of additional methyl groups present in the chromanol ring. Tocochromanols are primarily stored in the seed of grape berries (Fig. 11).

Fig. 10 Chemical structures of the ascorbic acid. (Drawn by the authors with ChemSketch (ACD/Labs))

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Fig. 11 Chemical structures of the tocochromanols. (Drawn by the authors with ChemSketch (ACD/Labs))

6

Genetic Resources and Extent of Genetic Diversity for Health-Related Compounds in Grapes

6.1

Diversity in the Muscadinia Subgenre

Grapes are part of the genus Vitis, a member of the Vitaceae plant family. According to morphological, anatomical, and cytological characteristics, species of the genus Vitis can be separated into two subgenera: Muscadinia (2n ¼ 2x ¼ 40) and Vitis (formerly known as Euvitis; 2n ¼ 2x ¼ 38) (Aradhya et al. 2013). The natural occurrence of Muscadinia is narrowed to the Southeastern USA and Eastern Mexico (Aradhya et al. 2013), and it includes 2–3 species, of which only about 100 V. rotundifolia cultivars and interspecific hybrids have commercial interest (Yuzuak and Xie 2022). Fruits from these cultivars are commonly known as muscadine grapes, and they are grown for fresh fruit production and wine, juice, jam, and jelly elaboration. Muscadine grapes are suggested to have multiple health benefits, which result from their high content of phenolic compounds, namely anthocyanins and proanthocyanidins (Yuzuak and Xie 2022). Screening results suggest a high diversity in their levels of phenolic compounds, which are majorly found in grape skins and seeds (Pastrana-Bonilla et al. 2003). Through the analysis of 10 muscadine cultivars (‘Carlos’, ‘Cowart’, ‘Early Fry’, ‘Fry’, ‘Ison’, ‘Late Fry’, ‘Noble’, ‘Paulk’, ‘Summit’, and ‘Supreme), Pastrana-Bonilla et al. (2003) highlighted the high concentration of ellagic acid, myricetin, quercetin,

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kämpferol, and trans-resveratrol in muscadine grape skins, with concentration values ranging from 6.2 to 22.2, 1.8 to 19.6, 0.5 to 3.8, 0.2 to 3.8, and 0.1 to 0.2 mg/100 g, respectively. In seeds, epicatechin, catechin, and gallic acid dominate (Pastrana-Bonilla et al. 2003). Focusing on the ellagic acid and its precursors in eight muscadine cultivars (‘Albermale’, ‘Carlos’, ‘Cowart’, ‘Doreen’, ‘Fry’, ‘Georgia Red’, ‘Nesbitt’, and ‘Noble’), Lee and Talcott (2004) reported a range of variation of 0.8 to 16.3, 0.7 to 11.5, and 58.7 to 190.0 mg/100 g, for free ellagic acid, ellagic acid glycosides, and total ellagic acid in the skin of ripe grapes, respectively. Regarding total anthocyanins, a wide range of variation in muscadine grapes has been indicated too, with an expected marked difference between black-berried cultivars (like ‘Floriana’ and ‘Noble’, with more than 10.0 mg/100 g dry weight) and white-berried cultivars (like ‘Sweet Jenny’, ‘Watergate’, and ‘Welder’, less than 0.03 mg/100 g dry weight) (Campbell et al. 2021). The overall high phenolic content of muscadine cultivars indicates their potential to develop new grape varieties with better fruit composition. However, hybrids between the Muscadinia and Vitis subgenera are generally infertile due to the discrepancy in the number of their chromosomes (Töpfer et al. 2011), limiting the usefulness of muscadine grapes in grapevine breeding programs.

6.2

Diversity Among Grape Vitis Species

The precise number of species belonging to the subgenus Vitis is challenging to estimate due to either hybridization between species or clinal variation within species. Thus, this subgenus is suggested to include between 60 and 70 species naturally occurring in Eastern Asia and North America and the only European grapevine species, V. vinifera (Péros et al. 2021). Comparative studies of the phenolic content and composition in ripe berries indicate significant differences among and within Vitis species. For example, the analysis of 147 grape accessions from 16 different Vitis species suggested that V. rupestris and V. acerifolia have the highest total phenolic concentration (20.2 mg/g and 19.2 mg/g fresh weight, respectively). On the other hand, V. monticola, V. champinii, and V. labrusca have the lowest concentration (3.8, 5.2, and 5.2 mg/g fresh weight) (Liang et al. 2012). Interestingly, these values are considerably higher than those reported for most of the V. vinifera L. cultivars analyzed by Liang et al. (2011) using the same methodology (1.4 mg/g fresh weight). A wide difference in anthocyanins content and composition between cultivars of different Vitis species has also been described. For example, delphinidin-derivatives might account for more than 60% of anthocyanins in species like V. novaeangliae and V. champinii, while it might be less than 20% in V. monticola (Liang et al. 2012). A wide range of variation for malvidinderivatives (the dominant anthocyanins in vinifera cultivars (Sikuten et al. 2021) has been indicated too, accounting for up to 30% of total anthocyanins in species like V. cinerea, V. palmata, V. vulpina, V. coignetii, and V. monticola, to less than 2% (V. novaeangliae) (Liang et al. 2012). The concentration of total flavanols and flavonols also varies among species. Thus, V. palmata and V. coignetii have been indicated as some of the species with the highest content of flavanols, while

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V. monticola and V. champinii have some of the lowest (Liang et al. 2012). Besides, V. palmata, V. doaniana, and V. novaneangliae are some of the species rich in flavonols, which contrasts with the low content reported in species like V. monticola, V. champinii, and V. cinerea (Liang et al. 2012). Substantial differences among Vitis species have also been indicated for stilbenes content and composition (Gabaston et al. 2020). As observed, non-vinifera Vitis species hold a wide range of variability for total phenolic content and individual phenolic compounds, which are of high interest for grape improvement. Nevertheless, some of these non-vinifera species carry certain off-flavors and undesirable aromas that, generally, are not positively perceived by consumers. As a result, the most common and realistic source of variability for developing novel grape cultivars with high fruit phenolic content is the one available within the V. vinifera species.

6.3

Diversity Among Wild and Cultivated Vitis vinifera Grapes

Most table and wine grape cultivars cultivated worldwide are part of the V. vinifera species, autochthonous of the Mediterranean Sea, southern and central Europe, northern Africa, and southwest and central Asia (Töpfer et al. 2011). Nowadays, two forms can still be found in these areas, the cultivated grapevine (V. vinifera subsp. sativa (or vinifera)) and its wild ancestor (V. vinifera subsp. sylvestris). Multiple sources indicate that the domestication process started in the Transcaucasian region during the early Neolithic Period (Myles et al. 2011). Genetic analyses based on different molecular markers indicate that the genetic diversity available in the V. vinifera subsp. sativa pool is highly structured, being linked to grape primary use (table or wine) and geographical origin (Bacilieri et al. 2013; Emanuelli et al. 2013; Laucou et al. 2018). Excluding novel grape cultivars achieved in breeding programs, these works indicate a major genetic division into four groups of cultivars: (i) table grapes from Eastern Mediterranean, Caucasus, Middle, and Far East countries, (ii) wine grapes from Western and Central Europe countries, (iii) wine grapes from the Balkans and Eastern Europe countries, and (iv) wine and table grapes from the Iberian Peninsula and the Maghreb. Further analyses indicate that this grouping correlates with significant differences in several grapevine reproductive and quality traits (Nicolas et al. 2016; Migicovsky et al. 2017). In this regard, differences in the phytochemical composition of V. vinifera subsp. sativa grapes between genetic groups have also been indicated (Teixeira et al. 2013; Sikuten et al. 2021). In a comparative study between 11 sylvestris accessions from the eastern Adriatic region and three sativa cultivars (‘Merlot’, ‘Plavac Mali’, and ‘Xinomavro’), BudicLeto et al. (2018) indicated some significant differences in the phenolic content between subspecies, like those affecting the content of delphinidin-derivatives (higher in sylvestris), and of acylated anthocyanins (higher in sativa). Interestingly, the authors found two black-berried sylvestris accessions that lack acylated anthocyanins in berry skins, which agrees with previous findings by Revilla et al. (2012). The lack of acylated anthocyanins in berry skins is a rare characteristic in sativa cultivars, and it has only been observed in a few cultivars like the black-berried cultivar ‘Pinot Noir’ (and its offsprings and somatic variants) or the slightly colored

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cultivar ‘Gaglioppo’ (Mattivi et al. 2006). Acylated anthocyanins in grapes not only increase phenolic fruit content but also stabilize the red color in wines during winemaking, leading to wines with a slight blue tint (Revilla et al. 2012). Regarding delphinidin-derivatives, delphinidin 3-O-glucoside was more abundantly found in sylvestris genotypes (on average, 22.5% of total anthocyanin content) than in the sativa cultivars ‘Merlot’, ‘Plavac Mali’, and ‘Xinomavro’ (on average, 10.3, 13.3, and 4.2%, respectively) (Budic-Leto et al. 2018). Given its relevance for grape production, the phenolic content and composition of V. vinifera subsp. sativa cultivars have been screened in a vast number of genotypes. The analysis of the phenolic profiles of ripe berries from 344 cultivars by HPLC-MS revealed 36 phenolic compounds, including 16 anthocyanins, six flavonols, six flavanols, six hydroxycinnamic acids, and two hydroxybenzoic acids (Liang et al. 2011). Instead, the use of high-performance liquid chromatography coupled with triple quadrupole mass spectrometry analysis enabled the detection and quantification of 96 phenolic compounds, including the constitutive units of proanthocyanidins present in the skins of ripe grapes from 279 cultivars, providing highly detailed data on grape polyphenol composition (Pinasseau et al. 2017). These comprehensive analyses have suggested that polyphenol content varies among cultivars according to their primary use, with an overall higher level for all compounds (but hydroxycinnamic acids) in wine grapes than in table grapes (Liang et al. 2011). Nevertheless, the differences in phenolic content between cultivars of different use might be an indirect effect of their different behavior to factors affecting polyphenols biosyntheses, like precocity (Migicovsky et al. 2017) or the response to abiotic and biotic factors (Pinasseau et al. 2017). Considering only wine grapes, Sikuten et al. (2021) indicated that genetic and geographical background also affects the different phenolic content and composition between cultivars. These findings suggest that the evolution of the biosynthetic pathways leading to current grape phenolic content and composition might have been affected by regional environmental conditions, likely shaped by additional human-driven selection processes. As expected, substantial differences in the total content of anthocyanins have been observed between grape cultivars of different berry colors. According to Liang et al. (2011), the average total anthocyanin content of black-berried cultivars is 30 times higher than the one found in pink-berried cultivars and 10 times higher than that of red-berried cultivars. As inferred from wine or table grapes studies, this effect is independent of the primary use of the cultivar. Regarding white-berried cultivars, only traces of anthocyanins have been detected from berry skin extracts in concentrations 5,000–60,000 times lower than in black-berried cultivars (Arapitsas et al. 2015). An interesting dietary source of anthocyanins is grapes from red-fleshed or ‘teinturier’ cultivars, which show an ectopic accumulation of anthocyanins in other plant organs, including berry flesh (Röckel et al. 2020). As a result, in proportion, grapes from ‘teinturier’ cultivars have a superior concentration of anthocyanins compared with white-fleshed cultivars (Kong et al. 2021; Röckel et al. 2020). Most of the available ‘teinturier’ cultivars derive from the French cultivar ‘Teinturier’, whose red-fleshed phenotype has been recently associated with the presence of a repetitive DNA element in the promoter of the VviMybA1 gene (Röckel et al. 2020). In addition, other non ‘Teinturier’-related red-fleshed cultivars

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have been detected, like ‘Gamay de Bouze’, ‘Gamay Fréaux’ (somatic variants of ‘Gamay’), and ‘Pinot Teinturier’ (a somatic variant of ‘Pinot Noir’) (Kong et al. 2021). Interestingly, cases of somatic variation causing red-fleshed berries have also been identified in table grape cultivars (Zhang et al. 2018), opening a promising sector for developing red-fleshed table grapes of higher nutritional quality. On the contrary, berry skin color does not seem to significantly impact the content of other phenolic compounds (Liang et al. 2011). Flavanols are the major non-anthocyanin polyphenols of grapes, followed by flavonols. There is significant variability in the content of both groups of polyphenols, with up to a 100- and 176-fold variation between cultivars for flavanols and flavonols, respectively (Liang et al. 2011; Pinasseau et al. 2017). In this line, the cultivars ‘Jampal’ and ‘Muscat St. Laurent’ are suggested to be especially rich in flavanols, while ‘Touriga Nacional’ and ‘Dornfelder’ are in flavonols (Liang et al. 2011). The concentration of hydroxybenzoic and hydroxycinnamic acids has been indicated to vary widely between cultivars (Liang et al. 2011; Pinasseau et al. 2017), as does that of stilbenes (Gatto et al. 2008; Pinasseau et al. 2017). Regarding stilbene derivatives, the ratio between trans-resveratrol, transpiceid, and cis-piceid also varies widely between cultivars (Gatto et al. 2008). The characterization of different grape cultivars indicates that lutein and β-carotene are the major components of grape carotenoids, with significant differences between genotypes. As an example, the comparative analysis of nine grape cultivars grown under conventional conditions indicated a varying concentration ranging between 470.9  46.0 and 825.0  39.0 0 μg/kg for lutein in grape skins (for cultivars ‘Aromat de Iaşi’ and ‘Feteascaregală’, respectively), and between 229.6  18.0 and 593.2  35.0 μg/kg for β-carotene (for ‘Napoca’ and ‘Muscat Ottonel’ grape skins, respectively) (Bunea et al. 2012). Besides, different works indicate that vitamin content also varies significantly among grape cultivars. For example, vitamin C content varied between 11.2  0.1 and 35.7  0.3 mg/100 g in a group of nine Turkish table grape cultivars (Eyduran et al. 2015), a similar range to the one found in the analysis of 10 table grape cultivars from Syria (from 9.7  1.2 to 30.9  3.3 mg/100 g fresh weight) (Khalil et al. 2017). Regarding vitamin E content (α- and γ-tocopherols), the analysis of six table grape cultivars indicated a range of variation from 5.0 to 8.1 mg/kg fresh weight (values for ‘Italia’ and ‘Muscat de Hambourg’ cultivars, respectively) (Aubert and Chalot 2018). In the analysis of 15 wine and table grape cultivars, the total tocopherol content (α-, β-, γ-, and δ- tocopherols) was found to range from 29.2  1.6 (in ‘Muscat of Alexandria’) to 102.7  1.3 (‘Syrah’) mg/kg dry weight in bagasse (skin and pulp), and between 6.0  1.1 (‘Semillon’) to 25.9  1.7 (‘Trakya Ilkeren’) mg/kg dry weight in seeds (Tangolar et al. 2011). Following this work, the principal use of the cultivar (table or wine) does not significantly affect vitamin E content, which is dominated by α- and γ-tocopherols in grapes in both cases. Another source of genetic variation affecting the content of health-related compounds in grapes is caused by somatic variation events. Spontaneous somatic mutations might cause changes in relevant phenotypic traits, deriving in clonal variation (Carbonell-Bejerano et al. 2019). To the interest of this chapter, different works report the identification of clones of some cultivars with significantly different phenolic content and composition (Ferrandino and Guidoni 2010; Muñoz et al. 2014; Pantelić et al. 2016; Royo et al. 2021). For example, the analysis of the

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phenolic amount in ripe berries of four clones of ‘Merlot’ revealed a fold variation of 2.0, while that of four clones of ‘Cabernet Franc’ was set at 3.9 (Pantelić et al. 2016). Similarly, the maximum differences observed in the total phenolic content within 30 ‘Tempranillo Tinto’ clones rose to 3.5-fold (Lemos et al. 2020). Following this work, the maximum fold variation in total anthocyanins was found to be 2.3, while one of the total flavonoids was 1.6.

7

Molecular Mapping Studies for Health-Related Compounds Content in Grapes

Understanding the genetic architecture of the accumulation of health-related compounds in grapevine berries implies identifying the number and location of the genomic regions (quantitative trait loci, QTLs) affecting trait variation, as well as their interaction. This information is essential for grapevine improvement, as it can be converted into practical knowledge for marker-assisted selection processes in modern breeding programs. Conventionally, QTL mapping is performed in populations segregating for the trait of interest through detecting significant associations between genetic markers segregation and trait phenotypic variation. This approach has been successfully applied over the past decades to reveal the genetic basis of traits related to the phenotypic determination of crop yield, grape quality, and adaptation mechanisms to abiotic and biotic factors. More recently, genomewide association studies (GWAS) have also been implemented in different grapevine diversity panels to explore the genetic architecture of complex traits. Here, we focus on the works exploring the genetic basis of the biosynthesis of different healthrelated compounds in V. vinifera grape berries.

7.1

Anthocyanins Biosynthesis: The Berry Color Locus

Phenolic compounds are the most abundant and important health-related compounds in grape berries. The color of grape berries (and grape-derived products) is mainly associated with the content and composition of anthocyanins in berry skins. In addition, anthocyanin content clearly impacts the antioxidant potential of grapes. Given the relevance of berry color on fruit quality, the genetic basis of anthocyanins synthesis and accumulation in berry skins has been of great interest to the scientific community, and it can be reflected by the numerous works exploring this topic (see Ferreira et al. (2018) for a recent review). Early genetic studies in different V. vinifera progenies segregating for berry color indicated that this trait is mainly regulated by a single locus on chromosome 2, named berry color locus. The same locus was found when using quantitative data of total anthocyanins extracted from berry skins (Fournier-Level et al. 2009; Sun et al. 2020), which added evidence to support the role of anthocyanins on berry skin color determination. The oligonenic architecture of this trait has also been found in different GWAS (Myles et al. 2011; Migicovsky et al. 2017; Laucou et al. 2018), a procedure that screens functional variation in a

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wider set, usually employing a panel of cultivars bearing most of the phenotypic variability existing for the target trait available at a species level. Further molecular studies indicated that the berry color locus spans over a 200-kb region on chromosome 2, which encompasses a cluster of four MYB-type transcription factors: VviMybA1, VviMybA2, VviMybA3, and VviMybA4 (Kobayashi et al. 2004; This et al. 2007; Walker et al. 2007; Fournier-Level et al. 2009). Different works have evidenced that both VviMybA1 and VviMybA2 are necessary for successfully accumulating anthocyanins in berry skins, indicating that white-berried cultivars (which lack anthocyanins in berry skins) only appear when these two genes are disrupted. This now widely accepted mechanism was first explored by Kobayashi et al. (2004) through the comparative study of the white-berried cultivar ‘Italia’ and its red-berried somatic variant ‘Ruby Okuyama’, which accumulates anthocyanins (mainly cyanidin-3-O-glucosides) in berry skins. Molecular and genetic studies revealed that the absence of anthocyanins in berry skins was tightly linked to the presence of a retrotransposon (called Gret1, from Grape retrotransposon 1) in the promoter of the VviMybA1 gene sequence, which causes a non-functional allele. Thus, if this allele is found in homozygosis (as in ‘Italia’) it causes an absence of anthocyanins in berry skins, which derives in non-colored berries. This mechanism was then observed in a high number of cultivars of different origins and uses, which confirmed the role of VviMybA1 on berry color variation at a species level (Lijavetzky et al. 2006; This et al. 2007). Later on, Walker et al. (2007) indicated that berry color loss is due to modifications in both VviMybA1 and VviMybA2. Thus, besides the inclusion of the Gret1 retrotransposon in VviMybA1 first indicated by Kobayashi et al. (2004), two additional non-conservative mutations in VviMybA2 are needed to inhibit the synthesis of anthocyanins in berry skins. Sequence analyses characterized these two mutations as (i) a single nucleotide polymorphism (SNP) causing a non-conservative amino acid substitution and (ii) a deletion of a dinucleotide that alters the reading frame in the functional VviMybA2 allele. Considering that VviMybA1 and VviMybA2 are closely linked on the same chromosome region, they are usually considered part of a single MYB haplotype. This haplotype configuration determines a “white allele,” which harbors non-functional alleles for both VviMybA1 and VviMybA2, and two different “colored alleles,” which harbor (i) VviMybA1 functional and VviMybA2 non-functional alleles, or (ii) VviMybA1 and VviMybA2 functional alleles (Ferreira et al. 2018). Functional analyses have indicated that both VviMybA1 and VviMybA2 are capable of inducing the VviUFGT gene expression (Walker et al. 2007). VviUFGT is the last gene of the phenylpropanoid pathway, and it has been suggested to be key for the biosynthesis of anthocyanins in berry skins and, consequently, berry pigmentation. As previously indicated, genetic variations in VviMybA1 have also been linked to the anthocyanin levels in the flesh of red-fleshed cultivars. After the analysis of a series of ‘teinturier’ cultivars, Röckel et al. (2020) associated the colored berry flesh phenotype with the presence of a 408-bp repetitive DNA element (called Grapevine Color Enhancer, GCE), found 338 bp upstream of the start codon in the VviMybA1 gene promoter region. Following this work, GCE has been found with varying repetitions (two, three, and five) in different cultivars. Interestingly, the number of

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GCE repeats correlates with the expression of VviMybA1 and VviUFGT genes, as well as with berry flesh color intensity. VviMybA3 sequence polymorphisms have also been significantly associated with berry color variation through a GWAS (Fournier-Level et al. 2009). However, it has been indicated that the cysteine-rich (CR) domain of the VviMybA3 gene is truncated, deriving into a non-functional protein with poor functional evidence in the accumulation of anthocyanins in berry skins and berry skin color variation. However, it has been recently revealed that VviMybA3 might contribute to regulating the accumulation of anthocyanins in berry flesh (Zhang et al. 2018). Finally, no associations between VviMybA4 sequence polymorphisms and anthocyanins content variation have been described (Fournier-Level et al. 2009), sustaining the observed lack of functional activity of this transcription factor in grape berry skins (Walker et al. 2007). Beyond the berry color locus, Deluc et al. (2008) found that another MYB transcription factor (VviMyb5b, located in chromosome 6) can activate several genes of the general anthocyanins biosynthetic pathway, but not VviUFGT. Following this work, VviMYB5b has been suggested to participate in regulating proanthocyanidins biosynthesis in developing grape berries. In addition, Cardoso et al. (2012) tested the association between berry color and anthocyanins content variation and the genetic diversity detected in 15 genes that are not part of the berry color locus but putatively involved in the synthesis or transport of anthocyanins. Modeling results indicated some significant associations between the content of anthocyanins in berry skins and several polymorphisms found in three MYB transcription factors (VviMYB11, VviMYBCC, and VviMYCB). These results suggest that other genes not included in the berry color locus might influence anthocyanins biosynthesis mechanisms, which agrees with the additional minor QTLs for grape berry color and/or anthocyanins accumulation found in other studies (Sun et al. 2020).

7.2

Flavonols and Flavanols Biosynthesis: The Role of VviMYBF1, VviMybPA1, and VviMybPA2

The genetic basis of how flavonols are synthesized and accumulated in mature grape berries was explored by analyzing 170 individuals from a ‘Syrah’‘Pinot Noir’ population segregating for flavonol content and composition (Malacarne et al. 2015). According to this work, the berry color locus exerts a significant effect on flavonol content variation, indicating a common genetic control between flavonols and anthocyanins biosynthesis. This result agrees with previous findings that indicated that the metabolic reactions leading to the biosynthesis of these two groups of phenolic compounds are (at least) partially connected (Mattivi et al. 2006). Besides this QTL, other genomic regions associated with the fine-tuning of flavonol biosynthesis were identified, including a series of flavonol-specific QTLs that do not co-localize with genomic regions previously associated with anthocyanin biosynthesis or berry color variation. The authors found a region on chromosome 7 associated with kämpferol variation, which co-localizes with one MYB-type transcription factor gene, VviMYBF1. Interestingly, expression and functional analyses of VviMYBF1 have

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indicated that this transcription factor is a significant regulator of flavonols biosynthesis in developing grape berries (Czemmel et al. 2009). Proanthocyanidins result from the polymerization of flavanol units. These compounds are secondary plant metabolites with multiple beneficial effects on human health, preferentially accumulated in berry skins and seeds. The genetic determinism of proanthocyanidin content in grape berries was first explored by considering two candidate genes: VviMybPA1 and VviMybPA2. Using a series of transcriptome and functional studies, these two MYB-type transcription factors have been proposed as the central regulators of proanthocyanidins biosynthesis in grape berries (Bogs et al. 2007; Terrier et al. 2009; Carrier et al. 2013). In fact, different functional studies indicate that VviMYBPA1 and VviMybPA2 induce the transcription of key enzymes of the flavonoid, which triggers the biosynthesis of anthocyanins, flavonols, and proanthocyanidins in berries (Bogs et al. 2007; Terrier et al. 2009). Nevertheless, different genetic mapping studies have indicated that proanthocyanidin content might be under a highly more complex genetic control. For example, the analysis of 191 individuals from a segregating population obtained from a ‘Syrah’  ‘Grenache’ cross revealed up to 43 and 103 QTLs for a series of skin and seed proanthocyanidins-content related traits (like total content or polymerization degree), respectively (Huang et al. 2012). These QTLs were virtually found on all chromosomes, suggesting a complex polygenic regulatory mechanism in berry skins and seeds. Interestingly, given the different numbers and positions of the QTLs identified for berry skins and seeds, results pointed out that the biosynthesis of proanthocyanidins in these two organs might be under different genetic regulation pathways. Based on a combination of QTL mapping and transcriptomic studies, Carrier et al. (2013) identified 20 genes in six chromosomes (1, 2, 3, 8, 14, and 17) as potential candidates to be involved in the proanthocyanidins biosynthetic pathway. Among them, three genes not previously associated with proanthocyanidins synthesis (VviMybC2-L1, VviGAT-like, and VviCob-like, in chromosomes 1, 3, and 17, respectively) were highlighted as promising candidates to be validated in subsequent works. Lastly, Huang et al. (2014) identified 21 eQTLs based on the transcript abundance of five downstream proanthocyanidins synthesis genes. Following this work, some of the more confident candidate eQTLs were related to genes linked to the general proanthocyanidins synthesis pathway, including VviDFR (in chromosome 18), VviLAR1 (chromosome 1), or VviLAR2 (chromosome 17).

7.3

Monoterpenes Biosynthesis: The 1-Deoxy-D-xylulose 5-Phosphate Synthase (DXS1) Activity

Other health-related compounds present in grape berries with antioxidant properties are monoterpenes. Grape monoterpenes have been classified into three categories: (i) free aroma compounds; (ii) free odorless polyols; and (iii) non-aromatic glycosidically bound forms of the monoterpenes (Mateo and Jiménez 2000). Given their contribution to the sweet and typical floral flavor of Muscat cultivars (Emanuelli et al. 2010), the genetic basis of the linalool, geraniol, and nerol content in grape

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berries has been explored in multiple works. Different QTL mapping studies have indicated that muscat aroma (and/or geraniol, linalool, and nerol levels) is under an oligogenic control (Doligez et al. 2006; Battilana et al. 2009; Duchene et al. 2009; Wang et al. 2020). Recent GWAS have supported this genetic architecture using sets of grapevine cultivars of different origins (Migicovsky et al. 2017; Yang et al. 2017; Laucou et al. 2018; Guo et al. 2019; Liang et al. 2019). All these works indicate that geraniol, linalool, and nerol content in grapes is controlled by a key QTL on chromosome 5, which co-localizes with VviDXS1 (Battilana et al. 2009; Duchene et al. 2009). This gene performs its action on the starting reaction of the plastidial MEP pathway (Battilana et al. 2009), whose functional role on monoterpene levels in grape berries was furtherly validated (Battilana et al. 2011). By association mapping, the causal SNP underlying this QTL has been identified (Emanuelli et al. 2010). Following this work, this SNP generates a non-neutral substitution present in the majority of Muscatflavored cultivars. Beyond this locus, other minor QTLs have also been indicated by QTL mapping in different progenies (Doligez et al. 2006; Battilana et al. 2009; Duchene et al. 2009), suggesting the potential involvement of additional genomic regions to the final content of monoterpenes in grape berries.

7.4

Carotenoids Biosynthesis: What Gene Is Prominent?

As previously indicated, different carotenoids have been found in grapes, enhancing their nutritional value. Nevertheless, the information available on the genetic basis of their content in grape berries is limited. Using a comparative genomics approach, Young et al. (2012) identified up to 42 genes putatively involved in the grapevine carotenoid biosynthetic pathway, scattered on 16 chromosomes. More recently, after a genome-wide screening study, Leng et al. (2017) identified a total of 54 putative carotenoid metabolism-related genes, which were found to be distributed on 17 chromosomes. Altogether, these two works suggested a complex genetic architecture for grapevine carotenoid biosynthesis and provided a list of candidate genes likely involved in carotenoid accumulation. Nonetheless, specific genetic mapping analyses (either QTL mapping or GWAS, or both) are still needed to uncover the genetic basis underlying the accumulation of carotenoids in grape berries.

8

Grape miRNAs and Their Likely Impact on Human Health

Plant bioactive metabolites such as polyphenols, monoterpenes, carotenoids, and tocopherols are suggested to be responsible for the beneficial effects of consuming fruits and vegetables on human health. Plant microRNAs (miRNAs) are new bioactive molecules that migrate from plants to mammalian cells through dietary intake, regulating specific genes and pathways, and resulting in interesting candidates for dietary therapy approaches (Sanchita Trivedi et al. 2018; Li et al. 2021b).

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miRNAs are endogenous, highly conserved, non-coding single-stranded RNAs. Specific miRNA genes code for these molecules, which consist of 18–24 nucleotides. At the post-transcriptional level, they can regulate gene expression by stimulating target messenger RNA (mRNA) degradation, translational repression, and chromatin modification of the corresponding target gene/s. Today, approximately half of the protein-coding mRNAs are thought to be influenced by miRNAs. miRNA gene silencing machinery is highly conserved in eukaryotes, even if notable differences exist between plants and animals concerning miRNA biogenesis, maturation, and mode of function (Achkar et al. 2016). These differences might contribute to the plant miRNA’s high stability compared to their animal counterparts, explaining plant miRNA cross-kingdom abilities. Previous findings have revealed that plant miRNAs can survive adverse conditions such as low pH levels, high temperatures, ribonuclease and RNase activities, and digestive processes like food homogenization and absorption processes. In plants, adding a methyl group to the sugar present at the 30 -terminal nucleotide safeguards miRNAs from exonuclease degradation and 30 -uridylation. Moreover, the high plant miRNA GC content determines the absence of RNase digestion motifs (Yang et al. 2018). The nexus between Argonaute proteins or cofactors, such as high-density lipoproteins, with miRNA avoid miRNA decay, and combining miRNA with plant secondary metabolites creates a favorable setting that is able to inhibit RNAse activities. The packaging of plant miRNAs into microvesicles or exosomes protects their transportation before being absorbed via intestinal epithelial cells (van der Pol et al. 2012). In recent years, plant miRNAs have attracted the attention of researchers for their cross-kingdom abilities and capability of regulating gene expression and cellular processes in humans through dietary intake. The first cross-kingdom study describing the detection of an exogenous plant miRNA (miR168a) in human serum was reported in 2012 (Zhang et al. 2012). Numerous other studies followed this pioneering work, and such studies can be found for diverse plant species like maize (Li et al. 2019), strawberry (Cavalieri et al. 2016), lettuce (Zhang et al. 2019), cabbage (Liang et al. 2014), spinach (Hou et al. 2018), and soybean (Chin et al. 2016). However, to our knowledge, only one cross-kingdom study has been conducted on grapes (Svezia et al. 2020). Following this work, authors proved the effects of grape miRNAs on human health by evaluating the cardioprotective role of cv. ‘Sangiovese grape juice intake, using three different models: a murine model of myocardial infarction, murine coronary endothelial cells, and healthy human subjects. More specifically, they investigated the grape miRNAs impact on the natriuretic peptide system gene expression in murine coronary endothelial cells culture, representing the central auto-/paracrine signals of cardiac remodeling in infarcted patients. Remarkably, the survival of such cell lines was significantly linked to an intensified uptake of grapevine miRNAs. In the same work, for the first time, the authors detected the grape miRNAs in the human plasma of four healthy humans after seven days of ‘Sangiovese’ grape juice regular intake. Interestingly, the levels of two conserved plant miRNAs (Vvi-miR159-3p and Vvi-miR166-3p) increased in the bloodstream after ‘Sangiovese’ grape juice consumption.

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To date, the ability of plant miRNAs to regulate key pathways in mammalian cells has been reported in an increasing number of studies. However, despite these promising results, works report contradicting evidence of cross-kingdom gene regulation by plant miRNAs, and the role of plant miRNAs on human metabolism regulation is still highly debated. In plants, miRNAs are implicated in many functions related to growth and development, fruit ripening processes, signal transduction, response to abiotic and biotic stresses, and secondary metabolites modulation. In grapes, the publication of the genome sequences eased the discovery of miRNAs and their putative role in grapevine molecular regulatory networks. Many studies have evaluated the role of grape miRNA in developmental processes and stress responses. Belli Kullan et al. (2015) described the abundance of miRNAs in several grapevine tissues (including berries) at different developmental stages of the grapevine cultivar ‘Corvina’. Accordingly, the distribution and abundance of miRNAs across samples are suggested to reflect the functional specificity of different organs, which ultimately aids in defining organ identity. Besides, Paim Pinto et al. (2016) compared the distribution of miRNAs in two grapevine cultivars (‘Cabernet Sauvignon’ and ‘Sangiovese’) collected in different vineyards and developmental stages. This work showed that both the developmental stage and cultivar influence miRNAs more than the vineyard. Chitarra et al. (2018) developed the first online database of grapevine miRNA candidates, called miRVIT. As a proof of concept study, this tool was successfully used to explore the response of ‘Barbera’ vines infected by Flavescence dorée, one of the most dangerous phytoplasma diseases. The ingestion of plants with an added concentration of functional miRNAs in the diet has been recently suggested as a potential solution to face specific clinical situations (Sanchita Trivedi et al. 2018; Li et al. 2021a). However, further investigations and validations are required prior to this recommendation, and specific studies on many related topics (including how miRNAs are transported or absorbed by the human system) are needed to avoid any potential risks.

9

Applicability of Breeding Techniques in Grapevine Improvement

Improving crop traits, including nutritional value or quality, is critical to meet the growing population demands, which puts pressure on land use due to urbanization. Indeed, as a consequence of population growth and negative climate change effects on agricultural systems, there is a need to ensure food availability while maintaining (or increasing) food quality. In such context, crop breeding approaches (both conventional and modern activities) can improve crop productivity and quality features. However, some limitations have hindered grapevine breeding activities. Despite its importance, grapevine genetic improvement did not begin until the nineteenth century as a defense strategy against the arrival of powdery mildew, phylloxera, and downy mildew from North America (Töpfer et al. 2011). Although grapevine can be improved through several breeding techniques, these are difficult and timeconsuming due to long generation cycles and the time required for selecting and

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testing reliable progenies (juvenile stages). In addition, the grapevine is a highly heterozygous crop that exhibits inbreeding depression (Dalla Costa et al. 2019; Campos et al. 2021). Despite these limitations, grapevine improvement efforts could result in high-value products with high content of phenolic, aromatic, and vitaminic compounds that might provide beneficial effects linked to their antioxidant, anti-inflammatory, and anticancer properties, among others.

9.1

Conventional Breeding

Conventional grapevine breeding has focused on using strategies to counteract pathogens’ negative effects and abiotic stressors on grapevine production. Chemical control is the most efficient way to deal with pathogens, but this approach has negative environmental, ecological, and sociological impacts. Thus, a way to reduce the use of chemicals is the development of novel resistant grapevine cultivars by the introgression of resistance R-loci from North American and Asian Vitis species into elite vinifera cultivars, developing more tolerant/resistant grapevine genotypes with high fruit quality (Töpfer et al. 2011; Pertot et al. 2017). To allow the preservation in time of the tolerant/resistant introgressed genes, gene pyramiding is used, aimed at incorporating more than one effective resistance gene (Pedneault and Provost 2016). This technique permits the parallel control of various pathogens or traits linked to grapevine resistance or tolerance. Moreover, these new genotypes might develop from multiple “back-crosses” steps with the elite cultivar, aimed to maintain a high percentage of the V. vinifera genome to preserve elite grape and wine quality properties. In this regard, several countries such as Austria, Chile, France, Germany, Hungary, Italy, Spain, and the USA have developed different wine and/or table grape breeding programs to obtain new cultivars with better yield and quality properties. The development of improved genotypes holding genes from non-vinifera individuals while maintaining a high proportion of V. vinifera in their pedigree was speeded up by the use of Marker-Assisted Selection (MAS) (Pedneault and Provost 2016). In this sense, informative genetic markers associated with relevant grapevine features like berry size, acidity, color, aroma, and fruit ripening time have also been discovered in the grapevine. Most of these markers are reported in the “Vitis International Variety Catalogue – VIVC” website (https://www.vivc.de/docs/ dataonbreeding/20220218_Table%20of%20Loci%20for%20Traits%20in%20Grape vine.pdf). Within them, some markers linked to genetic loci involved in the synthesis of metabolites with impact on the nutraceutical content of grapes can be found. For example, the available markers for berry color and muscat aroma (based on VviMybA1 and VviDXS1 gene sequences, respectively) could be used to trace the presence/absence of alleles related to increased color and increased aroma (so, to trace the presence/absence of antioxidant compounds) in breeding programs. The availability of these markers represents an interesting starting point to work on improving the nutraceutical properties of grapes via MAS. The conventional breeding process comprises three stages: hybridization, linefixation, and field trials. Plant breeding is an extensive logistical procedure requiring hundreds of thousands of vines in the hybridization and line-fixation stages;

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however, the amount of plants is drastically lowered to small-selected vines in advanced breeding lines by the end of the breeding process. Therefore, considering the presented limitations, conventional breeding is hardly exploitable. Specifically, because of a prolonged lifecycle, severe inbreeding depression, and complex genetic control of enological properties, other genetic improvement strategies must be considered for Vitis (Gray et al. 2014; Litz et al. 2020).

9.2

The Potential of New Plant Breeding Techniques (NPBTs)

Over the past 15 years, biotechnological application in breeding programs has developed New Plant Breeding Technologies (NPBTs) that can modify only specific target DNA sequences without changing other regions (linkage drag) and without the need for long backcrossing stages, a limitation of conventional breeding techniques (Enfissi et al. 2021; Giudice et al. 2021). NPBTs are a new generation of techniques able to improve plant disease resistance, abiotic stress resilience, and added nutritional values (Lusser et al. 2012; Giudice et al. 2021). Compared with traditional breeding techniques, NPBTs increase the precision and accuracy of making changes in the genomes, reducing the time and efforts needed to produce novel crop cultivars that meet new requirements and potentially reducing the loss of important traits such as the biosynthesis of nutraceutical compounds. Several NPBTs make small modifications to the plant DNA and do not introduce foreign genes. Even considering the great potential of these techniques, and even when the modification is impossible to be differentiated from the ones triggered by spontaneous mutations or conventional breeding (Bortesi and Fischer 2015), their applicability has encountered legislative constraints. The first developed NPBT strategy is called cisgenesis, which was proposed by Schouten et al. (2006). In this approach, one or more genes of interest can be isolated from a Vitis species that could potentially be utilized in conventional breeding and therefore transferred, maintaining its constitutional sequence composed of promoter, gene orientation, and terminator into the cultivar to be improved. There are a few examples of cisgenesis in grapevine: the proof of concept was demonstrated in 2016 using a recombinase system (Dalla Costa et al. 2016). This method allowed the production of genetically modified organism (GMO) plants that were easily selectable using conventional GMO approaches (i.e., antibiotics). Once the GMO plants containing the cisgene(s) were selected, through the activation of a recombinase system, it was possible to excise the transgene used for the detection of the transformed plants from the genomic DNA (Dalla Costa et al. 2016, 2020). Hence, the final products are plants containing only the cisgene(s), with their own promoter and terminator, without any exogenous sequence. Unfortunately, the transgene excision was never achieved completely, producing chimeric plants where the number of cells containing the transgene was limited but still present in the final product. Up to now, no real cisgenic grapevine plants have been obtained, and the difficulties related to this approach limit the application of this method.

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The most recent and famous NPBT developed is genome editing (GE). GE, and specifically Clustered Regulatory Interspaced Short Palindromic Repeats (CRISPR)Cas systems, can insert modifications in specific target DNA sequences without changing other sequences, avoiding the introduction of foreign DNA. Editing the genome is accomplished by applying three components: a protein with nuclease activity (e.g., Cas9, Cas12, Cas13, etc.), a single guide RNA (sgRNA) required to drive the Cas protein to the target sites, and a Protospacer Adjacent Motif (PAM), which is a short sequence upstream of the complementary DNA strand acting as a tag for the target site (Doudna and Charpentier 2014). Once the target sequence is identified, the endonuclease inserts a double-strand DNA (dsDNA) break and consequently stimulates the DNA repair pathway (Panda and Ray 2022), which are the two basic steps for taking advantage of the Cas systems in NPBTs. The CRISPR-Cas system could be used to obtain knock-out mutants, insert a DNA fragment using a donor vector through the homologous recombination system, base edit a target sequence to induce a specific mutation in regulatory sequences, and modify the epigenome (Vats et al. 2019; Khalil 2020; Giudice et al. 2021; Molla et al. 2021). Since the first application of CRISPR-Cas9, new advances have been achieved to improve its efficiency, versatility, and specificity (Gleditzsch et al. 2019; Giudice et al. 2021; Wang et al. 2021; Li et al. 2021b). Moreover, multiplex CRISPR-Cas9 gene editing can also be simultaneously accomplished using different gRNAs to edit a single gene and enhance editing efficiency (Najera et al. 2019), as demonstrated in a recent work where the targeting of TAS4 and MYBA7 genes efficiently prevented the accumulation of anthocyanins in the grapevine rootstock Milardet et Grasset 101–14 (Sunitha and Rock 2020). On the other hand, genome editing applied to a gene belonging to the bZIP family allowed the overaccumulation of anthocyanin in plant tissue (Tu et al. 2022). More in detail, knocking out the VvibZIP36 gene generated mutant plants, able to accumulate not only anthocyanin but also other secondary metabolites like naringenin chalcone, naringenin, dihydroflavonols, and cyanidin-3-O-glucoside. Although the potential of this technique is immense in woody plants, and specifically in grapevine, this strategy has many limitations, including the transformation method. This led laboratories to develop new delivery methods for plant systems. To date, methods such as the Agrobacterium-mediated transformation, nanoparticle platforms, biolistic transformation, or protoplast transfection can fulfill the role of delivering the DNA sequences encoding for Cas and sgRNA(s) into the host plant genome (Duan et al. 2021; Miller et al. 2021). In grapevine, the most used method to deliver CRISPRCas9 components into host cells still rely on A. tumefaciens-mediated transformation (Sandhya et al. 2020). This method includes the drawback of integrating the T-DNA into the plant genome (Lee and Gelvin 2008), leading to the production of edited plants. The CRISPR-Cas approach has already been used and validated to enhance food quality, also from the nutraceutical point of view. For instance, the enhancement of provitamin A content in edible parts of relevant crops is considered an important issue and has been previously addressed (Zheng et al. 2021). Besides, genome editing techniques have been successfully applied to enhance nutrient availability

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in cereals. For example, in a recent work, Ibrahim et al. (2021) used the CRISPR-Cas system to target genes implicated in the biosynthesis of phytic acid, responsible for the development of grains and involved in the bioavailability of iron and zinc in wheat, rice, and maize. Regarding the nutraceutical improvement of fruit crops, the CRISPR-Cas technology has been successfully used in ‘Cavendish’ banana cultivar to enhance β-carotene content by targeting the lycopene ε-cyclase (Kaur et al. 2020). Despite several limitations, these examples highlight the potentiality of CRISPR-Cas as a suitable strategy to improve grapevine nutraceutical features. Before being used, both genome editing and cisgenic approaches need the identification of suitable genes. Since these technologies work on one to a few target genes, exploiting traits under polygenic control would be challenging to achieve with the NPBTs. From the legislative perspective, plants containing exogenous DNA sequences (including marker genes necessary to confer resistance to selective chemicals for their early detection) are considered genetically modified organisms. In the case of plant species propagated by seeds, such as most of the herbaceous species (e.g., tomato, wheat, etc.), the elimination of the transgene containing T-DNA cassette could be achieved by co-transformation with different vectors and segregation of marker genes from the gene of interest in the progeny. Sadly, this approach is not applicable in vegetatively propagated plants characterized by long juvenile periods and highly heterozygous genomes. Despite these limitations, present-day plant genome editing applications remain the most versatile tool to improve the sustainability and nutraceutical features of several crops, including grapevine, but further studies are necessary to solve the abovementioned constraints.

10

Conclusion and Future Perspectives

Current grapevines show an extraordinary diversity of multiple health-related compounds, which contribute to their distinct antioxidant activities. Although some non-vinifera cultivars might not be a realistic source for commercial breeding programs, the high inter-cultivar variability available within the V. vinifera species might be a very relevant source to improve the nutritional quality of current grapes in the near future. In this process, selecting the most beneficial plant material is paramount, including, when available, the selection of the clone with the most adequate characteristics. This wide variability has aided in identifying the genetic architecture and the candidate genes responsible for phenotypic variation, which is the basis for detecting useful markers to assist breeding activities via marker-assisted selection. As summarized in this chapter, the leading role of anthocyanins in berry color and the importance of monoterpenes in muscat flavor (two traits with high relevance in breeding) led to multiple studies that ended up uncovering their genetic determinism. Then, this knowledge was efficiently used to design some genetic markers currently used in grapevine breeding activities. Nevertheless, the genetic architecture underlying the biosynthesis and accumulation of other grape health-related compounds is barely known. For example, the genetic basis of stilbene and stilbene derivatives (like resveratrol) accumulation in grape skins is unknown, although this compound is

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known to have multiple positive biological effects on human health. Similarly, little is known about the genomic regions affecting the accumulation of other phenolics with high potential in preventing cardiovascular and other chronic diseases. The function of grapevine miRNA in regulating plant networks has emerged in recent years thanks to several studies, although their possible effect on humans by dietary intake of fresh grapes or juice is still unknown. This limited information is an opportunity for more intensive research studies to identify the genomic regions, genes, and miRNA involved in the biosynthesis of relevant grape health-related compounds. These studies will be benefited from the new generation of molecular tools, technologies, and computational resources available nowadays. In this line, novel genome editing technologies might be key to validating the putative role of some candidate genes on the accumulation of health-related compounds in grape berries. The information obtained from these studies is expected to speed up grapevine breeding activities in modern breeding programs, fostering the obtaining of new grape cultivars of higher nutritional value and antioxidant properties.

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Mango Nutrigenomics for Nutritional Security Nimisha Sharma, Anil Kumar Dubey, and Ramya Ravishankar

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Need of Nutrigenomics Study for Fruit Crops Like Mango . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Mango and Dietary Benefits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Therapeutic Potentials of Bioactive Compounds from Mango Fruit Wastes . . . . . . . . . . . . . . 5 Gene and Genomics to Study Nutrigenomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Research Gaps and Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Nutrition is all about the study of food and the intake of food to stay healthy. As the community is developing, the world is also facing substantial challenges, such as malnutrition or hyperalimentation. Due to the imbalance of nutrition, chronic disease rates are also drastically increasing in the world. Furthermore, it is leading to high rates of obesity and diabetes in cities and villages. High rise in diet-related disorders such as obesity, cardiovascular diseases, diabetes etc., have resulted in seriousness regarding “Genomics of Nutrition” research worldwide. Therefore, the present global growth of the epidemic needs to be addressed through the promises of nutrigenomics. How genes and diet jointly may affect a person’s health and risk of developing the illness could be well studied by nutrigenomics. The goal of nutrigenomics is to study the interaction of nutrients with the genome, proteome, and metabolome,

N. Sharma (*) · A. K. Dubey Division of Fruits and Horticultural Technology, ICAR-Indian Agricultural Research Institute, New Delhi, India R. Ravishankar Sun Valley Family Care, Peoria, AZ, USA © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_46

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and it describes the affinity between these specific nutrients and nutrient regimes for quality health. A result of consolidated analyses that comprised fruit and vegetable utilization was connected to preventing coronary artery disease, cancer, and fatality, with similar results seen when fruits were scrutinized independently from vegetables. Mango (Mangifera indica L.) is one of the excellent tropical fruits in the world. Most of the mango tree parts are a rich reserve of bioactive compounds, which reside in leaves, bark, and fruit (pulp, peel, and stone). Contemporary studies have proven the presence of significant bioactive components of remedies in fruit waste parts like mango peel and kernel. Mangiferin, flavonoids, catechin, phenolic acids, and gallic acid are a few of the biologically active components contained in this fruit. Hence, the study of nutrigenomics in mango is very important to mitigate malnutrition and coronary diseases. Keywords

Mango · Diet-gene interaction · Nutrigenomics · Nutrition · Food supplement Abbreviations

BaCs BCO1 BMI DM EA FAO FW GT IU MAB MTHFD1 MTHFR NCDs NHANES OECD PKU PP QTL RAE RDA SNP UFGT US USDA

Bioactive compounds Beta-carotene oxygenase 1 Body mass index Dry matter Ellagic acids Food and Agriculture Organization Fresh weight Gallotannins International units Marker-assisted breeding Methylenetetrahydrofolate dehydrogenase Methylenetetrahydrofolate reductase Noncommunicable diseases National Health and Nutrition Examination Survey Organization for Economic Cooperation and Development Phenylketonuria Polyphenols Quantitative trait locus Retinol activity equivalents Recommended dietary allowances Single nucleotide polymorphism Udp glucose: flavonoid-3-O-glucosyltransferase United States United States Department of Agriculture

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Introduction

Nutrigenomics is defined as the relationship between nutrients, diet, and gene expression. It is a fascinating, upcoming field that explains the role of nutrition on gene expression. It brings together the science of bioinformatics, nutrition, molecular biology, genomics, epidemiology, and molecular medicine. The present chapter highlights the nutrigenomics research in mango. It includes the common outlook of nutrigenomics, relevant diseases, the role of single nucleotide polymorphism (SNP) in gene alteration, diet supplementation, and public consciousness in general and specifically in the fruit crop mango. It is very clear that with the accelerated changes in food habits and lifestyles, individuals are becoming more susceptible to diet-related disorders. Therefore, there is an imperative need to accelerate more research in this area so that the relationship between diet and health could be better understood and everyone could be benefitted from the genomic revolution (Neeha and Kinth 2013). The new science of nutrigenomics teaches us what specific foods tell your genes and how food affects a person’s genes and how a person’s genes affect the way the body responds to food. What you eat directly determines the genetic messages your body receives. These messages, in turn, control all the molecules that constitute metabolism: the molecules that tell your body to burn calories or store them. “If you can learn the language of genes and control the messages and instructions, they give your body and metabolism, you can radically alter how food interacts with your body, lose weight, and optimize your health” (Hyman 2006; Aswini and Varun 2010). The nutritional phenotype of individuals could be more precisely accessed via the science of omics (Collins et al. 2003; German et al. 2011). It is cardinal to understand human health both by the role of diet in the fluctuating declaration of a genome and the role of genetics in the uncertain responses to diet (Gopalan 1992; Ghoshal et al. 2003; Ghosh 2010; Ghosh and Gorakshakar 2010). It is quite obvious and understandable that individuals respond distinctively to the same dietary consumption. The most manifest goal of actively preventing disease and improving the health of all individuals, of all ages, becomes nutrition’s greatest golden chance and its strenuous provocation will be in establishing these basic relationships and implementing them (Gobard and Hurlimann 2009; Godbole et al. 2009). The comprehensive retort of metabolism to the quislings of the lifestyle and food choices, environmental oscillations, the status of nutrients, hereditary background, and epigenetic changes, within an individual at a discrete point in time (e.g., metabolic recessive) is possibly a susceptible and actionable reflection of nutritional and metabolic status (Zivkovic and German 2009). In India, some the diseases like epilepsy, type 2 diabetes, and neural tube defect disease are found to be associated with low nutrient uptake (Menon et al. 2010; Mohan et al. 2007a, b; Naushad et al. 2010). Further, nutritional status was observed in the Indian population (Rao 2001; Raj et al. 2007).

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Need of Nutrigenomics Study for Fruit Crops Like Mango

It is a treasure house of nutrition and supports the economic stamina of the territory (FAO 2020) in newly industrialized countries, where tropical fruits are mostly grown. The acceleration in worldwide production of tropical fruits elevated rapidly from 5% to as high as 23% in 2019, based on the approximate anticipation that it will be one of the flourishing agricultural sectors (OECD/FAO 2020). Tropical fruits contain multitudinous health-promoting bioactive compounds such as phenolic acids, carotenoids, flavonoids, anthocyanins, vitamins, minerals, fatty acids, and fiber. These fruits comprise tremendously bountiful antioxidants, and phytochemicals rank them a predominant nutritional source with good medicinal properties (Rymbai et al. 2013; Acham et al. 2018; Laldinchhana Lalrengpuii et al. 2020) and assist in accomplishing nutritional security for an ever-increasing world population. As a result, to circumvent nutritional forfeiture and superior merchantability, fruits need to be harvested at the perfect phases. Postharvest deprivation is around 20–40% (Bantayehu and Alemaye 2019; Rajapaksha et al. 2021) because of their highly decaying character. Accommodating an integrated “multi-omics” perspective supports escalating the genomic knowledge and its implementation in developing improved cultivars. A study on 15,000 adults in several US communities emphasized that both high and low percentages of carbohydrates as part of routine uptake were associated with high mortality, although a 50% reduction in carbohydrate uptake lowers the risk (Seidelmann et al. 2018). Higher salt and low-quality fat due to the intake of more animal protein and decreased consumption of fruits and vegetables lead to higher mortality risk (Mazidi et al. 2019). Therefore, the nutritionist suggests to take more veggies in a routine manner as it maintains sound health. Increased intake of certain fruits like mango corresponds with a medley of beneficial health outcomes. It not only lowered the risk of obesity but also decreased chronic illness (Slavin and Lloyd 2012; Dreher et al. 2018). Cardiovascular diseases and all-cause mortality (Aune et al. 2017) may be auxiliary with low risk with the excessive intake of fruits (apples, pears, and citrus fruits) and vegetables (green leafy and cruciferous vegetables). Studies on the intake of mango and its correlation with nutrient quality and health outcomes emphasize restricted information. Former research using NHANES 2001–2008 illustrated that the intake of mango in kids and adults corresponded with increased nutrients in comparison to those who did not consume mangoes. One cup (165 g) of raw mango give 100 kcal, 3 g dietary fiber, 277 mg potassium, 70 μg folate, DFE, 60 mg vitamin C, 90 μg vitamin A, RAE, 1060 μg beta-carotene, and 12 mg choline (USDA Database 2015). Therefore, it is considered as the supreme source of a healthy diet, although it is still less consumed in the United States. Papanikolaou and Fulgoni (2022) studied nutrient intakes, diet quality, and health results using data from NHANES 2001–2018 in children and adult mango consumers (n ¼ 291; adults n ¼ 449) compared with mango nonconsumers (children n ¼ 28,257; adults n ¼ 44,574). Children who consumed mangoes had a significantly lower daily intake of added sugar, sodium, and total fat, and a higher intake of dietary fiber, magnesium, potassium, total choline, vitamin C, and vitamin D, compared with

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nonconsumers. In adults, mango consumers had significantly higher daily intakes of dietary fiber, magnesium, potassium, folate, vitamin A, vitamin C, and vitamin E and significantly lower intakes of added sugar and cholesterol, compared with nonconsumers. Mango consumption was also associated with better diet quality versus mango nonconsumers ( p < 0.0001). Mango consumption in youngsters was associated with lower BMI z-scores, compared with nonconsumption. In adults, BMI scores, waist circumference, and body weight were significantly lower only in male mango consumers compared to mango nonconsumers. The key findings comprise a healthy nutrient pattern (more consumption of vegetables and fruits, whole grains, and less animal protein foods). The present data are affiliated with previously published data documenting numerous benefits associated with the inclusion of fruit within healthy dietary patterns.

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Mango and Dietary Benefits

Mango (Mangifera indica L.) is a member of the Anacardiaceae family (more than 70 genera and 1000 varieties) and is known as the “king of fruits.” It is widely consumed due to its exotic flavor, succulence, and sweet taste. Mango leaves, bark, and fruit (pulp, peel, and stone) are rich sources of bioactive compounds (BaCs). It contain proteins [0.36–0.40 g 100 g–1 fresh weight (FW) of pulp; 1.76–2.05% (w/w) of peel; 66.1 g kg–1 of kernel flour; and 3.0% (w/w) of leaves], vitamin A [0.135–1.872 mg 100 g–1 FW of pulp; 15.27 International Units (IU) in kernels; 1490 IU in leaves], vitamin C [7.8–172.0 mg 100 g–1 FW of pulp; 188–349 μg g–1 FW of peel; 0.17 g kg–1 DW of kernel flour; 53 mg 100 g–1 dry matter (DM) in leaves], carotenoids (0.78–29.34 μg g–1 FW of pulp; 493–3945 μg g–1 FW of peel), mangiferin (1690.4 mg kg–1 DM in peel; 4.2 mg kg–1 DW of kernel extract), phenolic compounds, dietary fiber (DF), carbohydrates, minerals, and other antioxidants known to have medicinal, nutritional, and industrial benefits. Certain diseases related to oxidative stress need several bioactive compounds due to their antioxidant properties. In mango fruit, only the pulp is used, while all other parts are relinquished that could be better utilized due to its therapeutic properties. Thus, there is an exigency to conduct research on all the bioactive constituents present in mango. These compounds not only provide substantial medical and nutritional properties but also have industrial applications, as well as role in defending the plant. The present-day, ascendant worldwide population leads to the dual challenges of nutritional insecurity and dietary disorders, engendering to health problems such as obesity, cancer, and cardiovascular disease (Clugston and Smith 2002). Mango encloses a complex mixture of antioxidants including xanthones and polyphenols whereby can help protect us from many diseases (Berardini et al. 2005). Mangoes are ingested as fresh fruit or are processed into enriched products such as nectar, puree, squash, or juice. In all instances, only the pulp is used, while the stones and peel are discarded, which results in a considerable waste of organic material. Details of nutrient composition of mango are given in Table 1.

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Table 1 Nutrient composition of ripe mango pulp (Masibo and He 2008) Component Water (g) Carbohydrate (g) Fiber (g) Protein (g) Fat (g) Riboflavin (mg) Niacin (mg) Tryptophan (mg) Methionine (mg)

Value (100 g–1 FW) 78.90–82.80 16.20–17.18 0.85–1.06 Ash (g) 0.36–0.40 0.30–0.53 0.025–0.068 0.025–0.707 3.00–6.00 4.00

Component Calcium (mg) Phosphorus (mg) Iron (mg)

Value (100 g–1 FW) 6.10–12.80 5.50–17.90 0.20–0.63

Vitamin A (mg) Thiamin (mg) Ascorbic acid (mg) Tocopherol (mg) Lysine (mg) Lycopene (mg)

0.135–1.872 0.020–0.073 7.80–172.00 1.12 32.00–37.00 0.35

Polyphenolics: polyphenolics (PP) are the most widely distributed secondary metabolites and serve as the dominant antioxidant compounds. Gallic acid and six hydrolyzable tannins constituted 98% of the total polyphenolics. Other polyphenolics reported in mango pulp include flavonoids, xanthones, phenolic acids, and gallotannins (Berardini et al. 2005); m-hydroxybenzoic acid, vanillic acids, and apigenin (Masibo and He 2008); and hydroxybenzoic acid, m-coumaric acid, coumaric acid, ferulic acid, myricetin, mangiferin, catechins, epicatechin, quercetin, ellagic acids (EA), benzoic acid, and protocatechuic acid (Kim et al. 2007; Jasna et al. 2009; Gorinstein et al. 2011) (Table 2).

4

Therapeutic Potentials of Bioactive Compounds from Mango Fruit Wastes

Mango contains a congregation of several bioactive compounds and has been used as a significant herb in the traditional and Ayurvedic medicinal system for centuries (Shah et al. 2010). Bioactive components (mangiferin, flavonoids, catechin, phenolic acids, gallic acid, and gallic acid derivatives) of therapeutic nature were identified in the kernel and peel of mango. The medicinal value of these compounds has been assessed in vitro and minimal pre-clinically (Asif et al. 2016). The seed of mango is an important source of therapeutic health benefits (Momeny et al. 2012). Mango contains 20–60% seed of the whole and the kernel is 45–75% of the whole seed fruit (Maisuthisakul and Gordon 2009). Peel is a waste product of the mango processing industry. It consists of 15–20% of mango weight (Masibo and He 2008). Various important compounds are distributed in various concentrations in different parts of mango fruit like seed, peel, and pulp (Ignat et al. 2011;Ghuniyal 2015; Parvez 2016; Torres-León et al. 2016). Several polyphenols like alkylresorcinol, flavonols, gallotannins, xanthones, and benzophenone derivatives have been reported in mango fruit waste; peel and seed kernel antimicrobial (Gadallah and Fattah 2011; Shabani and Sayadi 2014), anti-inflammatory (Robles-Sánchez et al. 2009), antidiabetic (Ediriweera et al. 2017), analgesic, immune modulator (Sahu et al. 2007), and antioxidative (Khandare 2016), Wauthoz et al. 2007).

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Table 2 Medicinal properties of polyphenols and vitamins present in mango Polyphenols 1. Gallic acid acts as a substrate for polyphenol oxidase (PPO) in the pulp 2. Ellagitannins inhibit cancer cell proliferation in vitro 3. Gallic acid, mangiferin, myricetin, and flavan-3-ols (e.g., catechin and epicatechin) can prevent membrane lipid peroxidation and protect cells from Parkinson’s disease 4. These antioxidants prevent coronary atherosclerosis lowering the levels of low-density lipoprotein cholesterol and triglycerides

Vitamins/carotenoids 1. Ascorbic acid is known to be a potent antioxidant that can eliminate reactive oxygen species (ROS) and maintain the membrane-bound antioxidant 2. Tocopherol, in its reduced state, act as a cofactor for the activity of a number of key enzymes and act as a substrate for oxalate and tartrate biosynthesis 3. Play roles in stress resistance and the synthesis of collagen, hormones, and neurotransmitters 4. Lower risk of degenerative diseases such as cancer, heart disease, inflammation, arthritis, immune system decline, brain dysfunction, and cataracts 5. b-carotene was the dominant carotenoid in mango plays a vital role against degenerative diseases such as cancer, cataracts, and muscular diseases, as well as neurological, inflammatory, and immune disorders

Lupeol 1. It is a pentacyclic triterpene. It possesses pharmacological properties, acting as a strong antioxidant, antimutagenic, antiinflammatory, and antiarthritic agent 2. Lupeol also prevented 7, 12 dimethylbenz(a)anthraceneinduced strand breaks in DNA, thereby reducing the incidence of tumors, lowering the tumor body burden, and causing a significant delay in the latency period of tumor appearance

Mango seed consists of about 29% shells, 68% kernel, and 3% testa (Diarra 2014). The composition of mango seed kernel varies according to different varieties (Barreto et al. 2008). Based on dry weight, 11% fat, 6.0% protein, 77% carbohydrate, 2.0% ash, and 2.0% crude fiber are the average composition of mango seed kernel. Mango seed kernel is high in minerals such as sodium, potassium, phosphorus, calcium, and magnesium (Sandhu et al. 2007). The mango seed kernel encompasses 52–56% unsaturated fatty acids and 44–48% saturated fatty acids (primary stearic acid). The mango seed kernel also comprehends a substantial amount of essential amino acids (lysine, leucine, and valine). Bioactive components that are embodied in mango kernel incorporate phytosterols (stigmasterol, campesterol, and also consists of vitamin K), sitosterol (β-sitosterols), tocopherols, and polyphenols (Soong and Barlow 2006). The mango peel contains a prominent proportion of total dietary fiber (45–78%), distributed into soluble (16–28%) and insoluble (29–50%) fractions (Ajila et al. 2007). Furthermore, the mango peel also contains cellulose, hemicelluloses, pectin, lipids, proteins, carotenoids, and polyphenols. Apart from this, mango peel also has an appreciable amount of reducing sugars, and due to reducing sugars, mango peel is

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also harnessed for the fermentation process, bioenergy, and various value-added products (Barreto et al. 2008). Sandhu et al. (2007) chronicled that mango peel comprises an elevated quantity of pectin (10–15%), and the soaking process before the extraction of pectin increases its yield to about 21%. The bioactive compounds or the polyphenolic connotations in 100 g of mango seed kernel comprise 20.7 mg tannin, 6.0 mg gallic acid, 12.6 mg coumarin, 7.7 mg caffeic acid, 20.2 mg vanillin, 4.2 mg mangiferin, 10.4 mg ferulic acid, 11.2 mg cinnamic acid, and 7.1 mg unknown compounds (Masibo and He 2008). Polyphenols include mangiferin pentoside, quercetin, syringic acid, and ellagic acid (Ajila et al. 2007).

5

Gene and Genomics to Study Nutrigenomics

Genomic data of both eukaryotes and prokaryotes are essential to understand the complete science of food. These genome sequences pave the way to get thorough knowledge about the composition of nutrients and their availability. Further, processing strategies and safety standards could be determined in a systematic way. It allows unlocking of a novel method to the post-genomic era that allows nutritionists to screen the genetic background and observe the omics as a whole (transcriptome, proteome, and metabolome). Genome science has resulted in development of new dietary strategies, targeted to supply the optimum nutrition for every person. These tools are the pivot of the ascending domain of nutrigenomics (Fig. 1a, b). The tools of genomics research come in to use to design markers from the candidate genes. It not only improves the health of humans but other living entities as well. Further, it accelerates the breeding efficiency of crops for quality traits and imparts better resistance against diseases (EFSA 2008; Kogel et al. 2010; Polesani et al. 2010). It allows breeders to design a genotype in silico based on the desired phenotype by the knowledge procured from recognizing the alleles at all places in a population. As far as the domains of food science, proteomics offers opportunities for discovering functional foods with metabolic effects. It is exceptionally pertinent in the research of proteins of fauna and flora for designer crop breeding (Agrawal et al. 2010), identifying new biomarkers (Pavlou and Diamandis 2010), and discovering therapeutic targets (Katz-Jaffe et al. 2009). By applying measurements of single biomarkers using traditional biochemical methods (Bakker et al. 2010), metabolomics is more helpful in identifying the complexities of metabolic regulation. Due to polyploidy in plants, genomes tend to be stupendous. Hence, because of the scale of the projects, the progression of entire plant genomes lags somewhat beyond other life forms. However, sequencing in a variety of agriculturally important genomes is complete or nearing completion and is forming the basis of a vital knowledge resource for food research. These genomes appraise from the frame of reference of production with agricultural nutritionists who are still struggling with the fundamental strategies for moving beyond the discovery of genes associated with essential nutrients to maximize their agricultural suitability and nutrient bioavailability under the Darwinian selection pressures that guided the organism’s development (Lagaert et al. 2009). A genome of organisms represents the culmination of its evolutionary

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a

Nutrients

b

• Genomics and Transcriptomics/Differentail gene expression up regulated and down regulated • Proteomics/protein network structural and functional proteins • Metabolomics/how genes and protein affect the metabolites

Microarray and RT-qPCR • Genetic expression could be assessed by interactive effect of genes and diet. • Diet-nutrients and genes SNPs • Variations in individual’s response to bioactive food components • Influence nutrient requirements Two-dimensional electrophoresis • Nutritionally important protein study • Production of digestive enzymes and transport molecules Biomarkers • Identification of molecular marker associated with diet related diseases

Fig. 1 (a, b) Conceptual nutrigenomics approach in mango for sound health. The model summarizes the proposed roles for various molecular tools to study the interaction among diet-nutrient and genes

history and the ensemble of genes emerging. Genetics could also influence nutrient and vitamin levels in individuals and changed gene expression. Hence, nutrigenetics emerges as a new science for unlocking the individual pedigree and their composition of nutrients. In mango, molecular markers like simple sequence repeats (SSRs) associated with fruit weight, width, volume, total soluble solid (TSS), titrable acidity, ascorbic acid, and total sugars, additionally reducing sugars, and succors will facilitate screening for varieties/seedlings with preferable fruit traits. Spongy tissue is a consequential physiological disorder influencing the palatable standard of mango drupes, producing a metabolic profile consisting of stress-related and flavor-suppressing metabolites that differ among different

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stages of the fruit (Ajila et al. 2007; Masibo and He 2008). Genes also affect the absorption, transportation, and activation of nutrients and vitamins. There are studies on markers like single nucleotide polymorphisms (SNPs) which affect vitamin availability and cause deficiency (Rubab et al. 2022). Recently transcriptome-based grouping study showed the impact of mango fruit as dietary intake on cardiometabolic health that appears to have interindividual variability (Keathley et al. 2022). A study on the expression of genes involved in carotenoids and anthocyanins during ripening in fruit peel of green-, yellow-, and red-colored mango cultivars was carried out (Karanjalker et al. 2018). Various genes involved in bioactive and metabolites’ production in mango like UDP-glucose: flavonoidOglycosyl-transferase (UFGT), dihydroflavonol (UFGT), dihydroflavonol 4reductase, and anthocyanin synthase are responsible for flavonoid synthesis (Karanjalker et al. 2018). Similarly, lycopene-β-cyclase is responsible for carotenoid synthesis. The gene MiUFGT2 synthesizes cyanidine-3-O-monoglucosides and peonidin-3-O-glucosides bioactive compounds (Bajpai et al. 2018). Transcriptomes (a set of RNA) are transcribed at a cellular level. Functional products derived through RNA not only affect physiological functioning but also impart knowledge about disease progression (Passos 2015). Although, gene response may be variable, environmental interaction also change the expression of the cell. Some nutrition composition improves the health of humans via transcriptomic modulation. Further, “Omics” science could identify new therapeutic targets relevant to variable conditions (Chambers et al. 2019). The transcriptomic analyses provide insights to identify new metabolic pathways affected by mango consumption in individuals who responded to the intervention (Ducheix et al. 2018; Stefania et al. 2021). A network of pathways such as hydrogen peroxide, cofactor catabolic and metabolic processes, gases (oxygen, carbon dioxide) transport, and transcriptional regulation (by RUNX1 and TP53) play a key role in this process. Metabolic pathways also modulated by mango consumption such as RUNX1 have been demonstrated to be one of the most frequently mutated genes in several hematological malignancies (Sood et al. 2017). Further, TP53 was found as expressed protein variant in human carcinoma (Khurana et al. 2016). Insulin resistance, diabetes, cardiovascular disease, and chronic diseases like cancer and kidney illness are regulated by hydrogen peroxide metabolism (Lismont et al. 2019). Previous studies with mango extracts have demonstrated beneficial health effects related to these conditions (Awodele et al. 2015; Fomenko and Chi 2016; Imran et al. 2017). Differential gene expression includes TNFAIP3, API5, and TAL1, etc., as up- and downregulated genes, that regulate the physiological processes. Based on these mechanistic findings, it appears that mango consumption could have a beneficial cardiometabolic effect. Moreover, a reduction in blood pressure following mango consumption is observed (Fang et al. 2018). Research on mangiferin component shows key inflammatory pathways involved in cancer progression (Gold-Smith et al. 2016; Imran et al. 2017; Piccolo et al. 2022). These mechanistic findings provide partial evidence supporting the anticancer potential of mangos.

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Research Gaps and Future Prospects

The propagation of tropical fruit trees for ameliorating fruit traits is intricate due to several constraints like long gestation period, heterozygous nature, variable embryonic nature, and lack of high-quality genome sequences (Mathiazhagan et al. 2021). New advanced molecular tools supplement conventional breeding efforts. Numerous genomics strategies have recently progressed to accommodate and compliment to traditional breeding methods. DNA-based markers associated with fruit burgeoning and fruit quality characteristics were identified in perennial fruit crops. Furthermore, it could be utilized in association mapping.

7

Conclusion

With the availability of genome sequences of fruit crops, identification of SNP variants/Indels, QTLs, functional genes, etc., could be utilized in quality fruit production. Hence, the fruit superiority was accredited through multi-omics perspectives. Moreover, the recognition and measurements of transcripts involved in sugar-starch metabolism, fruit development and ripening, genomic selection (GS), and genetic modifications via transgenics have paved the way for studying gene function and developing varieties with improved quality traits of fruit crops by overcoming long breeding cycles.

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Genetic Enhancement of Nutraceuticals in Papaya (Carica papaya L.) C. Vasugi, K. V. Ravishankar, Ajay Kumar, and K. Poornima

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Agricultural Importance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Nutritional Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Limitations of Conventional Breeding and Rationale for Intervention of Advanced Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Nutritional Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Chemical Type and Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Medicinal Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Agronomic and Postharvest Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Requirement of Biotechnological Intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genetic Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Classical Genetics and Traditional Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Genetics of Health-Related (HR) Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Breeding Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Limitations of Conventional Breeding and Rationale for Molecular Breeding . . . 5 Genetic Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Phenotypic Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Diversity Analysis Using DNA Markers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Relationship with Other Cultivated Species and Wild Relatives . . . . . . . . . . . . . . . . . . 5.4 Relationship with Geographical Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Molecular Mapping and QTLs for HR Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Marker-Assisted Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Germplasm Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Marker-Assisted Gene Introgression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Map-Based Cloning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Recent Concepts and Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Genome Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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C. Vasugi (*) · K. V. Ravishankar · A. Kumar · K. Poornima ICAR-Indian Institute of Horticultural Research, Bengaluru, India e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_39

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10 Genetic Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Role of Bioinformatics as a Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Gene, Genome, and Comparative Genome Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Gene Expression Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 Protein or Metabolome Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Social, Political, and Regulatory Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Not just in India, but all around the world, papaya (Carica papaya L.) is considered one of the most significant fruits. It is grown in tropical and subtropical areas all over the world. Over 37 nations around the world currently cultivate it. One of the biggest issues causing economic losses in the world is the papaya ringspot virus (PRSV-P). Therefore, producing resistant cultivars with good fruit quality and yield is the primary goal of papaya improvement. The fruits are abundant in vitamins, minerals, and other chemical components that have been linked to improved health. There are bioactive components in various plant parts, viz., shoots, leaves, immature and ripe fruit, latex, roots, and seeds, and these compounds possess antioxidant, anticancer, anti-inflammatory, wound–healing, and antifungal properties. The genetic resources have potential genes for both abiotic and stresses that could be exploited in the crop improvement program combining both traditional and modern molecular approaches like genetic engineering to achieve the set target. Keywords

Papaya · Nutritional composition · Medicinal properties · Genetic resources · Genetic diversity

1

Introduction

1.1

Agricultural Importance

One of the most significant and profitable fruit crops in the world is papaya (Carica papaya L.). It is native to Tropical America (Central America and Mexico) and a member of the Caricaceae family. The viral disease, papaya ringspot virus (PRSV-P), and postharvest losses are the two most serious problems affecting the papaya industry globally. The postharvest losses are quite high, ranging from 30% to 60% (Prasad and Paul 2021), while the economic yield losses due to PRSV disease are as high as 95% of expected yield (Babu and Banerjee 2018), rendering papaya orchards economically unviable.

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Nutritional Composition

The papaya fruit is incredibly high in minerals, including iron, calcium, potassium, magnesium, and phosphorus, as well as carbohydrates and proteins. Additionally, it is a plentiful source of vitamins, with 100 g of fruit providing 2020 IU of vitamin A, 40 mg of vitamin B1, and 46 mg of vitamin C (Alara et al. 2020). The fruit contains about 85–90% water and total sugars from 10% to 13%. It is also abundant in carotenoids, the main ones being lycopene, β-cryptoxanthin, and β-carotene (Daagema et al. 2020).

1.3

Limitations of Conventional Breeding and Rationale for Intervention of Advanced Strategies

The papaya ringspot virus (PRSV-P) is one of the major problems in almost all papaya-growing regions of the country and worldwide. Since this illness affects most cultivars of the genus Carica, one long-term solution is the introgression of a gene from a wild related. The other breeding objectives are to develop dwarf/semidwarf stature cultivars having gynodioecious nature with good fruit quality, shelf life, and dual purpose (table and processing) having resistance to major fungal diseases and abiotic stresses like cold tolerance. The conventional breeding method takes a very long period as attaining homozygosity for the specific traits takes several generations (Cortes et al. 2017). Hence, there is a need to integrate the modern biotechnological tools like marker-assisted selection (MAS), genetic engineering, genome-assisted breeding approaches like targeting-induced local lesions In genomes (TILLING), genome-wide association studies (GWAS), genomic selection (GS), and genome editing to develop superior cultivars.

2

Nutritional Composition

2.1

Chemical Composition

Approximately 60% portion of the ripe fruit is eatable per 100 g of fresh fruit and is composed of approximately 85–90% water and 10–13% total sugars. The major sugars are 29.8 g of glucose, 21.9 g of fructose, and 48.3 g of sucrose per 100 g of edible fruit. It contains an abundant amount of vitamins and minerals but is very low in calories. It has 200 kJ/100 g of energy and 10% carbohydrates per 100 g of edible fruit (Anjana et al. 2018). The sensory properties are caused by a number of volatile chemicals, including esters, hydrocarbons, terpenes, alcohols, aldehydes, benzyl isothiocyanate, ketones, and other organic acids. The highly abundant volatile compound of papaya is linalool, which occurred in 94% in solo varieties, whereas the oxide cislinalool is abundant in Taiwan varieties (Serra et al. 2016). Some of the major fatty

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acids present in papaya seeds are palmitic acid (13.90–19.7%), oleic acid (70.84–79.10%), stearic acid (4.20–6.68%), linolenic acid (0.17–0.90%), gadoleic acid (0.51%), and arachidic acid (0.38–1.10%) (Dotto and Abihudi 2021). According to Saeed et al. (2014), pulp contains various nutritional components like vitamin: ascorbic acid (25.07–58.59 mg); phenolics: ferulic acid (277.49–186.63 mg), p-coumaric acid (229.59–135.64 mg), and caffeic acid (175.51–112.89 mg); and carotenoids: lycopene (0.36–3.40 mg), β-cryptoxanthin (0.28–1.06 mg), and β-carotene (0.23–0.50 mg). Papaya has four types of cysteine protease enzymes, viz., papain (less than 10%), glycyl endopeptidase˗III and IV (23–28%), chymopapain A and B (26–30%), and caricain (14–26%) (Saeed et al. 2014).

2.2

Chemical Type and Structure

Papaya leaves contain flavonoids, saponin, tannin, alkaloids, and glycosides. The fruit is also an excellent source of carotenoids with major carotenoids lycopene (0.36–3.40 mg), β-cryptoxanthin (0.28–1.06 mg), and β-carotene (0.23–0.50 mg) (Saeed et al. 2014). The root of papaya contains benzyl isothiocyanate and glucosinolates carposide. The papaya seed oil also contains flavonoids, kaempferol, and myricetin (Adachukwu et al. 2013). Papain and chymopapain enzymes occur in the unripe fruit, and there are also some enzymes present in latex and other parts of the plant, viz., caricain, papain, chymopapain, and protease omega (Teng et al. 2019). Some enzymes are reported in papaya latex, that is, chitinase, cysteine endopeptidases, and glutaminyl cyclase (Daagema et al. 2020). Papaya leaves are also rich in a variety of bioactive compounds such as flavonoids like quercetin, kaempferol-3-rutinoside, quercetin 3-rutinoside, and myricetin 3-rhamnoside (Nugroho et al. 2017); carotenoids like lycopene, zeaxanthin, cryptoxanthin, β-carotene, and violaxanthin; and other phytochemicals such as kaempferol, myricetin, and quercetin. The leaves are rich in phenolic compounds, viz., “kaempferol, protocatechuic acid, quercetin, 5,7-dimethoxy coumarin, caffeic acid, p-coumaric acid, and chlorogenic acid” (Canini et al. 2007). There are many compounds present in various papaya portions, viz., pulp: linalool (Daagema et al. 2020); leaves: dehydrocarpaine I and II, carpaine, psudocarpaine, and alkaloids (Teng et al. 2019); latex: glutaminyl cyclase; shoots: quercetin, chitinases class II and III, kaempferol, and cysteine endopeptidases; and roots: cyanogenic compounds. The benzyl glucosinolate and their degradation products like benzyl isothiocyanate are present in all the tissues of papaya. According to Ghosh et al. (2017), papaya seeds have a good amount of oleic acid and the antifertility compound 1,2,3,4-tetrahydropyridin-3-yl-octanoate. The papaya pericarp, pulp, and seed also contain benzyl glucosinolate and benzyl isothiocyanate. An important nutritional quality aspect of papaya fruit is regarded to be its pulp color. Generally, the red pulp types are rich in lycopene and the yellow pulp types are rich in carotenoids. There are some phenolic compounds also identified in papaya, viz., “ferulic acid (277.49–186.63 mg), p-coumaric acid (229.59–135.64 mg), and

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Table 1 Important chemical compounds present in different parts of papaya Plant parts Fruits

Shoots

Compounds Vitamins: vitamins A, C, B1, B2, and B3 Acids: malic acid, citric acids, and amino acid Volatile compounds: linalool, benzyl isothiocyanate, cis and trans 2, 6-dimethyl-3, 6 expoxy-7-octen-2-ol Alkaloid: α; carpaine and benzyl-β-d glucoside Carpaine, benzyl isothiocyanate, benzyl glucosinolate, glucotropaeolin, benzyl thiourea, caricin, and myrosin Papain and chymopapain, glutamine cyclotransferase, chymopapain A, B, and C, peptidase A and B, and lysozymes Carpaine, pseudocarpaine, and dehydrocarpaine I and II, choline, carposide, vitamins C and E β-Sitosterol, glucose, fructose, sucrose, and galactose

Roots

Arposide and myrosin

Seeds Latex Leaves

References Adedayo et al. (2021)

Moses and Olanrewaju (2018) Ngafwan et al. (2018) Naureen et al. (2022) Naureen et al. (2022) Singh et al. (2021)

caffeic acid (175.51–112.89 mg)” per 100 g of fresh fruit that have antioxidant and antimicrobial properties (Alara et al. 2020) (Tables 1 and 2).

2.3

Medicinal Properties

2.3.1 Dengue Fever Dengue fever is an infectious ailment in human beings that is caused by dengue viruses and spread by mosquitoes. Because it can occasionally induce excruciating pain in muscles and joints that feel like bones are breaking, this illness was previously known as break-bone fever. The major critical condition in case of dengue fever is thrombocytopenia, which can be alleviated by the use of papaya leaves (Sarker et al. 2021). Studies conducted in vitro revealed that papaya leaf extracts have the ability to stabilize membranes and, at lower doses, reduce heatinduced and hypotonicity-induced hemolysis of erythrocytes in both healthy and dengue-infected persons (Ranasinghe et al. 2012); thus, it may be useful in preventing platelet lysis (Fig. 1). 2.3.2 Anti-Inflammatory Property This activity found in papaya is because of the presence of enzyme cysteine proteinases. Papain was found to be safe and effective in the treatment of chronic inflammation. The anti-inflammatory property of papaya seeds was confirmed by Amazu et al. (2010) 2.3.3 Anticancer Activity Due to the proteolytic enzymes present in papaya, which convert protein and the fibrin cancer cell wall into amino acids, the fruit possesses anticancer properties. Isothiocyanate (the degradation product of benzyl glucosinolate) is also very

CH3

CH3

Fruit, leaves

Anticancer

CH3

Roots, pulp, seeds

H3C

OH

Detoxifying properties

Antioxidant

Antioxidant

Fruit

Benzyl glucosinolate

CH3

O

H3C

H3C CH3

Antibacterial

CH3

CH3

CH3

H3C

Roots, pulp, seeds

HO

O

CH3

Glycosides Benzyl isothiocyanate

Violaxanthin

CH3

CH3

Fruit

H3C

CH3

β-Carotene

CH3

CH3

Properties

Plant source

Fruit

H3C

Structure

β-Cryptoxanthin

Bioactive compounds Carotenoids Lycopene

Table 2 Prominent bioactive compounds present in different parts of papaya: structure and properties

Pinnamaneni (2017)

Pinnamaneni (2017)

Kaur et al. (2019)

Adedayo et al. (2021)

Adedayo et al. (2021)

Adedayo et al. (2021)

References

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Antioxidant, anticancer

Antioxidant, anticancer

Shoots, seed

Leaves

Kaempferol

Kaempferol-3-rutinoside

Antioxidant, antidiarrheal

Shoots,

Flavonoids Quercetin

Anticancer

Roots, seeds

Glucosinolates carposide

(continued)

Nugroho et al. (2017)

Nugroho et al. (2017)

Adedayo et al. (2021)

Pinnamaneni (2017)

Genetic Enhancement of Nutraceuticals in Papaya (Carica papaya L.) 1007

HN

HN

O

O

Leaves

O

Pseudocarpaine

O

Leaves

Alkaloids Carpaine

Plant source Leaves

Seeds

Structure

Myricetin

Bioactive compounds Quercetin-3-rutinoside

Table 2 (continued)

Antioxidant

Antioxidant

Antioxidant

Properties Antioxidant, antidiarrheal

Teng et al. (2019)

Teng et al. (2019)

Nugroho et al. (2017)

References Nugroho et al. (2017)

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Antioxidant

Seeds

Fruit

Fruit, leaves

Leaves

Oleic acid

p-Coumaric acid

Caffeic acid

Chlorogenic acid

Antioxidant, antimicrobial

Antioxidant

Antioxidant

Antioxidant

Fruit, leaves

Phenolics Ferulic acid

(continued)

Canini et al. (2007)

Alara et al. (2020)

Alara et al. (2020)

Ghosh et al. (2017)

Alara et al. (2020)

Genetic Enhancement of Nutraceuticals in Papaya (Carica papaya L.) 1009

Properties Anti-inflammation, wound healing

Antifungal

Plant source Unripe fruit latex

Papaya latex

Chitinase

Structure

Bioactive compounds Enzymes Papain

Table 2 (continued)

Azarkan et al. (2006)

Azarkan et al. (2003)

References

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Fig. 1 Health-related beneficial role and products of papaya. (Sharma et al. 2020)

effective against various cancers, viz., colon, lung, breast, pancreas, prostate, and leukemia. The aforementioned enzymes have the ability to prevent the growth and development of cancer cells (Fauziya and Krishnamurthy 2013).

2.3.4 Antifungal Activity The latex of papaya combined with the chemical fluconazole can inhibit the growth of Candida albicans (Giordani et al. 1997). Antifungal activity is attributed to latex proteins, and for complete inhibition of fungal growth the minimum quantity required is about 138 mg/dl (Dwivedi et al. 2020). 2.3.5 Wound-Healing Activity Papaya has wound-healing property due to the presence of proteolytic enzymes. Papain is very effective in the treatment of ulcer in rats by blocking the acid secretion (Chen et al. 1981). Papain is a nonspecific cysteine proteinase that can digest the substrates of necrotic tissue (pH varied from 3.0 to 12.0). These proteolytic enzymes decrease the risk of oxidative tissue damage due to the increase in hydroxyproline content; additionally, they are capable of burn-healing activities (Chen et al. 1981) (Fig. 2 and Table 3).

2.4

Agronomic and Postharvest Techniques

As well as being consumed as fresh fruit, it can also be processed into various valueadded goods while retaining the nutritional value. The raw papaya fruits can be processed into tutti-frutti, pickle, jellies, and candies, while ripe fruit can be processed into canned papaya, ready-to-serve fruit beverages, nectar, pulp, fruit bar, bars, toffee, osmotically dehydrated products, minimally processed products from cut pieces of ripe papaya, and also it can be blended with other fruit pulps to use

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Febrifuge, jaundice, pectoral properties

Diuretic, antibacterial activity, laxative, used in snakebite to remove poison, abortifacent

Carminative, diuretic, chronic diarrhea, dysentery, wounds of urinary tracts, stomachic, ringworm, sedative and tonic, bleeding piles, expectorant

Flowers

Unripe fruit (Papain, chymopapain)

(Vitamin C and E, alkaloids, carpaine)

Asthma, beriberi, fever, abortion, dreesing wounds (fresh leaves), antibacterial activity, jaundice, gonorrhea, urinary complaints, vermifuge

Leaves (Zn, Mn, Fe, K, minerals)

Fruits (β-carotene, carotenoids, crytoxanthin, monoterpenoids, linalool)

Seeds (Papaya oil, glucosinolates, benzyl isothyocynate)

Anti-fungal activity, jaundice, antihaemolytic activity, sore teeth

Shoots (Flavanoids, Kaemferol, myricetin, minerals, Ca, Mg, Fe)

Roots (Carposides)

Carminative, anti-fertility agents in males, counter irritant, as a paste in the treatment of ringworm and psoriasis

Anti-fungal activity, diuretic, checking irregular bleeding from uterus, piles

Fig. 2 Medicinal benefits of different parts of papaya Table 3 Therapeutic benefits of various papaya portions (Anjana et al. 2018) Part Peel

Fruit

Methods of preparation Use peel as a mask on your face for around 20 min Peel and lemon juice apply to the scalp for 20 min Olive, almond, and rose oil are used to stew papaya peel, and the resulting papaya oil is then used with nectar and rose water to apply onto the skin Consumption of fresh fruit Apply unripe fruit on the influenced zone

Leaves

Leaf extracts

Root

Root infusion

Seeds Flowers Latex

Crisp or dried seeds Flower extract Latex of plant

Therapeutic uses To remove skin and facial blemishes Against dandruff Works as a skin tonner and skin cleanser

Indigestion, clogging, farts, and enhanced hunger Pimples, skin inflammation, and mouth ulcer Treating dengue fever, nervous pains, and elephantoid growth; and used to treat injuries and wounds Employed to treat syphilis and lessen urine concretions Bacteriostatic, bactericidal, and fungicidal Treating jaundice Curing psoriasis, ringworm, and dyspepsia

either in juice or fruit bar. Blending of papaya to an extent of 30% produced acceptable quality of juice (Pathak et al. 2021). Papaya sauce from the extracted pulp of ripe fruits has been prepared by Ang et al. (2017). The papain is milky latex extracted from mature green fruits when lanced. It contains a protein hydrolyzing

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Table 4 Utilization of different edible coatings to enhance the shelf life of papaya Coatings Burkholderia cepacia B23 plus calcium and chitosan coating Chitosan plus peppermint essential oil Chitosan plus extract of propolis Aloe vera gel

An essential oil and carboxymethylcellulose coating (CMC)

Features The addition of CaCl2 (3%) to the combination treatment raised the calcium content of the fruit (to 81%) and prolonged its shelf life Chitosan (1%) plus peppermint essential oil (0.2%) results in less peel discoloration, good color development, and higher marketability Chitosan (1%) in combination with propolis ethanolic extract (5%) improved postharvest quality of fruit Shelf life extended up to 15 days and during storage color development improved by adding aloe vera gel coating (1.5%) Postharvest quality is maintained and the severity of postharvest disease is decreased when CMC is used in combination with Lippia sidoides essential oil

References Rahman et al. (2012) Picard et al. (2013) Barrera et al. (2015) Sharmin et al. (2016) Zillo et al. (2018)

enzyme (protease or proteolytic enzyme) that has several industrial and medicinal uses. The demand for papain has significantly expanded during the last few years, and its production on commercial scale has started. The nutritional values in the processed products (tutti-frutti, pickle, jellies and candies, etc.) were estimated after 6 months of storage and found that they remain constant but the stability of dried papaya is only up to 30 days (Prasad and Paul 2021). The use of edible coatings can improve shelf life and appearance of papaya fruit, and reduce microorganism growth and decay after harvesting, improving its postharvest quality (Prasad and Paul 2021). The quality of the fruit can be enhanced by immobilizing the fresh-cut fruit in multilayered antimicrobial coatings (chitosan and pectin) (Brasil et al. 2012). Coating of papaya fruit with chitosan (1%) plus peppermint essential oil (0.2%) results in less peel discoloration, good color development, and higher marketability (Picard et al. 2013). Fruits that are packed in HDPE and kept under evaporative cooling maintain better fresh weight and contain higher TSS and vitamin C (Table 4).

2.5

Requirement of Biotechnological Intervention

Genetic engineering is a vital approach in genetic improvement of papaya that alters one or more desirable characters in elite varieties without interfering with the prevailing traits. The development of effective gene insertion techniques to impart the desired features has helped advancements in genetic engineering. A total of 21 quantitative trait loci (QTLs) were related to seven fruit quality attributes, viz., length and breadth of fruit, sweetness and thickness of pulp, skin freckle, fruit firmness, and fruit weight (Nantawan et al. 2019). These traits could be improved through biotechnological intervention in papaya. The shelf life of papaya fruit can also be improved through co-suppression ACC oxidase genes (Lopez-Gomez et al. 2009). A bacterial color

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complement test confirmed that the gene CpCYC-b controls papaya pulp color. Tomato chloroplast-specific lycopene b-cyclase and CYC-b is a DNA marker that is closely associated with flesh color co-localized on physical map contigs containing cDNA probes. So, papaya fruit pulp color and lycopene content can be improved through the incorporation of gene from tomato (Blas et al. 2010). The development and maturation of papaya fruit are regulated by the CpGRFs genes. The expression or overexpression of these genes can regulate the growth and ripening of fruit (Li et al. 2021). The markers, which are linked with many fruit quality parameters, including fruit size, pulp color, lycopene content, and carotenoid content, might facilitate marker-assisted selection and also improve quality in a short period. However, there are only a few attempts in this regard, and there is a need for more effort using modern next-generation sequencing (NGS)-based methods like QTL-seq, GWAS, etc.

3

Genetic Resources

Papaya belongs to the genus Carica, which is monotypic, and all the commercial varieties come under the genus Carica. The highly cross-pollinated nature of crop and seed multiplication is the cause of the diversity currently existing in germplasm (Chavez-Pesqueira and Nunez-Farfan 2017). Continuous research efforts made in this crop have resulted in the development of more than 25 improved cultivars. The papaya germplasm ranges from various commercial cultivars, wild types, local land races, and exotic collections. Some species of the genus Vasconcellea are tightly associated with C. papaya than others, which influence the successful use of Vasconcellea in papaya improvement. Commercially available cultivars are generally divided into two groups: gynodioecious (hermaphrodites and females) and dioecious (males and females). As the crop is commercially propagated through seeds, the purity is being maintained through selfing and sib mating. Several organizations around the world are involved in the conservation of germplasm in the form of seed bank and field gene banks. However, the global germplasm of papaya has not been organized into an accessible database. The USDA site of the U.S. National Plant Germplasm System in Hilo, Hawaii, reports 153 accessions of C. papaya and some Vasconcellea spp.; EBDA, Bahia (82 accessions), EMBRAPA Mandioca e Fruticultura, Cruz das Almas, Bahia (141 accessions), and IAC Campinas, São Paulo (169 accessions); Colombia at University Nacional Medellín and CORPOICA (83 accessions) with additional accessions at other locations; and Malaysia (72 accessions) (Vincent et al. 2019). Approximately 150 papaya germplasm samples are being preserved in field gene banks in India (Indian Council of Agricultural Research – All India Coordinated Research Project or ICAR-AICRP) at a number of ICAR institutes, including the Indian Agricultural Research Institute-Research station, Pune, Maharashtra (17), TNAUHC& RI, Coimbatore, Tamil Nadu (89), and ICAR-IIHR-National Active Germplasm Sites, Bengaluru, Karnataka (49) (http://www.aicrp.icar.gov.in) (Table 5).

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Table 5 Genetic resources of different wild species as potential gene donor Wild genetic resources V. cundinamarcensis (syn. V. pubescens) V. cauliflora V. goudotiana

V. parviflora

V. quercifolia V. stipulata V. candicans V. heibornii V. monoica V. pentagona V. pentandra

4

Specific traits Resistant to PRSV-P, blackspot and Erwinia species, cold tolerant Resistant to PRSV-P and bacterial canker (Erwinia papayae) Resistant to Erwinia species, Phytophthora, and bacterial canker (Erwinia papayae) Resistant to Paw paw die back (Mycoplasma) and interspecies for V. cundinamarcensis Resistant to PRSV-P Resistant to PRSV-P and cold tolerance Resistant to PRSV and distortion ringspot virus Resistant to PRSV and distortion ringspot virus Monoecious, leaves as vegetable Resistant to frost Cold tolerant

References Badillo (2000), Eeckenbrugge et al. (2014) Badillo (2000), Eeckenbrugge et al. (2014) Eeckenbrugge et al. (2014)

Drew et al. (1998)

Badillo (2000) Badillo (2000), Horovitz and Jiménez (1967) Badillo (2000), Horovitz and Jiménez (1967) Horovitz and Jiménez (1967) Swingle (1947) Singh (1964) Hamilton and Robinson (1937)

Classical Genetics and Traditional Breeding

Traditional breeding and classical genetics made significant advancements and generated information for a variety of quantitative and qualitative characteristics. Superior cultivars have been developed through a variety of breeding techniques, including plant introduction, inbreeding and selection, hybridization and selection, mutation, backcross breeding, and marker-assisted selection.

4.1

Genetics of Health-Related (HR) Genes

The knowledge of various genes and their controlling mechanism, which affects economic traits, will be helpful in the selection of superior genotypes for imparting specific traits. Thus, once information about genetic pattern is generated, breeding programs are initiated with the aim of incorporating a particular desirable trait. Fruit weight has direct positive correlation with fruit size and is controlled by multiple alleles. However, the heterosis in fruit weight is demonstrated over the superior parent in the presence of overdominant gene action (Chan 2001). Total soluble solids

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(TSS) and flavor are governed by a single homozygous recessive allele, which are important traits for taste and quality of fruit while there are some reports indicating that the trait TSS is determined by quantitative genes with additive effects (Rimberia et al. 2018). Pulp color is an important trait in relation to fruit quality and is controlled by a single gene. The yellow color (R) is predominating over red (r) and different shades of pink may be attributed to the influence of modifier genes. All red pulp (rr) varieties will breed true for pulp color. The green color of fruit peel is controlled by a single dominant gene (G) and yellow (gg) is governed by double-recessive gene (Aryal and Ming 2014). Traditional breeding has been used effectively to improve qualitative traits that are directly associated with other traits, for example, carotene is linked with orange flesh color (Rimberia et al. 2018), gynodioecious is linked with fruit shape (Ming et al. 2007), and parthenocarpy is linked with seedless; these are typical examples of selection using morphological markers.

4.2

Breeding Objectives

Current breeding goals in papaya develop gynodioecious-type cultivars that are dwarf or semi-dwarf in stature and good fruit quality (high TSS, less cavity percent, good shelf life, and high pulp recovery) coupled with resistance to major fungal, viral diseases, and abiotic stress like cold tolerance.

4.3

Limitations of Conventional Breeding and Rationale for Molecular Breeding

The selection of traits, which is primarily based on morphological parameters that are affected by environmental factors, is the primary drawback of traditional breeding (Jat et al. 2021). Traditional breeding has paved the way for the development of important quantitative traits like fruit size, early maturity, and fruit yield, which is the most effective method for selection of multiple allele traits. PRSV is the major problem faced by the papaya industry, and attempts are being made to develop PRSV-resistant types through traditional breeding by incorporation of resistance from the wild relative, viz., Vasconcellea cauliflora, V. stipulata, V. cundinamarcensis, and V. quercifolia. Resistance genes from wild relatives are typically difficult to incorporate into cultivars due to cross-incompatibility between the two genera, early embryonic abortion, nonviability, lethality, and sterility of hybrid seeds. However, the postfertilization barrier to intergeneric crosses can be overcome by using growth hormones and nutrient solution to reduce embryo abortion. Sucrose at 5% was noticed to break the intergeneric barriers by promoting pollen germination (Pujar et al. 2019). Due to their nondisruptive nature, ability to evaluate many characteristics simultaneously, and ability to eliminate trait-related environmental variation, molecular markers have the potential to overcome the constraints of conventional breeding

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techniques. But in molecular-assisted breeding, the traits that are important must be identified during marker identification and a segregating population must be created in order to produce the traits. Recently, many advanced technologies of genome sequencing, linkage disequilibrium (LD) mapping, or genome-wide association studies (GWAS) have been developed for the identification of trait of interest and their important QTL regions (Zhu et al. 2008). As PRSV is the major problem in the papaya industry, molecular breeding and genome editing technologies (CRISPR Case-9) can help us to overcome the problem.

5

Genetic Diversity Analysis

The germplasm of papaya shows considerable genetic variability for various horticultural importance traits. There are various criteria that can be used in the assessment of genetic variability, including pedigree records, morphological characteristics, and molecular markers. According to Baxy (2009), comparable external morphological features that are specific to the environment and developmental stages have historically been the basis for plant taxonomy. The fact that molecular markers can be found in all plant tissues and are unaffected by environmental changes makes them ideal for plant identification. Inter˗simple sequence repeats (ISSRs) are significant molecular marker that are widely used to identify various plant species and cultivars (Ahmad et al. 2010).

5.1

Phenotypic Diversity Analysis

Phenotypic characterization using descriptors related to leaf size and shape, types of flowers and inflorescence, and fruit size and shape has assisted in understanding the divergence of papaya germplasm and identifying suitable cultivars to enhance the genetic gain in papaya improvement programs (Silva et al. 2017). The flower and fruit traits are the most economically distinctive phenotypic traits used as the selection criteria for a genotype. According to the sex type of the tree, the inflorescence and flowers vary, and cultivars are basically either gynodioecious or dioecious. The female plant’s inflorescence peduncle is short (2.5–6 cm long) than the male inflorescence peduncle (60–90 cm to 150 cm). The female inflorescences bear spherical- to ovoidshaped fruits. Hermaphrodite plants have short inflorescence peduncles, are intermediate to unisexual in nature, and produce pear-shaped fruits with varying degrees of neck constriction as per the variety (Santa-Catarina et al. 2020). As mentioned, the fruit shape corresponds to the flower type, and the flower type corresponds to plant sex. Fruit size typically ranges from 10 to 50 cm in length, depending on the shape of the fruit, which can be spherical or pear-shaped. Fruits ranged in weight from 0.35 kg to 3.6. The most divergence traits are fruit weight, number of fruits, firmness of pulp, and TSS (Santa-Catarina et al. 2020), plant height, canopy diameter, stem diameter, the average number of leaves, and an insertion height of first fruit (Silva et al. 2017).

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Diversity Analysis Using DNA Markers

SSR marker libraries have been used in research, and their applications have helped in molecular-assisted selection and genetic variability evaluation. Genetic diversity analysis using 20 simple sequence repeat (SSR) markers was carried out on 164 accessions from Costa Rican and 20 known cultivars from the U.S. Department of Agriculture (USDA) (Brown et al. 2012). Genetic diversity was assessed using two SPAR (singleprimer amplification reaction) techniques, that is, random amplified polymorphic DNA (RAPD, 16 primers), ISSR (12 primers), for 13 cultivars and lines, and they found a great similarity among these cultivars, Pusa delicious and Pusa Giants, Pusa Dwarf and CO-7, and Pusa Nanha and CO-2 (Sabara and Vakharia 2018). In another study, analysis of morphological traits (fruit yield traits) revealed significant diversity among the 20 genotypes of papaya, with a total of 89 polymorphic and 45 monomorphic alleles being found out of a total of 134 alleles. The diversity of morphological attributes is closely resemblance to molecular diversity analysis (Suvalaxmi et al. 2019).

