The Jute Genome (Compendium of Plant Genomes) 3030911624, 9783030911621

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Compendium of Plant Genomes Series Editor: Chittaranjan Kole

Liwu Zhang Haseena Khan Chittaranjan Kole   Editors

The Jute Genome

Compendium of Plant Genomes Series Editor Chittaranjan Kole, President, International Climate Resilient Crop Genomics Consortium (ICRCGC), President, International Phytomedomics & Nutriomics Consortium (IPNC) and President, Genome India International (GII), Kolkata, India

Whole-genome sequencing is at the cutting edge of life sciences in the new millennium. Since the first genome sequencing of the model plant Arabidopsis thaliana in 2000, whole genomes of about 100 plant species have been sequenced and genome sequences of several other plants are in the pipeline. Research publications on these genome initiatives are scattered on dedicated web sites and in journals with all too brief descriptions. The individual volumes elucidate the background history of the national and international genome initiatives; public and private partners involved; strategies and genomic resources and tools utilized; enumeration on the sequences and their assembly; repetitive sequences; gene annotation and genome duplication. In addition, synteny with other sequences, comparison of gene families and most importantly potential of the genome sequence information for gene pool characterization and genetic improvement of crop plants are described.

More information about this series at https://link.springer.com/bookseries/ 11805

Liwu Zhang • Haseena Khan Chittaranjan Kole

•

Editors

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Editors Liwu Zhang College of Agriculture Fujian Agriculture and Forestry University Fuzhou, Fujian, China

Haseena Khan Department of Biochemistry and Molecular Biology University of Dhaka Dhaka, Bangladesh

Chittaranjan Kole President, International Climate Resilient Crop Genomics Consortium (ICRCGC), President, International Phytomedomics & Nutriomics Consortium (IPNC) and President, Genome India International (GII) Kolkata, India

ISSN 2199-4781 ISSN 2199-479X (electronic) Compendium of Plant Genomes ISBN 978-3-030-91162-1 ISBN 978-3-030-91163-8 (eBook) https://doi.org/10.1007/978-3-030-91163-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022, corrected publication 2022 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 Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

This book series is dedicated to my wife Phullara and our children Sourav and Devleena Chittaranjan Kole

Preface to the Series

Genome sequencing has emerged as the leading discipline in the plant sciences coinciding with the start of the new century. For much of the twentieth century, plant geneticists were only successful in delineating putative chromosomal location, function, and changes in genes indirectly through the use of a number of “markers” physically linked to them. These included visible or morphological, cytological, protein, and molecular or DNA markers. Among them, the first DNA marker, the RFLPs, introduced a revolutionary change in plant genetics and breeding in the mid-1980s, mainly because of their infinite number and thus potential to cover maximum chromosomal regions, phenotypic neutrality, absence of epistasis, and codominant nature. An array of other hybridization-based markers, PCR-based markers, and markers based on both facilitated construction of genetic linkage maps, mapping of genes controlling simply inherited traits, and even gene clusters (QTLs) controlling polygenic traits in a large number of model and crop plants. During this period, a number of new mapping populations beyond F2 were utilized and a number of computer programs were developed for map construction, mapping of genes, and for mapping of polygenic clusters or QTLs. Molecular markers were also used in the studies of evolution and phylogenetic relationship, genetic diversity, DNA fingerprinting, and map-based cloning. Markers tightly linked to the genes were used in crop improvement employing the so-called marker-assisted selection. These strategies of molecular genetic mapping and molecular breeding made a spectacular impact during the last one and a half decades of the twentieth century. But still they remained “indirect” approaches for elucidation and utilization of plant genomes since much of the chromosomes remained unknown and the complete chemical depiction of them was yet to be unraveled. Physical mapping of genomes was the obvious consequence that facilitated the development of the “genomic resources” including BAC and YAC libraries to develop physical maps in some plant genomes. Subsequently, integrated genetic–physical maps were also developed in many plants. This led to the concept of structural genomics. Later on, emphasis was laid on EST and transcriptome analysis to decipher the function of the active gene sequences leading to another concept defined as functional genomics. The advent of techniques of bacteriophage gene and DNA sequencing in the 1970s was extended to facilitate sequencing of these genomic resources in the last decade of the twentieth century. vii

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As expected, sequencing of chromosomal regions would have led to too much data to store, characterize, and utilize with the-then available computer software could handle. But the development of information technology made the life of biologists easier by leading to a swift and sweet marriage of biology and informatics, and a new subject was born—bioinformatics. Thus, the evolution of the concepts, strategies, and tools of sequencing and bioinformatics reinforced the subject of genomics—structural and functional. Today, genome sequencing has traveled much beyond biology and involves biophysics, biochemistry, and bioinformatics! Thanks to the efforts of both public and private agencies, genome sequencing strategies are evolving very fast, leading to cheaper, quicker, and automated techniques right from clone-by-clone and whole-genome shotgun approaches to a succession of second-generation sequencing methods. The development of software of different generations facilitated this genome sequencing. At the same time, newer concepts and strategies were emerging to handle sequencing of the complex genomes, particularly the polyploids. It became a reality to chemically—and so directly—define plant genomes, popularly called whole-genome sequencing or simply genome sequencing. The history of plant genome sequencing will always cite the sequencing of the genome of the model plant Arabidopsis thaliana in 2000 that was followed by sequencing the genome of the crop and model plant rice in 2002. Since then, the number of sequenced genomes of higher plants has been increasing exponentially, mainly due to the development of cheaper and quicker genomic techniques and, most importantly, the development of collaborative platforms such as national and international consortia involving partners from public and/or private agencies. As I write this preface for the first volume of the new series “Compendium of Plant Genomes,” a net search tells me that complete or nearly complete whole-genome sequencing of 45 crop plants, eight crops and model plants, eight model plants, 15 crop progenitors and relatives, and three basal plants is accomplished, the majority of which are in the public domain. This means that we nowadays know many of our model and crop plants chemically, i.e., directly, and we may depict them and utilize them precisely better than ever. Genome sequencing has covered all groups of crop plants. Hence, information on the precise depiction of plant genomes and the scope of their utilization are growing rapidly every day. However, the information is scattered in research articles and review papers in journals and dedicated Web pages of the consortia and databases. There is no compilation of plant genomes and the opportunity of using the information in sequence-assisted breeding or further genomic studies. This is the underlying rationale for starting this book series, with each volume dedicated to a particular plant. Plant genome science has emerged as an important subject in academia, and the present compendium of plant genomes will be highly useful to both students and teaching faculties. Most importantly, research scientists involved in genomics research will have access to systematic deliberations on the plant genomes of their interest. Elucidation of plant genomes is of interest not only for the geneticists and breeders, but also for practitioners of an array of plant science disciplines, such as taxonomy, evolution, cytology,

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physiology, pathology, entomology, nematology, crop production, biochemistry, and obviously bioinformatics. It must be mentioned that information regarding each plant genome is ever-growing. The contents of the volumes of this compendium are, therefore, focusing on the basic aspects of the genomes and their utility. They include information on the academic and/or economic importance of the plants, description of their genomes from a molecular genetic and cytogenetic point of view, and the genomic resources developed. Detailed deliberations focus on the background history of the national and international genome initiatives, public and private partners involved, strategies and genomic resources and tools utilized, enumeration on the sequences and their assembly, repetitive sequences, gene annotation, and genome duplication. In addition, synteny with other sequences, comparison of gene families, and, most importantly, the potential of the genome sequence information for gene pool characterization through genotyping by sequencing (GBS) and genetic improvement of crop plants have been described. As expected, there is a lot of variation of these topics in the volumes based on the information available on the crop, model, or reference plants. I must confess that as the series editor, it has been a daunting task for me to work on such a huge and broad knowledge base that spans so many diverse plant species. However, pioneering scientists with lifetime experience and expertise on the particular crops did excellent jobs editing the respective volumes. I myself have been a small science worker on plant genomes since the mid-1980s and that provided me the opportunity to personally know several stalwarts of plant genomics from all over the globe. Most, if not all, of the volume editors are my longtime friends and colleagues. It has been highly comfortable and enriching for me to work with them on this book series. To be honest, while working on this series I have been and will remain a student first, a science worker second, and a series editor last. And I must express my gratitude to the volume editors and the chapter authors for providing me the opportunity to work with them on this compendium. I also wish to mention here my thanks and gratitude to the Springer staff, particularly Dr. Christina Eckey and Dr. Jutta Lindenborn, for the earlier set of volumes and presently Ing. Zuzana Bernhart for all their timely help and support. I always had to set aside additional hours to edit books beside my professional and personal commitments—hours I could and should have given to my wife, Phullara, and our kids, Sourav and Devleena. I must mention that they not only allowed me the freedom to take away those hours from them but also offered their support in the editing job itself. I am really not sure whether my dedication of this compendium to them will suffice to do justice to their sacrifices for the interest of science and the science community. New Delhi, India

Chittaranjan Kole

Preface

Jute is an annual fibrous crop belonging to the genus Corchorus and family Malvaceae. It is distributed in the warm areas of the world including Africa, Asia, Europe, Australia, and South America. Under the genus Corchorus, more than 100 species are in existence, among which only two diploid (2n=14) species namely Corchorus olitorius, commonly called as dark or tossa jute and Corchorus capsularis, known also as white jute are cultivated. The two jute species are largely cultivated in the South Asian countries notably Bangladesh, China, and India, as well as marginally cultivated in other countries such as Egypt, Nepal, Zimbabwe, Thailand, etc. Jute contributes to about 80% of the world’s best fiber production. Genomics studies remain incomplete without a properly assembled reference genome. The genome of jute, a crop of immense economic importance, had long been misinterpreted to be large. This assumption together with a general negligence in studying the genetic make-up of this crop had initially led only to molecular-marker-based studies. However, jute genomics studies witnessed an important milestone after the publication of the reference genomes. The draft jute genomes of two economically important species, Corchorus capsularis var. CVL-1 (white jute) and C. olitorius var. O-4 (tossa or dark jute) were published in 2017, which were assembled using the short-sequence reads produced by next-generation sequencing (NGS) technology, Roche/454 platform, and sequences are stored in NCBI, Accession ID PRJNA215141. The assemblies covered 82.2% of the 338 Mb genome for C. capsularis var. CVL-1 with 30,096 genes and 91.6% coverage of 445 Mb genome for C. olitorius var. O-4 with 37,031 genes. Unassembled sequences (17.8% for C. capsularis and 8.4% for C. olitorius) were primarily due to the repetitive nature of a part of the genome. Later, in the same year, Corchorus olitorius cv. JRO-524 (Navin) genome with 377.3 Mbp was also released and the raw data is available in the NCBI SRA database SRX1506532. In 2021, high-quality genome assembly and annotation of C. capsularis var. “Huangma 179” (HM179) genome (336 Mb) and C. olitorius var. “Kuanyechangguo” (KYCG) genome (361 Mb) was released by integrating single-molecule real-time sequencing, and high-throughput chromosome conformation capture techniques. The sequence data is available at the National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Accession no. GWHBCLB00000000, accessible at https://bigd.big.ac.cn/gwh. xi

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Apart from accelerating the functional genomics research in the Corchorus genus, the availability of several whole-genome sequences of jute is also providing insights into fiber development in other allied genera. With these genome assemblies, devoted technologies were developed not only to compare with the comprehensively studied model plants’ genomes such as the Arabidopsis at the whole genome level but also to transfer the rich research information from the model plants to jute. This has led to the investigation of full details of whole-genome duplication in jute. About 160 syntenic blocks were found to be shared between the genomes of C. capsularis and C. olitorius. Phylogenetic studies revealed that the entire genome duplication in jute has occurred about 18.66 million years ago. A total of 57,087 protein-coding genes were functionally annotated in jute and about 6,077 genes were found to be upregulated during fiber development. Many disease resistance genes (1765) have also been identified. The available whole-genome studies on jute have paved the way for further genomics studies including gene detection and functional studies, genome evolution studies, and breeding of jute crop. Plant genome science has evolved as an important subject in the academic world. The current book series entitled, “Compendium of Plant Genomes” will be useful both to teaching faculties and students. Primarily, scientists/researchers engaged in genomics investigation will have access to efficient deliberations on genomes of their interest. Description of plant genomes is imperative not only for breeders and geneticists but also for experts of a range of plant science disciplines including taxonomy, cytology, evolution, pathology, entomology, nematology, physiology, biochemistry, crop production, and bioinformatics. Therefore, this book on “The Jute Genome” has dealt with fundamental aspects of the available genomic resources and their usefulness in understanding the plant better. It contains 21 chapters that begin with the economic importance of jute (Chap. 1) and concludes with the power of molecular markers and genomics technology in jute breeding (Chap. 21). The first few chapters (Chaps. 1–3) offer a general introduction to the jute crop, its origin and distribution, botanical description, chemistry, and economic importance. Chapter 4 describes germplasm resources, genetic diversity, and population structure in jute. Chapters 5 and 6 depict details on the DUS test, DNA fingerprinting, and utilization. Chapter 6 provides information on hybrid development, characterization, and utilization. Chapters 7 and 8 deliberate on classical genetics primarily cytology and cytogenetics and challenges for jute transformation. Chapter 9 describes molecular map construction and mapping of genes and QTLs underlying various important agronomic traits. Chapters 10–12 contain information on the jute genome sequencing initiative in Bangladesh, China, and India. Chapter 13 provides information on comparative genomics and synteny within and among Malvaceae genomes focusing on jute. Chapter 14 contains information on organelle genome sequencing. Chapters 15 and 16 present details on functional genomics, genomic resources of jute, and databases. Chapters 17–19 enumerate information regarding genomics and genetics of fiber development, abiotic (drought and salt), and biotic (diseases and pests) stresses. Chapter 20 provides information on the flowering pathways based

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on genomic data. Chapter 21, the last chapter of the book, emphasizes the power of molecular markers and established genomic technologies for jute breeding. We believe that the contents of this book chapters will offer jute scientists invaluable insight into the complexity underlying phenotypic variability while increasing their interest in undertaking new studies to further improve our perception of the same. Therefore, it will serve as an important resource material and will be much valuable to breeders, students, and researchers working on the jute crop. The book chapters have been authored by eminent scientists from different countries. The editors are thankful to them for reviewing the published research work in their areas of expertise and in certain cases sharing their unpublished results to upgrade the chapter manuscripts. Fuzhou, China Dhaka, Bangladesh Kolkata, India

Liwu Zhang Haseena Khan Chittaranjan Kole

Contents

Economic Importance of Jute. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Md. Sarwar Jahan, Shakhawat Hossain, and Mubarak Ahmad Khan

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Botany of Jute (Corchorus Spp.) . . . . . . . . . . . . . . . . . . . . . . . . . . . Rakha Hari Sarker

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Chemistry of Jute and Its Applications . . . . . . . . . . . . . . . . . . . . . . Tapan Kumar Guha Roy, Debanjan Sur, and Debashis Nag

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Germplasm Resources in Jute . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lilan Zhang, Jianmin Qi, Jianguang Su, and Liwu Zhang

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DUS Test and DNA Fingerprinting Construction of Jute Varieties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Qingyao He, Jiayu Yao, Pingping Fang, Jianmin Qi, and Liemei Zhang Jute Interspecific Hybrids: Development, Characterization and Utilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Anil Kumar, Hariom Kumar Sharma, R. T. Maruthi, Neetu Kumari, Basant Kumar Jha, and Shashi Bhushan Choudhary Classical Genetics, Cytogenetics and Traditional Breeding in Jute . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jiban Mitra and Chandan Sourav Kar

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Challenges of Jute Transformation . . . . . . . . . . . . . . . . . . . . . . . . . 115 Zeba I. Seraj, Ahmad S. Islam, and Rakha Hari Sarker Molecular Linkage Mapping: Map Construction and Mapping of Genes/QTLs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Moumita Das, Sumana Banerjee, and Reyazul Rouf Mir Jute Genome Sequencing: An Indian Initiative . . . . . . . . . . . . . . . . 145 Nagendra Kumar Singh and Debabrata Sarkar Jute Genome Sequencing: A Bangladeshi Initiative . . . . . . . . . . . . 167 Md. Shahidul Islam, Abu Ashfaqur Sajib, and Haseena Khan Jute Genome Sequencing: A Chinese Initiative . . . . . . . . . . . . . . . . 185 Xin Yang, Hu Li, Lilan Zhang, Siyuan Chen, and Liwu Zhang

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Contents

Comparative Genomics and Synteny Within Corchorus Species and Among Malvaceae Genomes. . . . . . . . . . . . . . . . . . . . . 193 Muhammad Zohaib Afzal, Niaz Mahmood, Mahdi Muhammad Moosa, Aminu Kurawa Ibrahim, Siyuan Chen, and Liwu Zhang Organelle Genome Sequencing and Phylogenetic Relationship of Jute . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Yi Xu, Siyuan Chen, Wubin Zhan, Lihui Lin, and Liwu Zhang Functional Genomics of Jute . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Sylvain Niyitanga, Pratik Satya, and Sabrina M. Elias Jute Genomic Resources and Database . . . . . . . . . . . . . . . . . . . . . . 247 Haseena Khan, Liwu Zhang, Dipnarayan Saha, Huawei Wei, Subhojit Datta, Pratik Satya, Jiban Mitra, and Gouranga Kar Genetic and Genomics of Bast Fiber Development in Jute . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259 Sylvain Niyitanga, Hu Li, Lilan Zhang, Gaoyang Zhang, and Liwu Zhang Genetics and Genomics of Biotic Stress Resistance of Jute . . . . . . 269 Shaheena Amin and Tahmina Islam Genomics and Genetics of Drought and Salt Tolerance in Jute . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291 Jiayu Yao, Jiantang Xu, and Aminu Kurawa Ibrahim Flowering Pathway of Jute Based on Genomic Data . . . . . . . . . . . 305 Md. Wali Ullah and Md. Shahidul Islam Power of Molecular Markers and Genomics Technology in Jute Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 Pratik Satya, Debabrata Sarkar, Chandan Sourav Kar, Dipnarayan Saha, Subhojit Datta, Surendra Kumar Pandey, Amit Bera, and Jiban Mitra Correction to: Jute Genome Sequencing: An Indian Initiative . . . Nagendra Kumar Singh and Debabrata Sarkar

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Contributors

Muhammad Zohaib Afzal College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China Shaheena Amin Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh Sumana Banerjee Department of Botany, University of Calcutta, Ballygunge, Kolkata, India Amit Bera ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Siyuan Chen Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding By Design, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China; Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China Shashi Bhushan Choudhary ICAR-National Bureau of Plant Genetic Resources, Regional Station Ranchi, Ranchi, Jharkhand, India Moumita Das School of Biotechnology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh, India Subhojit Datta ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Sabrina M. Elias School of Environment and Life Sciences, Independent University, Bashundhara, Dhaka, Bangladesh Pingping Fang Agricultural College, Fujian Agriculture and Forestry University, Fujian, China

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Qingyao He Agricultural College, Fujian Agriculture and Forestry University, Fujian, China Shakhawat Hossain BSCL Scientific Research Laboratory, Bombay Sweets & Co. Ltd, Dhaka, Bangladesh; Bangabandhu Textile Engineering College, Ministry of Textiles and Jute, Tangail, Dhaka, Bangladesh Aminu Kurawa Ibrahim College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China; Department of Agronomy, Faculty of Agriculture, Bayero University Kano, Kano State, Nigeria Ahmad S. Islam Department of Botany, University of Dhaka, Dhaka, Bangladesh Md. Shahidul Islam Basic and Applied Research on Jute Project, Bangladesh Jute Research Institute, Dhaka, Bangladesh; Genetic Resources and Seed Division, Bangladesh Jute Research Institute, Dhaka, Bangladesh Tahmina Islam Department of Botany, University of Dhaka, Dhaka, Bangladesh Md. Sarwar Jahan BSCL Scientific Research Laboratory, Bombay Sweets & Co. Ltd, Dhaka, Bangladesh; Bangabandhu Textile Engineering College, Ministry of Textiles and Jute, Tangail, Dhaka, Bangladesh Basant Kumar Jha Birsa Agricultural University, Kanke, Ranchi, Jharkhand, India Chandan Sourav Kar Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Gouranga Kar ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, India Haseena Khan Molecular Biology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh Mubarak Ahmad Khan BSCL Scientific Research Laboratory, Bombay Sweets & Co. Ltd, Dhaka, Bangladesh; Bangladesh Jute Mills Corporation, Ministry of Textile and Jute, Dhaka, Bangladesh A. Anil Kumar ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, West Bengal, India Neetu Kumari Birsa Agricultural University, Kanke, Ranchi, Jharkhand, India

Contributors

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Hu Li Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding By Design, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China; Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China Lihui Lin College of Agriculture, Fujian Agriculture and Forestry University, FuzhouFujian, China Niaz Mahmood Department of Biochemistry, Goodman Cancer Research Centre, McGill University, Montreal, QC, Canada R. T. Maruthi ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, West Bengal, India Reyazul Rouf Mir Division of Genetics & Plant Breeding, Faculty of Agriculture, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir (SKUAST-K), Kashmir, J&K, India Jiban Mitra Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Mahdi Muhammad Moosa Department of Physics, University at Buffalo, Buffalo, NY, USA Debashis Nag Technology Transfer Division, National Institute of Natural Fibre Engineering & Technology, Indian Council of Agricultural Research (NINFET-ICAR), Kolkata, India Sylvain Niyitanga Bast Fiber Biology Center, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China Surendra Kumar Pandey ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Jianmin Qi College of Agriculture, Fujian Agriculture and Forestry University, Fujian, China Tapan Kumar Guha Roy Chemical Processing Division, Indian Jute Industries’ Research Association (IJIRA), Kolkata, India Dipnarayan Saha ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Abu Ashfaqur Sajib Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, Bangladesh Debabrata Sarkar Biotechnology Unit, Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres (CRIJAF), Barrackpore, Kolkata, West Bengal, India

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Contributors

Rakha Hari Sarker Department of Botany, University of Dhaka, Dhaka, Bangladesh Pratik Satya Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, India Zeba I. Seraj Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh Hariom Kumar Sharma ICAR-Directorate Research, Sewar, Bharatpur, Rajsthan, India

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Nagendra Kumar Singh Rice Genome Laboratory, ICAR-National Institute for Plant Biotechnology (NIPB), Pusa, New Delhi, India Jianguang Su Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Hunan, China Debanjan Sur Physics Division, Indian Jute Industries’ Research Association (IJIRA), Kolkata, India Md. Wali Ullah Basic and Applied Research on Jute Project, Bangladesh Jute Research Institute, Dhaka, Bangladesh Huawei Wei College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China; Experiment Station of Jute and Kenaf in Southeast China, Ministry of Agriculture and Rural Affairs/Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China Jiantang Xu College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China Yi Xu College of Agriculture, Fujian Agriculture and Forestry University, FuzhouFujian, China Xin Yang Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding By Design, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China; Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China Jiayu Yao College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, China Wubin Zhan College of Agriculture, Fujian Agriculture and Forestry University, FuzhouFujian, China Gaoyang Zhang College of Life Sciences, Shangrao Normal University, Shangrao, China

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Liemei Zhang Agricultural College, Fujian Agriculture and Forestry University, Fujian, China Lilan Zhang Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding By Design, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China; Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China Liwu Zhang Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding By Design, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China; Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou, Fujian, China

Abbreviations

µM 2- DE 4CL AA ABA ABF abi1 abi2 ACT AFLP AGL20 amiRNA ANOVA AP1 AP2/ERF APL AT rich AUDPC AVR B. thuringiensis BC BD BEs BFC BGAL BH BHC BINA BJMC BJRI BLAST bp BR BSA Bt Bt Toxin

Micro Molar Two-dimensional 4-coumarate CoA ligase Amino acid Abscisic acid ABA-responsive element binding factor ABA insensitive 1 ABA insensitive 2 Actin Amplified fragment length polymorphism Agamous-like 20 Artificial micro RNA Analysis of variance Apetala 1 Apetala2/Ethylene responsive factor Altered Phloem Development AT-rich region is its high content of adenine (A) and thymine (T) residues Area under disease progress curve Avirulence Bacillus thuringiensis Backcross Basal diameter Base editors Bast fiber cellulose b-galactosidase Branching height Bihar hairy caterpillar Bangladesh Institute of Nuclear Agriculture Bangladesh Jute Mills Corporation Bangladesh Jute Research Institute Basic local alignment search tool Base pairs Bark rate Bulk segregant analysis Bacillus thuringiensis Endotoxin from Bacillus thuringiensis xxiii

xxiv

BUSCO bZIP C C. capsularis C. olitorius C2H5OH C3H C4H CAD CaMv CAPS Cas 9 Cas9 CAZymes CBC CBDP CCA1 CCACVL1 CCoAOMT CCR CCT cDNA CDPK CDS CEGMA CEGs CesA CIM cM CMA CMC CNC CNF CNS CO CO2 COG COLO4 COMT COP1 CoXTH 1 Cp cpInDel cpSSR

Abbreviations

Benchmarking Universal Single-Copy Orthologs Basic leucine zipper Carbon Corchorus capsularis Corchorus olitorius Ethanol Coumarate 3-hydroxylase Cinnamate 4-hydroxylase Cinnamyl alcohol dehydrogenase Cauliflower mosaic virus (CaMV) Cleaved amplified polymorphic sequence CRISPR/CRISPR-associated protein 9 CRISPR-associated 9 protein Carbohydrate-active enzymes Carpet backing cloth CAAT box-derived polymorphism Circadian clock associated 1 Corchorus capsularis CVL1 Caffeoyl CoA O-methyltransferase Cinnamoyl CoA reductase CONSTANS, CO-like, and TOC1 Complementary deoxyribose nucleic acid Calcium-dependent protein kinase family Coding sequences Core eukaryotic genes mapping approach Conserved eukaryotic genes Cellulose synthase Composite interval mapping Centimorgan Chromosome banding using fluorochrome staining with chromomycin A Carboxymethylcellulose Cellulose nanocrystal Cellulose nano-fiber Non-coding sequences CONSTANS Carbon dioxide Clusters of orthologous groups Corchorus olitorius O4 Caffeic acid O-methyl transferase Constitutive photomorphogenic 1 Xyloglucan endotransglycosylase/hydrolase 1 from C. olitorius Chloroplast Chloroplast InDel Chloroplast SSR

Abbreviations

xxv

CRIJAF CRISPR CRY2 Csl CSSL CtXTH 1 Cu cv. CWPs CYP D8 DAPI DArt DBW DEG DEGs DF DH DLB dlpf DM DNA DSM DUS E. coli EC EcoTTILLING EDS 1 EF EHD1 EIN3 ELF7 ELF8 EMS EQTL eSSRs EST EST-SSR ETI F1 F2 F5H FAO

Central Research Institute for Jute and Allied Fibres Clustered regularly interspaced short palindromic repeats Cryptochrome 2 Cellulose synthase-like Chromosome segment substitution lines Xyloglucan endotransglycosylase/hydrolase 1 from C. triocularis Copper Cultivar Cell wall proteins Cyclophilin Della protein dwarf 8 4′,6-DiAmidino-2-PhenylIndole Diversity arrays technology Dry bark weight per plant Differentially Expressed Gene Differentially expressed genes Days to flowering Double haploids Detached leaf bioassay Deficient in lignified phloem fiber Days to seeds mature Deoxyribonucleic acid Diallel selective mating Distinctness, uniformity, and stability Escherichia coli Ethylcellulose Ecotype TILLING (Targeting-induced local lesions in genomes) Enhanced disease susceptibility Elongation factor Early heading date 1 Ethylene insensitive 3 Early flowering 7 Early flowering 8 Ethyl methane sulfonate Epistatic QTL EST-derived SSRs Expressed sequence tag Expressed sequence tag-derived simple sequence repeat Effector triggered immunity First filial generation Second filial generation Ferulate 5-hydroxylase The Food and Agriculture Organization

xxvi

FAOSTAT FBT FBW FC FCA FCB FF FISH FLA FLAs FLC FLD FLK FLO FLS 2 FR FRI FRL FS FSW FT FW FY g G G. lineata GA GAPDH GAUT GBS GBY GC rich GD GDP GFG GGDP GH Ghd7 GI GO GPa GS GSM GW GWAS GXE

Abbreviations

Food and Agriculture Organization Corporate Statistical Database Fresh bark thickness Fresh bark weight per plant; Fiber content FLOWERING CONTROL LOCUS A Fiber cell bundle Fiber fineness Fluorescence in situ hybridization Fasciclin-like arabinogalactan Fasciclin-like arabinogalactans FLOWERING LOCUS C FLOWERING LOCUS D FLOWERING LOCUS K FLORICAULA Flagellin sensing 2 Fungal resistance FRIGIDA FRIGIDA LIKE, FRL Fiber strength Fresh stem weight per plant FLOWERING LOCUS T Fiber weight Fiber yield Gram Grouping characteristics Grammothele lineata Gibberellic acid Glyceraldehyde 3-phosphate dehydrogenase Galacturonosyltransferase Genotyping by sequencing Green biomass yield GC-rich region is its high content of guanine (G) and cytosine (C) Germination under drought Gross domestic product Guangfenghangguo Geranylgeranyl diphosphate Glycosyl hydrolase Grain yield and heading date 7 GIGANTEA Gene ontology Gigapascal Glutamine synthetase Grams per square meter Green weight Genome-wide association studies Genotype of X environment

Abbreviations

xxvii

H2O2 HAMPS HC Hd3a HEC Hi-C HIF HPC hpRNA HR HSP IAA IC ICAR ICIM-ADD ICJC IJO IJSG IL ILP InDel IR ISR ISSR iTRAQ ITS JARL JAZ JRI K K tones K2O KASP KEGG KIN1 KO KOG KOR lacZ LC-MS/MS LD LFY LG LL lncRNA

Hydrogen peroxide Herbal-associated molecular pattern Hairy caterpillar Heading date 3a Hydroxyethyl cellulose High-throughput chromosome conformation capture Heterogeneous inbred family Hydroxypropyl cellulose Hairpin double-stranded RNA Hypersensitive response Heat shock protein Indole acetic acid Indigo caterpillar Indian Council of Agricultural Research Inclusive composite interval mapping with additive effect Indian Central Jute Committee International Jute Organization International Jute Study Group Introgression line Intron-linked polymorphic Insertion/Deletion inverted repeats Induced systemic resistance Inter-simple sequence repeat Isobaric tag for relative and absolute quantification Internal transcribed spacer Jute Agricultural Research Laboratory Jasmonate zim Jute Research Institute Kilo Kilo Tones Potassium oxide Kompetitive allele-specific PCR Kyoto Encyclopedia of Genes And Genomes Kinase 1 KEGG Orthology Eukaryotic orthologous groups Korrigan Lactose targeting b-galactosidase Liquid chromatography-mass spectrometry LUMINIDEPENDENS LEAFY Linkage group Leaf length Long non-coding RiboNucleic Acid

xxviii

LOD LRR LRR-RLK LSC LTR LTRs M tones M. phaseolina MAB MAGIC MALDI-TOF-TOF MS MAPK 6 MAPK MAS Mb Mbp MC MCIM MD MEKPO MFE mg miR159A miR172A miRNA MIS4 MITE MITEs mM MOP MPa MPWGAIM M-QTL mRNA MS MYB33 N NAM NB NBPGR NBS-LRR NBTs NCBI ncRNA NDGA NGS

Abbreviations

Logarithm of Odds Leucine-rich repeat Leucine-rich repeat receptor-like protein kinase Long single copy Long Terminal Repeat Long terminal repeats Metric tones Macrophomina phaseolina Marker-assisted breeding Multi-parent advanced generation intercross Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry Mytogen activated protein kinase 6 Mytogen activated protein kinase Marker-assisted selection Million bases Million base pairs Methyl cellulose Mixed model composite interval mapping Middle diameter Methyl ethyl e ketone peroxide Minimal free energy Milligram MicroRNA 159A MicroRNA 172A Micro-RNA MULTICOPY SUPPRESSOR OF IRA1 4 miniature inverted-repeat transposable element Miniature inverted-repeat transposable elements Minimol Muriate of potash Megapascal Multiparent whole-genome average interval mapping Main QTL Messenger RNA Murashige and skoog medium Myb domain protein 33 Nitrogen Nested association mapping Number of branches National Bureau of Plant Genetic Resources Nucleotide binding site-leucine rich repeat New plant breeding techniques National Center for Biotechnology Information Non-coding RNA Nordihydroguaiaretic acid Next-generation sequencing

Abbreviations

xxix

NIL NL NMS NN Nptll Nr nt O2 ODM –OH –OR ORF P P2O2 PAF1 PAL PALG PAMPS PARE PAT PC PCA PCD PCR PDI PE PEN PFAM PGPR PH PhasiRNA PHYA PIC PIE1 PKs PLA POG Pool-seq PP PP2C PPE PPR PPT PQ PR proteins Prot PRR

Near-isogenic lines Number of leaves Nodes of the main stem Number of nodes Neomycin phosphotransferase II enzyme Non-redundant Nucleotide Oxygen Oligonucleotide-directed mutagenesis Hydroxyl groups Cellulose ethers Open-reading frames Phosphorus Phosphorus pentoxide Proteasome alpha subunit F1 Phenylalanine ammonia-lyase Phenylalanine ammonia-lyase gene Pathogen-associated molecular pattern Parallel analysis of RNA ends Phosphoinothricin acetyltransferase Principal component Principal component analysis Programmed cell death Polymerase Chain Reaction Percent Disease Incidence Polyethylene Penetration resistance Protein Families Plant growth-promoting rhizobacteria Plant height Trans-acting like phased siRNA Phytochrome A Polymorphic information content Photoperiod-independent early flowering 1 Protein kinases Polylactic Acid Peroxidase gene Pooled sequence Polypropylene Protein Phosphatase 2C Personal Protective Equipment Pentatricopeptide repeats Phophinothricin Pseudo qualitative characteristics Pathogens-related proteins Protein Plant pattern recognition receptor

xxx

PTI PVE PYR/PYL Q
E qBFC qJST QL QN qPCR qRT qRT-PCR qRT-PCR QTL RAD RAD-SNP RAPD RD29A RD29B RDBMS REF6 RFLP RIL RILs RIN RNA RNA Seq RNAi ROS rRNA RW SAR SAUR SBD SCAR SCoT SCW SD SDB SDT SG SGT 1 siRNA SL SLAF SLAF-seq SMD SMRT

Abbreviations

PAMP-triggered immunity Phenotypic variation explained Pyrabactin resistance 1-like receptors QTL by environmental interaction QTL for bast fiber cellulose QTL for jute salt tolerance Qualitative characteristics Quantitative characteristics Quantitative PCR Quantitative real-time Quantitative reverse transcriptase PCR Real-time quantitative reverse transcriptionPCR Quantitative trait locus Restriction site-associated DNA Restriction site associate digestion- single nucleotide polymorphism Random amplified polymorphic DNA Responsive to desiccation 29A Responsive to desiccation 29B Relational Database Management System RELATIVE OF EARLY FLOWERING 6 Restriction fragment length polymorphism Recombinant inbred line Recombinant inbred lines RNA integrity number Ribonucleic acid RNA sequencing RNA interference Reactive oxygen species Ribosomal RNA Root weight Systemic acquired resistance Small auxin up RNAs Stem basal diameter Sequence characterized amplified region Start codon targeted Secondary cell wall Stem diameter Stem diameter base Stem diameter top Sudan green Small glutamine-rich tetratrico repeat protein Small interfering RNA Semilooper Specific locus amplified fragment Specific locus amplified fragment sequencing Stem mid- diameter Single-molecule real-time

Abbreviations

xxxi

SNP SNPs SnRK2 snRNA SPAD spp. SPY SQL SRA SRAP SS SSC SSR ST STD STMS SuSy SW TALeN TD TE TEXQTL TF TFL1 TILLING TOC1 TPR TQ tRNA TS TSA TSP TUB 2 UBC UDP UDPG UGPase UNCTAD UPOV USD VIN3 VIP3 VIP4 VRN2 WD 40

Single nucleotide polymorphism Single nucleotide polymorphisms Sucrose nonfermenting related protein kinase 2 Small nuclear RiboNucleic Acid Soil and plant analyzer development Several species SPINDLY Structured Query Language Sequence read archive Sequence-related amplified polymorphism Stainless stile Short single copy Simple sequence repeat Salt tolerance Stem-top diameter Sequence-tagged microsatellite site Sucrose synthase Stick weight Transcription activator-like effector nuclease Top diameter Transposon element Target enriched X-QTL (extreme QTL) Transcription factors Terminal flower 1 Targeted induced local lesions in genomes Two-component response regulator-like aprr1 Tetratricopeptide repeats Technical questionnaire characteristics Transfer RNA Tensile strength Transcriptome shotgun assembly Triple superphosphate Tubulin 2 Ubiquitin-conjugating enzyme Uridine diphosphate Uridine diphosphate glucose UDP-glucose pyrophosphorylase United Nations Conference on Trade and Development International Union for the Protection of New Varieties of Plants The U.S. Dollar Vernalization Insensitive 3 Vernalization Independence 3 Vernalization Independence 4 Vernalization 2 WD or beta-transduction repeat of 40 amino acid

xxxii

WGAIM WGS WOX4 WPB WT WY XTH ZFN

Abbreviations

Whole-genome average interval mapping Whole-genome shotgun sequencing Wuschel-related HOmeoboX 4 Whole-plant bioassay Wild type Wood yield Xyloglucan endotransglycosylase/hydrolase Zinc figure nuclease

1

Economic Importance of Jute Md. Sarwar Jahan, Shakhawat Hossain, and Mubarak Ahmad Khan

Abstract

Economic importance means the status of particular goods or service production, distribution, and consumption by a consumer which is carrying marketing value. Jute is a naturally renewable, biodegradable, and bio-compostable fiber that is totally environment friendly. Since many centuries ago, jute makes an economical product in South Asia. A large amount of jute fiber is grown and the jute-based products are used every year for their special characterization. Jute was used as sacking and rope in the sixteenth century, in the eighteenth to nineteen century, jute rope was used in housing and sailboat but in the twenty to twenty-fist century jute is used in modern and hi-tech equipment. Jute contains a large amount of cellulose. So, the cellulose, modified cellulose, cellulosic polymer used in different types of additive, pharmaceutical and genetic engineering, high yield composite material, and even jute leaves are used is

health treatment. In this region, jute economical value is enhancing day by day. This chapter has discussed the statistics of jute, the economic and environmental impact of jute and also the different applications of jute.

1.1

Introduction

Economic value is important for any goods or service because this importance has changed our lifestyle and culture, and it leads to global movement. Since a long time ago, jute fiber contributes to the economy is globally. Jute is the second largest natural fiber which is one of the most abundant lignocellulosic bast fibers which are mainly grown in Bangladesh, India, China, especially in the South Asian region, which carries approximately cellulose 59–72%, hemicellulose 13–20%, lignin 12–13%, pectin 0.2– 0.4%, wax 0.5%, and 12.5–13.7% moisture (Dittenber and GangaRao 2012; Nasrin Akter et al. 2018; Nasrin Akter et al. 2020; Das et al. 2018; Md Mahbubul Islam and Ali 2017; Basu and Roy 2008; Roy and Lutfar 2012).

Md. S. Jahan
S. Hossain BSCL Scientific Research Laboratory, Bombay Sweets & Co. Ltd, Dhaka 1229, Bangladesh Md. S. Jahan
S. Hossain
M. A. Khan (&) Ministry of Textiles and Jute, Bangabandhu Textile Engineering College, Dhaka, Tangail, Bangladesh M. A. Khan Bangladesh Jute Mills Corporation, Ministry Jute and Textile, Dhaka 1000, Bangladesh © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_1

1

2

Md. S. Jahan et al.

Fig. 1.1 Chemical formula of jute fiber

H H

H

C

C

C H

O

H H C

C

H

H

O

O

O

H

H

O

C

C

O H

H

O

H

O

C

C

H O

H

H

O

C

C

C

H

H

H

C

H

O

H

n

CH2OH

Fig. 1.2 Chemical structure of cellulose

CH2OH

H

O

O

H OH

O H

H

HO

H H

Fig. 1.3 Chemical structure of hemi-cellulose

H

OH H

OH H

CH3C

H

-

H

O H OH

OH

COO

CH2

O

OH

O

HO O

H OH

H

H

H O

H H

H

O

H

n

OH

H H

OH O

H COO

H

H

CH2OH H

H

O

O

O O CH3COOCH2

H

n

OH

CH2OH H

H

O

H

H H

H

HO

OH

1

Economic Importance of Jute

3 OH

Fig. 1.4 Chemical structure of lignin

O O

OH OH

OH O

OH O HO

CH3

O

CH3 O

O

O O

OH

OH O

Fig. 1.5 Scheme of the jute cell-wall organization (Duan and Yu 2016) (Reprinted from under Open Access License)

1.2

Economic Statistics of Jute

1.2.1 Production of Jute in Major Jute-Producing Countries (FAOSTAT 2020) Statistics show the comparative data of jute production, according to the leading countries in jute cultivation, those are Bangladesh, China, and India (Table 1.1). From the FAOSTAT 2020, it appears that the jute cultivation area of Bangladesh has been varying since 2010–11. This occurred not only in Bangladesh, but also in the other major jute-producing countries. Compared with the other jute-cultivating countries only India is producing the maximum amount of jute.

However, it is increasing from 2010 to 2011, it is observed that both India and Bangladesh have a flourishing trend in their jute producing land area, and the other countries, China, Myanmar, and Nepal have significantly gone down in the jute production. Other countries’ jute production statistics is Uzbekistan 20,000 metric tons, Nepal 18,000 metric tons, Myanmar 17,000 metric tons, Thailand 12,000 metric tons, Vietnam 12,000 metric tons, Sudan 3,350 metric tons, and Egypt 2,508 metric tons (Jegede 2019; FAOSTAT 2020).

1.2.2 Export 2010–2019 See Table 1.2.

1,225,306

1,548,421

1,596,207

1,513,563

1,437,152

1,477,507

1,436,241

1,467,963

1,466,801

1,437,939

2011

2012

2013

2014

2015

2016

2017

2018

2019

749,658

758,218

737,770

677,678

677,575

665,699

681,000

760,427

708,723

416,346

665,300

685,750

706,070

733,714

773,000

741,000

800,000

800,000

800,000

767,630

7982

7296

8000

8554

9408

10,094

11,970

12,290

13,510

13,300

China

23,477

23,209

23,450

22,727

22,071

23,630

22,585

21,636

23,138

23,086

21,349

21,284

20,280

19,832

20,647

20,264

20,426

19,095

21,494

22,180

Bangladesh

World

India

World

Bangladesh

The yield of Jute (hg/ha)

Harvested Area (Hectares)

2010

Year

25,695

25,175

26,595

25,221

23,146

26,559

24,300

23,900

24,505

23,437

India

37,502

37,157

37,500

35,948

32,674

32,178

29,657

32,059

32,198

30,075

China

Table 1.1 Comparative data of the harvested area, yield, and production quantity of Jute (FAOSTAT 2020)

3,375,884

3,404,261

3,442,372

3,264,150

3,260,996

3,395,972

3,418,366

3,453,600

3,582,789

2,828,732

World

1,600,474

1,613,762

1,496,216

1,344,000

1,399,000

1,349,000

1,391,000

1,452,044

1,523,315

923,464

Bangladesh

Jute Production Quantity (Tone)

1,709,460

1,726,380

1,877,760

1,850,510

1,789,200

1,968,000

1,944,000

1,912,000

1,960,380

1,799,100

India

29,934

27,110

30,000

30,750

30,740

32,480

35,500

39,400

43,500

40,000

Chain

4 Md. S. Jahan et al.

1

Economic Importance of Jute

5

Table 1.2 Comparative data of the export quantity and export value of Jute (FAOSTAT 2020) Year

Export Quantity (Tone)

Export Value (in thousand USD)

World

Bangladesh

India

China

World

Bangladesh

India

China

2010

375,605

290,973

43,628

51

261,179

191,351

33,457

232

2011

471,256

420,441

25,991

61

290,736

248,147

17,729

184

2012

475,253

425,000

18,715

11

236,668

194,000

10,163

121

2013

340,431

283,246

16,711

18

187,009

134,247

9143

249

2014

271,196

203,616

29,039

24

166,954

107,416

15,811

135

2015

257,594

205,573

17,894

31

190,046

123,473

10,558

158

2016

310,986

261,490

16,710

58

234,527

182,087

11,660

417

2017

262,131

208,422

14,998

55

188,261

137,524

8154

513

2018

276,448

222,673

9830

88

154,330

119,840

5573

116

2019

250,506

185,503

17,609

8

171,084

107,247

12,854

101

1.2.3 Import 2010–2019 See Table 1.3.

1.3

Environmental Impact of Jute

Jute plant and jute fiber have many affirmative influences on the environment. It is an environmental-friendly natural fiber. Each and every part of jute has a good impact on the environment and economy directly and indirectly. The rotten leaf and root are used to enhance the fertility of the land. It is giving Urea, Triple superphosphate (TSP), Muriate of Potash (MOP), Zipsam, Dolomite, Ferrous Sulfate, Magnesium Sulfate, Zinc sulfate to the soil. Table 5 shows that every year the jute plants produce 956.38 K tone leaves and 423.4 K tone root on average. Also, the jute dry leaf, fiber, and stick emit P2O2, K2O and N and also acts as a pesticide. The green leaf of jute is a good source of nutrition. It provides vitamin-c, iron, calcium and used in herbal medicine to cure dysentery, gastric, fever, etc. Jute-stick is a good source of charcoal and fine carbon, used as a composite and particle, also it can be used as a fuel that can be reduced which reduces the cutting down of trees to protect the environment. Jute-based composite materials are environmental friendly. This can be an alternative to harmful materials

such as glass, iron, lead, ceramic, carbon, concrete, and other matrix materials. Jute-based composite (Jutin) is saline resistance, rust resistance, heat insulating, and lightweight. The production of jute is 1240 kg per hector within 100– 120 days, on the other hand, wood plant needed at least 10 to 14 years to properly harvest, so jute is called as a fast-growing plant. Jute can reduce the cost of paper pulp production due to its fastgrowing efficiency. Every year the production of jute sticks is an average of 3.0 million tonnes in Bangladesh (Mohammad Mahbubul Islam, 2019a; Rahman et al. 2012). Jute plants also purify the air. Per hectare of jute plants can absorb 15 M tonnes CO2 which protects the destruction of the ozone layer and emits 11 M tones of O2 in the atmosphere which is need for livelihood. Table 1.5 shows that every year jute plants absorbed 7302.38 K tonnes of CO2 and emit 5309.91 K tones on average. So, jute cultivation process is eco-friendly (Khan and Khan 2015; Mohammad Shahidul Islam and Ahmed 2012). Jute products are also environmental friendly. They are much better than synthetic fiber. It is 100 percent biodegradable and recyclable. Geotextile is an eco-friendly jute product. It can be used for river embankment, road construction, dam, etc. which will be low cost, prevent landscape erosion. At present Bangladesh has invented jute-based single-use poly bag which is completely bio-degradable and is an

America

Africa

Oceania

382,388

487,979

508,616

354,515

270,838

302,026

328,363

260,108

286,429

249,563

2011

2012

2013

2014

2015

2016

2017

2018

2019

200,520

238,680

209,041

28,538

234,187

213,728

303,994

448,579

436,094

329,790

24,029

24,007

25,539

23,392

23,463

25,588

22,910

23,867

20,167

13,927

11,227

9839

8816

9830

14,223

9563

5689

9924

13,291

15,121

13,699

13,792

16,626

9664

29,941

21,336

21,386

25,117

17,609

22,633

88

111

86

96

212

623

536

1129

818

917

174,707

184,900

203,962

301,551

244,555

178,980

230,418

282,050

342,090

285,128

127,155

140,693

150,433

258,389

178,565

128,973

185,320

227,929

286,749

235,125

Asia

World

Europe

World

Asia

Import Value (in thousand USD)

Import Quantity (Tone)

2010

Year

Table 1.3 Comparative data of the import quantity and import value of Jute (FAOSTAT 2020)

22,122

21,456

24,115

21,106

20,107

21,908

19,602

20,322

21,222

15,655

Europe

10,144

8708

8997

10,790

12,573

8125

5027

8453

13,648

12,858

America

15,082

13,818

20,202

11,060

33,203

19,841

20,189

24,318

19,930

21,236

Africa

204

225

215

206

107

133

280

1028

541

254

Oceania

6 Md. S. Jahan et al.

1

Economic Importance of Jute

7

alternative to single-use plastic bags. Because plastic bags need 100 years to decompose in the environment and it pollutes the environment and nature directly and indirectly. This jute cellulose Sonali Bag is grate invention in modern era (Ghorai and Mazumdar 2020; Aziz et al. 2020; Mohammad Shahidul Islam and Ahmed 2012; Pavel and Supinit 2017; Rafiqul Islam 2019b).

1.4

Economic Development

See Table 1.5.

1.4.1 Jute for Farmers Jute is not only environmentally beneficial but also economically valuable. Sheheli and Roy obtained the statistics of the economic situation of jute-cultivating farmers. In Kishoregonj district in Bangladesh, they selected 100 farmers in two villages (Nathapa and Damor) of Sadar Upazila of Kishoregonj to interview them on changes their economy and lifestyle based on jute cultivation. That statistics showed that 61 percent of farmers found an improvement in their quality of living within four years (Table 1.6). Most farmers grow

deshi jute for quality fiber and abundant adaptability. The demand of jute fiber is increased so the jute-cultivating area aggrandizes to abrogate of rice cultivation. In addition, farmers are motivated to cultivate jute where approximately 15 takas per kg was required for jute cultivation. This statistic indicated approximately 40% cost expenses in fiber weeding and extraction. The study confirmed that most farmers have found improved socioeconomic conditions through jute cultivation (Sheheli and Roy 2014). Afroz, S. and M.S. Islam found that the statistic compares the profitability of jute and Aus cultivation, in this reason they were selected three villages of Raipura upazila in Narsingdi where 50 percent farmers are cultivated jute and 50 farmers percent are cultivated aus rice but jute cultivated farmers was three-time benefited than aus cultivated farmers (Table 1.7; Afroz and Islam 2012).

1.4.2 Increase Physical and Chemical Properties of Soil Due to the soil properties, crop productivity decreases. Many researchers found that jute plants can be helpful for enhancing the fertility of

Table 1.4 Estimated amount of N, P, and K in fiber sticks and leaves as % of total dry weights of products (Mohammad Shahidul Islam and Ahmed, 2012). (Reprinted from under Open Access License) Dry fiber (%)

Dry sticks (%)

N

0.43

0.21

3

P2O5

0.19

0.09

0,37

K2O

1.65

0.75

2.2

Type of product nutrients

Table 1.5 Contribution of jute on the environment (Mohammad Shahidul Islam and Ahmed 2012) (Reprinted from under Open Access License)

Contribution of jute

Dry leaves (%)

Amount (Tone/ hectare)

Fiber production

1.98

Jute Stick

4.94

Leaf

1.92

Rotten Water

1.07

Root

0.85

Carbon-oxide Absorbent

14.66

Oxygen Emission

10.66

8 Table 1.6 Overall impact of jute cultivation on the livelihood of jute farmers during the past four years (n = 100) (Sheheli and Roy 2014). (Reprinted from under Open Access License)

Table 1.7 Comparative costs and returns of jute production (Afroz and Islam 2012). (Reprinted from under Open Access License)

Md. S. Jahan et al. Statement

Optioning of jute farmer (%) Improved

Same as before

Decreased

Household Income

68

28

4

Housing Condition

55

45

0

Health Situation

36

52

12

Participation in social activities

70

20

10

Freedom in cash expenditure

72

25

3

Overall livelihood

61

35

4

Particulars

Jute

Gross return

83,717.77

Total cost

50,254.77

Non-cash cost

17,745.54

Cash cost

32,508.65

Net return

33,463.58

Return over cash cost (TK)

51,209.12

Return over non-cash cost (TK)

69,972.23

BCR (Undiscounted)

the soil. They found out jute’s dry leaf and root provided many important ingredients for soil fertility (Islam and Ahmed 2012). Jute geotextiles are another environmental-friendly product of jute that helps to crop production by reducing soil limitation and enhancing the properties. It also protects seed from degradation and enhances vegetation by seedling emergence and seed germination. Many researchers studied jute agro textile which can be used for mulching. They use jute agro-textile on chili, tomato, and banana crops and they found out it is increasing the soil moisture content, available N, P, K contents, organic C, and microbial properties in the root part. They used different amounts of jute agro textile on the plant such as1000, 800, 600, 400, and 200 GSM, respectively. For banana 800

1.7

GSM, tomato 600 GSM, and chili 400 GSM show good results. The results indicated that soil properties enhance as per requirement for the plant and increased availability of nutrition for the plant in the soil. All this information pointed out the physical and chemical properties of soil can be easily enhanced by jute and jute agro textile (Sarkar et al. 2020; Adhikari et al. 2016).

1.4.3 Jute Can Be Cultivated in Difference Environments Copper toxicity is a big issue for agricultural land. Phytoremediation is a process that can be stabilize, remove or transfer heavy contaminants

1

Economic Importance of Jute

in agricultural lands. Jute plant is the best solution for this bioremediation process. Because jute plant can easily grow in Cu-contaminated soil and its growth leads to phytoremediation material in the soil for destroying great amount of Cu (Saleem et al. 2020).

1.4.4 Non-price Advantages from Jute Cultivation Since sixteenth century, Indians are using jute for fiber collecting and sacking. Then it is turned as the livelihood of millions of people, which is now a less profitable good in the community. But for motivating the farmer to cultivate jute, it is necessary to find some nonprofit advantage from this crop and researchers found some motive forces. Jute not only provides fiber but also sticks which can be used as 77% fuel for cooking. Jute stick is the main biomass of jute fiber production in which only 4–6% fiber is found. It also clean 70% of the agriculture field for the next crop (Chapke 2013).

1.4.5 Business Development Using Jute and Jute-Derivative Products Jute statistics in 2013 to 2019 shows that the market value of jute fiber increased and forecasted to increase than the years when compared

Fig. 1.6 Jute fiber market size by product 2013–2024 (Reprinted from under Open Access License)

9

to 2020 to 2024 market (Fig. 1.6) (Global Jute Fiber Market Research (2015–2019) and Future Forecast (2020–2025), 2019).

1.5

Health Benefits of Jute

Jute (Corchorus spp.) leaves are a good source of nutrition. They contain vitamins A, C, and E, and also protein and fulfill in minable nutrition like iron and calcium. Vitamin C helps in woundhealing quickly, enhances the immunity of cells, clears and smoothens the skin, and calcium helps to enhance the strength of teeth and bone. Iron keeps the red blood cell healthy. In Asia, the leaves of C. capsularis and C. olitorius are used as a vegetable. Also, jute leaves are used in different types of products such as leaf juice, fried leaf, skincare cream. Fresh jute leaves have many antioxidants so this is helpful in protecting from incurable diseases such as diabetes, cancer, hypertension, and heart disease. Also used to treat different types of diseases such as cystitis, dysuria, and fever. It is also used as a herbal medicine to cure cystitis, dysentery, gastric, and fever. 17 genotypes of Corchorus spp. contain different ranges of b-carotene from 34.33 to 81.33 mg per kg with an average of 60.20 mg per kg, which is good for eyesight. Few researchers also found 8 mineral elements and 17 kinds of amino acids and also crude proteins, soluble sugar and crude ashes are contained in Corchorus Olitorius L. Apart from the Corchorus

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Md. S. Jahan et al.

spp. genotypes, jute have some beneficial for wild species. They contain more vitamins and minerals, more protein and ash (Islam and Ahmed 2012; Islam 2013; Tareq et al. 2020; Traoré et al. 2017; Li et al. 2010; Choudhary et al. 2013).

1.6

Applications of Jute

1.6.1 Traditional Uses Jute is of great commercialization importance, which has been cultivated by farmers since a long time ago and used in different types of essential housing materials. In the primary cultivating period, jute fibers are made as ropes by hand spinning for navigation and domestic agriculture. Also jute is used in mechanically processing yarn which is used in handloom to making woven fabric, e.g., (i) sacking and hessian for different goods packaging, (ii) matting and bedding for household purpose, (iii) roofing fabrics, electric cables, windscreens, cordage for industrial propose, (iv) CBC (Carper Backing Cloth). Jute fabric is also used in sandbags, tents, rifle pull through, water bags, shopping bags, official bags, netting and stipe, etc. (Coelho 2013; Bag et al. 2016; Rahima Akter 2015).

1.6.2 Modern Uses In modern times, jute fiber and fabric are used to make cellulose, paper, dyed yarn, multiplied yarn, polished yarn, shoe, shikha, printed fabric, tape, scrim cloth, pillow cover, panels, laundry bags, vanity bag, toys, medicare textiles, dress materials, ladies purse, purse, school bag, tie, calendar, etc. Jute fabric and synthetic resins combination is used in water-repellant fabric, rope and fire-resistant cloth, dyed and printed furnishing textile, roofing, bituminized compounds, laminated compounds, needle felt, floor tiles, substitute, etc. In this century, jute-plastic reinforced composite material is used as an alternative to fiber-glass composite. This composite material can be used in furniture, grain seed, and water storage tanks, ships and boat

body, housing materials, etc. (Islam and Ali 2017). Jute and natural rubber-latex composite show an imaginary property. This composite has shown high sound absorption properties than glass composite, oxygen index value is higher than fiberboard so it can be used as a fire retardant material, low smoke density rating, low light absorption ability, and self-extinguishing ability in fire (Fatima and Mohanty 2011). Singh, H., et al. studied that Polylactic Acid (PLA) films adjoined with jute woven fabric to make composite material which is used as a composite materials. This composite material is an environment-friendly, biodegradable (Singh et al. 2018). Uddin et al. used jute, cotton, and fiber glass reinforced corrugated composite sheet for rural housing and poultry housing. In this composite reinforcing, they used polyester resin as a matrix compound. They found that this composite material is long-lasting, cost-effective, manufacturing is easy, and eco-friendly (Uddin et al. 2020). Zakaria et al. studied about jute fiber reinforced composite. They found that this composite increases compressive, tensile, and flexural strength compared with ordinary concrete (Zakaria et al. 2017). Uddin et al. studied about jute and cotton and polyester matrix based reinforced composite material. They used MEKPO (methyl ethyl ketone peroxide), nanocellulose which is suitable for the housing of poultry (Uddin et al. 2020). Siddiquee et al. used jute with polyethylene (PE) and polypropylene (PP) reinforced composite material. They found that it has better natural weather and soil degradation rate than PE and PP plastic (Siddiquee et al. 2014). Jute is used in civil construction application material of geotextiles, which are low cost, higher strength, lower density, natural abundance, biodegradable. Because of these properties, it is suitable for separation, drainage, filtration function can overcome in the problem of geotechnical (Nikita Choudhary 2013). Regenerated yarn is synthesized from cellulose. Jute is one of the most abandoned sources of cellulose so regenerated yarn can be synthesized from jute-based cellulose (Kocić et al. 2019; Manian et al. 2018; Jiang et al. 2020; Orelma et al. 2020).

1

Economic Importance of Jute

Worldwide huge amount of food packaging material are used daily, however that plasticbased packaging material contributes to environmental pollution. Bangladesh has invented jute-based polybag with biodegradable and water-soluble properties as a solution for plastic pollution in soil and water (Pavel and Supinit 2017). Cejudo-Bastante et al. studied that they used jute fibers and red grape pomace extract to make food packaging material. Enhanced Solvent Extraction Pressurized Liquid Extraction technique is used where 50 MPa, 55 °C, and C2H5OH present in this process (CejudoBastante et al. 2021). Jute’s chemical composition contains a large amount of lignin. The chemical structure of lignin is very complex, that is, hydroxyl phenyl propanoids. Lignin mainly consists of guaiacyl, phydroxyphenyl, and syringle units derived from p-Coumaryl, coniferyl and sinapyl alcohols. For this compound, lignin is converted to biofuel by the pyrolysis process (Balan 2014; Kim et al. 2020). By primary treatment, depolymerization, hydraoxygenation, and alkalization lignin are converted to jet fuel range cycloalkanes and aromatic-hydrocarbon is explored (Cheng and Brewer 2017). Nowadays, jute stick is converted into bio-fuel by the pyrolysis process. In pyrolysis reactor which is at a temperature of 425 °C and run for 30 min, jute stick is converted into biofuel (Ferdous et al. 2017). In the twenty-first century, jute cellulose is used to produce eco-friendly personal protective equipment (PPE). Bangladeshi scientist M. A. Khan and his team used jute cellulose with polysaccharide (chitosan) for the fabrication of PPE. They studied that this PPE is antimicrobial, non-toxic, easily biodegradable, and compostable (Mahfuz 2020). Many types of research are used in cellulose and cellulosic derivative to make hydrogel and superabsorbent polymer. Aili Suo et al. studied that cellulose with poly (acrylic acid-coacrylamide) grafted polymer has 920 g/g water absorbency. Klinpituksa, P. et al. found 544.95 g/g water absorbency, Zuoxin Liu et al. got 417 g/g water absorbency. Sutradhar SC et al. studied that CMC/acylic acid with gamma

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radiation for grafted polymer showed 16,000% absorbency rate. Yang, X., et al. and Fu, L.-H., et al. studied that cellulose-based hydrogel can be suitable and hygenic for biomedical application (Mingyang Chen et al. 2020; Liu et al. 2009; Klinpituksa and Kosaiyakanon 2017; Suo et al. 2007; Mondal, 2019; Yang et al. 2017; Fu et al. 2019; Sutradhar et al. 2015). Jute contains a large amount of cellulose. The hydroxyl groups (–OH) of cellulose can be partially or fully reacted with various reagents to afford derivatives with useful properties like mainly cellulose esters and cellulose ethers (– OR). The most important modified cellulose polymers are methylcellulose (MC), ethyl cellulose (EC), hydroxylpropylcellulose (HPC), hydroxyethylcellulose (HEC), carboxymethylcellulose (CMC), cellulose microcrystalline, cellulose nanofiber (CNF), and cellulose nanocrystal (CNC). These modified cellulose is used in industries such as food additives, pharmaceuticals and cosmetics, washing ingredients, dentifrice, etc. (Ria et al. 2020; Crabbe-Mann et al. 2018; Ciolacu and Suflet 2018; Pal et al. 2019; Zennifer et al. 2020; Sodipo and Owolabi 2019; Rabbi et al. 2019; Hossain et al. 2021; Nsor-Atindana et al. 2017; Fathi et al. 2019).

1.6.3 Hi-Tech Uses This computing world is dependent on technology. Every time science inventes new equipment for human beings. In this continuity, jute fiber participates in this computing age. Dubey, A. and his team converted jute fiber into a more valuable and good quality carbon material through biocharging supercapacitor and powerful battery (Dubey et al. 2017). Mekonnen, B. and Y. Mamo studied that jute fabric and glass fiber with polyester reinforcement composite show good flexural properties and also good damping ratio which is suitable for wind turbine blades (Murdani et al. 2017). Mekonnen, B. and Y. Mamo studied in 2020 that bamboo/jute/polyester composite shows the 131.5 MPa flexural strength, 72.2 MPa tensile strength, and

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Md. S. Jahan et al.

Table 1.8 Comparative properties of synthetic and jute geotextile (Choudhary 2013). (Reused from Choudhary 2013 with permission from Scitec Publications) Sl. no

Criteria

Jute Geotextile

Synthetic Geotextile

1

Biodegradability

Designed biodegradable

Non-biodegradable

2

Ionic property

Anionic

Non-ionic

3

Metal Content

None

Mercury, Cadmium, Lead, Zinc, Cobalt, Nickel, etc

4

Photodegradability

Photodegradable

Non-photodegradable

5

Warming Effect

No effect

Soil temperature increase of 1–2 °C

6

Filler/ Stabilizer/ pigment

Absent

Present

7

Biomass

Fertilizer effect

Harmful effect

8

Stacking effect

Non-slippery

Slippery

9

Leaching effect

-

pH changes

10

Effect on water

No pollution

Pollution on leaching

11

On burning

CO2 evolves

Toxic gas evolves

12

Effect on aquatic animals microbes etc

Harmless

Harmful

13

Effect on plants

Helpful

Harmful

14

Effect on biological pathway

No disturbance

Creates barrier

15

Effect on agriculture

No effect

Enhance insects growth due to increase in soil temperature

16

Size/ Shape

Any dimension

Any dimension

17

Expected design life

Possible

Not possible (If possible then with complication)

18

Cost

Cheap

Costly

19

Manufacturing process

Relatively safe

Harmful

20

Energy consumption in spinning fiber

Low energy consumed

High thermal energy required

2.98 mm elongation. Based on these properties, they suggested that this composite can be used in small wind-turbine blades (Mekonnen and Mamo 2020). Jute/granite powder/epoxy reinforced composite material is shown to have 34.2 MPa tensile strength, 97.8 MPa flexural strength, and 44Hv hardness, respectively. So this result can be used in wind turbine blades according to Pawar et al. 2017. Niedermann, P. et al. studied that jute fiber-carbon fiber with epoxy matrix based reinforced composite material which is is shown to have 100 MPa tensile strength, 9.22 GPa Young’s modulus, 131.66 MPa bending strength, and 11.13 GPa bending modulus. This

composite shows 167 °C glass transition temperature. So they suggested that this composite is suitable for potential aircraft interior (Niedermann et al. 2015). High yield of cellulose nanocrystal (CNC) can be extracted from jute fiber. Many emerging products are made using CNC: (i) Biomedical engineering: antimicrobial/antiviral systems, tissue engineering, drug/gene delivery, biosensors, protein scaffold/biocatalyst, alternative of graphene, nanocomposite, oil filter, (ii) Wastewater treatment: adsorbents, additional water treatment techniques, (iii) Energy and electronics sector: supercapacitors, conductive films, substrates,

1

Economic Importance of Jute

sensors, templating material/separator for energy storage, (iv) Textile sector: bulletproof dress, smart garments, regenerated high strength yarn, (v) Composite: alternative of glass, kevlar, SS, carbon and other fibers (Garces et al. 2020; Luo et al. 2019; Nitta and Numata 2013; Tracey et al. 2020; Noguchi et al. 2021; Wei Chen et al. 2019; Dhar et al. 2018; Chowdhury et al. 2019; Gonçalves et al. 2019; Fan et al. 2020; Patwary and Syduzzaman 2015).

1.6.4 Future Applications of Jute Jute cellulose based cellulose nanocrystal (CNC), CNC with graphene, carbon nanotube, ultra-high molecular weight polyethylene, fluorescence, carbon fiber, SS, kevlar, glass composite and CNC with drugs can be used in rocket body, missile body, satellite antenna, satellite body part, radiation shielding material, a new drug to protect harmful microorganisms, e. g., virus, bacteria, gene and drug delivery, etc.

1.7

Conclusion

Jute is economic and environment friendly. Jute polymer and jute-based cellulose derivatives application is raising in recent years. Jute composite is cost effective and eco-friendly. Hence, this composite can be used as an alternative for harmful materials. This study has shown that jute fiber can be used in housing as a hi-tech material. The proper utilization of jute fiber can lead economic and environment sustainability.

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15 Pavel, S., & Supinit, V. (2017). Bangladesh Invented Bioplastic Jute Poly Bag and International Market Potentials. Open Journal of Business and Management, DOI, 10. Pawar M, Patnaik A, Nagar R (2017) Investigation on mechanical and thermo-mechanical properties of granite powder filled treated jute fiber reinforced epoxy composite. Polym Compos 38(4):736–748 Rabbi MA, Rahman MM, Minami H, Rahman MA, Hoque SM, Ahmad H (2019) Biocomposites of synthetic polymer modified microcrystalline jute cellulose particles and their hemolytic behavior. Cellulose 26(16):8713–8727 Rahman, M. S., Khan, M., & Abser, M. (2012) Formation and utilization of jute composite and observation of its physical properties and it’s bio-degradability. Ria, S. A., Ferdous, T., Yasin Arafat, K. M., & Jahan, M. S. (2020). Pulp refining in improving degree of substitution of methylcellulose preparation from jute pulp. Biomass Conversion and Biorefinery, 1–9. Roy, S., & Lutfar, L. B. (2012). Bast fibres: jute. Handbook of Natural Fibres (pp. 39–59). Elsevier. Saleem MH, Rehman M, Kamran M, Afzal J, Noushahi HA, Liu L (2020) Investigating the potential of different jute varieties for phytoremediation of copper-contaminated soil. Environ Sci Pollut Res 27:30367–30377 Sarkar, A., Tarafdar, P., & De, S. (2020). Effect of Woven Jute Agro Textile Mulch on Soil Health and Productivity of Banana (Musa domestica L.) in New Alluvial Soil. International Research Journal of Pure and Applied Chemistry, 1–7. Sheheli S, Roy B (2014) Constraints and opportunities of raw jute production: a household level analysis in Bangladesh. Progress Agric 25:38–46 Siddiquee KM, Helali MM, Gafur MA, Chakraborty S (2014) Investigation of an optimum method of biodegradation process for jute polymer composites. Am J Eng Res 3(1):200–206 Singh H, Singh JIP, Singh S, Dhawan V, Tiwari SK (2018) A brief review of jute fibre and its composites. Materials Today: Proceedings 5(14):28427–28437 Sodipo, B. K., & Owolabi, F. A. W. T. (2019). Extraction of Nano Cellulose Fibres and Their Eco-friendly Polymer Composite. Sustainable Polymer Composites and Nanocomposites (pp. 245–257). Springer. Suo A, Qian J, Yao Y, Zhang W (2007) Synthesis and properties of carboxymethyl cellulose-graft-poly (acrylic acid-co-acrylamide) as a novel cellulosebased superabsorbent. J Appl Polym Sci 103 (3):1382–1388 Sutradhar SC, Khan MMR, Rahman MM, Dafadar NC (2015) The synthesis of superabsorbent polymers from a carboxymethylcellulose/acrylic acid blend using gamma radiation and its application in agriculture. Journal of Physical Science 26(2):23 Tareq Z, Bashar KK, Amin R, Sarker MDH, Moniruzzaman M, Sarker MSA et al (2020) Nutritional composition of some jute genotypes as vegetables.

16 International Journal of Vegetable Science 26(5):506– 515 Tracey, C. T., Torlopov, M. A., Martakov, I. S., Vdovichenko, E. A., Zhukov, M., Krivoshapkin, P. V., et al. (2020). Hybrid cellulose nanocrystal/magnetite glucose biosensors. Carbohydrate Polymers, 247, 116704. Traoré K, Parkouda C, Savadogo A, Ba H, F., Kamga, R., & Traoré, Y. (2017) Effect of processing methods on the nutritional content of three traditional vegetables leaves: Amaranth, black nightshade and jute mallow. Food Sci Nutr 5(6):1139–1144 Uddin MM, Karim R, Kaysar M, Dayan MAR, Islam KA (2020) Low-Cost Jute-Cotton and Glass Fibre Reinforced Textile Composite Sheet. Int. J. Mat. Math. Sci 2(1):1–7

Md. S. Jahan et al. Uddin, M. M., Sayeed, M. A., Dayan, A. R., & Habib, M. M. 2324 (2021) ‘Design and development of jutecotton reinforced polymer composite for rural poultry housing’ AIP Conference Proceedings. AIP Publishing LLC, p. 030014 1 Yang X, Liu G, Peng L, Guo J, Tao L, Yuan J et al (2017) Highly efficient self-healable and dual responsive cellulose-based hydrogels for controlled release and 3D cell culture. Adv Func Mater 27(40):1703174 Zakaria M, Ahmed M, Hoque MM, Islam S (2017) Scope of using jute fiber for the reinforcement of concrete material. Textiles and Clothing Sustainability 2(1):1–10 Zennifer A, Senthilvelan P, Sethuraman S, Sundaramurthi D (2020) Key advances of carboxymethyl cellulose in tissue engineering & 3d bioprinting applications. Carbohydrates 117561

2

Botany of Jute (Corchorus Spp.) Rakha Hari Sarker

Abstract

Jute fibers are procured from two species, namely Corchorus olitorius L. and C. capsularis L. belonging to the family Malvaceae. Jute is recognized as among the most important as well as an excellent source of natural fibers of the world. Fibers of jute are very attractive and a magnificent renewable resource because of their biodegradable properties. Apart from the two cultivated species, there are several wild relatives of jute considered as the potential resources for developing tolerance against biotic and abiotic stresses in cultivated varieties. The development of an ideal jute plant through sexual hybridization is a long-time desire of the jute breeders involving the two cultivated as well as the wild species. Desired improvement of jute plants through conventional breeding and modern biotechnology has been impeded as a result of the existence of sexual incompatibility among jute species, and its recalcitrant nature towards plant genetic transformation respectably. This chapter focuses on the taxonomic and botanical descriptions of Corchorus spp. including anatomy, physiology, cytology, genetics, as

R. H. Sarker (&) Department of Botany, University of Dhaka, Dhaka 1000, Bangladesh e-mail: [email protected]

well as a brief description of its origin and distribution. Moreover, it includes an account of the reproductive development following self- and cross-pollinations in Corchorus spp. as well as a short elucidation of previous breeding efforts in jute. The information compiled here may be useful in planning the future research program towards the improvement of jute.

2.1

General Account

Jute (Corchorus spp.) is the major long vegetable fiber of the world. The term jute is applicable both for the plant and the fiber which is obtained from two intimately related, annual herbaceous self-pollinated species of the genus Corchorus, namely C. olitorius and C. capsularis belonging to the family Tiliaceae (currently desegregated into family Malvaceae). Jute fibers derive from the secondary phloem of these plants and it is regarded as the foremost bast (phloem) fiber and second most important textile fiber after cotton (Kundu 1956; Dempsey 1975). Although there has been a decline in the volume of trade, jute is still considered as the most significant foreign currency earner of several jute-growing countries including Bangladesh. Due to its golden and silky shine fiber, it is designated as the “Golden Fiber of Bangladesh” and mostly regarded even as the pride as well as the prime cash crop of the country. For centuries, jute contributes towards

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_2

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the economy, agriculture, and industry of Bangladesh and the eastern part of India. Jute is so much attached to the culture and economy of the subcontinent that it has been placed in the National Emblem of Bangladesh, the monogram of Bangladesh Bank (Central Bank of Bangladesh), and in the state emblem of Pakistan. Jute is a well-built natural fiber, important for its complete biodegradable and recyclable properties and thus not harmful to the environment. The long shiny natural fiber is generally rough to touch and can be gyrate into rough, strong threads when required. With exception of cellulose (60%), other prominent constituents of jute fiber are hemicellulose (23%) and lignin (14%). This fiber possesses high tensile strength, low extensibility, and ensures better pervious of fabrics. The properly extracted fibers are fairly lustrous, pale-white to brown, and 1–4 m long with moderate tenacity (20–25 gtex-i). Unlike cotton, this multi-constituent fiber has the capacity to be mixed with both synthetic and natural fibers, and it receives a wide range of cellulosic and pigment dyes (Sreenath et al. 1996; Basu et al. 2005). Apart from fiber, sticks obtained from jute plants are also very important both for traditional and industrial applications. Although jute is produced by more than ten countries globally, major production of raw jute can be procured from Bangladesh and India (Hossain et al. 1994). Bangladesh used to produce jute at a commercial scale and even a few years ago contributed a significant portion of the country’s foreign exchange. Unfortunately, the production of jute is getting very uneconomic and losing its market value gradually and thus local jute industries are also shrinking remarkably. Currently, farmers are less interested in jute cultivation due to the high cost of production and not getting adequate market value. In order to enliven the agriculture productivity and to fulfill the industrial requirements, it is a demand to develop improved varieties of jute with high yielding potentials and suitable for cultivation under different agro-ecological conditions. This will certainly restore the heritage of jute both culturally and economically.

R. H. Sarker

The cultivars of jute possess a number of desired characteristics and the wild germplasm contains several diverse qualities and variability that is believed to be the potential resources for jute improvement (Islam et al. 1992). Improvement of jute through hybridization is a long-time aspiration of the jute breeders involving both the cultivars. Since the early endeavors of Finlow (1921; 1923), the scientists from Bangladesh and India particularly made enormous attempts to combine good characteristics of jute plants through hybridization. Successful recombinants have not been achieved yet through these intensive efforts (Ganesan et al. 1957; Islam and Rashid 1960; Iyer et al. 1961; Swaminathan et al. 1961; Raut and Naik 1983). Further these hybridization programs, selection, and mutation breeding have produced limited success in the varietal improvement of jute. Techniques of modern biotechnology including plant genetic transformation have been applied to obtain genetic gain in cultivated varieties, but the success following these techniques are still in infancy. Nevertheless, a number of successful studies have so far been done carried out towards in vitro regeneration and genetic transformation of recalcitrant jute cultivars. These findings certainly encompass the potential improvement of jute through the application of modern biotechnology (Ghosh et al. 2002; Sarker et al. 2008; Saha et al. 2014; Zhang et al. 2015, 2021; Majumder et al. 2018). However, the development of the most desired stress tolerance as well as the improvement of fiber quality through conventional breeding has been hampered due to the sexual incompatibility among jute species. In addition, recalcitrant nature of this plant towards in vitro culture, as well as the non-availability of effectual and reproducible genetic transformation protocol, has also obstructed its potential improvement. Thus, the future genetic improvement of jute mainly depends on its expressive genomic information, suitable genotypeindependent genetic engineering, and transformation protocols as well as the successful application of genome editing techniques like,

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Botany of Jute (Corchorus Spp.)

CRISPR/Cas technology (Zhang et al. 2019; Zhu et al. 2020).

2.2

Origin and Distribution of Jute

The “Index Kewensis (IK)” and its supplements recorded more than 170 species in Corchorus (Edmonds 1990; Mahapatra and Saha 2008). A wide range of studies has been carried out to understand the origin, distribution, and evolution of jute plants. Based on species concentration, East and South Africa were considered to be the center of diversity and place of origin of jute (Kundu 1951; Singh 1976; Edmonds 1990). Not very much is known about the early history of jute. Nonetheless, historical records indicated that the ancient Greeks, Egyptians, and Indians (“Patta” in Sanskrit) used jute for various applications (Watt 1889) and it has been used since ancient times in parts of Africa and Asia as strong threads as well as a textile fiber. Further, it was indicated that the Europeans started using Indian jute for packing purposes towards the end of the eighteenth century (Kundu et al. 1959). The origin of the term “jute”is also not very clear. It is most likely an Anglicized form of the word “Jhout or Jhut” used in some parts of India including Shibpur Botanical Gardens, Kolkata. Early large-scale commercial use of jute was recorded in 1828 when the first shipment of jute was made from India to Europe (Kundu et al. 1959). During the period of 1828 to 1833, jute industries were developed and flourished in Dundee, Scotland, and raw jute was exported from India for the jute mills of Scotland. Prior to 1947 (before independence), India produced about 95% of the world’s jute fiber, most of which was cultivated in the state of East Bengal (currently known as Bangladesh). Apart from the Indian subcontinent, this fiber was introduced to Brazil in the early twentieth century. During 1929–1930, a group of Japanese also tried to grow jute in mainland Japan. Additionally, cultivation of jute has been extended in several countries of the world including Nepal, Thailand, Indonesia, China, and Brazil. Interestingly, Brazil is the only country that

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produces two crops of jute annually on the same land (Dempsey 1975). From the obtainable information, it is understood that there are some disagreements on the origin and natural distribution of the two commercially important species, C. olitorius L., and C. capsularis L. as well as the wild relatives of Corchorus spp. Naturally, Corchorus germplasm is used to grow under a variety of ecological conditions. Corchorus capsularis was reported to be obtained naturally in many parts of India and China. This plant is believed to be native to the Indo-Burma region, however, according to Vavilov’s concept it was included in South China (Kundu 1951). Therefore, C. capsularis was regarded to be originated in South China from where it was migrated to India and Bangladesh (Purseglove 1968). However, in a separate view, this species was not contemplated as an immigrant to India but had evolved in Indo-Myanmar neighborhoods including South China (Mahapatra et al. 1998). Available information also indicated that this species has not been reported from Australia and Africa. Contrastingly, C. olitorius has been reported to occur in Asia, North Australia, and Africa. It has been suggested that Africa is its primary center of origin while India or Indo-Burma is a secondary center for this plant (Kundu 1951; 1956). This species has, however, become naturalized in most tropical regions of the world (Edmonds 1990). C. olitorius appears as wild, weedy, and cultivated types both at higher and lower altitudes with soils ranging from clay to sandy loams. The range of variation has been reported to be maximum in the African continent. Africa is considered to be the birthplace of C. olitorius. Apparently, C. olitorius grows wild in most of the tropical and subtropical regions of Asia and Africa and it is presently available in the Middle East, the Indian subcontinent, Thailand, Laos, Nepal, China, Myanmar, Malaysia, the Philippines, and Vietnam in Asia. This species is also available in Ghana, Nigeria, Sierra Leone, Senegal in Africa, and Brazil, Peru, Caribbean islands in South America. In Bangladesh, Jute is cultivated throughout the country. In India, apart from West Bengal, Bihar and Assam,

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R. H. Sarker

the other major jute growing states are Uttar Pradesh, Meghalaya, and Tripura. Herbarium specimens of C. olitorius are available in many important herbaria all over the world, such as the Kew Gardens Herbaria, the Australian National Herbarium at Canberra, the herbarium at Leningrad, Moscow, the New York Botanic Garden Herbaria, East African Herbarium in Nairobi, Kenya (Professor A S Islam, personal communication). The availability of the well-preserved annotated specimens of C. olitorius in the different herbaria indicates that it is cosmopolitan in occurrence throughout the tropical and subtropical regions. Bengal delta plain (Ganges Delta) is considered as the best area of jute cultivation most of which is covered by Bangladesh, and the rest is occupied by West Bengal of India. There are about 6,000 jute accessions available worldwide. In the past few years, about 5,000 genotypes of jute and related fiber crops have been collected through international efforts. These genetic resources have been maintained in the Germplasm Center of Bangladesh Jute Research Institute (BJRI), Dhaka.

2.3

Botanical Description

Botanical information including the taxonomic position is very important for the proper scientific identification of plant species of interest. The knowledge about the features of two commercial jute producing plants as well the wild species are significant for their utilization in various scientific endeavors including their varietal improvement and maintaining the diversity of jute plants/germplasm for the future.

2.3.1 Taxonomic Position Both C. capsularis and C. olitorius are diploid (2n = 14) in nature with uniform and regular meiosis (Sharma and Roy 1958; Dutta 1968). These plants are mostly self-pollinated (Dutt and Ghosh 1962), thus the verities evolved from these two plants are pure lines without having

major genetic variation, but they are very much isolated sexually. C. olitorius is popularly known as “Tossa” or “Mithapat” in Bangladesh and “Daisee” in India while C. capsularis is referred to as “White” jute or “Desi”. Taxonomic positions of the two cultivated species according to Cronquist (1988) are as follows: White Jute (Corchorus capsularis L.):

Tossa Jute (Corchorus capsularis L.):

Kingdom: Plantae Division: Magneoliophyta Class: Dicotyledone Order: Malvales Family: Malvaceae Genus: Corchorus Species: C. Capsularies

Kingdom: Plantae Division: Magneoliophyta Class: Dicotyledone Order: Malvales Family: Malvaceae Genus: Corchorus Species: C. olitorius

2.3.2 Botanical Description of White Jute (Corchorus capsularis L.) This is an annual herbaceous plant with a tap root system. Generally, these plants are 1.5–3.6 m tall. The stem of this plant is erect, cylindrical, glabrous, and woody with strong phloem fiber. The stem is generally green to dull coppery red to pink in color; branched or unbranched in nature. The leaves are simple, alternate, lanceolate, ovate, oblong, accuminate with a serrated margin of the lamina (Fig. 2.1). Petiole (4–8 cm); varies from green to pink in color in different varieties. The inflorescence is an axillary cyme. The flowers of this plant species are actinomorphic, pedicellate, hermaphrodite; calyx with 5 sepals, polysepalous, aestivation valvate; corolla with 5 petals, polypetalous, yellow or pale yellow, aestivation twisted. Androecium possesses many stamens, free, and present in several whorls, anthers are yellow to pale yellow; anthesis occurs 1–2 h after sunrise; gynoecium: ovary rounded with five carpels, syncarpous, ovary superior, placentation axile. There are 50 ovules in the ovary; style 2–4 mm; stigma pubescent in nature. Fruits are capsule, rounded, 1.0–1.5 cm in diameter. Wrinkled, rarely smooth, muricate, 5-

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Botany of Jute (Corchorus Spp.)

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corolla with petals 5, yellow, polypetalous, aestivation twisted. Androecium: stamens are many, yellow, free, and present in many whorls; gynoecium: ovary elongated, 5 carpels, syncarpous, ovary superior, placentation axile. Fruits are capsules elongated, 6–10 cm long, ridged lengthwise. Seeds are green to steel gray in color and slightly smaller than those of C. capsularis (Fig. 2.3).

2.3.4 Comparison of Two Cultivated Species

Fig. 2.1 Habit sketch of C. capsularis showing plant type, flower, and capsule

locular. Seeds are small and chocolate brown in color (Fig. 2.3).

2.3.3 Botanical Description of Tossa Jute (Corchorus olitorius L.) This plant is also an annual herb with a tap root system. Generally, 1.5–4.5 m tall; the stem of this plant is erect, glabrous, and woody with strong phloem fiber. The stem is green, light red, or dark red in color, there are intermediate types with various shades and intensity of green and red pigments; without vigorous branching habit. The leaves are simple, alternate, glabrous, oblong, and lanceolate with a serrated margin of the lamina (Fig. 2.2). The leaf base possesses a pair of filiform appendages. Both stem and leaves of this plant are highly mucilaginous. The inflorescence is an axillary cyme. The flowers of this plant species are actinomorphic, pedicellate, hermaphrodite; calyx: with 5 sepals, polysepalous, green in color, aestivation valvate;

Cultivated jute evolved through traditional breeding mostly by pure line selection (Ghosh 1983) and these varieties are well characterized based on their pigmentation, stipule character, test of the leaves, petal and anther color, pod shape and size, seed coat color, time requirements to maturity, yield and quality of fiber (Patel et al. 1945). The color of stem, leaf, and petiole in different varieties of jute are remarkably variable in nature. The color of the stem appears to be green, red, and pink or purple, however, no relationship has been established between the stem color and the color of the fiber. Available anthocyanin pigments are appeared to be responsible for the development of patterns of color in jute plants and this pigment variation has been used as a maker in jute breeding programs. The plants of C. olitorius grow taller than C. capsularis. Except in pod shape, it is difficult to distinguish a C. olitorius plant from that of a C. capsularis. The pod of C. capsularis is spherical in shape while the pods in C. olitorius are cylindrical and elongated, 10-ribbed characterized by prominent ridges and furrows, occasionally 10–12 times longer than broad. The tip of the pod unites to form a short beak-like structure. The quality of fiber is different in the two species. The fiber obtained in C. olitorius is mostly softer, stronger, and more lustrous than that of C. capsularis. The fiber of C. olitorius is usually yellowish red. But the fiber of C. capsularis are weaker and less lustrous type and not

22 Fig. 2.2 Habit sketch of C. olitorius showing plant type, flower, floral parts, and capsule

Fig. 2.3 a–d a and b showing frits of C. capsularis and C. olitorius, respectively. c and d are presented to show the seeds of and C. capsularis and C. olitorius, respectively

R. H. Sarker

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Botany of Jute (Corchorus Spp.)

uniform in color, generally varies from pale cream to dull grey or brown and occasionally black. The color variation is believed to be depending upon the quality of the water used in retting as well as the amount of iron in the retting water and its reaction with tannin in the stem. There are two linear stipules, shorter in length than petioles. The leaves are ovate-lanceolate, 3–5 nerved, serrated with a tapering end; the two teeth––one on each side near the base of the lamina, are prolonged into a filamentous structure called serrature. The latter is usually 1.5 cm long. Petioles measure 2–3 cm; stipules are linear and shorter than the petiole, shiny, light green; leaves are 10 to 15 cm long and about 5 cm wide. The plant of C. olitorius bears yellow flowers larger than that found in C. capsularis. Peduncles are 2–3 flowered, shorter than the petiole; sepals sharply pointed; sepal tips are sometimes differently colored than the rest of the structure (a varietal character); petals yellow, spathulate, and larger than the sepal. Stamens are free and indefinite arising from a short torus, style short and stigma is cup-shaped with numerous dry type papillae (Shivanna and Johri 1985). The pods of C. capsularis are globular in shape while those of C. olitorius are cylindrical (Fig. 2.3). Pods of C. olitorius contain black seeds with a greenish tinge; Pods contain 5–6 times more seeds (250– 300) than C. capsularis in which seeds are comparatively larger and their number ranges from 40 to 50 per pod. The characteristics of the root system of the two plants are different. In clayey as well as in sandy-loam soils,, the taproots of C. olitorius grow longer than that of C. capsularis. The secondary roots system is also different in both plants. In C. olitorius, they are well developed and more deeply penetrating while in the case of C. capsularis they are superficial and bushy in nature (Kundu 1956). The flowering patterns of both species are reported to be different. Apart from this, Tossa jute does not stand waterlogged conditions as much as white jute, therefore it is grown on higher lands only. However, white jute can be grown on both high and low lands.

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2.4

Anatomy

Several anatomical studies, particularly, the stem anatomy of jute plants, have been investigated by many researchers mostly to understand the components involved in the development of fiber. It has been demonstrated that fiber quality can be predicted through such anatomical characteristics (Majumder 2002). Moreover, these findings are also important since the anatomical features of donor plants can contribute significantly towards the improvement of fiber quality. Along with these features, the physical parameters of fiber have been investigated to a great extent to understand the process of its enlargement. Interestingly, several species of Corchorus can be identified from the anatomical studies and a strong genetic association between anatomical properties and fiber yield in white jute has been demonstrated by Chen et al. (1990). Jute fibers are certainly composed of several cells and the formation of these cells are associated with cellulose and well-developed layers of lignin and hemicellulose. Eventually, these several layers of cellulose with hemicelluloselignin layers are responsible for the secondary thickening of the cell wall and thus involved in forming a multiple layer composite. These cell walls of the fiber cells are mostly recognized by their composition and orientations. Jute fibers originate from secondary phloem and as such lie external to the xylem cylinder and immediately below the bark. Section through young jute stem showing the formation of secondary phloem fibers is shown in Fig. 2.4. Fibers that grow in the bark of the jute stem are composed of narrow triangular groups with alternative spots of sclerenchyma fiber and soft tissue. The ultimate layers of fiber are evolved through the activity of the cambium and are depending on the growth and vigor of the plant (Kundu 1956; Hazra and Karmakar 2008). Studies involving a number of genotypes of C. olitorious and C. capsularis revealed considerable variation at different growth stages of jute plants and the anatomical features are useful for

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Fig. 2.4 a Fluorescent micrograph of the transverse section of young jute stem showing the position of developing secondary xylem and phloem. b The same as

R. H. Sarker

Fig. 2.4 A but presenting the formation of secondary phloem fibers (arrows)
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Fig. 2.5 Photomicrographs of DAPI-stained mitotic metaphase chromosomes of C. hirtus, C. siliquosus, C. septentrionalis, C. brevicornatus, C. urticifolius, C. pinnatipartitus. (bar = 10 µm)

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Botany of Jute (Corchorus Spp.)

the identification of genotypes without a destructive sampling (Kumar et al. 2014). The degree of variations in length, breadth, and thickness of the wall also the dimensions of the lumen of the fiber cells contrast in different varieties of jute (Haque et al. 1976; Haque 1992). Besides the anatomical studies, the studies related to the mechanical characteristics of jute fibers particularly the compatibility of jute fibers with polymers have been reported to be excellent. Therefore, a variety of composites including jute-epoxy, jute-polyester, and jutepolypropylene have been developed and can be used as low-cost housing elements, silos for grain storage, etc. Proper surface treatment of jute fibers and the use of coupling agents strongly influence the tribological properties of jute fiber (Chand and Fahim 2021).

2.5

Physiology

The growth of jute plants and fiber yield depends upon a number of physiological factors. Several remarkable features of various physiological characteristics have been elaborately discussed by Sen Gupta (1953a, b) and Kar (1959). Physiological responses in different jute species are apparently variable in nature. In most cases, jute plants differ in their flowering time, seed germination time, height, root length, etc. from season to season. Both of the cultivated species are typical short-day plants which means that they flower if they are planted in seasons with day lengths less than 11 h. Physiologically jute is a C3 and short-day plant. Cultivated jute plants show the maximum growth when the seeds are sown in March –April, however, the growth of the plant is found to be minimum when seeds are sown between the months of November and December. The flowering time of cultivated varieties also varies from season to season. Due to specific photoperiod requirements, the optimum time of harvest for fiber (commercial purposes) and that for the seeds (propagation purposes) is generally separated at an interval of 6 weeks or more. The vegetative growth in jute is favored by long-day condition, while the

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reproductive growth is particularly dependent on the short-day condition (Sen Gupta and Sen 1944). Flowering is delayed when the cultivated varieties are sown between March and April and the flowering time was found to decrease with the late sowing of seeds. The cultivated varieties show their variation in seed germination time in the field throughout the year. Their seed germination rate and germination time vary from plant to plant. The cultivated jute species show about 100% seed germination but the germination rate of wild jute species was variable. The secondary phloem tissue emerges due to the cambial activity generally regulating the yield potentials of jute (Ghosh et al. 1943). Although cambial activity continues until fruiting, the commencement of flowering drastically reduces the length of the vegetative stem and eventually reduces the quality of the fiber (Kundu 1953; Johansen et al. 1985). Cultivated species depend upon a huge amount of water and humid conditions for their normal growth, but are very much affected by waterlogging conditions. Natural drought conditions are found to be better addressed by C. capsularis than C. olitorius. Thus water requirement and the moisture economy in the two species are different. Osmotic values are reported to be very important and associated with plant growth requirements. During the early stage of development osmotic values are appeared to be very high and the plants maintain that value throughout the active vegetative growth. Compared to vegetative growth the value remains low during the entire period of flowering.

2.6

Cytology

Cytological studies are very useful for characterizing the various species and to get a clear understanding of the evolutionary trends among these species. Studies involving cytology, karyomorphology, and cytogenetics of cultivated and wild species of Corchorus have been reported by several authors since the very early stage of

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investigations (Banerjee 1932; Rao and Datta 1953; Sharma and Roy 1958; Datta et al. 1966; Datta 1968; Paria and Basak 1973). Cytological information are significantly important to elucidate the species status of various jute germplasm. However, such studies on Corchorus species are a little limited due to the prevalence of the small size of chromosomes in these plants. Secondly, the existence of lignin in the cell wall creates considerable difficulties during the hydrolysis of materials for cytological preparations as well as proper staining of chromosomes (Maity et al. 2012; Zhang et al. 2019). Moreover, analysis and characterization of Corchorus spp. by conventional techniques are also hampered by a number of problems such as most of the Corchorus spp. possesses the same number of somatic chromosomes (2n = 14) with identical patterns of karyotypes (Alam and Rahman 2000). Both the cultivated species possess an identical number of somatic chromosomes (2n = 14) having a variable length from 1.3 to 2.7 mm in C. olitorius (Sharma and Roy 1958) and 1.7–3.7 mm in C. capsularis (Paria and Basak 1973), and among these 14 chromosomes, 6 are metacentric, 4 acrocentric, and two are documented as satellited. A different set of observations (Datta et al. 1975) further demonstrated that the chromosome of C. olitorius is larger (1.95–3.30 mm) than those of C. capsularis (1.65–3.10 mm). The existence of intrapair chromosomal heteromorphicity was reported in a few pairs of chromosomes among the diploid as well as colchicineinduced tetraploids developed in C. olitorius and C. capsularis (Akhter et al. 1991). The base specific banding similarity of the chromosomes in C. olitorius, C. capsularis, and C. trilocularis was reported by Alam and Rahman (2000) indicating the existence of 14 equalsized metacentric chromosomes in these three species along with one interstitial CMA as well as DAPI-positive bands suggesting the common ancestral origin of these species. Additionally, morphological similarities among the chromosomes of the two cultivated species suggesting that they have a common ancestry as well (Zhang et al. 2019).

R. H. Sarker

At the germplasm center (Gene Bank) of the Bangladesh Jute Research Institute (BJRI) there are about 5000 accessions belonging to 17 Corchorus spp. Out of these 17 species, two are cultivars (C. capsularis and C. olitorius) and the rest 15 (C. tridens, C. fascicularis, C. trilocularis, C. pseudo-olitorius, C. pseudo-capsularis, C. aestuans, C. hirtus, C. brevicornutus, C. siliquosus, C. pinnatipartitus, C. aesplenifolius, C. septentrinalis, C. urticifolius, C. baldaccii and C. depressus) are wild. Among the wild species, C. aestuans, C. hirtus, and C. trilocularis are native to this subcontinent. Several karyotype analysis have been made for the characterization of available germplasm of BJRI (Alam and Rahman 2000; Alam et al. 2011; Khatun et al. 2011). A study has been conducted recently using six wild species of Corchorus such as C. hirtus, C. siliquosus, C. septentrionalis, C. brevicornutus, C. urticifolius, C. pinnatipartitus to elucidate the extent of genomic affinities among these wild jute species. In this study the wild species were found to possess different numbers of chromosomes, such as 2n = 14 in case of C. septentrionalis, C. brevicornatus and C. urticifolius; 2n = 28 in C. hirtus and C. siliquosus and very differently 2n = 84 in C. pinnatipartitus. These species also exhibited dissimilarity in respect of other karyotypic features like total length of 2n chromosome complement, number of satellites, range of chromosomal length, and centromeric formulae. In addition, each species has a specific CMA and DAPI banding pattern (Fig. 2.4). The number, location, and distributions of GC- and AT-rich repeats are specific for each species. Corchorus urticifolius was found to possess a big centromeric DAPI-negative band (Afrose, Sultana and Sarker 2021, unpublished).

2.7

Genetics and Breeding

The two cultivated species of jute are exceedingly self-pollinated and morphologically are not different excepting pod characteristics, but they are sexually very much segregated. Unlike C.

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Botany of Jute (Corchorus Spp.)

capsularis, C. olitorius is partially crosspollinated, the crossing percentage being a little over 10% (Basak and Chaudhury 1966). Thus the genetic variability is believed to be narrow in both species since they are mostly selfpollinated. Inheritance studies on traits such as pod shape, bitter taste of leaves, anthocyanin pigmentation pattern, undulated leaf characters, anther and corolla color, capsule characteristics have been studied by a number of scientists. Related information indicates anthocyanin pigmentation is a useful marker for the identification and isolation of recombinants. Most of the characters segregate either in a simple or modified Mendelian fashion (Ghose 1942; Ghose et al. 1948; Dasgupta and Sharma 1954). Yield-contributing characters are entirely quantitative in nature and controlled by polygenes. The components of genetic variation due to quantitative characters are useful in determining their contribution to selection procedures in a breeding program. There has been considerable information dealing with the genetic analysis for quantitative traits of jute (Rahman 1968; Joarder et al. 1969; Eunus 1974; Basak et al. 1974; Paul et al. 1978; Ghosh et al 1979; Ghos Dastider and Das 1982). This has been demonstrated that the variation due to additive and dominance effects are responsible for the inheritance of important characters like plant height and earliness. However, the contribution of dominance variation was reported to be higher than additive effects in the case of fiber yield. Genetic constituents of white jute (C. capsularis) involving a diallel cross indicting that in F1 generation broad-sense heritability was found to be greater than that of narrow sense for all the significant yield contributing characteristics. While in F2 generations narrow-sense heritability was demonstrated to be very high for the characters like plant height, technical height, and base diameter. (Khatun et al. 2016). Several attempts were accomplished through hybridization and selection in producing advanced varieties of jute with improved fiber quality, superior stable yield, disease resistance, and vast adaptability. Ionizing radiation and chemical mutagens were also employed to obtain

27

desirable variability in cultivars. However, ionizing radiation alone did not demonstrate to be very successful. Nonetheless, through ionizing radiation, a single variety of C. capsularies called Atom Pat 38 was developed by the Bangladesh Institute of Nuclear Agriculture (BINA). Although India has produced a number of varieties through ionizing radiation, only very few of them have been accepted by the farmers (Islam et al. 1992). Thus, this method of mutation breeding has not been found suitable to obtain desired genetic variability in jute. Each of the cultivated species possesses a number of useful characteristics of its own. C. capsularis (white jute) grows well on low lands, is capable to adapt with wide range, withstands floods, salinity, and drought. It is apparently not very much sensitive to photoperiods and shows considerable responses towards fertilizer application and produces fiber of good textures and colors. Contrarily, C. olitorius (Tossa jute) generally produces superior quality golden fiber with greater strength, length, and luster but it grows only on the high land and susceptible to various diseases and pests. Unlike the cultivated species, wild species of jute arc are mostly bushy, shorter in size, contain tiny seeds with thick seed coats but they contain genes for various diseases and pests resistance. Thus these wild species are considered good materials for interspecific hybridization. Some of the species like C. aestuans, C. trilocularis, C. fascicularis, and C. pseudo-olitorius are resistant to Macrophornina phaseolina. C. tridens has the capacity to mite resistance. C. trilocularis is leaf mosaic resistant. C. fascicularis is damping-off disease resistance which is caused by Pythium spp. C. pseudo-olitorius has the capacity of jute mosaic virus-resistant (Ahmed 1956). The combination of the desired characters through sexual hybridization between Corchorus olitorius and C. capsularis is an important way to produce the desired variability which would result in an ideal jute plant possessing strong white fiber, wider adaptability, resistance to diseases and pests. However, the achievement of interspecific hybrids in jute plants is appeared to

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R. H. Sarker

Fig. 2.6 a–d a. Micrograph of sigma of Corchorus olitorius showing the magnified view of stigmatic papillae (arrows), b Fluorescence micrograph showing pollen germination and early development of pollen tube on the stigmatic surface of C. olitorius following self-pollination, c Fluorescent microscopic view of pollen tube from C.

olitorius pollen grains failed to develop (arrows) on the stigma of C. capsularis following interspecific crosspollination, d. Same as Fig. 2.6 C, but showing uniform and regular growth of a large number of callose invested pollen tubes from C. capsularis pollen grains within the pistil of C. olitorius following reciprocal cross

be extremely difficult due to the problems of sterility, physiology as well as the acquired genetic background of the parents involved in such crosses. Since the early twentieth century, there were repeated attempts to cross the two cultivated species in order to combine their good qualities. The interspecific hybridization in jute was first attempted by Finlow (1917, 1921, 1923), but he failed to get any hybrid. Later on, identical results were obtained by several researchers involved in interspecific crosses (Bhaduri and Chakrabarty 1948; Srinath and Kundu 1952; Ganesan et al.1957; Islam and Rashid 1960; Swaminathan et al. 1961; Islam 1964; Haque 1970; Arangzeb and Khatun 1980). However, the expectation has not been realized in spite of the fact that F1 hybrids have been reported by a number of researchers (Ganesen et al. 1957; Islam and Rashid 1960; Swaminathan et al. 1961). It was reported that F1 hybrids of the two species developed in one direction i.e. in cases

where C. olitorius was used as a female parent. Unfortunately, hybrids produced by involving C. olitorius as a mother plant failed to retain the recombinant characteristics of the two species beyond F3 generations (Hoque et al. 1988). Only maternal type of plants shows the skewed type of inheritance obtained in F3 and onward progenies. (Islam et al. 1992). However, when Corchorus capsularis was used as female the hybridization attempt it resulted in no success. The reasons are still unclear. However, the fluorescent microscopic observations following cross-pollinations demonstrated that when C. capsularis pistils were pollinated with C. olitorius pollen grains, the pollen tubes from C. olitorius were clearly found to face extensive difficulty to elongate within the pistilar tissue of C. capsularis (Fig. 2.6 C). This event of pollen tube rejection may be the reason for creating a prezygotic barrier in obtaining hybrid seeds when C. capsularis used as a female parent (Sarker and Hoque 1994). On the other hand in reciprocal

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Botany of Jute (Corchorus Spp.)

crosses involving C. olitorius as a female parent, the development of pollen tubes from C. capsularis pollen grains was uniform and found to grow within the pistil without any trouble (Fig. 2.6d) and thus producing fertile seeds involving this interspecific cross.

2.7.1 Reproductive Development Following Self-and CrossPollinations The improvement of yield contributing traits in jute can be accomplished by a suitable and effective hybridization program. In spite of the initial success, the hybrid plant developed in jute through interspecific crosses did not exhibit any recombinant characters after a few generations. Moreover, in a number of hybridization programs, it was not even likely to obtain the hybrid plant. Most of the reports involving interspecific crosses do not clearly demonstrate the actual reasons for the failure of the interspecific crosses involving both cultivars and wild species (Sarker and Hoque 1992; 1994). It is understood that successful hybridization depends on the nature of post-pollination events following self- and cross-pollinations and this is particularly important when the plant materials involved in hybridization are variable in their nature. Before applying the techniques of hybridization in obtaining hybrid progenies much more information is required regarding post-pollination development underlying the event of fertilization (Van dan Ende 1976; Knox 1984). The entire mechanism of fertilization in flowering plants is relatively complicated depending on the plant species and it is believed to be the result of successful interaction between pollen grain/pollen tube and pistil tissue (Knox 1984). Generally, pollen has a huge capability to carry its function throughout the events of pollen grain germination and pollen tube development leading to fertilization (Steer and Steer 1989). During the development of effective pollen tubes, tissues from both stigma and style provide physical as well as chemical support for the elongation and directional guidance to the pollen

29

tubes through the stigma and style (Knox 1984). Nevertheless, this interaction is absolutely very significant to understand the biology of sexual reproduction in higher plants and for the production of effective fertile seeds. Studies on pollen-pistil interaction have direct relevance to plant breeding programs science jute breeders are continuously striving to bring together desirable traits present in different potential plant materials through hybridization. A comprehensible knowledge about the biology of pollenpistil interaction would, no doubt, help the plant breeders in selecting the parental materials for specific hybridization programs effectively. The interaction between pollen grain and pistil is generally thought to be composed of a number of successive events leading to the recognition and acceptance or rejection of the gametes (HeslopHarrison 1975; Knox et a1. 1976; Roberts et al. 1980; Dumas and Guade 1981; Dickinson and Roberts 1986; Elleman et al. 1988). Major steps comprising the pollen-pistil interaction are generally considered to be pollen adhesion, hydration, pollen germination, and pollen tube development. All jute plants possess a dry type of stigma with a large number of papillae (Fig. 2.6a) and these stigmatic papillae are capable of receiving pollen grains following self- or crosspollinations. Since the development of hybrid jute plants has been desired for a long time, therefore it is interesting to examine critically the events of the post-pollination interactions leading to fertilization in Corchorus spp. (Sarker et al.1997). In compatible pollination, after landing the pollen grains adhere to the stigma surfaces. This adhesion depends on the nature of both pollen grains and stigmatic surfaces. After adhesion, hydration of the pollen grains takes place on the stigmatic surface. During this phase, pollen grains acquire water from the stigma which causes rehydration and activation of pollen grains. Rehydration is clearly an essential prerequisite for pollen germination. Next step of pollen-pistil interaction is pollen germination. In this step, pollen grains germinate on the stigmatic surface by proliferating swollen appendix

30

R. H. Sarker

through the germinal aperture (Fig. 2.6b). The tube initials develop into pollen tubes, which penetrate the stigmatic cell layers and elongate within the style, eventually reaching the ovary and where they enter the ovules and penetrate the embryo sacs to achieve fertilization (Cheung 1995). Events of pollen-pistil interaction leading to fertilization, including the nature of germination of jute pollen grain on the stigmatic surface following their adhesion was investigated in different jute species (Sarker et al. 1997). Postpollination events in case of C. olitorius is presented in Fig. 2.7. Morphologically the pollen tubes are elongated thread like structures. They are unbranched, with dense cytoplasm. A general feature of pollen tube is the deposition of a considerable amount of callose (Fig. 2.6d), which is a polymer of glucose (b-1, 3-glucan) down the length of the pollen tube (Shivanna and Johri 1985). However, callose is absent at the tip

of the tubes and form a layer inside the tube wall a little behind the tip. As the tube elongates, it also forms proteins and polysaccharides containing callose plugs inside the pollen tubes at various intervals. (Nakamura et al. 1984) These callose plugs (Fig. 2.7c) acts as a transversely sealing material between younger (with dense cytoplasm) and older regions of the pollen tubes (bearing scanty cytoplasm) (Knox 1984, Shivanna and Johri 1985). Callose plug formation has immense importance in tracing the direction and development of tubes within the pistil tissues. Such developing pollen tubes could also be traced while entering the ovule to effect fertilization (Fig. 2.7d). However, the formation of such callose plugs are not common event for all plants. In Lilium, peripheral callose plug is present but cytochemical analysis failed to identify the presence of transverse callose plugs (Reynolds and Dashek 1976). In incompatible pollination,

Fig. 2.7 a–d: Fluorescence micrographs showing the stages of pollen tube growth and elongation following self-pollinations in Corchorus olitorius. a. A part of the stigmatic surface showing a large number of germination pollen grains developing healthy pollen tubes; b. Same as

Fig. 2.7 A, but showing a magnified view of pollen tube development. c. A large number of callose (arrows) invested pollen tubes growing within the style and moving towards the ovary; d. Pollen tube (arrows) entering the ovule

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Botany of Jute (Corchorus Spp.)

31

pollen tubes may be arrested at the stigma or anywhere along the pathway of pollen tube elongation. A detailed study on self-pollination involving the cultivars (C. olitorius, C. capsularis) as well as wild species, namely, C. aestuans, C. trilocularis, C. fascicularis, C. baldaccii, and C. pseudo-olitorius revealed the variable nature of pollen grain germination and pollen tube development. In these plants pollen grain began to germinate within 15–20 min of pollination and maximum germination occurred within 60 min. The growth pattern of the pollen tubes through the stigmatic and stylar tissues is presented in Fig. 2.8. The growth pattern of the pollen tubes in the self-pollinated pistils from different species was found to be identical up to 30 min following such pollination. However, during the period of 30 to 60 min after pollination C. olitorius showed a sudden increase in growth rate of the pollen tubes compared to the other species studied (Fig. 2.8). The overall growth of pollen tubes in these plants was found to be less than that of C. olitorius. The faster rate of the pollen tube development in the case of C. olitorius is presumably related to the fact that they have to travel through a longer stylar length to accomplish fertilization as

compared to the other species of Corchorus studied. Further, it is evident that irrespective of the plant material the pollen tubes reached the ovules within 6 h from the time of pollination (Sarker and Hoque 1992; 1994). Moreover, such study also demonstrated a wide range of variations in callose plug formation within the pollen tube among the different species of jute. Presence of callose plug within the growing pollen tube in different species of Corchorus is remarkably variable in nature in respect to their size and structure (Fig. 2.9). Although no genetic analysis been carried out, such callose plugs appear to be a characteristic feature for each of the species of Corchorus established through several microscopic observations. The physiological responses of these plants may be associated with the formation of such variation in callose plugs in different species of jute during the event of fertilization. This spectacular variable feature of the pollen tube callose plugs can be exploited as a marker even for the depiction of both wild and cultivated species of jute (Sarker et al. 1997). The callose plugs of C. olitorius are elongated and possesses several unique contractions on their body, while these plugs in case of C. capsularis are comparatively shorter than that of C.

Fig. 2.8 Length of the developing pollen tubes following self-pollination in cultivars and wild species of jute at different time intervals following four hours from pollination. The mean length of pollen tubes was estimated

from 15 observations at each time interval. a, C. olitorius; b, C. capsularis; c, C. aestuans; d, C. pseudo-olitorius, e. C. tridens; f. C. fascicularis, g. C. baldaccii

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R. H. Sarker

Fig. 2.9 a–g Fluorescence micrograph showing the variable structure of callose plugs produced within the developing pollen tubes in various species of Corchorus. a. C. olitorius,
360, b. C. capsularis,
340, c. C.

aestuans.
340, d. C. pseudo-olitorius,
340 e. C. tridens
340, f. C. fascicularis,
340, g. C. baldaccii.
340

olitorius (Fig. 2.9a, b). Apart from these two species, the size and shape of these plugs in case of the wild species studied are also remarkably different visualized under fluorescence

illumination. To represent the variation in pollen tube callose plugs in jute, mean lengths with their standard deviations of 30 such callose plugs is presented in Fig. 2.10.

Fig. 2.10 Mean length of pollen tubes callose plugs obtained from the developing pollen tube in different species of Corchorus. Mean length and standard deviation were calculated from 20 observations. Bar represents the

standard deviation. a, C. olitorius, b, C. capsularis; c, C. aestuans; d, C. pseudo-olitorius, e, C. tridens; f, C. fascicularis; g, C. baldaccii

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Botany of Jute (Corchorus Spp.)

2.8

Conclusion

Contribution of jute in the jute-growing Asian countries is enormous and jute has been associated with the culture and heritage of these parts of the world. This has been playing a significant role in both agriculture and industry being recognized as the top most important and excellent source of natural fibers of the world. Apparently, jute has lost its eminence as a natural fiber due to the unfolding of low-cost synthetic fibers. Nevertheless, at present jute has created attention among the researches and scientists due to new and diverse application of jute as well as towards its improvement for yield and fiber quality. In the past, several ventures were made in developing a perfect jute plant through sexual hybridization involving the two cultivated as well as its wild relatives. Intensive botanical investigations are considered to be necessary and has created lots of attention mostly by the jute breeders in the past. For the past more than 100 years, huge data has been generated for all the pertinent branches of botany through several investigations. These classical and updated botanical information is certainly very important even for the advanced molecular genomic as well genomic studies. This botanical knowledge still contemplated to be important in formulating future appropriate research strategy towards the potential improvement of jute. Acknowledgements The author is grateful to Profs. A S Islam and M Imdadul Hoque for providing useful information and cooperation in various studies related jute breeding. Profound thanks to Dr. Tahmina Islam for her support during the preparation of this manuscript. Contributions of Rahima Khatun, Bithee Das, Saroj Kumar Paul, A K M Kamrul Hoque, and Masud Karim are sincerely acknowledged for their various studies related to reproductive biology and breeding of jute. Thanks are also to Mahin Afrose for cytological information for the wild species of jute, as well as Hiranmay Chanda and Bushrat Jahan for their help in preparing the drawings and graphs.

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R. H. Sarker Heslop-Harrison J (1975) Incompatibility and then pollen stigma interaction. Ann. Rev. Plant Physiol. 26:403– 425 Hossain MA, Mannan SA, Sultana K, Khandakar AL (1994) Survey on the constraints of quality jute seed at farm level. Agril. Support Service Project (GOB/WORLD BANK/ODA). Dhaka, Bangladesh. Hoque M, Imdadul, Haque MM, Islam AS (1988) Confirmation of Corchorus olitorius x C. capsularis hybrid through tissue culture and biochemical tests. Bangladesh J Bot 17 (1): 71–79 Islam AS (1964) A rare hybrid combination through application of hormone and embryo culture. Nature (london) 201:320 Islam AS, Haque MM, Hoque MI, Seraj ZI (1992) Tissue Culture and Micropropagation of Jute (Corchorus spp.). In High-Tech and Micropropagation III, Y.P.S. Bajaj, ed. (Berlin, Heidelberg: Springer Berlin Heidelberg), pp 505–526 Islam AS, Rashid A (1960) First Successful Hybrid between the Two Jute-yielding Species, Corchorus olitorius L. (Tossa)
C. capsularis L. (White). Nature 185:258–259 Iyer RD, Sulbha K, Swaminathan MS (1961) Fertilization and seed development in crosses between C. olitorius and C. capsularis. Indian J Genet Plant Breed 21 (3): 192–200 Joarder OI, Eunus AM, Rahman MA (1969) Inheritance of earliness and plant height in a six parent diallel cross of Corchorus olitorius. Cand. J. Genet. Cytol. 11:184–191 Johansen C, Wasque M, Ahmed MM, Begum S (1985) Plant growth curves and fiber quality changes of jute (Corchorus spp.) grown in Bangladesh. Field Crops Res 12:387–395 Kar BK (1959) Physiology of the golden fiber –its nature and production. Presidential address, Section of Agric Sci. In: Proc 46th Indian Sci Congr 21–28 Jan 1959, University of Delhi, Delhi, pp 166–184 Khatun M, Sultana SS, Ara H, Islam MN, SkS A (2011) Differential chromosome banding and isozyme assay of three Corchorus spp. Cytologia 76(1):27–32 Khatun R, Sarker RH, Sobhan MA (2016) Genetic components and variation in white jute (Corchorus capsularis L.) Bangladesh J. Bot. 45(5): 1107–1111 Knox R B (1984) Pollen pistil interactions. In: Cellular interactions, Encycl. Plant Physiol. 17: 508–608. Knox RB, Clarke AE, Harrison S, Smith P, Merchalonis JJ (1976) Cell recognition in plants: Determinants of the stigma surface and their pollen interactions. Proc Natl Acad Sci USA 73:2788–2792 Kumar V, Singh PK, Dudhane AS, De DK, Satya P (2014) Anatomical and morphological characteristics of nine jute genotypes. J. Crop Weed 10(2):334–339 Kundu BC (1951) Origin of jute. Indian Journal Genetics and Breeding. 11:95–99 Kundu BC (1953) Quality of Indian Jute. Jute Bull 15:450–462 Kundu B C (1956) Jute: World's Foremost Bast Fibre. I. Botany, Agronomy, Diseases and Pests. Source:

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Economic Botany, Published by: Springer on behalf of New York Botanical Garden Press. 10 (2): 103–133 Kundu BC, Basak KC, Sarkar PB (1959) Jute in India. Indian Central Jute Committee, Calcutta, pp 38–41 Mahapatra AK, Saha A (2008) Genetic resources: jute and allied fiber corps. Jute and allied fibre updates, Kolkata, Central Research Institute for Jute and Allied Fibers: 18–37 Mahapatra AK, Saha A, Basak SL (1998) Origin, taxonomy and distribution of Corchorus species in India. Green J. 1:64–82 Maity S, Chowdhury S, Datta AK (2012) Jute Biology, Diversity, Cultivation, Pest Control, Fiber Production and Genetics E. Lichtfouse (ed.), Organic Fertilisation, Soil Quality and Human Health, Sustainable Agriculture Reviews 9 Springer Science+Business Media, pp 227–262 Majumdar S (2002) Prediction of fibre quality from anatomical studies of jute stem. Part I Prediction of fineness. Indian J Fiber Text Res 27:248–253 Majumder S, Sarkar C, Saha P, Gotyal BS, Satpathy S, Datta K, Datta SK (2018) Bt Jute Expressing Fused dEndotoxin Cry1Ab/Ac for Resistance to Lepidopteran Pests. Front Plant Sci 8:2188 Nakamura N, Mori M, Suzuki H (1984) Chemical Characterization of the callose plug isolated from Camellia japonica pollen tube. Plant and Cell Physiol 25(2):233–238 Paria P, Basak SL (1973) The pachytene chromosomes of Jute (Corchorus olitorius ). Curr Sci 42:832 Patel JS, Ghose RLM, Sanyal AT (1945) The genetics of Corchorus (Jute). III. The inheritance of corolla color, branching habit, stipule character and seed coat color. Indian J. Genet. Pl. Breed. 4:75–79 Paul NK, Joarder OI, Eunus AM (1978) Inheritance of fiber yield in Corchorus olitorius L. Bangladesh J. Bot. 7(1):1–5 Purseglove JW (1968) Tropical Crops. Dicotyledons 2. Longhman, London, 613–618. Rahman MA (1968) Inheritance of fiber yield in a twelve parent diallel cross of C. olitorius L. Proc. Pak. Acad. Sci. 5:51–58 Rao NS, Datta RM (1953) Chromosomes of the genus Corchorus. Nature 171:754 Raut RN, Naik G (1983) Interspecific hybridization in cultivated jute. Proc FAO Expert Consultation on Jute and Kenaf Improvement, Calcutta, 5–9 Sep; Dhaka 12–15 Sep Renolds JD, Dashek WV (1976) Cytochemical analysis of callos localization in Lillium longiflonun pollen tubes. Ann Bot 40:409–416 Roberts IN, Stead AD, Ockendon DJ, Dickinson HG (1980) Pollen stigma interactions in Brassica oleracea. Theor Appl Genet 58:241–246 Saha P, Datta K, Majumder S, Sarkar C, China SP, Sarkar SN, Sarkar D, Datta SK (2014) Agrobacterium mediated genetic transformation of commercial jute cultivar Corchorus capsularis cv. JRC 321 using shoot tip explants. Plant Cell, Tissue Organ Cult 118:313–326

35 Sarker RH, Al-Amin GM, Hassan F, Hoque MI (2008) Agrobacterium-mediated genetic transformation of two varieties of jute (Corchorus capsularis L.). Plant Tissue Cult. Biotech. 18:7–16 Sarker RH, Hoque MI (1992) Fluorescent microscopic study of pollen tube development following interspecific crosses in Corchorus. SABRAO J 24(2):81– 86 Sarker RH, Hoque MI (1994) Investigation into the barriers of hybrid formation between Corchorus capsularis L. and C. olilorins L Bangladesh. Bot. 23 (l):53–59 Sarker RH, Paul SK, Haque AKMK, Hoque MI (1997) Pollen tube growth and variation in pollen tube callose plugs in some Corchorus species. Phytomorphology 47(3):311–317 Sen Gupta JC (1953a) Studies on the physiology of the jute plant. I. Effect of the time of sowing and vernalization on growth and development of jute plants. Agricultural Research Mem 6.I, Indian Jute Committee, Calcutta Sen Gupta JC (1953b) Studies on the physiology of the jute plant. II Mineral Nutrition of jute plants. Agricultural Research Mem 6.I1, Indian Jute Committee, Calcutta Sen Gupta JC, Sen NK (1944) On photoperiodic effect of jute plants. Indian J Agric Sci 14:196–202 Sharma AK, Roy M (1958) Cytological studies on Jute and its allies. Argon Lusitania 20:5–15 Shivana KR, Johri BM (1985) The angiosperm pollen structure and function. Wiley Eastern Limited, New Delhi, India. Singh DP (1976) Jute. In: Simmonds NW (ed) Evolution of crop plants. Longman, London/New York, pp 290– 291 Sreenath HK, Shah AB, Yang VW, Gharia MM, Jeffries TW (1996) Enzymatic polishing of jute/cotton blended fabrics. J Ferment Bioeng 81(1):18–20 Srinath KV, Kundu BC (1952) Cytological studies of pollen tube growth in reciprocal crosses between C. capsularis and C. olitorius L. Cytologia 17:219–223 Steer MW, Steer JM (1989) Pollen Tube Tip Growth. New Phylol. 111(3):323–358 Swaminathan MS, Iyer RD, Sulbha K (1961) Morphology, cytology and breeding behavior of hybrids between C. olitorius and C. capsularis. Curr Sci 30:67–68 Van dan Ende (1976) Sexual interaction in plants. Academic Press, London Watt G (1889) Dictionary of the economic products of India, vol II. Dept Revenue and Agril. Govt. of India, Calcutta, pp 534–562 Zhang G, Huang S, Zhang C, Li D, Wu Y, Deng J, Shan S, Qi J (2021) Overexpression of CcNAC1 gene promotes early flowering and enhances drought tolerance of jute (Corchorus capsularis L.). Protoplasma 258:337–345 Zhang G, Zhang Y, Xu J, Li FT, Tao A, Zhang L, Fang P, Lin L, Qi J (2015) An Efficient Regeneration System and Optimization of the Transformation from the

36 Cotyledonary Node of Jute (Corchorus capsularis L.). Journal of Natural Fibers 12:303–310 Zhang L, Ibrahim AK, Niyitanga S, Zhang L, Qi J (2019) Jute (Corchorus spp.) Breeding, JM Al-Khayri et al. (eds.), Advances in Plant Breeding Strategies: Industrial and Food Crops, Chapter 4, pp 85–113 https:// doi.org/10.1007/978-3-030-23265-8_4

R. H. Sarker Zhang Y, Malzahn AA, Sretenovic S, Qi Y (2019) The emerging and uncultivated potential of CRISPR technology in plant science. Nature Plants 5:778–794 Zhu H, Li C, Gao C (2020) Application of CRISPR–Cas in agriculture and plant biotechnology. Nat Rev Mol Cell Biol 21:661–677

3

Chemistry of Jute and Its Applications Tapan Kumar Guha Roy, Debanjan Sur, and Debashis Nag

Abstract

Jute is a lignocellulosic fiber, having three principal chemical constituents: alpha-cellulose, hemicellulose and lignin, while jute stick leftover after fiber extraction is also lingocellulosic. This chapter deals with the brief composition of lignin, cellulose, hemicelluloses and other minor components together with linkages of lignin with other components. Locations of major jute constituents as well as chemical composition of jute fiber at different stages of plant growth are discussed. The effects of common chemicals and light on jute as well as methods for estimation of major jute constituents have been described. Some important chemical processes such as bleaching, dyeing, woollenization for the production of high-value jute diversified products

T. K. G. Roy Chemical Processing Division, Indian Jute Industries’ Research Association (IJIRA), Kolkata, India D. Sur Physics Division, Indian Jute Industries’ Research Association (IJIRA), Kolkata, India D. Nag (&) Technology Transfer Division, National Institute of Natural Fibre Engineering & Technology, Indian Council of Agricultural Research (NINFET-ICAR), Kolkata, India

are briefly reported. Several useful products, developed by utilizing jute chemistry, have been mentioned, viz. pulp and paper, activated charcoal, furfural, oxalic acid, microcrystalline cellulose, carboxymethyl cellulose, and nanocellulose. In the end, major environmental impacts of natural jute fiber vis-à-vis synthetic fiber have also been mentioned.

3.1

Chemical Constituents of Jute

3.1.1 Jute Fiber Jute is a lignocellulosic fiber. It is obtained from an annual plant of the genus Corchorus. The two species of Corchorus are: Corchorus capsularis and Corchorus olitorius, which are commercially known as White jute and Tossa jute, respectively. The total carbohydrate fraction in jute is termed as holocellulose, which can be subdivided into alpha-cellulose and hemicellulose. Chemically, jute has three principal chemical constituents, namely alpha-cellulose, hemicellulose and lignin along with some minor components such as fats and waxes, inorganic/mineral matter, nitrogenous substances and traces of pigments. The chemical compositions of White and Tossa jute are almost similar (Table 3.1).

3.1.1.1 Alpha-Cellulose Chemically, cellulose has been defined as that fraction of carbohydrate which remains insoluble

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_3

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38 Table 3.1 Chemical Composition of Jute (as % of the bone dry weight of the fiber)

T. K. G. Roy et al. Constituent

White Jute

Tossa Jute

Alpha-cellulose

60.0–63.0

58.0–59.0

Hemicellulose

21.0–24.0

22.0–25.0

Lignin

12.0–13.0

13.0–14.0

Fats and Waxes

0.4–1.0

0.4–0.9

Pectin

0.2–0.5

0.2–0.5

Nitrogenous Matter

0.8–1.9

0.8–1.6

Mineral Matter (Ash)

0.7–1.2

0.5–1.2

Ref. Majumder et al. (1980)

in 17.5% sodium hydroxide solution at 20 °C (Ott et al. 1954). It is a linear condensation polymer and consists of 1,4 b-D anhydroglucopyranose units joined together by 1,4 b-glycosidic bonds (Fig. 3.1). Paper chromatography analysis of the hydrolysate of jute alpha-cellulose revealed that it is also associated with small amounts of other sugar residues i.e. xylan, glucuronic acid, etc. (Macmillan et al. 1956). Cellulose is also easily hydrolyzed by acids to water-soluble sugars and relatively resistant to oxidizing agents. Actually, the repeating unit for cellulose is cellobiose, a name given to two successive glucose units together. The number of glucose units in a cellulose molecule is referred to as the degree of polymerization (DP). However, DP and molecular weight are found to vary with the method of isolation of alpha-cellulose from jute plants. The degree of polymerization of cellulose in jute is reported to be the lowest among all the vegetable fibers (Sengupta and Dutt 1958) and according to an estimate (Chatterjee et al. 1954), it is 1,150.

Cellulose is a trihydric alcohol with one primary and two secondary hydroxyl groups per glucose unit. The reactions of cellulose may be classified into the following two types: (i) Those involving the hydroxyl groups resulting in substitution, addition and oxidation; such reactions are acetylation (as in the manufacturing of acetate rayon), nitration, xanthation (as in the manufacturing of viscose rayon fiber), alkylation (etherification), etc. and (ii) Those involving glycosidic linkage leading to chain degradation, i.e., hydrolytic breakdown of cellulose in the presence of acids and alkaline oxidation in alkaline, acid or neutral medium (Megregor and Greenwood 1982; Navell and Zeronian 1985).

3.1.1.2 Hemicellulose Hemicellulose in jute is heterogeneous and built up of polysaccharides and polyuronides. They are composed of cellulose chains, but are much shorter in length and are made up of a mixture of relatively low molecular weight polysaccharides,

Celloboise Unit Fig. 3.1 Chemical structure of cellulose

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Chemistry of Jute and Its Applications

39

Fig. 3.2 Chemical structure of xylan in jute hemicellulose

viz., pentosan (xylan), polyuronide, and a little hexosan such as galactose and mannose (Sarkar and Chatterjee 1948; Ott et al. 1954; Aspinal and Dasgupta 1958). These sugar units are basically present in anhydrous form. Polyuronide comprises 4-o-methyl glucuronic acid together with some acetyl groups. Jute hemicellulose contains a number of hydroxyl groups and acetyl groups. The degree of polymerization (DP) of this polysaccharide was found to be low (Sarkar 1931), about 140 (Dasgupta and Sarkar 1954; Aspinal and Dasgupta 1958). The chemical structure of hemicellulose is shown in Fig. 3.2. The hemicellulose may be characterized or differentiated from cellulose by: (i) their much shorter chain length, (ii) solubility in alkali and (iii) ease of hydrolysis by acid. Hemicellulose fractions, of fairly low molecular weight, get readily dissolved in 18% sodium hydroxide solution at room temperature, and they contribute largely to the copper number of the raw fiber (Sarkar and Chatterjee 1948). Ester linkage was found between the hydroxyl group of lignin and 4-o-Methyl-D-xylan in jute (Das et al. 1981).

3.1.1.3 Lignin The chemical composition of lignin has not been precisely established. But the functional groups and building units which make up the lignin molecules have mostly been identified. It is characterized by high carbon content, which indicates that it is either highly unsaturated or

aromatic in character along with the presence of hydroxyl, methoxyl and possibly carbonyl groups (Sarkar 1931, 1933). Lignin has been found to contain five hydroxyl and five methoxyl groups per building unit, with a minimum molecular weight of 830 (Ray 1968). It is a shortchain, isotropic and non-crystalline material (Sengupta and Dutt 1958) with a DP of about 60. The high rigidity of lignin is partly due to its non-linear cross-linked structure. Most researchers believe that the structural units of a lignin molecule are derivatives of 4-hydroxy -3 methoxyphenyl propane. Lignin may, therefore, be looked upon as having a highly complex amorphous structure, possessing a relatively high carbon and methoxyl content, nonhydrolyzable by acid, insoluble in hot alkali, readily oxidizable, easily condensable with phenols and giving a number of color reactions. Structural units of lignin are aromatic alcohols with a phenylpropane backbone, such as p-coumaryl alcohol, coniferyl alcohol and sinapyl alcohol as shown in Fig. 3.3 (Megregor and Greenwood 1982).

3.1.1.4 Other Constituents (a) Fats and Waxes in Jute. Fats and waxes (05–0.8%) are present as coatings on the outer sheath of the stem, which prevent the plant from desiccation (Barker 1939). Wax content in jute fiber has been found to consist essentially of higher alcohols, fatty acids, sterols, unsaturated and saturated acid contents and inert matter. It is

40

T. K. G. Roy et al.

Fig. 3.3 Chemical structure of lignin

soluble in organic solvents, e.g., benzene and ethyl alcohol mixture. The extracted wax is greenish brown in color. Due to the low fats and waxes content in jute fiber, it requires the addition of oil to soften the fiber and to promote their cohesion. (b) Pectin. The presence of pectineus substances, which bind the fiber bundles with other non-fibrous tissues and the woody core (stick), in case of bast fibers is well established. A small quantity of pectin is present in the jute fiber also (Majumdar 1956). Pectin is a large molecule built up of repeating units called, hexouronic acid, which is a derivative of hexose sugar and undergoes decomposition during retting of the jute plant to form watersoluble products through bacterial action. However, in raw jute, there is always some residual pectin left; the higher is the pectin content, the higher is the stiffness of the jute fiber. It has been found that the composition of rooty fiber pectin is somewhat different from that of bast pectin, particularly with respect to uronic acid content (Ray 1968). (c) Mineral and Coloring Matters. The mineral matter present in raw jute is composed of inorganic/metal salts and metal oxides such as silica, silicates, Fe2O3, Al2O3, CaO, MgO, K2CO3, etc. together with traces of other elements such as Mn, Ti and Cu (Chatterjee 1950).

The coloring substances comprise xanthophylls, carotene and tannin. The tannin combines with the iron in retting water to form iron tannate which confers dark gray color to retted jute. These coloring matters can be removed from the fiber by chemical treatments with mineral acids, bleaching agents, etc.

3.1.2 Jute Stick Jute stick is the woody part of jute stem that remains as leftover after extraction of fiber. It constitutes about 2.5 times of extracted fiber. Chemically jute stick is a lignocellulosic raw material. The chemical composition of jute sticks is given in Table 3.2.

Table 3.2 Chemical composition of jute stick Constituent

Percentage fraction (%)

Alpha Cellulose

40.8–47.1

Hemicellulose

23.0–23.6

Lignin

22.2–23.5

Fats and Waxes

1.7–2.4

Pectin

0.5–0.7

Mineral Matter (Ash)

0.6–0.8

Ref: Sur and Amin (2010)

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Chemistry of Jute and Its Applications

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3.1.3 Linkages of Lignin with Other Constituents

3.1.4 Location of Cellulose, Hemicellulose and Lignin

Although the mode of chemical linkages is not fully understood, there is evidence to suggest that lignin is linked with the carbohydrate fraction through two types of linkages, namely alkalisensitive and the other alkali-resistant. The hemicelluloses are strongly bound to the cellulose microfibrils by hydrogen bonds (Sarkar et al. 1947, 1948; Nevell and Zeronian 1985) and a portion of hemicellulose is linked to lignin hydroxyls through its uronic acid groups forming ester linkages (Sarkar et al. 1947). It has been suggested that the –OH group in the propyl side chain in the phenylpropane unit of lignin may be involved in this linkage (Megregor and Greenwood 1982). Some of the –COOH groups of hemicellulose appear to be involved in such ester linkages which are known as alkali-sensitive, while most others appear to be occupied by basic radicals like Ca2+ , Mg2+ , etc. and the rest appear as free carboxyl groups (Das et al. 1981). Different opinions were, however, expressed about the origin of acidity in jute. Earlier investigators (Sarkar and Chatterjee 1948) attributed it to –COOH groups of hemicelluloses, while a recent study ascribed the free acidity of jute to the phenolic groups of lignin component (Das et al. 1981). The tensile properties of jute fiber, both in dry and wet conditions, depend much on the role of lignin and hemicelluloses, acting as the cementing materials within the jute fiber matrix. It has been observed that when jute is treated with the chemical reagent employed in textile pretreatments and bleaching processes, lignin, hemicellulose and other encrusting substances are attacked and to some extent removed. The greater the extent of this removal, the more is the reduction of the strength of the jute fiber, particularly when the material is treated in the wet state (Ray 1968). Chemically, jute fiber may, therefore, be considered to be composed of cellulose and hemicellulose, which are intimately associated with lignin.

Jute fiber is multicellular, since each fiber is found to be a group of ultimate cells, cemented together laterally and longitudinally by means of inter-cellular materials being non-cellulosic in composition. Each ultimate cell has a thick cell wall and lumen, the central canal, while the cementing layer between ultimate cells is known as middle lamella. This cell wall can be considered as having a “fiber-reinforced composite” like structure with ultrafine microfibrils, being purely cellulosic, embedded in a matrix of hemicelluloses and lignin. According to the staining tests and other experimental studies, the lignin is found to be non-uniformly distributed over the fiber crosssection, the proportion being higher in the middle lamella. From an experimental study (Mukherjee et al. 1993), it was conjectured that while the microfibrils are composed of cellulose, the hemicelluloses reside mainly in the inter-fibrillar regions and lignin in the middle lamella mostly. For this, when lignin is greatly removed, the jute fiber gets disintegrated into the ultimate cells and loses its textile value.

3.1.5 Chemical Characters at Different Stages of Plant Growth The chemical composition of the fiber at an early pre-bud state differs considerably from that of the sample obtained from a more mature plant, while during the period from flowering to big-pod stages the chemical composition of the fiber remains practically unaltered. Since the decrease in the xylan content is accompanied by increments in lignin and alpha-cellulose, the formation of lignin in jute appears to be connected with a certain transformation of xylan and not of cellulose. There is practically no variation in the chemical composition of the fiber samples obtained from the pre-bud (50 days) to the bigpod (98 days) stage of the plant, although the

42

wax content tends to diminish with the age of the plant. At the over-matured stage (when seeds begin to ripen), the percentage of holocellulose and more specifically that of lignin begin to show a somewhat higher value. Iron content, furfural yield, and acetyl content tend to fall with growth; copper number tends to increase in the later stages, presumably due to the degradative action of the weather on hemicelluloses (Macmillan et al. 1955; Datta 1960). At the earliest (pre-bud) stage of growth, the degree of polymerization (DP) value of fiber cellulose is at the lowest level, since the fiber is only at the formation stage and immature. The DP value rises steadily as puberty sets in and is practically steady during the reproductive phase (bud to pod formation); it rises quickly to the maximum level at the large pod stage. If the stage of growth is extended further to the ripening of pod with maturing of the stem, both the DP and fiber cellulose content tend to fall (Chatterjee 1959).

3.1.6 Action of Chemicals and Light on Jute 3.1.6.1 Alkali Jute hemicellulose is very susceptible to alkalis which have little effect on lignin and cellulose. Alkali under mild condition cleaves the ester linkages between hemicellulose and lignin, and also dissolves lignin when the linkages between lignin and carbohydrate are broken down by acids or some other chemical treatments. Nonetheless, treatment with a dilute solution of alkali at room temperature or at boil imparts softness to jute and improves the pliability of the jute fiber. The losses in weight and wet strength of treated material vary from 5 to 8%, while the dry strength remains almost unaffected (Macmillan et al. 1954). When jute is treated with strong alkali (10– 18%), lateral swelling accompanied by considerable shrinkage in lengths takes place. As a result of which the fiber becomes softened to the touch/feel and develops crimp or waviness (Chakravarty 1962). The treated material suffers

T. K. G. Roy et al.

loss in weight about 15–20% and tensile strength about 25%. The fiber becomes more flexible and extensible. On treatment with alkali, white jute turns slightly brown while Tossa jute becomes deep brown.

3.1.6.2 Acid Jute is resistant to acid degradation or damage due to the presence of lignin. However, cellulose and hemicellulose are readily attacked or affected even with a cold aqueous solution of mineral acids. Sulfuric acid solution (about 20%) at room temperature has no appreciable effect on the tensile strength of jute and can be safely used for the processing of jute (Macmillan and Basu 1947). With dilute mineral acid or organic acid treatment, the color of jute is brightened by the removal of metallic cation usually anchored in the free –COOH group of uronic acid residue of jute. 3.1.6.3 Light When jute fibers or fabrics are kept exposed to sunlight for long hours, their color becomes deep yellowish to light brownish which is considered as a negative attribute of jute for its use as a textile fiber. The lignin content (12–14%) in jute fiber is believed to be mainly responsible for the occurrence of such photo-yellowing. Most of the researchers (Ridge et al. 1944; Callow and Speakman 1949; Macmillan et al. 1950) believed that the structural units of lignin molecule are derivatives of 4-hydroxy-3 methoxyphenyl propane and the lignin in jute is responsible for the yellowing. When the removal of lignin is affected to the extent of 95%, photoyellowing tends to decrease. On complete removal of lignin (*99%), yellowing stops (Sengupta and Callow 1951; Sengupta and Radhakrishnan.1972), but the fiber loses its textile value as mentioned earlier. It has also been demonstrated that when isolated jute lignin is deposited on bleached cotton yarn, the yellowing of cellulose is accelerated by the associated lignin (Bhatacherjee and Macmillan 1958). Photochemical degradation of textiles differs from jute because jute undergoes an additional degradation due to the photo-sensitizing action of lignin.

3

Chemistry of Jute and Its Applications

A study on different wavelengths of the solar spectrum (Mukhopadhyay 1976) revealed that the UV region (355–450 lm) has the most predominant yellowing action and the effect is continued in the visible region (400–430 lm). The energy of the absorbed light in the above region is higher than that associated with the part of the chemical linkages in jute. As a result, cleavage of the linkages occurs with the absorption of light in the above-mentioned region. It has been demonstrated (Callow and Speakman 1949) that lignin, under the influence of light, suffers some loss of methoxyl groups and undergoes degradation which leads to the formation of ortho-diphenols and ultimately of ortho-quinones which discolor the fiber. This discoloration is also associated with loss of strength. The onset of yellowing differs noticeably with bleaching agents used. Bleaching with alkaline hypochlorite gives a product with a somewhat rapid yellowing tendency, while that with alkaline hydrogen peroxide gives products with improved white color, showing lesser yellowing than that with hypochlorite. Sodium chlorite, applied under optimized acid conditions, is carried out with care to exhibit the least yellowing tendency and minimum loss in strength. When jute is exposed to light and air, all major constituents suffer degradation. The aqueous extract of the exposed jute material is more acidic than the unexposed jute. Part of the acid probably comes from degraded polyuronides and the rest from the lignin.

3.1.7 Methods for Estimation of Major Jute Constituents 3.1.7.1 Estimation of Holocellulose Content in Jute (Sengupta et al. 1958) Jute fiber is mainly composed of holocellulose, the water-insoluble carbohydrate fraction, and lignin. Thus, holocellulose content is estimated by completely removing lignin from the jute fiber, by adopting methods like chlorite treatment.

43

Raw jute fiber is first dewaxed with ethyl alcohol and benzene mixture (1:2 v/v) for 6 h in a soxhlet apparatus. The dewaxed fiber is then washed with ethyl alcohol and finally with distilled water followed by drying in the air. Dewaxed jute fibers are finely cut into small pieces. The cut fiber sample (2 g) is then treated with 0.7% sodium chloride solution for 2 h at boiling water-bath (*98 °C) at pH 4.0 (buffered with sodium acetate and acetic acid) using a liquor ratio of 1:50. The delignified fiber sample is then filtered through a pre-weighed sintered glass crucible (No.3), anti-chloride with 2% sodium meta-bisulfite solution, washed and finally dried to a constant weight at 105–110 °C and weighed. This weight when expressed as % of the initial oven-dry weight of jute fiber gives the holocellulose content (%).

3.1.7.2 Estimation of a-Cellulose Content (Doree 1947; TAPPI Test Methods 1991) A measured sample of holocellulose is treated with 17
5% (w/w) sodium hydroxide solution using a liquor ratio of 1:15 at 20 °C for 2–3 h. The insoluble residue is filtered through preweighed gooch crucibles and washed with dilute sodium hydroxide solution (2% followed by 0
2%) and water. The filtrate is made acidic with 0.2% acetic acid solution and then an equal volume of absolute ethanol is slowly added to it with constant stirring. The procedure is repeated three times and the filtrate was dried in an oven at 105–110 °C, cooled over phosphorus pentoxide to a constant weight and weighed. While this constant weight is the measure of alpha-cellulose content, the loss in weight on sodium hydroxide treatment accounts for the hemicellulose content. Cellulose and hemicellulose contents are usually expressed as a percent based on the initial ovendry weight of jute fiber. 3.1.7.3 Estimation of Lignin Content (Macmillan et al. 1952) The natural fats and wax of jute are removed by extracting the pulverized jute material with a mixture of alcohol-benzene (1:2 v/v) in a Soxhlet

44

T. K. G. Roy et al.

apparatus at least for 6 h. The solvent is then driven off and dried at 105 °C. 1 g finely powdered and dewaxed jute is treated with 72% sulfuric acid using a liquor ratio of 1:12.5 for 48 h at 2 °C with occasional stirring to break up the lump formed. At the end of the reaction period, the acid-treated and swelled mass is transferred to a 750 ml conical flask by diluting with water to make up a volume of 300 ml. The diluted mass is boiled under reflux for 2 h and allowed to settle for 15 min and then filtered through a pre-weighed sintered glass crucible (No. 3). The residue is washed with boiling water till it is free from acid. It is then dried to a constant weight at 105–110 °C and weighed. This weight when expressed as % of the initial oven-dry weight of jute fiber gives the lignin content (%).

3.2

Chemical Processing of Jute

3.2.1 Bleaching For the production of white or dyed jute goods, it is imperative to undertake a bleaching process for removing from jute fiber its natural golden or reddish-brown color and the non-cellulosic matter. In the case of jute yarns and fabrics, there is also a need to remove the small amount of mineral oil from the former and starch (sizing material) from the latter, since such oil interferes not only with the absorption of dyes and fastness properties, but also contributes additional yellowing on exposure to light (Bhattacherjee et al.1965; Guha Roy et al. 2002). For this, prior to the bleaching process, jute fabrics are made starch-free by washing with hot water or treatment with anionic / non-ionic detergent, while non-ionic detergent can remove mineral oil. Bleaching of jute can be achieved by treatment with oxidizing agents, such as hydrogen peroxide, sodium hypochlorite, bleaching powder, sodium chlorite, and peracetic acid. For obtaining brilliance in shades of deep color, as required later for good quality dyeing, a pre-bleaching treatment of jute material with reducing agents,

such as sodium bi-sulfite and sodium hydrosulfite, is recommended (Parsons 1939). Bleaching of jute with hydrogen peroxide is very popular in the jute industry and is carried out under alkaline conditions using H2O2, sodium silicate and non-ionic detergent or a good wetting agent at an elevated temperature (Chatterjee and Pal 1955). Hydrogen peroxide produces bleached jute with superior whiteness, as required for value-added end uses, and with a lesser impact on fiber quality. Bleaching with peroxide can be carried out in cold conditions also. The tendency of the bleached material to become yellow on storage is much less pronounced in the case of bleaching with peroxide than that with hypochlorite or chlorite. The point of attack by peroxide is believed to be phenolic hydroxyl group and the color change is mainly due to an unknown structural modification of native lignin (Chatterjee and Pal 1955). Usually, easy breakdown of the lignin molecule to watersoluble compounds takes place under an acidic medium, while under alkaline conditions dissolution of lignin gets reduced, favoring reactions that modify the residual lignin to a whiter component. Delignification reactions are, therefore, done under acidic conditions and bleaching is conducted under alkaline one. During bleaching water-soluble oxidation products of lignin, which are acidic in character, are formed. It is, therefore, customary to add alkaline buffer salts in bleaching bath in sufficient quantity to neutralize the acidity developed during the course of the reaction (Majumdar 1956). Other oxidizing agents like sodium hypochlorite and bleaching powder are also used in the jute sector. Bleaching of jute yarn with sodium hypochlorite or bleaching powder is mostly carried out for the manufacture of mats, matting, carpets or other cheap quality products. Bleaching of jute with hypochlorite cannot be done in a normal manner because jute has a high affinity for chlorine. An acidic or neutral bleaching solution produces yellowish color, while alkaline sodium hypochlorite solution (made with soda ash or caustic soda) gives good bleaching results (Macmillan et al. 1949). Pretreatment with fixed concentrations of bleaching

3

Chemistry of Jute and Its Applications

powder solution at fixed pH values followed by peroxide bleaching produces superior bleaching at much reduced cost and in a much shorter time. The process has good potential in the production of “super-white” jute textiles for decorative end uses (Guha Roy et al. 1988). Bleaching of jute fabric can also be carried out using peracetic acid (Majumdar et al. 1994; Chattopadhyay et al. 1999). A comparison of peracetic acid bleaching with conventional peroxide bleaching revealed that peracetic acid bleaching is more effective in reducing the losses in weight and tensile strength.

3.2.2 Dyeing Jute can be dyed with almost all classes of dyestuffs commonly used for cellulosic fibers viz. direct, sulfur, vat and reactive dyes (Patro 1971; Chattapadhyay et al. 2002) as well as pigment colors (Pan et al. 2007; Chattapadhyay and Pan 2018) and natural dyes (Gulrajani and Gupta 1992; Samanta and Agarwal 2008). Besides, jute has a high affinity for both acid dyes and basic dyes (Parsons 1939; Sarkar et al.1946), which have practically no dyeing affinity for cotton or rayon.

3.2.2.1 Dyeing with Synthetic Dyes Jute in either gray or bleached state can be dyed by conventional dyeing methods, but in some cases, certain modifications to dyeing processes/recipes are necessary. Moreover, dyes that show excellent light fastness on cotton and wool, will not exhibit the same high light fastness on jute. The poor quality of dyeing often results from the following technical shortcomings: (a) Jute differs somewhat in dyeing properties from cotton due to the presence of non-cellulosic matter (mainly hemicellulose and lignin); (b) The change in color of undyed or bleached jute on exposure to sunlight occurs due to the presence of lignin which also enhances the fading of the dyes as well; (c) The different auxiliary chemicals used in dyeing with various classes of dyestuff have a distinct effect on the color of the jute fiber/substrate; and

45

(d) Dyers make a random choice of dyes from the dye-class used for cotton or wool and do not have knowledge of their fastness properties on jute. Studies on dyeing of both gray and bleached jute fabrics were carried out using dyestuffs of acid, basic direct, reactive and vat classes and light fastness values of these dyed jute samples ware compared with those for cotton (Bell 1969). The studies revealed that yellowing is the major factor on which apparent fastness to light depends. As regards light fastness, a number of acid dyes showing a rating of 6 or more on wool yielded only 3–4 on jute, while some basic dyes known to give a rating of 6 or more on wool showed a rating of 2–3 on jute. About 200 direct dyes showing a light fastness grade of 4 or above on cotton were selected for test dyeing on gray, hydrogen peroxide bleached, and chlorite bleached jute fabrics; the overall light fastness rating for jute was found about one grade lower than that for cotton. Among the reactive dyestuffs used, 55% showed a rating of 5–6 and 6 + on cotton, but only 2% performed similarly in the case of jute. The average light fastness grade for cotton was 5.3, in comparison to 4.2 on gray jute and 4.1 on chlorite bleached jute. Color fastness characteristics of peroxide bleached fabric samples were evaluated using a large number of dyes as representatives of acid, basic, metal-complex (1:2), direct, sulfur, reactive, vat and pigment (Guha Roy et al. 1993). Of the dyes tested, 10% basic dyes, 18% acid dyes, 56% direct dyes, 63% reactive dyes, 77% sulfur dyes, 98% vat dyes and 100% pigment showed light fastness grade of 3 and above on bleached jute. The stability against light was found in the following ascending order: Basic < Acid < Direct < Reactive < Sulfur < Vat < Pigment. Shades with a fairly good degree of light fastness coupled with reasonable brightness or hue could be achieved for jute substrate with yellow, orange, red and brown colors, while the light fastness is generally of lower order with violet, blue, green and black. In general, higher fastness to light is obtained at a higher depth of shade, but pastel shades (0.2–0.3%) can only be obtained with pigment.

46

The dyestuffs of various classes, viz. basic, acid, metal-complex (1:2), direct, reactive, sulfur, vat and pigment, capable of imparting color fastness to light rating 3–5 on jute, were cataloged in the form of “Shade Card on Jute for Value-added Products” (Samanta and Guha Roy 2010).

3.2.2.2 Dyeing with Natural Dyes Natural dyes derived from renewable sources such as plant leaves, roots, bark, insect secretions, and minerals were applied for the coloration of textiles (Gulrajani and Gupta 1992), foods and cosmetics. After the discovery of the first synthetic dye from fossil fuel in 1856, the consumption and application of natural dyes for textiles got substantially reduced and its limitations became of concern. However, the toxic and allergic reactions of synthetic dyes, the stringent environmental standards and the environmental consciousness of consumers are reviving interest in the application of natural dyes. The majority of natural dyes are environment friendly or low impact dye (Alam et al. 2007), non-toxic and non-allergic, easily disposable, compostable, easily extractable, offering pleasing shades (Chavan 1999) and purifiable. Natural dyes with very few exceptions do not have an affinity for fiber, and hence are used in conjunction with mordants (usually a metallic salt) having an affinity for both the coloring matter as well as the fiber. Serious disadvantages for the application of natural dyes are: (a) nonavailability of standard dye recipes and methods, (b) use of metallic mordants (some of which are not eco-friendly), (c) poor to moderate color fastness properties, and (d) poor reproducibility of color shades. However, processes for dyeing jute with natural dyes are now available, which paved the way for the manufacture of valueadded jute diversified products (Pan et al. 2003; Samanta and Agarwal 2008; Chattopadhyay et al. 2013, 2018).

T. K. G. Roy et al.

3.3

Woollenization of Jute

On treatment with a strong alkali, jute fiber develops a wool-like crimp or waviness. The formation of such crimps on the fiber in alkali is believed to be formed due to the uneven distribution of non-cellulosic components and crystalline regions along the length of the individual filament (Chakravarty 1962). As a result, the degree of swelling on treatment with alkali varies from place to place, producing a lot of internal stress. To get rid of stress, the filament assumes the characteristic curly or wool-like appearance. Woollenization (chemical texturing or bulking) of jute fiber is achieved by treatment with 10– 18% aqueous caustic soda (NaOH) solution in the cold or at room temperature for a minimum period of 30 min. The material is then rinsed thoroughly, neutralized with acetic acid, squeezed and dried (Guha Roy 1996; Ghosh et al. 2004). Lower the temperature better is the crimp formation. The optimum temperature for crimp formation is 2 °C, but at a higher temperature the crimp parameters are reduced, becoming zero at 40 °C (Lewin et al. 1959). The stability of the crimp is however not permanent, like what wool fiber has. This process is commercially used for blending woollenized jute fibers with wool, acrylic and other fibers for producing a coarser variety of shoddy products in the woollen or shoddy industry rather than the jute industry (Guha Roy 1996).

3.4

Chemistry-Based Jute Product Development

The chemistry of jute motivated the scientists to develop a few useful products. The major characteristics of these products are originated from the chemical structure of cellulose and hemicelluloses of jute, while some other characteristics from the physical aspects of jute fiber. Some such products, having industrial importance, are briefly mentioned below.

3

Chemistry of Jute and Its Applications

3.4.1 Pulp and Paper As an alternative to the depleting forest resources, jute with substantial cellulose content can be used to make different grades of paper. Jute waste materials (old sacks, caddis, etc.) and jute sticks can be used for manufacturing paper by employing mechanical/mechano-chemical pulping processes; however, jute is being used for long for the production of hand-made paper (Abdullah 2010). Jute pulp, having a smaller fiber length, is generally used for making ordinary qualities of writing, printing and wrapping paper, but almost always in combination with other pulps. Mixed pulping of jute stick is advisable with bagasse, rice straw and jute root cuttings, but not with bamboo or hardwood (Pandey and Anantha Krishnan 1990). Mixed pulping of jute stick with rags, jute caddis, etc. yielded pulp suitable for file cover and boxboard. Fine grade specialty tissue paper could be made by using a mixture of jute root cuttings and hosiery cuttings as fibrous raw materials. Jute pulps are generally bleached using a 5 to 10% solution of sodium or calcium hypochlorite in a two-stage process. The process gives a brightness of 50 to 60. When additives like tamarind kernel powder (TKP), carboxymethyl cellulose and diacol were mixed with the pulp, the tensile strength and folding property of the jute stick pulp were found to be considerably improved; in pulping of jute root cuttings, the addition of anthraquinnone improved the strength characteristics (Pandey and Anantha Krishnan 1990). Jute can also be pulped using fungal treatment prior to an alkaline pulping process and the pulp has higher strength properties than the pulp produced without the fungal pre-treatment.

3.4.2 Activated Charcoal The activated carbon/charcoal, having a high surface area, is very effective for gas phase and liquid phase adsorption and hence can be used for the removal of heavy metals from industrial wastewater. It could also be used as a reinforcing filler in vulcanized natural rubber in place of

47

more expensive carbon black. Activated carbon can be prepared from both jute fiber wastes and jute sticks. Activated carbon can be prepared from jute fiber wastes by a two-step physical activation process. The raw material was first carbonized under nitrogen at 500 °C and 60 min and then activated by CO2 at 800–900 °C (Chen et al. 2018). Phan et al. (2006) used jute to produce activated carbon fibers (microporous) by activation with CO2 and H3PO4. Pyrolysis of pressed jute stick chips at about 500 °C in the presence of inorganic salts yielded charcoal having 90% fixed carbon and low volatile content (Pandey and Anantha Krishnan 1990). The time of carbonization was 2 h and the yield of charcoal, 38–40%. Activated carbon was also prepared from jute stick by chemical activation using ZnCl2 and physical activation using steam (Asadullah et al. 2010). The maximum surface area was obtained as 2304 m2/g for chemical activated carbon, while it was 730 for steam activated carbon and 80 m2/g for ordinary charcoal. Carboxylate-functionalized activated carbon, with a surface area of 615.3 m2/g, was prepared from a jute stick using NaHCO3 as the activation agent (Aziz et al. 2019).

3.4.3 Furfural The importance of furfural as a solvent and as an intermediate in pharmaceutical productions is well known. It is commercially made from bran, oat hulls, corn cobs, etc. Jute stick can be an additional raw material in this respect. Furfural can be obtained from jute stick chips by acidic hydrolysis using hydrochloric acid and sulphuric acid (Mathew et al. 1984). Using 12% solution of HCl, furfural was obtained with 11% yield by distillation at atmospheric pressure. Alternatively, by boiling jute stick with 15% solution of sulfuric acid at atmospheric pressure followed by steam distillation, furfural was obtained with a 10% yield. When the reaction was carried out under pressure, only catalytic amounts (1–2%) of sulfuric acid solution were needed to obtain furfural in a very short time.

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3.4.4 Oxalic Acid Oxalic acid is an important organic chemical and has several uses. It is used as a mordant in dyeing and cloth printing, in cleaning leather, as a constituent of metal polish, to dissolve out the rust in iron pipes, etc. Crystalline oxalic acid was obtained from alkali and nitric acid fusion of jute stick (Mathew et al. 1984). In the alkali fusion method, the yield of oxalic acid was found to be maximum (50– 55%) at a NaOH / KOH ratio of 4: 1 (in a CO2free atmosphere). In the nitric acid fusion method, at 95% concentration of HNO3, 66% of cellulose, 64% of hemicelluloses, and 52% of lignin were converted to oxalic acid. The purity of crude oxalic acid from the alkali fusion technique was 82% and from nitric acid fusion, 95%.

3.4.5 Microcrystalline Cellulose (MCC) Microcrystalline cellulose (MCC), being used in medicines (as compact pellets), food, cosmetics, textiles (for printing), can be prepared through acid hydrolysis of jute fibers or high-grade jute stick pulp. Finely powdered jute stick pulp (rayon-grade) was boiled for 15 min with 2.5 N HCl at a solid/liquid ratio of 100:1. The residue was filtered, washed with water, then with dilute ammonia, and again with water. Finally, it was washed with acetone and dried at 105 °C. The yield of microcrystalline cellulose was about 90% and the degree of polymerization was 180– 200 (Saha et al. 1973). MCC was also prepared from the jute cellulose based on the acid hydrolysis technique. The yield of MCC was obtained as 48–53% (based on the jute raw material) (Jahan et al. 2011).

T. K. G. Roy et al.

thickening agent in synthetic cream, ice cream, etc. CMC was prepared from semi-bleached (70% alpha-cellulose) and also from rayon grade (> 95% alpha-cellulose) jute stick pulp using caustic soda and monochloroacetic acid (Guha 1981). The yield of the product was 150% on the weight of pulp.

3.4.7 Nanocellulose Nanocellulose can have useful applications, such as fillers in biodegradable nanocomposite plastics used in automotives, packaging, and agriculture applications. An aqueous stable colloid suspension of cellulose nano-fibrils or nanocellulose was produced from jute fibers by adopting steam explosion technique along with mild chemical treatment, such as alkaline extraction, bleaching, and acid hydrolysis but with a very mild concentration of the chemicals (Abraham et al. 2011). The nanocellulose so produced was found to possess good thermal stability. Jute fibers were used as the source to produce nanocellulose by high-energy planetary ball milling process (Bahety 2012). Wet milling in the deionized water resulted in particle size below 500 nm. Jute fibers were also used to produce “Bionanowhiskers” (Kasyapi 2013). At first, cellulose microfibrils were formed by alkali treatment. The addition of an acid to the microfibrils triggered the formation of cellulose nanowhiskers. The rod-like morphology of the nanowhiskers (length = 550 ± 100 nm, width = 77 ± 30 nm) was observed after 1 h of acid hydrolysis, whereas a further increase in time resulted in triangular shape morphology.

3.5 3.4.6 Carboxymethyl Cellulose (CMC) Carboxymethyl cellulose (CMC), an ether derivative of cellulose, is used in detergent and soap formulation, as a textile sizing material, as a

Environmental Impact of Jute

From the perspective of environmentfriendliness, the usage of natural fibers is always preferable; since it was reported that the production of 1.0 MT of the synthetic fiber requires 5.0 MT of crude oil, while 1.0 MT of

3

Chemistry of Jute and Its Applications

49

Table 3.3 Environmental Impact of Jute Vis-à-vis Polypropylene (Synthetic) Fiber SN

Jute fiber

Polypropylene (PP) fiber

1

Obtained from the annually renewable agricultural crop, requiring only sunlight to grow

Produced from crude oil, a non-renewable fossil resource

2

Production of jute crop has a negative impact on CO2 generation, the chief offender for global warming

Production of synthetic fibers liberates much CO2 (3.7 of CO2 generation per MT of PP fiber production)

3

Jute fiber is biodegradable and compostable

PP fiber is not biodegradable. Disposal of synthetics has a much damaging impact on our ecosystem

4

Energy requirement for jute fiber production is about 3.8–8.0 GJ/MT

Production of PP fiber requires about 84.3 GJ/MT energy, 10 to 20 times more than that for jute fiber

5

Jute stick, a waste in jute fiber production, may be converted into paper or particleboard or used as fuel, reducing the need for cutting trees or deforestation

Solid waste from synthetic fiber production contains harmful substances causing many environmental problems

Guha Roy (2010)

natural fibers, like jute, only 0.04 MT. Thus, the ecological balance as desired for this planet gets severely disrupted with increasing synthetic fibers’ usage (about 60% of the total 70 million MT fibers being used in textiles), which are a major source of environmental pollution. With this as a backdrop, let us now consider the environmental impact of jute in the following paragraphs. Jute is an annually renewable crop, requiring only sunlight to grow, and jute products being biodegradable decompose in the soil at the end of the product life-cycle. For having such an environmental advantage, jute has been receiving increasing interest from today’s eco-conscious consumers. Keeping in view that atmospheric CO2 is an important greenhouse gas responsible for global warming, jute has much favorable environmental impact as one hectare of jute plants, in 120 days of the growing period, can absorb about 15 MT of CO2 from the atmosphere and liberate about 11 MT of oxygen, the life-supporting agent. The CO2 assimilation rate of jute was found several times higher than that of trees (Ingaki 2000). Jute is a fast-growing crop as it matures in about 4 months. In contrast, the fastest growing wood plant requires at least 10 to 14 years for maturity. Thus, the biological efficiency of jute

plants is much higher than that of wood plants. For this, the usage of jute in place of wood for the production of paper should be encouraged to reduce the need for cutting trees or deforestation (Liu 2000). In Table 3.3, major environmental impacts of jute vis-à-vis synthetic fibers are briefly presented to register the eco-merit of jute.

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T. K. G. Roy et al. Datta AS (1960) A Study on the Physical and Chemical Characteristics of Jute Fibre at Different Growth Stage of the Plant and on the Mode of Association of the Compounds of the Mature Fibre. PhD Thesis, University of Calcutta Doree C (1947) The Methods of Cellulose Chemistry. Chapman & Hall, London, UK, p 16 Ghosh P, Samanta AK, Basu G (2004) Effect of selective chemical treatment on jute fibres aimed at improved textile related properties and processibility. Indian J Fib Text Res 29:85–99 Guha AK (1981) Carboxymethyl cellulose from jute stick. J Tex Assoc. 42:151–152 Guha Roy TK, Chatterjee S, Adhikari D, Mukherjee AK (1988) Studies on the bleaching of jute. J Text Inst 79 (1):108–125 Guha Roy TK, Chatterjee SK, Das Gupta B, Mukherjee AK (1993) Improvement of Physico-Chemical Properties of Jute / Kenaf Fibre, Yarn, Fabric for the Production of Value Added and Diversified Products – Dyeing of Jute/Kenaf, IJO/CFC Project (IJO/Ind/07): Third Interim Report Guha Roy TK (1996) Woollenising jute to improve quality. Indian Text. J 106(12):102–103 Guha Roy TK, Chatterjee SK, Dasgupta BD (2002) Comparative studies on bleaching and dyeing of jute after processing with mineral oil in water emulsion vis-a-vis self-emulsifiable castor oil. Colourage 49 (8):27–33 Guha Roy TK (2010) Eco-Status of Jute. Jute Basics, International Jute Study Group, Dhaka, Chapter 7:133–145 Gulrajani ML, Gupta D (1992) Natural Dye and their Application to Textiles, Dept. of Textile Technology, Indian Institute of Technology, New Delhi, pp 20–35 Ingaki H (2000) Progress on Kenaf in Japan. American Kenaf Society, USA, Third Annual Conf Jahan MS, Saeed A, He Z, Ni Y (2011) Jute as raw material for the preparation of microcrystalline cellulose. Cellulose 18:451–459 Kasyapi N, Chaudhary V, Bhowmick AK (2013) Bionanowhiskers from jute: preparation and characterization. Carb Poly 92:1116–1123 Lewin M, Shiloh M, Banbaji J (1959) The crimp of alkali treated jute fibers. Text Res J 29:373–385 Liu A (2000) Jute–An environmentally friendly product. International Commodity Organisation in Transition, UN Conf on Trade and Dev Macmillan WG, Basu SN (1947) The detection and estimation of damage in jute fibres - Part I. a new microscopical test and the implications of certain chemical tests. J Text Inst 38:T350-370 Macmillan WG, Sengupta AB, Majumdar SK (1949) Studies in the bleaching of jute - Part I - The action of sodium hypochlorite. J Indian Chem. Soc, Indus & News Ed. 12:105–112 Macmillan WG, Sengupta AB, Majumdar SK (1950) Studies in the bleaching of jute - Part II - Action of common bleaching agents. J Indian Chem. Soc. Indus & News Ed. 13:115–128

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Macmillan WG, Sengupta AB, Ray A (1952) Observations on the determination of lignin in jute. J Text Inst 43(2):P103-111 Macmillan WG, Sengupta AB, Majumdar SK (1954) A study of the action of alkalis on jute. J Text Inst 45: T703-715 Macmillan WG, Dutt AS, Sengupta AB (1955) Observations on the chemical composition of jute at different stages of plant growth. Sci Cult 20:566–568 Macmillan WG, Sengupta AB, Dutt AS (1956) Chromatographic study of jute alpha –cellulose. Nature 178:1346–1347 Majumdar P, Sanyal S, Das Gupta B, Shaw SC, Guha Roy TK (1994) Bleaching of jute with peracetic acid. Indian J Fib Text Res 19(4):286–292 Majumdar SK (1956) Action of Some Common Bleaching Agents and Alkalis on Jute. PhD Thesis, University of Calcutta Majumder A, Samajpati S, Ganguly PK, Sardar D, Dasgupta PC (1980) Swelling of jute: heterogineity of crimp formation. Text Res J 50(9):575–578 Mathew MD, Gopal M, Banerjee SK (1984) Preparation of oxalic acid from jute stick, an agrowaste. Agri Waste 11:47–59 Mathew MD, Gopal M, Day A, Banerjee SK (1984) Production of furfural from jute stick. Indian Pulp Paper 39(3):17–18 Megregor EA, Greenwood CT (1982) Polymers in Nature. John Wiley, Chichester, UK Chapter 7 Mukherjee A, Ganguly PK, Sur D (1993) Structural mechanics of jute: the effects of hemicellulose or lignin removal. J Text Inst 84:348–353 Mukhopadhyay U (1976) Effect of different wavelengths in the solar spectrum on discolouration of jute. Text Res J 46(2):153–154 Navell TP, Zeronian SH (1985) Cellulose Chemistry and its Applications. Ellis Harwood Ltd., Chichester, UK Ott E, Spurlin MM, Grafflin MW (1954) Cellulose and Cellulose Derivatives. Interscience 93:461 Pan NC, Chattopadhyay SN, Day A (2003) Dyeing of jute natural dyes. Indian J Fib Text Res 28:339–342 Pan NC, Chattopadhyay SN, Roy AK, Patra A (2007) Pigment printing of jute fabric. J Inst Engg (India). Textile Engg 38:56–57 Pandey SN, Anantha Krishnan SR (1990), Fifty Years of Research 1939–1989. Jute Technol Res Lab, Calcutta, pp 46, 49 Parsons HL (1939) Chemistry in the processing of jute. J Text Inst 30(9):P311-317 Patro PS (1971) Dyeing of jute with basic, acid, direct and sulphur dyestuffs. Text Dyer Print 4(8):57–62

51 Phan NH, Rio S, Faur C, Le Coq L, Le Choirec P, Nguyen TH (2006) Production of fibrous activated carbons from natural cellulose (Jute, Coconut) fibers for water treatment application. Carbon 44(12):2569–2577 Ray A (1968) Chemistry of jute (Part II). Jute Chronicle 3 (6):134–138 Ridge BP, Little AH, Wharton J (1944) Jute cellulose and the relation of jute incrustants to fibre and yarn strength. J Text Inst 35:T93-116 Saha PK, Das Gupta PC, Mukherjee PP (1973) Annual Report. Jute Technol Res Lab, Calcutta, p 17 Samanta AK, Agarwal P (2008) Application of mixtures of red sandal wood and other natural dyes for dyeing jute fabric–studies on dye compatibility. Int Dyers 193 (2):37–42 Samanta AK, Guha Roy TK (2010) Chemical Processing of Jute. Jute Basics, International Jute Study Group, Dhaka, Chapter 5:98–102 Sarkar PB (1931) Chemistry of jute lignin Pt.1. comparative study of different methods of isolation. J Indian Chem Soc 8:397–405 Sarkar PB (1933) Chemistry of jute lignin Pt.2. potash fusion of lignin. J Indian Chem Soc 10:263–270 Sarkar PB, Chatterjee H, Majumdar AK (1946) Absorption of basic dyes by jute. Nature 157:486 Sarkar PB, Chatterjee H, Mazumdar AK (1947) Acid nature of jute fibre. J Text Inst 38(9):T318-332 Sarkar PB, Chatterjee H (1948) Studies on the absorption of methylene blue by the fibre. J Soc Dyer Color 64:213–221 Sarkar PB, Mazumdar AK, Pal KB (1948) The hemicelluloses of jute fibre. J Text Inst 39(2):T44-58 Sengupta AB, Callow HJ (1951) Progressive delignification of jute fibre with chlorine dioxide. J Text Inst 42: T375-384 Sengupta AB, Dutt AS (1958) Isolation and Mode of Association of Jute Alpha Cellulose with Other Sugar Residues. Cellulose Research–a Symposium, Council of Scientific and Industrial Research, India, pp 142–149 Sengupta AB, Majumdar SK, Macmillan WG (1958) Isolation of jute holocellulose by the action of sodium chlorite. Indian J Appl Chem 21:105–110 Sengupta AB, Radhakrishnan T (1972) New Ways to Produce Textiles, Proc. 57th Annual Conference of Text Inst, pp 112–124 Sur D, Amin MdN (2010) Physics and Chemistry of Jute. Jute Basics, International Jute Study Group, Dhaka, Chapter 3:35–55 TAPPI Test Methods (1991) Vol.1 T222-OM-88, Technical Association of the Pulp and Paper Industries, Atlanta, New York, USA

4

Germplasm Resources in Jute Lilan Zhang, Jianmin Qi, Jianguang Su, and Liwu Zhang

Abstract

Jute is one of the most important bast fiber crops in the world. There are more than 100 species in jute (Corchorus spp.), but only white jute (C. capsularis) and dark jute (C. olitorius) are cultivated as diploid (2n = 2x = 14) crops. There are some different opinions on the center of origin of the two cultivated species. It is generally believed that the cultivated jute originated in Africa or southern Asia. The classification of cultivated jute species is generally based on the morphology, maturing types, and quantitative classification, among which the quantitative classification is divided into hierarchical cluster analysis, two-dimensional distribution, and principal component analysis (PCA). However, the morphological variation of jute is very abundant, so it is difficult to study its genetic diversity based on morphological characteris-

L. Zhang
J. Qi
L. Zhang (&) College of Agriculture, Fujian Agriculture and Forestry University, Fujian 350002, China e-mail: [email protected]; lwzhang@fafu. edu.cn L. Zhang e-mail: [email protected] J. Su Institute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Hunan 410000, China e-mail: [email protected]

tics and classical plant taxonomy. The development of molecular markers provides a powerful tool for the study of population structure and genetic diversity. Among them, SSR markers have been widely developed and applied in the study of genetic diversity because of their high efficiency, codominant nature, good repeatability, and good universality. Based on the cluster analysis, population structure, and genetic diversity analysis with 63 polymorphic SSR markers, the 300 jute germplasm resources were classified into two groups of white jute and dark jute, further into five subgroups. Recently, Fujian Agriculture and Forestry University resequenced 300 diverse jute accessions, and they totally identified 3,415,772 single-nucleotide polymorphisms (SNPs). The genetic diversity and population structure calculated by these new markers were similar to those calculated by SSRs. It is feasible to estimate and differentiate jute population structure effectively using molecular markers, and the markers are promising in molecular assisted breeding, gene mapping and fiber development.

4.1

Distribution of Jute (Corchorus Spp.)

Jute is one of the most important bast fiber crops in the world. There are more than 100 species in jute (Corchorus spp.), but only dark jute (C.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_4

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as the eleventh century, jute had been cultivated as a textile raw material in China, and the morphological characteristics of jute had also been recorded in 1061 AD. The origin and evolution of jute are rarely studied by researchers all over the world. There are also different opinions on the center of origin of the two cultivated species. Since the 1970s, researchers have carried out many investigations on jute germplasm resources in Africa and IndoBurma countries including Southern China, and gradually found out the geographical distribution of jute species, which provides a basis for determining the origin and evolution of jute species. In 1987, J.M. Edmomds, the herbarium consultant of the International Jute Organization

olitorius) and white jute (C. capsularis) are cultivated as diploid crops (2n = 2x = 14) (Table 4.1) (Benor et al. 2010). Jute is mainly used as cloth, rope, and raw material for shoemaking and papermaking. Most varieties of jute are mainly distributed in the tropical and subtropical regions or countries, including Africa, America, Australia, China, India, Bangladesh, Japan, Thailand, Myanmar, and so on. Among them, China, India, and Bangladesh are the world's ancient agricultural countries and important origins of cultivated plants. And they are also the world's three major jute producing countries. Jute fiber is difficult to be preserved in the site of ancient cultural remains because of its water absorption and biodegradability. As early

Table 4.1 The chromosome number and geographical distribution of jute (Corchorus spp.) Species

x = 7, 2n =

Geographical distribution

C. acutangularis

–

Africa, Southeast Asia and China

C. aestuans

14

Africa, China and India

C. africanus

–

Tanzania

C. angolensis

–

Angola, Namibia

C. asplenifalais

14

Southeastern Africa

C. axillaris

–

China

C. baldaccii

–

Eastern Africa

C. brevicarnutus

–

Africa

C. capsularis

14

Asia, Tanzania, South America, Europe

C. cavalerici

–

South of China

C. cinerascens

–

Eastern Africa

C. confuses

–

Southeastern Africa

C. depressus

–

Northeastern Africa, India

C. elachocarpus

14

–

C. erinoceus

–

South Africa, Somalia

C. erodiades

–

Suo Tara

C. fascicularis

14

Africa, India, Australia and South Asia

C. gilettii

–

Kenya

C. hitus

28

–

C. junodis

–

South Africa, Mozambican

C. kirkis

14

Southern Africa (continued)

4

Germplasm Resources in Jute

55

Table 4.1 (continued) Species

x = 7, 2n =

Geographical distribution

C. longgipedunculatis

–

Southern Africa

C. merxmuelleri

–

Namibia

C. olitorius

14

Asia, Africa, South America, Europe

C. onotheroides

–

South of China

C. pascuorum

28

Australia

C. pinnatipartitus

–

South Africa, Botta Weiner

C. polygonatum

–

South of China

C. psammophilus

–

–

C. pseudo-olitorius

–

Africa, Southeast Asia, and China

C. pseudo-capsularis

–

Africa

C. saxatilis

–

Zaire, Zambia

C. schimperi

–

Southeastern Africa

C. schimpexi

–

South America

C. schiomperi

–

China

C. sidoides

14

–

C. siliguosus

28

–

C. stenophyllus

–

Somalia

C. tridens

14

Africa, India, and South America

C. trilocularis

14

Australia, Africa, India, Southeast Asia, and China

C. uriticifolius

–

Southeastern Africa, India

C. urticifolius

–

Africa

C. velutmais

14

Southeastern Africa

C. walcolta

14

–

Note represents the information is unknown

(IJO), discovered jute species in 40 countries in Africa, including South Africa, Tanzania, Zambia, Mozambique, Ethiopia, Kenya, and so on, which confirmed that Africa is the center of origin of jute species. Since the 1990s, our group, Laboratory of Bast Fiber Crops of Fujian Agriculture and Forestry University, made a systematic study on the origin and evolution of jute. We believe that the studies on the origin of jute, the numbers and distribution frequencies of wild species, and the diversity of cultivated species are an important basis for the study on the origin and evolution of jute. Based on previous studies, we systematically analyzed the natural distribution and cultivation history of wild and cultivated jute species

in the world. According to the concept of species in modern biology, we applied the theory of continental drift, phytogeography, and crop evolution, combined with taxonomic, historical, and geographical distribution evidence of modern jute and proposed viewpoints on the origin and evolution of wild and cultivated jute species: Southeast Africa is the world origin and differentiation center of wild jute species; southeast Africa is the origin and the first differentiation center of wild dark jute; India-Myanmarsouthern China is the second differentiation center of wild dark jute, which is also the evolution center of cultivated dark jute; southern China is the origin and differentiation center of wild and cultivated white jute.

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4.2

L. Zhang et al.

Classification of Jute Germplasm Resources

The diversity of genetic basis of jute germplasm resources is an indispensable material basis for breeding excellent jute varieties. Further study on the germplasm specifically on the genetic variation in the existing resources is helpful to determine the breeding objectives and also to expand the utilization of germplasm. The systematic classification of jute is very important not only for exploring the origin and evolution but also for genetic improvement in jute. The classification of cultivated jute species is generally based on biological and morphological characteristics, and it also involves in cytology, phylogeny, and cultivation factors. According to different classification standards, the classification results are obviously not consistent.

4.2.1 Classification Based on Morphology The morphological types are very abundant in jute germplasm resources. The morphological differences are important marks for classification in jute. According to stem color, petiole color, calyx color, fruit color, the position of flower and fruit, there are more types of white jute than dark jute. There are two types of jute leaf shapes: oval and lanceolate. The stem could be divided into the straight stem and the curved stem. Stem color could be divided into three categories - red, green, brown, and again red stem type could be divided into light red, dark red, bright red, purple-red, green between red, etc. The flowers and fruits of white jute varieties with axillary buds are borne on nodes, those of white jute varieties without axillary bud are borne between nodes, while those of dark jute varieties are usually borne on nodes. In addition, there are some special morphological types, for example,

the type of dwarf, the type of smooth capsule surface, the type of flowers and fruits, etc.

4.2.2 Classification Based on Maturing Types The fiber yield and economic characters are related to the maturing period in jute. According to the cultivation of the variety and the maturing days from seedling to seed maturity, jute can be divided into five maturing types: very early, early, medium, late, and very late (Table 4.2). Most of the local varieties are early maturing, and most of the improved varieties are late maturing. The length of the maturity period of jute varieties is mainly determined by the light and temperature parameters. In medium to late maturity varieties, the days from seedling to fiber maturity is 80 * 90 (d), and the days from seedling to seed maturity is 110–120 (d). In general, due to the delayed growth period and longer vegetative growth period, medium, late, and very late varieties have better economic characters and higher yields. However, when the very late mature varieties are planted in the northern regions of China, they could not reserve seeds for planting under natural conditions.

4.2.3 Quantitative Classification Quantitative classification methods, including cluster analysis, two-dimensional ordination analysis, and discriminant analysis, have been widely used in plant classification. At present, there are many reports for jute on the evaluation of comprehensive characters of varieties by principal component analysis (PCA) and the analysis of genetic differences among varieties by statistical analysis and cluster analysis. The analysis of the characteristics of quantitative

4

Germplasm Resources in Jute

57

Table 4.2 Maturing types of jute germplasm resources Species

Maturing types

Days to buds (d)

C. capsularis

Very early

40 * 55

Early

56 * 75

Medium Late Very late C. olitorius

Plant height (cm)

Branch height (cm)

134 * 175

56 * 85

141 * 160

150 * 250

100 * 183

1.01 * 1.3

0.61 * 0.9

76 * 95

161 * 180

230 * 300

174 * 261

1.19 * 1.6

0.74 * 1.1

96 * 130

181 * 200

301 * 400

257 * 365

1.5 * 1.9

0.94 * 1.39

> 131

Very early

40 * 55

Early

56 * 75

Days to seeds mature (d) 200 401

>317

Stem diameter (cm) 1.21

401

>317

>1.91

>1.21

introduced, that is, according to the characteristics of the large contribution rate of the first, second, or third PC, the first PC is used as the abscissa, and the second or third PC is used as the ordinate, respectively. The twodimensional distribution figure can reflect the distribution characteristics of the tested materials succinctly and intuitively, and reveal the obvious differences and similar or relative positions in the performance of various varieties. If the contribution rate of the first and second PCs is large, the result of two-dimensional distributions with the first two PCs is similar to that of hierarchical clustering, which is simple, intuitive, and close to the natural type grouping.

4.2.3.3 Hierarchical Cluster Analysis The agronomic characters of 288 jute germplasm resources were clustered by NB, PH, FBW, BH, DF, FSW, SD, FBT, NMS, DBW, and DM by Xu et al. (2019). These germplasm resources could be divided into eight groups based on Euclidean distance (0.036). The first group contained 34 germplasm resources, which were characterized by late flowering and maturity; the second group included 21 germplasms, which were characterized by moderate flowering but late maturity; the third group contained 68 germplasm resources, which were characterized

58

L. Zhang et al.

by moderate plant height and few numbers of branches; the fourth group contained 57 germplasms, which were characterized by low plant height and branch height; the fifth group contained 45 germplasms, which were characterized by early flowering and maturity; the sixth group contained 29 germplasm resources, which were characterized by high plant height and thick fresh bark; the seventh group contains 31 germplasms, which were characterized by high branch height but moderate nodes of the main stem; and the eighth group contained three germplasm resources, and their main characteristics were that their fresh stem weight per plant was larger. In Table 4.3, it could be seen that the variation coefficient of each characteristic of 288 jute germplasm resources was 13.06–84.87%. Among them, the largest was the number of branches, the smallest was the days to flowering, evidencing a rich genetic diversity in jute.

4.3

Molecular Analysis and Genetic Diversity

As known universally, the analysis of genetic structure and diversity are important components of germplasm resources. Plant genetic diversity

Table 4.3 Statistical analysis of main agronomic traits in 288 jute germplasm resources (Xu et al. 2019)

Traits

plays an important role in improving crop yield and disease resistance, which have been paid more and more attention. Although the morphological variation of jute is very abundant, it is difficult to study the genetic diversity based on morphological characteristics and classical plant taxonomy. Some researchers studied the genetic diversity in jute germplasm by morphologic characters, but this method was affected by environment and time. But now, people could use molecular markers to overcome this limitation. The development of molecular markers provided a powerful tool for the study of genetic relationships among species and genetic diversity. Tao et al. (2012) developed sequencerelated amplified polymorphism (SRAP) markers to study the origin and evolution of jute using 96 germplasm resources from 13 different countries. They believed that the centers of origin of wild and cultivated dark jute were all in Africa; and southern China was the center of origin of cultivated white jute. Zhang et al. (2015a) used 20 dark jute and 40 white jute varieties to analyze the genetic relationship and genetic diversity by a genetic coefficient and cluster analysis, and found that the genetic similarity relationships of white jute cultivars were higher than that of dark jute cultivars. The

Mean ± SD

Range

CV (%)

DF (d)

114.78 ± 15.00

91–158

13.06

DM (d)

175.05 ± 24.43

137–218

13.96

DBW (g)

38.22 ± 19.20

PH (cm)

334.69 ± 51.50

BH (cm)

106.62 ± 67.50

FBT (mm)

1.34 ± 0.82

2–110

50.24

168–482

15.38

4.1–391.4

63.28

0.635–2.023

19.27

FSW (g)

610.03 ± 209.80

64–1266

33.85

FBW (g)

130.86 ± 66.60

7.5–394.0

50.41

NMS

19.00 ± 14.40

1.0–78.7

75.74

NB

20.50 ± 17.40

1.5–74.0

84.87

BR (%) SD (mm)

6.21 ± 2.31 20.435 ± 3.308

1.23–16.11

37.13

10.751–28.965

16.19

DF: days to flowering; DM: days to seeds mature; PH: plant height; SD: stem diameter; FBT: fresh bark thickness; NMS: nodes of the main stem; FSW: fresh stem weight per plant; FBW: fresh bark weight per plant; DBW: dry bark weight per plant; BR: bark rate; BH: branching height; NB: number of branches

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59

cleaved amplified polymorphic sequence (CAPS) markers screened by Tao et al. (2020) could effectively distinguish 12 different accessions of jute germplasm, indicating CAPS to also be a reliable tool used in genetic research of jute. Tree diagram based on 119 polymorphic InDels, lead to the classification of 24 jute varieties into two groups, white and dark jute, and further into four subgroups (Zhang et al. 2017). Yang et al. (2018) analyzed the genetic diversity of 62 jute varieties by 29 polymorphic InDel loci. Molecular marker technology was mainly used in studies of the origin and evolution of species, analysis of phylogeny and genetic diversity, identification of hybrids, population genetics analyses, and other related fields. So far, the molecular markers have been widely developed and applied in jute, such as CBDP (Singh et al. 2013), AFLP (Das et al. 2011), ISSR (Saha et al. 2014), RAD (Kundu et al. 2015), RAPD (Roy et al. 2006), SSR (Kundu et al. 2013), and InDel (Zhang et al. 2017). Among these markers, SSRs have been widely developed and applied in the study of genetic diversity because of their high efficiency, codominant nature, good repeatability, and good universality (Banerjee et al. 2012; Khan et al. 2010; Kundu et al. 2013). High genetic diversity was reported among dark jute by SSRs indicating the utility of SSR

Table 4.4 Statistics of SSR markers in jute (Zhang 2018)

markers for providing useful polymorphism for jute genotypes (Ghosh et al. 2015). Zhang et al. (2015b, c) successfully evaluated the genetic diversity of 12 and 58 jute germplasm resources by SSR markers, and found that the jute germplasm resources were all divided into two groups (Cc and Co). The 159 jute germplasm resources were divided into Cc and Co groups when k (the number of subgroups) was at 2 by 63 SSRs (Zhang et al. 2015d). Using 63 pairs of SSR primers to study 300 jute germplasm resources, a total of 213 alleles were obtained, that is, the average number of alleles detected by each primer was 3.381 (Table 4.4). The polymorphic information content (PIC) of the SSR primers ranged from 0.0370 to 0.9281, with an average of 0.7289, and the PIC values of 26 primers were larger than 0.8 (Table 4.4). Among them, CcSSR045 had the greatest allele variation (9), and the PIC value was 0.9281. The second were CoSSR146 (7) and CoSSSR362 (7), and the PIC values were 0.9033 and 0.9058, respectively. CcSSR019, CoSSR057, CoSSR065, CoSSR086, CoSSR173, and CoSSSR244 were markers found with the least allele variation (1), with the PIC values of 0.2736, 0.4856, 0.3289, 0.4729, 0.0370, and 0.0842, respectively. It was observed that allele

SSR Primers

Allele number

PIC

SSR Primers

Allele number

PIC

CcSSR001

4

0.8398

CoSSR263

2

0.5441

CcSSR004

2

0.706

CoSSR266

3

0.727

CcSSR007

2

0.7175

CoSSR050

5

0.8705

CcSSR008

5

0.8578

CoSSR053

4

0.7678

CcSSR011

3

0.7866

CoSSR054

4

0.8248

CcSSR019

1

0.2736

CoSSR174

4

0.8467

CcSSR020

2

0.7365

CoSSR176

4

0.8333

CcSSR024

3

0.8079

CoSSR178

3

0.721

CcSSR025

2

0.656

CoSSR179

3

0.7979

CcSSR030

6

0.8692

CoSSR181

4

0.804

CcSSR038

3

0.7465

CoSSR188

3

0.7896

CcSSR045

9

0.9281

CoSSR191

3

0.7505 (continued)

60 Table 4.4 (continued)

L. Zhang et al. SSR Primers

Allele number

PIC

SSR Primers

Allele number

PIC

CoSSR057

1

0.4856

CoSSR192

4

0.8128

CoSSR058

3

0.7857

CoSSR195

4

0.8111

CoSSR062

3

0.7998

CoSSR196

4

0.8412

CoSSR065

1

0.3289

CoSSR228

5

0.8204

CoSSR072

2

0.704

CoSSR229

2

0.565

CoSSR086

1

0.4729

CoSSR227

6

0.9022

CoSSR099

2

0.7072

CoSSR238

3

0.7538

CoSSR105

2

0.5696

CoSSR239

3

0.7563

CoSSR119

2

0.639

CoSSR305

6

0.8937

CoSSR133

2

0.5923

CoSSR362

7

0.9058

CoSSR122

5

0.8739

CoSSR452

5

0.8706

CoSSR146

7

0.9033

CoSSR094

2

0.7025

CoSSR168

2

0.649

CoSSR052

5

0.8515

CoSSR173

1

0.037

CoSSR434

6

0.9011

CoSSR177

3

0.7935

CcSSR015

2

0.6491

CoSSR184

5

0.8443

CoSSR194

3

0.7299

CoSSR232

5

0.8534

CoSSR087

2

0.7043

CoSSR231

4

0.8157

CoSSR438

3

0.8125

CoSSR241

3

0.7592

CoSSR136

2

0.7365

CoSSR244

1

0.0842

variations and PIC values have a similar trend. When the number of alleles was higher, the PIC value was high. These SSR primers could indicate the genetic differences among different accessions, and the genetic diversity of these test accessions were abundant. The population structure of all tested accessions was analyzed using software Structure and maximum likelihood principle (Fig. 4.1). When K = 2, DK reached its maximum value. From this result, it could be concluded that the population was divided into two subgroups, Corchorus capsularis (Cc) and Corchorus olitorius (Co) (Fig. 4.2). We also classified the population structure of the two subgroups and found that

there were three subgroups in the Co group and two subgroups in the Cc group (Figs. 4.1 and 4.2). According to the geographical origin of the jute population, the Co group could be divided into three subgroups: Africa, Southern Asia, and China, while the Cc group could be divided into two subgroups: China and Southern Asia. The phylogenetic tree showed that the accessions that belonged to the same group tended to be clustered together, while those belonging to different groups tended to be far from each other (Fig. 4.3). This indicated the population structure was credible for the classification of 300 accessions.

4

Germplasm Resources in Jute

Fig. 4.1 The trend of DK with K value in jute natural population. a Total; b Cc subgroup; c Co subgroup (Zhang 2018)

Fig. 4.2 Population structure analysis of jute natural population (Zhang 2018)

61

62

Fig. 4.3 Neighbor-joining tree of 300 jute varieties based on Nei’s genetic distance (Cc1: Black; Cc2: Red; Co1: Yellow; Co2: Blue; Co3: Green) (Zhang 2018)

The genetic relationships of the jute population were evaluated by software SPAGeDi. The results showed that the average kinship value of 300 accessions was 0.0658. Among which, 55.6% of two accessions had a genetic relationship value of 0 and 24.3% had a genetic relationship value between 0 and 0.1 (Fig. 4.4). This

L. Zhang et al.

indicated that the genetic relationship of most accessions in this population was weak. Recently, our research group of Fujian Agriculture and Forestry University first published the chromosome level reference genome maps of the two cultivated jute species, and we resequenced 300 different jute materials from all over the world (Zhang et al. 2021). From these re-sequenced data, they totally identified 697,767 InDels and 3,415,772 SNPs. The genetic diversity and population structure calculated by these markers were fine but similar to those calculated by SSRs. In this chapter, large-scale simple repeat sequences have also proved the significance of population structure and genetic diversity. Using these polymorphic markers, the genetic relationship and population structure of these natural populations could be analyzed in jute, which provided a theoretical basis for genetic improvement of jute. It is of great scientific significance to study the genetic relationship and genetic diversity for its origin, evolution, collection, sorting, identification and utilization of germplasm resources, and protection of genetic diversity in jute. It can also provide a scientific basis for further breeding and germplasm innovation of jute.