5.3

Relationship with Other Cultivated Species and Wild Relatives

Papaya is a member of the Caricaceae family and is divided into six comparatively small genera such as Carica, Vasconcellea, Horovitzia, Jacaratia, Jarilla, and Cylicomorpha (Badillo 2000). The best-known and most significant species in terms of economic importance belong to the genus Carica, which has just one species (Carica papaya). The largest genus, Vasconcellea, has 21 species and was recently reclassified as a separate genus rather than a subgenus of the genus Carica (Badillo 2000). Accurate species identification can be difficult as natural interbreeding between species in the genus Vasconcellea is easy. The existence of hybrid Vasconcellea
heilbornii and its several variants, not all of which have been characterized, may provide an explanation. The commercially grown varieties of V. cundinamarcensis and V.
heilbornii cv. babaco possess untapped potential as sources of the proteolytic enzyme papain and genes for genetic improvement of papaya (Badillo 1993). Many molecular studies indicated that there is a large genetic gap between Vasconcellea and Carica. Studies on intraspecific relationship among Vasconcellea genus showed that intraspecific cpDNA variation was observed in V. microcarpa, and Vasconcellea
heilbornii was the most diverged species (Droogenbroeck et al. 2004). Intergeneric hybridization of the Vasconcellea and Carica papaya species has shown that Arka Prabhath proved to be a good combiner with Vasconcellea spp. (Pujar et al. 2019).

5.4

Relationship with Geographical Distribution

According to Rimberia et al. (2018), papayas are commonly planted throughout the world’s tropical and subtropical regions and are native to Mexico or South Central America. They are also said to be able to adapt to a broad spectrum of environmental

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variables. Although it thrives between 36oN and 36oS, the majority of papayas are produced between 26oN and 26oS. The geographical distribution of the papaya population, both wild and cultivated, can be used to find the collection locations for their utilization and conservation. The geographical distribution of papaya is widespread in Mexico. Variable climate (latitude, altitude, temperature, and rainfall) had the greatest influence on the ecological and geographic distribution of papaya. Papaya distribution has been better understood by the identification of 16 eco-geographical areas based on climatic and edaphic geophysical characteristics (Salinas et al. 2022). The promising dispersal of papaya species in Mexico covered a total area of 114,546.5 km2, with the coasts of Chiapas and the Gulf of Mexico possessing the highest potential. Three zones, namely the coast of Chiapas, the north part of Guerrero, and the southern region of Veracruz, are described as the highly promising spreading areas of cultivated papaya. This is done to gather genetic material and discover the many types of adaptations that exist in Venezuela’s various geographical regions. The Vasconcellea species distribution zones have been known using the FloraMap software (Trujillo et al. 2018). DIVA-GIS software has also been used to know the distribution zones and patterns of 21 Vasconcellea species.

6

Molecular Mapping and QTLs for HR Genes

There have been numerous papaya genetic molecular linkage maps created during the past 70 years. Hofmeyr produced the first genetic molecular map in 1939, and it was based solely on three morphological markers, that is, flower color, types of sex, and stem color. The initial map covered a region of 41 cM and revealed that stem color is associated with flower color at a distance of 17.3 cM between the loci and distantly associated with sex type at a distance of 41 cM. This map could not be used to predict sex type due to its poor resolution. It took over 60 years for the next genetic map to be created. A second genetic molecular map was based on 62 RAPD markers and created a sex-type locus on linkage group 1. A total of 999.3 cM and 11 linkage groups (LGs) were covered by the 62 markers, with a mean distance of 19.6 cM between contiguous markers (Sondur et al. 1996). The heterozygote genotype was suppressed due to the dominant character of RAPD markers, which led to increased map distances between markers. Nevertheless, using eight more markers, the sex-type locus, Sex1, was finally mapped for the first time on Linkage Group 1. There was no evidence of recombination suppression in the linkage groups, including the one carrying the sex locus. The third genetic molecular map was produced based on the morphological markers such as sex type and pulp color, which comprised 1498 AFLP markers and PRSV-P coat protein marker (Ma et al. 2004). Compared to the previous linkage map, which had 19.60 cM average distance between the markers, this map represented a tremendous improvement. The flesh color of fruit served as a morphological marker and was included in the most current high-density genetic map, which had 706 SSR markers. Twelve linkage groups were created by the map (9 major and 3 minor), totaling 1068.9 cM with an average distance of 1.5 cM between the markers (Chen et al. 2007) (Table 6).

–

–

–

–

–

–

–

1

1

1

–

–

1

–

–

–

1

–

– 61

–

1

–

–

RAPD –

Types of genetic maps and number of markers Stem Sex Flower Fruit flesh PRSV coat color type color color protein 1 1 1 – –

Table 6 An overview of papaya’s five genetic molecular maps

277

–

1498

–

AFLP –

712

706

–

–

SSR –

990

707

1501

62

No. of loci 3

945

1069

3294

999

Total cM mapped 41

14

12

12

11

No. of LG n/a

1.5

1.5

2.2

19.6

Average distance (cM) 20.5

References Hofmeyr (1939) Sondur et al. (1996) Ma et al. (2004) Chen et al. (2007) Blas et al. (2009)

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The results of the QTL study are anticipated to show that the alleles for fruit size may control cell division and growth, while the allele for fruit shape may influence floral development (Blas et al. 2012). Genetic linkage map was constructed in which 21 QTLs were observed for seven fruit quality characteristics, viz., length and breadth of fruit, thickness and sweetness of pulp, fruit weight, skin freckle, and fruit firmness. The QTLs were unable to forecast the fruit shape and size in individuals of the F1 and F2 progenies from the intraspecific hybrids. However, there are no studies related to fruit qualities and nutrient content.

7

Marker-Assisted Breeding

7.1

Germplasm Characterization

Papaya cultivars cannot often be identified by using morphological markers till the fruit production (Nishimwe et al. 2019). The papaya cultivars and accessions were characterized by using the 65 agronomic and morphological parameters. The morphological characterization of 60 Kenyan papaya germplasm has been carried out, and results revealed that some traits showed great variability, viz., tree habit, flower color, fruit diameter, fruit shape, and leaf size (Nishimwe et al. 2019). Molecular germplasm characterization of papaya has been done using different molecular markers AFLP (Oliveira et al. 2011), SSR (Pirovani et al. 2021), and ISSR (Hassan et al. 2022). Using ten polymorphic simple sequence repeats, 31 papaya genotypes from Spain, Brazil, Ecuador, China, Taiwan, India, and multiple spots in Bangladesh were genotyped. The P3K1024CC and P6K900CC markers had the largest numbers of alleles, great gene diversity, and polymorphism information richness (Hasibuzzaman et al. 2020). Based on the microsatellite markers, molecular characterization was done using SSR markers of 23 elite lines of papaya (Pirovani et al. 2021). In a study involving various genera of Caricaceae, the cultivated type of Carica is closely associated with the genus Jarilla and Horovitzia but diverged from the Vasconcellea species.

7.2

Marker-Assisted Gene Introgression

With a density of one per 0.7 kb, microsatellites are the most prevalent kind of tandem repetition in the papaya genome. However, it merely makes up 0.19% of the papaya’s whole genome (Wang et al. 2008). Using WGG (whole-genome genotyping) and the Illumina Miseq platform, a total of 28,451 SNPs with a Transition/Transversion (Ts/Tv) ratio of 2.45 and 1982 small InDels (insertions/ deletions) were recognized in order to forecast the effects of the identified variants and produce a list of ripening-related genes (RRGs) with associated variants. A total of 106 RRGs were identified to be linked with 460 variations; these variations might be converted into PCR markers to facilitate the genetic improvement of papaya through marker-assisted selection (MAS) for particular traits (Bohry et al. 2021).

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Microsatellite markers were used to examine the first backcross generation of papaya (BC1S) to assess the parental genomic ratio, degree of homozygosity, and gene or allele transfer that imparts the golden fruit color traits (Pinto et al. 2013). Markers are linked to HR traits such as pulp color (marker CPFC1), sex type (CPM1815Y52 marker), lycopene content, ripening-related genes, and other fruit quality traits (Bohry et al. 2021). The MAS helped to improve the health-related traits, viz., lycopene, pulp color, sweetness, and carotenoid content.

8

Map-Based Cloning

The genome size of papaya is quite small (372 Mbp) because of this, which makes it an ideal fruit crop for genetic study (Sharma et al. 2016). Information on map-based cloning in relation to the nutritional qualities of papaya is lacking. High-density genetic maps are necessary to isolate and clone desirable genes, deconstruct genomes, and MAS. The enzyme that promotes the conversion of lycopene to beta carotene, papaya lycopene-b-cyclase or CpLCY-b, was cloned by Blas et al. (2010). However, there was no difference in the expression of CpLCY-b between yellow and red pulp fruit. A chloroplast-specific CpLCY-b was expressed seven times more in leaves than in fruit. The pulp color locus was located at the end of LG-5 on a high-density genetic molecular map employing SSR markers, with the adjacent marker being 13 cM distant. The crystal structure of the complex between papain and cystatin B served as the basis for the design and synthesis of the tripodal synthetic papain inhibitors. The tripodal molecular construct was created by synthesizing it using the triazacyclophane (TAC) scaffold, simulating the discontinuous cystatin B epitope that is related in the interaction with papain. A b-hairpin loop, an N-terminal peptide segment, as well as C-terminal peptide segment are the three distinct peptide segments that help cystatin B bind to papain. When CysTACtins 5, 7, and 9 were examined for their ability to inhibit papain, CysTACtin 9 demonstrated outstanding papain inhibition with a Ki of 12 nm, which is similar to cystatin B’s inhibitory efficacy (Ki ¼ 0.12 nm) (Zoelen et al. 2007).

9

Recent Concepts and Strategies

Introduction of germplasm is vital in the growth and development of papaya. Various breeding approaches were followed for varietal improvement. Selection and sib mating has been the most successful method. Also, hybridization and selection to achieve homozygosity for the traits have given considerable success. Now the focus is on the development of PRSV disease-resistant cultivars using the wild genus Vasconcellea as a source of resistance. Genetic engineering will assist in the speedy development of novel variety by facilitating the direct introduction of genes into elite lines as conventional breeding requires a lot of time and effort (Alvarez et al. 2021). This is done to create new cultivars with better nutritional qualities by either decreasing the level of a particular antinutrient or increasing the concentration of essential

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ingredients like vitamins and carotenoids (Sabbadini et al. 2021). Recent developments in molecular methods paved the way for the discovery of potential genes that regulate specific classes of nutrient components in papaya, viz., “CpCYC-B, CpLCYB, CpPDS2, CpZDS, CpLCY-E, CpCHY- B” are for carotenoids (Sabbadini et al. 2021); CpLIS1 and CpP450-2 for linalool and linalool oxide (Zhou et al. 2021).

9.1

Genome Editing

Genome editing is one of the most significant recent advancements in genetic improvement of crop, and methods based on the adaptable CRISPR/Cas9 technology have been developed for a variety of features, including improvement in yield, improving resistant or tolerant to abiotic, abiotic stresses and pests, and alteration of genetics of plants for quality fruit. The TILLING technology is used for improved storage life with better fruit quality of papaya (Gauffier et al. 2016). The V. pubescens chloroplast genome was constructed and sequenced using Oxford Nanopore Technology. According to Lin et al. (2017), the genome size is 158,712 bp in length, which is less than the chloroplast genome of C. papaya (160,100 bp). These two structural haplotypes, LSC IRa SSCrc IRb and LSC IRa SSC_ IRb, were observed in the chloroplast genomes of V. pubescens and C. papaya. The chloroplast genome of C. papaya has 46 RNA editing locations with an approximate RNA editing effectiveness of 63%. The chloroplast genome, together with the nuclear and mitochondrial genomes, is an essential part of the plant genomes in a species, facilitating adaptation, diversification, and the emergence of plant lineages. Based on the above finding, V. pubescens can contribute to crop improvement in C. papaya. To create a visually scoreable albino phenotype in altered tissue, Brewer and Chambers (2022) used CRISPR/Cas9 to target the putative “C. papaya L. phytoene desaturase (CpPDS)” gene. A total of 73 plant lines were successfully transformed using the CRISPR construct pAC0025, which targets the CpPDS gene. 59 of them (81%) were entirely albinos. Ten pAC0025 (CpPDS construct) lines, one untransformed control line, and one transformed line with the negative regulation construct pAC0026 were genotyped for the targeted area in CpPDS (no gRNA construct). All three gRNA target locations showed mutations. Overall, high frequency of mutations found at CpPDS gRNA target locations and the high percentage of recovered albino plants point to a successful genome editing procedure that may be utilized to enhance papaya at the genetic level. However, there is no information available on work related to improvement of fruit quality.

9.2

Nanotechnology

Nanotechnology has been one of the most dynamic and emerging areas of science. In comparison to other physicochemical approaches, using the plant material fabrication of nanoparticles (NPs) results in more well-specified sizes and morphologies. Because plant materials operate as capping and reducing agents, which frequently aid in minimizing NPs’ agglomeration, plant extracts utilized for the creation of

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nanoparticles are more favorable than chemical synthesis. ZnO NPs have been synthesized using Carica papaya L leaf extract and characterized using UV-V in spectrum, X-ray diffraction, etc. The seeds of chickpea were treated with various concentrations of ZnO NPs, and the seed germination, shoot length, root length, and antioxidant enzyme were studied (Dulta et al. 2021). Green chemistry-based strategies for creating NPs have become a reality in recent years. Using papaya peel bio waste, the copper oxide NPs (CuO NPs) have been developed. These NPs were used as a photocatalyst to help palm oil mill effluent degrade when exposed to UV light (Phang et al. 2021). NPs based on extract derived from different parts of papaya have been extensively put into use as a green technology.

10

Genetic Engineering

The very first prerequisite for genetic engineering is the availability of plant regeneration protocols. It was effective to use premature zygotic embryos and juvenile seedling tissues in the papaya regeneration process developed by Fitch (2005). In order to obtain nutritionally rich papaya, it has to be grown in a disease-free condition. Two PRSV (papaya ringspot virus) resistant cultivars ‘SunUp’ and ‘Rainbow’ have been developed using a concept called parasite-derived resistance wherein the coat protein-mediated gene silencing mechanism is used (Gaskill 2001). Another significant problem with papaya is fast fruit ripening, and this problem has been addressed by downregulating “1-aminocyclopropane-1-carboxylate (ACC) synthase” enzyme involved in the biosynthesis of ethylene. In papaya, the ACC synthase enzyme, which is an important precursor in the biosynthesis of ethylene, has been downregulated to delayed fruit ripening. The genetics of papayas have undergone yet another modification to the ethylene perception pathway to postpone fruit ripening (Fitch 2005). A low-temperature stress tolerance was brought about by transgenics overexpressing CBF1 gene. This gene is responsible for the expression of COR genes that give freezing tolerance to papaya plants.

11

Role of Bioinformatics as a Tool

The multidisciplinary field of bioinformatics combines “biology, computer science, mathematics, and statistics.” It is used to extract, analyze, integrate, and present the biological data generated by omics platform technologies. There are several biological databases and bioinformatics tools available to other researchers working in related subjects.

11.1

Gene, Genome, and Comparative Genome Databases

The genome of the papaya has been sequenced. 90% of the euchromatic sections and 75% (277.4 Mb) of the genome (372 Mb) were represented by the sequences. 16,362

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unigenes were included in the assembled EST unigene set, and the assembled entire shotgun sequences matched 92.1% of them. The transcribed sequences accounted for 48% of the genic area and 3.6% (13.4 Mb) of the whole genome in the WGS (Ming et al. 2008). Unfortunately, there has not been any progress in the genome data sequences. With the aid of this database, we can locate promising genes related to fruit quality, growth, and development. The papaya genome sequence can be searched through these databases: “NCBI, PlantGDB, Phytozome, and PLAZA.” To examine the similarity and homology of the sequences, two initiatives have been introduced: HMMER and BLAST. “InterProScan, SMART, and Pfam” tools were developed to identify the gene family, domain association, and motif sequence, respectively. PLACE and PlantCARE tools are designed to identify the cis-regulatory elements and promoter of the desirable genes (Alok et al. 2019). The papaya genome sequence can be retrieved from open-access databases to start a comparative genomics investigation. The abovementioned databases are also used for the comparative genomics analysis. The gene sequences are also aligned using the multiple sequence alignment programs ClustalX and MAFFT. The MEGA tool is often used to create phylogenetic trees (Kumar et al. 2018).

11.2

Gene Expression Databases

These are the EBI ArrayExpress (EBI AE) and the NCBI Gene Expression Omnibus in an MIAME-compliant way. Contrary to the International Nucleotide Sequence Database, these two gene expression databases have not been exchanging information. As of 2017, AE no longer imports data from GEO. Furthermore, the DNA DataBank of Japan (DDBJ) recently started a similar repository called the Genomic Expression Archive (GEA). The proteomics data of MS origin can be submitted to a public database like the “ProteomeXchange Consortium” in order to promote reproducibility of proteomics data (Abidin et al. 2021) (Fig. 3).

Fig. 3 Schematic approaches for comparative genomics analysis of papaya. (Abidin et al. 2021)

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Protein or Metabolome Databases

There are some protein databases for papaya such as UniProt comprises UniProtKB for protein knowledge, UniRef for sequence cluster, UniParc for sequence archive, and another section is proteomes; NCBI; PlantGDB comprises CpGDB for papaya genomes; and RCSB PDB for the structure of a protein (1D–3D view) along with electron density (Abidin et al. 2021).

12

Social, Political, and Regulatory Issues

The nutritional security of expanding global population can greatly benefit from the health advantages of papaya plants. The major issues faced by papaya growers involve unfavorable weather, pest and disease incidence, nonavailability of disease-resistant good commercial cultivars, lack of processing and storage facilities, and huge postharvest losses. Awareness toward its nutritional and health benefit including the market potential of papaya is needed to boost its cultivation besides its use as a nutritious alternative. More importantly, developing postharvest techniques and value-added products that retain the phytochemicals and antioxidants present in the fresh fruit could be a boon to the industry and consumer market. Further, regulatory issues related to its biomedical application, nanotechnology, and alternative therapies need to be streamlined for its safe usage.

13

Future Prospects

Due to the significant genetic diversity that exists in papaya germplasm around the world and its importance as a fruit crop, it is possible to use this germplasm to develop a variety of improved traits. Though the crop has very good pharmacological value, viz., antioxidant, anticancer, anti-inflammatory, wound healing, antifungal and dengue cure, sufficient information is not available on these aspects and needs to be generated. There is a need to improve whole-genome sequencing data and develop a papaya genome database for easy access to genomic information. Integration of conventional breeding approach with recent biotechnological intervention like marker-assisted selection (MAS), marker-assisted introgression (MAI), association studies, genomic selection, genome editing, and transformation for health-related traits in addition to disease resistance needs to be intensified. Papaya cultivation for processing and papain production has become a profitable venture in a few countries that can be extended to other papaya-growing regions also. Very limited literature is available on map-based cloning and genomic libraries pertaining to health-related traits at present that needs more focus. Adoption of efficient production technologies like water budgeting and carbon sequestration, and integrated crop protection techniques for major fungal and viral diseases are some of the pressing needs that should be looked into and studied.

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Conclusions

Papaya is one of the most important fruit crops of India as well as other tropical countries all over the world. The fruits are rich source of vitamins, minerals, and other bioactive compounds, which are linked to improve the health-related traits. It has wide genetic diversity, which is contributing toward the development of improved varieties with desirable horticultural traits with improved fruit quality, including resistance to viral disease like papaya ring-spot virus. As the traditional breeding has some limitations, use of molecular approaches like MAS, genome-wide association studies (GWAS), transgenic approaches, and genome editing methods like CRISPR/Cas can help to speed up the results in improving various agronomic and health-related traits in addition to resistance or tolerance to biotic and abiotic stresses.

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Avocado: Agricultural Importance and Nutraceutical Properties A. Talavera, J. J. Gonzalez-Fernandez, A. Carrasco-Pancorbo, L. Olmo-García, and J. I. Hormaza

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Agricultural Importance of Avocado . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Relationship with Other Species and Wild Relatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Description on Nutritional Constituents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Products/Parts with Nutritional Interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Detailed Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Medicinal/Physiological Properties and Functions in Relation to Human Health . . . 2.4 Cultural Methods for Nutraceutical Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Molecular Tools for Genetic Improvement of Nutraceuticals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Limitations of Conventional Breeding and Rational for Next-Generation Molecular Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Molecular Genetics and Genomics of Nutraceuticals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Molecular Mapping, QTLs, and Gene Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Genetic Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

The avocado is a subtropical evergreen tree crop originated in Mesoamerica presently cultivated worldwide in more than 60 countries. Avocado fruits were consumed by Native American cultures as early as 10,000 years ago, and they are experiencing increasing popularity globally as highly nutritious and healthy food. In this chapter, we review the agricultural importance of the crop, compositional A. Talavera · J. J. Gonzalez-Fernandez · J. I. Hormaza (*) Instituto de Hortofruticultura Subtropical y Mediterranea La Mayora (IHSM La Mayora-UMACSIC), Malaga, Spain e-mail: [email protected]; [email protected] A. Carrasco-Pancorbo · L. Olmo-García Department of Analytical Chemistry, Faculty of Sciences, University of Granada, Granada, Spain e-mail: [email protected]; [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_40

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profile, genetic diversity, and molecular tools developed in avocado breeding. The avocado fruit and some of its byproducts (peels, seeds) show nutraceutical properties that can be different depending on the variety and the preharvest and postharvest management approaches. Keywords

Avocado · Genomics · Nutraceutics · Lauraceae · Persea americana

1

Introduction

1.1

Agricultural Importance of Avocado

The avocado (Persea americana Mill.) is a subtropical evergreen woody perennial tree crop, member of the family Lauraceae in the order Laurales. The center of origin of avocado can be located in Central America, in a wide geographical region that expands from the highlands of Mexico, Guatemala, and Honduras to the Pacific coast (Popenoe et al. 1997). According to archaeological findings, native cultures in Mexico already consumed avocados at least 10,000 years ago, as remains dating back to that time have been found in the Coxcatlan Cave, in Tehuacan (state of Puebla) (Knight 2002). Originally, the word avocado derives from the ancient nahuatl word “ahuacatl” that the Spaniards transformed into “aguacate” from which the English word “avocado” transliterated. As other trees native of the Americas that produce large fruits, it is likely that the avocado coevolved with the presently extinct American megafauna that probably was the main disperser of the fruits before humans arrived to the continent (van Zonneveld et al. 2018). From its center of origin in Central America, avocado was probably dispersed to South America in pre-Columbian times. In fact, the first description of avocado after the European arrival to America was made in Colombia in 1519 (Fernandez de Enciso 1519). Soon, the European explorers dispersed avocados to other regions of the world, and the first description outside the Americas was made in 1576 by the botanist Charles de l’Écluse (Carolus Clusius) (Clusius 1576), who observed a blooming avocado tree in a botanical garden in Valencia (Spain), established by Joan Plaza, a professor of “herbs and other simple medicines” at the University of Valencia (Lopez-Terrada 2011). Clusius named the tree Persea due to its resemblance to a traditional North African tree with that name (Mimusops laurifolia, Sapotaceae) (Schroeder 1977); this will later become the name of the genus (Miller 1754). At least eight botanical varieties or subspecies that have evolved in different edaphoclimatic conditions and geographically isolated from each other are usually recognized in the species Persea americana. Three of them, also called horticultural races, have agronomic importance (Schaffer et al. 2013): West Indian (P. americana var. americana), from the lowland tropics; Guatemalan (P. americana var. guatemalensis), from the valleys of the Central American mountain ranges; and Mexican (P. americana var. drymifolia), from the tropical highlands of Southern

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Mexico. Thus, the three horticultural races differ mainly in botanical characteristics and edaphoclimatic preferences. The Guatemalan and Mexican subspecies are better adapted to cooler subtropical climates although the Guatemalan subspecies is more vulnerable to low temperatures than the Mexican subspecies. The West Indian subspecies is more adapted to tropical climates. The three horticultural races are sexually intercompatible, and, in fact, most of the presently cultivated avocado commercial varieties in subtropical and Mediterranean climates are interracial Mexican x Guatemalan hybrids. Avocado is presently cultivated in most countries with subtropical and tropical climates all over the world and is grown commercially in more than 60 countries worldwide. Avocado international market and trading have seen an exponential increase in the last couple of decades, and global avocado world production in 2020 reached over eight million tons (FAO 2022). Mexico, Dominican Republic, Peru, Indonesia, Colombia, and Brazil contribute most of the production. Mexico is the most important avocado-producing country with approximately 30% of the global production (over two million tons in 2022). Most avocados in the international trade are exported from those main producing countries to big consumer regions, mainly USA and Western Europe, while the rest is predominantly consumed in local markets. Thus, the avocado can be considered as a staple fruit in most countries with tropical and subtropical climates, especially in the Americas, but also in some African and Asian countries. Local landraces that usually do not reach the export markets are very popular in most of those countries. Encouraging smallholder farmers to grow avocados together with other crops could, thus, help to reduce malnutrition and help to increase food security (Hakizimana and May 2018).

1.2

Relationship with Other Species and Wild Relatives

The Laurales, in addition to the Canellales, Magnoliales, and Piperales, form the magnoliid clade that is considered as a sister clade to the eudicot and monocot angiosperms (APG IV 2016; Chase et al. 2016). The order Laurales includes seven families: Atherospermataceae, Calycanthaceae, Gomortegaceae, Hernandiaceae, Lauraceae, Monimiaceae, and Siparunaceae. The Lauraceae is a monophylic family with more than 50 genera and between 2500 and 3000 species with a worldwide distribution, mainly in tropical and subtropical climates. Most of the species of the family are evergreen woody trees or shrubs, and, in addition to avocado, a few other species in the Lauraceae have agronomic and/or economic interest. Among them, the most important are spices, such as the camphor (Cinnamomum camphora [L.] J. Presl), the cinnamon (Cinnamomum verum J. Presl), or the laurel (Laurus nobilis L.); timber trees such as those of the genera Chlorocardium, Eusideroxylon, Mezilaurus, Nectandra, Ocotea, and Phoebe; and ornamental trees such as Persea indica. About 150 species are recognized in the genus Persea, 70 of which are distributed in America and 80 in Southeastern Asia, and a single species, P. indica, is endemic to the Macaronesian islands in the Atlantic Ocean. The genus possibly first evolved in African Gondwanaland, from where it dispersed to North America and Asia through

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Europe; by the Paleogene, the genus reached South America via Antarctica, and it was reunited thanks to the land bridge that during the late Neocene connected North and South America. Three subgenera are usually considered in the genus Persea: Machilus, Persea, and Eriodaphne, although Machilus, restricted to Asia, is treated as a separate genus by many authors. The 70 American species of Persea are divided in two subgenera (Kopp 1966): Eriodaphne (primarily with a South American origin) and Persea (primarily with a Central American origin). The subgenus Persea includes at least three species, although additional species are added by some authors (Chanderbali et al. 2013): P. pallescens, P. schiedeana, and P. americana, the avocado.

2

Description on Nutritional Constituents

2.1

Products/Parts with Nutritional Interest

Avocado fruits develop from flowers that are produced as panicles of cymes. A mature avocado tree may produce more than a million flowers, although less than 1% remain on the tree at harvest, which results in a very low fruit-to-flower ratio (Alcaraz and Hormaza 2021). The fruit of avocado is botanically a pyriform or globose fleshy drupe that contains one seed surrounded by the pericarp. The pericarp is formed by the outer skin (exocarp) with a variable thickness and color depending on the horticultural race and the variety, the pulp (mesocarp) that constitutes the edible part, and a thin endocarp, next to the two papery seed coats (Cummings and Schroeder 1942). The pericarp color and texture are highly variable, and the color at ripening can be black, brown green, or purple with intermediate intensities of each one depending on the genotype. The fruit shape and size are also variable and can range from spherical to different pear or egg shapes. The avocado fruit developmental process can be divided in two main phases: fruit maturation that takes place on the tree and that, depending on both the environmental conditions and the genotype, can last between 6 and 18 months and postharvest ripening that takes place after the detachment of the fruit from the tree and during which the mesocarp softens changing the organoleptic characteristics of the fruit. The avocado fruit is climacteric, and, consequently, during the ripening process after harvest, respiration levels related to ethylene production increase. The fruits are harvested when physiological maturity (the ability to ripen after harvest) is reached. Edible ripeness takes place several days after harvesting; the length of the phase between physiological and edible maturity is variable depending on the variety, the time of harvesting, and the conservation temperature after harvesting. The visual determination of the stage of physiological maturity is difficult in avocado, since no clear external changes are observed during this process. This topic has been addressed by a number of works (Stahl 1933; Lee et al. 1983; Landahl et al. 2009) resulting in the development of different approaches to accurately assess avocado physiological fruit maturity; among the most used is the correlation between dry matter and oil contents (Gamble et al. 2010).

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As avocado fruits develop on the tree, total mesocarp oil content increases, and, thus, oil content in the fruit can be used to establish the different fruit developmental stages in order to decide when physiological maturity has been reached (Lee 1981). Avocado is one of the few examples in which high amounts of triacylglycerols are accumulated in the mesocarp of the fruit (Kilaru et al. 2015). Although in the 1920s in California a minimum empirical value of 8% oil content was established for harvesting, this value was later considered as too low. In any case, determination of oil content is a cumbersome process, and, consequently, alternative determination methods were necessary. During avocado fruit development, as oil content increases, since oil replaces the water present in the fruit, water content decreases concomitantly. Then, during this process, the increase in both oil and dry matter contents is correlated. Consequently, measurement of dry matter (defined as the solid content of the fruit minus its water content) is an indirect indicator of oil content and, thus, of maturity and a reliable indicator of flavor. Dry matter measurements are easy to perform either using microwave or other ovens to dry avocado fruit slices or, more recently, using near-infrared (NIR) technologies. The minimum dry matter value for harvesting is variable depending on the variety and the region of production, but the standard value for ‘Hass’ avocado ranges from 21% to 23%. Most avocados are consumed fresh but also in salsas (such as guacamole), soups, and other elaborations, such as in Brazil and different Asian countries in which avocados are consumed sweet mixed with sugar and condensed milk, in milk shakes or as ice cream. In addition, increasing interest is being put into using the edible oil extracted from the avocado flesh in addition to the more traditional use of the avocado oil in the cosmetic and beauty industries. Although the main interest of this crop is the fruit consumed mainly fresh, in some cases, the leaves of the avocado trees (mainly of genotypes of the Mexican race which have a distinctive anise aroma) are also used in some traditional cuisines. Also, avocado leaves are used in some regions in traditional medicine against coughs or skin bruising. Other parts of the avocado fruits after processing (such as for guacamole production) that are usually considered as waste (peels, seeds, paste) could also be a source of interesting bioactive substances (Dalle Mulle Santos et al. 2016; Araújo et al. 2018). Exploiting the phytochemical properties of those byproducts will increase the added value of the avocado industry helping to improve sustainability of avocado production worldwide.

2.2

Detailed Chemical Composition

Avocado is a calorie-rich fruit with high levels of unsaturated fatty acids. The avocado fruit is particularly rich in ascorbic acid (vitamin C), vitamin B6, β-carotene, vitamin E, and potassium, and it also contains phytosterols and carotenoids, such as lutein (which represents about 70% of the carotenoids of avocado [Dreher and Davenport 2013]) and zeaxanthin. For a standard ‘Hass’ avocado, we can consider that about 72% of the flesh is water, although this percentage is variable depending on the location and on the stage of fruit development. Avocado

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composition of the edible flesh for the most important macro- and micronutrients per 100 g of ‘Hass’ avocados is shown in the following Table 1 (USDA 2018). Compared to other vegetables with high oil content, the avocado fruit shows high levels of monounsaturated fatty acids (such as oleic acid), whereas the levels of polyunsaturated fatty acids (such as linoleic and linolenic acids) are low. It also contains small proportions of additional fatty acids (stearic, palmitic, myristic, or arachidonic acids). For 100 g, it can be considered that 2.13 g corresponds to saturated fatty acids, whereas 9.8 g corresponds to monounsaturated fatty acids (about 70% of total fats) and 1.82 g to polyunsaturated fatty acids (USDA 2018). We can highlight some of the main health-related nutrients of avocado fruits as follows: • Relevant levels of monounsaturated fatty acids. • Relevant levels of dietary fiber, of which about 70% correspond to insoluble fibers and 30% to soluble fibers (Marlett and Cheung 1997). • Low sugar content compared to other fruits, mainly in the form of the heptose D-mannoheptulose and its reduced form, the sugar alcohol perseitol. Table 1 Most important macro- and micronutrients per 100 g of ‘Hass’ avocado

Water (g) Macronutrients (g) Lipids Proteins Total carbohydrates Dietary fiber Minerals (mg) Calcium Copper Iron Magnesium Phosphorous Manganese Potassium Selenium Sodium Zinc Vitamins Niacin (mg) Pantothenic acid (mg) Riboflavin (mg) Thiamin (mg) Vitamin A (IU) Vitamin B6 (mg) Vitamin C, ascorbic acid (mg)

72.3 15.4 1.96 8.64 6.80 13.0 0.17 0.61 29 54 0.15 507 0.40 8 0.68 1.91 1.46 0.14 0.075 147 0.29 8.80

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• High potassium and low sodium content, which can help to control blood pressure levels. • High magnesium levels. • High levels of antioxidant C and E vitamins. • High levels of B vitamins. • High levels of phytosterols, mainly β-sitosterol, followed by campesterol and stigmasterol (Duester 2001). Significant changes can be observed in the concentrations of some of these compounds along the harvesting season and also during ripening after harvest (Lu et al. 2009; Hurtado-Fernández et al. 2016; Serrano-García et al. 2022). Hence, the levels of saturated fat decrease, whereas those of monounsaturated oleic acid increase (Slater et al. 1975; Lu et al. 2009). The levels of carotenoids also increase along the avocado harvesting season (Lu et al. 2009). Avocado fruits also show high levels of certain types of nonnutritive compounds, such as alkanols, amino acids, carotenoids, or phenolics, which account for some of their organoleptic properties and that could also be relevant in improving human health. The first works in which powerful tools and ambitious analytical methods were used to characterize the avocado pulp exhaustively – considering many substances not described in the food composition databases – were performed by HurtadoFernández et al. (2011a, b). After that, other works have been published addressing the study of the substances present not only in the avocado pulp but also in the avocado peel and seeds (López-Cobo et al. 2016; Figueroa et al. 2018a, b).

2.3

Medicinal/Physiological Properties and Functions in Relation to Human Health

Avocado is considered as an excellent source of different macro- and micronutrients, and significant health benefits of avocado pulp and oil consumption have been described in different works (Bhuyan et al. 2019). Among them, we can include lowering risks of cardiovascular diseases, cataracts and other age-related macular degenerations, metabolic syndromes, prostatic hypertrophy, and prostate and other tumors, as well as blood cholesterol regulation, weight management, diabetes control, anti-inflammatory effects, and prevention and treatment of osteoarthritis, among others (Salazar et al. 2005; Dreher and Davenport 2013; Bhuyan et al. 2019). Those benefits are probably related to the presence of different phytochemicals in the avocado fruits including phenolic compounds, chlorophylls, carotenoids, or anthocyanins (Ashton et al. 2006; Ding et al. 2007) as well as to the high levels of monounsaturated and low levels of saturated fats that result in a similar healthy oil profile to that of the olive oil (Bhuyan et al. 2019). Most of the studies performed in the avocado fruit have been focused on the pulp, consumed either fresh or processed as oil, which often is cold-pressed, and, consequently, most of the bioactive compounds are preserved (dos Santos et al. 2014). In

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fact, there is a huge potential to improve the use of avocado as a high-quality oil, since generally all the breeding and selection of varieties in this crop have been focused on fruit quality for the fresh market and the diversity present in this species for oil production has not been studied in detail. Moreover, displacing the production of cooking oil from annual plants to perennial crops could have an overall impact on sustainability, similar to the case of the olive tree in the Mediterranean region, helping to reduce soil erosion and fertilizer and pesticide runoff while providing a more sustainable agricultural landscape (Bost et al. 2013). In some markets, fruits of West Indian and of hybrid Guatemalan x West Indian varieties that show a lower oil and calorie content than ‘Hass’ are marketed as “light avocados.” In addition to the monounsaturated acids, recent interest has been devoted to other fatty acid derivatives present in the avocado fruit, such as lauraceous acetogenins that show different interesting bioactive properties (Rodríguez-López et al. 2017; Colin-Oviedo et al. 2022). These substances were first reported in avocado leaves several decades ago (Chang et al. 1975). A recent work (Sánchez-Quezada et al. 2021) shows that nutraceutical properties of avocado seeds (which are responsible for about 16–22% of the avocado fruit weight and are often a byproduct from the guacamole industry) correlate positively with the fruit ripening process; as the fruit ripens, seed moisture decreases, and the antioxidant capacity increases due to an increasing concentration of phenolics.

2.4

Cultural Methods for Nutraceutical Improvement

Although avocado international trade is mainly based on a single variety, ‘Hass’ (Fig. 1), which allows the availability in the markets of an externally very Fig. 1 Fruits of the avocado variety ‘Hass’ hanging on a tree before harvesting

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homogeneous fruit all year round from different origins, pre- and postharvest management factors play a relevant role on ‘Hass’ avocado fruit quality and nutritional composition. Preharvest factors include fruit origin, which, in turn, is mostly related to edaphoclimatic conditions, especially soil type and chemical status, light intensity, relative humidity, temperature fluctuations during fruit development, harvest date along the harvesting season, and agronomic management, especially irrigation regimes and fertilization programs. Postharvest management includes handling at harvesting time, during transport to cooling facilities, and at packing operations, storage length and conditions, and processing and transport to final destination markets. Although very few works have addressed the influence of all those factors on avocado nutraceutical properties, the understanding and control of those factors are highly relevant in order to optimize avocado fruit quality and composition. One example is the length of the harvesting season of fruits derived from the same flowering period that, in some avocado-producing regions, can be extended up to 6 months with differences in fruit composition depending on the harvest time (Hurtado-Fernández et al. 2016) or the geographical origin (Pedreschi et al. 2022). In this sense, differences in avocado fruit composition in the same variety related to the growing area, ripening stage, and postharvest fruit storage conditions have also been described (Donetti and Terry 2014). Regarding crop management, key aspects that can explain heterogeneous ripening in avocado include mainly irrigation and pruning of fertilization practices (Rivera et al. 2017). In this sense, a recent work combining proteomic and metabolomic studies revealed clear differences after heat treatments between avocados from early and mid-harvesting seasons; those differences seem to depend on the fruit physiological stage at harvest (Gavicho-Uarrota et al. 2019). Heat treatments can improve the homogeneity of the ripening process by increasing the amount of soluble sugars (such as galactose or sucrose) and of some stress-related enzymes. Regarding postharvest management, a careful fruit handling has to be performed avoiding not only mechanical injuries but also controlling environmental conditions that could alter normal fruit maturation and avoiding fruit disorders or postharvest diseases that could affect final fruit quality and nutraceutical properties. Although, as discussed above, differences can be found in fruit composition in the same cultivar depending on the edaphoclimatic conditions and pre- and postharvest management procedures, the overwhelming use of ‘Hass’ in the international avocado market is a limiting factor to exploit the natural diversity present in this crop. Some studies have shown differences among avocado varieties in fruit composition (Hurtado-Fernandez et al. 2015; Di Stefano et al. 2017); this will allow in the future to combine the production of different varieties increasing the avocado production period; in some cases, such as in Spain and other countries with a Mediterranean climate, it is possible to produce avocados all year round with a combination of four or five varieties. In other countries with subtropical climates (Colombia or Mexico), different flowering periods can take place all year round allowing the production of fruits from the same variety during the whole year.

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On the other hand, in countries with Mediterranean climates where the pressure of pests and diseases is low compared to regions with tropical high humidity conditions, avocado organic production is relatively easy to perform with the consequently improvement of healthy food production due to the lack of application of toxic chemicals for pest and disease control.

3

Molecular Tools for Genetic Improvement of Nutraceuticals

3.1

Limitations of Conventional Breeding and Rational for Next-Generation Molecular Breeding

The avocado is highly heterozygous and shows a long juvenile period and, as stated before, with an extremely low fruit set due to massive flower abscission and immature fruit drop (Alcaraz and Hormaza 2021). Avocado is characterized by the presence of a synchronous protogynous dichogamy system in which each hermaphrodite avocado flower opens twice during two consecutive days, first functionally as a female flower and, during the second opening, as a functionally male flower. Avocado genotypes have been traditionally classified in two different types (A or B) depending on whether in the first day of the flowering cycle the flowers open in the female stage in the morning (type A cultivars) or in the afternoon (type B cultivars). This flowering behavior promotes outcrossing, since self-pollination in the same cultivar can only occur during the limited number of hours in which closing female flowers in the first day of the flowering cycle and opening male flowers in the second day of the flowering cycle can be found on the same inflorescence, tree, or cultivar. The length of this overlap is highly dependent on temperature and on the avocado genotype. Conventional breeding programs have been moderately successful to release new avocado varieties and rootstocks, although the majority of the most important commercial cultivars worldwide are derived from open pollinations and spontaneous interracial hybridizations. In general, the objectives of avocado breeding strategies have focused on (i) high consistent yield, (ii) high fruit quality, (iii) expanded harvesting season, and (iv) longer shelf life (Lahav and Lavi 2013). The most important avocado cultivar present in the international markets is ‘Hass’ that produces fruits with a black rough epicarp, followed, to a much lesser extent, by varieties such as ‘Fuerte’ that produce fruits with a green smooth epicarp. This has not always been the case, since ‘Fuerte’ was the leading avocado variety in the international markets until the 1970s. Several cultivars similar to ‘Hass’ in appearance have been released during the last decades, and some of them are cultivated in some regions, such as ‘Lamb Hass’, ‘Carmen’ (a mutation of ‘Hass’), or ‘Maluma’. Other interesting cultivars that ripen in green are ‘Reed’ (type A, as ‘Hass’) and ‘Bacon’, ‘Edranol’, or ‘Zutano’ which are type B and are used as pollinizers for ‘Hass’.

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In spite of the growing importance of avocado production worldwide, significant bottlenecks that limit breeding and development of new high-quality avocado varieties still remain worldwide. Among the main limiting factors, we can include the lack or scarce availability of molecular resources, the absence of adequate phenotypic data for many cultivars and environments, and the very limited germplasm used in most avocado breeding programs. There is an increasing demand to develop new high-quality avocado cultivars, since about 90% of the world avocado production is based on ‘Hass’, a variety that was developed in the 1920s in California (USA) from a chance seedling and, in fact, all presently cultivated ‘Hass’ trees derive clonally from that single tree patented in 1935 (Crane et al. 2013). Therefore, any pest or disease that affects this cultivar could threaten avocado production worldwide. Moreover, the present scenario of climate change requires adapting the breeding programs to rapidly changing environmental conditions. As in other crops, it is expected that the increasing availability of molecular data derived from high-throughput sequencing technologies will speed up avocado breeding in the next years.

3.2

Molecular Genetics and Genomics of Nutraceuticals

The avocado is a diploid (2n ¼ 2x ¼ 24) species with a haploid genome size of 896 Mb (Arumuganathan and Earle 1991). Different molecular markers have been used in this crop for fingerprinting, paternity assessment, diversity and phylogenetic analyses, development of genetic linkage maps or screening, and selection of traits of interest in avocado breeding programs. As with other crops, in avocado isozymes were the first genetic markers used (Torres and Bergh 1980) followed more recently by the development of different DNA-based markers. Early markers based on DNA included minisatellites (Lavi et al. 1991), variable number of tandem repeats (VNTRs) (Mhameed et al. 1996), random amplified polymorphic DNA (RAPDs) (Fiedler et al. 1998), and restriction fragment length polymorphism (RFLP) (Furnier et al. 1990; Davis et al. 1998). Later, codominant and highly polymorphic single sequence repeats (SSRs) or microsatellites were also specifically developed in avocado and widely applied for cultivar fingerprinting and genetic diversity studies (Sharon et al. 1997; Schnell et al. 2003; Ashworth and Clegg 2003; Ashworth et al. 2004; Borrone et al. 2007; Alcaraz and Hormaza 2007; Gross-German and Viruel 2013; Guzmán et al. 2017; Boza et al. 2018; Ge et al. 2019b; Juma et al. 2021; Ruiz-Chután et al. 2022). The more recent development of high-throughput new-generation sequencing technologies has enabled the use of single-nucleotide polymorphism (SNP) markers that are increasingly being considered as the preferable type of marker for genetic studies in different crops for diverse objectives such as the construction of genetic linkage maps, the characterization of quantitative trait loci (QTL), association studies with traits of agronomic interest, marker-assisted selection (MAS), or genomic selection (GS) (Scheben et al. 2017; Le Nguyen et al. 2019). SNPs show several advantages that are especially relevant in woody perennial crops, such as avocado, in which breeding programs are

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characterized by long generation times: the possibility of developing a large number of markers at increasingly reduced costs, their bi-allelism that results in a high accuracy in the analyses, or their high replicability. New-generation sequencing approaches in avocado have so far mostly been focused on transcriptome analyses and SNP development. In general, these studies have been applied to study disease resistance, plant development, stress tolerance, and genetic diversity (Ibarra-Laclette et al. 2015; Kilaru et al. 2015; Liu et al. 2018; Vergara-Pulgar et al. 2019; Ge et al. 2019a; Kuhn et al. 2019a, b; Ge et al. 2019c; Rubinstein et al. 2019; Talavera et al. 2019; Chabikwa et al. 2020; Pérez-Torres et al. 2021; Kämper et al. 2021; Fick et al. 2022; Hernández et al. 2022). However, recently, several avocado nuclear genome sequences have been published. Rendón-Anaya et al. (2019) developed genomic sequence drafts of ‘Hass’ as well as of a wild accession of the Mexican horticultural race. The ‘Hass’ assembly was anchored to a genetic map, and the generated genome consisting of 915 scaffolds covered approximately half (46.2%) of the estimated avocado genome. Furthermore, ten genomes representing the three avocado subspecies, as well as Hass-related cultivars and P. schiedeana, were resequenced helping to better understand the genetic diversity and the evolutionary history of avocado. Subsequently, another ‘Hass’ genome reference has been generated by Sharma et al. (2021). In this last work, the reference genome resulted in an assembly of 788 Mb representing approximately 88% of the avocado genome size. However, this assembly was not anchored into scaffolds. These new genomic resources in avocado will probably make a qualitative change in future avocado breeding. But additional efforts are needed to find solutions to new challenges, since the molecular knowledge of avocado lags far behind other crops.

3.3

Molecular Mapping, QTLs, and Gene Identification

The increased availability of saturated genetic maps in many crops has accelerated different breeding programs in recent years. These maps have been extensively applied in QTL mapping, MAS, and comparative and genome structure analyses allowing the identification of a large number of genes through QTL fine mapping studies (Jaganathan et al. 2020). However, in avocado, the number of linkage maps constructed to date is still low. The first avocado genetic linkage map was developed with 50 SSRs, 23 minisatellite DNA fingerprints (DFPs), and 17 RAPD markers, using the progeny from a cross between ‘Pinkerton’ and ‘Ettinger’. This map represented the 12 avocado linkage groups and covered 352.6 cM (Sharon et al. 1997). Later, a new linkage map was constructed by Borrone et al. (2009) using 715 F1 individuals (456 from the cross ‘Tonnage’ x ‘Simmonds’ and 259 from the reciprocal cross ‘Simmonds’ x ‘Tonnage’). This map was developed using SSR makers, and 12 linkage groups were also detected, but, in this case, the total map length was longer (1087.4 cM). More recently, a linkage map was constructed using SSRs and single-nucleotide polymorphisms for a ‘Gwen’ x ‘Fuerte’ progeny. The

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resulting linkage map covered 1044.7 cM distributed along 12 linkage groups. In this last study, a high number of molecular markers located in linkage group 10 showed remarkable association with flowering type, and a marker on linkage group 1 was associated with a QTL related to β-sitosterol fruit levels and a region on linkage group 3 with vitamin E (α-tocopherol) fruit levels. Unfortunately, the limited population size used restricted the possibility of developing a robust linkage map and detecting additional QTLs (Ashworth et al. 2019). Although the genetic maps generated so far are useful resources, new efforts are needed to develop more saturated genetic maps in avocado in order to optimize and boost breeding programs for specific traits. Several mapping populations have been developed in spite of the difficulty of this crop with a long juvenile period, the low yield obtained after natural or hand pollination, and the dichogamy system. However, larger populations, higher molecular resources, and phenotypic data will be required in order to detect QTLs and develop markerassisted programs. As a result of those limitations, the examples of the identification of health-related genes are still scarce in avocado. Those examples include the studies on oil accumulation in the mesocarp of avocado fruits. Kilaru et al. (2015) performed a comparative transcriptome analysis of some lipid metabolic pathways in ‘Hass’ and compared this with other species showing a similar oil biosynthesis patterns (avocado, oil palm, rapeseed, and castor bean) suggesting the conservation of these metabolic pathways during angiosperm evolution. However, some unique features were also detected in avocado. Similarly, comparative transcriptomic analyses of the mesocarp and seeds revealed higher expression levels of 17 carotenoid biosynthesis genes in the mesocarp than in the seed along five avocado fruit developmental stages (Ge et al. 2019a).

3.4

Genetic Engineering

As in other crops, genetic engineering could play an important role in future avocado breeding programs. Significant advances have been obtained using Agrobacterium rhizogenes and Agrobacterium tumefaciens (Pliego-Alfaro et al. 2020). Genetic transformation has been successful in a few cases to study some genes that affect different horticultural traits. Examples include the manipulation of the S-adenosyl-l-methionine (SAM) hydrolase (SAMase) gene to block ethylene production (Efendi 2003) or the study of genes involved in pathogenesis such as β-1,6-glucanase, chitinase, and the antifungal protein (AFP) gene (Raharjo et al. 2008) or targeting chloroplast RNA to avoid the replication of the avocado sunblotch viroid (ASBVd) in chloroplasts (Perea Arango et al. 2010). Transient gene expression has also been accomplished using biolistics in avocado embryogenic cultures (Chaparro-Pulido et al. 2014). In addition, as in other crops, CRISPR/Cas can make a qualitative change in avocado gene edition in the future. However, efficient regeneration protocols from single cells in this crop are still lacking in order for the approach to be effective.

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Future Prospects

This chapter has summarized relevant information about avocado, covering aspects such as the agricultural importance of the crop, description of compositional profile, genetic diversity, and molecular tools. Although the composition of this fruit has been described in considerable depth, there is still a long way to go, making use of recent advances in metabolomics, proteomics, sequencing, transcriptomics, and genomics. Thus, in spite of the importance of several compounds present in avocado fruits with nutritional and health benefits, such as carotenoids, lipids, sugars, proteins, minerals, or vitamins, avocado lags behind other crops in the breeding or varieties to take advantage of those excellent properties. Several studies have shown the exceptional nutritional and phytochemical composition of avocado fruits and their potential in the control and prevention of different human diseases, but additional in vitro, in vivo, and clinical studies are needed to understand the mechanisms of action of avocado phytochemicals in order to use this fruit in therapeutic and nutritional applications. However, recent advances in sequencing and transcriptomics together with gene editing can make a qualitative change to take advantage of the still underused genetic diversity present in this crop. It is expected that additional genes coding for important nutraceutical properties of avocado will be identified in the next years. This knowledge is crucial to use molecular breeding to improve classical breeding approaches as well as to provide appropriate material for the generation of DNA-edited plants with desired traits of interest.

5

Conclusion

The fruits of the avocado including several of their byproducts show interesting nutraceutical properties that can be different depending on the genotype and the preharvest and postharvest management of the crop.

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Melon Nutraceutomics and Breeding Prashant Kaushik

Contents 1 2 3 4 5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Description on Nutritional Constituents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Medicinal Properties in Relation to Human Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genetic Resources of Health-Related (HR) Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Brief on Genetic Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Relationship with Other Cultivated Species and Wild Relatives . . . . . . . . . . . . . . . . . . . . 5.2 Relationship with Geographical Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Extent of Genetic Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Biotechnological Intervention for Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Molecular Mapping for Health-Related Traits in Melon . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Molecular Breeding and Genomics for Health-Related Traits in Melon . . . . . . . . . . . . 7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Nowadays, people are preferring consumption of fresh fruits and vegetables with delicious taste. Further fruits and vegetables have high nutritional values, since they are enriched in minerals, vitamins, protein, fiber, and some other beneficial components for human health. Compared with other fruits, melon has more antioxidant properties and is beneficial for human health. Melons are considered a good source of vitamins C, B6, and K, and a maximum of potassium and copper is found in the pulps of melon, after using the fruits. Melon seeds are dried and powdered to be consumed to get maximum health benefits. In addition, there are many phytochemicals and useful components in melons, which were identified to be antifungal, antibacterial, antiviral, and anti-inflammatory. These compounds present in the melons promote health in humans by maintaining good source of P. Kaushik (*) Instituto de Conservación y Mejora de la Agrodiversidad Valenciana, Universitat Politècnica de València, Valencia, Spain e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_41

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vitamins in the human body. To achieve the desired yield and enriched beneficial nutritional compounds for human health, conventional breeding can be started, but it takes too long time, and so to overcome the challenges of conventional breeding, a new approach, namely, molecular breeding has been started. In molecular strategy, the approaches, namely, marker assisted selection MAS, quantitative trait analysis, next-generation sequencing, genome-wide association mapping, genomic selection, high-throughput analysis, and structural and functional genomics have been started recently. Keywords

Melon · Nutritional value · Nutraceutomics · Conventional breeding · Homologous recombination and molecular breeding

1

Introduction

Melons are unique yet important fruits consumed around the world. These fruits are known for their dietary fiber, vitamins, and minerals and are a good source of water. Melons are also known as summer fruits or summer melons. The fruits of these melons are referred to as pepo, a kind of berry. The melons belong to the Cucurbitaceae family and are sweet and fleshy, making them easy for consumption. Melons are native to Africa and are present in the southwest valleys of Asia, especially India and Iran. Later, the importance of the fruit was understood by the European countries and they spread to almost all parts of the world (Manchali et al. 2021). The name melon is derived from the Latin word “melo pepo.” The melons are used and adapted in a wide range of conditions with maximum diversity all around the world. The production of melons is topped by China, followed by Turkey, and India occupies the fourth place, behind the USA. In India, especially Uttar Pradesh and then Andhra Pradesh and Tamil Nadu are known to have the maximum area under melon production. Also, in the USA, California contributes to a maximum of 58% of total melon production, followed by Arizona, which contributes around 28% of the total melon production. Not only the aforementioned countries, but also many more countries cultivate melons, and increase of their production is due to their numerous beneficial and useful properties in promoting human health (Fraga et al. 2019). There are numerous benefits of melon cultivation, which can provide a good source of income for farmers who begin melon cultivation. This crop needs a maximum of 85–95 days from sowing to harvest and is fully packed with nutritional benefits. Therefore, melon cultivation, which has been popular in recent years, has become highly important in the agriculture field under proper supervision and care (Sharma et al. 2020). There are many species of melons with varied genome sizes, among which cantaloupe, watermelon, and honey dew are the best-known melons consumed in almost all parts of the world due to their sweet taste and flavor, along with added

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health benefits. As stated, melons contain many useful properties, providing good health upon consumption. Melons are considered a good source of vitamin C, B6, and K. Also, a maximum of potassium and copper are found in the pulps of melons. Along with this, the seeds of these melons are dried and consumed or powdered and consumed to get maximum health benefits. Most importantly, these melons contain maximum water content; hence, they are called summer fruits, making them profitable to farmers for production in summer and consumption for added health benefits (Gómez-García et al. 2020). Not only the fruits but also the seeds of the melons are highly healthy, containing many benefits. The seeds of these melons contain high vitamin B, minerals, and fats and are a good source of dietary fiber. These seeds are also known to regulate blood pressure, boosting energy levels while keeping the skin healthy and glowing. Apart from these, the melon fruits are known to cool the body after consuming them as a juice, whereas the seeds keep the human body active with their nourishing properties. Some recent studies revealed that watermelons contain lycopene, which is a phytochemical compound having antioxidant and antiinflammatory properties, keeping chronic diseases at bay (Fraga et al. 2019). Proper diet, physical health, and a calm mind are always recommendable to promote health and to fix many internal health issues. With their nutritional properties, these melons were known to promote mental calmness and, more importantly, to cure malnutrition in humans and children. A healthy diet will always fix malnutrition problems by providing the body with all the needed elements for growth. Along with starchy grains, dairy, other fruits, and vegetables, melons are also recommended to be added to the diet to keep many health issues at bay. It is recommended that a person should consume at least five fruits per day, which should include melons, as a must. Due to the lower carbs and total fats in the fruit pulp, melons can be consumed for dieting and regulating weight (Sánchez et al. 2021). Also, the lower sodium content is good for promoting proper brain functioning and is good for maintaining blood pressure. Along with this, the seeds of melons are known to contain maximum health benefits, especially in lowering the cholesterol in the blood vessels, thereby promoting a healthy lifestyle. Due to the presence of folate in these melons, they are considered good for bone health and bone mineral density. Also, the presence of lutein and zeaxanthin in the melons makes them good for eyesight and vision. The above factors, i.e., water content, dietary fiber, vitamins, minerals, especially vitamin C, less sodium, lower cholesterol, and improving bone density and vision, make melon a wonderful crop with all the daily required nutrients useful for a healthy human being and protect one from the symptoms of malnutrition (Thakur et al. 2019). Also, certain melon species like watermelons, honey dew, and cantaloupes are very healthy in promoting a wonderful diet and keeping away severe maladies. The phytochemicals and bioactive compounds, especially in watermelons, help in improving health by increasing the availability of antioxidants to the body. The lycopene, present not only in watermelons but also in tomatoes and pink guava, is a potential antioxidant that helps in reducing the growth and development of cancerous cells. Therefore, the presence of lycopene in watermelons has become the limelight in studying its antioxidant properties, making this species of melon very useful in arresting chronic diseases like cancer (Rolbiecki et al. 2021).

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There are many conventional breeding methods in melons, which include intraspecific crosses that generate variations; pedigree methods, which include selection of two parents and producing hybrids with diverse characteristics, etc., which were not very successful in melons, as these hybridization methods have not changed for many years, and similar procedures in all the crops may not be successful always. The breeding procedures can be carried out only when the plants are sexually compatible, and the insertion of new traits is also possible if the plants are sexually mated with each other. Also, a major limitation in conventional breeding is that during crossing of the plants, many unwanted genes are also transferred along with the desirable traits showing reduction in yields. Therefore, the use of these methods needs to be supplemented and new methods need to be employed in order to achieve proper growth, yields, and nutritional qualities in plants (Sultana et al. 2014). Therefore, the use of next-generation methods like high-throughput genotyping will improve the nature of the crop and yields as well. Certain gene editing techniques help in improving allelic variations in plants. Also, automated throughput phenotyping and bioinformatic tools help in improving the genotypes of the plants. The genomewide single nucleotide polymorphism (SNP) discovery in nonmodel organisms also helps in developing suitable melon species that are highly beneficial to farmers and breeders. The above newly emerging next-generation methods help in understanding the genetic nature of the crops and promote the development of new varieties, thereby increasing the production and productivity of the crops (Yashiro et al. 2005). In this chapter, we will describe the importance of melon and its many useful health properties in improving the immunity of humans and keeping chronic or harmful diseases at bay. The nature of conventional methods in how they affect the crops and the ability of next-generation methods to improve the production of the crops are also discussed, along with the genetic manipulations and the biotechnological tools to be implemented in order to increase the yields and the nutritional quality of melons.

2

Description on Nutritional Constituents

Melons were considered as useful sources of nutrition due to their properties and their nutritional constituents. The melons even though of different types contain varied nutritional parameters like minerals, vitamins, etc. The nutritional components in the fruits and the seeds of melons include many important compounds useful for human health with the abundance of water (Tables 1 and 2). Not only the water content, melon fruits contain high amount of vitamin C which is around 36.5 mg followed by vitamin A, i.e., 169 μg. The most abundant minerals found in the fruits of melons are potassium and magnesium, i.e., 267 mg and 12 mg, respectively. Not only the fruits but also the dried seeds contain high content of nutrients like proteins, around 27.40%, followed by useful fiber, around 25% adding up the importance of melon seeds along with the fruit. Therefore, the nutritional components in the seeds and the fruits of different melons make them good for consumption as they are packed with a whole lot of nutrition useful to human body on a daily basis. Due to the presence of these important compounds in melons, they were recommended for intake on a daily basis for extreme health benefits.

Melon Nutraceutomics and Breeding Table 1 Nutritional constituents in melon fruits

Table 2 Nutritional constituents in melon seeds

Components Water Proteins Carbohydrates Total fats Dietary fiber Sugars Vitamin C Vitamin A Potassium Magnesium

Components Moisture Oil Proteins Ash Carbohydrates Fibers Phenolic compounds

1057 Quantities in 100 g of raw fruit 90.5 g 0.84 g 8.15 g 0.18 g 0.8 g 0.9 g 36.5 mg 169 μg 267 mg 12 mg

Quantities in raw fruit 7.15% 30.55% 27.40% 4.81% 29% 25% Less quantities

Compared to all the other biochemical and nutrient molecules present in the melon fruits, glucose and fructose were the most abundant, which are converted into easily available sugar sucrose. These sugars or the biochemicals help in maintaining the metabolism of the plants and provide food for the growth of the fruits. The sucrose content directly corresponds to the sweet taste of the fruits, which is a major parameter for increasing the market value of fruits (Kolayli et al. 2010). Therefore, the production of glucose to carry out the plant’s physiological functions is given in a flow chart in Fig. 1. The available sucrose present in the plant system is utilized along with raffinose and stachyose, which is formed into fructose, glucose, and galactose that are considered as major biochemical compounds in melons and are again synthesized into simple sugars like sucrose, which is made available to the plants and also known for enhancing the sweet taste of the fruits.

3

Medicinal Properties in Relation to Human Health

There are many phytochemicals and useful components in melons, which were identified to be antifungal, antibacterial, antiviral, and anti-inflammatory. These compounds present in the melons promote health in humans maintaining good source of vitamins in the human body. Certain studies revealed that these medicinal

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Fig. 1 A schematic diagram of the process of glucose production in plants

Sucrose sucrose synthase

Stachyose

Raffinose

acid a-galactosidase

acid invertase

neutral a-galactosidase

neutral invertase

UDP glc

fructose

glucose

galactose

fructokinase hexokinase

PGI

fru6P

galactokinase

gal1P

glc6P

UDPglu/gal PPase

PGM

glc1P sucrose-P synthase

UDPglu PPase

UDPgal

UDPglc

epimerase

sucrose-P sucrose-P phosphatase

sucrose

properties in the melons were useful in reducing many chronic diseases or the entry of such disease-causing agents can be arrested and killed immediately after it enters human body (Rajasree et al. 2016). Melons provide maximum water content to the human body as they are abundant in water maintaining the cellular osmosis levels and promoting osmotic balance in human body. Moreover, the fruits of melons include important nutrients such as lycopene and citrulline, which are present because of the high levels of vitamins A and C. The lycopene is well-known to impart the red color to certain species of melons. Therefore, these red melons available in the market are well-known to have major health properties like reducing heart problems, arresting muscle soreness and treating inflammation in the human body wherever needed. Certain physicians and doctors recommended that the intake of melon seeds helps in solving kidney problems, urinary bladder issues, and lowers high blood pressures thereby improving human health. The lycopene, which is a well-known antioxidant, helps in scavenging the free radicals in human body caused by radiations. The lycopene increases the body’s tolerance ability toward sicknesses and ill health. Therefore, considering the above factors melons are considered as important sources of nutrition for humans to maintain balanced body weight and health (Manchali et al. 2021).

4

Genetic Resources of Health-Related (HR) Genes

The presence of particular genes in plants and the expressions of those genes have been shown to have a beneficial effect on human health. The presence of these genes in plants and the expressions of those genes have been shown to increase the

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nutritional qualities of the plant, which in turn benefits the consumer. There were certain evidences of the presence of genes whose expressions can trigger and create phytomedicine synthesis in melons. The secondary gene pool of melons contains closely related plant species and hybrids. These cultivars are used for crossing and are known to produce fertile offspring. The interchange or crossing between the cultivars of this gene pool with primary gene pool is considered difficult because such crosses lead to the production of weak, sterile hybrids. Therefore, recivering the chromosomes of better parent becomes difficult. Finally, the tertiary gene pool produces completely sterile hybrids upon cross with the primary gene pool, because this gene pool is distantly related to the primary gene pool. Some special techniques are needed to transfer genes from wild gene pool to other gene pools, especially the primary one. These techniques are embryo rescue, chromosomal doubling, and bridge crosses with plants from the secondary gene pool (Pavan et al. 2017). Cucumis melo, commonly known as melon, is a diploid plant species with a wide range of phenotypic diversity and economic importance. Melon fruits contain various nutraceuticals, such as carotenoids, flavonoids, vitamin C, and antioxidants, that have beneficial effects on human health (Garcia-Mas et al. 2012). The genetic basis of nutraceutical content in melon is not fully understood, but some candidate genes have been identified by GWAS and transcriptome analysis. For example, a gene encoding phytoene synthase (PSY), which catalyzes the first step of carotenoid biosynthesis, was found to be associated with β-carotene content in melon flesh (Pandey et al. 2016). Another gene encoding 9-cis-epoxycarotenoid dioxygenase (NCED), which regulates abscisic acid (ABA) synthesis from carotenoids, was found to be differentially expressed between climacteric and nonclimacteric melons. ABA is a hormone that influences fruit ripening and sugar accumulation. Moreover, some gene pools or germplasm collections of melon have been reported to have higher nutraceutical content than others. For instance, a wild relative of melon from India (Cucumis melo subsp. agrestis var. momordica) showed higher levels of antioxidants and phenolics than cultivated varieties (Zhang et al. 2022). Similarly, a landrace of melon from China (Cucumis melo var. makuwa) showed higher levels of metal ions than other types. These gene pools may provide valuable resources for breeding new varieties with improved nutraceutical content (Lotti and Fernández-Silva 2019).

5

Brief on Genetic Diversity Analysis

Melons were known for the differences in their phenotypical characters. These characters differ from one species to another in shape, size, and color of the fruits. Regarding melons, many studies previously suggested the changes in the phenotypic characters show diversity in their morphological parameters. Certain diversified traits were identified in case of melon’s sex expression, fruit color, shape, number of sutures, layer around the seeds, flesh color, and the number of placentas. In case of seeds, the melons were observed to have small seed size, less seed weight, sometimes seedless in some fruits like watermelons, etc. The presence of such traits differing from the wild relatives and land races was observed due to inter-crossing or gene transfer techniques. Therefore, new methodologies and techniques help in

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understanding the diversification in plants which ultimately leads to the changes in the phenotypic nature of the plants where sometimes these diversifications lead to positive changes, but sometimes they may be negative (Sensoy et al. 2007). For example, Al-Zaher et al. (2016) characterized 50 snake melon accessions from Palestine using 17 phenotypic characters and found significant variation among them. They also identified four distinct groups of snake melons based on their morphological traits. Similarly, Yetisir et al. (2006) evaluated 56 Turkish melon genotypes using 12 phenotypic characters and found high diversity among them. They also classified the Turkish melons into six groups according to their botanical varieties. Other studies have used molecular markers such as RAPD3, SNP4, and SSR5 to complement phenotypic data and reveal more details about the genetic relationships and population structure of melon collections (Sharma et al. 2014). Phenotypic characters are useful for assessing genetic diversity in Cucumis melo, but they may be influenced by environmental factors and human selection. Therefore, combining phenotypic and molecular data can provide a more comprehensive picture of the genetic variation and evolution of this crop (Kimura-Kawakami et al. 2021).

5.1

Relationship with Other Cultivated Species and Wild Relatives

These melons, which were originated in South Africa, were cultivated in different parts of the world. The changes in the names and appearance of the melons make them different from each other. These melons contain different cultivated species which differ from each other, i.e., cucumber differs from gherkins where both these fruits belong to the same family. Likewise, these melons which belong to Cucurbitaceae family are closely related to each other. It was also observed that the taste, shape, and sizes of each melon species differ from each other which does not imply that they belong to different families. Therefore, the melons which were cultivated now in one area have a close relationship in sharing genes, characters, and pedigree with the other cultivable species in the same family (Mliki et al. 2001). As India started the cultivation of melons long back, it was observed that many unexplored land races and wild relatives of melons having several useful characters were still unused. The accessions of such wild relatives were kept in store for future purpose as these wild relatives of any plants were known to contain many useful characters improving the yields, resistance against stresses, and the quality of the fruits. Understanding hybrid cultivars is a complex process. These cultivars come from crosses between wild relatives and cultivable species. This process takes a lot of time and effort. However, we can do this more efficiently now. We use techniques like marker-assisted breeding and genetic engineering. Although, some of the wild relatives of melons were explored to having many useful characters like maximum yields and stress resistance, many were yet to be explored as the process was time consuming (Endl et al. 2018).

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Melons belong to the Cucurbitaceae family and have several wild relatives within the same genus, such as C. amarus, C. mucusospermus, C. colocynthis, and C. zeyheri (Zhang et al. 2019). These wild species are genetically very diverse and can provide useful genes for improving cultivated melons in terms of pest and disease resistance, drought tolerance, fruit quality, and other traits (Lotti and Fernández-Silva 2019). Plant breeders have successfully crossed cultivated melons with some of these wild species, such as C. amarus, to introduce beneficial alleles into the melon gene pool. However, there are also challenges and limitations in using wild relatives for melon improvement, such as reproductive barriers, linkage drag, and genetic diversity loss (Guo et al. 2019). A comprehensive genome variation map of 1175 melon accessions and nine related species was recently published, which revealed the domestication history, population structure, and genetic diversity of melons and their wild allies. This resource could help identify novel genes and QTLs from wild species that could enhance melon-breeding programs (Zhao et al. 2019).

5.2

Relationship with Geographical Distribution

Melons are believed to have originated in Central Eastern Africa, and they spread throughout the world, possibly due to animals, humans, or birds carrying them. Musk melons come under Cucurbitaceae family with differences in their species, shapes, and sizes (Kerje and Grum 2000). Certain species of melons called winter melons, Citrullus, and water melon were known to have originated in Africa and distributed to all over the world. Whereas, horned melon which originated in Africa was immediately grown in Australia, New Zealand, and Chile. Also, cantaloupe melon was cultivated in Italy. Honey dew and honey melon cultivars were cultivated in some parts of China. Mirza melon was cultivated in central Asia. Sharilyn melons, Galia, and Northern American cantaloupes were cultivated in European countries. There were many other cultivars which were grown in different parts of the world. Therefore, the above distribution of different melons all around the world in different countries provides an insight regarding the positive relationship of melons with respect to geographical distributions (Pavan et al. 2017).

5.3

Extent of Genetic Diversity

Melons are diploid species with 2n ¼ 2x ¼ 24 chromosomes believed to be originated mostly in Africa and certain parts of Asia. After a few years, the melons’ domestication was observed in Egypt, Europe, Middle East, China, and Afghanistan, whereas some other species of melons were imported from one country to another. Even though Africa is known to be the center of origin for melons, China was considered as the maximum producer and exporter of different hybrid melons. On an

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average, these melons contain nearly 800 species or more under cultivation in different parts of the world (Nuñez-Palenius et al. 2008). Several diversified characters and forms of melons were observed in different areas which include size ranging between 5 and 20 kgs, flesh color – orange, pink, red, white, etc., rind color – green white, yellow, red, etc., and form – round, flat, elongated, etc., based on different variations observed among different melon species. The changes in the sexual nature of the species, sex expression, and productivity of melons differ from species to species where some species gave low quality compared to the others. Even though many plant-breeding techniques emerged in melon cultivation they were observed to be less successful compared to newly emerging marker-assisted breeding and genetic transformation methods. These methods were also known to increase the diversity among the species by developing new, tolerant, and high-yielding cultivars in all the species of melons. Therefore, it was observed that the presence of maximum species of melons with less yields and low quality previously, the changes in the techniques for improving the yield, and other parameters gave rise to highly improved cultivars which were able to tolerate any stress up to a certain level, and such species were adaptable in different environmental conditions which was purely attained by the developed techniques under molecular biology (Guliyev et al. 2018).

6

Biotechnological Intervention for Health-Related Traits

Even though melons contain high nutrients, their shelf life, pollination, and storage create many problems in reducing the market value of the fruits. Many scientists conducted experiments in melons to modify the fruits to be beneficial for consumption, and a few were successful in improving the yields and storage life of the fruits. Therefore, certain melon species were genetically modified for their ethylene biosynthesis in order to reduce the ripeness of the fruits to increase the shelf life for longer storage. On the other hand, seedless watermelons were developed by crossing male and female flowers. Also, certain gene modification in watermelons increased the sucrose content ultimately the sweetness of the fruits and the lycopene content, i.e., the antioxidant nature of the fruits so that they can be beneficial for consumption (Ezura et al. 2000). There are many other aspects through which the melon fruits can be improved and made beneficial not only for consumption but also to increase the market value of the fruits. Therefore, it was understood that the implementation of molecular biology and biotechnology techniques in the improvement of melon fruits for different aspects was proven to be beneficial and useful in meeting the nutritional requirements after consumption. Biotechnology makes crop improvement faster and more accurate. It’s a good alternative to traditional breeding methods, which take a lot of time (Ahmar et al. 2020). Cucumis melo is a highly diverse crop with many cultivars and landraces that differ in morphological and agronomic traits. Several studies have assessed the

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genetic diversity of melon collections based on phenotypic characters, such as fruit shape, size, color, texture, flavor, and yield.

6.1

Molecular Mapping for Health-Related Traits in Melon

Molecular mapping for health-related traits in melon is a technique that uses molecular markers to locate genes or quantitative trait loci (QTLs) that affect traits such as fruit quality, disease resistance, antioxidant content, or seed size. Molecular markers are DNA sequences that can be detected by various methods such as polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR), or single nucleotide polymorphism (SNP). These markers can be used to construct genetic linkage maps that show the relative position and distance of the markers on each chromosome (Diaz et al. 2011). By comparing the linkage maps of different individuals or populations with different phenotypes for a trait of interest, it is possible to identify the regions that are associated with the trait variation (Kumar and Sharma 2018). These regions are called QTLs, and they may contain one or more genes that influence the trait expression (Zhang and Liu 2017). Molecular mapping can help to identify candidate genes or regions that control these traits and facilitate marker-assisted selection or gene editing for improving melon breeding. Marker-assisted selection is a method that uses molecular markers to select individuals with desirable genotypes for a trait without relying on phenotypic evaluation (Leng and Xu 2017). Gene editing is a technique that uses engineered nucleases such as CRISPR-Cas9 to introduce targeted mutations or modifications in specific genes or regions of interest. Molecular mapping can also reveal the genetic diversity, population structure, and linkage disequilibrium of melon germplasm and provide insights into the evolution and domestication of different melon types (Liu and Zhang 2020). Genetic diversity is the amount and distribution of genetic variation within and among populations. Population structure is the pattern of genetic differentiation among populations due to factors such as geographic isolation, migration, selection, or drift. Linkage disequilibrium is the nonrandom association of alleles at different loci due to physical linkage or historical recombination events. Evolution and domestication are processes that shape the genetic and phenotypic changes in organisms over time due to natural or artificial selection pressures (Pandey and Saxena 2013).

6.2

Molecular Breeding and Genomics for Health-Related Traits in Melon

Molecular breeding and genomics for health-related traits in melon is a research field that aims to improve melon varieties by using molecular tools and genomic information. Health-related traits include disease resistance, fruit quality, antioxidant content, seed size, and other traits that affect human health and nutrition (Liu et al. 2020).

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Molecular tools include molecular markers, genetic linkage maps, quantitative trait loci (QTLs), candidate genes, genome editing, and gene expression analysis. Genomic information includes genome sequences, transcriptomes, proteomes, and metabolomes of different melon types (Zhang and Liu 2017). Molecular breeding and genomics can help to identify genetic variation, dissect trait inheritance, select desirable genotypes, and modify target genes or regions for improving melon breeding (Pandey and Saxena 2021). Molecular breeding and genomics are powerful tools for improving health-related traits in melon (Cucumis melo L.), such as disease resistance, fruit quality, and nutritional value (Chikh-Rouhou et al. 2023). Melon is a highly diverse crop with a wide range of morphological and physiological characteristics, making it a model plant for studying various aspects of plant biology. Several genomic resources have been developed for melon, including genome assemblies, molecular markers, gene expression data, and genetic maps (Liu et al. 2022). These resources enable the identification and characterization of quantitative trait loci (QTLs) or candidate genes associated with health-related traits in melon. For example, QTLs for resistance to Fusarium wilt, powdery mildew, cucumber mosaic virus, and melon necrotic spot virus have been mapped and validated in different melon populations (Zhao et al. 2021). Similarly, QTLs for fruit quality traits such as sugar content, flesh color, aroma, and antioxidant activity have been identified and used for markerassisted selection (MAS) in melon-breeding programs. Moreover, genomics allows the discovery of novel genetic diversity and functional variation in melon germplasm collections that can be exploited for enhancing health-related traits in melon (Gonzalo et al. 2005). In addition to conventional breeding methods such as hybridization and selection, molecular breeding techniques such as MAS, genomic selection (GS), gene pyramiding (GP), and genome editing (GE) can be applied to improve health-related traits in melon by increasing the efficiency +and accuracy of selection (Boualem et al. 2016). Molecular breeding and genomics have thus contributed significantly to the advancement of knowledge and innovation in melon research and development.

7

Conclusions

In conclusion, melons are delicious fruits with high nutritional value that offer numerous health benefits. They are packed with minerals, vitamins, fiber, and beneficial compounds, making them an excellent choice for a healthy diet. Melons, such as cantaloupe, watermelon, and honeydew, contain vitamins C, B6, and K, as well as potassium and copper. The seeds of melons also provide health benefits, including regulating blood pressure and promoting healthy skin. Additionally, melons possess medicinal properties, such as antioxidant and antiinflammatory effects. Through molecular breeding approaches, researchers aim to enhance the growth, yields, and nutritional qualities of melons. Incorporating melons into our daily diet can contribute to overall well-being and protect against malnutrition.

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Guava: A Nutraceutical-Rich Underutilized Fruit Crop Malarvizhi Mathiazhagan, Vasugi Chinnaiyan, and Kundapura V. Ravishankar

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Phytochemicals with Nutraceutical Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Guava Leaf . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Guava Fruit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Guava Seed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Guava Bark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Post-Harvest Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Biotechnological Interventions to Improve Nutraceutical Properties . . . . . . . . . . . . . . 3 Genetic Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Genetics and Traditional Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Analysis of Genetic Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Molecular Mapping and QTL Identification for HR Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Social, Political, and Regulatory Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Psidium guajava L., commonly known as guava, is native to the tropical and subtropical regions. It is one of the important commercial fruit crops rich in nutrients and phytochemicals that have many medicinal and nutritional benefits. It is now being recognized as “super fruit” due to the attractive color and compounds, which are known to be active as neutralizers of free radicals and are beneficial to human health. Guava fruit, leaf, bark, and seeds contain bioactive compounds that can M. Mathiazhagan · K. V. Ravishankar (*) Division of Biotechnology, ICAR–Indian Institute of Horticultural Research, Bengaluru, India e-mail: [email protected] V. Chinnaiyan Division of Fruit crops, ICAR–Indian Institute of Horticultural Research, Bengaluru, India © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_42

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function as antioxidants and anti-inflammatory agents, thereby helping in alleviating different types of cancer, diabetes, and infectious diseases and promoting overall health. Guava genetic resources are diverse, with more than 400 germplasm and cultivars available around the world. Morphogenetic and molecular studies have improved our understanding of the guava germplasms. This chapter discusses in detail about the health benefits of phytochemicals, as well as genetic and molecular studies for improvement of health-related traits in guava. Keywords

Guava · Phytochemicals · Bioactive compounds · Molecular markers · QTL · Nutraceutical

1

Introduction

Guava (Psidium guajava L) is widely grown across the tropical and subtropical countries of the world. Increased public awareness toward balanced diet along with nutrient benefits of guava has resulted in a global market demand for the fruit. In addition to the fruit, leaf, bark of stem, root, and seeds are also rich in phytochemicals, vitamins, and minerals. Because of their antioxidant, antidiabetic, anti-inflammatory, anticancerous, and antidiarrheal properties, many parts of the plant are found to be beneficial to human health (Shanthirasekaram et al. 2021; Blancas-Benitez et al. 2022) (Fig. 1). Further, because of its climacteric nature, the shelf-life of the fruit is less and

Fig. 1 Benefits of different parts of guava for human health

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warrants immediate consumption. Hence, to mitigate this post-harvest loss, a variety of processed and functional food products like guava purees, jams, jellies, RTS beverages, ice creams, tea, etc. have been developed, which preserve the bioactive compounds found in the fruit and thereby catering the nutritional needs of the consumers (Sampath Kumar et al. 2021) have been developed by various workers. In order to exploit the genetic resources available in guava, morphological and genetic diversity studies play a major role. Different molecular markers have been employed to characterize and analyze the variability of guava accessions and cultivars (Pavani et al. 2022; Usman et al. 2020). Because it is an underutilized crop, there have been little efforts to understand the quantitative trait loci (QTLs) or genes controlling the important fruit quality and health-related traits. In addition, application of markerassisted selection (MAS) and genome-assisted breeding approaches such as genomewide association studies (GWAS), genomic selection (GS), and genome editing has not been understood in guava. With the advancements in sequencing technologies and metabolomics, efforts to identify health-related traits like vitamin C content, lycopene content, shelf-life, etc. are expected to accelerate in the future.

2

Phytochemicals with Nutraceutical Properties

Various studies on the physical, chemical, and sensory attributes of guava fruit, leaf, seed, and stem bark have been undertaken all over the world. The fruit is a rich source of vitamin C (which is four times higher than orange) and other vitamins like vitamin A (retinol), vitamin B1 (thiamine), vitamin B2 (riboflavin), vitamin B3 (niacin), and vitamin B6 (pyridoxine) (Kumari et al. 2018); minerals like calcium, magnesium, phosphorus, potassium, zinc, and iron; proteins; carbohydrates; dietary fiber (5.2 g/ 100 g); and lycopenes and carotenes (USDA 2019; Pandian and Jayalakshmi 2019). It’s also a good source of pectin (0.5–1.9%). Many pharmacological studies have shown that the phytochemicals found in different parts of the guava plant possess various health benefits and have medicinal applications. The composition and concentration of several chemical compounds present in guava differ among the cultivars and are also influenced by the horticultural practices adapted.

2.1

Guava Leaf

The leaves are simple, opposite, oblong to elliptic with an entire margin, and have a specific aroma when crushed, which comes from an essential oil and smell depends on the cultivar. Because of its antioxidant potential and numerous phytochemicals which can boost health and ameliorate the effects of ailments or diseases, guava leaf tea is a better herbal tea alternative to commercial tea. The leaves have long been used in traditional medicine to treat diarrhea (Birdi et al. 2020) and other gastrointestinal ailments and infections. The leaf extracts have been used to treat a variety of pathogenic bacteria and viruses as natural antimicrobial agents. Some Ethiopian guava cultivars were found to have good antagonistic activity against Salmonella

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typhi and Shigella boydii (Oncho et al. 2021), whereas various commercial guava cultivars with high phenols, flavonoids, and increased antioxidant activity were found to have a high level of inhibition against Escherichia coli and Bacillus subtilis (Melo et al. 2020). Guava leaf extracts are more effective against Gram positive than Gram negative bacteria in many studies (Abdullah et al. 2019). In addition, guava leaf tea has been demonstrated to be effective in suppressing influenza H1N1 viruses (Sriwilaijaroen et al. 2012). The antimicrobial activity of the leaf extract was found to differ based on the solvents used for extraction (Biswas et al. 2013). The multitude of phytochemicals such as flavonoids, phenols, saponin, alkaloid, glycoside, terpenoids, tannins, polyphenols, and quinones found predominantly in the guava leaf extracts were found contributing to its plethora of health benefits (Shanthirasekaram et al. 2021). In addition, guava leaf extracts can also act as natural immune stimulants, enhancing our immune system’s ability to fight infections (Laily et al. 2015). The mouthwash of leaves was effective for aphthous ulcers in terms of reduction of symptoms of pain and faster reduction of ulcer size (Guintu and Chua 2013). The presence of functional compounds or the bioactive poly-phenolic compounds like quercetin, caffeic, ferulic, ascorbic, and gallic acids acts as antioxidants in the treatment of numerous diseases (Denny et al. 2013). The leaf extract has been found to be promising as a herbal medicine to treat hyperglycemia. The leaves were shown to possess antidiabetic activity in diabetic mice, protective activity on liver cells (Zhu et al. 2020), reduced oxidative stress, inhibition of inflammation, and β-cell death (Jayachandran et al. 2018). The bioactive substances such as triterpenoids, monoterpenoids, flavonoids, and phenolic compounds have been discovered as important components in the regulation of type 2 diabetes mellitus (Jiang et al. 2021). These compounds control the insulin secretion and thereby lower the blood glucose level. Furthermore, due to their high free radical scavenging activity, polysaccharides from guava leaf have shown potential to be used as an antidiabetic or antioxidant compounds (Luo et al. 2019). Guava leaves also have anticancer activity and show growth inhibition of cancer cells and inducing apoptosis. Kampferol in guava leaves have been proven to have scavenging and antiproliferative activity on thyroid cell lines (Kim 2011), betulinic acid on human cholangiocarcinoma cell lines (Phonarknguen et al. 2022), polyphenols on breast, lung, and prostate cancer cell lines (Alhamdi 2019). As an alternative, because of their antiproliferative, antioxidant, and antibacterial properties, essential oils from guava leaf have also been used for treating various diseases (Rakmai et al. 2018). The guava leaf oil is a rich source of volatiles like Caryophyllene, 1, 8-Cineole, Limonene, a-Pinene, and different proportions of terpenes and hydrocarbons (Soliman et al. 2016). As the leaves possess antimicrobial compounds, leaf extracts and essential oils are commonly used as a medicine against gastroenteritis.

2.2

Guava Fruit

The fruit is a berry with a thick pericarp and pulpy seed cavity, emitting a strong, sweet, musky odor when ripe. The shape ranges from glucose to sub-globose,

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spherical, oblong, ovate, and pyriform, with four or five protruding floral remnants (sepals) at the apex weighing up to 500 g depending upon the cultivars. The fleshy mesocarp is of varying thickness and has a softer endocarp with numerous small, hard yellowish-cream seeds embedded throughout (Malo and Campbell 1994). The skin is thin, and the color of ripe fruit varies from pale yellow to dark yellow or blushed with pink, sometimes completely pale green or dark purple, depending upon the cultivars. The pulp color may be white, creamy white, creamy yellow, pale pink to dark red, purple to orange, slightly juicy, acid, sub-acid, or sweet and flavorful. The fruits are rich sources of carbohydrates (12.16%), proteins (2.3%), fats (0.7%), ascorbic acid (241.86 mg/100 g), fiber (4.8%), and minerals like calcium (17.63 mg), iron (0.24 mg), and zinc (0.21 mg/100 g), and moisture content (84.31%). The calorie yield is around 68 calories/100 g of fruit (Bogha et al. 2020). Among the pulp colors, the pink/red pulp types are more nutritious due to the presence of higher amount of phytochemicals and secondary metabolites like phenolic compounds, flavonoids, carotenoids, and tannins, which contribute to its antioxidant potential (Suwanwong and Boonpangrak 2021) than the white pulped fruits. The whole fruit is generally consumed, as the peel is rich in ascorbic acid and phenolic compounds compared to pulp (Musaa et al. 2015; Emanuel et al. 2018). The pink or red pulped guava fruits have shown to be a promising therapeutic alternative due to their increased antioxidant potential and high levels of lycopene and vitamin C (Nwaichi et al. 2015). Numerous studies have emphasized the importance of using lycopene-rich guava fruit extract for treating different ailments, including reducing oxidative stress damage in human dermal fibroblasts (Alvarez-Suarez et al. 2018); ameliorative effects on cigarette smoke-damaged pulmonary tissues (Meles et al. 2021); cytostatic and cytotoxic effects on breast cancer cells (Dos Santos et al. 2018); modulating colon health (Blancas-Benitez et al. 2022); inhibition of intestinal resorption of glucose (König et al. 2019); frailty reduction and health promotion (Ruangsuriya et al. 2022). Pharmacological studies on pink-pulped guava fruits recorded increased hemoglobin levels in pregnant women (Sormin et al. 2020); antiplatelet activity (Rojas-Garbanzo et al. 2021); and apoptosis induction in breast cancer cells (Liu et al. 2020; Polinati et al. 2022). Guavinoside B, a biologically active compound found in guava fruit, displayed inhibitory activities on α-glucosidase, thereby providing a new therapeutic possibility for people with diabetes (Xu et al. 2022). Additionally, guava pulp, seed, and leaf phenols have shown to improve the diabetic parameters in albino rat model (Shabbir et al. 2020). Presence of high amounts of ascorbic acid, flavonoids, and polyphenols makes guava fruit a suitable candidate as a natural therapeutic agent.

2.3

Guava Seed

The seeds are good source of proteins, fats, dietary fiber, phenolics, flavonol, glycosides, tannins, saponins, and vitamins. They possess free radical scavenging activities due to the presence of phenolic compounds like chlorogenic acid, apigenin and its glycosides, caffeic acid derivatives, quercetin, phytosterols and fatty acids

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like ethylpalmitate, linoleic acid, stigmasterol, and campesterol, and dietary fiber (Prommaban et al. 2020; Emanuel et al. 2018). Additionally, the polysaccharides from guava seeds were also found effective in immunomodulation and inhibition of breast cancer cell growth (Lin and Lin 2020) and prostate cancer cell growth (Lin and Lin 2021). Further, the seed oil has exhibited wound healing properties and also demonstrated growth inhibition of human erythroleukemic cells (Prommaban et al. 2019). In addition, the seed protein hydrolysates displayed α-amylase inhibition, thereby making it a suitable plant peptide-based antidiabetic agents (Jamesa et al. 2020). The seeds, generally obtained as a by-product of processing industry, have the potential to be utilized as a functional food, food additives, or structural modulators in addition to their nutraceutical applications. An elaborate review on the uses of guava seeds in food processing and nutraceutical applications is available for further reading (Kumar et al. 2022).

2.4

Guava Bark

Along with the leaves, guava stem bark has been used in traditional medicine to treat diarrhea, dysentery, and fever. The presence of bioactive phenolic compounds like gallic acid, chlorogenic acid, caffeic acid, and ellagic acid and flavonoids like catechin, rutin, quercetin, and luteolin renders guava stem bark with good antimicrobial (Gurmachhan et al. 2020), antidiabetic, antinephrolithiatic (Irondi 2020), and other health benefits (Table 1). The presence of flavonoids, tannins, alkaloids, and saponins in the root barks of guava was also reported to have antimicrobial and antioxidant activities (Kuber et al. 2013).

2.5

Post-Harvest Techniques

The fruits are climacteric, ripens fast with increase in rate of respiration and metabolic activities due to which the shelf life of fruits does not last for more than 5–7 days and making them unpleasant and commercially undesirable. Hence, there is a need for processing raw fruit into ready-to-eat products with a longer shelf life coupled with enhanced nutritional attributes. It is processed into wide an array of products like juice, jam, jelly, puree, concentrate, cheese, toffee, fruit flakes, squash, syrup, nectar, powder, wine, and vinegar, as well as ready-to-eat snacks, drinks, ice cream, biscuits, dehydrated, and canned products (Kumari et al. 2018; Sampath Kumar et al. 2021; Kumar and Gupta 2021). The by-products obtained from pulp industries are generally used as food additives, pharmaceuticals, biofuels, etc. (Iha et al. 2018; Anjali and Manjul 2021; Hoyos et al. 2022) and serve as promising functional foods due to the presence of a large number of phytochemicals (da Silva Lima et al. 2019). Guava leaves, fruits, and seeds have become functional foods due to their health benefits. Biscuits made from guava seeds and pulp have been reported to have a significant effect in reducing the blood glucose levels in diabetes patients

Antioxidant

Leaf, bark

Leaf

Caffeic acid

Ferulic acid

Antioxidant

Antioxidant

Seed, bark

Ellagic acid

Antioxidant

Antioxidant, antimicrobial

Leaf, seed, bark

Fruit, seed

Properties

Plant source

Myricetin

Bioactive compounds Structure Phenolic and poly-phenolic compounds Chlorogenic acid

Table 1 Prominent bioactive compounds present in guava

Denny et al. 2013

(continued)

Denny et al. 2013; Gurmachhan et al. 2020

Prommaban et al. 2020; Gurmachhan et al. 2020

Emanuel et al. 2018

Prommaban et al. 2020; Gurmachhan et al. 2020

Reference

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Antioxidant

Leaf, bark

Fruit

Leaf, bark

Fruit, seed

Gallic acid

Guavinoside B

Tannins

Flavonoids Apigenin

Antioxidant and antimicrobial

Antioxidant, antimicrobial

Antidiabetic

Properties Antioxidant, antiinflammatory

Structure

Plant source Leaf, fruit

Bioactive compounds Ascorbic acid

Table 1 (continued)

Prommaban et al. 2020; Melo et al. 2020

Oncho et al. 2021

Xu et al. 2022

Melo et al. 2020; Gurmachhan et al. 2020

Reference Suwanwong and Boonpangrak 2021

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Antioxidant, antidiarrheal

Antioxidant

Antioxidant

Leaf, bark

Fruit, leaf

Fruit

Quercetin

Gallocatechin

Procyanidin B

Antioxidant and antimicrobial

Fruit

Myrcetin

Prommaban et al. 2020

Blancas-Benitez et al. 2022

(continued)

Emanuel et al. 2018; Gurmachhan et al. 2020

Shukla et al. 2021

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Antioxidant Antioxidant Antioxidant

Fruit

Seed Seed Seed

Polysaccharides Pectin

Fatty acids Ethyl palmitate

Linoleic acid

Oleic acid

Antidiabetic and antioxidant

Antioxidant

Fruit

Antioxidant

Properties Antioxidant, anticancer

Β-carotene

Plant source Leaf

Fruit

Structure

Carotenoids Lycopene

Bioactive compounds Kampferol

Table 1 (continued)

Prommaban et al. 2020

Prommaban et al. 2020

Prommaban et al. 2020

Chang et al. 2020

Nwaichi et al. 2015

Shukla et al. 2021

Reference Phonarknguen et al. 2022

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Antioxidant

Seed

Leaf, bark

Campesterol

Alkaloids Saponins Antioxidant, antimicrobial

Antioxidant

Seed

Stigmasterol

Antioxidant

Seed

Palmitic acid

Oncho et al. 2021

Prommaban et al. 2020

Prommaban et al. 2020

Prommaban et al. 2020

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(Kaushik 2019). Further, guava seeds have found applicability in anti-acne face wash gels that harnesses their antioxidant and antimicrobial properties (Kamble et al. 2019). Similarly, guava purees rich in vitamin C and polyphenols have been reported to have a positive effect on the hyperglycemic and hypercholesterolemic rats (PérezBeltrán et al. 2017). Guava acts as a prebiotic and improves the flavor and nutritional value of traditional dairy products like yogurt, whey beverages, mousse, and smoothies (Chauhan et al. 2015). In addition to adding value, post-harvest packaging techniques are critical for maintaining the fruit quality and nutritional attributes for an extended period of time (Etemadipoor et al. 2020). Different packaging techniques like modified atmosphere packaging (MAP) (Mangaraj et al. 2021), controlled atmosphere packaging (CAP), edible packaging (Murmu and Mishra 2018), antimicrobial/antifungal packaging (Elabd 2018), and nano packaging (Kalia et al. 2021) are available to extend the shelf life with minimal changes to the physiochemical properties of the fruit. Overall, post-harvest management, value-addition and processing in guava has gained significance in recent years with different kinds of functional foods being introduced into the market. However, in order to preserve the fruit’s functional properties in the processed goods, the guava processing technologies must be improved, and in-depth research is needed.

2.6

Biotechnological Interventions to Improve Nutraceutical Properties

Besides some phytochemical analysis and basic pharmacological studies, the information on the mechanism of action of bioactive compounds and their antioxidant pathways are scarce in guava. In order to speed up guava breeding efforts, research on molecular markers, genes, and QTLs linked to nutraceutical properties such as vitamin C, lycopene content, shelf life, etc. are essential. Further, gene expression studies, association mapping, prediction modeling (genomic selection), and genome editing techniques can help expedite the efforts in identifying and breeding new guava cultivars with enhanced nutritional and therapeutic applications.

3

Genetic Resources

Guava is an important commercial crop in the tropical and subtropical countries and is cultivated in India, Mexico, Brazil, Thailand, Spain, Portugal, Southern France, Israel, Panama, EI Salvador, Costa Rica, Nicaragua, Bolivia, Malaysia, Kenya, the USA (Hawaii, California, and Florida), New Zealand, the Philippines, China, Indonesia, Cuba, Java, Venezuela, Pakistan, Australia, and some African countries, with India contributing around half the world’s guava production. From tropical American countries, guava reached Asian and African countries through its colonizers like Spain and Portugal. It is reported that there are more than 400 guava cultivars are available around the world, majority of which belongs to the cultivated species,

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Psidium guajava L. There are other wild species that has a wide variability in fruit shape, size, and flavor. Some important species which are used in breeding program for imparting resistance to biotic and abiotic stresses are: Guinea guava or Castilian guava or Brazilian guava (Psidium guineense Sw syn: P. Molle Bertol, P. Araca Raddi, P. Schiedeanum O.Berg.), Strawberry or cherry guava or cattley guava or Chinese guava (P. Cattleianum Afzel. ex Sabine syn; Psidium littorale Raddi, P. littorale (Raddi) var. longipes (O.Berg.), P. cattleianum var. littorale (Raddi) Mattos, P. cattleianum var. Purpureum Mattos, P. Cattleianum var. Pyriformis Mattos), Costa Rican guava or Cas guava (Psidium friedrichsthalianum (O.Berg) Niedenzu, syn: Calyptropsidium friedrichsthalianum) (Rajan and Hudedamani 2019). Prominent guava cultivars around the world for commercial and breeding works are listed here (Table 2). Guava fruit quality parameters like shape, size, TSS, acidity, peel color, pulp color, pulp recovery, pectin content, ascorbic acid, phenols, dietary fiber, and shelf life vary greatly among guava germplasm collections around the world. Some of the traditional and modern cultivars rich in health-related traits are listed in Table 3.

4

Genetics and Traditional Breeding

Information on the genetics and inheritance of genes related to commercial traits is limited due to the perennial nature and heterozygosity of the guava plant. Guava breeding programs have generated segregating populations/progenies by crossing contrasting cultivars to understand the segregation phenomenon governing important quantitative traits like fruit peel color, pulp color, seed characters, fruit weight, yield, TSS, acidity, leaf characters, and tree characters. But only a small portion of the genetic diversity available in the crop has been utilized for commercial purpose, and the good amount of diversity that exists in the wild progenitors needs to be explored. When it comes to pulp color, red was reported to be dominant over white pulp, with a segregation ratio of 3:1. In addition, red pulp has shown strong linkage with large and hard seeds, whereas white pulp has been linked with small and soft seeds (Subramanyam and Iyer 1990). The fruit quality traits like TSS in guava appear to be due to non-additive gene effects, while fruit weight and seed hardiness exhibited a negative association at the phenotypic and genotypic levels (Dinesh et al. 2017). The characters like fruit yield, fruit weight, outer flesh thickness, acidity, number of seeds per fruit, seed weight, plant height, phenol, and pectin content were governed by additive gene action and had high heritability combined with high genetic advance as percent of mean (Patel et al. 2015; Singh et al. 2015a; Gupta and Kour 2019). Further, a few studies have reported a low genetic variability and a high phenotypic variability for characters like fruit mass, fruit width, sepal size, length of stalk, external flesh thickness, internal flesh thickness, and external/internal flesh thickness ratio. This indicates the influence of environmental conditions over the phenotypic variability of individual progenies in a population. In contrast, the length of fruit and the ratio of diameter of calyx/fruit had a very high heritability due to additive effects

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Table 2 Prominent guava cultivars grown around the world Country Australia

Bangladesh Brazil

China Cuba Egypt India

Indonesia Malaysia Mexico Pakistan

South Africa

Taiwan Thailand USA

Vietnam

Cultivar name ‘Northern Gold’, ‘Thai White’ (‘Glom Sali’), ‘Common’, ‘Cherry’, ‘Allahabad Safeda’, ‘Beaumont’, ‘Sardar’, ‘KaHua Kula’ ‘Swarupkathi’, ‘Mukundapuri’, ‘Kanchannagar’, ‘Kazi’ Paluma’, ‘Rica’, ‘Pedro Sato’, ‘Seculo XXI’ ‘Sassaoka, ‘Yamamoto’, ‘XXI Century’, ‘Kumagai’ ‘Pearl’, ‘Red Heart’, ‘China pear’ EnanaRoja’, ‘Cubana’, ‘EEA 1-23’, ‘Supreme Roja’ ‘Bassateen El Sabahia’, ‘Bassateen Edfina’, ‘Allahabad Safeda’ ‘Allahabad Safeda’, ‘Swetha’, ‘Dhawal’, ‘Apple Colour’, ‘Lucknow-42’, ‘Lucknow-49’, ‘Safeda’, ‘Seedless’, ‘Red Fleshed’, ‘Lalit’, ‘Lalima’, ‘Red Supreme’, ‘Red-flHybr’, ‘Banarasi Surkha’, ‘Chittidar’, ‘Harijha’, ‘Sardar’, ‘Arka Mridula’, ‘Arka Amulya’, ‘Arka Kiran’, ‘Nagpur seedless’, ‘Hisar Surkha’ ‘Kristal’, ‘Bangkok merah’, ‘Kamboja’, ‘Dadu1’, ‘Dadu 2’, ‘Pipit’, ‘Susupith’ Jambubiji’, ‘Gu-5’, ‘Beaumont Semeyih’, ‘Beaumont Sungkai’, ‘Hongkong Pink’ ‘Media China’, ‘China’ ‘Safeda’, ‘Allahabad’, ‘Lucknow-49’, ‘Red Fleshed’, ‘Seedless’, ‘Kerala’, ‘Apple Colour’ ‘Fan Retief’, and ‘TS-G2’, ‘Glom Toon’ ‘Klau’, ‘Khao Boon Soom Vietnam Xalynghe’, ‘Ruothong da lang’ ‘Jen-Ju’, ‘Di Wan’, ‘Pearl’, ‘Rainbow’, ‘Media China’, ‘China’ ‘Kim Ju’, ‘Pan Si Thong’, ‘Sa Li Thong’ ‘Homestead’, ‘Barbi Pink’, ‘Blitch’, ‘Hong Kong Pink’, ‘Patillo’, ‘Crystal’, ‘Lotus’, ‘Supreme’, ‘Webber’, ‘Beaumont’, ‘KaHua Kula’ ‘Le Dai loan’, ‘Nu hoang’, ‘Khong hat’, ‘Xa li nghe’, ‘Ruot do’, ‘Se’, ‘Tim’

Reference Mitra and Thingreingam Irenaeus 2016; Rajan and Hudedamani 2019 Rajan and Hudedamani 2019 Mitra and Thingreingam Irenaeus 2016; Rajan and Hudedamani 2019 Tan et al. 2020; Jaleel et al. 2021 Mitra and Thingreingam Irenaeus 2016 Rajan and Hudedamani 2019 Dinesh and Vasugi 2010

Mayadewi et al. 2016 Mitra and Thingreingam Irenaeus 2016 Mitra and Thingreingam Irenaeus 2016 Mitra and Thingreingam Irenaeus 2016 Mitra and Thingreingam Irenaeus 2016; Rajan and Hudedamani 2019 Mitra and Thingreingam Irenaeus 2016 Mitra and Thingreingam Irenaeus 2016 Mitra and Thingreingam Irenaeus 2016

Mitra and Thingreingam Irenaeus 2016

of genes and with less environmental influence, which makes them a suitable candidate for improvement and positive selection (Pelea et al. 2012). Seed hardiness, which is an important fruit trait, is negatively correlated with the number of seeds per fruit but positively correlated with 100 seed weight of the fruit (Rajan et al. 2012).