Fig. 4.4 Distribution of relative kinship coefficient between every two accessions among jute natural population (Only kinship coefficients of 0 to 0.5 are shown) (Zhang 2018)

4

Germplasm Resources in Jute

References Banerjee S, Das M, Mir RR, Kundu A, Topdar N, Sarkar D, Sinha MK, Balyan HS, Gupta PK (2012) Assessment of genetic diversity and population structure in a selected germplasm collection of 292 jute genotypes by microsatellite (SSR) Markers. Mol Plant Breed 3(1):11–25 Benor S, Blattner FR, Demissew S, Hammer K (2010) Collection and ethnobotanical investigation of Corchorus species in Ethiopia: potential leafy vegetables for dry regions. Genet Resour Crop Evol 57(2):293–306 Das M, Banerjee S, Topdar N, Kundu A, Sarkar D, Sinha MK, Balyan HS, Gupta PK (2011) Development of large-scale AFLP markers in jute. J Plant Biochem Biotechnol 20(2):270–275 Ghosh S, Meena K, Sinha MK, Karmakar PG (2015) Genetic diversity in Corchorus olitorius genotypes using jute SSRs. Proc Natl Acad Sci India Sect B Biol Sci 87(3):917–926 Khan H, Huq S, Islam MS, Sajib AA, Ashraf N, Haque S (2010) Genetic diversity and relationships in jute (Corchorus spp.) revealed by SSR markers. Bang J Bot 38(2):153–161 Kundu A, Topdar N, Sarkar D, Sinha MK, Ghosh A, Banerjee S, Das M, Balyan HS, Mahapatra BS, Gupta PK (2013) Origins of white (Corchorus capsularis L.) and dark (C. olitorius L.) jute: a reevaluation based on nuclear and chloroplast microsatellites. J Plant Biochem Biotechnol 22(4):372–381 Kundu A, Chakraborty A, Mandal NA, Das D, Karmakar PG, Singh NK, Sarkar D (2015) A restrictionsite-associated DNA (RAD) linkage map, comparative genomics and identification of QTL for histological fibre content coincident with those for retted bast fibre yield and its major components in jute (Corchorus olitorius L., Malvaceaes. l.). Mol Breed 35(1):19 Lu R, Yang Z, Dai Z, Xu Y, Tang Q, Cheng C, Chen J, Su J (2017) Evaluation for salt tolerance of 50 jute (Corchorus olitorius L.) germplasm resources. J Plant Genet Resour 18(6):1055–1066 Nyadanu D, Adu Amoah R, Kwarteng AO, Akromah R, Aboagye LM, Adu-Dapaah H, Dansi A, Lotsu F, Tsama A (2016) Domestication of jute mallow (Corchorus olitorius L.): ethnobotany, production constraints and phenomics of local cultivars in Ghana. Genet Resour Crop Evol 64(6):1313–1329 Roy A, Bandyopadhyay A, Mahapatra AK, Ghosh SK, Singh NK, Bansal KC, Koundal KR, Mohapatra T (2006) Evaluation of genetic diversity in jute (Corchorus species) using STMS, ISSR and RAPD markers. Plant Breed 125(3):292–297 Saha P, Sarkar D, Kundu A, Majumder S, Datta SK, Datta K (2014) Karyotype analysis and chromosomal

63 evolution in Asian species of Corchorus (Malvaceae s. l.). Genet Resour Crop Evol 61(6):1173–1188 Singh AK, Rana MK, Singh S, Kumar S, Kumar R, Singh R (2013) CAAT box- derived polymorphism (CBDP): a novel promoter -targeted molecular marker for plants. J Plant Biochem Biotechnol 23(2):175–183 Tao A, Qi J, Su J, Fang P, Lin L, Xu J, Wu J, Lin P (2012) Analysis of genetic diversity of jute (Corchorus L.) germplasm revealed by SRAP. Plant Sci J 30(2):178– 187 Tao A, You Z, Xu J, Lin L, Zhang L, Qi J, Fang P (2020) Development and verification of CAPS markers based on SNPs from transcriptome of jute (Corchorus L.). Acta Agron Sin 46(7):987–996 Xu Y, Zhang L, Guo Y, Qi J, Zhang L, Fang P, Zhang L (2019) Core collection screening of a germplasm population in jute (Corchorus spp.). Acta Agron Sin 45(11):1672–1681 Yang Z, Dai Z, Xie D, Chen J, Tang Q, Cheng C, Xu Y, Wang T, Su J (2018) Development of an InDel polymorphism database for jute via comparative transcriptome analysis. Genome 61(5):323–327 Zhang J, Chen C, Luo X, Jin G (2016) Comprehensive evaluation and cluster analysis on yield characters of 26 jute germplasm esources based on principal components. J Plant Genet Resour 17(3):475–482 Zhang J, Chen C, Luo X, Jin G (2015a) Analysis of the coefficient of parentage among major jute cultivars in China. Sci Agri Sin 48(20):4008–4020 Zhang L, Cai R, Yuan M, Tao A, Xu J, Lin L, Fang P, Qi J (2015b) Genetic diversity and DNA fingerprinting in jute (Corchorus spp.) based on SSR markers. Crop J 3(5):416–422 Zhang L, Li Y, Tao A, Fang P, Qi J (2015c) Development and characterization of 1,906 EST-SSR markers from unigenes in jute (Corchorus spp.). PLoS One 10(10): e0140861 Zhang L, Yuan M, Tao A, Xu J, Lin L, Fang P, Qi J (2015d) Genetic structure and relationship analysis of an association population in jute (Corchorus spp.) evaluated by SSR markers. PLoS One 10(6):e0128195 Zhang L, Gao Z, Wan X, Xu Y, Zhang L, Tao A, Fang P, Qi J, Zhang L (2017) Development of novel small InDel markers in jute (Corchorus spp.). Trop Plant Biol 10(4):169–176 Zhang L (2018) Development of InDel markers and association analysis of fiber quality related traits in jute (Corchorus spp.). MS Thesis of Fujian agriculture and Forestry University, Fuzhou, Fujian, China Zhang L, Ma X, Zhang X, Xu Y, Ibrahim AK, Yao J, Huang H, Chen S, Liao Z, Zhang Q, Niyitanga S, Yu J, Liu Y, Xu X, Wang J, Tao A, Xu J, Chen S, Yang X, He Q, Lin L, Fang P, Zhang L, Ming R, Qi J, Zhang L (2021) Reference genomes of the two cultivated jute species. Plant Biotechnol J 1-14. https://doi.org/10.1111/pbi.13652

5

DUS Test and DNA Fingerprinting Construction of Jute Varieties Qingyao He, Jiayu Yao, Pingping Fang, Jianmin Qi, and Liemei Zhang

Abstract

In order to promote the application of distinctness, uniformity and stability (DUS) test guidelines for jute and to promote the testing and identification of new jute varieties in this chapter, the details of DUS test guidelines were described, including the selection and determination of tested traits, the selection of standard varieties, and the evaluation of distinctness, uniformity and stability. There were 35 standard varieties and 33 tested traits in the DUS test, including 7 qualitative traits (QL), 18 quantitative traits (QN), 8 pseudo qualitative traits (PQ). Among the 33 tested traits, 21 characters with an asterisk were required to be tested, while 12 tested traits without an asterisk were selected. 5 tested traits were selected for variety grouping and 12 traits were used in the technical questionnaire. The formulation of jute DUS testing guidelines is helpful to strengthen the protection of new varieties, protect the interests of breeders and improve the enthusiasm of breeding. Furthermore, the applied core collection in jute was constructed,

Q. He
J. Yao
P. Fang
J. Qi
L. Zhang (&) Agricultural College, Fujian Agriculture and Forestry University, Fujian 350002, China e-mail: [email protected] J. Qi e-mail: [email protected]

including 61 accessions divided into 16 applications-oriented features, such as high yield, high quality, and disease resistance and so on, which were established based on the field performance from 300 jute germplasm. 12 fluorescent core primers were screened from 46 pairs of core primers. Fluorescence-labeled capillary electrophoresis was used to analyze the polymorphism of these 12 pairs of primers, and a total of 140 polymorphism sites were detected. The precise DNA molecular ID cards were constructed by the combination of the 12 core primer pairs from the data coded in the form of numbers and English letters. Bar code and quick response code DNA molecular were established and can be quickly scanned and recognized by electric gadget. These results could be beneficial to increase the application efficiency and rapid molecular identification in jute germplasm resources.

5.1

Introduction

DUS test, namely the distinctness, uniformity and stability test of new plant varieties, is the basis of new plant variety protection technology, the scientific basis for granting variety rights, the powerful tool and standard for approval of new varieties, and the corresponding international body is the International Union for the Protection of New Varieties of Plants (UPOV), UPOV is based on the International Convention for the

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_5

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Protection of New Varieties of Plants (UPOV 2014). The role of UPOV is primarily to coordinate and promote cooperation among member states in the administrative and technical fields, particularly in the development of basic legal and technical guidelines, the exchange of information and the promotion of international cooperation (Li et al. 2003). Therefore, the formulation of a DUS test guide for new jute varieties will make the development and utilization of jute germplasm resources more effective. The rights of plant breeders will also be better protected (Dai et al. 2007). In addition, mining jute core collection is also conducive to improve the utilization efficiency of germplasm resources (Wang et al. 2013). In order to identify the differences between core germplasm or applied core germplasm, more and more researchers are using molecular markers to construct DNA fingerprints. At present, the methods of fingerprint construction include polyacrylamide gel electrophoresis, fluorescence capillary electrophoresis, etc. With the rapid development of DNA fingerprinting by SSR fluorescence-labeled capillary electrophoresis, the DNA fingerprinting can be converted into strings, barcodes and two-dimensional codes, etc. on the basis of fingerprint, which is called DNA molecular identity (Tian et al. 2015). It can accurately and concisely identify different germplasm resources without being affected by environmental factors.

5.2

Jute DUS Test Guidelines

5.2.1 Components of Jute DUS Test Guidelines DUS test guidelines are divided into ten components: (1) The scope of the test guideline; (2) Normative reference document; (3) Terminology, definition, and abbreviation; (4) Symbol; (5) Requirements of reproductive materials; (6) Test method; (7) Determination of distinctness, uniformity and stability results; (8) Character table; (9) Grouped traits; (10) Technical questionnaire. The development process includes the selection and determination of test

characteristics, the expression state of characteristics, the selection of sample varieties, the sequence of characteristics, and the evaluation of distinctness, uniformity, and stability (DUS).

5.2.2 Application Scope of Jute DUS Test Guideline Jute (Corchorus L.) is an annual herb or subshrub plant which belongs to the genus of Malvaceae. The genus Corchorus has more than 100 species and is distributed in the tropics of the world. Of more than one hundred species in existence, only white jute (C. capsularis) and dark jute (C. olitorius) are exploited for fiber production and are primarily cultivated. Application of jute DUS test guideline is applicable to the distinctness, uniformity and stability test and results in determination of new white or dark jute varieties.

5.2.3 Selection of Test Traits The selection of traits for testing should meet the requirements for traits for DUS testing as stated in “General Introduction to Plant Variety Distinctness, Uniformity and Stability Testing”: (1) specific genotypes or combinations of genotypes; (2) repeatable under specific environmental conditions; (3) enough differences among varieties to be used for distinctness determination; (4) accurately identified and described; (5) the requirements of uniformity and stability. All forty-six morphological traits were discriminated against based on selected standard varieties. The twenty-three quality traits or pseudoquality traits had no change in different years. Among the twenty-three quantitative traits, fifteen were less affected by the environment. In combination with the characteristics of heritability, stable expression, difference, and easy recognition, thirty-three test traits were screened (Table 5.1), including twenty-one required test traits and twelve selected test traits. These traits include Cotyledon shape; Color of hypocotyl;

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DUS Test and DNA Fingerprinting Construction of Jute Varieties

Table 5.1 Testing traits of DUS test guidelines for jute (Zhang et al. 2020)

No

Types

Traits

1

PQ

(*) Cotyledon shape

2

PQ

(*) (TQ) Hypocotyl color

3

QL

(*) (G) (TQ) (a) Stem. Axillary bud with and without

4

QL

(*) (TQ) (a) Stem. Stem type

5

QL

(*) (TQ) (a) Stem. On the surface of tumor or not

6

PQ

(*) (G) (TQ) (a) Stem. Stem color

7

PQ

(*) (TQ) (a) Stem. Stipule

8

PQ

(*) (TQ) (b) Leaf shape

9

PQ

(*) (b) Leaf blade attitude

10

PQ

(*) (b) Leaf apex shape

11

PQ

(*) (G) (TQ) (b) Leaf petiole color

12

QN

(*) Budding date

13

QL

(*) (TQ) Calyx color

14

QN

(*) Flowering date

15

QN

(*) Fiber maturation stage

16

QN

(*) (b) Plant height

17

QN

(*) (b)The lowest branching number

18

QL

(*) (G) (TQ) (d) Fruit. Fruit Shape

19

QL

(*) (G) (TQ) (d) Fruit. Growing place of fruit

20

QL

(*) (TQ) (e) Seed. Seed coat color

21

QN

(*) (e) Seed.1000 seed weight

22

QN

(c) Plant. Main stem number of nodes

23

QN

(c) Plant. Stem diameter

24

QN

(c) Plant. Fresh bark thickness

25

QN

(c) Plant. Branching number

26

QN

(c) Plant. Fresh stem weight per plant

27

QN

(c) Plant. Fresh bark weight per plant

28

QN

(c) Plant. Dry bark weight per plant

29

QN

(c) Plant. Fiber Fineness (Only applicable to fiber varieties)

30

QN

(c) Plant. Fiber strength (Only applicable to fiber varieties)

31

QN

(c) Plant. The rate of hemp (Only applicable to fiber varieties)

32

QN

Young leaves yield (Only applicable to Vegetable varieties)

33

QN

(e) Seed mature date

67

QL qualitative characteristics, QN quantitative characteristics, PQ pseudo-qualitative characteristics, (*) asterisked characteristics, (G) grouping characteristics, (TQ) technical questionnaire characteristics, (a) Observation of mature leaves in the upper and middle parts of the main stem, (b) observation of mature leaves in the upper and middle parts of the plant, (c) random sampling of 20 plants from the middle of the experimental plot as observation objects, (d) observation of representative intact horned fruit and (e) observation of representative full seeds

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Q. He et al.

Stem: Axillary bud with and without; Stem: Stem type; Stem: on the surface of the tumor or not; Stem: Stem color; Stem: Stipule; Leaf: Shape; Leaf: Blade attitude; Leaf: Apex shape; Leaf: Petiole color; Days to buds; Color of Calyx; Days to flowering; Days to technical mature; Plant: Height; The lowest number of branches; Fruit: Fruit Shape; Fruit: Growing place of fruit; Seed: Color of Seed coat; Seed: 1000 seed weight; Plant: Nodes of main stem; Plant: Stem circumference; Plant: Fresh bark thickness; Plant: Number of branches; Plant: Fresh stem weight per plant; Plant: Fresh bark weight per plant; Plant: Dry bark weight per plant; Plant: Fiber number (Only applicable to fiber varieties); Plant: Fiber strength (Only applicable to fiber varieties); Plant: Bark rate (Only applicable to fiber varieties); Young leaves: yield (Only applicable to Vegetable varieties); Days to seeds mature. According to the type of traits, they were divided into seven qualitative traits, eight pseudo-qualitative traits, and eighteen quantitative traits (Table 5.2).

5.2.3.1 Basic and Selected Testing Traits According to the definition of traits in Chap. 4 of TG 1/3 General Introduction, the thirty-three traits were divided into three types: seven qualitative (QL) traits, eighteen quantitative (QN) traits, and eight pseudo-qualitative (PQ) traits (Table 5.2). At the same time, some traits (such as asterisk traits, TQ traits, and grouping traits) which are in DUS test guidelines have specific functions. Among them, the basic traits (required test traits) were named the asterisk trait, and the selected test traits were named the non-asterisk trait. The asterisk trait plays an important role in the international unification of species description (UPOV 2002) general introduction to the examination of distinctness, uniformity and stability and the development of harmonized descriptions of new varieties of plants 2017). Therefore, the selected asterisk traits that must be included in the Test Guidelines should always be used for variety description by all UPOV Member States (International Union for the Protection

Table 5.2 Statistical data on test characteristics of jute (Zhang et al. 2020) Items

QL

PQ

QN

Asterisked

Non-asterisked

Grouping

TQ

Total

Cotyledon

0

1

0

1

0

0

0

1

Hypocotyl

0

1

0

1

0

0

1

1

Stem

3

2

0

5

0

2

5

5

Leaf

0

2

0

2

0

0

1

2

Leaf apex

0

1

0

1

0

0

0

1

Leaf petiole

0

1

0

1

0

1

1

1

Budding date

0

0

1

1

0

0

0

1

Calyx

1

0

0

1

0

0

1

1

Flowering date

0

0

1

1

0

0

0

1

Fiber maturation stage

0

0

1

1

0

0

0

1

Plant

0

0

12

2

10

0

0

12

Fruit

2

0

0

2

0

2

2

2

Seed

1

0

1

2

0

0

1

2

Young leaves

0

0

1

0

1

0

0

2

Seed mature date

0

0

1

0

1

0

0

1

Total

7

8

18

21

12

5

12

33

QL qualitative characteristics, PQ pseudo-qualitative characteristics, QN quantitative characteristics, (*) asterisked characteristics, Non-asterisked characteristics, TQ technical questionnaire characteristics. Total = QL + QN + PQ or Total = Asterisked + Non-asterisked

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DUS Test and DNA Fingerprinting Construction of Jute Varieties

of New Varieties of Plants (UPOV 2014). According to the selection criteria, twenty-one traits (e.g., Stem: Axillary bud with and without, Leaf: Shape, and Budding stage) were selected as asterisk traits, while the remaining twelve traits (e.g., Plant: Fresh bark thickness, Young leaves: yield and Days to seeds mature) were labeled as non-asterisk traits. Among the asterisk traits, the number of main stem traits was up to five, while among the non-asterisk traits, the number of plant traits was up to ten (Tables 5.1 and 5.2).

5.2.3.2 Selection of Grouping Traits and Technical Questionnaire Traits Grouping traits are convenient for the classification and management of known varieties. In the screening of similar varieties, more similar varieties can be selected by grouping traits, and most of the known varieties can be excluded. The relationship between asterisks, groups, and TQ traits should be considered before selecting grouping traits and TQ (Technical Questionnaire) traits. Typically, grouping traits that should be marked with an asterisk in the trait table are derived from technical questionnaires. TQ traits that are not limited to grouping traits should be marked with an asterisk in the trait table and selected as grouping traits(International Union for the Protection of New Varieties of Plants (UPOV 2014). For the selection of group traits, in addition to considering the relationships described above, the principle that the grouped traits must be qualitative should be strictly followed(International Union for the Protection of New Varieties of Plants (UPOV 2014), unless useful quantitative or pseudo-qualitative traits can be provided to distinguish common sense from written expression states recorded in different locations. According to the scope of application of this guideline, the following five grouping traits were determined: (a) Stem: Axillary bud with and without (trait no. three); (b) Stem: Stem color (trait no. six); (c) Leaf: Petiole color (trait no. eleven); (d) Fruit: Fruit Shape (trait no. eighteen); (e) Fruit: Growing place of fruit (trait no. nineteen) in Table 5.1. During the selection of TQ traits, in addition to

69

satisfying the relationship between asterisk, grouping, and TQ traits, the following requirements must be met: TQ traits should include grouping traits and be the most differentiated traits (International Union for the Protection of New Varieties of Plants (UPOV 2014). The requirements are detailed and serve as a guide in selecting the TQ traits of new jute varieties. Twelve traits were used in the technical questionnaire, including the color of hypocotyl; Stem: Axillary bud with and without; Stem: Stem type; Stem: On the surface of the tumor or not; Stem: Stem color; Stem: Stipule; Leaf: Shape; Leaf: Petiole color; Color of Calyx; Fruit: Fruit Shape; Fruit: Growing place of fruit; Seed: Color of Seed coat (Tables 5.1 and 5.2). Five of these TQ traits are the main stem traits was shown in Table 5.1.

5.2.3.3 The State Division of Trait Expression and the Determination of Corresponding Codes To determine the completeness of the DUS test guidelines, it is necessary to determine the test traits and expression status of the sample varieties. To provide the variety to be tested and to establish a variety description, the range of expression for each trait in the Test Guide is divided into multiple states for description, and the wording of each state is assigned a digital ‘note’ (UPOV 2002) General introduction to the examination of distinctness, uniformity and stability and the development of harmonized descriptions of new varieties of plants. Among them, the expression status of seven quality traits was ‘none’ and ‘have’, which were labeled as “1” and “9”, respectively. Such as Stem: Axillary bud with and without. Stem types are “erect” and “spiral”, respectively, and the sepals “green” and “red” are also marked “1” and “9”. Among the eight pseudo quality traits, three were color traits. Among them, the hypocotyl color and petiole color are “green”, “light green”, and “red”, respectively, marked as “ 1”’, “ 2”, and “ 3” respectively. Another color trait is the stem color, which corresponds to “1, 2, 3, 4, 5” according to its expression state. There are also three shape traits, which also correspond to “1, 2, 3”

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according to their expression status. The remaining eighteen were quantitative traits with “1–9” ‘finite’ codes.

5.2.4 Selection of Standard Varieties Standard or example varieties are a group of known varieties with rich genetic diversity determined by auxiliary tests and reference standards for trait description and grading (Yan et al. 2014). Selecting standard varieties plays an important role in effectively eliminating year errors and improving test reliability (Wang et al. 2002). Standard varieties play a role in clarifying the state of trait expression in the Test Guidelines to account for traits and to develop internationally uniform varietal descriptions (UPOV 2002) General introduction to the examination of distinctness, uniformity and stability and the development of harmonized descriptions of new varieties of plants. To select the standard varieties and compare the different varieties of jute standard genetic differences, the use of thirty-three of SSR primers clustering analysis was carried out on the primary standard of thirty-five varieties

Q. He et al.

(Fig. 5.1) by using available molecular marker data in our research group. Taking coefficient of Euclidean distance, 0.75, as the classification line, it can be divided into nine categories. The most similar varieties are Funong 4 and Guangbaai, followed by Yueyuan 5 and Guangdong duwei ma, Taiwan galima and Taiwan 9, Riben 5 and Zaoshengchi. Therefore, thirty-five standard varieties were screened out to perfectly interpret thirty-three test traits (Table 5.3).

5.2.5 Jute DUS Determination Criteria 5.2.5.1 General Principles The determination of distinctness, uniformity, and stability was carried out in accordance with the principle determined by GB/T 19,557.1. 5.2.5.2 Determination of Distinctness The variety to be tested should be clearly distinguished from all known varieties. In the test, when the variety to be tested has obvious and reproducible differences with the most similar variety in at least one character, it can be deter-

Fig. 5.1 Cluster analysis of 35 jute standard varieties (Zhang et al. 2020)

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DUS Test and DNA Fingerprinting Construction of Jute Varieties

71

Table 5.3 Example varieties and their characteristics’ descriptions in the test guidelines in jute (Zhang et al. 2020) Example varieties

Char. No. and DUS characteristics’ descriptions

Qiongyueqing

1 Ovate; 7 Absent; 8 Ovate; 10 Broadly acute

huangma179

1 Oblong; 2 Green; 4 Erect; 8 Lanceolate; 9 Erect; 10 Narrowly acute; 18 Round fruit; 20 Grey; 21 Medium; 24 Medium; 29 Medium

Hainanqiongshanyuanguo

1 Long oblong; 9 Descending; 22 Many

Zaoshengchi

2 Light red; 6 Red; 13 Red; 17 Medium; 29 High

Gunonghongpi

2 Red; 6 Purple Red; 30 High

Meifeng 1

3 Absent

Meifeng 2

3 Present; 5 Absent; 6 Green; 7 Small

Meifeng 4

4 Curve; 16 High; 17 High

Bachang 4

5 Present

Yunxiaohongpi

6 Light red; 11 Light red

Kuaizaohong

6 Dark Red; 11 Red; 28 Medium

Taiwanjialima

7 Large; 30 Medium

Kuanyechanguo

8 Oblong; 13 Green; 18 Long fruit; 20 Atrovirens

Yueyin 1

9 Horizontal

Taiwan 9

10 Gradually acute; 16 Medium

Japan 3

11 Green; 22 Medium

Japan 5

12 Early; 14 Early; 15 Early; 16 Short; 17 Short; 19 Inter-node; 21 Big; 22 Few; 25 Many; 33 Early

Guangdongduweima

12 Medium; 31 High

Yueyaun 5

12 Late; 14 Late; 15 Late; 23 Thick; 25 Medium; 26 Weight; 27 Weight; 28Weight; 33Late

Hongtiegu

14 Medium; 29 Low

Lianjianghuangma

15 Medium; 26 Medium

Guangbaai

16 Very short to short

Niushuatiao

19 Node; 26 Light; 27 Light; 28 Light

Yangjuchiyuanguo

21 Small

Taiwanqingpi

23 Thin

Xinxuan 1

23 Medium

Zijinhuangma

24 Thin

Xieyang 8

24 Thick; 27 Medium; 33 Medium

Guangfengchanguo

30 Low

Zhaoanqingpi

31 Low

Xinlonghuangma

31 Medium

Funong 1

32 Low

Funong 2

32 Medium

Funong 4

32 High

Char. No. Characteristics number, consistent with those in Table 5.1

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Q. He et al.

mined that the variety to be tested has distinctness.

5.2.5.3 Determination of Uniformity For C. capsularis varieties tested, a 1% overall standard and a probability of acceptance of at least 95% were used. When the sample size is one hundred, a maximum of three heteromorphic strains may be allowed. When the sample size is two hundred, a maximum of five heteromorphic strains may be allowed. For C. olitorius varieties tested, a 2% overall standard and a probability of acceptance of at least 95% were used. When the sample size is one hundred, a maximum of five heteromorphic strains may be allowed. When the sample size is two hundred, a maximum of ten heteromorphic strains may be allowed. 5.2.5.4 Determination of Stability A variety is considered stable if it has uniformity. Stability is not generally tested. If necessary, the seeds of the next generation of the variety can be planted, and the variety can be judged to be stable if there is no significant change in the trait expression compared with the previously provided propagating material.

5.3

DNA Fingerprinting Characterization

5.3.1 Establishment of Applied Core Germplasm Through the accurate identification of agronomic traits of application core germplasm, screening high fiber production (high stalk, stem, fresh skin thickness), good fiber quality (high cellulose content, low matrix content, high fiber strength, high fibrous ratio), anti-counterprobulent (antisalt, drought resistance, high germination rate, anti-seed aging), suitable for application, suitable for mechanization (lodging resistance) and other applications. According to characteristics, it can be divided into 16 groups (Table 5.4). A total of 61 varieties (lines) were obtained by excluding the same germplasm in different groups.

5.3.2 Screening of SSR Core Primers From the application core germplasm of 61 varieties, 12 were randomly selected as a template, and 46 pairs of SSR core primers were designed. After electrophoresis detection, the PCR amplification product was screened to obtain a set of primers having a high polymorphism and a clear strip (Table 5.5). 61 application core germplasms were amplified by SSR fluorescent labeling capillary electrophoresis technology. A total of 140 polymorphic sites were detected, and the alternate polymorphism information content (PIC) variation is 0.8223 * 0.9499.

5.3.3 Establishment of DNA Fingerprints by SSR Fluorescent-Labeled Capillary Electrophoresis Twelve pairs of core primers were used for SSR fluorescence labeling capillary electrophoresis, and the molecular weight data were read by 3730XL sequence analyzer. Figure 5.2 shows 19 characteristic bands detected by fluorescent capillary electrophoresis with primer CcID071 (FAM), and the corresponding fragment sizes are 104/113, 108/129, 112/128, 113, 113/117, 113/125, 113/126, and 113/128. Figure 5.3 shows four characteristic bands detected by fluorescent capillary electrophoresis with primer CcSSR024 (HEX), and the corresponding fragment sizes are 196, 197, 199, and 200 bp respectively. Table 5.6 shows the fluorescent group labeled at the 5’ end of each core primer, the total number of polymorphic bands, the size of polymorphic fragments, and the coding summary. DNA molecular identity was constructed using polymorphic fragments and coded information in capillary electrophoresis. The results of capillary electrophoresis were numerically and alpha-coded according to Table 5.6. 12 pairs of primers, including CCID071, COSR083, COSR146, COSR179, COSR049, CCSSR001, COSR119, COSR133, COSR136, CCSSR024,

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DUS Test and DNA Fingerprinting Construction of Jute Varieties

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Table 5.4 Applied core collection of jute (Guo et al. 2021) Group

Number

Origin

Name

Characteristics

1

1

Guangzhou, Guangdong

Guangdongduweima

Tall plant height

2

Longhai, Fujian, China

Gunonghongpi

Tall plant height

3

Fuzhou, Fujian, China

Meifeng4

Tall plant height

4

Fuzhou, Fujian, China

Fuhuangma2

Tall plant height

5

Zhangzhou, Fujian, China

Yueyinchangguo1

Tall plant height

6

Changsha, Hunan, China

Zhongchanghuang1

Tall plant height

7

Guizhou, China

Tianma

Tall plant height

8

Sanming, Fujian, China

Minma273

Large stem diameter

9

Fujian, China

Minma737

Large stem diameter

10

Changsha, Hunan, China

Zhonghuangma1

Large stem diameter

11

Fuzhou, Fujian, China

Funong4

Large stem diameter

2

3

4

5

6

12

Guizhou, China

Tianma

Large stem diameter

13

Yuanjiang, Hunan, China

Danhongpi10

Large fresh bark thickness

14

Fuzhou, Fujian, China

Fuhuangma2

Large fresh bark thickness

15

Changsha, Hunan, China

Zhonghuangma1

Large fresh bark thickness

16

Pakistan

Bachang4

Large fresh bark thickness

17

Luojiang, Sichuan, China

Yuanzima

Large Fresh bark weight per plant

18

Fuzhou, Fujian, China

Fuhuangma2

Large Fresh bark weight per plant

19

Changsha, Hunan, China

Zhonghuangma1

Large Fresh bark weight per plant

20

Mali

807yuanyinmali

Large Fresh bark weight per plant

21

Guangzhou, Guangdong, China

Guangdongduweima

High cellulose

22

Changsha, Hunan, China

D-154

High cellulose

23

Taiwan, China

Xinlonghuangma

High cellulose

24

Zhangzhou, Fujian, China

Yueyinchangguo1

High cellulose

25

Zhangzhou, Fujian, China

Funong1

High cellulose

26

Zhangzhou, Fujian, China

Funong4

High cellulose

27

Guangzhou, Guangdong, China

Guangdongduweima

Low lignin

28

Changsha, Hunan, China

D-154

Low lignin

29

Taiwan, China

Xinlonghuangma

Low lignin

30

Zhangzhou, Fujian, China

Yueyinchangguo1

Low lignin

31

Fuzhou, Fujian, China

Funong1

Low lignin

32

Fuzhou, Fujian, China

Funong4

Low lignin (continued)

74

Q. He et al.

Table 5.4 (continued) Group

Number

Origin

Name

Characteristics

7

33

Longhai, Fujian, China

Gunonghongpi

High fiber strength

34

Fujian, China

Minma737

High fiber strength

35

Zhangzhou, Fujian, China

Minma429

High fiber strength

36

Yuanjiang, Hunan, China

Kuanyechangguo

High fiber strength

37

India

Cuilv

High fiber strength

38

Taiwan, China

Zaoshengchi

High fiber fineness

39

Yuanjiang, Hunan, China

Qiongyueqing

High fiber fineness

40

Taiwan, China

Taiwan8

High fiber fineness

41

Taiwan, China

Taiwan9

High fiber fineness

42

Pakistan

Bama72-1

High fiber fineness

43

Kenya

SM/034

High fiber fineness

44

Pakistan

Bachang4

High fiber fineness

45

Changsha, Hunan, China

Zhonghuangma1

Disease-resistant

46

Taiwan, China

55 Tailu

Disease-resistant

47

Guangxi, China

Aidianyeshengzhong

Disease-resistant

48

Pakistan

Bama72-1

Disease-resistant

49

Yuanjiang, Hunan, China

Guangbaai

Disease-resistant

8

9

10

11

50

Kenya

SM/034

Disease-resistant

51

Zijin, Guangdong, China

Zijinhuangma

Salt resistance

52

Fuzhou, Fujian, China

Sanyuanjikou

Salt resistance

53

Nanjing, Fujian, China

Nanjingqingpi

Salt resistance

54

Changsha, Hunan, China

Weimo1

Salt resistance

55

Fuzhou, Fujian, China

Funong5

Salt resistance

56

Guizhou, China

Tianma

Salt resistance

57

Taiwan, China

Taiwan8

Drought resistance

58

Taiwan, China

55 Tailu

Drought resistance

59

Burma

Miandianyuanguo

Drought resistance

60

Yuanjiang, Hunan, China

Kuanyechangguo

Drought resistance

61

Fuzhou, Fujian, China

Funong3

Drought resistance

62

Guizhou, China

Tianma

Drought resistance

12

63

Nanan,Fujian, China

Hongtiegu

Lodging resistance

13

64

Fuzhou, Fujian, China

Funong4

Suitable growth period

65

Hainan, China

Hainanhuangma

Suitable growth period

66

Guangzhou, Guangdong, China

Guangdongduweima

Suitable growth period

67

Guangzhou, Guangdong, China

Yueyuan5

Suitable growth period

68

Yuanjiang, Hunan, China

Qiongyueqing

Suitable growth period

69

Changsha, Hunan, China

Xianghuangma3

Suitable growth period (continued)

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DUS Test and DNA Fingerprinting Construction of Jute Varieties

75

Table 5.4 (continued) Group

Number

Origin

Name

Characteristics

14

70

Fuzhou, Fujian, China

Minge9

High germination rate

71

Pucheng, Fujian, China

Puchenghuangma

High germination rate

72

Viet Nam

Yuenanyuanguo

High germination rate

73

Guangzhou, Guangdong, China

Yueyin1

High germination rate

74

Taiwan, China

Taiwan8

High germination rate

75

Henan, China

Henanyeshengyuanguo

High germination rate

76

Mali

807yuanyinmali

High germination rate

77

Guizhou, China

Tianma

High germination rate

78

Fuzhou, Fujian, China

Funong3

High germination rate

79

Guangzhou, Guangdong, China

Yueyuan2

Seed aging resistance

80

Shaowu, Fujian, China

Shaowuhuangma

Seed aging resistance

81

Minhou, Fujian, China

Minhoubaipi

Seed aging resistance

82

Japan

Ribenchangfenqingpi

Seed aging resistance

83

Qiongshan District, Haikou, Hainan, China

Hainanqiongshanyuanguo

Seed aging resistance

84

Guangdong, China

Zisuma

Seed aging resistance

85

Nanan, Fujian, China

Nananhaoma

Seed aging resistance

86

Wuzhou, Guangxi, China

Wuzhoulv

Seed aging resistance

87

Pakistan

Bama72-2

Seed aging resistance

15

16

88

China

Changguohongjing

Seed aging resistance

89

India

D154

Elite parent

90

Fuzhou, Fujian, China

Lubinyuanguo

Elite parent

91

Guangzhou, Guangdong, China

Yueyuan1

Elite parent

92

India

JRC-212

Elite parent

93

Bangladesh

Xuan46

Elite parent

94

Yuanjiang, Hunan, China

Guangfengchangguo

Elite parent

CCSSR015, and COEMS333, were used for permutation and combination construction of DNA molecular identity card. According to the above sequence, the corresponding coding combination of the 12 pairs of primers constituted the applied core germplasm DNA molecular identity, that is, the string DNA molecular identity. For example, Bachang4 (germplasm number: 16) DNA molecular ID code is I2457612J227. When compared with Table 5.6, the first letter I represents the amplified fragment of primer CCID071 in germplasm 16, ranking 18th in its polymorphic fragment gradient. The second digit 2 represents the

amplified fragment of primer COSSR083 in germplasm 16. It ranks second in its polymorphic fragment gradient, and the rest of the code are analogized. The DNA molecular ID card code is imported into the online barcode generator to generate the barcode DNA molecular ID card. The main descriptors and DNA molecular ID codes of the applied core germplasm were imported into the QR code generating software to generate the QR code DNA molecular ID card. Based on the three forms of string, barcode, and two-dimensional code, 61 DNA molecular identity cards of applied core germplasm were successfully constructed.

Forward Primer (5□□□3)

CTCTCAACCCAAAGCAAAAG

TGCAGGGCTGTTGTGGCTGC

CCACCAAGCAAGGTGAATGCCC

GGGAGAGAGAGAGAGAGAGAGAGAGAG

GGCACGAGGGAACATCAACCA

TGAAAGGAGCCGCCATAGATCTCC

ACCAAATCGGAAGCATCAAACAAACAG

GCCATTGCCTTCCCCTCCTCC

GGCGCGGACAATGGCAGGAT

GGGGATTACCGATGCCGCGA

GCTTTGTGATTGTTTCAAAGGTGGCT

TGCCGCGGCTTCATCTAGACC

Primer name

CcID071

CoSSR083

CoSSR146

CoSSR179

CoSSR049

CcSSR001

CoSSR119

CoSSR133

CoSSR136

CcSSR024

CcSSR015

CoEMS333

65.7

57.3

59

60.11

59.16

57.26

58.1

57.04

57.41

58.58

60.46

55.2

Forward annealing temperature

GGGAACGCCTTACGCTCCCT

AGGCATTAGGCCTTGTAGAGAAACCA

CACCACCCACCACCGCACAA

ACGCACGGCCTGTAAGAGCG

TGGATCCAAATCGTAGCATTCCCCT

TCTTGACAACACTGGTCCTCTGCAT

GGATCTTTCGAGCTCTGGAGTCTGC

AAAGGAGCCGCCATAGATCTCCA

ACAACACGTACCCCACCTTACGC

ACACTCTAGATACCTTGATGGGGCTC

TGGTGGTGGTGGGTTGAAATGTCC

CTGAAATGAAAAAAGCAACA

Reverse Primer (5□□□3)

66.2

57.78

59.76

59.77

57.8

58.11

58.95

57.36

59.15

57.23

59.28

51.6

Reverse annealing temperature

231– 345

193– 203

197– 200

262– 434

101– 222

470– 497

242– 249

194– 203

235– 290

201– 217

205– 360

102– 129

Product size (bp

Table 5.5 Information of 12 core pairs of SSR primes and their characteristic values of polymorphism (Guo et al. 2021)

(GT)13

(TTCT)3.3

14

5

4

19

(CAA)15.3 (GTG)5.3

9

15

8

7

16

7

17

19

Observed number of alleles (na)

(CAA)32.3

(GA)13

(AAAAG)3.4

(TCTTT)3

(AG)30

(TTC)7.7

(GA)6

G/GACAAAGCT

SSR repeat types

0.9339

0.8288

0.8223

0.9499

0.9008

0.9369

0.8888

0.876

0.9415

0.8694

0.9442

0.9496

Polymorphism information content (PIC)

76 Q. He et al.

5

DUS Test and DNA Fingerprinting Construction of Jute Varieties

Fig. 5.2 Features of the primer CcID071 detected with capillary (Guo et al. 2021)

77

78

Q. He et al.

Fig. 5.3. Features of the primer CcSSR024detected with capillary (Guo et al. 2021)

Table 5.6 Implication results of 12 pairs of core primers detected with capillary electrophoresis technique (Guo et al. 2021) Primers

Fluorescent group

Observed number of alleles (na)

The code of capillary electrophoresis polymorphism fragments (bp)

CcID071

FAM (blue)

19

104/113 (1), 108/129 (2), 112/128 (3), 113 (4), 113/117 (5), 113/125 (6), 113/126 (7), 113/128 (8), 113/129 (9), 114 (A), 114/126 (B), 114/129 (C), 116/125 (D), 117 (E), 119/126(F), 122 (G), 125 (H), 126 (I), 129 (J)

CoSSR083

FAM (blue)

17

204 (1), 205 (2), 205/228 (3), 205/230 (4), 205/233 (5), 205/234 (6), 206/229 (7), 206/231 (8), 206/233 (9), 206/235 (A), 206/236 (B), 207/231 (C), 207/234 (D), 207/236 (E),219/360 (F), 234/309 (G), 359(H)

CoSSR146

FAM (blue)

7

199/216 (1), 200 (2), 201 (3), 210 (4), 217 (5), 218 (6), 219 (7)

CoSSR179

FAM (blue)

16

234 (1), 234/236 (2), 234/238 (3), 234/242 (4), 235/237 (5), 235/239 (6), 236 (7), 238/240 (8), 246/253 (9), 250/286 (A), 253 (B), 253/286 (C), 253/287 (D), 253/288 (E), 286/289 (F), 287/290 (G)

CoSSR049

FAM (blue)

7

193 (1), 194 (2), 195 (3), 196 (4), 197 (5), 202 (6), 203 (7)

CcSSR001

FAM (blue)

8

240 (1), 241 (2), 242 (3), 243 (4), 248 (5), 249 (6), 252 (7), 255 (8)

CoSSR119

HEX (green)

15

470 (1), 470/477 (2), 470/494 (3), 471 (4), 474/495(5), 477 (6), 489 (7), 490 (8), 491 (9), 492 (A), 493 (B), 494 (C), 495 (D), 496 (E), 497 (F)

CoSSR133

HEX (green)

9

202/219 (1), 218 (2), 218/222 (3), 218/223 (4), 219 (5), 219/222 (6), 222 (7), 222/238 (8), 223 (9)

CoSSR136

HEX (green)

19

262 (1), 291/323 (2), 292/323 (3), 295 (4), 295/407 (5), 317/322 (6), 317/323 (7), 323 (8), 323/402 (9), 323/407 (A), 355 (B), 357 (C), 398 (D), 398/407 (E), 399/432 (F), 402/407 (G), 403/407 (H), 422/425 (I), 422/434 (J)

CcSSR024

HEX (green)

4

196 (1), 197 (2), 199 (3), 200 (4)

CcSSR015

HEX (green)

5

193 (1), 194 (2), 195 (3), 203 (4), 204 (5)

CoEMS333

HEX (green)

14

231/311 (1), 231/326 (2), 234/345 (3), 237/326 (4), 310/326 (5), 311/326 (6), 319 (7), 319/326 (8), 319/344 (9), 326 (A), 326/344 (B), 327/345 (C), 344 (D), 345 (E)

5

DUS Test and DNA Fingerprinting Construction of Jute Varieties

5.4

Conclusions and Prospects

The diversity evaluation of 33 morphological traits of 35 jute standard varieties for DUS test showed that the morphological traits of 35 standard cultivars in this chapter were rich in genetic diversity, which could serve as an example and correction for the description of standard varieties. These traits covered the whole growth period of jute and phenotypic traits in different parts including stem, leaf, fruit, etc. In the technical document TGP/7, the International Union for Plant Protection (UPOV) described the selection principles of standard varieties in plant DUS testing: easy to obtain, stable in character, representative of more types, representative of more characters, and representative of more regions. In short, the selection of standard varieties is required to be as small as possible and have as much diversity as possible for jute DUS test. In addition, simple repeat sequence (SSR) was used as a parameter for cluster analysis of 35 jute standard varieties. The Euclidean distance 0.75 is taken as a classification line, which can be divided into 9 categories. DNA molecular identity card is an effective approach to verify and distinguish different varieties, which has the characteristics of uniqueness and discriminability. The string, barcode, and two-dimensional code DNA molecular identity cards of applied core germplasm of 61 varieties constructed in this chapter are unique molecular identity cards of each variety (line), and their numbers are unique. Based on the string, a barcode DNA molecular identity card could be quickly recognized by electronic devices, but it could not store a large amount of effective information. The use of twodimensional code technology can be quickly identified by computers, mobile phones, and other electronic devices, greatly increasing the scope of its use. With the application of these techniques, the DNA molecular identity card constructed by us can play an important role in the identification and protection of jute applied core germplasm. It can also be used for the

79

improvement and intelligent management of jute germplasm bank, which lays an important technical foundation for the construction of standardized jute germplasm DNA molecular identity bank, which has a broad application prospect in the preservation and utilization of jute germplasm resources.

Reference:s Dai J, Li HY, Ding KM, DL Hong (2007) Current status and prospects on DUS testing technique system for new plant variety protection. Seed 26(9):4–7 Guo YC, Zhang LL, Chen SY, Qi JM, Fang PP, Tao A, Zhang LM, Zhang LW (2021) DNA molecular identity card construction of core accessions for jute application. Acta Agron Sin 47(1):80–93 UPOV (2014) Development of test guidelines. TGP/7, ed. International Union for the Protection of New Varieties of Plants,pp 1–79 Li X, Li X, Zhang S (2003) New plant variety protection and DUS Testing Technology. Sci Agric Sin 36 (11):1419–1422 Tian H, Wang F, Zhao J, Yi H, Wang L, Wang R, Yang Y, Song W (2015) Development of maizeSNP3072, a high-throughput compatible SNP array, for DNA fingerprinting identification of Chinese maize varieties. Mol Breed 35(6):136–146 UPOV (2002) General introduction to the examination of distinctness,uniformity and stability and the development of harmonizeddescriptions of new varieties of plants. TG/1/3, ed. InternationalUnion for the Protection of New Varieties of Plants, pp 1–26 Wang Y, Cui YH, Nan ZB, Wang W (2002) Character selection and standard variety determination in DUS test guide of new plant varieties. Pratacultural Sci 19 (2):3–6 Wang L, Cheng X, Wang S, Liu G, Liu Z, Cai Q (2013) Adaptability and variation of an applied core collection of Adzuki Bean (Vigna angularis) in China. Journal of Plant Genetic Resources, 14(5): 794–799 Yan GR, Wang W, Bai YT, Liu ZY, HT Ai (2014) Study on test guideline of distinctness, uniformity and stability of fig. North Garden 17:40–43 Zhang LW, Qi J, Tang H, Zhang LM, Zhang LL, Xu Y, Tao A, Fang P (2020) National standards of People's Republic of China-Ministry of Agricultural Notice (NT/T 3738-2020), Guidelines for the conduct of tests for distinctness, uniformity and stability-Jute (Corchorus capsularis, C. olitorius), Beijing: China Agriculture Press, 1–14

6

Jute Interspecific Hybrids: Development, Characterization and Utilization A. Anil Kumar, Hariom Kumar Sharma, R. T. Maruthi, Neetu Kumari, Basant Kumar Jha, and Shashi Bhushan Choudhary

Abstract

Considerable studies on creation of the interspecific hybrids in jute for improvement of fiber quality, flowering behavior, biotic and abiotic stress resistance/tolerance, nutritional and medicinal attributes, seed dormancy, etc. are reviewed in this paper. Reported spectrum of interspecific hybrids and segregating progenies, namely, OIJ-248 (C. olitorius L.) x WB1 (C. aestuans L.), JRO 2407 (C. olitorius L.) x WCIJ-141–2 (C. aestuans L.), JRO 2407 (C. olitorius L.) x WCIJ-150–1 (C. fascicularis Lam) on important agronomic, economic and industrially important traits inspired researchers to tap yet unutilized potential of the technique for advancement of the crop.

A. A. Kumar
R. T. Maruthi ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata, West Bengal 700121, India H. K. Sharma ICAR-Directorate of Rapeseed-Mustard Research, Sewar, Bharatpur, Rajsthan 321303, India N. Kumari
B. K. Jha Birsa Agricultural University, Kanke, Ranchi, Jharkhand 834006, India S. B. Choudhary (&) ICAR-National Bureau of Plant Genetic Resources, Regional Station Ranchi, Ranchi, Jharkhand 834003, India

6.1

Introduction

The genus Corchorus L. belongs to family Malvaceae (Whitlock et al. 2003) and naturalized mostly as annual herbs in tropical and subtropical regions of Africa, Asia, Australia and America. Several wild species are reported to have coevolved across diverse habitats in these regions. These wild species are potential source of fiber quality (Palve et al. 2004), resistance/tolerance to biotic and abiotic stresses (Palve et al. 2003, 2004, 2006; Sinha et al. 2006). Besides, young tender leaves of wild and cultivated species of the genus are valued for their nutritional (Edmond 1990; Kreb 2001; Zeghichi et al. 2003; Ndlovu and Afolayan 2008; Choudhary et al. 2013; Jaarsveld et al. 2014) and pharmaceutical properties (Adebayo-tayo and Adegoke 2008; Mensah et al. 2008; Adegoke and Adebayo-Tayo 2009; Oboh et al. 2009; Rajput and Rajput 2011; Kapoor et al. 2012). Interspecific hybridization in jute is as old as intra-specific hybridization, first attempted by Finlow in 1917 between the two cultivated species, namely, C. capsularis L. and C. olitorius L. without success. Later on several successful attempts were claimed to produce hybrids between the two cultivated species (Islam and Rashid 1961; Swaminathan et al. 1961a and b; Mia and Shaikh 1967). However, all those putative hybrids reported dominance of the female parent traits in F1 and F2 generations.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_6

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A. A. Kumar et al.

Initially interspecific hybridization primarily concentrated on crossing between two cultivated jute species to transfer traits like fine fiber, water logging tolerance and stem rot resistance. Other jute species which were extensively used in crossing program were C. trilocularis and C. aestuans with C. capsularis and C. olitorius (Islam and Sattar 1961; Faruqui 1962; Chaudhuri and Jabbar 1962; Haque and Islam 1970; Arangzeb and Khatun 1980; Arangzeb 1994; Maity et al. 2008). Chaudhuri and Jabbar (1962) attempted several interspecific crosses and reported that most of the traits were inherited from maternal parent and few from paternal parent and similar report in C. capsularis x C. triloculris hybrid was reported by Maity et al. (2008). Present scenario of plateaued jute fiber yield is mainly attributed to narrow genetic base of cultivars (Kar et al. 2009). Some parental lines are found common in development of most of the cultivars, perhaps for the want of pre-mature flowering resistance. Besides, lack of adequate genetic diversity in germplasm of cultivated species led to utilization of selected lines in breeding program . In this backdrop improvement of cultivated species by utilization of untapped genetic potential of wild species through wide hybridisation is of paramount importance.

6.2

Development of Interspecific Hybrids in Jute

For any successful crossing program understanding the reproductive biology is of paramount importance. In jute difference in anthesis timing and pollen viability have specific bearing on success of interspecific hybridization. In wild jute species wide variation for anthesis timing was observed; however, the two cultivated species have anthesis period between 8.30 and 9.30 AM although anthesis timing varies with

atmospheric temperature. Other factors which affect the crossing success are temperature, photoperiod, contrasting parents and expertise in crossing program. By following the above parameters successful interspecific crosses can be developed even with wild x wild crosses.

6.3

Evaluation of Interspecific Hybrids

Phenotypic and genotypic variation in a wide cross and its progeny decides the success of the cross and systematic evaluation results in identification of useful progeny. A cross between OIJ-248 (C. olitorius L.) x WCIN-402(C. aestuans L.) was developed and their F1 and subsequent generations were evaluated for different breeding traits. The F1 hybrid completely resembled its maternal parent except intermediate root traits. In segregating generations wide variations were recorded for seed dormancy (Fig. 6.1), fiber fineness (0.83 tex to 2.80 tex), fiber yield (2.71 to 18.94 g/plant) and pre-mature flowering resistance. Similarly, 400 F2 population derived from interspecific hybridization of JRO 2407 (C. olitorius L.)  WCIJ-141-2 (C. aestuans L.) were characterized for plant morphological traits that revealed transgressive segregation for exstipulate and non-abscission leaf. Further, intermediate fibre color (Fig. 6.2) were recorded in F2 population where parents, namely, JRO 2407 (C. olitorius L.) and WCIJ-141-2 (C. aestuans L.) had golden brown and creamish white fiber color, respectively (self-communication). Interspecific hybridization was attempted between JRO 2407 (C. olitorius L.) x WCIJ-1501 (C. fascicularis Lam) and the F1 hybrid resembled the maternal parent but in the F2 population segregation for ex-stipulate leaf and stem pigmentation was observed (Fig. 6.3).

6

Jute Interspecific Hybrids: Development, Characterization and Utilization

83

Fig. 6.1 Variation in C. olitorius L. x C. aestuans L. population for a seed dormancy b fiber yield c Pre-mature flowering resistance

6.4

Trait-Specific Variations in Jute Interspecific Populations

6.4.1 Biotic Stress Resistance 6.4.1.1 Stem Rot Resistance Stem rot is a major disease in both the cultivated jute species. Among the cultivated species stem rot resistance was only reported in white jute, moderate resistance in tossa jute and problems associated with cross species incompatibility led to identification of new resistant sources in wild Corchorus species. Continuous evaluation for many years under sick plot conditions resulted in identification of stable stem rot resistance sources in C. aestuans L. (WCIN-136-1, WCIN-183A)

and C. fascicularis (WCIJ-150-1 and WCIJ-28) lines (ICAR-CRIJAF Annual report 2018 and 2019). Among these lines, WCIN-136-1 (INGR21036) was registered with ICARNational Bureau of Plant Genetic Resources (ICAR-NBPGR), New Delhi and was used to introgress stem rot resistance to cultivated tossa jute background. An interspecific population was developed by crossing OIJ-248 (stem rot susceptible) with WCIN-136-1 (stem rot resistant). The F1 hybrid resembled the maternal parent for agronomic traits but inherited red pigmentation from the wild parent. In the F2 population clear segregation pattern was observed for stem pigmentation and stem rot resistance. Screening of 217 F2 plants for stem rot resulted in 42 F2 plants as resistant and 175 F2 plants as susceptible

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Fig. 6.2 Fibre color variation in F2 plants and parents

Fig. 6.3 Variation in leaf morphology and pigmentation in parents and F2 plant

(Fig. 6.4) and chi square analysis indicated stem rot resistance is governed by a single recessive gene. Genotyping of these F2 plants with parental polymorphic SSR markers indicated introgression of genomic regions from wild C. aestuans parent (Fig. 6.5). In F4 and F5 generations of

these population, fifteen recombinant inbred lines (RILs) were showing stable resistance with 0% PDI and zero AUDPC values under sick plot conditions, and among these RILs a few lines recorded high fiber yield per plant (ICARCRIJAF Annual report_2020 2020).

6

Jute Interspecific Hybrids: Development, Characterization and Utilization

85

Fig. 6.4 Resistant and susceptible F2 plants in WCIN-136-1 derived population Fig. 6.5 Genotyping of resistant and susceptible F2 plants with marker MJM 519

6.4.1.2 Bihar Hairy Caterpillar Resistance Bihar hairy caterpillar (BHC) Spilosoma oblique is one of the major insect pests in jute, though the occurrence is sporadic but yield losses are reported up to be 10% and in severe conditions up to 30% (Bandyopadhyay et al. 2014). Quest for BHC resistance in cultivated jute germplasm has limited success in C. olitorius germplasm lines (ICAR-CRIJAF Annual Fig. 6.6 Percent pupation 100.00 and adult emergence of RILs 80.00 and parents 60.00 40.00 20.00 0.00

report_2019) but high level of resistance was identified in C. aestuans L. germplasm lines (WCIN-179, WCIN-136-1 and WCIN-183A) with 100% larval mortality. Introgression of BHC resistance into cultivated tossa jute background has been initiated from WCIN-136-1 and a few RILs (RIL 25, RIL 46 and RIL 74) were showing resistance to BHC (Fig. 6.6) based on percent pupation (ICAR-CRIJAF Annual report_2019).

% pupation % adult emergance

86

A. A. Kumar et al.

6.4.2 Pre-mature Flowering Tolerance Pre-mature flowering tolerance is the terminology used to represent short-day flowering tolerance which makes the jute crop suitable for multiple cropping system by sowing in the first week of March in jute growing areas. Among two cultivated species, tossa jute is found more sensitive to short-day photoperiod than white jute. As a result, introgression of pre-mature flowering tolerance in tossa jute remained principal objective of breeding program since last half decade. Only few exotic accessions of the species like Tanginyaka-02 (OEX-02) and Sudan Green (OEX-31) found potential source for this trait. Hence, their repeated utilization across breeding program led to narrow genetic base of tossa jute cultivar. To address this problem and to identify novel pre-mature flowering tolerance few interspecific populations were screened under short-day conditions. An interspecific population of OIJ-248 and WCIN-402 was screened for premature flowering tolerance in 2016 under short-day conditions (Day length 11.47 h) and selected tolerant lines were again screened in 2018 and 2020 resulting in identification of seven stable pre-mature flowering tolerant lines. One of these genetic stocks is JROBA-03, first identified for its pre-mature flowering tolerance in 2016 in F5 generation and in 2017 it was submitted to All India Network Project on Jute and Allied Fibres

coordinated trials. Similarly RS-06 is another elite line derived from an interspecific hybridization and expressing the same trait during trial (ICAR-CRIJAF Annual report 2017).

6.4.3 Herbicide Tolerance Herbicide tolerance is one of the major targeted traits in jute as weeding only contributes to 30% to total intercultural operating costs. So, targeting for this trait will drastically increase the profitability of jute farmers. Though major work in wild jute for herbicide resistance was not carried out but preliminary work done at ICAR-CRIJAF indicates that wild jute germplasm has enough variability to introgress into cultivated background. In this backdrop wild and cultivated jute accessions along with interspecific population (n = 200) were screened against different concentrations of Imazathapyr and Ethoxysulfuron. Among them, differential jute genotypic responses were recorded against Imazathapyr only. Therefore, evaluation for herbicide tolerance against Imazathapyr continued. Based on agronomic traits like visual necrosis symptoms and total carotenoid contents, wild jute germplasm, namely, WCIN-402 was showing tolerance to Imazathapyr. WCIN-402 derived interspecific population, namely, RIL-H39 and RIL-H46 showing increased carotenoid content and very less reduction in plant height (Figs. 6.7 and 6.8) after the herbicide spray. The finding indicates

Fig. 6.7 Differential 6 carotenoid profile in leaves of cultivated, wild and recombinant lines, four weeks 5 after spraying different concentration of Imazathapyr 4 Control 3

50 % RD 100 % RD

2 1 0 OIJ-248

WCIN-402 RIL-H10

RIL-H32

RIL-H39

RIL-H46

6

Jute Interspecific Hybrids: Development, Characterization and Utilization

Fig. 6.8 Differential plant height of cultivated, wild and recombinant lines, four weeks after spraying different concentration of Imazathapyr

87

160 140 120 100 80

Control

60

50% RD

40

100% RD

20 0

introgression of herbicide tolerance from wild parent to interspecific hybridization population (Unpublished data).

6.5

Way Forward

Although, interspecific hybridization in jute is still at nascent stage but holds promise to address the emerging challenges for diversified industrial applications and farming profitability. Its importance is further accentuated with changing biotic and abiotic stress dynamics in jute-based farming areas across regions. These factors have collectively redrawn focus on research in the area since the last two decades. In days to come its benefits will enrich jute sector in more than one way.

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Bandyopadhyay S, Gotyal BS, Satpathy S, Selvaraj K, Tripathi AN, Ali N (2014) Synergistc effect of azadirachtn and Bacillus thuringiensis against Bihairy caterpillar, Spilarcta obliqua Walker. Biopestcides Int 10:71–76 Chaudhuri SD, Mia J (1962) Species crosses in genus Ccorchorus. Euphytica 11:61–64 Choudhary SB, Sharma HK, Karmakar PG, Kumar AA, Saha AR, Hazra P, Mahapatra BS (2013) Nutritional profile of cultivated and wild jute (Corchorus) species. Aust J Crop Sci 7:1973–1982 Edmond JM (1990) Herbarium survey of African Corchorus species. Systematic and ecogeographic studies on crop genepools 4. International Board for Plant Genetic Resources, Rome Faruqui S (1962) Interspecific hybridization between C. olitorius and C. walcotti F.V.M. and C. trilocularis C. capsularis. M.Sc. Thesis, Sind University, Pakistan, 105 p Finlow RS (1917) Historical notes on experiments with jute in Bengal. Agric J India 12:3–29 Haque M, Islam AS (1970) Some promising material among F4 and back-cross derivatives of the natural hybrid C. aestuans  C. olitorius. Sindh Univ Res J (Sci Ser) 4:97–107 Islam AS, Sattar MA (1961) Inter-specific hybridization in the genus Corchorus: C. aestuans C. capsularis. In: Proceeding XIII Pakistan science conference, Dacca, Pakistan, 11 January 1961.Dacca, pp 6–7 Islam AS, Rashid A (1961) First successful hybrid between the two jute yielding species C. olitoriusx C. capsularis. Nature 185:258–260 Jaarsveld PV, Faber M, Heerden IV, Wenhold F, Rensburg WJV, Averbeke WV (2014) Nutrient content of eight African leafy vegetables and their potential contribution to dietary reference intakes. J Food Compos Anal 33:77–84 Kapoor BBS, Acharya S, Mishra R (2012) Antimicrobial screening of some medicinal plants of the Rajasthan desert. In: 3rd international conference on biology, environment and chemistry, vol 46. IPCBEE, IACSIT Press, Singapore, p 23

88 Kar CS, Kundu A, Sarkar D, Sinha MK, Mahaptra BS (2009) Genetic diversity in jute (Corchorus spp.) and its utilization: a review. Indian J Agric Sci 79(8):575– 586 Kreb G (2001) Tiliaceae. In: Hanelt P (ed) Institute of plant genetics and crop plant research. Mansfield’s encyclopaedia of agricultural and horticultural crops, vol 3. Springer, Berlin, pp 1560–1567 Maity S, Kumar A, Datta AK (2008) Cytomorphological studies in F1 hybrids (Corchorus capsularis L. X Corchorus trilocularis L.) of Jute (Tiliaceae). Comp Cytogenet 2(2):143–149 Mensah JK, Okoli RI, Ohaju-Obodo JO, Eifediyi K (2008) Phytochemical, nutritional and medical properties of some leafy vegetables consumed by Edo people of Nigeria. Afr J Biotechnol 7:2304–2309 Mia MM, Shaikh AQ (1967) Gamma radiation and interspecific hybridisation in jute (Corchorus capsularis L. and C. olitorius L.) Euphytica 16:61–68 Ndlovu J, Afolayan AJ (2008) Nutritional analysis of the South African wild vegetable Corchorus olitorius L. Asian J Plant Sci 7:615–618 Oboh G, Raddatz H, Henle T (2009) Characterization of the antioxidant properties of hydrophilic and lipophilic extracts of Jute (Corchorus olitorius) leaf. Intl J Food Sci Nutr 60:124–134 Palve SM, Sinha MK, Mandal RK (2003) Preliminary evaluation of wild species of jute (Corchorus spp.). Plant Genet Resour Newsl 134:10–12 Palve SM, Sinha MK, Mandal RK (2004) Source of stem rotMacrophomina phaseolina (Tassi) Goid.

A. A. Kumar et al. Resistance in wild species of jute. Trop Agric (trinidad) 81:23–27 Palve SM, Sinha MK, Mandal RK (2006) Evaluation of wild species of jute (Corchorus spp.) for fibre yield and resistance to stem rot [Macrophomina phaseolina (Tassi) Goid.] and stem weevil (Apion corchori Marshall). Indian J Genet Plant Breed 66(2):153–154 Rajput AP, Rajput TA (2011) Antibacterial and antifungal activity from leaves extracts of Corchorus fasciculris Lam. Intl J Pharm Tech Res 3:2195–2198 Sinha MK, Mandal RK, Palve SM (2006) Preliminary evaluation of wild species of jute (Corchorus species). PGR Newsl FAO-Bioversity 134:10–12 Swaminathan MS, Iyer RD (1961a) Skewed recombination in a rare interspecific jute hybrid. Nature 192:893–894 Swaminathan MS, Iyer RD, Sulbha K (1961b) Morphology, cytology and breeding behaviour of hybrids between Corchorus olitorius and C. capsularis. Curr Sci 30:67–68 Whitlock BA, Karol KG, Alverson WS (2003) Chloroplast DNA sequences confirm the placement of Oceanopapaver within Corchorus (Grewioideae: (Malvaceaes.l., formerly Tiliaceae). Genome Biol Evol 164:35–41 Zeghichi S, Kallithraka S, Simopoulos AP (2003) Nutritional composition of molokhia (Corchorus olitorius) and stamnagathi (Cichorium spinosum). World Rev Nutr Diet 91:1–21

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Classical Genetics, Cytogenetics and Traditional Breeding in Jute Jiban Mitra and Chandan Sourav Kar

Abstract

The genus Corchorus includes over 170 species out of which two cultivated species, namely, C. olitorius and C. capsularis, are of great global economic importance for bast fiber. This chapter critically reviews genetics— both Mendelian and quantitative of important fiber-related traits, cytogenetic aspects including karyotype, chromosome evolution, heteroploidy, and conventional breeding for varietal development in jute to collage and enrich the wealth of information in a holistic way to be useful for future research programs for genetic improvement in jute. Future strategies for successful hybridization between cultivated and wild species and subsequently generation of pre-breeding material to enhance genetic variability, broadening the genetic base through involvement of more diverse parents in crosses in form of diallel selective mating system or multi-parent advanced generation inter-cross population, insights into genetics of premature flowering, pectin and their genetic improvement in desired direction, use of cytogenetic tools, exploitation of heterosis have been suggested.

J. Mitra (&)
C. S. Kar Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, India

7.1

Introduction

Jute (Corchorus spp.) is one of the most important sources of natural fiber, covering around 80% of global bast fiber production (http://www. fao.org/faostat). Only two species, namely, Corchorus olitorius (locally known as tossa jute) and C. capsularis (locally known as white jute) are commercially cultivated in Asia particularly in India and Bangladesh for fiber (Kundu 1956), and to some extent as mucilaginous nutritious leafy vegetable in Africa (Nath and Denton 1980; Shanhua et al. 2010) though more than 170 species in the Malvaceae (more accurately Sparrmanniaceae) family as per Index Kewensis are distributed in the tropics, subtropics and warm temperate regions of the world (Wild 1984; Edmonds 1990; Heywood 1993), with most of the species diversity being concentrated in Africa. Africa accounts for the majority (30– 40) of world Corchorus species. Out of these, 15 are reported in South Africa, 13 in Tanzania and 12 in Ethiopia (Edmonds 1990). Thus, most of the species are distributed in the eastern to southern parts of the continent. In view of prevalence of species diversity and moreover, occurrence of C. olitorius in both wild and domesticated form (Oliver 1863), Africa is appropriately considered as the centre of origin of C. olitorius (Kundu 1951). On other hand Indo–Myanmar including South China has been considered as the origin of C. capsularis due to

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_7

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omnipresence of this species in this region. On the contrary, Kundu et al. (2013) opined the possibility of African origin of both species. The jute producing countries are largely concentrated in Asia, with two major producing countries, India and Bangladesh, accounting for about 98% of world output. Furthermore, India is the largest producer accounting for 55.5% of world jute fiber production (3.38 million tons in 2019) followed by Bangladesh with a share of 42.5% and China is the distant third sharing only 0.9% of global production (http://www.fao.org/ faostat). Most of the programs of varietal development in jute have been accomplished since the beginning in government organizations in these countries, namely, Central Research Institute for Jute and Allied Fibres under Indian Council of Agricultural Research (ICAR) and State Agricultural University in India, Bangladesh Jute Research Institute in Bangladesh and Institute of Bast Fiber Crops under Chinese Academy of Agricultural Science and Fujian Agriculture and Forestry University in China, with an achievement of continuous development of improved varieties for the long time as per changing needs. At the same time a better understanding on genetic, cytogenetic and breeding aspects of jute has been gained with open-ended opportunities of its further enrichment.

7.2

Floral Biology and Mating System

The jute flower is perfect and small in size. The inflorescences occur on the terminal and lateral branches in groups of two or three in olitorius and groups of two to six in capsularis. The flowers in both species are small, olitorius being slightly bigger (9–10 mm in length) than capsularis (4–5 mm) having usually five green sepals and yellow petals with variation of six or more in olitorius. Stamens are variable in number being 20–30 in capsularis and 30–60 in olitorius

and bearing oblong anthers with yellow or paleyellow pollen. Stigma having 2–3 lobes is pubescent in capsularis; globular and entirely pubescent in olitorius. Style is variable in length (2– 4 mm in capsularis and 5–6 mm in olitorius). The ovary usually being syncarpous and pentalocular with five carpels is round in capsularis and elongated and sometimes with 6 or more carpels in olitorius. In capsularis, there are two rows of ovules in a locule, each row usually consisting of five ovules making a total of 50 ovules per ovary, whereas in olitorius there is a single row of about 40 ovules making around 200 ovules per ovary. Anthesis occurs 1–2 h after sunrise in capsularis, half an hour to one hour before sunrise in olitorius, whereas flower closes at 3:30 PM and at 1:30 PM, respectively. The highest stigma receptivity of olitorius remains at 7–8 AM. However, in case of low temperature (below 20 ° C) it delays by 1–2 h. In case of capsularis receptivity extends to 10–11 AM (Ghose and Dasgupta 1945). For artificial crossing, emasculation is done in the afternoon preferably between 3 and 5 PM in a mature bud with pale yellow anthers without removal of sepals and petals (as seed set is very sensitive to their removal) and pollination in the next morning between 7 and 8 AM which may extend to 11 AM for capsularis as per timing of peak stigma receptivity (Ghose and Patel 1945). The phenomenon of fertilization in both the cultivated species (C. capsularis and C. olitorius) has been investigated by Banerji (1932b) who stated that syngamy appears to be normal and completes within 6 h of pollination where triple fusion occurs within 10 h after pollination. Second male (sperm) nucleus either remains associated with polar nuclei or fuses with one or both of them. Sometimes polar nuclei fuse first and then fusion nuclei fuse with second sperm nucleus. Successful double fertilization results in initiation of development of fruit within 48 h after pollination which matures as pod/ capsule after

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40–45 days. In capsularis, pods are round with diameter of 10–15 mm, muricate, wrinkled, rarely smooth, 5-locular; each locule bears 8–10 seeds in two rows without transverse partitioning making total of 40–50 seeds per pod. In olitorius capsules are elongated, 6–10 cm long, 3–8 mm in diameter, ridged lengthwise, 5–6-locular; having 25–40 seeds in single row in each locule, with transverse partitions between each seed making total of 140–200 seeds per capsule. The autogamous (self-pollination) nature of pollination in jute (both C. olitorius and C. capsularis) was reported in 1906 by Burkill (Burkill 1906) through detailed field study during 1902 as has been elaborated in his article as “In 1902, I visited the Bardwan Experimental Farm on… There I first studied the mechanism of flower; and… The flowers of Corchorus capsularis open about 7:30 AM and close in a clumsy fashion in the evening of the same day; I mean that they half close; and after midnight they cease to be shapely. By the dawn of the next day the petals are falling off. The anthers dehisce as the flowers open. They and stigmas lie exactly at the same level. Self-fertilization is insured in the absence of insect visitors…” Being predominately self-pollinated crop, jute also experiences cross-pollination to some extent (Finlow and Burkill 1912; Howard et al. 1919). Crosspollination of 10–15% occurs in olitorius, mainly by insects (Ray 1960) whereas, extent of cross-pollination in capsularis is negligible (up to 5%) (Dutt and Ghose 1962). Comparatively higher percent of natural crossing in olitorius is attributed to larger flower size and longer duration of flower-opening (Basak and Chaudhuri 1966). Mating system being an important factor in determining the amount and nature of genetic variability in populations and ultimately genetic structure and evolutionary potential of jute was quantitatively studied by Basak and Gupta (1972). More than 100,000 individuals of C. olitorius were scored for selfing versus outcrossing in various populations, at several locations, over a number of years and seasons with different four marker loci—red versus green anthocyanin pigment (AD/ao), nonshiny versus

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shiny seed-coat (Sh/sh), normal versus crumple leaf (Cr/cr) and lanceolate versus palmate leaf shape (Pl/pl). The frequency of outcrossing was extremely variable among loci, crosses and samples within a single locus and also with years, locations and seasons within years. Outcrossing, in general, was non-random also being independent of flowering dates. However, outcrossing frequency estimated pooling over all the observations over years, locations and seasons was found to be 0.1512 and it suggests that jute populations do not follow model of complete selfing (genetic assortative mating) nor random mating. Rather, the mating system of jute is partial inbreeding, i.e. a mixed system of selffertilization in majority and random mating to some extent and thus, the genetic structure of natural population of jute is heterogeneous with homozygous and heterozygous individuals.

7.3

Genetics

Till the establishment of the Jute Agricultural Research Laboratories under the Indian Central Jute Committee (ICJC) at Dhaka in 1939, the genetics of the jute crop was an unexplored field except for a paper by Finlow and Burkill (1912). With the setting up of the Jute Agricultural Research Laboratories there and its transfer to India (as Jute Agricultural Research Institute and renamed as Central Research Institute for Jute and Allied Fibres) intensive genetic investigations were initiated and a series of studies on genetics of different morphological, fiber-related quantitative traits have been carried out particularly in terms of mode of inheritance pattern, genetic effect.

7.3.1 Mendelian Inheritance of Important Morphological Traits Inheritance pattern of a number of morphological and fiber-related traits have been studied and a brief description is given below. Secondary phloem fiber: The gene controlling the formation of secondary phloem fiber (bast) is

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different from that controlling primary phloem or protophloem tissues. One X-ray induced mutant, “Undulating stem” from capsularis variety JRC 212 produces only primary phloic fiber without biogenesis of the secondary fiber. The study of F1, F2 and backcross of the mutant and JRC 212 has established that fibrous–nonfibrous stem (allelic variant of secondary phloem fiber biogenesis) is under simple monogenic control. Since it is the usual practice to term secondary phloem fiber as bast fiber, the gene symbols are “Bf” (bast fiber) for fiber-containing and “bf” for nonfibrous stem (Mitra 1994). Anthocyanin pigmentation: As early as in 1907, Burkill and Finlow recognized four patterns of color variation in capsularis: (a) red stem, red petioles, red fruits, bright yellow flowers; (b) green stem, rosy petioles, rosy fruits, red on the outside of flower buds, bright yellow flowers; (c) green stem, green petioles, green fruits, no red on the outside of flower buds, bright yellow flowers; (d) green stem, green petioles, green fruits, no red on the outside of flower buds, pale yellow flowers (Burkill and Finlow 1907). Constancy of these combinations with some patterns showing intermediate shades of pigment inspired them for inheritance study. And subsequently, they worked out the inheritance of pigment and reported a single gene governing stem color (red vs. green), red being dominant in C. capsularis (Finlow and Burkill 1912). Patel and Ghose (1940) and Das Gupta (1944) examined their data and found that more than one gene is involved in the production of red pigmentation. The differences in the patterns of anthocyanin pigmentation in the cultivated varieties of Corchorus are very helpful in varietal identification. Further work has shown that in C. capsularis the anthocyanin pigmentation ranging in intensity from pure green to dark-red is controlled by three genes: C—Chromogen gene, fundamental for the production of pigmentation (C—pigmented; c—green); A— Pigment-producing gene, with no visible effect on the plant body without presence of dominant chromogen gene C; (present in multiple alleles AR (red), AL (light red), A (coppery red), a (no color)); R—Pigment-reducing gene, the effect of

J. Mitra and C. S. Kar

which is most marked on the stem (R: reduction; r: no reduction). The pigmentation patterns fall into three groups: (a) full-green with combinations of different alleles of A with R-r but with recessive chromogen gene c; (b) greenpigmented types with different alleles of A with dominant C and R; and (c) red group with the allele of A with dominant C and recessive r (Patel et al. 1944; Ghose et al. 1947). Das Gupta and Sarma (1954) pointed that another allele AD for the chromogen gene C is present which causes greater intensity of pigmentation. Anthocyanin pigmentation in C. olitorius is controlled by a single gene with three alleles AD, AR, a (deep red-red-green). Thus the green type in C. olitorius is due to a recessive anthocyanin allele, whereas in C. capsularis recessive chromogen gene is responsible, and any particular green type is dependent on the anthocyanin multiple allele (Patel et al. 1944; Ghose et al. 1947). Pod-shape: From the F1 and F2 generation of cross between Deodhali (oval pod) and D 154 (round), pod shape of capsularis was found to be monogenic in nature where round is dominant. The gene for pod shape is linked with the gene for anthocyanin pigmentation, C, with eight per cent crossing-over (Ghose 1942). Branching habit: Branching habit in capsularis is controlled by a single gene, Br–br (branched-non-branched). All Indian capsularis types are branched, while the recessive gene, br, occurs only in some foreign capsularis types (Patel et al. 1945). Stipule character: In some foreign capsularis types, like Halmahera, the stipule is foliaceous, in marked contrast with the stipules in Indian capsularis. The character is controlled by a single gene-pair, Sfl/sfl. Bitter taste: Monogenic inheritance of bitter taste in C. capsularis, Tb–tb (bitter-nonbitter), has been established. The gene is linked with Br, gene for branching, with 22.2% crossing-over; there is no evidence of linkage with the anthocyanin genes (Ghose et al. 1948). Undulate leaf: F1 of a cross between undulate and normal flat leaf type results in intermediate and F2 segregates in a monogenic ratio, the

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Classical Genetics, Cytogenetics and Traditional Breeding in Jute

undulate type being dominant (undulate-W, normal-w) (Das Gupta and Ghosh 1954). Corolla color: Corolla color in capsularis jute is either yellow or pale yellow and is controlled by a single factor pair, Pp–py (yellow-pale). In Indian olitorius no pale-yellow types have been found, but in a foreign variety, light-yellow corolla and light-yellow anther are noticed, and the gene pair is designated Py/py (yellow vs. light yellow). The corolla color gene is not linked with any of the anthocyanin genes (Patel et al. 1945). Anther color: Monogenic inheritance has been established for anther color in C. capsularis. The light-yellow anther color is recessive to yellow anther and is completely linked with pale-yellow petal (Ghose et al. 1948). Seed-coat color: The seed of cultivated olitorius is leek green, while in wild olitorius the seed is dull black. Inheritance of seed-coat color is controlled by a single gene, Gr/gr (dull vs. leek green). Other traits: In C. olitorius crumpled/normal leaf and nonshiny/shiny seed coat are monogenically controlled, whereas glossy/nonglossy leaf and flat/rolled leaf are governed by two pairs of complementary genes, nonfuzzy/fuzzy seed coat by duplicate genes, and seed coat color (black, green and chocolate) and leaf size (narrow, intermediate and broad) show modified trigenic ratios (27: 21:16 and 36:15:13, respectively). In C. capsularis pale green/deep green leaf, shallow serrated/deep serrated leaf and nonfasciated/fasciated stem are found to be inherited monogenically. Fasciation of stem and branching in C. capsularis are linked (Basak et al. 1971).

7.3.2 Quantitative Genetics of FiberRelated Traits Fiber yield being polygenic quantitative trait reflects genotype x environment interaction to a greater extent in its phenotypic expression; and moreover, seed and fiber could not be harvested from the same plant in jute. Thus, unravelling this complex trait with componental traits, as genetic architecture of fiber yield is directly and multiply

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determined by fiber yield related traits (such as plant height, basal diameter), is appropriate for analysis of genetic basis of fiber yield in terms of genetic components of variance and resultant genetic effect. A number of studies on this aspect in fiber yield and its components both in capsularis and olitorius jute have been reported. Most interestingly, all possible mode of genetic effects —additive and nonadditive (dominance, epistatic) are found to be prevalent in governing single trait like plant height [additive by Singh (1973, 1974, 1975); nonadditive by Kumar (1987), Kumar and Palve (1995), Saha et al. (1996) dominance by Singh (1975); both additive and nonadditive by Roy et al. (2020)], basal diameter [additive by Ghosh et al. (1979), Palve and Kumar (1994), Sengupta et al. (2005); dominance by Singh (1975), nonadditive by Kumar and Palve (1995)], fiber percentage [additive by Kumar and Palve (1995), nonadditive by Kumar (1987), both additive and nonadditive by Sengupta et al. (2005)], fiber fineness [both additive and nonadditive by Chaudhury et al. (1998), Chattopadhyay and Chaudhuruy (2002)] and fiber strength [additive by Saha et al. (1983), both additive and nonadditive by Palve and Kumar (1991), Chaudhury (1987)]. The genetic component of variance or gene effect for a character depends on type of population studied, the mating design (diallel, line  tester, polycross, North Carolina designs) followed for deriving the population, and thus, no conclusive insight to genetic basis, in general, for a trait could be provided for use in breeding program. Rather quantitative trait locus (QTL) analysis approach through associating molecular marker with phenotypic variation of a candidate quantitative trait provides foundation of marker-assisted selection (MAS) in breeding improved crop variety more effectively. However, first QTLs in olitorius jute for different fiber yield related traits and fiber quality using RIL population of a cross JRO 524 (high yielder, coarse fiber) and PPO 4 (fine fiber) and linkage map of simple sequence repeat (SSR) markers (developed by Das et al. (2012a)) were detected by Das et al. (2012b). Later, QTLs for bast fiber quality yield related traits (Topdar et al. 2013),

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for root weight, basal diameter using linkage map of restriction site-associated DNA (RAD) markers (Kundu et al. 2015), for plant height using linkage map of specific locus amplified fragment sequencing (SLAF-seq) markers (Tao et al. 2017), for salt tolerance using genetic map of single nucleotide polymorphism (SNP) markers (Yang et al. 2019) have been identified.

7.4

Cytogenetics

The chromosome number (2n = 2x = 14) of different Corchorus species, namely, C. capsularis and C. olitorius and C. acutangulus was determined as early as in 1932 (Banerji 1932a) and subsequently Nakajima (1936) confirmed it in C. capsularis. Rao and Datta (1953) reported C. siliquosus as natural tetraploid (n = 14) with normal meiosis in pollen mother cell showing 14 bivalents in metaphase I. Seven haploid chromosomes in C. fascicularis, C. trilocularis and C. tridens have also been detected (Datta 1953; Rao and Datta 1953). The 2C DNA content in C. capsularis (cv. D 154), C. olitorius (cv. O 4) and their F1 hybrid was first estimated to be 2.3, 2.8 and 3.1 pg, respectively (Samad et al. 1992b). Based on this genome size (1C DNA amount) was also estimated to be 1100 and 1350 Mb for C. capsularis and C. olitorius, respectively (Mir et al. 2009). Later nuclear DNA content (2C values) being 0.502–0.695 pg for C. capsularis, and 0.643– 0.718 pg for C. olitorius and haploid genome (1C) sizes of *280 and *324 Mb of C. capsularis and C. olitorius, respectively, was accurately estimated by Sarkar et al. (2011) through flow cytometric analysis. C. fascicularis was reported to have the smallest haploid genome (*188 Mb) followed by C. aestuans (*194 Mb). On an average, genome sizes (1C values) are about one-fourth of their corresponding earlier-reported estimates. JRC 212 variety of capsularis has the smallest genome (*246 Mb) among the cultivated species. Normal seven bivalent formations at metaphase I along with normal disjunction at anaphase I is observed in both species of jute being

diploid (Bhaduri and Chakraborty 1948) but a degree of meiotic abnormality with hypo- and hyper-ploidy cell was first reported in olitorius (Datta 1952) and later in C. fascicularis with occurrence of pollen mother cell with 14 bivalents along with those bearing the normal seven (Rao and Datta 1953). This abnormality also observed under investigation in other species of Corchorus appears to be the characteristic of the genus Corchorus. From comparative embryological studies of in vitro and in vivo in C. olitorius (var. Chinsurah Green) for the first time (Banerji 1932b), the pollen grains, when released from the microsporangium, are observed to be oval and become round in shape on absorbing moisture rapidly. They germinate in a saturated atmosphere and produce pollen tubes. He observed only monosiphonous grains without any branching in pollen tubes. The pollen grain being uninucleate in the immature stage become binucleate (generative and tube nucleus) at the shedding condition where the generative nucleus follows the tube (vegetative) nucleus and the generative nucleus mitotically divides into two sperm nuclei within pollen tube (Banerji 1933). Polysiphonous pollen grains (more than one pollen tube emitting from a pollen grain) and resultant branched pollen tubes with circulatory movement of cytoplasm are observed for the first time by Datta (1955). The generative nucleus usually follows the tube nucleus but the reverse cases are also observed. Two viable pollen tubes are also noted in a polysiphonous condition of the jute pollen.

7.4.1 Karyotype Analysis Karyotype studies in jute species due to small sizes of chromosomes and presence of lignin in cell wall creating some difficulties in the hydrolysis of materials and improper staining have been meagre in the beginning (Banerji 1932a; Rao and Datta 1953; Sharma and Roy 1958; Datta et al. 1966; Datta 1968); though delayed strong concerted efforts result in successful accomplishment and valuable inference on cytological evolutionary later.

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Mitotic chromosome size in C. capsularis (Paria and Basak 1973) and C. olitorius (Sharma and Roy 1958) was reported to be 1.7–3.7 µm and 1.3–2.7 µm, respectively. Datta et al. (1966, 1975) and Datta (1968) reported that chromosomes of C. olitorius are larger (1.95–3.30 µm) than those of C. capsularis (1.65–3.10 µm). C. capsularis possesses 7 median chromosomes and C. olitorius 5 median and 2 submedian chromosomes. C. urticaefolius 5 submedian, 2 subterminals with varied length of 2.0–3.0 µm and C. aestuans 2 medians, 3 submedian and 2 subterminal with length of 1.00–2.5 µm and C. trilocularis 3 median and 4 submedian chromosomes and divaricated and intricate evolution in the genus of Corchorus is indicated. Karyotype analysis in diploid and colchicine induced tetraploids of C. olitorius and C. capsularis (Akhter et al. 1991) indicated intrapair chromosomal heteromorphicity in few pairs apart from predicting distinct centromeric and chromosomal formula, whereas homomorphic nature of chromosomes in C. olitorius was reported by Samad et al. (1992a). Alam and Rahman (2000) constructed somatic fluorescent banded karyotypes of C. olitorius, C. capsularis and C. trilocularis and reported 14 equal-sized median chromosomes with a pair of satellites, and the species were suggested to possess a common ancestor. Karyotype analysis in nine species of jute through image analyzing system (Maity and Datta 2009) revealed wide range of chromosome length among the species from 1.37 to 3.50 µm (C. capsularis: 2.10–3.15 µm, C. olitorius: 2.10– 2.94 µm, C. aestuans: 2.03–2.83 µm, C. fascicularis: 1.77–3.50 µm, C. pseudocapsularis: 1.58–2.74 µm, C. pseudoolitorius: 2.00– 2.73 µm, C. tridens: 1.37–2.00 µm, C. trilocularis: 1.50–2.07 µm and C. urticaefolius: 1.61– 2.25 µm). Haploid chromatin length ranged significantly among the species from 11.97 µm (C. tridens) to 17.72 µm (C. capsularis). Morphologically distinct chromosome types in different species—three in C. fascicularis, two each in C. capsularis, C. olitorius, C. pseudocapsularis, C. pseudoolitorius, C. aestuans, and one each C. trilocularis, C. tridens and C. urticaefolius

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with prevalence of median chromosomes, mostly graded (evidenced from relative chromosome length) and symmetric are also reported. A dendrogram on the basis of karyomorphological data (chromosome pair with satellite, satellite in median chromosome, all chromosomes median, number of sub-median chromosomes, chromosome types, relative length of shortest chromosome compared to longest and total haploid chromatin length) depicts close relationship between C. olitorius and C. aestuans and among C. trilocularis, C. pseudoolitorius and C. urticaefolius and also suggests a complex evolution in the genus. Through karyotypes analysis with idiograms of the 10 Asian Corchorus species, chromosomes of Corchorus, in general, are found to be small, with a mean chromosome length of 2.30 µm with the largest chromosome in C. pseudoolitorius (3.50 µm) and the shortest in C. pseudocapsularis (1.60 µm) (Saha et al. 2014). The karyotypes of two wild species C. depressus and C. trilocularis were the least diverse, whereas cultivated species (C. capsularis and C. olitorius) and C. pseudoolitorius were the most diverse and specialized. C. fascicularis and C. urticifolius had the most asymmetrical and the most symmetrical karyotypes, respectively. Increase in genome size is highly correlated with increasing karyotype diversity with respect of interchromosomal asymmetry, dispersion index, morphological distinctness and with uneven distribution of additional DNA throughout the karyotype and progressive asymmetrical karyotype has been resulted in during the course of evolution. From the point of view of chromosomal evolution based on degree of karyotype diversity and karyotype asymmetry index in these species it has been suggested that Corchorus is secondary polyploid with a possible basic chromosome number of 4 (x = 4; n = 7) arisen as a result of selective doubling of chromosomes as well as cytological diploidization in the course of evolution or even an ancient paleopolyploidy event. But this mere hypothesis obviously requires confirmation at molecular and genomic (nucleotide sequence) level to be established. However, pattern of chromosomal

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evolution in relation to genome size in the genus Corchorus being more complex, the exact cytological event driving the mechanism to duplicate DNA remains unanswered.

7.4.2 Tetraploid The first attempt of developing autotetraploid through doubling the chromosome number by colchicine treatment in the two cultivated species of jute was made by Rao et al. (1944) and succeeded in C. capsularis in the Jute Research Laboratories at Dhaka in East Bengal (now in Bangladesh). Some preliminary observations on morphological characters were reported by them. During the partition of India, the material got lost. Bhaduri and Chakravarty (1948) successfully induced polyploidy in both the cultivated species, but without any further investigation. Rao and Kundu (1949) reported to have induced polyploidy in C. capsularis by gammaxane treatment. In Japan, Nakajima (1949) induced tetraploidy in C. capsularis and China jute and reported some initial cytotogicaI and morphological observations on them. In autotetraploid of jute (C. olitorius) induced through 0.4% colchicine treatment maximum number of pollen mother cells were found to contain three to five quadrivalents, four quadrivalents being the modal class, the coefficient of realization of quadrivalent being high (0.57). All types of quadrivalent configurations—predominantly ring (52.12%), chain (22.12%), spoon (11.79%) and figure of eight (8.84%) along with linear, convergent, parallel types of coorientation were observed. Chiasma per chromosome in tetraploid and diploid was found to be 0.89 and 0.93, respectively (Basak and Biswas 1968). Elaborate investigation on induced autotetraploids of C. olitorius (cv. Chinsurah Green) reveals a great variation in the meiotic pairing including hexavalents, pentavalents and trivalents in addition to commonly occurring quadrivalents, bivalents and univalents (Datta 1963). The maximum number of quadrivalents noticed were six. Six types of quadrivalent configurations

J. Mitra and C. S. Kar

were observed, the ring and the chain types being the most common. Over 60% pollen mother cell showed univalent at metaphase I. The maximum number of univalent observed were eight. Lagging chromosomes were seen in 55% pollen mother cell at anaphase and telophase I. Lagging chromosomes and the chromosomal bodies lying out in cytoplasm were occasionally found at anaphase II. The chromosome pairing in autotetraploid of capsularis (cv. D 154) showed the occurrence of only quadrivalents, bivalents and univalents at diakinesis. Multivalents other than quadrivalents were not recorded unlike Chinsurah Green. The number of quadrivalents, on an average, was higher in capsularis than olitorius. Univalents and laggards were commonly noticed. Over 40% of the pollen were found aborted. The autotetraploids were highly sterile.

7.4.3 Trisomics Primary trisomics have been shown to be useful in cytogenetic analysis in crop species. Although Nandi (1937) reported the first spontaneous occurrence of trisomic mutant in capsularis jute early where on the basis of observation of gametes containing eight and six chromosomes it was suggested that trisomics might have arisen due to mating of an abnormal egg cell (n + 1 = 8) with a normal pollen grain (n = 7), induced development of trisomic in jute and investigation on its cytology and breeding behavior were initiated at later stage. Swaminathan and Iyer (1961) succeeded for the first time in producing red pigmented trisomic from F2 generation interspecific hybrids between C. olitorius  C. capsularis (by crossing two red pigmented varieties of both species in which olitorius was used as the female parent). They were maintained by selfing as well as back crossing with either of the parents. Back crossing was done with a view to ascertaining the crossability of trisomics with the parents. In the F3 generation of selfing of red pigmented trisomics a few green trisomic plants were isolated for the first time. Simultaneously, more green trisomics were obtained from the back cross generation.

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Classical Genetics, Cytogenetics and Traditional Breeding in Jute

A detailed study of cytogenetic and breeding behavior of red and green trisomics was carried out over periods by Sachar et al. (1967), Iyer (1968) and Das and Iyer (1972). In totality, abnormalities in spore formation after meiosis resulting in monad to septad with majority (75%) of tetrad, higher pollen sterility, higher frequency of trivalent of different configuration—ring, chain and Y-shaped in comparison to uni- and bivalent for the extra chromosome were reported. Thakare et al. (1974) also identified four primary trisomics from irradiated populations of C. olitorius with higher pollen sterility. Paria and Basak (1979a) independently developed all possible seven trisomics in C. olitorius from the progeny (both selfed and intercrossed with diploids) of autotriploid resulted from crossing between colchicine-induced autotetraploid and diploid; and identified all these primary trisomics chromosomally on the basis of length and chromomeric pattern of extra chromosome in seven trisomics from well spread trivalents or univalents at pachytene stage and morphologically through different distinguishing characteristic morphological features associated with these chromosomally identified trisomics. Subsequently cytological and breeding behavior of those was analyzed (Paria and Basak 1979b). The frequency of trivalent formation was not dependent on the length of the extra chromosome. Trivalents in the form of chain were most frequent and the extra chromosome was found to move to either of the poles during anaphase I. The univalents lagging during anaphase I were found to divide equationally and the resulting half chromosomes were found to move to opposite poles. Though a marked reduction in pollen fertility was not observed, a definite reduction in ovule fertility and seed set per pod was observed in all the trisomics. The average frequencies of trisomics in selfed trisomic, (2n + 1)  2n, and 2n  (2n + 1) progenies were 8.60, 14.26 and 2.21%, respectively. No relationship between the length of extra chromosome and the rate of its transmission in different progenies could be established.

7.5

97

Breeding

The demand of an investigation into improvement of yield and quality of jute fiber dates back to as early as 1873, when under resolution of the Lieutenant Governor of Bengal a Commission consisting Mr Hamilton Anstruther, Merchant of Calcutta and Baboo Hem Chunder Kerr, Deputy Magistrate to inquire production and trade of jute was appointed. A voluminous report depicting the scenario of jute cultivation at that time in totality was issued (Kerr 1874) wherein the total area under jute in Bengal Province in 1874 was reported to 900,000 acres as against 30,00,000 acres in 1916 (when the paper of Finlow was read before Bengal Provincial Agricultural Association). The huge jute cultivation was due to the fact that Bengal ryot was beginning to thoroughly realize the profitability of jute cultivation and Crimean war had secured a regular market for fiber in Europe. The report was placed for discussion in 1901 by Calcutta Baled Jute Association to Agriculture Department, Bengal for improving jute. As a result a Sub-committee of the Board of Scientific Advice under Inspector General of Agriculture Mr. Mollison and others was formed. In 1904 the Sub-committee issued a report merely depicting the characteristics of two cultivated species as well as races (cultivar) of those in common cultivation. Actual turning point of jute breeding came when R. S. Finlow was appointed as Fiber Expert to the Government of India in 1904 and he in collaboration with I. H. Burkill commenced an elaborate survey of the cultivated races of jute in Bengal and published in Agricultural Ledger No. 6 of 1907 (Burkill and Finlow 1907) and subsequently pure line selection for genetic improvement of better fiber yield and quality in jute was initiated as early as 1910s by Finlow RS (1911, 1917) in comparison to year 1903 when the concept of “pureline” as genetic basis of individual plant selection from a heterogeneous population (mixture of different homozygous individuals) in self-pollinated crop was given by Johannsen (1903). As a result, first capsularis variety Kakya Bombai was purified through this

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method and later, two high-yielding varieties, D 154 (C. capsularis) and Chinsurah Green (C. olitorius), were developed which remained predominant in jute cultivation for many years. On the recommendation of Royal Commission on Agriculture, Government of India in 1928, the Indian Central Jute Committee was constituted in 1936 by a resolution of the Government of India in the Department of Education, Health and Lands for taking up intensive research work on jute. Subsequently, under this Committee a research organization—Jute Agricultural Research Laboratories, was established in Dhaka in 1938, where research work on all aspects of the improvement of the crop and of the fiber was undertaken. In order to overcome different difficulties for creation, evaluation and selection of breeding material in jute faced by breeders, technique for selection and handling of breeding material was developed (Ghose and Patel 1945) where concern over difficulty in selection of individual plant performing better for fiber yield as seed and fiber could not be harvested from the same plant due to maturity of plant for fiber even before flowering, indirect selection based on plant height and basal diameter, correlation coefficient between these two traits with fiber yield being high 0.76 and 0.91 respectively, detailed procedural methodology on artificial crossingparticularly selection of bud, timing for emasculation and pollination are well documented.

7.5.1 Varietal Development in India With the Independence of India in 1947, the Jute Agricultural Research Laboratories was shifted to Chinsurah, West Bengal in 1948 and then in 1953 the Institute was re-established under the name of Jute Agricultural Research Institute (again renamed as Central Research Institute for Jute and Allied Fibres in 1990) at Barrackpore, West Bengal functioning under ICJC up to 1965 and afterward under Indian Council of Agricultural Research. On the other hand, during partitioning in 1947, most of the jute growing tracts went to the share of Bangladesh with majority of

J. Mitra and C. S. Kar

jute mill in India which resulted in short supply of raw jute to the mill as D 154 (C. capsularis) and Chinsurah Green (C. olitorius) with low productivity were the available varieties. Under a definite direction toward jute research with major emphasis on breeding for high yield and quality fiber this Institute has been developing since 1953 a number of improved varieties of both cultivated species with continuous changing fiber productivity, quality, wider adaptability and required specific attribute like premature flowering resistance, disease resistance. During 1954, one olitorius variety—JRO 632, and two capsularis varieties—JRC 212 and JRC 321 developed through pure line selection from indigenous landrace collection catered the fiber requirement and these varieties were extensively cultivated up to end of seventies. During late sixties to seventies the ratio of area under capsularis to olitorius jute in India was 3:1. Though olitorius jute varieties were higher yielder with stronger fiber than capsularis ones, later ones were preferred due to its premature flowering resistance. This attribute of capsularis jute in general of not flowering early if sown in end March to mid-April unlike olitorius made it suitable in cropping system (jute–rice) in jute growing area. Identifying premature flowering resistance in an exotic germplasm accession “Sudan Green” and incorporating this trait into a series of varieties (JRO 878, JRO 7835 and JRO 524) through crossing this exotic line with available higher yielder JRO 620 (for JRO 878) and JRO 632 (for JRO 7835, JRO 524) followed by pedigree method had been a path-breaking achievement. These varieties were adopted by the farmers due to their higher productivity in comparison to capsularis and suitability to fit jute in cropping system with aman rice due to premature flowering resistance and particularly variety JRO 524 gained farmers’ preference to a greater extent due to its higher adaptability, tolerance to insect and disease. This event brought a paradigm shift in jute cultivation resulting in gradual replacement of capsularis with olitorius jute and now area under olitorius has become 95%. During eighties three varieties of olitorius jute (TJ 40, JRO 3690, KOM 62) and four

7

Classical Genetics, Cytogenetics and Traditional Breeding in Jute

varieties of capsularis jute (JRC 7447, JRC 4444, UPC 94, Hybrid C) were developed for different agroecological situations of jute growing state. Like Sudan Green, Tanganyika 1, an exotic strain from Tanzania, Africa was identified to possess resistance to premature flowering character. Utilizing this strain in the hybridization program (IC 15901  Tanganyika 1), JRO 8432 (Shakti) was developed and released in 1999, with a yield superiority of 10–13% and good quality fiber. This variety is suitable for jute–paddy cropping sequence. JRO 8432 shares a different gene pool from IC 15901 and Tanganyika 1, and thereby broadens the gene pool of olitorius jute varieties. During late nineties and in early twenty-first century, improvement for fiber fineness (for olitorius) and fiber strength (for capsularis) being the great demand for diversified value-added products was the priority and varieties like JRO 66, JRO 8432, JRO 128, S 19 (olitorius), JRC 698, JRC 80 (capsularis) were developed. In 2007, two olitorius varieties namely, JRO 204— being recommended for cultivation in West Bengal, Assam, Bihar, Orissa and AAU 0J 1— for Assam were released and variety JRO 204 due to its superiority to predominantly cultivated variety JRO 524 for fiber yield and quality has been gaining farmers’ acceptability/adoption and along with other newly released varieties replacing JRO 524 around 40% till recent. However, an annotated list of varieties of both capsularis and olitorius jute released and notified by Central Sub-Committee on Crop Standards, Notification and Release of Varieties for Agricultural Crops are presented in Table 7.1 (Kar et al. 2010; Pandey et al. 2020).

7.5.2 Varietal Development in Bangladesh Before partition of India in 1947, the Bangladesh under British India had always been the global central point of research and development on jute and credit of all the varieties developed up to in 1947 obviously goes to Bangladesh and the important ones are D 154 (capsularis),

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Chinsurah Green (olitorius) including others The list of varieties developed at Bangladesh are presented in Table 7.2. After 1947 in Bangladesh also keeping in view of change in cropping system and cropping intensity, varietal improvement efforts were directed to meet the specific requirement in different edapho-ecological situations. Till recent, a total of around 42 (25 capsularis and 17 olitorius) jute varieties have been developed at Bangladesh. Among these seven varieties of capsularis namely CVL 1, CVE 3, CC 45, BJRI Deshi Pat 5, BJRI Deshi Pat 6, BJRI Deshi Pat 7, BJRI Deshi Pat 8, and six varieties of olitorius jute namely O 4, O 9897, BJRI Tossa Pat 4, BJRI Tossa Pat 5, BJRI Tossa Pat 6, BJRI Tossa Pat 7 have been of paramount importance in gaining the popularity at farmers’ level (Islam 2019) and their important features are described below. White Jute Varieties (Corchorus capsularis) CVL 1 (Shabuj Pat): This variety is released in 1977 and characterized by green stem stipule petiole and capsule, ovate lanceolate leaf, fine and strong fiber. Medium to low land is suitable for this variety with sowing at end March to early April. CVE 3 (Ashu Pat): This variety being released in 1977 is characterized by green stem, with bright coppery red upper portion of the petiole and stipule, ovate lanceolate leaf, bright red capsule, and chocolate brown seeds, fine fibre and is suitable for sowing at last week of March. CC 45 (Jo Pat): Being released in 1979 this variety is characterized by green stem with upper part of the petiole of light coppery red, light brown seed, nearly ovate leaf. This is suitable for early sowing (February to April). BJRI Deshi Pat 5 (BJC-7370): This is released in 1995 and possesses green tall stem, serrated leaf, coppery red petiole, light coppery red capsule at young stage. BJRI Deshi Pat 6 (BJC-83): Being released in 1995 it is characterized by serrated leaf with wavy margin, and early maturity. BJRI Deshi Pat 7 (BJC-2142): Being released in 2007 this is characterized by green tall stem, lanceolate leaves, resistance to low temperature, early maturity and suitable for early sowing.

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J. Mitra and C. S. Kar

Table 7.1 List of varieties of jute developed in India Variety

Year of release

Pedigree

Characteristics

JRC 321 (Sonali)

1954

Selection from indigenous type “Hewti”

Stem and upper surface of leaf petiole coppery red, shining chocolate seed, red non-dehiscent capsule, suited for late February sowing without premature flowering, 120– 130 days fiber crop, yield 20–25 q/ha

JRC 212 (Sabuj Sona)

1954

Selection from indigenous type

Full green, shining chocolate seed, non-dehiscent capsule, suited for mid-March sowing without premature flowering, 150–160 days fiber crop, yield 25–28 q/ha

JRC 7447 (Shyamali)

1971

X-ray induced mutant of JRC 212

Full green, shining chocolate seed, non-dehiscent capsule, suited for mid-March sowing without premature flowering, fiber 150–160 days, yield 28–30 q/ha

JRC 4444 (Baldev)

1980

JRC 212  D 154

Full green, shining chocolate seed, non-dehiscent capsule, early March sowing does not induce premature flowering, fiber 150–160 days, yield 25–28 q/ha

UPC 94 (Reshma)

1983

JRC 321  JRC 212

Stem and upper surface of leave foliage coppery red, shining chocolate seed, non-dehiscent capsule, late February sowing does not induce premature, fiber 130– 140 days, Fiber yield 25–27 q/ha

Hybrid C (Padma)

1983

Inter-mutant cross of JRC 6165  JRC 412

Stem and upper surface of leave foliage coppery red, shining chocolate seed, non-dehiscent capsule, late February sowing does not induce premature, fiber 140– 150 days, yield 25–28 q/ha with higher tolerance to waterlogging

KC I (Jaydev)

1992

Gamma-ray derivative of JRC 4444

Full green, shining chocolate seed, non-dehiscent capsule, early March sowing does not induce premature, fiber 125– 130 days, yield 26–30 q/ha

JRC 698 (Shrabanti white)

1999

Multiple crosses involving13 parents

Full green, shining chocolate seed, non-dehiscent capsule, early March sowing does not induce premature flowering, fiber 120–125 days, yield 28–30 q/ha

Bidhan Pat 1

2001

Gamma-ray mutant of D-154

Green ovate lanceolate leaf, green stem and pod, photoperiod insensitive, fiber 80 days,, yield 10–15 q/ha

Bidhan Pat 2

2001

D 154  D 18 (photo-insensitive mutant)

Green ovate lanceolate leaf, green stem and pod, photoperiod insensitive, fiber 80–90 days, yield 20–25 q/ha

Bidhan Pat 3

2001

D 154  D 18(mutant)

Green ovate lanceolate leaf, green stem and pod, photoperiod insensitive, strength 19.2 g/tex, fineness 1.8 tex, fiber 100–110 days, yield 25–27 q/ha

JRC 80 (Mitali)

2005

CIN 114  JRC 321

Late flowering, green foliage, seed extra-large, strength 19.42 g/tex, fineness 1.25 tex, fiber 110 days, yield 28–30 q/ha

JRC 517 (Sidhartha)

2009

JRC 212  JRC 4444

Green tall stem, lanceolate green leaf, grade W2-W3, strength 17.10 g/tex, fineness 1.49 tex, fiber 115-120 days, yield 30–32 q/ha

JRC 532 (Sashi)

2009

CHN/FJ/044C  JRC 321

Green tall stem, lanceolate green leaf, trace red pigmentation on capsule, grade W2-W3, Strength 18.06 g/tex, fineness 1.83 tex, fiber 110 days, Yield 25–30 q/ha

C. capsularis

(continued)

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Classical Genetics, Cytogenetics and Traditional Breeding in Jute

101

Table 7.1 (continued) Variety

Year of release

Pedigree

Characteristics

RRPS 27 C 3 (Monalisa)

2009

JRC 321  NPL/KUC/094C

Red pigmentation on stem, leaf margin reddish, fiber less defective, W3 grade, strength (19.24 g/tex), fineness (1.61 tex), lignin content (12.98%), Fiber 110–115 days, yield 25–28 q/ha

NDC 2008 (Ankit)

2009

71/20  JRC 321

light red stem, glabrous green oval leaves with light red stipules, fiber 110–115 days, yield 25 q/ha

JBC 5 (Arpita)

2010

JRC 321  THA/Y/086C

Fiber day 110 days, with W3 grade fiber, resistance to premature flowering, better fiber quality, resistance to major pest and diseases, yield 28–30 q/ha

JRCM 2 (Partha)

2013

JRC 321  THA/Y/086C

fiber fineness 1.25 tex being W3 grade fiber 120 days yield 28–30 q/ha

KJC 7 (Shrestha)

2016

KC-1  JRC 212

Green tall stem, lanceolate green leaf, strength 18.10 g/tex, fineness 1.52 tex, Days to flowering 120 days, yield 20–27 q/ha

JRC 9057 (Ishani)

2016

JRC 698  CIJ 121

Fiber 110–115 days, yield 30–32 q/ha fiber strength 17.31 g/tex, fineness 1.31 tex, tolerant to stem rot and jute semilooper

AAUCJ 2 (Kkhyati)

2017

CEX 045  CEX 050

Fiber120 days, yield 30 q/ha, resistant to stem rot

BCCC 1 (Shweta)

2018

Pure selection from CIJ 123

Fiber 120 days, yield 27–30 q/ha with fiber tenacity 15.0 g/tex and fiber fineness 1.66 tex. tolerant to stem rot

BCCC 2 (Bidhan Pat 5)

2019

Pure line selection from CIN 492

Fiber 120 days, yield 25–30 q/ha, tolerant to apion, semilooper

JRCJ 11

2021

JRC 698  JRC 517

Fiber 11–120 days, yield 30–32 q/ha, fineness 1.78 tex and higher tolerance to hairy caterpillar and yellow mite

JRO 632 (Baisakhi)

1954

Selection from indigenous type

Full green, brownish grey seed, susceptible to premature flowering if sown before mid-April, sowing mid-April to end-April, suitable for late sowing, 130–140 days fiber crop, pod shattering type, yield 30–32 q/ha

JRO 878 (Chaitali)

1974

JRO 620  Sudan green

Red, pods non shattering, blackish grey seed, resistant to premature flowering on mid-March sowing, sowing midMarch to end-April, better fiber fineness, 180–200 days fiber crop, sowing mid-March to end-April, yield 30–32q/ha

JRO 7835 (Basudev)

1974

JRO 632  Sudan green

Full green, non-dehiscent on maturity, blackish grey, resistant to premature flowering on mid-March sowing, sowing mid-March to end-April, waterlogging tolerance at late growth stage, 180–200 days fiber, yield 32–34 q/ha

JRO 524 (Navin)

1977

Sudan Green  JRO 632

Full green, non-dehiscent on maturity, blackish grey, resistant to premature flowering on mid-March sowing, mid-March to end-April, resistant to root rot and yellow mite, better retting and easy fiber extraction, 180–200 days fiber, yield 34–36 q/ha

TJ 40 (Mahadev)

1983

Inter-mutant cross of JRO 632

Full green, dehiscent on maturity, brownish grey seed, susceptible to premature flowering if sown before midApril, mid-April to end-April, better fiber quality, 140– 150 days fiber, yield 30 -35 q/ha

C. olitorius

(continued)

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Table 7.1 (continued) Variety

Year of release

Pedigree

Characteristics

JRO 3690 (Savitri)

1985

Inter-mutant cross of Tobacco leaf  Long internode

Full green, dehiscent on maturity, steel grey seed, susceptible to premature flowering if sown before midApril, sowing Mid-April to end-April, better fiber quality, suitable for late sowing, 130–140 days fiber crop, yield 30– 33 q/ha

KOM 62 (Rebati)

1993

Gamma-ray irradiation of JRO 878

Full green, blackish grey seed, non-dehiscent, susceptible to premature flowering if sown before mid-April, suitable for early sowing mid-March to late-April, adapted to rainfed situation, 135–145 days fiber crop, yield 30–35 q/ha

JRO 66 (Golden Jubilee)

1998

Multiple crosses involving six parents CG, TM, JRO 524, Peaking, Bangkok and Tanganyika 1

Full green, steel grey seed, non-dehiscent on maturity, susceptible to premature flowering if sown before midApril, fiber quality TD2 grade,145–155 days, yield 35–40 q/ha

JRO 8432 (Shakti)

1999

IC 15,901  Tanganyika l

Full green, steel grey, non-dehiscent on maturity, resistant to premature flowering on mid-March sowing,170– 180 days, Mid-March to late-April, yield 35–40 q/ha

JRO 128 (Surya)

2002

TJ-6  Tanganyika 1

Full green, steel grey seed, non-dehiscent on maturity resistant to premature flowering on mid-March sowing, good fiber quality(strength 27.5 g /tex, fineness 2.6 tex), flowering 170–180 days, fiber yield 35–40 q/ha

S 19 (Subala)

2005

(JRO 620  Sudan Green)  Tanganyika 1

Stem, leaf vein, leaf petiole, stipule and pod red, leaf lamina green, resistant to premature flowering on mid-March sowing, finer fiber quality (fineness 2.7 tex, strength 25.95 g/tex) with less lignin content, flowering 170– 180 days, fiber yield 35–40 q/ha

JRO 204 (Suren)

2007

IDN/SU/053  KEN/DS/060

Non shattering pod, resistant to premature flowering, nonlodging tall cylindrical stem, flowering 120 days, fiber yield 36–38 q/ha

AAU OJ 1 (Tarun)

2007

Selection from S 2 derived from Tanganyika-l  JRO 640

Full green, non-shattering pod resistant to premature flowering, tolerant to stem rot, root rot, anthracnose, yellow mite, Fiber grade TD2, fineness 2.9 tex, strength 3 3 g/tex, flowering 120 days, fiber yield 34–36 q/ha

JBO 2003H (IRA)

2008

(JR0632  Sudan Green)  Tanganyika-1

Full green, non-shattering pod resistant to premature flowering, tolerant to stem rot, root rot, anthracnose, yellow mite, Fiber grade TD2, strength 23.89 g/tex, fineness 2.86 tex, flowering 120 days, fiber yield 34–36 q/ha

CO 58 (Sourav)

2010

TJ 40  Tanganyika 1

Full green, non-shattering pod, resistant to premature flowering, tolerant to stem rot, root rot, anthracnose, yellow mite semi-looper and stem weevil, fiber grade TD3 + 25%, strength 26.61 g/tex, fineness 2.59 tex, flowering 110– 115 days, fiber yield 30–34 q/ha

JBO 1 (Sudhangsu)

2010

(JRO 632  Sudan Green)  Sudan Green

Green, leaf largely ellipsoid with upper part lanceolate; Non dehiscence pod; Premature flowering resistant, fiber strength 25.25 g/tex, fiber fineness 2.38 tex, seed color steel grey

JROM 1 (Pradip)

2013

JRO 524  TAN/NY/018C

It has 5.51% and 4.91% better fiber yield than JRO-524 and JRO-8432 (checks) respectively, with higher fiber strength, better fiber fineness, TD3 grade fiber d. It has been released for cultivation for tossa jute growing belt of India

JROG 1 (Rithika)

2015

JBO 1  JRO 524

It has 5.24% and 10.48% better productivity compared to JRO 524 and JRO 8432 respectively and resistance to semilooper. Fiber is more finer than JRO 8423 and at par with popular variety JRO 524 and categorized as TD3 grade

(continued)

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Classical Genetics, Cytogenetics and Traditional Breeding in Jute

103

Table 7.1 (continued) Variety

Year of release

Pedigree

Characteristics

JRO 2407 (Samapti)

2016

KEN/SM/024  JRO 524

A high-yielding deep red stem colored variety of tossa jute with average yield 33.82 q/ha. It has pre-mature flowering resistance attribute. Drought resistance at early stage of growth and can tolerate water logging at later stage of crop growth. Suitable for entire tossa jute growing regions especially, West Bengal, Assam, Bihar and Odisha states for early March sowing. High humid areas having alternate rain and sunshine is the ideal growth condition for this variety

KRO 4 (Gouranga)

2017

OIM 028  JBO 2003H (IRA)

High-yielding variety with average yield potential 29.61 q/ha. Field resistant to stem rot disease and insect pests like semilooper, apion, Bihar hairy caterpillar and yellow mite. Adapted to tossa jute growing especially, West Bengal, Assam, Bihar and Odisha for mid-March to mid-May sowing

BCCO 6 (Kisan Pat)

2017

Selection from OEX 05

Coppery red stem color variety with average yield potential 28.35 q/ha with better fiber quality in terms of both fiber tenacity (21.18 g/tex) and fineness (2.81 tex), Specifically adapted to West Bengal state but also adapted to other tossa jute growing states like Assam, Bihar and Odisha for sowing 2nd fortnight of April to May

NJ 7010 (Rani)

2018

Selection from EMS treated JRO 524

Green stem pre-mature flowering resistant variety with average yield potential 30.92 q/ha. Suitable for jute-green gram intercropping with very fine fiber (2.66 tex). Fiber maturity 120–125 days Adapted to tossa jute growing belt especially, West Bengal, Assam, Tripura, Odisha, Bihar and Uttar Pradesh for early (March) sowing

JROMU 1

2020

Selection from gamma irradiated JRO 204

Green stem with pre-mature flowering resistant highyielding variety with average yield potential 32.89 q/ha. Fairly good fiber strength (20.80 g/tex) and fine fiber (2.90 tex) quality. Suitable for entire tossa jute growing regions especially, West Bengal, Assam, Bihar and Odisha states for late March to mid-April sowing

JROB 2 (Purnendu)

2021

JRO 204  JRO 524

Developed specially for higher biomass for production of value-added diversified products like paper pulp, charcoal, etc. with potential of 59.1 q/ha green biomass which is 7.7 and 10% higher than the check varieties JRO 204 and JRO 524, respectively. In addition, it has also potential of 32.1 q/ha fiber yield

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BJRI Deshi Pat 8 (BJC-2197): Being released in 2013 this is characterized by light coppery red tall stem, lanceolate leaf, slightly red petiole, brown seed, quick growing, medium salt tolerant and mosaic virus tolerant. Tossa Jute Varieties (Corchorus olitorius) O 4: This variety is released in 1967 and is fully green, with ovate lanceolate leaf, green capsule steel grey seed, fine fiber and wider adaptability, and is suitable for late sowing. O 9897: This is released in 1987 and characterized by deep green stem, ovate lanceolate leaf, brown seeds with green tinge on seed coat with higher fiber recovery, fine fiber, free from premature flowering. OM 1: This was released in 1995 and is characterized by tall green stem, lanceolate leaf, brownish seed, fine fiber and suitable for early sowing and for 3-crop pattern. BJRI Tossa Pat 4 (O-72): This is released in 2002 and possesses tall green stem, brownish grey, higher fiber recovery, fine fiber. BJRI Tossa Pat 5 (O-795): This is released in 2008 and characterized by tall red or reddish stem, ovate lanceolate leaf, brownish grey seed, higher fiber recovery, fine and strong fiber. BJRI Tossa Pat 7 (MG-1): Being released in 2017 this variety is characterized by tall green stem, ovate lanceolate leaf, brownish grey seed, higher fiber recovery fine, strong fiber.

7.5.3 Varietal Development in China China also has long history in jute cultivation initially with many local landraces. In 1947 D 154 of capsularis was introduced from India and leading variety till 1950. Later through pure line selection New Capsularis 2 and Guangfong were developed. Inter-varietal hybridization began since mid-1950 and has led to development of a number of jute varieties—most importantly Yueyuan 4 and Yueyuan 5 and release in 1964, Minma 45 and Minma 179 in 1962 and 71–10 in 1970 in capsularis as well as Xiang Huangma 2 was released in 1990 and Kuanye in 1981 in olitorius (Xiong 2008; Zhang et al. 2019). A list

J. Mitra and C. S. Kar

of varieties of jute developed in China is presented in Table 7.3. However, some varieties in Indonesia (CC 15, CC 22 of capsularis) and in Thailand (Non Soong 1 and Khon Kaen of olitorius) have also been reported.

7.5.4 Mutation Breeding Use of physical mutagenesis (X-ray, gamma ray) for creating variability in jute has been reported as early as in 1961 (Kundu et al. 1961) and continued extensively for a long time (Basu 1965, 1966, 1967; Ghosh and Sen 1971; Rakshit 1967, 1977; Thakare et al. 1973; Singh et al. 1973; Bose and Banerjee 1976; Shaikh and Maith 1985; Rao et al. 1983) and many mutants with variation in morphological traits, special attributes of applied significance as briefly reflected in Table 7.4 were obtained. Remarkably the “soft stem” mutant induced from JRC 212 through gamma radiation having undulated stem has been catalogued as germplasm accession CMU 013 (Mahapatra et al. 2006) and later Sengupta and Palit (2004) designated it as dlpf as it is deficient in lignified phloem fiber containing 50% less lignin (8.49%) in fiber than the parent JRC 212 (18.34%). Further comparison of the bast transcriptome of mutant dlpf with parent revealed downregulation of cad7 gene (cinnamyl alcohol dehydrogenase 7) in bast tissues of the mutant, irrespective of growth stages as its cause. (Chakraborty et al. 2015). Similarly, a low-lignin (7.23%) mutant of C. olitorius through gamma irradiation of JRO 204 (13.7%) was also developed and temporary silencing at early growth stage of the CCoAMT1 gene (Caffeoyl-CoA 3-Omethyltransferase) in the mutant was perceived as the cause for the reduction in lignin content (Choudhary et al. 2017). Another mutant “dissected ribbon” in olitorius jute catalogued as OMU 043 (Mahapatra et al. 2006) induced through thermal neutron irradiation of JRO 632 was found to be deficient in phloic fiber and was designated as bfs (bast fiber shy). This deficiency was associated with a

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Table 7.2 List of jute varieties developed in Bangladesh Varieties

Year of release

Pedigree

Capsularis jute Oocarpus

1910

Pure line selection

Kakya Bombai

1910

Pure line selection

R 85

1916

Pure line selection

D 154

1919

Pure line selection

D 386

1931

Pure line selection

Funduk

1939

Pure line selection

C 212

1939

Pure line selection

C 13

1941

Pure line selection

C 412

1942

Pure line selection

C1

1952

Pure line selection

C2

1952

Pure line selection

C3

1952

Pure line selection

C 4 (C-320)

1955

Pure line selection

C 5 (C-321)

1955

Pure line selection

D 154–2

1961

Pure line selection

C 6 (C-322)

1967

Pure line selection

CVL 1

1977

Pure line selection

CVE 3

1977

Pure line selection

CC 45

1979

Pure line selection

BJRI Deshi Pat 5 (BJC-7370)

1995

D-154  CC-45

BJRI Deshi Pat 6 (BJC-83) ari

1995

CVL-1  Fuleshw

BJRI Deshi Pat 7 (BJC-2142)

2008

CC-45  BJC-718

BJRI Deshi Pat 8 (BJC-2197)

2013

CC-45  FDR

BJRI Deshi Pat Shak 1 (BJC-390)

2014

Cap dwarf red  BINA Pat Shak-1

BJRI Deshi Pat 9 (BJC-5003)

2017

CVL-1  Acc.1831

Chinsura Green (D-38)

1915

Pure line selection

R 26 1929

1929

Pure line selection

olitorius jute

R 27 1929

1929

Pure line selection

O 620 193

1939

Pure line selection

O 632 193

1939

Pure line selection

O 753 1939

1939

Pure line selection

O1

1955

Pure line selection

O2

1955

Pure line selection

O3

1955

Pure line selection

O4

1967

Pure line selection

O5

1964

Pure line selection

O 9897

1987

O-5  BZ-5 (continued)

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Table 7.2 (continued) Varieties

Year of release

Pedigree

OM 1

1995

Pure line selection

BJRI Tossa Pat 4 (O-72)

2002

O-9897  O-2021  O-9897

BJRI Tossa Pat 5 (O-795)

2008

O-4  Uganda Red

BJRI Tossa Pat 6 (O-3820)

2013

Pure line selection

BJRI Tossa Pat 7 (MG-10)

2017

Pure line selection

developmental specific loss of cambium function. (Kundu et al. 2015). On the other hand, straight selection from mutant population with desirable changes or further inter-mutant cross or mutant  variety cross followed by selection has led to development of 10 high-yielding varieties, namely—TJ 40, JRO 3690, KOM 62, Bidhan Rupali (olitorius jute); JRC 7447, Hybrid C, KC 1, Bidhan Pat 1, Bidhan Pat 2, Bidhan Pat 3 (capsularis jute) in India (Table7.1). Some more varieties in Bangladesh, namely, Binadeshipat 2 derived from NaN3 treatment of CVL 1, Atompat 28, Atompat 36 and Atompat 38 (of capsularis jute) through gamma radiation of D 154; in China, namely, Xianghuangma 3 (capsularis) from gamma irradiation of Kuanyechangguo and in Myanmar olitorius variety Shwegontun through gamma radiation of C 28 have also been developed (Maluszynski et al. 2000).

7.5.5 Interspecific Hybridization Interspecific hybridization between two cultivated species for creating variability was attempted as early as in 1921 by Finlow (Finlow 1921). In his paper he commented “It may be of interest to note here repeated attempts have been made to produce a hybrid between C. capsularis and C. olitorius; but although the cross fertilized flower has set fruit in which seeds have formed, the latter have never been capable of germination. Great interest would naturally attach to a hybrid plant of this kind, but the only conclusion admissible so far is that the two species are too far apart biologically for the hybrid to be fertile”.

Later several attempts were made but were reported to be unsuccessful (Banerjee and Datta 1960; Datta et al. 1960; Patel and Datta 1960). Viable seeds were never obtained from crosses between the two species, though in some of the crosses pods were formed and matured, and even shrivelled, underweighted seed were obtained but they always failed to germinate (Swaminathan and Iyer 1961; Islam and Haque 1967; Mia and Shaikh 1967). The main barriers in the successful hybridization of olitorius and capsularis are firstly the ineffectiveness of most of the pollen tubes to grow rapid enough and fertilize the majority of ovules (Chaudhuri and Mia 1962) including degeneration of the embryo and free endosperm nuclei at the early stage of development (Ganesan et al. 1957), premature embryo growth (Srinath and Kundu 1952) and secondly inviability of F1 seed due to phylogenetical divergence between two species (Datta and Sen 1961). Islam and Rashid (1960) reported first successful hybridization between C. olitorius and C. capsularis, using the former as female parent. The hybrids were weak, slow growing and showed dominance of the female parent in respect of some traits (presence of pair of stipules, shape of buds and fruits). Swaminathan et al. (1961) also reported successful hybridization between these two species. Later a number of similar reports on success of interspecific hybridization between C. olitorius and C. capsularis using growth hormones and embryo culture (Islam 1964) and between wide range of wild species and cultivars with prevalence of maternal dominance (Arangzeb and Khatun 1980) and between C. olitorius (JRO

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Table 7.3 List of jute varieties developed in China Variety

Year of release

Pedigree

1915

Introduced from India

C. capsularis D 154 Hongtiegu (Tieguma)

1958

Selected from local variety

Xinfeng

1950

Selected from local variety Xinfengqingpi

Yuanguo 564

1973

Selected from Meifeng 4

Xinyuan 1

1952

Selected from D154

Xinyuan 2

1957

Selected from JRC-212

Yueyuan 1 (Xinxuan 1)

1955

1955 Selected from Taiwan local variety

Yueyuan 2 (Xinxuan 2)

1964

Selected from Xinxuan 1

Yueyuan 3

1961

Selected from Xinxuan 1 GDAAS

Yueyuan 4

1963

Yueyuan 1  Xinxuan 1

Yueyuan 5

1963

Yueyuan 1  Yueyuan 2

Yueyuan 6

1968

Yueyuan 2  57–1289

681

1972

Yueyuan 5  63-161,111

713 57-172

1973

321  Yueyuan 5

715 57-172

1973

921  Yueyuan 5

716

1975

Yueyuan 5  Yueyuan 6

Xuan 46 (C46)

1962

Selected from local variety Liuanhuangma

Kuaizaohong

1962

Selected from a mass population

Meifeng 1

1969

C46  1 FAFU

Meifeng 2

1969

Yueyuan 1  C46

Meifeng 4

1969

Xinxuan 1  Lubinyuanguo

Minma 5 (Minge 5)

1970

Yueyuan 1  Lubinyuanguo

Fuma 1

1973

(Yueyuan 1  Xinxuan 1)  Xinxuan 1

Huangma 179 (77-17P)

1979

Meifeng 2  Minma 5

912

1991

Selection from Huangma 179 treated with gamma ray

C2005-43

2007

Selection from gamma irradiated Zhonghuangma 1

Minma 91

1972

Selected from local variety Pinghezhuhaoma

Minma 396

1972

Selected from Yueyuan 5

Minma 273

1972

Yueyuan 5  Yueyuan 4

Minma 407

1973

Minma 407 Selected from Yueyuan 5 ISSFJ 1973

Minma 603

1973

Yueyuan 5  Hongtiegu

Qiongyueqing

1974

Qiongshan  Yueyuan 5

Huangma 71-10

1981

Yueyuan 5  Hainanqiongshan

Zhonghuangma 1

19,881

Zhonghuangma 1

C90-2

1990

[(71–8  79–51)  79–51]  79–51

Fuhuangma

2011

Meifeng 2  Minma 5

C olitorius (continued)

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J. Mitra and C. S. Kar

Table 7.3 (continued) Variety

Year of release

Pedigree

Cuilv

1919

Introduced from India

Bama 72-1

1972

Introduced from Pakistan

Bama 72-2

1972

Introduced from Pakistan

Bama 72-3

1972

Introduced from Pakistan

Bachang 4 (0–4)

1966

Introduced from Pakistan

Maliyeshengchangguo

Introduced from Mali

Zhema 1

1955

Selected from Cuilv

Changguo 751

1972

Mutant from Guangfengchangguo

Yuanjiang 101

1963

Selected from Cuilv

Guangfengchangguo

1965

Selected from local variety

Changguo 134

1970

Selected from Yuanjiang 101

Tupihuang

1972

Selected from F1 (Guangfengchangguo  Jiegan No. 1) treated with Co60

Guangbaai

1973

Guangfengchangguo  Bama 72–2

Xianghuang 2 (Changguo 277)

1975

Selected from Guangfengchangguo

Kuanyechangguo (070-36)

1980

Guangfengchangguo  Bachang 4

Xianghuangma 1 (075-22)

1986

(Maliyeshengchangguo  Guangbaai)  Maliyeshengchangguo

Xianghuangma 2 (078-13)

1990

Bama 72–2  Kuanyechangguo

Xianghuangma 3 (089-1)

1997

Kuanyechangguo treated with Co60 IBFC 1997

Y007-10

2007

Xianghuangma 1  Bachang 4

Funong 1

2009

Taizi 4 treated with Co60

Funong 4

2010

Cuilv  Bama 72-3

524) and C. capsularis (CMU 011-low lignin mutant) with F1 being intermediate for plant height, fiber weight, stick weight and fiber percentage but low lignin (Sinha et al. 2004), between C. trilocularis and C. capsularis with F1 being intermediate for stem color, bud shape and flower color and maternal dominance (Maity and Datta 2008, 2010) are available. To enhance the genetic variability and to break the plateau in fiber yield in jute, interspecific hybridization would play an important role. Though several reports on successful interspecific hybridization have been reported as reviewed but very unfortunately, its continuity toward advancement of generation with genotypic and phenotypic evaluation for its practical utilization is completely lacking. Thus, due to

one or other reasons of prezygotic (ineffective pollen tube growth, failure of fertilization due to wide phylogenetic distance between the two species) and post-zygotic barrier (hybrid inviability, hybrid sterility, hybrid break down and dominance of maternal parent in segregating generation), the interspecific hybridization could not be utilised effectively till date in breeding programme in jute. However, very recent successful hybridization between C. capsularis (JRC 212) and C. olitorius (JRO 524) using capsularis as female for the first time and stabilization of its advanced population at F8 generation with 194 lines as reported (Sarkar 2019) are of great importance having expectation in realisation of higher transgressive segregation in this advanced recombinant lines

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Table 7.4 Induced mutant with special attributes in jute Mutant

Attributes

Source Gamma radiation of JRC 212

Capsularis jute Patchy albino leaf

Rectangular fiber wedged

Riboon leaf

Male sterile

Soft stem

Reduced lignin

Unfolded lamina

No lignification in secondary phloem

Snow white

White fiber

Waterlogging tolerance

Submergence tolerance

Short petiole

Efficient solar radiation

Narrow erect leaf

Efficient solar radiation utiliser

olitorius jute Crumped leaf

Tolerance to drought and nonshattering pod

Tobacco leaf

Increased number of nodes

Internode mutant

Longer internode

DR1, DR2, DR3

Tolerance to stem rot

Water logging tolerance

Submergence tolerance

Narrow leaf

Efficient solar radiation utiliser

particularly for fiber yield. Most interestingly, resultant F1 was characterized by cylindrical capsule where capsularis possessing globose capsule was used as maternal parent and moreover SSR marker-based genotyping of F2 along with F1, parents revealed segregation distortion showing dominance of paternal parent—C. olitorius, thus proving dominance of maternal parent in F1, F2 in interspecific cross in jute as myth.

7.6

Conclusion

Concerted research efforts on classical genetics and traditional plant breeding have played an important role in continued genetic improvement of this fiber crop providing steady flow of new and improved varieties even by forward genetics (phenotype to genotype) approach like other crops but somehow to lesser extent as compared to cereal. Being long term by nature, plant breeding is continuous, simultaneous and cyclic

Gamma radiation of JRO 632

Gamma radiation with EMS treatment of JRO 632

process, resource dependent and time sensitive. Thus, higher flexibility in breeding methodology to be involved at any step of plant breeding— creation of variation, evaluation and selection of best variant, balancing number of crosses and size of segregation population to be handled effectively being most important factor for breeding efficiency and greater speed of generation advancement through utilization of green house, field, off-season nursery, regulation and manipulation of photoperiodism, light intensity, temperature for flower induction and double haploid breeding will accelerate it further. In-depth study of genetics—both Mendelian (inheritance pattern) and molecular (QTL) level of premature flowering phenomenon, pectin content, lignin content and fiber strength (in capsularis) and fineness (in olitorius) is the need of the hour to accelerate their genetic improvement particularly through marker-assisted selection. Where the research work on cytogenetics in jute has been discouraged and moreover,

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continuity of research on trisomics in jute is lost. Development of trisomics afresh is required for its use. In addition, development of seven possible monosomic lines in cultivated specie may explore inter-varietal disomic substitution line and even alien substitute/addition line for transfer of valuable genes from useful wild species as some C. aestuans accession lines have been reported to be resistant to stem rot as well as to hairy caterpillar. To broaden the genetic base (variation in parentage of varieties), breeding programme is required to involve double cross with diverse parents, diallel selective mating system (DSM) (Jensen 1970), or in modern approach multi-parent advanced generation inter-cross (MAGIC) population (Cavanagh et al. 2008) to evolve genotypes with high yielding and quality fiber. Germplasm exploration from centre of origin (Africa) and/or introduction of traitspecific germplasm should be encouraged. Continuity of advancement of a breeding material following a methodology in long term as successfully accomplished in barley (Suneson 1956) or in maize (Dudley and Lambert 2004) is required in jute to understand genetic architecture for fiber yield, quality and other traits through population genetics approach and to realize genetic gain for those traits. Long term generation advancement of a convergent cross involving a number of diverse parent following bulk method (random or selected as per convenience) would be a holistic approach in jute. Development of stable cytoplasmic genetic male sterility with strong maintainer (even without any restorer line as the economic product of jute is fiber, not F2 seed in hybrid) and development of hybrid for exploitation of heterosis as observed (Anil Kumar et al. 2016) in jute to a large extent is required. During QTL analysis from a RIL mapping population particularly for fiber yield or other useful trait, as mapping population representing normal distribution of all possible (recombinant) genotypes should have extreme positive genotype in homozygous state, selection of promising high-yielding homozygous variant should be explored which is nowhere reported.

J. Mitra and C. S. Kar

Ultimately, information on whole genome sequencing of both species—C. olitorius and C. capsularis with genomic comparison in relation to fiber biogenesis (Islam et al. 2017) and C. olitorius (JRO 524) (Sarkar et al. 2017) provides a valuable genomic source to enrich understanding of fiber genesis at molecular level and should be utilized through translational genomics for overall genetic improvement in jute, in general, and evolving high-yielding premature flowering resistant variety, in particular, as JRO 524 being widely adapted possesses gene for premature flowering resistance from one of its parents—Sudan Green. Furthermore, very recent chromosome-level assembly of genome of both C. olitorius (genome of 361 Mb with 28,479 genes) and C. capsularis (genome of 336 Mb with 25,874 genes) based on population structure analysis of 57 varieties of olitorius and 242 capsularis by whole genome sequencing, identification of candidate genes for fiber biogenesis and quality along with marker-trait association for fiber fineness, cellulose content, lignin content (Zhang et al. 2021) would definitely open up new avenues toward approach of ‘breeding by design’ (Peleman and van der Voort 2003) for jute improvement by developing biotic- and abiotic-stress resistant, wider adaptable, high quality-fiber yielding varieties.

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112 studies on crop genepools No. 4. In: International board for plant genetic resources, Rome, 284 p Finlow RS (1911) Report on jute and flax experiments during past year. Agic J India 6:70–77 Finlow RS (1917) The improvement of the jute crop by pureline selection (paper read before Bengal Provincial Agricultural Association on 5th July, 1916). Agic J India 12:283–290 Finlow RS (1921) Historical note on experiments with jute in Bengal. Agic J India 16:265–279 Finlow RS, Burkill IH (1912) Inheritance of red colour and regularity of self-fertilization in Corchorus capsularis L., the common jute plant. Mem Dept Agric India (botanical Ser) 4:73–80 Ganesan AT, Shah SS, Swaminathan MS (1957) Cause for the failure of seed setting in the cross Corchorus olitorius  C. capsularis. Curr Sci 26:292–293 Ghose RLM (1942) The genetics of Corchorus (jute). The inheritance of pod shape and its linkage relationship. Indian J Genet 2:128–133 Ghose RLM, Das Gupta B (1945) Floral biology, anthesis and natural crossing in jute. Indian J Genet 4:80–84 Ghose RLM, Rao KR, Kundu BC (1948) The genetics of Corchorus (jute). V. The inheritance and linkage relations of bitter taste, anther and corolla colour. J Genet 49:14–22 Ghose RLM, Patel JS (1945) Jute breeding experimental technique. (Selection and handling of breeding material). Agricultural Research Bulletin No. 2 Indian Cent Jute Comm, 23 p Ghose RLM, Rao KR, Ghosh S (1947) The genetics of Corchorus (jute). IV. Inheritance of two new anthocyanin pigmentation patterns. Agr Res Mem 5 Indian Cent. Jute Comm Ghosh SN, Paria P, Basak SL (1979) Combining ability analysis in jute (Corchorus capsularis L). Bang J Bot 8:91–97 Ghosh N, Sen S (1971) Inheritance of x ray induced leaf and stem mutationin jute (Corchorus olitorius L) Z Pflanzenzücht 65:265–272 Heywood VH (1993) Flowering plants of the world. Oxford University Press, New York, p 335 Howard AG, Howard LC, Khan AR (1919) Studies on the pollination of Indian crops. Mem Dep Agric India Bot Ser 10:195–220 Islam AS (1964) A rare hybrid combination through application of hormone and embryo culture. Nature 201:320 Islam MM (2019) Varietal advances of jute, kenaf and mesta crops in Bangladesh: a review. Int J Bioorg Chem 4:24–41 Islam AS, Haque M (1967) A natural Corchorus species hybrid not possible to produce artificially. Sind Univ Res J 2:191–198 Islam AS, Rashid A (1960) First successful hybrid between the two jute-yielding species, Corchorus olitorius L. (Tossa)  C. capsularis L. (White). Nature 185:258–259 Islam MS, Saito JA, Emdad EM, Ahmed B, Islam MM, Halim A, Hossen QMM, Hossain MZ, Ahmed R,

J. Mitra and C. S. Kar Hossain MS, Kabir SMT, Khan MSA, Khan MM, Hasan R, Aktar N, Honi U, Islam R, Rashid MM, Wan X, Hou S, Haque T, Azam MS, Moosa MM, Elias SM, Hasan AMM, Mahmood N, Shafiuddin M, Shahid S, Shommu NS, Jahan S, Roy S, Chowdhury A, Akhand AI, Nisho GM, Uddin KS, Rabeya T, Hoque SME, Snigdha AR, Mortoza S, Matin SA, Islam MK, Lashkar MZH, Zaman M, Yuryev A, Uddin MK, Rahman MS, Haque MS, Alam MM, Khan H, Alam M (2017) Comparative genomics of two jute species and insight into fibre biogenesis. Nat Plants 3:16223–16229 Iyer RD (1968) Towards evolving a trisomic series in jute. Curr Sci 37:181–183 Jensen NF (1970) A diallel selective mating system for cereal breeding. Crop Sci 10:629–635 Johannsen W (1903) Über Erblichkeit in Populationen und reinen Linien. Ein Beitrag zur Beleuchtung schwebender Selektionsfragen. [On heredity in pure lines and populations. A contribution to pending questions of selection]. Jena, Gustav Fischer Kar CS, Satya P, Mitra J, Sarkar D, Sinha MK, Kundu A, Mahapatra BS (2010) Varietal development of jute and allied fibres in India. Indian Farming 60:5–9 Kerr HC (1874) Report on the cultivation of, and trade in, jute in Bengal and on Indian fibres available for the manufacture of paper. Bengal Secretariat Press, Calcutta, 107 + xc (Annexure) p Kumar D (1987) Combining analysis for yield and its components in jute (Corchorus capsularis). Phytobreedon 3:39–44 Kumar D, Palve SM (1995) Combining ability studies for yield and some attributes in white jute (Corchorus capsularis). Indian J Genet 55:260–263 Kundu BC (1951) Origin of jute. Indian J Genet 11:95–99 Kundu BC (1956) Jute—World’s foremost fibre I. Botany, agronomy, diseases and pests. Econ Bot 10:103–133 Kundu BC, Ghosh K, Sarma MS (1961) Studies on the effects of X-irradiation in Corchorus capsularis and C. olitorius. Genetica 32:51–73 Kundu A, Sarkar D, Mandal NA, Sinha MK, Mahapatra BS (2012) A secondary phloic (bast) fibre-shy (bfs) mutant of dark jute (Corchorus olitorius L.) develops lignified fibre cells but is defective in cambial activity. Plant Growth Regul 67:45–55 Kundu A, Topdar N, Sarkar D, Sinha MK, Ghosh A, Banerjee S, Das M, Balyan HS, Mahapatra BS, Gupta PK (2013) Origins of white (Corchorus capsularis L.) and dark (C. olitoriusis L.) jute: a reevaluation based on nuclear and chloroplast microsatellites. J Pl Biochem Biotechnol 22:372–381 Kundu A Chakraborty A, Mandal NA, Das D, Karmakar PG, Singh NK, Sarkar D (2015) A restrictionsite-associated DNA (RAD) linkage map, comparative genomics and identification of QTL for histological fibre content coincident with those for retted bast fibre yield and its major components in jute (Corchorus olitorius L., Malvaceae s. l.). Mol Breed 35:19

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Mahapatra AK, Saha A, Gupta D (2006) Catalogue on evaluation of tossa jute germplasm (Corchorus olitorius). Central Research Institute for Jute and Allied Fibres, Barrackpore, India 41 p Maity S, Datta AK (2009) Karyomorphology in nine species of jute (Corchorus L., Tiliaceae) Cytologia 74:273–279 Maity S, Datta AK (2008) Cytomorphological studies in F1 hybrids (Corchorus capsularis L.  Corchorus trilocularis L.) of jute (Tiliaceae). Compar Cytogenet 2:143–149 Maity S, Datta AK (2010) Cytomorphological studies in F2, F3 and induced amphidiploid of jute (Corchorus trilocularis L.  Corchorus capsularis L.). Nucleus 53:85–87 Maluszynski M, Nichterlien K, Zanten V, Ahloowalia BS (2000) Officially released mutant varieties-the FAO/IAEA database. Mutation Breeding Review No.12. Joint FAO/IAEA division. In: International Energy agency, Vienna, Austria, 84 p Mia MM, Shaikh AQ (1967) Gamma radiation and interspecific hybridization in jute (Corchorus capsularis L. and C. olitorius L.). Euphytica 16:16–68 Mir RR, Banerji S, Das M, Gupta V, Tyagi AK, Sinha MK, Balyan HS, Gupta PK (2009) Development and characterization of large-scale simple sequence repeats in jute. Crop Sci 49:1687–1694 Mitra GC (1994) Genetic control of secondary phloic fibres in jute (Corchorus capsularis L.) Genetica 63:9–11 Nakajima G (1936) Chromosome numbers in some crops and wild angiosperms. Jpn J Genet 12:211 Nakajima G (1949) Tetraploid plants of jute and China jute raised by colchicine method. Jpn J Genet (suppl) 2:121–131 Nandi HK (1937) Trisomic mutations in jute. Nature 140:973–974 Nath P, Denton L (1980) Leafy vegetables in Nigeria. Pl Genet Resour Newsl 42:14–17 Oliver D (1863) Flora of tropical Africa. Lovell Reeve and Co., 5 Henrietta Street, Covent Garden, London UK Palve SM, Kumar D (1991) Combining ability for fibre strength in white jute. Phytobreedon 7:4–8 Palve SM, Kumar D (1994) Diallel analysis for yield and its components in tossa jute. Ann Agric Res 17:156– 161 Pandey SK, Maruthi RT, Alam NM, Mitra S, Satya P, Kar CS, Mitra J (2020) Jute varieties in India—An overview. Technical Bulletin 1/2020, ICAR Central Research Institute for Jute and Allied Fibres, India, 60 p Paria P, Basak SL (1979a) Identification of seven trisomics of jute (Corchorus olitorius L.) Indian J Genet 39:178–187 Paria P, Basak SL (1979b) Cytology and breeding behaviour of trisomics in jute. Indian J Genet 39:471–479 Paria P, Basak SL (1973) The pachytene chromosomes of Jute (Corchorus olitorius). Curr Sci 42:832

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114 (C. capsularis L. and C. olitorius L.) are *300% smaller than the reported estimate of 1100–1350 Mb. Caryologia 64:147–153 Sarkar D, Mahato AK, Satya P,Kundu A, Singh S, Jasawal PK, Singh A, Bahadur K, Pattnaik S, Singh N, Chakraborty A, Mandal NA, Das D, Basu T, Sevanthi AS, Saha D, Datta S, Kar CS, Mitra J, Datta K, Karmakar PG, Sharma TR, Mohapatra T, Singh NK (2017) The draft genome of Corchorus olitorius cv. JRO 524 (Navin). Genomics Data 12:151–154 Sarkar D (2019) Advanced breeding in jute: Fertile sexual hybrid of the two cultivated jute species (Corchorus capsularis  Corchorus olitorius) Annual Report 2019. ICAR Central Research Institute for Jute and Allied Fibres, Barrackpore, India, pp 1–2 Sengupta G, Palit P (2004) Characterization of a lignified secondary phloem fibre deficient mutant of jute (Corchorus capsularis). Ann Bot 93:211–220 Sengupta D, Nandy S, Mitra S, Dutta P, Sinha MK, Kole PC, Chakraborty S (2005) Genetical study on tossa jute (Corchorus olitorius L.) for yield and quality parameters. Indian J Genet 65:29–32 Shaikh MAQ, Miah MM (1985) Genetic improvement of jute through nuclear technique. Bang J Nuc Agric 1:1– 16 Shanhua T, Benor S, Blattner FR, Demissew S, Karl H (2010) Collection and ethnobotanical investigation of Corchorus species in Ethiopia: potential leafy vegetables for dry regions. Genet Resour Crop Evol 57:293– 306 Sharma AK, Roy M (1958) Cytological studies on jute and its allies. Agron Lusit 20:5–15 Singh DP (1973) Combining ability in jute. Indian J Genet 33:77–81 Singh DP, Sarma BK, Banerjee SC (1973) X-ray induced mutations in jute (Corchorus capsularis and C. olitorius). Genet Agrar 27:115–147 Singh DP (1974) Diallel analysis of some quantitative characters in jute (Corchorus capsularis) Indian J Hered 6:63–65 Singh DP (1975) The analysis of additive and dominance variation in a diallel cross of jute (Corchorus olitorius) Acta Agron 24:167–172 Sinha MK, Mitra S, Nandy S, Sengupta D, Dutta P, Das F, Chakrabarty SC (2004) Interspecific hybrid between two jute (Corchorus) species for textile quality fibre. Indian J Genet 64:310–314 Srinath KV, Kundu BC (1952) Cytological studies of pollen-tube growth in reciprocal crosses between Corchorus capsularis Linn. And Chorchorus olitorius Linn. Cytologia 17:219–223

J. Mitra and C. S. Kar Suneson CA (1956) An evolutionary plant breeding method. Agron J 48:188–191 Swaminathan M, Iyer RD (1961) Skewed recombination in a rare interspecific jute hybrid. Nature 192:893–894 Swaminathan M, Iyer RD, Subbha K (1961) Morphology, cytology and breeding behaviour of hybrids between Corchorus olitorius and C. capsularis. Curr Sci 30:67–68 Tao A, Huang L, Wu G, Afshar RK, Qi J, Xu J, Fang P, Lin L, Zhang L, Lin P (2017) High-density genetic map construction and QTLs identification for plant height in white jute (Corchorus capsularis L.) using specific locus amplified fragment (SLAF) sequencing. BMC Genomics 18:355 Thakare RG, Joshua DC, Rao NS (1973) Induced viable mutations in Corchorus olitorius Indian. J Genet 33:204–228 Thakare RG, Joshua DC, Rao NS (1974) Radiation induced trisomics in jute. Indian J Genet 34:337–345 Topdar N, Kundu A, Sinha MK, Sarkar D, Das M, , Banerjee S Kar CS, Satya P, Balyan HS, Mahapatra BS, Gupta PK (2013) A complete genetic linkage map and QTL analyses for bast fibre quality traits, yield and yield components in jute (Corchorus olitorius L.). Cytol Genet 47:129–137 Wild H (1984) Tiliaceae. In: Leistner O A (ed) Flora of Southern Africa 21 (1). Botanical Research Institute, Department of Agriculture, Pretoria, South Africa, pp 30–44 Xiong HP (2008) Breeding sciences of bast and leaf fiber crops. Chinese Agricultural Science and Technology Press, Beijing Yang Z, Yang Y, Dai Z, Xie D, Tang Q, Cheng C, Xu Y, Liu C, Deng C, Chen J, Su J (2019) Construction of a high-resolution genetic map and identification of quantitative trait loci for salt tolerance in jute (Corchous spp.) BMC Plant Biol 19:391–400 Zhang L, Ibrahim AK, Niyitanga S, Zhang L, Qi J (2019) Jute (Corchorus spp.) breeding. In: Al-Khayri JM, Jain M, Johnson DV (eds) Advances in plant breeding strategies: industrial and food crops, vol 6, Springer Nature Switzerland AG, Switzerland, pp 85–113 Zhang L, Ma X, Zhang X, Xu Y, Ibrahim AK, Yao J, Huang H, Chen S, Liao Z, Zhang Q, Niyitanga S, Yu J, Liu Y, Xu X, Wang J, Tao A, Xu J, Chen S, Yang X, He Q, Lin L, Fang P, Zhang L, Ming R, Qi J, Zhang L (2021) Reference genomes of the two cultivated jute species. Plant Biotechnol J. https:// doi.org/10.1111/pbi.13652

8

Challenges of Jute Transformation Zeba I. Seraj, Ahmad S. Islam, and Rakha Hari Sarker

Abstract

Jute fiber yields strong but rough threads resulting in its major use as sacking material. However, it is a natural, biodegradable fiber and its genetic improvement will open the way not only for its diversified use but ultimately to replace synthetic fibers, such as plastic. There are two self-pollinating commercial species of jute, namely, C. olitorius and C. capsularis, each with desirable but contrasting characters, but which cannot be hybridized successfully. Thus genetic variation in the commercial cultivars of jute is limited and its improvement has to be species specific. Successful genetic transformation of C. capsularis has been achieved by both tissue culture and biolistic-based techniques. For C. olitorius, which is more recalcitrant to de-differentiation and in vitro regeneration, in planta transformation has been successfully reported. The best practices for obtaining non-chimeric jute transformants have been discussed in this chapter. So far, examples of genetic improvement are resistance to a

Z. I. Seraj (&) Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000, Bangladesh e-mail: [email protected] A. S. Islam
R. H. Sarker Department of Botany, University of Dhaka, Dhaka, Bangladesh

specific fungus and two insects, modest reduction in its lignin content and slight increase in its cellulose content. Sustained efforts at jute genetic transformation for its planned and targeted improvement for productivity, resistance to various stresses, ease of fiber extraction and fiber quality improvement are the need of the day. The recent publication of the sequences of both species of jute and validation of their genes pave the way for their focused genetic improvement through genome editing.

8.1

Introduction

Jute holds a pivotal position in our lives because it is a natural biodegradable fiber, and could one day replace the use of plastic and other synthetic fibers. However, concerted effort for its diversified use will need to be put in place for it to replace plastic. Wide commercial applicability means that some of its qualities may need to be modified, such as targeted reduction of its lignin content with a concomitant increase in cellulose content. In addition to this, incorporating biotic and abiotic stress resistance to jute would enhance its yield and reduce its production cost. Genetic transformation technologies are now in place for the sustained and systematic improvement of jute in order to make it a viable substitute for plastic products. Successful transformation of jute has already been reported by scientists in

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_8

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some of the major jute-producing countries like Bangladesh, China and India (reviewed in Majumder et al. 2020) which will be discussed in detail along with some of the problems and challenges which persist to date. Successful and consistent transformation protocols will eventually pave the way for genome-editing and tailormade jute crops for the benefit of a sustainable environment. The long and glossy jute fiber, which originates from the secondary phloem, yields rough but strong threads. It also has moderate heat and fire resistance and high tensile strength. Its most widespread use is in sacking of goods for transport purposes, but it has been shown that it can be successfully used as geotextiles for an environmentally friendly prevention of erosion, in jute blends with cotton, as shopping bags, beach bags, jute hessian cloth bags, sling bags as well as upholstery for cars and other furniture. It makes a good insulating material and could be useful for electromagnetic, mechanical shock or even sound insulation (Sanjoy 2016). India and Bangladesh produced a total of 3.3 million tons of jute fiber in 2018, of which India’s share is 1.7 and that of Bangladesh 1.6. In the same year China produced 30,000 tons of jute fiber (FAO 2019). However, Bangladesh is the main exporter of Jute with 1.21 million bales shipped overseas against 92,000 by India in 2019. India mostly uses the jute for its domestic consumption. Jute accounts for 5% of the total foreign exchange and 4% of the Bangladesh’s GDP (Akter et al. 2020). Given the importance of jute in the producer countries and its useful properties, it is important that modern tools of molecular biology are used for its improvement. With the publication of the genomic sequences of both the commercially cultivated species of jute, information on their *30 K genes and their validation by RNA sequencing data, the way forward to improvement of jute has become that much easier (Islam et al. 2017). Transformation technologies to be discussed in detail below have also greatly improved over the years. It is hoped that in the next decade or so, improved jute would lead to its versatile use in at least replacing the one-time use plastic, of which the world

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produced 360 million metric tons in 2018 (Mossman 2020). Moreover, there have been encouraging reports of the production of 100% degradable plastic bags made out of jute extracts called Sonali bag https://www.textiletoday.com. bd. Jute is commercially produced mainly from two species of Corchorus, which are C. olitorius and C. capsularis, locally referred to as Tossa and White, respectively, in both Bangladesh and West Bengal, where the majority of it is grown. The fibers extracted from C. olitorius have a golden appearance (leading to the popular term “golden fiber”) and are superior in tensile strength, compared to that of the white fibers of C. capsularis. Most of the morphological as well as physiological characteristics of these major cultivated species are contrasting, for example, the greenish black small seeds of C. olitorius range from 200 to 250 per plant, while C. capsularis seeds are chocolate brown, larger and a single plant produces 40–50 seeds. Both grow up to 9–10 feet high, are sparsely branched and the leaves and young stems contain a lot of mucilage, which may interfere when their tissues are subjected to tissue culture, transformation and in vitro regeneration. C. capsularis has the advantage of being flood tolerant and having moderate tolerance to dieback disease and partial tolerance to root rot and mite infestation. On the other hand, C. olitorius is immune to the mosaic virus and anthracnose as well partially tolerant to nematode infestation. Both are primarily self-pollinated with only 10% cross-pollination occurring in C. olitorius (Islam et al. 1992). Although hybridization between these two were reported (Islam and Rashid 1960), these reverted to maternal type at F3 (Islam et al. 1992). Thus variability is very limited in both and any genetic improvement has to be species specific. C. olitorius is reported to be more recalcitrant to tissue culture, transformation and in vitro regeneration and so far only in planta transformation of apical shoot tips has been successfully reported (Sajib et al. 2008; Shafrin et al. 2017). In case of C. capsularis, Indian scientists have had success in both biolistic and tissue-culture mediated

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Challenges of Jute Transformation

transformation and regeneration of shoot tips (Ghosh et al. 2002; Saha et al. 2014; Majumder et al. 2018b). Chinese scientists on the other hand have reported successful transformation with cotyledonary nodes (Zhang et al. 2015, 2021). In Bangladesh, transformation and regeneration was also reported from mature embryos (Sarker et al. 2008). Some of the challenges that still persist for genetic transformation and regeneration of jute are detailed below. It is hoped that a comparative discussion on these factors will pave the way for more rapid and routine transformation and easy genome editing of jute in the near future.

8.2

Choice of Explants, Media and Selection

Apical meristem or shoot tips have so far been observed to be the best choice for successful Agrobacterium-mediated transformation through tissue culture or in planta methods. This tissue has been shown to be suitable for biolistic transformation as well. The reported transformation efficiencies for the biolistic and in planta methods are between 13 and 15% (Ghosh et al. 2002; Bhattacharyya et al. 2015). On the other hand, the reported efficiencies of transformation and regeneration of shoot tips through tissue culture is 3-4% with the use of 100 µM acetosyringone (Saha et al. 2014; Majumder et al. 2018b). In almost all cases, the jute accession used for tissue culture-based and biolistic transformation was C. capsularis JRC321. C. olitorius accessions (O-72 and O-9897) could only be successfully transformed using in planta methods (Sajib et al. 2008; Shafrin et al. 2017). The Chinese scientists have reported the use of cotyledonary nodes for successful transformation of their local accessions of C. capsularis, where they have also used 100 µM acetosyringone (Zhang et al. 2015). The latter have not, however, made observations on the efficiencies of transformation but only report on an initial successful infection rate of 25%. There is a single report on the use of mature embryos of C. capsularis CVE3 and CVL1 for successful transformation (Sarker et al. 2008). Interestingly for all the

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transformation procedures a varying concentration of selectable marker concentrations were used, that is 0.1 mg/l (Sajib et al. 2008) to 194 g/l Kanamycin (Shafrin et al. 2015, 2017) for in planta transformation by the same group of scientists. More recently, there are reports of selection of T1 seeds after in planta transformation using the following methodology. The T1 seeds are sown in media containing ¼th MS media, 1% sugar and 0.6% agar and incubated at 30 °C in dark for 2 days. The yellow seedlings are then sprayed with 100 µg/ml kanamycin and placed in light. After 3–4 h of incubation, the leaves of the positive (containing the kanamycin resistance gene, nptll) plant are able to accumulate chlorophyll and continue to grow with green leaves while non-transformants fail to accumulate chlorophyll and remain yellow (M. Shahidul Islam, BJRI, Personal Communication). For the cotyledonary node explant, 50 mg/l Kanamycin (Zhang et al. 2015) or no selection (Zhang et al. 2021) in a total of 8 weeks was used in the presence of 100 µM acetosyringone. For the mature embryo explant, successively higher concentration from 25 to 200 mg/l every fortnight was used (14 weeks total), presumably to select against any chimeric transformants. Hygromycin concentrations for selection of transformants ranged from 5 mg/l (Chattopadhyay et al. 2011) to 12 mg/l (Saha et al. 2014). Observations from previous work with either Kanamycin or Hygromycin kill assays of control jute explants showed a clear gradient of nonsurvivors in case of the Kanamycin selection in tissue culture only (Seraj unpublished). In case of the Bar gene, mostly phosphinothricin concentration of 2.5 mg/l was used but was gradually increased up to 4 mg/l in successive subcultures in a total of 6 weeks (Majumder et al. 2018a). To summarize the success in transformation of C. capsularis so far, it is apparent that 3–4 fortnightly subcultures with successively higher concentrations of selectable markers may be needed in order to avoid production of chimeric transformants. The best explant is the apical meristem or shoot tips of young germinated seedlings followed by cotyledonary nodes and germinating mature embryos. It is also likely that

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addition of acetosyringone in the infection stages may enhance transformation efficiencies. In the case of C. olitorius, it is apparent that its recalcitrance to any kind of de-differentiation in tissue culture makes only in planta transformation by Agrobacterium possible. However, it is also probable that infection of germinating mature embryos of C. olitorius with Agrobacterium may be successful, particularly as the emergence of single shoots from such mature seeds were reported (Sarker et al. 2008). During Agrobacterium infection and co-culture, particularly in case of in planta transformation, the use of temperatures of 28 °C or below, the optimal being 22 °C is important to prevent destabilization of the vir genes (Fullner and Nester 1996). A comprehensive list of media components and their effects on regeneration from cotyledonary nodes has been reported, the best being 2mg/l BAP and 0.25 mg/l NAA for production of the maximum number of shoots without any beneficial effects of added amino acids (Zhang et al. 2015). Some authors have recommended the use of Glutamine and Casamino acids (Ghosh et al. 2002), whereas others suggest use of antioxidants like NDGA (nordihydroguaiaretic acid) and surfactants like Pluronic F-68, which help in interference by the excessive mucilage in jute tissue (Islam et al. 1999).

8.3

Genetic Improvement in Jute

8.3.1 Insect Resistance Major insect pests of the commercial cultivars of jute include the jute stem weevil, jute hairy caterpillar (HC), jute semilooper (SL) and jute yellow mite. Out of these HC and SL are lepidopteron species and cause a great deal of damage. For example, HC cause up to 30% loss in yield and SL almost 50% fiber loss due to induction of branching, leading to fiber breaks during extraction (Rahman and Khan 2012). Transgenic jute lines of C. capsularis JRC321 were produced by a synthetically fused cry1 Ab/Ac gene of B. thuringiensis and tested up to T4 for their efficacy against HC and SL. Insect

mortality was reported to be up to 100% for both (Majumder et al. 2018b).

8.3.2 Fungus Resistance The necrotrophic fungus Macrophomina phaseolina causes severe loss in both the cultivated species of jute due by producing stem rot, root rot as well as charcoal rot disease (Gotyal et al. 2014). Losses due to M. phaseolina infestation in jute were reported to be up to 40% and 30%, respectively, in India (Roy et al. 2008) and Bangladesh (Islam et al. 2012). Transgenic rice chitinase gene driven by the CaMv35S promoter was shown to significantly protect against M. phaseolina lesions compared to wilt type. Most importantly, there was no difference between uninfected wild type and highly tolerant infected transgenic plants in fiber length, strength and fineness (Majumder et al. 2018a).

8.3.3 Improvement in Jute Fiber Properties Jute fibers contain mainly cellulose (58–63%), hemi-cellulose (20–24%) and lignin (12–15%) (Wang et al. 2009). Jute fibers are stiff and harsh mainly due to the presence of the high amount of lignin (Vigneswaran and Jayapriya 2010) as well as the lower amount of cellulose in comparison with cotton, which has >90% cellulose (Hsieh 2007). It was observed that overexpression of the UDP-glucose pyrophosphorylase from C. capsularis could increase the cellulose content of transgenic jute by 4.7%, however, without any decrease in the lignin content. The CcUGPase transgenic lines grew faster and also had significantly increased height (Zhang et al. 2013). Transgenic C. olitorius lines with up to 15% reduction in fiber lignin was reported by separate downregulation of each of the two lignin biosynthesis genes of jute, coumarate 3hydroxylase (C3H) and ferulate 5-hydroxylase (F5H) by artificial micro-RNA (Shafrin et al. 2015). Similarly, hpRNA (hairpin double stranded RNA) against the lignin each of biosynthetic

8

Challenges of Jute Transformation

genes cinnamate 4-hydroxylase (C4H) and caffeic acid O-methyl transferase (COMT) also lowered lignin content by up to 14% in separate transformation events. Interestingly the cellulose content was also increased by 3.5% in the C4HhpRNA lines with better cellulose to lignin ratios (Shafrin et al. 2017). All four transgenic C. olitorius lines were tested in advanced generations up to T5 and found to inherit the lower lignin contents as well as the higher cellulose to lignin ratios in the C4H-hpRNA lines.

8.4

Conclusion

Stable transformation has now been shown to be possible in both the cultivated species of jute. Improved jute with pest and disease resistance has also been produced. Jute fiber improvement with lower contents of lignin and higher cellulose has also been shown to be heritable in advanced generations of the jute lines. In order to reduce the lignin content further and concomitantly increase the cellulose content, more than one lignin biosynthetic genes can easily be targeted by either crossing the existing lines or by using CRISPR-mediated downregulation of more than one gene (Zhang et al. 2019). With the ready availability of the genome and transcriptome information on the cultivated accessions of jute, its rapid improvement and role for bringing about a sustainable reduced plastic environment is no longer a distant dream.

References Akter S, Sadekin MN, Islam N (2020) Jute and jute products of Bangladesh: contributions and challenges. Asian Bus Rev 10:143–152 Bhattacharyya J, Chakraborty A, Roy S, Pradhan S, Mitra J, Chakraborty M, Manna A, Sikdar N, Chakraborty S, Sen SK (2015) Genetic transformation of cultivated jute (Corchorus capsularis L.) by particle bombardment using apical meristem tissue and development of stable transgenic plant. Plant Cell Tiss Org Cult 121:311–324 Chattopadhyay T, Roy S, Mitra A, Maiti MK (2011) Development of a transgenic hairy root system in jute (Corchorus capsularis L.) with gusA reporter gene

119 through Agrobacterium rhizogenes mediated cotransformation. Plant Cell Rep 30:485–493 FAO (2019) https://www.fao.org/economic/est/estcommodities/jute-hard-fibres/jute-hard-fibresmeetings/fibres40/en/2019 Fullner KJ, Nester EW (1996) Temperature affects the TDNA transfer machinery of Agrobacterium tumefaciens. J Bacteriol 178:1498 Ghosh M, Saha T, Nayak P, Sen S (2002) Genetic transformation by particle bombardment of cultivated jute, Corchorus capsularis L. Plant Cell Rep 20:936– 942 Gotyal BS, Tripathi AN, Selvaraj K, Ramash Babu V, Meena PN, Satpathy S (2014) Screening of some jute (Corchorus spp.) germplasms against stem rot caused by Macrophomina phaseolina (Tassi) Goid. J Mycopathol Res 52:363–365 Hsie (2007) 1—Chemical structure and properties of cotton. In: Gordon S, Hsieh YL (eds) Cotton. Woodhead Publishing, pp 3–34 Islam AS, Rashid A (1960) First successful hybrid between the two jute-yielding species, Corchorus olitorius L. (Tossa)  C. capsularis L. (White). Nature 185:258–259 Islam AS, Haque MM, Hoque MI, Seraj ZI (1992) Tissue culture and micropropagation of jute (Corchorus spp.). In: Bajaj YPS (ed) High-Tech and micropropagation III. Springer, Berlin, Heidelberg, pp 505–526 Islam MRK, Mahboob H, Zohra FT, Hossain MB, Seraj ZI (1999) Stable transformation of jute (Corchorus capsularis L. var CVL-1) Calli and high efficiency marker gene insertion in explants. Plant Tiss Cult Biotechnol 9:35–43 Islam MS, Haque MS, Islam MM, Emdad EM, Halim A, Hossen QMM, Hossain MZ, Ahmed B, Rahim S, Rahman MS et al (2012) Tools to kill: genome of one of the most destructive plant pathogenic fungi macrophomina phaseolina. BMC Genomics 13:493 Islam MS, Saito JA, Emdad EM, Ahmed B, Islam MM, Halim A, Hossen QMM, Hossain MZ, Ahmed R, Hossain MS et al (2017) Comparative genomics of two jute species and insight into fibre biogenesis. Nat Plants 3:16223 Majumder S, Datta K, Sarkar C, Saha SC, Datta SK (2018a) The development of Macrophomina phaseolina (Fungus) Resistant and Glufosinate (Herbicide) tolerant transgenic jute. Front Plant Sci 9:920 Majumder S, Sarkar C, Saha P, Gotyal BS, Satpathy S, Datta K, Datta SK (2018b) Bt jute expressing fused dEndotoxin Cry1Ab/Ac for resistance to lepidopteran pests. Front Plant Sci 8:2188 Majumder S, Saha P, Datta K, Datta SK (2020) Chapter 22—Fiber crop, jute improvement by using genomics and genetic engineering. In: Tuteja N, Tuteja R, Passricha N, Saifi SK (eds) Advancement in crop improvement techniques. Woodhead Publishing, pp 363–383 Mossman S (2020) Plastics and social responsibility. In: Lambert S (ed) Provocative plastics: their value in

120 design and material culture. Springer International Publishing, Cham, pp 275–295 Rahman S, Khan MR (2012) Incidence of pests in jute (Corchorus olitorius L.) ecosystem and pest–weather relationships in West Bengal India. Arch Phytopathol Plant Protec 45:591–607 Roy A, De RK, Ghosh SK (2008) Diseases of bast fibre crops and their management. In: S.K.H. Karmakar PG, Ramasubramanian T, Mandal RK, Sinha MK, Sen HS (eds) Jute and allied fibre updates. Central Research Institute for Jute and Allied Fibres, Kolkata, pp 217–241 Saha P, Datta K, Majumder S, Sarkar C, China SP, Sarkar SN, Sarkar D, Datta SK (2014) Agrobacterium mediated genetic transformation of commercial jute cultivar Corchorus capsularis cv. JRC 321 using shoot tip explants. Plant Cell Tiss Org Cult 118:313– 326 Sajib AA, Shahidul Islam M, Shamim Reza M, Bhowmik A, Fatema L, Khan H (2008) Tissue culture independent transformation for Corchorus olitorius. Plant Cell Tiss Org Cult 95:333–340 Sanjoy D (2016) Thermal insulation material based on “jute”. In: Almssad AAaA (ed) Insulation materials in context of sustainability. Intech Open Sarker R, Al-Amin G, Hassan F, Hoque M (2008) Agrobacterium-mediated genetic transformation of two varieties of jute (Corchorus capsularis L.). Plant Tiss Cult Biotechnol 18:7–16 Shafrin F, Das SS, Sanan-Mishra N, Khan H (2015) Artificial miRNA-mediated down-regulation of two monolignoid biosynthetic genes (C3H and F5H) cause

Z. I. Seraj et al. reduction in lignin content in jute. Plant Mol Biol 89:511–527 Shafrin F, Ferdous AS, Sarkar SK, Ahmed R, Amin A, Hossain K, Sarker M, Rencoret J, Gutiérrez A, del Rio JC et al (2017) Modification of monolignol biosynthetic pathway in jute: different gene. Differ Conseq Sci Rep 7:39984 Vigneswaran C, Jayapriya J (2010) Effect on physical characteristics of jute fibres with cellulase and specific mixed enzyme systems. J Textile Inst 101:506–513 Wang H, Huang L, Lu Y (2009) Preparation and characterization of micro- and nano-fibrils from jute. Fibers Polym 10:442–445 Zhang G, Qi J, Xu J, Niu X, Zhang Y, Tao A, Zhang L, Fang P, Lin L (2013) Overexpression of UDP-glucose pyrophosphorylase gene could increase cellulose content in Jute (Corchorus capsularis L.). Biochem Biophys Res Commun 442:153–158 Zhang G, Zhang Y, Xu J, Li FT, Tao A, Zhang L, Fang P, Lin L, Qi J (2015) An efficient regeneration system and optimization of the transformation from the cotyledonary node of jute (Corchorus capsularis L.). J Nat Fib 12:303–310 Zhang Y, Malzahn AA, Sretenovic S, Qi Y (2019) The emerging and uncultivated potential of CRISPR technology in plant science. Nat Plants 5:778–794 Zhang G, Huang S, Zhang C, Li D, Wu Y, Deng J, Shan S, Qi J (2021) Overexpression of CcNAC1 gene promotes early flowering and enhances drought tolerance of jute (Corchorus capsularis L.). Protoplasma 258:337–345

9

Molecular Linkage Mapping: Map Construction and Mapping of Genes/QTLs Moumita Das, Sumana Banerjee, and Reyazul Rouf Mir

Abstract

Jute is considered as one of the major fibre crops next to cotton and is distributed throughout the tropical and sub-tropical regions of the world. Jute has two commercially important cultivated fibre yielding species including Corchorus capsularis and Corchorus olitorius. The major constraint in jute improvement programs is its narrow genetic base and sexual incompatibility between the two cultivated species. Until recently, jute crop was considered as one of the orphan crops. However, due to recent advances in genomics tools and techniques, the crop is now considered rich in genomics resources. Different types of molecular markers have been developed and have been

deployed for the jute improvement programs world-wide. A number of different types of mapping populations have been developed and used in the preparation of frame-work genetic linkage maps. The maps once developed have been used in genetic dissection through QTL interval mapping. The QTL mapping has been done for important targeted traits in jute and genes/QTLs have been discovered. The genes/QTLs discovered will be deployed into jute molecular breeding programs for the improvement of different traits. In this chapter, we have emphasized on the research undertaken so far on the development of linkage maps and their use for QTL mapping in jute as well as the challenges faced and ways to overcome them.

9.1 M. Das School of Biotechnology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, Madhya Pradesh 462033, India S. Banerjee Department of Botany, University of Calcutta, 35 Ballygunge Circular Road, Ballygunge, Kolkata 700019, India R. R. Mir (&) Division of Genetics & Plant Breeding, Faculty of Agriculture, Sher-e-Kashmir University of Agricultural Sciences & Technology of Kashmir (SKUAST-K), Wadura Campus, Sopore, Kashmir, J&K 193201, India e-mail: [email protected]

Introduction

Jute (2n = 2x = 14) belongs to genus Corchorus of the family Malvaceae of Angiosperms and is considered as one of the major fibre crops in the world. The crop is next to cotton in terms of both areas covered and fibre production (Rowell and Stout 2007). The genus Corchorus comprises approximately 100 species, and 215 sub-species, varieties, and forms that are distributed throughout the tropical and sub-tropical regions of the world (Kundu 1951; Purseglove 1968; Chan and Miau 1989; Saunders 2006). Corchorus capsularis and Corchorus olitorius are the

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_9

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two commercially important cultivated species. Wild Corchorus taxa are mostly distributed in the tropical/sub-tropical regions of Africa, America (including Brazil, Mexico, Bolivia, Venezuela, and West Indies), Australia, China, Taiwan, India, Myanmar, Bangladesh, Nepal, Sri Lanka, Japan, Indonesia, Thailand, Malaysia, and Philippines (Kundu 1951; Brands 1989–2007). The primary centre of origin and diversity of the wild taxa of Corchorus appears to be Africa, while the secondary center of origin is Australia, which is native to 32 wild species of the genus Corchorus (Hinsley 2006, 2008; Kew Science Directory 2009). The two cultivated species of jute (Corchorus capsularis and Corchorus olitorius) differ from each other both in terms of their genome size (1350 Mb for C. olitorius and 1100 Mb for C. capsularis; Samad et al. 1992) and their geographical locations of origin (Basu et al. 2004). Indo-Burma region, including South China, is considered as the centre of origin for white jute (Kundu 1951), while that of tossa jute is Africa (Roy et al. 2006). The two species are sexually incompatible, and contribute to a narrow genetic base of the crop. This is one of the major constraints in jute improvement program. The current yield and agronomic performance of the two cultivated varieties (C. capsularis and C. olitorius) cannot meet the industrial and market demand. Therefore, there is an urgent need for redesigning the breeding strategies in order to develop and introduce high yielding varieties of jute with improved fibre quality. The conventional breeding methods certainly helped in the development of large number of jute varieties. However, development of jute varieties through conventional breeding is time consuming and cost ineffective, also due to loss of resistance against diseases in the farmers field. Other limitations associated with conventional plant breedng include the following: (i) very long duration required for improvement of a trait; (ii) lack of precision in selection of genotypes that is some times due to linkage, and (iii) labour intensive cultivation and breeding. The recent advances in genomics and their use in crop improvement programs have

M. Das et al.

revolutionized agriculture. Several disadvantages/limitations associated with conventional breeding can be overcome by the use of marker-assisted breeding (MAB) in the crop improvement programs. The major advantages of MAB like lesser time requirement, higher precision, and cost effectiveness have been widely discussed. Keeping these advantages in view, the MAB has now become an integral component of any crop improvement program. For MAB, the first step is the identification of markers associated with the QTLs controlling the trait of interest. Interval mapping and association mapping (GWAS) are the two major approaches for identification of marker-trait association, of which interval mapping has been widely used. For the discovery of genes/QTLs for important traits in crop plants including jute, one of the prerequisites is the development of a linkage map. The linkage map once developed in a crop species including jute will be used for a variety of purposes including the following: (i) mapbased cloning of important genes, (ii) comparative mapping and linking genomic information between a model and related non-model crop species (Kakioka et al. 2013; Kundu et al. 2015), (iii) anchoring scaffolds in genome sequencing projects, (iv) identification of candidate genes, (v) identification of gene/QTL through QTL mapping approaches, and (vi) marker-assisted selection (MAS). This chapter reviews the research undertaken so far on the development of linkage maps and their use for QTL mapping in jute.

9.2

Populations for Linkage Map Construction and Genes/QTLs Mapping

Linkage mapping is one of the conventional mapping methods which depend upon the genetic recombination that occurs during the development of the mapping populations. For more than past two decades, linkage mapping has been successfully undertaken in a number of crops/plant species for identification of thousands of QTLs, which have sometimes been used for

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Molecular Linkage Mapping: Map Construction …

map-based gene cloning (Price 2006). In QTL mapping, the initial step is the development of the experimental populations that can be a biparental population like F2, backcrosses (BC), double haploids (DH), recombinant inbred lines (RIL), and near-isogenic lines (NIL). Each of these mapping population types has their advantages and disadvantages. The different types of mapping population already developed or need to be developed in jute has been tabulated (Table 9.1) and also presented in Fig. 9.1. The sequential steps in linkage map construction and mapping of genes/QTLs include the following: (i) choice of parents depending upon the desired traits, (ii) choice of appropriate molecular markers that will distinguish the two parental genotypes, (iii) development of the mapping population, (iv) genotyping and phenotyping the mapping population, and (v) identification of QTLs using suitable statistical methods (Fig. 9.2). Until recently jute crop was treated as an orphan crop with limited genomics resources. However, with the discovery of genomics resources in recent years, the gene discovery programs have also been started in jute worldwide. Several mapping populations including biparental mapping populations have been developed for mapping genes for different traits (Fig. 9.1). The mapping populations have been separately developed for both the cultivated species of jute (Corchorus capsularis and Corchorus olitorius). However, due to the presence of a powerful sexual incompatibility barrier between these two cultivated species of jute (Patel and Datta 1960; Swaminathan and Iyer 1961; Haque 1987; Sinha et al. 2011), no interspecific mapping populations could be developed between Corchorus capsularis and Corchorus olitorius. One of the first intra-specific RIL (recombinant inbred line) mapping population comprising of 120 individuals was developed from the bi-parental cross between C. olitorius c. v. JRO-524 (male) and C. olitorius mt. PPO-4 (female). The PPO-4 is a selection from the exotic jute genotype OIJ-154 (Das et al. 2012a, b; Topdar et al. 2013). This population was developed to map genes/QTLs for fibre fineness.

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Genetic linkage maps have also been developed using bi-parental mapping population developed from intra-specific cross in jute (Sarkar et al. 2016). Later, another RIL mapping population of C. capsularis comprising of 100 individuals was derived by the single seed descent (F8) method at Fujian Agriculture and Forestry University, China (Tao et al. 2017). This population was developed from a cross between elite cultivar ‘179’ (female parent) that was derived from the cross Meifeng No. 2′
‘Minma No. 5’ and ‘Aidianyesheng’ (male parent) which is a long established local variety. In addition to the above efforts for development and use of linkage maps in jute, a number of F2 mapping populations were also developed which was reported in several studies that are listed below. (i) An incomplete/partial linkage maps were developed using F2 mapping populations of C. olitorius for cold sensitivity/ tolerance (Sultana et al. 2006; Haque et al. 2008) and mite tolerance (Keka et al. 2008). This was one of the earliest mapping populations comprising only 35 lines in jute. (ii) Another F2 mapping population (67 individuals) was developed for mapping genes for resistance to Macrophomina phaseolina in the background of cultivated species “C. capsularis” (Mir et al. 2011). (iii) The third F2 mapping population comprising 185 individuals was also developed in white jute from a cross between the female parent Qiongyueqing (derived from the cross between ‘Qiongshan’ and ‘Yueyuan No. 5’ in China) and the male parent Xinxuan No. 1 which is a pure line collected from India (Chen et al. 2014). (iv) Fourth F2 mapping population was developed in the background of ‘C. olitorius’ species. This population comprised of 176 individuals and was developed from a cross between an exotic cultivar Sudan Green and a unique thermal neutron-induced secondary phloic mutant of C. olitorius cv. JRO 632 (Kundu et al. 2015). (v) Fifth F2 mapping population of 150 individuals was recently developed for salt tolerance from the cross between the wild C. olitorius genotype ‘J009’ from Nepal and another C. olitorius genotype ‘Guangfengchangguo

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Table 9.1 Details of the genetic linkage maps developed in the two cultivars of jute Species

Mapping population

Size

Software

Number of linkage groups

Total genetic distance (cM)

Number of mapped markers

Average distance between adjacent markers (cM)

References

C. olitorius

F2 from an intraspecific cross between cold sensitive o-9897 and cold tolerant Ac No. 1805

22

Mapmaker version 3.0

3

87.3

10 ISSRs

8.73

Sultana et al. (2006)

C. olitorius

F2 from an intraspecific cross between cold sensitive o-9897 and cold tolerant Ac No. 1805

112

MapMaker version 3.0

18

463.7

40 RAPDs

19.6

Haque et al. (2008)

C. olitorius

RIL6 mapping population derived from a cross between JRO 524 and PPO4

120

MapMaker version 3.0

6

784.5

36 SSRs

21.8

Das et al. (2012)

C. olitorius

RIL6 mapping population derived from a cross between JRO 524 and PPO4

120

JoinMap 4

7

799.9

82 SSRs

10.7

Topdar et al. (2013)

C. capsularis

F2 mapping population from a cross between ‘Qiongyueqing’ and ‘Xinxuan No. 1’

185

Mapmaker/Exp V3.0

8

2185.7

44 SRAPS, 57 ISSRs & 18 RAPDs

18.7

Chen et al. (2014)

C. olitorius

F2 mapping population from a cross between an exotic cultivar Sudan Green accession no. OEX 031 and a unique thermal neutron-induced secondary phloic mutant cv. JRO 632

176

JoinMap 4

7

358.5

503 RADs

0.72

Kundu et al. (2015)

C. capsularis

RIL8 mapping population derived from a cross between elite cultivar ‘179’ and a local variety ‘Aidianyesheng’

100

JoinMap 4

11

1621.4

913 SLAF

1.93

Tao et al. (2017)

C. olitorius

F2 mapping population from a cross between wild germplasm J009 and variety Guangfengchangguo (GFG)

150

JoinMap 4

7

1375.41

4839 SNPs

0.28

Yang et al. (2019)

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Mapping Population in Jute (Developed/To be Developed)

Multi-Parental Mapping Population in Jute

Bi-Parental Mapping Population in Jute (Developed/To be Developed)

P1 Backcrossing

(Developed/To be Developed)

P2 F1

Chromosome Doubling

F1

F1

F1

F1

F2 F1 BC1F1

BC1F2 Back cross population

F1 F1

RILs Recombinant inbred lines

DHs Double haploids

Magic population

Fig. 9.1 Different types of mapping populations used/to be used in jute for development of linkage maps and identification of QTLs/genes for different targeted traits

(GFG)’ from China (Yang et al. (2019). They used the F2:3 progeny for the construction of the high-resolution genetic map.

9.3

Genetic Linkage Maps in Jute

The genetic linkage map is the linear arrangement of markers (loci) on the chromosome obtained on the basis of estimates of recombination frequencies (RF) among the markers. The linkage map is the ‘road map’ of the chromosomes developed from a mapping population derived from a cross between two different parental genotypes. Among crop plants, the first partial genetic map was developed in the maize crop (Emerson et al. 1935). For instance, if the recombination frequency is less between two markers, the closer they are located on a

chromosome and similarly, when there is more recombination frequency between markers, higher is the genetic distance between them. Unlinked markers having a recombination frequency of 50% are expected to be located far away on the same or on different chromosomes. Different chromosomal regions vary in recombination frequency, so that there are recombination-rich and recombination-poor regions. Genetic maps once developed will prove useful for different studies targeted towards certain objectives including the following: (i) providing information about genome organization, (ii) study of species evolution, (iii) study of synteny between related species, (iv) study of taxonomy involving rearrangement of taxa, and (v) QTL/gene identification for a trait of interest. A variety of software have been developed and used in the

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Genomics Resources

Genetic Resources

Selection of parental genotypes

Candidate genes

Development of mapping populations

Bi-parental Mapping populations

Parental Polymorphism

Multi-parental Mapping populations

Molecular Markers

Polymorphic markers/genes

Genotyping of mapping populations and Recording of genotyping data

Development of Linkage/genetic map

Trait phenotyping of mapping populations (Multiple locations & Years)

QTL mapping & identification of genes/QTLs

Fig. 9.2 Different steps involved in linkage map construction and mapping of genes/QTLs in Jute

development/construction of linkage maps in various plant species (see Table 9.2). The molecular genetic maps based on DNA markers are now available in almost all plants of academic and economic interest; the list of these plant species is growing. It is indeed a challenge for the plant breeders and geneticists to dissect the genetic architecture of the complex traits of all crops including jute with comparatively less genomics resources available. Again, for the selection of high-throughput superior traits and decoding genome composition the high-density genetic maps have been found useful in many crop species (Wang et al. 2012). When compared to the other bast fibre crops, the advances made in the breeding and genetic improvement of jute are really limited (Tao et al. 2017). A variety of molecular markers including SSR markers have

been already developed and used for different purposes including development of linkage maps in jute crop (Mir et al. 2008, 2009). In these earlier studies, it has been pointed out that the intra-specific mapping populations developed in jute revealed extremely low levels of parental polymorphisms (Das et al. 2012a; Topdar et al. 2013). This low level of polymorphism in jute coupled with an inherently narrow genetic base of the two cultivated species of jute (Mir et al. 2009) are the serious limitations in the genetic linkage mapping of jute. In jute, efforts have been made earlier to develop a preliminary linkage map. The first such map was based on only 8 ISSR (Inter Simple Sequence Repeat) markers (Sultana et al. 2006). This linkage map comprised of only 3 linkage groups varying in length from 4.8 to 52.9 cM

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Table 9.2 Software for linkage mapping in crop plants including jute Software programs

Population type

Features

Availability

References

MAPMAKER/EXP

F2 intercross, F2 backcross, RIL (self), F3 intercross (self), RIL (sib)

1. Combines an EM algorithm for recombination fraction estimation with a Hidden Markov Model (HMM) method for calculating the expected number of intermarker recombination events, significantly lowering computation time for large datasets 2. Enables the calculation of a LOD-error score regarding evidence for genotyping error

http://www. broadinstitute. org/ftp/ distribution/ software/ mapmaker3/

Lander et al. (1987)

JoinMap

BC1, F2 intercross, RILx (self), DH, DH1, DH2, HAP, HAP1, CP, BCpxFy, IMxFy

1. Has highly advanced MS Windows user interface for data management and analysis 2. The newer maximum likelihood approach was added to deal with larger datasets and is much faster than the regression mapping approach

http://www. kyazma.nl/

Stam (1993)

Map Manager QTX

Advanced intercross, advanced backcross, RILx

1. It carries out a combined marker grouping and ordering procedure that can be further refined using rippling 2. Allows markers under segregation distortion to be identified and is capable of analysis of many types of crosses, including complex crossing schemes

http://www. mapmanager. org/

Manly et al. (2001)

Neighbour Mapping

RIL

1. Estimates the minimum branch length tree and the properties of NJ, such as its rapid computation time and relatively good accuracy 2. Neighbour Mapping naturally gives most weight to the most closely linked marker pairs, minimizing the effect of erroneous markers on the map

Available from the author

Ellis (1997)

(continued)

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Table 9.2 (continued) Software programs

Population type

Features

Availability

References

AntMap

F2 intercross, F2 backcross, RIL (self), DH

1. Rapidly finds the marker order and implements a segregation test, categorizing markers with distorted frequencies according to P-value thresholds 2. Employs a bootstrap test to gauge the reliability of an estimated marker order 3. The associated software tool is written in the Java programming language and has a visually attractive graphical user interface (GUI)

http://cse.naro. affrc.go.jp/ iwatah/antmap/ index.html

Iwata and Ninomiya (2006)

CarthaGene

F2 intercross, F2 backcross, RIL, phase known outbreds

1. Focuses on the marker ordering problem and enables joining of maps from distinct crosses 2. Produces a set of best marker orders rather than a single optimum, enabling further user interaction 3. Includes a comparative mapping method that enables genome sequence data with known orthologous relationships to a subset of the markers

http://www. inra.fr/mia/T/ CarthaGene/

Schiex and Gaspin (1997), de Givry et al. (2005)

MadMapper

Specialises in RILs but flexible scoring scheme can be employed for many other design types

1. Developed for the analysis of high-throughput molecular marker datasets 2. Calculates distances between pairs of markers using two novel scoring schemes known as BIT and REC and performs various quality control procedures 3. Pairwise scores for both linked and unlinked markers are considered in this analysis, unlike in many other methods 4. Generates both graphical genotype plots and 2D heat maps of two-point scores, allowing users to spot misordered markers and potential genotyping errors

http://cgpdb. ucdavis.edu/ XLinkage/ MadMapper/

Kozik and Michelmore (2009)

(continued)

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Molecular Linkage Mapping: Map Construction …

129

Table 9.2 (continued) Software programs

Population type

Features

Availability

References

MSTMAP

BC1, DH, HAP, RIL

1. Uses concepts from graph theory and machine learning to rapidly estimate high-density genetic maps 2. Deals with missing data and uses a further neighbourhood-based algorithm to detect and remove scoring errors 3. Produces most accurate maps in a faster time

http://www. 138.23.191. 145/mstmap/

Wu et al. (2008)

RECORD

BC1, F2, F3, RIL

1. Useful for construction of dense maps, such as those with over 500 markers per linkage group 2. Removes genotyping errors during map construction, using neighbouring marker scores to identify potentially erroneous datapoints 3. Faster performance, which is, less sensitive to missing data and scoring errors

http://www. plantbreeding. wur.nl/UK/ software_ record.html

Van et al. (2005)

THREaD Mapper

F2 intercross, F2 backcross, RIL (self), DH

1. A Principle Co-ordinate analysis combined with a variant of the Local Principal Curve algorithm are used to map the data into three-dimensional (3D) space 2. The 3D nature lends itself well to visual interpretation of the data 3. Individual markers can be colour-coded by userdefined categories 4. Implements a Chisquared segregation test, reporting P-values of each marker to the user and allowing them to include or exclude markers accordingly

http://cbr.jic.ac. uk/dicks/ software/ threadmapper/ index.html

Cheema et al. (2008)

130

and a total length of 87.3 cM. Another early example is a map with 40 RAPD markers spread over 18 small linkage groups with a total map distance of 50 cM (Haque et al. 2008). The construction of linkage maps in jute was also started by us at Department of Genetics and Plant Breeding, Ch. Charan Singh University (CCSU) at Meerut under a DBT, funded research project. Under this project, we developed large number of SSR markers and finally used them in the study of genetic diversity, construction of linkage maps and QTL mapping (Mir et al. 2008, 2009; Das et al. 2012a, b; Banerjee et al. 2012). By utilizing a pair of 374 primers, SSR marker polymorphism study was conducted on the parental genotypes (JRO 524 and PPO4) of a bi-parental mapping population that was developed for mapping genes/QTLs for fibre fineness. However, among the 374 primer pairs, only 66 markers were found polymorphic between the two parental genotypes. Among the 66 polymorphic SSR markers used for genotyping of RIL mapping population (120 RILs), construction of a linkage map could be done using just 53 polymorphic SSRs (Das et al. 2012a). This is due to lower polymorphism rate between the parental genotypes and a higher level of segregation distortion in this RIL population. Eventually, the map covering a total genetic distance of 784.3 cM consisted of only 36 SSR loci that were distributed on the six linkage groups (Das et al. 2012a). In our map, the smallest linkage group had a length of 53.1 cM, with longest linkage group being 216.3 cM long. Out of the 55 SSR loci, 35 (66.63%) showed a significant deviation (P < 0.05) from the expected mendelian (1:1) segregation ratio (Fig. 9.3). It was observed that this mapping effort could not generate the seven linkage groups as expected from the haploid chromosome number of jute (n = 7) due to a high degree of segregation distortion and a low level of polymorphism (Das et al. 2012a). In another independent study using the same mapping population, Topdar et al. (2013) used a different set of 83 polymorphic SSRs and developed a linkage map that covered a total genetic distance of 799.9 cM distributed

M. Das et al.

over 7 linkage groups. Among the 82 loci that were mapped, 50 loci (61%) significantly deviated from the expected 1:1 mendelian segregation ratio (Fig. 9.3) which has confirmed our earlier results (Das et al. 2012a). The markers in the linkage groups LG2, LG5, and LG7 exhibited segregation distortion. As many as 76% of the distorted loci were skewed towards the female parent and 24% towards the male parent. Similarly, Chen et al. (2014) developed a linkage map in white jute (C. capsularis) using a combination of molecular markers that includes 44 SRAPs (sequence-related amplified polymorphisms), 57 ISSRs (intersimple sequence repeats), and 18 RAPDs (randomly amplified polymorphic DNAs). The total length of this map was 2185.7 cM comprising 8 linkage groups with a mean density of 18.7 cM between a pair of loci. Segregation distortion (P < 0.05) from the expected 3:1 Mendelian segregation ratio was observed in 10 loci (8.3%) and among these skewed segregation to the female parent Qinogyueqing clustered on LG1, LG3, and LG5 and one locus with skewed segregation to the male parent Xinxum No. 1 was located on LG6. With advent of the next-generation sequencing (NGS) technology, the single nucleotide polymorphism (SNP) markers became available and are used for construction of high-density genetic maps (Choi et al. 2007; Song et al. 2016). In order to perform a high-throughput SNP genotyping, specific length amplified fragment sequencing (SLAF-seq) technology can be used (Collard and Mackill, 2008; Sun et al. 2013). In white jute (C. capsularis), another high-density genetic map was constructed using specific locus amplified fragment (SLAF) sequencing (Tao et al. 2017). The linkage map consisted of 913 SLAFs on 11 linkage groups and a total genetic distance of 1621.4 cM. Average genetic distance of the map was 1.61 cM per locus. LG1 having 210 markers was the longest linkage group covering a length of 406.34 cM and LG11 was the shortest having a length of 29.66 cM with only 25 markers. A significant deviation (P 0.05) from the expected 1:1 Mendelian

9

Molecular Linkage Mapping: Map Construction …

segregation ratio was observed in 862 (94.4%) loci out of the 913 loci that were mapped. Each of the linkage groups were presented with segregation distortion with LG2 showing the highest (95%) and LG7 is having the lowest (83.64%) level of segregation distortion. Recently, in one of the study in soybean by Zuo et al. (2019), it was reported that the accuracy of grouping markers on their corresponding chromosomes, the consistency of the linkage maps with genome and genome coverage were enhanced by utilizing the very significantly distorted markers. One of the important study conducted in jute in order to identify the genome-wide SNPs involved the application of RAD (restriction-site-associated DNA). The genome-wide RAD SNPs were used to construct a dense linkage map spanning a total distance of 358.5 cM in 7 linkage groups and comprising 503 RAD markers (Kundu et al. 2015). The mapping population used for the construction of this dense linkage map was an F2 population of C. olitorius. The details of all the genetic maps developed so far in the two cultivated species of jute are presented in Table 9.1. Consistent with the previous reports as mentioned earlier Kundu et al. (2015), also reported a moderate level of segregation distortion. It was reported that 207 (33.8%) codominant RAD markers significantly (P = 0.5) deviated from the Mendelian expectation of 1:2:1 genotype ratios (Fig. 9.3). A non-random segregation distortion was noted across the linkage map with LG4 showing the highest (66.7%) number of distorted loci. More recently, another high-density genetic map spanning a genetic distance of 1375.41 cM on 7 linkage groups was developed. The map carried 4839 SNP markers with an average distance of 0.28 cM between any two adjacent markers (Yang et al. 2019). The number of markers and the genetic distance for individual linkage groups ranged from 299 markers on linkage group LG2 with a genetic distance of 113.66 cM to 1542 markers spanning 350.18 cM on LG7. This total number of markers in this genetic map was 8150 with no apparent segregation distortion.