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Table 3 Some guava cultivars rich in nutritional values HR traits High vitamin C

Shelf life High Lycopene content High Phenolic content High Carotenoid content High dietary fiber High Pectin content

Cultivar name ‘Jen Ju’, ‘Di Wan’ and ‘Rainbow’, ‘Supreme’, ‘Jambubiji’, ‘Allahabad Safeda’, ‘Fan Retief’, ‘Lucknow-49’, ‘Media china’, ‘Sangam’, ‘Cotorrera’, ‘Microguayaba’, ‘H-118’, ‘H-138’, ‘H-153’, ‘ H-345’, ‘Selection 106’, ‘Selection 126’, ‘BG 76-8’, ‘BG 76-14’, ‘Darío 18-2’, ‘BG 76-21’, ‘Red fleshed’, ‘Seedless’, ‘G. Vilas Pasand’, ‘Pant Prabhat’, ‘Mirzapur seedling’, ‘EC 162904’, ‘G-6’, ‘Chakaiya Ruthmanagar’, ‘Dhareedar’ ‘Yilan Red’, ‘Arka Amulya’, ‘Sardar’, ‘Swetha’, ‘Arka Mridula’ ‘Arka Kiran’

Reference Mitra and Thingreingam Irenaeus 2016; Medina and Herrero 2016; Dinesh and Vasugi 2010; Pommer 2012

Mitra and Thingreingam Irenaeus 2016; Dinesh and Vasugi 2010 Mitra and Thingreingam Irenaeus 2016

‘Allahabad Safeda ’, ‘Fan Retief’, ‘Lucknow-49’, ‘Sangam’

Medina and Herrero 2016

‘Cortibel 1’

Medina and Herrero 2016

‘Allahabad Safeda ’, ‘Lucknow-49’, ‘Sangam’, ‘Lalit’

Medina and Herrero 2016

‘Allahabad Safeda ’, ‘Arka Mridula’ ‘Lucknow-49’, ‘Sangam’, ‘Lalit’, Selected genotype no. 2’

Medina and Herrero 2016

It is interesting to see that fruit characters like fruit yield, number of fruits and fruit mass are unaffected by vegetative characters like plant height, stem diameter, and canopy volume. In contradiction, a high genetic correlation was observed between fruit yield with number of fruits; fruit weight with fruit length, width, fruit core diameter, number of seeds per fruit and seed weight which facilitate concurrent selection for these traits (Santos et al. 2017; Shiva 2017). Moreover, the total chlorophyll content has a positive correlation with Vitamin C content of the guava fruit. In case of leaf characters, leaf length and breadth had a positive correlation with leaf area, but were negatively correlated to stomata number (Shiva 2017). Further, high genotypic variance was observed in terms of width of leaf, whereas low variability for leaf length and length/width ratio (Nagar et al. 2018). More number of studies on heritability and genetic gain of important fruit traits with health benefits like vitamin C, TSS, phenolic and pectin content, flavonoids, and carotenoids are needed to improve the available germplasms and for the selection of progenies. Overall, the traditional breeding approaches in guava take a long period and require large parcels of land for progenies. Hence, adapting modern breeding

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methods employing molecular markers and prediction tools will have an immense impact in terms of progeny screening, marker-assisted selection (MAS), genetic diversity analysis, association studies, genome editing, and genetic engineering.

5

Analysis of Genetic Diversity

Assessing the genetic diversity of guava germplasm can aid in crop improvement for traits of our interest, especially in the selection of parents for effective hybridization programs. Diversity analysis using phenotypic, biochemical, and genetic methods have been applied to study the available guava genetic resources in different countries (Singh et al. 2015b; Usman et al. 2020; Krause et al. 2021). Phenotypic characterization using descriptors related to tree, leaf, fruit, seed, and yield characters have assisted in understanding the divergence of guava germplasm and to identify suitable cultivars to enhance the genetic gain in breeding programs (Krause et al. 2021; Singh et al. 2015b; Pavani et al. 2022). Further, digital phenotyping has been applied to study the seed characters like texture, geometry, and color through digital image analysis to understand the genetic diversity among inbred guava lines (da Silva et al. 2021; Krause et al. 2017). Biochemical characterization consisting of healthrelated traits like Total soluble solids (TSS), total acidity, total sugars, sugar acid ratio, total flavonoids, total phenols, ascorbic acid, β-carotene, lycopene, and antioxidant activity have been studied to apprehend the divergence pattern among different white pulped cultivars (Usman et al. 2020) and different guava accessions (Santos et al. 2011). Although many morphological characters are used for discriminating genotypes, they fail to differentiate between closely related genotypes. Thus, DNA markers or molecular markers were utilized for genetic diversity analysis of guava based on different origins, pulp color, vitamin C content, and cultivars. Markers like PCR-based, hybridization-based, and sequence-based have been used for diversity studies. Markers like Amplified Fragment Length Polymorphism (AFLP) (Thaipong et al. 2017), Random Amplified Polymorphic DNA (RAPD) (Ahmed et al. 2011), Inter simple sequence repeat (ISSR) (Sharaf et al. 2020), Inter-primer binding site (iPBS) (Mehmood et al. 2016), and sequence-related amplified polymorphism (SRAP) (Youssef and Ibrahim 2016) have been used to study the variability among the guava cultivars. Simple Sequence Repeat (SSR) markers have been predominantly used to study the genetic diversity of accessions/germplasms in different countries like India (Kumari et al. 2018; Kherwar et al. 2018), Kenya (Chiveu et al. 2019), China (Ma et al. 2020), United States (Sitther et al. 2014), Pakistan (Kareem et al. 2018), Bangladesh (Alam et al. 2018), Mexico (SánchezTeyer et al. 2010), and Venezuela (Aranguren et al. 2008). Genomic SSRs developed from cultivar ‘Allahabad Safeda’ through microsatellite-enriched libraries were found suitable for genetic diversity studies, population structure analysis and also had high cross-species transferability among Psidium species (Kumar et al. 2020). SSRs developed from Psidium guajava have had a high cross transferability potential to members of Myrtaceae family like E. citriodora, E. camaldulensis,

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C. lanceolatus, and S. aromaticum, which can be utilized for inter- and intra-species genetic diversity analysis (Rai et al. 2013). Further, SSR markers have found its utility in studies assessing sexual compatibility among the Psidium species (Mulagund et al. 2021) and DNA fingerprinting (Chaithanya et al. 2017). Lately, due to advancements in next generation sequencing (NGS) and construction of draft genome assembly in guava, development of sequencing-based single nucleotide polymorphisms (SNPs), InDels, and transcriptome-based SSR markers from different peel and pulp-colored cultivars have become feasible. These markers have high applicability in population structure analysis, genetic diversity studies, and in breeding programs (Thakur et al. 2021). In addition, SNP markers identified using DArTSeq-based genotyping among different native Psidium species have shown high interspecific diversity (Grossi et al. 2021). The development of SNP-PCR and transcriptome-based SSR markers strongly associated with health-related traits can aid in precise identification of the cultivars, accessions, and wild species suitable for breeding programs in guava.

6

Molecular Mapping and QTL Identification for HR Genes

Various molecular markers like AFLP, SSR, RAPD, and SRAP were used for molecular mapping studies in guava. Genetic linkage maps were developed by mapping populations derived from heterozygous parents. Polymorphic markers were used to construct individual parental linkage maps and then assembled into an integrated map (Lepitre et al. 2010). Further, integration of phenotypic data with the marker data has helped in identifying QTLs that are correlated to different quantitative traits in guava (Ritter et al. 2010a). The first molecular linkage map of guava contained 167 AFLP markers in the integrated map, which helped in the identification of 15 QTLs for vegetative characters (Valdés-Infante et al. 2003) (Table 4). A genetic linkage map utilizing 220 polymorphic AFLP markers was constructed along with the identification of QTLs for leaf length, leaf width, petiole length, height, fruit weight, acidity, total soluble solids, vitamin C content, and pulp thickness utilizing a mapping population derived from dwarf cultivar ‘Enana Rojacubana’ as the female parent (Rodriguez et al. 2005). Later, Ritter et al. (2010a) constructed an integrated parental linkage map in three guava mapping populations (‘Enana’  ‘N’, ‘Enana’  ‘Suprema Roja’ and ‘Enana  ‘Belic L-207’) using AFLP and SSR markers. They obtained 11 linkage groups (LGs) corresponding to the haploid guava genome of 11 chromosomes for each parent. The integrated maps contained markers between 408 and 850 and were covering 1885–2179 cM, in length, respectively. Further, Ritter et al. (2010b) had conducted a QTL analysis using the linkage maps constructed for three mapping populations in their previous study. Sixteen different traits related to leaf and fruit characteristics and yields were recorded in both the parents and progenies of the three-mapping population. A total of 75, 56, and 59 QTLs for all the traits studied were detected in populations MP1 (‘Enana’  N’), MP2 (‘Enana’  ‘Suprema Roja’) and MP3 (‘Enana’  ‘Belic L-207’), respectively. Some QLTs were found

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Table 4 Genetic linkage maps and QTLs identified in guava Mapping population derived from crosses ‘Enana’  ‘N6’

Number of segregating individuals 81

‘Enana’  ‘N6’

81

‘Enana’  ‘N6’ ‘Enana’  ‘Suprema Roja’ and ‘Enana’  ‘Belic L-207’ ‘Enana’  ‘N6’

100–120

‘Kamsari’  ‘Purple local’

94

80

Type of linkage map Integrated

Molecular markers employed AFLP

No. of QTLs identified 15 QTLs for vegetative traits Integrated SSR Fruit weight – 3, fruit width – 3, acidity – 3, TSS – 2, Vit. C content – 2, pulp thickness – 2, seed number – 1, seed weight – 5 Integrated AFLP and 75, 56, and SSR 59 QTLs in each mapping population respectively Integrated AFLP and – SSR Parental SSR, One major QTL SRAP, and for average fruit RAPD weight, four QTLs for seed strength (hardness/ softness)

References Valdés-Infante et al. (2003) Rodriguez et al. (2005)

Ritter et al. (2010a, b)

Lepitre et al. (2010) Padmakar et al. (2015, 2016)

to be linked to SSR markers, which could be used for marker-assisted selection of progenies with desired traits in conventional breeding. A similar type of study was conducted by Lepitre et al. (2010) in a guava mapping population derived from a cross between two heterozygous guava cultivars (‘Enana’  ‘N6’). A total of 1364 AFLP and SSR markers were used for linkage mapping. The integrated map length was 2179 cM and had an average linkage group length of 198 cM/chromosome. Further, high throughput genotyping of 94 guava F1 progenies using SSR and SRAP markers had generated scorable polymorphic markers, that were used for the construction of parental (Cultivar ‘Kamsari’ and ‘Purple local’) genetic linkage maps using a LOD score of 4.0 (Padmakar et al. 2015). Padmakar et al. (2016) have also identified one major QTL linked to fruit weight and two major and two minor QTLs for seed strength based on linkage map enriched further using RAPD markers. These studies have shown some insight into the QTL regions responsible for health related traits like vitamin C, TSS, and acidity, along with other fruit and leaf-related quantitative and qualitative traits. However,

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adapting NGS-based genotyping methods like Genotyping by sequencing (GBS) becomes vital for exact identification of QTLs or genes linked to health-related traits. In addition, an RNA-Seq based transcriptome analysis of genotypes with contrasting peel and pulp colors at different stages of ripening has set the stage for the functional genomics of traits like colored pulp and peel (Mittal et al. 2020) in guava. The study has identified 68 candidate genes that are involved in peel and pulp color development in guava fruits. These genes involved in ethylene biosynthesis, phenylpropanoid, and monolignol pathways, along with the QTLs identified, have the potential to be used as predictive markers in marker-assisted selection (MAS) in conventional breeding. Interestingly, even though there is a dearth of NGS-based research in this crop, guava got its first chromosome-level genome assembly for the cultivar ‘New Age’ recently (Feng et al. 2021). This development will aid in reference-based genotyping, thereby assisting in construction of high-density linkage map, genome-wide association studies (GWAS), and Genomic selection (GS) in guava.

7

Nanotechnology

Nanoparticles (NPs) are produced through a complex physico-chemical reaction which involves release of toxic wastes, unsafe by-products, and a high level of energy intake. Hence, an alternate and safe method for metal nanoparticle synthesis can be achieved through green biosynthesis of NPs utilizing plant sources. Guava leaves rich in phytochemicals like flavonoids, phenols, polyphenols, tannins, saponins, terpenoids, ascorbic acid, and proteins can mediate the redox reactions, thereby reducing the salts/ions, stabilizing and capping the nanoparticles formed. Several metal nanoparticles synthesized using guava leaf extracts were reported to possess antimicrobial properties. The aqueous extracts of guava leaves have been used in the preparation of iron oxide, silver oxide (Dildar et al. 2022), and Zinc oxide (Jyoti et al. 2020; Balalakshitha and Kolanjinathan 2021; Ramya et al. 2022) nanoparticles that exhibited radical scavenging and antimicrobial activities against pathogenic Gram positive and Gram negative bacterial strains. Similarly, the silver nanoparticles synthesized from guava extract coated with polymeric micelles possessed high antifungal activity against Candida albicans (Suwan et al. 2019). In addition, these silver NPs presented high level of antioxidant, antibacterial, and cytotoxicity against the colon cancer cells (Sandhiya et al. 2021). The copper NPs synthesized using aqueous guava extract comprised of high antibacterial activity against bacterial pathogens, E. coli and S. aureus due to the presence of antioxidant compounds like polyphenols and ascorbic acid in the guava extract (Caroling et al. 2015). Likewise, aqueous and ethanol extracts of guava leaves have yielded gold NPs due to the involvement of flavonoids present in the leaf extracts (Raghunandan et al. 2009; Putri et al. 2021). Furthermore, a lipophilic nano-emulsion containing purified lycopene from red guava had shown potential as a drug delivery system because

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of its successful delivery of the lycopene to liver, kidney, and prostate organs of mice and also for enhancing the cytotoxicity against the prostate cancer cells (Vasconcelos et al. 2021). Another interesting application of nanotechnology is for the improvement of shelf life of guava fruits using nanoparticle-based coating materials. The edible coatings, like Zinc oxide NPs combined with chitosan and alginate (Arroyo et al. 2020) and solid lipid NPs (Zambrano-Zaragoza et al. 2013), were shown to increase the shelf life of the guava fruits. In addition, incorporation of guava puree in chitosan nanoparticle-based edible films for packaging has imparted favorable color and odor for these films (Lorevice et al. 2012). The nano-technological application of guava leaf extracts in synthesis of metal NPs can prove to be a cost-effective and safe method with a wide biomedical application.

8

Social, Political, and Regulatory Issues

The health benefits of guava plants can immensely contribute to the nutritional security of the growing population. Unfavorable weather conditions, pests and diseases, unavailability of good commercial cultivars, lack of processing and storage facilities, and post-harvest wastages are the major problems faced by guava growers. Awareness toward the market potential of guava fruit is needed to boost its cultivation among the farmers of the tropical and subtropical countries. Moreover, popularizing guava fruit and its benefits among the public can provide consumers with a cheaper and nutritious alternative. More importantly, developing post-harvest techniques and value-added products that retain the phytochemicals and antioxidants present in the fresh fruit could be a boon to the industry and consumer market. In order to ensure its safe deployment, regulatory issues related to its biomedical application, nanotechnology, and alternative therapies need to be streamlined.

9

Future Prospects

The tropical and subtropical regions are home to Psidium guajava, which is highly diverse and spread across the world. Studies have proved the antioxidant, anticancerous, antidiabetic, antidiarrheal, and anti-inflammatory potential of this highly nutritious commercial fruit crop. Although there are a few conventional breeding efforts, application of modern breeding techniques using precise molecular markers for marker-assisted selection (MAS), marker-assisted introgression (MAI), association studies, genomic selection, genome editing, and transformation studies are lacking in guava. Using high-throughput sequencing techniques like NGS can help in identifying SNP and SSR markers for important health-related traits in guava and thereby assist in speed breeding of superior guava cultivars and hybrids. Also, there is a need to develop strong international collaborations, industrial and academic interactions to ensure adequate public and private funding of projects which helps in faster outcome.

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Conclusion

Nutraceutical properties present in guava plant is being utilized in the traditional medicine practices of different countries. From leaf to seed, the potential benefits provided by this underutilized crop can help cure and mitigate various ailments as documented by different studies. On the other hand, it is essential to develop breeding materials and value-added products and popularize its benefits among the general public for a sustainable growth in guava production and utilization.

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Chaithanya N, Sailaja D, Dinesh MR, Vasugi C, Lakshmana Reddy DC, Aswath C (2017) Microsatellite-based DNA fingerprinting of guava (Psidium guajava) genotypes. Proc Natl Acad Sci India Sect B Biol Sci 87(3):859–867 Chang YP, Woo KK, Gnanaraj C (2020) Pink guava. In: Valorization of fruit processing by-products. Academic Press, London, pp 227–252 Chauhan AK, Singh S, Singh RP, Singh SP (2015) Guava-enriched dairy products: a review. Indian J Dairy Sci 68(1):01–05 Chiveu JC, Mueller M, Krutovsky KV, Kehlenbeck K, Pawelzik E, Naumann M (2019) Genetic diversity of common guava in Kenya: an underutilized naturalized fruit species. Fruits 74(5): 236–248 da Silva Lima R, Ferreira SRS, Vitali L, Block JM (2019) May the superfruit red guava and its processing waste be a potential ingredient in functional foods? Food Res Int 115:451–459 da Silva CCA, Vieira HD, Viana AP, Santos EA, Maitan MQ (2021) Digital phenotyping in inbred guava lines: seed characterization. Funct Plant Breed J 3(2):33–50 Denny C, Melo PS, Franchin M, Massarioli AP, Bergamaschi KB, de Alencar SM, Rosalen PL (2013) Guava pomace: a new source of anti-inflammatory and analgesic bioactives. BMC Complement Altern Med 13(1):1–7 Dildar N, Ali SN, Sohail T, Lateef M, Khan ST, Bukhari SF, Fazil P (2022) Biosynthesis, characterization, radical scavenging and antimicrobial properties of Psidium guajava Linn coated silver and iron oxide nanoparticles. Egypt J Chem 65(2):145–151 Dinesh MR, Vasugi C (2010) Guava improvement in India and future needs. J Hortic Sci 5(2):94–108 Dinesh M, Bharathi K, Vasugi C, Veena GL, Ravishankar KV, Nischita P (2017) Inheritance studies and validation of hybridity in guava (Psidium guajava). Indian J Agric Sci 87:42–45 Dos Santos RC, Ombredane AS, Souza JMT, Vasconcelos AG, Plácido A et al (2018) Lycopenerich extract from red guava (Psidium guajava L.) displays cytotoxic effect against human breast adenocarcinoma cell line MCF-7 via an apoptotic-like pathway. Food Res Int 105:184–196 Elabd M (2018) Effect of antimicrobial edible coatings on quality and shelf life of minimal processed guava (Psidium guajava). Alex J Food Sci Technol 15(1):65–76 Emanuel N, Sao K, Kaushik A (2018) Bioactive compounds, antioxidant properties, and metal content studies of guava fruit by-products for value added processing. Braz J Anal Chem 5(21):8–18 Etemadipoor R, Dastjerdi AM, Ramezanian A, Ehteshami S (2020) Ameliorative effect of gum arabic, oleic acid and/or cinnamon essential oil on chilling injury and quality loss of guava fruit. Sci Hortic 266:109255 Feng C, Feng C, Lin X, Liu S, Li Y, Kang M (2021) A chromosome-level genome assembly provides insights into ascorbic acid accumulation and fruit softening in guava (Psidium guajava). Plant Biotechnol J 19(4):717–730 Grossi LL, Fernandes M, Silva MA, de Oliveira Bernardes C, Tuler AC et al (2021) DArTseqderived SNPs for the genus Psidium reveal the high diversity of native species. Tree Genet Genomes 17(2):1–13 Guintu FZ, Chua AH (2013) Effectivity of guava leaves (Psidium guajava) as mouthwash for patients with aphthous ulcers. Philip J Otolaryngol Head Neck Surg 28(2):8–13 Gupta N, Kour A (2019) Genetic parameters, character association and path analysis for fruit yield and its component characters in guava (Psidium guajava L.). Electron J Plant Breed 10(1):256–263 Gurmachhan CM, Tandukar U, Shrestha N, Bahadur P (2020) Antimicrobial and phytochemical studies of methanolic bark extract of Psidium guajava L. and Punica granatum L. J Plant Resour 18(1):211 Hoyos CG, Guerra AS, Pérez SA, Velásquez-Cock J, Villegas M, Gañán P, Gallego RZ (2022) An edible oil enriched with lycopene from pink guava (Psidium guajava L.) using different mechanical treatments. Molecules 27(3):1038 Iha OK, Martins GB, Ehlert E, Montenegro MA, Sucupira RR, Suarez PA (2018) Extraction and characterization of passion fruit and guava oils from industrial residual seeds and their application as biofuels. J Braz Chem Soc 29:2089–2095

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Date Palm: Genomic Designing for Improved Nutritional Quality Joseph Kadanthottu Sebastian, Praveen Nagella, Epsita Mukherjee, Vijayalaxmi S. Dandin, Poornananda M. Naik, S. Mohan Jain, Jameel M. Al-Khayri, and Dennis V. Johnson

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Chemical Composition and Biochemical Pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Chemical Type, Structure, and Biochemical Pathways of Production . . . . . . . . . . . . . . 2.3 Medicinal/Physiological Properties and Functions in Relation to Human Health . . . 2.4 Methods of Biofortification: Agronomic and Postharvest Techniques . . . . . . . . . . . . . . 2.5 Requirement of Genetic Biofortification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Breeding Using Molecular Markers for Genetic Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Sex Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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J. K. Sebastian · P. Nagella Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, India e-mail: [email protected]; [email protected] E. Mukherjee Amity Institute of Biotechnology, Amity University, Noida, India V. S. Dandin Department of Biology, JSS College, Dharwad, India P. M. Naik Department of Botany, Karnatak University, Dharwad, Karnataka, India S. M. Jain Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland e-mail: mohan.jain@helsinki.fi J. M. Al-Khayri (*) Department of Agricultural Biotechnology, College of Agriculture and Food Sciences, King Faisal University, Al-Ahsa, Saudi Arabia e-mail: [email protected] D. V. Johnson Agriculture Consultant, Middlebrook Ave, Cincinnati, OH, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_43

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3.4 Computational Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Genetic Manipulation of Date Palm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Recent Concepts and Strategies Developed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Gene Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Nanotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Bioinformatics of Date Palm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Genome Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Gene Annotation and Promoter Motifs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Gene Mapping for Trait-Linked Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 MicroRNA Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Image Analysis and Molecular Structure Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Conclusion and Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Date palm (Phoenix dactylifera L.) is one of the oldest fruit trees known where a significant amount of breeding has been carried out to improve various agronomic and nutritional characteristics. Numerous studies have been done to improve the nutritional composition and quality of the fruit due to its significant biological properties. Various strategies have been formulated for improving the agronomic characters through biofortification as well as preserving through postharvesting techniques. Modern breeding practices using molecular markers have significantly helped to identify the phenotypic, as well as genotypic, diversity for the selection of superior date palm cultivars, advanced agronomic characters like nutritional quality, disease resistance, and yield. Availability of the whole genome sequence, organellar sequence, and genetic map of date palm has helped breeders in modification and improvement of the characteristics. With the availability of bioinformatic tools and gene editing knowledge, the nutritional composition of date palm can be effectively manipulated to develop better crops along with good agronomic characters and resistance to diseases. The authors have compiled the nutritional composition of date palm fruits and detail the strategies to edit the genome and improve nutritional quality. Keywords

Date palm · Nutritional composition · Molecular markers · Whole genome · Bioinformatics · Genetic map

1

Introduction

Date palm (Phoenix dactylifera L.) trees are one of the cultivated plants for centuries and its fruits served as a staple human food since time immemorial. In the world, date palm cultivation varies from region to region. There are in total more than 2000 cultivars of date growing around the world some of which are available elite varieties with good fruit qualities (Ahmad Mohd Zain et al. 2022).

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Date fruits are consumed in both their fresh and dry states. Date palm fruit production volume in the world has surpassed 9.45 million mt (https://www. statista.com/statistics/960213/date-palm-market-value-worldwide/). Dried fruits of date can be stored for a long duration at ambient climatic conditions at exceptionally low cost. Date fruits have a worldwide market; primary exporters are Iran, Egypt, Saudi Arabia, Iraq, and Algeria. World-class date fruit exporters need to take some important steps with respect to good physical and chemical properties, date types, quality and size of package, main requirements of the importing countries, and transport mode (Al-Khayri et al. 2018). As a part of traditional nutritional therapy and religious practice, date fruits have been consumed all over the world for thousands of years by millions of people. Dates are rich in carbohydrates which give instant energy to the human body. Dates are composed of vital minerals such as Fe, Mg, Ca, P, Zn, Se, K, and Mn which are important to improve their nutritional values (Aljaloud et al. 2020). Fruits contain various vitamins such as β-carotene, thiamine, ascorbic acid, riboflavin, and folic acid niacin (El Hadrami et al. 2011; Aljaloud et al. 2020). Date fruits also supply essential amino acids like histidine, valine, aspartic acid, proline, arginine, serine, methionine, threonine, lysine and alanine, glycine, leucine, tyrosine, phenylalanine, and isoleucine (Assirey 2015). Bioactive compounds are the important ingredients of date fruits including caffeic, gallic, syringic, protocatechuic, vanillic, p-coumaric, and o-coumaric acids, quercetin, kaempferol, ferulic acid, and luteolin (Vayalil 2012; Ahmad Mohd Zain et al. 2022). The superfluity of nutrition composition of date fruits makes them highly medicinal and therapeutically important crop plants. Conventional breeding and biotechnological tools were used together to improve the quality of the date fruits, for quick growth, to develop resistance against a variety of stresses and diseases. Height reduction is one of the important objectives in the date palm breeding. In Kuwait, scientists have developed a seedless fruit by crossing tall female cvs. and a dwarf palm (Phoenix pusilla), combining both conventional breeding and tissue culture techniques (Sudhersan et al. 2010). Various chronic diseases of date palm reduce date fruit production. One such deadliest disease is bayoud, caused by Fusarium oxysporum f. sp. albedinis, which causes great losses in Morocco and Algeria (Sedra and Lazrek 2011). To control the disease, various control measures were applied including chemical and biological applications, but among them all, developing resistant varieties is the most promising way to fight against the bayoud disease. Date palm cv. Taqerbucht from the oases of Salah and Tidikelt, Algeria, is found to be the best resistant cultivar against bayoud (Bouguedoura et al. 2015). In Tunisia, a new disease named brittle leaf disease has destroyed around 40,000 date trees in a short time span due to leaf wilting; the cause of the disease is still unknown (Triki et al. 2003). The date palm crop has a breeding limitation due to its growing environmental conditions where the plant must survive extreme salt and drought stress. Another problem is sex determination; until the onset of fruiting, it is not possible to identify the sex of the plant which matures at 5–7 years of age. Farmers are using traditional and rudimentary agricultural techniques from past generations. Water scarcity, a primitive level of farm and crop

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management, applying traditional methods of irrigation, limited use of advanced breeding tools, lack of skilled labor, and a low level of mechanization are some constraints to date palm breeding (Al-Khayri et al. 2015).

2

Chemical Composition and Biochemical Pathways

2.1

Chemical Composition

The plant species of the family Arecaceae, Phoenix dactylifera, has been a staple food in the Indus valley region and Middle East since before than sixth millennium BCE. Extensive research has been conducted on its nutritional composition and related molecular biochemistry. The overall chemical composition of date palms suggests that it consists of a very large number of nutrients and associated molecules. Due to this long list of nutritional chemicals, the benefits of date palm consumption are many. Starting from its activity as an energy booster, it is also credited with elevating the iron content in the body. It helps in digestion and has various pharmacological activities. Due to their appropriate balance in composition, they have also been regarded as being sufficient for consumption during fasting. All these activities are credited with the presence of innumerable chemicals in the plant. The overall list of contents in various species of date palms is comprehensively reviewed in the following section. Almost every organ of the plant is rich in a variety of nutritional compositions. The stem of date palm consists of important nutritional compounds such as stilbene (Fernández et al. 1983a). Along with this, the same part of the plant also contains important steroid, polysterol, and stigmastane molecules (Fernández et al. 1983b). In addition, the stems also possess sterols such as ergosterol along with aromatic carboxylic acids like benzoic acid and its derivative like 3,5-dihydroxy-4-methoxy benzoic acid (Fernández et al. 1983a). Triterpenoids have already been tested and found to be very crucial anti-inflammatory, anti-pyretic, and hepatoprotective agents in medicine. For conditions associated with weight loss and reduction of cholesterol levels, it is also highly necessary to reduce the risk of heart attacks which are aided by the presence of plant sterols like campesterol. The seeds of date palm plants also consist of a variety of important phytochemicals that boost the immunological capabilities of humans. The long list starts with the presence of amino acids like alanine in seeds which help in metabolic activities in the human body (Hussein and El Zeid 1975). It relates to the muscle and improvement of physical functioning in humans. Notably, the concentration of amino acids is higher in the unripe stages of the seeds as compared to the ripe ones, as arginine, glutamic acid, aspartic acid, leucine, lysine, and serine were the highest in unripe stages, while proline and glycine were the highest in ripe stages (Auda et al. 1976). The seeds of the date palm are home to mostly several SFAs (Jindal and Mukherjee 1970; Mossa et al. 1986) (Table 1, Fig. 2). Pivotal agents to nutrition include the presence of saccharides obtained from plants as they help magnify nutrition levels, prevent blood clotting, and are one of the major products consumed as staple food in

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Table 1 Chemical composition and health benefits of date palm Plant Part Stem

Chemical Cis-3,5,30 ,50 -tetrahydroxy4-methoxystilbene

Specification Stilbene (olefin)

Health benefits Antioxidant benefits

Trans3,5,30 ,50 -tetrahydroxy-4methoxystilbene Trans3,5,40 -trihydroxystilbene 5α-Stigmast-22-en-3,6dione 5α-Campestan-3,6-dione

Stilbene (olefin)

Anticancer therapy

Stilbene (olefin)

Phytoalexin Anticancer therapy Anti-inflammatory

Stigmasta-4-ene-3-one

Phytosterol

Steroid Steroid

Stigmasta-4,22-diene-3-one Stigmastane Stigmasta-4,22-diene-3,6dione Lupeol

Stigmastane Pentacyclic triterpenoid

Lupeol acetate

Pentacyclic triterpenoid

Hydroxystigmast-4-en-3one Hydroxystigmasta-4,22dien-3-one

Stigmastane (oligopeptide) Stigmastane (oligopeptide)

6β-Hydroxy-campest-4ene-3-one

Stigmastane (oligopeptide)

Campest-4-en-3-one

Ergosterol

Campest-4-en-3,6-dione

Ergosterol

Campest-4-en-3-one

Ergosterol

Benzoic acid

Aromatic carboxylic acid

Phytosterol, lowers cholesterol in the gut Hypoglycemic metabolite Potential biomarker Antiplatelet aggregation Anti-inflammatory drug, acne treatment Anti-arthritic, leishmanicidal, anti-inflammatory, antifungal activity Reduction of blood cholesterol Antiparasitic, radical scavenging capacity Cytotoxicity against lung cancer cell lines Treatment of cardiovascular diseases Promotes energy consumption, reduces visceral fat Lowers LDL and cholesterol Antimicrobial food preservative

Reference Fayadh and Al-Showiman 1990 Fayadh and Al-Showiman 1990 Fernández et al. 1983 Fernández et al. 1983 Fernández et al. 1983 Toghueo 2019 Liolios et al. 2009 Fernández et al. 1983 Alam et al. 2009 El-Far et al. 2019

Fernández et al. 1983 Fernández et al. 1983 Fernández et al. 1983 Fernández et al. 1983 Suzuki et al. 2007 Suzuki et al. 2007 Das et al. 2017 (continued)

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Table 1 (continued) Plant Part Seeds

Chemical Alanine

Specification Amino acid

Arginine

Amino acid

Glutamic acid

Amino acid

Aspartic acid

Amino acid

Leucine

Amino acid

Lysine

Amino acid

Serine

Amino acid

Proline

Amino acid

Glycine

Amino acid

Arachidic acid

Saturated fatty acid

Tricosanoic acid

Saturated fatty acid

Stearic acid

Saturated fatty acid

Palmitoleic acid

Saturated fatty acid

Palmitic acid

Saturated fatty acid

Health benefits Hypoglycemia, urea cycle disorder treatment Chest pain, pregnancy complications Excitatory neurotransmitter in central nervous system Fatigue, athletic performance, muscle strength Energy for skeletal muscle Proper growth and carnitine production Enhancement of memory and thinking skills Collagen producer

A component of creatine and protection against muscle loss Chemical messenger released by muscles, detergent production An internal standard, hair growth stimulant Emulsifier, emollient, cosmetic product preparation, rubber processing Anti-inflammatory, improves insulin sensitivity Industrial mold release agent production, soap, detergent production

Reference El-Sohaimy and Hafez 2010 El-Sohaimy and Hafez 2010 Eeuwens 1978

Assirey 2015

Shaba et al. 2015 Shaba et al. 2015 Abdalla et al. 2020 Dhawi and Al-Khayri 2008 Dhawi and Al-Khayri 2008 Abdalla et al. 2020

Al-Shahib and Marshall 2003a Nehdi et al. 2018

Al-Shahib and Marshall 2003b Saafi et al. 2008

(continued)

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Table 1 (continued) Plant Part

Chemical Oleic acid

Specification Unsaturated fatty acid

Myristic acid

Saturated fatty acid

Margaric acid

Saturated fatty acid

Linolenic acid

Saturated fatty acid

Behenic acid

Saturated fatty acid

Lauric acid

Saturated fatty acid

Heneicosanoic acid

Saturated fatty acid

Linoleic acid

Saturated fatty acid

Rhamnose

Saccharide

Fructose

Saccharide

D-galactose

Saccharide

Health benefits Inflammation reduction, cholesterol reduction Flavor ingredient, soap or detergent production, surfactant, cleansing agent Anti-tumor, glutamate and lipid metabolite in vivo Cholesterol and high blood pressure reduction, atherosclerosis treatment Lubricating oils, anti-foaming agents in detergents Treatment of viral infections, soap and detergent production Foams, paints, viscous material production in industries Body-building, fitness, weight loss, cosmetics, and personal care products production Antiaging, antiwrinkle, natural furanose production Manufacturing low-calorie products, flavored water, taste enhancer Energy source, treatment of hepatitis C, hepatic cancer, precursor to glucose production

Reference Al-Shahib and Marshall 2003b Shehzad et al. 2021

Abdalla et al. 2020 Attia et al. 2021

Soliman et al. 2015 Nehdi et al. 2018

Di Cagno et al. 2017

Al Juhaimi et al. 2020

Khallouki et al. 2018 Nadeem et al. 2019

Ataei et al. 2020

(continued)

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Table 1 (continued) Plant Part

Chemical Glucose

Specification Saccharide

Lactose

Saccharide

D-mannose

Saccharide

Xylose

Saccharide

Zinc

Essential mineral

Iron

Essential mineral

Manganese

Essential mineral

Aluminum

Essential mineral

Potassium

Essential mineral

Health benefits Treatment of hypoglycemia, source of energy for the brain, overall health maintenance Ethanol production, pharmaceutical industry, diluent, bulking agent Treatment of carbohydratedeficient glycoprotein syndrome, alternative to antibiotics Food sweetener, flavoring agent, diagnostic agent for malabsorption Metabolism functioning, developing immune system, improved sense of taste and smell, wound healing Essential for blood production, healthy skin, bones, hair, immune system booster Metabolism of various amino acids, carbohydrate, bone formation, anti-inflammatory, blood clotting Food conservation, increase effects of vaccines and medicines in the body Increased uptake of nutrients into the body, contraction of muscles, nerve functioning

Reference Siddiqi et al. 2020

El-Kholy et al. 2019

Alyileili et al. 2020

Ataei et al. 2020

Adenekan et al. 2018

Alem et al. 2017

Kuhiyop et al. 2020

Badarusham et al. 2019

Alem et al. 2017

(continued)

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Table 1 (continued) Plant Part

Pollen

Fruits

Chemical Phosphorus

Specification Essential mineral

β-Sitosterol

Phytosterol

Rutin

Flavonoid

Quercetin

Flavonoid

β-Amyrin

Pentacyclic triterpenoid

Estrone

Steroid

Estrogen

Steroid

Alanine

Amino acid

Valine

Amino acid

Tyrosine

Amino acid

Tryptophan

Amino acid

Health benefits Aid in ATP synthesis, production of proteins for growth, helps build bones Benign prostatic hyperplasia treatment, cholesterol reduction Antioxidant, allergy treatment, vitamin C effect enhancer, arthritis treatment Heart disease risk reduction, cancer treatment, allergy treatment, infection reduction Potential antinociceptive, gastroprotectant, hepatoprotectant, antioxidant, antiinflammatory Perimenopausal and postmenopausal symptom treatment Regulation of female reproductive system, bone development, treatment of menopausal symptoms Hypoglycemia, urea cycle disorder treatment Energy enhancer, muscle growth, tissue repair Improvement in memory, attention, and focus Melatonin, serotonin, and niacin producer

Reference Bijami et al. 2020

Al-Samarai et al. 2018

El-Kholy et al. 2019

Otify et al. 2019

Hamed et al. 2017

El-Sisy et al. 2018 Otify et al. 2021

Mohammadi et al. 2018 Kadum et al. 2019 Abdul-Hamid et al. 2019 Yaish et al. 2017 (continued)

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Table 1 (continued) Plant Part

Chemical Threonine

Specification Amino acid

Serine

Amino acid

Proline

Amino acid

Phenylalanine

Amino acid

Methionine

Amino acid

Lysine

Amino acid

Leucine

Amino acid

Isoleucine

Amino acid

Histidine

Amino acid

Glycine

Amino acid

Glutamic acid

Amino acid

Health benefits Treatment of nervous system disorders Enhancement of memory and thinking skills Collagen producer

Treatment of Parkinson’s disease, depression, and other nervous disorders Treatment of liver disorders, helps in cell cycle, wound healer Improvement in calcium uptake and reduction in anxiety and stress, treatment of cold sores Provide ATP during exercise, tissue regeneration, protein synthesis, and metabolism Blood sugar regulation, hemoglobin synthesis, energy level maintenance Treatment of allergic diseases, kidney failure, ulcers, rheumatoid arthritis Treatment of benign prostatic hyperplasia, stroke, schizophrenia, protection of kidneys Protein production in the body, transforms into glutamate

Reference Assirey 2015

Assirey 2015

Al-Khayri and Al-Bahrany 2004 Assirey 2015

Assirey 2015

Assirey 2015

Assirey 2015

Assirey 2015

Assirey 2015

Assirey 2015

Al-Shahib and Marshall 2003b (continued)

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Table 1 (continued) Plant Part

Chemical Glutamine

Specification Amino acid

Asparagine

Amino acid

Aspartic acid

Amino acid

Arginine

Amino acid

Fructose

Saccharide

Sucrose

Saccharide

Glucose

Saccharide

Calcium

Essential mineral

Zinc

Essential mineral

Potassium

Essential mineral

Phosphorus

Essential mineral

Health benefits Helps gut function, immune system, provides ATP to the body Treatment of imbalanced foods, production of proteins, functioning of nervous systems Boosts up low testosterone levels, protein biosynthesis Chest pain, pregnancy complications Manufacturing low-calorie products, flavored water, taste enhancer Syrup processing, sweet drink softener, detergent, emulsifier carrier Treatment of hypoglycemia, source of energy for the brain, overall health maintenance Movement of muscles, transfer of essential messages across neurons Metabolism functioning, developing immune system, improved sense of taste and smell, wound healing Increased uptake of nutrients into the body, contraction of muscles, nerve functioning Aid in ATP synthesis, production of proteins for growth, helps build bones

Reference Zouine and El Hadrami 2007

Abbas and Saad 2009

Assirey 2015

Sghaier et al. 2009 Assirey 2015

Nwanekezi et al. 2015

Assirey 2015

Al-Shahib and Marshall 2003b Al-Shahib and Marshall 2003b

Uddin and Nuri 2021

Awofadeju et al. 2021

(continued)

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Table 1 (continued) Plant Part

Chemical Manganese

Magnesium

Iron

Ascorbic acid

Iso-chlorogenic acid

γ-Aminobutyric acid (GABA)

Vitamin A

Thiamine

Riboflavin

Nicotinic acid

Specification Essential mineral

Health benefits Metabolism of various amino acids, carbohydrate, bone formation, anti-inflammatory, blood clotting Essential Energy promotion, mineral maintenance of normal nerve functioning, immune system Essential Essential for blood mineral production and healthy skin, bones, and hair, immune system booster Vitamin C Collagen formation, additive wound healer, cartilage, teeth, bones, repair of body tissues Phenolic acid Lowers blood pressure, blood sugar, and weight Neurotransmitter Brain neurotransmitter, anxiety reducer, pain reliever Vitamin Normal vision, reproductive ability, helps organs work well Vitamin additive Pyruvate metabolism, conversion of carbohydrates to energy, nerve signal transmission Vitamin additive Fat and protein metabolism, conversion of carbohydrates to energy Vitamin additive Triglyceride and cholesterol improvement

Reference Ibraheem 2021

Uddin and Nuri 2021

Lamia and Mukti 2021

Rajan et al. 2021

El-Far et al. 2016 LópezCórdoba 2021

Hinkaew et al. 2021

Shehzad et al. 2021

Awofadeju et al. 2021

Tawfek et al. 2021

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our diets (Noorbakhsh and Khorasgani 2022). As far as seeds of date palm are concerned, they contain a large number of saccharides, essential for human life such as rhamnose, xylose, D-mannose, lactose, glucose, D-galactose, and most importantly, the sweetest sugar, fructose (Jindal and Mukherjee 1969; Mahran et al. 1976; Al-Whaibi et al. 1985). Zinc, phosphorus, potassium, aluminum, manganese, and iron are a few of the beneficial elements found along with other chemicals in the seeds (Sawaya et al. 1982; El-Shurafa et al. 1982; Hamad et al. 1983). The pollen of date palms also has been found to contain a few important biomolecules like β-sitosterol, which resembles cholesterol molecules and helps to reduce hypercholesterolemia (Mahran et al. 1976; Kikuchi and Miki 1978; Fernández et al. 1983b). Another fascinating glycoside, formed by the combination of flavonol quercetin and disaccharide rutinose, rutin is found in the pollen of the plant (Mahran et al. 1976). It is chiefly used in the production of medicines which has a similar function as that of sitosterol, in lowering cholesterol levels. In addition, it is also used to reduce arthritis pain and prevent blood clotting. The flavonoid quercetin is also present in the pollen along with female sexual hormones like estrogen and estrone (Hassan and Abou El Wafa 1947; Bennett et al. 1966; Mahran et al. 1976; Mossa et al. 1986). Estrone in the body is converted to estrogen when needed; thus, the former serves as a repository for hormone estrogen in females. A triterpenoid, i.e., β-amyrin, is also found in pollen that is responsible for the improvement of glucose tolerance owing to its anti-inflammatory and antioxidant effects (Mahran et al. 1976). The most important and maximum number of phytochemicals exists in the edible part – “fruit.” Nearly all amino acids like alanine, arginine, etc. and saccharides like fructose, glucose, and sucrose (Auda et al. 1973; Hussein and El Zeid 1975; Auda et al. 1976; Sawaya et al. 1983b) are present. Elements like Ca, Fe, Mg, Mn, P, K, and Zn with vitamin additives like ascorbic acid, nicotinic acid, riboflavin, thiamine, and vitamin A are also found (El-Shurafa et al. 1982; Sawaya et al. 1983; Mossa et al. 1986). Natural products with pharmaceutical potentials like neurotransmitter γ-aminobutyric acid (GABA) and iso-chlorogenic acid are added compositions (Cadi et al. 2021; Hattori et al. 2021) (Table 1).

2.2

Chemical Type, Structure, and Biochemical Pathways of Production

Date palms have a plethora of important nutrients and chemicals in their composition ranging from vitamins to amino acids and fatty acids. The extensive details about all the parts of the date palm containing the respective nutrients have already been explained. Specifically, when the leaf fiber extracts of date palm were studied, constituents obtained in decreasing order of their percentages were α-cellulose (58%) to pectin (2.3%) (Pandey and Ghosh 1995). In fact, a good replacement for synthetic fibers exists through the microcrystalline cellulose extracted from the fruit fibers of the date palm. Lignin and hemicellulose were also isolated from the date palm fiber, indicating their richness in nutraceutical properties (Hachaichi et al. 2021).

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The list of important therapeutic and immune condition-boosting biomolecules present in the fruits of the date palm is long, as already mentioned. The range commences at amino acids like alanine and terminates at nicotinic acid and other vitamin additives. Amino acids are structurally identical, except for the -R group which determines the nature of the molecule (Figs. 1 and 2). They are zwitter ionic Fig. 1 General structure of amino acids

Fig. 2 Structures of a few amino acids found in the fruits of date palm. (Source: PubChem) [a-Alanine, b- Valine, c- Tyrosine, d- Tryptophan, e- Threonine, f- Serine, g- Proline, h- Phenylalanine, i- Methionine, j- Lysine, k- Leucine, l- Isoleucine, m- Histidine, n- Glycine, o- Glutamic acid, p- Glutamine, q- Asparagine, r- Aspartic acid, s- Arginine]

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molecules that exhibit the acidic and basic character simultaneously at a given set of environmental conditions. Other parts of the plant are also rich in several important pharmaceutical biomolecules and guarantee a healthy immune system when consumed on a regular basis. One of the major reasons why date palms are included in our diet during a very physically demanding fast is because of the availability of enormous amounts of carbohydrates and fats, which is also the reason why date palms exist under “Ojas” or energy-giving food in Ayurveda (Haas 2015). Moreover, high amounts of soluble fibers (Maou et al. 2021) and the alkaline nature of fresh date palms (Alghamdi et al. 2019) further increase the beneficial properties of its consumption because it increases colon performance and compensates for the increased stomach acidity, respectively, after fasting. The “sattvic” nature of soft and succulent fresh dates as described in Ayurveda aids in cooling down the heated body after a long fast. Other important biomolecules present in date palms are stilbenes (Fig. 3a), steroids (Fig. 3b), phytosterols (Fig. 3c), minerals like calcium (Fig. 3d), saccharides (Fig. 3e), saturated (Fig. 3f) and unsaturated fatty acids (Fig. 3g), vitamins (Fig. 3h), triterpenoids (Fig. 3i), flavonoids (Fig. 3j), and carboxylic acids (Fig. 3k), as listed in Table 1.

Fig. 3 Structure of a molecule from each group of biomolecules present in different parts of date palm. (Source: PubChem)

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The biochemical pathways to produce biomolecules generally follow a distinct cascade of reactions in the organism. In the case of date palms, there are a wide range of biomolecules present in almost all organs as mentioned. When focusing on stems, olefins are present in the majority, which are produced by a variety of reactions like hydrogenation, dehydration, hydro-deoxygenation, or steam cracking. It has been found that almost all the important olefins are ultimately produced from the intermediates obtained from the basic metabolic cycles in respiratory pathways such as glycolysis or citric acid cycle. An example of such a pathway has been found starting from glucose to olefins like stilbene and various other secondary metabolites in plants (Fig. 4). Very interestingly, it has been observed that there are different changes in the amount and number of metabolites in the context of amino acid biosynthesis in date palms when subjected to UV-B light irradiation (Agwa 2021). There is a cascade of reactions that give rise to multiple metabolites in between two steps that can be significant to humankind, both in terms of economy and nutrition. The saccharide biosynthesis in date palms occurs through another series of reactions and biochemical pathways, as in any other fruit species as depicted by researchers already. Not only date palms have the biochemical pathways to produce metabolites, but they have been studied in other species, such as in maize. Sharma et al. (2012)

Fig. 4 Biosynthesis of various olefins in plants by metabolic pathways. (Modified from Bacigalupa et al. 2018)

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Fig. 5 Flavonoids’ biosynthetic pathway in maize (Sharma et al. 2012)

reported on flavonoid biosynthesis in maize (Fig. 5). Identification of crucial genes responsible for the authentic metabolism of raw products is important. In date palms, extensive research is ongoing on its biochemical pathways of metabolite production.

2.3

Medicinal/Physiological Properties and Functions in Relation to Human Health

Date palms are also consumed by humans because of their restorative and curative properties. The medicinal properties of the plant range from the simplest of

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Fig. 6 Protective activities of Phoenix dactylifera against various ailments

symptoms like cold and fever to life-threatening diseases such as liver cancer and bronchial catarrh (Fig. 6). The credit for being a remedy to this long list of ailments goes to the enormous number of phytochemicals present in the plant. The main biomolecules present in the plant are vitamins, minerals, flavonoids, carbohydrates, steroids, alkaloids, and many others (Ahmad Mohd Zain et al. 2022). Some of the important medicinal properties of the date palm are listed in Table 1.

2.3.1 Anticancer Activity One of the leading causes of death today is cancer and an extensive number of research is being done to prevent and treat this disease. The plant under study contains a good number of anticancerous agents and studying the effects of those molecules in rat models can increase its use for therapeutic purposes. For the prevention of hepatocellular carcinoma, restoration of antioxidant enzymes in the liver to accurate levels is very important, which can be performed using biomolecules like quercetin, luteolin, or glucans already existent in date palm (Lamia and

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Mukti 2021). For mammary cancer in humans, the effect of various concentrations of water extracts of Jordanian dates was assessed on MCF-7 breast cancer cell lines. On analyzing the effect of anticancerous agents using the MTT assay and calculating the percentage of inhibition, it was found that 100 mg/ml was the most effective in exhibiting the maximum inhibition (Al-Sayyed et al. 2021). Acetone extracts of date fruit (Ajwa variety) demonstrated cytotoxic effect on oral squamous cell carcinoma cell lines by inhibiting their growth and proliferation and inducing cell death by apoptosis (Shahbaz et al. 2022). Apart from these, the consumption of dates also increases the health condition of colon cells by colon cancer cell growth inhibition and enhancing beneficial bacterial growth in the colon (Eid et al. 2014). Various extracts of ethanol, acetic acid, and acetone using date palm have also reduced the proliferation of pancreatic stellate cells (PSC) in vitro. In addition, it also reversed the fibrotic phenotype of PSCs, thereby reducing fibrosis (Al Alawi et al. 2020). Thus, on further research, there is a high capacity for date palm to serve as a potential anticancerous agent, and isolation of the novel phytochemicals responsible for the same can be done on a commercialized scale for treatment purposes.

2.3.2 Anti-diarrheal Activity Diarrhea can be acute or chronic depending on the immune system of the individual. When castor oil was used to induce diarrhea in Wistar rats, it was observed that extracts of date palm used in the concentration of 1000 and 1500 mg/kg of body weight were successful in reducing the intensity of diarrhea (Agbon et al. 2013). The results were almost the same in another experiment when loperamide was administered as a control agent (Megbo et al. 2017). Comparatively, date palm aqueous extracts possessed completely nontoxic anti-diarrheal activity when used on male Wistar rats. Phytochemical screening and spectrophotometric methods revealed the high crude ash, carbohydrate contents with saponins, tannins, and flavonoids along with a low anti-nutrient concentration in date palm extracts. 2.3.3 Anti-ulcer Activity When gastric ulcer was introduced in rats using ethanol, different extracts of both dialyzed and undialyzed date fruits were administered to check the effect of dates on gastric ulcers in humans, at 4 ml/kg for 14 days. It was observed that both aqueous and ethanolic extracts could work successfully toward the reduction of severe gastric ulcers in rats (Al-Qarawi et al. 2005). The presence of the ethanolic extract of undialyzed date palm fruit could reduce the level of gastric mucin, histamine, and gastrin in the rats. The effect of date palms on peptic ulcer conditions was further affirmed when the report of Gangwar et al. (2014) suggested that chloroform extract of its leaves contained gastroprotective activity. This was supported by the inhibition of ulcer index, mean ulcer score, and reduction in gastric content when the pH increased and acidity levels, both free and total, decreased, along with doses. Thus, it has already been proven that painful sores can easily be removed by the consumption of date fruits, which become hard to remove even sometimes using synthetic molecules.

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2.3.4 Anti-hepatotoxic Activity As of 2021, diabetes ranks as one of the major reasons of the death of humans in the world due to a high cholesterol diet and eventually brings with it associated disorders. Liver health deterioration is a concern for people, irrespective of age, which can further be responsible for chronic illnesses, and thus, treatments for the prevention of this disease are the need of the hour. It has been observed that when date palm’s hydroalcoholic extracts were administered to rats having hepatotoxic effects due to diabetes, comparatively healthier sinusoids and hepatocytes were found (Zheng et al. 2021). On the other hand, when liver diseases were untreated, severe histopathological conditions such as dilated portal veins, fatty degeneration, and necrotic nuclei were seen. Since this observation was a remarkable advancement as conducted in 32 adult rats, further clinical research is solicited for the execution of the hepatoprotective activity of date palms on humans. In addition, Onyilo et al. (2021) reported the hepatoprotective potential of date palm’s aqueous extract when fat-induced damaged liver cells in adult Wistar rats were found to be reversed and Kupffer cells activated with changes in the level of hepatic enzymes as well as hepatocyte configuration. 2.3.5 Antioxidant Activity Antioxidants are important chemicals needed to protect the body against free radicals produced by catabolism and capable of causing cancer (Moslemi et al. 2022). They are necessary substances in the body and have been found in great abundance in date palms (Zihad et al. 2021). High quantities of phenolic, tannin, and flavonoid contents were recorded in three varieties of date palms, namely, Ajwah, Sakkari, and Safawy, using UPLC-QTOF-MS assays. Radical scavenging activity, both DPPH and hydroxyl, was found in all of them along with a total antioxidant capacity of IC50 87–192 μg/ml. Results were obtained, almost along the same lines when antioxidant and total phenolic levels were compared among methanolic extracts of four different date palm varieties (Bensaci et al. 2021). Folin-Ciocalteu and DPPH test along with superoxide anion and reducing power test exhibited the highest antioxidant levels of 0.006 mg/ml in the Chtaya variety using the cyclic voltammetry method. Thus, consumption of the fruit can also aid in keeping deadly diseases like cancer at bay, as proved in the literature already. 2.3.6 Anti-inflammatory Activity Out of the many visible therapeutic activities of date palms, one of the most important is its anti-inflammatory effect. In a report by Barakat et al. (2020), it has been proven that date palm seeds could exhibit anti-inflammatory effects on inflammation induced by LPS in RAW 264.7 cells. This was mainly done against the nitric oxide release and subsequent iNOS protein expression. In addition, suspensions of date palm pollen have been shown to improve immune-histochemical and histopathological conditions in rats with hyperplasia (Elberry et al. 2011). The presence of inflammation was confirmed due to the presence of chemical messengers like IL-6, IL-8, TNF-α, and IGF-1. Along with upregulation of autocrine or paracrine receptors, the date palm has been shown to modulate cytokine expression through a

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protective effect by suppressing inflammation. Cellular proliferation was accompanied by a reduction in apoptosis in the ventral prostate of rats with hyperplasia on the administration of date palm.

2.3.7 Antimicrobial Activity The term “viral infection” needs no new introduction in the present-day scenario of 2021 where the entire world fought and is fighting against the deadly coronavirus pandemic. At this juncture, it is highly essential that the availability of the number of antiviral commodities is increased as much as possible. For the same, the leaf extract of date palm had been tested in vitro using an MTT assay on the embryonic fibroblast cells of NIH/3 T3 mouse. Takdehghan et al. (2021) reported a significant decrease in CRP levels as well as elevation in partial pressure of oxygen levels in those patients administered with date palm leaves five times daily along with the recommended dosage of medicines as compared to the patients strictly on routine medication. When checked on days 7 and 14 post-administration, the inference was drawn and thus was recommended as a safe add-on along with the daily dosage of treatment. The efficiency of date palms against bacteria, both Gram-positive and Gramnegative, has also been studied when Ghosh (2021) reported that methanolic extracts of its seeds have exhibited antibacterial activities against Klebsiella pneumonia and Escherichia coli. Along with that, it has also reduced the side effect on the testosterone and muscles of rats and improved other hormonal functions. 2.3.8 Antihyperlipidemic Activity Due to the possibility of developing a heart disease, it is necessary to maintain a low blood lipid level or triglyceride. Lipoproteins are essential for providing energy in the body but only up to a certain level, because beyond that level, the severity of medical conditions can escalate to diabetes, alcoholism, kidney disease, and other chronic cases too. Date palm possesses antihyperlipidemic activity as has been reported by Innih and Lorliam (2021) in an experiment where it was determined whether date palm has hyperlipidemic properties, owing to the phytochemicals present in the plant. Against hyperlipidemia induced by margarine in rats, the differential blood count and lipid profile analysis revealed a decrease in cholesterol and LDL levels whenever date palms were used as a part of the therapeutic routine. The results were further confirmed when Silabdi et al. (2021) explained the reduction in total and LDL cholesterol along with that in triacylglycerol while the level of HDL in the blood of rats increased. These results were obtained from three different varieties of Algerian date palms, namely, Deglet Nour, Ghars, and Degle Baida. Date palms play a crucial role in keeping lipid and other lipid-related levels such as SGPT, ALT, LDH, and GOT at a normal level without any other side effects compared with synthetically derived products. 2.3.9 Anti-nephrotoxic Activity To keep one ailment at bay, the chemical medications may invite other illnesses. For severe diseases like lymphoma or leukemia, doxorubicin is a widely used drug with a high therapeutic index, linked with causing nephrotoxicity in patients as a side effect.

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Wang et al. (2019) reported the activity of date palm extract on the nephrotoxic effects caused by doxorubicin in patients. Levels of cardiac markers like LDH-1 were seen to decrease and nephrotoxicity was seen to be reversed on the administration of date palm extract. As far as nephroprotection is concerned, there was amelioration in the urine flow rate and a significant increase in the urine sodium-potassium ratio due to the activation of Na+/K+ ATPase in the presence of date palm extract. In addition, there can also be an improvement in the functioning of nephrons using its antioxidant potential on proximal tubular damage. On further investigation, the reason for the observed nephroprotective activity of date palm alluded to elevation in the level of antioxidant enzymes which possessed the capability of free radical scavenging (Al-Qarawi et al. 2008). Dates were already known to act as strong antioxidants for their mechanism of counteraction of free radicals. Hence, nephroprotection is a major function of date palms owing to their radical scavenging capacity.

2.3.10 Antimutagenic Activity The presence of any external agent or any other factor might be responsible for transformations in organisms, which can even be fatal in some cases and are phenotypically invisible. To safeguard or inhibit such a process from occurring, it is crucial that an intensive number of research is done on the naturally present antimutagenic substances. Vayalil (2002) reported the antimutagenic property of date palms on Salmonella tester strains TA-98 and TA-100. The property was tested for His+ revertant formation in the strains which exhibited 50% dose-dependent inhibition of benzo(α)pyrene-induced mutagenicity on the administration of date palms. Not only in this case but date palm’s antimutagenicity was also examined against N-nitroso-N-methylurea by the activity of chromosome aberration and other DNA fragmentation assays. On administration of date palm extract, it was seen that the DNA damage caused by the mutagen was restored back to its normal conditions (Diab and Aboul-Ela 2012). This was proven by the reduction in the chromosomal aberration and micronuclei in the bone marrow, and no further DNA fragmentation in hepatic cells was seen when date palm extracts were introduced before and after the treatment by intraperitoneal injection in mice. Furthermore, research on the medicinal properties of date palm might open doors to more innovative and therapeutic discoveries helpful to the economy and human health.

2.4

Methods of Biofortification: Agronomic and Postharvest Techniques

2.4.1 Agronomic Biofortification The procedure of application to increase the nutritional content in plants during their growth phase naturally through agronomic methods is termed biofortification. This is essential to maximize the mineral uptake by plants or nutrient availability while consuming the fruits and can be done by application of several mineral fertilizers to the plant parts or soil. To date, there have been numerous trials to improvise the mineral and nutrient values in several species of plants, but there is also huge

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potential for the same in the remaining plants (Stangoulis and Knez 2022). In date palm too, efforts were made to increase its nutritional value. However, the level of research conducted is very limited and needs more attention. With the advent of newer strategies and scientific advancements like insertional, somaclonal, and sitedirected mutations, biofortification in plants has become easy. Along with that, provisions for targeted and more accurate mutagenesis have also increased with the discovery of CRISPR-Cas gene editing and base editing systems in engineering date palm genomes (Sattar et al. 2017). There are several issues associated with breeding a plant, including both biotic and abiotic factors. Abiotic components include the issues of dry soil, inadequate mineral contents, scarcity of water, or insufficient root activity in a few cases. All of them can be improved by advanced techniques of agronomic biofortification like the usage of NPK, potassium sulfate, nitrate, silicate, iron sulfate, urea, zinc sulfate, etc. nutrients externally. Numerous studies have been conducted on the foliar spray of date palm for improvement of mineral composition in the date palm plant. Starting in 2007, the effect of urea (N 46%) has been observed when sprayed on the plant in different concentrations (0.5% and 1%) and in different stages of the plant (Khalal and Kimmri stages) (Abbas et al. 2007; Khayyat et al. 2007; Shareef 2011a, b). Positive traits of plant growth on the same included an increase in the pulp weight, nitrogen content, fruit length and diameter, dry matter, percentage of fruit ripening, and sugar content while decreasing dropping down of fruits from the plant. Similar results were obtained using 300–600 ppm zinc sulfate in terms of yield and quantity of fruits. Total soluble solids calculated were higher using 1500–2500 ppm boric acid along with the increased concentration of boron content in the fruits. Moreover, other nutrients like 1000–2000 ppm of calcium chelate were responsible for the increase in plant height, girth, and the number of new leaves (Jasim et al. 2016). An overall increase in fruit length and diameter, along with the increased percentage of sucrose and total dissolved solutes, was obtained by application of 125 and 250 mg/ L phosphorus (Fasal et al. 2014). It is essential that extra importance is laid on the status of nutrition of any crop and biofortification plays an added role in this process. A constant effort to elevate nutritional content in date palms has been initiated by several scientists across the globe, and one of the many noteworthy discoveries includes the introduction of (0.01–0.02%) sodium selenite for improvement in growth, bunch weight, and quality of fruits in the plant (El-Kareem et al. 2014). Nitrogen, phosphorus, and potassium (NPK) are mixed in various ratios to fasten plant growth and for other beneficial properties. In the cultivation of date palms too, NPK was prepared in the ratio of 20:20:20 and in 2.5% concentration which provided beneficial effects like increase in total yield; soluble solids; sugars; percentage of fruit ripening; chlorophyll content; soluble carbohydrates; potassium, phosphorus, and nitrogen content; chlorophyll a; fruit yield; and dry weight and decrease in the number of fruit drop (Shareef 2011a, b; Attaha and Al-Mubark 2014; Altememe et al. 2017; Jubeir and Ahmed 2019). Thus, usage of NPK is beneficial to a high commercial extent but the side effect of chemical pollution and chemical fertilizers always persists in this case, which may prove harmful for human consumption. It is well-known that the role of

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potassium in plants ranges from the transport of minerals, water, and carbohydrates and the production of protein, starch, and adenosine triphosphate to the improvement of drought resistance and others. In addition, various salts of potassium have been tested on the growth of date palms in various concentrations such as potassium sulfate, silicate, nitrate, and others. Potassium nitrate when used in the concentration of 1500 ppm exhibit a notable increase in the number of new leaves and clusters along with the increase in the content of ascorbic acid, abscisic acid, indole acetic acid, carbohydrates, gibberellin, and zeatin (Shareef 2019). When potassium silicate was used in concentrations of 0.01% and 0.02%, an increase in bunch weight and percentages of specific minerals in leaves, yield, and leaf area was noted (El-Kareem et al. 2014). Among pigments, there was higher chlorophyll a, carotenoid, and total chlorophyll when the same was applied. Similarly, the utility of iron compounds in the production of chlorophyll and other chloroplast maintenance activities in plants cannot be ignored. Iron sulfate itself when used in 250 ppm concentration can lead to a good increase in yield along with a decrease in the number of fruit dropping (Abbas et al. 2007). Again, when the same compound is used in 20–40 ppm, it results in an increase in weight and volume, diameter, length of fruits and flesh, carbohydrates, total soluble solids, reducing sugar, and dry weight (Abass et al. 2012). Apart from iron sulfate, Faisal et al. (2017, 2018) have reported that the usage of chelated iron compounds in date plants has led to an increase in the overall total soluble solids, reducing sugar, weight, and diameter of fruits. The list of agronomic biofortification methods continues to include the usage of 8–16 cm3/L seaweed as a biostimulant in date palm plants (Attaha and Al-Mubark 2014). It produced an increase in a long list of parameters such as soluble carbohydrates, potassium, phosphorus, as well as chlorophyll content. When the same biostimulant was used in the concentration of 4–8 ml/L, the effects observed in the fruits included elevated levels of chlorophyll, K, Mn, ascorbic acids, organic solutes, indole-3-acetic acid, zeatin, K+/Na+ ratio, and other ions as compared to that without seaweed (Taha and Abood 2018; Shareef et al. 2020). Shareef et al. (2020) also reported that 4 g/L Saccharomyces cerevisiae can bring about almost the same effects with an additional benefit of increase in plant height, new leaves, offshoot girth, and leaf area. Apart from this, the gelatinous milky white secretion produced by worker bees, also called “royal jelly,” is responsible for the production of high nutrient content like N, P, K, and Mg along with good quality fruits and increased growth (Al-Wasfy 2013). Refaai (2014) reported that using 0.5–2% wheat seed sprouts increase growth characteristics, plant pigments, total yield, nutrients, bunch weight, and carbohydrates along with improvement in characteristics of fruits – both physical and chemical. Macro and micronutrients together are essential for the plants to grow healthy and the higher the quantity of nutrients available to the plants, the better growth it exhibits. Through biofortification, the level of mineral uptake is maximized in plants and one such effort was put forward by combining many micronutrients like Fe, Zn, Cu, Mn, B, and Mo and chelating with EDTA. Here, boron and molybdenum are used in completely soluble form, under the name of “Fetrilon Combi,” and is commercially available as an agronomic biostimulant in crops (Altememe and Mahdi 2015). Using the product shows a remarkable increase

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in the invertase activity, ripening percentage, and ionic concentration of sucrose and water content in fruits. Another commercialized biostimulant available in the name of “Drin” (2–4 ml/L) helps date plants to synthesize free amino acids and readily uptake nitrogen content from the soil. Catalase activity is increased along with total chlorophyll content as this liquid organic solvent contains a high proportion of amino acids and organic nitrogen that activates the biochemical pathways in crops. Like many other biostimulants, addition of 4–8 ml/L humic acid is not only seen to increase the amount of N, P, and K but also the overall content of chlorophyll a (Altememe et al. 2017). Obtained from animal bones, 5–10 ml/L sugar chitosan is a good source of increasing K, Mn, amino acids, and dry weight of fruits in date palms (Taha and Abood 2018). Recent investigations also reveal the usage of 1.5 g/L commercialized Biocont-T in date palms shows benefits like increased bunch weight, yield, and percentage of fruits and 800 or 1600 mg/L potassium fertilizer by Alqawafel shows notable increases in fructose, glucose content, and fruit size with reduced sugar (Ressan and Al-Tememi 2019; Al-Hajaj et al. 2020). Date palm is an essential source of food in areas where there is water scarcity and thus demands a good number of postharvest techniques for their growth and biofortification. Among a wide range of technologies available, storing at 18  C and application of apple vinegar treatment have proven to be the most useful in effect (Kahramanoglu and Usanmaz 2019). Next effective in line are the treatments of grape vinegar followed by commercialized Ethephon; the former is credited with an increase in total soluble solids in the fruits, while the latter slightly affects the ripening of fruits due to reaction with tannins.

2.4.2 Postharvest Techniques After harvesting a crop, it is essential to protect and conserve the agricultural produce with minimum handling and effective management. This is mainly done using postharvest management strategies and employs many advanced scientific and technical processes. A good harvesting procedure and management can lead up to 100 kg of dates annually where the average economic life of a date garden can be around 150 years. While harvesting, it has been found that usage of blue and black polythene bags has increased the percentage of fruit ripening (Awad 2007). Similarly, it is advisable to implement the bagging process to protect the plants from birds, sunburn, and heavy rain (Zaid and de Wet 2002b). The grower’s experience plays a big role in deciding the time of harvest of the fruits depending on their texture and appearance which are connected to sugar content and moisture. If decided correctly, the timing of harvesting reduces chances of skin cracking, attacks by insects and pests, or extreme dehydration. In fact, when selectively harvested early, it also leads to higher prices in the market and avoids disadvantages of harvesting late such as adverse weather conditions, attacks by pests, yielding good quality dates at matured stages, etc. However, in case the dates fall on the ground, they are not supposed to be considered fit for human consumption as there are higher chances of microbial contamination and soil particles entering the date fruit (Kader and Hussein 2009).

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Artificial Ripening It is very important that the fruits harvested are taken for appropriate ripening if they are picked immature for any purpose. Ripening can be carried out either indoors or outdoors, where the former requires a room with adequate air-conditioning to keep temperatures at 45–46  C and 70% relative humidity, for dates with thick flesh to ripen in about 2–4 days (Hyde 1948). However, the latter is a cheaper technique and comes with many disadvantages such as adverse conditions or external attack. Apart from this, the quality of ripening further increases when fruits are treated with chemicals like 1% ethanol and 2% acetic acid +1% NaCl or acetaldehyde (Asif and Al-Taher 1983). It has also been observed that freezing at 35 to 50  C is beneficial for the plants as it prevents damage to cell membranes (Kader and Hussein 2009). Hydration The step necessary to soften the few hard fruits refers to the hydration process which includes dipping them in cold or hot water for around 4 to 8 h at 60–65  C (Kader and Yahia 2011). The relative humidity maintained in the same is around 100% to convert the dried dates into glossy ones. Maintaining a constant rate of temperature and relative humidity is essential through forced air circulation, which is also the method of controlling the growth of microorganisms. The methods of treatments vary from one country to another, depending on the climatic conditions. Chemicals like alkaline ammonium sulfate help in improving quality of acidic but hydrated dates (Yahia et al. 2014). The additional step of hydration is necessary only when the dates are unripe and not overdried. Pasteurization is an exclusive process in the postharvest treatment of date palms which is executed at 72–80  C for 2.5 min (Martínez Vega et al. 2014). It was also reported that maintenance of almost 15–70% of relative humidity is best, when keeping the fruit mass loss and sweetness index in mind along with the coloration of dates becoming darker when skin temperature reached around 66  C (Casagrande et al. 2021). Thus, hydration is essential only when the moisture content of the fruits is low and can be continued using the same solutions as applied during the harvest procedure (Dole John and Faust James 2021). Initial Transportation and Sorting Large boxes of wood, plastic, or cardboard capable of carrying 200–450 kg fruits are essential to prevent any postharvest losses while transferring the fruits to the packing station. The process is better when faster and speedy transportation can be done as that prevents microbial infection as fruits are more susceptible to pests during the postharvest period (Abd Elwahab et al. 2019). The transportation process is ideally carried out at cooler temperatures (0–2  C) to prevent spoilage and atmospheric heat damage to plants. Specifically, forced air cooling proves to be more efficient than hydrocooling, which is the removal of excess moisture and its disinfection before packing and the usage of perforated plastic lining adds to the technicality of the process (Kader and Hussein 2009). Further, dates are fumigated in closed chambers and transferred to shakers for primary washing followed by the removal of excess water from the fruits. Then they are sorted manually through visual inspection

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according to whether they are ripe or unripe and are discarded if they are damaged due to transportation, microbial infections, heat, or other external factors, so that only the fresh lot of fruits is kept (Sarraf et al. 2021). This is one of the most timeconsuming stages of all postharvest procedures because sorting and grading depend on either manual means or through a mechanized visual system where color values and sugar range play an important role in differentiating various types of dates. It is essential to remove those dates which are either unfertilized or disfigured or contain some blemishes or foreign particles. This can be executed manually or using a machine according to physiological parameters like color, shape, size, and others. Immature, overripe, diseased, parthenocarpic, and partially or completely damaged dates are ideally discarded in this stage and only fresh ones are sorted according to their quality. Date fruit colors range from yellow to brown, and consistency of flesh ranging from soft to dry; these are the two most essential characteristics at this point (Sarraf et al. 2021). The accuracy of grading was improved using automated systems like date quality analysis by near-infrared imaging of two-dimensional view (Lee et al. 2008). More advanced techniques are also being developed for the differentiation of a variety of species since the time of maturation of all fruits is not the same, which will hasten the entire process of sorting and transportation to the packing house.

Advanced Automation and Robotics in Fruit Handling Keeping in mind the disadvantages of water and soil unavailability, it is always advisable to make the optimum use of advancements in technology and automation, which not only increases the rate of accuracy but also speeds up the entire procedure in a limited area. Cull fruits can be discarded or storage of fruits for a longer period can be controlled by automated systems and algorithms fixed in advance. This highlights the necessity of attaching technology to agriculture, forming agri-tech and taking the help of GPS, the Internet, robots, sensors, and a many other electronic devices to execute the agricultural processes in a more organized, smart, and accurate manner (Rose and Chilvers 2018). The remarkable possibilities of the Internet going digital are well-known in the twenty-first century and in the whole world; thus, it is time to transform conventional procedures into smarter and faster techniques. Near-infrared spectroscopy has long been helping in the analysis of fruit colors and textures (De Jager and Roelofs 1996). Not only this, but the advancement has also reached to the level that packing lines containing several sensors and cameras attached to visible and infrared probes help in analyzing the different qualities and parameters of fruits (Walsh et al. 2020). A track record can be maintained for easy accessibility (Njoroge et al. 2002) of the intricate details of the fruits like color, shape, size, grower name, and others by consumers to guarantee the safety and security of the fruits. Furthermore, computer models are used for correct decision-making and 80% accurate grading of fruits according to RGB images produced (Al Ohali 2011). There can be no end to the innovation and technology when it comes to applying robotics and artificial programming for both consumer’s and manufacturer’s ease of transaction.

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Nanotechnology Utilization in Packaging The application of nanotechnology has become a well-researched topic in almost every sphere of life, from physics to the biomedical world. For the packaging of date fruits, nanotechnology can play a major role in packaging, coatings, and films for date fruits. There are various types of nanoparticles – metallic, nonmetallic, or synthesized – working as antifungal agents in the preservation of fruits. There is a provision for creation of edible packages also using chitosan-based nanoparticles, which helps in the reduction of postharvest decay in fruits (Chaudhary et al. 2020; Kumar et al. 2020). Additionally, respiration and transpiration rates can be controlled in date fruits by using nanotechnology materials with smart packaging and innovative technologies for increasing the shelf life of fruits when stored for long periods (Acharya and Pal 2020; Alfei et al. 2020). Thus, overall application of nanotechnology using nano-fertilizers can also aid in the process of postharvest management of date palms to minimize the losses incurred by it. Adding Surface Coatings It is essential to identify the presence of any metal particles or xenobiotic compounds present on the fruit that might have come from the environment. This is followed by the improvement in the appearance of dates by introducing polished surface coatings and reducing stickiness. In addition, a solution of 5–6% soluble starch can be used as a dipping agent, 3% methylcellulose, 6% vegetable oil, 2% mixture of butylated hydroxyanisole and hydroxytoluene, 90% water, and finally a wetting agent. Ethanol vapors or immersing the dates in water for 10 h has hastened the process of ripening as compared to the controls, and neither had any negative effect on the quality of fruits (Awad 2007). For the surface coating preparation, solutions of date syrup, vegetable oil, corn syrup, and sorbitol or glucose syrup can also be used. Cooling and Packaging As mentioned, hydrocooling, which affects the rate of microbiological and biochemical changes in temperature and maintaining date palms at an average temperature of 0–10  C, is always desired and recommended for further long-term storage under 65–75% relative humidity. Once removal of excess water and disinfection is done, dates can be cooled to 0  C in 10–20 min, based on their initial temperature. Hydrocooling delays the rate of spoilage caused by microbes and increases the shelf life of food products (Djihad et al. 2021). Maintaining the temperature is important as it affects physiological parameters like sugar crystallization and that is affected by the moisture content in the fruit, as water above 20% affects the fruits adversely (Glasner et al. 1999). Before commercialization, it is essential that the date palms are packed in suitable containers or packages so that they are protected from any further microbial attack or damage due to mishandling and transportation prior to consumption. Only those date palms that are packed and available in intact airtight packets are accepted for further research and analysis in the marketing sector (Kabir et al. 2021). Consumer packages and large cartons including transparent film bags and plastics include the containers for storing date palms apart from other bottles with metal caps and bottoms. Small

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packages suited to carry 50–60 g date palms are also used along with cardboard boxes weighing 5 kg, in countries like the USA, Jordan, Saudi Arabia, and others. It is very important to mention particulars about the specifications on the labels such as date of packaging, grower industrial details, nutritional benefits, date of expiry, country of origin, and other details so that consumers can get a glimpse of the overall status of the fruit.

2.5

Requirement of Genetic Biofortification

Fortification of any consumable product refers to deliberately making it enriched and more nutritious than normal by means of either the addition of micronutrients or bringing about modification genetically. It is done either through conventional techniques which are slower and vulnerable to bacterial invasions or through modern biotechnological approaches that are quicker, more reliable, and easier to obtain. Such an approach toward the biofortification of any consumable is essential when judged from the perspective of enriching the nutritional status of any country’s population. Processes of agronomic practices, food processing, and others fall under conventional fortification techniques, but for genetic modification of plant germplasm, selective breeding comes under modern biofortification tools and techniques. It is aimed toward the enrichment of a nutritional density of a plant, increasing accessibility to rural areas without the slightest drop in the overall yield of the crop. Especially after the COVID-19 pandemic, it has become essential to support the underdeveloped and developing countries in terms of food security and uplift their standards of living in terms of nutrition and health to prevent loss of life from malnutrition. Moreover, institutions like ICRISAT and CIMMYT in association with Harvest Plus have taken initiatives to scale up biofortification procedures to improve the nutrition and public health by providing and promoting higher iron content in pearl millets and zinc content in wheat available to the general population (https://www.harvestplus.org/where-we-work/india). India ranks tenth out of 117 countries and third out of 128 countries, respectively, as suitable place to grow iron pearl millet and zinc wheat. Increasing food security and the quality of life of people in developing countries and decreasing nutrition-related disorders, mortality, and morbidity are the main goals of biofortified crop production. When crops are genetically engineered to produce high micronutrient-enriched products, they are referred to as genetically fortified. One of the most common examples of genetically biofortified crops is the Golden Rice that was modified to produce and accumulate vitamin-A enriched genes (β-carotene), giving it a golden colored appearance. Rice being the staple food of a good portion of the entire world population, if targeted to be genetically biofortified, can automatically benefit a lot of people who might not get the required nutrients due to the reduction in zinc and iron, especially after milling. So, one of the most promising solutions brought very recently toward the mitigation of this problem is the production of genetically biofortified rice along with iron and zinc, and in addition special features were kept in mind, for the decrease in arsenic contamination in rice grains (Viana et al.

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2021). Not only rice, but there are also reports of wheat biofortification as wheat is also consumed by another major part of the population. Identification of Fe/Zn QTLs is an important step of biofortification, and a versatile domain is promised by the usage of biofortification tools and techniques in genetic engineering and molecular biotechnology field (Tong et al. 2020). Genomic selection has been considered as a good process for biofortification of Fe/Zn QTLs, but incorporation of the QTLs into the models as a fixed effect is questionable. The answer to why crops need to be genetically biofortified can be alluded to targeting the rural population which has restricted accessibility to nutritious foods and minerals or those who have almost no opportunity of genetic interventions like biofortification. Another reason is the requirement to meet a specific quantity of calories needed by the body to sustainably live. As of recent reports, Egypt has recorded the world’s highest date palm consumption of about 1.6 million mt, followed by Oman, United Arab Emirates, and Algeria (https://www.mordorintelligence.com/industry-reports/date-market). Africa and Middle East alone hold 70% of the entire consumption of date palm fruits worldwide and the trend increases daily. So, with the increase in date fruit consumption, the necessity to biofortify the fruit increases and achieving the target of uplifting lives in rural areas with micronutrient-enriched date fruits automatically becomes easier. The proteins like cell number regulator (CNR) play an important role in the genetic biofortification of Triticum aestivum by TaCNR5 expression in shoots of wheat analyzed under Cd, Mn, or Zn metal treatments (Qiao et al. 2019). Activity of these heavy metals as micronutrients in the biofortification of cereals, moderated using the expression levels of TaCNR5, can open a new avenue of research and development in the nutrition elevation. As of 2021, not enough research has been executed for the genetic biofortification of date palm, but the techniques are being studied and more possibilities are being discovered by plant biotechnologists. In their first book, Al-Khayri et al. (2021) provided comprehensive information on various proteomics and metabolomics technologies applicable for the genomic improvement of date palm fruits. The genomic stability of in vitro date palm plants and diversity of genomes with DNA barcoding processes along with genomic approaches for resistance to all stress factors have been reported already. At this juncture, this chapter proposes the urgency and essence to identify the possible genetic biofortification procedures applicable for date palm because that itself serves as one of the major mechanisms for nutrient level improvement in the world population. The requirement of genetic biofortification alludes to the necessity of nutritional security in a country, with respect to enhancement of the micronutrient status in the soil. Transgenic biofortification is a route that can answer the same question and curtail the issue of micronutrient deficiency in soil. At this juncture, microbes with plant growth-promoting benefits are beneficial to improve the nutritional quality of the soil. Reports of using Arthrobacter sp. (DS-179) and Arthrobacter sulfonivorans (DS-68) for the nutritional improvement of zinc and iron in the soil have been studied (Singh et al. 2017). Biofortification, depending on the insert type, can be classified into conventional and transgenic biofortification. The former type involves the introduction of artificial additives along with it and is thus largely limited to the

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developed countries only, due to the necessity of high infrastructure and machinery (Díaz-Gómez et al. 2017). There are various disadvantages connected to the introduction of added minerals to the food crop like taste, etc., but the brighter side includes a higher percentage of necessity, when focusing on the nutritional requirements among the masses. The importance and necessity of genetic biofortification, though well-known to scientists and researchers, has not much been implemented in the field of date genomics. This void needs to be filled through advanced research as soon as possible and that demands our attention to elevate the standards and processes that are linked with enhancement of mineral constitution in the plant at study.

3

Breeding Using Molecular Markers for Genetic Improvement

Molecular breeding via molecular biology and marker-assisted DNA analysis by considering phenotypic character and diversity is an effective strategy to analyze genetic polymorphism in breeding programs. Molecular breeding includes markerassisted selection (MAS), quantitative trait loci (QTL), genetic engineering, etc. Molecular markers with support of phenotypic data are involved in species and cultivar identification, diversity and phylogenetic relationships, and many breeding activities.

3.1

Diversity Analysis

3.1.1 Phenotypic Diversity Phenotypic diversity is seemingly a date palm diversity indicator. It is also a basis for selection, conservation, and improvement for sustainable utilization. There are 19 known or reported Phoenix species; however, 12 species (Zabar and Borowy 2012; Abul-Soad et al. 2017) are often considered as valid as there is still confusion regarding the exact number of Phoenix species. P. dactylifera, P. acaulis, P. canariensis, P. paludosa, P. reclinata, P. rupicola, and P. sylvestris are the most widely accepted species. P. dactylifera is the most commercially cultivated Phoenix species. Pinnate leaves and conduplicate leaflets with acute apex are the distinguishing characteristics of this genus (Uhl and Dransfield 1987). P. dactylifera, P. atlantica, P. canariensis, P. theophrasti, and P. sylvestris are closely related in overall appearance. However, they have been reported as separate species by molecular marker studies (Henderson et al. 2006). P. dactylifera is the original Middle Eastern wild representative and is distributed in different parts of South Asia and Africa. The domesticated date palm grows more than 30 m in height. It has a clustering trunk, but in cultivated varieties, it appears as a single trunk due to the removal of offshoots. The fruits are the largest among the Phoenix spp. reaching to a maximum of 100  40 mm in size. The other wild relatives like P. theophrasti have a restricted distributional range especially in coastal

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areas of Southwest Turkey, P. atlantica growing near the Atlantic shores of North Africa, which represents the feral populations of P. dactylifera (Rivera et al. 2008), and P. iberica with glaucous leaves, stout stem, and small fruit with thin flesh growing in the Mediterranean coast of Spain which is considered as an intermediate between P. theophrasti and P. sylvestris. P. chevalierii has greener leaves compared to P. dactylifera and is an Iberian-Moroccan group of cultivars grown in southeastern Spain (Rivera et al. 2008). P. reclinata has a bushy habit and seen in the southern parts of Arabia and Sahara Desert (Tengberg 2012), and P. sylvestris, the rain palm, is a nonsuckering 20 m tall tree adapted to tropical climates especially the Indus Valley (Zohary and Hopf 2000). P. canariensis, usually cultivated as an ornamental, has a 20 m high stout trunk which is adapted to moderate climate and is endemic to the Canary Islands (González-Pérez et al. 2004). However, P. rupicola, known as the cliff palm is about 7 m in height and has a thin trunk and is native to the northern parts of India. Similar in morphology is the P. pusilla palm but with a shorter trunk and is found in the southern parts of India and Sri Lanka. The Senegal date palm P. reclinata with 10 m thin clustering trunk is used as an ornamental and is native to tropical Africa. Ornamental palms P. paludosa (mangrove date palm) and P. reclinata have similar appearance and are found in the swampy regions of southeastern Asia. P. roebelenii (pygmy date palm), grown as an ornamental, has a single trunk and is native to Southeast Asia; P. acaulis, with short clumping stems, is found in northern India and Burma; and P. loureiroi, often confused as P. acaulis, has short stems and is found in northern India and southern China (Barrow 1998; Zohary and Hopf 2000). Thousands of cultivars have been reported from all over the world. These have been developed by various selection methods to improve crop yield and quality and to tolerate environmental stress, etc. Morphological description of characters like form of the tree, fruit (shape, size, weight, color, texture), fruit stalk, and leaf, especially leaflets and spines, is an important parameter for identification of cultivars (El-Houmaizi et al. 2002; Al-Yahyai and Al-Khanjari 2008; Ould Mohamed Salem et al. 2008; Elshibli and Korpelainen 2009; Markhand et al. 2010). Jaradat and Zaid (2004) have reported up to 5000 date palm cultivars. However, based on botanical descriptions, 1000 cultivars in Algeria, 450 in Saudi Arabia, 400 in Iran, 400 in Iraq, 250 in Tunisia, 244 or 453 in Morocco, 95 in Libya, 400 in Sudan, 250 in Oman, 321 in Yemen, 52 in Egypt, and 300 in Khairpur, Pakistan (Benkhlifa 1999; Bashah 1996; Hajian and Hamidi-Esfahani 2015; Zabar and Borowy 2012; Zaid and de wet 2002a, b; Sedra 2015; Battaglia et al. 2015; Osman 1984; Elshibli 2009; Al-Yahyai and Al-Khanjari 2008; Al-Yahyai and Khan 2015; Ba-Angood 2015; Rabei et al. 2012; Mahar 2007; Markhand et al. 2010; Abul-Soad et al. 2015;) along with other cultivars in different growing regions have been reported. Chemical characters of fruits and ripening stages of fruits are some of the apparent factors for the identification of cultivars (Elshibli and Korpelainen 2009, 2010). Numerous documented reports are available for date palm cultivars using vegetative, flowering, and fruit characters. In Saudi Arabia, 17 date palm cultivars were evaluated for vegetative parameters, flowering and yield characters, and fruit attributes (Al-Doss et al. 2001). Among five Sudanese date palm cultivars,

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physicochemical differences with respect to weight of fruit, and seed, thickness of flesh, fruit length, and phytochemical constituents were reported (Sulieman et al. 2012). Prominent fruit characters were reported among 85 cultivars from Pakistan (Markhand et al. 2010). Twenty-six date palm cultivars have been studied to identify descriptors (leaf, pinnae, and spine) for early-stage date palm characterization other than fruit characters (Elhoumaizi et al. 2002). Fruits of date palm have been classified based on texture as soft, semidry, and dry types (Barreveld 1993). Ecological distribution of soft and dry dates is reported only from Sudan. However, they also exist in different growing countries (Barreveld 1993; Zaid and de Wet 2002a). Although there is huge diversity in the cultivar of date palm, most information is unpublished or unavailable due to ownership of cultivars.

3.1.2 Genetic Diversity Using DNA Markers Phenotypic characterization has been utilized extensively for the identification and selection of various cultivars. However, it is difficult to identify the date cultivars without observing the fruiting stage. Molecular biology techniques and molecular marker-based selection have helped breeders to accurately select specific cultivars. The extent and distribution of genetic diversity is an important measure for genetic conservation of existing germplasm (Jubrael et al. 2005). The availability of nuclear and chloroplast genome sequence of date palm is an added advantage for assessment of genetic diversity (Yang et al. 2010; Al-Dous et al. 2011; Soumaya et al. 2014). In addition, molecular markers can be effectively used for genetic diversity assessment and constructing genetic maps for identification, genetic improvement, and conservation of true-to-type elite material (Eissa et al. 2009; Khierallah et al. 2011). Random Amplified Polymorphic DNA (RAPD) RAPD marker-based PCR techniques have been extensively used for identification of date palm cultivars as they are cost-effective and do not require blotting or radioactive materials (Mirbahar et al. 2014; Emoghene et al. 2015). Numerous studies have reported genetic diversity in date palm cultivars using RAPD markers in Saudi Arabia, Tunisia, Algeria, Iraq, Egypt, Bahrain, Syria, Nigeria, Morocco, India, and Pakistan (Al-Khalifah and Askari 2003; Al-Moshileh et al. 2004; Abdulla and Gamal 2010; Munshi and Osman 2010; Benkhalifa 1999; Jubrael 2001; Al-Khateeb and Jubrael 2006; Khierallah et al. 2014; Trifi et al. 2000; El-Tarras et al. 2002; Adawy et al. 2004; Soliman et al. 2006; Younis et al. 2008; Moghaieb et al. 2010; Pathak and Hamzah 2008; Haider et al. 2012; Sedra et al. 1998; Sedra 2013; Emoghene et al. 2015; Mirbahar et al. 2014; Toor et al. 2005; Singh et al. 2006; Rani et al. 2007). However, due to lack of dominance and detection of heterozygosity, these markers are relatively less used than other molecular markers. Amplified Fragment Length Polymorphism (AFLP) Large intervarietal polymorphism in date palm cultivars has been reported by various workers using AFLP markers (Mueller and Wolfenbarger 1999; Elhoumaizi et al. 2006; Khierallah 2007). These markers have also been effectively employed for making high-density linkage maps. There are several reports showing the detection

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of polymorphism in date palm cultivars. In Spain, Diaz et al. (2003) reported diversity and polymorphism of date palm cultivars using AFLP markers. Using AFLP markers, El-Khishin et al. (2003) characterized five date palm cultivars from Egypt. The genetic diversity of Egyptian date palm from eight locations was studied. Twenty-eight accessions and a few accessions from California were classified and found to represent the major date palm germplasm of North Africa (El-Assar et al. 2005). Genetic diversity and phylogenetic relationships among various Iraqi cultivars have been reported (Jubrael et al. 2005; Khierallah et al. 2011). AFLP markers have been also employed for assessing genetic variations that are seen in offshoots of tissue-cultured date palms (Saker et al. 2006). Restriction Fragment Length Polymorphism (RFLP) RFLP markers are locus-specific markers which can be used as important tools for identification between closely related species. Being codominant they show strong molecular differentiation. Date palm cultivars have been differentiated using these RFLP markers. In Tunisian date palms, 43 accessions have been utilized for identification of genotype and genotypic polymorphisms (Sakka et al. 2003). Shoot tips used to initiate tissue culture of five elite date palm cultivars were utilized to determine the polymorphism using RFLP markers (Cornicquel and Mercier 1994). Cornicquel and Mercier (1997) generated cultivar-specific hybridization using RFLP in four date palm cultivars. PCR-RFLP-based markers were utilized for sex determination in date palm (Al-Mahmoud et al. 2012). Intersimple Sequence Repeats (ISSR) Microsatellite-based primers are utilized to amplify intersimple sequence DNA repeats and have been also utilized for studying inter- and intraspecific genetic variations in date palm. The genetic diversity of date palm in different growing regions has been assessed by various workers in Egypt, Iraq, Iran, India, Morocco, Pakistan, Tunisia, Egypt, Saudi Arabia, Algeria, and Ethiopia (Younis et al. 2008; Khierallah et al. 2014; Sharifi et al. 2018; Srivastav et al. 2013; Bodian et al. 2012a; Mirbahar et al. 2013; Ahmad et al. 2020; Zehdi et al. 2002, 2004a, b, 2005; Karim et al. 2010; Zehdi-Azouzi et al. 2011; Hamza et al. 2012; Younis et al. 2008; Kumar et al. 2010; Munshi and Osman 2010; Sabir et al. 2014a; Boudeffeur et al. 2021; Takele et al. 2021). Microsatellites or Simple Sequence Repeats (SSR) SSR markers are codominant, species specific, and highly polymorphic, making them suitable markers for cultivar identification, genetic diversity assessment, and construction of linkage maps and gene-based maps in date palm. Akkak et al. (2003) have isolated simple sequence repeats from genomic library and detected high polymorphism in the analyzed samples. Researchers have reported genetic diversity and polymorphism in Tunisia (Zehdi et al. 2004a, b, 2006), Qatar (Elmeer and Mattat 2012), Iraq (Khierallah et al. 2011), Libya (Racchi et al. 2014), Saudi Arabia (Yusuf et al. 2015; Al-Faifi et al. 2017), Qatar (Ahmed and Al-Qaradawi 2009; Elmeer and Mattat 2015), Mauritania (Bodian et al. 2012b), Pakistan (Naeem et al. 2018), and

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Sudan (Elsafy et al. 2016). SSR markers have been developed for specific identification of gender in date palm for breeding (Maryam et al. 2016). Expressed Sequence Tags (EST) 28,889 EST sequences were analyzed from date palm genome database to develop gene-based markers, i.e., EST-SSRs (Zhao et al. 2012). One third of the primers designed detected polymorphism to differentiate the date palm cultivars used. In date palm, large-scale collection and annotation of gene models were also developed (Zhang et al. 2012). ESTs were also generated for understanding the high performance and quality of commercial cultivar (Al-Faifi et al. 2017). Single Nucleotide Polymorphisms (SNPs) High-density genetic maps are created using potential markers like SNPs. They are now widely used to study date palm genome sequences. The first draft genome of palm cultivar was assembled using EST markers (Al-Dous et al. 2011). SNP analysis by sequencing the mitochondrial DNA sequence of Saudi Arabian date palm cultivars revealed close phylogenetic relationships among the studied cultivars (Sabir et al. 2014b). In a study of date palm cultivars from different countries using generated SNPs, the date palms were segregated based on genetic background into two main regions, i.e., North Africa and Arabian Gulf (Mathew et al. 2015). Based on whole genome sequence of date palm, a catalog of about seven million SNPs from 62 cultivars was developed (Hazzouri et al. 2015).

3.2

Sex Determination

In dioecious trees, identification of male and female sex is a complex process, as it is not possible to identify the plants in the seedling or early growth stage. Date palm being dioecious takes 5–7 years before it starts flowering and fruiting, which is a limiting factor with respect to traditional breeding programs. It not only causes economic loss to farmers but also makes it difficult for the breeders to select the superior lines from the existing elite cultivars. The genetics of sex determination in date palm is fully understood, but attempts have been made at morphological level, biochemical level, and molecular level to determine the sex of the plant at the early development stages (Awan et al. 2017).

3.2.1 Morphological Markers Morphological features of the plant are usually taken into consideration to determine the sex of the plant. However, such characters can be applicable at maturity. Being laborious and the effect of environmental factors make it difficult to study. Identification of genotype of date palm is based on female tree morphology and characters of fruits. Date palm cultivars from Saudi Arabia have been identified based on morphological characters (Al-Khalifah et al. 2012). Similarly, male plants from elite cultivars have been identified based on morphological markers (Soliman et al. 2013). There are

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numerous reports stating that the leaf and leaflet characters can be utilized for identification (Ahmed et al. 2011; Hammadi et al. 2009; Haider et al. 2015).

3.2.2 Biochemical Markers Peroxidase serves as an important marker for the identification of male and female plants, as the diversity of peroxidase varies between male and female inflorescences. Researchers have reported lower peroxidase and acid phosphatase activities in male than in female date palm plants (Qacif et al. 2007; Bekheet et al. 2008). Moreover, glutamate oxaloacetate activity is higher in female than in male plants. Polypeptides specific to male plants which were isolated from the leaves were also reported. These also serve as a gender biomarker in date palm (Sonia et al. 2013). Chemical composition of leaves has also been a distinguishing parameter, where female leaves have higher concentration of pigments, phenolic acids, amino acids, and sugars, whereas male leaves have higher concentrations of proline and ash (El-Yazal 2008). Higher levels of sugar have been reported in male trees compared to female trees (Rao et al. 2009). Similarly, phenolic acid content is higher in male than in female plant saps (Makhlouf-Gafsi et al. 2016). 3.2.3 Molecular Markers Due to the limitations of the morphological and biochemical markers, molecular markers based on RFLP, RAPD, AFLP, and SSR markers were developed for the identification of gender in date palm. Numerous attempts to identify the male and female gender in date palm using RFLP (Al-Mahmoud et al. 2012), RAPD (Ben-Abdallah et al. 2000; Soliman et al. 2003; Ahmed et al. 2006; Al-Khalifah et al. 2006; Bekheet et al. 2008), ISSR (Younis et al. 2008; Al-Ameri et al. 2016a), AFLP (Atia et al. (2017), SCAR (Al-Qurainy et al. 2018; Dhawan et al. 2013; Al-Ameri et al. 2016b), and SSR markers (Elmeer and Mattat 2012; Maryam et al. 2016) have been made. A putative sex chromosome was identified using the constructed date palm genetic map (Mathew et al. 2014). Date-SRY gene and GWAS mapping of sex determination locus are some of the important tools for sex determination in postgenomic era (Hazzouri et al. 2019; Mohei et al. 2019).

3.3

Genomics

Sequencing and analysis of the genome have important applications in determining genetic diversity, systems biology, evolutionary process, etc. The sequenced genome of date palm has been used for developing genetic map (Al-Dous et al. 2011; Al-Mssallem et al. 2013; Mathew et al. 2014; Sabir et al. 2014b; Hazzouri et al. 2015). Sequencing technologies like pyrosequencing, ligation-based sequencing, etc. have been utilized for sequencing the nuclear genome (Al-Mssallem et al. 2013), chloroplast genome (Yang et al. 2010), and mitochondrial and plastid genomes (Sabir et al. 2014b). In addition, to understand the genomics of date palm, various projects have been undertaken for sequencing the whole genome like the Date Palm Genome Project (DPGP) by King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia, in association with Beijing

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Institute of Genomics in 2008. Weill Cornell Medical College, Qatar, using nextgeneration sequencing technology, sequenced the whole genome of date palm (https://qatar-weill.cornell.edu/research-labs-and-programs/date-palm-research-pro gram/date-palm-genome-data). The genome contains 500 Mbp.

3.4

Computational Analysis

Gene regulation has been highly influenced by micro-RNAs (mi-RNAs) during the development of the plant. The 276 novel date palm-specific mi-RNAs involved in regulating genes for fruit development and ripening have been characterized by using high-throughput sequencing and bioinformatics predictions (Xin et al. 2015). Similarly, 153 homologs of conserved miRNAs, 89 miRNA variants, and 180 putative novel miRNAs in date palms that can play an important role in salt tolerance were identified (Yaish et al. 2015).

3.5

Genetic Manipulation of Date Palm

Date palm has been genetically modified to incorporate new genes to improve the commercial value of the crop. Transformation via Agrobacterium-mediated and direct gene transfer using particle bombardment has been utilized for the transfer of specific genes of interest. Agrobacterium-mediated transfer utilized GUS (β-glucuronidase) as the reporter gene. Saker et al. (2009) reported the first case of successful infection of embryonic cells in date palm and a system was developed for the transfer. Aslam et al. (2015) reported detection of strong GUS activity and integration of uidA (GUS) and npt II genes into transgenic plants in cultivar Khalasah via somatic embryogenesis. Various researchers were involved in the transformation via particle bombardment, but pioneering work was using the Iranian cv. Khorma (Habashi et al. 2008). Likewise, factors affecting transformation via particle bombardment in Egyptian cv. Sewi were optimized (Saker et al. 2007). Mousavi et al. (2014) developed an efficient transformation for gene delivery in date palm. Somatic embryos of Estamaran cultivar were utilized for transient transformation of the uidA gene. Physical and biological parameters were optimized, and tissue bombarded with constructs having the uidA gene. Similarly, for introducing date palm resistance to pests, a construct with the cholesterol oxidase (ChoA) gene was introduced into embryonic callus of date palm by particle bombardment (Allam and Saker, 2017).

4

Recent Concepts and Strategies Developed

4.1

Gene Editing

Prevention and treatment of diseases in organisms using genome corrections or modifications refers to gene editing and is gaining ground today as conducted by researchers and scientists. Mainly for therapeutic purposes, gene editing is known

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for somatic body cells and germline – reproductive cell-based therapies. The applicability of gene editing is not only limited to animals or humans but also finds an extensive range of applications in plant biotechnology. Gene editing in plants, referring to the alterations in DNA and ultimately affecting the phenotype and associated traits in the plants, involves the use of various enzymes for the insertion and replacement of various DNA sections. Instead of random insertion and deletion of genes like traditional ways in organisms, gene editing targets the site-specific editing at specific locations only and is of immense interest in the treatment and cure of diseases like sickle cell anemia, cystic fibrosis, and others. The creation of herbicide-resistant, disease-resistant, or nutrient-rich crops is no longer a dream for scientists as they can be constructed even with specific alterations in the plant’s own DNA instead of the introduction of new or foreign genes. Both with and without plant tissue culture methods, the creation of identical copies from simple plant tissue is possible with the advancement in technology (Kim 2020). Out of the many techniques available, the two most applied ones in the construction of an edited plant include the addition of Streptococcus pyogenes cas9 protein-encoding DNA and a guide RNA using nature’s genetic engineer, Agrobacterium. CRISPRCas9 systems have revolutionized the entire world of plant editing genome and its associated areas. Knock-ins and other methods of delivery for CRISPR and other editing tools require a deeper understanding and knowledge of the processes for finer targeted procedures (Mao et al. 2019). It has been reported that not all CRISPR constructs and variables are successful owing to the differences in specificity required for the expression of Cas9 DNA nuclease, and such a comparison in levels of editing has been exhibited by Arabidopsis thaliana (Shockey 2020). Unwanted mutations can also be expected to be observed on introspection at the genomic level as nuclease activity was observed at locations that were targeted using single guide RNAs that were imperfectly matched. There are processes available that include genetic transformation even without the involvement of DNA, and one of the major concerns includes its cellular genome integration. This often becomes a hurdle in the experimental settings and practical modes, which often drives a reason for developing novel methods of gene editing without the necessity to transform or use DNA delivery (Tsanova et al. 2021). Few of the processes include the formation of ribonucleoprotein complexes, utilization of secretory systems in bacteria for Cas/gRNA delivery, or even application of viruslike particles. For the former option, Agrobacterium plays a major role in the CRISPR/ Cas9 cassette delivery. Although this method is gaining ground owing to its ease of techniques, low cost, and flexibility, there are a number of obstacles in transformation using genome editing of polyploid crops and germline gene expression (Vats et al. 2019). More precise technologies like promoter bashing, methylome, or gene editing can also be referred to as techniques for advancement in plant sciences and editing. As far as Phoenix dactylifera is concerned, gene editing reports revolve mostly around determination of genetic basicity. Measurable phenotypes as controlled by a set of genes and their interaction with the environment, referred to as quantitative traits, are primarily concentrated on when it comes to gene editing in date palms.

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Specific chromosome regions of that control continuous traits are referred to as quantitative trait loci (QTLs). The phenotypic evaluation might not be the ultimate method to identify QTLs, but they can be mapped to identify the location of complex traits as well. In addition, for the identification of QTLs, both genotype and phenotype play a major role by either linkage disequilibrium or overall structure of population or prediction of relatedness in the category of genotypes. CRISPRassociated protein 9-based approaches have been applied in fruit trees; they are cumbersome and practically difficult to apply in date palms due to their higher genome complexity and structure and high outcrossing and heterozygosity rate. The disadvantages of genetic instability owing to high frequency rate of single nucleotide polymorphisms are common in the same. Despite these issues, several approaches using CRISPR/Cas-9 for gene editing in date palms have been enlisted in a report by Sattar et al. (2017). Along with that, various prospects of genome editing tools have also been discussed in date palms. An array of experiments has been conducted on the genomic content of date palms alone. They have revealed the presence of 38 proteins, 3 ribosomal RNAs, and 30 tRNAs which make up 6.5% of the complete genome and are completely coding, whereas the remaining is noncoding and chloroplast-derived, consisting of tandem and long repeats with a constitution of 0.33% and 2.3%, respectively (Fang et al. 2012). This places the mitochondrial genomic data of date palms at the fourth position based on genomic length. Evolution along parallel lines can be well documented according to a report by Hazzouri et al. (2019) where domesticated species showed diversification in the evolutionary trend. A comprehensive genome assembly of the P. dactylifera genome has been made by the group that extends up to 772.3 Mb lengthwise with an 897.2 Kb contig N50, which is further used to execute genome-wide association studies (GWAS) of fruit traits or sex-determining region. It has also been reported that there are 18 polycistronic transcription units and three exclusive genes that are highly expressive in nature, namely atpF, rrn23, and trnA-UGC, as per information from RNA sequencing in date palm chloroplast genome. As observed in most angiosperms, the date palm genome also exhibits 112 unique genes along with 19 duplicated fragments in the inverted repeat regions. There is a typical similarity of date palm genomics with that of tobacco with slight rearrangements in genetic order, as reported by Yang et al. (2010). Major intravarietal polymorphisms as observed include 78 single nucleotide polymorphisms within the chloroplast genome, mostly in genes with vital functions. To get a comprehensive idea about the complications of dioecy and long-time generation, the draft genome for Khalas variety was executed by Al-Dous et al. (2011), constituting a 380 Mb sequence with gene models of more than 25,000, covering 60% of genome and 90% of genes.

4.2

Nanotechnology

The study and application of extremely small objects, being classified on a scale between one and a hundred nanometers on the meter range, refers to the branch of nanotechnology. Currently, it is one of the most developing branches in the

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scientific world and rightly gaining prominence among the scientists due to its promising avenues for study of almost any division of research world. The application of nanotechnology has been extended to biological systems especially to create new medicines for combating upcoming challenges in the world of diseases, along with preventing blood clot formation. The most important fluids maintaining the overall physiological conditioning of body, blood, and its components – erythrocytes, leukocytes, and platelets – are accessible to the nanoparticles through the induction of phosphatidylserine on erythrocyte membrane, thereby altering the hemorheological membranes (Zain et al. 2022). An increasing resonance has been found in the application of nanotechnology in the production of secondary metabolites in plants, especially in the usage of silver nanoparticles that possess both hermetic and antimicrobial properties (Rahmawati et al. 2022). This increased applicability is mostly due to microbial decontamination capabilities and elevation in the overall quantity of secondary metabolite content. Detection mechanisms are conducted using nano-biosensors and chips that provide a cheaper, reliable, portable, and faster method for sustainable agricultural procedures (Sellappan et al. 2022). This has already been applied to the detection of microbes, especially viruses in plants as higher pollution was observed on introduction of pesticides in the fields. The never-ending industrialization and urbanization have led to the overall rise in environmental pollution, and application of nanotechnology has helped in the bioremediation processes and decontamination measures taken up by the research centers and industries. In association with nanoparticles, the environmentally friendly and reactivity nature of nanotechnology has helped elevate the quality of bioremediation tasks aided with responsibility in keeping surroundings clean and green. Nyika (2022) has reported various examples where nanotechnology has hastened the process of environmental bioremediation measures that were apparently challenging owing to chemical reactions like photocatalysis, filtration, and other invasive chemical reactions. For the preparation of nanoparticles, until now several plant extracts have been used as reducing agents, and greener methods of production are more preferred over synthetic ones. Thus, in a report by Batool et al. (2021), nanoparticles were created using Phoenix dactylifera as the reducing agent and iron sulfate heptahydrate was the respective substrate to work on. Very interestingly, the nanoparticles have exhibited high antimicrobial activity with a zone of inhibition of about 25  0.360 mm against Bacillus subtilis, Klebsiella pneumoniae, Escherichia coli, and Micrococcus luteus. Apart from that, seeds of date palm were used for the same in another experiment by Sirry et al. (2020) for the synthesis of silver nanoparticles. Applications in the biomedical field were checked using the nanoparticles so formed, and extraction was mostly focused on with the usage of several solvents like acidic and alkaline media, ethanol, methanol, and water – both boiling and at normal temperature. In all cases, applicability of water was at a higher efficiency level as compared to other solvents, and anti-inflammatory efficiency was studied by inhibiting albumin denaturation to a higher extent as compared to that using piroxicam alone loaded onto silver nanoparticles.

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As explained earlier, almost all the parts of the plant are useful in some way or the other for scientific application. Apart from seeds, leaves of the plant have found applicability in the formation of zinc oxide nanoparticles, where FTIR, TEM, XRD, and UV-visible spectrophotometry are few techniques that have aided in its characterization (Salih et al. 2021). These nanoparticles so formed elevated the physiological characteristics necessitated for growth and development of callus of Juniperus procera, as analyzed using GC-MS. Further, there was an upliftment in the quality of biochemical parameters such as chlorophyll a, total flavonoid, and phenol, apart from improvement of total protein and SOD, CAT, and APX activity. In addition, aqueous extract from fruits of date palm have been exclusively used in the preparation of silver nanoparticles and further characterized and evaluated for their in vitro antimicrobial activities (Zafar and Zafar 2019). Potential studies about the cytotoxic activities of the nanoparticles obtained using fruits have been studied in breast cancer cell lines (MCF-7), and cytotoxicity has been found through apoptosis, necrosis, or mechanisms to suppress mitochondrial functioning that can lead to disruptions at various stages in cell cycle. Similar experiments have been performed by Farhadi et al. (2017) using date palm fruits as an extract to produce spherical silver nanoparticles using low-cost and eco-friendly approaches for the preparation of reducing and stabilizing agent from the same. The elemental or crystalline property of nanoparticles was characterized using EDX and XRD techniques, whereas their spherical nature was confirmed using scanning electron microscopy and transmission electron microscopy. Along with that, functional groups as found in biomolecules of date palm fruits are the major reasons for the reduction or stabilization property of nanoparticles, respectively. There are several active components in Phoenix dactylifera, also referred to as date pits, which include L-glutamic acid, gallic acid, or sinapic acid that can function as reducing agents, in accordance with manganese trioxide nanoparticles so synthesized (Sackey et al. 2021). These active compounds have helped in the nanoparticle preparation, and several advanced techniques such as HR-TEM, energy-dispersive detector, high resolution-scanning electron microscopy, and cyclic voltammetry have revealed the efficiency of computationally and experimentally synthesized nanoparticles. Apart from the protocols being cheap, another reason for the preference of green synthesis over synthetic ones includes its environment-friendly nature. Characterization of nanoparticles was conducted using advanced technologies such as UV-visible spectrophotometry showing a peak at 275 nm, indicating the presence of copper oxide. Berra et al. (2018) also confirmed the application of X-ray diffraction and scanning electron microscopy for the crystalline nature and aspherical shape of copper oxide nanoparticles, respectively.

5

Bioinformatics of Date Palm

Bioinformatics is the scientific discipline of collecting and storing biological information in searchable databases and handling the data effectively to draw significant conclusions. Data generated by omics approaches is understood by in silico tools to draw implications about mechanisms of the biological processes in date palm.

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To understand the DNA of date palm, whole draft sequence assemblies of nuclear, plastid, and mitochondrial genomes are being generated, and to understand the RNA, protein, phenotype, and chemotype, transcriptomes, proteomes, phenomes, and metabolomes have been generated, respectively.

5.1

Genome Analysis

Date palm is diploid (2n ¼ 36) and several studies have been carried out for the estimation of nuclear genome and organellar genome sizes (Al-Dous et al. 2011; Fang et al. 2012; Al-Mssallem et al. 2013; Sabir et al. 2014a; He et al. 2017; GrosBalthazard et al. 2018; Thareja et al. 2018; Chaluvadi et al. 2019; Hazzouri et al. 2019; Mohamoud et al. 2019;). Date palm genome assembly draft was analyzed and microsatellite motifs were screened using a script in Perl software, which showed 321,278,327 bases (Hamwieh et al. 2010). Transcriptome sequences were identified and 1000 SSR loci were utilized for developing new markers. 166,760 SSR regions with a density of 1 at every 2.2 Kb in the date palm genome were found (Manju et al. 2016). Xiao et al. (2016) observed at a density of 1 in every 1.36 Kb, 371,629 SSRs. As many as new 264,655 SSR loci were located when 62 cultivar genomes of date palm were re-sequenced and when compared them with known reference genome assemblies available in online database. Pathway annotation work carried out in date palm by using SSR regions and BLAST2GO methods showed 23 enzymes involved in metabolism of starch and sucrose and 16 enzymes involved in metabolism of amino/nucleotide sugar (Mokhtar et al. 2016). A database has been generated to show the SNP variation, using re-sequenced and known genomes of date palm (He et al. 2017). A density of 1 SNP per 217 bases was seen by date palm genome (Al-Dous et al. 2011). SNP peaks associated with sex-determining loci were found at linkage group (LG) 12 (Mathew et al. 2014; Hazzouri et al. 2019).

5.1.1 Organellar Genome (Chloroplast and Mitochondrial Genome) Various assembling software like CLC Genomics Workbench (CLC bio, Denmark) were used to assemble the NGS datasets from the pyrosequencing and Illumina systems of date palm chloroplast DNA (Khan et al. 2010). NOVOPlasty program was used for de novo assembly of chloroplast DNA from NGS data along with ORF Finder (http://www.ncbi. nlm.nih.gov/projects/gorf/), and Dual Organellar Genome Annotator (the DOGMA server) was employed for the annotation of chloroplast genomes (Wyman 2004; Dierckxsens et al. 2017; Rasheed et al. 2020). Also, tRNAscan-SE was carried out for annotation of some tRNAs (Lowe and Eddy 1997), and description of repeat sequences was carried out by using the REPuter program after searching for sequence similarity with annotated plastomes (Kurtz et al. 2001). Bioinformatics tools including the GenomeVx online and Gene Order tool were used for the circular genome map of date palm, and chloroplast genome and gene order were investigated (Celamkoti 2004; Conant 2008). mVISTA comparative genomics server was used for the construction of multiple sequence alignments of chloroplast genomes (Frazer et al. 2004). MEGA4 program was utilized for

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parsimony-based phylogenetic tree construction (Tamura et al. 2007). Various bioinformatics software had been used to examine and infer the date palm cp DNA sequence, and it showed a close association with the broad leaf cattail (Typha latifolia L.). The mitochondrial genomes of date palm are the circular DNAs of sizes ranging from 585,493 bp to 715,120 bp. In Phoenix dactylifera (NC016740), P. dactylifera (MH176159), and P. dactylifera cv. Naghal, the protein-coding sequence is composed of 5.35, 4.6, and 4.6% gene content, respectively. However, the noncoding region possesses only 1.8% in the unverified mitochondrial genome of P. dactylifera (MG257490). The gene content is similar among these mt genomes. In P. dactylifera (NC016740), in total 43 protein-coding genes were found.

5.1.2 Whole Genome Numerous web-based date palm databases have been constructed to map the date palm genome. Most databases available today are intended to help researchers and breeders to recognize predominant date palm cultivars by selecting highly specific polymorphic markers. These databases help researchers to search genetic variations among different date palm cultivars, thus helping in further breeding and genetic studies. The following are the databases used to map the date palm genome. Date Palm Genome Database (DRDB) DRDB was developed as a platform to help researcher and breeder in observing and recognizing different date palm varieties or cultivars using polymorphic markers using search functionalities that can be accessed freely – http://drdb.big.ac.cn/home (He et al. 2017). The database has sequenced genomic data of 62 different cultivars from different parts of the world, with 246,445 SSRs and 6,375,806 SNPs annotated in the genome assembly. Phylogenetic tree developed from these cultivars based on the geographic location shows three subclades. The database also helps in identifying and retrieving the SSR and SNP data sheets of specified cultivars, which can be customized based on requisite parameters. In addition, markers can be selected at cultivar, regional, or country level. The database also provides information associated with SNP annotation, etc. Information for external sources like UniProt is also available. The data can be accessed freely and downloaded. Plant Genome and System Biology (PGSB) PGSB is an online database comprising the databases of various plants. The date palm genome database can be accessed directly at http://pgsb.helmholtz-muenchen. de/plant/pdact/ index.jsp or https://qatar-weill.cornell.edu/ research/research-highlights/date-palm-research program. Date palm genome sequence and genome annotation is available at date palm draft sequence version 3.0. Shotgun next-generation DNA sequencing was utilized for creation of date palm genome draft assembly with an estimated genome size of ca 650 Mb. Over 3.5 million high-quality SNPs distributed among nine date palm genomes and the Khalas cv. as a reference genome is available. 90% of genes and 60% of the genome sequences including repetitive sequences and the chloroplast genome account for 381 MB of assemble sequences. Contig tables and genetics elements are placed as separate sections which can be accessed by name/id or free text methods. Information is available freely and can be

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downloaded from http://qatar-weill.cornell.edu/research/research-highlights/datepalm-researchprogram/datepalm-draft-sequence. Date Palm Molecular Markers Database (DPMMD) DPMMD contains information useful for basic and applied research that can be accessed freely at http://dpmmd. easyomics.org/index.php. DPMMD provides information of more than 3,611,400 DNA markers in addition to genetic linkage maps, KEGG pathways, DNA barcodes, and date palm markers related to articles indexed in PubMed journals. In DPMMD, a list of SSR and SNP primers is integrated from some previously published data (Al-Dous et al. 2011; Mokhtar et al. 2016) and compiled in a relational database using MySQL environment. Information of SSR markers is categorized into Genic SSR, Genic SSR-SNP, SNP markers, intergenic SSR-SNP and R-gene SSR markers, and DNA barcode. In addition, it has Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway where database 896 SSR markers were mapped to 111 pathways. DPMMD also contains the first ever constructed date palm genetic linkage maps of 1293 cM distance. NGS-Based Sequencing Gene functions and their involvement in pathways of date palm were determined by NGS-based sequencing techniques coupled with omics technologies (Safronov et al. 2017). The prospects of genetic mapping as a complementary method for the identification of QTLs related to abiotic stress have also been identified (Hazzouri et al. 2020).

5.2

Gene Annotation and Promoter Motifs

By using bioinformatics approaches, abiotic stress-responsive genes were analyzed. Bioinformatics methods were used to find the desaturases of date palm and their role in stress response (Sham and Aly 2012) and motif abundances in abiotic (heat, drought) stress-induced genes (Safronov et al. 2017). In aquaporin gene PdPIP1, two regions of date palm indicated abundant abiotic (drought and salinity) stressinducible motifs in its 2 Kb promoter region and occurrence of four groups of aquaporins in date palm genome in 40 members (Patankar et al. 2019). Phytoremediation by date palm of polluted sites to remove toxic metals especially Cd, Cu, Pd, and Cr and harmful dioxins has shown promising results (Hanano et al. 2016; Al-Najar et al. 2019; Sivarajasekar et al. 2019). Phytochelatin synthase (PdPCS1) was investigated in silico distributed in eight exons intervened by seven introns and was about 5.7 Kb long (Zayneb et al. 2017).

5.3

Gene Mapping for Trait-Linked Attributes

5.3.1 Sex-Linked Attributes Several studies were carried out to determine the sex of date palm seedlings by using markers (Heikrujam et al. 2015; Awan et al. 2017). XY sex determination pattern is seen in date palm. The sex-linked SRY region which is specific to male plants

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possesses recombination arrest mechanism. Analysis using bioinformatic tools was carried out to understand the gene, SSR, and SNP variation using transcriptomes and whole genomes of date palm (Hamweih et al. 2010; Al-Dous et al. 2011; Torres et al. 2018; Arunachalam 2021) to differentiate between sexes. The sex-determining region of the date palm having a size of approximately 6–13 Mb is present in the telomeric region of the long arm of linkage group (LG) (Mathew et al. 2014; Cherif et al. 2016; Hazzouri et al. 2019). SSR markers, SCAR marker, etc. have been developed for the identification of sexes (Billotte et al. 2004; Arunachalam 2021). The physical mapping of the genes and genomic regions on date palm LG 12 chromosome was developed by Mathew et al. (2014) to understand genomic arrangement and the evolution of sex by in silico methods (Premkrishnan and Arunachalam 2012; Thiel et al. 2003).

5.3.2 Attributes Fruit color differs in different cultivars of date palm. For example, dominant negative mutation suppresses purple color anthocyanin pigment to cause yellow peel color of the date fruit (Hazzouri et al. 2019). The pericarp color of the date fruit is determined by R2-R3-MYB transcription factor (VIR locus) virescence gene, etc. (Hazzouri et al. 2015). Similarly, change in color from purple to yellow is caused by retrotransposon insertion of 397 bp size in the exon region leading to truncation of R2-R3-MYB gene (Hazzouri et al. 2019). Deletion of copies of invertase gene can lead to changes in the content of sucrose, fructose, and glucose among cultivars (Ghnimi et al. 2017; Hazzouri et al. 2019; Malek et al. 2020).

5.4

MicroRNA Prediction

Gene expression at the posttranscriptional stage is regulated by microRNA (miRNA) molecules. An eightfold increase in galactose content in heat- and drought-stressed date palm in metabolome of date palm has been observed (Safronov et al. 2017).

5.5

Image Analysis and Molecular Structure Analysis

Fluorescence microscopy is used for phenotyping of date palm varieties like leaflet anatomy (Arinkin et al. 2014), size, and shape of the seed (Terral et al. 2012). The phytochelator synthase gene structure of date palm was predicted using the available structure of a similar gene from the cyanobacteria genus Nostoc as a template (Zayneb et al. 2017).

6

Conclusion and Prospects

Date fruit is highly nutritious compared to any other fruits. Several varieties of date fruits can be consumed which are associated with any metabolic syndrome and related diseases. Dates being a good source of antioxidants have a vital role in

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regulating human health. Hence, date fruit can be considered as a remarkable medicinal fruit due to its nutritive, bioactive, and therapeutic potentials. But there is a strong need to explore the nutra-pharmaceutical and health benefits of dates on the basis of their functional components and elucidate the mechanisms of action of such bioactives. The available genomic resources of date palm are useful for finding out bioinformatics approaches to understand the genomic variations among cultivars in different geographical regions. Availability of the whole genome sequence, organellar sequence, and genetic map of date palm have helped breeders to modify and improve various agronomic characteristics by manipulating the genome, to improve nutritional components of the fruits. The date palm genome provides scope to understand several other biological processes with unique features. Genes and markers linked to iron content in fruit in different cultivars of date palm need to be explored. Identified SNP markers till now in nuclear and organelle genomes of date palm provide potential for developing SNP chips for molecular marker-assisted selection of date palm. Molecular modeling and docking studies will improve our understanding of the gene structure, binding sites, and crucial residues. The data on the status of research by material and software used for in silico studies on date palm omics provided here can help to identify drawbacks, to further plan investigation on the nutritional value and iron content of fruits in different varieties of date palm, to develop new cultivars, and to promote the consumption and utilization of date palm worldwide in place of several staple food used at present. Acknowledgments The authors express their appreciation for the support provided by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. GRANT3173].

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Current Advances in Health-Related Compounds in Sweet Cherry (Prunus avium L.) Alejandro Calle, Ana Wu¨nsch, Jose Quero-García, and Manuel Joaquín Serradilla

Contents 1 Introduction: Sweet Cherries and Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Sugar Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Organic Acids and Total Acidity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Nitrogenous Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Phenolic Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genetics and QTL Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Sugar Content and Total Acidity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Fruit Color . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Anthocyanins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Hydroxycinnamic Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Candidate Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Sugars and Organic Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Fruit Color and Anthocyanins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Hydroxycinnamic Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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A. Calle (*) Plant and Environmental Sciences, Clemson University, Clemson, SC, USA e-mail: [email protected] A. Wünsch Centro de Investigación y Tecnología Agroalimentaria de Aragón, Zaragoza, Spain Instituto Agroalimentario de Aragón-IA2 (CITA-Universidad de Zaragoza), Zaragoza, Spain e-mail: [email protected] J. Quero-García UMR Biologie du Fruit et Pathologie, INRAE, Univ. Bordeaux, Villenave d’Ornon, France e-mail: [email protected] M. J. Serradilla Centro de Investigaciones Científicas y Tecnológicas de Extremadura (CICYTEX), Instituto Tecnológico Agroalimentario de Extremadura (INTAEX), Badajoz, Spain e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_38

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5 Gene Expression and Functional Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1172 6 Future Prospects and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1174 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1174

Abstract

Sweet cherry is a highly appreciated fruit by the consumer because of its attractiveness and flavor. But it is also a nutritious fruit and an excellent source of bioactive compounds associated with health benefits. These molecules include nitrogenous and phenolic compounds like melatonin, serotonin, anthocyanins, or hydroxycinnamic acids. Numerous studies have associated their consumption with health-related properties, such as blood pressure regulation, antiinflammatory properties, or cancer prevention. The concentration of these compounds has been evaluated in several cultivars, and a wide range of variability has been reported, which has been used as a starting point for genetic and molecular studies that have allowed identifying QTLs and candidate genes associated with bioactive compound concentration. At the same time, more recent transcriptomic and metabolomic studies are providing light into understanding their regulation and role during fruit development. Agricultural and postharvest practices are also showing useful to improve bioactive content. In this chapter, most relevant results of these works are reviewed. Keywords

Sweet cherry · Prunus avium · Bioactive compounds · Biofortification · Health

1

Introduction: Sweet Cherries and Health

Sweet cherry (Prunus avium L.) is a temperate climate fruit tree species with a high commercial value in national and international markets due to its attractive appearance, delicious taste, and rich nutritional value, which is related to the presence of vitamins, fiber, minerals, fatty acids, and sugars (Gonçalves et al. 2017; Serradilla et al. 2017). Additionally, sweet cherries contain other secondary metabolites with high biological value, like flavonoids such as anthocyanins, hydroxycinnamic and hydroxybenzoic acids, flavanones, flavonols, and flavan-3-ols (Ballistreri et al. 2013; Serradilla et al. 2016; Gonçalves et al. 2017; Martini et al. 2017). These compounds exhibit high antioxidant activity that helps in combating cell damage, reducing inflammation, and promoting overall health (McCune et al. 2011; Martini et al. 2017). Therefore, cherry consumption is linked to beneficial and healthpromoting effects (Nawirska-Olszańska et al. 2017). Specifically, sweet cherry consumption exhibits a reduced risk of gout and arthritis attacks and a reduction in gout-related pain (Singh et al. 2015). On the other hand, it also exhibits other healthrelated properties linked to blood pressure reduction, body weight control, diabetes, and the prevention of degenerative diseases like Alzheimer’s (Wu et al. 2014; Kent et al. 2016; Gonçalves et al. 2017). Additionally, the health effects of sweet cherry

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consumption and its derivatives have focused on physiological aspects related to anti-inflammatory and anticancer activities, protection against cardiovascular diseases, anti-obesity and antidiabetic activities, and neuroprotective factors (Blando and Oomah 2019). Moreover, these beneficial effects of sweet cherries are associated with the anti-inflammatory capacity shown by anthocyanins, inhibiting the production of nitric oxide and other pro-inflammatory factors, as well as improving vision, brain function, and sleep quality (Tsuda 2012; Garrido et al. 2013). Additionally, the consumption of sweet and sour cherry has been associated with regulating the sleepwake cycle, mood performance, sleepiness, and jet lag symptoms, thanks to molecules like melatonin (González-Gómez et al. 2009; Howatson et al. 2012). The use of biostimulants or elicitors, both preharvest and postharvest, with salicylic acid and its derivatives, methyl jasmonate, oxalic acid, and, recently, melatonin, has been found to increase the content of these bioactive compounds that can improve fruit quality and also bioactive capacity (Yao and Tian 2005; Giménez et al. 2014, 2015; Martínez-Esplá et al. 2014; Sharafi et al. 2021; Carrión-Antolí et al. 2022).

2

Chemical Composition

The scientific community has extensively studied the chemical composition of cherries (Usenik et al. 2008; Correia et al. 2017; Serradilla et al. 2017; Papapetros et al. 2018). Cherries are characterized by a low-calorie level (around 63.0 kcal [263.34 kJ] per 100 g), high water content (approximately 80%), and the absence of sodium (Serradilla et al. 2017; Gonçalves et al. 2017). Water content varies according to genotype and ripening stage, ranging from 75% offered by the late ripening cultivar ‘Starkrimson’ to 88% shown by the mid-season ripening cultivar ‘Sunburst’ (Gonçalves et al. 2021). Regarding inorganic matter or ash content, values from 0.44%, shown by the mid-season ripening cultivar ‘Skeena’, to 2.88%, measured by the early ripening cultivar ‘Burlat’, were reported (Gonçalves et al. 2021).

2.1

Sugar Content

One of the parameters that have the most significant influence on consumer acceptance is sweetness (Crisosto et al. 2003; Serradilla et al. 2016). This trait depends on the soluble solid content (SSC) and soluble sugars. This content is influenced not only by genotype but also by agronomic practices, climatic conditions of the production area, and even rootstock (Hrotko 2008; Usenik et al. 2010; Correia et al. 2017; Serradilla et al. 2017). A broad range of SSC has been reported in the literature depending on cultivar and geographic localization. In the northern hemisphere, this range varies from 11.9
Brix in the cultivar ‘Celeste’ to 24.5, led by the cultivar ‘Salmo’ (Girard and Kopp 1998; Gonçalves et al. 2021). Similarly, in the southern hemisphere, values ranging from 16.8 (‘Santina’) to 23.9
Brix (‘Bing’) have been described (Param and Zoffoli 2016). On the other hand, SSC tends to

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increase during fruit ripening (Serradilla et al. 2012). Cherries are characterized by different soluble sugars, such as disaccharides like sucrose, maltose, and trehalose and monosaccharides or reducing sugars like fructose, glucose, and especially D-glucose (Serradilla et al. 2017; Chen et al. 2022). In addition, other sugars, or polyols, such as sorbitol, are also present in cherries (Blando and Oomah 2019). The glucose content ranges from 6 to 10 g/100 g of fresh weight (FW), while the fructose content ranges from 4.6 to 6.7 g/100 g of FW. These values are influenced by genotype, rootstock, soil, climatic conditions, and fruit ripening stage (Serradilla et al. 2017). Like other stone fruits, the ripening process in cherries is characterized by a double sigmoid curve (Serrano et al. 2005), where three stages of development are identified. The first stage is mainly based on cell division and elongation when the fruit is entirely immature or green; the second stage is the endocarp hardening, which leads to the formation of the nucleus and fruit color appearance; the third stage is the period of exponential growth caused by cell enlargement, in which physiological and biochemical changes in sugar, organic acid, and color occur drastically (Blando and Oomah 2019; Chen et al. 2022). During this process, soluble sugars show a trend consistent with changes exhibited by SSC: an initial increase, followed by stabilization, and a further increase in the last stage of the ripening process (Chen et al. 2022). Generally, during ripening, disaccharides are cleaved into their monomers, such as glucose and fructose. The latter two tend to accumulate during fruit ripening, while sorbitol concentration does not show any significant changes at the end of ripening (Teribia et al. 2016; Serradilla et al. 2017; Chen et al. 2022). All these changes during fruit development result from the joint action of multiple metabolites and genes (Yang et al. 2021a).

2.2

Organic Acids and Total Acidity

The sweet cherry flavor is mainly defined by sweetness and sourness (Serradilla et al. 2017). Sourness is expressed as titratable acidity (TA), which depends on genotypes and ripening stages. In the sweet cherry germplasm, TA ranges from 0.48 (‘Garnet’) to 0.96%, shown by ‘4–84’ and ‘Sweetheart’ cultivars (Gonçalves et al. 2021), reaching maximum values of TA at the end of the ripening process (Teribia et al. 2016). Cherries are generally considered medium acidity fruits, with pH ranging from 3.49 to 4.5 depending on cultivars and ripening stage (Ballistreri et al. 2013; Teribia et al. 2016; Gonçalves et al. 2021). Organic acids contribute to the flavor and pH of the fruits and, therefore, their sensory characteristics (Serradilla et al. 2017; Yang et al. 2021a). Among the primary organic acids found in cherries, malic acid, a predominant acid in the Prunus genus, stands out. Malic acid concentration depends on the cultivar and varies between 300 and 1100 mg/100 g of FW (Usenik et al. 2008; Serradilla et al. 2016); thus, some cultivars are more acidic than others. The following most crucial organic acids are citric acid, with values between 5 and 300 mg/100 g of FW, and succinic acid, which varies from 4 to 32 mg/100 g of FW (Serradilla et al. 2016). Other organic acids like oxalic, fumaric, and shikimic acid

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have also been identified, showing concentrations below 8 mg/100 g of FW (Usenik et al. 2008; Serradilla et al. 2016). Like soluble sugars, malic acid content decreases at the beginning of ripening and then increases at the end of the process (Serrano et al. 2005). The balance of organic acids and sugars, defined by the SSC/TA ratio, affects cherry flavor and, consequently, customer acceptance (Crisosto et al. 2003; Serradilla et al. 2017). Gonçalves et al. (2021) found that this ratio ranged from 17.07 (‘Sweetheart’) to 32.33 (‘Starkrimson’). However, Picota-type cultivars that show peduncle excision and late ripening time, like ‘Ambrunés’, can reach values close to 40 (Serradilla et al. 2012).

2.3

Nitrogenous Compounds

Cherries have also acquired great importance because their composition contains nitrogenous compounds of great bioactive value, such as indolamines, including melatonin (N-acetyl-5-methoxytryptamine), serotonin (5-hydroxytryptamine), and its precursor, the amino acid tryptophan. Within them, melatonin, a signaling molecule that regulates a wide range of physiological processes in plants and human circadian cycles, is a relevant compound in cherries (González-Gómez et al. 2009; Carrión-Antolí et al. 2022). Both melatonin and serotonin are synthesized from the essential amino acid tryptophan via the shikimic acid pathway. Similarly to other compounds, the melatonin and serotonin content depends on the cultivar and ripening stage of the fruits. For melatonin, concentration ranged from 0.6, shown by the Picota-type cultivar ‘Pico Negro Limón’, to 22.4 ng/100 g of FW of the early ripening cultivar ‘Burlat’. Likewise, serotonin concentration ranges from 2.8 (‘Pico Negro’) to 37.6 ng/100 g of FW in ‘Ambrunés’. Regarding the impact of the ripening stage, melatonin increased during ripening, while serotonin showed a less defined behavior (González-Gómez et al. 2009).

2.4

Phenolic Compounds

In addition to nitrogenous compounds, cherries, like other fruits, have acquired great importance in recent years due to the great content of bioactive compounds of phenolic nature that present high antioxidant activity against free radicals, which are related to beneficial properties for human health (Serra et al. 2011; Chockchaisawasdee et al. 2016; Correia et al. 2017; Serradilla et al. 2017; Blando and Oomah 2019; Gonçalves et al. 2021). The content of total phenols shown by cherries varies from 44.3 to 192 mg/100 g of FW depending on cultivar, ripening stage, and soil and climatic conditions (Serradilla et al. 2016). Among phenolic compounds present in cherries, flavonoids (anthocyanins, flavonols, and flavan-3ols) and phenolic acids (hydroxycinnamic acids and hydroxybenzoic acids) are the most abundant (Fig. 1) (Serra et al. 2011; Ballistreri et al. 2013; Serradilla et al. 2017). Within phenolic acids, cherries stand out for hydroxycinnamic acids, especially neochlorogenic and p-coumaroylquinic acids, although chlorogenic and

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Fig. 1 Main phenolic compounds and indolamines present in sweet cherry fruits derived from shikimic acid (red) via different metabolic pathways

caffeoylquinic acids were detected in lower amounts (Serradilla et al. 2017). The concentration of these compounds is defined by genotype. For neochlorogenic acid, cultivars are classified based on concentration as low (4–20 mg/100 g of FW) like ‘Burlat’, ‘Lapins’, and ‘Sweetheart’; medium (20–40 mg/100 g of FW) like ‘Ferrovia’, ‘Blaze Star’, and ‘0900 Ziraat’; and high (40–128 mg/100 g of FW; ‘Bing’) (Ballistreri et al. 2013). For p-coumaroylquinic acid content, intervals from 0.77 (‘Lapins’) to 131.45 (‘Sam’) mg/100 g of FW were reported in the bibliography (Serradilla et al. 2016). Moreover, the ratio of these two primary hydroxycinnamic acids is characteristic of each genotype (Mozetič et al. 2006). Among flavonoids, cherries stand out for their high content of anthocyanins. These pigments are responsible for skin and flesh color and, therefore, for one of the most critical organoleptic characteristics that define consumer purchase (Serradilla et al. 2017; Gonçalves et al. 2021; Carrión-Antolí et al. 2022). Anthocyanins are characterized as water-soluble pigments present in the vacuole. They have a basic structure called aglycone or anthocyanidin (flavylium 2-phenyl-benzopyrylium) to which one or more sugars are attached by glycosidic bonds forming anthocyanins (Serradilla et al. 2016). The main anthocyanin identified in cherry has been cyanidin 3-O-rutinoside followed by cyanidin 3-O-ruthinoside and, in lower concentrations, peonidin 3-O-rutinoside, peonidin 3-O-glucoside, pelargonidin 3-O-rutinoside, and delphinidin 3-O-rutinoside (Serra et al. 2011; Ballistreri et al. 2013; Serradilla et al. 2017; Gonçalves et al. 2021). The cyanidin 3-O-rutinoside represents between 77% and 96% of the total anthocyanins, with light-colored cultivars showing average anthocyanin values between 2 and 47 mg/100 g of FW, while dark cherries can reach up to 297 mg/100 g of FW (Serradilla et al. 2016). Anthocyanins tend to accumulate during fruit ripening (Serrano et al. 2005; Serradilla et al. 2011). Other flavonoids present in cherries, considered as noncolored phenolic compounds, are flavonols, remarkably quercetin 3-O-rutinoside or rutin, which concentration ranges

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from 1.84 (‘Van’) to 51.97 mg/100 g of FW led by cultivar ‘Lapins’ (González-Gómez et al. 2010; Martini et al. 2017). Rutin content also increases during fruit ripening (Serradilla et al. 2011). Recently, Gonçalves et al. (2021) identified other flavonols such as quercetin 3-O-hexoside, kaempferol 3-O-rutinoside, kaempferol hexoside (3-gluc), and the kaempferol hexoside derivative 2, with concentrations strongly influenced by genotype. Other flavonoids listed as noncolored phenolic compounds are flavan-3-ols. In cherries, mainly epicatechin and catechin have been identified but also polymeric procyanidin (Blando and Oomah 2019). These represent less than 11.29% of the total noncolored compounds (Gonçalves et al. 2021), and their ratio is strongly influenced by genotype (Serra et al. 2011). Cherries are notorious for their high epicatechin content compared to catechin content, although this ratio also varies depending on the cultivar (Serra et al. 2011). Epicatechin levels range from 0.43 to 13.38 mg/100 g of FW, while catechin content ranges from 2.92 to 9.03 mg/100 g of FW (Serradilla et al. 2016). However, in the case of polymeric procyanidins, found in a few cultivars, levels of 20 mg/100 g of FW have been described, as is the case of the cultivar ‘Royal Ann’ (Chaovanalikit and Wrolstad 2004).

3

Genetics and QTL Analyses

In the last decade, several quantitative trait loci (QTLs) determining the genetic variation of the most relevant agronomic and fruit quality traits have been identified in sweet and sour cherry (Sooriyapathirana et al. 2010; Zhang et al. 2010; Dirlewanger et al. 2012; Rosyara et al. 2013; Castède et al. 2014; Quero-García et al. 2014; Campoy et al. 2015; Cai et al. 2019; Quero-García et al. 2019, 2021; Calle et al. 2020, 2021; Calle and Wünsch 2020; Branchereau et al. 2022; reviewed in Quero-García et al. 2022). Most of these works focused on physical traits like size, weight, firmness, and color (Sooriyapathirana et al. 2010; Zhang et al. 2010; Rosyara et al. 2013; Quero-García et al. 2014; Calle et al. 2020; Calle and Wünsch 2020). Despite the variation of nutritional and health-related compounds is well documented in sweet cherries during harvest and postharvest, as described above, few studies have investigated the genetics or carried QTL analyses of these compounds in sweet cherries (Quero-García et al. 2019; Calle et al. 2021).

3.1

Sugar Content and Total Acidity

Three works have focused on the genetics of sugar content and acidity in sweet cherry (Zhao et al. 2014; Quero-García et al. 2019; Calle and Wünsch 2020). These studies investigated sugar content, evaluated as SSC using a refractometer, TA, and pH (the latter only in Quero-García et al. 2019). Zhao et al. (2014) used 3-year phenotypic data from 601 pedigree-related individuals that included F1 seedlings, breeding parental and commercial cultivars in a combined way for QTL analyses. Two major QTLs were identified on linkage groups (LGs) 2 and 4, with a minor QTL on LG7 for SSC. Quero-García et al. (2019) used an F1 population

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(‘Regina’  ‘Garnet’, N ¼ 117) and 3-year data. This work identified SSC QTLs on LGs 1 and 3 by multi-year analysis, explaining from 6 to 10% of the variation. Later, in the multifamily QTL analysis conducted by Calle and Wünsch (2020), including 411 individuals from six populations of related pedigree and 2-year data, a major QTL for SSC, explaining nearly 30% of the phenotypic variation, was mapped on LG4. This QTL region overlapped with maturity and firmness QTLs on the same plant material. Also, a positive correlation among these traits was observed, with the latter maturing genotypes presenting a higher SSC value (Calle and Wünsch 2020). The results suggested the near presence of genes regulating sugar content and maturity, or genes with pleiotropic effects on these traits in this genome region (Calle and Wünsch 2020). In the same work, another minor SSC QTL was mapped on LG3, overlapping with the QTLs in the same region detected previously by Quero-García et al. (2019). For fruit acidity, high variability in QTLs detected between environmental years and populations was reported in these works, with QTLs on LGs 1, 2, 4, and 6 (Zhao et al. 2014; Quero-García et al. 2019; Calle and Wünsch 2020). Of them, only the genomic region at chromosome 6 seems stable across environments and plant materials for TA regulation in sweet cherry.

3.2

Fruit Color

Initial studies of the genetics of health-related compounds in sweet cherry were carried out indirectly by investigating fruit color. Sweet cherry color varies from yellow to mahogany or almost black, depending on the anthocyanin content profile (Gao and Mazza 1995; Jin et al. 2016; Calle et al. 2021). Fruit color was initially investigated as a relevant trait for sweet cherry breeding since different color fruits are preferred in different consumer markets (Crisosto et al. 2003). Furthermore, fruit color segregates in many breeding populations (Schmidt 1998). The cross of two red cultivars may result in blushed to dark cherries, and marker-assisted selection of this trait is desirable for breeders. By analyzing color segregation in sweet cherry progenies, the earliest studies showed that fruit skin color is determined by a major gene, in which alleles for red color are dominant to yellow or blushed (Fogle 1958; Schmidt 1998). The presence of minor genes exhibiting the epistasis effect was also proposed. More recently, research on the genetic control of skin and flesh color in sweet cherry by QTL analyses was carried out by Sooriyapathirana et al. (2010). In this work, fruit and skin color QTLs were mapped using a progeny from a cross of two cultivars with different flesh and skin color, blush-skinned and yellow-flesh ‘Emperor Francis’ and dark mahogany-skinned and red-fleshed ‘New York 54’ (Sooriyapathirana et al. 2010). The QTL analysis was conducted in 190 individuals that were phenotyped using a colorimeter, through a pseudotestcross mapping strategy of a consensus map of 198 markers (102 SSR, 61 AFLP, 28 gene-derived markers, and seven SNP; Olmstead et al. 2008). A major QTL, explaining a large percentage of the phenotypic variation for skin and

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flesh color, was identified on LG3. Also, minor QTLs were reported on LGs 6 and 8. This work confirmed that sweet cherry color was determined by a major regulatory gene (Sooriyapathirana et al. 2010). In a later study focused on deciphering the molecular mechanisms regulating fruit color, Jin et al. (2016) also mapped skin color using another sweet cherry F1 segregating population. In this population (‘Wanhongzhu’  ‘Lapins’), both parents are dark red, and a 3:1 (dark red and blush fruits) segregation was observed for the 465 hybrids, confirming the regulation model by a major gene with dominance for dark red. In this case, specific-locus amplified fragment (SPAF) markers were used, and fruit color was mapped at a narrowed QTL (70.4–70.5 cM) on LG3. More recently, Calle et al. (2021) mapped skin and flesh color QTLs using 161 individuals of an F1 population derived from the cross ‘Vic’  ‘Cristobalina’ and genotyped with the RosBREED Cherry 6 + 9 K Illumina Infinium ® SNP array (Vanderzande et al. 2020). The QTL analysis, using genetic maps of 910 (‘Vic’) and 789 (‘Cristobalina’) single nucleotide polymorphisms (SNPs) (Calle et al. 2021), also revealed a major QTL region for sweet cherry color on the same LG3 region previously reported by Sooriyapathirana et al. (2010) and Jin et al. (2016). This QTL region corresponds to chromosome 3, between 9.3–13.5 Mbp in Prunus avium v1.0.a1 (Shirasawa et al. 2017) and 11.1–15.4 Mbp of Prunus avium Tieton v1.0 genome (Wang et al. 2020). An additional minor QTL for flesh color was identified on LG4, explaining 15% of phenotypic variation when colorimeter data was used for QTL mapping (Calle et al. 2021).

3.3

Anthocyanins

QTL analyses of anthocyanin content in sweet cherry were also carried out by Calle et al. (2021) in the same work as previously reported for skin and flesh color QTLs. Anthocyanin compounds were extracted and quantified by high-performance liquid chromatography (HPLC) from 15 mature fruits of each progeny hybrid. Four anthocyanins (cyanidin 3-O-glucoside, cyanidin 3-O-rutinoside, peonidin 3-O-glucoside, and peonidin 3-O-rutinoside) were identified and quantified. The use of these data for QTL mapping revealed the most significant QTLs for the four anthocyanins on the same genomic region of chromosome 3 (Fig. 2) where fruit color had been mapped by Sooriyapathirana et al. (2010), Jin et al. (2016), and in the same population (Calle et al. 2021). The percentage of phenotypic variation explained by these QTLs ranged from 12 to 23%, and these results confirmed fruit color and anthocyanin biosynthesis have the same genetic determinants. In addition to this main QTL region on LG3, other minor anthocyanin content QTLs were also mapped on LG7 for cyanidin 3-O-glucoside, cyanidin 3-O-rutinoside, and peonidin 3-Oglucosideexplaining up to 10% of phenotypic variation and on LG4 for peonidin 3-O-rutinoside (Fig. 2) in the same region where a color QTL was also mapped in the same population (Calle et al. 2021). These results indicate that beyond a major gene in chromosome 3, other genes in chromosomes 4 and 7 also contribute, to a lesser extent, to anthocyanin content regulation in sweet cherry.

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Fig. 2 Physical position in the Prunus avium L. genome (‘Tieton’ v2.0; Wang et al. 2020) of QTLs (Sooriyapathirana et al. 2010; Jin et al. 2016; Calle et al. 2021) associated with health-related (HR) compounds identified in the species. Fruit color QTLs (qP-Color) are shown in red, anthocyanin content QTLs (qP-CyG, cyanidin 3-O-glucoside; qP-CyR, cyanidin 3-O-rutinoside; qP-PeG, peonidin 3-O-glucoside; and qP-PeR, peonidin 3-O-rutinoside) in orange, and hydroxycinnamic acid QTLs (qP-NA, neochlorogenic acid; qP-CQA, ρ-coumaroylquinic acid; qP-CA, ρ-coumaric acid) in green. Position of candidate genes associated with HR-compound biosynthesis (C3’H, coumarate 3-hydroxylase and MYB10) are also included (Sooriyapathirana et al. 2010; Calle et al. 2021). Physical position of Pav-Rf-SSR marker for fruit color prediction is also included (Sanderful et al. 2016)

3.4

Hydroxycinnamic Acids

The genetics of hydroxycinnamic acid content was also investigated in sweet cherry by Calle et al. (2021). Three compounds, neochlorogenic acid, p-coumaroylquinic acid, and p-coumaric acid, were also detected and quantified by HPLC and analyzed for QTL mapping using the same population and maps as for color and anthocyanin content in Calle et al. (2021). In this case, a major QTL was detected at the bottom region of LG1 (Fig. 2) for the three compounds (141.34–141.63 cM; 46.67–47.17 Mbp in the peach genome v2.0.a1). These QTLs were highly significant (logarithm of the odds: LOD > 20) and explained a substantial percentage of the phenotypic variation (60–78%; Calle et al. 2021). Other less significant QTLs were found on LGs 3, 4, 5, and 6. These were associated with minor variations in the concentration of these compounds (4–11% of phenotypic variation). Similarly, two additional minor QTLs for p-coumaroylquinic acid and p-coumaric acid were found on the same region of LG2

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(Fig. 2) (2.24–6.09 Mbp; peach genome v2.0.a1) (Calle et al. 2021). The results of this work showed that a major gene also regulates the concentration of these compounds and is likely located at the bottom of chromosome 1.

4

Candidate Genes

4.1

Sugars and Organic Acids

Genetic regulation of sugars and organic acids in cherries remains largely uncharacterized. Only a few studies investigated changes during fruit development related to the biosynthesis of these compounds (Beaver et al. 1995; Gao et al. 2003; Yang et al. 2021a). Initial studies in sour cherry revealed two sorbitol transporter genes (SOT1 and SOT2) that were expressed during fruit development playing a major role in sorbitol accumulation in the species (Gao et al. 2003). In a more recent study by Yang et al. (2021a), transcriptomic analysis during the fruit development period of the sweet cherry cultivar ‘Black Pearl’ revealed genes like SOT, PFK (phosphofructokinase), NINV (neutral invertase), or SUS (sucrose synthase) highly upregulated during early stages of fruit development and another set of genes like PGI (phosphoglucoisomerase), UGP (UDPG-pyrophosphorylase), PGM (phosphoglucomutase), and SPS (sucrose-phosphate synthase) upregulated during the late stage of fruit development when sucrose accumulation was enhanced. Six additional genes of the SWEET family were identified, showing different expression patterns related to sugar transports (Yang et al. 2021a). Regarding organic acids, just a few genes like PEPC (phosphoenolpyruvate carboxylase) and one MDH (malate dehydrogenase) that were downregulated during fruit development were observed to keep acid content low by decreasing malate acid during cherry development (Yang et al. 2021a). In this same study, other genes responsible for the metabolism of organic acids like GOGAT (glutamate synthase) and GDH (glutamate dehydrogenase) increased their expression during fruit development, reaching the highest transcription close to harvest time (Yang et al. 2021a).

4.2

Fruit Color and Anthocyanins

Most of the genetic and molecular studies involving health-related compounds in sweet and sour cherries focused on anthocyanin content regulation. Transcription factors (TFs) are known to be critical regulators of anthocyanin biosynthesis in cherries (Lin-Wang et al. 2010; Jin et al. 2016; Chen et al. 2022). The complexes of TFs containing an R2R3 MYB, a WD40, and a basic helix-loop-helix (bHLH) were observed in other species to promote anthocyanin accumulation through binding to genes involved in the flavonoid pathway (Allan et al. 2008). In sweet cherry, various studies indicated that the R2R3-MYB TF PavMYBA/PavMYB10 interacts with two other TFs (PavbHLH3 and PavWD40) to form an MBW complex (MYB-bHLHWD40) that regulates the expression of two key genes associated with the

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anthocyanin pathway (PavANS and PavUFGT) (Shen et al. 2014; Starkevič et al. 2015; Jin et al. 2016; Guo et al. 2018). This MYB TF (MYB10) is located at the primary color, and anthocyanin QTLs reported in sweet cherry chromosome 3 (Sooriyapathirana et al. 2010; Jin et al. 2016; Calle et al. 2021), supporting its relevance. This transcription factor was first cloned by Lin-Wang et al. (2010) in sweet and sour cherry. Based on additional expression analysis by qPCR, a clear correlation between anthocyanin content and gene expression was confirmed (Lin-Wang et al. 2010). Later works found the same correlation in the dark red cultivar ‘Hong Deng’ (Shen et al. 2014). These studies confirmed PavMYB10 as one of the key genes associated with variation in flavonoid content in the species, and it was the basis for developing a DNA test (Pav-Rf-SSR) to predict fruit color in sweet cherry (Fig. 2) (Sanderful et al. 2016). Additionally, various alleles for PavMYB10 were associated with different ranges of flavonoid accumulation and fruit coloration in sweet cherry (Sooriyapathirana et al. 2010; Jin et al. 2016). Other TFs belonging to 22 different families, specifically bZIP, C2C2-Dof, NAC, bHLH, and R2R3MYB, were also observed to mediate in anthocyanin regulation in response to light in the ‘Rainier’ cultivar (Guo et al. 2018).

4.3

Hydroxycinnamic Acids

The study by Calle et al. (2021) suggested a candidate gene for the regulation of the main hydroxycinnamic acid content in sweet cherries. The gene, ρ-coumarate 3-hydroxylase (C3H), located within LG1 QTL confidence interval identified in the same work, was considered the strongest candidate gene for hydroxycinnamic acid regulation in sweet cherry (Calle et al. 2021). This enzyme was previously observed in other species and is involved in the hydroxycinnamic acid biosynthesis pathway (Chagné et al. 2012; Kim et al. 2019). The LG1 region in which sweet cherry had the most significant QTLs for hydroxycinnamic acids was found to be syntenic to LG15 in apple (Illa et al. 2011), where also a major QTL for hydroxycinnamic acid content had been identified in apple (Chagné et al. 2012), leading to the identification of this candidate gene by Calle et al. (2021) and suggesting a common mechanism for the regulation of these phenolic acids.

5

Gene Expression and Functional Analyses

In sweet and sour cherry, strong correlations between the expression of structural and regulatory genes have been associated with health-related compound biosynthesis pathways (Lin-Wang et al. 2010; Liu et al. 2013; Shen et al. 2014; Starkevič et al. 2015; Wei et al. 2015; Guo et al. 2018). Within health-related compounds, anthocyanin biosynthesis was the widest studied in cherries. These compounds are synthesized through the flavonoid pathway (Winkel-Shirley 2001), in which most of the genes related to the regulation and biosynthesis of anthocyanins are well characterized in model plants (Allan et al. 2008). Initial studies were conducted to find candidate genes associated with anthocyanin biosynthesis in cherries by real-time PCR (RT-PCR)

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targeting some candidate genes reported in other species. Lin-Wang et al. (2010) analyzed the expression level of two genes (anthocyanidin synthase [ANS] and chalcone synthase [CHS]) potentially involved in the anthocyanin biosynthesis pathway through RT-PCR. Two cultivars, ‘Stella’ (red coloration) and ‘Rainier’ (bicolor coloration), were used for comparison of expression profiling during fruit development, in which expression of ANS and CHS genes showed upregulation correlated with anthocyanin content (Lin-Wang et al., 2010). Similarly, the expression level of six anthocyanin biosynthesis genes (ANS, CHS, chalcone isomerase [CHI], flavanone 3-hydroxylase [F3H], dihydroflavonol 4-reductase [DFR], and UDP glucose: flavonol 3-O-glucosyltransferase [UFGT]) was analyzed by RT-PCR in high-anthocyanin-content cultivars (‘Hongdeng’ and ‘Caihong’ by Liu et al. (2013); ‘Kitayanka’, ‘Irema BS’, ‘Werdersche braune’, and ‘Belobokaya rannyaya’ by Starkevič et al. (2015)). In these studies, as previously reported by Lin-Wang et al. (2010), all investigated gene expression manifested a significant correlation with anthocyanin content, in which the expression level of these genes increases through fruit development. Whole genome transcriptome analyses have complemented these findings. Wei et al. (2015) sequenced and annotated a reference transcriptome of sweet cherry to identify genes associated with anthocyanin biosynthesis. In this study, they sampled total anthocyanin content during four stages of fruit development (from 20 to 55 days after pollination) and sequenced the transcriptome of yellow (‘13–33’) and dark red (‘Tieton’) cultivars for comparison. The biological pathway analysis of these transcripts revealed 72 genes related to anthocyanin biosynthesis during fruit development, including key genes like ANS, CHS, CHI, F3H, DFR, UFGT, phenylalanine ammonia-lyase (PAL), 4-coumarate-CoA ligase (4CL), and flavanone 30 -hydroxylase (F3’H) involved in anthocyanin pathway (Wei et al. 2015). As observed in the RT-PCR studies, these genes were highly upregulated in the dark red cultivar (‘Tieton’) and downregulated in the yellow fruits of ‘13–33’ (Wei et al. 2015). Guo et al. (2018) also performed RNA sequencing (RNAseq) analysis of anthocyanin biosynthesis in sweet cherry to investigate the anthocyanin accumulation mechanism further. The transcriptomes of two contrasting cultivars, ‘Hongdeng’ (dark) and ‘Rainier’ (bicolor), were sequenced during fruit development, and as observed in previous studies in cherries (Starkevič et al. 2015; Wei et al. 2015; Shen et al. 2014; Lin-Wang et al. 2010), genes encoding enzymes like CHS, CHI, F3H, and F3’H were significantly upregulated in dark fruits. Similarly, results were reported by Yang et al. (2021b) in which weighted gene co-expression network analysis (WGCNA) indicated similar expression patterns of 4CL2 and ANS with 11 TF (bHLH13/74, DIV, ERF109/115, GATA8, GT2, GTE10, MYB308, PosF21, and WRKY7). Additionally, another set of genes related to hormone and light signaling, like protein phosphatase 2Cs, PHYTOCHROME INTERACTING FACTOR 3 (PIF3), phytochromes, and ELONGATED HYPOCOTYL 5 (HY5), were also significantly differentially expressed between dark- and light-colored fruits and therefore associated with anthocyanin biosynthesis (Guo et al. 2018). Together, gene expression analyses have shown significant differences in transcript accumulation between cultivars with high and low anthocyanin accumulation, which are especially significant in expression for UFGT and CHS (Shen et al. 2014; Starkevič et al. 2015; Wei et al. 2015).

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In addition to the genes directly involved in the anthocyanin pathway, various studies suggested that genes related to the signaling pathways of phytohormones like abscisic acid (ABA) and gibberellic acid (GA) play essential roles in the accumulation of health-related compounds (Sun et al. 2010; Jia et al. 2011; Guo et al. 2018; Chen et al. 2022). Shen et al. (2014) reported that silencing a gene (PavNCED1) essential for ABA biosynthesis (Zhang et al. 2009) blocked anthocyanin biosynthesis in sweet cherry, suggesting a complex interaction of genes regulating anthocyanin pathway beyond enzymes involved in the flavonoid pathway. In the same way, Guo et al. (2018) identified 32 genes required for plant hormone biosynthesis that were regulated in response to light exposure. In this study, differentially expressed genes related to ABA, GA, auxin, and ethylene pathways were modulated by light, being ABA and GA the only phytohormones that correlated with expression profiles of HY5 and PIF3 genes, suggesting that ABA and GA might be the main lightdependent hormones associated with anthocyanin biosynthesis (Guo et al. 2018).

6

Future Prospects and Conclusions

The works reviewed here show that sweet cherries are a health-valuable fruit, which is also highly appreciated by consumers, including children, making them an excellent source of health-related compounds. Therefore, it is important that the healthy quality of sweet cherries is known and communicated so it can be further consumed and produced. At the same time, sweet cherries are highly perishable and seasonal, which complicates their availability throughout the year and to markets far from the cultivation area. Agronomic practices, breeding, and postharvest technology research are allowing to improve these drawbacks, and sweet cherry production, quality, and availability (in time and space) have largely improved in the last years. Extensive efforts are being made in these areas, which have resulted in remarkable improvement, but it is essential not to lose the healthy qualities of sweet cherry in the way. In fact, breeding for a healthier cherry is still lacking, and a more extensive evaluation of HR compounds in sweet cherry collections would be needed. As healthy nutrition is more evident every day and society more aware of it, it is necessary to move forward to obtain a healthier fruit, if possible, or a designed fruit that can help mitigate diet deficiencies or fight specific diseases. The availability of new technologies will help to move forward in this direction. In this sense, agronomic and postharvest practices are useful in improving sweet cherries’ health qualities.

References Allan AC, Hellens RP, Laing WA (2008) MYB transcription factors that colour our fruits. Trends Plant Sci 13:99–102. https://doi.org/10.1016/j.tplants.2007.11.012 Ballistreri G, Continella A, Gentile A, Amenta M, Fabroni S, Rapisarda P (2013) Fruit quality and bioactive compounds relevant to human health of sweet cherry (Prunus avium L.) cultivars grown in Italy. Food Chem 140:630–638. https://doi.org/10.1016/j.foodchem.2012.11.024 Beaver JA, Iezzoni AF, Ramm CW (1995) Isozyme diversity in sour, sweet, and ground cherry. Theor Appl Genet 90:847–852. https://doi.org/10.1007/BF00222021

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Part V Vegetable Crops

Potato Nutraceuticals: Genomics and Biotechnology for Bio-fortification Teresa Docimo, Nunzia Scotti, Rachele Tamburino, Clizia Villano, Domenico Carputo, and Vincenzo D’Amelia

Contents 1 Potato: Introduction to an Outstanding Food Crop for Nutraceuticals . . . . . . . . . . . . . . . . . . . . 2 Nutraceutical, Metabolic, and Proteomic Repertoire in Potato Germplasm . . . . . . . . . . . . . . 2.1 Potato Nutrients: Starch, Sugars, and Lipids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Specialized Metabolites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Glycoalkaloids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Potato Proteins and Peptides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 A Glance on Potato Conventional Breeding: Mapping of Gene/QTLs . . . . . . . . . . . . . . . . . . . 4 An Overview of the Genomic/Transcriptomic Strategies to Help Nutraceutical Bio-Fortification in Potato Tubers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Mineral Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Vitamins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Specialized Metabolites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Protein Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Metabolic Engineering for Nutraceuticals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Conventional Genetic Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Targeted and Innovative Methods: Organelle Transformation and Genome/Gene Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Future Challenges for Increasing Nutraceutical Molecules in Potato . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Potato is a perfect target for bio-fortification strategies. This crop has contributed for thousand years to human diet, and its tubers still represent a staple food fundamental for worldwide food security. Besides being an important source of T. Docimo · N. Scotti · R. Tamburino · V. D’Amelia (*) Institute of Biosciences and Bioresources, National Research Council of Italy (CNR-IBBR), Portici, Italy e-mail: [email protected] C. Villano · D. Carputo Department of Agricultural Sciences, University of Naples Federico II, Portici, Italy © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_48

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energy, potato tubers contain compounds with nutraceutical properties including minerals, vitamins, proteins, and specialized metabolites. Therefore, we outlined this chapter devoting a significant space to both genomic and biotechnology studies addressed, respectively, to identify genomic sequence and genes influencing the amount nutraceutical molecules accumulated and to increment/introduce existing nutraceutical molecules or novel nutrients in the tuber. Before entering in the core of the chapter, we made an extensive introduction to the nutraceutical molecules which have been investigated in potato tubers. Then, we focused on innovative approaches, including gene editing and organelle transformation, with great potential for the nutraceutical bio-fortification of the potato. The leitmotiv of the chapter is the biodiversity of potato germplasm (including wild tuber-bearing species), which is a key aspect in potato tuber bio-fortification. The critical review of the literature suggested us to conclude pointing out the current scientific challenges for fully exploiting potato as a “vibrant feedstock for nutraceuticals.” Keywords

Tubers · Specialized metabolites · Vitamins · Minerals · Metabolic engineering · Genomic approach

1

Potato: Introduction to an Outstanding Food Crop for Nutraceuticals

The tubers of the cultivated potato (Solanum tuberosum) play a significant role in human nutrition and represent an established source of starch for the food industry. The worldwide production of potato stands 359 million tons, and its cultivation occupies 20 million hectares of farmland globally (FAOSTAT. In: FAO [online]. http://www.fao.org/faostat/). The biochemical composition of potato tubers varies according to the variety, agronomic practice, soil and climate, and storage condition. Because of the high concentration of carbohydrate in the form of starch (more than 60% of the dry matter), potato tubers are considered a rich energy providing food. One hundred grams of boiled tuber (that can correspond to a tuber of average size) provides about 110 Kcal, with less of 0.5 g of lipids (Burgos et al. 2020). However, potato is not only starch. A single tuber can also provide 50% of the recommended daily allowance of vitamin C and also balanced proteins of high biological value (i.e., the proportion of absorbed proteins which are incorporated into protein of the human body) (Burgos et al. 2020; Singh et al. 2020). The current research direction is toward valorizing the presence of important vitamins and phytochemicals (belonging to the primary and specialized metabolites) and exploiting potato proteins for several technological purposes (Hussain et al. 2021). There are numerous valuable papers and book chapters which have analyzed or reviewed the nutraceuticals and biochemical composition of potato tubers (Burgos et al. 2020 and Singh et al. 2020 just to mention the most recent). All these works emphasized potato tubers as “vibrant feedstock for nutraceuticals” (to use the words

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of Stewart and Taylor 2017), with a large biochemical variability enclosed in more than 10,000 varieties (Dolničar 2021). Polyphenols, vitamin C, vitamins of B group, and carotenoids have been particularly reviewed in these works which also underlined that many of these molecules are greatly accumulated in tuber peels, a typical by-product of food and starch industries. Another important aspect which is covered by studies dealing with potato nutraceuticals is the effect of cooking methods on these molecules (D’Amelia et al. 2022). Potatoes are not commonly consumed as fresh, and, therefore, the presence of toxic glycoalkaloids is one of the reasons why potato is needed to be cooked before consumption. Fortunately, these latter compounds are not generally stable at high temperature (D’Amelia et al. 2022); however, potato glycoalkaloids, which are especially accumulated in the peels, may even have positive function as anticancer and antiviral drugs (Hellmann et al. 2021). Many of the minerals and molecules contained in potato tubers are indeed considered nutraceuticals, whose accumulation and bio-fortification can contribute to reach the nutritional and medical or health benefits in different countries, including the prevention and treatment of disease. Potato being the world’s third most important crop in terms of human consumption, it is the perfect food crop to be enriched with functional molecules. Although the cultivated potato displays complex genetic features (a tetraploid – 2n ¼ 4x ¼ 48 – nature, a high level of heterozygosity, a tetrasomic inheritance, and a severe inbreeding depression), there have been several genomic and metabolic engineering research studies aimed at the bio-fortification of its tubers with healthy molecules. Its metabolic and proteomic repertoire has also been exploited for different industrial applications. The purpose of this chapter is to review these major researches and to identify novel cutting-edge technologies which can open new horizon of research in nutraceutical bio-fortification of potato. This first and second section of this chapter introduce to the metabolic and proteomic repertoire that characterize potato tubers from wild and cultivated species and to the genomic studies carried out to identify the regulation of nutraceutical molecules. The third section is the core of the chapter, where nuclear and organelle cis/transgenic along with next generation biotechnologies are reviewed. We concluded the chapter by providing critical perspectives on the exploitation of these technologies, underlining current challenges for potato tuber bio-fortification. We are not going to consider in detail aspects related to agronomic practices and conventional breeding approaches, which have been extensively described in the chapter of Bradshaw (2019), previously published in the book titled Improving the Nutritional Value of Potatoes by Conventional Breeding and Genetic Modification.

2

Nutraceutical, Metabolic, and Proteomic Repertoire in Potato Germplasm

Before the nineteenth century, potato was consumed mostly by Andes population, and then it was introduced to Europe to supply secure food for the large demographic growth. Today, population is expected to increase by two billion in 2050, and in view

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of higher food demand, potato is again attracting great attention as food security crop since tubers supply nutrients at lower cost than other vegetables and fruits. The scientific communities are actively involved in maximizing potatoes’ nutritional value. From a nutraceutical point of view, potato skin is rich in dietary fibers, and the flesh provides carbohydrates and several vitamins such as vitamin C (ascorbic acid), vitamin B1 (thiamine), vitamin B3 (niacin), vitamin B6 (pyridoxine), vitamin B9 (folate), riboflavin, and pantothenic acid. Moreover, a relevant presence of minerals in the tubers, such as calcium (Ca), phosphorus (P), magnesium (Mg), sodium (Na), potassium (K), chloride (Cl), sulfur (S), and iron (Fe), concurs to the whole-body homeostasis maintenance. The nutritional composition of potato tubers is summarized in Fig. 1. Tables 1 and 2 report the dietary reference values according to EFSA (European Food Safety Authority) reports (EFSA NDA Panel (EFSA Panel on Dietetic Products 2015)). An adequate macro- and micronutrient uptake is necessary for human health; indeed, insufficient intake of vitamins and minerals can affect disease resistance, cognitive development, and physical growth and can lead to serious metabolic disorders and even death. “Hidden hunger” refers to the deficiencies of multiple micronutrients in the diet, which is associated not only to poverty but also to bad dietary habits commonly due to the lack of diversification in food consumption and to diet rich in energy but poor in nutrients. By looking at the latter aspect, several programs are currently oriented toward fruit and vegetable bio-fortification, and this is also true for potato tubers (Ierna et al. 2020). Potato bio-fortification programs have been followed by the International Potato Center (CIP) for the past 15 years, by launching breeding

VITAMINS Vit C (Ascorbic acid) 19.7 mg Vit B4 (Choline) 12.1 mg Vit B3 (Niacin) 1.054 mg Vit B5 (Pantothenic acid) 0.296 mg Vit B6 (Pyridoxine) 0.295 mg Vit B1 (Thiamine) 0.08 mg Vit B2 (Riboflavin) 0.032 mg Vit B9 (Folate) 16 μg Vit E (Alpha tocopherol) 0.01 mg Vit K (Phylloquinone) 1.9 μg

Carbohydrate 17.49 g Totallipid 0.09 g Energy 77 Kcal Water 79.25 g Protein 2.05 g Dietary fiber 2.1 g Starch 15.29 g Sugar 0.82 g

Fig. 1 Nutritional composition of potatoes per 100 g1 FW

MINERALS Potassium 425 mg Phosphorus 57 mg Magnesium 23 mg Calcium 12 mg Sodium 6 mg Manganese 0.153 mg Iron 0.81 mg

Gender (adults  18 years) Both genders Both genders Both genders Both genders Both genders Both genders Both genders Both genders Both genders Male Male Female Male Female Both genders Male Female Both genders AI 40 μg/day 400 mg/day 4 μg/day NA NA NA 5 mg/day NA NA NA NA NA NA NA 15 μg/day 13 mg/day 11 mg/day 70 μg/day

AR NA NA NA 250 μg DFE/day 1.3 mg NE/MJ 1.3 mg NE/MJ NA 1.3 mg/day 0.072 mg/MJ 570 μg RE/day 1.5 mg/day 1.3 mg/day 90 mg/day 80 mg/day NA NA NA NA

PRI NA NA NA 330 μg DFE/day 1.6 mg NE/MJ 1.6 mg NE/MJ NA 1.6 mg/day 0.1 mg/MJ 750 μg RE/day 1.7 mg/day 1.6 mg/day 110 mg/day 95 mg/day NA NA NA NA

AI adequate intake, AR average requirement, PRI population reference intake, UL tolerable upper intake level

Nutrient (vitamins) Biotin Choline Cobalamin (vitamin B12) Folate Niacin Niacin Pantothenic acid Riboflavin Thiamin Vitamin A Vitamin B6 Vitamin B6 Vitamin C Vitamin C Vitamin D Vitamin E Vitamin E Vitamin K as phylloquinone

UL ND NA ND 1000 μg/day 900 mg/day nicotinamide 10 mg/day nicotinic acid ND ND ND 3000 μg RE/day 25 mg/day 25 mg/day ND ND 100 μg/day 300 mg/day 300 mg/day ND

Table 1 Dietary reference values for vitamins and minerals for the EU according to https://multimedia.efsa.europa.eu/drvs/index.htm accessed on July 25, 2022

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Chloride Copper Copper Fluoride Fluoride Iodine Iron Magnesium Magnesium Manganese Molybdenum Phosphorus

Calcium

Nutrient (minerals) Calcium

Gender (adults  18 years) Both genders 18–24 years Both genders  25 years Both genders Male Female Male Female Both genders Male Male Female Both genders Both genders Both genders NA 1.6 mg/day 1.3 mg/day 3.4 mg/day 2.9 mg/day 150 μg/day NA 350 mg/day 300 mg/day 3 mg/day 65 μg/day 550 mg/day

NA

AI NA

NA NA NA NA NA NA 6 mg/day NA NA NA NA NA

750 mg/day

AR 860 mg/day

NA NA NA NA NA NA 11 mg/day NA NA NA NA NA

950 mg/day

PRI 1000 mg/day

ND 5 mg/day 5 mg/day 7 mg/day 7 mg/day 600 μg/day ND 250 mg/day 250 mg/day ND 0.6 mg/day ND

2500 mg/day

UL 2500 mg/day

3.1 g/day

Safe and adequate intake

Table 2 Dietary reference values for minerals for EU according to https://multimedia.efsa.europa.eu/drvs/index.htm accessed on July 25, 2022

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Both genders Both genders Both genders Adults (LPI 300 mg/day) Adults (LPI 600 mg/day) Adults (LPI 900 mg/day) Male adults (LPI 1200 mg/day) Adults (LPI 300 mg/day) Female adults (LPI 600 mg/day) Adults (LPI 900 mg/day) Female Adults (LPI 1200 mg/day) NA

3500 mg/day 70 μg/day NA NA NA NA NA NA NA NA 10.2 mg/day

NA NA NA 7.5 mg/day 9.3 mg/day 11 mg/day 12.7 mg/day 6.2 mg/day 7.6 mg/day 8.9 mg/day 12.7 mg/day

NA NA NA 9.4 mg/day 11.7 mg/day 14 mg/day 16.3 mg/day 7.5 mg/day 9.3 mg/day 11 mg/day 25 mg/day

ND 300 μg/day ND 25 mg/day 25 mg/day 25 mg/day 25 mg/day 25 mg/day 25 mg/day 25 mg/day

For adults, ARs and PRIs for zinc are provided for four levels of phytate intake (LPI): 300, 600, 900, and 1200 mg/day

Zinc

Potassium Selenium Sodium Zinc Zinc Zinc Zinc Zinc Zinc Zinc 2 g/day

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Fig. 2 Examples of commercial potato varieties and Italian landraces showing variable coloration of the flesh due to the different content of anthocyanins (purple/red) and carotenoids (yellow/ orange)

programs oriented to increase the concentration of Fe and zinc (Zn), which raised almost of the doubled amount. However, the concentration of all these minerals and phytonutrients, besides being naturally different according to the varieties and agronomical practices, can be influenced by several other factors. For example, the amount of potato vitamins can be especially affected by pre- and postharvesting conditions. It should also be considered that the effective intake of potato nutraceuticals in the diet is largely influenced by their bioavailability. As matter of fact, cooking potatoes, without peeling off the skins, can guarantee a good intake of minerals and dietary fibers, but vitamins are largely reduced after cooking (Singh et al. 2020, 2022). Carotenoids and polyphenols can be considered nutraceuticals, and these molecules are noteworthy present in potato tubers. Indeed, antioxidants in foods are key players against degenerative processes, cardiovascular diseases, and aging. Besides high-quality proteins, these antioxidants have probably been among the few nutraceuticals which domestication, breeding, and selection of potatoes have been addressed to. Carotenoids and anthocyanins characterize the color of potato tuber flesh. Commercially available, there are white, yellow, red, and purple fleshed potatoes (an example is reported in Fig. 2), whose flesh color intensity mirrors the amount of “dye” antioxidants. Yellow fleshed potatoes are richer in lutein and zeaxanthin carotenoids, whereas red and purple potatoes have a notable content in anthocyanins. These varieties can be ranged among the “functional foods.”

2.1

Potato Nutrients: Starch, Sugars, and Lipids

Potato starch content is highly variable according to the genotype, environmental condition of growth, and agronomical practices. In general, fresh potatoes contain about 80% of water; 60–80% of the dry matter consists of starch. Potato starch is composed by amylopectin and amylose, with amylopectin ranging from 70% to 80% of the starch amount. The ratio between amylose (linear glucose polymers) and

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amylopectin (highly branched glucose polymers) influences the degree of digestibility of starch, since amylose-rich starches are digested more slowly as opposed to starches with a high amylopectin content. The ratio amylose/amylopectin influences the glycemic index, which is a value indicating how much a specific food affects human blood sugar level (glucose). Starch is the major storage for carbohydrates, but potatoes have also free sugars mostly represented by the monosaccharide glucose and fructose and the disaccharide sucrose. Tubers of the tetraploid potato S. tuberosum have a total sugar amount up to a maximum of 300 mg 100 g1 fresh weight (FW), while almost three times more (of about a maximum of 700 mg 100 g1 FW) have been reported in tubers of diploid S. phureja (Duarte-Delgado et al. 2016). Potato sugar content is strongly dependent on the genotype. However, pre- and postharvest factors may play a crucial role. For example, particularly important are tuber maturity, growing temperature, agricultural conditions such as soil minerals and irrigation, mechanical stresses, and storage conditions. Sugar content in potato tubers is indeed particularly important since the high temperature of baking, frying, and roasting usually employed to cook potato, although are food safety measures, can also determine the formation of toxic molecules such as acrylamide. Acrylamide formation, which is considered a potential carcinogen, is present at elevated concentrations in different types of heat-treated foods, and it is formed during cooking at high temperature as reaction products of Maillard reaction between amino acids and reducing sugars. Therefore, a high basal level of potato sugars, as acrylamide precursors, and the specific processing conditions put potato in the group of food products with the highest level of acrylamide. In order to avoid acrylamide formation (probably carcinogenic to humans), the content of reducing sugar should be maintained below a level of 100 mg 100 g1 FW (Liyanage et al. 2021). Lipids are present in a relatively low amount, in a range of 0.1–0.5 g 100 g1 FW. Phospholipids (47%), glycol, and galactolipids (22%) are the most represented. Their localization between the peel and the vascular ring of the tuber makes their content even reduced if the potatoes are thickly peeled. The composition in fatty acids of total lipids is mostly constituted of polyunsaturated fatty acids, e.g., linoleic and linolenic acids. Therefore, potato lipid composition is particularly “safe,” since it is known that omega-3 fatty acids are beneficial against cardiovascular diseases and might also reduce the risk of type 2 diabetes. Finally, potatoes contain fibers in the cell wall of the peel. These dietary components represent the portion of indigested carbohydrates which can be fermented in the large intestine. One hundred grams of potatoes cooked with the skin provide 2.1 g fiber, whereas for the same amount without skin the amount of fiber is reduced to 1.8 g. By way of comparison, potatoes contain less fiber than whole-grain cornmeal but more than white rice or whole-wheat cereal (1.6 g 100 g1).

2.2

Vitamins

Vitamins are molecules with different organic skeleton derived from various precursors. For example, vitamin C is a small soluble carbohydrate whose biosynthesis starts from glucose, and vitamin B complex belongs to pyridinecarboxylic acid

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group of compounds. These molecules are not synthesized by humans, and their intake can occur only thought the diet. Deficiency of vitamin C causes scurvy, and the common symptoms of a poor vitamin C diet are fatigue, sore legs, and arms. The recommended dietary allowance (RDA) of vitamin C, as reported in Table 2, is about 90 mg daily for men and 80 mg for women and even more in particular condition such as pregnancy and for smokers. Potato, among vegetables, is a rich and inexpensive source of vitamin C, and its average content ranges from 84 to 145 mg 100 g1 dry weight (Kawar 2016). Vitamin C content can vary according to the genotype, but the factor mostly influencing its content reduction is the oxidation. This can be caused by washing, peeling, slicing, cooking at high temperature, freezing, cooling, and storage (Sonar et al. 2020). Another important group of potato vitamins belongs to the B complex. Members of this group are vitamin B1 (thiamin), vitamin B2 (riboflavin), vitamin B3 (niacin or niacin amide), vitamin B5 (pantothenic acid), vitamin B6 (pyridoxine), vitamin B7 (biotin), vitamin B9 (folic acid), and vitamin B12 (cobalamins). The RDA for thiamin is 1.2 mg/day and 1.1 mg/day for adult man and woman, respectively, and potato varieties contain approximately 10 mg of thiamin in 100 g of tubers. Niacin can be assumed through the diet, but it can be also synthesized from the tryptophan. Its deficiency can cause pellagra, whose symptoms can be diarrhea, skin inflammation, and loss of memory (Fu et al. 2014); this disease is highly diffused among those populations relying on a maize based diet. It is estimated that potatoes can provide about one-tenth of adult’s daily requirement of niacin considering that RDA values for niacin are 14 mg/day and 16 mg/day for men and women, respectively. Vitamin B5 and B6 are present in potato with similar amount, less than 1 mg for 100 g of potato, and RDA for vitamin B5 is close to 5 mg/day for both adult men and women and for vitamin B6 is about 2.0 mg/day and 1.6 mg/day for men and women. Both vitamin B5 and B6 vitamins are resistant to cooking and high temperatures. In this group of vitamins, vitamin B9 (folate) deserves particular attention because its deficiency is becoming a global dietary issue. Folic acid deficit promotes cell oxidation processes, and it causes DNA genomic instability. For this reason, increasing dietary intake of folate is particularly important during pregnancy, and folate based food supplements are recommended to reduce the risks of congenital disabilities (Wierzejska and Wojda 2020). Potato can provide about the 1–2% of the daily RDA for folic acid, which is about 0.2 mg. Finally, K naphthoquinone is the last group of lipophilic antioxidant vitamins present in potato. Vitamin K has some essential beneficial properties deriving from its capability of blood clotting properties. Vitamin K is a group of chemically related compounds known as naphthoquinones and named vitamins K, K1, K2, and K3. One hundred grams of potatoes can contain from 1.5 to 3.0 micrograms of vitamin K, which is almost the 2–4% of the daily recommended value for an adult.

2.3

Specialized Metabolites

In industrialized countries, potato is erroneously associated to bad diet habits, mostly because of the consumption of french fries and chips. However, potato is recognized

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by the Food and Agriculture Organization of the United Nations (FAO) as a staple and sustainable food for the growing world population (http://www.fao.org/potato-2008/ en/aboutiyp/index.html, accessed on 2022). This is not only for the nutritional properties previously described but because it has a plethora of specialized metabolites whose consumption in the diet beneficially promotes human health. The high content of antioxidant compounds, mainly carotenoids and phenylpropanoids, makes tubers an optimal functional food. Carotenoids in plants are more than 700; they are isoprenoidbased compounds typically represented by a tetraterpene skeleton. The modification of this backbone influences color and antioxidant activities of tubers. Carotenoid content ranges from 2.7 to 7.4 μg g1 FW in commercial white potatoes. The highest amounts of carotenoids are present in yellow- and orange-fleshed potatoes. Zeaxanthin is the carotenoid most responsible for orange color, whereas lutein is responsible for yellow. Andean cultivated landraces have been reported to accumulate a very high content of carotenoids; the concentration of lutein/zeaxanthin may reach up to 18 μg g1 DW and about 2 μg g1 DW of β-carotene (Milczarek and Tatarowska 2018). Similarly, diploid S. stenotomum and S. phureja may contain up to 20 μg g1 FW of zeaxanthin (Brown et al. 2019). Through metabolic engineering approaches, β-carotene content in Désirée was increased in up to about 50 μg g1 DW (Diretto et al. 2007a). Although this strategy resulted very efficient to produce what is referred as “golden potato,” its consumption is limited to few European and American countries due to specific regulatory limitations and also consumer acceptance. Among antioxidants, hydroxycinnamic acids are the most abundant with chlorogenic acid (CGA) as the most accumulated. In white and yellow potatoes, CGA can constitute 90% of tuber total soluble phenolics, with 5-O-caffeoylquinic acid being the most abundant CGA. Two hundred grams of potatoes could provide over 250 mg of CGA, which is much more than the amount found in a cup of coffee (the most known source of CGA) (Lu et al. 2020). Interestingly, red and purple potatoes produce an even higher quantity of CGA than white-fleshed tuber. Tubers also contain flavonoids, including anthocyanins and flavonols. Flavonoids have a C6-C3-C6 backbone; acylation, hydroxylation, methylation, and glycosylation of this skeleton give rise to thousands of compounds. Anthocyanins are synthesized in the general flavonoid pathway, and the first committed step in the anthocyanin pathway is catalyzed by dihydroflavonol reductase (DFR). The conversion from colorless leucoanthocyanidins to anthocyanidins by anthocyanidin synthase is the coloring reaction of the biosynthetic pathway. The six major anthocyanidins in potato are cyanidin, delphinidin, malvidin, pelargonidin, peonidin, and petunidin; the degree of hydroxylation/methoxylation of the B-ring influences the color of the tuber. For example, B-ring hydroxylation increases blue color, whereas methylation can turn the tuber red. Higher hydroxylation on the B-ring positively influences the antioxidant activity.

2.4

Glycoalkaloids

Another class of important and characteristic solanaceous specialized metabolites is glycoalkaloids. These molecules, due to their toxicity, play an important defensive

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role in plants against pathogens and predators (Cárdenas et al. 2019). Main glycoalkaloids in cultivated potato are α-solanine and α-chaconine, where the latter is usually present in higher amounts than solanine (D’Amelia et al. 2022). These molecules consist of a lipophilic steroid nucleus, which is extended by two fused nitrogen-containing heterocyclic rings at one end and bound to a polar water-soluble trisaccharide at the other. The level of toxic glycoalkaloids in potatoes varies depending on the variety, growing conditions, storage and transportation, temperature, cutting, sprouting, and general exposure to any biotic or abiotic stress. Glycoalkaloids are present at high concentration in the skin of tubers, and higher concentrations are found around the potato eyes and wounded areas and in the sprouts. On average, a potato tuber can contain about 12–20 mg kg1 of glycoalkaloids, while a green and germinated tuber reaches 250–280 mg kg1. It is worth to mention that a toxic dose has been estimated at approximately 2–5 mg kg1 body weight, whereas a lethal one is around 3–6 mg kg1 of body weight (Schrenk et al. 2020).

2.5

Potato Proteins and Peptides

Potato protein content ranges from 1% to 1.5% of tuber fresh weight. Despite the low content in tubers, these proteins have high nutritional value because they are rich in essential amino acids such as lysin, threonine, tryptophan, and methionine (Kärenlampi and White 2009). Therefore, they are nutritionally superior to those of many other plants (Kärenlampi and White 2009). Potato proteins are obtained as by-products of the starch industry and are commonly divided into three groups: (i) patatin, (ii) protease inhibitors, and (iii) highmolecular-weight proteins (Kowalczewski et al. 2019). Patatin, also known as tuberin, is a 40–45 kDa glycoprotein that represents 40% of total soluble proteins (TSP) in potato tubers (Lehesranta et al. 2005). It occurs in multiple isoforms being encoded by two multigene families, and different potato varieties show distinctive patterns of putative patatin isoforms. As an example, Désirée showed nine isoforms, whereas Bintje four (Lehesranta et al. 2005). Protease inhibitors (PIs) also account for 40% of TSP and are the structurally heterogeneous group with broad range of antifungal and antimicrobial activities (Bártová et al. 2019). PIs are classified into seven different families, based on their target, structural properties, and mechanism of action: protease inhibitors I (PI-1) and II (PI-2), potato cysteine protease inhibitors (PCPI), potato aspartate protease inhibitors (PAPI), potato Kunitz-type protease inhibitor (PKPI), potato carboxypeptidase inhibitors (PCI), and other serine potato protease inhibitors (Meenu Krishnan and Murugan 2016). The third group of potato proteins consists of high-molecular-weight proteins mainly involved in starch biosynthesis that have not been fully studied. Potato proteins are gaining increasing interest in food industry applications for their well-known functional features. These include activities that are strictly linked to food processing such as emulsifying, foaming, gel forming, antifungal, antimicrobial, and antiviral properties. They also show multiple health promoting

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properties. Particularly, patatin demonstrated antioxidant and lipase activities (Wu et al. 2021). These have been associated to protection against oxidative stress in chronic degenerative disease, anticancer activity, and anti-obesity effects (Wu et al. 2021). Similarly, protease inhibitors showed anticarcinogenic activity through three main mechanisms: interfering with tumor-cell proliferation, forming hydrogen peroxide, and blocking solar ultraviolet (UV) irradiation (Sitjà-Arnau et al. 2005). Potato protease inhibitors also increased the level of the peptide cholecystokinin that increases satiety via trypsin inhibition, thus reducing food intake in humans (Komarnytsky et al. 2011). Other studies have demonstrated that peptides obtained from potato protease inhibitors positively affect serum lipids (e.g., cholesterol) through their sterol binding properties (Liyanage et al. 2010). Tuber proteins can be hydrolysate (e.g., Alcalase treatment) to produce bioactive peptides with multiple and enhanced pharmacological functions. Potato protein hydrolysate (PPH) revealed several beneficial effects: antihypertensive, through the enhanced inhibition of the angiotensin converting enzyme I (ACE); protective against hepatic and cardiac functions, through lipolytic activity; and anti-inflammatory by the activation of AMPK, a major signaling molecule controlling the pathways of hepatic metabolic homeostasis (Boudaba et al. 2018). High-quality, allergy-free, and clear activity against various disease conditions described supports the promising usage of potato proteins and peptides in novel therapeutic food products.

3

A Glance on Potato Conventional Breeding: Mapping of Gene/QTLs

As previously stated, conventional breeding approaches, addressed at improving the nutritional value of potato tubers, have been largely reported by the recent work of Bradshaw (2019). Here, we have summarized few aspects related to the limit of conventional breeding and the mapping of QTLs for potato, aspects which extend also to the bio-fortification. Most crops are polyploids and potato is among these ensuring fulfilling food demand. Due to its complex genetics, potato breeding is a heavy task. The introduction of favorable traits in potato by means of conventional breeding techniques is very laborious and time consuming. The polyploidy offers several advantages such as heterosis and gene redundancy but also produces high heterozygosity which translates in broad segregation for many traits during breeding (Bonierbale et al. 2020). Cultivated potatoes Solanum tuberosum (ssp. tuberosum) is an autotetraploid (2n ¼ 4x ¼ 48), and four homologous chromosomes are matched pairs during meiosis process. This genetic conformation results in a tetrasomic inheritance which complicates the studying of locus interactions, allelic combinations, and genetic effects, and these effects become even more complicated for quantitative (polygenic) traits such as the amount of nutritional compounds and proteins. In this context, the pyramiding of desirable alleles in a potato breeding line or population requires screening of a progeny of thousands or even million seedlings for the identification of the desirable traits into a single clonal line, thus discouraging

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progress in breeding improvements for tetraploid potatoes. In the last 10 years of the last century, various molecular markers were made available such as random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), inter simple sequence repeats (ISSR), inter-retrotransposon amplified polymorphism (IRAP), and simple sequence repeats (SSR), and lately high-throughput assays, such as single-nucleotide polymorphism (SNP) markers, have become increasingly important in genetic studies for several crops. However, in autotetraploid genetic mapping technique, such as linkage and quantitative trait locus (QTL) analysis, the genomic complexity can limit assessing correctly allelic dosage (difficulty to determine the correct allelic combination and frequency of recombination between loci), thus jeopardizing proper linkage map construction and quantitative trait loci (QTL) mapping (Bradshaw 2019). In this regard, for SNP array in polyploids, two important platforms, Illumina Infinium and Affymetrix Axiom, have been developed. The development of a potato array provided a genome-wide set of single-nucleotide polymorphism (SNP) markers which, along with the development of statistical models and suitable software, have significantly increased the power of SNP data (Hackett et al. 2017). Further, the development of Tetraploid SNP Map, a userfriendly software specifically designed to analyze SNP markers in polyploid germplasm (Hackett et al. 2017), encouraged implementation of QTL analysis with tetraploid mapping populations of potato. At present, the hybridization based SNP array and next generation sequencing (NGS) enabled the use of genotyping by sequencing (GBS) as the most popular high-throughput genotyping platforms. Table 3 reported a summary of QTL studies related to quality traits in potato carried on biparental population, selected for their allelic variation affecting the trait of interest.

Table 3 Summary of QTL mapping studies related to quality traits of potato Traits Tuber starch content (TSC) Tuber starch and tuber starch content Tuber starch Dry matter content (DMC)

Markers DArT RFLP AFLP and SSR

QTL QTL on chr 1 QTLs on chr 5, 8, 9, 10, 12

RFLP, AFLP AFLP and SSR, SNPs

Specific gravity (SG)

RFLPs, RAPDs, AFLP, and SSR AFLP and SSR AFLP and SSR RFLP, AFLP SolCAP 8 K SNP array AFLP and SSR AFLP, CAPS, SSR AFLP, SSR, and DarT

QTLs on all chromosomes QTLs on chr 2, 3, 5, and 7, 8, and 11 QTLs on chr 1, 2, 3, 5, 7, and 11 QTLs on chr 5 and 1 on chr 8 QTLs at chr 2, 3, 5, 7, and 10 QTLs on all chromosomes QTLs on chr 4, 5, 6, 10, and 11 QTL on chr 2, 6, and 12 QTLs on chr 5, 8, and 9 QTLs on chr 3 and 9

Cold induced sweetening Amylose content Sugars Glucose and fry color Skin texture Tuber flesh color Tuber carotenoids

Modified from Naeem et al. (2021) and reference therein

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Although several candidate genes and QTLs were identified, the detected QTLs represent small haplotype blocks since it is restricted only to the diversity of the two parents. To obtain more stable and reliable QTL, it is necessary to enhance mapping resolution. Currently, efforts have been started to produce diploid potato parental lines for breeding. The use of diploid based inbreed lines may open potato breeding to more sophisticated mapping population such as recombinant inbred lines (RILs), introgression lines (ILs), and multi-parent advanced generation intercross (MAGICs) populations to identify gene-trait association. In this perspective, the work of Zhang and collaborators published on Cell is a smart example of how to develop diploid potato inbred lines and vigorous F1 hybrids by using genome design approach. Surely, this approach could be also used in the future to remodel the potato nutraceutical value.

4

An Overview of the Genomic/Transcriptomic Strategies to Help Nutraceutical Bio-Fortification in Potato Tubers

The sequencing of the potato genome, together with the successive re-annotations (http://spuddb.uga.edu), allowed scientists to carry out several transcriptomic (e.g., microarray, RNA sequencing) and genomic studies (e.g., single-nucleotide polymorphism (SNP) genotyping, genome-wide association studies (GWAS), comparative genomics) that have been strategic for examining the genetic diversity of potato germplasm (among recent papers, see Tang et al. 2022; Zhang et al. 2022). The sequencing of a vast number of plant genomes allowed to perform comparative analyses of nucleotide sequences to evidence similarities and diversity between related species and uncover evolutionary relationships. Wild potatoes, for example, have been used in the past to introgress novel traits, and related genes, in the cultivated potatoes. However, these species have been used to a limited extent for improving the nutritional value of cultivated potatoes (Bradshaw 2019). It is only in recent years that breeders have considered the increment of nutraceuticals as target trait in breeding programs (e.g., https://potatoes.colostate.edu/potato-breeding/; https://potato.tamu.edu/program/); in this scenario, genomic resources provide an important contribution in identifying genes involved in the accumulation of nutraceutical molecules. As genome sequencing has revolutionized all research approaches, in this paragraph we are going to concentrate to those studies that exploited the sequence of the potato genome to identify genes (or classes of genes) with a direct/indirect effect on the accumulation in the tubers of compounds recognized as nutraceuticals.

4.1

Mineral Elements

Mineral elements are important supplements in human diet. Variability in the amounts of mineral elements is present in potato germplasm. Differences are present

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between modern varieties especially for N, P, K, S, Ca, Mg, Cu, Fe, Mn, and Zn; between Andean landraces as regards Ca, Fe, and Zn; and between tuber-bearing wild species as regards Ca (Bradshaw 2019). Though the amount of mineral elements that accumulates in potato tubers showed good heritability, bio-fortification through breeding is not sufficient to increase the concentration of certain elements, and it is needed to be complemented with fertilization strategies (Kromann et al. 2017). Moreover, with the aim to increase the content of mineral elements, it should be taken into account that a complex network of homeostasis mechanism guarantees an adequate and not toxic level of mineral elements and that an important regulation between source and sink is present. For example, Mengist and colleagues (Mengist et al. 2018) showed that the accumulation of Zn in tubers is regulated by stems and also identify a QTL controlling the correlation between Zn and Cd, the latter being toxic to humans (Mengist et al. 2018). A reverse genomic approach can be an alternative to resolve the complex network governing mineral uptake. For example, by analyzing on nucleotide sequences which encode for transporters with important function on mineral accumulation, it could be possible to identify allelic variants with a higher efficiency in increasing the mineral element concentration in tubers or to be used as candidate gene in biotechnological approaches. Twenty-three putative transporters with specific affinity for K (belonging to the family of High-Affinity Potassium transporter (HKT), Potassium Proton Antiporters (KEAs) and Proton-coupled potassium transporters (KUP/HAK/KTs), 8 genes encoding for high-affinity transporter of phosphorus (PHT1) family (Cao et al. 2020; Azeem et al. 2021), and 12 SULTR involved in sulfur transportation (Vatansever et al. 2016) have been identified in potato. Transporters with wider affinity for minerals have been also characterized. For example, 36 gene members of heavy metal ATPase (HMA) family and 21 of zinc/iron-regulated transporter-like (ZIP) gene family were systematically analyzed (He et al. 2020; Li et al. 2020). Aquaporins are also important proteins involved in the transcellular membrane transport of water and other small solutes like silicon (Si). For these transporters, 41 encoding genes have been found within the potato genome (Venkatesh et al. 2013).

4.2

Vitamins

Vitamin C, B6, and folate (vitamins B9) are the most represented vitamins in the potato tubers. These vitamins showed a very diversified concentration among varieties and wild species. Several have been the breeding efforts addressed to increase the content of vitamin C. Though the first evidence for the genetic basis of vitamin C has been reported more than 30 year ago and studies are still coming along showing the differences of concentration of this vitamin within potato germplasms, the literature regarding the identification of major loci or marker affecting vitamin C accumulation specifically in tubers is quite rare. However, there is a great interest to increase the accumulation of vitamin C in the tubers of potato, and substantial efforts have been made through biotechnological approaches

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(described later in this chapter) involving genes of the vitamin C pathway (Goo et al. 2008; Hameed et al. 2018). As regards other vitamins, the literature reviewed indicates interest of plant scientists to use genomic tools to identify loci involved in their accumulation. For example, Bali et al. (2018) identified a total of 497 significant SNPs associated with folate (vitamin B9) in a diploid segregating population developed from S. boliviense. Eighteen of these markers were directly associated with folate metabolism. The sequenced potato genome allowed also the identification of genes encoding for proteins forming the multimeric complex necessary for vitamin B6 biosynthesis. These proteins were identified in a potato cDNA library by using an Arabidopsis thaliana pyridoxal biosynthesis (PDX) protein as bait in a yeast two hybrid screening (Mooney et al. 2013). However, no studies have been carried out so far to understand differences at genomic level that are responsible for the different accumulation of vitamin B6 in tubers.

4.3

Specialized Metabolites

In the last 15 years, a high number of researches have been dedicated to identify genomic regions affecting or associated with the accumulation of carotenoids and phenylpropanoids in potato. Specific markers associated to accumulation of carotenoids tubers of potatoes have been developed by using diploid populations. SNP analyses in both diploid and tetraploid populations marked one dominant allele of beta-carotene hydroxylase 2 (CHY2) (Y locus on chr3) having a major effect in changing white into yellow flesh color. CHY2, when combined with a recessive Zeaxanthin epoxidase (zep) allele, produced orange-fleshed tubers that accumulated large amounts of zeaxanthin (Sulli et al. 2017). In another diploid population, genome-wide QTL mapping combined with expression QTL (eQTL) analyses was used to identify another major carotenoid locus on chr9 and a potential gene candidate annotated as early light inducible protein (Campbell et al. 2014). Phenylpropanoids represent probably the class of healthy compounds mostly studied in potato tubers. In particular, anthocyanins and chlorogenic acid followed by hydroxycinnamic acids and flavonols have been subjected to different genic, molecular, genomic, or transcriptomic researches (e.g., D’Amelia et al. 2018; Bao et al. 2022). Being anthocyanins visible at naked eyes, earlier genetic investigations were particularly focused on the inheritance of loci influencing the presence or absence of red and purple pigmentation of tuber skin and flesh (De Jong et al. 2004). Anthocyanin regulatory elements (mainly characterized by the complex of R2R3 MYB, bHLH, and WD40 transcription factors) activate the genes encoding for relevant enzymes of the pathway. In potato, genes having these roles have been largely characterized by genetic, transcriptomic, and genomic approaches. The utility of RNA data resides in the fact that they evidenced the structural genes differently expressed between fleshes of pigmented and white tubers or between purple- and red-fleshed tubers. Consequently, lists of genes mainly involved in anthocyanin accumulation or in anthocyanin post-biosynthetic modifications (decorations of molecules to produce the different anthocyanin fractions) have been obtained (Ahn et al. 2022).

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Compelling genomic outcomes are those which revealed noncoding RNAs showing a regulatory activity on the expression of both regulatory and structural genes. For example, a microRNA (miR828) was identified to influence the biosynthesis of anthocyanins in tuber flesh by targeting a R2R3 MYB transcription factors (Bonar et al. 2018). Another work, though carried out by using leaf materials, revealed potential long noncoding RNA (lncRNA) regulating the expression of genes encoding for important enzymes of phenylpropanoid pathway (i.e., phenylalanine ammonia lyase, flavanone 3-hydroxylase, and chalcone synthase) (Bao et al. 2022). Chlorogenic acids largely contribute to the antioxidant repertoire of potato tubers. However, genomic results on this compound came out mainly from studies conducted for investigating anthocyanins. A strong metabolic flux connection is present between anthocyanins and chlorogenic acids, and a molecular co-regulation is also hypothesized as side of anthocyanin works (Rommens et al. 2008). In recent work of Yang et al. (2021), a natural variation of the major isoform of chlorogenic acid was screened in diploid populations including 40 wild species and 374 landraces. The authors revealed the presence of 18 SNPs associated with this compound. Considering that consumers prefer white-fleshed varieties of potato rather than colored flesh (Barlagne et al. 2021), the possibility to increase the presence of this important antioxidant also in not purple/red potatoes is attractive.

4.4

Protein Content

Hereditability of total protein content is moderate, and it is a particularly complex regulated trait influenced by inter-locus interactions and environmental factors (Klaassen et al. 2019a, b). Genome sequencing coupled with transcriptomic and proteomic studies allowed to dissect the genetic architecture influencing this trait and to identify loci that can be used in breeding or biotechnology programs. Main outputs of these studies have been the identification of QTL, eQTL, and proteomic QTL (pQTL). Acharjee et al. (2018) used diploid potatoes and a proteomic approach to map pQTLs for over 300 different protein spots on every chromosome. Klaassen et al. (2019a) mapped QTLs on chromosomes 1, 3, and 5 using a biparental tetraploid population genotyped through SNPs. The QTL on chromosome 5 was then confirmed by a study which used a panel of tetraploid varieties in a GWAS (Klaassen et al. 2019b).

5

Metabolic Engineering for Nutraceuticals

Potato is among the most widely consumed vegetable in the world. Because of it is adaptability to different environments and its yielding capacity, potato plays an important role in worldwide food security. Potato tubers are rich in carbohydrates, high-value proteins, vitamins (vitamin c, above all), and also antioxidant molecules (e.g., anthocyanins and chlorogenic acid). However, the concentration of most of these compounds is often not sufficient, especially after cooking treatment, to satisfy the RDA for those populations where a diversity of diet is limited. Metabolic engineering

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approaches accelerate the bio-fortification of crop with nutraceuticals compared to conventional breeding process or when natural variation in sexually compatible germplasm is insufficient to achieve satisfactory level (Van Der Straeten et al. 2020). In this paragraph, examples of genetic engineering approaches to accelerate bio-fortification will be described. With the aim of meeting different readers’ expertise, we will introduce various concepts related to the genetic transformation (trans/intra/cisgenesis), giving also a general idea of the techniques. We will also discuss non-conventional methods (such as organelle transformation) and gene editing as alternative or emerging techniques.