131

9.4

QTLs/Genes Identified in Jute

A quantitative trait locus (QTL) is a part of the genome that is responsible/influences a quantitative trait. The principal of mapping QTL was known long time ago in 1923 when Sax discovered association between seed coat colour and seed weight in beans. He suggested that the genes responsible for seed colour in beans is genetically linked to one or several factors controlling seed weight in beans. The mapping of QTL is based on systematic search for linkage disequilibrium between marker loci and QTLs. The science of QTL mapping is continuously advancing and several sophisticated methods are now available to discover QTLs for important quantitative traits in crop plants. In jute crop due to lack of sufficient genomics and genetics resources only few QTL mapping studies have become available. We in the Molecular Biology Laboratory at CCSU, Meerut under a DBT funded project conducted QTL analysis for fibre yield and fibre quality traits (8 and 2) for the first time (Das et al. 2012b; Table 9.3). Using the composite interval mapping (CIM) of the QTL Cartographer v2.5, single locus QTL analysis was performed for each of the 10 fibre yield and quality traits. For the eight fibre yield traits, 21 QTLs were identified out of which 15 were definitive QTLs that were detected above the threshold LOD score and 6 QTLs were suggestive having higher than 2 LOD score value. A total of four major QTLs explaining >20% PVE were identified and the value of PVE by individual QTLs ranged from 6.29% for the trait green weight (GW) to 37.73% for top diameter (TD). For fibre fineness (FF), one QTL was detected at LOD score above threshold value which explained 8.31–10.56% of the PV (Table 9.3). In the same study, two-locus QTL analysis based on mixed-model composite interval mapping (MCIM) was used to identify main effect QTLs (M-QTLs) using the QTLNetwork v2.0. The MCIM approach was also useful in identifying the epistatic QTLs (QQ or E-QTLs) and QTL
environment interactions (QE or

132 Fig. 9.3 Representation of the level of segregation distortion in the different genetic mapping efforts in Jute

M. Das et al. Level of segregation distortion 100 90 80 70 60 50 40 30 20 10 0 Das et al. 2012

Topdar et al. 2013

QQE). Except for the trait TD, all the remaining 7 fibre yield traits had 11 M-QTLs that revealed a range of PVE from 0.41 to 5.44%. Again MQTLs for these 7 traits also revealed significant Q
E interactions. One M-QTL, ‘QFf.ccsu-5.3’ was identified between the markers MJM1182 and MJM1150 which was also detected by the single locus analysis. Sixteen epistatic QTLs (EQTLs) for the six fibre yield traits and four EQTLs for fibre fineness were identified. This study is one of the first reported in jute for the identification of QTLs for fibre yield and quality (Das et al. 2012b). Using the same mapping population derived from a cross between JRO-524
PPO4 as used by us (Das et al. 2012b) and a different set of polymorphic SSRs, Topdar et al. (2013) performed QTL analyses using various functions of the MapQTL 6 (Ooijen et al. 2009) based on the log-transformed mean values over three biological replicates. A set of 26 definitive QTLs with LOD *  2.5 were identified and the suggestive QTLs with chromosome-wide significant LOD score (*  1.7) were ignored (Topdar et al. 2013). Two QTLs were identified for fibre yield (FY) on LG1 and LG4 associated with MJM650 and MJM602. Both these QTLs together explained 21.2% of phenotypic variation

Chen et al. 2014

Kundu et al. 2015

Tao et al. 2017

(Table 9.3). For tensile strength (TS), one QTL was detected at LG1 on MJM644 that explained 11.0% of the observed variation. Again, for fibre fineness four QTLs associated with MJM566 and MJM635 on LG2 and LG5 was detected that explained 9.2 and 8.1% of phenotypic variation. Maximum number of OTLs was detected for plant height (PH) and stem diameter top (SDT) followed by stem diameter base (SDB) and wood yield (WY) among the bast fibre yield components. Phenotypic variation of 23% was observed for the two QTLs for SDM located on LG 3 and LG 7. Four QTLs for SDT explained 40.5% of phenotypic variance and three QTLs for WY located on LG 1, 4, and 5 explained 41% of phenotypic variance. Results of these QTL mapping studies will be extremely useful in future for understanding the complex genetics of the fibre fineness and would also accelerate the development of jute cultivars with improved fibre fineness. In another study, QTLs were identified using MapQTL 6 and utilizing F2:3 mapping population of C. olitorius and co-dominant RAD markers (Kundu et al. 2015). In this study, 9 QTLs were detected across two environments, one each for fibre content (FC), fibre yield (FY), and three each for plant height (PH) and stem

9

Molecular Linkage Mapping: Map Construction …

base diameter (SBD). At 40.2 cM on LG 1 and on a single SNP (C/T) marker, one QTL (qFC11) was detected that accounted for 10.2–10.6% of phenotypic variance in FC (Table 9.3). At the same position on LG 1, one QTL each for FY, RW, PH, and SBD was also detected that explained 7.5–8.1, 7.2–9.2, 6.3–8.2, and 6.3– 10.3% phenotypic variance, respectively. Later, QTL analysis was performed for plant height by using the improved QTL mapping software ICI Mapping (ICIM) package (Tao et al. 2017) using specific locus amplified fragment (SLAF) sequencing in the RIL mapping population of C. capsularis. This study revealed a phenotypic variance ranging from 4.4 to 15.63% for the 11 stable QTLs that were identified for plant height across the two locations as well as the pooled data. Out of these 9 QTLs, LG2 harboured 5 QTLs, LG9 had three and one each on LG1, LG3, and LG10. More recently, very first attempt for QTL mapping related to salt tolerance in jute was carried out by Yang et al. (2019). F2 population of C. olitorius and the genotyping data of mapped SNPs was used to perform QTL analysis using QTL Cartographer v2.5. Three obvious QTLs involved in salt tolerance were identified with LOD values of more than 3.5 on LG 4 and 13 minor QTLs on four LGs. Phenotypic variance of 11.81 and 19.61%, respectively, was observed for the major QTL, qJST-1 that was detected under the two salt stress conditions. These QTLs may prove useful in the markerassisted selection and breeding for salt tolerance in jute. The mapping of QTLs in different studies in jute was done using different QTL detection methods and using different software programs. A list of software being used for QTL mapping in different crop plants including jute is available in the form of (Table 9.4).

9.5

Statistical Approaches for QTL Mapping in Jute

Single marker analysis is the simplest approach for QTL mapping and can be undertaken using any one of the following four available

133

approaches involving markers: t-test, regression, ANOVA and maximum likelihood (ML). Sax (1923) conducted QTL analysis using loci controlling phenotypic trait like seed colour as a marker, but phenotypic markers are not easily available and are difficult to use. Therefore availability of DNA-based markers made this task easier. Lander and Bolstein (1989) introduced interval mapping based on the maximumlikelihood (ML) approach for the first time to detect the effect as well as the location of a QTL within an interval flanked by two DNA-based markers available on the genetic map. Initially, interval mapping using ML, being computationally demanding, regression approach of interval was proposed by Haley and Knott (1992). Simple interval mapping ignores the effect of the background. This problem has been addressed in composite interval mapping, which makes use of a subset of markers to be used as cofactors (Zeng 1993). An improved version of CIM is inclusive composite interval mapping (ICIM), that retains all the advantages of CIM while providing a better control over sampling variance and avoiding complicated selection of marker covariates (Li et al. 2007). Multiple interval mapping (MIM) which is an extension of interval mapping to multiple QTL was introduced, which is more powerful and accurate than CIM (Kao et al. 1999). MIM helps in simultaneous estimation of multiple QTL with epistasis. Software packages that utilize the above methods for QTL analysis using the bi-parental mapping population are QTL Cartographer, QTL Network, and R/qtl (Table 9.4).

9.6

Challenges in QTL/gene Mapping Methods and Future Directions to Overcome Them in Jute

9.6.1 Mapping Population In the QTL mapping experiments, different types of bi-parental mapping populations including F2, backcrosses (BC), doubled haploids (DH),

134

M. Das et al.

Table 9.3 List of major QTLs detected in various QTL mapping studies in Jute Trait

QTL

LOD

Linkage group

Position

Flanking markers/nearest marker

Phenotypic variance

References

Green weight

QGw.ccsu1.1 QGw.ccsu1.3

3.0992 3.7985

1 1

6.01 52.21

MJM659MJM895 MJM631MJM1265

13.04 13.51

Das et al. (2012b)

No. of nodes

QNn.ccsu1.3 QNn.ccsu6.1

2.2– 3.37 2.997

1 6

52.21 16.01

MJM631MJM1265 MJM1084MJM1134

7.51–12.85 17.31

Plant height

QPh.ccsu1.1

3.2316

1

2.01

MJM659MJM895

10.77

Basal diameter

QBd.ccsu1-3

2.992– 4.33

1

52.21

MJM631MJM1265

11–14.78

Middle diameter

QBd.ccsu1-3 QMd.ccsu1.3 QMd.ccsu3.1 QMd.ccsu3.3

1.96– 2.07 4.1589 3.0191 2.8306

2 1 3 3

100.51 52.21 6.01 94.01

MJM1267MJM051 MJM631MJM1265 MJM47MJM238 MJM1033MJM1139

21.36– 34.82 14.1 12.99 36.52

Top diameter

QTd.ccsu2.4

2.6169

2

136.71

MJM051MJM1262

37.73

Fibre weight

QFw.ccsu1.1

2.409– 5.0231

1

6.01

MJM659MJM895

9.57–20.62

Stick weight

QSw.ccsu1.1

2.159– 4.461

1

6.01

MJM659MJM895

7.6–16.23

Fibre fineness

QFf.ccsu5.3

2.404– 2.965

5

99.01

MJM1182MJM1150

8.31–10.56

Fibre fineness

qFF_l3_1 qFF_l3_2

5.07 4.48

3 3

19.2 69.661

MJM722 MJM667

58.707 13.2

Fibre yield

qFY_l1

3.74

1

37.7

MJM650

12.2

Tensile strength

qTS_l1

3.0

1

0.00

MJM644

11.0

Green biomass yield

qGBY_l2

3.93

2

113.031

MJM581

21.5

Number of nodes

qNN_l1

3.90

1

81.188

MJM679

16.6

Plant height

qPH_l7

3.40

7

4.00

MJM305

11.8

Stem diameter base

qSDB_l2

4.36

2

111.031

MJM581

12.0

Topdar et al. (2013)

(continued)

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Molecular Linkage Mapping: Map Construction …

135

Table 9.3 (continued) Trait

QTL

LOD

Linkage group

Position

Flanking markers/nearest marker

Phenotypic variance

Stem diameter mid

qSDM_l3 qSDM_l7

3.71 3.78

3 7

60.478 16.058

MJM722 MJM500

10.8 12.7

Stem diameter top

qSDT_l3_2 qSDT_l5

3.98 3.14

3 5

60.478 217.152

MJM722 MJM668

11.3 12.0

Wood yield

qWY_l5

4.2

5

192.744

MJM663

25

Fibre content

qFC-l1

4.7

1

40.2

Co_Sb0237

10.6

Stem-base diameter

qSBD-l1 qSBD-l2-2

5.6 5.8

1 2

40.2 26.9

Co_Sb0237 Co_Sb0117

10.3 10.3

Kundu et al. (2015)

Plant height

qPH2.3

7.2

2

225.5

Marker595Marker17742

15.63

Tao et al. (2017)

Salt tolerance

qJST-1 Under salt stress 4.1 4.2

4 4

19.31 19.31

mk5633mk6723 mk6160mk6484

11.81 19.61

Yang et al. (2019)

140 mM 160 mM

recombinant inbred lines (RIL), and nearisogenic lines (NIL) have been used (Fig. 9.1). However, there are several limitations of using bi-parental mapping populations in mapping genes including less recombination events occurring during the development of these populations and dependency on the phenotypic diversity of the two parents that may account for only small part of the genetic variation in the species. In order to overcome the limitations of the bi-parental population in QTL mapping of crops, multi-parent mapping populations like the nested association mapping (NAM) and multiparent advanced generation intercross (MAGIC) populations can be utilized in jute. The genetic diversity of multiple parents will eventually result to a population with large phenotypic diversity, thus making it suitable for high

References

resolution QTL mapping. NAM population is an excellent multi-parent population design (Yu et al. 2008) that was used for the genetic dissection of several important traits in different crop plants. The NAM population provides a very high resolution and power for detecting QTL due to combination of several highresolution bi-parental populations in one large population. On the other hand, in the MAGIC populations prior to the construction of the inbred lines, inter-mating multiple inbred founders are used for multiple generations and this improves the accuracy of QTL detection (Xu et al. 2017). This makes the MAGIC population very important in the dissection of complex traits and in improving breeding populations which can be employed in the future breeding programmes in jute.

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M. Das et al.

Table 9.4 Software for QTL mapping in crop plants including jute Software

Features

Operating system

URL

References

EBEN

• Provides the Empirical Bayesian Elastic Net for handling multicollinearity in generalized linear regression models • Enables selection of relevant variables and estimation of the corresponding non-zero effects by the help of the grouping effects

Unix/Linux, Mac OS, windows

https://cran.rproject.org/web/ packages/EBEN/ index.html

Huang et al. (2015)

FastQTL

• It is fast; with a permutation scheme relying on Beta approximation. There is need to perform millions of permutations to reach low significance levels • Association testing is implemented without qualitative/quantitative covariates • Only standard file formats are used and easy-to-use options implemented

Unix/Linux, Mac OS

http://fastqtl. sourceforge.net/

Ongen et al. (2016)

FlexQTL

• Achieved via Markov chain Monte Carlo (MCMC) simulation algorithms that is based on the Bayesian analysis theory • Evaluates the position and QTL numbers, effect size and individuals’ genotypes for each QTL • Evaluates the Identity by decent (IBD) probability at a specific chromosomal position

Unix/Linux

https://www.wur.nl/ en/show/FlexQTL. htm

Hern´andez Mora et al. (2017)

HpQTL

• It is useful in case of highly polygenic genetic backgound for QTL analysis using its R package • Applies the linear model (LM), linear mixed model (LMM), linear mixed model with specific genetic similarity matrix for each chromosome (LMML1O)

Unix/Linux, Mac OS, windows

https://github.com/ simecek/HPQTL

Sun et al. (2017)

Ici Mapping

• Useful for construction of linkage maps in bi-parental populations and also enables removal of redundant markers • Construction of consensus map from multiple linkage maps that share common markers and also useful in mapping of segregation distortion loci • Additive, dominant, and digenic epistasis gene mapping and analysis of QTL-by-environment interaction • QTL mapping in NAM populations

Windows

http://www. isbreeding.net/ software/? type5detail&id518

Li et al. (2007)

lme4qtl

• The R package lme4 implements major LMM features using sparse matrix methods • Also useful for association studies in situations where multiple covariance matrices need to be modeled, which is not covered by many genome-wide association study (GWAS) softwares

Unix/Linux, Mac OS, windows

https://github.com/ variani/lme4qtl

Ziyatdinov et al. (2018)

(continued)

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Molecular Linkage Mapping: Map Construction …

137

Table 9.4 (continued) Software

Features

Operating system

URL

References

Map Manager QTX

• Includes functions for mapping both Mendelian and quantitative trait loci • QTX supports the use of fixed marker distances specified by the user • optional methods are available for linkage and distance calculations that are not affected segregation distortion

Mac OS, windows

http://mapmgr. roswellpark.org/ mmQTXhtml

Manly et al. (2001)

MapQTL

• Inclusion of Haley and Knott regression approximation to maximum likelihood interval and MQM mapping that enabled higher speed and reduced use of RAM memory • Simple experimental design (e.g., blocking) and covariates can be analyzed jointly with interval and MQM mapping • Based on a common (integrated) linkage map, traits observed in multiple populations can be studied combined over the populations with interval and MQM mapping

Windows

https://www. kyazma.nl/index. php/mcMapQTL

Ooijen 2004

Qgene

• It is an open-source Java program that runs on any computer operating system and intended for doing comparative analyses of QTL mapping data sets • Written with a plug-in architecture for ready extensibility

Unix/Linux

http://www.qgene. org/qgene/index. php

Joehanes and Nelson (2008)

QTL Network

• It can simultaneously map quantitative trait loci (QTL) with individual effects, epistasis and QTL–environment interaction • It is able to handle data from F2, backcross, recombinant inbred lines and double-haploid populations, as well as populations from specific mating designs (immortalized F2 and BCnFn populations) • Facilitates the analysis results with a visualization environment, which can help in better understanding of the genetic architecture of complex traits

Unix/Linux, Mac OS, windows, web

http://ibi.zju.edu.cn/ software/ qtlnetwork/ webservise/

Yang et al. (2008)

WinQTL Cart

• QTL mapping in cross populations from inbred lines. The powerful graphic tool of WinQTLCart also presents and summarizes the mapping results • Includes the modules found in QTL Cartographer, and provides a graphical interface to its features

Unix/Linux, windows

http://statgen.ncsu. edu/qtlcart/index. php

Wang et al. (2006)

QTLseqr

• Useful for QTL mapping using NGS Bulk Segregant Analysis by utilizing its R package

Unix/Linux

https://github.com/ bmansfeld/QTLseqr

Mansfeld and Grumet (2018) (continued)

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M. Das et al.

Table 9.4 (continued) Software

Features

Operating system

URL

References

• Recognizes QTL by the QTL-seq and G’ approaches that enables identification and assessment of the statistical significance of QTL • Enables import and filtration of SNP data and calculation of SNP distributions relative allele frequencies, G’ values, and log10 (p-values) and also allows identification and plotting of QTL R/qtl

• Implemented as an add-on package for the freely available and widely used statistical language/software R • Useful for estimation of genetic maps, identification of genotyping errors, and performing single-QTL genome scans and two-QTL, two-dimensional genome scans, with the help of interval mapping, Haley-Knott regression, and multiple imputation

Unix/Linux, Mac OS, windows

http://www.rqtl.org/

Broman et al. (2003)

RASQUAL

• A novel statistical approach for association mapping that models genetic effects and accounts for biases in sequencing data in a single, probabilistic framework • RASQUAL substantially improves finemapping accuracy and sensitivity of association detection over existing methods in RNA-seq, DNaseI-seq and ChIP-seq data

Unix/Linux, Mac OS, windows

https://github.com/ dg13/rasqual

Kumasaka et al. (2015)

Solarius

• Performs linkage and association mapping of the quantitative trait loci (QTLs) in pedigrees of arbitrary size and complexity • Allows the user to exploit the variance component methods implemented in SOLAR • Automates such routine operations as formatting pedigree and phenotype data • Enables parallel computing of the linkage and association analyses that makes the calculation of genome-wide scans more efficient

Unix/Linux, Mac OS, windows

https://github.com/ ugcd/solarius

Ziyatdinov et al. (2016)

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Molecular Linkage Mapping: Map Construction …

Development of the mapping populations like the recombinant inbred lines (RILs) takes a longer time which may be considered as another limitation in the QTL mapping experiments. Therefore, in order to accelerate the breeding process and generation advancement, a technique called speed breeding was proposed recently (Hickey et al. 2019). As the name suggests, speed breeding relies on use of environmentcontrolled growth chambers equipped with artificial lights which can accelerate the plant growth and development so that multiple generation of crop plants can be advanced per year (Ahmar et al. 2020). Speed breeding technique can be employed in the development of a number of mapping populations for genetic mapping projects in jute in a relatively shorter period of time.

9.6.2 Jute Phenomics Lack of precise phenotypic data is one of the major limitations in the progress of molecular breeding in jute. In the last decade, invasive or destructive methods of phenotyping were replaced by the high-throughput precise nondestructive methods of phenotyping (Mir et al. 2015, 2019). The advancement made has revolutionized crop phenomics and allowed screening of large germplasm (mapping populations, core collections, and breeding material) with high precision/accuracy with less efforts, time, and labour. These advances not only have generated huge amount of information, but has also necessitated use of novel techniques for the analysis of the big data. Phenomics is becoming popular in many crops with the recent advances in computing, robotics, spectroscopy, and image analysis. Phenomics has also been used for the study of plant responses to various abiotic stresses including drought, heat, cold tolerance, salinity, and nutrient-starving. For drought tolerance, trait phenotyping either in glasshouse or in field have been conducted and approaches like osmotic balance in hydroponics to conveyer systems in glass house to rainout shelters in the field have been used very extensively. A number of state-of-the-art international phenomics

139

centers/facilities have been developed for precisely recording high-throughput phenotyping data in cost effective manner. Some of the important phenomics facilities include the Plant Accelerator in Adelaide, Australia (http://www. plantaccelerator.org.au/), High Resolution Plant Phenomics Centre (http://www.plantphenomics. org/HRPPC) in South Australia, the Jülich Plant Phenotyping Centre (http://www.fz-juelich.de/ ibg/ibg-2/EN/methods_jppc/methods_node.html) in Jülich, Germany, Leibniz Institute of Plant Genetics and Crop Plant Research in Gatersleben, Germany and the National Plant Phenomics Centre (http://www.phenomics.org.uk/ temp-site/about.html) in the UK to name a few (Gupta et al. 2012; Mir et al. 2015, 2019). Keeping this in view, the phenomics platforms should be used to record data in highthroughput/precise fashion for variety of traits in jute and the trait evaluation may lead to the genetic dissection leading to precise gene discovery for several traits including root system architecture traits, seed shape, osmotic tolerance, biotic and abiotic stresses and biomass traits, etc.

9.6.3 High-Density Genotyping The advances in genomics has not only resulted in development of large numbers of markers in important crops and in crops once considered orphan and resource poor crops. As sequencing cost continues to decrease, researchers are developing novel methods that leverage nextgeneration sequencing (NGS) platforms for genotyping. Therefore numerous types of molecular markers including SSR, diversity arrays technology (DArT), single nucleotide polymorphism (SNP), different SNP platforms, micro-array based markers, GBS, InDel markers, etc. are available in various crops (Gupta et al. 2008, 2013; Mir et al. 2013; Mir and Varshney 2013; Tyagi et al. 2019, 2021; Kumar et al. 2021). Several genotypic platforms including Kompetitive Alelle Specific PCR (KASP) assays, GoldenGate assays, Vera-code assays, and 60 K SNP chips using Affymetrix SNP platform and Axiom SNP array with thousands of SNPs

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uniformly distributed across the genome are available now (Gupta et al. 2008, 2013). These marker resources have been used in the study of genetic diversity, population structure, development of genetic maps and QTL mapping/GWAS; meta-QTL analysis, QTL validation for key traits in all major food crops (Mir et al. 2012a, b; Mohan et al. 2009; Gupta et al. 2010a, b; Tyagi et al. 2014a; Jaiswal et al. 2016; Tyagi et al. 2019; Kumari et al. 2019). The genes/QTLs once identified are being deployed into molecular breeding programs aimed at enhancing targeted traits in different crop plants through markerassisted selection (MAS), marker-assisted recurrent selection (MARS), and genomic selection (GS)/genome-wide selection (GWS) (Gupta et al. 2010a, b; Mir et al. 2015; Tyagi et al. 2014b). It is expected that the improved versions of nextgeneration crop varieties could be developed with enhanced quality traits, better yield, and disease resistance. Keeping this in view, efforts shall be made in near future to make use of recently emerged high-throughput and ultrahigh-throughput genotyping platforms for genotyping genetic resources in jute crop. This will facilitate jute crop improvement at a very past pace.

M. Das et al.

1998a, b). MCQTL software to perform QTL mapping in multi-cross designs using CIM and iterative QTL mapping was developed by Jourjon et al. (2005). The R package HAPPY for fine QTL mapping developed by Mott et al. (2000) was used to detect QTL in MAGIC population of A. thaliana (Kover et al. 2009). In 2011, R package, mpMap was developed for QTL mapping of multi-parent RILs that accommodates linear mixed models (Huang and George 2011). All these methods are limited to IM and CIM. Later, Whole-genome average interval mapping (WGAIM) was introduced, that was modified for multi-parent populations (MPWGAIM). MPWGAIM was found to be superior than CIM and uses the probability of inheriting founder alleles (Verbyla et al. 2012, 2014). Recently, a random-model approach for MAGIC populations by assuming founder effects at each locus to be random effects following a common normal distribution was developed by Wei and Xu (2016). This approach was found to be more powerful and substantially faster than MPWGAIM which can be employed in the future QTL mapping methods in Jute.

9.6.5 Large-Scale Meta-Analysis 9.6.4 Statistical Analysis QTL mapping is done in both bi-parental and multi-parent mapping populations. To overcome the limitations of the bi-parental populations as discussed in the earlier section, use of multiparent population has been proposed in several studies. Though, analysis of multi-parent populations has much in common with that of biparental population, it cannot provide information about the parental origin of alleles from the observed marker information. Hence, in multiparent mapping, methods used for bi-parental mapping cannot be employed. The first interval mapping approach for a four-way cross design based on the multiple linear regression was proposed by Xu (1996). It was demonstrated later that fixed and random model-approaches perform equally well for multi-parent mapping (Xu

The sample size used for a QTL mapping study determines the statistical power to detect a QTL. Performing a single study using a large sample may prove costly; therefore to overcome this limitation meta-analysis has been used to combine results from multiple studies to increase the power of genetic mapping (Han and Eskin 2012). This approach is a promising method for detecting new genetic loci in crop plants. Random-effects models have been used to deal with the problem of heterogeneity due to genetic and environmental factors. The random effectsbased meta-analysis (Meta-G
E) can be applied to identify gene-by-environment interactions by treating the interactions as heterogeneity (Kang et al. 2014). This method can be useful for the identification of loci involved in gene by environment interactions in the future studies in jute.

9

Molecular Linkage Mapping: Map Construction …

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Jute Genome Sequencing: An Indian Initiative

10

Nagendra Kumar Singh and Debabrata Sarkar

Abstract

We assembled using merged overlapping sequence reads (2
250 bp) from Illumina MiSeq platform a high-coverage draft genome (GenBank: LLWS00000000.1) of pioneering Indian tossa jute variety JRO-524 (Corchorus olitorius cv. Navin). The JRO-524 genome assembly that comprises 52,371 contigs (total 377,376,943 bp), with an N50 size of 16,573 bp, was 92.7% complete as assessed by Benchmarking Universal Single Copy Orthologs (BUSCO) scores, which is comparable to the tossa jute cv. O-4 genome (93.7%) sequenced by Bangladesh (GenBank: AWU E00000000.1). Based on RNA-Seq evidence,

The original version of this chapter was revised (two missing references have been included, the caption for Fig 10.3 has been corrected and some minor corrections in the text have been incorporated). The correction to this chapter can be found at https://doi.org/10.1007/978-3030-91163-8_22

N. K. Singh (&) Rice Genome Laboratory, ICAR-National Institute for Plant Biotechnology (NIPB), Pusa, New Delhi 110 012, India

we predicted in the JRO-524 genome 47,035 protein-coding genes with an average length of 3220 bp covering a total length of 209.4 Mbp and annotated 37,959 of these genes, most of which were classified into molecular functions followed by biological processes. Our annotation completeness (83.9%), as assessed by BUSCO scores, was also comparable to that of the O-4 genome (81.9%). With 187.1 Mbp of repeat elements, the JRO-524 genome was characterized by rather high frequency of repetitive sequences within the Malvids, particularly long terminal repeat (LTR) retrotransposons. Mapping seven chromosome-level pseudomolecules, we showed that C. olitorius has close syntenic relationships with cacao and diploid cotton genomes, though collinearity was less conserved at the chromosome level. We used the JRO-524 genome to construct a genomeintegrated genetic map of tossa jute, with a set of 382 genomic (RAD) and transcriptderived genic-SNP markers over the seven linkage groups. We discuss the translational limitations of this draft genome and propose further research to develop a high-quality reference genome of tossa jute.

D. Sarkar Biotechnology Unit, Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres (CRIJAF), Barrackpore, Kolkata, West Bengal 700 121, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022, corrected publication 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_10

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10.1

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Introduction

Perhaps no other fibre crop is as versatile as jute that comprises two cultivated species, viz., Corchorus capsularis (white jute) and C. olitorius (dark or tossa jute), with the latter occupying more than 90% acreage of jute-growing areas in the world (Sinha et al. 2011). High yielding potential, improved tensile strength and suitability for crop rotation with transplanted paddy were mainly instrumental for the gradual predominance of tossa jute in intensive agriculture in India since the 1970s, almost coincident with the ‘Green Revolution’. Nevertheless, the phenomenal success of tossa jute owed much to the successful development of improved varieties resistant to premature flowering under early sowing. Otherwise, jute ‘would have gone the indigo way’ as Karmakar et al. (2008) rather correctly assessed. Despite it producing one of the strongest vegetable fibres with diversified engineering and industrial usage (Rowell and Stout 2007), there are several biological constraints—such as narrow genetic base, reproductive isolation from its counterpart under natural habitats, varying degrees of sexual incompatibilities, photoperiod sensitivity, absence of cytoplasmic male sterile (CMS)restorer lines and precocious reproductive behavior—that restrict the scope of its genetic improvement by conventional breeding approaches. With rapid climate change particularly over the past decade, tossa jute is gradually becoming more susceptible to premature flowering under early sowing, resulting in progressive deferment of its sowing date and significant yield losses. Its biological yield has almost reached a plateau, and conventional breeding approaches based on pedigree selection with restricted access to African germplasm have proved ineffective in developing improved varieties with quality fibre. With this background, we initiated jute genomics early in the last decade, with a primary objective to generate genomic resources, both biological and genome sequence, that could be used not only to address fundamental biological issues and genetically dissect the complex

agronomic traits including bast fibre quality, but also to implement genomics-assisted breeding (Sarkar et al. 2016). Since most of our jute nucleotide sequences were generated by de-novo approaches using next-generation sequencing (NGS) platforms (see Sarkar et al. 2016 for a comprehensive review and other chapters of this volume), we concurrently initiated the sequencing of a leading Indian tossa jute variety JRO524 (Navin) and released its draft genome sequence in 2017 (Sarkar et al. 2017). With the availability of the JRO-524 draft genome, there is a renewed impetus to the application of translational genomics in genetic improvement of tossa jute, though it still continues to be rather recalcitrant for regeneration in vitro (Majumder et al. 2020). Here, we have argued for the sequencing of tossa jute cv. JRO-524 genome, shown how revalidation of jute genome size has accelerated the sequencing effort, described the genomic architecture of its draft sequence and evaluated the genome-assembly and annotation completeness in comparison to the draft genomes of both the cultivated jute species sequenced by Bangladesh (Islam et al. 2017). We briefly describe how we used the JRO-524 genome information to construct a genome-integrated genetic map of tossa jute. Further, we raise the key issue underlying the translational limitations of the draft genome and propose a way-forward to upgrading it to a chromosome-level reference genome in the near future.

10.2

Why JRO-524 Genome of Tossa Jute?

JRO-524 (Navin) is one of the most popular tossa jute varieties (Fig. 10.1) developed in 1977 from a cross between JRO-632—a local selection susceptible to premature flowering, and Sudan Green—an exotic African germplasm with complete resistance to premature flowering (Karmakar et al. 2008). With durable resistance to premature flowering under early sowing (midMarch) and an average bast fibre yield of 34–36 q ha−1, JRO-524 has revolutionized the tossa jute

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147

Fig. 10.1 Corchorus olitorius cv. JRO-524 growing in the demonstration plot at ICAR-Central Research Institute for Jute and Allied Fibres (CRIJAF), Barrackpore, Kolkata, India ( Source CS Kar)

production in India (Kar et al. 2010) and still continues to be the most popular variety even more than 40 years after its release. Corchorus olitorius originated in east Africa, but was dispersed to India together with many other African crops in the prehistorical times (Kundu et al. 2013) followed by its domestication for bast fibre production (Sarkar et al. 2019). Besides highyield and desired agronomic traits including bast fibre qualities, JRO-524 is an admixture of African as well as Indian gene pools. In contrast, tossa jute variety O-4 sequenced by Bangladesh (Islam et al. 2017) is a local selection from a landrace (Huq et al. 2009), while the variety Kuan Ye Chang Guo sequenced by China (Zhang et al. 2021) is a cross between a local selection Guang Feng Chang Guo and Bachang 4 —an introduction from Pakistan (Zhang et al. 2019). Thus decoding of the JRO-524 genome

was of potential interest in capturing the polymorphic sequences (genomic diversity) of both the African and Indian gene pools that essentially constitute the population structure of tossa jute (Sarkar et al. 2019). In this context, it must be noted that presence/absence variation and other technical difficulties render it virtually impossible to assemble the complete genome of a species from a single individual (Lu et al. 2013).

10.3

Genome Size

Till a decade back, the reported genome size (1C) estimates of both the cultivated jute species continued to be highly inflated in a range of 1100–1350 Mbp, with an average of 1250 Mbp (Samad et al. 1992; Mir et al. 2009). We reestimated and validated the genome size of the

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cultivated jute species including Asiatic Corchorus species using flow cytometry (Sarkar et al. 2011), which was concurrently corroborated by Benor et al. (2011). Using CRBC as an internal standard, JRO-524 genome was estimated to be 329 Mbp (Fig. 10.2A), while Sudan Green and JRO-632 genomes, the parents of JRO-524, were estimated to be 315 Mbp and 332 Mbp, respectively (Sarkar et al. 2011; Saha et al. 2014). Building a predictive regression model based on mean 1C genome size and mean total haploid chromatin length (THCL), Saha et al. (2014) reported a good agreement (r2 = 0.85; P  0.001) between the THCL-transformed and

a

b

flow cytometry-derived genome size estimates in Corchorus species (Fig. 10.2B). However, the draft genome sequence of JRO-524 yielded a Kmer-analyzed haploid genome size estimate of 415 Mbp (Sarkar et al. 2017). Similarly, Islam et al. (2017) reported a genome size estimate of 448 Mbp for C. olitorius cv. O-4, whereas Zhang et al. (2019) assembled 361 Mbp of sequence for C. olitorius cv. Kuan Ye Chang Guo, with a genome size estimate of 387 Mbp based on K-mer analysis of high-quality Illumina reads (Zhang et al. 2021). Incidentally, though the flow cytometry-based haploid genome size of C. capsularis cv. CVL-1 was reported to be 274 ± 10.7 Mbp (Akashi et al. 2012), its draft genome sequence yielded a K-mer-analyzed haploid genome size estimate of 404 Mbp (Islam et al. 2017). Taken together, it is not entirely unusual because K-mer estimates of genome size are often on the higher side as compared to that derived from flow cytometry (Guo et al. 2015). Genome size estimates derived from published genome assemblies are sometimes 2.5- to 3.0-fold higher than that estimated by flow cytometry; therefore Kooij and Pellicer (2020) have recently recommended to use flow cytometry for pre-calibrating the genome assembly pipelines in order to obtain correct estimates of the K-mer-analyzed genome size.

10.4

Fig. 10.2 Genome size estimation of Corchorus olitorius cv. JRO-524 by flow cytometry (FACSCalibur, Beckton Dickinson) using propidium iodide-stained nuclei and CRBC as an internal standard (a) and a comparison between flow cytometry-based and THCL-transformed monoploid genome sizes (Saha et al. 2014) in Corchorus species (b). Acronyms: aest, C. aestuans; caps, C. capsularis; CRBC, chicken red blood cell; depr, C. depressus; fasc, C. fascicularis; olit, C. olitorius; pcap, C. pseudocapsularis; poli, C. pseudo-olitorius; trid, C. tridens; tril, C. trilocularis; urti, C. urticifolius

De-Novo Genome Assembly

We used Illumina MiSeq platform to sequence the JRO-524 genome, generating 52,507,986 overlapping 2
250 bp pair-end raw reads (15.65 Gbp; SRA: SRX1506532), which were merged into 24,996,514 high-quality reads, with an average read length of 450 bp and genome coverage of 31.32
(Table 10.1). The Newbler-assembled genome (GenBank: GCA_002141455.1; DDBJ/ EMBL/GenBank accession: LLWS00000000.1; BioProject: PRJNA278717; BioSample: SAMN0 4160039) comprised 52,371 contigs with a total assembly size of 377,376,943 bp, average contig size of 7206 bp and N50 size of 16,573 bp. This de-novo assembly covered 90.8% of the K-meranalyzed genome size of JRO-524. Benchmarking

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149

Table 10.1 Genome assembly statistics for Corchorus olitorius cv. JRO-524a

a

Item

Statistics

Raw reads

52,507,986

High-quality merged reads

24,996,514

Number of assembled contigs

52,373

Size of assembled contigs (bp)

377,376,943

Longest contig (bp)

177,749

Shortest contig (bp)

500

Number of contigs > 1 kb

41,086

Number of contigs > 10 kb

11,958

Number of contigs > 100 kb

38

Mean contig size (bp)

7206

Contig N50 (bp)

16,573

GenBank accession LLWS00000000.1 (assembly: GCA_002141455.1)

Fig. 10.3 Benchmarking Universal Single Copy Orthologs (BUSCOs) scores of genome assemblies and corresponding annotations of Corchorus olitorius cv. JRO-524 (GenBank: LLWS00000000.1), C. olitorius cv. O-4 (GenBank: AWUE00000000.1) and C. capsularis cv. CVL-1 (GenBank: AWWV00000000.1). BUSCO

analyses were performed using the linage dataset eudicotyledons_odb10 that comprises 2121 BUSCOs across 40 species. C, complete BUSCOs; S, complete and singlecopy BUSCOs; D, complete and duplicated BUSCOs; F, fragmented BUSCOs; M, missing BUSCOs

Universal Single Copy Orthologs (BUSCO v4.1.4) analysis (Simão et al. 2015), using the eudicotyledons_odb10 lineage dataset (eukaryota, 2017–12-01) and Theobroma cacao (cacao) as an AUGUSTUS (Hoff and Stanke 2013) species, showed the presence of 92.7% complete, 89.6% complete single-copy, 3.1% complete duplicated, 3.0% fragmented and only 4.3% missing BUSCOs

(Fig. 10.3). We compared the completeness of our JRO-524 genome assembly with that of C. olitorius cv. O-4 and C. capsularis cv. CVL-1 (henceforth O-4 and CVL-1) released by Bangladesh (Islam et al. 2017). The O-4 genome assembly completeness was comparable to that of JRO524, with 93.7% complete, 91.5% complete single-copy, 2.2% complete duplicated, 2.1%

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fragmented and 4.7% missing BUSCOs. By comparison, the genome-assembly completeness of CVL-1 was relatively better than that of both JRO-524 and O-4, with 95.7% complete, 93.2% complete single-copy, 2.5% complete duplicated, 1.9% fragmented and only 2.4% missing BUSCOs (Fig. 10.3). Genome assembly gaps that result from an inherent difficulty associated with assembling GC-rich and repeat-rich regions (genomic ‘dark matter’) may be attributed to the differences in genome-assembly completeness between the two cultivated jute species (Peona et al. 2021). This could further be reinforced by almost similar proportions of genome-assembly completeness in both the cultivars of C. olitorius (JRO-524 and O-4), although they were not only characterized by disparate pedigrees, but sequenced and assembled using entirely different approaches including NGS platforms and software (Islam et al. 2017; Sarkar et al. 2017). The C. olitorius genome was indeed characterized by rather high frequency of repetitive sequences (Sarkar et al. 2017; also see below). Moreover, with current sequencing technologies, short-read sequence data are much more prone to being confounded when the genome is characterized by repetitive regions with numerous identical sequence tracts (Collins 2018).

10.5

Genome Annotation Using RNA-Seq Evidence

Though initially in the absence of RNA-Seq data we predicted gene models ab initio (Sarkar et al. 2017), the availability of 454 RNA-Seq reads of C. olitorius cv. Sudan Green (DDBJ/EMBL/ GenBank TSA: GFDJ00000000.1; SRA: SRR5145920; BioProject: PRJNA278717; BioSample: SAMN06199046), one of the parents of JRO-524, allowed us to revise the JRO524 genome annotation using evidence from RNA-Seq alignments. We constructed the JRO524 repeat library according to Campbell et al. (2014) by searching for miniature inverted repeat transposable elements (MITEs) and long terminal repeat (LTR) retrotransposons using MITEHunter v11-2011 (Han and Wessler 2010) and

LTRharvest (Ellinghaus et al. 2008)-LTRdigest (Steinbiss et al. 2009), respectively. Next, we identified and collected most of the repetitive sequences de novo using RepeatModeler v1.0.10 (Flynn et al. 2020). Relatively recent LTR retrotransposons (  99% similarity) were first collected followed by the collection of older ones (85% similarity) while identifying and removing the LTRs with nested insertions (with each other or other repeat elements) in order to avoid misclassification and building exemplars (representative LTR sequences) to reduce redundancy (complete computational protocols together with Unix terminal commands are available as a Figshare entry https://doi.org/10.6084/m9.figshare. 14812848.v1). We soft-masked the JRO-524 genome for all repeats using RepeatMasker v4.0.7 (http://www.repeatmasker.org), and RNASeq reads of C. olitorius cv. Sudan Green (see above) were aligned to both masked and unmasked genomes by using HISAT2 v2.1.0 (Kim et al. 2015). Genes were predicted by WebAUGUSTUS (Hoff and Stanke 2013) as implemented in Blast2GO/OmicsBox v1.4.11 (Conesa et al. 2005), with intron hints collated from RNA-Seq alignments and cacao as the AUGUSTUS species due to its closest synteny with C. olitorius (Kundu et al. 2015). We predicted a total of 47,035 protein-coding genes from the soft-masked genome, with an average length of 3220 bp and 25,108 sequence regions covering a total length of 209.4 Mbp (Table 10.2). Interestingly, we predicted the same numbers of genes including the total numbers of CDSs, exons and mRNAs when the genome was not soft-masked for repetitive elements. Even the distributions of CDSs, exons and transcripts per gene, as retrieved by the R (R Core Team 2020) package GenomicFeatures v1.24.4 (Lawrence et al. 2013), were identical irrespective of repeat-masking of the genome prior to gene prediction (Fig. 10.4). Thus, our results suggested high effectiveness of the AUGUSTUS-based gene prediction using evidence from RNA-Seq alignments even when the genome was not masked for repetitive sequences. Expectedly, more genes were predicted in our JRO-524 genome than in the O-4 and Kuan Ye

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Table 10.2 Comparative gene-prediction statistics for soft-masked and unmasked genomes of Corchorus olitorius cv. JRO-524a based on evidence from RNA-Seqb alignments

151

Featurec

Unmasked

Soft-masked

Sequence regions

25,108

25,108

Total length (bp)

209,390,614

209,390,614

Genes

47,035

47,035

Protein-coding genes

47,035

47,035

mRNAs

47,434

47,434

Protein-coding mRNAs

47,434

47,434

Exons

217,043

217,043

CDSs

209,879

209,879

Introns

162,445

162,445

a

The same as in Table 10.1 RNA-Seq reads of C. olitorius cv. Sudan Green (GenBank TSA: GFDJ00000000.1 and SRA: SRR5145920) were used for alignment c Genes were predicted using WebAUGUSTUS (Hoff and Stanke 2013), with Theobroma cacao as the closest species of C. olitorius b

Fig. 10.4 Histograms of features per gene predicted in soft-masked and unmasked Corchorus olitorius cv. JRO524 genomes (GenBank: LLWS00000000.1) and

retrieved as T
Db objects with the R package GenomicFeatures v1.24.4 (Lawrence et al. 2013)

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Fig. 10.5 Gene ontology (GO) classification of genes annotated in Corchorus olitorius cv. JRO-524 using Blast2GO/OmicsBox and WEGO 2.0. A total of 35,575

genes were assigned to three main GO categories and 59 sub-categories

Chang Guo genomes (Islam et al. 2017; Zhang et al. 2021). It is not unusual because higher gene numbers are known to be positively correlated with genome assembly size, which in turn depends on the genome coverage and software used to assemble the genome (Kooij and Pellicer 2020). Incidentally, with assembly sizes of 334.91 Mbp (GenBank: GCA_001974825.1) and 361 Mbp (Zhang et al. 2021), the O-4 and Kuan Ye Chang Guo genomes are shorter than the JRO-524 genome by 42.47 Mbp and 16.38 Mbp, respectively. We annotated the genes using the functional annotation pipeline (blastx, GO mapping, annotation, InterProScan and GO Slim) as implemented in Blast2GO/OmicsBox v1.4.11 (Götz et al. 2008) and classified the GO functional annotations using WEGO 2.0 (Ye et al. 2018). Of the 37,959 annotated genes, the largest number of genes was classified with molecular functions (34,394) followed by biological processes (30,627) and cellular components (17,732), with substantial overlaps and ‘cell’, ‘cell part’,

‘organelle’, ‘membrane’, ‘membrane part’, ‘catalytic activity’, ‘binding’, ‘cellular process’, metabolic process’, ‘biological regulation’ and ‘regulation of biological process’ being the predominant GO functional groups (Fig. 10.5). The BUSCO scores for annotation completeness of the JRO-524 genome were as follows: 83.9% complete, 79.8% complete single-copy, 4.1% complete duplicated, 6.3% fragmented and 9.8% missing BUSCOs (Fig. 10.3). In contrast, the O4 annotation (Islam et al. 2017) showed only 81.9% complete, 79.2% complete single-copy, 2.7% complete duplicated, 8.3% fragmented and 9.8% missing BUSCOs. However, the completeness of C. capsularis cv. CVL-1 annotation was higher (Islam et al. 2017), with 89.8% complete, 87.3% complete single-copy, 2.5% complete duplicated, 4.1% fragmented and 6.1% missing BUSCOs (Fig. 10.3). Higher annotation in CVL-1 is attributed to its comparatively higher coverage genome-assembly as compared to C. olitorius (JRO-524 and O-4). In this context, it is

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to be noted that the C. capsularis genome is relatively smaller in size than the C. olitorius (Benor et al. 2011; Sarkar et al. 2011; Islam et al. 2017; Zhang et al. 2021), and it is rather wellknown that genome size is the most important factor that greatly influences the outcome of genome assembly and annotation projects in terms of the amount of data required for completeness (Jung et al. 2020). Though we are not aware of any comprehensive study in plants yet, Lobb et al. (2020) have recently reported a significant correlation between genome size and annotation completeness in bacterial tree of life, with larger genomes being correlated with a higher fraction of unannotated proteins. With a total of 187,059,797 bp of repeat elements identified, the JRO-524 genome was characterized by rather high proportion of repetitive sequences (49.6%) as compared to 25.7% for its closest related species T. cacao (Argout et al. 2011). However, it was lesser than that reported for its second-closest species Gossypium raimondii (diploid cotton), which was characterized by 57.0% repetitive sequences (Wang et al. 2012). Though the O-4 genome was also reported to be characterized by more than 50% repetitive elements (Islam et al. 2017), Zhang et al. (2021) have recently reported as high as 59.3% repeat fraction in the Kuan Ye Chang Guo genome of C. olitorius. Further, the JRO-524 genome assembly was characterized by a higher proportion of retrotransposons (45.7%) than DNA transposons (5.5%). The LTR retrotransposons, particularly gypsy (34.3%) and copia (5.7%), were the most abundant classes. Molecular cytogenetic analyses combined with FISH karyotyping have earlier reported an abundance of LTR retrotransposons in both the cultivated jute species (Begum et al. 2013), which are characterized by different LTR-burst events (Zhang et al. 2021), with the occurrence of a more ancient LTR burst in C. capsularis (0.6 Mya) than in C. olitorius (0.4 Mya). Using Infernal v1.1.2 (Nawrocki and Eddy 2013) that queries the Rfam database (Kalvari et al. 2018), we identified a large number of non-coding RNA genes (ncRNAs) in the JRO-524 genome (Fig. 10.6). Besides tRNAs (802 genes) and

153

rRNAs (232 genes), the most abundant families of ncRNAs were snRNA, snoRNA, microRNA, splicing, cis-regulatory element, sRNA, intron, riboswitch, antisense and leader. Dominant classes of microRNAs identified were mir-166, mir-172, mir-399, MIR159, MIR169_2, MIR171_1 and MIR1122, while snoR71 was the most dominant snoRNA, cobalamin, histone3 and TwoAYGGAY were the most dominant cisregulatory elements, U6 the most dominant splicing and C4 the most dominant antisense RNA. Interestingly, cspA was the sole thermoregulator identified in the JRO-524 genome. For comparing the distribution of SSRs in the JRO-524 genome with its closely related species within the Malvids, we used GMATA v2.2.1 (Wang and Wang 2016) with default motif-unit settings (min length 2, max length 6 and mean repeat-times 5) and identified a total of 74,181 SRRs at a frequency of 197 SSRs/Mbp, with 82.7% di-, 14.3% tri-, 2.0% tetra-, 0.6% pentaand 0.5% hexa-nucleotide repeats (Fig. 10.7a). TA (28.9%) and AT (27.2%) were the most abundant SSR motifs followed by AG (4.9%), TC (4.5%) and CT (3.9%), while TA/TA (28.9%), AT/AT (27.2%), CT/AG (8.8%) and TC/GA (7.9%) were the most abundant grouped complementary motifs (Fig. 10.7b, c). Among the tri-nucleotide motifs, AAT/ATT was the most abundant class (2.5%) followed by ATA/TAT (1.8%), GAA/TTC (1.8%) and TTA/TAA (1.5%). The majority of SSRs were of 10 bp in length (41.9%) followed by 12 bp, 15 bp, 18 bp and 14 bp (Fig. 10.7d). We compared the distribution patterns of JRO-524 SSRs with that of CVL-1 (C. capsularis) and O-4 (C. olitorius) genomes and few other released Malvid genomes, namely, Arabidopsis thaliana, G. barbadense, G. harknessii, G. raimondii and T. cacao closely related to jute. Of all the genomes characterized, the frequency of SSRs was the highest in CVL-1 (234 SSRs/Mbp) followed by A. thaliana (215 SSRs/Mbp), O-4 (214 SSRs/Mbp) and T. cacao (210 SSRs/Mbp), while the lowest in G. harknessii and G. barbadense genomes (Table 10.3). Overall, we observed that the motif length and composition of SSRs were almost conserved, with relatively higher

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Fig. 10.6 Distribution of non-coding RNAs (ncRNAs) in Corchorus olitorius cv. JRO-524 genome. ncRNAs were identified using Infernal v1.1.2 (Nawrocki and Eddy 2013)

occurrence of AT motif in Gossypium genomes (34.7–39.7%). Motif-abundance pattern was similar in A. thaliana, Gossypium spp. and T. cacao. However, both the cultivated jute species were characterized by distinct motif-abundance patterns, with the CVL-1 (C. capsularis) pattern being more similar to the other Malvid genomes. The JRO-524 and O-4 genomes were characterized by similar motif length-distribution, composition and abundance.

10.6

Genome Synteny

Using the restriction site-associated DNA (RAD)SNP genetic map of tossa jute (Kundu et al. 2015), we constructed seven chromosome-level pseudomolecules of JRO-524 anchored with 501 RADSNP markers, with a mean size of 1,219,051 bp and N50 of 2,038,915 bp (Fig. 10.8). Chr1 was the largest pseudomolecule (76 contigs/2.37 Mbp) followed by Chr3 (69 contigs/2.04 Mbp) and Chr2

(65 contigs/1.98 Mbp), whereas Chr6 was the smallest pseudomolecule (6 contigs/0.40 Mbp). There was a significant syntenic relationship between C. olitorius and cacao (Fig. 10.9) as revealed by pairwise synteny mapping of these seven pseudomolecules with 10 cacao chromosomes (Argout et al. 2011). In brief, jute Chr 1 shared synteny with chromosome 9 of cacao, jute Chr 2 with Chr 3 and 10 of cacao, jute Chr 3 with Chr 2 and 4 of cacao, jute Chr 4 with Chr 5 of cacao, jute Chr 5 and 6 with Chr 1 of cacao and jute Chr 7 with Chr 3 of cacao, suggesting both fusion and fragmenttion of chromosomes between the two species. Similarly, comparison of jute pseudomolecules with the 13 diploid cotton (G. raimondii) chromosomes (Wang et al. 2012) showed that jute Chrs 1–3 have conserved orthologous regions dispersed in multiple chromosomes (Chr 9, 10, Chr 4, 9, 11 and Chr 6, 13, respectively) of diploid cotton, jute Chr 4 and 6 showed poor syntenic relationaships with cotton, jute Chr 5 with cotton Chr 7, and jute Chr 7 with

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155

Fig. 10.7 Distribution of simple sequence repeat (SSR) motifs and length in Corchorus olitorius cv. JRO-524 genome. (a) Length (mer) distribution of

repeated motifs. (b) Distribution of the repeated-motif nucleotides. (c) Distribution of grouped complementary motifs. (d) SSR length distribution

cotton Chr 13 (Fig. 10.9). Our results demonstrate that cacao was more closely related to C. olitorius than diploid cotton, though colinearity within syntenic chromosomes was not conserved. This is in close agreement with our earlier results based on RAD-SNP genetic map (Kundu et al. 2015). Many eudicotyledonous species, such as Arabidopsis, cacao, diploid cotton, grape, papaya, poplar and soybean are thought to have evolved from an ancestral 21-chromosomes intermediate via an effective reduction in chromosome numbers followed by their fusions (Argout et al. 2011; Wang et al. 2012). That most of the C. olitorius chromosomes share syntenic relationships with multiple cacao and diploid cotton chromosomes points to a reduction in chromosome numbers by fusion during the diplodization process. Since chromosomal evolution in Corchorus species is

suggested to have been driven by an ancient palaeo-polyploidization event followed by an increment in DNA content (Saha et al. 2014), the role of an ancestral palaeo-hexaploidization event in the evolution of the C. olitorius chromosomes cannot be ruled out (Kundu et al. 2015).

10.7

A JRO-524 Genome-Integrated Genetic Map of Tossa Jute

Earlier we generated using Roche 454 GS FLX platform transcriptome sequences representing leaf, root, seed and stem of C. olitorius cultivars Sudan Green (see section ‘Genome annotation using RNA-Seq evidence’) and JRO-632 (DDBJ/EMBL/GenBank TSA: GFDO000 00000.1; SRA: SRR5145919; BioProject:

a

74,459

GCA_000208745.2

Theobroma cacao

68,184

129,215

105,594

334,333

210

173

144

152

234

214

197

215

SSRs/Mbp

23.9

21.2

18.7

11.24

22.8

19.0

18.3

15.0

>= 20 bp SSR (%) 77.3

77.3

79.9

78.9

82.3

82.7

82.5

82.7

21.7

21.7

14.8

15.4

13.2

14.2

14.4

14.3

20.2

28.6

36.4

34.7

39.7

29.7

28.1

27.2

23.8

28.2

27.2

27.4

29.6

30.0

28.9

19.0

TA

AT

2

3

Top motif (%)

Top motifmer (%)

AT > TA > TC > AG

AT > TA > TC > AG

AT > TA > TC > AG

AT > TA > TC > AG

AT > TA > AG > TC

TA > AT > AG > TC

TA > AT > AG > TC

AT > TA > TC > AG

Motif abundance

SSRs were identified using GMATA v2.2.1 (Wang and Wang 2016), with default motif-unit settings (min length 2, max length 6 and mean repeat-times 5)

GCA_013677255.1

GCA_000327365.1

Gossypium harknessii

Gossypium raimondii

GCA_001974805.1

GCA_008761655.1

Corchorus capsularis

Gossypium barbadense

71,758

GCA_001974825.1

Corchorus olitorius cv. O-4

25,789 74,181

GCA_000001735.2

GCA_002141455.1

Arabidopsis thaliana

Number of SSRsa

GenBank genome assembly

Corchorus olitorius cv. JRO-524

Species

Table 10.3 SSR distribution and motif abundance in both the cultivated jute species in comparison with that in their closely related species within the Malvids

156 N. K. Singh and D. Sarkar

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a b

Fig. 10.8 Seven chromosome-level pseudomolecules of Corchorus olitorius cv. JRO-524 based on a RAD-SNP genetic map of tossa jute (Kundu et al. 2015). a Distribution of 501 RAD-SNP markers in seven pseudomolecules.

b Distribution of the number of genetically anchored contigs in seven pseudomolecules, with corresponding contig length (Mbp)

Fig. 10.9 Genomic synteny of Corchorus olitorius cv. JRO-524 with its closest relatives Gossypium raimondii and Theobroma cacao within the Malvids (Sarkar et al. 2017)

PRJNA278717; BioSample: SAMN06199045) comprising 19,978 and 18,576 unigene contigs, respectively. High-quality reads of these two TSAs were reassembled using MIRA v4.0 (Chevreux et al. 2004) and mapped by GsMapper (Roche, Basel) to discover a total of 24,785 genic-SNPs (10,841 and 13,944 genic-SNPs from JRO-632 and Sudan Green, respectively),

which were filtered by removing the SNPs located in low-complexity/repetitive regions and intron/exon splice junctions and following other recommended criteria. Thus, a total of 1,385 genic-SNPs were selected, of which 1,068 were validated by Sanger sequencing (Genetic Analyzer 3730xl, Thermo Fisher Scientific, Waltham). For the development of a GoldenGate®

158

N. K. Singh and D. Sarkar

Fig. 10.10 A functional genic-SNP-based linkage map of Corchorus olitorius for the Sudan Green
bfs intercross (F2) composed of 92 transcript-derived 113 genicSNP markers spanning a total genetic distance of 346.3 cM (Kosambi centiMorgan) over seven linkage groups, plotted as pairwise recombination fractions and LOD scores

genotyping assay, we selected a set of 384 genic-SNPs for custom OPA design by Illumina (OPA: GS0014193-OPA/Test Version: 09464019), and 176 F2 plants of the C. olitorius Sudan Green
bast fibre-shy (bfs; Kundu et al. 2012) biparental mapping population (Kundu et al. 2015) were genotyped together with their two founder parents. Excluding markers with highly significant segregation distortion at P < 0.001 against the expected 1:2:1 segregation ratio, we constructed a functional genic-SNP-based linkage map using R/qtl (Broman et al. 2003) with an error probability of 0.01 (Fig. 10.10). This functional linkage map comprised 113 genic-SNPs (derived from 92 transcripts) across the seven linkage groups, with a total genetic length of 346.3 cM and an average marker interval of 3.34 cM (Table 10.4). This was not entirely unexpected because C. olitorius, in general, is characterized by high segregation distortion, with as high as 61–67% and 34.4% reported for microsatellite (Das et al. 2012a, b; Topdar et al. 2013) and RAD-SNP (Kundu et al. 2015) markers, respectively. However, the total genetic length of this genic-SNP linkage map was in close agreement with the RAD-SNP linkage map (358.5 cM) reported earlier (Kundu et al. 2015). We mapped on LG1 the genes encoding SAMMTase, ARM repeat superfamily protein, Bblock binding subunit of TFIIIC, cullin 3,

Emp24/gp25L/p24 family/GOLD family protein, Fru-2,6-P2, galactose oxidase/kelch repeat superfamily protein, GDA1/CD39 nucleoside phosphatase family protein, hedgehog-interacting protein, kinase 2B, leucine-rich repeat transmembrane protein kinase, MA3 domain-containing protein, malectin/receptor-like protein kinase family protein, pumilio, purple acid phosphatases superfamily protein, SWAP/surp domain-containing protein/ubiquitin family protein and T-box transcription factor TBX5. Similarly, genes encoding ABI1 isoform 1, BZIP transcription factor, chaperone DnaJ-domain superfamily protein, ERD4, Fbox/RNI-like superfamily protein, guanylatebinding family protein, 3-ketoacyl-CoA synthase 4, nitrate reductase 2, pyruvate decarboxylase-2, SBP family protein and vascular plant one zinc finger protein were mapped on LG2. Other important candidate genes encoding C2 calcium/lipid-binding plant phosphoribosyltransferase family protein (LG4), CPK6 (LG5), CTC-interacting domain 11 isoform 1 (LG3), cytochrome P450 71A9 (LG3), cytochrome P450 family 77 subfamily B (LG4), ETO1-like protein 1 (LG4), EXORDIUM like 3 (LG5), extra-large GTP-binding protein 3 (LG4), FG-GAP repeat-containing protein (LG3), galacturonosyltransferase-like 7 (LG4), glucanaseslike protein (LG3), heat shock transcription factor B2A (LG5), light-harvesting complex II protein

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Table 10.4 Summary of functional genic-SNP-based linkage map of tossa jute constructed by GoldenGate genotyping of the Sudan Green
bfs intercross (F2) population Linkage group

Number of transcripts

Number of SNPsa

Length (cM)

Average marker interval (cM)b

LG1

29

LG2

25

39

68.3

1.75

29

108.7

3.75

LG3 LG4

21

26

84.7

3.26

9

11

47.9

4.36

LG5

4

4

23.5

5.87

LG6

3

3

13.2

4.41

–

LG7

1

1

Average

13.1

16.1

49.5

Total

92

113

346.3

– 3.34 -

a

A maximum of two genic-SNPs were called per transcript b Derived from summed recombination fractions of all mapped intervals

Lhcb4 (LG6), Myb-like HTH transcriptional regulator (LG3), NAC domain transcriptional regulator (LG3), phosphatase 2C 49 (LG4), RING/U-box domain-containing protein (LG3) and tubby-like Fbox protein (LG3) were also mapped. After integrating the Sudan Green
bfs genic-SNP-based linkage map with its corresponding RAD-SNP linkage map (Kundu et al. 2015), we used Chromonomer v1.07 (Catchen et al. 2020) to integrate the JRO-524 genome sequence (contigs) into the genetic map, with rescaffolding of the contigs based on the genetic map and using a minimum of two markers to anchor a scaffold (contig) on a particular map node (defaults). This resulted in a linkage map with 382 markers (317 genomic RAD markers and 65 genic-SNPs) integrated with 301 contigs across seven linkage groups (Fig. 10.11). With 365.7 cM genetic and 9,831,073 bp physical length (Table 10.5), this genome-integrated linkage map was characterized by an average length and marker interval of 52.2 cM (1,404,439 bp) and 1.2 cM (25,736 bp), respectively. LG2 was the longest (112.2 cM) and LG6 the shortest (13.2 cM), with the longest gap between two mapped loci (17.4 cM) detected on LG7 (Fig. 10.11). This is in close agreement with the RAD-SNP linkage map reported earlier (Kundu et al. 2015). However, as compared to the RAD-SNP linkage map, LG2 had the highest (104) and LG6 the lowest (14) number of

markers (Table 10.5). Of the 382 markers, 239 (178 RAD markers plus 61 genic-SNPs) were significantly (E value < 10–15) associated with 206 genes predicted and annotated in the JRO524 genome. Maximum number of geneassociated markers were identified on LG2 (70) followed by LG1 (60) and LG3 (52). This JRO-524 genome-integrated linkage map represents a unique genomic resource in tossa jute, for detecting QTL for different agronomic traits and map-based cloning of candidate genes.

10.8

Conclusions and Future Prospects

We have sequenced the genome of the most popular Indian tossa jute cultivar JRO-524 using Illumina MiSeq overlapping pair-end reads due to several advantages offered by this platform for whole genome shotgun (WGS) assembly, including a medium throughput fast-turnaround technology with optimum coverage even on GCrich, neutral and moderately AT-rich genomic regions (Quail et al. 2012). Despite the 92.7% complete JRO-524 genome assembly as assessed by BUSCO scores (Seppey et al. 2019), it is characterized by too many small contigs resulting in a lower contig N50 value. This is not unexpected because short-read Illumina MiSeq technology is known to yield highly accurate but

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N. K. Singh and D. Sarkar

Fig. 10.11 A JRO-524 genome-integrated SNP-based linkage map of tossa jute (Corchorus olitorius) for the Sudan Green
bfs intercross (F2), with 382 genomic RAD (317) and transcript-derived genic-SNP (65) markers being resolved into a total genetic and physical distances of 365.7 cM and 9,831,073 bp, respectively, over seven linkage groups. The scale is based on Kosambi

centiMorgan (cM), with horizontal lines representing the position of mapped loci on each linkage group. Markers suffixed with alphanumeric and numeric characters represent RAD and genic-SNP markers, respectively. Geneassociated loci are highlighted in red. LG linkage group; RAD, restriction site-associated DNA

fragmented genomic sequences (Neal-McKinney et al. 2021). Besides, we embarked on the JRO524 genome project with complete information about its genome size (Sarkar et al. 2011) and ploidy level and heterozygosity (Das et al. 2012a, b; Topdar et al. 2013; Saha et al. 2014), without assessing its genome complexity that affects the outcome of a genome sequencing project (Jung et al. 2020). Indeed, our results revealed a rather higher proportion of repetitive sequences in the C. olitorius genome (Sarkar et al. 2017; see above) that was nearly two-folds higher than that in its closest relative T. cacao within the Malvids (Argout et al. 2011). With several limitations of the existing sequencing platforms, short-read

sequence data are prone to being confounded by repetitive elements within the genome because of inherent limitations in accurate sequence assembly, while long-read sequence data have often been characterized by higher error rates (Collins 2018). Nevertheless, recent results (Rhie et al. 2021) have unequivocally confirmed that long-read sequencing technologies are a prerequisite for enhancing the quality of a genome assembly by way of resolving the complex repeats such as that identified in the JRO-524 genome. Keeping in view the recent advances and technical lessons, we would embark on upgrading the JRO-524 draft genome assembly by generating a hybrid assembly using

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Table 10.5 Summary of the JRO-524 genome-integrated SNP-based linkage map of tossa jute for the Sudan Green
bfs intercross (F2) Linkage group

Number of markersa

Length cM

Average marker intervalb bp

cM

Number of gene-associated markersc

bp

LG1

98

64.0

2,607,110

0.65

26,603.2

60

LG2

104

112.5

2,600,223

1.08

25,002.1

70

LG3

84

79.0

2,100,363

0.94

25,004.3

52

LG4

46

24.0

926,738

0.52

20,146.5

24

LG5

20

25.3

702,893

1.27

35,144.6

13

LG6

14

13.2

508,613

0.94

36,329.5

9

LG7

16

47.7

385,133

2.98

24,070.8

11

Average

54.6

52.2

1,404,439

1.20

25,735.8

34.1

Total

382

365.7

9,831,073

–

–

239

a

Of the 382 loci mapped, 317 represent RAD markers and 65 transcript-derived genic-SNPs. For RAD markers, a maximum of three SNPs were called per haplotype that refers to the configuration of SNPs at a RAD locus (Kundu et al. 2015) b Derived from summed recombination fractions and physical distances of all mapped intervals c Of the 239 loci identified to be associated with genes predicted in the JRO-524 genome (LLWS00000000.1), 178 represent RAD markers and 61 transcript-derived genic-SNPs

PacBio (Pacific Biosciences) long-read sequencing. Increasingly, Illumina MiSeq and PacBio sequencing techniques are being deployed in microbial genomics to produce hybrid assemblies (Berbers et al. 2020; Brede et al. 2020). Another challenge on the biological front is the non-availability of an ultra-high-density linkage map of Indian tossa jute. The intraspecific C. olitorius biparental mapping populations genotyped so far (see Sarkar et al. 2016) have resulted in hundreds of molecular markers being mapped on the seven linkage groups, with the densest one harboring as high as 638 RAD-SNPs (Kundu et al. 2015). However, only a small fraction of the JRO-524 genome could be genetically anchored using the RAD-SNP linkage map (Sarkar et al. 2017; see above). Since the RAD-SNP linkage map, with a total genetic length of 358.5 cM representing 96.8% of the total genome length (370.4 cM), covers 87.0% of the tossa jute genome (Kundu et al. 2015), it is highly likely that the smaller coverage of genetic anchorage is due to highly fragmented JRO-524 genome assembly with 52,372 sequence contigs. With PacBio longread sequencing resulting in larger average contig

lengths, it is expected that a much larger fraction of the JRO-524 genome could be genetically anchored. However, at the same time, we must emphasize that Indian C. olitorius population is inherent with a narrow genetic base, perhaps due to domestication bottleneck (Sarkar et al. 2019), which remains one of the major limitations to our ability to genetically map thousands of loci (markers) in C. olitorius using intraspecific intercross populations. Recently, we have developed the first interspecific C. capsularis cv. JRC-212 (♀)
C. olitorius cv. JRO-524 (♂) recombinant-inbred (RI10) population (194 RILs). In addition, we have also developed a MAGIC population (341 lines; ML9) of tossa jute from 19 parental lines by four rounds of intermating followed by inbreeding (Sarkar et al. 2016). By genotyping these mapping populations by resequencing, we would embark on developing an ultra-high-density SNP-based genetic map. Together with PacBio long-read sequencing, a complete chromosome-level reference genome of C. olitorius cv. JRO-524, with seven ‘chromonomes’ (Braasch et al. 2015), will be reassembled.

162 Acknowledgements We thank Indian Council of Agricultural Research Network Project on Transgenics in Crops (ICAR-NPTC) for financial support (sub-project grant ID: ICAR-NPTC-3070). We acknowledge NxGenBio Life Sciences, New Delhi for assistance in Illumina MiSeq sequencing and Xcelris Labs Ltd., Ahmedabad for assistance in 454 sequencing and Illumina GoldenGate genotyping. Authors who cannot be cited here due to space limitation are sincerely acknowledged. Data Availability The JRO-524 gene prediction and functional annotation data together with BUSCO results and other summary statistics including different source files are available as a Figshare entry. https://doi.org/10.6084/m9.figshare. 14812848.v1.

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N. K. Singh and D. Sarkar Rowell RM, Stout HP (2007) Jute and kenaf. In: Lewin M (ed) Handbook of fibre chemistry, 3rd edn. CRC Press, Boca Raton, pp 405–452 Saha P, Sarkar D, Kundu A, Majumder S, Datta SK, Datta K (2014) Karyotype analysis and chromosomal evolution in Asian species of Corchorus (Malvaceae s. l.). Genet Resour Crop Evol 61:1173–1188. https:// doi.org/10.1007/s10722-014-0099-0 Samad MA, Kabir G, Islam AS (1992) Interphase nuclear structure and heterochromatin in two species of Corchorus and their F1 hybrid. Cytologia 57:21–25. https://doi.org/10.1508/cytologia.57.21 Sarkar D, Kundu A, Das D, Chakraborty A, Mandal NA, Satya P, Karmakar PG, Kar CS, Mitra J, Singh NK (2019) Resolving population structure and genetic differentiation associated with RAD-SNP loci under selection in tossa jute (Corchorus olitorius L.). Mol Genet Genom 294:479–492. https://doi.org/10.1007/ s00438-018-1526-2 Sarkar D, Kundu A, Saha A, Mondal NA, Sinha MK, Mahapatra BS (2011) First nuclear DNA amounts in diploid (2n = 2x = 14) Corchorus spp. by flow cytometry: genome sizes in the cultivated jute species (C. capsularis L. and C. olitorius L.) are *300% smaller than the reported estimate of 1100–1350 Mb. Caryologia 64:147–153. https://doi.org/10.1080/ 00087114.2002.10589776 Sarkar D, Mahato AK, Satya P, Kundu A, Singh S, Jayaswal PK, Singh A, Bahadur K, Pattnaik S, Singh N, Chakraborty A, Mandal NA, Das D, Basu T, Sevanthi AM, Saha D, Datta S, Kar CS, Mitra J, Datta K, Karmakar PG, Sharma TR, Mohapatra T, Singh NK (2017) The draft genome of Corchorus olitorius cv. JRO-524 (Navin). Genomics Data 12:151–154. https://doi.org/10.1016/j.gdata. 2017.05.007 Sarkar D, Satya P, Mandal NA, Das D, Karmakar PG, Singh NK (2016) Jute genomics: emerging resources and tools for molecular breeding. In: Ramawat KG, Ahuja MR (eds) Fiber plants- biology, biotechnology and applications, vol 13. Sustainable development and biodiversity, vol 13. Springer International Publishing AG, Cham, pp 155–200. https://doi.org/10.1007/ 978-3-319-44570-0_9 Seppey M, Manni M, Zdobnov EM (2019) BUSCO: assessing genome assembly and annotation completeness. Methods Mol Biol 1962:227–245. https://doi. org/10.1007/978-1-4939-9173-0_14 Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM (2015) BUSCO: assessing genome assembly and annotation completeness with singlecopy orthologs. Bioinformatics 31:3210–3212. https:// doi.org/10.1093/bioinformatics/btv351 Sinha MK, Kar CS, Ramasibramanian T, Kundu A, Mahapatra BS (2011) Corchorus. In: Kole C (ed) Wild crop relatives: genomic and breeding resources, industrial crops. Springer-Verlag, Berlin and Heidelberg, pp 29–61. https://doi.org/10.1007/ 978-3-642-21102-7_2

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Jute Genome Sequencing: A Bangladeshi Initiative

11

Md. Shahidul Islam, Abu Ashfaqur Sajib, and Haseena Khan

Abstract

Jute is the second most abundant natural source of bio-based fiber after cotton. This fiber, known to have high tensile strength, is non-abrasive in nature, light-weight, non-toxic, and most importantly biodegradable. Due to its excellent physical and mechanical properties as well as environment friendly nature, jute fiber is fittingly called the “Fiber offuture”. Bangladesh is fortunate to be home to the finest-quality jute. For many decades, the jute industries have been the lifeblood of Bangladesh's economy, and they remain one of the foundations of the country's rural economy today. For the people of Bangladesh jute is not just a crop linked with the

Md. Shahidul Islam Basic and Applied Research on Jute Project, Bangladesh Jute Research Institute, Dhaka, Bangladesh A. A. Sajib Department of Genetic Engineering & Biotechnology, University of Dhaka, Dhaka, Bangladesh e-mail: [email protected] H. Khan (&) Molecular Biology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh e-mail: [email protected]

country’s pursuit for economic liberation; it is their national representation, their identity. Many of their time-worn folklore is based on the golden colored jute fibers from where the country got its maxim, “Sonar Bangla”. A strong and growing demand for jute fiber from environmental and commercial stand points in both local and international markets and the necessity for producing diversified value-added products demand a robust study on jute. Research on fiber development, physiology, genomics, and evolution are much needed to increase our knowledge and ability for improving jute yield and fiber quality. In this backdrop it is thus not surprising that Bangladesh took the initiative of unravelling the mystery of the wonder crop, it has been blessed with. An endeavor to decode the jute genome was made by the Government of Bangladesh in late 2009. Draft genome sequences of the two commercially cultivated species of jute, C. capsularis and C. olitorius, were published in 2017. In addition, transcriptomic data of these two species grown under varied conditions are available in public databases. These genomic and transcriptomic data have opened opportunities to improve jute yield and fiber quality and widened the scopes of potential applications. This chapter discusses the key findings of the jute genome sequence project and the studies that derived from this initiative.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_11

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Introduction

Jute (Corchorus spp.) is a natural lignocellulosic fiber well-known for its high tensile strength, non-abrasiveness, light-weight, non-toxicity, low cost, and biodegradability. It is the second most abundant natural source of bio-based fiber after cotton. Due to its exceptional physical and mechanical qualities as well as environment friendly nature, jute fiber has received a lot of attention in recent years and is dubbed as the “Fiber of future”. It has good thermal and acoustic insulating properties with moderate moisture regain. Jute fiber has mechanical qualities similar to glass fiber in terms of specific strength and modulus. Jute fiber is widely used in yarns, textiles, geotextiles, ropes, twines, paper and fiber board products, packaging and construction materials, composites and automotive parts among others. Besides these, jute leaf has medicinal properties and possesses antioxidative, anti-inflammatory, and antimicrobial activities (International Jute Study Group 2010). Jute is typically grown in tropical and subtropical regions of the world. Although the genus Corchorus contains over 100 species, only two are economically cultivated: C. capsularis (white jute) and C. olitorius (black jute/tossa jute). These two species belong to the family Malvaceae. These species originated in the East Africa. Later these were domesticated in Asia, particularly in Bangladesh, India, and China. Although the genomes of C. capsularis and C. olitorius comprise seven pairs of chromosomes each, these differ distinctly in a number of desirable agronomic and biomass-associated traits as well as fiber quality (International Jute Study Group 2010). At the beginning of the twentieth century, part of India consisting of West and East Bengal could claim only one manufacturing industry, and that was jute. Nearly half of the total workforce of this region was involved in this crop’s production and to the manufacture of yarns. Jute exports accounted for roughly a third of the region's total value in 1900–1. Partition of Bengal in 1947, saw all jute mills of this region to be

placed in West Bengal (a part of India) and all major jute growing districts in East Pakistan (a province of Pakistan), which in 1971 became Bangladesh. Due to the lack of a jute industry, raw jute was difficult to market in this eastern region. The problem was, however, quickly overcome by establishing jute mills in East Bengal. Jute has played a significant role in Bangladesh's economic development. The significance of the jute industry to the Bangladeshi economy cannot be overstated. It is a major cash crop for over three million small farm households, the largest industry in Bangladesh, accounting for around one-third of manufacturing production, and the most important agricultural export commodity. Jute-related activities in agriculture, domestic marketing, manufacturing, and commerce support the livelihoods of around 25 million people (almost one-fifth of the total population). Considering the importance of Bangladesh in global jute supply the International Jute Organization (IJO) was set up in the country in 1984. This intergovernmental body under the aegis of United Nations Conference on Trade and Development (UNCTAD) functions as the International Commodity Body (ICB) for jute, kenaf, and related fiber crops. Following the dissolution of the IJO, the new International Jute Study Group (IJSG), which was established in 2002 as the legal successor to the IJO, provides a framework for international cooperation, consultation, and policy development among members, which include jute producing, importing, and exporting countries. The IJSG represents 27 member countries and over 60% of global jute trade (both import and export). Bangladesh has regulatory measures and policies that impose directly or indirectly on the production, trading, processing, and export of jute fiber and its products. The jute sector is considered socially and politically far too important to be left entirely to market forces. The Bangladesh Jute Research Institute (BJRI) is the oldest “single-crop” based research institute in the country. The government of Bangladesh established the Bangladesh Jute Mills

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Corporation (BJMC) to manage the country's jute mills. Bangladesh Jute Mills Corporation (BJMC), a public corporation in Bangladesh, is the world's largest state-owned jute manufacturing and exporting company.

Laboratory (JARL) was established in Dhaka to strengthen research on jute. After the British had left this subcontinent in 1947, JARL was reorganized and renamed as Jute Research Institute (JRI) in 1951. After the liberation war and gaining independence in 1971, the jute sector was given special focus. In 1974 the Government of Bangladesh implemented The Bangladesh Jute Research Institute Act and the JRI was upgraded and modernized as Bangladesh Jute Research Institute (BJRI) with a specific mandate, which was modified in 2017 with the following primary aims: a. control, develop, and undertake agronomic, technological, and economic research on jute and related fiber crops and productions, as well as dissemination of findings; b. to produce, test, supply, manage improved varieties of jute seeds by maintaining improved genetic purity and to produce and collect improved lines of jute seeds in limited way and to distribute those to the selected growers, recognized organizations and such other agencies as may be approved by the Board; c. to carry out pilot projects in various parts of the country for the study of jute and allied fiber crops, jute products, and related concerns; d. to disseminate the new varieties of jute developed by BJRI for the expansion of jute cultivation and to organize training of farmers for cultivation of jute of those varieties; e. to publish and disseminate monographs, press release and other publications related to jute research; f. to provide training to the employees of the Institute on advanced cultivation methods of jute and related fiber crops, also provide training to the beneficiaries associated with the production of jute and jute derived products regarding the technological research findings and utilization thereof; g. to undertake research programs in collaboration with national and international institutions and organizations; h. to perform any other duty conferred upon it, from time to time, subject to the directions given by the Government; and

11.2

History and Culture of Bangladesh are Knitted with Jute

Jute is an integral part of the independence, history, and culture of Bangladesh. It is known as the “Golden fiber” of Bangladesh. For hundreds of years jute have been used for varied applications in Bangladesh. It was one of the major goods which were exported by the East India Company during the British rule in the Indian subcontinent. Jute was a cornerstone of the six-point program which called for greater autonomy. It ultimately drove the independence movement in the former East Pakistan, which culminated in 1971 through the birth of a sovereign and independent country —Bangladesh. Currently, Bangladesh ranks first in the world in terms of the quantity of jute exports and second as for production. In 2019, Bangladesh contributed 74% to global jute exports. Jute sector contributes *5% to the total export earnings of Bangladesh and was positioned second (with export earnings of USD 882.35 million) only after the readymade garments sector in 2020. Therefore, jute holds great potential in terms of contribution to the national economy and earnings from the growing international market demand, particularly for jute diversified products. Research on jute fiber development, physiology, genomics, and evolution is, therefore, much needed to increase our knowledge and ability for improving jute yield and fiber yield.

11.3

History of Jute Related Research in Bangladesh

The Bengal Department of Agriculture was launched in 1904 to advance agricultural research on jute. In 1936 the Jute Agricultural Research

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i. to carry out such other tasks that may be required. Considering the importance of Bangladesh as a jute producing country the headquarters of International Jute Organization (IJO) was set up under UNCTAD sponsorship in 1984 in Dhaka, Bangladesh. However, in 2002, IJO became the International Jute Study Group. In the agriculture sector the first and most important project taken up by IGO was the project, titled “Collection, Conservation, Characterization and Exchange of Germplasm for the Development of Improved Varieties of Jute, Kenaf and Other Allied Fibers” (also known as the Germplasm Project). The objective of the project was to develop high yielding varieties of jute and kenaf with superior fiber quality. Under this IJO project, Bangladesh became home to the largest genetic resource of jute and related fiber crops. BJRI Gene Bank houses nearly 6000 accessions of a total of 53 species of jute and allied fiber producing plants (Haque 2007). BJRI conducts a large portion of the agricultural research on jute and allied fibers (including kenaf and mesta) in Bangladesh with the goal of developing new jute, kenaf, and mesta varieties with higher yields, better fiber quality, photoperiod neutrality, short field duration, water logging tolerance, pest and disease tolerance, and other traits. BJRI has developed 50 varieties of jute and allied fibers applying conventional breeding techniques. Among these, twelve varieties (with resistance to leaf mosaic virus, super white fiber with least cuttings, early maturing and less photosensitive mesta, nematode resistant kenaf, etc.) are currently being commercially cultivated. Ribbon retting technique for jute fiber extraction in water deficit areas is another remarkable achievement of BJRI. Jute fiber is in high demand in both local and worldwide markets for generating a variety of value-added goods, both from an environmental and commercial standpoint. Therefore, there is both scope and interest for improvements in various aspects. Some of the major challenges on the way to increase the yield and quality of jute include high lignin content and fragility of fiber,

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susceptibility to insect pests and fungal diseases, photoperiod sensitivity, low yield under unfavorable conditions (such as salinity, flood, drought, and cold), etc. Application of traditional plant breeding techniques to address these challenges suffers from certain setbacks. The available elite jute cultivars are essentially the products of pure line selection from a few common accessions. The two commercially cultivated jute species differ in certain desirable aspects. For example, C. capsularis is comparatively more resistant to abiotic stresses (such as flood and drought), but slightly more susceptible to pest as well as diseases. It produces slightly weak whitish fiber. C. olitorius, on the other hand, produces stronger fiber and is relatively resistant to diseases and pests. As a result, combining the beneficial traits of the two species in a single genotype is very desirable. However, due to genetic incompatibility, these two species are unable to successfully cross-fertilize. Advanced molecular biology and biotechnology related research on jute is also being conducted at the Molecular Biology Laboratory in the Department of Biochemistry and Molecular Biology, University of Dhaka. Jute is recalcitrant to genetic transformation and regeneration in vitro through tissue culture. This lab developed a tissue-culture independent in planta genetic transformation method for jute that obviates the need for in vitro culture. In fact, this laboratory pioneered research on jute at the molecular level and developed genetic markers for many important varieties of jute. Jute grows in hot and humid conditions. Therefore, it is only a single season crop. For jute to be considered as a source of raw material for various industries, it is necessary for the crop to grow even in the winter seasons of Bangladesh. The gene bank set up by IJO at the BJRI had in its collection four accessions that could germinate at 16 °C, a temperature at which the commercially cultivated varieties do not survive. Since no genome sequence data was available and jute specific primers could not be designed in the early 2000, two low temperature-sensitive and four low-temperature tolerant accessions were characterized using amplified fragment

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length polymorphism (AFLP) and rapid amplification of polymorphic DNA (RAPD) markers. One RAPD marker was particularly successful in differentiating between the jute accessions, which could germinate at 16 °C and the popular farmer varieties, which do not. The polymorphic band was excised from the agarose gel and sequenced. Sequence analysis through the use of the meager bioinformatics tools available around 20 years ago revealed the sequence to be part of a big gene. This first-ever partial sequence of a jute gene was used in chromosome walking in order to obtain the full-length gene, which was later identified as VPS51, the product of which is involved in transporting proteins from early and late endosomes to the trans-Golgi network (unpublished data). The pioneering and ground breaking work on jute molecular biology, brought this often-over-looked crop into the focus of the policy makers, which ultimately led to sequencing of the jute genome. The expertise, competence, and initiative of this laboratory were invaluable in decoding the whole genomes of the two jute species—C. capsularis and C. olitorius. The number of complete or partial jute genes identified until the completion of jute genome sequencing project was very limited. Islam et al. (2005) published the sequences of 15 jute genomic and cDNA clones that were highly similar to Arabidopsis genes. Wazni and coworkers (2007) identified 16 expressed sequence tags (ESTs) that had genetic sequences that were similar to Arabidopsis and other higher plant genes. Genes so identified through homology-based approach were found to be engaged in a variety of metabolic and stressrelated pathways. Ahmed et al. (2009) attempted both computational and experimental methods to create jute ESTs from genomic clones. Characterization of two jute genetic libraries, one containing 157 (Akter et al. 2008) and the other 208 clones (Mir et al. 2008) was made by Samira et al. (2010). Presence of sequence data of 365 clones from these libraries led to bioinformatics investigations to determine coding or other functional sequences, despite the fact that the SSR libraries were established for the identification of markers connected to various desirable

features. In 80 of the 213 sequences (contigs and singletons), GENESCAN and GeneID predicted the presence of genes. Among these, 19 had at least two matches in BLAST searches (any two of blastn, blastx, or blastEST). Despite the small sample size, the study provided an insight into jute at the molecular level and provided an early glance into the genetic makeup of jute.

11.4

Initiative on Jute Genome Sequencing Project “Swapna Jaatra”

Jute is considered as the most important nonfood crop in Bangladesh. It has been a part of the national heritage and a remarkable constituent of the economy. It holds a huge potential to contribute more to the nation’s welfare in future. To harness the maximum potential of jute a collaboration, named Swapna Jaatra (meaning a journey to achieve a cherished goal), was established among Bangladeshi researchers working in the country and abroad. This collaborative work was funded by the government of Bangladesh. Biology and computing were the two key components of the core team. The biology and computing teams were led by Professor Haseena Khan of the Molecular Biology Laboratory in the Department of Biochemistry and Molecular Biology at the University of Dhaka and Mr. Mahboob Zaman of DataSoft Systems Bangladesh Limited, respectively. Professor Maqsudul Alam of the University of Hawaii at Manoa, who led the genome sequencing of papaya in 2008, coordinated both teams.

11.5

Jute Genome in Brief

Comparative genomics and transcriptomics hold the potential to unveil new opportunities to understand and tackle challenges. As previously stated, it is highly desired to combine valuable features from C. olitorius and C. capsularis (two prominent commercially farmed species) into a single genotype. The genomes of C. olitorius var. O-4 and C. capsularis var. CVL-1 (Fig. 11.1)

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were sequenced following the whole-genome shotgun (WGS) approach using the Roche 454 sequencing platform to better understand the molecular basis of differences in fiber quality, stress tolerance, disease susceptibility, and other traits (Islam et al. 2017).

11.5.1 Isolation of High Molecular Jute DNA The seeds of Corchorus olitorius var. O-4 and Corchorus capsularis var. CVL-1 were collected from the Breeding Division of Bangladesh Jute Research Institute, Dhaka. Both the varieties were developed through a pure line selection method. A single plant from each variety (O-4 and CVL-1) was selected based on their identifying characters and vegetatively propagated through cuttings from the top of the plants at the age of 100 days (before flowering). Seeds were produced from the selected plants by selfing under controlled conditions to avoid cross

Fig. 11.1 Morphological characteristics of C. capsularis (variety CVL-1) and C. olitorius (variety O-4) (Islam et al. 2017). C. capsularis plant (a), its fiber (b) and seeds (c). C. olitorius plant (d), its fiber (e) and seeds (f)

Md. Shahidul Islam et al.

pollination. Next year those seeds were multiplied again by selfing under a controlled environment to maintain genetic purity. Seeds were surfacesterilized, plated on wet blotting paper, and transferred to a dark growth chamber to discourage chlorophyll formation. Four-day old axenically grown, etiolated seedlings were harvested and directly used to isolate nuclear DNA and RNA for sequencing. High molecular weight genomic DNA was prepared following isolation of nuclei from the seedlings using a sucrose gradient protocol. Till date jute seedlings have remained the only source of quality DNA. Total RNA was extracted from jute seedlings following the guanidinium thiocyanate-phenol– chloroform extraction method.

11.5.2 Genome Assembly More than 100X coverage of the genomic sequence were used for assembling the genome. C. olitorius and C. capsularis have genome sizes of roughly 448 and 404 Mb, respectively. The draft genome sequence assemblies for C. olitorius and C. capsularis, respectively, cover 91.6% and 82.2% of the expected genome sizes. In the draft genomes of C. olitorius and C. capsularis, in silico research predicted 37,031 and 30,096 genes, respectively (Table 11.1). Expression of most of these predicted genes was confirmed by RNA-Seq method using Illumina HiSeq 2500 system. Like the other eukaryotic genomes, jute also carries a significant number of repetitive elements in the genomes (Tables 11.2 and 11.3). As mentioned earlier, these two cultivated jute species vary in multiple traits, particularly in fiber quality and color. It was hypothesized that the comparative transcriptomic analysis would complement the information derived from the draft genome sequence and provide insights into the molecular basis of the difference in fiber quality and color. The RNA-seq approach was used to produce transcriptomic data from isolated fiber cells and seedlings of C. olitorius and C. capsularis to explore differentially expressed genes in fiber cells (elongated cells undergoing secondary cell wall deposition). The expression

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Table 11.1 Genome sizes and gene densities of C. olitorius, C. capsularis and other sequenced plant genomes (Islam et al. 2017) Species name

Plant type

Genome size (Mb)

Gene number

Gene density#

Zea mays

Maize

2,200

Glycine max

Soybean

1,115

46,430

0.42

Gossypium raimondii

Cotton

880

40,976

0.47

Sorghum bicolor

Millet

740

34,496

0.47

Vitis vinifera

Grapevine

487

30,434

0.63

Populus trichocarpa

Poplar

485

45,555

0.94

Medicago truncatula

Barrelclover

470

47,845

1.02

Corchorus olitorius

Jute

447

37,031

0.90*

Theobroma cacao

Cocoa

430

28,798

0.67

Oryza sativa

Rice

420

40,577

0.97

Corchorus capsularis

Jute

404

30,096

0.91*

Linum usitatissimum

Flax

373

43,484

1.16

Carica papaya

Papaya

372

24,746

0.66

Ricinus communis

Castor bean

350

31,237

0.89

Arabidopsis thaliana

Flowering plant related to mustard

120

27,228

2.2

32,540

0.15

# Gene density expressed in number of genes per 10 kb. *Based on the 410.19 Mb and 331.96 Mb draft genome sequences of C. olitorius and C. capsularis, respectively

Table 11.2 Distribution of repetitive and nonrepetitive sequences in C. olitorius and C. capsularis genomes (Islam et al. 2017)

Genomics regions

Copy number

Non-repetitive regions

1

Repetitive regions

levels of 174 C. olitorius genes and 216 C. capsularis genes were significantly different between the fiber cells and the seedlings (Islam et al. 2017). These genes encode transcription factors such as WOX4, APL, and HAT22, as well as the TDIF signaling peptide, which are known to have a role in vascular cambium initiation and fiber cell proliferation. In addition, transcription factors that regulate the secondary cell wall (SCW) formation in fiber cells were up regulated in fiber cells. In jute fiber cells, the

Genome coverage (%) C. olitorius

C. capsularis

46.28

43.83

>1–2

38.65

36.04

3–100

13.18

18.58

>100

1.89

1.55

Arabidopsis homolog of MYB83 (a master regulator of initiating the production of all major SCW components, i.e., cellulose, lignin, and xylan) showed significant up-regulation. CesA4 and CesA7 genes were also up regulated in fiber cells, indicating a link to SCW cellulose deposition, whereas CesA1, CesA3, and CesA6 genes were significantly up-regulated in seedlings. Jute fiber has a high lignin content (15%), making it coarser than other plant bast fibers like flax and ramie (which have less than 5% lignin in

174 Table 11.3 Distribution of different types of repetitive elements in the assembled C. olitorius and C. capsularis genomes (Islam et al. 2017)

Md. Shahidul Islam et al. Type

Total repeats (%) C. olitorius

DNA elements Retrotransposons

6.13

7.58

LTR

46.18

43.04

LINE

5.62

6.55

SINE

0.14

0.14

40.07

40.73

0.28

0.25

Unclassified Satellites

Table 11.4 Components of jute fibers (Islam et al. 2017)

C. capsularis

Simple repeats

1.38

1.51

Small RNA

0.2

0.2

Retted jute fiber

Component

C. olitorius

C. capsularis

Cellulose

58.0–59.0

60.0–63.0

Hemicellulose

22.0–25.0

21.0–24.0

Lignin

13.0–14.0

12.0–13.0

Lipids

0.4–0.9

0.4–1.0

Pectin

0.2–0.5

0.2–1.5

Proteins, nitrogenous matter, etc

0.8–1.6

0.80–1.9

Others

0.5–1.2

0.7–1.2

their cell walls) (Table 11.4). Based on the draft genome sequence, certain lignin biosynthesis gene families, such as cinnamoyl-CoA reductase (CCR), 4-coumarate:CoA ligase (4CL), caffeic acid Omethyltransferase (COMT), and trans-caffeoylCoA 3-O-methyltransferase (CCoAOMT), were found to be expanded in both C. capsularis and C. olitorius (Table 11.5). However, gene expression profiles revealed that in jute fiber cells, only a few homologues of these gene families were preferentially expressed at high levels. In addition, pathway enrichment analysis using bioinformatics tools indicated an up regulation of autophagy and proteolysis pathways in jute fiber cells, whereas most of the metabolic pathways were down regulated. Senescence and cell death are known to occur during the last stages of fiber synthesis, and both processes entail autophagy and proteolysis. The physical and physiological variations between the two jute species were also revealed

by transcriptome analysis. C. olitorius fiber is higher in lignin and lower in cellulose than C. capsularis fiber. The expression patterns of lignin and cellulose synthase genes in these two species appeared to be distinct. Furthermore, genes encoding key enzymes in the proanthocyanidin biosynthesis pathway were found to be more abundantly expressed in the fiber cells of C. olitorius (golden color) than C. capsularis (whitish color), suggesting that proanthocyanidin biosynthesis pathway genes are involved in fiber pigmentation. As mentioned earlier, C. capsularis has comparatively more tolerance to water logging condition, drought, and salinity stresses than C. olitorius. C. olitorius, on the other hand, is less prone to diseases and pests than C. capsularis. When the genomes of these two jute species were analyzed, it was discovered that the genes responding to abiotic stresses were considerably

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Table 11.5 Comparison of the copy number of lignin and cellulose biosynthetic pathway genes in different plant genomes (Islam et al. 2017) Type of activity

Class*

C. olitorius

C. capsularis

Cotton

Cacao

Flax

Poplar

Arabidopsis

Lignin and phenylpropanoid biosynthesis

PAL

4

4

3

6

4

5

4

C4H

2

3

3

2

5

3

1

C3H

1

1

1

3

4

3

1

4CL

14

10

3

9

8

5

5

HCT

9

5

6

16

6

7

2

CCR

Cellulose synthesis

8

10

9

9

5

7

2

CCoAOMT

10

10

9

9

7

2

2

CAD

10

13

8

7

12

1

9

F5H

2

2

2

4

8

2

2

COMT

17

15

9

9

8

2

1

Total

77

73

53

74

67

37

29

CesA

10

10

12

5

10

12

10

CslA

0

2

2

1

2

2

8

CslB

7

7

1

4

1

3

6

CslC

1

4

9

4

9

8

5

CslD

8

6

6

5

19

12

6

CslE

5

4

11

8

1

3

1

CslG

10

9

10

13

6

8

3

Total

41

42

51

40

48

48

39

*

PAL: Phenylalanine amonnia lyase, C4H: Cinnamate-4-hydroxylase, C3H: Coumaroyl 3-hydroxylase, 4CL: 4Coumarate:CoA Ligas, HCT: Hydroxycinnamoyl-CoA:shikimate/quinate hydroxycinnamoyl transferase, CCR: Cinnamoyl-CoA reductase, CCoAOMT: Trans-caffeoyl-CoA 3-O-methyltransferase, CAD: Cinnamyl alcohol dehydrogenase, F5H: Ferulate 5-hydroxylase, COMT: Caffeic acid 3-O-methyltransferase

over-represented in C. capsularis compared to C. olitorius. These stress responsive genes encode proteins which regulate homeostatic processes, vacuolar and transmembrane transport, signal transduction, oxidoreductase activity, ATPase activity, etc. (Islam et al. 2017). These are indicative of the better adaptability of C. capsularis in different habitats and environmental pressure.

relevant technical expertise, and confidence to undertake further tasks to improve jute yield and quality. Some of the important studies that were inspired by and/or derived from the jute genome sequence project are described briefly in the following sections.