5.1

Conventional Genetic Transformation

Genetic transformation consists in the targeted manipulation of specific plant characters using genes from a range of sources. Through genetic engineering techniques (named transformation techniques), foreign genetic material can be added within a plant genome. Nowadays, several transformation techniques have been tuned in potato. The most used are the DNA uptake into isolated protoplasts mediated by chemical procedures and the Agrobacterium-mediated transformation in leaf explants. The frequency of stable transformants is higher when the Agrobacterium-mediated transformation is used. It is, indeed, the most commonly used method for plant genetic engineering. The pathogenic soil bacteria Agrobacterium tumefaciens that cause crown gall disease have the ability to introduce a tumor-inducing (Ti) plasmid into the nuclear genome of infected plant cells. Biotechnologists were able to engineer the Ti plasmid introducing the gene of interest within the transfer DNA or tDNA containing a regulatory sequence (including the promoters), the gene of interest, and the selection marker gene. Various protocols based on Agrobacterium-mediated transformation available in potato and transgenic potato varieties have been approved for planting and commercialization. Potato GM varieties, approved for public uses, are listed in The International Service for the Acquisition of Agri-biotech Applications database at the Internet website www.isaaa.org. In most cases, these varieties have been withdrawn from the market because of low sales due to consumer/farmer rejection (Mi et al. 2015). For this reason, during the last decades, alternative methodologies of genetic transformation, such as cisgenesis and intragenesis, have been set up in metabolic engineering. Cis- and intragenesis are based on the exclusive use of genetic material from the same species or genetic material from closely related species capable of sexual hybridization. This is in contrast to transgenesis where one or more genes and DNA sequences can derive either from any organism or from a sexually incompatible donor plant. In detail, intragenesis and cisgenesis is a genetic transformation where genes are transferred from the same plant or a close relative plant species and any transgene, such as a selection marker gene and vector-backbone genes, is absent in the progeny. The main difference between intragenesis and cisgenesis is based on the concept that in the former methodology, the combination of genetic element through in vitro rearrangement is allowed. The topic of the use of metabolic

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engineering approaches to increase nutrients in potato tubers has been reported by (Bradshaw 2019); more recently, several metabolic engineering approaches for the enhancement of potato nutritional value have been reported (Upadhyaya and Bagri 2021). In this chapter, a number of representative transgenic and cisgenic approaches have been itemized in Table 4, detailing the origin of the gene of interest and the potato variety used for the transformation. To obtain a successful bio-fortification of potato tubers by genetic transformation, it is fundamental to select the correct promoters. Indeed, this will drive a correct spatial and temporal expression of the selected gene/s. Therefore, in Table 4, we also summarized the promoters chosen by previous researchers in potato genetic transformation experiments. Numerous studies have been addressed to increase the level of several types of carotenoids in the flesh of potato tubers, and many studies were particularly interested in the β-carotene, the precursor of vitamin A (Table 4). The earliest strategies attempted to modulate the flux of precursors through the introduction of either genes encoding for enzymes of the primary metabolism or belonging to early carotenoid biosynthetic steps. An important increment (sixfold) in β-carotene was obtained by introducing the gene encoding for the bacterial phytoene synthase (CrtB) under the control of the tuber-specific B33 promoter (Ducreux et al. 2005). However, the most successful approach was accomplished by the coordinated expression of genes isolated from Erwinia herbicola. In particular, under a tuber-specific promoter, genes encoding for the CrtB, the phytoene dehydrogenase (CrtI), and the lycopene β-cyclase (CrtY) were introduced (Diretto et al. 2007a). The authors developed the “golden tubers,” where the provitamin A β-carotene increased by 3600-fold (about 47 mg g1 of dried weight). More recently, Campbell et al. (2015) combined β-carotene ketolase (CrtW) and β-carotene hydroxylase (CrtZ) from bacteria with the Orange (Or) gene from cauliflower leading to substantial increment of the concentration of astaxanthin and also total ketocarotenoids. Or was identified from the spontaneous cauliflower orange mutant which accumulates high level of β-carotene in chromoplasts (Lu et al. 2007). Orange protein regulates carotenoid accumulation by posttranscriptionally regulating phytoene synthase, promoting the formation of chromoplast, and also preventing process of carotenoid degradation (Osorio 2019). The cauliflower Or was also overexpressed alone in potato, and the obtained transgenic tubers showed chromoplast neoformation and more than tenfold as much β-carotene as the level of non-transgenic cold-stored tubers (Lopez et al. 2008). Overall, these latter studies suggest that there is still a large possibility to further increase the total carotenoids or specific molecules in potato by combining the expression of biosynthetic genes and their regulators. Several regulatory genes of carotenoid pathway have been characterized in tomato (e.g., D’Amelia et al. 2019; Tang et al. 2022). Considering the phylogenetic relatedness between the two Solanaceae species, it is likely to have some success in the increment of carotenoid content by transgenically expressing these tomato genes in potato tubers. Vitamin E and vitamin B6 have been also successfully increased through transgenic approaches (Table 4) (Crowell et al. 2008; Bagri et al. 2018). The strategy used by Qin et al. (2011) and De Lepeleire et al. (2018) to increase the content of vitamin C and folate (vitamin B), respectively, is quite interesting to discuss. The former can

CrtW/CrtZ from Brevundimonas sp. SD212 Orange gene from B. oleracea

LCY-E from S. tuberosum cv. Désirée

CrtB, CrtI, and CrtY from E. herbicola

CrtB, CrtI, and CrtY from E. herbicola

CHY1/CHY2 from S. tuberosum cv. Désirée HPPD/HPT from A. thaliana

GTPCHI/ADCS from A. thaliana

GTPCHI/ADCS from A. thaliana

FPGS from A. thaliana and HPPK/DHPS from O. sativa DHAR from S. indicum

DHAR from S. indicum

Carotenoid

Carotenoid

Carotenoid

Carotenoid

Carotenoid

Carotenoid

Folate

Folate

Folate

Ascorbic acid

Ascorbic acid

Vitamin E

Gene/s and origin CrtB from Erwinia uredovora

Compound Carotenoid

S. tuberosum cv. Jowon

S. tuberosum cv. Jowon

S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

S. tuberosum cv. Spunta and MSE149-5Y S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

Genotype S. tuberosum cv. Désirée and S. phureja cv. Mayan Gold S. phureja cv. Mayan Gold

Table 4 Examples of genetic transformation used for nutraceutical bio-fortification of potato tubers

CaMV 35S

B33 patatin

B33 patatin

B33 patatin

GBSS

CaMV 35S

B33 patatin

B33 patatin

CaMV 35S

B33 patatin

GBSS

GBSS

Promoter B33 patatin

Methodology/ effect Transgenesis/ activation Transgenesis/ activation Transgenesis/ activation Cisgenesis/ silencing Transgenesis/ activation Transgenesis/ activation Cisgenesis/ silencing Transgenesis/ activation Transgenesis/ activation Transgenesis/ activation Transgenesis/ activation Transgenesis/ activation Transgenesis/ activation

(continued)

Goo et al. (2008)

References Ducreux et al. (2005) Campbell et al. (2015) Lopez et al. (2008) Diretto et al. (2006) Diretto et al. (2007a) Diretto et al. (2007a) Diretto et al. (2007b) Crowell et al. (2008) Blancquaert et al. (2013) Blancquaert et al. (2013) De Lepeleire et al. (2018) Goo et al. (2008)

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Gene/s and origin GLOase gene rat

DHAR gene from S. tuberosum

PDXII from A. thaliana

DGAT1 from A. thaliana and WRI1, OLEOSIN from S. indicum

CAX1 from A. thaliana

CAX1 from A. thaliana

CAX2 from A. thaliana

9-LOX

9-LOX

Compound Ascorbic acid

Ascorbic acid

Vitamin B6

Triacylglycerol

Calcium

Calcium

Calcium

Lipid

Lipid

Table 4 (continued)

S. tuberosum cv. Désirée

S. tuberosum cv. Désirée

Solanum tuberosum var Russet Norkotah Solanum tuberosum var Russet Norkotah Solanum tuberosum var Daejiree

S. tuberosum cv. Atlantic

S. tuberosum cv. Kufri chipsona

S. tuberosum cv. Favorita

Genotype S. tuberosum cv. Taedong Valley

CaMV 35S

CaMV 35S

CaMV 35S

CDc2a

CaMV 35S/B33 patatin CaMV 35S

CaMV 35S

CaMV 35S

Promoter CaMV 35S

Transgenesis/ activation Transgenesis/ activation Transgenesis/ activation Cisgenesis/ silencing Cisgenesis/ silencing

Methodology/ effect Transgenesis/ activation Cisgenesis/ activation Transgenesis/ activation Transgenesis/ activation

Göbel et al. (2003) Eschen-Lippold et al. (2007)

Kim et al. (2006)

Park et al. (2005)

Park et al. (2005)

Bagri et al. (2018) Liu et al. (2016)

References Upadhyaya et al. (2010) Qin et al. (2011)

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be considered a cisgenic approach because the authors activated the gene encoding for dehydroascorbate reductase directly in potato. Moreover, the authors found that the increment of vitamin C was reached only by overexpressing the cytosolic isoform of the enzyme and not the chloroplastic one, reminding that also the selection of the right protein with the correct motif and signal peptide is fundamental if a specific tissue expression is desired. The work of De Lepeleire et al. (2018) is a smart example of synthetic biology approach in potato. By combining Arabidopsis and rice genes encoding for mitochondrial enzymes of folate biosynthetic pathway, under the control of a specific tuber promoter, they managed to get up to 12-fold increase in folate content in mature tubers. A similar result is quite difficult to reach by exploiting the natural variation of potato folate content (De Lepeleire et al. 2018). The four most significant minerals in terms of nutrient deficiency are Fe, Zn, Si, and Ca. In the last decades, there has been an increasing interest in the development of crops tailored to provide all these limiting nutrients simultaneously. In potato, much attention has been drawn on Ca. In this context, the target genes for Ca increase in tubers are Ca2+ transporters such as calcium exchanger 1 (CAX1) and 2 (CAX2). Kim et al. (2006) induced an activation of A. thaliana CAX2 in S. tuberosum var Daejiree obtaining tubers containing 50–65% more Ca than wild-type tubers. Concerning Fe accumulation in potato, nowadays there are no studies on activation or repression of genes for Fe accumulation. Singh et al. (2022) suggested a list of candidate genes for future studies. Very few metabolic engineering researches aimed to biofortify potato tubers with specialized metabolites like anthocyanins and, generally, phenylpropanoids. Indeed, as discussed in previous paragraphs, purple potato varieties already have an important amount of anthocyanins and other phenolics like chlorogenic acids. Moreover, these compounds become quite stable at domestic cooking method (D’Amelia et al. 2022). Most of the studies on purple potatoes were conducted for the characterization of genes encoding for key enzymes of the phenylpropanoid pathway. Among the plethora of studies available, Kostyn and collaborators (Kostyn et al. 2013) were the few which tested the nutritional power of DFR-transgenic and non-transgenic S. tuberosum cv. Desiree tubers on 20 rats. Their results demonstrated the positive impact of flavonoids on lipid profile. They observed that the level of toxic glycoalkaloids (α-chaconine and α-solanine) increased for about 70% in the DFR-overexpressing tubers. As regards other compounds with nutraceutical value, there are very few studies in potato. For example, lipids (and in particular fatty acids) have been principally studied to increase tolerance to biotic and abiotic stressors. To the best of authors’ knowledge, antisense-mediated silencing of lipoxygenase isoforms has been used in S. tuberosum to increase tolerance to insects, while no studies for bio-fortification of tubers have been released (Table 4).

5.2

Targeted and Innovative Methods: Organelle Transformation and Genome/Gene Editing

Over the past decades, the expression of transgenes in the plastid genome attracted biotechnologists because it offers several potential advantages compared to the

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transformation of the nuclear genome, such as the precise integration of transgenes in the host genome by homologous recombination, the high expression levels and the biological containment of transgenes and recombinant products, the cellular compartmentalization of compounds harmful to the plant, and the possibility of co-expressing several transgenes in prokaryotic like operons. Notwithstanding the potential advantages of this technology, not all attempts have been successful. Many factors (e.g., choice of expression elements, coding region, integration sites, etc.) and parameters (e.g., host plant, growth conditions, tissue, etc.) can affect the achievement of a promising result. In most crops, the efficiency of the tissue culture, selection, and regeneration procedures is considered the most serious bottleneck to plastid transformation (Scotti et al. 2013). Another important limitation in some crops is the generally inefficient gene expression in nongreen plastids, due to deficiencies in the expression machinery of nongreen plastids compared to leaf chloroplasts (Valkov et al. 2009). The first attempts of potato plastid transformation were carried out using vectors developed for tobacco and are characterized by low transformation frequencies and low transgene expression in tubers of transplastomic plants (Thanh et al. 2005). A strong increase in plastid transformation efficiency in potato (one shoot per bombardment), comparable to those obtained with tobacco, was achieved using a combined strategy based on an optimized selection/regeneration procedure and speciesspecific vectors (Fig. 3) containing potato homologous flanking sequences and regulatory sequences to improve transgene (gfp) integration and expression in amyloplasts (Valkov et al. 2021). Although protein accumulation in amyloplasts was low, the GFP protein obtained in tubers using clpP regulatory sequences (i.e., promoter and 50 untranslated region, UTR) confirms its positive effects on transgene translation in

Fig. 3 Schematic representation of unconventional and innovative methods for metabolic engineering. (a) Improved chloroplast transformation in potato based on the use of an optimized selection/regeneration procedure and species-specific vector containing potato homologous flanking and regulatory sequences. (b) Gene editing strategy based on CRISPR/Cas9 and Agrobacterium-mediated transformation

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nongreen plastids, with clpP being one of the less downregulated genes in tubers compared to leaves (Valkov et al. 2009). To increase protein accumulation (up to 1.3% total soluble protein, TSP) in potato amyloplasts, Yu et al. (2019) developed a different regulatory approach based on a variant of the maize RNA-binding protein PPR10, which activates the expression of the plastid atpH gene by binding to a cis-element in the atpH 50 UTR increasing the translation efficiency, and a cognate binding site upstream of gfp. Attempts to increase other nutraceutical molecules by means of organelle transformation have been made in particular for specialized metabolites. Indeed, several metabolic pathways occur within the plastids producing, for example, precursors of phenylpropanoid and isoprenoids (through, respectively, the shikimate and methylerythritol 4-phosphate pathways). In tomato, a closely related potato species, Lu et al. (2013) obtained an increase of up to tenfold in vitamin E by including, in the synthetic operon construct, a binding site for an RNA-binding protein from the pentatricopeptide repeat (PPR) family (the intercistronic expression element, IEE). Methods for organelle transformation are not of recent origin, but these can be considered more unconventional than nuclear transgenesis and with a great potential for metabolic engineering of potato. The above reported results suggest that the use of these regulatory sequences may be sufficient to manipulate the expression of enzymatic proteins for metabolic engineering purposes in order to biofortify potato tubers. More innovative for plant is the genome editing. A group of advanced biotechnological tools are becoming very useful for targeted mutagenesis. These tools can be fully exploited in crop also to improve the production of nutraceuticals through gene knockout or by modifying nucleotide sequences (Hameed et al. 2018). Among these technologies, today, much attention is being paid to the RNA-guided nuclease clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas), which is handier technology than to previous methods of editing such as zinc finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs). The CRISPR/Cas system has two main components, the single guide RNA (sgRNA) and the endonuclease Cas. The former is complementary to the target DNA sequence that must be immediately followed by an adjacent protospacer motif recognized by the Cas protein. Once the CRISPR/Cas system recognizes the target DNA, Cas generates a double-stranded break that can be repaired by the nonhomologous end-joining (NHEJ) or by the homology-directed recombination (HDR). In particular, NHEJ causes random mutations, while HDR can introduce specific mutations with the help of an additionally provided donor DNA carrying the desired mutation (reviewed by Gonzalez-Salinas et al. 2022). There are few examples of applications of CRISPR/Cas-mediated mutagenesis, and in general of the gene editing approach, addressed to positively impact the nutraceutical potential of potato tubers. Recent studies have been mainly focused to improve the efficiency of these technologies in potato. The gene GBSSI, encoding for granule bond starch synthase I enzyme, has been particularly targeted to assess the technology. GBSSI is a single copy gene and its knockout produces an easily identifiable phenotype (amylose-free starch). From the nutraceutical point of view, the low value of amylose/amylopectin ratio caused by the de-functionalization of GBSSI is not a desirable trait since it is associated with a higher glycemic index of the starch. In this regard, results obtained by the CRISPR/Cas9 editing approach of Tuncel

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et al. (2019) can be considered of nutraceutical interest since the authors managed to edit the gene SBE (Y08786) that, opposite to GBBSI, is responsible for amylopectin formation in tubers and consequently produces an increment of the amylose/amylopectin ratio. Zheng et al. (2021) mutated the sterol side chain reductase 2 encoding gene (SSR2) obtaining a reduction of more than half of the content of toxic steroidal glycoalkaloids accumulated in the peel and the tubers of wild-type potato. Several works have fixed important technical features that will allow to perform efficient CRISPR/Cas-mediated mutagenesis in potato. A doubling in editing frequency of regenerated potato plants has been reached by using endogenous potato U6 promoter, driving the expression of RNA guides, rather than the standard Arabidopsis one (Andersson et al. 2017). By using the endogenous promoter to drive CRISPR/Cas components, mutation in all four alleles for 35% tetraploid ex plants was also observed (Johansen et al. 2019). Indeed, the chance to get mutation in all four alleles during the first edited generation is fundamental to reduce or even avoid selfing or backcrossing which is more complicated in tetraploid potato. Furthermore, crossings are also needed to eliminate vector cassette containing both nuclease and the sgRNA. A successful alternative approach consists in the delivering of CRISPR/Cas9 as ribonucleoproteins (RNPs) into cells, with the added potential of generating transgene-free targeted genome edits efficiently (Woo et al. 2015). Indeed, RNPs are more specific than vectors delivering CRISPR/Cas and act more rapidly because they do not need intracellular transcription and translation. A clear reduction in off-target mutations has also widely been demonstrated. Among all, González et al. (2020) developed potato varieties with reduced enzymatic browning in tubers by the specific RNP-based editing of a single member of the StPPO gene family (polyphenol oxidases). Their selected edited lines displayed mutations only in the StPPO2 gene (U22921.1), with no alteration in the coding sequences of other members of the StPPO gene family. Another peculiar strength of RNP-based editing is the avoidance of transgene integration in the cellular genome, which reduces the regulatory burden in some countries and allows the edited plants to be labeled as “GMO-free.” But “all that is gold does not glitter”! The weaknesses of RNP-based editing are the protoplast transformation methods, which are laborious and require expensive enzymes, and the onset somaclonal variations in edited plants due to much longer culture periods. However, in comparison with the protoplast method, the Agrobacterium system (used for CRISPR/Cas vector delivering) is less expensive and needs shorter time frame for regenerant production, reducing the occurrence of somaclonal variations. For this reason, the scientific community is moving forward a CRISPR/Cas variant with reduced DNA cleavage off-targets such as the SuperFi-Cas9 (Bravo et al. 2022).

6

Future Challenges for Increasing Nutraceutical Molecules in Potato

Potato is a perfect candidate for nutrient bio-fortification. The literature reviewed showed that there has been great deal of interest in characterizing the variability of the biochemical composition of potato tubers, but genomic and biotechnological

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studies dedicated to biofortify potato tubers are still limited compared to other relative species. For example, relatively few genome-wide studies have been dedicated to identify and characterize structural variants of genes associated to the production of specific metabolites, and most of these concern with the anthocyanin biosynthesis. Association between genomic variants and amount of minerals, vitamins, or carotenoids is still rare, limiting the development of specific markers to improve the content of these compounds by classical breeding approaches. Biotechnological reports (i.e., metabolic engineering approaches) are also relatively few. In our opinion, there are three main challenges that should be considered when developing new breeding programs addressed to potato bio-fortification: • A considerable increment of nutraceuticals is needed for potato, compared to fresh consumed vegetables, to counterbalance the reduction caused by heat treatments. Potato tubers need to be cooked before consumption, and cooking methods may degrade phytochemicals with nutraceutical properties. There are different studies that checked the stability of these phytochemicals in tuber skin and flesh after different domestic cooking methods (D’Amelia et al. 2022). Anthocyanins and chlorogenic acids have been reported to be stable, while other compounds, such as vitamins (vitamin C and folate) and flavonols, showed a consistent reduction in the total amount (Stewart and Taylor 2017). The storage of tubers may also lead to the reduction of instable compounds. Therefore, another challenge in the field of tuber bio-fortification regards the possibility to drive post-biosynthetic modification of main molecules to stabilize them over time. For example, it is known that hydroxylation negatively influences anthocyanin stability; instead, methoxylation/acylation positively affects stability. • There are several side effects evaluated in the bio-fortification of the tuber flesh. For example, a high tendency of tuber flesh with improved CGA to browning during cutting and cooking because of CGA oxidation has been observed (Ali et al. 2016). It has also been observed that the level of toxic glycoalkaloids (α-chaconine and α-solanine) increased by about 70%, along with anthocyanins, in the DFR-overexpressing tubers (Kostyn et al. 2013). Hence, an accurate selection of the promoter, besides genes and relative alleles, is important to drive a well-balanced expression. • The tetraploid genetic asset of the cultivated potato S. tuberosum is an aspect which discourages breeders and biotechnologists working in the field of food bio-fortification. The tetrasomic inheritance makes genetic studies and breeding programs addressed to introduce new traits quite complicated and time consuming compared to those of a diploid plant. There are also additional noteworthy constraints. In fact, depending on gene-centromere distance, alternative segregation patterns in the gametes are possible. Besides normal chromosome segregation, the possibility exists that portions of two sister chromatids merge in the same gamete. This occurs when recombination happens between a locus and the centromere. Due to this phenomenon (called double reduction), a triplex AAAa individual can produce aa gametes, with a frequency proportional to the distance between the locus and the centromere. In addition, as any clonal crop, the

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cultivated potato is highly heterozygous, and homozygous genotypes are difficult to obtain upon selfing due to inbreeding depression. The recent development of self-compatible diploid potatoes makes it possible to obtain homozygous parental lines to use in creating F1 hybrid diploid potatoes (Zhang et al. 2021).

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Tomato: Genetics, Genomics, and Breeding of Health-Related Traits Ibrahim C¸elik, Nergiz Gu¨rbu¨z C¸olak, Sami Doğanlar, and Anne Frary

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Agricultural Importance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Nutritional Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Importance in the Face of Chronic Diseases and Malnutrition . . . . . . . . . . . . . . . . . . . . 1.4 Limitations of Conventional Breeding and Rationale for Alternative Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Description of Nutritional Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Chemical Composition, Structures, and Biochemical Pathways . . . . . . . . . . . . . . . . . . . 2.2 Medicinal and Physiological Properties in Relation to Human Health . . . . . . . . . . . . 2.3 Methods of Nutraceutical Improvement: Agronomic and Postharvest Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Requirement for Biotechnological Intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genetic Resources of Tomato . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Section Lycopersicon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Section Lycopersicoides . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Germplasm Collections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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I. Çelik Department of Agricultural and Livestock Production, Çal Vocational School of Higher Education, Pamukkale University, Denizli, Turkey e-mail: [email protected] N. Gürbüz Çolak Plant Science and Technology Application and Research Center, Izmir Institute of Technology, Urla, Turkey e-mail: [email protected] S. Doğanlar (*) Plant Science and Technology Application and Research Center, Izmir Institute of Technology, Urla, Turkey Department of Molecular Biology and Genetics, Izmir Institute of Technology, Urla, Turkey e-mail: [email protected] A. Frary Department of Molecular Biology and Genetics, Izmir Institute of Technology, Urla, Turkey e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_49

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4 Traditional Breeding and Classical Genetics of HR Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Breeding Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Phenotype-Based Diversity Analysis of HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Protein and Crude Fiber Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Carotenoid Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Phenolic Compounds and Total Antioxidant Activity Diversity . . . . . . . . . . . . . . . . . . . 5.4 Vitamin Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Polyamine Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 GABA Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.7 Glycoalkaloid Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.8 Other HR Compound Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.9 Molecular Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Brief Account of Molecular Mapping of HR Genes and QTLs . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Genomic Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Transcriptomic Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 Limitations in Studies to Date . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Marker-Assisted Breeding for HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Map-Based Cloning of HR Genes/QTLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Carotenoid Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Ascorbic Acid Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Glycoalkaloid Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Editing of HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Carotenoid Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Vitamin Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Other Compounds: GABA, Glycoalkaloid, and Anthocyanin Contents . . . . . . . . . . 10 Genetic Engineering of HR Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1 Carotenoid Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Flavonoid Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Ascorbic Acid Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.4 Polyamine Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 GABA Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 Glycoalkaloid Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.7 Anthocyanin Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Bioinformatics as a Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Future Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 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References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Tomato (Solanum lycopersicum) is a popular crop due to its versatility and nutritional quality. In addition to its nutritional content, tomato is rich in various phytochemicals that are known to have beneficial effects on human health. These bioactive components include pigments like lycopene and β-carotene, ascorbic acid (vitamin C), phenolic compounds, polyamines, and glycoalkaloids. Tomato metabolites have various bioactivities such as antihypertensive, antioxidant, anticancer, anti-inflammatory, antidiabetic, antiallergenic, antiatherogenic, antithrombotic, and antimicrobial effects. Research aimed at improving tomato for many of these specific activities is still in its infancy; however, a foundation of knowledge has been established for health-related (HR) traits in the crop. In this chapter, previous works surveying tomato germplasm for HR traits, conventional breeding, and genetic investigation of these characteristics are described. We also

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discuss research aimed at HR gene mapping and isolation as well as efforts to improve these traits via genetic engineering and genome editing. Keywords

Antioxidants · Ascorbic acid · β-carotene · Glycoalkaloids · Lycopene · Phytochemicals · Solanum lycopersicum

1

Introduction

1.1

Agricultural Importance

Tomato (Solanum lycopersicum) is in the Solanaceae family which includes potato, eggplant, and pepper. Cultivated tomato evolved from an ancestor with small green tomatoes and its domestication began in Mexico (Peralta and Spooner 2007). Today, the crop is cultivated worldwide because of its versatility, nutritional quality, and economic importance (Kim et al. 2021). Tomato is grown in the field and greenhouse with different cultivars grown for processing and fresh consumption (Campos et al. 2021). Cultivars vary widely for shape, size, and color (Fig. 1). According to Food and Agriculture Organization (FAO) statistics, the annual global production of tomatoes was approximately 187 million tons in 2020 (https://www.fao.org/ faostat/en/#data). Tomato is an important part of the diet and is one of the most consumed vegetable crops worldwide. It is used fresh or processed as sauce, soup, juice, or paste (Ali et al. 2020).

Fig. 1 Example of the wide array of phenotypic diversity available in cultivated tomato. Color, size, and shape variation have been associated with some HR traits. (Photo credit: Mehmet Ülger, MULTI Tarim Seed Co.)

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For many years, the improvement of agronomic traits, especially yield, was the main focus of tomato breeding. For this reason, breeding programs often concentrated on development of disease-resistant cultivars (Kim et al. 2021). However, yield gains are often associated with decreased fruit quality (Goff and Klee 2006). More recently, quality traits such as color, flavor, and nutritional quality have become popular breeding targets due to consumer demand and the knowledge that fruits and vegetables make significant contributions to human health (Kusano and Fukushima 2013). Although consumer demands are constantly changing, most people want to consume more nutritious products that also contribute to better health and well-being. This increased interest in health-related (HR) traits in tomato has galvanized the scientific community to gain a greater understanding of the underlying genetic factors and metabolic pathways that control HR traits. Tomato is a model species for scientific research due to its moderate genome size (950 Mb), diploidy, self-fertility, ease of manipulation, growth under different cultivation conditions, and relatively short life cycle (Kim et al. 2014; Campos et al. 2021). Moreover, the tomato genome has been sequenced and re-sequenced and these data are available online (https://solgenomics.net/).

1.2

Nutritional Composition

A balanced diet consists of certain amounts of vitamins, minerals, proteins, and fats, many of which are found in plants (Ali et al. 2020). In addition, plants are rich in bioactive phytochemicals which have been used to treat or prevent several human diseases (Rao 2003; Giampieri and Battino 2020). Tomato is a good source for the human diet because it is rich in both nutritional and bioactive compounds (Table 1). The nutritional content of tomato mainly consists of a critical amount of soluble and insoluble dietary fibers, carotenoids, phenolic acids, vitamins, proteins, minerals, essential and other amino acids, and fatty acids including monounsaturated fatty acids (Delzenne et al. 2020; Merenkova et al. 2020; Ali et al. 2020). In addition to these nutritional compounds, tomato organs including the fruit contain alkaloids which are antinutritional bioactive compounds (Chaudhary et al. 2018). Tomatoes are considered part of a healthy diet because they contain low fat and cholesterol and harbor significant amounts of specific HR compounds such as lycopene, β-carotene, certain phenolic acids, vitamins C and A, folate, and potassium (Tan et al. 2010). The presence of these HR compounds makes tomato a good source of protection against some diseases such as blindness, respiratory disorders, cardiovascular diseases, and some forms of cancers (Chaudhary et al. 2018). These phytochemicals can also help prevent mutations in DNA and have anti-inflammatory, antimicrobial, and other beneficial activities. The content of tomato fruit is not constant and varies with many factors like variety, growth conditions, developmental and ripening stage, environmental conditions, and post-harvest and storage conditions (Hall et al. 2008; Manganaris et al. 2018; Boz and Sand 2020). For instance, water-soluble antioxidant activity is high when the fruit are green and decreases when the fruit are ripe, while lipid-soluble antioxidant activity, which is mostly related to lycopene content, increases at the red ripe stage (Cano et al. 2003). Lutein is found at high levels at the red stage but not when fruit are unripe

Tomato: Genetics, Genomics, and Breeding of Health-Related Traits Table 1 Nutritional composition of 100 g raw, red, ripe tomatoes (USDA FoodData Central)

Compound Proximates Water Energy Protein Total lipids Ash Carbohydrates Dietary fiber, total Sugars, total Minerals Calcium Iron Magnesium Phosphorus Potassium Sodium Zinc Copper Manganese Fluoride Vitamins Ascorbic acid, total Thiamin Riboflavin Niacin Pantothenic acid Vitamin B6 Folate, total Choline, total Betaine Vitamin A, RAE β-carotene α-carotene Lycopene Lutein þ zeaxanthin Vitamin E Vitamin K (phylloquinone) Lipids Fatty acids, total saturated Fatty acids, total monounsaturated Fatty acids, total polyunsaturated

1221 Amount 94.5 g 18 kcal, 74 kJ 0.88 g 0.2 g 0.5 g 3.89 g 1.2 g 2.63 g 10 mg 0.27 mg 11 mg 24 mg 237 mg 5 mg 0.17 mg 0.059 mg 0.114 mg 2.3 μg 13.7 mg 0.037 mg 0.019 mg 0.594 mg 0.089 mg 0.08 mg 15 μg 6.7 mg 0.1 mg 42 μg 449 μg 101 μg 2570 μg 123 μg 0.54 mg 7.9 μg 0.028 g 0.031 g 0.083 g

(Chaudhary et al. 2018). Phenolic acid content increases during the early stages of ripening but decreases after the pink stage (Nour et al. 2014) and is negatively affected by solar UV radiation (Sharma et al. 2018). Phenolic acid, vitamin, and glycoalkaloid

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contents are also affected by the type of cultivar (Chaudhary et al. 2018). Moreover, bioavailability and the levels of tomato constituents, such as lycopene, can be altered by processing such as cooking. However, genetic architecture or genotype is the major factor determining HR trait variation within species (Manganaris et al. 2018). Improvement of the nutritional and HR composition of tomato is complex because these traits are under polygenic control, have quantitative inheritance, and are affected by environmental conditions (Fernie et al. 2006).

1.3

Importance in the Face of Chronic Diseases and Malnutrition

The world’s human population is predicted to reach more than nine billion within 30 years (Gerten et al. 2020). Rapid population growth causes hunger and malnutrition. According to a 2019 FAO report on food security, one in every ten people suffers from malnutrition (FAO 2019). In order to cope with malnutrition, it is not enough to increase agricultural production. The nutritional content of crops and dietary diversity must also be improved (Manganaris et al. 2018). These factors also affect disease incidence because it is well known that malnutrition and diseases (e.g., cancer, cardiovascular problems, blindness) are closely related (Baldermann et al. 2016). Poor nutrition can also result in increased body mass index which is a causal factor of diseases like obesity and type 2 diabetes (Trujillo et al. 2006). Therefore, a balanced, diverse, and healthy diet may prevent many diseases. Examination of the effects of nutrition and diet on human health has gained popularity in recent years (Campestrini et al. 2019). Although it is known that nutrients affect gene expression in humans, most chronic diseases are controlled by more than one gene, and the exact mechanisms are not known (Hall et al. 2008). However, it is clear that maintaining cell and organ homeostasis is related to maintaining human health. Bioactive compounds support human health by helping to maintain this homeostasis. Plants are especially valuable sources of metabolites and contain more than 200,000 compounds with huge structural diversity (Hall et al. 2008). Many of these metabolites are associated with the prevention of various diseases. In the last decade, the nutrient and bioactive compound content of tomato has been extensively studied. It has been discovered that tomato metabolites have various bioactivities such as antihypertensive, antioxidant, anticancer, anti-inflammatory, antidiabetic, antiallergenic, antiatherogenic, antithrombotic, antimicrobial, vasodilator, and neuro and cardioprotective effects (Ramos-Bueno et al. 2017; Ali et al. 2020). Regular and adequate consumption of tomatoes is reported to prevent certain human diseases and increase lipid peroxidation levels (Ilahy et al. 2016).

1.4

Limitations of Conventional Breeding and Rationale for Alternative Approaches

Conventional plant breeding relies on selecting useful agronomic traits based on phenotype (Phan and Sim 2017). Germplasm is screened for the desired traits, and

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selected parental lines are crossed to combine these traits in a new genotype (Ishitani et al. 2004). In this method, selection of parents and progenies is mainly according to their appearance/morphology. The progeny carries genes/traits from each parent, but their effects on phenotype may not be detected until the plant is grown and the crop harvested. The main disadvantages of conventional breeding are its intensive use of labor and time and the ineffectiveness of subjective phenotyping for many traits (Moose and Mumm 2008). Despite these disadvantages, conventional breeding has been very successful in improving yield, some quality parameters, and stress resistance in tomato (Dalal et al. 2006). In addition, compared to other approaches, conventional breeding is more acceptable to consumers because it seems more natural. On the other hand, genotype-based selection and breeding are more precise, rapid, and cost-effective than conventional breeding (Yang et al. 2016). Next-generation sequencing (NGS) platforms provide high-throughput and cost-effective DNA sequencing which allows identifying the relationship between genotypic and phenotypic variation (Barabaschi et al. 2016). In this context, whole genome sequencing and re-sequencing techniques are being used to breed new crop cultivars that are rich in nutritional compounds (Phan and Sim 2017). Re-sequencing of different varieties helps to identify single nucleotide polymorphisms (SNPs) which enable genome-wide association studies (GWAS). Thus, quantitative trait loci (QTLs) can be identified with virtually no limitation on marker availability and can be used in marker-assisted selection (MAS) studies (Barabaschi et al. 2012, 2016; Phan and Sim 2017). MAS provides some advantages over conventional breeding methods. MAS is relatively cheap and rapid, can be applied at seedling stages, and is independent of environmental influences (Collard and Mackill 2008). Moreover, the availability of genome sequence information provides thousands of markers for genomic selection, allows analysis of genetic diversity, and enables site-specific mutagenesis by genome editing (Barabaschi et al. 2016; Phan and Sim 2017). The integration of NGS technologies and other multidisciplinary platforms should accelerate crop improvement and allow the manipulation of more complex traits.

2

Description of Nutritional Compounds

2.1

Chemical Composition, Structures, and Biochemical Pathways

Tomato is rich in nutritional and bioactive compounds. In addition to its proximate composition, the main nutritional and medicinal components found in tomato are carotenoids, phenolic acids, vitamins, polyamines, GABA, and glycoalkaloids. The composition and concentrations of those compounds in tomatoes vary depending on many factors such as the tomato variety/cultivar, part of the fruit (peel, flesh, seed), extraction process, analytical approaches, and environmental conditions (Ali et al. 2020; Lu et al. 2019) as described in Sect. 5.

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2.1.1

Proximate Composition, Dietary Fiber, Minerals, and Amino Acids The proximate constituents of tomato are protein, fat, moisture, ash, and carbohydrates. Proximates and dietary fiber are especially important for determining quality parameters and regulatory processes in the food industry (Thangaraj 2016). Proteins are important biological macromolecules with different cellular functions, and their analysis is important for nutritional labeling in foods (Ali et al. 2020). Protein is mostly found in tomato seeds with only 0.88 g/100 g serving in ripe fruit (Table 1, USDA FoodData Central 2019). Tomato also has very little total lipids and ash. Moisture content of ripe fruit is 94.5% with 3.89 g of carbohydrates/100 g serving. Fiber consists of carbohydrates (oligosaccharides, polysaccharides, and lignins) that are digested in the large intestine. Tomato is reported to have lower crude fiber content than other popular vegetables (e.g., sweet pepper, cabbage, lettuce, spinach, and potato), with approximately 0.3 g fiber/100 g dry weight (DW) or 1.2 g/100 g fresh weight (FW) (Hanif et al. 2006; USDA FoodData Central 2019). Dietary fiber is mainly found in tomato peel (Elbadrawy and Sello 2016). According to recent reviews, the dietary fiber content of tomato peel varies between 1.32 g and 88.53 g/ 100 g DW (Lu et al. 2019; Ali et al. 2020). According to USDA data, ripe tomato fruits contain ten different minerals (USDA FoodData Central, Table 1). Tomatoes are considered to be good sources of potassium, phosphorus, and calcium. They also contain 18 different amino acids including those that humans must obtain through diet. The only amino acids not present in tomato are asparagine and glutamine. 2.1.2 Carotenoids Carotenoids are polyphenolic pigments found in the plastid membranes of leaves, flowers, and fruits. They are produced by the isoprenoid biosynthetic pathway (Martí et al. 2016). Several carotenoids are found in tomato including lycopene, β-carotene, α-carotene, γ-carotene, δ-carotene, phytoene, and lutein (Chaudhary et al. 2018). Carotenoid structures vary in terms of the presence of oxygen atoms and end group cyclization (Rao and Rao 2007). Lycopene is the immediate precursor of β-carotene with lycopene β-cyclase catalyzing this conversion. Thus, red-fruited cultivars have lower activity of this enzyme than orange-fruited ones. Carotenoids are one of the most important compounds found in tomatoes due to their contribution to tomato’s antioxidant capacity. Among carotenoids, lycopene is the most abundant carotenoid with β-carotene, also known as provitamin A, ranking second (Ilahy et al. 2017). Red tomatoes have predominantly lycopene (Kabelka et al. 2004), while orange tomatoes have mainly β-carotene (Manoharan et al. 2017). Thus, the red-fruited S. pimpinellifolium contains lycopene at high levels (Sharma et al. 2008), and the orange-colored wild relative, S. cheesmaniae, contains β-carotene at high levels (Stommel 2005). Tomato provides almost 85% of the lycopene consumed in the human diet (Rao and Rao 2007). Lycopene content increases with ripening and is found at the highest levels when ripe (Boz and Sand 2020). This increase is primarily the result of increased phytoene synthase-1 enzyme activity which catalyzes the first step of lycopene synthesis (Fraser et al. 1999).

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Other carotenoids occur at low concentrations and include lutein and zeaxanthin (Raiola et al. 2014). Although the USDA database indicates that 100 g ripe tomato contains 2.57 and 0.45 mg of lycopene and β-carotene, respectively, a recent review reported that lycopene content varied from 7.8 to 18.1 mg and β-carotene content varied from 0.1 to 1.2 mg (Table 1, Martí et al. 2016). In another review, Ali et al. (2020) reported values of lycopene content from 5.0 to 11.1 mg/100 g and β-carotene content from 3.7 to 10.2 mg/100 g.

2.1.3 Phenolic Compounds Phenolic compounds are secondary metabolites that are common in plants and are produced via the shikimate, pentose phosphate, and phenylpropanoid pathways (Lattanzio 2013; Lin et al. 2016). All phenolic compounds have at least one benzene with attached hydroxyl groups in their structure. Phenolic acids have one aromatic ring and include caffeic, ferulic, and chlorogenic acids. Polyphenols have more than one ring and include carotenoids, flavonoids, anthocyanins, and lignins. Both phenolic acids and polyphenols make major contributions to the antioxidant capacity of tomatoes (Stratil et al. 2006). Most studies in the literature have focused on total phenolic content instead of specific phenolic acids or flavonoids. Common phenolic acids in tomato are caffeic acid, chlorogenic acid, ferulic acid, and p-coumaric acid (Ramos-Bueno et al. 2017; Sharma et al. 2018). Tomato also contains a good level of flavonoids. The most abundant flavonoids in tomato are rutin, quercetin, kaempferol, and naringenin (Ramos-Bueno et al. 2017; Sharma et al. 2018). It is challenging to summarize the phenolic content of tomato because it varies with cultivar and environmental and physiological conditions. For instance, Martí et al. (2016) reported that 100 g of fresh tomato contains 0.9–18.2 mg naringenin chalcone, 0.5–4.5 mg rutin, 0.7–4.4 mg quercetin, 1.4–3.3 mg chlorogenic acid, 0.1–1.3 mg caffeic acid, and 0–1.3 mg naringenin. Total phenolic content was reported in the range of 21.34–31.23 mg chlorogenic acid equivalent/g extract, and total flavonoid content was reported in the range of 3.06–6.36 mg quercetin equivalent/g extract (Ali et al. 2020). Phenolic compound content is highly, positively correlated with antioxidant capacity (Stratil et al. 2006). The antioxidant capacity of tomato is difficult to compare because it changes based on the measurement method (ferric-ion reducing power, DPPH radical scavenging activity, ABTS radical cation scavenging activity) and extraction solvents and methods. Moreover, carotenoids and vitamin C and E also contribute to the antioxidant capacity of tomato (Ali et al. 2020). 2.1.4 Vitamins The most abundant vitamins in tomato are ascorbic acid (vitamin C), provitamin A (described in Sect. 2.1.2), and vitamin E. Ascorbic acid is mainly synthesized by the L-galactose pathway in plants (Mellidou et al. 2021). It is a water-soluble antioxidant compound that neutralizes free radicals. The oxidized forms of ascorbic acids are recycled via the ascorbate-glutathione cycle. The name vitamin E encompasses four (α, β, δ, γ) tocopherols and the corresponding four tocotrienols (Raiola et al. 2015). These compounds are lipid-soluble antioxidants and only synthesized by plants. The precursors of tocopherols and tocotrienols are phytyl pyrophosphate and

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geranylgeranyl pyrophosphate, respectively, which are produced in the isoprenoid pathway in plastids (Raiola et al. 2015; Mène-Saffrané 2017). Ascorbic acid is the most significant vitamin in tomato with 13.7 mg found in 100 g fresh fruit (Table 1). During domestication, ascorbic acid levels decreased; thus, wild relatives of tomato contain higher levels of this vitamin than cultivated tomato (Mellidou et al. 2021). Ascorbic acid content is affected by various factors. Its levels increase during maturation and decrease during ripening (Chaudhary et al. 2018). Moreover, ascorbic acid levels are greatly affected by genotype. Ali et al. (2020) reported ascorbic acid levels ranging from 10.86 to 85.00 mg/100 g. Another vitamin that contributes to the antioxidant capacity of tomato is vitamin E. The most abundant structural form of vitamin E is α-tocopherol (Raiola et al. 2015). The USDA reports the vitamin E content of tomato as 0.54 mg in a 100 g fruit. In a review, Ali et al. (2020) reported α-tocopherol levels varying from 0.59 to 0.88 mg/100 g. Folate is another nutritional compound found in tomato. Humans cannot synthesize this phytochemical, so it must be consumed in the daily diet (Vats et al. 2022). Folate content varies in the range of 4–60 μg/100 g FW (Upadhyaya et al. 2017), while in another study it was found in the range of 4.1–35.3 μg/100 g (Iniesta et al. 2009). The USDA reports folate levels of red ripe tomato as 15 μg/100 g (Table 1).

2.1.5 Polyamines Polyamines are small aliphatic amines that occur in free, conjugated, and covalently bound forms in plants (Fortes and Agudelo-Romero 2018). The main plant polyamines are putrescine, spermidine, and spermine. Polyamine synthesis occurs in the cytoplasm. Putrescine is synthesized from the amino acid arginine and can then be converted to spermidine which can then be converted to spermine. Polyamine biosynthesis has been linked to a larger network involving abscisic acid, nitric oxide, and tricarboxylic acid cycle as well as GABA. Polyamines are important metabolites for plants due to their roles in fruit ripening and stress conditions and for humans due to their beneficial effects on health. Putrescine, spermidine, and spermine are abundant polyamines in tomato (Fortes and Agudelo-Romero 2018). Spermidine and spermine are reported to have roles in water stress tolerance (Montesinos-Pereira et al. 2014). During tomato fruit maturation, putrescine levels increase while spermidine and spermine levels decrease (Tsaniklidis et al. 2016; Gutierrez et al. 2021). Moreover, polyamine content differs based on the cultivar (Montesinos-Pereira et al. 2014). 2.1.6 Gamma-Aminobutyric Acid (GABA) GABA is a non-proteinogenic amino acid and has been attracting attention in recent years for its health benefits. GABA is produced by the GABA shunt (Takayama and Ezura 2015). The precursor of GABA is glutamate and biosynthesis occurs in the cytoplasm. Tomato accumulates GABA at high levels. During fruit development GABA levels increase at the mature green stage but decrease during red ripe stage (Takayama and Ezura 2015). Depending on factors such as genotype, environmental conditions, and post-harvest treatment, Gramazio et al. (2020) reviewed GABA concentrations in tomato as 0.35–2.01 mg/g.

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2.1.7 Glycoalkaloids Unlike polyamines and GABA which occur throughout the plant kingdom, glycoalkaloids are nitrogen-containing compounds found in only a few species and are used in defense (Zhao et al. 2021). Solanaceous species like tomato contain steroidal glycoalkaloids (SGAs). SGAs have nitrogenous aglycone and glycoside residues and are derived from acetyl CoA via cholesterol. The two main tomato SGAs are α-tomatine and dehydrotomatine. Although they are toxic, glycoalkaloids can be used in medicine for disease treatment (Chaudhary et al. 2018). One of the important factors that affect the glycoalkaloid accumulation in tomato is fruit maturation. α-tomatine is found at high levels at green stage and decreases at the red ripe stage due to increasing enzymatic activity that metabolize the glycoalkaloids (Friedman 2002). In a review, Friedman (2002) reported that α-tomatine levels varied between 10 and 548 mg/kg at the unripe green stage and between 0.3 and 11 mg/kg at the red ripe stage in different tomato varieties.

2.2

Medicinal and Physiological Properties in Relation to Human Health

Tomato has a large part in the human diet. It is very popular due to its culinary versatility and because it is well known to contain bioactive compounds. The most abundant bioactive compounds found in tomato are carotenoids, phenolic compounds, vitamins (especially ascorbic acid), polyamines, GABA, and glycoalkaloids (Chaudhary et al. 2018). These diverse bioactive compounds play different roles in the maintenance of human health. For instance, dietary fiber has positive effects on cancer, diabetes, obesity, hyperlipidemia, and coronary heart disease (Hasegawa et al. 2017; Ali et al. 2020). Protein is essential in our daily diet because insufficient protein intake is related to risks of frailty, sarcopenia, and immunodepression (Wu 2016). Tomato is a source of powerful antioxidants due to its rich and varied content of carotenoids, phenolic acids, ascorbic acid, and vitamin E. In addition to their antioxidant properties, these molecules have diverse bioactivity. A diet rich in carotenoids prevents certain types of cancers (Botella-Pavía and Rodriguez-Conceptíon 2006). Among carotenoids, lycopene has anticancer, anti-inflammatory, and immunostimulatory properties and positive effects on colitis and cardiovascular diseases (Fawzi et al. 2000; Gouranton et al. 2011; Holzapfel et al. 2013; Cheng et al. 2019). β-carotene helps in the prevention of atherosclerosis, photooxidative processes, and congestive heart disease (Stahl and Sies 2003; Karppi et al. 2013; Miller et al. 2020). It is also the precursor of vitamin A, thus preventing vitamin A deficiency (Fernández-García et al. 2012). The other minor carotenoids, lutein and zeaxanthin, protect humans against cataracts and age-related macular degeneration (Gale et al. 2003). Phenolic compounds are another category of powerful antioxidant molecules. Phenolic acids have antioxidative, antimicrobial, antiallergic, antimutagenic, anti-inflammatory, and anticancer properties (Martínez-Valverde et al. 2002; Ramos-Bueno et al. 2017). Flavonoids are a predominant type of phenolic compound in tomato and have anti-inflammatory effects and reduce cardiovascular

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diseases and cancer (So et al. 1996; Tomlinson et al. 2017). Among the vitamins, ascorbic acid and vitamin E play roles in the prevention of certain cancers (RamosBueno et al. 2017). Moreover, ascorbic acid has antiatherogen effects and plays role in the regulation of inflammation and insulin metabolism (Tousoulis et al. 2003). Vitamin E is important in preventing type II diabetes, cardiovascular diseases, and age-related muscular degeneration and has anti-inflammatory affects (Montonen et al. 2004; SanGiovanni et al. 2007; Cordero et al. 2010). In addition to vitamins C and E, folate also exhibits HR properties. It helps regulate the metabolism of homocysteine and reduce anemia (Solini et al. 2006; Castellanos-Sinco et al. 2015). Polyamines, especially spermidine, also have positive effects on human health (Dala-Paula et al. 2021). Spermidine helps control blood pressure and the incidence of heart disease, has anti-aging properties, and is important for the synthesis and stabilization of nucleic acids and proteins (Eisenberg et al. 2016; Madeo et al. 2018; Muñoz-Esparza et al. 2019). GABA is another important molecule that helps to reduce blood pressure, induce relaxation, and enhance immunity (Takayama and Ezura 2015). Glycoalkaloids are important in protection against human pathogens (Chaudhary et al. 2018). Glycoalkaloids also have anticancer properties and antimicrobial activities (Iijima et al. 2013). Phytosterols play roles in the prevention of some cancer types such as colon cancer and heart disease (Ramos-Bueno et al. 2017; Uddin et al. 2018).

2.3

Methods of Nutraceutical Improvement: Agronomic and Postharvest Techniques

Plant breeding helps to improve the quality, yield, flavor and aroma, and nutritional and medicinal contents of crop plants. In addition to genotype, the levels of HR components are greatly affected by agronomic practices and environmental factors. Agronomic techniques include the regulation of UV radiation, cultivation temperature, adequate irrigation, salt stress, and cultivation methods. UV radiation (UV-B, 280–315 nm) causes DNA damage, and plants can increase the synthesis of antioxidant molecules to cope with this damage (Huché-Thélier et al. 2016). During fruit ripening, very high (>30  C) temperatures and altered light profiles cause increased levels of both lycopene and phenolics (rutin and caffeic glucoside) (Gautier et al. 2008; Dzakovich et al. 2016). It is also reported that low ( chokeberry and bilberry > purple carrot and grape > radish and elderberry. Interestingly, monoglycosylated NAA exerted the strongest antiproliferative effects, whereas triglycosylated AA had the least effect. Another study by Sevimli-Gur et al. (2013) expanded the anticancer in vitro evaluation of purple carrot extracts to various cancer cell lines from human (MCF-7, SK-BR-3, and MDA-MB-231 for breast cancer; HT-29 for colon cancer;

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and PC-3 for prostate cancer) and mouse (Neuro 2A for neuroblastoma), reporting potent and dose-dependent cytotoxic effects on all of these cancer lines, with the strongest antiproliferative effects found in brain neuroblastoma. Considering that the study also found very little cytotoxicity by the carrot extract in a normal – not cancerous – cell line (VERO, from African green monkey kidney), the authors concluded that purple carrot extracts may have greatest potential as a dietary treatment for brain cancer, avoiding negative side effects in normal cells.

2.3

Genetics and Genes Controlling Carrot Anthocyanin Pigmentation

2.3.1 Inheritance and Mapping of Simply Inherited Traits A first inheritance study by Simon (1996) described a major effect locus, termed P1, controlling the presence or absence of purple color in the taproot of carrot, being purple dominant over non-purple, by analyzing segregation ratios in different populations derived from crosses between purple and non-purple rooted carrots. Purple pigmentation was also scored in aerial plant parts of the same segregating populations, leading to the discovery of another simply inherited dominant locus, P2, which conditioned pigmentation in the nodes, and it was estimated that both loci were genetically linked at a distance of ~36 cM. In two subsequent studies by Vivek and Simon (1999) and Yildiz et al. (2013), P1 was mapped to carrot chromosome 3 in F2 mapping populations derived from crosses that used “B7262” as the purple root progenitor. B7262 is a Turkish carrot with anthocyanin accumulation only in the outer phloem of the root, being the inner phloem and xylem orange. A later study by Cavagnaro et al. (2014) identified and mapped another simply inherited dominant locus, called P3, controlling anthocyanin accumulation in the taproot and in leaf petioles in the genetic backgrounds of P9547 (from Turkey) and PI652188 (from China), both exhibiting purple color in the taproot and petioles. P3 mapped to Chr. 3 but it was positionally unrelated to P1, distanced from the latter at >30 cM, as indicated from results of comparative map analysis using common markers across the three segregating populations were the two traits had been mapped (Cavagnaro et al. 2014). Figure 2b presents root phenotypes of the purple-rooted progenitors and derivative segregating populations used to map these and other simply inherited and QTLs conditioning root and petiole anthocyanin pigmentation. More recently, Iorizzo et al. (2019) analyzed segregation for anthocyanin pigmentation in the root and petioles in an F2 mapping population derived from BP85682, a Syrian carrot with purple root and petioles, and in advanced progenies (F3 and F5 families) of the populations used earlier by Cavagnaro et al. (2014). Phenotypic segregations for root and petiole anthocyanin pigmentation co-segregated in the F2, and both traits exhibited a 3:1 ratio (purple:non-purple), suggesting that a single major-effect locus conditions both traits. Comparative linkage mapping using markers in common across this population and other populations with known pedigree revealed that this anthocyanin-conditioning locus in the Syrian BP85682 background corresponds to P3. Thus, the phenotypic

Fig. 2 Genomic locations of anthocyanin QTLs in chromosome 3 and phenotypes mapped in carrot with respective references. (a) Representative QTLs and simply inherited traits conditioning the presence and concentration of anthocyanins mapped onto carrot chromosome 3, displaying the physical position of genes associated with anthocyanin biosynthesis. Transcription factors are indicated in purple; anthocyanin biosynthetic structural genes in black; anthocyanin acyltransferases, glucosyltransferases, and methyltransferases in green; and genes involved in anthocyanins cellular transport in orange. The genes were labeled

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locus P3 conditions root and petiole anthocyanin pigmentation in all of the purple carrot materials evaluated to date, except for the Turkish carrot B7262, in which P1 controls root but not petiole pigmentation. Bannoud et al. (2019) investigated tissue-specific anthocyanin pigmentation in the carrot root and leaves, using F2 and F3 populations segregating for purple color in the root phloem and xylem tissues, and in the leaf petiole. They described and mapped two simply inherited loci controlling the presence/absence of pigmentation in the root xylem and leaf petioles, with purple color being dominant over non-purple in both tissues. These loci, called XAP and PAP, for “xylem anthocyanin pigmentation” and “petiole anthocyanin pigmentation,” respectively, were mapped in the same chromosome region of P3 (Fig. 2a). In this genetic background, purple phloem pigmentation segregated consistently with a two-gene model, dominant for purple over non-purple, with its main effects co-localizing with the P1 and P3 regions. In a recent follow-up study concerning tissue-specific pigmentation in the root outer phloem (also called “cortex”) and inner phloem tissues, Bannoud et al. (2021) genetically mapped purple pigmentation in both the outer and inner phloem tissues. The mapping of these simply inherited phenotypic traits, called ROPAP and RIPAP, for “root outer-phloem and root inner-phloem anthocyanin pigmentation,” respectively, revealed colocalization of ROPAP with the P1 and P3 regions, whereas RIPAP co-localized with P3 only (Fig. 2a). Noteworthy, the populations used by Bannoud et al. had the unprecedented characteristic that P1 and P3 as well as pigmentation in the root phloem and xylem, and in leaf petioles all segregated in the same mapping population (3242). Together, the studies of Bannoud et al. (2019, 2021) provide information on the tissue-specificity of P1 and P3, and reinforce previous findings by Cavagnaro et al. (2014) and Iorizzo et al. (2019) suggesting that, in some genetic backgrounds, P3 controls root and petiole anthocyanin pigmentation, while in other backgrounds (e.g., B7262), P1 controls pigmentation exclusively in the root outer phloem (Yildiz et al. 2013).

ä Fig. 2 (continued) by their abbreviated names followed by the DCAR or LOC number, in parenthesis. The physical position of each gene in the chromosomes is expressed in terms of nucleotide coordinates from the carrot genome assembly and indicated by the ruler on the left. Major-effect phenotypic traits are denoted in red, italic, and bold fonts. QTLs conditioning absolute (i.e., expressed on a fresh weight basis) or relative pigment concentration (i.e., % of the total anthocyanin content) in the whole root (in black), as well as in the root phloem (in blue) or xylem tissues (in orange), are presented. QTLs for total or combined anthocyanin pigments (e.g., sum of acylated anthocyanins) are indicated in bold. QTLs bars indicate the 1.5 LOD interval (nt) and the position of the maximum LOD value. QTLs are labelled by their pigment abbreviations G ¼ Cy3XG; GG ¼ Cy3XGG; CGG ¼ Cy3XCGG; FGG ¼ Cy3XFGG; SGG ¼ Cy3XSGG; Total ANT ¼ total anthocyanins; Sum AA ¼ sum of acylated anthocyanins (i.e., CGG + FGG + SGG); Sum NAA ¼ sum of non-acylated anthocyanins (i.e., G + GG) preceded by the type of root tissue (Ph ¼ phloem, Xy ¼ xylem), in the case of tissue-specific QTLs, and followed by “(%)” to indicate QTLs expressed as relative concentration. (b) Main characteristics of the segregating populations and purple-root sources used for mapping anthocyanin traits (Modified from Bannoud et al. (2019, 2021) and Iorizzo et al. (2020))

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Besides the phenotypic loci described above conditioning the accumulation of anthocyanins in different tissues of the root and the aerial part of the plant, a majoreffect trait locus controlling the proportion (%) of AA (relative to the total anthocyanin content) was discovered and mapped to Chr. 3, located between the P1 and P3 loci, at a distance of 17.9 cM from the latter (Cavagnaro et al. 2014) (Fig. 2a). This locus was termed Raa1, for “root anthocyanin acylation” (Cavagnaro et al. 2014). More recently, Curaba et al. (2020) performed fine mapping of Raa1 in F3 populations derived from the 70,349 family used by Cavagnaro et al. (2014) and an F2 family obtained by crossing a 70,349-F3 plant homozygous recessive at the Raa1 locus with a homozygous dominant plant of Chinese origin known as “Ping Ding.” Overall, the phenotyping and genotyping of a total of 926 plants allowed narrowing down the Raa1-containing genomic region, which was used for identifying candidate genes for Raa1 (described in Sect. 2.3.3).

2.3.2 QTL Mapping A first study concerning carrot anthocyanin QTLs was published by Cavagnaro et al. (2014) and reported on the genetic mapping of QTLs for individual and total root anthocyanins using an F2 population derived from the Turkish purple-root progenitor P9547 (Fig. 2b). Fifteen significant QTLs conditioning total root anthocyanin levels, referred to as RTPE (for “root total pigment estimate”), and relative content of four cyanidin glycosides were identified and genetically mapped to five chromosomes. The QTLs with largest phenotypic effects (26.6–73.3% explanatory power) co-localized in two regions of Chr. 3. Five of these major-effect QTLs co-localized with P3, and included a QTL for RTPE with 50% phenotypic effect, and four major QTL for concentration of three acylated pigments and one NAA (Fig. 2a). These results confirmed that the P3 region controls anthocyanin accumulation in the carrot root and petioles in the P9547 genetic background (Cavagnaro et al. 2014). In a more recent study, fine mapping was performed in the P3 region using a larger mapping population of the same genetic background as used earlier by Cavagnaro et al., detecting the same 5 major-effect QTLs for RTPE and four root cyanidin glycosides. Because of the larger population used, a better map resolution was obtained for this region, with overlapping QTLs for RTPE, Cy3XG, Cy3XSGG, and Cy3XFGG within a 3 cM region. Bannoud et al. (2019) used two biparental populations (3242 and 5171) to map QTLs for concentration of individual and combined (i.e., AA, NAA, and total) anthocyanins, and relative percentages of individual and combined anthocyanins, in the root phloem and xylem. In the 3242 population, which was the most informative population with regards to the number of tissue-specific segregating traits, 41 and 8 QTLs for phloem and xylem anthocyanins, respectively, with QTLs explanatory power ranging from 1.3% to 53.4% were mapped across four carrot chromosomes (chromosomes 3, 4, 6, and 7). Thirty of the QTLs for phloem anthocyanins, including those with greatest phenotypic effect, and all of the QTLs for xylem anthocyanins co-localized to two region of Chr. 3, corresponding to the P1 and P3 regions previously described and mapped (Fig. 2a). While the QTL for phloem anthocyanins mapped to both of these regions, all the xylem QTLs mapped

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to the P3 region only, co-localizing with other phloem QTLs and the simply inherited traits XAP, PAP, ROPAP, and RIPAP conditioning presence/absence of pigmentation in the root xylem and phloem, and in leaf petioles. Altogether, these data strongly suggest that the P3 region controls anthocyanin pigmentation (i.e., presence/absence of purple color) and concentration in the root phloem and xylem, and in leaf petioles, whereas P1 conditions only phloem pigmentation and anthocyanin concentration, particularly in the outer phloem or cortex (Fig. 2a). The QTLs mapped in other chromosomes had relatively low explanatory weight, suggesting little phenotypic effect and/or interactions with major loci of Chr.3, as was revealed by Bannoud et al. (2019). This chapter focused on the most important simply inherited phenotypic traits and QTLs with strongest effects conditioning anthocyanin pigmentation in carrot, as well as on the genes underlying these traits. These correspond to the P1, P3/RTPE, and Raa1 regions in chromosome 3 controlling the presence, concentration, and acylation of these pigments. Additional and detailed information concerning all of the anthocyanin-related QTLs mapped to date across different chromosomes and carrot genetic backgrounds can be found in a recent review by Iorizzo et al. (2020).

2.3.3

Candidate Genes Conditioning Anthocyanin Biosynthesis, Acylation, Glycosylation, and Transport By means of linkage analysis, Yildiz et al. (2013) attempted to identify candidate genes for P1, mapping regulatory (DcMYB3, DcMYB5, and DcEFR1) and structural biosynthetic genes (UFGT, PAL3, LDOX2, F3H, and FLS1) of the anthocyanin pathway in the same population used for mapping the phenotypic trait. However, the map position of these genes did not coincide with P1, indicating that none of them is a likely candidate for P1. Later, Xu et al. (2014) compared gene expression of 13 anthocyanin structural genes in purple and non-purple roots of nice cultivars, finding upregulation in anthocyanin-containing roots for 9 of these genes, being their expression levels correlated with total root anthocyanin contents. The correlated expression of these anthocyanin genes with root pigment levels suggests a coordinated transcriptional regulation and their involvement in anthocyanin biosynthesis. However, no candidates for P1, P3, or Raa1 – the phenotypic traits described prior to their study – could be identified. A glycosyltransferase gene, termed DcUCGalT1, was isolated and cloned from the root of a purple carrot (Xu et al. 2016). The cloned gene encodes a galactosyltransferase that catalyzes the glycosylation of cyanidin with galactose. The enzyme has high affinity for galactosylation of cyanidin, but not for other anthocyanidins and flavonoid substrates, as indicated by its much lower galactosyltransferase activity for pelargonidin, peonidin, quercetin, and kaempferol observed in a heterologous expression system of E. coli. It was also found that the enzyme encoded by DcUCGalT1 catalyzes exclusively the transfer of UDP-galactose to cyanidin, but it was unable to use other glycosyl donors like UDP-glucose or UDP-xylose, suggesting that DcUCGalT1 is highly specific for galactosylation of cyanidin. Gene expression analysis of DcUCGalT1 in nine purple and non-purple rooted cultivars revealed significantly greater expression in all purple roots compared to

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non-purple ones, and the expression level was correlated with pigment content in the taproot. Together, these data indicate that DcUCGalT1 is involved in cyanidin galactosylation. A BLAST search of DcUCGalT1 in the carrot genome assembly showed greatest sequence homology with DCAR_009912 which is located in Chr. 3 at a position (12,350,188-12,351,646) unrelated to P1, P3, Raa1, RTPE, and the other tissue-specific phenotypic loci positionally associated with P1 and P3, suggesting that DcUCGalT1 is not a major gene controlling anthocyanin pigmentation in the carrot root or petioles. Following a similar approach as used for the DcUCGalT1 gene, Xu et al. (2017) isolated and described an R2R3-type MYB transcription factor, designated DcMYB6, from purple carrot roots. The expression pattern of DcMYB6 in purple and non-purple carrots was correlated with anthocyanin content in the roots. Arabidopsis thaliana plants genetically transformed with DcMYB6 under a strong promoter showed anthocyanin pigmentation in various plant parts, including reproductive organs, paralleled with increased transcription of structural anthocyanin genes. These results suggest that DcMYB6 upregulated the expression of Arabidopsis structural anthocyanin genes and may – presumably – play a similar role in the carrot root. In a subsequent study by Kodama et al. (2018), the transcriptomes of purple versus non-purple tissues from carrot roots and calli were compared by mean of RNA-Seq analysis and searched for differentially expressed members of the MYB, bHLH, and WD40 transcription factor families. They found a total of 104 differentially expressed TF genes, of which 32 had expression levels significantly correlated with root anthocyanin content. Additional analyses in other genetic stocks and root developmental times revealed that 11 of the 32 genes were consistently up- or downregulated in purple-rooted carrots, and included 6 MYBs, 4 bHLH, and 1 WD40 TF. Only one of these genes is located in Chr. 3, with the remaining ones being located throughout seven other chromosomes (and therefore are disqualified as potential candidates of the phenotypic traits in Chr. 3P1, P3/RTPE, and Raa1). The gene in Chr. 3 is a MYB TF (LOC108213488), which the authors referred to as DcMYB6, the same MYB gene described earlier by Xu et al. (2017). However, a closer analysis of the position of this gene in the carrot genome sequence revealed that the gene annotated as LOC108213488 is not DcMYB6 butDcMYB7, another MYB TF described later as a potential candidate of P3 by Iorizzo et al. (2019) and Xu et al. (2019). Along with the sequencing and publication of the carrot genome, a list of 97 annotated structural biosynthetic flavonoid genes, including genes involved in anthocyanidin/anthocyanin biosynthesis and modification (e.g., glycosyltransferases and methyltransferases) was reported by Iorizzo et al. (2016). Besides facilitating this first large-scale catalogue of predicted structural genes involved in carrot flavonoid/anthocyanin biosynthesis, the availability of an annotated carrot genome sequence was instrumental for the discovery of key genes conditioning some of the phenotypic traits previously described and mapped. Among the first studies to take advantage of such an unprecedented genomic tool were those of Iorizzo et al. (2019), Xu et al. (2019), and Bannoud et al. (2019); the first two aiming at identifying candidate genes for P3, while the latter investigated candidates for tissue-specific pigmentation in the root phloem and xylem.

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Iorizzo et al. (2019) performed high-resolution mapping in the P3/RTPE region of Chr. 3 using five mapping populations of different genetic backgrounds, including a larger-size population of the 70,349 F2 used to first map these traits by Cavagnaro et al. (2014), for a total of 1669 plants phenotyped (421 individuals were phenotyped for RTPE, by HPLC analysis, and 1248 for P3, by visual phenotyping of root color) and genotyped using different molecular marker types. The inclusion of common sequence-based SNP markers across the different maps allowed their comparative analysis to further delimit the region of interest, as well as anchoring such region of interest to the carrot genome assembly. Thus, by this approach, it was able to obtain a higher resolution of this map region, restricting the confidence interval of the RTPE QTL to a 2.6 cM region, whereas the closest flanking markers of P3 delimited a 0.3–0.8 cM map region. A close examination of the linkage blocks harboring RTPE and P3 in the different maps allowed further narrowing down the position of P3 to a 494 kb region flanked by SNP markers K2590 and K0363 (Fig. 3). In this region, 8 anthocyanin-related transcription factor (TF) genes (6 MYB and 2 bHLH) were identified, whereas no structural anthocyanin biosynthetic genes were found. By means of gene prediction, orthologous, and phylogenetic analyses using MYB and bHLH TFs from other species with known functions, allowed the identification of six MYBs that had high sequence homology with MYBs involved anthocyanin biosynthesis, which were considered potential candidates for P3/RTPE. The identified MYB TFs positionally associated with P3/RTPE were designated as DcMYB6-DcMYB11, and they belong to the R2-R3-MYB family (Table 2). Noteworthy, DcMYB6 corresponds to the MYB gene previously described by Xu et al. (2017). In the same study, the transcriptomes of purple versus non-purple roots and petioles were compared by means of RNA-Seq analysis, followed by validation of the candidate genes by RT-qPCR analysis. Of all six MYB TFs identified in the P3 region, DcMYB7 was the only gene consistently upregulated in all of the anthocyanin-containing tissues (as compared to non-purple tissues), suggesting that this MYB controls anthocyanin pigmentation in both the carrot root and petioles. DcMYB11 was consistently upregulated in purple petioles (relative to green petioles) but not in purple roots, suggesting that it may co-regulate petiole pigmentation along with DcMYB7. Together, these results strongly point at DcMYB7 as the main candidate for P3 and a key gene conditioning root and petiole pigmentation, while DcMYB11 specifically (co)regulates petiole pigmentation. These results by Iorizzo et al. (2019) suggest that, for the purple carrot lines used in their study, DcMYB6 described earlier by Xu et al. (2017) does not play a major role in regulating anthocyanin biosynthesis in neither the taproot nor in the leaf petioles. Table 2 presents the MYB transcription factors associated with carrot anthocyanin pigmentation described to date, including their chromosome positions and gene IDs. The six anthocyanin-related MYB TFs found by Iorizzo et al. (2019) in the P3 region are arranged in a small cluster of genes within a ~166 Kb region of Chr. 3 (Fig. 3b). A number of studies concerning genome wide analysis of R2-R3-MYB family members have revealed that MYB TFs are commonly found in gene clusters in the genomes of many plants species. Interestingly, it has been proposed that the expansion of MYB gene-families and their organization into gene clusters is mainly driven

DCAR_10797

K1402

K3321

K0363

DcMYB7

DcMYB6

P3

K25 90

K05 45

pop. 70349

a

DCAR_10731

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1 4

Region 1 - 1,511 kb pop. 95710

2 2

Region 2 - 1,093 kb pop. 5394

1 1

Region 3 - 2,708 kb pop. 5723

1 1

Region 4 - 535 kb

H B

b

Region 5 - 494 kb

DcMYB7 DcMYB8 DcMYB6

27,850

27,900

DcMYB9

DcMYB10

27,950

DcMYB11

28,000

Fig. 3 Scheme of the fine mapping approach and identification of candidate genes in the P3/RTPE region of chromosome 3 associated with anthocyanin pigmentation in the carrot root and petioles. (a) haplotypes delimiting the genomic regions controlling the RTPE QTL in population 70,349 (region 1), and the P3 locus in populations 95,710, 5394 and 5723 (regions 2–4). White bars indicate the heterozygous haplotypes (Aa) and gray bars indicate the homozygous recessive haplotypes (aa). Region 5 represents the genomic sequence delimited by the nearest markers flanking RTPE and the P3 locus across regions 1–4. The number of plants with recombinant genotypes is indicated by on the right of each bar. (b) Schematic representation of carrot chromosome 3 containing regions 1–5 and the six anthocyanin related MYBs (DcMYB6-DcMYB11) denoted in black boxes (Modified from Iorizzo et al. (2019))

by the occurrence of tandem and segmental duplications (Feller et al. 2011). Thus, it is possible that tandem and segmental duplications could have also influenced the genome organization of the carrot R2-R3-MYB gene family. Xu et al. (2019) functionally characterizedDcMYB6 and DcMYB7, both candidates of P3, by upregulating and shutting down their expression in carrot using a transgenic approach. It was found that overexpression of DcMYB7, but not DcMYB6, in the orange-rooted carrot cultivar ‘Kurodagosun’ led to the accumulation of large amounts of anthocyanin in the root and other tissues of this cultivar. Conversely, knockout of DcMYB7 in the solid purple-rooted cultivar ‘Deep Purple’, obtained by gene-editing using the CRISPR-Cas9 system, resulted in carrots with yellow roots. These results confirm the role of DcMYB7 as a major regulator of anthocyanin pigmentation in carrot root, as well as the main candidate of P3. Their study also

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Table 2 MYB transcription factors associated with carrot anthocyanin pigmentation described to date Gene ID DcMYB1 DcMYB2

Gene ID DCAR_030745 DCAR_011083

Chr. # 9 3

Genome coordinates Start End 29,370,465 29,370,597 32,098,199 32,100,603

DcMYB3-1 DcMYB3-2 DcMYB4

DCAR_028315 DCAR_028315 DCAR_015002

8 8 4

8,778,266 8,778,266 16,426,186

8,779,336 8,779,336 16,428,272

DcMYB4.2

DCAR_015002

5

22,226,323

22,229,683

DcMYB4.3

DCAR_028315

2

21,943,650

21,943,310

DcMYB5

DCAR_024737

7

18,692,086

18,693,681

DcMYB6a

DCAR_000385

3

27,831,723

27,833,545

DcMYB7

DCAR_010745

3

27,816,911

27,819,103

DcMYB8 DcMYB9 DcMYB10 DcMYB11 DcMYB12/ DcMYB113 DcMYB13 DcMYB14 DcMYB15 DcMYB16 DcMYB17

DCAR_010746 DCAR_010747 DCAR_010749 DCAR_010751 DCAR_008994

3 3 3 3 3

27,824,309 27,901,372 27,938,999 27,980,959 3,370,872

27,826,050 27,903,024 27,939,453 27,982,962 3,376,028

DCAR_009089 DCAR_010791 DCAR_010853 DCAR_003738 DCAR_007287

3 3 3 1 2

4,318,404 28,667,859 29,535,747 41,577,479 33,010,740

4,319,725 28,669,181 29,537,844 41,578,680 33,013,213

DcMYB18 DcMYB19 DcMYB20 DcMYB21 DcMYB22 DcMYB23 DcMYB24

DCAR_014214 DCAR_015602 DCAR_016459 DCAR_018481 DCAR_018882 DCAR_019908 DCAR_020645

4 4 5 5 5 6 6

23,846,982 10,021,890 3,566,349 30,483,119 34,067,212 35,858,709 29,610,878

23,848,124 10,023,032 3,567,632 30,484,602 34,068,530 35,860,309 29,613,179

References Maeda et al. (2005) Wako et al. (2010), Meng et al. (2020) Wako et al. (2010) Wako et al. (2010) Wako et al. (2010), Kodama et al. (2018) Wako et al. (2010), Kodama et al. (2018) Wako et al. (2010), Kodama et al. (2018) Wako et al. (2010), Meng et al. (2020) Xu et al. (2017), Iorizzo et al. (2019), Bannoud et al. (2019, 2021), Meng et al. (2020) Kodama et al. (2018), Iorizzo et al. (2019), Xu et al. (2019), Bannoud et al. (2019, 2021), Curaba et al. (2020), Meng et al. (2020) Iorizzo et al. (2019) Iorizzo et al. (2019) Iorizzo et al. (2019) Iorizzo et al. (2019) Bannoud et al. (2019, 2021), Xu et al. (2020) Bannoud et al. (2019) Bannoud et al. (2019) Bannoud et al. (2019) Meng et al. (2020) Kodama et al. (2018), Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) (continued)

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Table 2 (continued) Gene ID DcMYB25 DcMYB26 MYB1R1-1 MYB1R1-2 DcMYB27b DcMYB28b

Gene ID DCAR_028146 DCAR_030321 DCAR_031036 DCAR_026095 DCAR_026095 DCAR_026095

Chr. # 8 9 9 7 1 8

Genome coordinates Start End 14,422,378 14,423,688 23,408,024 23,410,706 32,191,963 32,196,585 33,127,347 33,129,362 41,375,308 41,396,955 9,013,410 9,014,567

References Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Meng et al. (2020) Bannoud et al. (2021) Bannoud et al. (2021)

DcMYB6 was first described by Xu et al. (2017) and later incorporated manually into the carrot genome assembly [i.e., this gene was not included in the published genome assembly (Iorizzo et al. 2016)] with the coordinates above (Iorizzo et al. 2019) b In the study of Bannoud et al. (2021), these MYBs were referenced with a generic name (i.e., “MYB” followed by their DCAR number); here we propose DcMYB27 and DcMYB28 to designate DCAR_026095 and DCAR_026095, respectively a

demonstrated that DcMYB7 could interact with – and activate the expression of – DcbHLH3 (a homolog of the anthocyanin related bHLH3 from Malus domestica) and structural genes of the anthocyanin biosynthetic pathway, and could also activate the expression of a putative glycosyltransferase (DcUCGXT1) and an acyltransferase (DcSAT1) genes identified in the same study (by orthologous analysis with related genes from other species). Together, these results provide strong evidence on the role of DcMYB7 as a transcriptional activator of other regulatory and structural anthocyanin genes, including genes involved in pigment decoration (i.e., glycosylation and acylation). Interestingly, in non-purple carrots, the promoter of DcMYB7 was interrupted either by DcMYB8, a nonfunctional tandem duplication of DcMYB7, or by two transposons, leading to the transcriptional inactivation of DcMYB7, thereby resulting in no anthocyanin synthesis and accumulation in their roots. In the P1 region, another MYB transcription factor, initially identified by Bannoud et al. (2019) and termed DcMYB12, was recently renamed as DcMYB113 and functionally characterized by Xu et al. (2020). DcMYB113 is an R2R3-MYB TF that controls anthocyanin pigmentation in the root of the carrot cultivar ‘Purple Haze’ and related genetic backgrounds [e.g., in B7262 (Bannoud et al. 2021)]. The function of DcMYB113 is root- and tissue-specific, conditioning pigmentation only in the root periderm and outer phloem (also known as “cortex”). Also, as mentioned above, it is genotype-dependent, as indicated by the fact that this gene was not expressed in the roots of genetic backgrounds exhibiting anthocyanin pigmentation in both roots and petioles, including the commercial cultivars Deep Purple, Cosmic Purple, and Pusa Asita, and the inbred line P9547 (Xu et al. 2020; Bannoud et al. 2021). The root-specific activity of this gene was verified by genetic transformation of the orange carrot cultivar ‘Kurodagosun’ with DcMYB113 fused to its own promoter and – in an independent transformation event – under the action of the CaMV 35S promoter. Transgenic ‘Kurodagosun’ plants carrying DcMYB113 driven by the CaMV 35S promoter had solid purple roots and petioles, while the transgenic ‘Kurodagosun’ expressing DcMYB113 with its own promoter had purple root and

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green petioles, suggesting that root-specific expression of DcMYB113 was determined by its promoter (Xu et al. 2020). As found previously for DcMYB7, it was also reported that DcMYB113 could transcriptionally activate the expression of DcbHLH3 and a number of structural anthocyanin biosynthetic genes, as well as two genes involved in pigment glycosylation (DcUCGXT1) and acylation (DcSAT1). Together, results from this study indicate that DcMYB113 is the most likely candidate for P1 and provide insights into its role in regulating anthocyanin biosynthesis and modification in the carrot root phloem. Recently, a candidate gene for the Raa1 locus, conditioning the relative content (%) of AA in the root, was identified and characterized by Curaba et al. (2020). By means of fine mapping in populations segregating for high AA versus low AA (individuals with more than 60% of the NAA Cy3XGG were scored as “low AA” and those with less than 22% of Cy3XGG were scored as “high AA”), followed by linkage blocks analysis, a genomic region of 576 kb harboring Raa1 was identified and further searched for candidate genes. In this region, three predicted “Serine Carboxypeptidase-Like” (SCPL) genes, designated as DcSCPL1-DcSCPL3, were identified and analyzed at various levels. Phylogenetic analysis clustered the three carrot SCPLs with anthocyanin-related acyltransferase SCPL genes from other species, suggesting a similar role in carrot. Comparative transcriptome analysis indicated that only DcSCPL1 was always expressed in association with anthocyanin pigmentation in the root and was co-expressed with DcMYB7. Structural (gene sequence) and expression analyses of DcSCPL1 in roots with high AA and low AA revealed an insertion causing an abnormal splicing of the third exon during mRNA editing, likely resulting in the production of a nonfunctional acyltransferase and explaining the reduced acylation phenotype in the “low AA” plants. Together, results from this study strongly suggest that DcSCPL1 is a major regulator of anthocyanin acylation in the carrot root and the main candidate of Raa1. Furthermore, the 700 bp-insertion found in the recessive allele of DcSCPL1 was used to design flanking primers to develop a codominant PCR-based marker for aiding in the selection of plants with high or low AA in carrot breeding programs. It must be noted that the DcSAT1 and DcSCPL1 acyltransferase genes described independently by Xu et al. (2019, 2020) and Curaba et al. (2020), respectively, correspond to the same gene, with locus ID LOC108214129. A few studies have addressed the genetics underlying tissue-specific pigmentation in the carrot root, using linkage mapping and comparative transcriptomic approaches in purple and non-purple root tissues. In addition to mapping QTLs for phloem and xylem anthocyanins, Bannoud et al. (2019) searched for candidate genes controlling pigmentation in the phloem, reporting that DcMYB7 conditions both presence/absence and concentration of anthocyanins, while two cytochrome CYP450 genes with putative flavone synthase activity may negatively influence pigment content in this tissue. In a similar follow-up study concerning pigmentation in the outer phloem (ROPAP) and inner phloem (RIPAP), DcMYB7 and DcMYB113 appear as the main candidates for ROPAP, depending on the genetic background analyzed, while only DcMYB7 conditions RIPAP (Bannoud et al. 2021). A MADSbox gene (DCAR_010757) located in the P3 region was consistently upregulated in

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association with purple pigmentation in the outer phloem (as compared to the non-purple inner phloem) in the two genetic backgrounds analyzed (3242 and B7262), as well as with RIPAP in P9547. However, this MADS-box was not phylogenetically related to MADS-box genes from other species known to be involved in anthocyanin biosynthesis and, therefore, its role in carrot anthocyanin biosynthesis is still inconclusive. Considering that the most striking differences in purple pigmentation between carrot cultivars are between the root xylem and phloem, comparative transcriptome analysis in these tissues may uncover major genes influencing their pigmentation. Such comparative analysis was conducted by Meng et al. (2020), finding 10 MYBs (Table 2) and 14 bHLHs, including DcbHLH3, differentially expressed between these two tissues. Interestingly, four of these MYBs, including two that were predicted as MYB1R1-like TFs (DcMYB1R1-1 and DcMYB1R1-2), were downregulated in both purple phloem and purple xylem tissues, suggesting that they may act as transcriptional repressors of anthocyanin structural genes, thereby negatively regulating anthocyanin biosynthesis. Their role in carrot anthocyanin pigmentation deserves further investigation, as MYB transcriptional repressors of anthocyanin biosynthetic genes have been reported in several plant species, including the ornamental Mimulus lewisii and grapevine. The regulation of anthocyanin metabolism ends with their transport into the vacuole, a process which can involve glutathione S-transferases (GSTs) (reviewed by Sylvestre-Gonon et al. 2019), and members of the “multidrug and toxic compound extrusion” (MATE) (Gomez et al. 2009) and “ABC-C transporter” gene families (Behrens et al. 2019). DcGST1 (DCAR_003401), which co-localized with a minor-effect QTL on Chr. 1 conditioning total root anthocyanins, was reported to be upregulated in two solid purple cultivars compared to orange-rooted ones, and its upregulation correlated with increased vacuolar anthocyanin accumulation in purple carrots (Meng et al. 2020). Very recently, Bannoud et al. (2021) evaluated the expression of DcGST1, DcMATE1 (DCAR-031151), and a carrot ABC Transporter gene (DCAR-010639) located in the P3 region of Chr. 3, in purple versus non-purple root phloem tissues in two unrelated genetic backgrounds, B7262 (controlled by DcMYB113) and 3242 (controlled by DcMYB7), reporting significant upregulation of DcGST1and DcMATE1 – but not of ABC Transporter – in all the purple tissues. Both of the upregulated genes were co-expressed with DcMYB113 (in B7262) and DcMYB7 (in 3242). Interestingly, according to Xu et al. (2020), DcMYB113 was also co-expressed with DcMATE1 in purple tissues of the cultivar ‘Purple Haze’. Altogether, results from these three studies strongly suggest that DcMYB113 and DcMYB7 transcriptionally activate DcGST1and DcMATE1 in their respective genetic backgrounds. Such regulatory role of MTB TFs on anthocyanin transporter genes has been reported in other plant species (Zhang et al. 2014).

2.4

Perspectives and Implications for Breeding

In recent years, candidate genes for the main phenotypic traits (P1, P3/RTPE, and Raa1) and QTLs conditioning anthocyanin biosynthesis, glycosylation, and

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acylation across different carrot tissues and genetic backgrounds, as well as genes involved in cellular transport and vacuolar accumulation of these pigments, have been discovered and functionally characterized, and their causal mutations described and – for one of these genes (DcSCPL1) – used for the development of a molecular marker to aid in marker-assisted breeding (MAB). These advances are encouraging for breeding programs aiming at improving anthocyanin content and pigment profile for different end purposes, such as fresh consumption carrots with increased content of bioavailable NAA and – consequently – greater nutritional value; or carrots with high concentration of chemically stable AA suitable for the food colorant industry; and/or introgressing such pigment profiles into carrot genetic backgrounds with other desirable agronomic and consumer-quality traits. Also, the fact that these pigments have a role, in the plant, of ameliorating abiotic stresses (Shirley 1996), suggest that increasing general anthocyanin levels may result in more resilient carrot cultivars, of relevance in the current climate change context. Moreover, not only total anthocyanin content but also pigment profile, particularly with regards to AA:NAA ratios, may be relevant for this purpose, as it has been shown in other crops, such as red grapes, that exposure to high temperature results in reduced total anthocyanin content but increased proportion of AA, mediated by an upregulation of acyltransferases, suggesting that pigment acylation may be a mechanism for attenuating high temperature-stress consequences by reducing anthocyanin degradation (de Rosas et al. 2022). To pursue these goals more rapidly and effectively, it would be ideal for breeding programs to combine well-stablished classic breeding strategies with molecular tools that allow tagging gene variants associated with specific pigment phenotypes. An example of such type of molecular tool is the codominant PCR-based marker targeting the DcSCPL1 gene which allows differentiation of “low acylation” and “high acylation” alleles, which could be very useful for assisting early selection of plants with high or low proportion of AA. However, such MAB strategy would require developing additional markers for other key genes conditioning anthocyanin concentration and accumulation in different purple carrot backgrounds (e.g., DcMYB7 and DcMYB113), and evaluating their usefulness for predicting pigment phenotypes across diverse carrot germplasm. Considering that the efficacy of molecular markers for predicting a phenotype relies on how tightly linked they are to the mutation that effects the phenotype, among other factors, marker development should ideally target the causal mutation of these genes, as was done with the DcSCPL1 gene. Alternatively, transgenic approaches represent technologically effective strategies for developing carrots with high anthocyanin content and specific pigment profiles. For example, increased anthocyanin concentration could be achieved by transforming carrots with DcMYB7 under a strong constitutive promoter (CaMV 35S), whereas manipulating pigment profiles for high or low ratios of AA/NAA may be done using a similar strategy for upregulating DcSCPL1 or generating a DcSCPL1knockout by editing this acyltransferase gene, respectively. These and other transgenic approaches have been experimentally successfully applied to carrot for a number of traits (reviewed by Baranski and Lukasiewicz 2019), including

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anthocyanin pigmentation (Xu et al. 2019, 2020). However, consumer’s perceptions of transgenic crops vary widely across geographical regions and may represent an important barrier for a general wide acceptance of carrot cultivars developed by these methods. However, it can be speculated that food colorants derived from transgenic carrots may be accepted with less resistance than transgenic carrots for fresh consumption, especially considering the (publically perceived?) negative health effects associated with the consumption of some synthetic colorants.

3

Other Non-anthocyanin Phenolics

3.1

Introduction and Biosynthesis

As described for anthocyanins, phenolic compounds are secondary metabolites composed of an aromatic ring bearing one or more hydroxyl groups, and they exert similar functions in the plant as described for their colored-relatives anthocyanins, conferring protection against biotic and abiotic stresses (e.g., drought, salinity, ultraviolet radiation, extreme temperatures, phytopathogenic and predator attacks, etc.) and contributing to the organoleptic properties of plant foods (reviewed by Balasundram et al. 2006). Phenolic compounds can be subclassified as phenolic acids, flavonoids, tannins, lignans, stilbenoids, and curcuminoids. Carrot roots accumulate mainly phenolic acids, among which HCAs large predominate, being chlorogenic acid the major carrot HCA (Sharma et al. 2012). These phenolic acids are formed from the phenylpropanoid pathway, a late branch of the shikimic acid pathway. Figure 4 illustrates the core part of the pathway leading to HCAs and chlorogenic acid synthesis. HCAs are produced from phenylalanine through a series of reactions catalyzed by several enzymes, the first one being phenylalanine ammonia lyase (PAL), which converts phenylalanine to cinnamic acid. Cinnamic acid is then converted to coumaric acid by “cinnamate 4-hydroxylase” (C4H), and then to 4-coumaroyl CoA by “4-coumarate: CoA ligase” (4CL). 4-coumaric acid and 4-coumaroyl CoA represent important branch points in the phenylpropanoid pathway from which other subclasses of phenylpropanoids can be produced, such as coumarins, lignins, flavonoids, and hydroxybenzoic acids (another type of phenolic acids). 4-coumaroyl CoA is then converted to 4-caffeoyl quinic acid, known as chlorogenic acid, by a series of reactions catalyzed by the enzymes “hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase” (HCT), “hydroxycinnamoyl CoA quinate hydroxycinnamoyl transferase” (HQT), and “4-coumarate-3-hydroxylase” (C3H) (Fig. 4).

3.2

Chemical Diversity and Distribution

Total phenolics content (TPC) in the carrot root varies broadly across accessions and root color phenotypes, as measured spectrophotometrically (Singleton et al. 1999; Fukumoto and Mazza 2000), with estimated ranges in different germplasm collections of 19.8–342.2 mg/100 g fw (Leja et al. 2013), ~25.9–426 mg/100 g fw

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Phenylalanine PAL Cinnamic acid Coumarins

C4H 4-Hydroxybenzoic acid

4-Coumaric acid Lignins

4CL

4-Coumaroyl CoA HQT

CHS

HCT

4-Coumaroyl quinic acid

4‚2´,4´,6´-Tetrahydroxychalcone CHI

C3H

Naringenin

4-Caffeoyl quinic acid (CGA)

Anthocyanins Tannins

Flavonols Flavones

Isoflavonoids

Fig. 4 Simplified phenylpropanoid biosynthetic pathway leading to the production of chlorogenic acid. Abbreviations used: PAL phenylalanine ammonia-lyase, C4H Cinnamate 4-hydroxylase, 4CL 4-coumarate: CoA ligase, HCT hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyl transferase, HQT hydroxycinnamoyl CoA quinate hydroxycinnamoyl transferase, C3H 4-coumarate3-hydroxylase, CHS chalcone synthase, CHI chalcone isomerase, CGA chlorogenic acid (4-caffeoylquinic acid) (Reproduced from Bartley et al. (2016))

(considering a dry matter content of 11% for expressing values on a fresh weight basis) (Sun et al. 2009), and 8.7–74.6 mg/100 g fw (Alasalvar et al. 2001). Because anthocyanins account for a large proportion of the TPC in purple carrots, the latter had much higher TPC than other root colors, with overall TPC means for purple carrots being 9 times (Leja et al. 2013) and 13 times higher than mean TPC in other carrot colors (Sun et al. 2009). In non-purple carrots, TPC levels varied little among the different root colors, with reported overall ranges of means – for white, yellow, orange, and red carrot cultivars – of 18–31, 24.2–40.4, and 18.3–25.9 mg/100 g fw, with mean differences among these root colors being statistically insignificant or marginally significant (Sun et al. 2009; Leja et al. 2013). By means of HPLC analysis, it was possible to precisely quantify non-anthocyanin TPC in purple and non-purple carrot cultivars, revealing significantly greater mean values in purple carrot (74.6 mg/100 g fw) than in orange (16.2 mg/100 g fw), yellow (7.7 mg/ 100 g fw), and white (8.7 mg/100 g fw) carrots (Alasalvar et al. 2001). Similar results were obtained in another HPLC-based study of phenolic composition in 10 carrot cultivars with different root colors grown across two locations and 3 years, reporting greater non-anthocyanin TPC in purple carrots (with a range of ~28.6–101.2 mg/100 g fw) than red (~ 0.07–6.41 mg/100 g/fw), orange (~ 0.09–3.41 mg/100 g fw), yellow (~ 0–0.93 mg/100 g fw), and white carrots (~ 0–0.77 mg/100 g fw) (for comparison purposes, values were converted on a basis of fw, considering 11% of dry matter for all the cultivars) (Kramer et al. 2012).

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In the HPLC-based studies, non-anthocyanin TPC in different root color cultivars varied in the following rank order: purple > red > orange > yellow ≈ white (Alasalvar et al. 2001; Kramer et al. 2012). Altogether, data from these studies indicate that purple carrots generally have not only greater TPC but also greater total concentration of colorless phenolics than carrots of other colors. Among the non-anthocyanin phenolics, HCAs and derivatives largely predominate in all the root color phenotypes (Kramer et al. 2012), including typical orange carrots where HCAs accounted for 73.7–99.7% of the root TPC (Zhang and Hamauzu 2004). With a few exceptions, in most of the cultivars analyzed to date, chlorogenic acid (5-O-transcaffeoylquinic acid) is the predominant HCA and – more generally – the predominant phenolic compound found in carrot roots. According to Kramer et al. (2012), this compound was detected in highest quantities in purple carrots, accounting for 54.1–79.7% of the total non-anthocyanin phenolics, while it showed broader ranges of variation in the other root colors, representing 5.1–64.9%, 13.2–68.2%, and 0–68.7% in red, orange, and yellow carrots, respectively, as varying across different growing locations and years. White carrots were the exception, with chlorogenic acid accounting for only 0.1–12.1% of the total phenolics, with vanillic acid derivatives being the predominant phenolics found in their roots, representing 10.4–83.6% of the TPC. Also, in one of the yellow cultivars evaluated (Yellowstone), ferulic acid and vanillic acid derivatives predominated over chlorogenic acid (Kramer et al. 2012). According to Alasalvar et al. (2001), chlorogenic acid represented 51–72% of the non-anthocyanin TPC in carrots of different root color (purple, orange, yellow, and white), whereas Zhang and Hamauzu (2004) reported that this compound accounted for 42–62% of the TPC in two orange-rooted cultivars. Besides the generally predominant chlorogenic acid, other phenolic acids that can be found in sufficient quantities in some carrot genetic backgrounds are derivatives of ferulic, vanillic, and caffeic acids (Alasalvar et al. 2001; Kramer et al. 2012). In orange carrots, the concentration of phenolics varies across root tissues in the following order: periderm > phloem > xylem. According to Zhang and Hamauzu (2004), the root periderm only accounts for 11% of the carrot fresh weight, yet it provides 54.1% of the TPC in the root, whereas the phloem and xylem tissues provide 39.5% and 6.4% of the root TPC, respectively. Coincidently, chlorogenic acid levels and AOC in these three tissues followed the same relative ranking (i.e., periderm > phloem > xylem), with the periderm providing 67.4–80.1% of the total AOC and 66.5–88.2% of the total chlorogenic acid content, the phloem 7.5–9.6% and 10.7–29.6%, and the xylem 3.2–7.5% and 1.1–4.0%, for these two variables, respectively. These data illustrate the tissue-specific distribution of phenolic compounds in the carrot root and strongly suggest that chlorogenic acid is the major phenolic and antioxidant agent in orange carrots. In line with the proposed role of phenolics in conferring protection to the plant against biotic and abiotic stresses, carrot TPC, chlorogenic acid, and AOC have been shown to concomitantly increase in response to numerous postharvest stimuli/ stresses, including ultraviolet light radiation and wounding (Surjadinata et al. 2017), UVC light and hyperoxia (Formica-Oliveira et al. 2016), storage in modified

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atmosphere (Pace et al. 2020), and water loss and wounding (Becerra-Moreno et al. 2015). In the field crop, nitrogen fertilization, boron deficiency, the cultivation system (organic vs. conventional), and the growing location and year can also influence carrot phenolic levels and AOC (Søltoft et al. 2010; Kramer et al. 2012; Singh et al. 2012).

3.3

Carrot Phenolics and Human Health

The consumption of polyphenols-rich plant foods has been associated with various health benefits, including maintenance of normal blood glucose and cholesterol levels, prevention or delayed onset of cognitive decline, and decreased risk of cardiovascular disease, diabetes, neurodegenerative disorders, and some cancer types (reviewed by Soto-Vaca et al. 2012). These general health-enhancing effects have been attributed – to a considerable extent – to the antioxidant and antiinflammatory properties of phenolic compounds. Based on data concerning the relative impact on health of different phenolic subclasses, mainly with regard to their antioxidant, anti-inflammatory, and antiproliferative effects, the average dietary intake of polyphenols was estimated to be 1058 mg per day for males and 780 mg for females, with half of these composed of HCAs, 20–25% of flavonoids, and 1% anthocyanins (Stevenson and Hurst 2007). A number of health-related studies, conducted in vitro and in vivo, have used purple carrot extracts as sources of anthocyanins and other phenolics, evidencing significant and substantial antioxidant, anti-inflammatory, and antiproliferative effects (described in Sect. 2.2.3). In germplasm evaluations including carrots of diverse geographical origins, root color, and genetic structure, significant and strong positive correlations have been found between TPC and AOC (evaluated by different methods), with reported correlation coefficient (r) values of 0.98–0.99 (for all root colors included) and 0.64–0.82 (considering only non-purple carrots) (Leja et al. 2013), 0.99 (includes all root colors) (Sun et al. 2009), 0.98–0.99 (includes only orange carrots) (Zhang and Hamauzu 2004), 0.62–0.93 (includes only orange carrots) (Surjadinata and Cisneros-Zevallos 2017), and 0.92 (only orange carrots) (Alegria et al. 2016). Similarly, significant positive and strong correlations between chlorogenic acid content and AOC were found, with estimated r values of 0.91 (Sun et al. 2009) and 0.89 (Alegria et al. 2016). Altogether, these data, and the fact that chlorogenic acid is the major carrot phenolic compound, strongly suggest that phenolics in general, and chlorogenic acid in particular, are largely responsible for carrot antioxidant properties. Bioavailability is a relevant aspect for phenolic compounds being able to exert their health benefit effects in the organism. Generally, there is limited absorption despite the epidemiological studies showing significant health benefits associated with polyphenolic consumption. According to Soto-Vaca et al. (2012), the absorption of phenolic compounds in humans is a multifactorial, complex, and highly variable phenomenon, influenced by the type of phenolic compound, its molecular structure, the accompanying food matrix, interactions with other macromolecules and minerals (e.g., forming iron-chelating complexes), the processing by the

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microbiome and resulting profile of phenolic metabolites, among many other factors. Because phenolics are generally considered to have poor bioavailability, there is considerable amount of literature – and ongoing studies – on these factors affecting the absorption of phenolic compounds (reviewed by Soto-Vaca et al. 2012).

3.4

Genetics of Carrot Phenolics

Compared to other nutraceutical classes, very little is known about the genetic regulation of non-anthocyanin carrot phenolics. Thus, very few studies have investigated possible genes involved in carrot HCAs and chlorogenic acid synthesis. A first work by Becerra-Moreno et al. (2015) examined the effect of water stress and wounding, applied alone or combined, on the expression of structural genes of the early shikimic acid pathway and later phenylpropanoid pathway, estimated by RT-qPCR analysis, along with the accumulation of related phenolic metabolites. Their findings indicate that both pathways are activated by these stresses applied alone, being wounding a stronger activator than water stress, while both stresses combined acted synergistically and showed the strongest pathway activation. Water stress favored the lignification process, while wounding led to the preferential accumulation of shikimic acid, phenolic compounds, and lignin. The increase in these phenolic compounds due to both types of stresses combined was accompanied by upregulation of PAL, C4H, 4CL, “caffeoylCoA3-O-methyl transferase” (CCoAOMT), “cinnamoyl-CoA reductase” (CCR), and “cinnamyl alcohol dehydrogenase” (CAD) genes involved in the phenylpropanoid pathway, whereas three upregulated genes of the early shikimic pathway were found, namely “3-deoxy-D-arabino heptulosonate 7-phosphate synthase” (DAHP synthase), 5-enolpyrovylshikimate 3-phosphate synthase (EPSP synthase), and chorismate mutase-prephenate dehydratase (CMPD). Another study by Bartley et al. (2016) analyzed the expression of 12 structural genes (4 PAL, 2 CHS, and 1 each of C4H, 4Cl, HCT, HQT, C3H, and CHI) and 7 transcription factors (4 MYBs and 1 each of HY5, ERF, and UVR8) described or predicted earlier as being involved in phenylpropanoid synthesis in carrot and other species, in carrot root slices irradiated and not irradiated with UV-B light followed by incubation at 15  C and 45% relative humidity for 6 days. Increases in gene expression – varying in intensity, duration of the peak maximum, and time of onset from the application of the UV treatment – after UV radiation were reported for all the structural genes except CHI, and most of the regulatory genes analyzed [except for ERF, which was not induced, and one of the MYB TF (termed DcPcMYB1) showing very little induction by UV] relative to their UV-untreated counterparts. These increases in gene expression by the UV treatment were paralleled with increases in the content of chlorogenic, caffeic, ferulic, and coumaric acids, compared to the content in untreated samples. These results suggest that most of the structural and regulatory genes evaluated in their study are involved in the UVB-induced synthesis of carrot HCAs. While these two studies revealed genes involved in postharvest stress-induced synthesis of phenolic compounds, additional comparative studies using genetic

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backgrounds varying in phenolic concentration and/or profile are necessary to identify genes influencing carrot phenolic levels under non-stressed field-cultivation conditions. Furthermore, in order to identify hierarchical genes controlling root phenolic content and profile, such studies should be combined with, or preceded by, linkage or association mapping approaches to localize the genomic region of the trait locus or QTLs conditioning such compositional variations, to then search for candidate genes – in the region of interest – using comparative gene expression analyses in contrasting phenotypes. This approach has been successfully used for identifying key genes controlling the type and content of other carrot nutraceuticals, namely anthocyanins and carotenoids (discussed in Sects. 2 and 6, respectively).

4

Polyacetylenes

4.1

Introduction

Polyacetylenes are a large and diverse chemical class of bisacetylenic oxylipins derived from fatty acids, characterized by the presence of at least two, usually conjugated, triple carbon-carbon bonds. Polyacetylenes are widely distributed in the plant kingdom, but they are also present in fungi, lichens, moss, marine algae, and invertebrates. The majority of the more than 2000 known polyacetylenes have been isolated from higher plants and notably from the botanically related plant families Apiaceae, Araliaceae, and Asteraceae (Dawid et al. 2015). The predominant structural types of polyacetylenes are different between Apiaceae and Asteraceae. In the Apiaceae and the closely related Araliaceae family, C17-polyacetylenes with a variable number of additional double bonds and hydroxyl functions are dominating, while Asteraceae family members accumulate structurally diverse polyacetylenes. The most common C17-polyacetylenes are falcarinol (FaOH) and falcarindiol (FaDOH). They occur in the edible and nonedible parts of vegetables and herbs of the Apiaceae family including carrots, parsnip, fennel, celery, and parsley. Falcarinol-type polyacetylenes, also called as falcarins (Santos et al. 2022), are less common in other food species, although falcarinol, falcarindiol, and related C14- and C15-polyacetylenes have been described for Solanaceae species like tomatoes and aubergines, where they are known to function as phytoalexins (Christensen 2011). Excessive amounts of falcarinol-type polyacetylenes have often been reported to contribute to the undesirable bitter off-taste of carrots and their products such as juice or puree. Quantitative chemical analyses combined with sensory perception tests indicate that falcarindiol is highly correlated with bitterness, whereas falcarinol is not (Czepa and Hofmann 2004). Apart from that, several in vitro studies have confirmed that falcarinol is among the most cytotoxic polyacetylenes in Apiaceae vegetables and, according to the current state of knowledge, has a higher bioactivity than falcarindiol (Christensen 2020). The accumulation of falcarins in external plant tissue layers such as the root periderm is also in accordance with their assumed roles in plant defense, either as protective agents present constitutively in plant tissues or induced in response to

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pathogen attack. For instance, in carrots, falcarindiol could inhibit the growth of the fungal leaf blight pathogen Alternaria dauci during in vitro tests, and the polyacetylene levels increased in response to A. dauci infection (Lecomte et al. 2012). However, compared with the knowledge available for polyacetylene effects on human health, there is still much to be learned about the role of these compounds in plant defense. With regard to putative effects of polyacetylenes on human health, falcarins have demonstrated numerous interesting bioactivities including antimicrobial as well as anti-inflammatory, antiplatelet-aggregatory, neuritogenic, and serotonergic effects. In addition, the cytotoxicity of falcarin-type polyacetylenes on human cancer cells and their proposed anticancer effects indicate that these compounds may contribute to the nutraceutical effects of carrots (Christensen 2011). Despite their interesting biological functions, the genetic basis of the structural diversity and function of falcarins is widely unknown. A better understanding of the genetics of falcarin production in carrot roots might support breeding of carrot cultivars with tailored polyacetylenes levels for food production or nutraceuticals. The following sections summarize the knowledge on the distribution of falcarins in carrots, their bioactivity, biosynthesis, genetics, and genomics. A perspective is given for future carrot breeding programs aimed at elevating the levels of these specific polyacetylenes in specific carrot cultivars with high human health potential.

4.2

Diversity, Quantification, and Distribution

Among the more than 1400 polyacetylenes known to date in higher plants, a subset of 14 structurally related bisacetylenic oxylipins has been identified in Daucus carota. The first polyacetylenes isolated from carrots were falcarinol, falcarindiol, and falcarindiol-3-acetate. Besides these quantitatively predominating polyacetylenes which are typically C17 compounds with conjugated triple bonds, nine additional C17 falcarins were identified in D. carota by Schmiech et al. (2009), and Busta et al. (2018) recently identified two additional carrot polyacetylenes, falcarintriol-8-acetate and falcarintriol-9-acetate. A subset of five falcarin-type polyacetylenes present in carrot in noteworthy concentrations is shown in Fig. 5. A joining molecular characteristic of falcarin structures is their conjugated carbon– carbon triple bond system. Using this feature as a reference point to compare diverse falcarin structures by atom-to-atom correspondence analysis, a falcarin structural similarity network was constructed for 80 representative falcarins from the four families Apiaceae, Asteraceae, Araliaceae, and Solanaceae (Santos et al. 2022). This network suggests that falcarin metabolism may have diverged in these lineages and might support future efforts to elucidate falcarin biosynthesis in specific taxa. Quantification of falcarinol-type polyacetylenes in tissues of carrots and other plants is generally based on chromatographic methods such as several HPLC and GC-MS methods. For the isolation of falcarins from plant extracts a combination of column chromatography (CC) and preparative and semi-preparative high-performance liquid chromatography (HPLC) have been used for the isolation of relative large amounts of these polyacetylenes, allowing the analysis of their bioactivity, for

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Fig. 5 Chemical structures of falcarin-type polyacetylenes present in carrot roots and leaves: (1) falcarinol, (2) falcarindiol, (3) falcarindiol-3-acetate, (4) falcarintriol-9-acetate, and (5) falcarintriol-8-acetate (Modified from Santos et al. (2022))

example, in preclinical studies. Modified qualitative and quantitative chromatographic methods have been described for falcarins, including analytical HPLC combined with UV-detection (Zidorn et al. 2005), HPLC with diode array detection (HPLC/DAD) (Christensen and Kreutzmann 2007), and capillary gas chromatographic techniques (GC–FID and/or GC–MS) (Czepa and Hofmann 2004). An alternative method based on plasma samples by liquid chromatography combined with mass spectrometry (LC–MS/MS) was used for the quantification of falcarinol and related polyacetylenes (Christensen and Brandt 2006). The nondestructive FT-Raman spectroscopic approach has been reported to differentiate the main falcarin compounds occurring in different tissues of a single plant (Krähmer et al. 2016). In many reports, it has been shown that the concentration of falcarin-type polyacetylenes depends on factors such as genotype, developmental stage, cultivation, postharvest storage, and processing (for review, see Dawid et al. 2015). However, considering the numerous factors that influence the falcarin levels and the circumstances under which falcarin concentrations were obtained in the different studies, partly using different analytical methods, the falcarin levels published in different carrot papers are difficult to compare. Moreover, falcarin accumulation patterns in the carrot plant may be influenced by several abiotic and biotic stress factors. For instance, it has been shown that water stress due to drought or waterlogging may influence the major falcarin contents (Lund and White 1990), but previously it was reported that the genotypic effect (i.e., cultivar) appeared to have a stronger impact under these stress conditions (Schmid et al. 2021). The accumulation of falcarins can vary strongly among carrot cultivars, and major differences were found between cultivated orange carrots and differently colored carrots such as white, yellow, and purple cultivars (Czepa and Hofmann 2004; Schulz-Witte 2011). Recently, two main polyacetylenes, falcarinol and falcarindiol, were quantified by HPLC/DAD in different taproot tissues of seven carrot cultivars with purple, yellow, and orange taproot colors. Periderm tissue of the two purple cultivars, ‘Deep Purple’ and ‘Anthonina’, accumulated on average 580 or 720μg/g

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dry weight (DW) falcarinol, respectively, but in the three orange cultivars significantly lower falcarinol levels ranging from 50 to 240μg/g DW were found. With regard to falcarindiol in root periderm, the purple cultivar ‘Deep Purple’ showed the highest concentration of 1230μg/g DW, whereas the levels of the orange cultivars were in the range of 450–650μg/g DW (Dunemann and Böttcher 2021). The falcarin distribution in the carrot plant can vary considerably among the different plant organs and even within the different root segments. The most abundant falcarin in cultivated carrots is falcarindiol, and the highest total falcarin levels are generally found in the root periderm (Czepa and Hofmann 2004). Busta et al. (2018) analyzed tissuespecific accumulation of the five falcarins shown in Fig. 5 in the orange cultivar ‘Danvers’ and measured the highest total falcarin level in the periderm tissue, with falcarindiol as the dominating compound. In the purple cultivars ‘Anthonina’ and ‘Deep Purple’, the levels of falcarinol and falcarindiol were also significantly increased compared with phloem, xylem, and leaf tissue samples (Dunemann and Böttcher 2021). Detailed analysis of the spatial distribution of falcarins from the top to the bottom as well as from the outer phloem to the inner xylem of carrot roots indicate specific accumulation pattern dependent of the falcarin compound (Schmiech 2010). Results from in situ Raman spectroscopy experiments have indicated that polyacetylenes are located in vascular bundles in the young secondary phloem as well as in pericycle oil channels located close to the periderm layer. Moreover, analysis of the falcarin distribution in roots of some carrot wild relatives, for instance, D. carota ssp. commutatus, showed that the whole phloem tissue was enriched for falcarins with a maximum concentration near the pericyclic parenchyma (Baranska et al. 2005). Two novel falcarins detected previously in carrot cultivar ‘Danvers’ reached concentrations in the leaf, petiole, and root xylem, which are in the same magnitude as the levels of falcarinol, falcarindiol, and falcarindiol-3-acetate, with the difference that these novel falcarins appear to be accumulated preferably in the aboveground plant parts (Busta et al. 2018). In the rare studies focused on polyacetylene accumulation in carrot wild relatives, it was shown that Daucus species and subspecies can contain often much higher falcarin contents than cultivated carrots (Schulz-Witte 2011). The concentration of falcarinol and falcarindiol in some wild D. carota accessions and other wild carrot (sub-) species, such as D. c. maximus, D. c. maritimus, or D. c. halophilus can be up to 10 or even 20 times higher in comparison to cultivated forms of carrots. Moreover, comparative quantification of falcarinol, falcarindiol, and falcarindiol-3-acetate in more than 100 accessions of wild carrot relatives revealed a large variation for falcarin content, indicating the enormous genotypic variability for this natural substance in the genus Daucus. Falcarins such as falcarinol and falcarindiol can also be produced in vitro in large amounts by carrot hairy root cultures obtained after genetic transformation with the soil bacterium Rhizobium rhizogenes. HPLC/DAD quantification of falcarins in freeze-dried hairy root samples derived from different carrot cultivars revealed concentrations of these compounds that are considerably higher than reported to date for carrot root periderm tissue. The average falcarinol contents of the hairy roots varied from 1200 to 3000 μg/g DW, and the concentrations of falcarindiol were in the same magnitude (Dunemann and Böttcher 2021).

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Bioactivity and Relevance for Human Health

Bioactive C17-falcarins were first described for traditional medicinal plants such as ginseng (Panax ginseng, Araliaceae), the wild carrot Queen Anne’s lace (Daucus carota subsp. carota, Apiaceae), and the understory native shrub Devil’s Club (Oplopanax horridus, Araliaceae), all members of the closely related Apiaceae and Araliaceae families. Later it was found that the edible members of the Apiaceae family such as carrot, parsnip, celery, fennel, and parsley also contained falcarin-type polyacetylenes, and it was assumed that the content of these compounds, and falcarinol in particular, might be responsible for the beneficial effects of carrot consumption (Christensen and Brandt 2006). On the other hand, these phytochemicals might have some unwanted toxic side effects in plant foods. Some polyacetylenes, such as falcarinol, are powerful skin sensitizers and known to be neurotoxic in high concentrations, but at nontoxic concentrations, they may function as highly bioactive compounds with potential health-promoting properties. The number of reports about biological and pharmacological activities of polyacetylenes and in particular the contribution to health benefits associated with C17-falcarins is increasing. In a recent review article, the cytotoxic, anti-inflammatory, and anticancer effects of C17-falcarins and other acetylenic oxylipins from terrestrial plants including Apiaceae species are comprehensively described, and their possible mechanisms of action and structural requirements for optimal cytotoxicity are presented in detail (Christensen 2020). With regard to anticancer actions of polyacetylenes in in vitro studies, both falcarinol and falcarindiol have been shown to have toxicity against a large variety of cancer cells including gastric, skin, intestine, colorectal, lymphoma, leukemia, breast, and lung, but their cytotoxic potential depends on the cell lines (Christensen 2020). Overall, from several in vitro studies it has been concluded that falcarinol is generally more cytotoxic than falcarindiol in many different cell types (Warner 2019). Furthermore, falcarinol and falcarindiol may have a synergistic inhibitory effect on cell proliferation. In the study of Purup et al. (2009), it was demonstrated that the cytotoxicity of lipophilic extracts from different carrot cultivars depended on the amounts of falcarinol, falcarindiol, and falcarindiol-3-acetate in the extracts. It was shown that falcarinol can reduce cell proliferation of Caco-2 cells at 2.5 μg/mL but maintains healthy cells at the same concentration. This was the case up to 10μg/ mL at which concentration it significantly reduced proliferation of both cell types. Moreover, it was shown that the cytotoxic effect of falcarinol on Caco-2 cells was enhanced synergistically when combined with falcarindiol in different ratios. Falcarindiol was less potent in this experiment but reduced Caco-2 proliferation up to 20 μg/mL with no effect on healthy cells (Purup et al. 2009). Falcarinol was reported to have high cytotoxic activity to leukemia (L-1210), mouse fibroblastderived tumor cells (L-929), mouse melanoma (B-16), and human gastric adenocarcinoma (MK-1) cells, showing the lowest ED50 values in the MK-1 cancer cells (Christensen 2011). Falcarindiol and its derivative falcarindiol-3-acetate isolated from carrots were able to induce apoptosis in different leukemia cell lines (CCRF-CEM, Jurkat, and MOLT-3). Falcarinol only caused induction of apoptosis

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in CCRF-CEM cell lines but was the most cytotoxic substance on leukemia cells (Zaini et al. 2012). Falcarin-type polyacetylenes have also been shown to bind covalently to cysteine in enzymes such as mitochondrial aldehyde dehydrogenases (ALDHs) in cancer cells leading to a reduction of activity (Heydenreuter et al. 2015). Reduction of the activity of ALDHs may lead to oxidative stress and endoplasmic reticulum (ER) stress causing cell injuries, cell cycle arrest, and apoptosis, and thus could be one of the mechanisms of action that could explain the cytotoxicity of falcarins (Christensen 2020). Falcarins may also play a role in cancer chemotherapy. For instance, it has been demonstrated that falcarins function as inhibitors of the breast cancer resistance protein BCRP/ABCG2, which is an efflux transporter involved in breast cancer chemotherapy resistance (Tan et al. 2014). Bioactive C17-polyacetylenes may also inhibit the formation of proinflammatory cytokines and inflammatory enzymes such as COXs and LOXs indicating that inhibition of these inflammatory-promoting substances might be an important mechanism of cancer prevention (Christensen 2020). While there is strong evidence that polyacetylenes may have anticancer effects in vitro, much less information is available about the mechanisms and effects in vivo. A small number of investigations with rodents have been conducted with the aim to study both the effect of carrots and isolated falcarins as dietary supplements in feeding studies. However, little is known about their effects in vivo in humans. Rat feeding experiments with purified falcarinol and falcarindiol suggest preventing effects of these polyacetylenes on the development of colorectal cancer (CRC). Both falcarins can have an inhibitory effect on certain inflammatory markers in neoplastic lesions, and it has been proposed that falcarins may act as selective COX-2 inhibitors in relation to CRC prophylactics (Kobaek-Larsen et al. 2019). A large prospective cohort study in a Danish population of 57,053 individuals examining the risk of being diagnosed with CRC indicated a CRC-preventive effect of carrot intake. Selfreported intake of 2–4 raw carrots per week (>32 g/day) was associated with a 17% decrease in risk of CRC (Deding et al. 2020). These results and the results from the rat feeding experiments suggest a CRC-preventive effect of carrot falcarins. Epidemiological studies have also shown that carrot intake is inversely associated with cardiovascular heart disease (CHD). In a prospective study, a 25 g/day increase in the intake of carrots was associated with a 32% lower risk of 10-year incidence of CHD (Oude Griep et al. 2011). One way the polyacetylenes could be affecting CHD risk is through modulation of platelet activity in the blood. Antiplatelet aggregatory abilities of polyacetylenes are most likely due to their anti-inflammatory activity in relation to COXs, LOXs, and other enzymes (Warner 2019). Furthermore, falcarins may also have impact on type 2 diabetes. Falcarinol and falcarindiol from carrots may function as ligands for nuclear receptors such as peroxisome-proliferatoractivated receptors (PPARs), suggesting their usage as partial PPAR agonists with possible antidiabetic properties (El-Houri et al. 2015). Falcarinol was also identified as an inverse agonist of the cannabinoid receptor CB1. Acting by selectively alkylating the anandamide binding sites, falcarinol can increase the expression of chemokines in the skin involved in the induction of allergic reactions (Leonti et al. 2010). In addition, GABA receptors are exquisitely sensitive to polyacetylenic

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oxylipins. In comparison to the activity of falcarindiol, falcarinol has a higher affinity for GABA receptors and a substantially different profile of pharmacological actions. Taken together, falcarin-type polyacetylenes are highly bioactive natural products that may be used in the prevention and treatment of cancers but likely possess additional positive properties with regard to human health and well-being. The health-promoting effects of carrot falcarins should be evaluated and confirmed in further preclinical and clinical studies in future.

4.4

Biosynthesis, Genetics, and Genomics

Compared with the extensive research concerning the analytical and biochemical identification and characterization of plant falcarin-type polyacetylenes, and the relatively large number of studies about their bioactivity, by far less is known about the biosynthesis, genetics, and genomics of falcarins. Major advances have only recently been made toward understanding their biosynthesis (reviewed by Santos et al. 2022), and carrots are among the species, where most knowledge exists. In carrots and other plants, falcarin biosynthesis starts from unsaturated fatty acids such as oleic acid and linoleic acid. Results of several metabolic studies have pointed out that a diverse pathway from linolenic acid to “unusual” fatty acids, such as crepenynic and dehydrocrepenynic acid, is the major route for the biosynthesis of falcarins (Minto and Blacklock 2008). A proposed model for falcarin biosynthesis is shown in Fig. 6. The enzyme primarily responsible for the synthesis of linoleic acid from oleic acid is a Δ12-fatty acid desaturase. Numerous divergent forms of FATTY ACID DESATURASE 2 (FAD2) enzymes with diversified functionalities in fatty acid modification are also known to have diversified functionalities in fatty acid modification, such as hydroxylation, epoxidation, and the formation of acetylenic bonds and conjugated double bonds (Minto and Blacklock 2008). Some functionally divergent FAD2 enzymes are multifunctional, such as the bifunctional hydroxylase/desaturase from Lesquerella fendleri. FAD2 enzymes that introduce a triple bond within a fatty acid are designated as acetylenases. The first FAD2 acetylenase gene cloned was termed Crep1 and derived from Crepis alpina, a herbaceous species from the Compositae family. Crep1 encodes a functional acetylenase and its activity leads to the accumulation of the acetylenic fatty acid crepenynic acid in C. alpina seeds (Minto and Blacklock 2008). The genomes of other plant families like Apiaceae, Araliaceae, and Asteraceae also harbor FAD2 acetylenase genes, although only a few members of these families accumulate acetylenic fatty acids in their seeds, a fact that raises questions about the role of these divergent FAD2s in the plant. The FAD2 gene family has been extensively studied in plants at the molecular and biochemical levels. Since cloning of the first plant FAD2 gene in Arabidopsis thaliana (Okuley et al. 1994), additional FAD2 genes from other species have been described and functionally characterized, including members with acetylenase activity. Although only a single FAD2 gene was found in Arabidopsis, in most other

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Fig. 6 Proposed biosynthetic steps of production of falcarin-type polyacetylenes in carrots. Carrot FAD2 genes functionally characterized by Busta et al. (2018) are shown at their presumed positions. FAD2 desaturase genes are in bold letters, and FAD2 acetylenase genes are shaded in gray. Bifunctional FAD2 desaturase genes are underlined. FAD2 gene designation was according to Table 4 (Adapted from Cavagnaro (2019) and Santos et al. (2022))

plant species, multiple FAD2 homologues have been reported. For example, seven FAD2 gene family members were identified in soybean, and nine each in cotton and tomato (Lee et al. 2020). Species with the largest known number of FAD2s are all family members of the Asteraceae, Apiaceae, and Araliaceae. The carrot genome contains at least 30 FAD2 genes (Dunemann et al. 2022). In sunflower (Helianthus annuus, Asteraceae), about the same number of FAD2 genes is present, and for ginseng (Panax ginseng, Araliaceae), over 50 FAD2 gene copies have been reported recently (Santos et al. 2022). A major contribution for the inventory and putative function of carrot FAD2 genes was made by the work of Busta et al. (2018), which identified 24 carrot FAD2s. To identify which of these genes participate in falcarin biosynthesis, six FAD2 genes were selected for functional analysis by screening of published, tissue-specific carrot transcriptomic data sets for co-expression of genes that are highly expressed in root periderm. These candidate genes were heterologously expressed, individually and in combination, in yeast and A. thaliana,

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resulting in the identification of one canonical FAD2 that converts oleic to linoleic acid and three divergent FAD2-like acetylenases that convert linoleic into crepenynic acid (Busta et al. 2018). In addition, two bifunctional FAD2s with Δ12 and Δ14 desaturase activity were found (DCAR_013547, DCAR_019786) that are involved in two biosynthetic steps, the conversion of oleic acid into linoleic acid and the conversion of crepenynic into dehydrocrepenynic acid. Three of the characterized FAD2s are located in a tandem array of six FAD2genes, two of which encode FAD2 acetylenases and one encoding a bifunctional Δ12/Δ14 desaturase, in a small region (29.30–29.35 Mbp) of carrot chromosome 4 (Busta et al. 2018). Tandemly arrayed FAD2 genes, which might represent biosynthetic gene clusters, were previously described also in tomato, lettuce, and sunflower and might have been originated from local tandem duplications, as suggested from phylogenomic and microsyntenic analyses (Busta et al. 2018). The largest carrot FAD2 cluster in the carrot genome, consisting of nine FAD2s, is located on chromosome 8, spanning the genomic region 20.87–21.54 Mbp (Dunemann et al. 2022). This gene cluster also contains the newly discovered FAD2 genes DcFAD2-25 to DcFAD2-28. The seven new carrot FAD2 genes identified recently after a reannotation of the whole carrot genome sequence extend the total number of Daucus FAD2s to 31. The total list of known carrot FAD2s and a proposed renaming are shown in Table 3. The newly predicted FAD2 genes DcFAD2-29, DcFAD2-30, and DcFAD2-31 are located as unclustered genes on chromosomes 1, 3, and 4. A phylogenetic analysis of the carrot FAD2s (Fig. 7) showed that DcFAD2-25, DcFAD2-26, DcFAD2-27, and DcFAD2-28 are located in a common clade containing ten known Daucus FAD2s which have been classified as divergent FAD2s. This clade contains also the genes DcFAD2-6 (DCAR_017011), DcFAD2-7 (DCAR_013552), and DcFAD2-8 (DCAR_013548) which were functionally characterized by Busta et al. (2018) as Δ12-acetylenases. These three genes are also highly similar (amino acid identity >95%) to the parsley gene PcELI12, which was identified as a pathogen-inducible FAD2 acetylenase gene (Cahoon et al. 2003). Table 3 List of 31 Daucus carota FAD2 gene models sorted by their physical position on the assembled 9 carrot chromosomes according to the whole-genome sequence (Iorizzo et al. 2016) and the carrot FAD2 inventory published by Busta et al. (2018) and Dunemann et al. (2022) Chrom. 1 1 1 3 3 3 4 4 4 4 4 4 4 5 5 5

Gene name DcFAD2-29 DcFAD2-18 DcFAD2-3 DcFAD2-30 DcFAD2-14 DcFAD2-15 DcFAD2-31 DcFAD2-22 DcFAD2-7 DcFAD2-17 DcFAD2-16 DcFAD2-8 DcFAD2-19 DcFAD2-13 DcFAD2-6 DcFAD2-23

Locus name Not annotated DCAR_002026 DCAR_003420 Not annotated DCAR_011708 DCAR_011709 Not annotated DCAR_013553 DCAR_013552 DCAR_013551 DCAR_013549 DCAR_013548 DCAR_013547 DCAR_017010 DCAR_017011 DCAR_017012

Genomic Start 2623973 24320363 38720179 11882922 39497199 39502342 10151245 29308974 29312792 29318510 29340355 29343013 29348356 10549274 10559828 10593543

posion Protein Genomic Stop lenght Chrom. Gene name Locus name Start 2625091 373 5 DcFAD2-24 DCAR_017923 24911311 24321512 382 5 DcFAD2-11 DCAR_019786 41732457 38721331 383 5 DcFAD2-20 DCAR_019787 41738175 11884034 371 6 DcFAD2-10 DCAR_020161 33657256 39498366 388 6 DcFAD2-12 DCAR_019845 36316385 39503509 388 7 DcFAD2-5 DCAR_025967 32083676 10152378 378 8 DcFAD2-4 DCAR_027655 20875213 29310153 392 8 DcFAD2-25 Not annotated 20877925 29313944 383 8 DcFAD2-26 Not annotated 20881526 29319686 391 8 DcFAD2-27 Not annotated 20885064 29341522 388 8 DcFAD2-28 Not annotated 20887620 29344165 383 8 DcFAD2-1 DCAR_027616 21164452 29349505 382 8 DcFAD2-9 DCAR_027615 21168523 10550426 383 8 DcFAD2-21 DCAR_027614 21171805 10560980 383 8 DcFAD2-2 DCAR_027583 21538656 10594722 392

posion Protein Stop lenght 24912904 367 41733609 383 41739333 385 33658405 382 36317537 383 32084828 383 20876365 383 20879073 383 20882677 383 20886215 383 20888768 383 21165604 383 21169678 384 21172963 385 21539808 383

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Fig. 7 Similarity of Daucus FAD2s shown by a phylogenetic tree (ClustalW) of deduced FAD2 protein sequences from D. carota (Busta et al. 2018, Dunemann et al. 2022) and some other putative FAD2 acetylenases and desaturases (Pc Petroselinum crispum; Ca Crepis alpina; Ha Helianthus annuus; At Arabidopsis thaliana; Bo Borago officinalis; Cp Crepis palaestina; Ah Arachis hypogaea). Carrot FAD2s newly identified by Dunemann et al. (2022) are shaded in gray. Carrot FAD2 genes with known function are indicated in bold/ underlined (Busta et al. 2018)

The biochemical formation of falcarindiol from its presumed precursor falcarinol in later steps of the falcarin pathway was largely unknown until now. It is hypothesized that plants having the enzymatic machinery necessary for cuticular waxes should also be able to perform decarbonylation and in-chain hydroxylation of fatty acids required for falcarin biosynthesis (Santos et al. 2022). However, the substrates and mechanisms for these processes are unclear. Recently a pathogen-induced biosynthetic gene cluster was discovered in tomato and shown to be putatively involved in falcarindiol production (Jeon et al. 2020). The four genes of this cluster were consistently and strongly co-expressed, three of which were FAD2 acetylenases or desaturases, with the remaining one being a CER1 decarbonylase homologue. In Arabidopsis thaliana, CER1 (ECERIFERUM1) and CER3 (ECERIFERUM3) gene products catalyze fatty acid decarboxylation in the alkane biosynthetic pathway and play a major role in wax production (Aarts et al. 1995). Although the study of Jeon et al. (2020) implicates a possible role for CER1 in falcarindiol production, a functional proof for a possible involvement of CER1 in the decarbonylation of falcarin precursors has, to date, not been described.

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Compared with the outcome from research on identification and functional characterization of genes putatively involved in biosynthesis of falcarin-type polyacetylenes, relatively less is known about the genetic control of falcarin contents in carrots. However, in carrot breeding programs aiming at reducing bitter taste (e.g., for baby food or juice and puree production), or – conversely – increasing pathogen resistance and/or enhanced health benefits, more information about the inheritance of falcarin accumulation is needed. Especially the availability of molecular markers linked to QTLs, or usage of functional markers developed directly from candidate TPS genes, would strongly support such breeding strategies. First QTLs for carrot falcarins were identified by using a segregating F2 family and indicated that levels of falcarin compounds are heritable traits (Le Clerc et al. 2019). In the carrot population used in this study over a 2-years period for QTL identification of three major falcarins, a relatively low environmental influence on the falcarin contents was found, and broad-sense heritability, for example, falcarindiol, was estimated to be 0.88. A transgressive segregation pattern was also observed in this study. Several QTLs could be mapped for falcarindiol and falcarindiol-3-acetate in carrot roots, and some of these QTLs were also associated with QTLs for bitterness and resistance to the fungal leaf blight pathogen Alternaria dauci (Le Clerc et al. 2019). In another biparental carrot F2 progeny derived from a cross of a cultivated breeding line and the wild relative D. carota subsp. commutatus, large phenotypic variability was obvious for the contents of falcarinol and falcarindiol (Dunemann et al. 2022). The observed frequency distributions in this F2 family indicated a polygenic inheritance, which is expected considering the assumed complex biosynthetic pathway of falcarin production. Nevertheless, the large phenotypic variation, ranging from individuals with no measurable falcarins to plants with very high contents of 1000 μg/g DW (dry weight) falcarinol or even 3000 μg/g DW falcarindiol, suggests the action of major regulatory or structural genes. However, significant falcarin QTLs were identified on six of the nine carrot chromosomes, which is a sign for the complexity of the genetic control of falcarin production in carrot roots. Common QTLs with high LOD scores were identified for both falcarinol and falcarindiol on carrot chromosomes 4 and 9, indicating a major involvement of these two genomic regions in polyacetylene biosynthesis (Dunemann et al. 2022). The six-gene FAD2 cluster associated with QTLs on chromosome 4 contains the two genes, DcFAD2-7 and DcFAD2-8, which have been functionally characterized as Δ12-fatty acid acetylenases, and DcFAD2-19, described as a bifunctional desaturase (Busta et al. 2018). The genetic association of three CER1 candidate genes with the strongest QTLs on chromosome 9 might be a further indication that these genes might also play a role in falcarin production. However, a functional proof that CER1 genes contribute to the production of falcarin-type polyacetylenes is still missing and remains to be biochemically established.

4.5

Implications for Breeding

Falcarin-type polyacetylenes are among the phytochemicals that may contribute to bitter taste of fresh carrots or carrot products, being an undesirable trait that can

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cause consumer rejection. Therefore, carrot breeding generally aims at low bitterness. Bitterness is a very complex trait, because not only polyacetylenes but also a variety of other chemically different potential bitter compounds, such as volatile mono- and sesquiterpenes, phenylpropanoids, and isocoumarins, may be involved in this quality trait. Recently, Schmid et al. (2021) analyzed and listed more than ten known bitter off-taste compounds present in carrot roots including the major falcarins, falcarinol and falcarindiol. Nevertheless, the falcarins appear to be a lead substance for bitter taste. In the study of Le Clerc et al. (2019), total falcarin content was closely related to bitterness, and the highest quantities of this compound accumulated in the most bitter genotypes, whereas the lowest amounts were measured in the least bitter genotypes. It is likely that lowering falcarin levels in carrots occurred in the past during the domestication process and breeding of cultivated orange carrot forms with the desired low bitterness. However, carrot cultivars with relatively high falcarin contents, such as the purple-rooted cultivar ‘Anthonina’ are still available in the seed market. This dark-purple cultivar also contained the highest contents of other putative health-relevant phytochemicals such as special phenylpropanoids and flavonols, when compared with white, yellow, orange, and red cultivars (Leja et al. 2013). As shown in a carrot biodiversity study, ‘Anthonina’ is closely related to carrot landraces originating from continental Asia (Baranski et al. 2012). Therefore, this cultivar is a good example that early domesticated purple carrots might be used directly as nutraceuticals or, alternatively, for the large-scale production of pharmaceutically relevant falcarins to be used, for instance, as food supplements. On the other hand, some modern purple F1 hybrid cultivars, such as ‘Deep Purple’, might also be suited. Considering the proposed health-promoting effects of falcarins, specific carrot chemotypes with high but acceptable amounts of bioactive falcarins may be developed in future by molecular breeding using genespecific functional markers or, to reach the goal faster, by application of genome editing techniques such as CRISPR/Cas. For both approaches, it will be necessary to first reveal the most important genes that control the decisive steps in the biosynthesis of falcarins.

5

Terpenes

5.1

Introduction

Terpenes are the largest and most structurally diverse class of plant natural products, comprising tens of thousands different substances. They can be classified into the subclasses monoterpenes (C10), sesquiterpenes (C15), diterpenes (C20), and triterpenes (C30), according to the number of isoprenoid structures. In plants, lowmolecular-weight terpenes produced by terpene synthases (TPS) contribute to multiple ecologically and economically important traits. Low-molecular-weight terpenes are involved in plant-to-plant communication and plant protection against abiotic and biotic stresses. They play an important role in plant defense against insect, fungal, and bacterial pathogens, which has been demonstrated in numerous studies

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(Yoshitomi et al. 2016; Chen et al. 2018; Shaltiel-Harpaz et al. 2021). A typical characteristic of mono- and sesquiterpenes is their volatility, and therefore they contribute to the typical flavor and aroma of many plant species including carrot. The typical flavor of carrots is determined by a complex blend of mono- and sesquiterpenes, representing up to more than 90% of the total volatile compounds. In a few studies, the correlation between volatile terpenes and carrot sensory attributes has been investigated (Alasalvar et al. 2001; Fukuda et al. 2013). Because carrots contain a huge amount of different terpene compounds, it is difficult to relate single terpene compounds to specific aroma notes and positive or negative sensory perception by humans. Using a GC olfactometry (GC-O) approach, an association between the carrot aroma and flavor and several isolated terpenes could be established (Kjeldsen et al. 2003). On the other side, terpenes are often involved in harsh or bitter flavor notes, and these off-flavor characteristics were shown to increase with terpene contents in different carrot genotypes. The combination of chemical analyses with sensorial approaches has predicted the monoterpenes sabinene, α-terpinolene, and β-pinene as candidates for bitterness in carrots (Le Clerc et al. 2019). Terpenes are present abundantly in essential plant oils of many plants, and they are also important components of resins and floral scents. Although there is general acceptance that volatile terpenes play a role as bioactive substances which might have an impact on human physiology and health, the current knowledge about putative health effects of terpenes present in carrots is restricted. Furthermore, the existing knowledge is rarely based on studies with terpenes isolated directly from D. carota but is generally founded on terpenoid compounds present in considerable quantities in other plant species such as, for instance, Cannabis sativa or the tea tree Melaleuca alternifolia. A better understanding of the genetic and molecular bases of the TPS enzymes involved in terpene biosynthesis will be needed for future breeding strategies aimed at the improvement of quality traits, such as aroma and taste, but might be also relevant for phytopathological aspects, for example, resistance against fungi or insects. In addition, the development of specific carrot chemotypes to be used for pharmaceutical applications might be feasible. In the following sections, we briefly describe the analysis, the spectrum of volatile terpenes in carrot roots and seeds, and their putative bioactivity with regard to human health. We further review the current knowledge about TPS enzymes and genes involved in terpene biosynthesis in carrot.

5.2

Diversity, Quantification, and Distribution

The most common analytical method for determining volatile terpenes is headspace solid-phase microextraction gas chromatography (HS-SPME-GC). This method was used in several investigations on carrot roots, leaves, and seeds, either coupled with flame-ionization-detection (FID) or with mass-spectrometry (MS). As a sensitive sampling method, headspace (HS) sampling of terpenes emitted by carrot tissues has been proved successful to achieve a complete qualitative and quantitative volatile organic compound (VOC) analysis. Particularly, solid-phase micro-extraction

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(SPME), which is a popular and simple HS sampling technique requiring no or little preparation of the samples, was mostly used in the past for the analysis of carrot VOCs, including terpenes. For example, using HS-SPME-GC-FID and MS, Ulrich et al. (2015) analyzed the diversity of terpene volatile patterns of carrot roots and leaves, and the same method was used to examine the terpene profiles in a large collection of carrot cultivars (Keilwagen et al. 2017). Since a full multi-compound quantitation using the SPME technique is impossible in complex organic matrices like homogenates of carrot leaves and roots, semiquantitative data are usually reported, for instance, as relative concentrations. Auto-HS-SPME-GC-MS was used for terpene analysis of differently colored carrot roots and carrot seed oil (Yahyaa et al. 2015, 2016). Headspace sorptive extraction (HSSE), a technique similar to SPME, was applied in carrots to link special volatile terpene profiles with sensory attributes (Fukuda et al. 2013). This technique uses a twister stir bar coated with polydimethylsiloxane (PDMS) to adsorb VOCs in the headspace of diced carrot tissue prior to thermal desorption and GC-MS analysis (Ibdah et al. 2019). For determination of absolute amounts of terpenes by the headspace sampling method, a precise calibration using authentic standards is required. An alternative is to use ground plant tissue for extraction with an organic solvent such as hexane and to use the extracts for GC-FID or GC-MS with the appropriate internal standards (Ibdah et al. 2019). Detailed chemical analysis of the volatile terpene pattern in carrot leaves and roots revealed differences in total amounts and proportions of individual compounds, suggesting large tissue-dependent differences in terpene biosynthesis (Habegger and Schnitzler 2000). In contrast to carrot roots, the terpene profiles of leaves have rarely been studied. Conversely to results of Hampel et al. (2005), reporting no correlation between leaf and root terpenes, Ulrich et al. (2015) showed strong correlations for some compounds present in leaves and roots. Another investigation based on different carrot root tissues revealed that the biosynthesis of terpenes is mainly localized in the phloem (Hampel et al. 2005). Higher concentration of terpenoids in the root phloem than in the xylem has been explained by the observation that oil ducts, a possible site of volatile terpenoid biosynthesis, are found only in the phloem. Nevertheless, in the root xylem, biosynthesis of terpenes was also detectable, even in the absence of oil ducts in this tissue (Hampel et al. 2005). The existing knowledge about volatile terpene patterns in carrot roots is mainly based on research aimed at the identification of compounds involved in flavor, aroma, and taste. The majority of the terpenes identified from roots are mono- and sesquiterpenes (Fig. 8). Although a comparatively large number of publications is available for VOCs in carrots, no accordance exists about typical carrot volatile profiles. The lack of agreement in finding typical patterns of major terpenes related to flavor and taste was documented by Ulrich et al. (2015), who examined about ten publications dealing with carrot terpenes. Out of the more than 120 compounds described in the literature, about 80 VOCs are single entries and were identified only in a single study. In 11 studies, the following 5 terpenes were identified: sabinene, limonene, terpinolene, β-caryophyllene, and α-humulene. In addition, other frequently mentioned volatiles were α-pinene, β-pinene, γ-terpinene, and p-cymene

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Fig. 8 Chemical structures of typical mono- and sesquiterpenes present in carrot roots, leaves, and seeds

(Ulrich et al. 2015). The monoterpenes α-terpinolene and α-pinene were found as the main terpenes in extracts from 11 differently colored carrot cultivars, and among the totally identified 16 monoterpenes, the monoterpenes α-pinene, β-pinene, β-myrcene, d-limonene, γ-terpinene, α-terpinolene, and p-cymene constituted more than 60% of total VOCs identified (Güler et al. 2015). A compilation of predominant mono- and sesquiterpenes identified by different researchers in fresh roots of differently colored carrots was shown by Ibdah et al. (2019). In the study of Keilwagen et al. (2017), 85 D. carota accessions representing the worldwide gene pool of cultivated carrots were analyzed for the qualitative and semiquantitative composition of VOCs in both roots and leaves. Totally, 31 VOCs, mostly monoterpenes and sesquiterpenes, were identified in roots or leaves, and some of them were present in both organs. In leaves, the most abundant compounds were β-myrcene, β-caryophyllene, and limonene, whereas terpinolene, β-caryophyllene, and bornyl acetate dominated the VOC patterns of roots. The majority of the root VOCs were monoterpenes, whereas only four sesquiterpenoids were present in the roots, namely β-caryophyllene, β-farnesene, β-bisabolene, and caryophyllene oxide. Five of the compounds (sabinene, β-caryophyllene, ocimene, α-pinene, and terpinen-4-ol) showed correlations between leaves and roots, which was in accordance with earlier results for sabinene and β-caryophyllene (Ulrich et al. 2015; Keilwagen et al. 2017). Twenty-three of these substances were also present in a biparental carrot F2 mapping population consisting of 320 individuals (Dunemann et al. 2019). In the work of Koutouan et al. (2018), targeted analyses of terpene volatiles in carrot leaves identified compounds potentially linked to resistance to the leaf fungus Alternaria dauci. In total, 30 terpenes, 15 monoterpenes, and 15 sesquiterpenes were quantified over several environments and years. In all genotypes, the main monoterpenes were β-myrcene, sabinene, α-pinene, and limonene, and the main sesquiterpenes were caryophyllene and germacrene. Seven terpenes differentiated resistant genotypes from the susceptible H1 genotype. Compared with carrot cultivars, very little information is available about terpene distribution and their amounts in wild Daucus relatives. A rare example is the study of Reduron et al. (2019), in which seedling root extracts of wild populations of D. carota from Corsica (France) were chemically analyzed and separated by their individual VOC profiles. For instance, the D. c. ssp. commutatus population 786, adapted to stony soils and a dry and hot habitat, showed

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very high contents of limonene and sabinene in roots, and γ-himalachene in leaves, indicating an eco-subspeciation process and adaptation to specific environmental conditions (Reduron et al. 2019). The cultivated carrot is mainly used as a root vegetable, while its seed oil is sometimes employed as a flavoring agent in food products, in the cosmetics industry, and aroma therapy. Therefore, a number of investigations have focused on the identification and quantification of VOCs from essential oils of carrot seeds. Since wild carrots have been used as a medicinal plant since ancient times, the majority of analyses was performed in carrot wild relatives and local natural carrot populations. Aćimović et al. (2016) analyzed the essential oil from seeds of wild (D. carota ssp. carota) and cultivated carrots (D. carota ssp. sativus) collected in northern Serbia and reported that the oil derived from wild-grown carrots contained mainly sabinene and α-pinene, followed by β-bisabolene, β-pinene, and trans-caryophyllene as further dominant compounds. The major constituents of essential oil from seeds of the cultivated carrots were carotol, sabinene, and α-pinene. Sabinene and α-pinene, together with myrcene, p-cymene, and limonene, were also the major compounds among 70 terpenoid VOCs identified in nine carrot cultivars (Flamini et al. 2014). In another study based on seeds of wild growing D. carota ssp. carota in Lithuania, the oils from all samples were of the sabinene chemotype. The other major constituents were α-pinene, terpinen-4-ol, γ-terpinene, and limonene (Mockute and Nivinskiene 2004). In the work of Sieniawska et al. (2016), the chemical composition of commercially available (Moroccan and French) and hydrodistilled (Polish) wild carrot seed essential oils from D. carota ssp. carota was analyzed, and the sesquiterpene alcohol carotol was found to be the main constituent in three seed oils. Pinene, sabinene, myrcene, limonene, geranyl acetate, bisabolene, caryophyllene oxide, and daucol were identified as other main compounds. Profiling the terpene metabolome in carrot seeds of wild carrot accessions from Israel revealed significant differences in volatile composition among the accessions. In most, but not all the accessions, the monoterpene α-pinene was the most abundant volatile, followed by limonene (Yahyaa et al. 2016). As discussed by these authors, there are many factors, such as genotypic differences, stage of development, environment, and geographical origin that can considerably influence the volatile composition pattern of D. carota seed oil. It is therefore not surprising that values obtained in the different studies are inconsistent to some extent.

5.3

Bioactivity and Relevance for Human Health

Despite the large diversity of terpenoid volatiles in carrot roots and their high relevance for flavor and taste, their biological effects have been particularly associated with the essential oils of the carrot seed and their compounds, which seem to be primarily terpenes. Essential oil of D. carota ssp. carota from Portugal, enriched for geranyl acetate, α-pinene, and other terpenes showed antibacterial and antifungal activity against several Gram-positive and Gram-negative bacteria, yeasts, dermatophytes, and Aspergillus strains. In addition, this seed oil was also able to inhibit germ

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tube formation and preformed biofilms of Candida albicans (Alves-Silva et al. 2016). Essential oil derived from D. carota ssp. halophilus has displayed antifungal properties against several human pathogenic fungi (Tavares et al. 2008), while the oil from D. carota ssp. maritimus has been shown to have potential antibacterial effects (Jabrane et al. 2009). Antimicrobial and antioxidant activities of carrot seed oil were also reported by Jasicka-Misiak et al. (2014). Vasudevan et al. (2006) described antinociceptive and anti-inflammatory properties of wild carrot seed extracts, and Shebaby et al. (2013) demonstrated antioxidant and anticancer effects. Hydrodistilled yellow and red carrot oils derived from seeds of D. carota ssp. sativus (yellow carrot) and D. c. ssp. boissieri (red carrot) were able to suppress 5-LOX and prostaglandin E2 production indicating excellent anti-inflammatory activities (Khalil et al. 2015). The cytotoxicity of both essential oils was evaluated on two human cancer cell lines, namely HepG-2 (liver hepatocellular carcinoma cells) and MCF-7 (breast adenocarcinoma cells), after 72 h incubation. The highest cytotoxic activity was observed against HepG-2 cells with IC50 values in the range of 163–172 μg/ml for both oils (Khalil et al. 2015). The observed cytotoxic activity of the two oils may be caused by carotol, which is the major component in both yellow and red carrot oils. Carotol was also among the main compounds in three carrot seed oils of different origin, amounting 19–33% of the sum of compounds (Sieniawska et al. 2016). Cytotoxicity tests based on green monkey kidney (VERO) and human pharynx squamous cell carcinoma (FaDu) cell lines treated with isolated carotol indicated nonselective moderate cytotoxicity on both cell lines, but apparently this substance was not solely responsible for the cytotoxic effects of the seed oils (Sieniawska et al. 2016). In another study, carotol was reported to inhibit the growth of myeloid leukemia cancer cell lines (Radoslaw 2012). The bioactivity of essential oil from wild carrot seeds is also probably due to its high contents of the monoterpenes sabinene and α-pinene. For instance, both terpenes are major components of pharmaceuticals which are used to treat the protozoan Trypanosoma brucei causing the African sleeping sickness disease. Other reports about the wide spectrum of bioactive effects of carrot terpenes are available from studies with other plant species containing the same terpene compounds. For example, the monoterpene limonene, comprising up to >90% of orange peel oil, and other monoterpenes have shown chemopreventive activity against rat mammary, lung and forestomach cancers (Crowell 1999). The sesqiterpene β-caryophyllene (BCP) was shown to increase the cytotoxic activity of paclitaxel in various cancer cell lines (Legault and Pichette 2007), with the largest observed effect on DLD-1 cells treated with paclitaxel plus 10 μg/mL BCP. Application of geraniol has been shown to sensitize cancer cells to the conventional chemotherapeutic agent 5-fluorouracil (5-FU), and it supported an increased uptake of the drug (Carnesecchi et al. 2004). The monoterpene terpinen-4-ol is known as the main component of the oil of tea tree (Melaleuca alternifolia), which has pharmaceutical importance due to its known antibacterial and anticancer effects (Lee et al. 2020). The sesquiterpene BCP is not only one of the major terpenoids in carrots but also known as a major plant volatile present in large amounts in the essential oils of many different spice and food plants. BCP is a major component (up to 35%) in the

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essential oil of Cannabis sativa and has been identified as a functional nonpsychoactive CB2 receptor ligand in foodstuff and as a macrocyclic antiinflammatory cannabinoid (Gertsch et al. 2008). BCP selectively binds to the cannabinoid receptor CB2 and functions as a CB2 agonist. Among numerous cannabinoids, BCP has received attention in the past few years due to its therapeutic potential by mediating anti-inflammatory and immunomodulatory properties. The various pharmacological properties and the therapeutic potential of BCP are comprehensively summarized by Jha et al. (2021). Only recently, it has been hypothesized that BCP could be a promising therapeutic agent to target the triad of infection, immunity, and inflammation in COVID-19 (Jha et al. 2021). Evidence from a preclinical study also suggests that a BCP-CB2 interaction might be involved in anxiety and depression disorders of mice, and that CB2 receptors may provide alternative therapeutic targets for the treatment of anxiety and depression (Bahi et al. 2014). The monoterpenes β-pinene and linalool can directly hit the central nervous system and have an enhanced activity after inhaling (Guzmán-Gutiérrez et al. 2014). Another interesting finding is that β-pinene can interact with dopaminergic D1 receptors, which is a mechanism used by many antidepressant drugs (Cox-Georgian et al. 2019).

5.4

Biosynthesis, Genetics, and Genomics

Terpenoids represent the largest class of natural substances produced by land plants. Many of these secondary metabolites are highly specialized and often involved in interactions with the environment. Thus, continued innovation of terpenoid biosynthesis has played an important role in the adaptation of land plants during evolution and diversification. The large diversity of terpenes is formed by members of terpene synthase (TPS) family from few substrates by similar carbocation-based reaction mechanisms (Tholl 2006). Terpenoids derive from the isomeric 5-carbon building blocks isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP). Two independent pathways in plants, the methylerythritol phosphate (MEP) pathway operating in plastids and the mevalonate (MVA) pathway operating in the cytosol/peroxisomes, lead to the synthesis of both IPP and DMAPP. Geranyl pyrophosphate (GPP) or geranylgeranyl pyrophosphate (GGPP) formed in the MEP pathway, and farnesyl pyrophosphate (FPP) formed in the MVA pathway are the substrates for terpene synthases, which catalyze the production of mono- or diterpenes from GPP or GGPP, respectively, or sesquiterpenes from FPP. Many volatile terpenes are formed directly by TPS enzymes, and various other enzyme classes are involved in modification of the primary terpene skeletons. These other enzymes belonging for a major part to the classes of dehydrogenases, methyl- and glycosyltransferases, and cytochrome P450 hydroxylases, can increase the volatility of terpenes and modify their olfactory features (Pateraki et al. 2015). In plants, the classification of the TPS gene family comprises eight subfamilies, known as TPS-a to TPS-h, based on their protein sequences and functional characteristics (Chen et al. 2011). The subfamilies TPS-a, TPS-b, and TPS-g are only

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present in angiosperms and, among these, the TPS-a subfamily includes mainly sesquiterpene and diterpene synthases, whereas members of the TPS-b subfamily are responsible for the production of monoterpenes or isoprenes. Members of the smaller TPS-g subfamily are predominantly monoterpene synthases. The TPS-d subfamily is only found in the gymnosperms, whereas TPS-h is specific to the spikemoss Selaginella moellendorffii. The TPS-c subfamily is, presumably, the ancestral clade, and it includes several copalyl diphosphate synthase genes. The TPS-f clade derived from the TPS-e subfamily, and they are, therefore, often combined and referred to as the TPS-e/f subfamily, which harbors ent-kaurene synthase genes and other diterpene, monoterpene, and sesquiterpene synthase genes (Chen et al. 2011). Analysis of sequenced plant genomes have revealed varying TPS gene family sizes among species, ranging from 30 to more than 100 members, which presumably evolved – as for many other gene families – by duplication followed by functional divergence. For example, the genomes of A. thaliana, rice, and grapevine contain 32, 34, and 69 full length TPS, respectively (Chen et al. 2011). More than 100 putative TPS genes were identified each in the representative Eucalyptus species E. grandis and E. globulus (Külheim et al. 2015). TPS gene families have also been studied and described extensively in several other plant species such as tomato (Falara et al. 2011) and Vitis vinifera (Martin et al. 2010). Using the first published carrot whole-genome assembly, Iorizzo et al. (2016) performed a preliminary characterization of the carrot TPS family and predicted 36 potentially functional TPS genes. Using the same version of the carrot genome, Keilwagen et al. (2017) conducted a genome-wide identification of carrot TPS genes by applying a newly developed homology-based gene prediction software called GeMoMa. In total, the carrot TPS inventory actually consists of 65 predicted fulllength TPS gene models. The predicted carrot TPS genes were assigned, with one exception (TPS-d) to all angiosperm TPS subfamilies, TPS-a to TPS-g. Subfamily TPS-b (monoterpene synthases) was identified as the largest subfamily in the carrot genome with a total of 32 putatively functional genes. Subfamily TPS-a (sesquiterpene synthases) was found to be the second largest subfamily with 22 genes. The huge number of TPS-a and TPS-b genes correspond with the dominance of monoand sesquiterpenes present in the large panel of carrot genotypes (Keilwagen et al. 2017). Results from this study revealed that carrot is among the species with high or very high number of TPS genes, suggesting broad potential for further functional diversification and specialization of terpene metabolism. Analyzing the carrot genome sequence, most of the TPS genes are found in gene clusters, dispersed throughout all of the chromosomes (Keilwagen et al. 2017). Especially the TPS gene clusters on chromosomes 1, 3, 4, and 9 might be results of multiple gene duplications (Fig. 9). The whole known inventory of Daucus TPS genes together with existing information about their putative function is shown in Table 4. A maximumlikelihood phylogenetic tree including all predicted TPS genes in D. carota was presented by Ibdah et al. (2019). In contrast to the high impact of mono- and sesquiterpenes for the total volatile profile and, therefore, for taste and flavor of carrots, only a few research papers had

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Fig. 9 Schematic representation of the physical location of the TPS gene cluster on chromosome 4 of the carrot genome (Reproduced from Reichardt et al. 2020)

focused on functional characterization of carrot TPS genes. A DcTPS1 recombinant protein synthesized in a heterologous expression system in E. coli produced mainly the sesquiterpenes β-caryophyllene and α-humulene, while recombinant DcTPS2 functioned in E. coli as a monoterpene synthase with geraniol as the main product (Yahyaa et al. 2015). DcTPS2 is a gene encoding a monoterpene synthase of the TPS-b subfamily and produced also β-myrcene, which is among the carrot terpenes with strongest influence on carrot aroma. The function of DcTPS2 as a geraniol synthase was confirmed by analysis of a very similar gene cloned from a wild carrot accession, which contained geraniol as the predominant terpene in seeds (Yahyaa et al. 2016). Based on QTLs mapping results and the genetic dissection of a five-TPS gene cluster on chromosome 4 with molecular markers, Reichardt et al. (2020) selected DcTPS04 and DcTPS54 for further functional analyses. In vitro enzyme assays in E. coli showed that DcTPS54 encodes a single-product enzyme catalyzing the production of the monoterpene sabinene, whereas DcTPS04 was found to be a multiple-product terpene synthase producing α-terpineol as a major product and four other products, namely sabinene, myrcene, β-pinene, and β-limonene. These results were confirmed by Muchlinski et al. (2020), who functionally characterized 19 carrot TPS genes in the double-haploid orange carrot genotype DH1 and compared spatial expression profiles and in vitro products of their recombinant proteins with the volatile terpene composition of DH1 and the respective terpene profiles from four genotypes with different root colors. As TPS enzymes involved in the production of major compounds of carrot flavor, DcTPS07 and DcTPS11 (germacrene D), DcTPS30 (γ-terpinene), and DcTPS03 (α-terpinolene) were biochemically identified

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Table 4 List of 64 Daucus carota TPS gene models sorted by their physical position on the assembled 9 carrot chromosomes according to the whole-genome sequence (Iorizzo et al. 2016) and the carrot TPS inventory published by Keilwagen et al. (2017). For functionally characterized TPSs, only the main product is named together with the reference publication: (1) Yahyaa et al. (2015), (2) Reichardt et al. (2020), and (3) Muchlinski et al. (2020) Chrom. Gene name Locus name 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4

DcTPS32 DcTPS11 DcTPS45 DcTPS46 DcTPS19 DcTPS47 DcTPS10 DcTPS24 DcTPS48 DcTPS22 DcTPS49 DcTPS41 DcTPS40 DcTPS42 DcTPS03 DcTPS15 DcTPS50 DcTPS37 DcTPS08 DcTPS51 DcTPS05 DcTPS12 DcTPS18 DcTPS25 DcTPS31 DcTPS52 DcTPS30 DcTPS53 DcTPS06 DcTPS38 DcTPS13 DcTPS26 DcTPS04 DcTPS54 DcTPS55 DcTPS27 DcTPS09 DcTPS02

DCAR_002080 Not annotated DCAR_002829 DCAR_002830 DCAR_002831 DCAR_004091 Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated DCAR_012483 Not annotated DCAR_012537 DCAR_012538 Not annotated Not annotated Not annotated Not annotated DCAR_013310 DCAR_013298 DCAR_013297 DCAR_013294 DCAR_013293 DCAR_012965 DCAR_012963

TPS Main product Chrom. Gene name subfamily (Reference) TPS-b 5 DcTPS56 TPS-a germacrene D (3) 5 DcTPS28 TPS-g 5 DcTPS14 TPS-g 5 DcTPS17 TPS-g linalool (3) 5 DcTPS57 TPS-b 5 DcTPS58 TPS-b 5 DcTPS33 TPS-b 5 DcTPS59 TPS-b linalool (3) 6 DcTPS01 TPS-b 7 DcTPS23 TPS-b 7 DcTPS60 TPS-a 7 DcTPS61 TPS-a 8 DcTPS62 TPS-a germacrene D (3) 8 DcTPS21 TPS-b α-terpinolen (3) 8 DcTPS29 TPS-a α-phellandrene (3) 8 DcTPS44 TPS-a 8 DcTPS43 TPS-a 9 DcTPS36 TPS-a 9 DcTPS35 TPS-b 9 DcTPS63 TPS-b 9 DcTPS64 TPS-b 9 DcTPS07 TPS-b 9 DcTPS34 TPS-c 9 DcTPS65 TPS-b 9 DcTPS20 TPS-b 9 DcTPS39 TPS-b γ-terpinene (3) TPS-a δ-elemene (3) TPS-a TPS-a TPS-a TPS-b limonene (3) TPS-b α-terpineol (2) TPS-b sabinene (2), (3) TPS-b sabinene (3) TPS-b TPS-b TPS-b geraniol (1)

Locus name DCAR_016843 DCAR_016844 DCAR_017536 DCAR_018214 DCAR_018422 DCAR_019208 DCAR_019208 DCAR_019490 DCAR_023152 DCAR_024752 DCAR_024753 Not annotated DCAR_028138 Not annotated DCAR_027915 DCAR_026972 DCAR_026971 Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated Not annotated DCAR_031040

TPS Main product subfamily (Reference) TPS-e TPS-e TPS-b TPS-b TPS-c TPS-b TPS-b TPS-c TPS-a β-caryophyllene (1) TPS-g TPS-g TPS-a TPS-b TPS-b TPS-f TPS-b TPS-b TPS-a TPS-a TPS-a TPS-a TPS-a germacrene D (3) TPS-a TPS-a TPS-b TPS-a

(Table 4). No functional characterization of isolated TPS genes in planta has been published yet but would be highly desirable in order to analyze TPS genes putatively involved in plant pathogen defense mechanisms. Overexpression of isolated TPS genes in carrot hairy root cultures in vitro might be a possible way to produce large amounts of pharmaceutically relevant terpenes in future. Compared with the knowledge about carrot terpene profiling, the TPS genes involved, and their putative functions, less was known about the inheritance of carrot terpenes until the studies of Keilwagen et al. (2017) and Le Clerc et al. (2019). However, for targeted breeding, for example, to enhance specific aroma notes or, vice versa, to avoid unwanted terpene profiles leading to bitter taste, it will be necessary to define the most important TPS and other genes from the MEP and MVA pathways involved in the production of major terpenes in carrot roots. Using a combinatorial approach of terpene metabolite profiling, SNP analysis through

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genotyping-by-sequencing (GBS), and a subsequent genome-wide association study (GWAS) in a panel of 85 carrot cultivars, Keilwagen et al. (2017) detected 30 QTLs for 15 terpenoid volatiles. Genetic association analysis identified 21 significant QTLs in roots, and 9 QTLs were detected in leaves. Root QTLs were mostly detected for the monoterpenes sabinene, ocimene, β-pinene, borneol and bornyl acetate, and most QTLs were located on carrot chromosomes 4, 5, 7, and 9. Three genomic regions were detected after GWAS, which contained terpene QTLs either associated with a single TPS candidate gene (DcTPS03 for bornyl acetate and DcTPS29 for γ-terpinene) or with the cluster of five mono-TPS genes with high sequence homology on chromosome 4 (DcTPS04, DcTPS26, DcTPS27, DcTPS54, and DcTPS55) which were associated with QTLs for sabinene and terpinen-4-ol. Analysis of this TPS cluster by QTL mapping in a biparental carrot F2 population confirmed the results found by GWAS for sabinene and terpinen-4-ol and identified additional QTLs for the monoterpenes α-thujene, α-terpinene, γ-terpinene, and 4-carene in the same genomic region of chromosome 4 (Reichardt et al. 2020). Another previous QTL study, which focused on bitterness trait variation and resistance to Alternaria dauci in a segregating carrot F2 population, identified 71 QTLs for 25 terpenes (Le Clerc et al. 2019). These QTLs were placed mainly on chromosomes 3, 4, and 9, and eight terpenes were the same as in the work of Keilwagen et al. (2017). However, only the QTLs for sabinene on chromosome 4 appeared to be the same in both studies indicating the importance of this genomic region for monoterpene metabolism.

5.5

Implications for Breeding

Marker-assisted breeding (MAS) based on molecular markers linked to QTLs for volatile terpenes might be utilized in carrot breeding programs. Determination of the functional allelic diversity of TPS genes present in Daucus germplasm can help to select putative crossing parents. The molecular KASP marker developed by Reichardt et al. (2020) is a first example for such approach (Fig. 9). This allelespecific marker developed from the sequence of the gene DcTPS54 can discriminate carrot F2 individuals as well as cultivar genotypes with high or low sabinene content (Reichardt et al. 2020). Sabinene is likely one of the predominant and most important terpenes in carrots, since this substance may be involved in carrot flavor and taste, but was also described to be responsible for bitterness and fungal resistance (Le Clerc et al. 2019). Such correlations between wanted (aroma and resistance) and unwanted (bitterness) traits might lead to conflicts when molecular breeding would ignore such relationships. Therefore, for molecular breeding of high-quality carrot cultivars fulfilling all demands of growers and consumers, specific molecular markers for single terpenoid volatiles would be probably not helpful without a concomitant sensorial perception analysis. Nonetheless, carrot appears as a very promising target crop for breeding programs aiming at the development of specific chemotypes possessing enhanced levels of economically important terpenes for industrial or pharmaceutical exploitations. Special new carrot varieties containing

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large amounts of bioactive terpenes but, if necessary, with compromised taste may also be considered as nutraceuticals.

6

Carotenoids

6.1

Introduction

Carotenoids comprise a family of 40-carbon isoprenoids that includes nonoxygenated carotenes as well as oxygenated xanthophylls, among other compounds. They are found in a variety of organisms, including plants, animals, and microbes. Plant carotenoids aid in the absorption of light during photosynthesis and provide protection against photooxidative stress. As accessory pigments, they are essential to development and growth (Lu and Li 2008). In addition, plant growth, flavor, and mycorrhizal connections need carotenoid pathway byproducts (Della Penna and Pogson 2006; Cazzonelli and Pogson 2010). Moreover, carotenoids enhance the plants’ non-photosynthetic parts by attracting animals and insects that help pollinate and disperse seeds. It is essential for animals, including humans, to get carotenoids from their diets since with very few exceptions – mammals cannot synthesize carotenoids on their own. These pigments are present in a diverse range of food plants, including carrots, and are the primary precursors of vitamin A, required for immune system function, sight, maturation, and reproduction. In addition, specific carotenoids, such as lycopene and lutein, have been found to reduce the risk of some types of cancers, osteoarthritis, neurodegenerative disorders, and cardiovascular disease (Tanumihardjo 2012). When it comes to the number and composition of carotenoids in a plant, there is a wide range of variation among tissues and organs within a plant, which also vary during the plant’s growth, and across different accessions within a species. Since carotenoids are attractive to animals, their bright colors may have attracted humans’ interest as they were domesticated. Multiple regulatory mechanisms are involved in controlling metabolite transport across pathways and cells involved in carotenoid accumulation via biosynthesis (Sun et al. 2018), degradation (Yuan et al. 2015), and sequestration, many of which are characterized by alterations in photomorphogenesis and plastid growth in certain cases (Lu and Li 2008). The recent advances in carrot genomics provided opportunities to expand knowledge about the genetic mechanism controlling carotenoid accumulation in carrot. Carotenoids are present in very small quantities in the unpigmented roots of wild carrots (Daucus carota subsp. carota), also called Queen Anne’s Lace (QAL), and in white-rooted cultivated carrots, whereas they are present – in varying concentrations – in the majority of the cultivated colored carrots. The primary carotenoid pigments in carrot roots are yellow, orange, and red, and the main compounds that account for such colors are lutein, α- and β-carotene, and lycopene, respectively (Arscott and Tanumihardjo 2010). Yellow carrots predominantly accumulate lutein, zeaxanthin, and α- and β-carotene in small levels (Alasalvar et al. 2001; Arscott and Tanumihardjo 2010), whereas orange carrots typically accumulate large quantities of α- and

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β-carotene, and trace amounts of phytoene, lutein, and ζ-carotene. Red carrots accumulate primarily lycopene and often include small amount of α- and β-carotene, as well as lutein (Arscott and Tanumihardjo 2010). Carrot is among the main dietary sources of PACs in many regions of the world, with particular relevance in the USA, where it ranks first in the relative contribution of PACs to the general population’s diet. When compared to other dietary sources of PCAs, orange carrots are distinct in that α-carotene can account for a much higher percentage of the total carotenoids content, representing 13–40% of total carotenoids, with higher percentages observed in carrot roots with higher total carotenoid content (Simon and Wolff 1987; Santos and Simon 2006). According to a previous study, carrots can provide 67% of the α-carotene required by the average American diet. The total carotenoid concentration of dark orange cultivars can exceed 500 ppm on a fresh weight (fw) basis. According to Simon et al. (1989), dark orange cultivars may have a total carotenoid content as high as 500 ppm of fw, and this potential to accumulate carotenoids is associated with the formation of carotenoid structures and crystals in root chromoplasts (Maass et al. 2009; Sun et al. 2018). Interestingly, there was no report of orange carrots until the seventeenth century. Indeed, when it was first domesticated, about 1100 years ago in Central Asia, carrots had purple or yellow roots (reviewed by Simon 2000). The first orange-rooted carrots were reported in Southern Europe in the sixteenth century and the first red carrot was reported in Asia in the seventeenth century. Since their selection, orangerooted carrots became – and still are – the predominant market type worldwide. However, red, yellow, and purple carrots still have a relatively large market in some parts of Asia.

6.2

Role of Carrot Carotenoids in Human Nutrition

Orange carrots are rich in carotenes, which predominantly include α- and β-carotene, as well as smaller and varying amounts of γ- and ζ-carotenes, β-zeacarotene, and lycopene, with total carotene content varying from 63 to 548 ppm across different orange-rooted cultivars (Simon and Wolff 1987; Simon 2000). One of the most important functions of carotenoids in the human diet is the role of α-carotene, β-carotene, and cryptoxanthin as precursors of vitamin A. α-carotene and β-carotene account for 13–40% and 45–50% of the total PACs present in orange carrots (Simon and Wolff 1987; Simon 2000). After ingestion, PACs can be cleaved in the intestine or liver, yielding retinaldehyde (retinal) which can then be reduced to retinol, vitamin A (reviewed by Krinsky 1998, and Semba 1998). Vitamin A plays an essential role in human vision and immune function, including apoptosis, keratinization, and B-lymphocyte function (Semba 1998). Vitamin A deficiency can cause a variety of symptoms such as night blindness, xerophthalmia, and increased susceptibility to infections and cancer (Semba 1998). In addition to its ability to produce vitamin A, β-carotene also possesses strong antioxidant activity in humans (Krinsky 1998). Red-rooted carrots are particularly rich in lycopene, another carotenoid frequently found in the human diet. Lycopene is not a PAC. However, because of the high

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number of conjugated double bonds, lycopene has higher antioxidant activity than other carotenoids with fewer double bonds. Several studies have reported an inverse relationship between serum levels of lycopene and risk for several types of cancer, especially prostate cancer, suggesting that lycopene possess anticancer effects (reviewed by Rao and Agarwal 2000). Red carrots are widely consumed in some regions of the world, such as India, where they are preferred over orange carrots. Yellow carrots are rich in xanthophylls, predominantly lutein and in less amount zeaxanthin. Compared to orange-rooted forms, yellow carrots generally have lower concentration of total carotenoids and β-carotene (Sun et al. 2009). The xanthophyll pigments present in yellow carrots provide protection against cataracts and age-related macular degeneration (Tanumihardjo 2012). These pigments accumulate in both the lens and the macula of the human eye, where they are thought to play a role quenching reactive oxygen species generated by high exposure to ultraviolet light. In addition, it has been indicated that increased intake of lutein may also prevent early atherosclerosis. White carrots have trace amounts of carotenoids, if any. Because of their extremely low carotenoid content, they lack the carotenoid-related health enhancing properties of the other root color phenotypes. However, the do provide fiber and other nutrients found as well in other colored carrots.

6.3

Biosynthesis of Carrot Carotenoids

Carotenoids are produced in two separate pathways in the plastids and the cytosol. In plastids, the 2-C-methyl D-erythritol-4-phosphorate (MEP) pathway converts pyruvate and glyceraldehyde 3-phosphate to Isopentenyl diphosphate (IPP), and in the cytosol, the mevalonic acid (MVA) pathway converts acetyl-CoA to IPP and geranylgeranyl diphosphate (GGPP). GGPPs are then transformed into phytoene, which is the first step in the carotenoid pathway. Figure 10 presents the MEP and MVA pathways with the respective carrot genes, loci, and enzymes. It is mostly through the MEP route that the majority of carotenoid precursors are made (reviewed by Rodriguez-Concepcion and Stange 2013). There are 44 isoprenoid and 24 carotenoid biosynthesis genes in carrot. Each gene contains various paralogues involved in a variety of modifications, indicating that distinct paralogues evolved specialized functions in different plant taxa, tissue types, developmental stages, environmental conditions, and/or pathways (Rodriguez-Concepcion and Stange 2013; Iorizzo et al. 2016; Simpson et al. 2016). Most of the carotenoid biosynthetic genes are functional in all of the color phenotypes of carrot storage roots, including white-rooted cultivated (Wang et al. 2014; Perrin et al. 2016, 2017a) and wild carrots (Just et al. 2007; Clotault et al. 2008; Bowman et al. 2014; Ma et al. 2017). This is indicative that pathway metabolites serve as precursors for key substances needed for general plant growth and development, such as the hormones abscisic acid and strigolactones. In carrots with orange, yellow, and red roots, carotenoid concentration increase during root development (Clotault et al. 2008; Fuentes et al. 2012; Perrin et al. 2016; Wang et al. 2014). While the expression of genes increase during root development, it

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Fig. 10 MEP (2-C-methyl D-erythritol-4-phosphorate) (a) and carotenoid (b) pathways. Enzyme names, carrot locus tags (in curly brackets), abbreviations (in parentheses), and Enzyme Commission numbers (in square brackets) are included (Reproduced from Simon et al. 2019)

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has often been observed that such increase in gene expression is not proportional to – i.e., it is several folds less than – the increase in pigment content (Clotault et al. 2008; Stange et al. 2008; Fuentes et al. 2012; Bowman et al. 2014; Wang et al. 2014; Ma et al. 2017). Greater expression levels of Lycopene β-cyclase 1 (DcLcyb1) were found in leaves and roots of mature plants than in those organs in immature plants (Moreno et al. 2013). DcLcyb1 overexpression in transgenic carrots led to increased carotenoid content and increased expression of other carotenoid genes – namely DcPsy1, DcPsy2, and DcLcyb2 – in leaves and roots. These results suggest that DcLcyb1 does not possess an organ specific function and modulate carotenoid gene expression and accumulation in carrot leaves and roots. Transgenic approach has been used by Arango et al. (2014) to study the role of carotene hydroxylase in the metabolism and accumulation of carotenoids in carrot root and leaves. When CYP97A3 was overexpressed in transgenic orange carrots, the leaves had levels of α-carotene that were about the same as those of untransformed wild carrots. Furthermore, levels of carotenoids were significantly reduced in orange transformed carrots, as was PSY protein expression, despite the fact that PSY was not expressed in these carrots. This indicated that there is a mechanism that regulates carotenoid metabolism. Indeed, exposure of storage roots to light has a significant impact on the amount of carrot carotenoids and gene expression (Stange et al. 2008; Fuentes et al. 2012). As with the carotenoid content and the levels of most of the genes involved in the process, the carrot root’s shape altered when it was exposed to light in the research. As a consequence of inadequate light and temperature conditions, the carotenoid content of both roots and leaves is decreased (Perrin et al. 2016). The transcriptional control of all of the carotenoid genes in the leaves, as well as the zeaxanthin epoxidase (ZEP) and phytoene desaturase (PDS) genes in the roots, was held responsible for the observed reduction in AOC. Changes in carotenoid transcript levels, on the other hand, could not explain changes in carotenoid content in contexts with both Alternaria dauci infection and water scarcity (Perrin et al. 2017b). This shows that there are other regulatory mechanisms that are not involved in the pathway’s functioning. Due to the wide range of carotenoid content and color intensity found in different carrot genetic stocks and cultivars, many studies have looked at how the expression of carotenoid genes varies in carrots of different colors (Clotault et al. 2008). The enormous and diversified changes in carotenoid composition throughout a wide range of storage root colors are not matched by qualitative differences in gene expression in the pathway, although there are certain similarities in gene expression that are paralleled by carotenoid accumulation patterns (Bowman et al. 2014). White and orange carrots have different levels of two to four times more PSY1 and PSY2 genes than white carrots. This is what happened in studies that compared the levels of these two genes in white and orange carrots (Wang et al. 2014). Clotault et al. (2008) reported that yellow carrots have a higher concentration of genes that produce lycopene and ζ-carotene desaturase than orange or white carrots. According to the findings of Ma et al. (2017), yellow cultivars exhibited more genes that produce xanthophyll than orange cultivars. During the period of plant growth in a controlled environment, the expression of carotenoid genes modulates in a way that is comparable to the method in which carotenoid accumulation changes in phloem tissue.

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Among genes that encode enzymes are involved in the MEP and MVA pathways, 1-deoxy-d-xylulose-5-phosphate (DXP) synthase 1 (DXS1) was the only one to be upregulated in a way that is consistent with the amount of carotenoid present in carrot root (Iorizzo et al. 2016). DXS has been identified to be a regulator of isoprenoid biosynthesis in a number of Arabidopsis experiments. According to Simpson et al. (2016), DXS is the rate-limiting enzyme in the synthesis of carotenoid pigments in transgenic carrots. In addition, the study found that PSY transcript was upregulated in the DXS regulatory cascade, which confirms PSY’s important role in carotenoid metabolism (Lu and Li 2008; Yuan et al. 2015; Sun et al. 2018). The results that the PSY transcript was upregulated in assessments of orange and white carrot roots are likewise consistent with these findings (Bowman et al. 2014). Many studies have also looked at how carotenoid gene sequences change over a wide range of root colors. Carotenoid genes have different nucleotides in carrots from different parts of the world, suggesting that root color was highly relevant in the domestication of carrots. Variation for gene sequence and expression levels were found for seven carotenoid alleles in 46 carrots with different root colors from across the world (Clotault et al. 2012). They found that there was a lot of variation in how much selection was put on genes like PDS and IPP isomerase (IPI), which are at the beginning of the process. The carotene isomerase (CRTISO), LCYB1, and LCYE genes, which are closer to lycopene in the pathway, were also found to be selected for. The sequence variation for LCYB1 was different between color groups, suggesting that it was selected during domestication. However, there was not a pattern of sequence variation that pointed to candidate genes in the carotenoid pathway that could account for color variation. Jourdan et al. (2015) examined 17 carotenoid genes in 67 carrot cultivars from across the globe and concluded that there were linkages between α-carotene content and the plastid terminal oxidase (PTOX) and CRTISO polymorphisms, as well as links between total carotenoid content and the ZEP, PDS, and CRTISO polymorphisms. Genetic linkage between individuals who have the Y and Y2 genes on the same chromosome as ZEP and PDS may have occurred, which may have contributed them in their connection with one another (Just et al. 2007).

6.4

Carrot Carotenoids Genetics and Genomics

In the late 1960s and early 1980s, Gabelman and his students discovered multiple genes that influence carrot root color. Segregation analysis in populations derived from intercrosses of carrots with different root color revealed that a single dominant gene conditions white root color over yellow, whereas F2, F3, and backcross populations from white  orange intercrosses exhibited white and orange-rooted plants consistent with a 2–3 gene patterns of inheritance (Imam and Gabelman 1968; Laferriere and Gabelman 1968). The yellow root color was shown to be more strongly influenced by a monogenic inheritance pattern than the orange root color in this study. One or two additional dominant genes, Y1 and Y2, were identified by Kust (1970) as governing white coloration over yellow, as reported by Laferriere and

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Gabelman (1968). O and IO, two genes that enhance orange phloem color, were also discovered by Kust (1970), and further characterized by Buishand and Gabelman (1979), who analyzed segregation of orange color in phloem and xylem tissues in derivatives of orange  white crosses. When the dominant alleles were present in the cross, the carotenoid contents in the offspring of “white  yellow” and “yellow  orange” crosses decreased. Additionally, Umiel and Gabelman (1972) determined that orange root color predominated over “red white  orange” and “white  yellow” crosses. Two simply inherited loci, A and L, that influence the accumulation of lycopene and α-carotene were identified by segregation analysis in F2 and backcross populations derived from intercrosses between red and orange rooted carrots (Umiel and Gabelman 1972). Buishand and Gabelman (1980) found three key genes segregating in progenies from red  yellow crosses: Y2, which inhibits the synthesis of carotene; L, which promotes the synthesis of lycopene; and A1, which has a phenotypic impact comparable to either O or IO described by Kust (1970). Gabelman and colleagues uncovered a number of critical genetic elements influencing root color. Because there were no intercrosses to test for allelism or chromosomal complementation, the only way to distinguish between alleles was to look at the phenotypic traits alone. On the basis of accounts of their characteristics, researchers have emphasized on the L, O, and IO genes. As previously reported by Arango et al. (2014), the activity of the carotene hydroxylase gene CYP97A3 in orange carrot roots is reduced, resulting in a higher concentration of α-carotene and higher ratio of α-carotene/β-carotene. This indicates that the “A1” phenotypic locus described earlier by Buishand and Gabelman (1980) and reported to be essential for α-carotene synthesis in orange carrots, has been identified. A frameshift mutation in the CYP97A3 gene, which is found only in orange carrot roots, was reported as the causal mutation leading to reduced expression of CYP97A3 and – thereby – increased accumulation of α-carotene (Arango et al. 2014). This reveals the genetic and molecular foundation for orange carrots’ high α-carotene content. Goldman and Breitbach (1996) described an orange carrot mutant, characterized by “reduce pigment” in the root, caused by the recessive gene “rp.” This gene reduces the concentration of α- and β-carotene in storage roots by more than 90%, while raising the concentration of phytoene (Koch and Goldman 2005). A distinguishing green color is developed by the sixth leaf in the development of rprp plants, which are initially chlorotic and even white. The rp mutation results in a decrease in plant vigor, which is rare among genes that regulate carotenoid color in carrots. The carotenoid pathway is thought to be suppressed in the rp mutant (Goldman and Breitbach 1996); however, this hypothesis has yet to be tested. Because of its uniqueness, further characterization of rp might provide new insights into the metabolism of carrot carotenoids. In three orange  yellow crosses, Simon (1996) used carotenoid mapping populations to examine the relationship between Y2 and genes that govern sugar and anthocyanin accumulation. He found that Y2 had a monogenic inheritance pattern. Because the observed phenotype most closely correlated with Buishand and

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Gabelman’s (1979) phenotypic descriptions of this trait, the gene was designated as Y2. An AFLP fragment genetically linked to Y2 was converted into a PCR-based marker to help in the phenotyping of carotenoid accumulation genes in breeding programs (Bradeen and Simon 1998). AFLPs were initially used to map the Y2 gene, which conditions yellow versus orange root color and carotene concentration (Vivek and Simon 1999). Santos and Simon (2002) employed AFLP markers to map QTLs for carotenoids concentration (assessed by HPLC analysis) in two mapping populations. Significant QTLs were identified for several carotenoid products, including phytoene, lycopene, β-carotene, and α-carotene. Eleven QTLs for concentration of α- and β-carotene were detected and they were associated with orange root color. Carotenoid accumulation genes were formerly thought to be metabolic pathway structural genes, like in other crops. It is possible that the genes conditioning carotenoid-related coloring of carrot roots are not structural biosynthetic genes but rather control carotenoid accumulation (Santos et al. 2005). A single major QTL for β-carotene, total carotene, and lycopene content was identified in the F2 population of P50006 and HCM A.C. using sequence related amplified polymorphism (SRAP) markers, and this QTL accounted for ~12.8–14.6% of the total phenotypic variation for the three pigment traits. The genetic variability of these three QTLs was attributed to additive genetic variance rather than additive genetic variation. Furthermore, a pair of epistatic QTLs for β-carotene and lycopene accumulation was shown to account for 15.1% and 6.5% of the total phenotypic variance, respectively. The SRAP markers tightly linked to these QTLs might be employed in carrot breeding to select for high carotenoids and lycopene content via QTLs pyramiding or selection for high carotenoids and lycopene content through selection. Santos and Simon (2006) also estimated broad-sense heritability values for individual carotenoids and cumulative carotenoid concentration in the two populations. A segregating pattern was revealed in the progeny of a hybrid between a wild, white-rooted carrot, known as QAL, and a dark orange cultivated carrot, known as B493, in which the Y and Y2 genes were segregating, as well as quantitative loci that contributed to variation in total carotenoid concentration. In the same study of Santos and Simon (2006), progenies from another cross between the orange-rooted Brasilia and the dark orange HCM were examined. Although the genotypes of the progenies were all recessive for the Y and Y2 loci (yyy2y2), the progenies were quantitatively segregating for carotene content, in approximately fivefold difference between the two parents. The total heritability of carotenoid content in the ‘B493  QAL’ population ranged from 0.89 to 0.98, while it ranged from 0.38 to 0.45 in the ‘Brasilia  HCM’ background, demonstrating that the Y and Y2 genes had a significant influence on descendants in the B494  QAL population. Carotenoid concentrations in the same orange carrot genetic stocks may vary up to twofolds in different environments, according to Simon and Wolff (1987) and Perrin et al. (2016), explaining why the ‘Brasilia  HCM’ population had lower heritability than the other HCM populations. It was hypothesized that the genes encoding the carotenoid biosynthesis enzymes could be linked to the carotenoid color genes, hence Just et al. (2007, 2009) identified and mapped 22 probable carotenoid enzyme genes in carrot. The population used in this research was generated from a cross between a wild

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white-rooted carrot known as QAL and a cultivated carrot known as B493, which has a dark orange root. This population segregated for orange, yellow, and white root colors, with ratios consistent with a two-gene model. Bradeen and Simon (1998) genetically mapped the Y2 gene on linkage group 5 and Y on linkage group 2. ZEP and ZDS were found to be positionally associated with the Y1 and Y2 genes, respectively. The Y1 gene was shown to be associated with ε-ring carotene hydroxylase (CHXE), 9-cis-epoxycarotenoid dioxygenase 2 (NCED2), and phytoene desaturase (PDS). Due to the lack of close relationships, they were designated positional candidates (Just et al. 2009). After sequencing the carrot genome (Iorizzo et al. 2016), a Y gene candidate was found. Fine mapping in this study revealed a 75-kb region of chromosome 5 responsible for both the orange and pale orange (YYy2y2) root color segregating as a monogenic trait in the B493  QAL cross population, as well as the yellow (yyY2Y2) and white (YYY2Y2) root color segregating in an unrelated population. In this study, the light orange phenotype (yyy2y2) has not previously been connected to aYYy2y2 genotype, since earlier phenotyping had not been able to differentiate it from orange (yyy2y2). The identification of a potential Y locus gene was made using differential expression analysis and nucleotide polymorphisms (DCAR_032551) (Iorizzo et al. 2016). It was observed that this gene co-expressed with DXS1 and LCYE, two genes engaged in the isoprenoid pathway, in non-photosynthetic root tissue, along with a slew of other genes involved in photosynthetic induced changes and functioning, plastid biosynthesis, and chlorophyll metabolism. Arabidopsis has a pseudo-etiolated morphology and interacts with genes that control light response and photomorphogenesis, including the Y gene potential homolog pseudo-etiolation in light (Ichikawa et al. 2006). DXS1 is involved in the production of carotenoid precursors in photosynthetic metabolism and is activated by light (Stange et al. 2008; Fuentes et al. 2012). DXS1 overexpression and carotenoid synthesis may be facilitated by a recessive allele (yy) in etiolated roots, according to a study by Iorizzo et al. (2016). Orange carrot roots exposed to light have been shown to undergo morphological changes that might be explained by this hypothesis, which is currently being tested out (Stange Klein and Rodriguez-Concepcion 2015). The Y2 and Y genes were shown to be segregating in the ‘B493  QAL’-derived population (Just et al. 2009). By combining molecular mapping with transcriptome analysis, it was feasible to determine the location of the gene Y2 in a population that was homozygous recessive for Y (yy) but segregated for root color associated with the Y2 region (Ellison et al. 2017). Many carotenoid-related genes were found to be differentially expressed between orange and yellow roots at 40 and 80 days following planting. A total of 6 genes were discovered in the 650-kb region, including PSY1, PSY3, geranylgeranyl diphosphate synthase 1 (GPPS1), neoxanthin synthase 1 (NSY1), carotenoid cleavage dioxygenase 1 (CCD1), LUTEIN DEFICIENT 5 (LUT5), and two cytochrome genes. In this study, it was observed that DXP reductoisomerase (DXR) was the only MEP or carotenoid pathway gene expressed present in that region, despite the fact that it did not express differently in orange versus yellow carrots. Among the 17 genes that changed between 40 and 80 days were detected in the fine-mapped region, only 4 were found in the fine-mapped region. A recessive phenotype was anticipated for just one of the four, the “protein

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dehydration-induced 19” homolog 5 (Di19) (DCAR 026175) gene, which showed lower expression in orange roots than yellow roots. AtDi19-7, a member of the Arabidopsis Di19 gene family, has been associated with light signaling responses, and other abiotic stimuli, including abscisic acid (Milla et al. 2006). Variations in the expression of Di19 during photomorphogenesis may have an impact on the synchronized synthesis of chlorophyll and carotenoids throughout this process. In order to confirm the Y2 candidate, more testing is needed since the 650-kb region reported by Ellison et al. (2017) contains several candidate genes. Another gene that impacts carotenoid accumulation in carrot roots and includes the whole spectrum of carotenoid colors was identified in a recent association research that included data from 154 wild and 520 cultivated carrots from geographically diverse worldwide growing regions (Ellison et al. 2018). This carrot collection was analyzed using genotyping by sequencing (GBS) to look for evidence of domestication. The study discovered a connection between high levels of carotene and the existence of the Or gene in a 143-kb genomic region of chromosome 3, which lacked any MEP or carotenoid genes. Or is essential for chromoplast formation, which acts as a sink for carotenoids in several plants species, including Arabidopsis, cauliflower, and sweet potato (Lu and Li 2008; Yuan et al. 2015; Sun et al. 2018), and a similar role for Or in carrot root has been hypothesized (Lu and Li 2008; Yuan et al. 2015; Sun et al. 2018). Cultivated carrots from Central Asia, which is the principal source of carrot diversification (Iorizzo et al. 2013), had higher expression levels of the Or gene than cultivated carrots from Europe. While the wild-type allele for Or (Orw) causes yellow root color, recessive genotypes present light orange root, and the storage roots of OrcOrcyyy2y2 plants are yellow in color, while the wild-type allele for Or (Orw) causes yellow color. Orc allele polymorphism may have had a role in carrot domestication in Central Asia prior to the Or gene being fixed for use in European carrots. Scientists are currently investigating the relationship between Or allele-specific gene expression and phenotypes.

6.5

Genetic Engineering for Enhancing Carotenoids Levels in Carrot

Increased carotenoid production and accumulation were achieved by introducing the phytoene synthase (PSY) gene from Erwinia herbicola into the carrot plant and combining it to a plastid transit peptide, which targets the enzyme that targets chromoplasts (Hauptmann et al. 1997). Its expression enhanced phytoene biosynthesis in orange carrot root, which resulted in ~twofold increase in β-carotene concentration. When the crtB gene under the control of a yam root-specific promoter was genetically engineered into wild carrot, the color of the transformed roots shifted from white to brilliant yellow, indicating that the gene was successfully expressed. A high concentration of carotene intermediates, such as phytoene, phytofluene, and ζ-carotene and lycopene, which accompanied β-carotene in significantly lower proportions than in normal orange root, were responsible for the different root colors, whereas α-carotene was not detected in this sample. In this way, upregulation of PSY in resulted in higher

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carotenoid concentrations in carrot roots and enhanced carotenoid storage in chromoplasts in the crystalline form, similar to what occurs in orange carrots, despite the fact that the carotenoids composition was different (Maass et al. 2009). The carrot homologue of the carotene hydroxylase gene from ArabidopsisCYP97A3 was found to be expressed in orange carrot roots as well as in other plants. However, while the Arabidopsis gene (AtCYP97A3) is fully functional, the carrot DcCYP97A3 present in orange-rooted cultivars is only partially functional or nonfunctional, due to an 8-nucleotide frameshift insertion that generated a premature stop codon, resulting in the production of a truncated hydroxylase protein (Arango et al. 2014). As a result, the conversion of α-carotene to lutein is inhibited, therefore α-carotene content and the α/β carotene ratio are increased (Fig. 1). The overexpression of AtCYP97A3 in transgenic orange carrots resulted in a reduction in the quantity of α-carotene present in the carotenoid composition. It was also noticed that carotene hydroxylase overexpression was associated with a reduction in total carotenoids, which was due to a lower PSY protein level, despite no changes observed in PSY gene expression. It was hypothesized that carotene hydroxylase overexpression may negatively affect PSY protein translation (Arango et al. 2014). Similarly, the significance of precursors in carotenoid biosynthesis was investigated by introducing – via transgenics – the Arabidopsis deoxyxylulose 5-phosphate synthase (DXS) and reductoisomerase (DXR) genes from the MEP pathway in carrot. The overexpression of DXS increased PSY transcript levels and, as result, increased carotenoid quantities by an average of twofold, but the overexpression of DXR had no significant impact (Simpson et al. 2016). The effect of the algal Haematococcus pluvialis β-carotene ketolase (bkt) on carrot carotenoids production was investigated. In the presence of this enzyme, β-carotene is converted to ketocarotenoids such as canthaxanthin and astaxanthin, which have great antioxidant effects and are useful nutraceuticals in the human diet, as well as feed additives for pale fish, salmon, and trout cultures. It was necessary to fuse the bkt gene to the ribulose bisphosphate carboxylase-oxygenase (RuBisCO) signal peptide in order to assure that the enzyme would function in plastids. Leaf and root levels of carrot β-carotene hydroxylases were upregulated in comparison to other tissues. The accumulation in carrot roots of ketocarotenoids, primarily astaxanthin, adonirubin, and canthaxanthin, up to concentrations of 2400μg/g dry weight, was seen in conjunction with a decline in carotenes (Jayaraj and Punja 2008). The growth of plants having high concentrations of ketocarotenoids was improved when they were subjected to intense UV-B irradiation, and the leaves were less damaged when H2O2 or methyl viologen stress was administered to them. As a result of the significant antioxidant and free radical scavenging activity of ketocarotenoids, it was inferred that the cells were protected from oxidative stress (Jayaraj and Punja 2007).

6.6

Perspectives on Carrot Carotenoids

Carrot roots may store a variety of carotenoids via divergent pathways. The study of carotenoid production and accumulation in carrot storage roots employs a

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multidisciplinary approach that includes genetics, gene expression, and metabolic interactions. There are three primary root colors associated with the accumulation of carotenoids in this organ: yellow, orange, and red. Each color represents a very simple set of metabolic activities that are linked to variations in genetic differences for the genes involved, expression levels, and carotenoid accumulation throughout periods of development. However, when looking at the link between root color and carotenoid content, it has been difficult to figure out how the carotenoid pathway may account for the variations observed in carotenoid composition in orange, yellow, and red carrots. The color of carotenoid pigments is affected by variations in the way they are synthesized, as well as by changes in photomorphogenesis and plastid development. We know relatively little about the regulatory genes involved in the non-carotenoid biosynthesis pathway, discovered by means of carrot genome sequencing and other multi-omics approaches, and we hope to learn more in the future.

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Umiel N, Gabelman WH (1972) Inheritance of root color and carotenoid synthesis in carrot, Daucus carota, L.: orange vs. red. J Am Soc Hortic Sci 97:453–460 Vasudevan M, Gunnam KK, Parle M (2006) Antinociceptive and anti-inflammatory properties of Daucus carota seeds extracts. J Health Sci 52:598–606 Vivek BS, Simon PW (1999) Linkage relationships among molecular markers and storage root traits of carrot (Daucus carota L. ssp. sativus). Theor Appl Genet 99:58–64 Wako T, Kimura S, Chikagawa OY (2010) Characterization of MYB proteins as transcriptional regulatory factors for carrot phenylalanine ammonia-lyase gene (DcPAL3). Plant Biotechnol 27: 131–139 Wang H, Ou CG, Zhuang FY, Ma ZG (2014) The dual role of phytoene synthase genes in carotenogenesis in carrot roots and leaves. Mol Breed 34:2065–2079 Warner SR (2019) Carrots and cancer: the bioavailability of polyacetylene from carrots and their association with biomarkers of cancer risk. PhD thesis dissertation, Human Nutrition Research Centre, Faculty of Medical Sciences, Newcastle University, UK Xu ZS, Huang Y, Wang F (2014) Transcript profiling of structural genes involved in cyanidin-based anthocyanin biosynthesis between purple and non-purple carrot (Daucus carota L.) cultivars reveals distinct patterns. BMC Plant Biol 14:262 Xu ZS, Ma J, Wang F, Ma HY, Wang QX et al (2016) Identification and characterization of DcUCGalT1, a galactosyltransferase responsible for anthocyanin galactosylation in purple carrot (Daucus carota L.) taproots. Sci Rep 6:27356 Xu Z-S, Feng K, Que F, Wang QX, Xiong A-S (2017) A MYB transcription factor, DcMYB6, is involved in regulating anthocyanin biosynthesis in purple carrot taproots. Sci Rep 7:45324 Xu Z-S, Yang Q-Q, Feng K, Xiong A-S (2019) Changing carrot color: insertions in DcMYB7 alter the regulation of anthocyanin biosynthesis and modification. Plant Physiol 181:195–207 Xu Z-S, Yang Q-Q, Feng K, Yu X, Xiong AS (2020) DcMYB113, a root-specific R2R3-MYB, conditions anthocyanin biosynthesis and modification in carrot. Plant Biotechnol J7:1585–1597 Yahyaa M, Tholl D, Cormier G, Jensen R, Simon PW, Ibdah M (2015) Identification and characterization of terpene synthases potentially involved in the formation of volatile terpenes in carrot (Daucus carota L.) roots. J Agric Food Chem 63:4870–4878 Yahyaa M, Ibdah M, Marzouk S, Ibdah M (2016) Profiling of the terpene metabolome in carrot fruits of wild (Daucus carota L. ssp. carota) accessions and characterization of a geraniol synthase. J Agric Food Chem 66:2378–2386 Yildiz M, Willis DK, Cavagnaro PF, Iorizzo M, Abak K et al (2013) Expression and mapping of anthocyanin biosynthesis genes in carrot. Theor Appl Genet 126:1689–1702 Yoshitomi K, Taniguchi S, Tanaka K, Uji Y, Akimitsu K et al (2016) Rice terpene synthase 24 (OsTPS24) encodes a jasmonate responsive monoterpene synthase that produces an antibacterial γ-terpinene against rice pathogen. J Plant Physiol 191:120–126 Yuan H, Zhang J, Nageswaran D, Li L (2015) Carotenoid metabolism and regulation in horticultural crops. Hortic Res 2:15036 Zaini RG, Brandt K, Claench MR, Le Maitre CL (2012) Effects of bioactive compounds from carrots (Daucus carota L.), polyacetylenes, beta-carotene and lutein on human lymphoid leukaemia cells. Anti Cancer Agents Med Chem 12:640–652 Zhang D, Hamauzu Y (2004) Phenolic compounds and their antioxidant properties in different tissues of carrots (Daucus carota L.). J Food Agric Environ 2:95–100, ISSN:14590263 Zhang Y, Butelli E, Martin C (2014) Engineering anthocyanin biosynthesis in plants. Curr Opin Plant Biol 19:81–90 Zhang H, Liu R, Tsao R (2016) Anthocyanin-rich phenolic extracts of purple root vegetables inhibit pro-inflammatory cytokines induced by H2O2 and enhance antioxidant enzyme activities in Caco-2 cells. J Funct Foods 22:363–375 Zidorn C, Jöhrer K, Ganzera M, Schubert B, Sigmund EM et al (2005) Polyacetylenes from the Apiaceae vegetables carrot, celery, fennel, parsley, and parsnip and their cytotoxic activities. J Agric Food Chem 53:2518–2525

Metabolomics and Cytoplasmic Genomics of Allium Mostafa Abdelrahman, Rawan Rabie, Magdi El-sayed, and Masayoshi Shigyo

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Unique Resources for Genetics and Breeding in Allium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Cytoplasmic Male Sterility (CMS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Inbred Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Wild Species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Chloroplast Genome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Mitochondrial Genome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Nuclear Genome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Linkage, Cytogenetic, and Physical Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Novel Analysis Methods for Large Genome Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Metabolomic and Transcriptomic Landscapes of Allium Crops in Response to Environmental Stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Allium is the biggest genus of petaloid monocotyledons, with more than 750 species widely distributed in a range of climatic conditions worldwide, especially in the Northern Hemisphere. Allium comprises commercially significant food crops, including onions, garlic, leeks, and chives, as well as species with medicinal M. Abdelrahman (*) Aswan University Faculty of Science, Aswan, Egypt e-mail: [email protected] R. Rabie · M. El-sayed Faculty of Science, Galala University, Suze, Egypt M. Shigyo Laboratory of Vegetable Crop Science, College of Agriculture, Graduate School of Sciences and Technology for Innovation, Yamaguchi University, Yamaguchi, Japan © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_52

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qualities. Bulb onions rank second only after tomatoes in terms of global production, which indicates the importance of Allium crops and the need for developing new Allium crop varieties with beneficial agronomical traits. Recently, there has been considerable interest in investigating the genetic resources of Allim crops and their wild relatives for improving Allium breeding and possible future genetic manipulation. This chapter provides a comprehensive review of major Allium crops and their wild relatives from scientific and horticultural perspectives. This chapter broadly covers the unique resources for Allium genetics and breeding, including the recent development of cytoplasmic male sterility, inbred lines, and wild species. We also discuss and summarize the recent developments in Allium genome sequencing, including novel tools for large genome sequencing, the chloroplast genome, mitochondrial genomes, and the nuclear genome. Furthermore, we provide a brief overview of the linkage, cytogenetic, and physical mapping in various Allium crops. Finally, we provide a special focus on Allium metabolome and transcriptome analysis as important approaches for understanding Allium stress responses. Our book chapter provides recent developments in Allium genomics and metabolome dynamics, which open the possibility of developing novel Allium crop cultivars with enhanced nutritional value and stress tolerance under current climatic conditions. Keywords

Allium · Cytogeneitcs · Allium genome · Genetic resource · Allium metabolomics · Stress tolerance

1

Introduction

Onions (A. cepa L. Common onion group), shallots (A. cepa L. Aggregatum group), garlic (A. sativum L.), Japanese bunching onion (A. fistulosum L.), and leeks (A. ampeloprasum L. Leek group) are all in the same genus Allium that have been cultivated globally as important spices, condiments, and vegetables (Abdelrahman et al. 2016). The genus Allium comprises ~1000 species (Govaerts et al. 2005–2020), of which onions, shallots, and leeks are widely cultivated, and displayed remarkable diversity in their morphological and physiological properties, particularly in life form (Abdelrahman et al. 2017a, b, c). Allium is propagated commonly through the Northern Hemisphere from the boreal region to the dry subtropics. A region with high density of species diversity started from the Mediterranean Basin to Central Asia, in addition to a second smaller centre of species diversity which is located in North America (Fritsch et al. 2010; Abdelrahman et al. 2017a, b, c) (Fig. 1). Additionally, Allium species show significant variation in a number of cytogenetic traits, including ploidy level (ranging from 2
to 16
), genome size, and chromosomal numbers (x ¼ 7, 8, and 9). Specifically, the largest genomes have been found in Alliums, ranging from 18.1 picograms (pg) in A. triquetrum L. to 31.5 pg in A. ursinum L. (Bennett et al. 2000; Peška et al. 2019). For instance, the haploid

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Fig. 1 Allium distribution in the northern and southern hemisphere. The red and purple circles indict the center for high Allium diversity from Central Asia to the Mediterranean Basin

genome size of the bulb onion was calculated to be about 16,400 Mega bases (Mb)/1C, making it the largest among all cultivated diploid crops. This size is 120 times larger than Arabidopsis (ca. 125 Mb) and 5 times larger than the human genome, which is only about 3000 Mb (Ricroch et al. 2005). At least 95% of the onion genome is made up of repetitive sequences (Vitte et al. 2013), which are typically associated with large genome sizes (Kelly and Leitch 2011). As a result, mapping and genomicassisted breeding in Alliums are behind that of other crops like tomato (Solanum lycopersicum), wheat (Triticum aestivum), and rice (Oryza sativa), making the entire genome sequencing of bulb onions a considerable problem. With the development of next-generation sequencing (NGS) technology, DNA sequencing of many plant species, including Allium, grew faster and more efficient with higher throughputs and greater genome coverage (Abdelrahman et al. 2017a, b, c; Abdelrahman 2020; Valliyodan et al. 2017). With the use of these NGS technologies, the first waves of crop genome sequencing, gene expression atlases, and a better knowledge of the signalling networks underlying plant responses to biotic and abiotic stresses were all made possible (Rothberg et al. 2011; Abdelrahman et al. 2019). In this chapter, we report the first trail of the genome assembly of doubled haploid (DH) A. cepa. Additionally, the presentation of the Allium genome organization, which includes the nuclear, mitochondrial, and chloroplast genomes are given. This chapter also addressed how the genetic resources of the Allium species, such as DHs, alien chromosomal addition lines, and cytoplasmic substitution lines, have been employed in various genetic research to comprehend the discrepancy between Allium’s phenotype and genotype traits. This chapter’s contents will be a useful tool for studying onion breeding genetic resources, which are valuable for onion breeding and research.

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Unique Resources for Genetics and Breeding in Allium

Since Peffley et al. (1985) published their pioneering research, monosomic addition lines (MALs) have been useful genetic resources for studying important agronomic traits in cultivated Alliums and assigning linkage groups to physical chromosomes. For example, in a backcross population (BC2) of amphidiploid hybrids between A. fistulosum (FF) and shallot (A. cepa Aggregatum group, AA), a full set of A. fistulosum and A. cepa MALs (2n ¼ 2x + 1 ¼ 17, genomes + chromosomes FF +1A-FF+8A) was identified (Shigyo et al. 1996). To confirm the integrity of the chromosomal constitutions, the MALs were subjected to genomic in situ hybridization (GISH) as described by Shigyo et al. (1996). Following that, 48 shallot chromosomespecific molecular markers were developed in conjunction with qualitative data for morphological identifications (Shigyo et al. 1997a, b). All of these morphological characteristics appear to be related to the genetic effects of the shallot additional chromosome(s) on the A. fistulosum integral diploid background. The reddishbrown sheaths of FF+5A indicated that this line had a high flavonoid and anthocyanin content (Shigyo et al. 1997b). Evidently, integrated metabolome and transcriptome assessment of the entire set of MALs provides additional evidence that shallot chromosome 5A harbored many candidate genes associated in flavonoid biosynthesis (Abdelrahman et al. 2019). When compared to other MALs, FF+5A exhibited high expression of many downstream and upstream flavonoid and anthocyanin-related genes, which was coherent with the accumulation of several flavonoids and anthocyanin-related compounds. Similarly, saponin transcriptome and phytochemical screening in MALs revealed that FF+2A accumulated Alliospiroside, a saponin with powerful antifungal activity against Fusarium pathogens and an useful attribute for disease resistance (Abdelrahman et al. 2017a, b, c). Furthermore, Yaguchi et al. (2013) also investigated antioxidant capacity and polyphenol concentration in MALs, discovering that the FF+2A and FF+6A lines had the greatest polyphenol concentration and antioxidant capacity. As a result, the additional chromosomes 2A and 6A contain anonymous genes associated with polyphenol production increased expression. Shigyo and co-workers carried out such approaches in six interspecific-combinations, A. cepa – A. fistulosum (Hang et al. 2004; Yaguchi et al. 2008), A. cepa – A. roylei Stearn (Vu et al. 2012), A. fistulosum– A. roylei (Ariyanti et al. 2015), A. fistulosum – A. galanthum Kar. et Kir. (Tashiro et al. 2000), A. fistulosum – A. oschaninii O. Fedtsch. (Tashiro et al. 2000), and A.fistulosum – A. vavilovii M. Pop. et Vved. (Tashiro et al. 2000) together with further approaches for disomic additions (Shigyo et al. 2003; Yaguchi et al. 2008) and multiple alien chromosome additions (Masuzaki et al. 2007), some of which are relevant to elucidating a specific epistatic regulation related to secondary metabolite biosynthesis (Masuzaki et al. 2006).