11.6

Lignin, a cross-linked polymer of hydrophobic aromatic chemicals that imparts added rigidity to plant cell walls, is abundant in jute fiber. It is the second most abundant organic polymer after cellulose. Lignin is highly recalcitrant in nature and hinders the processing of plant fiber and

Offshoots of Jute Genome Sequencing Project

Swapna Jaatra, the jute genome sequencing project, was the first of its kind in Bangladesh. This project helped developing new knowledge,

11.6.1 Improvement of Jute Fiber Quality

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other lignocellulosic parts for various industrial purposes. In comparison to non-lignocellulosic fibers like cotton, lignin hardens the jute fiber and diminishes its elastic characteristics. As a result, its high lignin content is a major deterrent to its usage as a textile fiber. Lignin also prevents the release of cellulose and hemicellulose from lignocellulosic biomass like jute fiber and stem, which have enormous promise as biofuel raw materials. There are chemical methods to remove lignin from jute fiber and stems. But chemical delignification processes are expensive and use corrosive chemicals which are detrimental to the environment. Moreover, reduced lignin content in fiber improves tensile strength, elasticity, and overall quality. As a result, jute with lower lignin concentration in the fiber and stem has a lot of promise in the textile sector, forage and bioenergy production, paper and pulp manufacture, and so on. The draft jute genome sequences revealed the list of genes involved in lignin biosynthetic pathways in two commercially cultivated species of jute. RNA interference (RNAi) technology was used to limit the expression of four monolignoid biosynthesis genes in jute: coumarate 3hydroxylase (C3H), ferulate 5-hydroxylase (F5H), cinnamate 4-hydroxylase (C4H), and caffeic acid O-methyltransferase (COMT) (Nath et al. 2021; Shafrin et al. 2015, 2017). Lignin content in the stem and fiber was reduced in these transgenic lines (7th generations of the COMT and C4H lines, and 5th generation of the C3H and F5H lines). In the whole stem of the COMT, C4H, F5H, and C3H lines, lignin content decreased by 21.5%, 22.1%, 22.7%, and 21.7%, respectively, as compared to non-transgenic controls (Fig. 11.2). For the COMT, C4H, F5H, and C3H lines, lignin in fiber was reduced by approximately 15.5%, 16.1%, 12.1%, and 14.7%, respectively. The cellulose content of all four transgenic lines was higher (cellulose content on average increased 5.3%, 5.0%, 4.1%, and 5.5% in COMT, C4H, F5H, and C3H transgenic lines, respectively). The tensile strength of fibers from transgenic lines ranged from 512.50 to 576.13 MPa, compared to 493.80 MPa for the control.

Md. Shahidul Islam et al.

Jute fibers with lower lignin and higher cellulose content produce higher-quality fibers with significant cost savings. It has been observed that plants can tolerate a 40% reduction in lignin content without significant adverse impacts on normal plant growth, physiology, adaptability, or disease susceptibility. Therefore, there is scope to improve the fiber quality of jute by reducing lignin content even further.

11.6.2 Decoding the Genome of Macrophomina phaseolina Macrophomina phaseolina is a necrotrophic fungas that can infect over 500 plant species, including key food crops (maize, sorghum, etc.), pulses (common bean, green gram, etc.), fiber crops (jute, cotton, etc.), and oil crops (soybean, sunflower, sesame, etc.). It spreads quickly in host plants, producing a significant amount of sclerotia, which blocks the capillaries and causes the plant to wilt. The fungus is found throughout the world (Africa, Asia, Europe, North and South America), with a higher prevalence in tropical and subtropical areas with arid to semi-arid climates. M. phaseolina can remain viable as sclerotia for more than four years in soil and crop residues. It is, therefore, difficult to get rid of this fungus from soil and plant debris. This devastating fungus can cause serious crop losses. M. phaseolina, for example, was responsible for a total yield loss of $173.80 million in soybeans in the United States alone in 2002. The yearly jute fiber yield in Bangladesh has been reduced by roughly 30% as a result of infection with this pathogen. As mentioned earlier, the jute genome sequencing project developed technical expertise and confidence to undertake similar tasks to improve jute yield and quality. The genome of M. phaseolina was sequenced in a wholegenome shotgun technique utilizing a mix of Roche 454 and Illumina platforms as a spin-off from the jute genome sequence effort (Islam et al. 2012). The draft sequence covered 92.83% of the genome of M. phaseolina. Based on in silico

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Fig. 11.2 Representative images of reduced lignin in transgenic jute plants (Shafrin et al. 2017). A. Lignin deposition in the stem of wild type plant. B and C. Transgenic lines in which expression of COMT and C4H genes, respectively, were inhibited using RNAi method. The colored arrows indicate difference in lignin content in

transgenic and wild type jute plants (red: epidermis, orange: pith and yellow: vascular cambium). The area between the epidermis and vascular cambium (indicated with black arrows) is the bast region that forms the jute fiber. This area is significantly less lignified in transgenic plants compared to the wild type

study, 13.07% (1,863) of the genes in the M. phaseolina genome encode secreted proteins, compared to 7–10% in other plant pathogens. The sequenced regions contain 14,249 ORFs, most of which were validated by transcriptomic analysis. The M. phaseolina genome sequence provided deeper insight on the infection process at the cytological and molecular level. M. phaseolina uses a diverse arsenal of enzymes to exploit the host plants (Fig. 11.3). This pathogen has a large number of secreted oxidases, peroxidases, and hydrolytic enzymes that help it infiltrate host tissue and establish an infection by destroying cell wall components. The genome of M. phaseolina encodes a unique set of carbohydrate esterases (CE), with the CE9 and CE10 families being far more prevalent than in any other known fungus. M. phaseolina also has a significant number of pathogen-host interaction genes that code for adhesion proteins, cell wall breakdown proteins, signal transduction proteins, and the powerful mycotoxin “Patulin.” The number of glycoside hydrolases (GH) in M. phaseolina is higher than the average number possessed by other plant pathogenic fungi. To hydrolyze cellulose, the M. phaseolina genome encodes 25 putative endoglucanases, 7 exocellobiohydrolases, and 28 glucosidases. M. phaseolina was shown to have considerably stronger cellulolytic activity than Aspergillus niger and Trichoderma reesei. M. phaseolina has

the most laccases, which are enzymes that degrade lignin, when compared to seven other fungal species. M. phaseolina appeared to be second reported fungus after Phanerochaete chrysosporium that has the gene encoding lignin peroxidase. M. phaseolina genome differs from that of other fungi in that it contains a greater number of genes that code for cytochrome P450s and enzymes that produce secondary metabolites. M. phaseolina may be able to adapt to a wide range of osmotic and pH environments and infect a wide range of hosts due to presence of these extraordinary number and varieties of enzymes.

11.6.3 Sequencing of Jute Enodophytes—A Community of Microbes with Enormous Potentials Endophytes are a community of microbes that live closely within a plant host and play important role in host metabolism and function. These are known to stimulate growth of the host, enhance nitrogen fixation, provide protection against pathogens, assist in drought tolerance, regulate phytohormone production as well as provide nutrients. The raw genome sequence of jute contained substantial amount of microbial DNA sequence with it. Although it was startling

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Md. Shahidul Islam et al.

Fig. 11.3 Molecular insights on pathogenic lifestyle and infection process of M. phaseolina (Islam et al. 2012). A. Conidia or sclerotia are formed and released from the pathogen. B. Conidia or sclerotia disperse during early rainy season and contact the host tissue. C. Pathogen neutralizes the host primary defense with salicylate-1-

monooxygenase. D. Conidia forms appressorium, which is centrally controlled by PMK1. E. Penetration and invasion into the plant epidermis. F. Inside the host, the pathogen releases an array of cell wall degrading enzymes and toxins to finally breakdown the host defense. G. Host cell death and infection-establishment

at the beginning, it was soon realized from previous encounters that these sequences might come from endophytic microbes of jute. This inspired an in-depth search for jute endophytic microbes.

Jute seeds, seedlings, and various sections of the plant (roots, stems, leaves, and flowers) contain both culturable and nonculturable endophytic bacteria and fungi (Najnin et al. 2014). Both endophytic bacteria and fungi were

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identified from various parts of jute using molecular characterization based on bacterial 16S rDNA and fungal internal transcribed spacer (ITS) regions of 18S rDNA sequences. Based on the properties of these endophytes, it appears that they may provide diverse benefits to jute. All culturable endophytic bacteria, for example, generate auxin and have catalase activity, which could help with root growth and stress tolerance, respectively. In addition to their service to the host, these bacteria have other useful properties which may find use in bioremediation as well as medical and industrial applications. One of the endophytic fungi was discovered to produce an agent that can inhibit growth of M. phaseolina. The fungal endophytes of jute express lignin peroxidase, cellulose, and xylanase. These enzymatic activities may be harnessed for applications like biofuel production from lignocellulosic biomass. One particular jute (C. olitorius acc. 2015) endophyte, Grammothele lineata, can produce paclitaxel (Das et al. 2017) (a chemotherapy medication used to treat a number of different cancers) in substantial quantity. G. lineata can produce 382.2 lg L−1 of paclitaxel in potato dextrose broth (PDB), which is 7.6
103 times more than the first paclitaxel-producing endophytic fungus, Taxomyces andreanae. G. lineata is the first reported species of the Basidiomycota phylum that produce paclitaxel. G. lineate holds immense potential as a source for commercial production of paclitaxel. The genome of this strain was examined using a variety of bioinformatics tools to determine whether it was linked to the synthesis of commercially important chemicals such as taxol. (Ehsan et al. 2020). The annotation of carbohydrate-active enzymes (CAZymes), proteases, and secretory proteins indicated a complicated endophytic connection with the plant host. The inclusion of a varied variety of CAZymes, including multiple lignocellulolytic enzymes, supports its biomass breakdown ability. The identification of 28 clusters for secondary metabolite production was made possible by genome annotation. AntiSMASH analysis revealed several biosynthetic

gene clusters for terpene biosynthesis, but none could be explicitly linked to taxol production. Another jute endophyte, Staphylococcus hominis strain MBL AB63, isolated from jute seeds, was discovered to have antibacterial action against a variety of Gram-positive bacteria. BAGEL4 and antiSMASH 5.0 were used to annotate the whole genomic sequence of this strain. This led to the prediction of a gene cluster for a novel antibacterial molecule called Homicorcin, which belongs to the class I lantibiotic group. An novel oxido-reductase enzyme was discovered in the genome, which converts dehydroalanine, the N-terminal first residue of Homicorcin, to 2-hydroxypropionate, resulting in Homicorcin 1. Both Homicorcin and its derivative are highly active and stable at a whole range of pH and temperature (Uddin et al. 2021).

11.6.4 Identification of Stress Related Genes in Jute Calcium-mediated signaling serves as a sensor to different stressor like salinity, drought, and high temperature. Bioinformatics analyses were used to detect CDPK genes in the genomes of C. olitorius and C. capsularis. (Ahmed et al. 2020). The genomes of C. olitorius and C. capsularis contain different sets of CDPKs. In total, 16 and 18 CDPK genes with serine/threonine protein kinase domains and EF-hand calcium-binding domains are present in C. olitorius and C. capsularis, respectively. Expression of these CDPK genes were analyzed in C. olitorius and C. capsularis under stressed conditions (salinity and drought). CoCDPK6, CoCDPK11 and CoCDPK12 (“Co” stands for C. olitorius) in C. olitorius and their corresponding homologs in C. capsularis CcCDPK18, CcCDPK10, CcCDPK8 (“Cc” stands for C. capsularis) were highly expressed under salt and drought stress conditions (Ahmed et al. 2020). CoCDPK6, CoCDPK11, and CoCDPK13 expression was increased in both root and leaf at high salt concentrations, however CcCDPK1, CcCDPK8, CcCDPK10, and CcCDPK18 expression was

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higher in the root than in the leaf. In response to salinity, CoCDPK15 and CoCDPK8 genes were up regulated and two genes CoCDPK4 and CoCDPK9 down-regulated in the roots of both cultivars. In addition, CoCDPK6, CoCDPK7, CoCDPK11, CoCDPK12 in C. olitorius and their homologs in C. capsularis CcCDPK18, CcCDPK17, CcCDPK10 and CcCDPK8 were highly expressed in fiber cells. Functional assessment of these genes may provide more insights about the roles CDPKs on jute physiology. Fasciclin-like arabinogalactan proteins (FLAs) are a type of arabinogalactan protein (AGP) that play a key role in plant growth and development by facilitating cell-to-cell communication and adhesion. FLAs are also linked to the synthesis of fiber and wood in plants. In silico analyses could predict 19 CoFLA genes in toto in the draft genome of C. olitorius (Hossain et al. 2020). Four of these genes (CoFLA11, CoFLA12, CoFLA20, and CoFLA23) were highly expressed in fiber cells, while the expression levels of 6 genes (CoFLA2, CoFLA3, CoFLA4, CoFLA6, CoFLA14 and CoFLA19) were relatively more in stem. CoFLA12 and CoFLA20 had higher expression levels in middle bark tissues, implying that they are involved in fiber elongation. CoFLA11 and CoFLA23, on the other hand, were found to be more prevalent in bottom bark tissues, suggesting that these may be involved in secondary cell wall formation. In plants, the APETALA2/EthyleneResponsive Element Binding Factor (AP2/ERF) super-family contains conserved transcription factors (TF) that play key roles in stress response. In silico analysis of the draft genome of C. olitorius revealed a total of 119 CoAP2/ERF genes (Kabir et al. 2021). RNA-Seq and qRT-PCR were used to analyze the expression levels of these genes in jute under biotic (in the presence of M. phaseolina) and abiotic (water logging, salinity, and drought) conditions. Three genes (CoERF21, CoERF34 and CoERF39) were significantly up regulated under water logging condition and three other genes (CoDREB11, CoDREB14 and CoRAV01) were up regulated under salinity and drought stresses in C. olitorius. Following fungal infection, expression of

Md. Shahidul Islam et al.

CoDREB01, CoDREB28 and CoDREB30 was increased, whereas CoERF01, CoERF39, CoDREB18, CoDREB23 and CoDREB13 genes followed an opposite trend. Genetic engineering techniques like CRISPR/Cas9, TALEN, etc. may be used in future to exploit the function and potential of these genes to address stress responses in the cultivated species of jute.

11.6.5 Reference Genes for Quantitative Gene Expression Analysis Availability of jute genome and transcriptomic data gave an impetus to explore the mechanisms of fiber development, biotic and abiotic stress tolerances, developmental processes, etc. Quantitative gene expression analysis is an important means to understand the spatiotemporal expression and regulation of different genes. However, relative and absolute quantification of gene expression calls for one or more reliable reference genes with stable expression across various biotic and abiotic conditions. The expression of common housekeeping genes often varies a lot depending on the tissue, the environment, and the species. To address this issue, C. olitorius homologs of 11 candidate Arabidopsis genes (28S RNA, ACT7, CYP, EF1A, EF2, ETIF3E, GAPDH, PP2Ac, PTB, UBC2 and UBI1) were retrieved from The Arabidopsis Information Resource (TAIR) database (www.arabidopsis.org) (Hossain et al. 2019). The expression of these genes in C. olitorius was measured in a variety of jute tissues (root, stick, bark, leaf, flower, seed, and fiber), as well as under biotic (after M. phaseolina infestation) and abiotic (waterlogged, drought, and salinity) stress conditions. The candidate genes showed variable expressions under different conditions. The most constant expression in diverse tissues was found for the PP2Ac and EF2 genes, while ACT7 and UBC2 were expressed stably under drought stress. CYP and PP2Ac expressions were stable following infection with M. phaseolina. PP2Ac and UBC2 exhibited stable expression under salt stress.

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Under waterlogged conditions ACT7 and PP2Ac expression level remained more stable. Among the tested genes, PP2Ac appears to be a more widely applicable reference gene for quantitative gene expression analysis.

cell cycle regulation, organelle production, developmental processes, and environmental reactions were identified to be the most common gene targets. Five gene targets (NAC domain containing protein, WRKY DNA binding protein, 3-dehydroquinate synthase, S-adenosyl-LMet–dependent methyl transferase and vascularrelated NAC-Domain) were discovered to be involved in lignin biosynthesis, phenylpropanoid pathways, and secondary wall formation.

11.6.6 Jute Micro-RNAs A deep sequencing strategy for jute small RNAs was undertaken in the year 2015, before the jute genome sequence was publicly available, to identify conserved and novel jute miRNAs (Islam et al. 2015). Because of the sequence homology of this species with jute, the genome data of Vitis vinifera was chosen as a reference in the absence of a jute genome sequence. There were 227 known miRNAs, with 164 belonging to 23 conserved families and 63 belonging to 58 non-conserved families. There were 18 specified families and 40 undefined families among the non-conserved families. Jute conserved miRNA families shared a high degree of similarity with their counterparts in other model plants. The number of family members of conserved miRNAs, on the other hand, was widely diverse, with miR156 having the largest family with 26 members and miR403, miR394, miR827, miR477, and miR2111 having the smallest families with only one member each. miR166 and miR169 were the second largest with each having 18 members, while miR171 was the third largest family with 14 members. Expression of many of these miRNAs was validated by qPCR. A recent work (Ahmed et al. 2021) on jute miRNAs used a comprehensive in silico technique to find and characterize conserved miRNAs in the C. capsularis draft genome sequence, including functional annotation of specific gene targets. The prediction of 5 possible miRNA candidates belonging to five different miRNA families was made using an EST-based homology search of 3350 known dicotyledon miRNAs against 763 non-redundant ESTs of the jute genome (miR1536, miR9567-3p, miR4391, miR11300, and miR8689). A total of 1052 potential miRNA gene targets were discovered and their functions investigated. Plant growth,

11.6.7 Characterization of Gibberellin Metabolism Genes in Jute Gibberellin (also known as Gibberellic acid, GA) is a phytohormone that regulates plant growth and development by taking part in a variety of physiological processes such as seed germination, shoot elongation, leaf expansion, flower formation, and senescence, among others. GAs are a diterpene hormone family that includes over 130 members found in plants, fungi, and bacteria. Geranylgeranyl diphosphate is used to make GAs (GGDP- a common precursor of terpenes in plants). In model plants, GA biosynthesis is well defined, and the majority of genes encoding GA biosynthesis enzymes have been found. This pathway is divided in two steps- early and late, where the early steps convert GGDP to GA12 and the later steps convert GA12 to active GAs. Enzymes that participate in the later steps are more important in the regulation of endogenous level of bioactive GA. Exogenous GA is known to stimulate fiber cell elongation as well as the production of longer stems and internodes in jute. Twenty-two potential GA biosynthesis genes were discovered in a recent genome-wide investigation (Honi et al. 2020). In jute, spatial gene expression analysis revealed that 11 GA oxidases are involved in GA synthesis. Based on their expression characteristics, four of these were identified as important regulators. This in-depth study of GA biosynthesis genes in jute could be used in the future to boost jute and other allied fiber yields.

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11.6.8 Reverse Genetics for Investigating Gene Function The decoding of genomic sequence data has spawned the field of functional genomics, which focuses on determining gene function through the analysis of phenotypic effects caused by changes in specific gene sequences. The Basic and Applied Research on Jute (BARJ) project at BJRI has begun the establishment of a TILLING (Targeted Induced Local Lesions in Genomes) based reverse genetic population of jute to aid functional research. TILLING is a reverse genetics method in which mutations are screened for single nucleotide mutations in a specific region of a gene of interest using highthroughput genotyping. TILLING is a promising non-transgenic method for improving domesticated crops by introducing and discovering unique genetic variation in genes that control critical agricultural properties. The reference genotype of C. olitorius Var. O-4 (produced through pure line selection) was modified with ethyl methane sulfonate (EMS) mutagen to develop the TILLING population at BJRI to define the function of essential genes. In total nearly a million seeds were treated with EMS and sown in Jute Agricultural Experimental station, Manikganj during the year 2011–2012. A total of 1,500 single plant M1 lines yielded fertile M2 seeds. When compared to the parent line, a number of plants in the M2 generation had different morphologies (such as dwarf, bushy, tall, higher bark thickness, cylindrical stem, and difference in fiber color). Among these one variety was found to provide 10–15% higher yield compared to the present cultivable varieties and released for commercial cultivation under the name BJRI Tossa Pat 8 (Robi-1). Efforts are currently underway to expand the other useful variant populations and introduce the traits to other lines and identify the causal genetic variants.

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11.7

Conclusion

Jute genome sequence project has had a huge impact on jute related research in Bangladesh. This project not only helped in the advancement of new knowledge on jute genomics and transcription of important genes of this cash crop of Bangladesh, it also allowed for the development of technical expertise which provided confidence to undertake further NGS related tasks. Data from jute sequencing has opened up possibilities for improving jute yield and fiber quality, as well as expanding the range of potential applications.

References Ahmed B, Alam M, Hasan F, Emdad EM, Islam S, Rahman N (2020) Jute CDPK genes and their role in stress tolerance and fiber development: a genome-wide bioinformatic investigation of Chorchorus capsularis and C. olitorius. Plant Gene 24: 100252 Ahmed M, Ahmed F, Ahmed J, Akhand MRN, Azim KF, Imran MAS, Hoque SF, Hasan M (2021) In silico identification of conserved miRNAs in the genome of fibre biogenesis crop Corchorus capsularis. Heliyon 7 (4): e06705 Ahmed S, Nabi MZ, Alam MM, Islam MS, Samira R, Moosa MM, Khan H (2009) A computational and experimental approach for developing jute ESTs from genomic clones. Aust J Crop Sci 3(6):322–328 Akter J, Islam MS, Sajib AA, Ashraf N, Haque S, Khan H (2008) Microsatellites markers for determining genetic identities and genetic diversity among jute cultivars. Aust J Crop Sci 1(3):97–107 Das A, Rahman MI, Ferdous AS, Amin A, Rahman MM, Nahar N, Uddin MA, Islam MR, Khan H (2017) An endophytic Basidiomycete, Grammothele lineata, isolated from Corchorus olitorius, produces paclitaxel that shows cytotoxicity. PLoS One 12(6): e0178612 Ehsan T, Reza RN, Das A, Ahmed O, Baten AKMA, Ferdous AS, Khan H (2020) Genome and secretome analysis of jute endophyte Grammothelelineata strain SDL-CO-2015-1: Insights into its lignocellulolytic structure and secondary metabolite profile. Genomics 112(4):2794–2803 Honi U, Amin MR, Kabir SMT, Bashar KK, Moniruzzaman M, Jahan R, Jahan S, Haque MS, Islam S (2020) Genome-wide identification, characterization and expression profiling of gibberellin metabolism genes in jute. BMC Plant Biol 20(1):306

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Hossain MS, Ahmed B, Ullah MW, Aktar N, Haque MS, Islam MS (2020) Genome-wide identification of fasciclin-like arabinogalactan proteins in jute and their expression pattern during fiber formation. Mol Biol Rep 47(10):7815–7829 Hossain MS, Ahmed R, Haque MS, Alam MM, Islam MS (2019) Identification and validation of reference genes for real-time quantitative RT-PCR analysis in jute. BMC Mol Biol 20(1):13 International Jute Study Group (2010) Jute Basics. 1 ed, Dot Net Limited. Dhaka-1215, Bangladesh Islam MS, Haque MS, Islam MM, Emdad EM, Halim A, Hossen QM, Hossain MZ, Ahmed B, Rahim S, Rahman MS, Alam MM, Hou S, Wan X, Saito JA, Alam M (2012) Tools to kill: genome of one of the most destructive plant pathogenic fungi Macrophomina phaseolina. BMC Genomics 13:493 Islam MS, Saito JA, Emdad EM, Ahmed B, Islam MM, Halim A, Hossen QM, Hossain MZ, Ahmed R, Hossain MS, Kabir SM, Khan MS, Khan MM, Hasan R, Aktar N, Honi U, Islam R, Rashid MM, Wan X, Hou S, Haque T, Azam MS, Moosa MM, Elias SM, Hasan AM, Mahmood N, Shafiuddin M, Shahid S, Shommu NS, Jahan S, Roy S, Chowdhury A, Akhand AI, Nisho GM, Uddin KS, Rabeya T, Hoque SM, Snigdha AR, Mortoza S, Matin SA, Islam MK, Lashkar MZ, Zaman M, Yuryev A, Uddin MK, Rahman MS, Haque MS, Alam MM, Khan H, Alam M (2017) Comparative genomics of two jute species and insight into fibre biogenesis. Nat Plants 3:16223 Islam MT, Ferdous AS, Najnin RA, Sarker SK, Khan H (2015) High-Throughput Sequencing Reveals Diverse Sets of Conserved, Nonconserved, and SpeciesSpecific miRNAs in Jute. Int J Genomi 2015: 125048 Kabir SMT, Hossain MS, Bashar KK, Honi U, Ahmed B, Emdad EM, Alam MM, Haque MS, Islam MS (2021) Genome-wide identification and expression profiling of AP2/ERF superfamily genes under stress conditions

in dark jute (Corchorus olitorius L.). Industr Crops Products 166: 113469 Mir RR, Rustgi S, Sharma S, Singh R, Goyal A, Kumar J, Gaur A, Tyagi AK, Khan H, Sinha MK, Balyan HS, Gupta PK (2008) A preliminary genetic analysis of fibre traits and the use of new genomic SSRs for genetic diversity in jute. Euphytica 161:413–427 Najnin RA, Shafrin F, Polash AH, Zaman A, Hossain A, Taha T, Ahmed R, Tuli JF, Barua R, Sajib AA, Khan H (2014) A diverse community of jute (Corchorus spp.) endophytes reveals mutualistic host–microbe interactions. Ann Microbiol 65(3): 1615–1626 Nath M, Chowdhury FT, Ahmed S, Das A, Islam MR, Khan H (2021) Value addition to jute: assessing the effect of artificial reduction of lignin on jute diversification. Heliyon 7(3): e06353 Samira R, Moosa MM, Alam MM, Keka SI, Khan H (2010) In silico analysis of jute SSR library and experimental verification of assembly. Plant Omics J 3 (2):57–65 Shafrin F, Das SS, Sanan-Mishra N, Khan H (2015) Artificial miRNA-mediated down-regulation of two monolignoid biosynthetic genes (C3H and F5H) cause reduction in lignin content in jute. Plant Mol Biol 89 (4–5):511–527 Shafrin F, Ferdous AS, Sarkar SK, Ahmed R, Amin A, Hossain K, Sarker M, Rencoret J, Gutierrez A, Del Rio JC, Sanan-Mishra N, Khan H (2017) Modification of monolignol biosynthetic pathway in Jute: different gene different consequence. Sci Rep 7:39984 Uddin MA, Akter S, Ferdous M, Haidar B, Amin A, Molla AHMSI, Khan H, Islam MR (2021) A plant endophyte Staphylococcus hominis strain MBL_AB63 produces a novel lantibiotic, homicorcin and a position one variant. Sci Rep 11:11211 Wazni MW, Islam AS, Taliaferro JM, Anwar N, Sathasivan K (2007) Novel ESTs from a Jute (Corchorus olitorius L.) cDNA Library. Plant Tissue Cult Biotechnol. 17(2): 173–182

Jute Genome Sequencing: A Chinese Initiative

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Xin Yang, Hu Li, Lilan Zhang, Siyuan Chen, and Liwu Zhang

Abstract

Jute (Corchorus L.) is one of the important fiber crops, and its fiber yield accounts for about 80% of the total bast fiber yield in the world. Compared with other crops, there is a lack of high-quality reference genome for researches, which has seriously hindered genetic studies and limited the application of jute fiber improvement. Here, the initiative jute genome sequencing in China was launched by Fujian Agriculture and Forestry University and other related institutes in 2012. Two high-yield, good-quality and disease-resistant jute varieties, ‘Huangma 179’ (Corchorus capsularis) and ‘Kuanyechangguo’ (C. olitorius), were selected for reference genome sequencing. They were sequenced for the whole genome sequences

X. Yang
H. Li
L. Zhang
S. Chen
L. Zhang (&) Key Laboratory of Ministry of Education for Genetics, Breeding and Multiple Utilization of Crops / Fujian Key Laboratory for Crop Breeding By Design, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China e-mail: [email protected] X. Yang
H. Li
L. Zhang
S. Chen
L. Zhang Experiment Station of Ministry of Agriculture and Rural Affairs for Jute and Kenaf in Southeast China / Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China

by PacBio RSII, and assembled by CANU package in 2017. As a result, 336 Mb of C. capsularis and 361 Mb of C. olitorius, including seven pseudo-chromosomes, were assembled. The two jute chromosome-scale genomes, that are publicly accessible at https:// bigd.big.ac.cn, will provide new insights for analyses of the fiber biogenesis, and other biologically important traits in jute.

12.1

Introduction

The two cultivated jute species (2n = 2x = 14), white jute (C. capsularis) and dark or tossa jute (C. olitorius), are the second most important bast (phloem) fiber source after cotton. Both are cultivated as a raw material to produce coarse cloth, paper, rope, canvas and so on in Bangladesh, India and China. With the development of genome sequencing tecnnology, we can reveal the mechanism of plant development, growth and differentiation at the molecular level by analyzing plant genome data. And it will help us to analyze genome structure and gene functions. Currently, more and more fiber-producing plant species completed the whole-genome sequencing, such as H. cannabinus (Zhang et al. 2020), Cannabis sativa (van Bakel et al. 2011) and Gossypium hirsutum (Li et al. 2015). The whole genome sequencing of fiber crops can not only analyze the molecular mechanism of fiber

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_12

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development, but also facilitate genetic engineering to obtain new varieties with excellent agricultural features (Niyitanga et al. 2021). The draft genomes of ‘CVL-1’ (C. capsularis) and ‘O-4’ (C. olitorius) were launched by Islam et al. The initial strategy is based on WGS sequencing and assembled the genomes using CABOG6. However, the initial assemblies were composed of contigs that were often arbitrarily ordered and oriented (Islam et al. 2017). To get the high-quality reference genomes, it is imperative to combine the PacBio RSII sequencing with high-density genetic map and Hi-C technology to assemble the jute genomes (Zhang et al. 2021).

12.2

Jute Genome Sequencing, Assembly and Annotation

The plants of ‘Huangma 179’ (Corchorus capsularis) (Cc) and ‘Kuanyechangguo’ (C. olitorius) (Co) were grown at the farm of Fujian Agriculture and Forestry University, Fuzhou, China in 2015. For the PacBio sequencing, DNA was extracted from young leaves and sequenced on the Illumina HiSeq platform. Then, raw single molecule real-time (SMRT) data of approximately 41 Gb (*120 coverage) of C. capsularis (Cc) and 41Gb (*112 coverage) of C. olitorius (Co) were generated using the PacBio Sequel System (Table 12.1). The two jute genomes were assembled by CANU package for contig assembly and selfcorrection. Subsequently, the draft assembly was polished using Quiver. Illumina short reads were recruited to increase the accuracy of assembly, and for further polishing using the Pilon

Table 12.1 PacBio sequencing data in C. capsularis (Cc) and C. olitorius (Co) (Zhang et al. 2021)

program. We generated 340 Mb and 394 Mb genome assembly for ‘Huangma 179’ (Corchorus capsularis) and ‘Kuanyechangguo’ (C. olitorius), respectively (Table 12.2). We also evaluated the integrity of the assembly using the CEGMA v2.5 and BUSCO version 3. Hi-C was used to assist the assembly of jute genome, and 148,568,585 and 239,559,361 clean paired-end reads for Cc and Co, respectively were obtained (Table 12.3). The Hi-C heatmap of the final assembly showed the connection between chromosomes in the centromere and telomere regions, which means the accuracy of the chromosome connection (Figure 12.1). The assembly has 336 Mbp of sequences for Cc with an N50 of 46 Mb and 361 Mbp for Co with an N50 of 50 Mb (Table 12.2, Figure 12.2), and the assembly index has been greatly improved compared with that previously published genomes (Islam et al. 2017). To detected the quality of Cc and Co genome assembly, it was evaluated by BUSCO (Benchmarking Universal Single-Copy Orthologs). The results showed that complete, fragmented and missing BUSCOs in C. capsularis were 94.2%, 2.1% and 3.7%, respectively. While, complete, fragmented and missing BUSCOs in C. olitorius were 94.4%, 2% and 3.6%, respectively. These data indicate that the current two jute genomes are more complete than the earlier jute genome assembly (Table 12.4). In addition, we analyzed the assembly results of jute genome by software CEGMA. The results indicated that 86.1% and 90.8% of the gene models were detected as complete in the assembled genome sequences of C. capsularis and C. olitorius, respectively (Table 12.5). By searching 248 conserved eukaryotic genes

Sequence data

Cc

Co

Total number of reads

4,614,998

4,676,413

Total number of sequenced Bases (Gb)

41

41

Mean subreads length (bp)

8,878

8,463

N50 (Subreads length, bp)

12,527

11,723

Coverage (X)*

120

112

*

Coverage (X) = (read length * read number)/ estimated genome size

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Jute Genome Sequencing: A Chinese Initiative

Table 12.2 Summary of the genome assembly of C. capsularis and C. olitorius (Zhang et al. 2021)

Table 12.3 Statistics of mapping and Hi-C sequencing of C. capsularis and C. olitorius (Zhang et al. 2021)

Items

187 Contig level assembly

Chromosomal-level assembly

C. capsularis

C. olitorius

C. capsularis

C. olitorius

No. of sequences

340

678

71

284

Max length (Mb)

17

15

57

60

Total size (Mb)

340

394

336

361

N50 (Mb)

3,2

1,5

46

50

Average length (bp)

1,001,680

580,535

4,797,158

1,386,532

Statistics of mapping

C. capsularis

C. olitorius

Clean Paired-end Reads

148,568,585

239,559,361

Unmapped Paired-end Reads

5,263,469

9,191,837

Unmapped Paired-end Reads Rate (%)

3.543

3.837

Paired-end Reads with Singleton

75,072,434

160,092,332

Paired-end Reads with Singleton Rate (%)

50.53

66.828

Multi-Mapped Paired-end Reads

16,753,609

13,085,599

Multi-Mapped Ratio (%)

11.277

5.462

Unique Mapped Paired-end Reads

51,479,073

57,189,593

Unique Mapped Ratio (%)

34.65

23.87

Unique Mapped Paired-end Reads

51,479,073

57,189,593

Dangling End Paired-end Reads

1,591,027

3,418,909

Dangling End Rate (%)

3.09

5.98

Self-Circle Paired-end Reads

924,196

336,323

Self-Circle Rate (%)

1.79

0.59

Dumped Paired-end Reads

11,933,170

11,561,565

Statistics of valid reads

Dumped Rate (%)

23.18

20.21

Interaction Paired-end Reads

36,345,735

40,599,248

Interaction Rate (%)

70.19

70.99

Lib Valid Paired-end Reads

28,073,957

35,500,285

Lib Valid Rate (%)

54.53

62.07

Lib Dup (%)

45.47

37.93

(CEGs), we found that the genome of C. capsularis covered 235 (94.76%) complete gene elements and 244 (98.39%) partial gene elements, while the genome of C. olitorius covered 240 (96.77%) complete gene elements and 245 (98.79%) partial gene elements (Table 12.6). These indicated that the genome assembly of

these two jute species was relatively complete and feasible. By comparison of six plant genomes (A. thaliana, B. rapa, V. vinifera, P. trichocarpa, O. sativa and C. papaya) with C. capsularis and C. olitorius, the predicted genes, the average lengths of CDS and exxon as well as intron in

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Fig. 12.1 Hi-C heatmap of C. capsularis (Cc) and C. olitorius (Co) using 150 kb resolution (Zhang et al. 2021) Fig. 12.2 A flowchart of the pipeline for the assembly of the two jute genomes

the C. capsularis genome are 25,874, 219.67 bp, 267.56 bp, and 404.96 bp respectively, while those in C. olitorius genome are 28,479 genes, 229.18 bp, 276.06 bp and 405.29 bp, respectively (Table 12.7). Repeat sequences are widely distributed in eukaryotic genomes and are closely related to genetic variation and evolution of species. Repeats are usually distributed or clustered in

different positions of the genome, which is one of the important factors affecting the size of the genomes. Therefore, we identified and analyzed repeat sequences of the two jute genomes after genome assembly and annotation. The results showed that total repeat fraction, Class I: retroelement and Class II: DNA transposon of C. capsularis 482666 (53.6%), 196879 (36.03%) and 135381 (10.64%) respectively, while those

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Table 12.4 The statistics of genome assembly of C. capsularis (Cc) and C. olitorius (Co) using BUSCO (Zhang et al. 2021) Description

Cc Number

embryophyta_odb9

embryophyta_odb10

Co Percentage (%)

Number

Percentage (%)

Complete BUSCOs (C)

1359

94.4

1360

94.5

Complete and single-copy BUSCOs (S)

1325

92

1326

92.1

Complete and duplicated BUSCOs (D)

34

2.4

34

2.4

Fragmented BUSCOs (F)

26

1.8

25

1.7

Missing BUSCOs (M)

55

3.8

55

3.8

Total BUSCO groups searched

1440

100

1440

100

Complete BUSCOs (C)

2191

94.2

2195

94.4

Complete and single-copy BUSCOs (S)

2138

91.9

2147

92.3

Complete and duplicated BUSCOs (D)

53

2.3

48

2.1

Fragmented BUSCOs (F)

48

2.1

46

2

Missing BUSCOs (M)

87

3.7

85

3.6

Total BUSCO groups searched

2326

100

2326

100

Table 12.5 Gene annotation analysis of C. capsularis (Cc) and C. olitorius (Co) using BUSCO (Zhang et al. 2021) Description Complete BUSCOs (C)

Cc

Co

Number

Percentage (%)

Number

Percentage (%)

1240

86.1

1308

90.8

Complete and single-copy BUSCOs (S)

1207

83.8

1269

88.1

Complete and duplicated BUSCOs (D)

33

2.3

39

2.7

Fragmented BUSCOs (F)

78

5.4

49

3.4

Missing BUSCOs (M)

122

8.5

83

5.8

Total BUSCO groups searched

1440

100

1440

100

of C. olitorius was 529791 (59.33%), 229833 (40.91%) and 152361 (13.00%) respectively. Among the repeat sequences of two jute species, retroelement is the most abundant type. Long terminal repeat (LTR) is the most abundant type of transposable elements, accounting for 50.69% and 53.66% of the repeats of Cc and Co, respectively. These results are similar to the early jute genome (Islam et al. 2017). Further sequence analysis showed that gypsy was the most widespread LTR in the genomes of two jute species,

accounting for 16.11% and 21.12% of the genomes of Cc and Co, respectively (Table 12.8). Then, the single-copy genes of each jute species were identified using the PYTHON script on the basis of the OrthoMCL clusters and multiple alignments of protein sequences with MUSCLE (Edgar 2004). Divergence times between Cc, Co and other Malvaceae (G. raimondii and T. cacao) were estimated using MEGA (Tamura et al. 2011). The divergence time of G. raimondii (Gr) and T. cacao (Th) is

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Table 12.6 CEGMA analysis of C. capsularis (Cc) and C. olitorius (Co) genomes (Zhang et al. 2021) Description

C. capsularis

C. olitorius

Fully mapped CEGs

Fully + partially mapped CEGs

Fully mapped CEGs

Fully + partially mapped CEGs

Number of CEGs present in the assembly

235

244

240

245

Completeness of the genome (%)

94.76

98.39

96.77

98.79

Average number of orthologs per CEG

1.66

1.83

1.64

1.85

CEGs with more than one ortholog (%)

40.85

47.13

40.42

48.16

Table 12.7 General Statistics of predicted protein-coding genes in several plant genomes (Zhang et al. 2021) Gene set

Total numbers of gene

Average length of CDS (bp)

Average length of exon (bp)

Average length of intron (bp)

A. thaliana

45,483

950

242

237

C. papaya

45,992

835

238

213

P. trichocarpa

46,063

845

231

223

V. vinifera

38,783

949

233

232

O. sativa

34,875

1009

255

229

B. rapa

41,174

1172

233

209

C. capsularis (Huangma 179)

25,874

219.67

267.56

404.96

C. olitorius (Kuanyechangguo)

28,479

229.18

276.06

405.29

approximately 28.66 MYA (Million years ago), Cc and Gr is approximately 38.27 MYA, Cc and Th is approximately 16.75 MYA, and Cc and Co is approximately 4.63 MYA (million years ago) (Table 12.9).

12.3

Important Events of Jute Breeding and Genome Sequencing in China

China is one of the world's major suppliers of jute fiber. There are six varieties arising in China since the founding of new China in 1949. The representive varieties from Fujian Agriculture and Forestry University and important events of genome sequencing are as follows. 1915–1919: Introduction of jute

varieties ‘D154’ (Corchorus capsularis) and ‘Cuilv’ (Corchorus olitorius) from India. The two introduced varieties increased yield significantly and gradually became the main varieties in jute production area at that time. 1958: The local varieties ‘Hongtiegu’ (Corchorus capsularis) collected from Nan'an, Quanzhou, Fujian. 1961–1965: An elite jute variety ‘Guangfengchangguo’ (Corchorus olitorius) was systematically selected from a farm cultivar in ‘Guangfeng’. 1958–1963: ‘Yueyuan 5’ (Corchorus capsularis) was selected from hybridization progenies of ‘Yueyuan 1’ and ‘Xinyuan 2’. In the 1970s– 1980s, ‘Yueyuan 5’ became one of the largest variety in China at that time. It was widely planted in the Yangtze River Valley, which

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Table 12.8 Summary of different types of transposable elements in C. capsularis (Cc) and C. olitorius (Co) genomes (Zhang et al. 2021) C. capsularis

C. olitorius

Number

Length (bp)

% of repeats

% of genome

Number

Length (bp)

% of repeats

% of genome

Total repeat fraction

482,666

182,562,750

100

53.6

529,791

233,621,785

100

59.33

Class I: Retroelement

196,879

122,711,710

67.22

36.03

229,833

161,078,125

68.95

40.91

LTR Retrotransposon

106,862

92,539,611

50.69

27.17

124,639

125,365,119

53.66

31.84

Ty1/Copia

18,445

12,970,077

7.1

Ty3/Gypsy

46,219

54,887,128

30.06

3.81

16,923

14,437,327

6.18

3.67

16.11

60,428

83,170,456

35.6

21.12

Other

42,198

24,682,406

13.52

7.25

47,288

27,757,336

11.88

7.05

Non-LTR Retrotransposon

55,433

22,029,792

12.07

6.47

64,001

26,188,610

11.21

6.65

LINE

43,204

20,558,985

11.26

6.04

49,646

24,136,737

10.33

6.13

SINE

12,229

1,470,807

0.81

0.43

14,355

2,051,873

0.88

0.52

Unclassified retroelement

34,584

8,142,307

4.46

2.39

41,193

9,524,396

4.08

2.42

Class II: DNA transposon

135,381

36,248,759

19.86

10.64

152,361

51,203,504

21.92

13

CMC [DTC]

2108

921,776

0.5

0.27

3197

1,330,302

0.57

0.34

hAT

17,669

5,255,489

2.88

1.54

14,200

5,361,051

2.29

1.36

TIR

Mutator

10,350

3,488,794

1.91

1.02

4393

1,701,379

0.73

0.43

Tc1/Mariner

5245

1,026,065

0.56

0.3

6406

1,221,085

0.52

0.31

PIF/Harbinger

2707

635,360

0.35

0.19

1727

392,559

0.17

0.1

Other

92,057

23,895,210

13.09

7.02

116,032

39,976,043

17.11

10.15

Helitron

1957

869,172

0.48

0.26

2708

1,127,689

0.48

0.29

Tandem Repeats

128,852

27,563,620

15.1

8.09

126,158

30,913,572

13.23

7.85

Unknown

13,770

4,659,831

2.55

1.37

18,222

5,682,247

2.43

1.44

Table 12.9 Phylogenetic analysis of different plants in the Malvaceae family (Zhang et al. 2021)

Ks_median

Divergence time (MYA)

Cc-Co

0.0601764

4.63

Cc-Gr

0.497513

38.27

Cc-Th

0.217796

16.75

Gr-Th

0.372586

28.66

Cc: C. capsularis; Co: C. olitorius; Gr: G. raimondii; Th: T. cacao; MYA: Million years ago

192

increased the yield by more than 10% compared with the local varieties. 1963–1969: ‘Meifeng 4’ (Corchorus capsularis), which has strong resistance to anthracnose and stem blight disease, was selected from hybridization progenies of 'Yueyuan 1' and ‘Lvbinyuanguo’. 1970: Fujian Agriculture and Forestry University individually selected a new variety ‘Kuaizaohong’ (Corchorus capsularis L.) from the mixed population. 1970–1980: ‘Kuanyechangguo’ (Corchorus olitorius) was selected from hybridization progenies of ‘Guangfengchangguo’ and ‘Bachang 4’. Its resistance to black spot anthracnose is stronger than ‘Guangfengchangguo’. 1977–1980: A high-yield, good-quality and disease-resistant jute variety ‘Huangma 179’ was selected from hybrid progenies of ‘Meifeng 2’ and ‘Minma 5’ by Fujian Agriculture and Forestry University. Since 1979, it has become a popular variety in China. 1999: ‘Fuhuangma 3’ (Corchorus capsularis) was selected from hybrid progenies of ‘Meifeng 2’ and ‘Minma 5’ by Fujian Agriculture and Forestry University. 2006–2009: A Jute vegetable variety ‘Funong 1’ (Corchorus olitorius) was bred by Nuclear physics mutagenesis breeding techniques. It has good palatability and high nutritional value. Dec. 2015: De novo transcriptome of 'Huangma 179' was published in BMC Genomics (Zhang et al. 2015). Oct. 2018: In the National Congress of Plant Biology in Tai’an, Shandong, China, Liwu Zhang reported the reference genomes of the two jute varieties, ‘Kuanyechangguo’ and ‘Huangma 179’, obtained by using PacBio RSII sequencing, high-density genetic map and Hi-C technology. Jun. 2021: The genome sequence of two jute varieties ‘Kuanyechangguo’ and ‘Huangma 179’

X. Yang et al.

was published in Plant Biotechnology Journal (Zhang et al. 2021). The Database of whole genome sequences (dark jute (PRJCA002487, SAMC153388, GWHBCLB00000000); white jute (PRJCA002486, SAMC153387, GWHBCL C00000000)), are publicly accessible at NGDC (https://ngdc.cncb.ac.cn/).

References Bakel HV, Stout JM, Cote AG, Tallon CM, Sharpe AG et al (2011) The draft genome and transcriptome of Cannabis sativa. Genome Biol 12:R102 Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32(5):1792–1797 Islam MS, Saito JA, Emdad EM, Ahmed B, Islam MM et al (2017) Comparative genomics of two jute species and insight into fibre biogenesis. Nature Plants 3:16223 Li FG, Fan GY, Lu CR, Xiao GH, Zou CS et al (2015) Genome sequence of cultivated Upland cotton (Gossypium hirsutum TM-1) provides insights into genome evolution. Nat Biotechnol 33(5):524–530 Niyitanga S, Yang X, Guerriero G, Jin SX, Qi JM et al (2021) Editorial: applied genetics of natural fiber plants. Front Genetics 12:647225 Tamura K, Peterson D, Peterson N, Stecher G, Nei M et al (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28(10):2731–2739 Zhang LW, Zhang LL, Xu Y, Zhang XT, Ma XK et al (2020) The genome of kenaf (Hibiscus cannabinus L.) provides insights into bast fibre and leaf shape biogenesis. Plant Biotechnol J 18:1796–1809 Zhang LL, Ma XK, Zhang X T, Xu Y, Ibrahim AK et al (2021) Reference genomes of the two cultivated jute species. Plant Biotechnol J. https://doi.org/10.1111/ pbi.13652 Zhang LW, Ming R, Zhang JS, Tao AF, Fang PP et al (2015) De novo transcriptome sequence and identification of major bast-related genes involved in cellulose biosynthesis in jute (Corchorus capsularis L.). BMC Genomics 16: 1062

Comparative Genomics and Synteny Within Corchorus Species and Among Malvaceae Genomes

13

Muhammad Zohaib Afzal, Niaz Mahmood, Mahdi Muhammad Moosa, Aminu Kurawa Ibrahim, Siyuan Chen, and Liwu Zhang

Abstract

Jute (Corchorus spp.) is an important bast fiber crop which covers 80 percent of the bast fiber production worldwide. This crop belongs to the Malvaceae family, which includes 243 genera of flowering plants with many of important crop species. The only two cultivated species of jute (C. capsularis and C. olitorius) are found worldwide, whose stem barks are used to produce the fiber. The fiber is used for making ropes, sackings, papers, twines, bags, burlaps, yarn, coarse cloths, and so on. This chapter reviews the available genomic information among the Corchorus species. Besides, we discuss the comparative genetic studies between the jute and other

M. Z. Afzal
A. K. Ibrahim
S. Chen
L. Zhang (&) College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China e-mail: [email protected] N. Mahmood Department of Biochemistry, Goodman Cancer Research Centre, McGill University, Montreal, QC 313, Canada M. M. Moosa Department of Physics, University at Buffalo, Buffalo, NY 14260, USA A. K. Ibrahim Department of Agronomy, Faculty of Agriculture, Bayero University Kano, PMB 3011, Kano State, Nigeria

Malvaceae plants. The present information will be helpful for future comparative genomic studies and for improvement of jute.

13.1

Introduction

The Malvaceae family comprises of 243 genera (including Corchorus) with 4225 known species that are dispersed across the world, particularly in the tropical areas. This family includes the flowering plants with many important crop species (Tanmoy et al. 2015; Chase et al. 2016). Corchorus (jute) genus consists of more than 100 species that include some shrubs, subshrubs, or herbs distributed in the tropics, sub-tropics, and warm temperate regions (Saha et al. 2017; Benor 2018). Most of the Corchorus species have geographical distribution in Africa, especially in Tanzania, Ethopia, and South Africa (Benor et al. 2010, 2012). This genus was earlier included in Tiliaceae family but now it has been transferred to Malvaceae (subfamily, Grewioideae) (Bayer 1998; Alverson et al. 1999). The majority of the species under the mentioned genus are similar in morphology, and species identification is very difficult at the vegetative stage. However, a careful analysis for the presence or absence and color of stipules and setae helps in differentiating the species at this stage. The right identification for the Corchorus spp. is possible at the reproductive phase by using seed and capsule morphologies (Benor 2018). Corchorus spp. have a

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_13

193

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M. Z. Afzal et al.

haploid chromosome number of seven (n = 7), except the natural polyploid species (n = 14), including C. hirtus L., C. siliquosus L., C. cunnighamii, C. argutus, C. pascuorum, C. junodii, and C. orinocensis (Sarkar et al. 2017). There are only two cultivated species of jute (C. capsularis and C. olitorius) that are utilized as a key source for natural fiber production (Benor et al. 2012). C. olitorius (tossa jute) occupies 90% of the jute cultivated area with high production potential as compared to C. capsularis (Maiti et al. 2011). The cultivation of jute was first occurred 200 years back in the tropics (Basu et al. 2004). Jute covers approximately 80% of the global bast fiber production and generates a total farm value of 2.3 billion US dollars annually (Islam et al. 2017). Both the cultivated species are physiologically and morphologically different, and interspecific hybridization is limited due to their crossincompatibility (Patel and Datta 1960; Swaminathan et al. 1961). The lignocellulosic jute fiber is a vital source of fiber for ropes, sackings, twines, bags, burlaps, yarn, and carpet backing cloths. Besides, jute has applications in geotextiles, agriculture, automobiles, biofuels, paper, and pulp industries (Roul 2009; Rahman 2010; Satya and Chakraborti 2015). Here, we will review the comparative genomics and syntenic relationships among the jute species and in the Malvaceae genomes.

13.2

Jute: Origin and Dispersal

The genus Corchorus comprises more than 100 dicotyledonous species of herbs, shrubs, and subshrubs that have their distribution in the tropics, subtropics, and temperate latitudes of the world (Bayer 1998; Kubitzki and Bayer 2013; Tanmoy et al. 2015; Saha et al. 2017; Benor 2018). The two widely cultivated species belonging to this genus are and C. capsularis and C. olitorius (also known as white jute and tossa jute, respectively), whose stem barks are used to produce the jute fiber while the leaves are consumed as vegetables (Benor et al. 2010). The origin and evolution of the Corchorus genus in

general and its two main cultivated species, in particular, has been a matter of discrepancy for decades due to the lack of comparable molecular evidence in addition to the morphological data (Edmonds 1990; Mahapatra et al. 1998). According to the previously hailed notion that mainly relied on species adaptation and biogeographic diversity, C. olitorius originated in Africa while C. capsularis is native to the IndoMyanmar region (Kundu 1951, 1956). With the advancement of molecular phylogenetics, it is now clear that Corchorus is monophyletic, and both C. olitorius and C. capsularis originated from Africa (Benor 2011, 2018; Tanmoy et al. 2015). Benor analyzed the internal transcribed spacer (ITS) region, most widely used to differentiate between species, and demonstrated that two cultivated Corchorus species are monophyletic (Benor 2011). Kundu et al. used a combination of morphological characteristics and molecular markers to assess the evolutionary origin of the two cultivated jute species and concluded that both originated in Africa (Kundu et al. 2013). Tanmoy et al. performed a comprehensive analysis of three different regions of the chloroplast DNA (MatK, IGS1 and IGS2), the ITS regions as well as the evolutionarily conserved xyloglucan endotrans glucosylase/hydrolase (XTH) gene of different species of Corchorus and reported that C. olitorius and C. capsularis are related to each other through maternal inheritance (Tanmoy et al. 2015). How the latter species migrated to the Indo-Myanmar region and subsequently attained different morphological and genetic features remains a scientific conundrum. There are several hypotheses regarding the dispersal of Corchorus from Africa to the Indian subcontinent (Benor et al. 2012; Tanmoy et al. 2015). Benor and colleagues postulated that the dispersal of jute from the East African region (Ethiopia) to Asia occurred through the Mediterranean-Indian trade route (Benor et al. 2012). However, this hypothesis does not completely align with the archeological evidence. Trade relationship between India and East Africa (Ethiopia) only dating back to the first century AD, while the use of jute-based clothing (from

13

Comparative Genomics and Synteny Within Corchorus Species …

the fibers of C. olitorius and C. capsularis) in the Indus civilization dates back to the second millennium BC (Stearns 2001; Wright et al. 2012). This implies that jute plant already existed in the Indian subcontinent even before the trade relation between East Africa and the Indian subcontinent was established. There are records of a trade route between India and Egypt called the lapis lazuli in the third millennium BC (Rao 1985). Another trade route between Ethiopia and Egypt existed from the fourth millennium BC (Greene 1989). Accounting for these archeological evidences, Tanmoy and colleagues proposed a model of jute dispersal where the seeds were brought to the Indian subcontinent from East Africa by the Egyptian traders somewhere between the third and fourth millennium BC (Tanmoy et al. 2015). Another possible migration route of jute from East Africa to the Indian subcontinent is through the currents of the Indian Ocean that flows along the East African coast before reaching the coastal regions of India (Tanmoy et al. 2015). Migratory birds have played a significant role in the LDD (longdistance dispersal) of plants across various parts of the world (Higgins et al. 2003; Nathan et al. 2008). Such dispersion of jute seeds through the migratory birds could also explain Corchorus migration from Africa to India.

13.3

Early Glimpse into the Genomes of Different Jute Species

13.3.1 Molecular Marker-Based Characterization Molecular markers have great significance in genetic diversity analysis, trait categorization, gene mapping, genes detection on map, and crop improvement (Sobha et al. 2019). The different types of molecular markers have been discovered and applied in jute for the genetic diversity and evoutionary studies, linkage map construction, and QTLs identification (Satya and Chakraborti 2015; Saha et al. 2017). These markers include genomic SSRs (Huq et al. 2009; Mir et al. 2009;

195

Das et al. 2012; Topdar et al. 2013; Ghosh et al. 2014; Zhang et al. 2015a; Zhang et al. 2015c; Yang et al. 2018b; Adeyemo et al. 2021), ESTSSRs (Zhang et al. 2014; Zhang et al. 2015b; Saha et al. 2017), RAPD (Haque et al. 2008; Ogunkanmi et al. 2010; Mandal et al. 2013; Chen et al. 2014), AFLPs (Das et al. 2011; Ghosh et al. 2014), SRAPs (Chen et al. 2014), ISSRs (Mandal et al. 2013; Chen et al. 2014), SNPs (Biswas et al. 2015; Yang et al. 2019b) RAD (Kundu et al. 2015), SLAFs (Tao et al. 2017), and InDels (Zhang et al. 2017; Yang et al. 2018a).

13.3.1.1 Simple Sequence Repeats A total of 4,509 SSR loci were dicovered by Saha et al. (2017) from 34,163 unigenes of C. capsularis. The trinucleotide sequences were more frequet followed by the dinucletide repeats. Saha et al. (2017) validated 74 primer pairs among the twenty four accessions. Among them, 43 pairs of primers generated an average of 2.7 allels and 58% polymorphism. Zhang et al. (2015b) identified 1906 EST-SSRs from the assembled 48,914 unigenes of white jute. The di, tri, and tetranucleotide types were the abundant, and AG rich repeats were predominant. Moreover, 97 polymorphic SSRs were utilized to evaluate the GSC (genetic similarity coefficients) for the twelve jute accessions. Cluster analysis separated the genotypes into two major groups with GSC of 0.61 (Zhang et al. 2015b). Genetic diversity among 16 C. olitorius cultivars was assessed by using 13 polymorphic SSR markers of dark jute. In total, 41 alleles revelaed amplification with a mean value of 2.75 per locus. The PIC (polymorphism information content) value was in the range of 0.06 to 0.73 with a mean value of 0.42. The results indicated the moderate genetic dissimilarity among the studied cultivars (Adeyemo et al. 2021). Yang et al. (2018b) analyzed the genetic variations and population structure among 453 C. olitorius accessions of by using thirty nine SSR markers. The results showed the moderate genetic diversity among all accessions with mean genetic diversity and PIC values of 0.322 and 0.270, respectively. The population structure analysis separated the genotypes into two populations

196

(Pop. 1 and Pop. 2) that were further divided into three and two subpopulations, respectively. Fifty eight jute accessions were evaluated by Zhang et al. (2015a) with 28 SSR primer pairs. The 184 polymorphic loci were observed, and each primer identified three to fifteen polymorphic loci. The GSC was ranging from 0.520 to 0.910 which revealed a relatively high genetic diversity for the studied genotypes (Zhang et al. 2015a). Also, the genetic structure and relationships among 159 jute accessions were assessed by using 63 SSR markers. The accessions were from 11 different countries and regions. Structural analysis classified the accessions into C. olitorius (Cc) and C. casularis (Cc) groups, and each group was further divided into two subgroups. Besides, the genetic relationship study identified the most diverse genotypes from both dark and white jute (Zhang et al. 2015c). Moreover, Topdar et al. (2013) reported a complete SSRs-based genetic map in C. olitorius by using F6 RIL population. Among the 403 screened microsatellites (SSRs), eighty two were mapped on 7 LGs (linkage groups) covering an overall distance of 799.9 cM and mean distance of 10.7 cM between the adjacent markers. QTL mapping identified 26 definitive quantitaive trait loci (QTLs) for bast fiber yield and qulaity traits (Topdar et al. 2013).

13.3.1.2 Single Nucletide Polymorphisms Biswas et al. (2015) developed the EST-SNPs to consruct the genetic linkage map for C. capsularis. Among the 43,335 variant nucleotide positions detected, 768 SNPs were used for genotyping of RIL population. Overall, 91.7% SNPs positively identified the segrgating polymorphism. The study constructed a genetic linkage map comprising of 9 linkage groups with estimated overall map distance of 2016 cM and average inter-locus distance of 4.2 cM. Similarly, a high-density genetic linkage map comprising 4839 SNPs was developed by Yang et al. (2019b) using F2 indviduals in jute (C. olitorius). The generated map sapnned a complete distance of 1375.41 cM on 7 LGs with an average covered distance of 0.28 cM between the markers on 7 LGs. Besides, Yang et al. (2019b) identified 3

M. Z. Afzal et al.

major and 13 minor QTLs for salt-induced tolerance on 4 LGs revealing 0.58 to 19.61% of the phenotypic variance.

13.3.1.3 Others Molecular Markers A genetic map was constructed by Chen et al. (2014) among 185 F2 individuals of white jute. The constructed map was comprised of 44 SRAPs, 57 ISSRs, and 18 RAPD markers with total length of 2185.7 cM and mean density of 18.7 cM at each locus. The mentioned markers had uniform distribution on the linkage groups (Chen et al. 2014). AFLPs were utilized to examine the genetic variations among 63 jute genotypes from both C. olitorius and C. capsularis. The PIC values were varied from 0.44 to 0.50 by mean value of 0.47. The highest value of PIC was reported for EAGG/MCTA primer combination indicated its importance for the genetic diversity analyses among the jute genotypes (Ghosh et al. 2014). Yang et al. (2018a) used three transcriptome datasets from C. olitorius and C. capsularis to identify the InDel markers. They discovered a total of 51,172 InDel positions from 18,800 sequences of unigenes, and loci number per unigene for InDel was ranged form 1 to 31. Twenty nine polymorphic pairs of primers were considered to examine the genetic diversity for 62 accessions including 26 from C. capsularis and 36 from C. olitorius. Their results revelaed that PIC value had range of 0.340 to 0.680 and mean value of 0.491. Likewise, Zhang et al. (2017) identified 4815 InDels from the assembled 48,914 unignes of white jute. About 70% of these InDels had bp size of 10 members for selected fiber-producing Malvaceae plants are shown. See Table 13.1 for details

204

M. Z. Afzal et al.

Table 13.2 Lignin biosynthesis genes in selected Malvaceae genomes, primarily focusing on fiber-producing plants. Theobroma cacao is shown for reference Corchorus olitorius

C. capsularis

Theobroma cacao

Gossypium raimondii

Hibiscus cannabinus

PAL

4

4

3

6

2

C4H

2

3

3

2

3

C3H

1

1

1

3

3

4CL

14

10

3

9

7

HCT

9

5

6

16

2

CCR

8

10

9

9

3

CCoAOMT

10

10

9

9

6

CAD

10

13

8

7

16

F5H

2

2

2

4

5

COMT

17

15

9

9

4

Total

77

73

53

74

51

fiber-producing Malvaceae plants was compiled (with sequenced genomes; Table 13.2). Number of genes for each lignin biosynthesis pathway families were obtained from the references (Islam et al. 2017; Zhang et al. 2020). Within the lignin biosynthesis pathway, both C. olitorius and C. capsularis demonstrate remarkable enrichment of 4CL, CCR, and CCoAMT gene families (Islam et al. 2017). On the other hand, kenaf (H. cannabinus) genome show marked enrichment of the CAD gene family (Table 13.2). The differences between expanded lignin biosynthesis gene families in jute vs. kenaf are quite interesting. One interesting explanation for this observation could be that expansion in a segment of lignin biosynthesis pathway is sufficient to make significant impact in the end lignin products. For C. olitorius, these expansions primarily happen in the upstream steps of the lignin biosynthesis pathway (e.g., COMT, 4CL), whereas for kenaf, the expansion happens at later steps of lignin biosynthesis (e.g., CAD). A corollary to this hypothesis would be reduction of metabolic flux through the upstream steps in C. olitorius lignin biosynthesis could result in a significant reduction in plant lignin content. Quite interestingly, Khan and co-workers observed that knock down of upstream lignin biosynthesis genes indeed results in significant

reduction of jute fiber lignin content (Shafrin et al. 2015, 2017; Nath et al. 2021). These results would suggest that CAD family member knockdown could have significant impact in reducing lignin content of kenaf. However, one has to take account of the tissue and developmental stage-specific expression patterns of individual lignin biosynthetic genes prior to undertaking metabolic re-engineering efforts (esp. since only a subset of the identified lignin biosynthesis genes were reported to be expressed in jute and kenaf fiber tissues Islam et al. 2017; Zhang et al. 2020).

13.7

Conclusion

Jute has great commercial importance due to its biodegradable, recyclable, and environment friendly lignocellulose fiber. It ranks second after the cotton in the natural fiber production across the world. This chapter reviewed the Corchorus spp. (jute) with their several aspects including origin and dispersal, marker-based characterization, phylogenetic relationships, chromosomal organizations, and syntenic relationships among the jute species. Besides, we described the comparative genomic studies between the jute and other Malvaceae genomes. The reviewed

13

Comparative Genomics and Synteny Within Corchorus Species …

information could potentially be valuable for further genetic studies in jute. Conflicts of Interest The authors declare no conflict of interest.

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Organelle Genome Sequencing and Phylogenetic Relationship of Jute

14

Yi Xu, Siyuan Chen, Wubin Zhan, Lihui Lin, and Liwu Zhang

Abstract

Chloroplast and mitochondria are important organelles in plants. Understanding genetic variability of organelles has emerged as new ways for taxonomy study, population structure study, and reconstruction of the breeding history of crop cultivars. The chloroplast and mitochondrial genome sizes of Corchorus capsularis are 161, 088 bp and 1, 999,602 bp, respectively and that of C. olitorius are 161,766 bp and 1, 829,341 bp, respectively. Both chloroplast genomes contain 112 unique genes including four rRNA, 78 protein-coding, as well as 30 tRNA genes. The mitochondrial genome of Corchorus capsularis contains 23 transfer RNAs, three ribosomal RNAs, and 39 protein-encoding genes. Similarly, C. olitorius contains 21 transfer RNA genes, and 36 protein-encoding, and three ribosomal RNA genes. Phylogenetic relationship of the chloroplast genomes showed that Corchorus species

Y. Xu (&)
S. Chen
W. Zhan
L. Lin
L. Zhang College of Agriculture, Fujian Agriculture and Forestry University, FuzhouFujian 350002, China e-mail: [email protected] W. Zhan e-mail: [email protected]

are closer to Gossypium species. This further proves that jute belongs to Malvaceae. 58 and 68 chloroplast-derived sequences are strongly associated with mitochondrial genes, contributing 94,915 bp and 102,689 bp (4.7% and 5.6% of the mitochondrial genome size). Mitochondrial segment sizes are in the range between 77 and 8,883 base pairs (bp) in C. capsularis and C. olitorius, respectively.

14.1

Chloroplast Genome

14.1.1 Introduction of Chloroplast Genome Chloroplast (cp), which originated from photoautotrophic cyanobacteria, is a kind of organelle with semi-autonomous genetic system in terrestrial plant cells. As a unique organelle of plants, chloroplasts are the metabolic centers of plant life activities, where plant cells carry out photosynthesis and provide the necessary energy for plant activities. Compared with the nuclear genome, chloroplast has the characteristics of a stable structure, small size, low genetic recombination rate, more copies, and highly conserved sequence (Lu et al. 2021). Previous studies have shown the existence of chloroplast, mitochondrial and nuclear genes associated with functional and metabolic processes as well as the signaling pathway of jute (Samira et al. 2010).

L. Zhang e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_14

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The maternal inheritance and unique evolutionary features of chloroplasts have led to the wide use of their genome sequences in plant phylogenetic studies. Complete chloroplast genome sequences have revealed many mutation events, including InDels (insertions or deletions), substitutions, and inversions (Pogson et al. 2015). The cp genome usually comprises a long single copy (LSC) and a short single copy (SSC) region, as well as two IR (inverted repeats). Its size ranges from 115 to 210 kb (Jansen et al. 2005). By sequencing and assembling the cp genome with high-throughput sequencing tools, we can reveal the structure and function of the cp genome, which can provide an important reference for the study of plant phylogeny.

14.1.2 Assembly and Annotation ‘Kuanyechangguo’ (Corchorus. olitorius) and ‘Huangma179’ (Corchorus. capsularis) are the most commonly cultivated jute species in China for their excellent quality and were selected as sequencing varieties. Table 14.1 shows the toolkit used for de novo assembly of organelle genomes. After filtering out the low-quality reads, 1.2 Gb and 2.6 Gb clean data were obtained for dark jute (Corchorus olitorius) and white jute (Corchorus capsularis), respectively. The chloroplast genome size of C. capsularis (accession ID MK251464 under NCBI) is 161,088 bp, which is 678 bp smaller than the cp genome size C. olitorius has 161,766 base pairs (bp) in size, and its assembled sequence is available in the NCBI under accession ID: MK251465 (Fig. 14.1), both of which are within the range of plant chloroplast genome size (115– 210 kb). The cp genome of C. capsularis comprises 26,063 bp of a couple of IRs, disconnected by an SSC (20,347 bp) and LSC (88,615 bp) regions (Fig. 1). The C. olitorius cp genome has a couple of IRs of 25,845 bp, disjointed by two regions: an LSC (89,661 bp) and SSC (20,415 bp) (Table 14.2). The jute cp genome contains GC content (61%) for C. capsularis and 62% for C. olitorius, much higher than kenaf

Y. Xu et al.

(36.65%) (Cheng et al. 2020) and cotton (37.1– 37.4%) (Wu et al. 2018). The cp genome of two jute species contains four rRNA (ribosomal RNA) genes, 30 tRNA (transfer RNA) genes as well as 78 protein-coding genes (Table 14.3). The C. olitorius and C. capsularis cp genomes are quite distinct, and there are 2417 bp of transversions and transitions between the two cp genomes (Fig. 14.2). Four highly variable loci are located in single-copy regions that were precisely located (Fig. 14.3).

14.1.3 Phylogenetic Analysis The phylogenetic tree of C. capsularis and C. olitorius whole genomes (Islam et al. 2017) showed that both species are clustered with G. raimondii and T. cacao, indicating that jute belongs to Malvaceae. It should be pointed out that there has always been controversy about whether jute belongs to Malvaceae or Tiliaceae. To verify this conclusion, considering that chloroplast is maternally inherited, its genome has been widely used in the analysis of plant phylogenetic relationships. The phylogenetic relationship comprising white jute (C. olitorius), dark jute (C. olitorius), and cotton (Gossypium spp.) cp genomes were investigated (Fig. 14.4). The results showed that dark jute and white jute were closer to Gossypium species in the genetic relationship. This further proves that jute belongs to Malvaceae, not Tiliaceae based on plant phylogeny. A comparative study of cp genomes from five different plant species belonging to the Malvaceae family is shown in Fig. 14.5. Difference between dark jute and white jute was less than the difference observed among the genera in Malvaceae. Seven intervals with highly variable regions were observed in the five chloroplast genomes of Malvaceae. In these regions, trnQUUG, trnL-UAA, trnL-UAG, trnS-GGA, trnTGGU, trnW-CAA, rpl33, psbL, petN, and psbM genes were found. Comparison of cp genomes of the five Malvaceae plant species revealed that there is a breakpoint on the locus accD, which is

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Table 14.1 The toolkit used for de novo assembly of organelle genomes Software/website

Function

SPAdes 3.6.1 and SOAPdenovo2

The paired sequences were assembled into contigs

Sequencher 4.10 (http://www.genecodes.com)

Proofreading and assembling contigs

DOGMA

Gene annotation

https://chlorobox.mpimp-golm.mpg.de/OGDraw.html

Organelle genome mapping

Fig. 14.1 Gene map of Corchorus capsularis and Corchorus olitorius chloroplast genomes. Genes drawn outside the circle are transcribed clockwise and those inside counterclockwise. The dark gray in the inner circle

indicates GC content of the chloroplast genomes of C. capsularis and the light gray, AT content. Short single copy (SSC), long single copy (LSC), and inverted repeats (IRa, IRb) are also indicated (Fang et al. 2020)

implicated in fatty acid biosynthesis in Corchorus (Fig. 14.6). The locus suggests that some of the genes in the nuclear genome have been transferred from the chloroplast. Synteny

investigation of this locus among the chloroplast (accession KT894204.1), mitochondrial (accession KT894205.1), and nuclear genomes of the two jute species supports this result.

212 Table 14.2 Summary of two complete plastomes of Corchorus (Fang et al. 2020)

Table 14.3 Genes of Corchorus chloroplast genomes (Fang et al. 2020)

Y. Xu et al. C.capsularis

C. olitorius

Total cpDNA size (bp)

161,088

161,766

Length of long single copy (LSC) region (bp)

88,615

89,661

Length of inverted repeat (IR) region (bp)

26,063

25,845

Length of short single copy (SSC) region (bp)

20,347

25,845

Total GC content (%)

61%

62%

Total number of genes

112

112

Protein encoding

78

78

tRNA

30

30

IRNA

4

4

Gene group

Gene name

Photosynthesis genes Rubisco

rbcL

Photosystem I

psaA, psaB, psaC, psaI, psaJ

Assembly/stability of Photosystem I

a

Photosystem II

psbA, psbB, psbC, psbD, psbE, psbE, psbF, psbH, psbI, psbJ, psbK, psbL, psbM, psbN, psbT, psbZ

ATP synthase

atpA, atpB, atpE, aatpF, atpH, atpI

Cytochrome b/f

petA, apetB, apetD, petG, petL, petN

ycf3, ycf4

complex Cytochrome c

ccsA

synthesis NADPH

a

ndhA, andhB, ndhC, ndhD, ndhE, ndhF, ndhK,

dehydrogenase

ndhG, ndhH, ndhI, ndhJ

Transcription and translation genes Transcription

rpoA, rpoB, arpoC1, rpoc2

Ribosomal proteins

rps2, rps3, rps4, rps7, rps8, rps11, arps12,rps14, rps15, rps16, rps18, rps19, arpl2,rpl14, arpl16, rpl20, rpl22, rpl23, rpl32,rp133, rp136

Translation initiation infA factor RNA genes Ribosomal RNA

rrn5, rrn4.5, rrn16, rrn23

Transfer RNA

a

trnA-UGC, trnC-GCA, trnD-GUC, trnE-UUC, trnF-GAA, trnG-UCC, atrnG-GCC, trnH-GUG, trnI-CAU, atrnI-GAU, atrnK-UUU, trnL-CAA, a trnL-UAA, trnL-UAG, trnfM-CAUI, trnMCAU, trnN-GUU, trnP-UGG, trnQ-UUG, trnRACG, trnR-UCU, trnS-GCU, trnS-GGA, trnSUGA, trnT-GGU, trnT-UGU, trnV-GAC, atrnVUAC, trnW-CCA, trnY-GUA (continued)

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Table 14.3 (continued)

Gene group

213

Gene name

Other genes RNA processing

matK

Carbon metabolism

cemA

Proteolysis

a

clpP

Genes of unknown function Conserved reading

ycf1, ycf2

frames Pseudogene Gene group is not defined a

ycf15

Intron-containing genes

Fig. 14.2 Patterns of nucleotide substitutions among C. capsularis and C. olitorius plastomes. The plastome of C. capsularis was used as a reference (Fang et al. 2020)

Fig. 14.3 Evaluation of nucleotide variation of the plastomes of C. capsularis and C. olitorius with C. capsularis as a reference (Fang et al. 2020)

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Fig. 14.4 Phylogenetic relationship of C. capsularis and C. olitorius with species of the Malvaceae family based on chloroplast genome sequences (Xu et al. 2021)

14.1.4 Repeat Features A total of 66 SSRs with repeat sizes of not less than ten nucleotides were detected in the white jute (C. capsularis) cp genome (Fig. 14.7), including 16 mono-, 11 di-, eight tri-, 13 tetra-, ten penta-, and eight hexanucleotides. In the C. olitorius cp genome, a total of 56 SSRs with repeat sizes of not less than 10 nucleotides were detected, including four hexa-, ten penta-, 11 tetra-, two tri-, eight di-, and about 21 mononucleotides (Fig. 14.7). Of these, the mono-repeats were dominant, with occurrences of 24.2% for C.

capsularis and 37.5% for C. olitorius cp genomes. The frequencies of trinucleotide and hexanucleotide repeats were the least, accounting for 12.1% in C. capsularis. Similarly, the frequency of trinucleotides in C. olitorius was also the lowest, accounting for 3.6%.

14.1.5 Microstructural Variants By relating the chloroplast genomes of the two jute species, a large number of InDel and SNP markers were detected (Fig. 14.2). Among these

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Fig. 14.5 Identity plot comparing the chloroplast genomes of C. capsularis, C. olitorius, Gossypium hirsutum, G. raimondii, and Theobroma cacao using Arabidopsis thaliana as a reference sequence. The vertical scale indicates the percentage of identity (50% to 100%),

using a 50% identity cutoff. The horizontal axis indicates the coordinates in the chloroplast genome. Genome regions are color-coded as protein-coding, rRNA, tRNA, intron, and conserved non-coding sequences (CNS) (Fang et al. 2020)

markers, SNPs were the dominant type of mutation in the C. capsularis and C. olitorius (Fig. 14.2). The 2053 detected SNPs included 1032 transversions and 990 transitions. Among the latter one, 560 were detected amid C and T or G and A, and 430 were found amid A and G or T and C. Of the 1032 transversions, 299 were detected amid A and T or T and A, 296 were

found amid A and C or T and G, 129 were found amid C and G or G and C, and 308 were detected amid C and A or G and T. About three repeat expansions, five repeat contractions, 148 insertions, and 138 deletions were identified. The major InDel with the size of 110 base pairs was detected amid psbM and petN gene sequences in the LSC region. The second-

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Fig. 14.6 Identity plot comparing the region from rbcL to psaI in the chloroplast genomes of Theobroma cacao, Gossypium raimondii, G. hirsutum, C. capsularis, and C.

Fig. 14.7 Statistics of simple sequence repeats in the chloroplast genomes of C. capsularis and C. olitorius (Fang et al. 2020)

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olitorius, using Arabidopsis thaliana as a reference sequence (Fang et al. 2020)

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Organelle Genome Sequencing and Phylogenetic Relationship of Jute

largest InDel had 38 base pairs and was located in rpl16 genes responsible for producing ribosomal proteins.

14.2

Mitochondrial Genome

14.2.1 Introduction of the Mitochondrial Genome Mitochondria are recognized as semiautonomous organelles in countless eukaryotic cells. It is the main organelle of energy metabolism and plays an important role in providing energy to plants. The mitochondrial genome has the characteristics of maternal inheritance, independent replication, and rapid evolution (Liu et al. 2013). Its gene composition, genetic code, and replication mode record rich evolutionary information in the process of biological evolution. It is an important material to study the origin and evolution of species (Liao et al. 2018). At present, mitochondrial genome information analysis technology has become an important means of developing molecular markers, which are being widely used in classification, population genetic relationship, interspecific molecular evolution, and so on, as a supplement to traditional classification. Cytoplasmic male sterility in plants may be caused by mitochondrial gene mutation, rearrangement, or recombination, and male sterility genes can be found by comparing mitochondrial genes (Liao et al. 2020; Li et al. 2018).

14.2.2 Assembly and Annotation The C. capsularis (KT894204) and C. olitorius (KT894205) mitochondrial genomes were obtained from the NCBI Organelle Genome Resources database. The mitochondrial genome size of C. olitorius is 1,829,341 bp, which is 170,268 bp smaller than that of C. olitorius (1,999,602 bp) (Fig. 14.8). The GC content of the mitochondrial genome is 43.47% for C. capsularis and 42.85% for C. olitorius. The mitochondrial genome of C. capsularis contains

217

three rRNA genes, 23 tRNA, and 39 proteinencoding genes. Similarly, C. olitorius contains three ribosomal RNA (rRNA) genes, 36 proteinencoding, and 21 transfer RNA genes. The jute mitochondrial genes include only 39 and 36 of the 41 protein-encoding genes existing in lineal plant mitochondrial genomes, demonstrating that two and five protein-coding genes have been moved to other organelles or lost through evolutionary selection and domestication of jute mitochondria. The missing genes in mitochondrial genomes of C. capsularis and C. olitorius are rpl2 and rps11.

14.2.3 Chloroplast (Cp)-Like Sequences In C. capsularis, 58 cp (chloroplast) fragment sequences are found in the mitochondrial genome (more than 80% identity to the C. capsularis chloroplast genome), a total of 94,915 bp (4.7% of the mitochondrial genome size) comprises segment sizes in a range between 77 and 8,883 base pairs (bp). Eight out of the 58 chloroplast fragment sequences are associated with transfer RNA sequences, eight are associated with photosynthesis sequences, and the remaining fragments are other types of cp sequences. In C. olitorius, 68 chloroplast fragment sequences are found in the mitochondrial genome (more than 80% identity to the C. olitorius cp genome), a total of 102,689 bp (5.6% of the mitochondrial genome size) with segment sizes in the range between 77 and 8,883 bp. This data is significantly higher than that of kenaf (Liao et al. 2018) and cotton (Liu et al. 2013). Three of the 68 chloroplast fragment sequences are associated with tRNA sequences, two are associated with photosynthesis sequences and the remaining fragments are other types of cp sequences.

14.2.4 Repeat Features Five and four different types of repeats were detected in C. olitorius (dark jute) and white jute (C. capsularis), respectively (Table 14.4). A total

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Fig. 14.8 Map of C. capsularis (a) and C. olitorius (b) mitochondrial genome

Table 14.4 Summary and content analysis of different types of repeat elements in the Corchorus mitochondrial genome Items

Corchorus capsularis

Corchorus olitorius

Number of elements

Length occupied (bp)

Percentage of sequence (%)

Number of elements

Length occupied (bp)

Percentage of sequence (%)

182

84, 856

4.24

172

109, 245

5.97

Retroelements LINEs: L1/CIN4 LTR elements: Ty1/Copia

21

11, 130

0.56

Unclassified:

212

40, 597

2.03

94

22, 507

1.23

Total interspersed repeat

415

136, 583

6.83

266

131, 752

7.2

Simple repeats:

108

4, 375

0.22

131

5, 107

0.28

Low complexity:

40

1, 638

0.08

29

1, 106

0.06

of 13 SSRs with repeat lengths of not less than seven nucleotides were detected in the white jute cp genome, including one mono-, eight di-, 14 tri-, 19 tetra-, 22 penta-, and 31 hexanucleotides (Fig. 14.9). In the C. olitorius cp genome, a total of 14 SSRs with repeat lengths of not less than seven nucleotides were detected, including two mono-, six di-, 11 tri-, 21 tetra-, 45 penta-, and 32

hexanucleotides (Fig. 14.9). Among them, the mono-repeats were the least, with frequencies of 1.7% in dark jute and 1.1% in white jute. The frequencies of hexanucleotide repeats were abundant, accounting for 32.6% in C. capsularis. Similarly, the frequency of trinucleotides in C. olitorius was also the highest, accounting for 38.5%.

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Numbers

Fig. 14.9 Statistics of simple sequence repeats in the mitochondrial genomes of C. capsularis and C. olitorius

50 45 40 35 30 25 20 15 10 5 0

14.2.5 Phylogenetic Analysis A phylogenetic investigation was carried out to reveal evolutionary kinships among the mitochondrial genomes of 13 species, including Corchorus capsularis, Corchorus olitorius, Hibiscus cannabinus (MF163174), Gossypium raimondii (KU317325), Gossypium hirsutum (JX065074), Fig. 14.10 The phylogenetic tree of all mitochondrial genes in several species

Corchorus capusularis

219 Corchorus olitorius

Marchantia paleacea (NC_001660), Cycas taitungensis (NC_010303), Cannabis sativa (NC_029855), Zea mays subspecies Mays (NC_007982), Nicotiana tabacum (BA000042), Ricinus communis (HQ874649), Oryza rufipogon (AP011076), and Oryza sativa subspecies japonica (BA000029). Monocot plants and dicot plants have also separated in this phylogenetic tree and

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the tree was rooted with Marchantia paleacea. Corchorus species, Gossypium species and Hibiscus cannabinus are divided into one clade, which once again proves that Corchorus species belongs to Malvaceae (Fig. 14.10).

14.3

Conclusion

The chloroplast and mitochondrial genomes of two jute species have been summarized in this chapter. Chloroplast is maternally inherited; its genome has been widely used in the analysis of plant phylogenetic relationships. It has been shown that Corchorus capsularis and Corchorus olitorius are closer to cotton (Gossypium spp.) in the genetic relationship. This further proves that jute belongs to Malvaceae, not Tiliaceae based on plant phylogeny. Incorporation of chloroplast (cp)-like sequences is a well-recognized event in plant mitochondrial genomes. 58 and 68 chloroplast-derived sequences are strongly associated with mitochondrial genes, contributing 94,915 bp and 102,689 bp (4.7% and 5.6% of the mitochondrial genome size) in C. capsularis and C. olitorius, respectively. The speciation time of jute species was earlier than that of Hibiscus cannabinus and Gossypium species, and C. olitorius was earlier than C. capsularis.

References Cheng Y, Zhang L, Qi J, Zhang L (2020) Complete chloroplast genome sequence of hibiscus cannabinus and comparative analysis of the Malvaceae family. Frontiers Gene 11:227. https://doi.org/10.3389/fgene. 2020.00227 Fang S, Zhang L, Qi J, Zhang L (2020) De novo assembly of chloroplast genomes of Corchorus capsularis and C. olitorius yields species-specific InDel markers. Crop J https://doi.org/10.1016/j.cj.2020.05.010 Islam MS, Saito JA, Emdad EM, Ahmed B, Islam MM, Halim A, Hossen QM, Hossain MZ, Ahmed R, Hossain MS, Kabir SM, Khan MS, Khan MM, Hasan R, Aktar N, Honi U, Islam R, Rashid MM,

Wan X, Hou S, Haque T, Azam MS, Moosa MM, Elias SM, Hasan AM, Mahmood N, Shafiuddin M, Shahid S, Shommu NS, Jahan S, Roy S, Chowdhury A, Akhand AI, Nisho GM, Uddin KS, Rabeya T, Hoque SM, Snigdha AR, Mortoza S, Matin SA, Islam MK, Lashkar MZ, Zaman M, Yuryev A, Uddin MK, Rahman MS, Haque MS, Alam MM, Khan H, Alam M (2017) Comparative genomics of two jute species and insight into fibre biogenesis. Nat Plants 3:16223. https://doi.org/10.1038/nplants.2016. 223 Jansen RK, Raubeson LA, Boore JL, dePamphilis CW, Chumley TW, Haberle RC, Wyman SK, Alverson AJ, Peery R, Herman SJ, Fourcade HM, Kuehl JV, McNeal JR, Leebens-Mack J, Cui L (2005) Methods for obtaining and analyzing whole chloroplast genome sequences. 395:348–384. https://doi.org/10.1016/ s0076-6879(05)95020-9 Li S, Chen Z, Zhao N, Wang Y, Nie H, Hua J (2018) The comparison of four mitochondrial genomes reveals cytoplasmic male sterility candidate genes in cotton. BMC Genomics 19(1):775. https://doi.org/10.1186/ s12864-018-5122-y Liao X, Wei M, Khan A, Zhao Y, Kong X, Zhou B, Li M, Peng S, Munsif F, Ullah A, Zhou R (2020) Comparative analysis of mitochondrial genome and expression variation between UG93A and UG93B reveals a candidate gene related to cytoplasmic male sterility in kenaf. Ind Crops Prod 152:112502. https://doi.org/10. 1016/j.indcrop.2020.112502 Liao X, Zhao Y, Kong X, Khan A, Zhou B, Liu D, Kashif MH, Chen P, Wang H, Zhou R (2018) Complete sequence of kenaf (Hibiscus cannabinus) mitochondrial genome and comparative analysis with the mitochondrial genomes of other plants. Sci Rep 8 (1):12714. https://doi.org/10.1038/s41598-018-30297w Liu G, Cao D, Li S, Su A, Geng J, Grover CE, Hu S, Hua J (2013) The complete mitochondrial genome of gossypium hirsutum and evolutionary analysis of higher plant mitochondrial genomes. PLoS ONE 8 (8):e69476. https://doi.org/10.1371/journal.pone. 0069476.g001 Lu H, Dong Z, Qu S, Xia M, Wang Z, Shen W, Wang H, Yu Q, Xin P (2021) Characteristics analysis of chloroplast genome of pinus armandii. Mol Plant Breed 19(10):3223–3234 Samira R, Moosa MM, Alam MM, Keka SI, Khan H (2010) In silico analysis of jute SSR library and experimental verification of assembly. Plant Omics 3 (3):57–65 Wu Y, Liu F, Yang DG, Li W, Zhou XJ, Pei XY, Liu YG, He KL, Zhang WS, Ren ZY, Zhou KH, Ma XF, Li ZH (2018) Comparative chloroplast genomics of

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gossypium species: insights into repeat sequence variations and phylogeny. Front Plant Sci 9:376. https://doi.org/10.3389/fpls.2018.00376 Xu Y, Zhang L, Qi J, Zhang L, Zhang L (2021) Genomics and genetic improvement in main bast fiber crops:

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advances and perspectives. Acta Agron Sin 47 (6):997–1019. https://doi.org/10.3724/sp.j.1006.2021. 04121

Functional Genomics of Jute

15

Sylvain Niyitanga, Pratik Satya, and Sabrina M. Elias

Abstract

Jute (Corchorus spp., 2n = 14) is one of the main sources of natural fiber and have enormous environmental, economic, health, and medicinal values. Jute is grown in warm areas of the world, primarily in countries such as Bangladesh, India, and China. With the recent novelties and developments in biotechnologies, considerable progress in jute plant genetics and genomics has been attained, which has aided our insight into molecular components underlying the important agronomic traits and the development of the jute genome. Under this chapter, we summarized the accomplishments of recent years which mainly include the current progress in jute genomics such as gene family identification, genome wide microRNA identification, reference gene identification,

S. Niyitanga (&) Bast Fiber Biology Center, College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China e-mail: [email protected] P. Satya Division of Crop Improvement, ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore 700 120, India S. M. Elias School of Environment and Life Sciences, Independent University, Bashundhara, Dhaka, Bangladesh e-mail: [email protected]

and the development of InDel (insertion / deletion), simple sequence repeat, and single nucleotide polymorphism markers. We have also discussed transcriptome analyses in jute notably transcriptome and gene discovery, transcriptome sequence of jute plants, regulatory sequence/transcription factors, and functional gene sets and regulation networks which mainly include the analysis of mutants for gene discovery, tissue/growth stage-specific gene identification, gene expression in response to environmental stimulus, and reconstruction of metabolic pathways. Further, we talked about the analysis of the microRNA and DNA methylations, application of proteomics and genome editing techniques (CRISPR/Cas9, small RNA interference, and mutagenesis), and quantitative trait loci (QTL) mapping for important agronomic attributes such as salt tolerance, plant height, bast fiber cellulose content, histological bast fiber, and others. Besides, we have provided challenges and present outlook for forthcoming functional genomic investigations that will enhance breeding programs in jute plants.

15.1

Introduction

Jute (Corchorus spp., 2n = 14) is one of the most important sources of natural fiber, covering approximately 80% of the global bast fiber production (FAO 2014). Only white (Corchorus

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_15

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capsularis) and dark jute (Corchorus olitorius) species are cultivated among the more than 100 species in existence (Saunders 2001). Cultivation of the two species is concentrated in the warm areas of the world, mainly in countries including India, China, and Bangladesh. Jute is also grown together with its allied bast fibers (flax, hemp, kenaf, etc.) on a small scale in countries such as Brazil, Uzbekistan, and others (Bhandari et al. 2018). In terms of global fiber production, requirement, and usage, jute is ranked second after cotton (Roy et al. 2006). Jute fibers are well recognized for their versatility, eco-friendly nature, fitness, and durability. They are also used to make various products including packaging materials (bags), ornamentations (such as rugs, carpets, curtains, chair covers), and others (Biswas et al. 2015; Bhandari et al. 2018). Besides, young leaves of dark jute are consumed as green vegetables (Denton et al. 2004; Adediran et al. 2015) and they are known to contain several vitamins, proteins, antioxidants, and minerals (Ngomuo et al. 2017; Mollah et al. 2020; Tareq et al. 2020). In addition, jute has medicinal applications as it contains several medicinal components including antioxidants, antitumor properties and many other secondary metabolites essential for human health (Nyadanu and Lowor 2015; Al-Snafi 2016; Yakoub et al. 2018). Moreover, jute is recognized for improving soil nutrients when utilized as geotextile (Sinha et al. 2009). They are normally rotated with other crops and their roots and leaves left after harvest enrich the soil with micronutrients and maintain soil fertility. However, compared with other plants, notably rice (Li et al. 2018), research on jute functional genomics has lagged much behind. This has hindered jute improvement via molecular breeding. A hasty upsurge and modernism of biotechnologies, mainly next-generation sequencing (NGS), have led to considerable improvements in comprehending the genetics and genomics of jute during the recent decades, which can be concisely condensed into four main aspects: (i) decoding of the genome and transcriptome of jute plants with various nextgeneration technologies; (ii) detection and

S. Niyitanga et al.

functional investigation of important agronomic trait-associated genes as well as their controlling networks; (iii) investigation of the ncRNAs (noncoding RNAs) implicated in various biological processes; (iv) progress of novel approaches and tools for characterizing new genes. This chapter briefly condenses the primary accomplishments in recent years and presents challenges and viewpoints for prospective functional genomic investigations that would lead to a hastening of jute breeding programs.

15.2

Current Progress in Jute Genome

Availability of jute genome sequences (Islam et al. 2017; Sarkar et al. 2017; Zhang et al. 2021b) facilitated multifaceted molecular and genomic studies in jute. However, the number of QTL mapping studies is still limited. Most of the studies are based on the annotation of gene families, transcriptomics-based differential gene expression analysis, sequence-based molecular marker development, etc. Some of these studies are discussed below.

15.2.1 Gene Family Identification Since the publication of the jute genome, several in silico identification studies of different gene families relevant to fiber biogenesis have been conducted. For example, a genome-wide investigation of WRKY gene families in white jute was performed by Zhang et al. (2020). They found that most CcWRKY genes are expressed in different tissues primarily in stem bark and stem stick tissues of two jute plants “Aidianyehuangma” a GA3 sensitive genotype and “Huangma 179” an elite cultivar. However, under GA3 stress, the expression of many CcWRKY genes was significant in stem basts of Aidianyehuangma when compared to “Huangma 179”. Most of the expression of many genes (CcWRKY) was regulated by genes associated with secondary cell wall biosynthesis. This indicates their implication in fiber formation and

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Functional Genomics of Jute

gibberellin biosynthesis. Hossain et al. (2020b) characterized the PAL (phenylalanine ammonialyase) gene family in C. olitorius. The PAL enzyme initiates the biosynthesis of metabolites like lignin in the phenylpropanoid pathway. They identified 4 PAL genes on two chromosomes in the jute genome, grouped into three different subfamilies. They found CoPAL1 to be predominantly expressed in stem tissues signifying its involvement in lignin buildup in the fiber, hence it can serve as a potential target for lowering lignin content in jute. Other studies on gene families in jute include AP2/ERF superfamily (Kabir et al. 2021), Calcium-dependent protein kinase family (CDPK) (Ahmed et al. 2020), NAM2 like gene in white jute (Zhang et al. 2021a), Fasciclin-like arabinogalactan proteins (FLAs) (Hossain et al. 2020a) and others.

15.2.2 Reference Gene Identification Hossain et al. (2019) used the genome data for reference gene identification for use in qRT-PCR studies. They designed primers for 11 prospective genes and evaluated their potentials in jute tissues including the stem stick, root, stem bark, flower, leaf, fiber, and seed, under various environmental stresses notably abiotic (waterlogging, drought and salinity) and biotic stresses (such as invasion with Macrophomina phaseolina, a fungal phytopathogen). They reported EF2 and PP2AC as the most steadily expressed in diverse tissues and identified UBC2 and ACT7 for drought, CYP, and PP2AC for biotic stress, PP2AC and UBC2 for salinity, and pp2AC and ACT7 for waterlogged conditions. Ferdous et al. (2015) used qRT-PCR and RefFinder (a webbased tool) to evaluate seven jute candidate genes including ELF, ACT, UBC, TUB, G3PDH,18S, and U6 under different stress conditions including biotic stresses such as fungal infection and abiotic stresses including dehydration, low temperature, and salinity. Their results suggested that UBC and ELF were consistently expressed in three abiotic stress conditions, while TUB was the utmost steady in fungal infestations. Moreover, Niu et al. (2015) also used RefFinder

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tool and qRT-PCR to evaluate 11 candidate reference genes (UBQ, UBC, TUBa,18S rRNA, ACT7, TUBb, DnaJ, UBI, EF1a, ACT, and RAN) in C. capsularis, under different stress (biotic and abiotic) conditions and three diverse tissue types. They identified RAN and ACT7 as steady reference genes for gene expression normalization under NaCl and biotic stress subsets. Two (DnaJ and UBC) and four (UBI, TUBb, RAN, and EF1a) reference genes were also identified as accurate genes for normalization under polyethylene glycol subsets and in three diverse tissues, respectively. These data on candidate reference genes, will be helpful for quantitative studies of genes in jute.

15.2.3 Development of InDel, SSR, and SNP Markers Fang et al. (2021) performed de novo assembly of the chloroplast genome of C. capsularis and C. olitorius. They identified 2417 SNP and 294 InDels, among which cpInDel 205 was discriminatory between the two cultivated species. Evidence of gene transfer from the chloroplast to the nuclear genome was also observed. Zhang et al. (2017) developed InDel markers from expressed sequence tags (ESTs) related to cellulose content of bast fiber. Yang et al. (2018) developed an insertion/deletion (InDel) polymorphism database for jute through relative transcriptome investigations of 3 datasets where polymorphism information content varied from 0.34 to 0.68. Satya et al. (2017) identified genic SSRs in C. capsularis and developed simple sequence repeat markers for phenylpropanoid biosynthesisrelated genes. This pathway is involved in lignocellulosic-based fiber formation and the manufacture of diverse phytochemicals. These sets of markers will be valuable for molecular MAB (marker aided breeding) aiming at stress tolerance, fiber quality enhancement, and phytochemical-associated features in jute plants. Sarkar et al. (2019) carried out RAD (restriction site-associated DNA) sequencing using 1115 RAD-SNPs from 221 fiber-type lines from 9 geographic regions. They identified specific

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RAD-SNP under selection and revealed that fiber production was due to artificial selection whereas biotic and abiotic stress responses were due to natural selection pressure in dark jute adaptation.