2.1

Cytoplasmic Male Sterility (CMS)

CMS is a maternally inherited trait that prevents the formation of viable pollens while leaving female gametes unaffected, allowing them to serve as seed parents in hybrid

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seed production (Yamashita et al. 2007). In contrast, a single nuclear locus renowned as Ms is known to revive CMS male fertility in onions. In a recent study by Yu and Kim (2020), inheritance patterns in segregating populations implied that the Ms and Ms2 loci were both engaged in fertility restoration in onions. The Ms2 locus was found at the end of chromosome 2 at a distance of 70cM from the Ms locus (Yu and Kim 2020). Although it is unknown whether the causal genes for Ms and Ms2 loci are paralogs, transcription levels of orf725, a CMS-associated gene in onions, were significantly down-regulated in male-fertile individuals of segregating populations, suggesting that the causal gene for Ms2 may be able to restore male fertility by suppressing transcription of orf725 or degrading transcripts (Yu and Kim 2020). Allium galanthum (G) cytoplasm induces CMS in bulb onion (Havey 2002), Japanese bunching onion (Yamashita et al. 1999a, b, 2002, 2005; Yamashita and Tashiro 2004), and shallot (Yamashita et al. 1999). In shallot, the G cytoplasm was introduced through continuous backcrossing to shallot the recurrent parent, to obtain interspecific F1 hybrids (Yamashita et al. 1999). A. roylei (R) originated CMS lines, were identified in the BC2 progenies of a single amphidiploid (possessing Rcytoplasm) between A. roylei (female parent) and A. cepa. Breeding onion F1 hybrid varieties takes 10–12 years to establish the A (malesterile line), B (male-sterile maintainer), and C (restorer) lines (Shigyo and Kik 2008), while alloplasmic lines possessing either GorR cytoplasm saves breeders’ time and nullifies the need for B line. Moreover, since the CMS system is conditioned by the incompatibility between the wild species’ cytoplasm and the A. cepa nucleus, any onion population acts as a male sterility maintainer. Unfortunately, no G or R CMS onion lines have been used in actual onion F1 seed production. It should be noted, however, that compared to the S-type cytoplasmic male sterility, there are concerns about nectar production, a preferred factor by flowervisiting insects, and/or interaction of pollen production with the environment. Further research on the ecology and physiology of cytoplasm in wild species is needed.

2.2

Inbred Lines

The traditional breeding of onion inbred lines is long and difficult because of its biennial life span, inbreeding depression, and high heterozygosity. Thus, DH lines provide several advantages, including complete homozygosity, reduced DNA methylation, and elimination of deleterious alleles compared with inbred lines (Bohanec 2002) and consequently exhibit vigorous vegetative growth, morphological uniformity (Hyde et al. 2012; Khan et al. 2020). Single- and two-step protocols have been used to generate gynogenic haploids in onion. The former involves culturing whole flower buds, ovaries, or ovules to the embryo, or plantlet stage (Bohanec and Jakše 1999; Bohanec 2002). Whereas the latter includes preculture of flower buds on basal media with or without plant growth regulators. Then, isolation of ovary or ovule and subsequent subculturing on regeneration media with growth regulators (Michalik et al. 2000; Martinez et al. 2000). DH lines may be induced in vitro by culturing haploid cells from the male (androgenesis) or female (gynogenesis) gametophytes. However, the efficiency of androgenic generation DHs is limited in some Allium

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cepa genotypes due to defective pollen or anthers, or/and the production of albinos during culture. Gynogenesis has been the most commonly used method for producing haploids in A. schoenoprasum L. (Keller 1990), leek (Kaska et al. 2013; Alan et al. 2016), A. altaicum (Keller 1990), A. giganteum (Susek et al. 2002), shallot (Sulistyaningsih et al. 2006), A. fistulosum (Ibrahim et al. 2016), A. tuncelianum (Yarali and Yanmaz 2016), and others. DH lines offer very promising tools to understand the gap between phenotype and genotype, and DH chromosomal doubling can shorten the time, offer homozygous pure lines, and provide valuable materials for genomic analysis. For example, comparative metabolome analysis of shallot and bulb onion DHs (DHA, and DHC, respectively) and F1 hybrid revealed genotype-specific metabolites for each. DHA accumulated several stress-related metabolites, which is consistent with the biotic and abiotic stress shallot tolerance compared with bulb onion (Abdelrahman et al. 2015). Similarly, Khosa et al. (2016) developed transcriptome data from reproductive and vegetative organs of onion DH line ‘CUDH 2107’ to identify tissue-specific expressed genes involved in pollen fertility. The Cornell onion breeding program compared 20 DH lines with commercial hybrids and open-pollinated cultivars (OP) developed from the same source germplasm over 2 years, under field conditions (Hyde et al. 2012). Results indicated a similar vegetative vigor of both DH and OPs, with minimal inbreeding depression. A comparison between two sets of hybrids produced using male DH lines and two different commercial females showed increased vegetative growth vigor of DH lines and their derived hybrids probably due to elimination of deleterious lethal genes during gynogenesis, an additional benefit for onion breeding strategies (Hyde et al. 2012). DH lines lack allelic exchanges within a locus, thus genetic effects are controlled by single alleles or interactions between loci, thus facilitating detection of quantitative trait loci (QTL) (Duangjit et al. 2014). Hence, onion DH lines from the four Spanish cultivars, including highly pungent landrace ‘BGHZ1354’, sweet cultivar ‘Fuentes de Ebro’, and ‘Recas’ and ‘Rita,’ two commercial Valenciana-type varieties (Fayos et al. 2015) served for the development of linkage maps. More comprehensive research and improved DH in vitro gynogenesis production methods are needed and would be useful to produce DH in onion and other Allium species.

2.3

Wild Species

Wild relatives have great potential to expand the supply of usable genetic variation and useful traits, thus are important for introgression breeding (Hao et al. 2020). Allium roylei (RR, 2n ¼ 16) possess several desired traits, including resistance to Botrytis leaf blight and downy mildew (Abdelrahman et al. 2014). Similarly, Alliumfistulosum (AF) exhibits several important agronomical traits for onion improvement (Matsuse et al. 2022), thus great attention has been given to the introgression of A. fistulosumgenes to A. cepa. However, the interspecific hybrid is largely sterile, and heteromorphic bivalents are present (Emsweller and Jones 1935; Albini and Jones 1990). In addition, the backcross (BC1) of the interspecific hybrid

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with A. cepa usually yields a small progeny, due to nucleo-cytoplasmic incompatibility (van der Valk et al. 1991). Using A. roylei as a bridging species helps to circumvent these problems. Hence, A. cepa (CC)
A. roylei (CR), A. cepa
A. fistulosum (CF), and A. fistulosum
A. roylei (FR) (Khrustaleva and Kik 1998) were bridge-crossed with (CC
FR) where A. Cepa served as the female parent and A. roylei as a male parent (Khrustaleva and Kik 1998). Thereafter, genome organization of the interspecific hybrids and trihybrid population were analyzed using multicolor GISH (Khrustaleva and Kik 1998). In a follow-up study, trihybrid genotypes from the CC
RF population where only one homolog of a chromosome pair underwent interspecific recombination, were used for GISH analysis of chromosomes 5 and 8 recombinants. Visualization of recombination points and the physical positions of recombination were integrated into amplified fragment length polymorphism (AFLP) linkage maps of both chromosomes, thus concluding that in Allium, recombinations predominantly occur in the proximal half of chromosome arms. Of the PstI/MseI markers, 57.9% are located near the centromeric region, thus suggesting genes’ presence in this region (Khrustaleva et al. 2005). Investigations of trihybrid ‘CC
RF’ population for root traits inheritance revealed quantitative trait loci (QTLs) for the rooting system, implying that breeding for an enhanced rooting system in onion is feasible (De Melo 2003). Analyzes of trihybrid ‘CC
CF’ population for the genetic background for response to arbuscular mycorrhizal fungus Glomus intraradices revealed that the amalgamation of three genomes increases the genetic variation for plant development and the mycorrhizal reaction (Galván Vivero et al. 2011). On linkage group 9, one QTL for the number of stem-borne roots of mycorrhizal plants was discovered, which was connected with A. fistulosum alleles. This QTL co-segregated with QTLs for mycorrhizal and nonmycorrhizal plant average performance and total dry weight. Another QTL for Fusarium basal rot (FBR) resistance from A. roylei was identified on a distal region of chromosome 2, and one QTL from A. fistulosumwas identified on the long arm of chromosome 8 (Galván Vivero 2009). These QTLs showed an additive effect and together accounted for 31 and 40% of the total variation for FBR incidence and severity at harvest; and 31 and 29% after storage, respectively.

3

Genomes

Plant cells have three genomes, mitochondrial, plastid, and nuclear. The number of genome copies per organelle depends on the cell type, the age of tissue, and species. Hence, each Arabidopsis thaliana (L.) Heynh cell has two copies of the nuclear genome (gDNA) (Lutz et al. 2011). The number of mitochondria and plastid DNAs (mtDNA, and ptDNA, respectively), however, vary with cell types. Arabidopsisroot cells have ~400 mtDNA (Kato et al. 2008), whereas maize anther cells have a 20 to 40-fold higher number of mtDNA (Warmke and Lee 1978). In Arabidopsis and sugar beet, the copy number of ptDNAs remains at ~1700 per a single gDNA molecule, and the ratio of ptDNA to gDNA remains constant even as the ploidy level of the cell changes (Lutz et al. 2011).

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Chloroplast Genome

The chloroplast (cp), which evolved from photosynthetic bacteria, is the primary organelle responsible for carbon fixation and photosynthesis in green plants (Cho et al. 2015). Most angiosperms have maternally inherited cps genomes and genetic information (Song et al. 2017). The evolutionary conserved genome architecture and gene content assisted in the creation of genetic markers for DNA barcoding, molecular identification, phylogenetic classification, and genetic resource and breeding screening. (Hu et al. 2016). The Allium cp whole-genome DNA sequencing initiation (von Kohn et al. 2013) resulted in cpgenomes sequencing of A. obliquum L., A. prattii C. H. Wright, A. victorialis L. Sp. Pl. 1: 295. 1753, A. cepa, and A. sativum (http://www. ncbi.nlm.nih.gov/genome/organelle/). Recently, the cp genomes of A. tuberosum Rottl. ex Spreng., A. fistulosum, A. sativum, and A. cepa have been sequenced using NGS technologies (Huo et al. 2019), and comparisons with cp genomes of A. cepa CMS-T and CMS-S, A. victorialis, A. obliquum, and A. prattii revealed that the length of cp DNAs ranged from 152 (A. obliquum) to 154 kb (A. prattii) and that the genomic structure and gene organization are well conserved (Huo et al. 2019). The Allium cp genome contained large and small single-copy regions (LSC and SSC, respectively) separated by large inverted repeats (IRs) (Fig. 2). The nine cp genomes had typically quadripartite structures, with two IRs (ranged from 26,370 to 26,564 bp) splitted by the LSC (81,588 to 83,392 bp) and SSC (17,853 to 18,066 bp) regions (Huo et al. 2019) (Fig. 2). Furthermore, all Allium cp genomes had a similar gene arrangement and content, with 140–141 genes in the IR regions, including 8 rRNA genes, 5–10 pseudogenes, 37–38 tRNA genes, and 88–89 protein-coding genes (Huo et al. 2019) (Fig. 2). The GC copy number of nine complete cp genomes was very similar in each region, including the entire cp genome, LSC, IR, SSC, coding sequences (CDSs), rRNA, tRNA, and pseudogene. The highest was observed in rRNA (>55%) and the lowest in SSC (>29%). The numbers and distributions of 3 repeat types in the 9 Allium cp genomes, including 394 repeats with 131 tandem repeats, 154 dispersed repeats, and 109 palindromic were similar and conserved. The number of simple sequence repeats (SSRs) varies between the nine Allium genomes, ranging from 73 in A. tuberosum to 96 in A. cepa. CMS-N and CMS-T (Huo et al. 2019). In the phylogentic analysis of the genus Allium, nine accessions were separated into two sister clusters. The first cluster comprised A. prattii and A. victorialis; the second cluster comprised seven entrees, in which A. cepa CMS-T and CMS-N were grouped in a sister branch and then clustered with A. fistulosum, A. obliquum, A. cepa CMS-S, A. sativum, and A. tuberosum (Huo et al. 2019).

3.2

Mitochondrial Genome

Scheffler (2008) stipulates that the plant mitochondrial genome harbors important information, such as mode of gene expression, organizational diversity, evolution, and nuclear-cytoplasmic interactions. Collectively these make the mitochondrial

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Fig. 2 Comparison of the large single copy (LSC), inverted repeat (IR), and small single-copy (SSC) boundary regions among the nine chloroplast genomes of different Allium species. The numbers indicate the distances from the end of the gene to the boundary sites. (This figure is adopted from Huo et al. 2019 after modification)

genome one of the most interesting genomes to molecular biologists and plant genetics. Plant mitochondrial genomes typically have many long and short repeated sequences and intra- and intermolecular recombination may create various DNA molecules in this organelle, and recombination may create a novel gene that causes CMS (Tsujimura et al. 2019). The complete onion mitochondrial genome sequence was reported for a CMS-S inbred line (Kim et al. 2016), of which ~10% consisted of repetitive sequences with short repeats of 1000
copies) and 40% has 100–1000 copies (Stack and Comings 1979). Overall, at least 95% of the A. cepa genome consists of repetitive sequences, most of which are dispersed repeats (Shibata and Hizume 2002). Due to the size of the genome and its repetitive nature, developing an onion reference genome assembly is challenging. Although the accessibility of the structural genomic resources in Allium species is limited, using next-generation sequencing (NGS; e.g., Roche, Illumina, and ABI Solid platforms) technologies and large computational abilities, sequencing, assembly, and annotation of large genomes has become feasible. The advantages of third-generation sequencing (TGS) technologies such as Pacific Biosciences over short-read sequencing as Illumina’s HiSeq, NovaSeq, NextSeq, MiSeq instruments, and Ion Torrent sequencers (Thermo Fisher Scientific) include greater read lengths, thus facilitating the assembly of large and complex genomes such as onion (Abdelrahman et al. 2018a, b), i.e., reads of up to 600 bases (Goodwin et al. 2016), and >10 kb (Rothberg et al. 2011), respectively. Consequently, improved de novo assembly, mapping certainty, transcript isoform identification, and detection of structural variants become feasible (Depledge et al. 2019). Concomitantly, the ever-diminishing computational power costs and the growing availability of on-demand cloud-based computing steadily increase assembly and annotation efficiency. Hence, large-scale and cost-effective sequencing, assembly, and annotation of onion DNA are becoming feasible (Abdelrahman et al. 2020a, b). The three key approaches to large genome sequencing like the onion genome include the shot-gun sequencing, where DNA is fragmented into short reads, which are then sequenced. Since a large proportion of onion reads are repeated sequences, shot-gun sequencing is unsuitable for its large and complex genome. Suzuki et al. (2001) were the first to Sanger sequence large genomic fragments cloned into BACs. Two entire BAC clones, and the random ends of genomic fragments cloned into BACs, yielded 298 kb of random-end sequences and 202 kb from the entire BAC clones (Jakše et al. 2008), with AT content of 35.7%, which is close to the estimate of 32% by Kirk et al. (1970). Additionally, only 5% of these random genomic sequences showed significant similarities to nonorganellar proteins, 25% were highly similar to transposons or retrotransposons, and 70% showed no significant hits to the databases and were primarily degenerated retroelements (Jakše et al.

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2008). Additional sequence survey of onion random genomic sequences was conducted using DNA isolated from DH line 15,197. The DNA was trimmed, and random fragments were sequenced using Sanger and 454 technologies, generating 6590 reads, among them, 82% had no significant hits in the databases, 4% matched nuclear-encoded proteins, and 14% matched transposons (Jakše et al. 2008). The second approach efficiently samples expressed regions. Sequencing random cDNAs thus revealed the collection of genes (the transcriptome) expressed in any given tissue, at a specific developmental stage, or after treatment (Abdelrahman et al. 2017a, b, c, 2020a, b). However, the normalization of the cDNA reduces the frequencies of highly expressed genes and increases the number of sequencing reads from rarer transcripts (Abdelrahman et al. 2017a, b, c). A free access web-based tool named Allium TDB (http://alliumtdb.kazusa.or.jp/) contains several transcriptional data of Allium species. Likewise, the transcriptome sequencing on vegetative and reproductive tissues of homozygous DH CUDH2107 was used to develop a multi-organ reference transcriptome catalogue (Khosa et al. 2016). In general, the 271,665 contigs of transcripts were generated using the Trinity pipeline. This dataset was analyzed for gene ontology (GO), and the bulb onion transcripts were grouped into 95 functional groups, and among which Binding Domains the most abundant GO term followed by Carbohydrate-Binding (Khosa et al. 2016). The third approach involves enrichment for lower-copy regions by removing repetitive DNAs, and reduced representation sequencing involves selection against methylated DNA (Rabinowicz et al. 1999). In bulb onion, the sequencing of these fragments is an efficient approach to enrich genic regions in its enormous genome. Hence, the complete onion DH 15197 sequencing of methyl-filtered DNA fragments revealed that among the 2712 methyl-filtered fragments, 3% matched transposons, 55% were anonymous, and 42% were similar to nonorganellar proteins (Jakše et al. 2008). The first insight into the genome sequencing of A. cepa is now ongoing through the SEQUON project (http://www.oniongenome.net) using Illumina HiSeq 2500, intending to sequence the onion nuclear DNA and provide de novo genome assembly and ab initio annotation thus applied to the doubled haploid onion line DHCU066619, for a whole-genome shotgun sequencing of an onion genome (Finkers et al. 2021). Initially, Illumina HiSeq 2500 sequencing of 3 small libraries yielded 769 Gb sequence data, whose analyses provided an estimated genome size of ~13.6 Gb. Secondly, the MaSurCa based assembly resulted in 10.8 Gb in 6.2 M contigs with a contig N50 of 2.7Kb. This assembly was further scaffolded using 18.1 M PacBio RS II reads. Finally, the hybrid Illumina/PacBio assembly was further improved using Dovetail Chicago and subsequent HiRise scaffolding, thus indicating no misassemblies in the Illumina/PacBio hybrid contigs. The combination of these 3 technologies resulted in an assembly of 14.9 Gb in 92.9 K scaffolds with a scaffold N50 size of 436Kb. With an estimated genome size of 164 Gb/1C. To further organize genome assembly, three intraspecific genetic linkage maps (Duangjit et al. 2013; Fujito et al. 2021; Choi et al. 2020) and two interspecific genetic linkage maps (Scholten et al. 2016) were used to anchor scaffolds into pseudomolecules using AllMaps (Tang et al. 2015). A final assembly of 14.9 Gb with an N50 of 461 Kb. out of which, only 2.2 Gb (~6.7%) was ordered into

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8 pseudomolecules using 5 different genetic linkage maps (Finkers et al. 2021), whereas the remaining of the genome is presented in 89.8 K scaffolds. Additionally, 72.4% of the genome was successfully identified as repetitive sequences consisting mainly of retrotransposons. The ab initio gene prediction indicated 540,925 putative gene models, which is far more than expected, possibly due to the presence of pseudogenes. Of these models, 86,073 showed similarity to UNIPROT published proteins. No gene-rich regions were found, and most genes were uniformly distributed across the genome (Finkers et al. 2021). The analysis of synteny with garlic showed collinearity but also major rearrangements between both species. This assembly is the first high-quality genome sequence available for the study of onion and will be a valuable resource for further research. Similarly, garlic chromosome-level reference genomes and annotations by combining SMRT sequencing with PacBio Sequel Nanopore, 10x Genomics, Illumina HiSeq paired-end, and high-throughput chromosome conformation capture (Hi-C) sequencing resulted in a genome of 16.24 Gb (contig N50 length ¼ 194 kb, scaffold N50 length ¼ 725 kb (Sun et al. 2020). Then, 252.5-Gb of long reads obtained from Nanopore sequencing were mapped to the assembly. Thereafter, the Hi-C technology was applied to assemble a chromosome-level genome. A total of 6.34 billion reads from four Hi-C libraries were used, and approximately 87.5% of the assembled sequences were mapped to 8 pseudomolecules with a super-scaffold N50 length of 1.69 Gb (Sun et al. 2020). The final assembly covered 96.1% of the garlic genome (approximately 16.9 Gb), as estimated by the k-mer analysis. In addition, a total of 38 alliinase genes were expressed in various tissues, out of which, 4 tandem duplicated genes (Asa5G05557.1, Asa5G05559.1, Asa5G05560.1, and Asa5G05561.1) produced highly abundant transcripts in bulb tissues (Sun et al. 2020). In addition, their expression levels increased during bulb growth and expansion, suggesting that these four genes exhibited functional redundancy and may be responsible for the biosynthesis of allicin at a high concentration in garlic bulbs (Sun et al. 2020).

6

Metabolomic and Transcriptomic Landscapes of Allium Crops in Response to Environmental Stress

Because of the high yield losses in principle crops caused by global warming in addition to the rapidly increasing consumption of food, there is an urgent need to boost food security (Abiala et al. 2018; Zhang et al. 2019). Nevertheless, there have been few studies that address the Allium metabolome and transcriptome profiling in the context of environmental stress, so the Allium international community may need to make more efforts in this area. Transcriptome analysis of commercial brown onion cv. ‘Orlando’ inner and outer scales in response to heat stress revealed that oxidation and lipid metabolism pathways, in addition to cell-wall adjustment, were abundantly expressed in the onion outer scale under heat stress (Galsurker et al. 2018). However, defense response-related genes, such as those gene that encodes antioxidant activities, heat shock proteins, or even the manufacturing of osmoprotectant metabolites, were highly stimulated in the inner scale. (Galsurker et al. 2018). These transcriptomic data

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led to the creation of a conceptual framework that proposes sequential processes for the advancement of desiccation and browning on the outer scale versus processes associated with defense response and high temperature tolerance in the inner scales (Galsurker et al. 2018). Transcriptome sequencing of cold-tolerant and cold-sensitive onion genotypes under freezing and cold conditions revealed that freezing and cold stresses significantly induced numerous genes in tolerant lines compared to susceptible genotypes (Han et al. 2016). Among these transcript, genes-encoding hypothetical proteins, heat shock proteins (HSPs), zinc finger (ZIP) proteins, and CBL-interacting protein kinase (CIPK) , as well as a subset of transcription factors (TFs), especially TFs that function as activators including dehydration-responsive element (DRE)-binding (DREB), CBL, MYB, bZIP, zinc finger of Arabidopsis thaliana (ZAT), HSPs, and basic helix-loop-helix (bHLH) were radically changed during freezing and cold stress conditions (Han et al. 2016). Likewise, a genome-wide transcriptome profiling analysis of garlic under cold stress revealed that enzyme-encoding genes, which knowingly enriched in the “proteasome” pathway such as γ-glutamyltranspeptidase-, δ-aminolevulinic acid dehydratase-, and alliinase-encoding genes are conceivably implicated in garlic discoloration under low temperature stress (Li et al. 2018). These stress-responsive genes could be to blame for garlic discoloration caused by low temperatures (Li et al. 2018). Because environmental stress impacts plant growth, identifying stress biomarkers is an important prerequisite for breeding stress-tolerant crops. In this respect, shallots are recognized as an important genetic resource for the breeding of common onions due to their high versatility to subtropical and tropical climates (Abdelrahman et al. 2015). The bulb onion double haploid, shallot double haploid, and its F1 hybrid were checked using LC-QqQ-MS. There were 113 targeted metabolites found in total, and the principal component analysis and volcano plot analysis clearly revealed genotype-specific metabolites that can be used as metabolic markers of environmental tolerance (Abdelrahman et al. 2015). Likewise, incorporated transcriptome and metabolome analysis of A. fistulosum with extra shallot chromosome 5A disclosed an accumulation of many flavonoids that are important in abiotic and biotic stress tolerance (Abdelrahman et al. 2019). The increase in flavonoid pool in A. fistulosum with extra chromosome 5A from shallot was also coherent with the increased expression of many upstream and downstream flavonoid biosynthesis and regulatory genes (Abdelrahman et al. 2019). The above study proved that shallot can be used as a genetic resource to enhance onion stress tolerance. Similarly, Zhang et al. (2018) used transcriptome analysis of two contrasting dark-red and white onion cultivars to discover that both flavonoid 30 ,50 -hydroxylase (F30 ,50 H) and dihydroflavonol 4-reductase (DFR) genes play important roles in the biosynthesis of dark-red bulbs, and that flavonol synthase (FLS) and DFR gene expression levels could respond to prevent blue coloration. In addition, the positive variation in the F30 ,50 H/F30 H ratio also affects onion bulb color diversity (Zhang et al. 2018). The metabolic characteristics in the bulbs of eight Indonesian shallot landraces and seven short-day and three long-day bulb onion cultivars have been identified using LC-QTOF-MS/MS in order to generate new genetic materials for the development of a novel bulb onion cultivar derived from intraspecific hybrids with beneficial agronomic traits from shallots (Abdelrahman et al. 2020a, b). The results showed that free and

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conjugated amino acids, flavonoids (particularly metabolites containing flavonol aglycone), anthocyanins, and organic acids were among the top metabolite factors that were largely correlated with shallot landraces when compared to bulb onion cultivars (Abdelrahman et al. 2020a, b). Furthermore, the measurement of 21 amino acids using traditional HPLC analysis revealed that shallots had elevated concentrations than bulb onions (Abdelrahman et al. 2020a, b). The current study found that shallots reprogrammed their metabolism to accumulate more amino acids and flavonoids as an adaptation to incredibly hot tropical environments.

7

Prospects

Omics’ techniques such as transcriptomics, proteomics, metagenomics, metabolomics, and genomics have the potential to provide new avenues of research as well as advancement for Allium crops with restricted genome sequence knowledge. NGS systems have lately been regularly used to reveal markers such as SSRs and SNPs in numerous bulb onion populations. For example, a high-throughput genotyping method, such as diversity arrays (DArTseq), was used to analyze population dynamics in a large garlic population with 417 accessions. (Egea et al. 2017). Likewise, SNPs were discovered using the double digest restriction site-associated DNA sequencing (ddRAD-seq) method in inbred lines of Korean short-day onion, allowing for structure analyses and genetic relationship studies (Lee et al. 2018). Even though genomic resources in Allium species have been limited to date, the latest rapid advancement of NGS technology has rendered whole-genome sequencing much easier than previously. The genome sequencing of A. cepa is now ongoing through the SEQUON project (http://www.oniongenome.net) by using Illumina HiSeq 2500 sequencer. More recently, HiFi reads [a type of data produced using the circular consensus sequencing (CCS) mode on one of the PacBio Sequel Systems], provide base-level resolution with >99.9% single-molecule read accuracy. HiFi reads can accurately detect all types of variants, from single nucleotide to structural variants, with high precision and recall and phase haplotypes, even in hard-to-sequence regions of complex genomes such as onion. Transcriptome sequencing is an efficient approach to generate sequence information from expressed regions of the genome and has been widely used in the Alliums. Several workers use RNA-seq for studying organ development, marker discovery, male sterility, flavonoid biosynthesis, the abiotic stress response in different Allium species (Abdelrahman et al. 2015; Abdelrahman et al. 2019). In context, AlliumTDB (http://alliumtdb.kazusa.or.jp/) contains many useful transcript libraries of root, stem, bulb, and leaves for various Allium species. Similarly, a draft reference transcript for onion, using long-read sequencing technology will help in wholegenome sequencing in Alliums (Sohn et al. 2016). A transcriptome catalogue for homozygous double haploid line ‘CUDH2107’ for understanding the genetic and molecular basis of various traits was developed (Khosa et al. 2016). After the establishment of omics platforms, plant metabolism research has transitioned from the study of individual gene functions to metabolic system research.

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Mass spectrometry (MS) is a major instrument that has high sensitivity and broad metabolite detection capabilities, thus facilitated the detection of hundreds of metabolites having diverse bioactivities in the alliaceous crops (Abdelrahman et al. 2020a, b, 2021a, b). In the future, the individual bio-resource-specific metabolic patterns can be used for molecular breeding of Allium crops while the broad metabolic profiles of Allium bio-resources can be used for integrated omics approaches. The integration of metabolomics and transcriptomics will provide insight into the molecular mechanism of Allium metabolite biosynthesis. Image techniques such as GISH and FISH using fluorescent imaging systems are important approaches for Allium breeding and genetic studies, thus further developments in Allium imaging analysis are needed. Recently, the selection of fusarium basel rot-resistant onion was carried out using digital image analysis to quantify symptom development in the basal plate of dormant bulbs (Mandal and Cramer 2021). Analysis with confocal microscopy identified bright blue-green autofluorescence from Fusarium oxysporum-infected tissue, effectively differentiating diseased from healthy tissue. Visual scoring of the fusarium basel rot symptom was combined by stereo fluorescence microscopic images, captured using a green fluorescence protein dual filter to quantify accurately fusarium basel rot severity in the basal plate tissue (Mandal and Cramer 2021). The new developed method could be used for developing resistant cultivars for onion breeding programs in the near future. Targeted genome-editing technologies, especially clustered regularly interspaced short palindromic repeats (CRISPR)/(CRISPR)-associated protein 9 (Cas9), have great potential to aid in the breeding of crops that can produce high yields under biotic/abiotic stress (Abdelrahman et al. 2018a, b). This is due to their high accuracy and low risk of off-target effects, compared with conventional methods. The use of the CRISPR/Cas9 system is commonly used for targeted mutagenesis in crop plants, including gene knockouts, modifications, and the activation and repression of target genes. However, there are no reports regarding genome editing in onion probably due to the complex genome structure with many repetitive sequences, affecting the efficacy of the CRISPR/Cas9 system. Genomic selection (GS) is being increasingly applied in plant breeding programs to enhance the genetic gain of economically important traits. For example, the GS scheme was proposed to prevent inbreeding depression in onions by avoiding the co-selection of closely related plants and combining the shortening of generation time (Sekine and Yabe 2020). Ten years of breeding programs to evaluate the efficiency of different selection schemes in onion, including general phenotypic selection, self-crossing phenotypic selection, general genomic selection, and inbreeding avoiding genomic selection were compared (Sekine and Yabe 2020). General GS with shortening of generation time yielded the highest genetic gains among the selection schemes, however, inbreeding depression increased rapidly in later years. The proposed GS combining shortening of generation time with updating of the prediction model was superior to the others in later years, as it yielded relatively high genetic gain while maintaining significantly low levels of inbreeding. These results suggested that GS can be beneficial in onion breeding, and an optimal scheme should be selected depending on the selection period.

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Conclusion

In conclusion, the study of metabolome and cytoplasmic genomics of Allium holds significant promise in advancing our understanding of this plant genus. By analyzing the metabolites present in the cytoplasm and investigating the genetic information within the organelles, researchers can gain valuable insights into the biochemical pathways and genetic mechanisms that underlie various traits and processes in Allium species. This knowledge could have broad implications for agriculture, medicine, and biotechnology, potentially leading to improved crop yields, novel pharmaceutical compounds, and more sustainable farming practices. However, further research and collaboration are needed to fully unravel the complex interplay between metabolome and cytoplasmic genomics in Allium and unlock its full potential for practical applications.

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Eggplant (Solanum melongena L.) Nutritional and Health Promoting Phytochemicals Partha Saha, Jugpreet Singh, N. Bhanushree, S. M. Harisha, Bhoopal Singh Tomar, and Bala Rathinasabapathi

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Eggplant as a Source of Food, Nutrition, and Health Promoting Compounds . . . . . . . . . . . 3 Major Bioactive Nutraceutical Compounds Present in Eggplant . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Polyphenolics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Anthocyanins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Glycoalkaloids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Metabolomics to Identify Novel Eggplant Phenotypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Eggplant Genomes and Resequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Eggplant is one of the most important Solanaceous vegetable crops which has been cultivated in different continents of the world. The greatest diversity of landraces and cultivars is found in India, China, and several countries in the Southeast Asian region. Eggplant has various culinary and medicinal uses and a great phytochemical diversity defines these uses. Phenolic compounds in eggplant are excellent antioxidants. While numerous studies on eggplant anthocyanins showed their value as antioxidative and radical-scavenging compounds, more studies on potential medicinal properties are needed. Multiple studies on the identification and mapping of genes/QTLs for the contents of chlorogenic acid, solasonine, and solamargine indicate the possibility of breeding lines P. Saha · N. Bhanushree · S. M. Harisha · B. S. Tomar Division of Vegetable Science, ICAR–Indian Agricultural Research Institute, New Delhi, India e-mail: [email protected] J. Singh LeafWorks Inc., Sebastopol, CA, USA B. Rathinasabapathi (*) Horticultural Sciences Department, University of Florida, Gainesville, FL, USA e-mail: brath@ufl.edu © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_53

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specifically improved for these phytochemicals. Metabolomics, where highthroughput identification and quantification of metabolites are done using mass spectral methods, are increasingly applied to study crop plants. Eggplant metabolites have been profiled and attempts have been made to link metabolite profiles to fruit morphology and nutrition, drought stress, nutrient use efficiency, response to pathogens, and other desirable traits. This crop has emerged as a model system for improving health benefiting traits with additional yield components. Different nuclear genomes of the eggplant have been sequenced within the last decade. With the availability of high-quality chromosome scale genomes, it is now feasible to characterize the genomic diversity and evolutionary footprints of eggplant. The information of genome sequencing is very useful to assist breeding programs to develop new varieties via marker-based selection. In this chapter we have discussed the importance of eggplants, bioactive compounds present and their role, biosynthetic pathways and progress in genome sequencing and metabolomics. We have suggested effective strategies to improve the quality of eggplant cultivars of the future. Keywords

Anthocyanins · Chlorogenic acid · Crop breeding · Fruit quality · Nasunin · Solanum alkaloids · Solanum melongena

1

Introduction

Eggplant (Solanum melongena L.) is an important vegetable crop widely grown in many parts of the world for its immature fruit. More than 90% of production is in Asia and top producing countries are China, India, Egypt, Turkey, and Iran (Solberg et al. 2022). Eggplant and its wild relatives are grouped in the Leptostemonum clade of the Solanaceae (Weese and Bohs 2010; Särkinen et al. 2013) along with “spiny” Solanums. This crop is known as eggplant (US, Canada, Australia), brinjal (Indian subcontinent, Singapore, Malaysia, South Africa), aubergine (UK, Ireland), and Guinea squash (Southern US). The fruit of the eggplant contains numerous edible soft seeds that are bitter because of their alkaloid content. It is a rich source of vitamins, minerals, fibers, and other phytochemicals (Chlorogenic acid) which have medicinal properties (Saha et al. 2016). Solanum melongena is native of “Indo-Chinese Center” (Taher et al. 2017) and is cultivated worldwide primarily in the tropical and subtropical regions and in temperate zone especially in the summer months or in greenhouses as off-season crop. Eggplant is known to have originated from the progenitor species Solanum incanum and Solanum insanum which have a wide distribution in India, Africa, the Middle East, and Southeast Asia (Aubriot et al. 2018; Ranil et al. 2017). A recent compilation indicated more than 19,000 accessions in various seed banks (Solberg et al. 2022). Figure 1 illustrates the species dispersal from Africa to Asia during eggplant domestication (Weese and Bohs 2010). Some of the variations in fruit shape, size, and color are shown in Fig. 2.

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G

E F

A B

Fig. 1 Biogeography of Solanum melongena and related species. (Diagram adapted from Weese and Bohs (2010) and Aubriot et al. (2018)). S. incanum types are naturally present in regions marked A–D in eastern Africa and the Middle East and S. melongena types are distributed in regions marked E–H (India, China, Thailand, Korea, Vietnam, and Japan). Arrows indicate suggested directions of migration according to Weese and Bohs (2010) and Aubriot et al. (2018) Fig. 2 Some of the variations in relative fruit size, shape, and color of immature fruit of eggplant. (Photo by B. Rathinasabapathi)

The greatest diversity of landraces and cultivars is found mainly in India, China, and countries in the Southeast Asian region. The secondary centers for this crop are in the Middle East and the Mediterranean region (Frary et al. 2007). Eggplant has been thought to be domesticated several times in Asia from Solanum incanum, in which human selection played a significant role. The primary traits involved in domestication process are selection for increased fruit size, decrease in prickliness, and fruit bitterness as compared to the wild progenitor species (Daunay and Hazra 2012; Meyer et al. 2012). The wild relatives S. incanum and another species recognized as S. insanum or S. melongena insanum have the phenotype of large spiny leaves and small, hard-textured green fruit. Species of Solanum that are used as

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major or minor vegetables are shown in Table 1. Species of Solanum that are useful as sources of disease and pest resistance in eggplant breeding are shown in Table 2. A taxonomic key to the species of the eggplant clade is available in Knapp et al. (2013). Table 1 Solanum species used as vegetables, their common names, distribution, and edible parts Species S. aethiopicum

Common name Molk tomato Golden apple

Distribution Tropical Africa

S. americanum

Glossy nightshade

Central Eastern USA

S. gilo S. hirsutissimum S. incanum

Gilo, Jilo Lulita Sodom apple

Western Africa, Brazil Central and South America West Africa, India

S. indicum S. integrifolium

Indian nightshade Scarlet eggplant

S. lycopersicum S. macrocarpon

Tomato African eggplant

S. melanocerasum

S. muricatum

Garden Huckleberry, Wonderberry, Black nightshade Eggplant, brinjal, aubergine Pepino, melon pear

S. quitoense

Naranjillo, lulo

S. sessiliflorum S. torvum

Cocona Turkey berry

Southeast Asia Warm temperate, Subtropical Asia American Tropics Subtropical and tropical regions, West and Central Africa Warm temperate regions, Subtropical America and West Africa Warm temperate, Subtropical and tropical regions Subtropical and tropical America Subtropical and tropical America Northern South America South American tropics

S. tuberosum

Potato

Central and South America

S. melongena

Edible part(s) Leaves and immature fruit Leaves and green fruit Fruit, shoot Mature fruit Immature fruit Fruit, leaves Fruit Fruit Fruit, leaves

Mature fruit

Immature fruit Mature fruit Mature fruit Mature fruit Immature fruit Tuber

Table 2 Wild Solanum species as sources of resistance to pests and diseases (Swarup 1995) Species S. melongena var. insanum, S. integrifolium S. incanum, S. indicum, S. integrifolium S. indicum, S. aculeatissimum S. xanthocarpum, S. nigrum, S. sisymbrifolium S. torvum, S. mammosum, S. khasianum S. sisymbrifolium, S. aethiopicum S. viarum, S. incanum, S. gilo

Source of resistance Bacterial wilt Fusarium wilt Verticillium wilt Fruit rot Spotted beetle Root knot nematode Little leaf

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Eggplant as a Source of Food, Nutrition, and Health Promoting Compounds

Eggplant has various culinary and medicinal uses. Here, we summarize a variety of culinary uses for immature fruit of eggplant from different areas of the world. Eggplant is mainly used to prepare Baingan ka Bhartha or Gojju, stir fries and soups in India, Yu Xiang Qiezi and Di San Xian stir fries in the Chinese cuisine, nasu dengaku of Japan, ratatouille of the French cuisine, moussaka and melitzanosalata of the Greek, baba ghanoush of the Middle East, nigvzianibadrijani in the Caucasus and the melanzaneallaparmigiana of the Italian cuisine. Two species namely, S. aethiopicum and S. macrocarpon are commonly grown for the consumption of cooked leaves in Africa. Eggplant is a “low-calorie vegetable” due to its low energy density. But the presence of vitamins, minerals, proteins, fiber, and phenolic compounds in the fruit proves its beneficial value to human health (Frary et al. 2007). The nutritive value of eggplant is presented in Table 3. A comparative study on tomato, pepper, and eggplant showed that eggplant had greater levels of mineral nutrients potassium, magnesium, and copper, total sugars, and the antioxidant chlorogenic acid compared to pepper and tomato (Rosa-Martínez et al. 2021). Besides, as a source of food, eggplant is used in traditional medicine to treat asthma, bronchitis, cholera and dysuria, skin-related problems, and in lowering blood cholesterol levels (Rotino et al. 2014; Meyer et al. 2014). Studies in rats suggested that eggplant could reduce the absorption of dietary cholesterol (Kritchevsky et al. 1975). However, small scale clinical trials on the potential of dietary eggplants in reducing serum lipid levels have shown either no or transitory effects only (Guimaraes et al. 2000; Praca et al. 2004). Donmez et al. (2020) showed hemorrhoid healing activity for the extracts of eggplant calyx in an animal model. Additional controlled clinical studies are needed to test efficacy and modes of action. As other Solanaceous crops tomato, potato, and pepper, eggplant also contains glycoalkaloids such as solasonine and solamargine, which are known to have beneficial biological and anticancer properties (Cham 2012). However, these alkaloids at excess levels exert potential toxic effects (Chami et al. 2003) and impart bitterness to fruits making them unpalatable (Frary et al. 2007). But the cultivated varieties of S. melongena have levels of alkaloids which are acceptable for human consumption, unless the plants have been subjected to stress conditions. Figure 3 depicts structures of major health promoting phytochemicals in eggplant. Several studies have documented that the Solanum alkaloid solamargine induces apoptosis of cancer cells. Via multiple signaling pathways, solamargine sensitizes the cells to certain cancer drugs, and hence may have promising applications for cancer therapy (Kalalinia and Karimi-Sani 2017). Solamargine has also been reported to have anti-inflammatory effects against UVB-induced skin hyperpigmentation (Zhao et al. 2022). Phenolic compounds in eggplant are excellent antioxidants and there is high genetic variation for this trait (Nandi et al. 2021; Plazas et al. 2013a, b). In addition to their antioxidant potential eggplant extracts were shown to inhibit alphaglucosidase and angiotensin converting enzyme, target enzymes for therapies for

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Table 3 Nutritional profile of raw eggplant (per 100 g fresh weight). Values from the USDA “Food Data Central” (Haytowitz et al. 2019) are compared to mean and standard error values from a study that examined ten eggplant varieties grown under same horticultural conditions (Rosa-Martínez et al. 2021) Composition Proximate Water (g) Energy (kcal) Protein (g) Total lipid (g) Carbohydrate, by difference (g) Total sugars (g) Total dietary fiber (g) Minerals Calcium (mg) Iron (mg) Magnesium (mg) Phosphorus (mg) Potassium (mg) Sodium (mg) Zinc (mg) Vitamins Vitamin C (mg) Niacin (mg) Pantothenic acid (mg) Folate, total (μg) β-Carotene (μg) Vitamin A (IU) Vitamin E (α-tocopherol) (mg) Vitamin K (phylloquinone) (μg) Lipids Fatty acids, total saturated (g) Fatty acids, total monounsaturated (g) Fatty acids, total polyunsaturated (g) Cholesterol (mg)

Raw

Mean and standard error for ten varieties

92.3 25 0.98 0.18 5.88 3.53 3

90.07 + 27.2 NA 1.49
0.37 NA NA 3.19
0.83 NA

9 0.23 14 24 229 2 0.16

10.29
2.3 0.35
0.11 17.93
4.66 38.89
7.79 326.64
56.71 4.10
1.52 0.30
0.08

2.2 0.649 0.281 22 14 23 0.3 3.5

5
1.0 NA NA NA 48
52 NA NA NA

0.034 0.016 0.076 0.000

NA NA NA NA

type 2 diabetes and hypertension respectively (Kwon et al. 2008). Among the wild accessions, Solanum insanum has significantly higher phenolic content than Solanum xanthocarpum and Solanum khasianum. The wild accessions are rich sources of total phenolics (Kaur et al. 2014; Kaushik et al. 2020; Nandi et al. 2021). Early research in eggplant breeding focused on the improvement of horticultural characteristics such as fruit yield, fruit size, color, and shape (Kashyap et al. 2003; Frary et al. 2007), low prickliness, and adaptation to climatic conditions (Daunay et al. 2001). A few studies focused on the resistance to biotic stresses (Rotino et al. 2014). Within the last few years, however, there is an increased research interest on

Eggplant (Solanum melongena L.) Nutritional and Health Promoting Phytochemicals Chlorogeic acid

L-Ascorbic Acid

Lutein

Nasunin

α-Solasonine

α-Solamargine

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Fig. 3 Health promoting phytochemicals in eggplant. Representative compounds from the organic acids, phenolic compounds, carotenoids, anthocyanins and glycoalkaloids are shown. Note that other forms of these compounds and related compounds with bioactivity are also known but not depicted. Structures are from PubChem database

organoleptic and nutritional properties, bioactive metabolites, and postharvest traits of eggplant fruit. A few of these studies also highlight genetic and genomic perspectives (Prohens et al. 2007, 2013; Gajewski et al. 2009; Plazas et al. 2013a, b; Zhang et al. 2016; Docimo et al. 2016b; Scalzo et al. 2016; Mangino et al. 2022). Eggplant is a nutritionally valuable vegetable as a good a source of vitamins and minerals (Grubben et al. 1977, Table 3). It also contains several classes of healthpromoting metabolites including anthocyanins (delphinidin glycosides) and chlorogenic acid (Stommel and Whitaker 2003; Mennella et al. 2010) with nutraceutical and antioxidant properties (Cao et al. 1996; Kwon et al. 2008; Akanitapichat et al. 2010). An eggplant variety ‘Pusa Hara Baingan 1’ developed from ICAR-IARI, New Delhi has fruit with high antioxidant activity (3.41 CUPRAC μ mol trolox /g, 3.07 FRAP μ mol trolox /g) (Kumar et al. 2020). The bioactive compounds and health promoting properties of eggplant is presented in Table 4. Eggplant also contains certain antinutritional compounds, like toxic saponins and steroidal glycoalkaloids (SGA), which form the basis for the bitter taste of the flesh (Aubert et al. 1989a, b; Sánchez-Mata et al. 2010). The accumulation of these metabolites in the fruit and the total amount of all these metabolites appear to be influenced by genetic and developmental factors (Mennella et al. 2012). There is genetic variability for phytochemical accumulation traits among different eggplant varieties and environmental stress affects these traits (Plazas et al. 2013a, b). Multiple studies focused on the genetic basis for fruit quality traits in eggplant. Quantitative trait loci (QTLs) affecting the content of health promoting or

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Table 4 Reports of bioactive compounds and health promoting properties of eggplant Compound Chlorogenic acid

Nasunin

Potential health benefits Antioxidant, anti-inflammatory, cardioprotective, antidiabetic, antimicrobial, and neuroprotective Antioxidant activity, neuroprotective, cardiovascular protection, anticancer, anti-diabetic, anti-inflammatory

Solasodine

Anticancer, anti-inflammatory

Fiber content Polysaccharides

Digestion, anticancer against colon cancer Immuno modulation, antitumor effects, and antioxidant Reduction of oxidative stress and vascular inflammation

Delphinidin

Kaempferol Myricetin Quercetin

Luteolin Isorhamnetin

Lutein

Zeaxanthin β-Cryptoxanthin Tannins

Hydroxycinnamic acids

Antioxidant defense and a reduction of the risk of chronic diseases, especially cancer Antioxidant defense, anti-carcinogenic, antimicrobial, and antiplatelet Antioxidant defense, cytoprotective effects, antimicrobial, anti-inflammatory, and muscle-relaxing properties Antioxidant defense, anti-inflammatory, properties Antioxidant and antitumor activity on human cancer cells, prevention of endothelial cell injuries caused by oxidized low-density lipoprotein Non-nutritive carotenoid, antioxidant in the retina, protecting the eye from inflammatory damage by light Anti-inflammatory effects via reducing oxidative damage of the retina Vitamin A precursor, may help reduce free radical damage to biomolecules, anticancer Enhance glucose uptake and inhibit adipogenesis. Inhibition of LDL-cholesterol oxidation Free radical-scavenging properties, protection from side effects of chemotherapy

References Plazas et al. (2013a)

Casati et al. (2016), Matsubara et al. (2005), Lin and Li (2017), and Wang and Stoner (2008) Shen et al. (2017), da Costa et al. (2015), and Friedman (2006) Fraikue (2016) Mei et al. (2017) Watson and Schönlau (2015) and Harisha et al. (2023) Chen and Chen (2013) Li and Ding (2012) Jan et al. (2010)

Jiang et al. (2013) Jaramillo et al. (2010)

van Lent et al. (2016)

Manikandan et al. (2016) Lorenzo et al. (2009) Kumari and Jain (2012) El-Seedi et al. (2012)

antinutritional compounds are known. These studies have also identified QTLs for various other fruit quality traits (Shetty et al. 2011; Gramazio et al. 2014). QTLs associated to fruit content of sugars, organic acids, dry matter and total soluble solids, chlorogenic acid, the steroidal glycoalkaloid solamargine, pigments delphinidin-3-

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rutinoside (D3R), and delphinidin-3-(p-coumaroylrutinoside)-5-glucoside (nasunin) are useful resources to breed cultivars improved for specific phytochemical profiles. Very recently, the HPLC analysis identified cyanidin-3-O-glucoside, delphinidin-3-Oglucoside and delphinidin-3-rutinoside anthocyanins in brinjal lines and the highest delphinidin-3-O-glucoside was found in purple fruited variety Pusa Upkar, delphinidin 3-rutinoside in purple fruited line BR-40-7 (Harisha et al. 2023).

3

Major Bioactive Nutraceutical Compounds Present in Eggplant

3.1

Polyphenolics

Among all the studied Solanaceous crops, eggplant is a rich source of total phenolic acids, which are nutritionally important bioactive constituents (Helmja et al. 2007). The most prevalent group of phenolic compounds present in eggplant are the conjugates of hydroxycinnamic acid (HCA) and their concentration ranges from 4240 to 9610 mg/kg. HCA conjugates are synthesized by converting phenylalanine to cinnamic acid by the enzyme phenylalanine ammonia-lyase (PAL). Among HCA conjugates, chlorogenic acid (5-O-caffeoyl-quinic acid; CGA) an ester of HCA, contributes to 70% to over 95% of the total phenolic content (Whitaker and Stommel 2003; Plazas et al. 2013a; Niño-Medina et al. 2017). Quinic acid has four stereocenters namely carbons 1, 3, 4, and 5, and each one of these positions can be substituted by caffeic acid giving rise to 15 possible combinations. While CGA is the major hydroxycinnamic acid conjugate in eggplant, its 3-O, 4-O, 5-O-cis isomers, and 3,5and 4,5-dicaffeoylquinic acid isomers have also been identified (Whitaker and Stommel 2003). Chemistry, synthesis, analytical challenges and bioactivity of caffeoylquinic acids in plants have recently been reviewed by Magania et al. (2021). Growing interest in breeding for high CGA is mainly due to its beneficial properties including antioxidant (Chen et al. 2009; Zhao et al. 2012), anti-inflammatory (Morishita and Ohnishi 2001; dos Santos et al. 2006; Jin et al. 2006; Sheu et al. 2009; Sato et al. 2011), anticarcinogenic, antimicrobial (Almeida et al. 2006), antiobesity (Cho et al. 2010), antipyretic, neuro-protective and analgesic properties (Cho et al. 2010; Plazas et al. 2013a; dos Santos et al. 2006). As a source, eggplant contributes substantially to CGA intake and there exists a significant variability among eggplant lines studied as compared to other sources of fruits and vegetables (Chumyam et al. 2013; Kaur et al. 2014; Prohens et al. 2013; Okmen et al. 2009; Chioti et al. 2022). The biochemical pathway and range of CGA content in different eggplant lines in comparison to other sources are shown in Fig. 4 and Table 5, respectively. Fruit CGA content of eggplant fruit is influenced by both genetics and environmental factors including the fruit developmental stage, season, and storage conditions (Plazas et al. 2013a). The crop grown in the summer season showed a trend of decrease phenolic compounds compared to spring-grown crop suggesting negative influence of high temperatures on phenolic content. This information will help in monitoring the suitable time of harvest (García-Salas et al. 2014). In some of the

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4CL p-Coumaryl-CoA Shikimic acid

HCT

HCT p-Coumaryl-Shikimic acid

p-Coumaryl-quinic acid

C3’H

C3’H

Caffeoyal Shikimic acid

3-O-Caffeoyal quinate (Chlorogenic acid)

HQT

Shikimic acid Caffeoyal-CoA Quinic acid

Fig. 4 Biosynthetic pathway of chlorogenic acid in eggplant. Enzyme catalyzed steps are shown with an arrow and the names of the enzymes are shown in three-letter abbreviations of enzyme names listed in Table. (Adapted from Plazas et al. (2013a)) Table 5 Chlorogenic acid contents of eggplant compared with other major vegetables (as summarized by Plazas et al. 2013a) Plant source Eggplant

Carrot Tomato Pepper Artichoke

CGA (g kg1 dw) 4.9–21.6 4.2–9.5 1.5–2.2 5.0–8.1 2.6–6.7 11.2–24.0 1.4–8.4 14.1–28.0 0.3–18.8 0.2–0.4 0.7–0.9 1.1–1.8

References Stommel and Whitaker (2003) Whitaker and Stommel (2003) Gajewski et al. (2009) Singh et al. (2009) Luthria et al. (2010) Mennella et al. (2010) Luthria et al. (2010) Mennella et al. (2012) Sun et al. (2009) Hallmann (2012) Hallmann and Rembiałkowska (2012) Lutz et al. (2011)

studies it was also noticed that organically grown eggplants had greater levels of total phenolics than conventionally produced eggplants (Raigon et al. 2010), but the contrary report also exists in which conventional and organic cultivation of the American variety ‘Blackbell’ had comparable levels of phenolic contents (Luthria et al. 2010). As compared to other derivatives of phenolic compounds CGA is quite stable at high temperatures, therefore boiling eggplant boosts its bioavailability when compared to uncooked eggplant (Lo Scalzo et al. 2010).

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3.1.1 Genetic Sources of Phenolic Compounds Generally, wild relatives had higher content of total phenolics with broader range of variation in them as compared to cultivated eggplant (Kaushik et al. 2017). The results of screening of the eggplant germplasm for the sources of high CGA content indicate that wild species S. incanum can contribute significantly for improving the CGA content in eggplant. Other species, like S. sodomaeum L. (S. linneanum Hepper & Jaeger) also showed a higher CGA content than that of S. melongena (Mennella et al. 2010). Therefore, utilization of wild relatives, such as S. incanum, in breeding of eggplant varieties will be of great interest. Along with the wild species the landraces also represent another useful source of variation. Introgressive breeding and selection for desired profiles of phenolic compounds along with other horticulturally relevant traits should be useful in this regard. 3.1.2 Breeding Strategies for Increased CGA The strategies proposed for breeding of high CGA content exploit naturally available variation to selection among accessions, selection from intraspecific variation, development of hybrids and inbred lines or introgression of the high CGA trait from wild species into cultivated background. It is also necessary to have good horticultural and commercial characteristics along with the improved concentrations of CGA in new cultivars (Daunay 2008). Molecular markers for traits associated with high CGA content will be useful for developing new and improved cultivars in a resource-efficient manner. In case of conventional breeding methods, utilization of intraspecific variation and selection among the accessions or varieties resulted in the identification of lines with increased content of CGA (Stommel and Whitaker 2003; Whitaker and Stommel 2003; Hanson et al. 2006; Prohens et al. 2007; Raigón et al. 2008; Okmen et al. 2009; Mennella et al. 2012). An alternative and very successful method of breeding for high CGA is to develop hybrids along with commercial traits by using the lines having parents with high CGA content. The developed hybrids can be further used to select and develop inbred lines with higher content in CGA as suggested by the researchers (Prohens et al. 2007: Raigón et al. 2008). Prohens et al. (2013) improved the phenolic acid content in commercial eggplant lines by developing interspecific S. melongena and S. incanum backcross generation (BC1) progenies to introgress the alleles of S. incanum involved in CGA biosynthesis in the genetic background of S. melongena. S. incanum was found fully fertile with S. melongena. The individuals having high content in CGA in the first backcross generation was found and selected. The gene action studies from the population suggested the presence of additive genetic effects explaining CGA variation. Therefore, it is necessary to have the alleles of S. incanum in homozygous state to obtain lines with stable and high levels of CGA in the fruit. The identification and mapping of genes involved in the CGA synthesis pathway was carried out by Gramazio et al. (2014). The authors were successful in amplifying the candidate genes encoding enzymes of CGA synthetic pathway and the identified genomic regions were syntenic with the tomato genome (Wu et al. 2009). Table 6 lists the candidate genes and their linkage group locations in the eggplant genome as reported by Gramazio et al. (2014).

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Table 6 Candidate genes encoding enzymes of chlorogenic acid (CGA) biosynthesis and their chromosomal locations S. No 1 2 3 4 5 6

Candidate genes coding for biosynthetic enzymes PAL (phenylalanine ammonia-lyase) C4H (cinnamic acid 4-hydroxylase), 4CL (4-coumaroyl: CoA-ligase) C3H (p-coumarate 3-hydroxylase), HQT (hydroxycinnamoyl CoA quinate hydroxycinnamoyltransferase), HCT (hydroxycinnamoyl-coAshikimate/quinatehydroxycinnamoyltransferase)

Linkage group 9 6 3 1 7 3

Gene transfer technologies are well developed in eggplant and have been used to improve several traits (Acciarri et al. 2000; Donzella et al. 2000; Pal et al. 2009). Kaushik et al. (2020) obtained transgenic plants overexpressing the central enzyme hydroxycinnamoyl CoA-quinate transferase (SmHQT), which catalyzes the reaction to the chlorogenic acid synthesis. Using agro infiltration technique the gene construct having SmHQT gene was transformed into the eggplant and was further validated by HPLC analysis of transgenic tissue for CGA. The results of the study confirmed the increase in CGA content by twofold in the transformed plants. When the general public’s acceptance of genetically modified crops (Raybould and Poppy 2012) improve and national policies toward genetically modified crops become favorable, nutritionally enhanced transgenic eggplant cultivars will become more widely useful.

3.1.3 Effect of CGA Content on Fruit Flesh Browning When an eggplant fruit is cut, the phenolic compound CGA present in eggplant fruits acts as the substrate for polyphenol oxidases which catalyze the oxidation of phenols to quinones. Quinones reacting non-enzymatically with O2 and other molecules cause tissue browning (Ramírez and Virador 2002; Prohens et al. 2007; Plazas et al. 2013b; Mishra et al. 2013; Prohens et al. 2013; Docimo et al. 2016a). The polyphenol oxidase reaction is a major drawback for increasing the CGA content in fruit (Prohens et al. 2007, 2013; Plazas et al. 2013b; Mishra et al. 2013) because browning reduces the visual quality of the fruit both for the fresh market and for the processing industry (Mishra et al. 2013). In order to reduce this potential side effect, it has been emphasized for indirect selection for lower content of total phenolic compounds in fruit flesh. Also, variation for PPO activity was observed between the different groups of the germplasm. The primary gene pool species consisting of cultivated eggplant and hybrids display significantly lower PPO specific activities than those of the wild species of the secondary and tertiary gene pools (Kaushik et al. 2017). Eggplant’s wild relatives had higher PPO activity than the cultivated species (Shetty et al. 2011), suggesting enhanced defense in the wild species. In several crops, PPO activity was shown to have a positive correlation with browning traits, which indicates that by selecting for low PPO activity, it is possible to develop materials with reduced browning (Di Guardo et al. 2013; Nayak et al. 2015;

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Urbany et al. 2011). In eggplant, the correlation between fruit flesh phenolic concentration, and particularly CGA content, and fruit flesh browning has been found to be moderate (Prohens et al. 2007; Plazas et al. 2013a; Docimo et al. 2016a). Other physiological or cell anatomical factors related to flesh browning were suggested (Docimo et al. 2016a; Mishra et al. 2013; Prohens et al. 2007). Prohens et al. (2007) found a moderate relationship (r ¼ 0.389) between the total phenolic content and fruit flesh browning among the cultivated eggplants. This study suggests that there is a possibility to select varieties with high content in phenolics but with low or moderate fruit flesh browning traits. In the later studies by Prohens et al. (2013), fruit flesh browning and total content of hydroxycinnamic conjugates (CGA) has been correlated in interspecific progenies between S. melongena and S. incanum. The genetic and QTL mapping studies carried out by Gramazio et al. (2014) led to identification and mapping of five genes that encode PPO enzymes in eggplant. All the five genes PPO1, PPO2, PPO3, PPO4, and PPO5 were mapped on the linkage group 8 and were found to be syntenic with the tomato genome (Wu et al. 2009). Presence of all the five genes on same linkage group suggest that PPO genes form a cluster in eggplant genome (Newman et al. 1993; Thipyapong et al. 2007; Tran et al. 2012) and it was also confirmed that the genes involved in CGA synthetic pathway were not linked to the PPO gene cluster.

3.2

Anthocyanins

Anthocyanins are the most abundant class of water-soluble pigments in plants (Mazza 2007). They are mainly responsible for red, purple, and blue colors in fruits, vegetables, flowers, and grains. Derivatives of six anthocyanidins, namely pelargonidin, cyanidin, delphinidin, peonidin, petunidin, and malvidin are widespread in plants (Kong et al. 2003). Among the above mentioned anthocyanidins, delphinidin glycosides [i.e., delphinidin-3-rutinoside (D3R) and delphinidin-3(p-coumaroylrutinoside)-5-glucoside (nasunin)] were found more abundantly in eggplant than any other groups (Toppino et al. 2016). Multiple studies have identified several delphinidin derivatives in eggplant accessions and they have been reviewed by Niño-Medina et al. (2017). Anthocyanins are found to have significant biological functions in plants as insect pollinator attractants, seed dissemination agents and protector of plants against various biotic and abiotic stresses (Chalker-Scott 1999; Ahmed et al. 2014). They were found to have photo protective activity, by absorbing excess visible and UV light and scavenging free radicals thus protecting the photosynthetic apparatus (Guo et al. 2008). Anthocyanin extracts have been shown to have antioxidative and radical-scavenging activities (Astadi et al. 2009), and serve as chemoprotective agents. Anthocyanins also have anti-diabetic characteristics, such as decreasing cholesterol (DeFuria et al. 2009), and increasing insulin secretion (Matsui et al. 2004). There are lines of evidence that a balanced diet rich in anthocyanin-rich foods can significantly reduce the chance of developing various chronic illnesses, including cancer (He and Giusti 2010). While certain health-promoting effects of

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anthocyanins could be due to their high antioxidant activities, specific anthocyanins can modulate signaling pathways in mammalian cells, which could explain some of their specific beneficial effects (Salehi et al. 2020). Light and temperature are the main environmental factors regulating the anthocyanin biosynthetic pathway. In general, high light intensity increases anthocyanin production in many plant species (Maier and Hoecker 2015). In one study addition of UV-A irradiation improved anthocyanin pigmentation of eggplants when grown in a greenhouse with low UV transmittance (Matsumaru et al. 1971). It is well known that low temperature stress induced anthocyanin accumulation in plants of the Solanaceae (Løvdal et al. 2010; Jiang et al. 2016). It has been proposed that the promotion of anthocyanin accumulation by low temperature and light might be through the same or overlapping mechanism (Jaakola 2013; Xu et al. 2015), as induction of anthocyanin biosynthesis at low temperature needed light.

3.2.1 Biosynthetic Pathway of Anthocyanin Malonyl-CoA and 4-Coumaroyl-CoAarethe precursors for the flavonoid biosynthetic pathway in plants. Chalcone synthase (CHS) catalyzes the first committed step. The anthocyanin biosynthesis process is a conserved network which is well studied in crop plants. Figure 5 illustrates the steps leading to delphinidin, the most abundant anthocyanin in the eggplant. 4-Coumaryl-CoA +

3 x Malonyl-CoA CHS

Naringenin chalcone

CHI Naringenin F3H Dihydrokaempferol F3’5’H Dihydromyricetin DHR

Leucodelphinidin ANS Delphinidin UGT

Delphinidin 3-rutinoside 5-glycoside

Delphinidin 3-glycoside

Fig. 5 Key steps in the biosynthesis of anthocyanin nasunin (delphinidin 3-rutinoside-5-glucoside) based on KEGG pathway database’s anthocyanin biosynthesis. Steps with dotted arrows denote uncharacterized steps, but beginning to be understood (Florio et al. 2021). Enzyme name abbreviations are CHS chalcone synthase, CHI chalcone isomerase, F3H hydroxylase, F30 ,50 H hydroxylase, DHR dihydromyricetin reductase, ANS anthocyanin synthase, UGT glycosyltransferase

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The early biosynthetic genes (EBGs) are known to involve in genetic regulation of anthocyanin biosynthesis. The EBGs namely – CHS, CHI, and F3H are the common flavonoid biosynthetic pathway genes which are involved in the synthesis of all flavonoids and late biosynthetic genes (LBGs) namely – F30 H, F30 50 H, DFR, ANS, and UFGT are required for the biosynthesis of specific classes of flavonoids, including anthocyanins. In eggplant, EBGs (SmCHS, SmCHI, and SmF3H) were reported to respond to low temperature and light earlier than LBGs (SmF30 5H, SmDFR, and SmANS) (Jiang et al. 2016). Positive correlations between expression levels of LBGs and anthocyanin content have been recorded in many Solanaceous vegetables (Borovsky et al. 2004; André et al. 2009; Povero et al. 2011; Aza-Gonzalez et al. 2013). MYB-bHLH-WD40 (MBW) complex regulates the structural genes of the anthocyanin biosynthetic pathway. This complex consists of MYB, basic helix-loop-helix (bHLH) and WD40 repeat family proteins. A study combining transcriptomic and proteomic analyses on light-induced anthocyanin biosynthesis in eggplant (Li et al. 2017) identified multiple genes and gene products critical in the accumulation of anthocyanins. It should be noted that although much is known about the pathway, phytochemistry of various forms of delphinidin derivatives in eggplant and the enzymatic steps leading to them are poorly known.

3.2.2 Breeding for Anthocyanin Content in Eggplant In recent days, consumers prefer anthocyanin-rich food products, and such products are marketed for their health promoting potentials (Pojer et al. 2013). The correlation study between the antioxidant activity and total anthocyanin concentration in different eggplant types was carried out by Nisha et al. (2009). The extracts from small sized purple-color fruit showed greater antioxidant activities with maximum concentration of anthocyanin (0.756 mg/100 g) than that of other samples, such as long green (0.0475 mg/100 g), purple colored moderate size (0.525 mg/100 g) and purple colored big size (0.553 mg/100 g). Similar study was carried out by Dhruve et al. (2014) to screen the available eggplant genotypes and to quantify the amount of anthocyanin present. In those studies, AB-07-02 was found to have maximum anthocyanin content in peel of about 474.85 mg/100 g and in the genotypes GBL-1 and GP-White anthocyanin content was not detected. Screening of 26 different colored eggplant genotypes by Koley et al. (2019) reported that the total anthocyanins (in monomeric form) in the purple genotype varied from 27.63 to 359.28 μg C3G/100 g FW, whereas in green and white-colored genotypes anthocyanin was not detected. It is important to know the inheritance pattern and nature of gene action for selection of breeding methods to improve a particular trait. A study was conducted to decipher the inheritance pattern for anthocyanin using the F2 and backcross population from a cross of ‘Pusa Safed Baingan 1’ and ‘Pusa Uttam’ implying dominant epistasis (Bhanushree et al. 2019). Efforts have been made to develop purple fruited varieties in India. Few dark purple fruited varity Pusa Oishiki, Pusa Vaibhav, Pusa Unnat (F1) rich in anthocyanin were developed very recently (Saha et al. 2021, 2022, 2023). Barchi et al. (2012) identified QTLs determining anthocyanin

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pigmentation in different plant parts of eggplant by conducting the experiment in two different locations. This study looked for marker associations to the following phenotypes: adaxial leaf lamina anthocyanin (adlan), stem anthocyanin (stean), abaxial leaf lamina anthocyanin (ablan), calyx anthocyanin (calan), corolla color (corcol), leaf venation anthocyanin (lvean), and fruit peduncle anthocyanin (pedan). The list of QTLs detected is shown in Table 7. This study revealed that QTLs located in five different chromosomes control anthocyanin accumulation in this population. Later, QTL studies by Toppino et al. (2016) identified the QTLs affecting fruit color traits and nasunin. Two QTLs for fruit color traits were mapped on chromosome 5, explaining 56.3% and 69.9% of the phenotypic variance in two different locations respectively. One QTL was detected on the same chromosome (chromosome number 5) explaining 28% and 28.4% of the variance in two different locations. In a different study eggplant was genetically engineered by introducing SmMYB1 gene encoding a R2R3 MYB transcription factor involved in regulating anthocyanin biosynthesis in the peel of eggplant into a non-anthocyanin-accumulating cultivar (Solanum aethiopicum group Gilo) via Agrobacterium-mediated transformation (Zhang et al. 2016). The transgenic plants had high concentrations of anthocyanin

Table 7 QTLs detected in the mapping population by Barchi et al. (2012), their chromosomal location (Chrom), log of odds ratio score (LOD) for detection of the QTL, percent contribution to phenotypic variance (PVE), and additive (A) and dominant variance (B) contributions Trait code Adlan Stean Ablan

Calan

Corcol Lvean Pedan

QTL adlanE06.M adlanE10.M steanE05.ML steanE10.ML ablanE06.ML ablanE10a.ML ablanE10b.ML ablanE11.ML calanE05.ML calanE06.ML calanE08.ML calanE10.ML corcolE05.ML lveanE05.ML lveanE10.ML pedanE01.ML pedanE05.ML pedanE10a.ML pedanE10b.ML pedanE12a.ML pedanE12b.ML

Chrom 6 10 5 10 6 10 10 11 5 6 8 10 5 5 10 1 5 10 10 12 12

Position (cM) 151.48 69.39 69.73 68.92 151.482 68.92 0 83.275 75.30 151.48 27.53 68.92 75.30 75.30 69.13 118.30 59.81 69.13 0.00 106.73 30.23

LOD 7.93 36.98 14.59 36.60 8.21 29.89 6.59 4.51 12.39 4.48 5.11 47.53 34.08 13.71 58.94 4.69 5.95 73.20 6.33 7.12 5.73

PVE 8.00 60.60 14.80 53.60 8.70 45.20 6.80 4.50 8.80 2.70 3.40 61.00 63.70 7.80 73.90 1.50 1.90 76.40 2.00 2.30 1.80

A 20.282 20.948 20.251 20.487 20.209 20.642 20.255 20.177 20.213 20.094 20.112 20.553 21.545 20.274 20.833 0.067 20.110 21.029 20.191 20.190 0.181

D 0.287 0.060 0.234 0.252 0.259 20.004 20.101 0.227 0.147 0.117 0.130 0.290 1.490 0.189 0.398 0.191 0.227 0.551 20.039 0.020 0.032

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in leaves, petals, stamens, and fruit peels under normal growth conditions, especially in fruit flesh. Later studies of qRT-PCR analysis revealed that transformed plants showed significantly high up-regulation of anthocyanin structural genes than the non-transformed plants. Additionally, they had a greater tolerance to freezing stress and better recovery under rewarming conditions, suggesting that anthocyanin synthetic and regulatory circuits are potential targets to improve eggplants for stress tolerance. Recently, the proof for R2R3-MYB transcription factor SmMYB75 promotes anthocyanin biosynthesis in eggplant was supported by the study of Shi et al. (2021). Overexpression of SmMYB75 in the eggplant cultivar ‘116’ showed increased accumulation of anthocyanins, which resulted in a change in the color of the calli from green to purple. The Yeast one-hybrid (Y1H) and dual-luciferase (Dual-LUC) assays showed that SmMYB75 could bind to the promoter of SmCHS and activate its expression for anthocyanin synthesis. SmMYB75 was suggested to modulate the anthocyanin’s accumulation by combinatorically interacting with a basic helix-loop-helix (bHLH) factor. A study analyzing a multiparental population identified two MYB113 genes on chromosomes 1 and 10 to be involved in anthocyanin accumulation in the fruit (Mangino et al. 2022).

3.3

Glycoalkaloids

Glycoalkaloids are biologically active secondary metabolites, which are chemically defined by the presence of their nitrogenous steroidal aglycone and glycoside residues located at the C-3 position (Zhao et al. 2020; Al Sinani and Eltayeb 2017). The crops of the Solanaceae family are the warehouse of steroidal glycoalkaloids (SGA) which are present in all tissues of eggplant (Sawai et al. 2014) and are better characterized in tomato and potato (Friedman 2002, 2006; Kozukue et al. 2008). The first discovery of SGA is from the species Solanum nigrum in 1820. The higher concentration of Solanum glycoalkaloids in fruits have a significant impact on the organoleptic properties of flesh by imparting a characteristic bitter taste and off flavor (Aubert et al. 1989a, b; Sánchez-Mata et al. 2010). Eggplant is a source of two main glycoalkaloids namely, water-soluble triglycosides solasonine (SN) and solamargine (SM), which are in general referred to as α-compounds (Trivedi and Pundarikakshudu 2007). The chemical structures of solasonine and solamargine of eggplant are represented in Fig. 3. The glycoalkaloid accumulation is modulated by several environmental factors during plant growth, harvesting, and post-harvest treatment including light exposure, temperature, altitude, soil type, soil moisture, drought, and soil fertility. Wounding increased glycoalkaloid contents (Sinden et al. 1984; Zhao et al. 2020). Solamargine and solasonine are known to play important roles in plant abiotic and defense stress resistance, assisting plant-environment interactions against a variety of pathogens and predators (Zhao et al. 2020; Al Sinani and Eltayeb 2017). They were also found to have allelopathic effects to suppress seedling growth in crop fields (Vaananen 2007). However, depending on the dose, they can also be used as drugs due to their various biological activities with potential therapeutic potentials (Lee et al. 2007;

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Tiossi et al. 2012). But the higher concentration of these glycoalkaloids were known to cause toxic effects on target organisms leading to cell-membrane disruption, acetylcholinesterase inhibition, liver damage, heart damage, teratogenicity, and embryotoxicity (Al Sinani and Eltayeb 2017). Various methods have been employed for analyzing glycoalkaloids in foods and plant materials, of which high performance liquid chromatography (HPLC), high performance thin-layer chromatography (HPTLC), gas chromatography (GC), and mass spectrometric methods and rarely immunoassays are routinely used (Kuronen et al. 1999; Kreft et al. 2000; Dinan et al. 2001; Trivedi and Pundarikakshudu 2007; Vaananen 2007; Eanes et al. 2008).

3.3.1 Biosynthesis Pathway Cholesterol is a key intermediate for biosynthesis of glycoalkaloids which is obtained as intermediate of acetyl-CoA pathway. SGA biosynthesis begins with the cytosolic mevalonate pathway and a multi-step pathway for the production of cycloartenol, cholesterol, and core SGA, culminating in the synthesis and glycosylation of the steroidal alkaloid aglycone (Zhao et al. 2020). The aglycones are glycosylated through the action of a series of glycosyl transferases (Wang et al. 2017) to form the final products α-solasonine and α-solamargine (Wang et al. 2017) (Fig. 6). The biosynthesis is regulated by a group of genes clustered together in Solanum species and the modulation of these genes changes the biosynthesis in the plant (Wang et al. 2017). The site of synthesis of glycoalkaloids has been extensively studied in tomato. The storage of glycoalkaloids occurs in the soluble phase of the cytoplasm and/or in the vacuoles. The alkaloids are not transported throughout the plant system, but they tend to remain confined to the site of synthesis. It is also known that the isopentenyl pyrophosphate (IPP) acts as an intermediate in the biosynthetic pathways of chlorophyll, carotenoid, and glycoalkaloid; therefore, the biosynthesis of each of these three compounds influence that of the others (Zhao et al. 2020). The presence of a gene encoding dioxygenase involved in the Cholesterol CYP 16, 22, 26-tri-OH-Cholesterol CYP

(22S, 25S)-spirosol-5-en-3β-ol Glucose 2 Rhamnose

UGT α-Solamargine

UGT

Galactose Rhamnose Glucose

α-Solasonine

Fig. 6 Suggested biosynthetic pathway for solasonine and solamargine in eggplant. (Adapted from Akiyama et al. (2021)). Enzyme abbreviations are shown in three letters near the arrows: CYP1 cytochrome P450 monooxygenase involved in cholesterol hydroxylation, CYP2 cytochrome P450 monooxygenase involved in oxygenation, UGT uridine diphosphate-dependent glycosyltransferase

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conversion of spirosolane alkaloids to solanidane-type alkaloids in eggplant suggest that leaves of eggplant could contain solanidane alkaloids also but have not been tested for its role (Akiyama et al. 2021).

3.3.2 Breeding for Glycoalkaloid Content Reduction in glycoalkaloid content has been an important breeding objective for crop improvement in eggplant. In certain populations of eggplants studied, the longfruited cultivars contained a higher concentration of reducing sugars, phenolics, and dry matter than round-fruited types. The range of glycoalkaloid contents in the Indian commercial cultivars varied from 0.37 to 4.83 mg/100 g fresh weight, whereas increase in concentration to 20 mg/100 g fresh weight results in bitter taste and off flavor (Dhruve et al. 2014). The range of glycoalkaloid content in the study of Dhruve et al. (2014) varied from 0.128 to 0.191% with the lowest concentration found in the cultivar ‘Doli-5’ and significantly higher concentration in ‘GOB-1’ cultivar. The studies of Sanga et al. (2019) reported the cultivar ‘G-3’ was found to have the highest concentration of solasodine with the value of 28.25 mg/100 g, whereas lowest concentration of solasodine was in the cultivar ‘G-5’ (8.78 mg/100 g). Other studies (Lelario et al. 2019) confirmed the phytochemical diversity for alkaloid content in eggplant varieties and others have shown such variation in different species of Solanum (Amadi et al. 2013; Eze and Kanu 2014; Chinedu et al. 2011). A significant negative association (r ¼ 0.588) was observed between ascorbic acid content and glycoalkaloid content. And glycoalkaloid content had a positive correlation with fruit weight (r ¼ 0.381) and fruit volume (r ¼ 0.399) (Sanga et al. 2019). The identification and mapping of genes/QTLs for the contents of solasonine, and solamargine were carried out by Toppino et al. (2016) using an F2 intraspecific mapping population of 156 individuals (“305E40”  “67/3.”). The QTL analysis revealed the presence of one major QTL, SME06.ML on chromosome number 6 having the LOD value of 5.02 and PVE of 13.9. The genetic transformation studies paved the path to understand the effects of photosynthetic pigment accumulation on glycoalkaloid biosynthesis in eggplant. Since both chlorophyll and carotenoid biosynthesis pathways share intermediate metabolites with glycoalkaloid synthesis and are regulated by light, it was hypothesized that changes in one pathway could affect the others. Therefore, the study was carried out to silence three key genes involved in carotenoid biosynthesis (PDS) and chlorophyll biosynthesis (ChlI and ChlH) using TRV-mediated VIGS to block the biosynthesis of respective metabolites. The transformed plants were quantified for carotenoid and chlorophyll levels using liquid chromatography-mass spectrometry. The results revealed a significant reduction in glycoalkaloid production in transformed plants along with the other metabolites in the silenced lines suggesting the crosstalk of both the SGA and chlorophyll biosynthesis. This finding of Toppino et al. (2016) suggests strategies to reduce the levels of endogenous antinutritional compounds in crops. Later, Barchi et al. (2019) studied the evolution of glycoalkaloid biosynthesis in solanaceous crops. In eggplant most core genes for steroidal glycoalkaloid (SGA) biosynthesis genes form two metabolic gene clusters, on chromosome 7 and chromosome 12, while the one on chromosome

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12, contains genes named GLYCOALKALOID METABOLISM 4 and 12 (GAME4 and GAME12).

4

Metabolomics to Identify Novel Eggplant Phenotypes

Metabolomics, where high-throughput identification and quantification of metabolites are done using mass spectral methods, are increasingly applied to study crop plants. Eggplant metabolites have been profiled and attempts have been made to link metabolic profiles to fruit morphology and nutrition, drought stress, nutrient use efficiency, response to pathogens, and other desirable traits (Mauceri et al. 2022; Chen et al. 2021; Hanifah et al. 2018; Mibei et al. 2017). Hanifah et al. (2018) analyzed eggplant fruit from 21 accessions using untargeted metabolomics with gas chromatography and mass spectrometry in tandem (GC-MS) and liquid chromatography with mass spectrometry (LC-MS) methods. Untargeted metabolomics identified 207 and 51 putative metabolites from GC-MS and LC-MS analysis, respectively, and they belonged to terpenoids, alkaloids, flavonoids, and fatty acid pathways. Two metabolite clusters were identified from GC-MS analysis that further discriminated the 21 eggplant accessions into two respective groups. For example, linoleic acid, palmitic acid, alpha-tocopherol (vitamin E), and neophytadiene metabolites from GS-MS were present across most of the eggplant accessions. Similarly, 2, 5-Bis (N-hexylmethylsilyl) thiophene, 2-(Methylthiomethyl)3-phenyl-2-propenal, and Boscalid metabolites from LC-MS were present across more than three eggplant accessions. These metabolites represent terpenes and alkaloid pathways. Interestingly, most of the metabolites detected from both GC-MS and LC-MS analysis were accession-specific (Hanifah et al. 2018), suggesting a unique metabolic landscape from fruits of diverse eggplant accessions. Some of these accession-specific metabolites represented the steroids, flavonoids, alkanes, terpenoids, saturated and unsaturated fatty acid pathways. In addition to known metabolites, the LC-MS also detected previously unknown metabolites in a sub-set of eggplant accessions. Furthermore, different fruit characteristics also showed significant correlations with specific metabolic profiles in the 21 eggplant accessions (Hanifah et al. 2018). These fruit traits represented curvature (CVT), spininess of calyx (SCL), anthocyanin coloration under calyx (IUC), depth of indentation of pistil scar (DPS), and fruit patches (PTC), density of stripes (DST), and ribs (RBS). For instance, G55 eggplant accession had strong fruit CVT and showed high correlation with 1,2,4nonadecanetriol. Similarly, PTC trait correlated with farnesyl acetone, and lariciresinol, and clionasterol metabolites, while SCL trait had high correlations with ethyl 9-heptadecenoate and 1-tetradecanoyl-glycero-3-phosphoserine metabolites in different eggplant accessions. Studies also demonstrated the use of metabolomics to understand the effect of biotic and abiotic stresses in eggplant. For example, eggplant genotypes with high (‘AM222’) and low (‘305E40’) nitrogen utilization efficiency (NUE) were characterized for primary and secondary metabolites under nitrogen starvation, and short- and lone-term nitrogen-limiting resupply conditions using GC-MS and

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UPLC-qTOF-MS approaches (Mauceri et al. 2022). A differential metabolite analysis revealed several pathways associated with differential NUE in eggplant. For instance, glycine and glyA transcript accumulation in high NUE genotype appears useful for acclimation to the N-limiting stress conditions. An abundance of sucrose and starch pathway metabolites were associated with improved NUE. Similarly, higher levels of L-aspartate and L-asparagine in high NUE genotypes were also identified at short-term low-nitrogen treatment, whereas granule-bound starch synthase and endoglucanase were downregulated under long-term nitrogen stress (Mauceri et al. 2022). These results delineate specific metabolic pathways to target for improving NUE in eggplant. In a similar way, GC-MS was applied to analyze the biochemical changes related to drought stress in African eggplant accessions (Mibei et al. 2017). Nineteen eggplant accessions were analyzed for metabolite changes under regular and water limiting conditions. Drought stress broadly affected the metabolic landscape of eggplant genotypes by changes in sugar, amino acid, and organic acid pathways. The levels of sucrose, fructose, trehalose, xylose, and mannose sugars were positively correlated with the drought stress (Mibei et al. 2017). Likewise, the concentrations of proline, glutamate, citrate, isocitrate, malate, and fumarate were relatively abundant in drought conditions. In contrast, the levels of glucose, myo-inositol, glycine, alanine, quinic acid, aspartate, and malate were less abundant under water-limiting conditions (Mibei et al. 2017). The metabolic changes were defined by genotype, growth stages, and water stress conditions, hence suggesting the complexity of drought stress responses in eggplant. Recently, a metabolome and volatilome analysis has been conducted to elucidate the biochemical responses of eggplant and tomato against infestation from Tuta absoluta, a destructive pest of Solanaceae crops (Chen et al. 2021). A total of 141 volatiles and 797 metabolites were identified that consisted of alcohols, aldehydes, amines, ketones, and terpenes (Chen et al. 2021). The terpene metabolites were differentially enriched in eggplants than tomato. Interestingly, several compounds were either unique in eggplant or were present in lower quantity in tomato in both control and T. absoluta infested samples. The study identified about 35 differentially regulated compounds associated with evoked T. absoluta response, hence were considered to regulate the pest behavior (Chen et al. 2021). Overall, the differentially accumulated compounds might determine the eggplant resistance against T. absoluta infestation, which helps to develop integrated pest control measures for sustainable eggplant production.

5

Eggplant Genomes and Resequencing

Different nuclear genomes of the eggplant have been sequenced within last decade. First draft genome sequence “SME_r2.5.1” of the common eggplant (Solanum melongena L.) cultivar ‘Nakate-Shinkuro’ was assembled using the Roche 454 GS FLX Titanium and Illumina HiSeq 2000 technologies (Hirakawa et al. 2014). It had a total length of 833.1 megabase (Mb) from 33,873 assembled scaffolds. These scaffolds covered about 74% of the predicted 1.12 gigabase (Gb) genome size (Hirakawa

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et al. 2014). Annotation of “SME_r2.5.1” genome revealed a total of 85,446 coding sequences, which represented about 48% transposable elements, 2% pseudogenes, and 0.7% short length genes. The repeat sequences constituted about 70% (586.8 Mbs) of the draft genome assembly and mainly represented Gypsy class retrotransposons (Hirakawa et al. 2014). Out of remaining 42,035 genes, 91.6% and 8.4% were designated as “intrinsic” genes having start and stop codons, and partial genes without start and/or stop codons, respectively. A comparative genomic analysis of predicted eggplant genes against other solanaceous plant genomes revealed about 4018 genes exclusive to eggplant genome. In addition, a total of 16,573 orthologous gene pairs were identified between eggplant and tomato that were spread across 56 conserved syntenic blocks. These observations indicated a considerable level of synteny between these two solanaceous crop species. Due to highly fragmented nature of “SME_r2.5.1” genome, recent efforts from the Eggplant Genome Project (http://www.eggplantgenome.org) led to a chromosome scale fully anchored eggplant genome by integrating single molecule optical mapping and Illumina sequencing approaches (Barchi et al. 2019). This genome assembly from an inbred eggplant line ‘67/3’ consisted of 0.92 Gb ungapped and 1.22 Gb gapped sequences across 469 scaffolds – a significant improvement from the previously available draft genome (Hirakawa et al. 2014). The hybrid scaffolds were anchored to 12 chromosomes using a genetic map of 5964 markers, and the resulting anchored pseudomolecules represented 1.14 Gb gapped and 0.82 Gb ungapped sequences (Barchi et al. 2019). The ‘67/3’ genome had low residual heterozygosity (0.027%) and high (73%) transposable element sequences. It had a total of 34,916 predicted protein-coding genes (Barchi et al. 2019), which were comparable to other Solanaceae genomes (Barchi et al. 2019). A Benchmarking Universal Single-Copy Orthologs (BUSCO) score was 96.9%, indicating a near complete gene annotation of the ‘67/3’ eggplant genome. An ortholog analysis with the new eggplant gene models indicated that 667 gene families were specific to eggplant – with a significant enrichment of “pentatricopeptide repeat-containing protein” family than found in tomato, potato, pepper, and Arabidopsis. A survey of single-locus simple sequence repeats (SSRs) identified about 125 SSRs/1 Mbs of ‘67/3’ genome space. More recently, another chromosome-scale genome of ‘GUIQIE-1’ eggplant cultivar has been assembled by combining the long read PacBio and Hi-C sequencing approaches (Li et al. 2020). The total length of ‘GUIQIE-1’ genome is 1155.8 Mb (N50 ¼ 93.9 Mb), out of which, repetitive sequences were 70.1% of the total assembly. Genome annotation identified a total of 35,018 protein-coding genes – a little higher than the annotated genes in the ‘67/3’ eggplant genome. The number of eggplant-specific gene families (n ¼ 646) were almost similar between ‘GUIQIE-1’ and ‘67/3’ genomes. An additional orthologous gene family analysis indicated an expansion in disease resistance genes for bacterial spot resistance in eggplant and pepper than in tomato and potato (Li et al. 2020). Overall, the fully anchored and high-quality genome assemblies from ‘67/3’ and ‘GUIQIE-1’ accessions provide important resources for genetic improvement and functional genomics studies in eggplant and related species.

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With the availability of high-quality chromosome scale genomes, it is now feasible to characterize the genomic diversity and evolutionary footprints of eggplant and its wild relatives. Until now, the genomes of a small set of seven S. melongena and one wild S. incanum accession has been re-sequenced at 19.8  depth (Gramazio et al. 2019). Alignments of these eight re-sequenced genomes against ‘67/3’ reference genome identified about nine million single nucleotide polymorphisms (SNPs) and 700,000 Insertion/Deletions (Indels). The wild S. incanum accession represented most of this variation. The variants in the S. melongena accessions ranged from 0.8 to 1.3 million (Gramazio et al. 2019), indicating a narrow genetic diversity in cultivated eggplant. In addition, about 98% of the variants were present in intergenic and intronic regions. The moderate effect protein-coding (codon insertion/deletion, codon substitution) SNPs ranged from 0.61% to 0.78%, while the large effect SNPs (loss of function mutations or protein truncation) ranged from 0.05% to 0.09% (Gramazio et al. 2019). This analysis provides a preliminary overview of genetic variation and its use for eggplant genetic improvement. Genome sequence resources should allow us to develop and utilize DNA markers for key traits of importance in eggplant that are connected to health promoting metabolites and methods to select desirable plants. Exploration of genomic and phytochemical diversity in the eggplant will also lead to future synthetic biology strategies to overproduce specific phytochemicals of value.

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Stommel JR, Whitaker BD (2003) Phenolic acid content and composition of eggplant fruit in a germplasm core subset. J Am Soc Hortic Sci 128(5):704–710 Sun T, Simon PW, Tanumihardjo SA (2009) Antioxidant phytochemicals and antioxidant capacity of biofortified carrots (Daucus carota L.) of various colors. J Agric Food Chem 57(10):4142–4147 Swarup V (1995) Genetic resources and breeding of aubergine (Solanum melongena L.). Acta Hortic 412:71–79 Taher D, Solberg SO, Prohens J, Chou YY, Rakha M et al (2017) World vegetable center eggplant collection: origin, composition, seed dissemination and utilization in breeding. Front Plant Sci 8:1484 Thipyapong P, Stout MJ, Attajarusit J (2007) Functional analysis of polyphenol oxidases by antisense/sense technology. Molecules 12(8):1569–1595 Tiossi RFJ, Miranda MA, de Sousa JPB, Praça FSG, Bentley MVLB et al (2012) A validated reverse phase HPLC analytical method for quantitation of glycoalkaloids in Solanum lycocarpum and its extracts. J Anal Methods Chem 2012(947836). https://doi.org/10.1155/2012/947836 Toppino L, Barchi L, Lo Scalzo R, Palazzolo E, Francese G (2016) Mapping quantitative trait loci affecting biochemical and morphological fruit properties in eggplant (Solanum melongena L.). Front Plant Sci 7:256 Tran LT, Taylor JS, Constabel CP (2012) The polyphenol oxidase gene family in land plants: lineage-specific duplication and expansion. BMC Genomics 13(1):1–12 Trivedi P, Pundarikakshudu K (2007) Novel TLC densitometric method for quantification of solasodine in various Solanum species, market samples and formulations. Chromatographia 65(3):239–243 Urbany C, Stich B, Schmidt L, Simon L, Berding H et al (2011) Association genetics in Solanum tuberosum provides new insights into potato tuber bruising and enzymatic tissue discoloration. BMC Genomics 12(1):1–14 Vaananen T (2007) Glycoalkaloid content and starch structure in Solanum species and interspecific somatic potato hybrids (dissertation). EKT-series 1384. Department of Applied Chemistry and Microbiology, University of Helsinki, Helsinki, pp 79 + 45 van Lent DM, Leermakers ETM, Darweesh SKL, Moreira EM, Tielemans MJ et al (2016) The effects of lutein on respiratory health across the life course: a systematic review. Clin Nutr ESPEN 13:e1–e7 Wang LS, Stoner GD (2008) Anthocyanins and their role in cancer prevention. Cancer Lett 269(2): 281–290 Wang CC, Sulli M, Fu DQ (2017) The role of phytochromes in regulating biosynthesis of sterol glycoalkaloid in eggplant leaves. PLoS One 12(12):e0189481 Watson RR, Schönlau F (2015) Nutraceutical and antioxidant effects of a delphinidin-rich maqui berry extract Delphinol: a review. Minerva Cardioangiol 63(2):1–12 Weese T, Bohs L (2010) Eggplant origins: out of Africa, into the Orient. Taxon 59(1):49–56 Whitaker BD, Stommel JR (2003) Distribution of hydroxycinnamic acid conjugates in fruit of commercial eggplant (Solanum melongena L.) cultivars. J Agric Food Chem 51(11):3448–3454 Wu F, Eannetta NT, Xu Y, Tanksley SD (2009) A detailed synteny map of the eggplant genome based on conserved ortholog set II (COSII) markers. Theor Appl Genet 118(5):927–935 Xu W, Dubos C, Lepiniec L (2015) Transcriptional control of flavonoid biosynthesis by MYB– bHLH–WDR complexes. Trends Plant Sci 20(3):176–185 Zhang Y, Chu G, Hu Z, Gao Q, Cui B et al (2016) Genetically engineered anthocyanin pathway for high health-promoting pigment production in eggplant. Mol Breed 36(5):1–14 Zhao Y, Wang J, Ballevre O, Luo H, Zhang W (2012) Antihypertensive effects and mechanisms of chlorogenic acids. Hypertens Res 35(4):370–374 Zhao DK, Zhao Y, Chen SY, Kennelly EJ (2020) Solanum steroidal glycoalkaloids: structural diversity, biological activities, and biosynthesis. Nat Prod Rep 38(8):1423–1444 Zhao J, Dan Y, Liu Z, Wang Q, Jiang M et al (2022) Solamargine alleviated UVB-induced inflammation and melanogenesis in human keratinocytes and melanocytes via the p38 MAPK signaling pathway, a promising agent for post-inflammatory hyperpigmentation. Front Med 13:812653

Genome Designing for Nutritional Quality in Amaranthus Isadora Louise Alves da Costa Ribeiro Quintans, Valesca Pandolfi, Thais Gaudencio do Reˆgo, Jose´ Ribamar Costa Ferreira Neto, Thais A. R. Ramos, and Dinesh Adhikary

Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Agricultural Importance of Amaranth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Amaranth Is a Rich Source of Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Amaranth and Nutrigenomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Amaranth’s Importance to Prevent Diseases and Malnutrition . . . . . . . . . . . . . . . . . . . . . . 1.5 Bioavailability of Amaranth Nutrients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Amaranth Biofortification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7 Biochemical Pathways of Amaranth Compounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Genetic Resources of Amaranth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Brief on Genetic Diversity Analysis of Amaranth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Molecular Mapping of Genes/QTLs Underlying Nutritional Traits in Amaranth . . . . . . . . 4 Limitations of Conventional Breeding and Genetic Resources of Amaranth . . . . . . . . . . . . . 5 Strategies for Amaranth Gene Editing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Brief Account on the Role of Bioinformatics as a Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Amaranth Genome Sequencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Amaranth Sequences Among the Gene and Genome Databases . . . . . . . . . . . . . . . . . . . . 6.3 Amaranth and Comparative Genomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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I. L. A. da Costa Ribeiro Quintans (*) Universidade Federal Rural do Semi-Árido, Mossoro, Brazil e-mail: [email protected] V. Pandolfi · J. R. C. F. Neto Universidade Federal de Pernambuco, Recife, Brazil e-mail: valesca.pandolfi@ufpe.br; [email protected] T. Gaudencio do Rêgo · T. A.R. Ramos Universidade Federal da Paraíba, João Pessoa, Brazil e-mail: [email protected]; [email protected] D. Adhikary Department of Agricultural, Food & Nutritional Sciences, University of Alberta, Edmonton, AB, Canada e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_56

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7 Conclusion and Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1520 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1521

Abstract

Known for its high nutritional value and ability to thrive in the most adverse conditions, amaranth grain is considered a superfood by many. Amaranth is gluten-free and rich in protein, especially lysine, an essential amino acid very scarce in other plants. The antioxidant properties of amaranth may improve the nutritional status and health of consumers. In fact, as an antioxidant, antiinflammatory, and anticancer agent, amaranth has been pharmacologically reported to be highly effective against chronic inflammation. Other benefits of amaranth include lowering cholesterol and preventing cardiovascular disease. Even amaranth antinutrients, such as phenolic compounds, have antioxidant properties. Amaranth can be used for the biofortification of staple food by simply adding amaranth compounds to flour or bakery products. A more complex approach involves creating transgenic plants with higher nutritional profiles. Amaranth biofortification may also increase yield and resistance to multiple diseases. Despite these unique characteristics, amaranth is considered an underutilized grain, with greater potential to overcome hunger and diseases. One of the limitations of amaranth cultivation is the lack of high-yielding varieties. Therefore, we provide in this chapter a broad overview of amaranth grain cultivation and the current state of the art of genetic breeding of this crop. We highlight plant breeding using molecular markers and genetic diversity assessment. In addition, we describe the development of transgenic plants that have been enhanced by amaranth genes as well as new and promising gene editing techniques for amaranth, such as CRISPR and nanotechnology. Furthermore, we highlight the main germplasm and genomic databases for amaranth, as well as bioinformatic tools for assessing and analyzing the data. Altogether, this information may aid the rational design for nutritional quality and yields in Amaranthus and other plants, by using amaranth as a role model for nutritional improvement design. Keywords

Amaranthus · Gene editing · Biofortification · Bioinformatics · Genetic diversity · Nutrition · Malnutrition · Food security

1

Introduction

1.1

Agricultural Importance of Amaranth

Amaranth is an ancient grain, with the first archeological register dated from 4000 BC in South America, more specifically in Mexico (Jimoh et al. 2018). Amaranth is mainly cultivated in South America (yielding 4600–7200 kg/ha), Africa (50–2500 kg/ha), and Europe (1200–6700 kg/ha) (D’Amico and Schoenlechner 2017). Amaranth

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is widely grown in Africa (Ma et al. 2021), and it has been domesticated in the Americas (Stetter et al. 2016). There are three Amaranthus species cultivated for grain production: Amaranthus caudatus, Amaranthus cruentus, and Amaranthus hypochondriacus (Jimoh et al. 2018; Stetter et al. 2016). Amaranth is a flowering plant belonging to the Amaranthaceae family and Amaranthus genus and includes more than 60 species (Sauer 1957; Tabio-García et al. 2021). Amaranth is considered a superfood, rich in many macro- and micronutrients necessary for humans (Jimoh et al. 2018). Besides, amaranth can grow in harsh environmental conditions, making the species very suitable for agriculture in a vast geographic range (Jimoh et al. 2018). Amaranth presents resistance to water deficit, saline soils, and acid/alkaline stresses (Tabio-García et al. 2021). Amaranth’s resistance to drought and increased photosynthesis effectiveness are due to the C4 photosynthetic pathway (Jimoh et al. 2018). C4 plants can use CO2 and water more efficiently, lowering photorespiration, compared to C3 plants, like many cereals (Jimoh et al. 2018). Therefore, amaranth tolerates heat and drought, which are typical of arid and semiarid regions (Jimoh et al. 2018). Besides being resistant to abiotic stresses, amaranth is also resistant to biotic stresses (Packard et al. 2021). Due to amaranth’s resistance to several stresses, ability to thrive in a vast range of environments, and great nutritional value, this vegetable is suitable to supply highquality foods in countries affected by hunger, such as in South Africa (Emmanuel and Babalola 2021; Ma et al. 2021). Even though amaranth has been cultivated in South Africa and many other regions, this crop has been underutilized (Emmanuel and Babalola 2021; Ma et al. 2021) due to the lack of improved, high-yielding varieties, as we will further discuss.

1.2

Amaranth Is a Rich Source of Nutrients

The three main macronutrients for the human diet are protein, carbohydrates, and fat (Holesh et al. 2022). Amaranth has high levels of the majority of the nutrients required for a balanced diet, exceeding many staple crops, such as barley, corn, rice, maize, and wheat (Adhikary et al. 2020; Joshi et al. 2018). Amaranth presents high-quality essential nutrients, such as protein, lipids, carbohydrates, vitamins, and minerals (Table 1). Protein intake is a very important part of the human diet, providing the essential amino acids (EAA) that the human body needs, but does not synthesize itself (Floret et al. 2021; Lopez and Mohiuddin 2021). The proteins are the major effector of the cells, participating in signaling cascades, gene expression regulation, and several enzymatic reactions (Floret et al. 2021). Besides, amino acids are the building blocks for enzymes, antibodies, hormones, muscle, and many other cellular processes (Lopez and Mohiuddin 2021). One way to determine the nutritional value of a food item is by measuring the protein content, on which if some essential amino acid is missing, it can be defined as the “limiting amino acid” (Jimoh et al. 2018). By definition, a complete protein source contains all the essential amino acids (Lopez and Mohiuddin 2021). This

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Table 1 Nutrient composition from amaranth grains Nutrient

Protein

Lipid

Carbohydrate

Vitamins

Minerals

Nutrient Type Water Energy Total protein Glutamic acid Glycine Aspartic acid Serine Arginine Leucine Alanine Lysine Proline Valine Isoleucine Threonine Phenylalanine Histidine Tyrosine Methionine Cystine Tryptophan Total lipid Tocopherol, beta Tocopherol, delta Tocopherol, gamma Phytosterol By difference Starch Fiber Sugars, total Vitamin C (ascorbic acid) Vitamin B5 (pantothenic acid) Vitamin E (alpha-tocopherol) Vitamin B3 (niacin) Vitamin B6 Vitamin B2 (riboflavin) Vitamin B1 (thiamin) Phosphorus Potassium Magnesium Calcium Iron Sodium

Value per 100 g 11.29 371 13.56 2.26 1.64 1.26 1.15 1.06 0.88 0.80 0.75 0.70 0.68 0.58 0.56 0.54 0.39 0.33 0.23 0.19 0.18 7.02 0.96 0.69 0.19 24.00 65.25 57.27 6.70 1.69 4.20 1.46 1.19 0.92 0.59 0.20 0.12 557 508 248 159 7.61 4.00

Unit g kcal g g g g g g g g g g g g g g g g g g g g mg mg mg mg g g g g mg mg mg mg mg mg mg mg mg mg mg mg mg (continued)

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Table 1 (continued) Nutrient

Nutrient Type Manganese Zinc Copper Selenium

Value per 100 g 3.33 2.87 0.53 0.02

Unit mg mg mg mg

Adapted from Jimoh et al. (2018)

notion holds particular significance when examining vegetarian diets since the most complete protein sources are usually derived from animals (Jimoh et al. 2018; Lopez and Mohiuddin 2021). On the other hand, plant-based foods are usually considered incomplete sources of proteins, for which they may lack some essential amino acid or the limiting amino acid is present in a very low concentration that it does not meet the requirements for human nutrition (Lopez and Mohiuddin 2021). Consequently, it is very important to find good sources of vegetables and cereals for a well-balanced vegetarian-based diet. Plant-based food promotes many benefits to human health, because they are a healthy source of macronutrients and dietary minerals, reducing calorie density and cholesterol consumption (Ivanova et al. 2021). The amaranth symbolizes a nearly complete source of protein for humans. For instance, amaranth grains are abundant in protein (15% of the content) and have nearly all the essential amino acids required for human nutrition (Adhikary et al. 2020). Amaranth is especially rich in lysine, which is a limiting amino acid in other grains (Gebreil et al. 2020; Sisti et al. 2019). Amaranth’s only limiting amino acid is leucine, which can be easily obtained by combining amaranth with other food sources (Adhikary et al. 2020). Besides its nutritional value, amaranth proteins also have antioxidant capacity (Coelho et al. 2018), and it has been considered a good source of antihypertensive peptides (Nardo et al. 2020). On the other hand, carbohydrates have been considered a “great villain” of a healthy nutrition. However, carbohydrates are a great source of energy and, therefore, a fundamental component of the human diet (Holesh et al. 2022). Carbohydrates are categorized based on both the composition of sugars present in their structures and the specific types of sugars they contain (Holesh et al. 2022). Regarding the sugar content, they are classified into: monosaccharides (single sugar molecules), disaccharides (two sugars molecules), oligosaccharides and polysaccharides (more than two sugar molecules linked in long chains, with polysaccharides being the longest) (Holesh et al. 2022). Regarding the sugar type, they are classified as simple (one or two types of sugars), complex (three or more types of sugars), starches (complex carbohydrates rich in glucose) and fiber (non-digestible complex carbohydrates) (Holesh et al. 2022). Plants are one of the richest sources of all types of carbohydrates, with starches and fiber being very specific to these organisms (Holesh et al. 2022). A healthy and balanced diet should favor complex carbohydrates (such as whole grains) and dietary fiber, which are low in glycemic index and calories. These features are important for preventing diabetes, obesity, and inflammatory-mediated diseases (Ivanova et al. 2021). A highlight should be given

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to the maintenance of the gut microbiota, which is related to many aspects of human health, such as immunity and energy metabolism (Holesh et al. 2022; Valdes et al. 2018). The consumption of low-digestible carbohydrates (LDC), present in processed foods, can be very detrimental to the gut health (Hollie et al. 2009). The LDC tends to accumulate in the large intestine, serving as substrates for pathogenic bacteria fermentation leading to the dysregulation of the gut microbiome and many other health issues (Hollie et al. 2009). Therefore, the intake of natural or unprocessed food is the best choice for a healthier gut. For instance, amaranth is a great source of healthy carbohydrates. Amaranth is rich in starch, ranging from 47% to 72% of the grains, depending on the species (Coelho et al. 2018; Nardo et al. 2020). Amaranth starch is mainly formed of amylopectin, and the unusual characteristics of the starch granules, such as small size, low resistance, and granular structure, make amaranth’s grains very unique (Coelho et al. 2018). Amaranth is also rich in insoluble fiber, such as lignin and cellulose, which contributes to lowering cholesterol and to preserving gut health (Coelho et al. 2018). Additionally, amaranth is a great source of unsaturated fatty acids, tocopherols, squalene, phytosterols, and polyphenols (Jimoh et al. 2018; Sisti et al. 2019). For instance, amaranth oil has a reasonable amount of squalene, when compared with other vegetable oils, such as olive oil (Coelho et al. 2018; Jimoh et al. 2018). Squalene is a precursor of all steroids in animals and plants (Coelho et al. 2018) and has many health properties, such as anticancer, antioxidant, and antiinflammatory (Jimoh et al. 2018; Joshi et al. 2018). Squalene from fish oils (especially shark liver oil) has been consumed in high amounts (Kim and Karadeniz 2012). However, due to the regulations on the consumption of animal products, amaranth oil could be a great alternative source for squalene to fish oil (Ibrahim et al. 2020; Jimoh et al. 2018). Amaranth is also rich in tocopherols which are important precursor molecules for vitamin E (Ryan et al. 2007). Aside from the macronutrients, amaranth is also rich in micronutrients, such as vitamins and minerals (Jimoh et al. 2018). Worldwide, human diets are deficient in vitamins and minerals, especially magnesium (Jimoh et al. 2018). Children and pregnant women are most affected by it, resulting in many diseases (Jimoh et al. 2018). Some of the micronutrients found in amaranth leafy vegetables and/or grain are phosphorus, iron, calcium, potassium, and vitamin A, B, C, and E (Table 1) (Jimoh et al. 2018). Therefore, amaranth is a very promising plant that can be used by humans to replenish their food needs, as well as promoting their health (Jimoh et al. 2018). Amaranth is a very promising vegetable for human consumption because of its unique nutritional and medicinal properties, as well as its ability to grow in non-abiotic and biotic soil conditions throughout the world (Gebreil et al. 2020; Jimoh et al. 2018).

1.3

Amaranth and Nutrigenomics

Food choices affect our body on many levels, including the molecular one. Nutrigenomics is the science that integrates how food constituents affect the

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genomics, transcriptomics, proteomics, and metabolomics of an individual (Berná et al. 2014). Diseases occur when environmental conditions act on a predisposed genome. These external factors can be related to healthy or unhealthy lifestyles (Berná et al. 2014). This means that what we eat may interfere with gene expression and downstream signal transduction and ultimately prevent or increase the risk of diseases (Berná et al. 2014). There is a lack of information on how amaranth-specific nutrients work at the genomic level. Besides, even though some diseases appear to have a genetic predisposition component, sometimes the pathogenesis of the disease is not very well comprehended, for instance, diabetes mellitus (DM) (Berná et al. 2014). Ultimately, it is well known that many disorders, such as obesity, cardiovascular diseases, and cancer, might be related to an interaction of predisposing genes with an imbalanced diet (Berná et al. 2014) and oxidative stress (Berná et al. 2014). Amaranth is rich in antioxidant compounds that play an important role as scavengers of the free reactive oxygen species (ROS) (Coelho et al. 2018), preventing further damage to molecules such as DNA, protein, and lipids, among others. Antioxidant molecules may as well have a role in epigenetics and nutrigenomics (Berná et al. 2014). In order to develop personalized diets, we need to understand how epigenetics, microRNA, and others affect the expression of genes related to disease (Berná et al. 2014). A healthy diet, based on individual genomic profiles, will maximize gut microbiota health and minimize inflammation and disease susceptibility (Berná et al. 2014).

1.4

Amaranth’s Importance to Prevent Diseases and Malnutrition

Plant-based food sources are a great way to combat both starvation and obesity, which pose great threats to food security. Hunger affects the lives of billions of people worldwide, especially in Africa, and it is a great concern for all nations (Emmanuel and Babalola 2021; Webb 2021). The UN World Food Program (WFP) raised the concern that COVID-19 pandemics would accelerate and amplify the lack of food, as a result of the lockdowns to control the virus spreading (Webb 2021). The COVID-19 pandemic has increased the economic and social damage, leading to more than 70 million people to extreme poverty by the end of the year of 2020 (Webb 2021). The increased food prices amplified the consumption of lower quality food and, therefore, have increased malnutrition (Webb 2021). The COVID-19 pandemic has worsened the food crisis, but, even before that, it was estimated that almost 39% of the world population subsisted on a suboptimal diet because a healthy diet could not be afforded (Webb 2021). It is well known that simple solutions may have a great impact to improve the human diet, such as adding iodine to table salt, which prevents iodine deficiency disorders (that range from hypothyroidism to infant mortality) (Eastman and Zimmermann 2000). Likewise, introducing amaranth vegetable and/or grain as a great source of macronutrients, micronutrients, and bioactive compounds will supply requirements for a balanced diet and improve the medical conditions of consumers.

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For instance, amaranth can be used for dietary fortification, improving the nutritional value of processed food (Jimoh et al. 2018). Amaranth flour could be used as a replacement for corn flour in the preparation of many bakery products, such as crackers, cookies, tortillas, and bread, increasing the nutritional value of these processed foods (Gebreil et al. 2020; Jimoh et al. 2018). Besides, amaranth flour is glutenfree, which is very important with the growth of gluten sensitivity and celiac disease (Gebreil et al. 2020; Jimoh et al. 2018). Amaranth can also be used to make pastes, sauces, dressings, and a very large variety of processed food (Jimoh et al. 2018). The high consumption of cheap processed food has been associated with overweight/ obesity in both developed and developing countries (Żukiewicz-Sobczak et al. 2014). It is estimated that obesity levels and, consequently, several associated diseases are tending to increase (Żukiewicz-Sobczak et al. 2014). These diseases are more than ever in the spotlight, due to the COVID-19 pandemic (Sattar et al. 2020). People with comorbidities are more vulnerable to the acute respiratory syndrome caused by COVID-19 and also are at the greatest risk for severe illness and even death (Ivanova et al. 2021; Sattar et al. 2020). A recent study has suggested that amaranth might be important in preventing diseases, such as the COVID-19 (Datta 2021). Amaranth compounds, from proteins to lipids and bioproducts, are potent antioxidants (Adhikary et al. 2020). Since inflammation is a major factor in many chronic diseases, a diet rich anti-inflammatory antioxidants is very important (Ivanova et al. 2021). Amaranth compounds contribute to lowering cholesterol and consequently diminishing the chances of cardiovascular diseases (Jimoh et al. 2018; Sarker et al. 2020). For instance, amaranth fiber and protein consumption affects cholesterol metabolism and prevents hypercholesterolemia (Sisti et al. 2019). Amaranth is also a great source of vitamin E that, likewise squalene, can contribute to lower cholesterol. Vitamin E also has antioxidant, anticancer, and cardio-protectant properties, besides preventing Alzheimer’s (Ryan et al. 2007). Amaranth is also rich in phytosterol, which is a plant sterol. Plant-based diets may lower cholesterol levels and reduce the risk of cardiovascular disease because they reduce sterol absorption by the digestive system (Ryan et al. 2007). Amaranth also has antihypertensive peptides (Nardo et al. 2020). Amaranth is rich in unsaturated fatty acids, such as omega-3 and omega-6 (Soriano-García et al. 2018). Amaranth lipid portion, such as squalene, has antioxidant, autoinflammatory, and anticancer properties (Soriano-García et al. 2018). Besides the aforementioned medical properties, amaranth natural antioxidants may also have a role in the prevention of cataracts and retinopathies, arthritis, atherosclerosis, and even neurodegenerative diseases (Sarker et al. 2020). The bioactive compounds of the lipid fraction may additionally have antidiarrheal and antidepressant effects as well (Coelho et al. 2018). Great attention has been given to the Amaranthus component betalain, which is responsible for amaranth red color (betacyanin) (Adhikary et al. 2019) (Fig. 1) and can be used as a natural colorant for food (Coelho et al. 2018). Betalains have antioxidant, anticancer, antibacterial, and antimalarial properties (Packard et al. 2021). The betalain from amaranth is therefore a potential natural coloring agent with interesting health benefits for the food industry (Tabio-García et al. 2021). Consumers who want a

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Fig. 1 A. tricolor “Red Leaf”

healthier lifestyle and are concerned about synthetic colorants’ detrimental effects have been attracted to these features (Tabio-García et al. 2021). There are many nutrients in amaranth, but some compounds, such as nondigestible glucosides, can reduce its ability to be digested and utilized (Jimoh et al. 2018). However, it is possible to improve the bioavailability of nutrients in the edible parts of plants through biofortification (Malik and Maqbool 2020). In the next section, we will discuss bioavailability and biofortification in more detail.

1.5

Bioavailability of Amaranth Nutrients

Bioavailability is the nutrient portion that is utilized by the human body (Jimoh et al. 2018). The fact that amaranth contains a diversity of compounds does not mean all of them are absorbed by the body. For instance, the bioavailability of amaranth proteins can be reduced by the presence of antinutrient compounds, such as phytic acid, nitrate, oxalates, and tannins (Coelho et al. 2018; Jimoh et al. 2018). So far, these compounds have not been associated with toxic effects on human nutrition (Coelho et al. 2018). Therefore, amaranth grain should be properly processed before

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ingestion, to increase bioavailability (Coelho et al. 2018; Jimoh et al. 2018). Another trending field is using encapsulation to improve bioavailability of amaranth bioactive compounds (Coelho et al. 2018).

1.6

Amaranth Biofortification

Micronutrients, such as iron, zinc, iodine, and vitamins, are crucial for human health, and their lack in malnourished populations can lead to many disorders and diseases (Malik and Maqbool 2020). In countries with a limited choice of diets, biofortification holds the promise of providing a single source of complete nutrition (Malik and Maqbool 2020). Some health conditions affected by malnourishment are highlighted in Table 2. Pregnant women and children are particularly vulnerable to these conditions (Malik and Maqbool 2020). Biofortification can be obtained through agricultural practices, traditional breeding, or genetic editing (Malik and Maqbool 2020). Staple cereals, vegetables, beans, and fruits have been biofortified using these approaches (Garg et al. 2018). Different from simply adding nutritional value to staple foods, biofortification attempts alterations in the plant phenotype (Malik and Maqbool 2020). Besides creating grains with enhanced nutritional value, the biofortified plants also may become less susceptible to biotic and abiotic stresses (Malik and Maqbool 2020). So far, our agricultural practices have not been focused on increasing nutrient quality but, instead, maximizing yield, which can decrease the nutritional quality of the grains (Garg et al. 2018). Agricultural practices that can favor crops’ biofortification involve fertilization, seed treatment and nurseries, and certified seeds (Ochieng et al. 2019).

1.6.1 Genetic Approaches for Amaranth Biofortification There is a great effort from the scientific community to produce plants with an improved protein profile, including limiting amino acids (Wenefrida et al. 2013). Table 2 Micronutrient deficiency and health conditions Deficiency in micronutrients Iron Zinc Iodine Vitamin A Vitamin B Vitamin C Vitamin E

Health condition Anemia Night blindness, dermatitis, loss of appetite, impaired immune system Pregnancy related issues (affects the neurodevelopment of fetus), affects growth and cognitive functions in children Blindness, pregnancy and breastfeeding related issues, impaired immune system Skin inflammation, impaired immune system, fatigue, and depression Dermatologic issues, joint pain, and impaired immune system Nerve and muscle damages, impaired immune system, hemolytic anemia, ophthalmological disorders

Source: Malik and Maqbool (2020)

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Several methods can be used with this purpose, such as genetic breeding and genetic engineering, genomics, and selection assisted by markers (Wenefrida et al. 2013). Biofortification through genetic breeding is possible when genetic diversity is available for a given species (Garg et al. 2018). Genetic diversity is represented in the germplasm databases, which are a collection of genetic resources for a given organism. Amaranth includes up to more than 11,000 accessions among 8 gene banks (Joshi et al. 2018). However, it seems that amaranth genetic diversity has been poorly used in breeding programs (Joshi et al. 2018). Finally, genomic editing is one of the most promising approaches to improving amaranth nutritional value. The increased amount of genetic data generated by sequencing, such as amaranth reference genome (Lightfoot et al. 2017) and other genomic and transcriptomic data (Clouse et al. 2016; Délano-Frier et al. 2011; Sunil et al. 2014), is increasing the potential to edit amaranth genome. Using gene edition, amaranth macronutrients, such as protein, have been targeted (Garg et al. 2018). The amaranth lysine pathway, for example, is an attractive biofortification target. According to Sunil et al. (2014), amaranth contains more lysine and threonine than major cereals such as rice and wheat, and some plants don’t even produce lysine or threonine (Wenefrida et al. 2013). Using amaranth genes, many crops have been biofortified. To modify rice grains, which lack lysine and threonine, synthetic genes combining endogenous rice sequences with lysine and threonine coding sequences were inserted under the promoter 35S to produce these amino acids in large quantities (Jiang et al. 2016). However, there are limitations to the production of transgenic biofortified plants (Jiang et al. 2016). Still, Jiang et al. (2016) research opened venues for producing transgenic plants with synthetic genes with enhanced lysine and threonine content. In order to produce plants biofortified with lysine and threonine, we must understand their biosynthetic pathway. In this regard, the draft of Amaranthus hypochondriacus genome and transcriptome was obtained in 2014 (Sunil et al. 2014), with particular attention given to the annotation of the genes involved in lysine biosynthesis. Amaranth genes such as albumin genes (AmA1) have also been used to change the protein content in plants, such as wheat (Triticum aestivum L.) (Garg et al. 2018). The amino acids that increased in content were methionine, cysteine, and tyrosine, besides lysine (Garg et al. 2018; Tamás et al. 2009). In addition, transgenic potatoes were also improved in amino acid content using the same albumin gene (AmA1) from amaranth (Chakraborty et al. 2010; Garg et al. 2018). A further result of this biofortification was an increase in potato photosynthetic activity and yield, proving the importance of biofortification with the AmA1 albumin gene from amaranth (Chakraborty et al. 2010). It appears that amaranth genes have been used more to biofortify plants than to alter the amaranth itself. It is likely that the most recent gene editing strategies will increase the possibility of improving amaranth traits in the near future.

1.7

Biochemical Pathways of Amaranth Compounds

Understanding the genes and proteins underlying a biosynthetic pathway is crucial to improving plant breeding programs using gene editing.

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This chapter will focus on two amaranth compound biosynthetic pathways, which may be of great interest for the food and health industries: lysine biosynthesis and betalain biosynthesis. The lysine biosynthetic pathway in plants shares a common route with the amino acids threonine, isoleucine, and methionine: the aspartate pathway, where L-aspartate is the precursor of these amino acids (Sunil et al. 2014). Two main enzymes regulate the lysine biosynthetic pathway: the aspartate kinase (AK; EC 2.7.2.4) and the dihydrodipicolinate synthase (DHDPS; EC 4.3.3.7) (Sunil et al. 2014). As stated by Sunil et al. (2014), the high-lysine content in Amaranthus is due to the presence of only one ortholog of aspartate kinase 1 (AK1) gene and high expression of the dihydrodipicolinate synthase (DHDPS) gene in seeds. The lysine biosynthetic pathway in amaranth is not very clear yet. Sunil et al. (2014) published a draft of A. hypochondriacus genome and found several isoenzymes AK and DHDPS, among other five important enzymes of the aspartate biosynthetic pathway in plants, such as aspartate semialdehyde dehydrogenase (ASD; EC 1.2.1.11), dihydrodipicolinate reductase (DHDPR; EC 1.17.1.8), diaminopimelate aminotransferase (DAPAT; EC 2.6.1.83), diaminopimelate epimerase (DAPE; EC 5.1.1.7), and diaminopimelate decarboxylase (DAPDC; EC 4.1.1.20). The gene expression profile of the AK and DHDPS revealed a correlation with the high-lysine content in amaranth (Sunil et al. 2014). The study of amaranth lysine biosynthesis as a model for understanding plant lysine biosynthesis is of great importance in order to produce high-lysine content plants. Regarding betalains, these molecules are composed of at least one heterocyclic ring containing a nitrogen atom and are derived from betalamic acid [4-(2-oxoethylidene)1,2,3,4- tetrahydropyridine-2, 6-dicarboxylic acid] (Böhm and Rink 1988; Packard et al. 2021). The betalain biosynthetic pathway is controlled by several factors and conditions, and it was very well discussed by Packard et al. (2021). In summary, betalamic acid condensates with cyclo-DOPA, forms betacyanin, and, when it condensates with amino acids or amines, forms betaxanthin (Böhm and Rink 1988; Packard et al. 2021). L-tyrosine is the main precursor of betalains, being first converted to L-DOPA and subsequently to cyclo-DOPA by several enzymes of this biosynthetic pathway (Böhm and Rink 1988; Packard et al. 2021). The betalain biosynthetic pathway has been carefully reviewed by Packard et al. (2021), and it is a reliable source of information to guide gene editing or gene expression of betalain-related genes. It is interesting to notice that betalains are not very well represented among many plant edible species; therefore, they are less consumed than other antioxidant pigments (Grützner et al. 2021). Grützner et al. (2021) suggested that incorporating betalain biosynthetic genes in a varied range of transgenic species, such as tomatoes, could increase betalain consumption. Moreover, many other transgenic plants producing betalain have been obtained through heterologous expression (Packard et al. 2021). Therefore, these techniques can be exploited to scale up betalain production commercially (Packard et al. 2021). Since many plants lack the amino acid lysine, and the betalain pigment is restricted to the order of Caryophyllales, amaranth is an excellent role model for

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understanding the biosynthesis of these two compounds, which present many desirable effects for human nutrition and health.

2

Genetic Resources of Amaranth

2.1

Brief on Genetic Diversity Analysis of Amaranth

Amaranth and its wild relatives harbor considerable phenotypic plasticity and genetic variability (Gerrano et al. 2017) which contribute to their adaptability to a variety of soil and agroclimatic conditions (Dharajiya et al. 2021). Therefore, amaranth has excellent potential for breeding and variety development. In this respect, the characterization of genetic diversity of amaranths is fundamental for the development of germplasm widely diverse to be efficiently used in genetic breeding programs (Dharajiya et al. 2021; Thapa et al. 2021). As previously described, amaranth grain has high potential from cultivation in the field to the production of value-added products, including nutritional and health benefits (D’Amico and Schoenlechner 2017). The amaranth genus has gained attention as a promising food crop, mainly owing to its tolerance to stressful conditions (Pulvento et al. 2021) besides its great nutritional and functional benefits (Coelho et al. 2018; D’Amico and Schoenlechner 2017). Moreover, in view of the wide geographic distribution and genetic diversity, cultivated and weedy amaranths emerged as appealing models to be explored in improving yield and nutraceutical value (Soriano-García et al. 2018). Efforts have been made to maintain amaranth’s diversity in germplasm banks worldwide (Das 2016; Joshi et al. 2018). Examples of germplasm banks include the US National Plant Germplasm System, with more than 3000 accessions of amaranth from 40 countries (Joshi et al. 2021; Trucco and Tranel 2011). Various morphological and molecular markers have been used for the study of genetic diversity and evolutionary relationships in selected species of the genus Amaranthus. We will further discuss the use of molecular markers in the characterization of the amaranth germplasm.

2.1.1

Genetic Diversity Analysis of Amaranth Assisted by Morphological Traits An approach adequately used to assess genetic diversity is through a combination of morphological, biochemical, and molecular data within amaranth genus (Govindaraj et al. 2015). Morphological descriptors (i.e., color of leaf, flower, stem, and panicle; leaf and panicle shape; plant habit; etc.) have been used to assess amaranth’s diversity (Gerrano et al. 2017; Thapa and Blair 2018). Such characteristics are useful to obtain basic information on existing morphological variability from cultivated species and their wild relatives, which can be incorporated into pre-breeding programs (Showemimo et al. 2021). Examples include the selection of parental materials based on the existence of genetic variation. Gerrano et al. (2017) used morphological traits of Amaranthus species, aiming to identify the best parents for

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the traits of interest that could be used in the Amaranthus breeding program. This study revealed a wide genetic diversity among the species evaluated, helping with the selection of target accessions for the amaranth breeding program in South Africa (Gerrano et al. 2017). Thapa and Blair (2018) observed a wide diversity in phenotypic traits among amaranth species when studying 293 cultivated grain amaranths and their wild relatives. According to the authors, field assessment of major morphological traits can be successful in amaranth grain with implications for breeding varieties (Thapa and Blair 2018). In another study (Showemimo et al. 2021), 12 amaranth grain accessions exhibited high phenotypic and genetic variability for all the traits measured (particularly the desired leaf traits and grain yield traits). Phenotypic variances were slightly higher than the genotypic variance for all the traits measured, revealing little influence of the environment, suggesting that the accession variability is considered useful for amaranth selection and improvement (Showemimo et al. 2021). Morphological characters also have been useful in understanding the evolutionary relationship of Amaranthus species. In India, a study revealed an evolutionary relationship of six amaranth species (A. blitum, A. blitoides, A. deflexus, A. dubius, A. polygonoides, and A. retroflexus) from different states (Kamble and Gaikwad 2021). However, the insufficient distinctive morphological characters for Amaranthus species have hampered the use of morphological markers alone (Govindaraj et al. 2015; Thapa and Blair 2018). For this purpose, molecular markers have been widely considered to assess Amaranthus genetic diversity in complementing morphological information (Oduwaye et al. 2019).

2.1.2

Genetic Diversity Analysis of Amaranth Assisted by Molecular Markers Germplasm characterization based on molecular markers has gained importance due to the speed and quality of information of genetic diversity data created. The use of improved marker systems may aid in the better characterization of the vegetal germplasm, rather than using only the morphological trait system (Dar et al. 2019). For this purpose, molecular markers have been employed in germplasm characterization, phylogenetic analysis, and genetic diversity of the major crop species (Dar et al. 2019). Markers such as amplified fragment length polymorphism (AFLP), random amplified polymorphic DNA (RAPD), microsatellites or simple sequence repeats (SSRs), inter-simple sequence repeat (ISSR), and single nucleotide polymorphisms (SNPs) have been efficiently used to evaluate the variability of germplasm accessions in amaranth (Thapa and Blair 2018). For instance, AFLP was applied by Chandi and collaborators (2013), to assess genetic diversity in Palmer amaranth populations (from North Carolina and Georgia) and to characterize diversity among states, populations, gender, and even response to glyphosate. These results are important, for example, to optimize weed management in breeding programs of amaranth populations (Chandi et al. 2013). The RAPD marker has also been used to assess genetic diversity and in the selection of potential parents for characters of interest in plant breeding programs. For instance, the genetic diversity within 29-grain amaranth accessions in Southwest

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Nigeria was accessed using 27 phenotypic characters (10 morphological and 17 nutritional) and RAPD marker (Akin-Idowu et al. 2016). The level of polymorphism obtained with RAPD primers (81%) broadly indicates the degree of heterogeneity observed in this amaranth germplasm (Akin-Idowu et al. 2016). The RAPD marker has also contributed to the understanding of the origin and evolution of cultivated amaranth and wild species. In this sense, seven amaranth species from different phytogeographic regions were evaluated by RAPD which was sufficient to promote a level of (intra- and interspecific) informative characters (Kumar Pandey et al. 2019). Furthermore, the availability of high-throughput sequencing technologies has facilitated the fast discovery of thousands of microsatellite regions, which may further facilitate understanding evolutionary relationships, genetic diversity, and genomic texture of Amaranthus species (Tiwari et al. 2021). Due to their multiallelic nature, codominant inheritance, and wide distribution throughout the plant’s and animals’ genome, including organellar genomes (mtSSR and cpSSR) (Gupta et al. 2021), microsatellites have gained considerable importance in plant genetic diversity studies, population genetics, and evolutionary studies. They have also been used in fundamental research such as genome analysis, gene mapping, and marker-assisted selection, among others (Gupta et al. 2021). Using A. hypochondriacus genome, Tiwari et al. (2021) identified and characterized a set of SSRs, which facilitated the identification of 97 alleles among 10 Amaranthus species (A. hypochondriacus, A. caudatus, A. retroflexus, A. cruentus, A. tricolor, A. lividus, A. hybridus, A. viridis, A. edulis, and A. dubius), revealing relationships among amaranth spp. that could be useful in species identification, DNA fingerprinting, and QTL/gene identification (Tiwari et al. 2021). Amaranthus genetic diversity has also been accessed by chloroplast sequences. Fulllength chloroplast sequences for four Amaranthus species (A. hypochondriacus, A. cruentus, A. caudatus, and A. hybridus) were assembled by Chaney et al. (2016) revealing polymorphic microsatellite and informative SNP (single nucleotide polymorphism) markers, with application in amaranth phylogenetic and genetic diversity studies. A chloroplast matK marker (maturase K gene) was used to identify leafy amaranth species from Vietnam (Nguyen et al. 2019). Twenty-one SSR markers were developed for A. tricolor ‘Biam’, which successfully amplified single alleles in 294 Vietnamese and overseas accessions (Nguyen et al. 2019). According to the authors, there was a positive relationship between geographic distance and genetic differentiation among most of the overseas groups and the Vietnamese collection (Nguyen et al. 2019). In another study, Hong et al. (2019) also related a close relationship among the chloroplast genomes of Amaranthus hybridus, A. hypochondriacus, and A. caudatus. This relationship was reassured by the complete chloroplast genome of A. hybridus sequencing (Bai et al. 2021), which revealed a close relationship between A. hypochondriacus and A. caudatus. These studies are fundamental to promoting a better understanding of the phylogeny and evolution of the genus Amaranthus.

2.1.3 The Evolutionary Relationship of Amaranth Molecular markers have also made great contributions to the elucidation of the origin and evolution of amaranth. The evolutionary relationship among A. caudatus,

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A. hybridus, and A. quitensis was determined by Stetter et al. (2016). In this study, 119 accessions of the 3 species from the Andean region were genotyped using genotyping by sequencing (GBS) with phenotypic variation in 2 domestication-related traits: seed size and seed color (Stetter et al. 2016). As a result, 9485 SNPs were obtained, and a strong genetic differentiation of the cultivated A. caudatus from the relatives A. hybridus and A. quitensis was observed (Stetter et al. 2016). Given its utility in detecting large numbers of SNPs, the GBS technology was applied to study the diversity and population structure of the grain amaranth, compared to an outgroup of Amaranthus species (Wu and Blair 2017). This analysis revealed a high variation within amaranth grain species and their close relatives (Wu and Blair 2017). Thapa et al. (2021) studied the diversity and relationship among collections of amaranth (accessions of all three cultivated grain amaranth species and their wild relatives). The authors suggested that two Mesoamerican species (A. cruentus and A. hypochondriacus) were intercrossed and distantly related to the South American species (A. caudatus and the weedy relative A. quitensis), which persisted in a wildcultivated hybrid state (Thapa et al. 2021). The knowledge and characterization of genetic diversity, within amaranth’s populations, as well as germplasm conservation, are essential steps for developing new varieties/cultivars with desired agronomic traits, and it is useful for exploring its nutritional and medicinal properties. Collectively, molecular markers have been an excellent approach for various purposes, including genetic studies, breeding efforts, and marker-assisted selection of amaranth.

3

Molecular Mapping of Genes/QTLs Underlying Nutritional Traits in Amaranth

DNA markers have been a useful tool not only for assessing intraspecific variation but also for the subsequent characterization and identification of quantitative trait loci (QTLs) for agronomic and nutritional quality in amaranth genotypes (AkinIdowu et al. 2016). Marker-assisted breeding employs the linkage between known QTLs and genetic markers to select individuals. SNP markers have therefore been effective when used in marker-assisted selection (MAS), especially when linked to target QTLs (Stetter et al. 2016). When it comes to complex traits, effective breeding methods are needed to identify and exploit previously unexplained trait variation caused by a large number of small-effect QTLs, as well as methods that utilize genomic selection (GS) information (Varshney et al. 2021). As high-throughput sequencing technologies have improved, crop breeding programs have become more precise and efficient due to the discovery and mapping of genome-wide allelic variation (Varshney et al. 2021). For instance, genome-wide surveys on comprehensive diversity panels and reference genomes have facilitated phenotypic associations. The DArTSeq technology (based on GBS methods) was used by Jamalluddin et al. (2022) to determine the genetic relationships and population structure between 188 amaranth accessions from 18 agronomically important vegetable, grain, and weedy species. Out of the

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74,303 SNP markers identified, 63,821 could be physically mapped to the A. hypochondriacus genome (Jamalluddin et al. 2022). This marker allowed a genome-wide association study (GWAS) analysis for ten morphological traits and, hence, provided useful information on genetic diversity and its correlation with agronomic traits in amaranth (Jamalluddin et al. 2022). In addition, a universal SNP dataset across Amaranthus species was produced using double-digest restriction site-associated DNA (ddRAD-Seq) sequencing, allowing access to genetic diversity across the major species of the World Vegetable Center (with over 1000 Amaranthus accessions) (Lin et al. 2022). Candidate loci that regulate days to flowering were revealed by an interspecific genome-wide association study (GWAS) (Lin et al. 2022). This study showed that genotypic data is useful for species demarcation in the genus Amaranthus and that interspecific GWAS can detect quantitative trait loci (QTLs) across species (Lin et al. 2022). Recently, A. tricolor accessions (preserved by the World Veg and USDA gene banks) were also evaluated using genome-wide SNPs developed by ddRAD-Seq (Hoshikawa et al. 2023). The 440 accessions contained 10,509 SNPs, with 5638 without missing data (Hoshikawa et al. 2023). With these results, a core collection is now available that represents a wide diversity of amaranth germplasm. This collection will help researchers find important agronomic gene loci to improve genetic breeding, thus improving the economics of amaranth (Hoshikawa et al. 2023). In addition, Ma et al. (2021) assembled the genome of A. cruentus at the chromosome level using short-read, long-read, and phased sequencing technologies. The goal of this study was to identify the genomic features related to the high levels of micronutrients and proteins in these species leaves (Ma et al. 2021). In this study, gene colocations for the key enzymes that synthesize betalain were found across the Amaranthaceae family (Ma et al. 2021). Furthermore, 22 possible biosynthetic gene clusters were identified in A. cruentus genome (10 of which are conserved in A. hypochondriacus) that may facilitate the elucidation of other metabolic biosynthetic pathways present in this plant species (Ma et al. 2021). This will benefit amaranth breeding programs. As in cultivated species, the genome sequencing of wild and weedy species would be advantageous for various large-scale genotyping applications, including germplasm characterization, cultivar identification, and QTL discovery (Joshi et al. 2018). In contrast to major crops (including model plants), amaranth weeds have not been adequately explored, and genomic tools can be efficiently applied in the identification and characterization of genes related to genetic traits that make weeds so resilient when compared with crops in identical niches. Thus, weed species of agronomic importance, such as A. rudis (common waterhemp), A. palmeri (palmer pigweed), and A. hybridus (smooth pigweed), are also potential candidates for genomics studies (Trucco and Tranel 2011). The QTL regions for different traits of amaranth have been identified (Lightfoot et al. 2017; Maughan et al. 2011). Recently, Stetter and collaborators (2020) showed strong evidence that the grain amaranth was domesticated three times and that the white seed color was independently selected in each grain species. Furthermore, the authors identified a MYB-like transcription factor (TF) gene within a QTL region

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showing to be a potential regulator of seed coat color variation of amaranth grain (Stetter et al. 2020). TFs have also been related in different amaranth studies as the most promising gene family involved in response to biotic and abiotic stresses (Palmeros-Suárez et al. 2021). Therefore, TFs are important candidates to increasing plant resistance to stresses through genetic engineering (Palmeros-Suárez et al. 2021). Genetic mapping is an important resource to gain further insight into the underlying genes for traits of economic importance. Thus, the knowledge of genetic diversity in amaranth breeding programs is essential, especially in the identification of the best parents to a generation of segregating population with genetic variability for introgression of desired traits in the development of high-yielding varieties of amaranth (Dharajiya et al. 2021). The use of genomic prediction could largely accelerate the genetic gain for nutritional traits and holds great potential for biofortification breeding in grain amaranth (Joshi et al. 2018).

4

Limitations of Conventional Breeding and Genetic Resources of Amaranth

A little number of amaranth cultivars with enhanced agricultural traits have been released so far (Schafleitner et al. 2022). The most successful amaranth variety implemented in the USA has been the Plainsman (Baltensperger et al. 1992), which is an improvement of A. hypochondriacus genotype, where the trait earliness was introduced (Joshi et al. 2018). However, there is still so much room for improvement of amaranth cultivars, especially if the “wild” genes from native species, which represents a diverse genetic resource, were more explored (Joshi et al. 2018). One of the challenges to the amaranth breeding program is the nature of amaranth flowers, which are numerous and self-pollinating, making the crossing processes difficult (Stetter et al. 2016). Stetter et al. (2016) evaluated different crossing methods within three amaranth grain species, where the highest success rate was obtained with the hand emasculation method (74%). It has been suggested that amaranth heterotic breeding across the grain cultivars could also be a good strategy for advanced breeding in amaranth (Joshi et al. 2018). Additionally, mutation breeding has shown great results in increasing the polygenic variability of four cultivars of amaranth (Joshi et al. 2018). Lysine content, among other traits, has been increased in amaranth species through mutational approaches (Joshi et al. 2018). Other traits that have been targeted for amaranth genetic breeding are plant height reduction, increased seed size, and adaptation to the mechanical harvesting (Joshi et al. 2018; Schafleitner et al. 2022; Stetter et al. 2016). Besides, improving the taste and nutritional quality of the leaves, rapid growth, and resistance to biotic and abiotic stresses are important targets to plant breeding programs (Schafleitner et al. 2022). Even though amaranth is very resistant to abiotic and biotic stresses, this trait should be kept in breeding pools to improve amaranth’s abundance and distribution (Joshi et al. 2018). The knowledge of the genetic diversity of

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Fig. 2 Improved crop design flowchart

Amaranthus species will provide information for creating superior cultivars in plant breeding programs (Joshi et al. 2018). Amaranth genetic traits and the current state of genetic breeding have been carefully reviewed by Joshi et al. (2018). Genetic resources, genotyping, and genomics are the core information to create superior genotypes through traditional breeding programs, genetic engineering, and genome editing (Fig. 2) (Joshi et al. 2018). This will lead to an increased use of amaranth as a main agricultural crop. The use of minor crops will increase agrobiodiversity and, therefore, favor food global security (Joshi et al. 2018). Although genomic prediction can accelerate the selection of grain with increased nutritional value, very few studies have been performed with Amaranthus so far (Joshi et al. 2018) as previously discussed. The available strategies for amaranth gene editing will be discussed in the next section.

5

Strategies for Amaranth Gene Editing

Gene editing is a great strategy for precise genome modifications in plants (Wada et al. 2020). The most advanced technologies for gene editing are zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 9 (CRISPR/Cas9) (Liang et al. 2014; Wada et al. 2020). CRISPR has many advantages when compared with ZFNs and TALENs, because it is simpler, while these other techniques require more complex constructs (Bortesi and Fischer 2015; Joshi et al. 2018; Liang et al. 2014). CRISPR allows using multiple targets for genetic improvement and therefore can aid in the creation of new crop varieties in an unprecedented way, by inducing double-strand breaks (DSBs) in DNA (Wolter et al. 2019). CRISPR is a powerful tool for genome editing and is generating exciting new possibilities to increase the genetic diversity of amaranth (Joshi et al. 2018). However, none of these genome editing techniques have been used with amaranth so far (Joshi et al. 2018), even though many other studies using reverse genetics have been published for this plant (Packard et al. 2021).

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Amaranth is a great candidate for gene editing since it has a vast repository of genomic data (Clouse et al. 2016; Délano-Frier et al. 2011; Lightfoot et al. 2017; Sunil et al. 2014), and protocols for regeneration using tissue culture are wellestablished for this plant (Adhikary et al. 2019; Joshi et al. 2018). In fact, the technology VIGS (virus-induced gene silencing) has been successfully used to study genes of betalain biosynthesis in amaranth (Adhikary et al. 2019). Adhikary et al. (2019) work established an efficient genetic transformation protocol that can be used for the improvement of genes involved with amaranth’s nutritional and medicinal properties, besides the yield (Joshi et al. 2018). That being said, it is very important to invest in the development of protocols for using the most varied gene editing techniques in amaranth. Another potential technology for amaranth genome editing is the nanotechnology-based genome editing system (Ahmar et al. 2021). This technology claims to be even more efficient, safe, and simpler than CRISPR (Ahmar et al. 2021). It is also possible that CRISPR/Cas9 nanotechnology coupled systems represent the most advanced technology available in gene editing (Naik et al. 2022). These techniques have not been employed in amaranth so far but could speed up the creation of improved varieties at a lower cost, by overcoming the challenges of traditional breeding methods (Ahmar et al. 2021). In conclusion, the production of varieties with high nutritional value and yields, and many times also resistant to biotic and/or abiotic stresses, would be an incredible mark for food safety and in the combat of malnourishment worldwide.

6

Brief Account on the Role of Bioinformatics as a Tool

For some years, biology and computer science were very connected. Therefore, a new field has emerged named bioinformatics, which is the science of managing, mining, integrating, and interpreting information from biological data from different levels of an organism. Given the complexity and exponential growth of biological data from omics projects, computational storage and analysis techniques have become increasingly demanded, to solve three main problems: efficient storage, information’s management, and extraction of relevant information from the data (Quintans et al. 2022). The last problem is one of the main challenges of computational biology and bioinformatics, which requires the development of tools/databases capable of transforming all this heterogeneous data into biological knowledge (Greene et al. 2014). These bioinformatic databases and tools go beyond a description of the data, by delivering new biological insights. It is almost impossible to carry out research in bioinformatics without using a database and bioinformatic tools to process and explore the vast collection of available data, both public and private. In this context, in this sections, we will describe databases of genes, genomes, gene expression, proteins, genome comparison tools, and the integration of other different types of data from plants of the amaranth genus that allow increasing knowledge about the system biology of these plants, providing nutritive and weed

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resistance biotechnological advances. Furthermore, the amaranth genome study will underpin the research of this orphan crop and accelerate the development of improved varieties.

6.1

Amaranth Genome Sequencing

To date, a few amaranth genomes have been published, such as A. hypochondriacus (Clouse et al. 2016; Sunil et al. 2014) and A. cruentus (Clouse et al. 2016; Ma et al. 2021) of grain species and A. tuberculatus, A. hybridus, and A. palmeri (Montgomery et al. 2020) of weed species. Table 3 summarizes the genomic information of amaranth, such as haploid chromosome number, total genome length (Mb), and the GC content. A. hypochondriacus genome was sequenced in 2014 (Sunil et al. 2014) representing the first C4 dicot genome and the first grain species from Caryophyllales. A. hypochondriacus is an interesting species for its C4 metabolism, being capable of tolerating many adverse conditions, such as drought, and still producing highly nutritious seeds (NCBI Resource Coordinators 2016; Sunil et al. 2014). A. hypochondriacus genome encodes at least 24,829 proteins (Sunil et al. 2014). However, only 112 gene results are displayed after a search at NCBI, when the query “Amaranthus hypochondriacus” is used in the “Gene” category (NCBI Resource Coordinators 2016, Access 24 June, 2022). Likewise, a high-quality draft of A. hypochondriacus L. genome (N50 of 371 kb) was obtained by Clouse et al. (2016) using whole-genome sequencing (WGS) and transcriptome sequencing (TS). The assembled genome presented 377 Mb, being rich in repetitive sequences (48% of the sequences), including many retrotransposons (Clouse et al. 2016). In this study 23,059 protein-coding genes were identified (Clouse et al. 2016) corroborating with Sunil et al. (2014). Clouse et al. (2016) also acknowledged that A. hybridus is the progenitor species of the grain amaranth. Table 3 Summary of information about the genomes of Amaranthus species: haploid chromosome, total length (Mb) of genome, and GC content

Amaranthus Amaranthus hypochondriacus hypochondriacus (Clouse et al. (Sunil et al. 2014) 2016) 16 16

Haploid chromosomes Total length 417.46 (Mb) GC% 34.5087

377 34.7

Amaranthus tuberculatus (submitted by the University of Illinois) 16

Amaranthus palmeri (submitted by Clemson University) 17

Amaranthus cruentus (Ma et al. 2021) 17

572.9

395.293

370.914

35

33.45

33.0875

Source: (CABI 2022; Clouse et al. 2016; Ma et al. 2021; Montgomery et al. 2020; Sunil et al. 2014)

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Furthermore, a genome draft of three Amaranthus weed species of agricultural importance was published in 2020: A. tuberculatus, A. hybridus, and A. palmeri (Montgomery et al. 2020). Montegomery and collaborators (2020) obtained the most contiguous draft assemblies for these amaranth weeds, including the very first genome assembled for A. hybridus, by combining several sequencing approaches, such as long-read sequencing and chromatin mapping (Montgomery et al. 2020). The study of the weed’s genome will aid in a better understanding of herbicide’s resistance evolution, which is essential for weed’s management (Montgomery et al. 2020). In 2021, another amaranth grain species, A. cruentus, had its genome sequenced (Ma et al. 2021). A. cruentus genome (370.914 Mb and 33.0875% of GC content) was sequenced using short-read, long-read, and phased sequencing technologies by the University of York (Ma et al. 2021). However, A. cruentus lacks details regarding the genome annotation, and also, there is no gene associated with this species in NCBI (Ma et al. 2021; NCBI Resource Coordinators 2016). Currently, the NCBI holds 1109 plant genomes and 476,498 plant genes, of which 518 are from Amaranthus species (NCBI Resource Coordinators 2016, Access 31 March, 2022). There are four species of Amaranthus with their whole genomes sequenced and available at the NCBI, namely, A. hypochondriacus, A. tuberculatus, A. palmeri, and A. cruentus (NCBI Resource Coordinators 2016, Access 31 March, 2022). The amaranth genome sequencing supplies a reference genome for transcriptomic and proteomic studies, besides being valuable for evolutionary insights of Amaranthus genus, the Caryophyllales order, and, ultimately, angiosperms in general (Sunil et al. 2014; Adhikari et al. 2021). This knowledge will be useful for the rational design of amaranth crops, with increased productivity and quality traits (Ma et al. 2021).

6.2

Amaranth Sequences Among the Gene and Genome Databases

Genomic databases are DNA sequence repositories from many different species of plants and animals. The National Center for Biotechnology Information (NCBI), for instance, is one of the most important biological databases and stores genes from different organisms in domains of life (NCBI Resource Coordinators 2016). There are many types of databases according to the biological data, such as genomic databases (DNA sequences), transcriptomic databases (RNA sequences), proteomic databases (protein sequences), and structure databases (mainly protein structures). There are also more specific databases, such as Metabolic and Signaling Pathways, Diseases Databases, Gene Expression Databases, Plant Databases, and Taxonomic Databases. Each of them includes a specificity, and some can integrate a variety of database functions (Quintans et al. 2022). These databases offer information on the sequences and can be created for specific organisms, such as animals and plants. For instance, the AmaranthGDB (Gonçalves-Dias and Stetter 2021) is a genetics and genomic database specific to the genus Amaranthus.

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6.2.1 AmaranthGDB AmaranthGDB is a database with genetic and genomic information on amaranth and tools to accelerate amaranth research (Gonçalves-Dias and Stetter 2021). One of the available tools is the PopAmaranth, which is a genetic browser that combines amaranth genomic data and genome-wide population (Gonçalves-Dias and Stetter 2021). The information is easily retrieved and may be used to identify target genes by the researcher (Gonçalves-Dias and Stetter 2021). Regarding improving the nutritional value of amaranth, some genetic features have been pinpointed as putative targets, such as genes that participate in the synthesis of phytic acid (which is an antinutrient), gene families of ion transporters, and biosynthetic gene clusters within amaranth line (Gonçalves-Dias and Stetter 2021).

6.2.2 Amaranth and Gene Expression Databases The genomic projects have been adding expressive data to the current databases, as we previously discussed. Although genomic data are important, the identification of genes linked to important agronomic traits requires gene function analysis, which is why Gene Expression Databases, such as Gene Expression Omnibus (GEO), are essential (Edgar et al. 2002). However, GEO, which is a nonspecific database, does not hold any data from amaranth species (Edgar et al. 2002; Accessed 12 April, 2022). There are plant-specific gene expression databases: DRASTIC (Button et al. 2006), PLANEX (Yim et al. 2013), and PLEXdb (Dash et al. 2012); however, no data is available for the Amaranthus genus. These databases hold data of genes regulated in response to abiotic and biotic stresses, as well genes important to the phytopathogens (Dash et al. 2012; Yim et al. 2013). Although there is no data on amaranth in the gene expression databases, some authors have carried out research on the subject. Délano-Frier et al. (2011) were pioneers in attempting to increase the limited transcriptomic information on amaranth, a highly nutritious and stress-tolerant crop. Briefly, they performed large-scale transcriptome analysis from different tissues (leaves and stems) of A. hypochondriacus, in response to several biotic (herbivory and bacterial infection) and abiotic stresses (water and salt stresses), using 454 pyrosequencing (Délano-Frier et al. 2011). The comparative transcriptome analyses returned 8260 homologous sequences between A. tuberculatus and A. hypochondriacus transcriptomes, and 1971 DEG were identified in response to at least 1 of the treatments applied (Délano-Frier et al. 2011). This study greatly contributed to underpin the multiple stress resistance in plants, a desired trait for plant biotechnology (Délano-Frier et al. 2011). The lack of expression data on amaranth in the main databases reinforces the need of increasing functional gene analysis research of this crop, with transcriptomic experiments, such as RNA-seq, with different tissues and conditions. The increasing amount of data is not the only limiting factor to improve the knowledge on amaranth gene expression: the data integration is likewise important, facilitating research. This knowledge will be useful to reveal genes and mechanisms related to agronomic traits of interest, such as increased nutritional value and resistant varieties.

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6.2.3 Amaranth and Protein Databases In addition, transcriptomic information, proteomic data, and metabolomic data are crucial for understanding how plants function. The information necessary to create new amaranth varieties with desirable nutritional traits is directly related to functional omics data. Therefore, the UniProt (Universal Protein Resource) (The UniProt Consortium 2018) is the main curated database of annotated protein sequences. There are 2090 protein records on UniProt related to Amaranthus genus, in which only 23 were curated, and are now available on Swiss-Prot (The UniProt Consortium 2018; Accessed 5 April, 2022). Rodríguez et al. reviewed the amaranth potential bioactive proteins from the UniProt database with potential to prevent chronic diseases (Montoya-Rodríguez et al. 2015). In addition, protein 3D structures are very important to design food of high nutrition and benefits for health. The Protein Data Bank (PDB) archive is the only repository for protein (Altschul et al. 1997). A quick search in PDB using the term “viridiplantae” returns 7165 structures (Altschul et al. 1997, Accessed 24 June, 2022). Of those, 17 protein structures seem to be related to the Amaranthus genus (when the term “Amaranthus” was searched) (Altschul et al. 1997, Accessed 24 June, 2022). However, five of the retrieved matches were from heterologous expression systems, mainly Zea mays (Altschul et al. 1997, Accessed 24 June, 2022). Another option to increase amaranth 3D structures and function is using protein modeling tools, molecular dynamics, and molecular docking (Rasheed et al. 2020). Although bioinformatics is a growing science, only 9% of the structures from RSCB PDB (Research Collaboratory for Structural Bioinformatics Protein Data Bank) are from plants (Rasheed et al. 2020). Rasheed et al. (2020) claimed that the elucidation of seed storage protein structure and function is crucial to plant applications in the food industry. However, few studies regarding the structure of storage proteins have been performed. Therefore, amaranth structure prediction using bioinformatics might lead to the prediction of targets for enhancing the nutritional value of this plant (Rasheed et al. 2020). Increasing proteomics research is of great importance to elucidate proteins with economic importance for this plant. For instance, the effect of an A. cruentus peptidome fraction on enzymes involved in the cholesterol biosynthesis was studied by Soares et al. (2015). This study showed that very small peptides (under 3 kDa) from amaranth might be involved in the hypocholesterolemic effect of this grain (Soares et al. 2015). These results show the importance of proteomics and peptidome’s studies of amaranth to identify bioactive peptides with importance to health and nutrition. In conclusion, with the arising data from HT NGS (high-throughput next-generation sequencing), several specific databases for genomic, transcriptomic, and proteomic data have been created, as we previously stated. However, the data is scattered across the platforms in many different formats, making it difficult to mine innovative knowledge. Integrative bioinformatics attempts to solve this problem by unifying this biological data (Quintans et al. 2022).

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Amaranth and Comparative Genomics

Another powerful resource to analyze data from next-generation sequencing (NGS) is the Comparative Genome Databases (GGD) such as CoGe (Lyons and Freeling 2008) and Phytozome (Goodstein et al. 2012), which we will further discuss.

6.3.1 CoGe The CoGe (Comparative Genomics research) holds data from 21,016 organisms and 56,091 genomes, where 23 genomes are from 4 species of the Amaranthus genus: A. hybridus, A. hypochondriacus, A. palmeri, and A. tuberculatus (Lyons and Freeling 2008; Accessed in June 24, 2022). The tools available for the comparative genome analyses at CoGe are CoGeBlast (Lyons et al. 2008), which performs an alignment of a query sequence with other genomes; SynMap (Haug-Baltzell et al. 2017), which identifies syntenic regions between genomic sequences from two organisms and creates a dotplot; SynMap3D, which plots the results from synteny analyses, from up to three genomes, in 3D (Haug-Baltzell et al. 2017); the SynFind tool, which identifies syntenic regions in whichever set of genomes; and GEvo, which is a genomic evolutionary tool analysis. Additionally, genomic features can be analyzed and visualized with tools such as FeatView and LoadExp+ (Grover et al. 2017; Lyons and Freeling 2008). For instance, SynMap4.2 (Haug-Baltzell et al. 2017) has been used to infer synteny analysis between A. hypochondriacus, B. vulgaris (Ref Beet-1.1), and Arabidopsis thaliana (genome assembly TAIR10) revealing insights about amaranth evolution, such as the events of polyploidization, and a high correlation with other members of Amaranthaceae family (B. vulgaris) (Clouse et al. 2016; Lightfoot et al. 2017). Montgomery and collaborators (2020) also inferred evolution events (such as genomic duplication and translocation) among amaranth genomes by the comparison of Amaranthus tuberculatus, Amaranthus hybridus, and Amaranthus palmeri with Amaranthus hypochondriacus, using Sinmap2 (Haug-Baltzell et al. 2017). Besides, the genetic mapping performed in this study was used to authenticate the quality of the scaffolds and revealed a need to use different methods in order to obtain a higher quality genomic assembly for A. tuberculatus (Montgomery et al. 2020). Regarding the genomic composition, Sunil et al. (2014) used the SinMaP to compare amaranth genome with other plants, such as S. lycopersicum, V. vinifera, and A. thaliana, and found that A. hypochondriacus A-T (66%) content is very comparable within the studied plants, revealing common genomic features. Transcriptomic comparative analyses are also possible using CoGe tools (Grover et al. 2017). For instance, the tools available are tRNAView, which searches for tRNAs in genomes or a given genomic sequence; the MatrixView which creates a dotPlot between two genomes and may be used to analyze genomic duplications (Nguyen et al. 2019); QuotaAlign, which analyzes and screens for whole syntenic blocks, based on expected coverage; GenomeMap, which is a visual map of the distribution of genomic features in the genome; GenomeView, which is a CoGe’s

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interactive genome browser (also known as EPIC-CoGe); and CodeOn, which is a tool for generating an amino acid usage table binned by the C-G content of each CDS (Grover et al. 2017). Regarding amaranth comparative transcriptome analysis, using SynMap (Haug-Baltzell et al. 2017), Sunil et al. (2014) have found that amaranth transcriptome is also rich in A-T content, which is also very comparable to other plant transcriptomes. The degree of synteny among genomes can also be used to infer the nutritional quality of plants, by revealing genomic features of interest (Ma et al. 2021).

6.3.2 Phytozome There are databases and tools for comparing genes and genomes specific to plants, such as the Phytozome (Goodstein et al. 2012). Phytozome includes several genomic sequences from selected algae to land plants, allowing the researcher to infer their evolutionary stories from a molecular level (Goodstein et al. 2012). Phytozome v13 (Goodstein et al. 2012) holds 274 assembled and annotated genomes, where only the A. hypochondriacusv2.1 genome is available for the Amaranthus genus, with an estimated size of 466 Mb (Clouse et al. 2016; Lightfoot et al. 2017). This database is very useful to easily retrieve gene sequences from A. hypochondriacus that will support research with this plant. Beyond the dataset, Phytozome provides several tools to analyze and compare amaranth genome with others species, such as BLAST (a search tool based on sequence similarity) (Altschul et al. 1997), JBrowse (a web-tool for genome visualization and analysis) (Buels et al. 2016), and PhytoMine, which is an interface to visualize data from Phytozome.

7

Conclusion and Prospects

This work presented the recent advancement in amaranth research focusing on the genetic resources that can be leveraged to improve the crop. After decades of neglect, the crop was redomesticated and brought to the attention of farmers and researchers. Despite its exceptional nutritional quality, medicinal and industrial uses, climate resiliency, and ability to thrive in a broad range of climatic zones, the crop is still underutilized. Since the pioneering work of Jonathan Sauer in the 1950s, there has been slow progression in the development of taxonomic, biological, and molecular information on the crop. In recent years, reference genome and transcriptome information are developed, and several genes related to biotic and abiotic stresses, growth, and development were identified. Reverse genetics tools such as VIGs were developed for amaranths; however, there is still a lack of functional genomics work; therefore, numerous putative genes with potentially important agricultural traits are not functionally validated. Molecular breeding efforts especially utilizing multiomics approaches are lacking. Most of the genomics and transcriptomics work involve domesticated species; there is also a need for high-quality “omics” information comparing wild-type, cultivated, and weedy amaranths; DNA fingerprints from the comparative studies aid not only in the discovery of genes and QTLs that are agronomically useful but also in high-throughput genotyping and understanding of

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the complexity that exists in the Amaranthus genus. Taken together, all this omics information helps in the molecular improvement of the crop, which can add nutritional value to the agricultural systems for our future generations.

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Cucumber (Cucumis sativus L.): Genetic Improvement for Nutraceutical Traits Ashutosh Rai, Vishal Chugh, and Sudhakar Pandey

Contents 1 2 3 4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cucumber for Culinary Purposes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Cosmetic Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nutraceuticals and Therapeutic Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Antioxidant Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Antimicrobial Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Wound-Healing Activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Genome Structure and Fruit Quality-Related Genes in Cucumber . . . . . . . . . . . . . . . . . . . . . . 6 Biosynthesis of Phytochemicals in Cucumber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Transcriptional Control of Bitterness in Cucumber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Cucumber Genome-Wide Delineation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Transcriptome Analysis in Cucumber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Mapping of Fruit Quality-Related Quantitative Trait Loci (QTLs) . . . . . . . . . . . . . . . . . . . . . . 11 Metabolic Pathway Studies for Quality Traits in Cucumber . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Conclusion and Future Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Among the cucurbits, cucumber (Cucumis sativus L.) is a valuable vegetable crop cultivated for its immature fruits. The cucumber is one of the oldest cultivated vegetable crops. It has been known in history for over 5,000 years and probably originated in India. A lot of diversity exists with respect to shape, size, and color of the fruits which contain 0.4% protein, 2.5% carbohydrates, 1.5 mg iron, and 2 mg of vitamin C per 100 g of fresh weight. Fruits are good for

A. Rai · V. Chugh College of Horticulture, Banda University of Agriculture and Technology, Banda, India e-mail: [email protected]; [email protected] S. Pandey (*) ICAR-Indian Institute of Vegetable Research, Varanasi, India © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_57

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people suffering from constipation, jaundice, and indigestion. The quality of cucumber depends on its total soluble solids, fruit firmness, desired fruit size, and other phytochemicals like antioxidant capacity, phenols, and vitamin C content. As Ayurvedic and conventional remedy, cucumber is used for various skin-related problems, including inflammation under the eyes, and sunburn, and is assumed to have cooling, curative, comforting, emollient, lenitive, antiitching effect to irritated skin, and extended cosmetic effects. Due to the presence of numerous active constituents distributed throughout the plant parts, including vitamins, minerals, amino acids, phytosterols, phenolic acids, fatty acids, and curcurbitacin, cucumber exhibits a variety of pharmacological properties. Cucumber fruit that have an orange colored endocarp or mesocarp have high β-carotene content. Carotenoids play vital roles in human nutrition as potent precursor for various vitamins for biosynthetic pathways. Cucurbitacins, the bitter triterpenoid compounds found in cucurbits, are toxic to most of the organisms but are able to attract specialized insects. The expression of cucrbitacin depends on a Mendelian gene known as “Bi.” The enzyme oxidosqualene cyclase (OSC) catalyzes the biosynthesis of responsible triterpene carbon skeleton in fruits and plants. An oxidosqualene cyclase (OSC) gene in squash (Cucurbita pepo L.) known as cucurbitadienol synthase (CPQ) is the first enzyme of biosynthetic pathway of cucurbitacin. The mapping of fruit quality-related quantitative trait loci and metabolic pathway studies are enabling researchers to enhance quality traits. Keywords

Cucumber · Nutraceuticals · Cosmetic · Antimicrobial activity · Fruit quality

1

Introduction

Among the cucurbits, cucumber (Cucumis sativus L.) is A valuable vegetable crop cultivated for its immature fruits and is one of the oldest cultivated vegetable crops. It has been known in history for over 5,000 years and probably originated in India (Whitaker & Davis 1962). Cucumber was domesticated about 3000 years ago; total cultivated area under cucumber and gherkins is 26,500 ha with 168,000 tones production and 7.5 t/ha productivity in India (FAOSTAT 2018). It is considered as an important salad crop grown both in north and lower as well as higher hills in India (Pandey & Kujur 2022) (Fig. 1). A lot of diversity exists with respect to shape, size, and color of the fruits which contains 0.4% protein, 2.5% carbohydrates, 1.5 mg iron, and 2 mg of vitamin C per 100 g of fresh weight (Pandey et al. 2018). Fruits are good for people suffering from constipation, jaundice, and indigestion. The quality of cucumber depends on its total soluble solids, fruit firmness, desired fruit size, and other phytochemicals like antioxidant capacity, phenols, and vitamin C content.

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Fig. 1 Diverse sectors and uses of cucumber

2

Cucumber for Culinary Purposes

Most of the human diseases like cancer, inflammation, heart-related disease, diabetes, and autoimmune diseases as well as neurodegenerative diseases which affect neurotransmitter levels resulting various mental disorders are resultant of oxidative stress or disturbance in the cellular redox balance. The cell proliferation is promoted with more oxidizing conditions. Diet plays a crucial role including various phytochemicals maintaining human health. Cucumber is rich in water content and very low in calories. Cucumber is considered as vegetable crop rich in phytochemicals and polyphenolics. Major groups of dietary antioxidants-phytochemicals found in cucumber are vitamin C (ascorbic acid), folic acid, phenolic compounds (phenolic acids such as cinnamic acid and polyphenols such as flavonoids), and Phytocassane D; Cucurbitacin E; Cucurbitacin I; Nomilin; terpenes such as Limonin; and isoprenoids (vitamin E tocopherols and carotenoids). The exocarp of cucumber is also a rich source of different minerals such as calcium, magnesium, iron, potassium, phosphorus, sodium, manganese, zinc, and sulfur. These amino acids are also found in cucumber in their higher to lover concentrations as glutamine, oxoproline, alanine, glycine, citrulline, leucine, isoleucine, valine, tyrosine, serine, glutamic acid, gaba, aspartic acid, proline, phenylalanine, threonine, histidine, ornithine, lysine, methionine, 4-aminobutyric acid, beta-alanine, and homoserine (Zhao et al. 2016). The seeds of cucumber also contain

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considerable quantity of minerals having mainly magnesium (8.5%), calcium (2.0%), manganese (66.3 ppm), sodium (79.4 ppm), and iron (21.4 ppm) with small quantity of zinc (11.7 ppm), copper (3.3 ppm), and potassium (5.1%) (Abiodun and Adeleke 2010). Cucumber is well known for its anticarcinogenic, antioxidant, antielastase, antihyaluronidase, hypolipidemic, antihyperglycemic, anti-inflammatory, diuretic, antimicrobial, amylolytic, and analgesic properties. With strong nutty flavor, cucumber seeds are used as dry fruit as well as to extract oil. Seed kernel of C. sativus contains proteins like globulins, albumins, and glyoxysomal enzymes in peroxisomes such as isocitrate lyase, malate synthase, citrate synthase, malate dehydrogenase, crotonase, and catalase (Köller et al. 1979). Tender and fresh fruits of cucumber are consumed as salads and desserts and as cooked vegetables known as slicers, were as it is also preferred as preserved in form of pickles from cultivars know as picklers. The whitish to greenish mesocarp of cultivated cucumber has been of culinary importance for consumer preference worldwide. Diverse types of cucumber are commercially grown worldwide, together with American food processing and fresh market industries, Oriental trellis (burpless) varieties, European gherkin and glasshouse variety, the Mideast Beit Alpha type, and the German Schalgurken (Staub et al. 2008). Tender fruits of particular small-fruited cultivars known as ‘gherkin’ are most excellently used pickled in vinegar. Cucumber fruits are also preserved in high concentration of salt. Cucumber in Korea as Oi sobagi kimchi and oiji as pickled, whereas in Egypt, brine soaking is common, known as torshi khiar. In many Asian countries, the seed kernels are dehusked and used in confectionary. The oil extracted from cucumber seeds is used for salad dressing in French cooking (Lim 2012).

3

Cosmetic Properties

As ayurvedic and conventional remedy, cucumber is used for various skin-related problems, including inflammation under the eyes and sunburn, and is assumed to have cooling, curative, comforting, emollient, lenitive, anti-itching effect on irritated skin, and extended cosmetic effects (Sotiroudis et al. 2010). Cucumber fruits are extensively used as skin-cleansing agent and are an integral part of various skin-whiteningand -softening-related cosmetic formulations. In addition, the cucumber fruit juice is utilized for a number of cosmetic formulations (Grieve 1998; Chiej 1984).

4

Nutraceuticals and Therapeutic Properties

Due to the presence of numerous active constituents distributed throughout the plant parts, including vitamins, minerals, amino acids, phytosterols, phenolic acids, fatty acids, and curcurbitacin, cucumber exhibits a variety of pharmacological properties. Cucumber fruit that have an orange-colored endocarp or mesocarp have high β-carotene content. Carotenoids play vital roles in human nutrition as potent precursor for various vitamins for biosynthetic pathways.

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Antioxidant Activity

The cucumber fruit and seeds contain various antioxidants and secondary metabolites such as terpenoids, flavonoids, cardiac glycoside, tannins, phenols, and abundance of carbohydrates. The sturdy antioxidant activity and phytochemical analysis of ethanolic seeds extracts of cucumber have been performed by various workers (Begum et al. 2018). Methanolic extracts of cucumber pulp have also been reported to show powerful antioxidant activity through DPPH assay owing to its high amount of phenolics (Sotiroudis et al. 2010). Agarwal et al. (2012) reported good antioxidant activity in the aqueous solvent extracts from peel of the cucumber based on phospho molybdenum assay and established that this activity is due to the polyphenols content. In another study, cucumber fruit extract was tested for its ability to scavenge free radicals and functions as an analgesic. The extract was tested for analgesic effects at doses of 250 and 500 mg/kg and in vitro antioxidant investigations at 250 and 500 g/ml, respectively. Ascorbic acid and BHA (butylated hydroxyl anisole) were tested for their ability to scavenge free radicals, whereas diclofenac sodium (50 mg/kg) was used to examine their analgesic effects. The greatest antioxidant and analgesic effects of the cucumber fruit extract were observed at 500 g/ml and 500 mg/kg, respectively. According to early phytochemical screening, the extract contains flavonoids and tannins, which may be the cause of the analgesic and free radical-scavenging properties (Kumar et al. 2010).

4.2

Antimicrobial Activity

Three antimicrobial sphingolipids, first (2S,3S,4R,10E)-2-[(20 R)-2-hydroxy-tetracosanoyl amino]-1,3,4-octadecanetriol-10-ene, second 1-O-β-D-glucopyranosyl, and third soyacerebroside-I, have been identified in crude methanolic homogenate of cucumber stems. Cucumber extract exhibited antifungal and antibacterial activity against microorganisms, including four fungal and three bacterial species (Tang et al. 2010). Antimicrobial activity in the ethanolic extracts of seeds of cucumber has also been reported against Staphylococcus aureus, Salmonella typhi, Acremonium, Verticellium, Pythium, and Tricoderma spp. using disc diffusion assay (Begum et al. 2018). Antimicrobial activity against six Gram negative and Gram positive bacterial strains have been reported along with three human-pathogen fungi (Candida albicans, C. tropicalis, and C. glabrata) in methanolic and dichloromethane extracts of the fleshy pericarp and the exocarp of cucumber fruit (Sotiroudis et al. 2010).

4.3

Wound-Healing Activity

The aqueous extract cream formulation containing soft white paraffin as base in 2.5%, 5%, and 10% w/w of cucumber fruit have been reported for its ameliorative effects on 300 mm wide and 2 mm deep wounds in rats (Patil et al. 2011). Significant

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Table 1 Nutraceutical compounds in different plant parts of cucumber and their use Parts of plant Fruit

Seed oil Kernel of fruit Pericarp of fruit Gum of bark

Therapeutic and medicinal uses Astringents, bronchitis, hepatitis, dyspepsia, diarrhea, piles, cough hoarseness of voice, asthma, and eye diseases Skin care properties like soothing, moisturizing, and protection from UV rays Rheumatism, narcotic, and purgative action Dropsy, dysenteric-diarrhea, piles, and leprosy Demulcent, purgative

Reference Mallik et al. (2013), Sahu and Sahu (2015) Abiodun and Adeleke (2010) Campbell (2008), Mallik et al. (2013) Gopalakrishnan et al. (2014), Sahu and Sahu (2015) Arya et al. (2012), Mallik et al. (2013), Sahu and Sahu (2015)

decrease of P < 0.05, P < 0.001, and P < 0.001 was observed for wound area, epithelization period, and scar width, respectively. The faster wound contraction compared with control samples indicated that cucumber’s wound-healing abilities are attributable to its antioxidant and scavenging properties due to various flavanoids and secondary metabolites. Phytofabrication has been achieved and found significantly wound healing potential in rat model. The ointment was obtained by encapsulated metallic silver-encapsulated bioactive molecules in metallic silver nanoparticles using callus (CAgNPs) and leaf extracts (LEAgNPs) of cucumber (Venkatachalam et al. 2015) (Table 1).

5

Genome Structure and Fruit Quality-Related Genes in Cucumber

Cucumis hystrix Chakr. is a wild species native to Asia whose fruits possess a flavor typical of cultivated cucumber (Chen et al. 1994). Although the literature indicates that C. hystrix is 2n ¼ 2x ¼ 14 (Dane 1991), no definitive cytogenetic analysis has been made of this species, and its taxonomic placement has been based entirely on morphological characteristics (Kirkbride 1993). Isozyme analysis of C. hystrix, C. sativus, and C. melo led to the theory that a triangular phylogenetic relationship exists among these species (Chen et al. 1995). Cucumis, a genus of twining, tendril-bearing plants in the family Cucurbitaceae, can be divided into two designated subgenera as Cucumis (2n ¼ 2x ¼ 14 and 24) and Melo (2n ¼ 2x ¼ 24) forming five number of cross-sterile species groups (Jeffrey, 1980). Furthermore, the subgenus Cucumis has been separated as Sino-Himalayan species, including C. sativus (2n ¼ 2x ¼ 14) and C. hystrix Chakr. (2n ¼ 2x ¼ 24). C. sativus is the most commercially utilized group including var. sativus, the cultivated cucumber, and the wild, naturally occurring var. hardwickii (R.) Alef. (Kirkbride 1993).

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Biosynthesis of Phytochemicals in Cucumber

Cucurbitacins, the bitter triterpenoid compounds found in cucurbits, are toxic to most of the organisms but are able to attract specialized insects. The expression of cucrbitacin depends on a Mendelian gene known as “Bi.” The enzyme oxidosqualene cyclase (OSC) catalyzes the biosynthesis of responsible triterpene carbon skeleton in fruits and plants. An oxidosqualene cyclase (OSC) gene in squash (Cucurbita pepo L.) known as cucurbitadienol synthase (CPQ) is the first enzyme of the biosynthetic pathway of cucurbitacin (Shibuya et al. 2004). Four oxidosqualene cyclase genes have been previously identified responsible for cucurbitacin synthesis; the ortholog of CPQ, Csa008595, has been recognized in cucumber which resides in a genetic interval that defines the Bi gene. It was also deduced that Csa008595 constitutes a cluster of genes, which include one acyltransferase-encoding gene (Csa008594) and two cytochrome P450–encoding genes (Csa008596 and Csa008597) (Huang et al. 2009). Authors have also reported that abovementioned three genes (Csa008594, Csa008595, and Csa008597) are expressed simultaneously strongly in cucumber leaf tissue in a similar fashion to that of the operon like gene cluster involved in thalianol biosynthesis in Arabidopsis (Field and Osbourn 2008). This gene set may consequently catalyze the stepwise formation of cucurbitacin in cucumber. Cucumber is considered as model system for studying sex expression in plants. Ethylene promotes the femaleness and is thought as the sex hormone of the cucumber (Rudich et al. 1972). Huang et al. (2009) also reported 137 genes in cucumber related to ethylene biosynthetic and signaling pathways. A crucial regulating enzyme in the ethylene biosynthesis pathway is 1-aminocyclopropane-1-carboxylate synthase (ACS), which is encoded by the melon gene Cm-ACS7 (Boualem et al. 2008) and its cucumber ortholog Cs-ACS2, respectively (Boualem et al. 2008). Both the genes are essential for the development of the female flower and the suppression of male organ development. The Cm-ACS7 and Cs-ACS2 transcripts exclusively accumulate in the pistil and ovule, according to in situ mRNA hybridization assays, while its Arabidopsis ortholog, AT4G26200, is only expressed in the roots (Yamagami et al. 2003). These results suggest that the acquisition of novel cis regions of the ACS genes may have contributed to the evolution of unisexual flowers in cucurbits. A 454 pyrosequencing analysis of 359,105 expressed sequence tag (EST) sequences from near-isogenic unisexual and bisexual flower buds revealed that six auxin-related genes and three shortchain dehydrogenase or reductase genes are more highly expressed in unisexual flowers (Huang et al. 2009).

7

Transcriptional Control of Bitterness in Cucumber

Regulation of bitterness has been well studied in cucumber. Two transcription factors, responsible for bitterness in fruits and leaves, have been identified by Shang et al. (2014). The bitterness-related loci, which have already been reported, have Bitter (Bi) and Bitter fruit (Bt) genes that regulated bitterness basically due to

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Cucurbitacin C (CuC) in cucumber and related plants. Cucumber genome variation map has been drawn by use of association analysis. An oxidosqualen cyclase gene (Csa6G088690) was identified known as cucumber Bi gene. To elucidate further, researchers made an ethylmethane sulfonate (EMS)-based mutation-induced library and screened for nonbitter leaves in large number of plants. On sequencing two mutant plants, a single nucleotide polymorphism (SNP) in gene Csa5G156220 was obtained, which encodes a transcription factor expressed exclusively in leaves. This gene was renamed as Bitter leaf (Bl), and that actually regulated the expression of Bi gene. A total of 11 variants in homolog of Bl (Csa5G157230) were found associated with extreme bitterness via local association analysis. The cosegregation with Bt gene was observed in F2 population suggesting that it should be Bt gene. It was well established by several workers that the expression of Bi gene is regulated by Bt gene. A total nine genes have been identified downstream of Bl and Bt for the biosynthetic pathway for CuC via RNA-interference system.

8

Cucumber Genome-Wide Delineation

Cucumber genome (Huang et al. 2009), melon genome (Garcia-Mas et al. 2012), and multiple other Cucurbitacae genomes (Guo et al. 2020; Kim et al. 2016) have been analyzed and published that elucidated various aspects of genome architecture and functions. The sequence information have opened the doors for various genome-wide expression analysis and identification of gene families and functional characterization at genome scale. As cucumber was the first released genome among cucurbits, all the focus for identification and characterization of gene families was on cucumber. Most of the transcription factors with structural and functional genes were well-described by various studies in cucumber; their transcriptional expression has been instigated under adverse climatic conditions like high salinity, high and low temperatures, hormonal disturbances, etc. in different tissues (roots, leaves, stems, flower buds, and fruits) at different developmental stages. The novel bioinformatic methods are minimizing sequencing errors offering a good-quality genome contiguity on manyfold less costs. The even resequencing of many crops is being done with magnifying exploration of the genome. Simple sequence repeats (SSRs) or microsatellites and other functional markers from cucumber, melon, watermelon, bitter gourd, and spine gourd have been identified (Blanca et al. 2011; Cavagnaro et al. 2010; Zhu et al. 2016; Shukla et al. 2015; Ameen et al. 2022). Other important genomic regions like long intergenic noncoding RNA (lincRNA) have also been identified in cucumber that are at least 200 nucleotide long intergenic transcripts (Hao et al. 2015). Intergenic transcripts encode linc RNAs associated predominantly with the euchromatic or gene-rich regions of the genome with ability to transcription termination and initiation mainly targeting miRNAs. The gene regulation and transcription factor gene activities are together governed by these regulatory repeats. These unique properties compel researchers for identification and characterization of these microsatellites and small RNAs in cucumber and other plant species (Fig. 2).

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Fig. 2 Some important quality-related traits and responsible genes

9

Transcriptome Analysis in Cucumber

The speedy advancement of high-throughput sequencing tools and genome assembly pipelines has made huge gene annotation information, which offers a prospect for functional studies of genes that are associated to vital traits. RNA-seq technology has made it easy to study various complex traits related to plant growth and development. The technique allows exploring and integrating various gene expression studies and novel gene identification studies. Sex determination, a complex process with many metabolic pathways (e.g., ethylene biosynthesis and other hormone-signaling pathways), is being studied in cucumber since long. These are confirming engagements of strong regulatory processes like ion homeostasis, cell wall synthesis, cytoskeleton modifications, ubiquitination, lipid and sugar metabolism, and gene expression mediated by transcription factors for sex differentiation. Comprehensive analysis of mRNA-Sequence data also enables to identify key genes influenced under various stresses in cucumber. With the aid of high-throughput technologies, it became easy to simultaneously discover and estimate abundance of RNA-Seq data. The novel technology has helped to search new genes as well as to study the transcriptomes. The RNA-Seq can be achieved with the help of algorithms that are not bound to use old annotations and are responsible for alternative transcription and splicing (Trapnell et al. 2010). Prior to this RNA-Seq technology, the experiments were mostly dependent on microarray platform with a limited number of genes plotted on the microarray slides/chips. The major limitation to the

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microarray technology is its inability to identify novel transcripts desired for the development of functional molecular marker. The new technologies like next-generation sequencing (NGS) have ramped the genomics, transcriptomics, and proteomics studies in cucurbits. The availability of cucumber genome has accelerated the molecular studies. The genetic data along with clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-based new genome editing techniques are flourishing. Simultaneously the advancement of breeding technologies and sequence-based marker system with genomic and bioinformatics-based tools are also contributing to genetic improvement of cucumber and related cucurbits. This extensive research will lead to better knowledge about cucumber genomics, and scientists will be able to change various traits according to the consumer needs. The sequence data exploration studies of two cucumber lines PI 308915 (compact vining) and PI 249561 (regular vining) resulted in a total of 200 genes expressed differently, and the SNPs and SSRs among two isogenic lines were also obtained. The protein coding genes were studied by comparison with different types of tissues (leaf, root, stem, female flower, male flower, tendril, ovary, expanded ovary under fertilization, expanded ovary unfertilized, and base part of tendril). The results were compared with previously available protein-coding gene set (Li et al. 2011; Huang et al. 2009). In the study, 8700 genes were found to be structural modifications, where 5300 genes were identified showing similarity with cucumber genome (Li et al. 2011). As per results of de novo transcriptome analysis, SSRs, single nucleotide variants (SNVs) and singly nucleotide molecular markers were useful for vegetable improvement. The construction of genetic map helps to conduct genetic studies of cucumber and related family of plants.

10

Mapping of Fruit Quality-Related Quantitative Trait Loci (QTLs)

The quantitative trait loci (QTLs) control a number of agronomic traits. When one or more sequence-based DNA markers are used in conjunction with an appropriate experimental method and statistical analysis, a quantitative trait locus (QTL) can be described as any region of the genome that is linked to the persistent variation for a trait phenotype in a pertinent reference population. It is determined by analyzing the associated molecular markers for these clusters of sequences governing QTLs for specific traits, helps breeders in genetic studies and Marker Assisted Selection. The ideal populations for QTL mapping are recombinant inbred lines (RILs), nearisogenic lines (NILs), or any segregating wide cross population. RILs and NILs are almost homozygous and have less environmental influences, which increase the accuracy of QTL detection. It is then possible to clone the gene underlying the QTL and use the detected markers in molecular breeding programs. Similar to a Mendelian hereditary characteristic, the QTLs controlling horticultural traits can be introduced into desirable parents by molecular marker assisted selection

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(MAS). Using the F3 population (GY14 x PI 432860), Wenzel et al. (1995) determined the QTLs for fruit length, fruit diameter, seed cavity size, and color. They noticed that several QTLs overlapped with fruit length and diameter as well as seed cavity size and fruit diameter. It was suggested that QTL overlapping is due to phenotypic positive correlation between fruit diameter and seed cavity size and negative correlation between fruit length and diameter. The QTLs for sex expression, the number of lateral branches, fruit weight, fruit length, and fruit diameter were examined by Serquen et al. (1997). Fruit diameter was discovered to be close to the QTLs for fruit weight, while QTLs underlying lateral branching and fruit diameter were shown to be in the same chromosomal area. Four QTLs (LOD > 3) for sex expression, four for multiple lateral branching, two for earliness, and two for fruit length were also detected. OP-AJ2-F (sex expression), de-OP-L18-2 and BC-403-OP-W7-2 (multiple lateral branching), BC-551-II and II-BC592 (fruit weight), and II-BC592, de-OP-L18-2, and BC551-II were the flanking markers linked to the QTLs (fruit length and diameter). Fazio et al. (2003) developed and studied 171 RILs using the phenotypes having unique alleles for gynoecious (F), determinate (de), standard-sized leaf, the monoecious, indeterminate, and little-leaf (ll) and found additional QTLs for multiple lateral branches, fruit form, and sex expression in addition to confirming the findings of Serquen et al. (1997). In cucurbits, MAS has been successfully demonstrated for phenotypic screening of the Fom-2 gene (Fusarium wilt disease resistance in melon)-associated markers and for multiple lateral branching (MLB) in cucumber (Wang et al. 2000; Burger et al. 2003; Fazio et al. 2003). The color of fruits is dependent on concentration and composition of some pigments, mainly flavonoids (especially anthocyanins and chalcones), carotenoids, and chlorophylls. Melon rinds contain a number of colors, e.g., green, orange, white, variegated, and yellow, and are striped too. It is well known that pigments like β-carotene accumulate to contribute orange color (Ma et al. 2022).

11

Metabolic Pathway Studies for Quality Traits in Cucumber

Metabolites are the final products of cell biological regulation process, and metabolomic analysis enables us investigate the relationship between biological processes and plant characteristic. The content of anthocyanins and flavonoids has crucial effect on fruit color and taste. The metabolome data combining with transcriptome profiling discovered genes involved in anthocyanins and flavonols synthesis, thus searching for useful information to illustrate phenomenon of different colors in cucumber fruits (Table 2).

12

Conclusion and Future Perspectives

The diversity in cucumber is mostly found due to simple genetic factors in association with various environmental factors constituting fruit quality, such as bitterness, fruit shape, skin color, spine color, presence or absence of warts and spines, and fruit firmness. Fruit firmness is a crucial factor that is influenced by the

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Table 2 Volatile compounds found in cucumber Functional group Alkaloids Anthocyanins

Carbohydrates

Coumarins

Flavone

Flavanone

Photochemical Hordenine; Piperidine; Isohemiphloin; Betaine; Trigonelline; and Aminophylline Peonidin O-hexoside; Rosinidin O-hexoside; Peonidin; Cyanidin O-syringic acid; Cyanidin O-acetylhexoside; Malvidin 3-O-galactoside; Malvidin 3-O-glucoside (Oenin); Pelargonidin; and Malvidin 3,5-diglucoside (Malvin) D()-Threose; Ribulose-5-phosphate; Glucosamine; 2-Deoxyribose 1-phosphate; D(+)-Melezitose O-rhamnoside; Glucarate O-Phosphoric acid; Trehalose 6-phosphate; D-(+)Sucrose; D(+)-Melezitose; Gluconic acid; D-(+)-Glucono1,5-lactone; (+)-Glucose; DL-Arabinose; L-Gulonic-γ-lactone; N-Acetyl-D-glucosamine; D-Glucose 6-phosphate; D-Sedoheptuiose 7-phosphate; D-Fructose 6-phosphate; and D-glucoronic acid N-sinapoyl hydroxycoumarin; O-Feruloyl 4-hydroxylcoumarin; 7-hydroxycoumarin-beta-rhamnoside; Scopoletin (7-Hydroxy5-methoxycoumarin); 4-Hydroxycoumarin; Esculetin (6,7-dihydroxycoumarin); 6-Methoxy-7,8-DihydroxyCoumarin; Psoralen; and Daphnetin Selgin 5-O-hexoside; Chrysoeriol 5-O-hexoside; Tricin 5-Oacetylglucoside; Selgin O-malonylhexoside; Tricetin O-malonylhexoside; Spinacetin; Syringetin 5-O-hexoside; Luteolin O-sinapoylhexoside; Chrysoeriol O-sinapoylhexoside; Chrysoeriol O-hexosyl-O-rutinoside; Chrysoeriol 7-Orutinoside; Chrysoeriol O-hexosyl-O-pentoside; Syringetin 7-Ohexoside; Chrysoeriol O-malonylhexoside; Tricin 5-O-hexosylO-hexoside; Tricin 7-O-hexosyl-O-hexoside; Tricin O-malonylhexoside; Tricin 7-O-feruloylhexoside; Tricin 7-Ohexoside; Tricin O-sinapoylhexoside; Tricin; Acetyl-eriodictyol O-hexoside; Acacetin O-acetyl hexoside; Chrysoeriol O-hexosyl-O-hexosyl-O-Glucuronic acid; Chrysoeriol O-acetylhexoside; Apigenin 7-O-glucoside (Cosmosiin); Chrysoeriol 7-O-hexoside; Tricin O-sinapic acid; Tricin O-saccharic acid; Tricin 5-O-hexoside; Tricin 5-O-rutinoside; Tricin di-O-hexoside; Tricin O-glucuronic acid; Luteolin; Apigenin 7-O-neohesperidoside (Rhoifolin); Chrysoeriol; Apigenin 7-rutinoside (Isorhoifolin); Baicalein (5,6,7-Trihydroxyflavone); Nobiletin; Tangeretin; Luteolin 7-O-glucoside (Cynaroside); Tricetin; and Butin Naringenin O-malonylhexoside; Eriodictyol O-malonylhexoside; Hesperetin O-malonylhexoside; Hesperetin 7-O-neohesperidoside (Neohesperidin); Naringenin 7-Oneohesperidoside (Naringin); Naringenin 7-O-glucoside (Prunin); Naringenin; Xanthohumol; Hesperetin 5-O-glucoside; 7-O-Methyleriodictyol; Hesperetin; Hesperetin 7-rutinoside (Hesperidin); Naringenin chalcone; Isosakuranetin-7neohesperidoside (Poncirin); Afzelechin (3,5,7,40 -Tetrahydroxyflavan); and Homoeriodictyol (continued)

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Table 2 (continued) Functional group Flavone C-glycosides

Flavonol

Flavone C-glycosides

Photochemical Naringenin C-hexoside; Apigenin C-glucoside; O-methylChrysoeriol 8-C-hexoside; C-hexosyl-chrysoeriol O-hexoside; Apigenin 6-C-hexosyl-8-C-hexosyl-O-hexoside; Hesperetin C-hexosyl-O-hexosyl-O-hexoside; 8-C-hexosylhesperetin O-hexoside; Chrysoeriol 6-C-hexoside 8-C-hexosideO-hexoside; 6-C-hexosyl chrysoeriol O-hexoside; C-hexosylapigenin O-feruloylhexoside-O-hexoside; 6-C-hexosylhesperetin O-hexoside; 8-C-hexosyl-luteolin O-pentoside; di-C, C-hexosyl-apigenin; 8-C-hexosyl-luteolin O-hexoside; 6-Chexosyl-apigenin O-sinapoylhexoside; 6-C-hexosyl-apigenin O-feruloylhexoside; 8-C-hexosyl-chrysoeriol O-feruloylhexoside; C-hexosyl-chrysoeriol O-sinapoylhexoside; 8-C-hexosyl-apigenin O-feruloylhexoside; C-hexosyl-apigenin O-p-coumaroylhexoside; 8-C-hexosyl chrysoeriol O-hexoside; Chrysoeriol 8-C-hexoside; 6-C-hexosyl-chrysoeriol O-feruloylhexoside; Eriodictyol C-hexoside; Luteolin C-hexoside; and Isovitexin MethylQuercetin O-hexoside; Kaempferide; Isorhamnetin O-hexoside; Isorhamnetin 5-O-hexoside; Quercetin 5-Omalonylhexosyl-hexoside; Quercetin 7-O-malonylhexosylhexoside; Quercetin 7-O-rutinoside; Isorhamnetin O-acetylhexoside; Quercetin O-acetylhexoside; Di-O-methylquercetin; Quercetin 3-O-rutinoside (Rutin); Quercetin; Quercetin 3-alphaL-arabinofuranoside (Avicularin); Kaempferol 3-O-rutinoside (Nicotiflorin); Myricetin; Isorhamnetin 3-O-neohesperidoside; Isorhamnetin; Kaempferol 3-O-robinobioside (Biorobin); Kaempferol 3-O-glucoside (Astragalin); Dihydromyricetin; Quercetin 40 -O-glucoside (Spiraeoside); Quercetin 3-Oglucoside (Isotrifoliin) Kaempferol 3-O-galactoside (Trifolin); Kaempferol 3-O-rhamnoside (Kaempferin); Fustin; Kaempferol3-O-robinoside-7-O-rhamnoside (Robinin); Myricetin 3-Ogalactoside; and Morin Naringenin C-hexoside; Apigenin C-glucoside; O-methylChrysoeriol 8-C-hexoside; C-hexosyl-chrysoeriol O-hexoside; Apigenin 6-C-hexosyl-8-C-hexosyl-O-hexoside; Hesperetin C-hexosyl-O-hexosyl-O-hexoside; 8-C-hexosylhesperetin O-hexoside; Chrysoeriol 6-C-hexoside 8-C-hexosideO-hexoside; 6-C-hexosyl chrysoeriol O-hexoside; C-hexosylapigenin O-feruloylhexoside-O-hexoside; 6-C-hexosylhesperetin O-hexoside; 8-C-hexosyl-luteolin O-pentoside; di-C, C-hexosyl-apigenin; 8-C-hexosyl-luteolin O-hexoside; 6-Chexosyl-apigenin O-sinapoylhexoside; 6-C-hexosyl-apigenin O-feruloylhexoside; 8-C-hexosyl-chrysoeriol O-feruloylhexoside; C-hexosyl-chrysoeriol O-sinapoylhexoside; 8-C-hexosyl-apigenin O-feruloylhexoside; C-hexosyl-apigenin O-p-coumaroylhexoside; 8-C-hexosyl chrysoeriol O-hexoside; Chrysoeriol 8-C-hexoside; 6-C-hexosyl-chrysoeriol O-feruloylhexoside; Eriodictyol C-hexoside; Luteolin C-hexoside; and Isovitexin (continued)

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Table 2 (continued) Functional group Lipids_fatty acids

Lipids_glycerolipids

Lipids_glycerophospholipids

Phytohormones

Nucleotide and its derivates

Photochemical 14,15-Dehydrocrepenynic acid; 9-Hydroxy-(10E,12Z,15Z)octadecatrienoic acid; delta-Tridecalactone; 4-oxo-9Z,11Z,13E,15E-octadecatetraenoic acid; Punicic acid; Octadecadien-6-ynoic acid; Octadeca-11E,13E,15Z-trienoic acid; 4-Hydroxysphinganine; 8,15-DiHETE; Lauric acid (C12: 0); Myristoleic acid (C14:1); 9,10-EODE; 13-HOTrE; 9-HOTrE; 9-KODE; 13-HpOTrE(r); 9-HpOTrE; 13-HOTrE(r); 12,13-EODE; 13-HPODE; and α-Linolenic acid MAG (18:4) isomer1; DGMG (18:2) isomer2; MAG (18:3) isomer5; DGMG (18:2) isomer1; DGMG (18:2) isomer3; MAG (18:2) isomer1; MAG (18:4) isomer2; MAG (18:1) isomer2; AG (18:2); MAG (18:4) isomer3; MAG (18:3) isomer3; MGMG (18:2) isomer1; MAG (18:3) isomer4; DGMG (18:1); MAG (18:3) isomer2; MAG (18:1) isomer1; MGMG (18:2) isomer2; and MAG (18:3) isomer1 LysoPC 16:2; LysoPC 16:1; PC 16:1/14:1; LysoPC 16:1 (2n isomer); LysoPC 18:2; LysoPC 18:3; LysoPC 16:0; LysoPE 18:1 (2n isomer); LysoPC 18:1 (2n isomer); LysoPC 16:2 (2n isomer); LysoPE 14:0; LysoPC 18:3 (2n isomer); LysoPC 14:0; LysoPC 18:2 (2n isomer); LysoPE 18:2 (2n isomer); LysoPC 18:1; LysoPE 18:0; LysoPC 19:0; LysoPC 15:1; LysoPC 15:0; LysoPC 18:0 (2n isomer); LysoPC 17:0; LysoPE 16:0; LysoPE 18:1; LysoPC 20:4; LysoPC 14:0 (2n isomer); LysoPC 16:0 (2n isomer); LysoPC 18:0; LysoPC 20:1 (2n isomer); LysoPC 20:1; LysoPE 14:0 (2n isomer); and LysoPE 16:0 (2n isomer) Kinetin 9-riboside; trans-zeatin N-glucoside; trans-zeatin 9-Oglucoside; Salicylic acid O-glucoside; Methyl jasmonate; Indole 3-acetic acid (IAA); (+)-Jasmonic acid (JA); Salicylic acid (SA); N6-Isopentenyladenine (iP); trans-Zeatin (tZ); cis-Zeatin (cZ); Gibberellin A1 (GA1); Gibberellin A4 (GA4); (+)-cis,transAbscisic acid (ABA); N-[()-Jasmonoyl]-(L)-Isoleucine (JA-L-Ile); GIBBERELLIN A15; Gibberellin A20; and GIBBERELLIN A9 N2-methylguanosine; Xanthine; Adenosine 30 -monophosphate; Nicotinic acid adenine dinucleotide; Inosine 50 -monophosphate; iP7G; Adenosine 50 -monophosphate; Guanosine 50 -monophosphate; Cyclic AMP; Uridine 50 -diphospho-Dglucose; 20 -Deoxyinosine-50 -monophosphate; 6-Methylmercaptopurine; Adenosine O-ribose; Succinyladenosine; Adenosine; Thymine; Hypoxanthine; Cytosine; Adenine; 5-Methylcytosine; β-Nicotinamide mononucleotide; 2-Hydroxy-6-aminopurine; Uracil; Thymidine; Uridine; Guanine; Inosine; Guanosine; Deoxyguanosine; Deoxycytidine; Xanthosine; 8-Hydroxyguanosine; 20 -Deoxycytidine-50 -monophosphate; 1-Methyladenosine; 50 -Deoxy-50 -(methylthio)adenosine; Guanosine monophosphate; Flavin adenine dinucleotide (FAD); 7-Methylxanthine; Uridine 50 -diphosphate; 1-Methyladenine; Deoxyribose 5-phosphate; Cytidine 50 -monophosphate (continued)

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Table 2 (continued) Functional group

Organic acids

Terpenoids Vitamins

a

Photochemical (Cytidylic acid); 20 -Deoxyadenosine-50 -monophosphate; Uridine 50 -monophosphate; 1-methylguanidine; N6-Succinyl Adenosine; Cytidine; Deoxyadenosine; 2-(dimethylamino)guanosine; β-Pseudouridine; H; and ypoxanthine-9-β-D-arabinofuranoside Sinapoyl malate; Xanthurenic acid; Methylglutaric acid; Phosphoric acid; 4-Hydroxy-3-methoxymandelate; Argininosuccinate; Citramalate; Diethyl phosphate; 2-Isopropylmalate; Rosmarinic acid; 3-Hydroxybutyrate; Kynurenic acid; Ethyl 3,4-Dihydroxybenzoate (Ethyl protocatechuate); lutaric acid; Adipic acid; Azelaic acid; Azelaic Acid; Sebacate; 2-Methylsuccinic acid; Maleic acid; 6-Aminocaproic acid; Terephthalic acid; Phthalic acid; 4-Guanidinobutyric acid; 2-Hydroxyisocaproic acid; Dl-2Aminooctanoic acid; 4-Acetamidobutyric acid; Shikimic acid; Methylmalonic acid; 2-Picolinic acid; D-Pantothenic dcid; 3-Hydroxy-3-methyl butyric acid; D-Erythronolactone; Succinic acid; Creatine; Suberic acid; L-(+)-Tartaric acid; L()-Malic acid; Citric acid; (S)-()-2-Hydroxyisocaproic acid; Fumaric acid; Citraconic acid; 3-Aminosalicylic acid; Dodecanedioic aicd; A-Ketoglutaric acid; α-Hydroxyisobutyric acid; Cis-Aconitic acid; Oxoadipic acid; 3-Hydroxypropanoic acid; Guanidinoethyl sulfonate; 4-Hydroxybenzoic acid; trans-Citridic acid; γ-aminobutyric acid; ethylmalonate; Taurocholic acid; 2-(Formylamino)benzoic acid; Aminomalonic acid; (Rs)-Mevalonic acid; trans,trans-Muconic acid; 2-Methylglutaric acid; 5-hydroxyhexanoic acid; and D-Xylonic acid Phytocassane D; Cucurbitacin E; Cucurbitacin I; Nomilin; and Limonin Pyridoxine O-glucoside; Niacinamide; 4-Pyridoxic acid O-hexoside; D-Pantothenic acid; Thiamine; Menaquinone (K2); Pyridoxal 50 -phosphate; Pyridoxine 50 -phosphate; Pyridoxine; Nicotinic Acid Methyl Ester (Methyl Nicotinate); Riboflavin; L-ascorbate; Orotic acid; Biotin; Vitamin D3; 4-Oxoretinol; All-trans-13,14-dihydroretinol; and Pantetheine

Table adopted from Wang et al. (2020)

firmness of the flesh and the seed cavity (endocarp). Various genetic and metabolic datasets for cucumbers are now accessible for cucurbit breeding and biological study. Cucumber serves as a model plant for the cucurbit family because of the strong collinearity between it and the majority of other cucurbits. The cucumber’s genome has just undergone an upgrade, making it possible to use this knowledge for focused breeding efforts. The metabolic profile identified the metabolic intermediates as well as potential dietary and nondietary components. Alkaloids, tannins, flavonoids, steroids, phlobatannins, and saponins are just a few of the physiologically active, nonnutritive phytochemicals that are present in both cucumber fruits and seeds at the same time. Knowledge of the mechanisms

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underlying sex determination can speed up the process of obtaining desired fruit quality and will help breeders meet other objectives like producing cucumbers with a high and steady yield.

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Sweetpotato: Nutritional Constituents and Genetic Composition Guilherme Silva Pereira, Victor Acheampong Amankwaah, Mercy Ketavi, Bonny Michael Oloka, Aswathy G. H. Nair, Ana Paula da Mata, Carla Cristina da Silva, Iara Gonc¸alves dos Santos, Joa˜o Ricardo Bachega Feijo´ Rosa, and Hugo Campos Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Description of Nutritional Constituents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Detailed Chemical Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Chemical Type, Structure, and Biochemical Pathways of Production . . . . . . . . . . . . . 2.3 Medicinal Properties and Functions in Relation to Human Health . . . . . . . . . . . . . . . . 2.4 Cultural Methods of Nutraceutical Improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 The Need for Biotechnology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Genetic Resources and Sources of Health-Related Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Origin of Sweetpotato and Its Available Germplasms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Gene Pools and Wild Relatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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G. S. Pereira (*) · A. P. da Mata · C. C. da Silva · I. G. dos Santos · J. R. B. F. Rosa Department of Agronomy, Federal University of Viçosa, Viçosa, Brazil e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected] V. A. Amankwaah Biotechnology, Seed and Post-Harvest Division, Crops Research Institute, Kumasi, Ghana e-mail: [email protected] M. Ketavi Research Technology Support Facility, Michigan State University, East Lansing, MI, USA e-mail: [email protected] B. M. Oloka Department of Horticultural Science, North Carolina State University, Raleigh, NC, USA e-mail: [email protected] A. G. H. Nair Division of Crop Improvement, Central Tuber Crops Research Institute, Thiruvananthapuram, India e-mail: [email protected] H. Campos International Potato Center, Lima, Peru e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2023 C. Kole (ed.), Compendium of Crop Genome Designing for Nutraceuticals, https://doi.org/10.1007/978-981-19-4169-6_58

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4 Classical and Molecular Genetics and Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Genetics of Health-Related Genes and Breeding Objectives . . . . . . . . . . . . . . . . . . . . . . 4.2 Molecular Genetics and Inheritance Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Genetic Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Phenotype-Based Diversity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Molecular Marker-Based Assessment Diversity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Relationship with Geographical Distribution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Molecular Mapping of Health-Related Genes and QTLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 Molecular Markers: Types, Evolution of Molecular Markers . . . . . . . . . . . . . . . . . . . . . 6.2 Genetic Linkage Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3 QTL Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Association Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Marker-Assisted Breeding for Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Germplasm Characterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Limitations and Prospects of Marker-Assisted Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 GWAS and Genomic Selection (GS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Genomics-Aided Breeding for Health-Related Traits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Health-Related Functional Genomics Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Other Functional Genomics Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Gene Editing and Transgenics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Role of Bioinformatics as a Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Gene and Genome Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 Comparative Genome Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 Gene Expression Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 Other “Omics” Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Final Considerations and Prospects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abstract

Sweetpotato, Ipomoea batatas (2n ¼ 6x ¼ 90), is a polyploid, outcrossing species considered a staple food in many developing countries due to its starch-rich storage roots. In addition to energy, roots or leaves can provide minerals (such as Fe and Zn), and vitamins (such as A and C). β-carotene- or anthocyanin-rich varieties and their respective orange and purple fleshed roots have attracted great attention given the increased nutraceutical properties they present. Originally from Latina America, several studies have been conducted to assess germplasm diversity around the world using both morphological and molecular descriptors. Similarly, there have been some attempts to describe genetic architecture of traits of interest such as dry matter content and resistance to sweetpotato virus disease and nematodes. However, only recently, major developments in molecular tools have allowed the genetic mapping of major quantitative trait loci and genomewide-based characterization of population structure. Releasing new varieties that show high yield under challenging environments combined with resistance to pests and diseases plus nutritious characteristics is a long-lasting process. Recent advances such as the availability of diploid, wild relative genomes, and their associated bioinformatics tools have facilitated functional studies. Likewise, the ability of detecting single nucleotide polymorphisms and measuring the allele

Sweetpotato: Nutritional Constituents and Genetic Composition

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dosage have facilitated genetic studies in sweetpotato and have paved the way to the implementation of genomics-assisted breeding. Keywords

Superfood · Vitamins · Minerals · Genetics · Diversity · Breeding

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Introduction

Sweetpotato [Ipomoea batatas (L.) Lam.] belongs to the Convolvulaceae or morning glory family of the genus Ipomoea, where it is the only economically important species. It is an autohexaploid with 90 somatic chromosomes (2n ¼ 6x ¼ 90), with a large genome size of about ~4.4 Gb (Yang et al. 2017), and complex inheritance pattern. According to Food and Agriculture Organization of the United Nations, its estimated global production of 90 million metric tons in 2020 is led by Asia and sub-Saharan Africa (SSA), accounting for most of the global sweetpotato production with 83% production in Asia and 14.6% in Africa. In SSA, the crop is a major starch staple and a source of calories, fiber, vitamins, and mineral requirements for humans and domestic animals (Low et al. 2017). In fact, the various parts of sweetpotato crop have been reported to contain phenolics, dietary fiber, and mineral nutrients. Sweetpotato leaves have been reported to contain more polyphenols compounds and at least 15 anthocyanins compared to other commercial vegetables such as spinach, cabbage, and lettuce (Nguyen et al. 2021). Its roots are enriched with secondary metabolites of immense nutritional value and high sensory versatility in terms of taste, texture, and flesh color (white, cream, yellow, orange, and purple). Orange-fleshed sweetpotato (OFSP) is a very nutritious food, as it is a very good source of β-carotene, iron, potassium, vitamin C, fiber, and protein (Low et al. 2017). Sweet OFSP clones with low dry matter (