15.3

Transcriptome Analysis in Jute

15.3.1 Transcriptome and Gene Discovery in Jute Transcriptome analysis or transcriptomics is a pivotal step for gene discovery and functional genomics. Although the term transcriptome was coined in 1996 by Charles Auffray (Piétu et al. 1999), large-scale gene expression studies were initiated during the early phases of the human genome project (Adams et al. 1991). These studies included the generation of ESTs (expressed sequence tags) leading to microarray experiments. However, the initial EST analysis experiments required cloning of genes and prior sequence knowledge to design primers. Subsequently, methods for bypassing the cloning steps were developed. The invention of microarray or gene chips (Velculescu et al. 1995) was the next boost for large-scale expression analysis. It was, however, not possible to understand the biological meaning of such large-scale, complex expression patterns of genes without the advances in statistical methods and increased computing power. At the same time, revolutionary sequencing methods with machines able to sequence many fragments at a single run led to the invention of the ‘next-generation’ sequencing (NGS) technologies. All these helped to make transcriptome analysis a profitable commercial venture, drawing many investors. By the laws of economics, increased competition fuelled research in designing more efficient sequencers, and gradually the first-generation sequencers, initially used widely for transcriptome analysis were replaced by upgraded versions or successors (2nd-generation sequencers), which are now being replaced by still more efficient thirdgeneration sequencers, resulting in a reduction

of cost of analysis and increase in sequencing speed, accuracy, and variation (Ray and Satya 2014). Although jute is the primary important nontextile fiber of the globe in terms of production volume or diversity of use, it has received comparatively less research focus than other fiber crops such as cotton or flax. Consequently, the extent of basic genetic research in jute is limited, primarily being conducted in India, Bangladesh, China, and few African countries. Due to recent domestication and localized cultivation, the genetic base of jute is very narrow (Sarkar et al. 2019). Wide hybridization and genetic engineering are two popular approaches to broaden the genetic base of a species. Unfortunately, the two jute species do not readily cross with each other, neither are they crossable with other wild Corchorus species, except for C. aestuans, with which only C. olitorius can be crossed with limited success (Sinha et al. 2011). Moreover, a robust in vitro regeneration protocol, particularly for C. olitorius, is not yet available, making genetic engineering a difficult approach for developing new improved genotypes. Although successful in-planta transformation has been achieved in a few studies (Shafrin et al. 2015, 2017), practical application of routine genetic engineering for functional validation of genes would require more research. Considering these bottlenecks, transcriptome sequencing can be the perfect tool to identify genes and understand their function. The first jute transcriptome data put in the NCBI SRA archive in 2014 were generated from the bast tissue of a mutant, deficient in lignified phloem fiber production (dlpf) and its wild-type cultivar JRC-212 (Chakraborty et al. 2015). Currently, the SRA archive of NCBI holds 143 RNA entries which are scanty in comparison with that of cotton (3572) or rice (14464). However, the number of genes and their sequence quality is comparable to those of other plant species, as most of the jute genes discovered to date through transcriptome analysis have well-conserved homologs in taxonomically related species, such as cocoa and cotton.

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15.3.2 Transcriptome Sequence of Jute Over the last six years, whole transcriptome sequences have been generated from various tissue types (bast, hypocotyl, fiber cell, shoot apical meristem, and fruit tissues) and growth conditions (salt-stressed, drought-stressed). Since transcriptome is a dynamic entity, where gene expression varies widely among the tissues based on the complex interaction network of the genes, environmental influences, and physiological state of the tissues, results of transcriptome analysis vary widely within a species. In addition, technical issues like quality of the isolated RNA, sequencing platform, method of sequencing, post-sequencing processing of the raw sequence, sequence assembly, and annotation, and availability of expert human resources play crucial roles in the generation of a robust transcriptome dataset. To date, all jute transcriptome studies have predominantly utilized the Illumina sequencing platforms. Therefore, errors in sequencing due to variation in sequencing platform are not a major problem in jute. Despite that, a wide variation in the number of genes identified has been reported. This creates problems for researchers interested in utilizing these functional genomic resources. For example, a recent report (Tao et al. 2020) estimates the number of genes expressed in C. capsularis to be 72, 674, which is considerably higher than previous reports. On the other hand, only 14, 050 genes could be recovered from a shoot apex transcriptome of C. olitorius (Choudhary et al. 2019), both beyond the ranges of other reports (Chakraborty et al. 2015; Zhang et al. 2015; Yang et al. 2017a, 2017b; Satya et al. 2018; Yang et al. 2020). Overall, jute has an estimated number of 35,000–40,000 annotated genes. While a lower estimate indicates that some of the expressed genes might have been missed during the sequencing process, a larger estimate is a sign of a problem in assembly and annotation and should be very cautiously interpreted. Several indicators are available to assess the quality of a transcriptome assembly, including RNA quality, read depth/read coverage of the transcriptome,

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number of overrepresented sequences, duplicate reads, kmer count (a measure for a technical artifact), and the methods of annotation used. In general, a minimum of three biological replicates, RNA integrity number (RIN) > 7, pairedend sequencing, Phred quality score (Q) > 28, low kmer and read length > 200 nt should be used to generate a robust transcriptome sequence. In addition, in the case of de novo assembly, more than one assembly workbench should be used. In their pioneer study, Chakraborty et al. (2015) pooled RNA from bast tissues of 10 plants, checked RNA integrity, cleaned the raw reads using Q
20, and filtered the non-coding sequences using Bowtie (Langmead 2010), used three assemblers (CLC Genomics Workbench, SOAPdenovo-Trans, and Trinity) for de novo assembly, and realigned the reads to the transcripts by SOAPaligner (Li et al. 2009) allowing up to 2-base mismatches. Yang et al. (2017a) pooled total RNA isolated from the root and the leaves of an individual plant in equal volumes for the sequencing libraries. For quality control, they checked RNA integrity, after sequencing cleaned the raw data using an in-house Perl script, and assembled the transcriptome de novo using Trinity. On the other hand, reference-based assemblies were generated by Islam et al. (2017) using Cufflinks and by Yang et al. (2020) using Bowtie and TopHat. A transcriptome shotgun assembly (TSA) is an archive of transcript sequences generated from either EST or NGS data. While SRA contains unassembled reads, TSA contains more valuable information in the form of primary transcripts. They are generated both from genome and transcriptome sequence data. As of now, four jute TSAs are available at the NCBI TSA archive (GBSD00000000, GBSE00000000, GCNR00000000 and GCNS00000000, containing 34,163, 29,463, 44,675 and 52,368 transcripts, respectively) (Chakraborty et al. 2015; Satya et al. 2018). The main features of the four TSAs are provided in Table 15.1, which indicates that about 90% of these transcripts have known homologs in other species. As these transcripts are well annotated, they are valuable resources for functional genomics in jute.

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Table 15.1 Transcriptome shotgun assemblies of C. capsularis archived at NCBI (Chakraborty et al.2015; Satya et al. 2018) NCBI TSA id

Tissue

Number of genes annotated

BLASTX hits aligneda Nr

SwissProt

KEGG

COG

Total (%)

GBSD00000000

Bast

34,163

26,413

3,233

454

438

89.4

GBSE00000000

Bast

29,463

23,304

2,916

494

412

92.1

GCNR00000000

Hypocotyl

44,675

32,860

4,454

769

712

86.8

GCNS00000000

Hypocotyl

52,368

39,094

7,858

896

1,134

93.5

a

The databases were used in the priority arrangement of Nr (non-redundant) > SwissProt (swiss protein) > KEGG (Kyoto encyclopedia of genes and genomes) > COG (Clusters of orthologous groups), significant unigene sequence (Evalue < 10–5) hits in one database were not searched against the other database (s)

15.3.3 Functional Gene Sets and Their Regulatory Network Wide variations have been reported in the number of genes expressed in different tissues of both the jute species. The earliest transcriptome study (Chakraborty et al. 2015) reported the presence of 29,000–34,000 genes in the bast tissue of C. capsularis, In the same year, Zhang et al. (2015) reported a total of 48,914 genes in pooled RNA from various tissues of C. capsularis. Satya et al. (2018) observed that in the hypocotyls of a C. capsularis jute cultivar and its mutant, a total of 44,675 and 52,368 unigenes were expressed, respectively. On the other hand, 37,031 and 30,096 genes were expressed in the fiber cells of C. olitorius and C. capsularis, respectively (Islam et al. 2017). Yang et al. (2020) examined various C. olitorius plant parts including tissues from the vegetative growth stage, flowering stage, bast of the technical mature stage, and fruit. They identified a set of 15,491 core transcripts expressed in all the tissues. Of these, the estimate of the genes expressed in the hypocotyl tissue seems more reliable, as 87–94 % of genes were annotated using multiple annotation databases, and the resources are publicly available. Moreover, the annotation of reference-based assemblies would be similar to genome annotation, as the genes were identified using the genomic assemblies as the reference and annotated as per the reference. Thus, we can exclude the reference-based transcriptome assemblies

here, as genome annotations are discussed elsewhere in this book. Below, we provide an outline of the hypocotyl transcriptome of jute, for which the entire set of the TSA is publicly available for further research. The hypocotyl transcriptomes of C. capsularis cultivar JRC 212 were assembled using three assemblers, of which Trinity generated the utmost quality reads without gaps, greatest average lengths (1,098 bp), N50s (2,104 bp), as well as a maximum of 40.3% of unigenes with greater than 20-fold read-depth coverage (Fig. 15.1). More than 95% of these reads were mapped to the C. capsularis genome with high confidence. The Trinity assembled unigenes were annotated with four annotation databases (see Table 15.1), generating a total of 38,795 BLASTX aligned unigenes. The Nr-COG annotated unigenes were categorized into 25 diverse functional categories of orthologous groups, revealing major COG categories including transcription (1865 genes), general function (3886), signal transduction mechanisms (1680), and replication, recombination, and repair (1807) genes. Gene ontology (GO) mapping classified 9118 unigenes into three major classes and 44 sub-classes, and widely classified into 36.9%, 37.2%, and 25.8% GO-annotated unigenes under biological process, molecular function, and cellular component, respectively (Fig. 15.2). Transcriptional research in jute can be divided into four broad categories, gene discovery by characterizing mutant lines, comparative

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Fig. 15.1 Read length and read coverage of Trinity assembled hypocotyl transcriptome of JRC 212 (Satya et al. 2018)

Fig. 15.2 GO classification of unigenes of hypocotyl transcriptome of JRC 212 (Modified from Satya et al. 2018)

transcriptomics of tissues/growth stages, transcriptome analysis of tissues in response to external stimulus, and reconstruction of specific metabolic pathways.

(i) Analysis of mutants for gene discovery Functional characterization of a mutant is a primary approach for gene discovery. Since there is

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difficulty in the regeneration of jute, gene knockout experiments are rare in this crop. Alternately, transcriptome characterization of natural/induced mutants was found to provide valuable information on gene function in jute. The bast transcriptome of a low-lignin mutant, deficient in lignified phloem fiber (dlpf) was first characterized by Chakraborty et al. (2015) in comparison with the transcriptome of its wild type JRC-212, resulting in the identification of genes responsible for lignin synthesis. Both the bast transcriptomes represented a broad variety of transcripts implicated in metabolic and cellular processes, with dominant catalytic and binding activities. Over 200 bast-associated genes were mapped to the plant hormone signal transduction pathway, which suggests a crucial role of plant hormones in fiber biogenesis. Further, key genes in monolignol biosynthesis pathways were identified, and disruption of expression in phenylalanine ammonia-lyase (PAL) in the mutant at early vegetative growth stages was noticed, which, however, was reverted in later stages of growth. Conversely, the CcCAD7 (cinnamyl alcohol dehydrogenase isoform) was robustly down-regulated in mutant fiber tissues regardless of growth periods, demonstrating an implication of this gene in the expression of the mutant phenotype. Later, Satya et al. (2018) characterized the hypocotyl transcriptome of the same mutant (also showing a defect in hypocotyl development) and identified the crucial role of a cell wall degrading enzyme, b-galactosidase in remodelling of the cell wall during hypocotyl development. 11 b-galactosidases of GH-35 family were detected in transcriptomes generated from the mutant hypocotyl and many of which were absent in bast tissues. Bioinformatics analyses, gene expression studies, enzyme study, histochemistry, and genetic analyses identified CcBGAL4 and CcBGAL1 as the primary pectintargeting b-galactosidases in jute. This study also led to the discovery of a novel GH-2 family bgalactosidases (CcBGAL2), ubiquitously present in the plant kingdom, which bears close structural homology with E. coli lactose targeting bgalactosidase (lacZ). Finally, the authors used phylogenetic relationships of prokaryotic and

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eukaryotic b-galactosidases to develop a domaincentric model for the development of different classes of b-galactosidases depicting the loss and gain of specific domains at specific evolutionary stages. The model also explained the presence of a large number of b-galactosidases in plants, while in animals and the prokaryotes, only a few b-galactosidases are present. To understand the biological basis of flowering in jute, shoot-apex transcriptome of a gamma-irradiated delayed flowering-time mutant of jute (pfr 59) was compared with that of JRO 204 (wild type) (Choudhary et al. 2019). A total of 240 differentially expressed transcripts were identified between the mutant and the WT, of which 10 were related to photoperiod-related genes. A total of 123 transcripts were strongly upregulated and 117 downregulated in the mutant relative to the WT. The Co-KSB gene, which ciphers for the enzyme (Ent-Kaur-16-ene synthase) implicated in the gibberellic acid (GA) biosynthesis, showed the highest variation in expression in both shoot apex and leaves, suggesting a role of gibberellin biosynthesis in flowering. (ii) Tissue/growth identification

stage

specific

gene

A second and more common approach in the study of plant transcriptomes is to compare transcriptomes of various plant parts or specific groups of cells and identify differentially expressed genes. Many studies have attempted to study the expression pattern of genes in various plant tissues. For example, Islam et al. (2017) characterized the fiber cell transcriptome and compared it with the seedling transcriptome. They observed that in the fiber cell transcriptomes, signal transduction was a major GO category in both C. olitorius and C. capsularis, but abiotic stress-related GO classes were predominant in C. capsularis which might contribute towards higher abiotic stress tolerance and adaptation in different habitats. Based on their observation of jute genomes and transcriptomes, they proposed a model for fiber biogenesis in jute. Yang et al. (2020) made extensive comparisons of various plant parts of

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jute (19 RNA samples were taken from jute C. capsularis cv. Yueyuan5hao fruit, flower, leaf, and stem bast tissues). A total of 29,605 genes differentially expressed in seven tissues were compared. They observed that in comparison with leaf tissues, 2,035 upregulated and 2,231 downregulated genes were present in the bast tissues. In the flowering period, 7,108 genes were upregulated and 6,059 genes were downregulated in flower tissue relative to bast tissue. Likewise, 275 genes were upregulated and about 207 genes were downregulated in the leaf tissues in comparison with all other investigated tissues. Pathways like triterpenoid and sesquiterpenoid biosynthesis, hormone signal transduction, gluconeogenesis/glycolysis, and protein processing in the endoplasmic reticulum were enriched in tissues from stem bast, suggesting the association of these pathways in bast fiber formation. (iii) Gene expression in response to environment stimulus Various stress factors modulate gene expression in plants, including upregulation or downregulation of biological processes and pathways. Effects of two major abiotic stresses, drought and salt stress, have been investigated in jute using the transcriptomic approaches. Drought is a major abiotic stress affecting jute productivity, particularly at the seedling stage. Yang et al. (2017b) studied the effects of water deprivation on drought-tolerant dark jute and droughtsensitive white jute genotypes, discovering 794 and 39 differentially expressed genes, many of which are components of phenylpropanoid biosynthesis and peroxisome pathways. More recently, Zhang et al. (2021a) identified 1,329 differentially expressed genes in C. capsularis under drought stress, of which about 903 genes displayed an up-regulated expression. The biosynthesis pathways of both cellular nitrogen and inorganic compounds were found to be enriched under drought stress, specifically identifying crucial roles of NAM (non-apical meristem)-2-like gene in drought resilience. Transcriptome characterization of different tissues of white and dark jute under salt stress led to

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the identification of 127 DEGs (common differentially expressed genes) (Yang et al. 2017b). Of these, 13 DEGs are related to hormone signal transduction, most of which were upregulated in response to stress. In addition, many DEGs related to oxidation-reduction and protein phosphorylation were also upregulated in leaf and root tissues under salt stress. A set of 32 transcription factors (TF) was also expressed differentially in both the species under stress, indicating a role of TFs in stress signalling pathways. (iv) Reconstruction of metabolic pathways At the cellular level, enzymes are the key to metabolism. Although biochemical investigations have resulted in the purification and characterization of many enzymes, there are many reactions for which enzymes could not be purified. Moreover, many diseases are the results of metabolic errors. In such cases, identification of nucleotide/protein sequences of enzymes is essential. Transcriptome analysis complements biochemical genetics by allowing the assignment of annotated genes to metabolic pathways operating in a cell. The KEGG project (Kanehisa et al. 2012) reconstructs metabolic pathways from the genomic information, assigning genes to primary and secondary metabolic pathways. Chakraborty et al. (2015), using the KEGG pathway mapping tools, for the first time, reconstructed the lignin biosynthesis pathways in jute, including the phenylpropanoid biosynthesis pathway. They first assigned 5019 (JRC 212, WT) and 4802 (dlpf, mutant) unigenes to about 189 recognized pathways. About 38 isoforms of 16 genes, among which 37 being homologs, were found to be implicated in the shikimate-AAA pathway. Of these, about 43 isoforms of ten genes were associated with monolignol biosynthesis. Using the same transcriptome, they also identified genes involved in bast fiber biosynthesis, such as CesA (cellulose synthase) (12 genes), Csl (cellulose synthase-like) (1 gene), SuSy (sucrose synthase) (5 genes), BGAL (bgalactosidase) (8 genes) and FLA (fasciclin-like arabinogalactan) (21 genes) from the WT and the

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mutant. Zhang et al. (2015) also mapped 14,216 unigenes to 268 KEGG pathways and identified Susy (5), CesA (9), Csl (18), Korrigan (2), and Cobra (12) genes related to cellulose biosynthesis. Islam et al. (2017) made an extensive analysis of the fiber cell transcriptome and identified 329 C. olitorius and 344 C. capsularis candidate genes for fiber formation, generating a model for bast fiber biogenesis. They identified 10 CesA and 32 Csl genes and observed that CesA4 and CesA7 were upregulated in fiber cells, suggesting their involvement in fiber biosynthesis. Also, autophagy and proteolysis pathways were upregulated in the fiber cells, which could have been due to the degradation of nuclear and cytoplasmic components in these cells. Like lignin, pectin is an important component of many plant fiber cells like flax and hemp. However, jute fiber is characterized by the absence of pectin in its fiber, although it is an essential component of the primary cell wall of other tissues. More importantly, the post-harvest separation process of jute fiber from the other tissues of the bast is achieved by natural microbial retting (degradation) of non-fiber tissues in water bodies in which pectin is degraded, but lignocellulosic fibers are left intact. Characterization of pectin biosynthesis is therefore crucial for engineering the pectin biosynthesis process in order to enhance the retting process. Satya et al. (2021) reconstructed the pectin biosynthesis pathways in C. capsularis, detecting 27 isoforms of about 17 genes as well as 12 isoforms of pectin polymerizing gene galacturonosyltransferase (GAUT). By comparative chemical analysis of C. olitorius and C. capsularis fiber cells before and after retting, they found that rhamnogalacturonan is a major component of jute pectin and proposed that a pectin-lignin network in the middle lamella of fiber cells allow holding the fiber cells together, forming the fiber bundles in jute. Regulation of rhamnogalacturonan biosynthesis may hold the key to the separation of individual jute fiber cells from the fiber bundle, allowing the production of finer jute fiber.

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15.3.4 Regulatory sequences/Transcription factors Transcription factors are widely distributed in a genome executing regulation of key cellular biological processes including cell cycle regulation, chromatin modelling, intracellular metabolism, growth and differentiation, reproduction, and response to external stimulus. Several transcription factors such as bHLH, MYB, and WRKY have been reported to be involved in fiber cell growth in flax and cotton. Therefore, the identification of transcription factors is a key first step in understanding the regulatory networks in jute. In their study, Chakraborty et al. (2015) identified a total of 4,179 and 2926 unigenes (from C. capsularis wild type and its mutant) corresponding to 40 and 34 major classes of TFs, respectively. They identified C3H (373), MADS (356), FAR1 (269), WRKY (236), NAC (234), and MYB-related (233) to be the top six TF classes (Fig. 15.3). Satya et al. (2017) expanded the search and identified 457 SSRs related to various regulatory genes. Among these, 137 markers were developed from various transcription factors including bHLH, MYB-related, WRKY, zinc finger, and MYB TFs, many of which are the main regulators of phenylpropanoid biosynthesis. Saha et al. (2017) also developed 139 expressed gene-derived SSRs (eSSRs) from different transcription factors of jute. A total of 1769 transcription factors of 81 families and 948 protein kinases (PKs) of 122 families were reported by Yang et al. (2017a) in two jute species. They further identified 19 receptor-like kinases, many of which were downregulated under drought stress. Yang et al. (2017b) identified 2,303 TFs, of which 206 were up-regulated and 862 were down-regulated in leaf tissues compared to root tissues in C. capsularis under salt stress. To understand the regulation of fiber development in jute, Zhang et al. (2020) identified 43 jute WRKY transcription factors expressed in jute in response to gibberellic acid (GA3) and observed 21 of these to be upregulated in GA3-treated

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Fig. 15.3 Major transcription factor classes in jute (adapted from Chakraborty et al. (2015))

plants. Although this work claims to be the first to identify the WRKY group of TFs from jute, it may be noted that Chakraborty et al. (2015) first discovered 236 WRKY group of TFs, followed by Satya et al. (2017), who further designed a set of 43 WRKY TF sequence-based SSR markers for genetic analysis in jute. Yang et al. (2017b) also identified 2303 TFs, reporting the presence of MYB, WRKY, CCAAT, bZIP, NAC, and other classes.

15.4

Proteomics for Jute Improvements

Proteomics includes a comprehensive study of proteins, mainly their structure and physiological functions (Shah and Misra 2011). However, proteomic studies in jute are very limited, but a stable development of jute genome sequencing, resequencing, and availability of techniques in proteomic studies, embrace a great prospective for proteomics of jute, as has been done in other crops. Aslam et al. (2017) have summarized available proteomic techniques and their applications. The earlier studies on proteomics of fiber were confined to model plants such as Arabidopsis and the primary emphasis of these studies and concentration were limited to cell wall proteins (CWPs). Plant CWPs are actively implicated in changes of the cell wall structure

and components, signalling, and interplay with plasma membrane’s peripheral proteins. Minic et al. (2007) revealed the implication of proteomics in the detection and determination of functional and structural aspects of cell wall proteins. This method proves to be relevant in related cell wall proteins of fiber-producing plants such as jute. Also, diverse cell wall protein families, most of which may have a role in detecting pathogens, have been identified and characterized (Jamet et al. 2006). Some new techniques such as iTRAQ (isobaric tag for relative and absolute quantification) LC-MS/MS and others were also established and used to investigate proteomics of variances in fiber development between cultivated and wild cotton (Qin et al. 2017). Two proteins (zeatin and peroxidase) involved in fiber thickening and elongation in cotton were identified. This showed the role of proteomics in revealing mechanisms associated with various phenotypes. Proteome analysis can contribute to a profound understanding of developmental mechanisms. Further, proteomic profiling analysis of developing wild and cultivated cotton species detected 1317 proteins in its fiber (Hu et al. 2013). Thus, these methods can be replicated for related studies in jute. For jute, Ma et al. (2015) performed a proteomic study of salt response in C. olitorius and C. capsularis and detected 39 differentially expressed proteins using the MALDI-TOF-TOF

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MS approach and proposed a salt stressresponsive protein network in roots of jute seedling. They also observed significant variations in the expression of 44 protein spots in the seedling roots of both C. olitorius and C. capsularis based on the 2-DE (two-dimensional) gel electrophoresis. These data provide an understanding of salt responses and can help further studies on the dissection of salt tolerance mechanisms in C. olitorius and C. capsularis.

15.5

DNA Methylation and MiRNAs of Jute

15.5.1 DNA Methylation DNA methylation is an epigenetic mechanism that happens by the addition of a methyl group to the DNA, thus altering function and influencing gene expression in plants (Tariq and Paszkowski 2004) and animals (Goll and Bestor 2005). It also plays a vital role in TE (transposable element) silencing and cell differentiation (Zhang et al. 2018). DNA methylation is commonly seen in animals and higher plants, where it plays a major role in the growth and developmental courses (Feng et al. 2010). Recently, many considerations have shifted to DNA cytosine methylations (Lee et al. 2010). They have been largely analysed in model plants like rice and Arabidopsis owing to their genomic features which include low complexities and small sizes (Cokus et al. 2008; Li et al. 2008). Nevertheless, these investigations are very limited in jute plants. Begum et al. (2013) analysed cytosine methylation of satellite arrays in C. olitorius using immunolabelling (antibodies against 5-methylcytosine DNA) and detected visible hypomethylations in large cytosine satellite arrays but less visible in small satellite arrays (Begum et al. 2013). However, the causes of these variations are not very clear due to the lack of sufficient data on DNA methylation in jute. More studies focusing on DNA methylation and epigenetics are urgently needed for a better understanding of jute.

15.5.2 MiRNAs of Jute Plant miRNAs, which are known as a group of endogenous small ncRNAs (non-coding RNAs) with 18-24 nucleotides (nt), have been known as important genetic regulators mainly involved in various cellular functions in animals and plants (Kwak et al. 2009). In jute, various studies have identified miRNA using different approaches (Islam et al. 2015; Dey et al. 2016). With a deep sequencing approach, 227 known miRNA (including 164 belonging to 23 conserved families and 63 belonging to 58 families) and 17 novel miRNA have been identified, and about 133 target genes including both conserved and nonconserved miRNA were predicted and categorized into molecular, biological, cell component functions (Islam et al. 2015). Dey et al. (2016) detected nine mature miRNAs among which two miR-845b and miR-166 were found to play a role in defense against Macrophomina phaseolina in Corchorus capsularis. These miRNAs implicated in the defense against disease can be targeted to develop jute varieties that are resistant to Macrophomina phaseolina. However, all these miRNAs were identified when the jute reference genomes were not available, which was a big challenge during these studies. The recent completion of jute reference genomes (Islam et al. 2017; Sarkar et al. 2017; Zhang et al. 2021b) has provided an opportunity for identifying miRNA in genomic data such as ESTs. Very recently, 763 ESTs from jute were used to identify five candidate miRNAs (miR8689, miR9567-3p, miR1536, miR11300, and miR4391) targeting transcription factor genes that were observed to be implicated in lignin biosynthesis (3-dehydrogenate synthase, NAC), secondary cell wall formation (Sadenosyl-L-Met–dependent methyltransferase), and phenylpropanoid pathways (WRKY DNA binding protein), which play important roles in fiber development (Ahmed et al. 2021). Characterization of certain target genes and their functional annotation may lead to more microRNA detection and understanding of microRNA affiliation in lignin biosynthesis.

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15.6

Application of Gene Editing Techniques for Jute Improvement

15.6.1 Small RNA Interference Micro (miRNA) and siRNA are prominent genebased silencing techniques with significant applications in plant functional genomics. They differ in biogenesis, mode of action, and precursor structures. Shafrin et al. (2017) performed transformation of two monolignol biosynthetic genes, C4H (Cinnamate 4-hydroxylase) and COMT (caffeic acid O-methyltransferase) in dark jute by the incorporation of hpRNA-mediated constructs. The generated transgenic lines, C4HhpRNA and COMT-hpRNA, exhibited a substantially decreased level of gene expressions, which led to a 16–25% decrease of lignin content in stem and 13–14% decrease in fiber lignin as compared to the control data. Moreover, Shafrin et al. (2015) used amiRNA (artificial miRNA) based constructs to successfully downregulated C3H (coumarate 3- hydroxylase) and F5H (ferulate 5-hydroxylase) genes responsible for monolignoid biosynthesis in C. olitorius. By RTPCR, northern and southern blot assays, they observed a decreased level of gene expressions in C3H–amiRNA and F5H–amiRNA transgenic lines, which led to a 25% decrease in stem lignin and 12–15% decrease in fiber lignin as compared to non-transformed lines. These studies showed the possibility of producing jute cultivars yielding fiber with the required lignin and cellulose to manufacture standard jute products.

15.6.2 Mutagenesis Mutations can be created in a plant’s genome by the use of X- and gamma rays. However, it can create undesired random mutations in the genome, thus produce irregularities other than the concerned ones. For example, low lignin mutants of white jute created by x-ray irradiation exhibited some with reduced lignin content (50%), and simultaneous development of cellulose content,

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but also showed an obvious decline in fiber yield. The deficiency of secondary bast fiber bundles was also observed (Sengupta and Palit 2004). Choudhary et al. (2017) also detected irregularities in the mutant during a comparative analysis of dark jute llpf (low-lignin phloem fiber) mutant with 7.23% lignin content and WT (JRO 204) with 13.7% lignin content. The reduction of lignin in the mutant was due to the downregulation of the CCoAMT1 gene. This mutant has great implications in various studies on developmental processes. Moreover, Chakraborty et al. (2015) performed a comparative investigation of white jute var. JRC 212 with its mutant (dlpf ) produced by irradiation with X-rays, revealed that cad7 gene was down-regulated in the bast tissues of the mutant, regardless of the developmental stages.

15.6.3 CRISPR/Cas9 The CRISPR/Cas9 is a genome-based geneediting system and like most other organisms it can be used to target desired genes in plants and obtain ideal plant materials. To date, the application of CRISPR/Cas9 for genome-editing in jute is yet to be reported, but a stable development in genome sequencing, resequencing, and flexibility of CRISPR/Cas9 has great prospects for jute. CRISPR/cas9 has more advantages as it can be applied not only to knock out specific genes for the loss of function but can also be used to knock in and alter an individual gene at the transcriptional and epigenetic levels (Sauer et al. 2016; Mishra et al. 2018; Ahmad et al. 2020). Owing to some limitations such as off-target effects and others (Pattanayak et al. 2013; Zeng et al. 2020), the system of CRISPR/Cas9 has been reorganized. Recently, an efficient CRISPR/Cas-base editor (BEs) and CRISPR/LbCpf1 system have been established (Molla and Yang 2019). However, all these CRISPR/Cas9 systems depend on a precise knowledge of the target plant genome and genome annotation for analysis of the CRISPR/Cas9’s “off-target effects’’. Unfortunately, such detailed information is not yet

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S. Niyitanga et al.

available for jute. These related analyses can only be successfully achieved for jute, and once more details are obtained in the future. Therefore, transformation of jute using CRISPR editing system will remain complicated until more details on jute genome annotations are available.

15.7

QTL (Quantitative Trait Loci) Mapping

QTL mapping is an effective approach for elucidating the molecular root of complicated features of organisms (Würschum 2012). Although QTL mapping has been extensively applied in countless crops (McCough and Doerge 1995; Szalma et al. 2007), the use of this approach in jute is still limited, primarily owing to the self-incompatibility nature of jute (Patel and Datta 1960; Swaminathan et al. 1961), which display low cross fertility and production of fewer seeds, steering to the propagation of scant plant individuals for mapping quantitative trait loci. However, for the economic significance of jute plants (Al-Snafi 2016; Nyadanu and Lowor 2015) and the increasing demand for high-quality fiber for manufacturing diversified products, efforts are concentrating on QTL mapping of various agricultural attributes of jute, particularly attributes related to yield components such as plant height (Tao et al. 2017) and stem diameter, fiber quality traits like bast fiber cellulose content (Niyitanga et al. 2019), fiber fineness (Das et al. 2012), complex traits such as salt stress (Yang et al. 2019) and others. QTLs are regions in the genome that are responsible for a certain trait of the plant. Mapping specific regions responsible for an important trait can help in marker aided selection and improve molecular marker-assisted breeding programs. This can overcome lots of limitations of conventional breeding such as environmental effects. So far not many QTL studies are reported in jute. Studies on the identification of DNA markers and the construction of high-density linkage maps are accelerating QTL mapping and will pave the way for markerassisted breeding approaches in jute. Information

on QTL mapping in jute up to the year 2020 are summarized in Table 15.1.

15.7.1 QTL for Salt Tolerance Yang et al. (2019) used a high-density linkage map containing 4839 SNP markers dispersed on seven chromosomes (or linkage groups) and covering 1375.41 cM in a dark jute F2 populations derived from J009 (salt-tolerant variety)  Guangfenghangguo (GFG), to identify 16 salt tolerant QTLs including three obvious and thirteen minor QTLs. All these QTLs are distributed on 4 LGs (linkage groups) and are explained by phenotypic variance of 0.58–19.61%. A major QTL qJST-1 is positioned at 11.423.7 cM on LG4 flanking mk5633 (left marker) and mk6723 (right marker) (Table 15.2) under 140 mM salt stress condition and at 16.9–21.6 cM of the same linkage group between mk6160 (left marker) and mk6484 (right marker) under 160 mM salt stress condition. qJST-2 was also detected at 9-11.4 cM on LG4 flanking mk7047 (left marker) and mk5638 (right marker) under 140 mM of salt stress. QTL qJST3 was identified under 160 mM salt stress on LG4 at a position of 13.41 cM and flanking mk6393 (left marker) and mk6391(right marker). Among the minor QTLs (13), eight were detected under 160 mM and five under 140mM salt stress, and all together explained a phenotypic variance of 0.58–8.12%. This was a novel study on jute salt tolerance QTLs as many earlier investigations on salt tolerance of jute have concentrated only on physiological, proteomic, and morphological constituents.

15.7.2 QTL for Plant Height Jute plant height is a major component of fiber yield and is strongly correlated with both fiber content and yield. Tao et al. (2017) utilized a highly dense linkage map comprising of 913 polymorphic SLAF markers distributed on 11 linkage groups and 100 white jute lines of an F8

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Functional Genomics of Jute

237

Table 15.2 Information on QTLs identified in Jute (till Dec. 2020) Trait / Treatment

QTL name

Crossing parents

LG

Peak Location (cM)

Markers

Reference

140 mM salt stress

qJST-1

J009 x GFG

LG4

19.31

mk5633 - mk6723

(Yang et al. 2019)

160 mM Salt stress

qJST-1

LG4

19.31

mk6160- mk6484

(Yang et al. 2019)

140 mM Salt stress

qJST-2

LG4

10.01

mk7047- mk5638

(Yang et al. 2019)

160 mM Salt stress

qJST-3

LG4

13.41

mk6393- mk6391

(Yang et al. 2019)

Bast cellulose

qBFC1 − 1

LG1

159

Marker4610 Marker36215

(Niyitanga et al. 2019)

qBFC2-1

LG1

226

Marker595Marker17742

(Niyitanga et al. 2019)

qBFC4-1

LG4

30

Marker17979Marker26772

(Niyitanga et al. 2019)

qBFC1-1

LG1

159

Marker4610Marker36215

(Niyitanga et al. 2019)

qBFC1 − 3

LG1

230

Marker28143Marker18926

(Niyitanga et al. 2019)

Plant Height (PH)

179  Aidianyesheng

qPH2.3

179  Aidianyesheng

LG2

223

Marker595Marker17742

(Tao et al. 2017)

QPh.ccsu1.1

JRO-524  PPO-4

LG1

2.01

MJM659-MJM895

(Das et al. 2012)

LG1

52.21

MJM631MJM1265

(Das et al. 2012)

LG1

79.19

MJM679

(Topdar et al. 2013)

qPH- l2

LG2

93.97

MJM536

(Topdar et al. 2013)

qPH- l5

LG5

201.35

MJM635

(Topdar et al. 2013)

qPH- l7

LG7

4.0

MJM305

(Topdar et al. 2013)

LG1

40.2

Co_Sb0237

(Kundu et al. 2015)

qPH-12–1

LG2

24

Co_Sb0254

(Kundu et al. 2015)

qPH12-2

LG2

26.9

Co_Sb0117

(Kundu et al. 2015)

QPh.ccsu1.3 qPH-l1

qPH-11

Stem-base diameter (SBD)

JRO-524  PPO-4

Sudan Green  bfs

QBd.ccsu1.3

JRO-524  PPO-4

LG1

52.21

MJM631MJM1265

(Das et al. 2012)

qSDB-l1

JRO-524  PPO-4

LG1

39.57

MJM650 1

(Topdar et al. 2013)

qSDB-l2

LG2

111.03

MJM581

(Topdar et al. 2013)

qSDB-l7

LG7

5.29

MJM305

(Topdar et al. 2013)

(continued)

238

S. Niyitanga et al.

Table 15.2 (continued) Trait / Treatment

Stem-mid diameter (SMD)

Stem-top diameter (STD)

Number of nodes (NN)

QTL name

Crossing parents

qSBD-11

Sudan Green  bfs

LG

Peak Location (cM)

Markers

Reference

40.2

Co_Sb0237

(Kundu et al. 2015)

qSBD-121

LG2

24

Co_Sb0254

(Kundu et al. 2015)

qSBD-12–2

LG2

26.9

Co_Sb0117

(Kundu et al. 2015)

MJM1267MJM051

(Das et al. 2012)

QMd. ccsu2.3

JRO-524  PPO-4

LG2

QMd. ccsu1.1

LG1

6.01

MJM659-MJM895

(Das et al. 2012)

QMd. ccsu1.3

LG1

52.21

MJM631MJM1265

(Das et al. 2012)

QMd. ccsu3.1

LG3

6.01

MJM47-MJM238

(Das et al. 2012)

QMd. ccsu3.3

LG3

94.01

MJM1033MJM1139

(Das et al. 2012)

QMd. ccsu6.3

LG6

60.31

MJM136MJM1140

(Das et al. 2012)

qSDM-l3

LG3

60.48

MJM722

(Topdar et al. 2013)

qSDM-l7

LG7

16.058

MJM500

(Topdar et al. 2013)

QTd.ccsu2.4

JRO-524  PPO-4

LG2

136.71

MJM051MJM1262

(Das et al. 2012)

qSDT- l1

JRO-524  PPO-4

LG1

79.19

MJM679

(Topdar et al. 2013)

qSDT- l3-1

LG3

27.89

MJM513

(Topdar et al. 2013)

qSDT- l3-2

LG3

60.48

MJM722

(Topdar et al. 2013)

qSDT-l5

LG5

217.15

MJM668

(Topdar et al. 2013)

LG1

52.21

MJM631MJM1265

(Das et al. 2012)

QNn. ccsu1.2

LG1

9.21

MJM895-MJM631

(Das et al. 2012)

QNn.ccsu6.1

LG6

16.01

MJM1084MJM1134

(Das et al. 2012)

LG1

81.88

MJM679

(Topdar et al. 2013)

QNn.ccsu1.3

qNN- l1

JRO-524  PPO-4

JRO-524  PPO-4

(continued)

15

Functional Genomics of Jute

239

Table 15.2 (continued) Trait / Treatment

QTL name

Crossing parents

LG

Peak Location (cM)

Markers

Reference

Fiber yield (FY)

QFw. ccsu1.1

JRO-524  PPO-4

LG1

6.01

MJM659-MJM895

(Das et al. 2012)

LG1

11.21

MJM895-MJM631

(Das et al. 2012)

LG1

37.57

MJM650

(Topdar et al. 2013)

LG4

89.68

MJM602

(Topdar et al. 2013)

QFw. ccsu1.2 qFY-l1

JRO-524  PPO-4

qFY-l4

Wood yield (WY)

qFY-1

Sudan Green  bfs

LG1

40.2

Co_Sb0237

(Kundu et al. 2015)

QSw.ccsu1.1

JRO-524  PPO-4

LG1

6.01–8.01

MJM659-MJM895

(Das et al. 2012)

QSw. ccsu1.2

LG1

11.21

MJM895-MJM631

(Das et al. 2012)

QSw.ccsu1.3

LG1

52.21

MJM631MJM1265

(Das et al. 2012)

LG1

37.57

MJM650

(Topdar et al. 2013)

qWY-l4

LG4

89.68

MJM602

(Topdar et al. 2013)

qWY-l5

LG5

192.74

MJM663

(Topdar et al. 2013)

LG4

30.41

MJM152-HK60

(Das et al. 2012)

QGw. ccsu1.1

LG1

6.01

MJM659-MJM895

Das et al. (2012)

QGw. ccsu1.3

LG1

52.21

MJM631MJM1265

Das et al. (2012)

LG2

113.03

MJM581

Topdar et al. (2013)

LG4

89.68

MJM602

Topdar et al. (2013)

qWY-l1

Green biomass yield (GBY)

QGw. ccsu4.2

qGBY-l2

JRO-524  PPO-4

JRO-524  PPO-4

JRO-524  PPO-4

qGBY-l4 Root weight (RW)

qRW-l1

Sudan Green  bfs

LG1

40.2

Co_Sb0237

Kundu et al. (2015)

Fiber fineness (FF)

QFf.ccsu5.3

JRO-524  PPO-4

LG5

99.01

MJM1182MJM1150

Das et al. (2012)

qFF-l2

JRO-524  PPO-4

LG2

100.704

MJM566

Topdar et al. (2013)

qFF-l3-1

LG3

58.707

MJM722

Topdar et al. (2013)

qFF-l3-2

LG3

69.96

MJM667

Topdar et al. (2013)

qFF-l5

LG5

199.89

MJM635

Topdar et al. (2013)

Tensile strength (TS)

qTS- l1

JRO-524  PPO-4

LG1

0.000

MJM644

Topdar et al. (2013)

Histological fiber content (FC)

qFC-11

Sudan Green  bfs

LG1

40.2

Co_Sb0237

Kundu et al. (2015)

240

population generated from an elite cultivar 179 (female parent)  local variety ‘Aidianyesheng’ (male parent) to identify eleven QTLs for jute PH. Of the 11 PH QTLs identified, one is major QTL (consistent in two environments) and a single QTL is explained with a phenotypic variance of 44.14–15.63%. The eleven QTLs are distributed on LG1, LG2, LG3, LG9, and LG10 with the major QTL found in LG2 between markers 595 and 177742 with a LOD score of 7.2. In the study, Tao’s group found a good number of segregation distortion among the markers which could be the result of using genetically distant parents, self-incompatibility alleles, structural rearrangements, etc. They argued that the map with 11 LGs instead of seven LGs (as jute is a diploid organism with seven chromosomes) is not saturated. The QTLs could not be compared with the previously identified height QTLs due to the use of different parents, mapping strategies, number and type of mapping loci, choice of mapping software, and mapping population number. But consistent with previous studies, they found that the female parent contributed the main QTL for PH as discussed by Topdar et al. (2013) and Kundu et al. (2015).

15.7.3 QTL for the Histological Bast Fiber Das et al. (2012) identified 21 QTLs for eight fiber yield-related traits and one QTL for two fiber quality (fiber fineness) traits using 120 recombinant lines in F6 populations and a linkage map of 36 SSR markers (Das et al 2011). F6 RILs were generated from C. olitorius varieties, JRO524 (coarse fiber), and PPO4 (fine fiber) by single seed descent. Among the eight FY traits, BD, MD (in cm), and TD (in cm) were measured at the base, middle portion, and tip of the plant. NN was detected as the number of nodes in the stem, GW was measured as the total aboveground plant weight after harvesting, dried fiber weight (FW in g) after retting of the plant, and extraction of fiber followed by washing and

S. Niyitanga et al.

drying. Stick weight (SW in g) is referred to the weight of the dried woody stalk that remains after the extraction of the fiber. Two fiber quality traits investigated were FF (in tex) and fiber strength (FS in g/tex). FF measures the thickness or diameter of the fiber filament as mass per unit length, i.e. linear density (g/km), and is referred to as tex. Fiber strength defines the ability of the fiber to resist strain to the limit of rupture that is measured as the breaking load of the fiber sample divided by the linear density of the unstrained fiber (tenacity). 14 QTLs for fiber yield (FY) related traits were found in LG1 at the SSR marker intervals NJN659-MJM895, MJM895-MJM631, and MJM631-MJM1265. They also elucidated QTL  QTL epistatic interactions and QTL x Environment interactions using single-locus and twolocus QTL interval mapping. Main effect QTL of (M-QTL as designated by the authors) PH, SBD, SMD, NN, and GBY and FY exhibited significant Q  E interaction. For FF one M-QTL was detected and no QTL for TS was identified. 16 EQTLs (epistatic QTL) were identified for six FY-associated traits. Sarkar et al. (2016) have thoroughly reviewed the QTLs identified in JRO524 x PPO4 and Sudan green x bfs progeny. The latter cross was developed by Kundu et al. (2015) who reported a linkage map containing 503 RAD markers distributed on 7 seven linkage groups and spanning 358.5 cM. QTLs were detected for FC which denotes the total number of fiber cell bundles in a stem cross-section. FC was found to be correlated with other phenotypes like FY, PH, RW, and SBD. Nine QTLs were identified across two environments for all the above-mentioned traits. FC QTL was coincident with one QTL each for the traits at 40.2 cM on LG1. An F2 mapping population was developed by crossing exotic cultivar Sudan Green (SG) (Female) and thermal neutron-induced phloic (bast) mutant of C. olitorius JRO-632 known as bfs (bast fiber shy). It is defective in bast fiber development but develops normal secondary phloic fiber cell bundle (FCB) and can produce lignin-rich bast

15

Functional Genomics of Jute

fiber upon retting. QTLs for FY, PH and SBD mapped in LG4, 5, but KG7 in JRO524 x PPO4 progeny could not be detected in this case.

15.7.4 QTL for Bast Fiber Cellulose A SLAF linkage map developed by Tao et al. (2017) was enriched with simple sequence repeat markers by Niyitanga et al. (2019) and used to detect QTLs for fiber cellulose in white jute. Epistatic effects and epistasis x environment interaction were also observed. 104 F8 recombinant inbred line individuals derived from a cross between Aidianyehuangma and Huangma 179 were used as a mapping population. Fiber cellulose content was measured using a modified colorimetric method (Zuk et al. 2016). Five definitive QTLs were detected on two out of seven chromosomes (or linkage groups) by an inclusive composite interval mapping with an additive effect (ICIM‐ADD) approach. QTL qBFC1-1 in LG1 was detected as a major stable QTL. The major qBFC1-1 is co-localized in LG1 between 158.47 and 159.04 cM suggesting the involvement of multifunctional genes for cellulose production and accumulation.

15.8

Conclusion and Perspectives

The availability of jute reference genomes and the development of biotechnology have revolutionized molecular biology and genomic studies in jute. Substantial efforts have been made in past decades in genomics and molecular biology studies, including genome sequencing, transcriptome analysis, quantitative traits analysis, using genome editing techniques, and others. However, most of these studies for example miRNA investigation, proteomics analysis, identification of gene regulatory networks, biosynthetic pathways, and the regulatory mechanisms underlying important traits, proper genome annotation, etc. are still not fully understood. More studies are urgently needed for a better understanding. Lack of sufficient and detailed gene information has restricted the

241

generation of transgenic plants using geneediting tools. Traditional breeding is time-consuming and is affected by the environment. It is a serious bottleneck for traditional cross-breeding. Jute plants (C. olitorius and C. capsularis) are asexually incompatible due to their strong crossincompatibility which has complicated their propagation. Transgenic breeding techniques have furnished us with novel answers for the molecular design of breeding strategies, which mostly depend on the increase of knowledge of molecular biology and functional genomics. Although substantial efforts and developments have been made in the past years, the molecular biology and genomics of jute are still not completely understood, primarily owing to problems in resource identification and collection, population construction, and the identification and generation of mutant plants. Notably, insufficient data on functional genomics and evolving biology have dimmed our insight into their essential biological features. Thus, in comparison to some other crops like rice, a lot of improvement has to be made in jute molecular biology and genomics studies. In the future, plant scientists should concentrate more on industry-driven elementary biological investigations, as a chance for improving research on regulation and biosynthesis of metabolites, genetic foundation of desired agricultural attributes, molecular mechanisms underlying disease and stress resistance, as well as the developmental biology of jute to hasten molecular breeding programs. These developments will promote industrial growth and the manufacture of value-added jute products.

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Jute Genomic Resources and Database

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Haseena Khan, Liwu Zhang, Dipnarayan Saha, Huawei Wei, Subhojit Datta, Pratik Satya, Jiban Mitra, and Gouranga Kar

Abstract

Jute, a homozygous diploid commercial crop, is undergoing an exciting phase of genomic resource expansion after being overlooked for

H. Khan (&) Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000, Bangladesh e-mail: [email protected] L. Zhang College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China e-mail: [email protected] H. Wei Experiment Station of Jute and Kenaf in Southeast China, Ministry of Agriculture and Rural Affairs/Public Platform of Fujian for Germplasm Resources of Bast Fiber Crops, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China e-mail: [email protected] D. Saha
S. Datta
P. Satya
J. Mitra
G. Kar ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore 700121, India e-mail: [email protected] S. Datta e-mail: [email protected] P. Satya e-mail: [email protected] J. Mitra e-mail: [email protected] G. Kar e-mail: [email protected]

several years. The past decade saw extensive developments in the generation of physical and genetic mapping data, genomic and transcriptomic information of the two jute cultivars (Corchorus olitorius and Corchorus capsularis), molecular markers together with karyotype and cytogenetic landscapes and a web-based jute marker database. These data have helped to reveal key regulatory and structural factors of the jute genome. Such genomic resources are steadily contributing to the expansion of our understanding of different molecular mechanisms functional in jute. In the post-genomic data generation period, utilization of the jute genomic resources through integration of comparative genomics, molecular breeding and genomic selections would be the major focus in advancing high-precision jute breeding. Thus, it is high time to assess the status of genomic and other genetic resources that are expected to cater to the much-needed functional analysis of a large number of jute genes and their contributions to the inherent phenotypic plasticity in this important crop.

16.1

Introduction

Jute, the most versatile crop in the world, attains huge biomass in just 120 days and is considered a renewal gold mine. Even though the industrial use of jute is centuries old, research on jute

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_16

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molecular biology was initiated only at the beginning of the twenty-first century. The two cultivated jute species, Corchorus capsularis and Corchorus olitorius, are cross-incompatible. The self-pollinating nature of jute has led to a narrow genetic base in the cultivated species. This together with a misinterpretation of genome size had initially slowed down the genomic research on this crop. The beginning of the molecular investigation of jute for unravelling its genetic makeup was modest. Up until the first decade of the new millennium, jute genomic research was limited to the analysis of genetic diversity of the crop using RAPD and SSR markers, tissue culture, somatic hybridization, ESTs and genetic transformation. However, the advent of nextgeneration sequencing facilities and their affordability accelerated the investigation and characterization of jute genomic resources. The present status of jute genomics, development and utilization of molecular markers, generation of a large wealth of jute omics data allow for the selection of superior traits like fibre quality etc. It has allowed the advancement of mutagenesisbased reverse genetic strategies for developing low-lignin jute. Therefore, it is apt to appraise the status of proliferating advances made in the diverse genomic resources and databases in jute. It will not only speed up the analysis of gene functions but will also encourage jute breeders to strategize and strengthen the jute breeding programs for the development of varieties with superior fibre qualities and jute plants adapted to adverse environmental stresses. In this chapter we take a brief but comprehensive account of all the prevailing jute genomic resources, such as molecular markers and linkage maps, source of gene and noncoding sequence information, the status of genome and transcriptome sequences, karyotype and chromosomal resources, and a database for easy accessibility of the molecular marker resources.

H. Khan et al.

16.2

Types of Genomic Resources

16.2.1 Molecular Markers Among the molecular markers, random amplified polymorphic DNA (RAPD) markers, the first to be used in jute, had the ability to distinguish between the two cultivated jute species, C. capsularis and C. olitorius. From the first dendrogram created between the various members of these two species, existing genetic classification was found to agree with the molecular marking data (Hossain et al., 2002). The first organelle-specific microsatellite markers, which were developed from tobacco, and AFLP markers were next developed to determine genetic diversity between C. olitorius and C. capsularis (Basu et al. 2004). The molecular markers were capable of distinguishing between the two different cultivated jute species, but at the intra-specific level, the resolution of genetic diversity was relatively low. The geographical collections of jute were also indistinguishable through the use of these molecular markers. Thus, the molecular markers revealed a narrow genetic base in the cultivated jute within a species and regardless of geographical differences. Thereafter, several molecular markers were developed for amplifying microsatellite-related loci in jute. Cross-species transferability of these SSR markers from cotton and jute exhibited their applicability in several heterologous species of the Malvaceae family (Satya et al. 2016). In the next few years, with the advancement and use of nextgeneration sequencing (NGS) technologies in jute, a large number of molecular markers, like genomic SSRs, expressed transcript-derived SSRs (EST-SSRs), single nucleotide polymorphism (SNP), InDels etc. were enriched in jute research with diverse applications like characterization of jute germplasm, linkage map construction and molecular breeding (Kundu et al. 2015; Saha et al. 2017; Satya et al. 2017; Yang et al. 2018).

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16.2.2 Gene and Protein Sequence Resources

16.2.4 Transcriptome-Derived Unigene Resources

In the NCBI database, a search for Corchorus genes produced only 286 (till May 2021), the majority of which are ribosomal protein-coding, tRNA or photosystem-related genes. However, the NCBI nucleotide database shows 81,046 hits for C. capsularis and 26,864 hits for C. olitorius. The protein sequence database highlighted 29,614 and 35,997 hits for C. capsularis and C. olitorius, respectively. In UniProt database, 29,392 and 35,783 protein sequences are available from the C. capsularis cv. CVL-1 and C. olitorius O-4 genomes, respectively. Similarly, 29,356 gene sequences of C. capsularis cv. CVL-1 could be accessed from the Biomart tool of the EnsemblPlants database. The plant comparative genomic database, PLAZA 4.5 (https:// bioinformatics.psb.ugent.be/plaza/versions/ plaza_v4_5_dicots/) comprises of 37,281 genes (35,704 protein-coding) and 1577 noncoding RNA genes of C. olitorius origin. The database also provides homologous and orthologous gene family information for each gene.

Lignin content in jute fibre is crucial for fibre quality, such as fineness and strength. Low-lignin jute is one of the major considerations in jute breeding. The bast tissue-derived transcriptome was developed in white jute cv. JRC-212 and its deficient lignified phloem fibre (dlpf) mutant to identify important genes involved in the secondary cell wall (SCW) formation and lignin biosynthetic pathway (Chakraborty et al. 2015). The transcriptome produced 34,163 and 29,463 unigenes, respectively. It enabled the identification of lignin biosynthetic pathway-related genes, such as phenylalanine ammonia-lyase 1 (PAL1) and cinnamyl alcohol dehydrogenase 7 (CAD7) genes regulating the lignin biosynthesis irrespective of any growth stages. Similarly, in a separate study with hypocotyl transcriptome from the same genotypes, b-galactosidases (b-Gal) of glycoside hydrolase-2 (GH2) family was reportedly involved in the cell wall degradation and hypocotyl development in jute (Satya et al. 2018). Another important trait, early flowering under short-day conditions (EFS), popularly known as ‘premature flowering’, is crucial for the early sowing of jute. Early sowing enables farmers. However, the early sowing leads to exposure of jute plants to short-day conditions resulting in early flowering and excessive branching. This leads to poor quality and yield of fibre. Thus ‘premature flowering’ resistance variety is of paramount interest in jute breeding. Transcriptome sequencing of the shoot apex tissues from a dark jute cultivar, JRO-204, and a gammairradiation-derived delayed flowering mutant line pfr59 (Choudhary et al. 2019) produced 14,050 unigenes and 240 differentially expressed genes, leading to the identification of crucial photoperiodic and gibberellin signalling pathway genes as candidates of flowering time regulation in jute. Using transcriptomic data, Yang et al. (2017) have made a comprehensive study on drought

16.2.3 Public Database Sources of Noncoding RNA Sequences There is scattered information on jute noncoding RNA sequences. However, the RNAcentral database (https://rnacentral.org/), which deals with a comprehensive collection of ncRNA sequences from diverse organisms, comprises a total of 4942 ncRNA and rRNA sequences from all Corchorus sp.; 2455 and 2288 sequences of C. olitorius and C. capsularis, respectively. The database also consists of RNA sequences from several wild Corchorus sp. Similarly, the Rfam database (https://rfam.xfam.org/), which hosts all RNA families, including the noncoding RNAs, consists of 2280 and 2205 RNA sequences of C. olitorius and C. capsularis, respectively.

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tolerance in two jute species—a tolerant and a drought-sensitive one. In total, 45,831 nonredundant unigenes were identified. Several differentially expressed genes from transcription factor families were found to be involved in drought stress regulations. Also, the SNPs identified in the DEGs are expected to be utilized as a source for candidate markers in droughttolerance studies in jute.

16.2.5 Genome Resources Availability of genome sequence in any agricultural crop is extremely valuable towards accelerating genetic improvement in that crop either through targeted and precision molecular breeding approaches or through genetic engineering, like transgenic and genome editing. The decoded genome sequence thus enables researchers to identify key genes and regulatory sequences for plant disease resistance, abiotic stress tolerance and other agronomically important traits. Besides, diverse molecular markers like nuclear SSRs and SNPs can also be physically mapped on the chromosomes at the genome-wide scale enabling molecular breeders to tag important quantitative trait loci (QTL) for genomic selection and breeding. In jute, the genome sequence of a few cultivars has been developed in recent years. The draft genomes of the two cultivated jute species have been reported by Islam et al. (2017), Sarkar et al. (2017) and Zhang et al. (2019). Islam et al. (2017) determined the genome sizes for C. olitorius and C. capsularis to be  448 and  404 Mb, respectively. The high-quality draft genomes of the two jute species and their comparisons made by them at the functional genomics level showed the assemblies to cover 91.6% and 82.2% of the estimated genome sizes for C. olitorius and C. capsularis, respectively. In total, 37,031 C. olitorius and 30,096 C. capsularis genes were identified, and most of the genes were validated by cDNA and RNA-seq data. RNA expression analysis from isolated fibre cells has helped to understand key regulatory and structural genes involved in fibre formation.

H. Khan et al.

The genome of a popular Indian cultivar JRO524 (Navin) was sequenced and the genome size was determined to be 377.3 Mbp (Sarkar et al. 2017). The draft genome of JRO-524 was assembled into seven chromosomes and annotated for 57,087 protein-coding genes. The chromosomes of the JRO-524 jute genome were found syntenic with the cocoa (Theobroma cacao) and cotton (Gossypium raimondii) genomes. Several disease resistance-like genes, repeat elements and transposable elements were identified from the genome. The JRO-524 genome is expected to provide a strong platform to study the biology of early flowering under shortday conditions and accelerate the development of improved and durable cultivars for premature flowering in jute. Zhang et al. (2019) sequenced C. capsularis var. Huangma 179 and C. olitorius var. Kuanyechangguo genomes by integrating wholegenome shotgun reads, Pacbio sequences and HiC as well as high-density genetic maps. They assembled 361 Mb for C. olitorius and 336 Mb for C. capsularis, and annotated 28,479 C. olitorius genes and 25,870 C. capsularis genes These paired-end Hi-C reads were then uniquely mapped onto contigs, which were grouped into seven pseudo-chromosomes in each species (Zhang et al. 2019).

16.3

Physical Maps

Jute cultivars are diploid (2n = 2x = 14) with wild Corchorus species showing higher ploidy levels. The chromosomes of Corchorus species are not very extensively characterized. These chromosomes have been found to be relatively small in size with lengths varying between 15 and 35 µm (Sinha et al. 2011). Because the chromosomes are typically metacentric to submetacentric and have similar morphology their discrimination has not been readily possible until recently. Efforts to identify jute chromosomes were initially made by the determination of chromosome lengths and arm ratios (Samad et al. 1993; Morakinyo and Baderinwa 1997) and fluorescent banding methods (Alam and Rahman

16

Jute Genomic Resources and Database

251

2000). However, Alam and Rahman (2000) could identify only two chromosomes by fluorochrome staining chromomycin-A3 and DAPI. Begum et al. (2013) have made use of four repetitive probes entailing two major sequence families and ribosomal genes in multicolourFISH and rehybridization to develop karyotypes of jute. Joshi et al. (2014) described the chromosome-specific physical location of genes in jute. They studied the specific association of 63 single-copy ESTs and determined their position on jute chromosomes. Karyotype analysis made by Prof. Zhang’s group (Chen et al., 2011) found the longest chromosome length of jute to be 6.17 and the shortest 3.34. The chromosomes arm ratios are between 1.21 and 1.54. In addition, chromosome 4 had a pair of accompanying bodies (Table 16.1, Fig. 16.1) from the work of Chen et al. (2011). Thus, the karyotype formula that they deduced was 2n = 2x = 14 = 12m + 2m (SAT) (Table 16.2). Moreover, cytogenetic analysis of karyotype and chromosome number of Corchorus were computed from some species and wild relatives of Corchorus using the root tip squash method (Chen et al. 2011). The number of chromosomes in these materials was 2n = 14, however, chromosome clumping was observed in virtually all cells at the metaphase stage with morphological similarities among the chromosomes (Fig. 16.2).

Table 16.1 RNA resources from the Rfam database v. 14.5 (status March 2021)

Fig. 16.1 Chromosome karyotype analysis diagram of jute

16.4

One of the prime foci of plant genetic improvement through molecular breeding or markerassisted breeding is to construct a high-density genetic or linkage map with robust molecular markers, which facilitates mapping of the quantitative trait loci (QTLs). The quality of a genetic map directly depends on the advancement of genomic resources in that crop. A couple of genetic maps were constructed in jute using a diverse set of molecular markers and QTLs. With respect to the two jute cultivars, C. olitorius has received more attention than C. capsularis for the

Jute species

RNA type

C. olitorius

Total

C. capsularis

Genetic Maps

Number 2280

Ribosomal RNA (rRNA)

358

Transfer RNA (tRNA)

803

Small nuclear RNA (snRNA)

748

miRNA

182

Total

2205

Ribosomal RNA (rRNA)

366

Transfer RNA (tRNA)

757

Small nuclear RNA (snRNA)

663

miRNA

169

252 Table 16.2 Karyotype analysis of Corchorus olitorius L

H. Khan et al. No. of chromosome

Short arm

Long arm

Total length

Arm ratio

Type

I

2.73

3.44

6.17

1.45

m

II

2.16

3.32

5.48

1.54

m

III

2.17

3.05

5.22

1.41

m

IV

1.13

2.82

4.95

1.32

M+Sat

V

2.19

2.76

4.95

1.26

m

VI

2.08

2.52

4.6

1.21

m

VII

1.42

1.92

3.34

1.35

m

Fig. 16.2 Chromosome karyotypes of Kuanyechangguo (A, C. olitorius), Nanyangyeshengchanguo (B, C. olitorius), Tansangniyayeshengchangguo (C, C. olitorius), Minma 5 (D, C. capsularis), Aidianyeshenghuangm (E, C. capsularis), Lianjiangyeshengyuangguo (F, C. capsularis), Jiahhuangm (G, C. aestuans), Jiachangguozhong (H, C. pseudoolitorius), Tianma (I) (arrows indicating satellite chromosome) (Chen et al. 2011)

generation of genetic maps and QTL documentation. Although the first generation of linkage map in jute was constructed using dominant markers, like RAPD, ISSR and SRAP (Chen et al. 2014), co-dominant SSR markers generated through SSR library enrichment sequencing were also eventually used. From the modest beginning of Sultana et al. (2006) and Haque et al.’s (2008)

work on the construction of a linkage map covering a small part of the jute genome, progress on mapping C. olitorius saw a gradual expansion. A genetic linkage map using 122 sequencerelated amplified polymorphism loci and three morphological markers, with an average marker interval of 17.86 cM were used by Chen et al. (2011) in developing a genetic map for C.

16

Jute Genomic Resources and Database

olitorius. Using 36 polymorphic simple sequence repeats (SSRs) markers in a recombinant inbred population developed from a cross between two C. olitorius genotypes (Das et al. 2012) generated a linkage map spanning 784.3 cM in six linkage groups. This allowed the identification of 21 QTLs for eight fibre yield traits and one for fibre fineness. Restriction-site-associated DNA markers were used by Kundu et al. (2015) for the construction of a genetic map, which spanned 358.5 cM in seven linkage groups and led to the identification of 26 QTLs for fibre quality, yield and yield-related traits. The average marker density achieved in this map (0.72 cM) held the promise to allow marker-aided selection in jute with high precision. A total of 503 RAD-SNP markers were utilized to construct a linkage map in C. olitorius which spanned the seven linkage groups. Similarly, a high-density linkage map of 4839 SNP markers was constructed to map QTLs for salt tolerance in this jute species (Yang et al. 2019). These SNP markers span the sevenlinkage group with an average distance of 0.28 cM between two adjacent markers. For C. capsularis, Chen et al. (2014) described a linkage map made out of 119 markers comprising 44 SRAPs, 57 ISSRs and 18 RAPD markers that covered 2185.7 cM and had a mean density of 18.7 cM per locus. Kundu et al (2015) made use of SNP markers in the construction of a linkage map for a RIL population of C. capsularis, which led to a total map length of 2016 cM and the identification of nine linkage groups with an average marker interval of 4.2 cM. Highthroughput sequencing strategies have facilitated the development of specific locus amplified fragment sequencing (SLAF-seq). This method has proved to be efficient for large-scale de novo SNP discovery and genotyping (Sun et al. 2013). It provides an efficient strategy for developing SNP and InDel markers for use in the construction of high-density genetic maps. Tao et al (2017) employed this efficient strategy for developing SNP and InDel markers for use in the construction of high-density genetic maps for C. capsularis. Out of 5074 polymorphic SLAF markers, 913 were utilized in constructing a genetic linkage map to identify plant height QTL.

253

Eleven QTLs associated with plant height were identified using this new genetic linkage map. Together, the 5074 SLAF, 173 InDels, and 748 unigene-derived SSR markers were integrated into another genetic linkage map in white jute to identify five QTLs for bast fibre cellulose content for marker-assisted selection and breeding (Niyitanga et al. 2019). Single nucleotide polymorphism markers were developed in jute using the restriction-site-associated DNA (RAD) sequencing technique.

16.5

Transposable Elements of Jute

Early studies on the isolation and characterization of the reverse transcriptase domains of jute long terminal repeat (LTR) retrotransposons and their estimated copy number were made by Ahmed et al. (2011) and their heterogeneity investigated. LTR retrotransposons were found to constitute about 19% of the jute genome having approximately 31,000 copies of Ty1gypsy elements and 3,600 copies of Ty3-gypsy elements. This they thought was possibly an indication of the importance of Ty1-copia retrotransposons in jute genome evolution. Their study also led to the identification of transcriptionally active retrotransposons in jute leaves. Sarkar et al.’s (2017) draft genome analysis of Corchorus olitorius cv. JRO-524 (Navin) found the most dominant classes of transposable elements (TEs) to be gypsy (34.3%) and copia (5.7%). A high number of LTR retrotransposons in jute was also reported by Begum et al (2013). Different transposable elements present in the available genome sequences of the two jute cultivars (C. capsularis and C. olitorius) is shown in Table 16.3.

16.6

Database

Genetic and genomic studies in jute are being developed over the ages. Random and dominant molecular markers, like RAPD, IISR and SRAP, have been used as early-age markers to estimate genetic diversities in jute germplasm (Hossain

254

H. Khan et al.

Table 16.3 Summary analysis of different types of transposable elements in C. capularis and C. olitorius genomes C. capularis

C. olitorius

Number

Length (bp)

Percentage of repeats

Total repeat fraction

482,666

182,562,750

100

Class I: retroelement

196,879

122,711,710

LTR retrotransposon

106,862

Ty1/copia

18,445

Percentage of genome

Number

Length (Mb)

% of repeats

% of genome

53.6

529,791

2.34E + 08

100

59.3

67.22

36.0

229,833

1.61E + 08

68.95

40.9

92,539,611

50.69

27.2

124,639

1.25E + 08

53.66

31.8

12,970,077

7.1

3.8

16,923

14,437,327

6.18

3.7

Ty3/gypsy

46,219

54,887,128

30.06

16.1

60,428

83,170,456

35.6

21.1

Other

42,198

24,682,406

13.52

7.3

47,288

27,757,336

11.88

7.1

Non-LTR retrotransposon

55,433

22,029,792

12.07

6.5

64,001

26,188,610

11.21

6.7

LINE

43,204

20,558,985

11.26

6.0

49,646

24,136,737

10.33

6.1

SINE

12,229

1,470,807

0.81

0.4

14,355

2,051,873

0.88

0.5

Unclassified retroelement

34,584

8,142,307

4.46

2.4

41,193

9,524,396

4.08

2.4

Class II: DNA transposon

135,381

36,248,759

19.86

10.6

152,361

51,203,504

21.92

13

2108

921,776

0.5

0.3

3197

1,330,302

0.57

0.3

hAT

17,669

5,255,489

2.88

1.5

14,200

5,361,051

2.29

1.4

Mutator

10,350

3,488,794

1.91

1.0

4393

1,701,379

0.73

0.4

Tc1/mariner

5245

1,026,065

0.56

0.3

6406

1,221,085

0.52

0.3

PIF/harbinger

2707

635,360

0.35

0.2

1727

392,559

0.17

0.1

Other

92,057

23,895,210

13.09

7.0

116,032

39,976,043

17.11

10.1

Helitron

1957

869,172

0.48

0.3

2708

1,127,689

0.48

0.3

Tandem repeats

128,852

27,563,620

15.1

8.1

126,158

30,913,572

13.23

7.9

Unknown

13,770

4,659,831

2.55

1.4

18,222

5,682,247

2.43

1.4

TIR CMC [DTC]

et al 2002; Hosain et al. 2003; Roy et al. 2006; Rana et al. 2013). In the absence of jute genome sequence, the development of more reliable codominant molecular markers, especially the nuclear microsatellite or SSR markers, was heavily dependent on SSR-enriched library sequencing approaches (Mir et al. 2008; Das et al. 2012). Subsequently, with the publication of genome sequences (Islam et al. 2017; Sarkar et al. 2017) and several transcriptomic sequences (Chakraborty et al. 2015; Zhang et al. 2015b) in jute, it was possible to develop a large number of

diverse molecular markers, including the ESTSSRs (Zhang et al. 2015a; Saha et al. 2017; Satya et al. 2017). All the molecular markers reported are either inaccessible from the subscriptionbased publications or the primer sequences are presented in limited numbers for only those which were used for validation. For example, as per Mir et al. (2009), out of the 1648 SSR markers designed, primers are available only for 100 SSRs. This limits the jute researchers to use only a limited set of primers resulting in analysing a narrow window of genetic information.

16

Jute Genomic Resources and Database

The genomes and transcriptomes of jute although facilitated the identification of large numbers of diverse molecular markers, accessibility of simple PCR-based molecular markers with nonredundant primers binding sites in jute still poses a challenge. To facilitate easy accessibility of PCR-based diverse molecular markers with no restrictions by the jute researchers and students irrespective of their skills in genomics and bioinformatics, a web-based jute marker database was developed (Saha et al. 2017). The database named ‘JuteMarkerdb’ is hosted by the ICAR-Central Research Institute for Jute and Allied Fibres, India. All the molecular markers and other information related to jute genomic resources, keeping in view the embargo restrictions of published data from the journals, were integrated into different menus. The database was constructed in the form of a relational database management system (RDBMS) using the Microsoft Structured Query Language (SQL) server. Programming languages, such as Microsoft ASP.NET and C sharp, were used to bring the hierarchical organization of classes and

255

subclasses into the database. A total of 2079 EST-SSR markers, which were mined from the bast fibre transcriptome of white jute (Chakraborty et al. 2015) was integrated into the database. These markers can be accessed by the users through browsing mode from the ‘eSSR database’ menu. Users are provided with hyperlink options to check the unigenes sequences (from the NCBI database) from which the corresponding markers were derived. The markers can be downloaded either all together or in batches using different query modes, such as those based on repeat motifs (di, tri, tetra etc.) or by annotations of unigenes containing the SSR motifs (like transcription factors). The database was created with dynamic interactions for the users to choose to download the primer sequences along with their length, melting temperature, expected product size and related unigene NCBI accession numbers in excel files (Fig. 16.3). The above database is being updated (JuteMarkerdb v.2.0) to integrate other diverse PCR-based non-redundant molecular markers (Saha et al. unpublished). These diverse markers were mined and compared in silico from jute

Fig. 16.3 Screenshot of the published JuteMarkerdb portal interface

256

H. Khan et al.

Table 16.4 Details of molecular markers accessible through the updated JuteMarkerdb S. no.

Marker type

1

Candidate polymorphic SSRs (cpSSRs)

6085

Genome sequence of cv. JRO-524, O-4 (dark jute), and CVL-1 (white jute)

2

Expressed SSRs (eSSRs)

2079

Bast transcriptome unigenes of white jute cv. JRC-212

3

Long non-coding RNA sequence-derived SSRs (lncRNA-SSRs)

101

Bast transcriptome unigenes of white jute cv. JRC-212

4

Intron-linked polymorphic (ILP) markers

6037

Bast transcriptome unigenes of white jute cv. JRC-212

5

Miniature inverted-repeat transposable element (MITE) insertion polymorphism (MIP) markers 300

(ii) O-4

326

Candidate polymorphic InDels

genomes and transcriptomes and include intronlinked polymorphic (ILP) markers, candidate polymorphic genomic SSR markers, long noncoding RNA-derived SSR markers, miniature inverted-repeat transposable element (MITE) polymorphic markers, candidate InDel markers, etc. Integration of all these diverse markers in a single comprehensive database is likely to enable users to employ them in the characterization of jute germplasm, genetic and population-level diversity estimations, marker-aided selections and breeding of fibre quality traits, QTL mapping with densely linked markers and varietal identifications (Table 16.4).

16.7

Origin

Genome sequence of cv. JRO-524, O-4 (dark jute), and CVL-1 (white jute)

(i) JRO-524 (iii) CVL-1 9

No. of markers

408 1036

Genome sequence of cv. JRO-524 and O-4 (dark jute)

germplasms not achievable by conventional breeding as the two jute cultivars (C. capsularis and C. olitorius) are usually cross incompatible. Recent years have seen remarkable progress in the generation of jute genomic and physical resources and the development of databases. This is expected to break the shackles and accelerate the pace of economically important gene function discovery. With the enrichment of a large number of diverse molecular markers and several genetic linkage maps, an understanding of the nature, type, the scale of genetic variability for the desired characters in jute cultivars and germplasm collections, and interrelationship among them will enable us for the future development of jute with desired attributes.

Conclusion and Future Perspectives References

Advances in varietal improvement of jute, a principally self-pollinated crop, has suffered from the lack of adequate genetic diversity within the available genetic stock. The vast pool of proteincoding genes, their regulatory sequences and the non-coding genetic elements waiting to be identified would be important resources for biotechnological procedures in generating unique

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Jute Genomic Resources and Database

cultivated jute determined by means of SSR markers and AFLP profiling. Crop Sci 44:678–685 Begum R, Zakrzewski F, Menzel G, Weber B, Alam SS, Schmidt T (2013) Comparative molecular cytogenetic analyses of a major tandemly repeated DNA family and retrotransposon sequences in cultivated jute Corchorus species (Malvaceae). Ann Bot 112 (1):123–134 Chakraborty A, Sarkar D, Satya P, Karmakar PG, Singh NK (2015) Pathways associated with lignin biosynthesis in lignomaniac jute fibres. Mol Genet Genom 290:1523–1542 Chen T, Qi J-M, Tao A-F, Xu J-T, Chen F-C, Wang G-M, Li X-Z, Chen M-X, Ruan Q-C (2011) A karyological study of two cultivated species and their wild species and three wild relatives of corchorus. J Plant Genet Resourc 12(4):619–624 Chen Y, Zhang L, Qi J, Chen H, Tao A, Xu J, Lin L, Fan P, Flachowsky H (2014) Genetic linkage map construction for white jute (Corchorus capsularis L.) using SRAP ISSR and RAPD markers. Plant Breed 133:777–781 Choudhary SB, Saha D, Sharma HK, Kumar CI, A, (2019) Transcriptional analysis of a delayed-flowering mutant under short-day conditions reveal genes related to photoperiodic response in tossa jute (Corchorus olitorius L.). Ind Crops Prod 132:476–486 Das M, Banerjee S, Dhariwal R, Vyas S, Mir RR, Topdar N, Kundu K, Khurana JP, Tyagi AK, Sarkar D, Sinha MK, Balyan HS, Gupta PK (2012) Development of SSR markers and construction of a linkage map in jute. J Genet 91:21–31 Haque S, Ashraf N, Begum S, Sarkar RH, Khan H (2008) Construction of genetic map of jute (Corchorus olitorius L.) based on RAPD markers. Plant Tissue Cult Biotechnol 18:165–172 Hossain MB, Haque S, Khan H (2002) DNA fingerprinting of jute germplasm by RAPD. J Biochem Mol Biol 35(4):414–419 Hossain MB, Awal A, Rahman MA, Haque S, Khan H (2003) Distinction between cold sensitive and cold tolerant jute by DNA polymorphism. J Biochem Mol Biol 36(5):427–432 Islam MS, Saito JA, Emdad EM, Ahmed B, Islam MM, Halim A, Hossen QM, Hossain MZ, Ahmed R, Hossain MS, Kabir SM, Khan MS, Khan MM, Hasan R, Aktar N, Honi U, Islam R, Rashid MM, Wan X, Hou S, Haque T, Azam MS, Moosa MM, Elias SM, Hasan AM, Mahmood N, Shafiuddin M, Shahid S, Shommu NS, Jahan S, Roy S, Chowdhury A, Akhand AI, Nisho GM, Uddin KS, Rabeya T, Hoque SM, Snigdha AR, Mortoza S, Matin SA, Islam MK, Lashkar MZ, Zaman M, Yuryev A, Uddin MK, Rahman MS, Haque MS, Alam MM, Khan H, Alam M (2017) Comparative genomics of two jute species and insight into fibre biogenesis. Nat Plants 3:16223 Joshi A et al (2014) Chromosome-specific physical localisation of expressed sequence tag loci in Corchorus olitorius L. Plant Biol 16:1133–1139

257 Kundu A, Chakraborty A, Mandal NA, Das D, Karmakar PG, Singh NK, Sarkar D (2015) A restrictionsite-associated DNA (RAD) linkage map, comparative genomics and identification of QTL for histological fibre content coincident with those for retted bast fibre yield and its major components in jute (Corchorus olitorius L., Malvaceae s. l.). Mol Breed 35:1–17 Mir RR, Rustgi S, Sharma S, Singh R, Goyal A, Kumar J, Gaur A, Tyagi AK, Khan H, Sinha MK, Balyan HS, Gupta PK (2008) A preliminary genetic analysis of fibre traits and the use of new genomic SSRs for genetic diversity in jute. Euphytica 161:413–427 Mir RR, Banerjee S, Das M, Gupta V, Tyagi AK, Sinha MK, Balyan HS, Gupta PK (2009) Development and characterization of large-scale simple sequence repeats in jute. Crop Sci 49:1687–1694. https://doi.org/10.2135/cropsci2008.10.0599 Morakinyo JA, Baderinwa AO (1997) Karyotype analysis and meiotic chromosome behaviour in Corchorus olitorius, C. tridens and C. aestuans. Nigerian J Genet 12:20–28 Niyitanga S, Xu Y, Ibrahim AK, Zhang L, Fang S, Qi J, Zhang L (2019) Evaluation of newly developed SSR markers and identification of quantitative trait loci for bast fibre cellulose in white jute (Corchorus capsularis). Plant Breed 138:897–906. https://doi.org/10. 1111/pbr.12747 Rana MK, Arora K, Singh S, Singh AK (2013) Multilocus DNA fingerprinting and genetic diversity in jute (Corchorus spp.) based on sequence-related amplified polymorphism. J Plant Biochem Biotechnol 22:1–8. https://doi.org/10.1007/s13562-012-0104-7 Roy A, Bandyopadhyay A, Mahapatra AK, Ghosh SK, Singh NK, Bansal KC, Koundal KR, Mohapatra T (2006) Evaluation of genetic diversity in jute (Corchorus species) using STMS, ISSR and RAPD markers. Plant Breed 125:292–297 Saha D, Rana RS, Chakraborty S, Datta S, Anil Kumar A, Chakraborty AK, Karmakar PG (2017) Development of a set of SSR markers for genetic polymorphism detection and interspecific hybrid jute breeding. Crop J 5:416–429 Samad MA, Kabir G, Haque MM, Islam AS (1993) Karyomorphological studies in the cultivated jute (Corchorus) species and their F1 hybrid. Dhaka Univ J Biol Sci 2:15–20 Sarkar D, Mahato AK, Satya P, Kundu A, Singh S, Jayaswal PK, Singh A, Bahadur K, Pattnaik S, Singh N, Chakraborty A, Mandal NAD, D, (2017) The draft genome of Corchorus olitorius cv. JRO-524 (Navin). Genom Data 12:151–154. https://doi.org/10. 1016/j.gdata.2017.05.007 Satya P, Chakraborty A, Jana S, Majumdar S, Karan M, Sarkar D, Datta S, Mitra J, Kar CS, Karmakar PG, Singh NK (2017) Identification of genic SSRs in jute (Corchorus capsularis, Malvaceae) and development of markers for phenylpropanoid biosynthesis genes and regulatory genes. Plant Breed 136:784–797 Satya P, Chakraborty A, Sarkar D, Karan M, Das D, Mandal NA, Saha D, Datta S, Ray S, Kar CS,

258 Karmakar PG, Mitra J, Singh NK (2018) Transcriptome profiling uncovers b-galactosidases of diverse domain classes influencing hypocotyl development in jute (Corchorus capsularis L.). Phytochemistry 156:20–32. https://doi.org/10.1016/j.phytochem.2018. 08.017 Satya P, Paswan PK, Ghosh S, Majumdar S, Ali N (2016) Confamiliar transferability of simple sequence repeat (SSR) markers from cotton (Gossypium hirsutum L.) and jute (Corchorus olitorius L.) to twenty two Malvaceous species. 3 Biotech 6:1–7. https://doi.org/ 10.1007/s13205-016-0392-z Sinha M, Kar C, Ramasubramanian T et al (2011) Corchorus. In: Wild crop relatives: genomic and breeding resources. Springer, pp 29–61 Sultana N, Khan H, Ashraf N, Sharkar MTK (2006) Construction of an intraspecific linkage map of jute. Asian J Plant Sci 5(5):758–762 Sun X, Liu D, Zhang X, Li W, Liu H, Hong W, Zheng H et al (2013) SLAF-seq: an efficient method of largescale de novo SNP discovery and genotyping using high-throughput sequencing. PLoS One 8(3):e58700. https://doi.org/10.1371/journal.pone.0058700 Tao A, Huang L, Wu G, Afshar RK, Qi J, Xu J, Fang P, Lin L, Zhang L, Lin P (2017) High-density genetic map construction and QTLs identification for plant height in white jute (Corchorus capsularis L.) using specific locus amplified fragment (SLAF) sequencing. BMC Genom 18:1–12

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Genetic and Genomics of Bast Fiber Development in Jute

17

Sylvain Niyitanga, Hu Li, Lilan Zhang, Gaoyang Zhang, and Liwu Zhang

Abstract

Jute fiber or phloem fibers are sclerenchymatous and extraxylary cells with a notable size and a cell wall comprising crystalline cellulose. They are stripped from the stem of two cultivated jute plant species (2n = 14), Corchorus capsularis and Corchorus olitorius belonging to the genus Corchorus, which contains more than 100 species growing in the warm areas of the world. Bast fibers from jute have great features including corrosion resistance, fast water dispersion, good moisture absorption, and are used for making decorative pieces, packaging materials, clothes, and other diverse products. The recent development of next-generation sequencing and high-throughput analysis has allowed the exploration of genetics and genomics of fiber development in jute, which is among the key knowledge for breeders to improve bast fiber of jute through breeding. Thus, this chapter will focus on the present knowledge about genetics and genomics of bast fiber development and mainly discusses cytogenetics,

S. Niyitanga
H. Li
L. Zhang
L. Zhang (&) College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China e-mail: [email protected] G. Zhang College of Life Sciences, Shangrao Normal University, Shangrao 334001, China

application of molecular markers, bast-related transcriptomes, gene expressions, and gene function analysis. We then conclude with a perspective on the future of genetics and genomic studies aimed at improving jute bast fiber.

17.1

Introduction

Jute fiber, which is also known as bast or phloem fiber, is sclerenchymatous and extraxylary cells with a notable size, and the cells contain crystalline cellulose. They are obtained from the stem of plants belonging to the genus Corchorus, which contains more than 100 species grown in the warm areas of the world. To date, only two species, C. capsularis and C. olitorius, are commercially exploited for bast fiber production in this genus. The development of bast fiber from jute plants or other plants notably hemp, kenaf, flax, and ramie generally undergoes different stages such as fiber initiation, fiber elongation, and secondary cell wall thickening (Mokshina et al. 2018). The fiber from jute possesses great advantages, including corrosion resistance, fast water dispersion, good moisture absorption, and is primarily used in the cottage industries for making decorations, packaging materials, clothes, and other diverse products (Biswas et al. 2015; Bhandari et al. 2018). As a versatile economic crop, each tissue of a jute plant owns a specific usage. For instance, the stem of the plant

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_17

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can be used to produce paper and composite materials, protect the environment, and others (Bhandari et al. 2018). The leaves of jute are used as green vegetables, as well as animal feed, and are also used to make herbal medicine and skincare products (Islam 2013). The seeds can be utilized for extracting oil and various other products (Siriamornpun et al. 2006). Recently, advances in next-generation sequencing and high-throughput sequencing tools have enabled the assembly of wholegenome sequences of jute (Islam et al. 2017; Sarkar et al. 2017; Zhang et al. 2021) and promoted the investigation of jute genetics and molecular biology. Various molecular markers comprising SNPs, SSRs, and others have been developed through high-throughput sequencing (Tao et al. 2015; Satya et al. 2017; Yang et al. 2018, 2019). Also, various transcriptome and gene expression investigations in jute have been published (Zhang et al. 2015d; Yang et al. 2017). Jute plants yield phloem fibers with a xylan-type cell wall. Molecular investigations with NGS are very suitable to elucidate the variations in the development of this kind of fiber. This chapter attempts to offer an inclusive review of the present advances of jute genetics and genomics research aimed at understanding the bast fiber development. We will mainly discuss cytogenetics, application of molecular markers, bastrelated transcriptomes, and gene expressions, followed by conclusion and future prospects.

17.2

Cytogenetics in Jute

Jute is an economically important crop. Jute karyotypes have enabled our basic insight into their chromosomal biology (Maity and Datta 2009; Begum et al. 2013). Maity and Datta initially studied karyotype in nine Corchorus species, including C. fascicularis, C. tridens, C. pseudocapsularis, C. pseudoolitorius, C. capsularis, C. olitorius, C. aestuans, C. trilocularis, and C. urticaefolius, and found a diploid number (2n = 14) of chromosomes in all species except C. fascicularis which revealed 2n = 28. An increasing number of karyotype studies have also

confirmed a diploid number (2n = 14) in the Corchorus species, including C. olitorius, C. capsularis, and others (Chen and Qi 2011; Olawuyi et al. 2014; Saha et al. 2017). Information about the total amount of DNA contained in the haploid genome of an organism (or genome size) is essential for genome sequencing, evolutionary analyses, and comparative genomics. The genome sizes of the two cultivated species, C. olitorius and C. capsularis, were initially estimated to be 1350 and 1100 Mbp, respectively (Samad et al. 1992). The 2C nuclear DNA was estimated on the chemical investigation of DNA extracted from seeds. Further investigations based on flow cytometry analysis (Sarkar et al. 2011; Akashi et al. 2012) have shown that genome sizes for the two Corchorus species are about 300% lower than that estimated in the initial report. Recent genome sequencing of C. capsularis variety CVL-1, C. olitorius variety O-4, and C. olitorius cv. JRO524 found the genome sizes to be  404 Mb,  448 Mb, and 377.3 Mb, respectively (Islam et al. 2017; Sarkar et al. 2017). This shows genomic variation among these species.

17.3

Application of Molecular Markers in Jute

DNA or molecular markers are “benchmarks” throughout the genome that can be chosen owing to their proximity to a quantitative trait locus (QTL) of importance. The selection of molecular markers associated with the QTL upsurges the effectiveness of breeding, and typically cuts costs as well as subjective phenotypic selection using the least number of backcrossing. DNA markers denote a site of visible discrepancy throughout the genomic DNA and are generally categorized into PCR-based molecular markers (SSRs, RAPD, ISSR, SRAP, etc.), restriction enzymebased molecular markers (e.g., AFLP and RFLP), SNP-based (single nucleotide polymorphism) markers, and InDel-based (insertion/deletion) markers. The application of DNA markers in jute started 20 years ago with the use of RAPD and AFLP markers (Hossain

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et al. 2003). Nevertheless, many studies were confined to DNA fingerprinting (Rana et al. 2013; Zhang et al. 2015b), as well as genetic diversity investigations among Corchorus species and common varieties (Basu et al. 2004; Roy et al. 2006; Haque et al. 2007; Mir et al. 2009). However, most of these DNA markers were developed before the publication of reference genomes and were based on DNA libraries. Simple sequence repeat markers are the most versatile, informative, and easily detectable molecular markers (Saeed et al. 2016). Therefore, consideration was moved to the application of simple SSR markers, and their polymorphism in jute was found to be relatively higher than the polymorphism observed in others crops (Mir et al. 2009). These markers have been utilized to investigate genetic discrepancy, develop genetic linkage maps, and detect QTLs associated with important agronomic traits which are valuable resources for marker-aided selection (MAS). Besides nuclear markers, organelle markers such as chloroplast SSRs (cpSSRs) were also reported (Kundu et al. 2013). Even though the traditional approach for SSR marker development is costly and time-consuming (Lopez et al. 2015), a good number of SSRs have been developed in jute (Mir et al. 2009). At first, MAS (marker-aided selection) could not be applied in jute owing to the low-resolution density maps (Sultana et al. 2006; Haque et al. 2008). Nevertheless, a high-density genetic map of C. olitorius has been constructed recently by RAD (restriction site-associated DNA) and microsatellites markers (Topdar et al. 2013; Kundu et al. 2015). Moreover, genetic differentiation and population structure-based RAD-SNP investigation of about 221 fiber-type dark jute lines have been reported (Sarkar et al. 2019). This is important for the genomic investigations in jute plants and will aid in the marker-assisted selection of the best jute cultivars. Advances in next-generation and high-throughput tools for sequencing have revolutionized the identification of molecular markers. Zhang et al. (2017) have identified InDel markers associated with fiber cellulose. Moreover, genic SSRs associated with phenylpropanoid biosynthesis were identified in

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jute bast fiber transcriptomes (Satya et al. 2017). A good number of genic SSRs were developed and used for studying genetic diversity (Zhang et al. 2015c; Saha et al. 2017). Recently, SLAF markers have been developed and used to detect QTLs for jute plant heights (Tao et al. 2017) and bast fiber cellulose content (Niyitanga et al. 2019). SNP markers were developed and used to detect QTL for salt tolerance in jute (Yang et al. 2019). As a result, many fiber traits (yield components and quality) associated with marker loci and fiber development have been identified (Topdar et al. 2013; Tao et al. 2017; Niyitanga et al. 2019).

17.4

Transcriptomes of Bast Fiber and Expression Analysis of Gene Involved in Bast Fiber Formation

Roles of jute transcriptome have been investigated by using various approaches, including BLAST, comparative genomics, KEGG (pathway enrichment by Kyoto Encyclopedia of Genes and Genomes), and GO (Gene Ontology) investigations, and some prominent bast-related results were found. In this section, we condense some of these major findings. C. capsularis cultivar JRC-212 (wild type) and its dlpf (deficient-lignified phloem fiber) mutant were used (Chakraborty et al. 2015) to reveal bast-associated genes and pathways implicated in lignin biosynthesis via a comparative transcriptome analysis using an Illumina Hiseq200 platform. 29,463 unigenes for the mutant and 34,163 for the wild type were identified. Different gene isoforms, including 43 for the monolignol pathway and 37 for shikimatearomatic amino acids, were also identified by the authors. Of the total unigenes, 77–79% were marked and allotted to GO, COG, and mapped to about 189 KEGG pathways. Additionally, the white jute cultivar (Huangma 179) was used in bast transcriptome assembly and detection of key genes implicated in cellulose synthesis in white jute (Zhang et al. 2015d). Bast transcriptome assembly using HiSeq 200 (Illumina platform)

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and de novo assembly detected about 48,914 unigenes with an N50 length of 1703 base pairs and a mean length of 903 base pairs (Genbank accession: SRP060467, BioSamples SRS980707). The CDS (coding sequences) of predicted proteins and unigenes are presented in Fig. 17.1. About 57.1% were functionally annotated in more than one database (Nr, GO, KOG, KO, Swiss-Prot, or PFAM). About 14216 unigenes were assigned to 268 KEGG pathways, while 1190 were assigned to GO (Fig. 17.2), and 21856 unigenes to the KOG database. Unigenes representing bast fiber displayed great sequence semblances with poplar (Populus trichocarpa), castor (Ricinus communis), and grape (Vitis vinifera), which is in agreement with that reported for JRC-212 cultivar and its dlpf mutant (Chakraborty et al. 2015) and for expressed sequence tags (ESTs) from unigene sequences obtained by depicting a normalized cDNA library created from leaf samples (Tao et al. 2015). KEGG pathway analysis has revealed metabolic processes related to bast fiber development. They primarily comprise amino acid and carbohydrate transport as well as metabolic processes (Chakraborty et al. 2015; Zhang et al. 2015d).

Comparative investigation of the bast transcriptome between dlpf and JRC-212 (wild-type) revealed candidate genes and their isoforms, notably sucrose synthase (CcSuSy1-CcSuSy5), cellulose synthase (CcCesA1, CcCesA2), bgalactosidase (CcBGAL1-CcBGAL8), cellulose synthase-like (CcCsl), and CcFLA (fasciclin-like arabinogalactan genes), implicated in producing components necessary for secondary cell wall development (Chakraborty et al. 2015). Expression studies with qRT-PCR revealed that CcFLA6 may integrate with cellulose synthase (CesA) for the settling of S-layers in the xylan secondary cell wall of jute fibers. CcFLA15 is implicated in setting the developmental change of bast fiber, from its elongation up to the formation of the secondary cell wall, while the CcCesA7 is specific to the secondary cell wall in bast tissues. Cellulose is one of the core constituents of the cell wall in plants and comprises glucose residues (Fig. 17.3). Through the analysis of KEGG-pathway mapping, Zhang et al. have identified major genes implicated in cellulose biosyntheses such as SuSy (sucrose synthase), CSL (cellulose synthase-like), UGPase (UDP-glucose pyrophosphorylase), CesA (cellulose synthase), COBRA, and KOR (KORRIGAN)

Fig. 17.1 An overview of assembled bast transcriptomes of white jute cv. Hauang 179, with respect to the length distributions of CDS a illustrates predicted protein of CDS by Basic Local Alignment Search Tool (BLAST), b explains predicted protein of CDS using ESTScan. CDS were obtained from the assembled unigene sequences by BLASTX (with a threshold E-value equal to 10−5) queries

against the Swiss-Protdatabase, Nr, non-redundant proteins, and KEGG database (Kanehisa et al. 2012). Also, the ESTScan program (Iseli et al. 1999) was used to predict coding sequence for unigenes without performing BLASTx search against both protein databases (Nr, Swiss-Prot) and then translated into peptide sequences (Zhang et al.2015d)

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Fig. 17.2 Gene ontology classification of assembled unigenes by using Blast2GO platform (Conesa et al. 2005), demonstrating the phloem transcripts generated from white jute cultivar Huangma 179 (Zhang et al. 2015d)

Fig. 17.3 A structural representation of main genes involved in cellulose biosynthesis in plants. PM (plasm membrane)-related SUSY (sucrose synthase) directly conveys uridine diphosphate glucose (UDPG) substrate to CESA (cellulose synthase), a rosette compound that helps in glucan chain development while reprocessing

UDP back to sucrose synthase. The cellulose synthase compounds move in the plasma membrane with the help of microtubules. Finally, KOR (korrigan) cellulase monitors or edits the self-assembly of glucan chains into microfibrils (Joshi et al. 2004)

(Zhang et al. 2015d). Analysis of differential expression of all these cellulose biosynthetic genes with RT-qPCR revealed that many of the cellulose biosynthesis genes are comparatively greater in bast tissues than in all other tissues

studied. However, expression levels of UGPase, CesA, and SuSy were greater than that of other genes (Fig. 17.4), signifying their vital role in fiber development.

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Fig. 17.4 Differential expression patterns of main genes implicated in cellulose biosynthesis in jute plants. The Xaxis FPKM (blue and red color together) demonstrates gene expression in mixed tissues (root, stem bast, leaf,

and stem stick). The X-axis FPKM (blue color: stem bast) demonstrates gene expression in bast tissues (Zhang et al. 2020)

Moreover, bast fiber transcriptomics enabled the discovery of various bast-associated TF genes and transcription controlling gene families, mainly zinc fingers, FAR1, MADS, WRKY, MYBrelated, and NAC, which are recognized in regulating lignin biosynthesis and secondary cell wall development. MADS and C3H-type zinc fingers are the most common types of transcription factors expressed in bast tissues. About 236 unigenes were found to have great sequence semblance with WRKY genes, which are known to play a significant function in jute bast fiber development (Samanta et al. 2015). Moreover, recent genome sequencing of white jute variety CVL-1 and dark jute variety O4 identified 30,096 and 37,031 genes for white and dark jute, respectively, by merging transcriptome assemblies, and homology-centered methods (Islam et al. 2017). Additionally, expression analysis of RNA extracted from bast fiber cells has shown a high expression level of major structural and regulatory transcription factor genes involved in fiber formation notably APL (Altered Phloem Development), WOX4 (Wuschel related HomeoboX 4), TDIF, and HAT22. The same authors also detected the expansion of genes implicated in lignin biosynthesis with regard to flax (L. usitatissimum), viz., CCR (cinnamoyl-

CoA reductase), COMT (caffeic acid Omethyltransferase), 4CL (4-coumarate CoA ligase), and CCoAOMT (Caffeoyl CoA Omethyltransferase). They have also highlighted the role of CesA in the biosynthesis of secondary wall. This transcriptome designates an essential supplement to the investigation of fiber crops as it relates to two jute species with distinct features, for example, dark jute bast comprises less cellulose and more lignin in comparison to white jute.

17.5

Functional Analysis of Gene Involved in Bast Fiber Formation

The sequencing of the genome has opened new doors to enable the precision breeding of jute crops (Islam et al. 2017; Zhang et al. 2020). However, genome sequencing does not necessarily reveal the function of the genes related to fiber formation. So, it is very important to reveal the molecular mechanism of fiber development and identify the function of genes related to fiber formation. At present, studies on functional analysis of genes related to fiber development in jute mainly include. Samanta et al successfully

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identified the genes involved in fiber formation in two genotypes of jute using the suppression subtractive hybridization method. Among these genes, the WRKY transcription factor was documented to be the most important transcript which was possible regulation related to cell wall biosynthesis, expansion, and lignification. Overexpression of the metabolism category genes of secondary metabolism in normal plants indicated their critical role in fiber formation (Samanta et al. 2015). Zhang et al. revealed that the genes related to cellulose biosynthesis, sucrose synthase, UDP-glucose pyrophosphorylase, and cellulose synthases were higher expressed in the bast fibers (Zhang et al. 2015d). Zhang et al.’s research suggests that overexpression of the CcUGPase gene in jute could increase plant height and cellulose content compared with control plants, although the lignin content remained unchanged. The results indicate that the jute UGPase gene participates in cellulose biosynthesis and fiber formation (Zhang et al. 2013). At the same time, the function of the gene was also analyzed in Arabidopsis thaliana. The results also showed that the jute UGPase gene participates in cellulose biosynthesis in plants (Zhang et al. 2015a). Guerriero et al. using the genome sequencing method revealed the molecular mechanisms during bast fiber differentiation in C. olitorius and C. capsularis, the TFs MYB83, WOX4 (WUSCHEL RELATED HOMEOBOX 4), APL (ALTERED PHLOEM DEVELOPMENT), and the homeobox gene HAT22 were of high expression in the fibers, and the role of CesA7 and CesA4 gene was confirmed in secondary cell wall biosynthesis (Islam et al. 2017; Guerriero et al. 2017). MicroRNAs (miRNAs), 18–22 nucleotides long small regulatory RNAs could play a significant role in different cellular functions in plants. Some putative miRNAs were identified and their functions were extensively analyzed in jute by Milad et al., five genes which were somehow involved in lignin biosynthesis and secondary cell wall formation process, NAC domain containing protein, WRKY DNA binding protein, 3dehydroquinate synthase, S-adenosyl-L-Metdependent methyl transferase and vascular-

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related NAC-domain were found to be involved in the lignin biosynthesis, phenylpropanoid pathways, and secondary wall formation. We believe that with deeply research in jute crop, more and more genes related to fiber formation will be verified experimentally.

17.6

Conclusions and Perspectives

For jute and other crops particularly those with a narrow genetic diversity, genetic improvement will depend on innovative exploitation of genetic resources and efficient use of both molecular and traditional technologies. Inclusive information is desired from various research to comprehend genetics and molecular mechanisms underlying fiber development in jute. With the development of high-throughput and next-generation studies on jute, various genetic and genomic resources related to bast fiber formation such as genetic markers, linkage maps, QTLs related to the desired agronomic features including fiber yield as well as quality component features, karyotype, bast-related transcriptomes, and genes linked to fiber formation and others were generated. However, further improvement of these resources is needed, particularly in the application of molecular markers and linkage mapping. Cellulose and lignin pathways, as well as their related genes, have been elucidated. Future studies will target cellulose and lignin biosynthetic pathways for bast fiber improvement as they are key players not only for jute fiber development but for fiber quality as well. Jute fiber has many economic applications and the production of various products should soon become a primary emphasis. In this regard jute cultivars with low bast lignin content are necessary. Lignin has a strong ability to resist enzymatic degradation, hence it is a serious hindrance in processing fibers for making various products. During the paper-producing process using jute fiber, toxic chemicals that are harmful to the environment have to be used to break down lignin. Therefore, plenty of lignin in jute fiber limits its industrial applications. An undesirable relationship between jute fiber lignin and its fineness has been

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observed (Meshram and Palit 2013). However, lowering its content to a certain degree by targeting the enzymes responsible for lignin synthesis remains a challenge as it could negatively impact plant phenotype (Boerjan et al. 2003). To date, only a few lignin biosynthetic pathwayassociated genes have been investigated (Chakraborty et al. 2015) and described in jute (Zhang et al. 2013, 2014; Zhang et al. 2015a). Also, the silencing of C3H and F5H genes using the RNAi approach has proven to be an efficient technique to lower the lignin content in jute (Shafrin et al. 2015). However, further studies are needed for a better understanding of the lignin biosynthetic pathway in jute.

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S. Niyitanga et al. in jute (Corchorus capsularis L.). BMC Genom 16 (1):1062. https://doi.org/10.1186/s12864-015-2256-z Zhang L, Gao Z, Wan X, et al (2017) Development of novel small InDel markers in jute (Corchorus spp.). Tropical Plant Biol 10(4):169–176. https://doi.org/10. 1007/s12042-017-9193-8 Zhang L, Wan X, Xu Y, Niyitanga S, Qi J, Zhang L (2020) De novo assembly of transcriptome and genome-wide identification reveal GA3 stressresponsive WRKY transcription factors involved in fiber formation in jute (Corchorus capsularis). BMC Plant Biol 20(1):403–417. https://doi.org/10.1186/ s12870-020-02617-8 Zhang L, Ma X, Zhang X, Xu Y, Ibrahim AK, Yao J, Huang H, Chen S, Liao Z, Zhang Q, Niyitanga S, Yu J, Liu Y, Xu X, Wang J, Tao A, Xu J, Chen S, Yang X, He Q, Lin L, Fang P, Zhang L, Ming R, Qi J, Zhang L (2021) Reference genomes of the two cultivated jute species. Plant Biotechnol J. https:// doi.org/10.1111/pbi.13652

Genetics and Genomics of Biotic Stress Resistance of Jute

18

Shaheena Amin and Tahmina Islam

Abstract

Plants frequently remain unprotected against viruses, fungi, bacteria, nematodes, insects, protists and various other biotic stress factors. These biotic stresses significantly reduce a plant’s productivity, which implies that ‘flight or fight’ mechanism is not an option; they are compelled to adapt to their changing interactions for survival. Consequently, this required them to evolve an intricate mechanism that would render them combating the biotic (and abiotic) stressors. Researchers have put in enormous efforts to understand how plants carry out these defense mechanisms when subjected to such stresses. This knowledge provides background information for diverse aspects of plant defense patterns ranging from anatomy, physiology, biochemistry, genetics encompassing the various mechanisms of plant molecular patterns and also their evolution. As a result, scientists have come up with different procedures for developing crops’ immunity to attack the various pathogenic entities. These include the acquiring resistance

S. Amin Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka 1000, Bangladesh T. Islam (&) Department of Botany, University of Dhaka, Dhaka 1000, Bangladesh e-mail: [email protected]

in commercial or farmer popular crops through the insertion of directed genes for the expression of PR proteins, antifungal peptides, biosynthesis of phytoalexins, and so on. In this chapter, we provide an extensive outline of various defense techniques implemented by jute (Corchorus sp.), against biotic stresses. Jute is one of the major fiber crops after cotton extensively cultivated in the South Asian region; however, it contains only two farmers’ popular species C. olitorius (known as dark jute) and C. capsularis (known as white jute). Therefore, the crop faces frequent attacks by biotic stressors and gains the attention for genetic modification for betterment. Despite being the high recalcitrance in tissue culture, remarkable advancements have been made in the study of jute. Recent achievements and perspectives on the molecular response of jute to biotic stress, including genetic expression, where genomic sequencing, targeted functional analysis, and development of resistant jute cultivars via the implementation of advanced tools of biotechnology are discussed in this chapter.

18.1

Introduction

When plants are damaged by various live entities such as bacteria, virus, fungi, parasites, salutary and detrimental insects, weeds, cultured or endemic plants, then the phenomenon is known

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_18

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as biotic stress (Flynn 2003). Climatic conditions and resistance against certain species pressures are instrumental for any organism to withstand biotic stresses inflicted on the concerned organism. The destruction caused by different animate and inanimate factors might appear to be in close proximity to one another, but it can be difficult to diagnose accurately even after close observation especially in regulating biotic stress in an investigational circumstance in regards to abiotic stress (Flynn 2003). Biotic stress factors are responsible for extensive damage to cash crops and hence they are a major concern to researchers. Important economic decisions are taken based on the interplay between the yield of plants and biotic stresses. The effects of biological trauma on the yield of crops affect community mobility, plant–microbe coexistence and ecosystem nutrient cycling (Peterson and Higley 2001). Biotic stress also affects the health and natural habitat environment of horticultural plants. It also dramatically changes the host recipient. Biotic stress has caused enormous adversity for humanity, for example, the blight of potato, where a fungus was responsible for severe and prolonged hunger in England, Ireland and Belgium in the 1840s (Flexas et al. 2012). Another instance is the arrival of grape phylloxera from North America in the nineteenth century, which set off the Great French Wine Blight (Flexas et al. 2012). Other biotic stresses of historical significance are fungal disease (coffee rust) caused by Hemileia vastatrix Berk in Brazil, Cochliobolus heterostrophus induced leaf blight of maize in the United States and Cochliobolus miyabeanus induced fungal brown spot disease in rice that cause the Bengal famine of 1943 (Hussain 2015). Insect damage and malady in crop plants present a crucial tribulation for food and agricultural safety. Farmers opted to use artificial chemical pesticides and toxicants to eradicate pathogens at an increasing rate from the last half of the twentieth century. This practice was more extensively followed in the comprehensive agricultural sector prevalent in the advanced countries. But this practice of using chemicals to keep pests in check is proving to be unstable.

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Pesticides have a finite duration of utility due to initiation of resistance to targets and are notably recognized in various instances to present detrimental effects on biodiversity, the well-being of farmers and consumers (Robert 2013). Currently, new breeds of pathogens and insect biotypes additionally threaten crop yield (Sanghera 2011). Pathogens cause close to 15% loss in worldwide food production which poses vital challenges to the reproduction of resistant crops. The presence of genetic polymorphisms in phytopathogenic agents and insect populations, which are thought to be further affected/modified by the climatic factors, engender the modification of invasive strains or biotypes (Onaga and Wydra 2016) which may cause new outcomes in host-pathogen interactions. Thus, outbreaks of disease or insects are expected to cause losses in the production of food or exacerbate by spreading to such regions (Siddra 2012). This presents a cardinal implication for the governance choices accessible that may be more reliable using a combination of options. However, in resource limiting areas, for example, in small-scale agricultural methods in bucolic Africa and Southeast Asia, scientists are forced to reap the benefits of disease and pathogen resistance alleles that exist among the wild varieties and the domesticated cultivars. Hence, to explore the methodologies of resistance controlled by these resistant alleles, the cultivated non-pareil germs which bolster the development of most rustic indigent livelihoods must be able to absorb them for improvement.

18.1.1 Mechanisms of plant’s Disease Resistance The resistance mechanism of a plant toward numerous biotic stressors, such as pathogens and insects, involves various genetic, morphological, biochemical and molecular processes in an ordered and organized way (Fig. 18.1) (Howe and Jander 2008). The mechanism of defense has been divided into different categories, such as innate and systemic response, outlined in Fig. 18.1 (Onaga and Wydra 2016). These mechanisms can be activated before or induced

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after any particular type of attack. Plants have evolved these preventive measures to stay afloat in adverse and changing environments (Nürnberger and Kemmerling 2018). Unlike adaptive immune system, which is unique to organisms, the innate immune responses have some common features including distinct receptors for microbial molecules, production of antimicrobial peptides and conserved mitogen-activated protein (MAP) kinase cascades, which are a result of convergent evolution and exhibit ingrained constraints of the natural immune system (Ausubel 2005).

Plant innate defense mechanism could be manifested in both specific (color/pathogen-race specific) and non-specific (natural resistance) ways, probably depending on the inducible responses and constitutive barriers which include various biochemical compounds produced before or during the infection (Jones and Dangl 2006; Király et al. 2007). Structural and morphological barriers (cell wall, epidermis, trichomes, thrones etc.), biochemicals (metabolites, phenolics, saponins, steroids, terpenoids, glucosinolates and nitrogen compounds), protein, and enzymes together form constitutive defense mechanisms

Fig. 18.1 Overview of plant’s resistance mechanisms against biotic stress response. Plant PRRs or R-genes perceive PAMPS and effectors, which activate signal cascades inside the cell. This includes the activation of multiple signaling pathways involving reactive oxygen species (ROS), defense hormones (such as salicylic acid,

jasmonic acid and ethylene), mitogen-activated protein kinases (MAPK) and transcription factor families, e.g., AP2/ERF, WRKY, MYB, bZIP etc. These signals activate either innate response or acquired immune response or both. The figure was modified and adopted from Onaga et al. (Onaga and Wydra 2016)

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to provide plants strength, rigidity and tolerance against biotic stresses. Inducible defense mechanisms of plants such as generation of lethal compounds, enhancement of various degrading enzymes (chitinases and glucanases) and deliberate cell suicide are not used by the plants frequently due to the requirement of high energy and essential micronutrients. Although innate immunity is considered to be more efficient and is the commonly used form of plant resistance mechanism, both defenses rely mostly on the plant’s ability to differ among self and non-self molecules. Pathogen-associated molecular patterns (PAMPS) or herbal-associated molecular patterns (HAMP) are used by plant pattern recognition receptor (PRR) to identify conserved molecules of pathogens or insects. Recognition of PAMPS subsequently exerts pattern-triggered immunity (PTI) and exemplifies the plant-pathogen interaction, which is known as the first layer of plant defense to restrict pathogen entry. Inversely, the ability of a pathogen to avoid PTI enhances the survival potential. Recognition of PTI signaling components is often targeted as virulence effector protein that diminishes plant defense and increased virulence that has revived the studies on effector-induced ‘gene-for-gene’ resistance in the plant. Notably, effectors target the host proteins to evade PTI. These proteins help the plant to activate the second layer of effector-triggered immunity (ETI) by sensing the association of cytoplasmic immune resistance proteins with the effector (Zhang and Zhou 2010). This is one of the most successful ways to combat PTI evading pathogens (Nürnberger and Kemmerling 2018). Despite this, in order to provide long-term protection against wide-ranging biotic pathogens, systemic acquired resistance (SAR) acts as the important resistant mechanism where defense proteins accumulate at the site of infection as well as in uninfected tissues systemically. Induced systemic resistance (ISR) is another form of inducible resistance similar to SAR, which is initiated by plant growth-promoting rhizobacteria (PGPR), mainly belonging to Pseudomonas species. For being sessile an efficient signaling technique is obvious at the plant-

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pathogen interface to activate SAR and ISR, which give a quick, effective and feasible means of protective measures in high disease pressure. Moreover, virus and fungal-derived nucleic acids are targeting and neutralizing through the RNA interference mechanism of plants (Onaga and Wydra 2016). This background information of natural plant defense responses, including quantitative and qualitative mechanisms along with their associated patterns, provides knowledge to the scientists and researchers to develop and improve genetically modified plant varieties having the characteristics of combating biotic stresses using a variety of modern techniques.

18.1.2 Current Methodologies for the Improvement of Biotic Stress-Tolerant Plants and Jute Through the advancement of biotechnology, the selection of new varieties by conventional breeding methods becomes more efficient with a high success rate. Marker-assisted breeding (MAB) is one such tool that has made a noteworthy impact in improving the effectiveness of conventional breeding. However, a large gap prevails in the improvement of traits monitored by many small effects, epistatic QTLs that exhibit notable genotype X environment (GXE) interactions. Therefore, emerging genetic and genomic tools are constantly devoted to developing efficient breeding strategies using an indirect selection of such traits. As a result, more than 55 plant species genome has been sequenced (Guo et al. 2016) to date and many are being in the process. Genome sequences avail the information that is used in developing genome-wide markers covering the whole genome. These genome-wide markers played an important role in developing various special populations including nearisogenic lines (NILs), recombinant inbred lines (RILs), introgression lines (ILs) or chromosome segment substitution lines (CSSLs). Different variety including meticulous QTL mapping

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Genetics and Genomics of Biotic Stress Resistance of Jute

populations could be developed using heterogeneous inbred family (HIFs) and multi-parent advanced generation inter-cross (MAGIC) technologies (McCough and Doerge 1995; Arends et al. 2010). Molecular marker information is used in GWA analysis to predict the result of a set of crosses. Quantitative measurement of desirable traits is a particularly important aspect for the plant breeder not only for examining the breeding efficiency but also for identifying the most suitable genes for the desired phenotypes. Among so many molecular techniques, next-generation sequencing (NGS) and real-time PCR are the most reliable and efficient techniques for identifying the genetic makeup of the desired phenotype. In order to unveil the genetic basis of intricate agronomic traits, NGS techniques have been used as the main backbone of direct sequencing of the whole genome, and its comparison with the reference genome has become more feasible in understanding complex traits. Therefore, in model species Arabidopsis, as well as in rice, maize, soybean, grape and poplar, resequencing has been performed to reveal the whole-genome sequence variation that subsequently unveils single nucleotide polymorphism (SNPs) (Cao et al. 2011; Abe et al. 2012; Yano et al. 2016; Contreras-Soto et al. 2017; Varshney et al. 2017). Whole-genome sequencing along with transcriptomics, metabolomics, proteomics, epigenomics and biochemical methods will impart significant knowledge of plant biology of agronomic traits and consequently develop improved crop varieties. The newly developed genotyping by sequencing (GBS) technique allowed us to detect single nucleotide polymorphism, illustrate QTLs and identify candidate stress tolerance genes without genome sequence information and minimized ascertainment biases (Onaga 2014; Dossa et al. 2016). In order to identify markers linked to genes, a new method combining both the highthroughput sequencing method and bulk segregant analysis (BSA) has been developed. Recently, this method is further modified to target-enriched X-QTL (TEX-QTL) mapping (Guo et al. 2016) which combines a large F2

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population, 10–20% bulk size and deeply sequenced markers. To enhance BSA analysis efficacy, TEXQTL mapping exploits the targetenriched SNP markers deep sequencing. Most QTLs can be detected within two generations in this method. Regarding the genotyping pooledsegregant sequencing, BSA is likely to strengthen the credibility and lessen the time required to detect causative superior alleles and map all QTL underlying the trait of interest that can be eventually employed for the improvement of crops through targeted genetic engineering. Other functional genomic tools such as comprising insertional mutagenesis, RNA interference (RNAi), targeting induced local lesions in genomes (TILLING), ecotype TILLING (EcoTILLING) techniques are being used to identify the desirable alleles. These strategies are the socalled reverse genetics approach by which plant scientists are now able to predict the functions and phenotypes associated with a given gene. Through NGS technology a large volume of sequences is now available that considerably increased the number of TILLING and EcoTILLING studies from which many crops could be benefited including maize, rice, barley, pea and melon (for review, see Perez-de-Castro et al. 2012). In order to modify a specific target sequence leading to the desired trait, several improved recombinant DNA techniques such as oligonucleotide-directed mutagenesis (oDM), transcription activator-like effector nuclease (TALEN), zinc finger nuclease (ZFN) and clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) systems are now widely used. However, the performance of germplasm that originated through these techniques and the functional use of it are yet to be fully demonstrated in developing countries under environmental conditions (Zinsou et al. 2005; Wydra et al. 2007; Banito et al. 2008). Using a combination of different approaches, a new rice cultivar (known as ‘Green Super Rice’) with multiple abiotic and biotic stresses tolerance potential has been developed (Wing et al. 2018). This integrated process of breeding

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by the selection of genome can be used to design novel plants comprising most of the functional loci determining the key desirable commercial traits. These modern bio-techniques such as QTL mapping, plant breeding, genetic transformation, NGS, RNAi-mediated gene transformation, CRISPR/Cas9 system etc. are applied for jute improvement (Majumder et al. 2020). The following sections will illustrate the genetics and genomics approaches to improve jute plants.

18.2

Biotic Stress Factors of Jute

Production of jute has encountered problems from biotic and abiotic stress factors, instability of nutrients due to the high cost of artificial fertilizers, global warming and climate change. These stressors affect both the yield and quality of jute fiber. Among the factors, climate change, variation in cultivation pattern and economic growth have changed the relative abundance of pest population in many species (Satpathy et al. 2016). Table 18.1 summarizes the biotic stress factors of jute reported to date. Among various pathogens, the major constraints are the yellow mite (Polyphagotersonamous latus Banks), soilborne Macrophomina phaseolina (tassi) Goid phugus causing stem and root rot, and semilooper of jute (Anomis sabulifera Guen) (Chakraborty 2014). One of the most common infestations is done by Lepidopteran insects in jute. Apart from all the Lepidopteran that causes damage to fiber yield and quality, some of the most potent insects of jute are semilooper (Anomis sabulifera Guenee), indigo caterpillar (Spodoptera exigua Hubner) and hairy caterpillar (Spilarctia obliqua Walker), infecting at different stages of plant growth causing 20–48.5% fiber losses (Rahman and Khan 2012; Selvaraj et al. 2015). Fungi is another important biotic stress factor causing severe yield loss in jute production. Among them, the most devastating one is the Macrophomina phaseolina that causes a 30% yield reduction for both jute genotypes (C. olitorius and C. capsularis) (Islam et al. 2012).

18.3

Genetics and Genomics of Biotic Stress Resistant in Jute

As an emergent necessity, so many successful attempts have been made to achieve biotic stress resistance in plants through breeding and genetic engineering. However, the development of jute cultivars with improved agronomic traits remains challenging due to its strong sexual incompatibility, the narrow genetic base of cultivated varieties, early flowering etc. Nevertheless, researchers are continuing to apply newer techniques to unveil the genetic basis in natural defense response and generate a successful genetic transformation of these traits to develop improved crop varieties. One such initiative was done by Majumder et al., where a transgenic jute plant was developed through molecular breeding that provided resistance against insects, fungi and herbicides (Majumder et al. 2018a, b). The study of jute genetic and genomic approaches regarding biotic stress resistance can be categorized as fungal resistance, insect and mite resistance, and weed resistance. Table 18.2 summarizes the different approaches and respective outcomes to develop jute crops with improved agronomic traits.

18.3.1 Fungus-Resistant (FR) Jute Among the biotic stressors, the fungal stresses such as Black band (Botryodiplodia theobromae), Anthracnose (Colletotrichum corchorum; C. gloeosporioides), stem rot and charcoal rot (Macrophomina phaseolina) are the most common in jute. Fungal infection is one of the most important economic factors in jute that causes severe damage to its fiber quality and great loss in production. Unavailability of fungal-resistant jute cultivars or other successful biocontrol system, the management of fungal infection primarily depends on the use of fungicide. But this management is not an effective method as it is not only expensive and labor-intensive but also a time-consuming process recovering the

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Table 18.1 Summary of biotic stress factors of jute (Chakraborty 2014; Majumder et al. 2020) Common name

Scientific name

Pathophysiological symptoms

Black band

Botrydiplodia theobromae

Black colored band on the stem

Pod’s sooty mold

Cercospora corchori, Corynespora cassicola, Alternaria spp.

Black and powdery coating adhering to plants

Anthracnose

Colletotrichum corchorum; C. gloeosporoides

Irregular-shaped spots on leaves, curled leaves, leaf drop

Tip blight

Curvularia subulata

Brown, yellow, and straw color needle at the tip, branch dibank

Stem rot and charcoal rot

Macrophomina phaseolina

Chlorosis, wilting, plant death

Powdery mildew

Oidium sp.

Light, gray or white powdery

Stem gall

Physoderma corchori

Turner like swelling

Hooghly wilt

Ralstonia (=Pseudomonas) solanacearum

Affected plants whiter, droops, hang down

Semilooper

Anomis sabulifera

Leaves are eaten by larvae, defoliation

Hairy caterpillar

Spilarctia obliqua

Young caterpillars cause leaf skeletonization, defoliation

Indigo caterpillar

Spodoptera exigua

Caterpillars feed on leaves

Bollworm

Helicoverpa armigera

Caterpillars feed on leaves

Weevil of stem

Apion corchori

Pierces stern at nodal region resulting in knot formation

Gray weevil

Myllocerus discolor

Adults feed rapaciously on leaves and roots

Yellow mite

Polyphagotarsonemus latus

Uptake sap cause leaf curling, twisted apical, browning, stunted plants

Root-knot causing nematode

Meloidogyne incognita

Cause knotted roots, stunted growth, wilting

Girdler of stem

Nupserha bicolor

Girdling of the stem by female cause dying and drying up of above plant parts, larvae feed on pith tissues

Leaf miner

Trachys dasi

Larvae feed on leaves, stunt the growth of leaf

Red mite

Oligonychus coffeae

Uptake sap from leaves

Mealy bug

Phenacoccus solenopsis

Uptake sap from leaves, stem, and petiole

Termite

Odontotermes obesus

Feed on plant’s stem by attacking at the base

Jute thrips

Ayyari chaetophora

Leaves browning, curling, and stunted growth

Fleabeetle

Monolepta signata

Adults nourish on leaves creating short holes

Hooder hopper

Otinotus elongates

Uptake sap from soft stem causing wilting of plants

Field cricket

Brachytrupes portentosus

Adult feed and destroyed seedlings

Cutworm

Agrotis ipsilon

Caterpillars destroyed seedlings to feed

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Table 18.2 The overview of the genetic and genomic approaches and the respective outcome regarding diseaseresistant traits in jute Objectives

Genetic and genomic approaches

Respective outcomes

Comparative study between two natural species C. olitorius and C. capsularis

Whole-genome shotgun sequencing

Identification of jute-specific genes that express defense-related proteins

The draft genome (377.3 Mbp) of C. olitorius cv. JRO-524 (Navin)

Developed through a cross between African (cv. Sudan Green) and indigenous (cv. JPO-632) jute types

1765 disease resistance-like and defense-related protein identified

Identification of unigene-derived SSR markers from C. capsularis cv. JRC-212

Using a non-redundant 2079 flanking primer sets, a total of 4509 SSR loci from 34,163 unigenes sequences of C. capsularis were identified

Among 907,139 encoded transcription factors, 70 disease resistance proteins and 65 other proteins including tetratricopeptide repeats (TPR), pentatricopeptide repeats (PPR), leucine-rich repeats (LRR) and WD40 proteins were identified

Development of a variety of high yielding and better fiber quality, JRC 9057 (Ishani)

JRC 698 X CIJ 121 following pedigree method

Exhibits higher tolerance to stem rot (most damaging diseases) and jute semilooper than both the parent varieties

177 RIL lines of jute (C. capsularis) were generated by crossing resistant CIM 036 and susceptible JRC 412

1. Sanger sequencing and 454 Newbler (Roche Diagnostics) or SeqManTM NGenTM to analyze the RIL transcriptomes 2. Illumina Hiseq instrument to identify novel mature miRNA and integrated PARE (parallel analysis of RNA ends) data to reveal their cleavage sites

1. Genes including cell wall biosynthesis, reactive oxygen species, hormone signaling, hypersensitive response and programmed cell death (PCD) pathways were identified 2. The trans-acting siRNAs (tasiRNAs)-mediated defense response was also evaluated in these RIL populations

Identification and validation of host-pathogen interacting novel miRNAs

In silico analysis of illumine HiSeq

Abundant expression of miR-845b and miR-166 superfamily members

A comparative analysis between C. trilocularis (wild-type resistant sp.) and C. olitorius (susceptible)

Real-time expression analysis

Highly expressed genes involved in SAR pathway and cell fortification

To elucidate the disease-resistant gene loci linkage map in F2 population was developed

Involvement of RAPD and SSRassisted breeding

Assignment of nine markers in two linkage groups covering 628.4 cM with an average distance of 28 cM

Genome-wide identification and expression profiling of ethyleneresponsive element under stress conditions in Corchorus olitorius L

RNA-Seq data and qRT-PCR were performed to analyze the expression of CoAP2/ERF

Downregulation of CoERF-01, CoERF-39, CoDREB-18, CoDREB-23, CoDREB-13 genes but upregulation of CoDREB-01, CoDREB_28 and CoDREB-30 genes were observed. CoDREB-12 and CoDREB-34 found downregulation to upward

Chitinase gene from rice (OsChi11) and the bar gene has been incorporated in C. capsularis JRC321

Agrobacterium transformationmediated genetic transformation and analyzed up to T2 generation

Complete resistance against M. phaseolina was found

(continued)

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Table 18.2 (continued) Objectives

Genetic and genomic approaches

Respective outcomes

The breeding of the new jute variety Tainung selection 1

Plant breeding

Resistant to damping-off and Colletotrichum corchori and fairly resistant to drought

‘Funong No.1’ is a new variety of vegetable jute

Released ‘Taizi No.4’ jute after 60 Co c-ray treatment in a dosage of 219 Gy through several generations’ selection

Has stronger resistance to spots on jute anthracnose, blight and stem spot disease

Bt jute plants

A fused Cry1AB/AC gene under rice actin1 promoter in the C. capsularis genome

The transgenic plants were resistant to lepidopteran insects, similar to control plants regarding agronomic parameters and fiber quality

An F2 population of resistant O7/95 and sensitive O-72 was used to increase selection efficiency for mite tolerance

Construction of genetic linkage map using MAPMAKER/EXP ver 3.0

Mite resistance linked with an SSR marker (M-66) with a threshold LOD (logarithm of the odds) of 3

Screening of mite-resistant and sensitive crossed F2 population

Construction of genetic linkage map using 88 polymorphic SSR primers

Two SSR markers J-170 and HK-89 have been mapped at 34.1 cM and 35.4 cM, respectively with a selection efficiency of 100% in combination

The development of herbicidetolerant jute through molecular breeding (via a transgenic approach)

The bar gene encoding phosphinothricin acetyltransferase enzymes used as a selectable marker, cloned from Streptomyces hygroscopicus using biolistic transformation system

Bar gene provides resistance to herbicidal ingredients, including glufosinate-ammonium, phosphinothricin, and glufosinate. Bar is highly effective against commercially available herbicides such as basta, buster, finale and liberty

pathogenic fungal infection in infected plants. Therefore, to combat the fungal stress the development of a fungus stress-resistant jute variety is an urgent but arduous process that has been carried out for a long time by conventional breeding with the confined outcome.

18.3.1.1 Colletotrichum Corchori Colletotrichum is a pathogenic fungal species (Fig. 18.2a) that causes anthracnose disease and production loss in jute (Fig. 18.2b–c) (Hasan et al. 2015). The primary symptom of the disease is chlorotic regions with black-brown sunken necrotic pits on the surfaces of stems (Fig. 18.2 c). With the disease progression, plants become defoliated, dieback and blight (Fig. 18.2a–c). The disease was first observed on ‘Jap-Red’—a capsularis introduction from Formosa (Taiwan)

at Dhaka (Bangladesh) in 1945. From Dhaka the disease spread to other parts of Bangladesh. Later it entered India through Assam. The survival of this pathogen depends on some environmental conditions such as successive rain, high humidity and temperature around 35 °C. In India, especially in Assam, North Bengal, Bihar and Uttar Pradesh, this disease is predominantly found in Capsularis sp. (Sarkar and Gawande 2016). Besides, this disease has also spread to China. In a study in China, seven different strains of Colletotrichum fungi were found to be causal agents of anthracnose disease that were obtained from the infected stem of jute plants in different regions, including Zhejiang, Fujian, Guangxi and Henan plantations (Niu et al. 2016). A combinatorial study of the multi-locus sequence of different genes (such as ACT, TUB2, CAL, GS,

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Fig. 18.2 Biotic stress factors of jute and its effects. a– c Colletotrichum corchori and its effects. d–f Botryodiplodia theobromae and its effects. g–j Macrophomina

phaseolina and its effects (https://plantlet.org/differentdisease-of-jute/; Islam et al. 2012)

GAPDH and ITS) and morphological assessment showed different strains are widespread in different regions. Among them, C. fructicola, C. siamense and C. corchorum-capsularis sp. nov. were found prevalent in southeastern China. A new species C. corchorum-capsularis as well as other species previously not associated with jute anthracnose which include C. fructicola and C. siamense were also observed (Niu et al. 2016). Significant efforts have been made to attain resistance against this deadly fungus. Tainung selection 1 is resistant to damping-off and Colletotrichum corchori and fairly resistant to drought which was late maturing but has rapid seedling growth. Its fiber strength is similar to that of Tainung 1 but it is higher-yielding (Chi et al. 1970). ‘Funong No.1’ is a new variety of vegetable jute, released by ‘Taizi No.4’ jute after 60Co c-ray treatment in a dosage of 219 Gy through several generations selection which has stronger resistance to spots on jute anthracnose, blight and stem spot (Lin et al. 2010).

obtained. The disease first appears as a small blackish-brown lesion that gradually enlarges and encircles the stem resulting in the withering of epical and side branches (Fig. 18.2d–f). Stems infected at the lower portion often break at that point. The affected plants lose leaves and turn brown to black and remain standing as dry sticks. On rubbing the stem surface, unlike stem rot profuse black shooty mass of spores adhere to the fingers. Seeds infected with the pathogen beget infected plants with seedling blight disease (Sarkar and Gawande 2016).

18.3.1.2 Botryodiplodia Theobromae The black band a caused by Botryodiplodia theobromae (Fig. 18.2d–e) which was a minor disease but spread gradually. The pathogen affects both the species of jute and causes serious damage to the older crop from July onwards, from which neither fiber nor seeds can be

18.3.1.3 Macrophomina Phaseolina One of the most subversive fungal pathogen Macrophomina phaseolina (Tassi) Goid is a soil and seed-borne pathogen (Fig. 18.2g–i) in the ascomycete family Botryosphaeriaceae. It causes diseases not only in jute but also in more than 500 crop and non-crop species, including soybean, common bean, corn, sorghum, cowpea, peanut and cotton. In spite of being worldwide distribution, the fungus effect is more prevalent in subtropical and tropical countries with semiarid climates that lead to great economic loss regarding jute production in Bangladesh and the Indian subcontinent. This fungus causes a wide range of diseases such as seedling blight, root and stem rot, wilt, and pre- to post-emergent damping off. The affected plants ultimately

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become decreased in stem height, girth, root and head weight, or may die. This phytopathogen possesses an abundance of secreted oxidases, peroxidases, and hydrolytic enzymes for degrading cell wall polysaccharides and lignocelluloses to penetrate the wide range of host tissues and species (Islam et al. 2012). The progress of stem rot diseases involved the initial evasion hyphae in the cortical tissue of jute plants, followed by sclerotia formation (Fig. 18.2g–j). Among various processes of chemical, biological and biotechnological approaches, the infection caused by Macrophomina phaseolina could be prevented. The transgenic plant production is the most effective one to decrease the economic damage (Ghosh et al. 2018). Nevertheless, advanced researches should explore to apprehend its pathogenic factors and an effective management system to avail successive protection against this pathogen in wide geographic distribution. Continuous effort to combat this devastating necrotrophic fungal pathogen has disclosed the genetic insight of resistant mechanism in natural species as well as in genetically modified or inbred jute plants some of which is prospected in the section. Despite the broad spectrum and severe virulence effect of Macrophomina, a wild jute species, Corchorus trilocularis, comparatively shorter in height, bushy in appearance, and shortlived, is resistant to M. phaseolina in some studies from Bangladesh (Mahmood et al. 2010; Sharmin et al. 2012). Using differential display method transcripts showing different banding patterns were identified, cloned and sequenced for the development of markers for molecular breeding and development of resistance gene analogs for jute. The result disclosed the homologous transcripts with the disease resistance gene of other plants and is differentially expressed under M. phaseolina stress (Mahmood et al. 2010). In another study, a comparative analysis was performed between C. trilocularis (wild type resistant sp.) and C. olitorius var O-72 (farmer popular sp.) under both stressed and control conditions. Two xyloglucan endotransglycosylase/ hydrolase (XTH) genes were identified from

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each of the two species defined as CoXTH1 (from C. olitorius) and CtXTH1 (from C. trilocularis) which show differential expression patterns upon fungal attack. The expression of CoXTH1and CtXTH1 in response to Macrophomina infection was observed by quantitative real-time PCR. The expression of CtXTH1 was found to be upregulated within the infectious period whereas the CoXTH1 was found to be downregulated in resistant and susceptible species respectively which confirms the association of XTH gene regarding the host-microbe interaction of M. phaseolina and jute (Sharmin et al. 2012). In a recent study, quantitative real-time PCR was performed to compare the expression of the genes involved in systemic acquired resistant (SAR) pathway and cell fortification between fungal infected and healthy plants of the farmer popular O-4 variety of Corchorus olitorius and Corchorus trilocularis. The genes were found to be highly expressed in C. trilocularis, after Macrophomina application. On the other hand, the sensitive species C. olitorius showed aberrant expression of these genes. Again, lignification, a key defense adaptation, was observed upon M. phaseolina infection in the resistant species (Amin 2018). Plants’ growth, development and stress responses are regulated by so many cis-acting transcription factors, among which the APETALA2/ethylene-responsive elementbinding factor (AP2/ERF) superfamily is one of the largest and conserved transcription factors (TF). Bangladesh Jute Research Institute (BJRI) identified and characterized a total of 119 CoAP2/ERF genes in the whole genome under stress conditions in dark jute (Corchorus olitorius L.). Among them, 17 AP2, 97 ERF, 4 RAV and 1 soloist gene family were divided into 10 groups by phylogenetic analysis and were randomly distributed across the linkage groups and possess ancient duplication events that contain three tandem and eight segmental duplications. Although a majority of the CoAP2/ERF genes followed a similar pattern, however, some genes were differentially expressed during tissue’s development as well as in biotic (Macrophomina phaseolina) and abiotic (waterlogging, salinity,

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drought) stresses. The expression was characterized using RNA-Seq data and qRT-PCR analysis. During waterlogging stress CoERF-21, CoERF-34 and CoERF-39 genes were found upregulated whereas under salinity and drought stress conditions an increased expression was observed in CoDREB-11, CoDREB-14 and CoRAV-01 genes. In case of fungal stress, downregulation trends in CoERF-01, CoERF-39, CoDREB-18, CoDREB-23 and CoDREB-13 genes and upregulation in CoDREB-01, CoDREB-28 and CoDREB-30 genes were observed in qPCR data within 2 h interval in the infectious period from 0 to 24 h. However, CoDREB-12 and CoDREB-34 genes were found to be upregulated in 0–8 h, which is followed by downregulation in the rest of the infectious time period. The study resolved the AP2/ERF gene evolution and diversity in dark jute C. olitorius that provide valuable information for the development and validation of functional stressresistant jute variety (Kabir et al. 2021). Besides, to explore the resistant mechanisms against Macrophomina different molecular and biotechnological techniques have been imposed, which not only unveil the depth knowledge of the genetic basis of desired traits but also helped to generate improved jute varieties. However, in many cases, the resistance was not certainly achieved in genetically modified plants and was confined to a limited number of fungi. For a long time, insertion of desired genes that produce antifungal compounds, including toxic proteins, enzymes and metabolites in transgenic plants, remains successful but their level of resistance and range need to be extended through the successive adaptation of new genes with the more qualified and combinatorial application. Unlike other plants such as sorghum, castor and cowpea, the characteristic QTL mapping related to M. phaseolina resistance (Srinivasa Reddy et al. 2007; Muchero et al. 2011; Tomar et al. 2017; Mahmoud et al. 2018; da Silva et al. 2019) disclosed potential candidate genes that facilitated breeding and most importantly the development of some genetically modified jute plants (Sharmin et al. 2012; Biswas et al. 2014; Dey et al. 2016).

S. Amin and T. Islam

One such example is the development of a linkage map in the F2 segregated population of selected parents (from an interspecies cross between resistant (CIM 036) and susceptible (JRC 412) species of C. capsularis) which elucidate the disease-resistant gene loci for Macrophomina phaseolina resistance trait (Mir et al. 2011). The linkage was mapped between resistant trait and molecular markers that include randomly amplified polymorphic DNA (RAPD) and simple sequence repeat (SSR). Among 18 SCAR (sequence characterized amplified region) markers generated from five polymorphic RAPD markers (OPP-4, OPS-3, OPS-13, OPG-10 and OPU-10), 11 primer combinations gave the polymorphic results between M. phaseolinaresistant and -susceptible accessions of Corchorus capsularis. Sixty-seven F2 segregated plants were used as the mapping population where nine markers were assigned to two linkage groups (LGs) of length 257.2 and 35.4 cM. This linkage map covered a total length of 628.4 cM with an average distance of 28 cM between adjacent. The grouping through molecular markers showed clear correspondence to the morphological characteristics of Macrophomina resistant and susceptible accession of C. capsularis ultimately ascertaining the successful breeding programs achieving desired jute varieties (Mir et al. 2011). As most of the fungal cell wall is built with chitin (about 60%) including Macrophomina phaseolina, it is the major target of researchers to use for pathogen destruction. For this purpose chitinase enzymes that break chitin and cause major damage to fungi are mostly targeted by the researchers to be inserted into plants through genetic engineering. For the development of fungal-resistant (FR) jute variety, Sharmin et al. took the first initiative of the introduction of chitinase enzyme in jute from rice (OsChi11) (Bartnicki-Garcia 1968; Sharmin et al. 2012). Using Agrobacterium-mediated genetic transformation the chitinase (chi11) gene in combination with the bar gene has been incorporated in C. capsularis JRC-321 to provide fungal and herbicide tolerance at a time and the outcomes were analyzed up to T2 generation. These genetically modified jute plants were found to be efficient in

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eradicating M. phaseolina infections and maintaining fiber integrity through the production of high levels of effective chitinase enzyme. In the experiment, a comparative analysis of M. phaseolina infection was carried out using detached leaf bioassay, where a very small lesion area was observed in transgenic leaves compared to the large lesions on non-transgenic control leaves. A whole-plant bioassay was also performed under greenhouse conditions. The data represented the complete resistance against M. phaseolina and is very minimal stem damage in FR jute as compared to non-transgenic control plants (Sharmin et al. 2012). For the assessment of defense response in jute, an interspecies cross was performed between the resistant accession CIM 036 and the susceptible variety JRC 412 of C. capsularis which produced 177 RIL (recombinant inbred lines) population (Biswas et al. 2014). The disease status of these RIL population was observed by the inoculation of M. phaseolina hyphal suspension. Among 177 RIL population 69 lines were found resistant and 108 lines were susceptible that showed 1–100% disease incidence. The transcriptome, as well as miRNA analysis, was performed in noninoculated, inoculated healthy and inoculated infected to elucidate the resistant mechanism (Biswas et al. 2014). Sanger sequencing coupled with pyrosequencing produced more than 7.2 million reads of 1.5 million nucleotides cDNA sequences in the C. capsularis. Among the approximate 93,018 contigs from each of the healthy and infected transcriptome of RIL population 48,501 contigs were identified in the Macrophomina-infected RIL population. From the GO annotation distribution, 158 genes were identified to be involved against biotic and abiotic factors and 22% of which were involved against biotic stressors and abundantly found in stem rot tissues. These genes include cell wall biosynthesis, reactive oxygen species (ROS), salicylic acid (SA), ethylene, jasmonic acid (JA), abscisic acid (ABA), hormone signaling, hypersensitive response (HR) and programmed cell death (PCD) pathways.

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In addition, microRNA-mediated defense response was also evaluated in the RIL population which revealed the trans-acting siRNAs (tasiRNAs) like phasi RNA (phased siRNA) and three 22-nt miRNA families (miR154, miR210 and miR211) as negative regulators of these target transcripts. 22-nt highly expressed miRNAs were found to target the SA/JA/ABA pathway through the WIN1 motif of HopW1-1 interacting proteins, TIRl motif and P-loop in NBS-LLR defense, myb transcription factors and protein kinases involved in SA pathway. These miRNAs also triggered the phasi siRNAs production that cleaved the SA/JA/ABA precursor complementary with tryptophan enriched protein kinases. Out of 177 lines 69 resistant lines were found to produce phasi RNAs, which comprises 114 PHAS loci. The highly expressed 22-nt miRNAs and their activated 21-nt phasi miRNAs excite the silencing pathway that inhibits the pathogenic effect by Macrophomina phaseolina in host plants of the RIL population (Biswas et al. 2014). In the next study, novel miRNAs were identified and validated for host-pathogen interaction targets from these RIL populations (Dey et al. 2016). Among the identified 42 new miRNAs candidates in 21 RIL population, nine novel mature microRNAs that passed the minimum free energy (MFE Kcal/mol) criteria, were characterized through target site and secondary structure prediction. These novel miRNAs were found to be highly expressed and functioned in ubiquitination and selective autophagy activity. Known microRNAs such as miR-845b and miR166 superfamily are abundantly expressed in the RIL population. Unlike the reference genome Arabidopsis thaliana, the jute miR-845b superfamily was found identical sequence except for the 18th position. The bioinformatics analysis predicted that miR-845b and miR-166 superfamily give NBS-LRR and ROS-related defense responses targeting the coding sequence of the Ploop motif in disease resistance proteins. This process subsequently stimulates the novel microRNAs that activate the autophagy pathway

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and concomitant defense cascade against M. phaseolina in jute (Dey et al. 2016).

18.3.2 Genetics of Insect-Resistant (IR) Jute In South-Asian region, Lepidopteran insect, especially the semilooper (Anomis sabulifera Guen.) and the hairy caterpillar (Spilarctia obliqua Walk), causes severe damage in jute production than any other insect pests (Table 18.1). As a result of continuous climate change, the range of jute pests has increased. Some minor pests became considerable jute pests with serious effects, such as the indigo caterpillar (Spodoptera exigua) and the cotton bollworm (Helicoverpa armigera) (Selvaraj et al. 2013). Semilooper (SL), Hairy caterpillar (HC) and indigo caterpillar (IC) insects, respectively, cause about 22– 42%, 30% and 20% production loss in jute (Ramasubramanian et al. 2009). Different factors such as infection periods, age of crops, number of insects infested influence the severity of yield loss. Hairy caterpillar (HC) attacks during rainy seasons, mainly in June to mid-September. Indigo caterpillar (IC) infect jute in March and April (Ramasubramanian et al. 2009). Farmers use chemical pesticides to combat the insect’s infestation in jute. The frequent use of chemical insecticides is injurious to the health of farmers and farm animals as well as other beneficial insects, soil microbes, and herbivores the process also burden the cost of jute cultivation. Another option for pest management strategy is the use of biopesticides. Approximately 2% of available biopesticides are derived from the entomopathogenic gram-positive soil bacterium Bacillus thuringiensis Berliner (Bt) (Bravo et al. 2011). Bt produces characteristic proteinaceous crystal protein known as d-endotoxins or Cry toxins. The toxin bind to the receptors present in the gut epithelium creates membrane pores after ingestion of Bt toxin with their food. The membrane pores cause an influx of water followed by cell swelling and lysis (Bravo et al. 2004). Bt toxin requires specific receptors, proteases and an alkaline pH to be effective (therefore only lethal

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to the insects but harmless to mammals as they have an acidic gut and lack the analogous receptors). The Bt toxin containing bio-insecticides are fruitful against the major jute pests such as SL (Das and Singh 1976), HC (Bandyopadhyay et al. 2014), and IC (Zhu et al. 2006). However, the recurrent use of bio-insecticide is not feasible in gaining broad-spectrum resistance and intensifying the need for Bt-formulated genetically modified (GM) jute crops. Bt jute plants were first developed by introducing a fused Cry1Ab/Ac gene under rice actin1 promoter in the C. capsularis genome by Agrobacterium-mediated shoot tip transformation (Majumder et al. 2018b). This transgenic jute produces an adequate amount of Cry1Ab/Ac protein throughout plants’ life span which is efficient enough to eradicate the lepidopteran insect pests. The efficacy of the Bt jute was examined against three major insect pests’ SL, HC, and IC using detached leaf bioassay (DLB) and whole plant bioassay (WPB). The result showed larvae feeding on transgenic plants, consumed lower food, limited body size, body weight and dry weight compared to the larvae feeding on non-transgenic control plants. The mortality range among transgenic feeding insects was 66–100% for SL and HC and 87.50% for IC. In addition to the resistance to Lepidopteran insects, the transgenic plants were similar to the non-transgenic control plants regarding the agronomic parameters and fiber quality (Majumder et al. 2018b).

18.3.3 Genetics of Mite Resistance Mite infection is another important economic constraint of jute production. Among the biotic stress factors yellow mite, Polyphagotarsonemus latus is a baleful pathogen and has frequent yield losses (Sanghera et al. 2011). Yellow mites suck the cell sap from the epical tender which leads to leaf curl. Mite-tolerant jute cultivar is economically significant in ameliorating jute production. Among the jute genotypes, C. olitorius O-7/95 was known to be tolerant to mite attack but is not

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farmer popular variety in terms of use and yield. Therefore, an illustration of the genetic basis behind mite tolerance is exigent. Several SSR or microsatellite markers were used to map the linkage between the mite-tolerant traits in F2 segregating population of resistant O-7/95 and susceptible O-72 variety of jute which boost the targeted selection of genes with desired phenotypes. Based on 10 SSR markers and one phenotypic marker M-11 corresponding to mite infection susceptibility, a genetic linkage map was constituted among 35 F2 population by MAPMAKER/EXP (ver 3.0) software. The result showed mite resistance linked to M-66 SSR marker at LOD threshold of 3 found efficient in marker-assisted breeding in jute for the selection of mite resistance loci (Keka et al. 1970). In another study 21 polymorphic SSR were observed in mite resistant (O-7/95) and sensitive (O-72) parent, while screened against 88 SSR primers. The genetic linkage was mapped with a recombination frequency of 0.35 using these polymorphic primers in 150 F2 populations derived from a cross between the parents. The linkage map yields five linkage groups with 50 cM maximum distance. Unlike other four groups that contain two markers, group-4 contains six markers among which SSR markers J170 and HK-89 have been mapped at 34.1 cM and 35.4 cM, respectively. These two markers in combination with HK-64 provide 100% selection efficiency. This molecular linkage map opens up good opportunities in building up the genetic linkage map dense with SSR markers linked to mite-resistant traits in jute (Ghosh et al. 2010).

uncontrolled weeds in this period can cause up to 70% fiber yield loss (Kumar et al. 2013). Lack of herbicide-resistant jute variety and weed management depend on applying nonselective, broad-spectrum herbicides. Moreover, the management practice remains troublesome as it demands skilled manpower and accuracy during spraying for the protection of susceptible jute plants. As a result, the production cost increased by more than 35% in India and 30–40% in Bangladesh (Kumar et al. 2013). For the development of herbicide-tolerant jute, molecular breeding coupled with desired genes transformation has already been practiced globally. These genes include EPSPS against glyphosate, aad-1 and aad-12 against 2, 4-D, hppd against isoxaflutole, bar and pat against glufosinate, bxn against oxynil, and als against sulfonylurea herbicide. In the jute, phosphinothricin acetyltransferase (PAT) enzymes encoding bar genes (cloned from Streptomyces hygroscopicus) were introduced using a biolistic transformation system and used as a selectable marker (Bhattacharyya et al. 2015). The bar genes expressing PAT enzymes target glufosinate-ammonium, phosphinothricin (PPT) or glufosinate components; therefore highly effective to protect them against commercially available herbicides named Basta (13.50–18.02%), Buster (20.00%), Finale (11.33%) and Liberty (10–24.50%). The herbicide-tolerant jute plants containing the bar gene were introduced by Majumder et al. and found to be tolerant against 0.25% (v/v) Basta treatment (Majumder et al. 2018a).

18.3.4 Herbicide-Tolerant (HT) Jute

18.4

Unwanted weed growth in fields is an important agro-economic factor that reduces jute production. Jute plantation favors the hot (20–40 °C temperature) and humid (70–80%) with alternate rainfall (50–80 mm) climatic conditions which also foster the weed overgrowth and ultimately causes a nutrient deficiency in the cultivated land. Weed management is critical for the first 15–45 days after sowing in jute cultivation, and

So many studies have been conducted to develop improved jute varieties that combat biotic stress factors using breeding and genetic engineering. But due to the genetic complexity and involvement of multiple traits in resistant phenotype very few successes have been achieved. As advanced technologies employed in genome research and more are evolving, the genomic approaches

Genomics of Jute Disease Resistance

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Fig. 18.3 Outline of genetic and genomic approaches regarding the biotic stress resistance of jute

witnessed successes that provide a genetic basis of multiple trait loci involved in the resistant mechanism. Figure 18.3 summarizes the genetic and genomic obtained and their reliant outcomes. The first initiative of unveiling jute genome was the comparative genome analysis of C. olitorius and C. capsularis for fiber formation, was done in Bangladesh through whole-genome shotgun (WGS) sequencing with Roche/454 platform and sequences were assembled using CABOG (Islam et al. 2017). In C. olitorius 445 Mb sequence assemblies with 3.3 Mb scaffold N50 length and 45.5 Mb longest scaffold were observed, whereas in C. capsularis the assemblies were 338 Mb with 4.1 Mb scaffold N50 length and 28.5 Mb longest scaffold. The C. olitorius assemblies covered 80% of 415 scaffolds with a minimum length of 76 kb and the

estimated genome size was 448 Mb. 80% of the C. capsularis assemblies were covered by 231 scaffolds with a minimum length of 120 kb and the respected genome size was 404 Mb. With a combination of de novo, homology and transcriptome-based analysis, the study predicted 37,031 and 30,096 protein-coding genes in C. olitorius and C. capsularis, respectively. Phylogenetic analysis confirmed the jute as a member of the Malvaceae family and the protein-coding genes were clustered into 47,186 gene families, of which 8,177 were common to all five groups and 8,816 were confined to the Malvids. Among them, only 613 and 152 genes are unique to C. olitorius and C. capsularis, respectively, and were abundant in genes involved in the oxidation–reduction process, transcription factors, transposases and defense-related proteins.

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Although the comparative genome analysis was done regarding the fiber formation in two commercially cultivated species, these whole-genome sequences and transcriptome also unravel the genetic sequence as well as protein-coding sequence of all other proteins of different phenotypic traits. Therefore, this whole-genome sequencing broadens the chances to develop the improved jute crops with desired agronomic traits including disease resistance (Islam et al. 2017). To accelerate the genomics-assisted breeding program availing desired phenotype, the genome of C. olitorious cv. JRO-524 (Navin) was sequenced and reported (Sarkar et al. 2017). This dark jute is an inbred cultivar that originated from a cross between African (cv. Sudan Green) and indigenous (cv. JRO-632). The estimated genome size was 377.3 Mbp which encodes a total of 57,087 protein-coding genes. The gene function annotation showed that 1765 protein-coding sequences comprised disease resistance-like (R like) and defense response (DR) genes in the jute genome. These sequences were found to be similiar to Theobroma cacao and Gossypium raimondiic (Sarkar et al. 2017) and categorized into 831 (47.1%) LRR-TM, 440 (25%) NBS-LRR, 352 (19.9%) LRR, and 44 (2.49%) LZ-NBS-LRR like genes. Among them, 87 (4.9%) DR genes were identified and comprises 40 chitinases, 28 glucanases and 19 thaumatin-like protein-coding genes. The disease resistance-like (R-like) and defense response (DR) genes were further categorized into five main classes as follows: (i) NBSLRR (matching with NBS-LRR, but not with LZNBS-LRR and LRR, CC-NBS-LRR, Pib, Pita, Rp 1-d8, Lr10, Mla 1 and rust resistance), (ii) LZNBSLRR (matching with LZ-NBS-LRR, but not with NBS-LRR, CC-NBSLRR, LRR, and RPM1), (iii) LRR-TM (matching with Xa21, serine/ threonine kinases, and Cf2/Cf5 resistance), (iv) LRR (matching with disease resistance, viral resistance, Yr10, LRR, but not with NBS-LRR, CC-NBSLRR, LZ-NBS-LRR) and (v) defense response genes (matching with glucanases, chitinases and thaumatin-like genes) (Sarkar et al. 2017). In a study a set of SSR markers were developed and the information was preserved in a user-friendly database as eSSR primers that aid

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the marker-assisted breeding for jute modification with enhanced quality agronomic traits. A total of 2079 sets of non-redundant flanking primers were developed from 4509 simple sequence repeat (SSR) loci collected from 34,163 unigenes sequences of C. capsularis (Saha et al. 2017). Two types of SSRs termed trinucleotide repeats and dinucleotide repeats were found abundantly with 60% and 37.6% frequency, respectively. Unlike the noncoding SSR, coding SSR was annotated from unigenes potentially functioning in different bio-molecular processes; most importantly, responses to biotic and abiotic signals. About 907 unigenes sequences were found to cover eSSR loci within the putative ORF sequence. eSSR containing jute unigenes comprised 907,139 major transcription factors (TFs) among them 70 (R-genes) were diseaseresistance proteins, and 65 were various repeat proteins which include tetratricopeptide repeats (TPR), pentatricopeptide repeats (PPR), leucinerich repeats (LRR) and WD40 proteins. Association of the eSSR with different functional domains containing unigenes can be utilized as powerful functional domain markers (FDMs) to ascertain desired polymorphic traits. A variety (JRC 9057) of high yielding and better fiber quality has been developed from the selection of the progenies of JRC 698 X CIJ 121 following pedigree method (Shil and Mitra 2018). The selection has been made for quality textile fiber coupled with high yield. For this purpose, pedigree of CIJ 121 was selected for quality and JRC 698 was used to incorporate high yield. This variety is mainly suitable for low and medium land rain-fed situation and areas where jute is cultivated, followed by transplanted aman paddy. JRC 9057 variety exhibits higher tolerance to stem rot (most damaging diseases) and jute semilooper than both the check varieties. This variety showed 13.90% and 87.76% more tolerant to stem rot than checks JRC 698 and JRC 321, respectively (Shil and Mitra 2018). The whole-genome transcriptome analysis was performed in recombinant inbred lines (RIL) generated from crossing between resistant accession CIM 036 and susceptible varieties JRC 412 through Sanger sequencing of approximately

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9000 cDNA clones followed by pyrosequencing as well as Illumine HiSeq sequencing which evaluate the respective resistant mechanisms against M. phaseolina infection (as described in Sect. 18.3.1.3) (Biswas et al. 2014). 22% of the transcripts were identified that involved in disease-resistant pathways, which include cell wall biosynthesis, reactive oxygen species (ROS), salicylic acid (SA), ethylene, jasmonic acid (JA), abscisic acid (ABA), hormone signaling, hypersensitive response (HR) and programmed cell death (PCD) pathways. From the Illumina HiSeq sequencing platform and integrated PARE (parallel analysis of RNA ends) data, the defense responsive novel miRNAs and their targeted cleaving sites were identified for each annotated gene.

18.5

Conclusion

Jute is the golden fiber, also considered as future fiber for its versatile use and potential for biodegradable packaging, an alternative of plastics equally important for its medicinal property. However, jute production is threatened by so many biotic stress factors; therefore, proper management is emergent. But the jute improvement through breeding or genetic modification faces some obstacles due to its high indolent nature, limited genomic knowledge, the utility of only two farmer popular species (C. olitorius and C. capsularis), lack of proper genetic transformation protocol and emergence of very high pest spectrum. However, rigorous efforts for gaining effective protection against the biotic and abiotic stresses have conquered these hindrances and still continue for successive outcomes. As a result, jute research testified advances in understanding the basis of genetic and genomic constitute behind the agronomic traits, most importantly the disease-resistant traits against biotic stressors. Current research not only unveils the natural resistant mechanism but also employes advanced techniques for a genetically modified crop with improved characteristics. However, to get the best outcome research should be continued to develop reliable resistant

jute crops against biotic stressors with the improved agronomic trait that can combat the climate change burden as well.

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Genomics and Genetics of Drought and Salt Tolerance in Jute

19

Jiayu Yao, Jiantang Xu, and Aminu Kurawa Ibrahim

Abstract

There are about 100 species of genus Corchorus, however, only two have been cultivated; Corchorus capsularis L. (white jute) and C. olitorius L. (Tossa jute). Salt and drought stresses are among the global catastrophes facing humanity nowadays; it is a significant threat to agriculture. Although jute can be grown on saline soil, the production is negatively affected under drought and saline conditions. Moreover, molecular mechanisms and biotechnology aspects concerning salt and drought tolerance in jute are scarce. Therefore, molecular-based breeding and exploring new genomics approaches to develop tolerant cultivars are needed. Some quantitative trait loci (QTLs) and genes associated with salt and drought tolerance were identified. In addition, the latest development of phenotypic analysis and genomic tools has opened up a new

J. Yao
J. Xu
A. K. Ibrahim (&) College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China e-mail: [email protected] J. Yao e-mail: [email protected] J. Xu e-mail: [email protected] A. K. Ibrahim Department of Agronomy, Faculty of Agriculture, Bayero University Kano. PMB 3011, Kano, Nigeria

prospect for the research on salt and drought tolerance of jute. In this chapter, we presented genetics and genomics approaches as well as their integration with classical breeding methods to improve salt and drought tolerance in jute. Some breeding challenges, mechanisms as well as molecular markers for salt and drought tolerance in jute are described. Application of bi-parental mapping to dissect salt and drought tolerance in jute, transcriptomic, and future perspective to enhance salt and drought tolerance in jute, are also highlighted.

19.1

Introduction

There are about 100 species of genus Corchorus, however, only two have been cultivated; Corchorus capsularis L. (white jute) and C. olitorius L. (Tossa jute) (Rowell and Stout 2007). Corchorus is the haploid genome size that of the two cultivated species were reported to be about 336 Mb (C. capsularis) and 361 Mb (C. olitorius) (Zhang et al. 2021). Salt and drought stresses are among the global catastrophes facing humanity nowadays; it is a significant threat to agriculture, where inadequate irrigation management and water scarcity severely reduce yield (Fao 2008). Saline soils are characterized as low yield, which are widely distributed across the globe. Soil EC > 4 dS/m (about 40 mM NaCl) at 25 °C is considered saline

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_19

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soil (Munns and Tester 2008), while seawater has a salinity of about 40 dS/m (Shabala et al. 2013). The osmotic stress, mineral deficit, and ion toxicity are among the salt stress factors affecting plant growth and development (Munns 2002). Ca2+ and K+ contents reduced significantly, although Cl− and Na+ increased considerably under salt stress in rapeseed (Peng et al. 2004). Moreover, K+/Na+ and Ca2+/Na+ contents decrease due to an increase in salt concentration; thus, plants’ growth is inhibited. At biochemical levels, salt stress negatively affects all plant developmental stages (Munns 2002). Islam et al. (2011b) have also stated adverse effects of salinity on dry matter accumulation and root length in jute. Ghosh et al. (2013) also studied the contents of chlorophyll (SPAD values) of the jute accession. The higher the NaCl concentration in Hoagland's nutrient solution, the lower will be the total dry matter and the shoot length, moreover, the lower will be the relative water contents of the root among various jute genotypes (Ghosh et al. 2013). Jute plants exhibit moderate tolerance to soil salt content, and some white jute genotypes can tolerate a soil salt content up to 160 mM NaCl (Ma et al. 2015; Naik et al. 2015). Although jute can be grown on saline soils, the production quality will be adversely affected under drought and saline conditions (Dhar et al. 2018). Root, shoot, and dry matter accumulation are reduced due to the effects of salt stress (Islam et al. 2011a). Moreover, variation in growth characteristics and leaf relative water contents were also reported (Ghosh et al. 2013), this has been reported in Tossa jute (dark jute) (Chaudhuri and Choudhuri 1997). Jute is the ideal choice for saline soil cultivation in China (Javed et al. 2014) as such screening of salinity and drought-tolerant genotypes are very important for developing tolerant cultivars adapted to such environmental conditions. However, molecular mechanisms and biotechnological aspects concerning salt

J. Yao et al.

tolerance in jute are scarce (Ma et al. 2015), as such, there is a need to address these issues for the betterment of our future generation.

19.2

Threading Challenge for Salt and Drought Tolerance in Jute

Salt and drought tolerance of jute are quantitative traits, and their phenotypes are very challenging to determine. Due to the complex mechanisms involved in different developmental stages of plants, tolerance at a particular growth stage may not often be correlated with that of the other, as such very difficult to deal with genetic research (Kumar et al. 2015). Some of the burdens of jute improvement especially concerning abiotic tolerance are narrow genetic base, sexual incompatibility, and jute's susceptibility to several abiotic and biotic stresses (Sarker et al. 2008). The important selective role of salt and drought stress in plant growth and development, physiology and evolution, and are therefore among the major jute production constraints, especially the two species cultivated around the globe. The future climatic changes may increase the effects of these stresses (Rizza et al. 2004). As such, developing tolerant varieties is urgently needed to cope with these devastating conditions (Cattivelli et al. 2008). We noted that, in the dry seasons, breeders use direct selection (Richards et al. 2002) for biomass underwater-limited conditions; however, it is very difficult due to the complexity of the traits and stress tolerance mechanism (Lakew et al. 2011). Breeders have targeted several secondary traits to select for stress tolerance in jute, such as plant height, relative water content, chlorophyll content, fresh and dry shoot weight, etc. However, under stress conditions, direct selection for such secondary traits has been affected by low heritability, high genotype by environment (G  E) interactions, and epistasis

19

Genomics and Genetics of Drought and Salt Tolerance in Jute

(Baum et al. 2007). Most of the new varieties are bred by conventional breeding methods. However, these conventional breeding methods focus mostly on yield forgoing other important traits especially tolerance to abiotic stress.

re-evaluated under the seedling stage exposed to control, NaCl, and PEG treatment conditions, and genetic diversity study was conducted.

19.4 19.3

Molecular Markers for Salt and Drought Tolerance in Jute

Hossain et al. (2003) used RAPD and AFLP molecular markers in jute 20 years ago. In recent years, most studies have centered on jute DNA fingerprint analysis and assessment of genetic diversity among important jute varieties (Roy et al. 2006; Haque et al. 2007; Saha et al. 2014). It is gradually observed that the microsatellite polymorphism of jute is higher than that of other crop varieties (Mir et al. 2008, 2009). Initially, marker-assisted selection (MAS) could not be used for jute because of the prevalence of lowdensity maps. However, it has recently been reported that the high-density linkage map of C. olitorius uses microsatellites and restriction siteassociated DNA (RAD) markers (Haque et al. 2008; Kundu et al. 2015; Sultana et al. 2006). Genetic diversity and relationship studies in jute mainly related to salt tolerance at the molecular level are minimal. Most of the genetic diversity studies are concentrated on other agronomical traits rather than salt and drought tolerance. Genetic diversity study on 292 jute genotypes using 172 SSRs primers was conducted by Banerjee et al (2012). Zhang et al. (2015b) assessed the relationship and genetic structure in a panel of 159 jute accessions from 11 countries and regions using 63 SSRs. We utilized and evaluated about 292-jute germplasms, sourced from 12 countries including China (from 14 different areas) under control, 200 mM salt (NaCl), and drought (6000 PEG 15%) treatment conditions, at the germination stage. From the phenotypic data evaluation results (result not shown), 24 salt-tolerant extreme lines were obtained from which were

293

Bi-Parental Mapping to Dissect Salt and Drought Tolerance in Jute

We used two different parents to study the genetics of salt and drought tolerance of jute at the germination and seedling stages. Huangma179 is tall but sensitive to abiotic stresses, and Aidianyehuangma is short but tolerant to abiotic stresses. Consequently, recombinant inbred lines (RILs) of C. capsularis were generated through single seed descent. These were evaluated under control, drought, and salt treatment conditions during the germination and seedling stages. Figure 19.1 indicates the frequency distribution of three germination-related traits (percentage germinations underwater, salt, and drought). 35, 28, and 14 accessions underwater, salt, and drought, respectively, had germination rates between 90 and 100%. Whereas 3, 12, and 23 accessions underwater, salt, and drought, respectively, had germination rates of about 0– 30%. The two parents (Huangma179 and Aidianyehuangma) differ significantly (Fig. 19.1); under control (water) treatment, the rate of germination ranges from 90–100% to 0–30% for Aidianyehuangma and Huangma179, respectively. Under salt treatment, the rate of germination ranges from 90–100% to 0–30% for Aidianyehuangma (90.7%) and Huangma179 (16.7%), respectively. Moreover, under drought treatment, significant differences between the two parents were observed; 60–90% and 0–30% were recorded for Aidianyehuangma (83.3%) and Huangma179 (8%) parents. Mean squares from ANOVA and broad-sense heritability of the three germination-related traits are presented in Table 19.1. The results indicate that RILs were highly significant (p  0.001) in all three germination-related traits. Higher percent broad-

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%GermW

J121

%GermS

60

F re q u e n c y

Fig. 19.1 Frequency distribution of germinationrelated traits under three treatments (Control (deionized water), 120 mM NaCl, and 15% PEG 6000)

%GermD J116

40

J116 J116 J121

20

J121

0 0-30

30-60

60-90

90-100

Germination percentage

Table 19.1 ANOVA and broad-sense heritability of three salt-related traits at the germination of the RIL population in jute Trait

Source of variation Repetition

GW

SS

MS

F value

691.52

345.76

6.79** 18.91**

99.00

105,047.95

963.74

Error

218.00

11,108.48

50.96

Total

319.00 2.00

72.16

1.20 35.22**

99.00

229,941.14

2109.55

Error

218.00

13,058.35

59.90

Total

319.00 2.00

Broad sense heritability (%) 94.98

116,847.95 144.32

RIL

Repetition GD

2.00

RIL

Repetition GS

DF

97.24

243,143.81 125.96

62.98

1.06 44.36**

RIL

99.00

288,054.65

2642.70

Error

218.00

12,986.04

59.57

Total

319.00

301,166.65

97.80

GW: Germination rate under control, GS: Germination rate under salt, GD: Germination under drought, DF: Degree of freedom, and ** : Significant level at 1% probability. Highly significant differences were observed in all the treatments tested with the heritability value greater than 90%

sense heritability was observed in germination under drought (GD) > germination under salt (GS) > germination underwater (GW) (97.80, 97.24 and 94.98%, respectively). We observed highly significant differences (p  0.001) between RILs and stress conditions at the germination stage (Table 19.1), even at the seedling stage highly significant differences (p 0.001) were also observed among the RILs and treatments conditions (control, salt, and drought) were also observed, indicating the presence of considerable variability. Substantial variability in

Corchorus olitorius genotypes was reported (Biswas et al. 2018). Dabholkar et al. (1999) reported that heritability estimates varied from low to high. High estimates of broad-sense heritability (97.24 and 97.80%) for NaCl-induced salt and PEG-induced drought, respectively, were recorded at the germination stage (Table 19.1). Similarly, we also recorded (49.99–98.46%) heritability at the seedling stage in jute. A higher percentage heritability estimate (>80%) for physiological parameters was also reported by Ghosh et al.

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Genomics and Genetics of Drought and Salt Tolerance in Jute

Table 19.2 Pearson correlation coefficients of three salt tolerance-related traits at the germination stage in jute

295

GW

GS

GD

GW

1

0.57687**

0.46721**

GS

0.57687**

1

0.84925**

GD

**

**

0.46721

0.84925

1

GW: Germination rate under control, GS: Germination rate under salt, GD: Germination rate under drought treatments and ** : Significant level at 1% probability. A highly significant positive correlation was observed among the tested treatment

(2013). Moreover, at the seedling stage, most of the study traits had higher percent broad-sense heritability (49.99–98.46%). We also recorded a significant and positive correlation (0.85) (Table 19.2) between GS (germination rate under salt treatment condition) with GD (germination rate under drought treatment condition), suggesting that NaCl and PEGinduced stress had a similar response at the germination stage and probably underlined by similar genetic factors. In contrast, in sesame, several genetic factors control the stress induced by NaCl and PEG (Li et al. 2018). Moreover, we observe that due to the type of mapping strategy utilized, the genetic map contains 11 linkage groups instead of 7 linkage groups (as expected). The genetic composition of the diverse mapping populations, the ratio between the number of markers and population size, the type of the mapped loci, and the choice of the mapping software (Das et al. 2012) all might cause such inconsistencies. We utilized a relatively low population size (100), which leads to this inconsistent linkage group and jute chromosome number compared with some previous studies (Das et al. 2012). From our findings at the germination stage, the same specific flanking left and right markers (M26548-M35561) at LG7 were found to be associated with salt and drought stresses (Table 19.3); it can, therefore, effectively be used in MAS. The same genetic factors possibly govern similar markers, as is also evident from the correlation between the traits. It can be seen from our results that the PVE (21.60 and 17.27%) (Table 19.3) of the two QTLs (qGS3-7– 1 and qGD2-7–1) for the germination under salt and drought stresses, respectively, mapped on the same linkage group (LG 7). These indicated their

reliability to be used across the two conditions; similar findings were reported by Lang et al. (2017) who identified several QTLs related to salt stress (chlorophyll content [SPAD values]) with 20% of PVE. Moreover, Yang et al. (2019) identified major QTL qJST-1 under 140 and 160mMNaCl concentration at the germination stage. QTL detected under PEG-induced drought stress at the germination stage displayed higher additive effects (Table 19.3) and ranges (9.82– 9.84) than that of NaCl induced salt stress (4.30– 5.16), as such selection for drought stress at the stage of germination will be more useful and effective. Contrary to the findings of Abdelraheem et al. (2018), who stated that NaCl treatment showed most QTL analysis, which always has a higher added effect of traits than the heritability under PEG conditions. Moreover, interestingly the most abundant candidate genes identified in our study were Corchorus capsularis PP2C (25) (Table 19.4), which plays a major negative regulator in the ABA signaling pathway, responsible for several abiotic stresses (Yoshida et al. 2006) especially salt and drought tolerance.

19.5

Transcriptomic Analyses

The numbers of genes so far identified in jute are few (Samira et al. 2010). Islam et al. (2005) reported 15 genomic jute sequences and cDNA clone homologs with Arabidopsis. Moreover, Wazni et al. (2007) found 16 expressed sequence tags (ESTs) that have a significant relationship with Arabidopsis. C. olitorius leucine-rich repeat receptor-like protein kinase (LRR-RLK) gene has been identified, sequenced, analyzed, and

61

61

1

1

1

1

6

6

6

6

6

6

6

6

6

7

7

7

7

7

9

9

9

9

qGWM-1–1

qGW3-1–2

qGW2-1–1

qGWM-1–2

qGW2-6–1

qGW1-6–1

qGW2-6–2

qGW3-6–1

qGWM-6–1

qGW1-6–2

qGW2-6–3

qGW3-6–2

qGWM-6–2

qGW3-7–1

qGS3-7–1

qGD2-7–1

qGSM-7–1

qGDM-7–1

qGW2-9–1

qGWM-9–1

qGW2-9–2

qGW2-9–3

Marker28515

Marker29824

Marker35617

Marker35617

Marker26548

Marker26548

Marker26548

Marker26548

Marker29857

Marker24354

Marker24354

Marker24354

Marker24354

Marker35329

Marker35329

Marker35329

Marker35329

Marker33330

Marker26821

Marker37200

Marker37200

Marker26712

Marker26712

Left marker

Marker17326

Marker24734

Marker23138

Marker23138

Marker35561

Marker35561

Marker35561

Marker35561

Marker25506

Marker27813

Marker27813

Marker27813

Marker27813

Marker37165

Marker37165

Marker37165

Marker37165

Marker37075

Marker19007

Marker26821

Marker26821

Marker34288

Marker34288

Right marker

GW

6.00

6.23

5.47

6.89

3.57

8.38

8.68

11.16

7.05

5.88

5.51

8.60

4.04

4.11

7.79

8.86

8.32

8.78

9.62

LOD

2.81 11.47 7.21 3.71 2.78 14.66 7.17 10.34

−31.08 −42.38 −31.90 −33.43 −31.42 −34.01 −32.26 −26.59

2.60

3.72

−33.18

2.60

2.33

−24.42

−33.77

7.53

−29.53

−33.77

2.60

−34.16

6.97

14.61

−34.66

2.60

6.97

−33.50

−33.55

14.60

−34.64

−33.78

R2 (%)

A

2.63

2.56

LOD

GS

4.30

5.16

A

17.60

17.27

R2 (%)

2.89

3.21

LOD

GD

9.84

9.82

A

19.48

21.60

R2 (%)

q: QTL, GW: Germination rate under control, GS: Germination under salt, GD: Germination under drought, A: Additive effects, LOD: Logarithm of the odds, R2 (%): Phenotypic Variance

38

33

23

23

61

61

54

39

39

39

39

36

36

36

36

34

298

295

294

289

289

1

qGW3-1–1

Position (cM)

Linkage group

Putative QTL

Table 19.3 Putative QTL for three germination-related traits (underwater, salt, and drought) in the RIL population of white jute

296 J. Yao et al.

19

Genomics and Genetics of Drought and Salt Tolerance in Jute

Table 19.4 Physical map of PP2C candidate genes identified

297

S/N

Chromosome

Physical mapping

PP2C candidate genes

1

1

12,719,035

Cc.01G0009520

2

1

19,093,541

Cc.01G0028490

3

1

22,071,284

Cc.01G0032360

4

1

74,624,387

Cc.04G0013340

5

2

7,176,786

Cc.02G0000770

6

2

7,178,109

Cc.02G0005900

7

2

51,026,483

Cc.02G0024270

8

2

117,463

Cc.05G0010230

9

2

21,934,772

Cc.05G0014550

10

2

12,557,258

Cc.05G0029870

11

2

12,616,622

Cc.05G0029950

12

2

51,024,943

Cc.06G0018170

13

3

17,592,869

Cc.03G0003110

14

3

54,810,999

Cc.03G0016550

15

3

1,060,102

Cc.03G0020320

16

3

2,765,212

Cc.03G0022250

17

3

41,298,183

Cc.07G0002210

18

3

50,667,225

Cc.07G0010300

19

4

30,418,579

Cc.04G0042080

20

4

34,160,617

Cc.04G0045880

21

4

34,926,382

Cc.04G0046980

22

4

35,353,025

Cc.04G0047530

23

4

35,882,110

Cc.04G0048240

24

5

26,371,080

Cc.07G0024730

25

5

29,376,913

Cc.07G0028160

reported to be part of stress response-related pathways (Basu et al. 2004). As such, the advancement of the RNA-seq and nextgeneration sequencing of C. capsularis and C. olitorius has advanced gene annotation and mining. Transcriptome analysis of 24 salt-tolerant (Shao’anhongpi) and sensitive (Riben No.5) jute samples using Illumina paired-end sequencing technology was conducted to explore the Differentially Expressed Genes (DEGs) related to sodium chloride (NaCl) stress in jute (utilizing two biological replicates in each case; tissues (leaf and roots) and time (0, 6, and 12 h). As such, we observed that most of the unigenes (26,413) were aligned with that of the NR

database, followed by eggNOG_Annotation (22,539) and Pfam_Annotation (19,493). However, annotation in the KEGG database (8992 unigenes) presented the least number of unigenes. It was observed that the most significantly enriched set of genes was associated to plant hormones as such vital in response to jute NaCl exposure. As mentioned, plant hormone signal transduction (ko04075) and cysteine and methionine metabolism (ko00270) were the most enriched pathways in root tissues at 6-h exposures to NaCl stress. Plant hormonal signal transduction pathways of the up-and down-regulated DEGs in the two germplasms’ root tissues (Shao’anhongpi and Riben No.5) at 6 h of exposure to NaCl stress

298

J. Yao et al.

Up regulated (Shao’anhongpi) Down regulated (Shao’anhongpi) Up regulated (Riben No.5) Down regulated (Riben No.5)

Fig. 19.2 Plant hormone signal transduction pathway for up- and down-regulated DEG root tissues of the two germplasms (Shao’anhongpi and Riben No.5) at 6 h

exposure to NaCl stress of comparative transcriptomes of salt treatment in jute

are presented in Fig. 19.2. The results indicate that three DEGs are involved in AUXIN1 production. These genes were down-regulated in Shao’anhongpi and Riben No.5, respectively. For IAA, five DEGs were identified; however, only Cc.07G0002340 (down-regulated) and Cc.07G0003430 (up-regulated) were recorded in Shao’anhongpi. Additionally, two DEGs (Cc.01G0010780 and Cc.07G0003430) and three DEGs (Cc.04G0043620, Cc.04G0045370, and Cc.07G0002340) were up- and down-regulated in Riben No.5, respectively (Fig. 19.2). For ARF, three DEGs were involved, but only one (Cc.06G0025590) was down-regulated in both Shao’anhongpi and Riben No.5. Another one (Cc.06G0027580) was down-regulated in Riben No.5 only. For IAA, one DEG (Cc.07G0005110) was up-regulated in both Shao’anhongpi and Riben No.5, while for the GH3 signaling pathway, two up-regulated DEGs were found (Cc.01G0028710 and Cc.02G0006030) in both Shao’anhongpi and Riben No.5. Small auxin-up RNAs (SAUR) involve eight DEGs, among which four (Cc.03G0019440, Cc.03G0029630, Cc.04G0007220, and Cc.05G0005100) were upregulated in both Shao’anhongpi and Riben No.5. However, the remaining four (Cc.02G0011530, Cc.02G0022670, Cc.04G0014260, and Cc.06G0027410) were up-regulated only in Riben No.5. For PYL, one DEG (Cc.03G0016680) was only up-regulated in Riben No.5 whereas six DEGs were involved in the PP2C pathway, out of which three

(Cc.03G0000600, Cc.03G0030800, and Cc.07G0001880) were up-regulated in both Shao’anhongpi and Riben No.5, Cc.03G0016550, and Cc.07G0028160 were upregulated in Shao’anhongpi while Cc.06G0030850) was only up-regulated in Riben No.5. SnRK2 signaling pathway had only three DEGs, including Cc.02G0003620 and Cc.04G0017920 that were up-regulated, and Cc.02G0021190, which was down-regulated in Riben No.5. For ABA-responsive element binding factor (ABF), three DEGs were involved; one (Cc.04G0004780) was up-regulated in both Shao’anhongpi and Riben No.5, whereas Cc.01G0035870 and Cc.06G0010680 were, respectively, up-and down-regulated specifically in Riben No.5. Two DEGs were involved in the Jasmonate zim domain (JAZ) pathway; however, only one (Cc.06G0030170) was up-regulated in both Shao’anhongpi and Riben No.5. In the MYC2 pathway, only one gene (Cc.04G0013900) was down-regulated in both Shao’anhongpi and Riben No.5. The cysteine and methionine metabolism pathways were only enriched in Riben No.5 root tissues. Seventeen DEGs were observed in this pathway (Fig. 19.3). Five homocysteine Smethyl transferase (out of which four were down-regulated and one up-regulated), one Sadenosyl-L-homocysteine hydrolase (Cc.05G0024270, up-regulated), one S-adenosylL-homocysteine (Cc.02G0028130, downregulated), one S-adenosylmethionine

19

Genomics and Genetics of Drought and Salt Tolerance in Jute

299

Fig. 19.3 Methionine metabolism pathways in Riben No.5 root tissues at 6 h of exposure to NaCl and the expression profile of 17 DEGs

synthetase (Cc.05G0005220, down-regulated), three S-adenosylmethionine decarboxylase (Cc.01G0008160 and Cc.04G0038020 upregulated while Cc.07G0011580 was downregulated), four 1-aminocyclopropane-1carboxylate synthases (which were all upregulated, except for one; Cc.07G0031080 that was down-regulated) and one amino cyclopropane carboxylate oxidase (Cc.02G0015210 down-regulated). We noted that the sensitive germplasm had the highest number of DEGs compared with the tolerant individual. These findings are similar to previous studies by Yang et al. (2017c); Fracasso et al. (2016); Lei et al. (2020), indicating that salt-sensitive germplasms display the highest number of DEGs than the tolerant germplasms. Moreover, this is because the effects of salt stress on the salt-sensitive germplasm are greater than that of the tolerant germplasm. Furthermore, we observed that the roots of Shao’anhongpi and Riben No.5 had more DEGs than the leaves that indicate there are other genes associated with roots that do not necessarily play roles in plant response to salt stresses. For the PYL-ABA-PP2C pathway (Fig. 19.2), we recorded 17 DEGs (Cc.03G0016680, Cc.03G0000600, Cc.03G0016550, Cc.03G0027770,

Cc.03G0030800, Cc.06G0030850, Cc.07G0001880, Cc.07G0028160, Cc.07G0031700, Cc.02G0003620, Cc.02G0021190, Cc.03G0023450, Cc.04G0017920, Cc.07G0021650, Cc.01G0015540, Cc.01G0035870, and Cc.04G0004780) in the salt-stressed root tissues of both Shao’anhongpi and Riben No.5. Interestingly, our results showed that the PYL gene (Cc.03G0016680) was up-regulated, supporting the basic ABA signaling model but contradicts the findings of Yang et al. (2017c) who reported down-regulation. Under normal circumstances, PYL binds to ABA and PP2Cs to form PYL-ABA-PP2C complexes, thereby inhibiting PP2Cs. This inhibition releases autophosphorylating SnRK2s, which then phosphorylate many downstream effectors (Zhu 2016). As such, PYL expression is anticipated to keep pace with ABA concentration and up-regulated under stress conditions. Moreover, Yang et al. (2017a) conducted a comprehensive study on the drought tolerance of the two species of jute and found approximately 45,831 non-redundant unigenes. Here, they identified a higher number of DEGs in sensitive species (794) compares to the tolerant one (39), indicating that drought-sensitive species are relatively more susceptible to drought stress at the molecular level. Under salt stress, Yang et al.

300

(2017b) found 127 common differentially expressed genes (DEG) by conducting highthroughput transcriptome sequencing on 24 white jute and Tossa jute samples. They reported that cytokinin signal and Abscisic acid pathways were the most enriched in roots and leaf tissues of the two cultivated jute species and recorded about 20 DEGs. Ma et al. (2015) treated jute at the seedling stage with 50, 100, and 150 mM NaCl for 4 days and analyzed the physiology, morphology, and proteomics of the two jute genotypes. The authors found that the expression of 44 protein sports in the roots of the seedlings of the two genotypes changed significantly in response to salt stress. They also identified 39 differentially expressed proteins by MALDI-TOF-TOF MS and divided them into nine groups. The authors concluded that after 4 days of salt-stress induction, the seedlings have adapted to salt stress through accelerating ROS scavenging, altering signal transduction, enhancing nucleotide metabolism, lipid metabolism, and cell wall metabolism, as well as altering cytoskeleton in roots. We noted that ABA plays vital regulatory roles in salt and drought stresses tolerance during the plant developmental stages (Kuhn et al. 2006; Liu et al. 2008). As such, NaCl stress in jute was assessed by monitoring the expression pattern of

J. Yao et al.

the key stress marker genes (RAB18, RD29B, KIN1, and RD29A) in Shao’anhongpi (tolerant) and Riben No.5 (sensitive) under control and stress conditions at 1 and 2-week exposure to NaCl (Fig. 19.4). The result indicated that Shao’anhongpi had the highest relative gene expression level in all studied genes across the period. However, the relative expression level of Cc.04G002237 (RAB18) and Cc.03G0029910 (RD29B) was higher in Shao’anhongpi roots tissues across the period of NaCl exposure whereas, Cc.01G0008270 (KIN1) and Cc.03G0029910 (RD29A) had the highest expression level in Shao’anhongpi leaf tissues across the time points. Our findings were consistent with those reported by Singh et al. (Singh et al. 2015), this signifies that the overexpression profiles of these key stress marker genes of Corchorus capsularis PP2C (Cc.04G002237, Cc.03G0029910, Cc.01G0008270, and Cc.03G0029910) genes revealed a significant interplay of ABAdependent and independent pathways for abiotic stress. Moreover, high expression of these genes in Corchorus capsularis may exhibit high ABA insensitive, as such Corchorus capsularis PP2C genes act as the major negative regulator of ABA signaling (Yoshida et al. 2006). Moreover, we noted that the expression profile of

Fig. 19.4 Expression profile of key stress marker genes at 1 and 2 weeks of exposure to NaCl

19

Genomics and Genetics of Drought and Salt Tolerance in Jute

these stress marker genes reveals that they were tissue-specific; this indicated that RAB18 and RD29B were highly expressed in root tissues, whereas KIN1 and RD29A expressed the highest in leaf. This is consistent with the findings of Zhang et al. (2013) who stated that group A PP2C has distinctive roles in different tissues and organs as indicated by tissue-specific expression patterns. We further find out that, most PP2C Corcharus capsularis genes were involved in segmental duplication, and this is consistent with the findings of Cao et al. (2016) and Shazadee et al. (2019). This duplication type plays a vital role in expanding the PP2C Corchorus capsularis gene family. The qPCR analysis was conducted to generate the relative expression profile level of key established stress marker genes such as RAB18, RD29B, and KIN, and RD29A (a to d, respectively) in Shao’anhongpi and Riben No.5 leaf (L) and root (R) tissues at 0 (control), 1, and 2 weeks duration of the exposure to NaCl. The X-axis represents the samples at control (C) and treated (T) and the relative expression level is indicated in Y-axis. Data from the mean of the replicated samples are presented as columns, and an error bar denotes the standard deviation. *pvalue < 0.05 and **p-value- < 0.01 indicate statistically significant level.

19.6

Conclusion and Future Perspective

Conclusively, molecular-based breeding and exploring new genomics approaches to develop tolerant cultivars are recently needed. We have identified some genes and QTLs related to salt and drought tolerance. The current development in NGS tools and bioinformatics along with high throughput phenotyping approaches will enable us to detect loci associated with abiotic stress tolerance, and in investigating natural dynamics at these loci for breeding novel varieties via MAS (marker-aided selection). The progress of genomic selection is expected to solve the problem of conventional selection that is difficult to perform phenotypic

301

analysis and time-consuming traits to select multiple genes with small genetic effects. The implication of narrow genetic basis and highly recalcitrant nature, moreover, only C. capsularis and C. olitorius still available are the main research limitations that narrow the breeding options in jute. Comprehensive interspecific hybridization approaches between some wild species especially (C. trilocularis, C. tridens, and Corchorus depressus) and cultivated species must be undertaken to enhance breeding of abiotic stress tolerance in jute. Alternatively, through proteomics, metabolomics, and transcriptomics methods, the underlying genes for salt tolerance and drought tolerance of wild Corchorus species are determined. Several salts and drought-tolerant genes so far identified from other crops species that are not available in jute can be combined into the jute genome by a transgenic approach.

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Flowering Pathway of Jute Based on Genomic Data

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Md. Wali Ullah and Md. Shahidul Islam

Abstract

The transition from vegetative to flowering is important for survival of plants as well as reproductive success. Timely flowering is one of the important traits of bast fiber and has a major impact on fiber yield in crops. In jute, flowering is the result of the primary induction of a short-day length. Early flowering occurred in jute mainly due to early sowing of jute varieties in short day length period and might be partly due to prolonged drought, stunted growth, dry air, low fertility of soil, cloudy weather, etc. Although flowering pathway-related genes have been extensively analyzed in several plants but, a systemic study is lacking in jute. With the accomplishment of two jute species genome sequence, now has made the opportunity to broadly study the flowering pathway-related genes. This chapter gives an overview of the genetics of flowering time in jute. The key flowering time genes are presented and their interaction

Md. W. Ullah
Md. S. Islam Basic and Applied Research on Jute Project, Bangladesh Jute Research Institute, Dhaka, Bangladesh Md. S. Islam (&) Genetic Resources and Seed Division, Bangladesh Jute Research Institute, Dhaka, Bangladesh

in different pathways is discussed with the help of the current knowledge proceeding from the model species Arabidopsis thaliana and rice.

20.1

Introduction

Flowering plants are the dominant group of land plants both in terms of species number (ca. 300,000) and ecological importance. Flowering plants show many innovations relative to other seed plants, which indicates that it is difficult to determine which features were responsible for their dominance. There are possible key innovations that have been highlighted, such as xylem vessels (Feild et al. 2002), reticulate venation (Givnish 1979), endosperm development (Floyd and Friedman 2000), and seed enclosure in fruit (Regal 1977). Nevertheless, there is a good reason to assume that the flower itself contributes to the increased rate of diversity seen in the angiosperms. In flowering plants, the transition from vegetative to reproductive development results from the expression of flower meristem identity genes, those are responded to environmental and endogenous signals in order to convert meristems into floral meristems. An important key integrator of exogenous and endogenous signaling is the FLORICAULA (FLO) gene of Antirrhinum majus (Coen et al. 1990) and its ortholog in Arabidopsis, LEAFY (LFY) (Weigel et al. 1992).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_20

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A mutant of FLO/LFY tends to show the transformation of flower meristems into shoot meristems. In contrast, overexpression of FLO/LFY in different eudicot species results in some degree of transformation of vegetative meristems into flower meristems. The results indicate that FLO/LFY plays an important role in reproductive development throughout the seed plants (Frohlich and Meyerowitz 1997; Frohlich and Parker 2000). The angiosperms or flowering plants have evolved elaborate mechanisms to ensure that flowering occurs at an optimal time for reproductive success. The consistency of these regulatory mechanisms requires the integration of different signals from the environment with endogenous physiological cues in order for the floral alteration to occur at the correct time. In the last century, comprehensive physiological experiments have established a ground upon which present genetic models are conterminous in order to reveal the mechanisms underlying the floral transition. Intensive molecular and genetic analyses have identified four major flowering pathways, viz the photoperiod, vernalization, autonomous, and gibberellin pathways, in plants (Kim et al. 2009; Amasino and Michaels 2010; Song et al. 2013; Capovilla et al. 2015). Although the recent integration of several additional pathways, viz sugar, hormone, and ambient temperaturedependent pathways, has been reported (Bolouri Moghaddam and Van den Ende 2013; Wahl et al. 2013; Conti 2017; Seo et al. 2011; D’Aloia et al. 2011; Susila et al. 2018). In a model plant Arabidopsis, at least four floral inductive pathways have been incorporated into a genetic model of a flowering pathway network. This network contains several nodes, each of which represents a site of signal integration. Integration of these pathways is required for coordinated initiation of flowering by the various pathways. In Arabidopsis, generally determining of four floral pathways does not mean that the same genetic stratification exists in all plant species. Indeed, the environmental stimuli perceived by plants vary depending on geographical location, and the individual flowering processes may have developed

Md. W. Ullah and Md. S. Islam

independently in different plant species. However, flowering pathways derived from intensive studies of Arabidopsis mutants define the basic processes common for most plant species. Jute is one of the most fiber crops in Bangladesh and two species, namely, Corchorus capsularis (White jute) and Corchorus olitorius (Tossa jute), are commercially cultivated. Both of the cultivated species of jute are sensitive to short day length (Husain 1977). They are generally sown between March and May and harvested during July–August. The appropriate time for sowing of white jute is after 15 March–15 April and for tossa jute is 15 April–15 May (Husain 1977). If sowing made earlier than the actual time produces stunted growth and tend to branching in plants and gives lower fiber yield. Thus, fiber production from jute is limited to that part of the year with day lengths exceeding the critical day length. Therefore, jute is sown a month earlier, in many cases, jute growers will be able to protect their crops from unpredictable natural calamities and above all, gives higher yield. The major components of genetic regulators of floral induction have been well characterized in model species, and increasing numbers of related genes are being identified in crops. However, systematic studies of flowering pathways in jute have not been addressed yet based on genome data. So, using genomic data, to uncover the flowering pathway-related genes in jute will be strong foundation for future studies. This chapter will discuss the current understanding of each flowering pathway operating in jute based on genome data. In addition, how the components of each pathway interact will be discussed.

20.2

Impact of Flowering Time on Yield in Jute

Jute is predominantly grown for fiber. Jute fiber is obtained from the bark of Corchorus olitorius L. and C. capsularis L. India, Bangladesh, China, Myanmar, Nepal, Thailand, Vietnam, Uzbekistan, and Sudan are at present the major producers of Jute, Kenaf, and Roselle fibers. Among them, India, Bangladesh, and China are the largest jute producers and they produce about

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Flowering Pathway of Jute Based on Genomic Data

97% of world jute production. But the land and climatic condition of Bangladesh are favorable for the production of high-quality jute. Jute is a photoperiod sensitive and short-day plant. The critical photoperiod is being 12 h for white jute and 12.5 h for tossa jute plants (Ali 1961; Kar 1962). Due to photo-sensitivity, jute plants sown or planted subjected to short days (less than the critical photoperiod) giving stunted growth and introducing premature flowers (Johansen et al. 1985). According to Gupta and Sen (1946) in an imposed short photoperiod (exposed to short photoperiods of 3 h. less than the normal light period), both species, Corchorus capsularis and Corchorus olitorius, showed short vegetative period, early flowering and branching nature at flowering. Due to exposure to short photoperiod, all the plants’ height of Corchorus capsularis and Corchorus olitorius is about 60 cm and 35 cm, on the contrary, the total height reached by normally grown plants of 250 cm and 300 cm, respectively, at flowering. Therefore, they conclude that the earliness of flowering due to short photoperiod treatments greatly impacts on fiber yield. Choudhury and Ali (1962) observed that plants having more vegetative growth produced more fiber but less seeds; therefore, checking vegetative growth by late sowing was the improved device to increase the seed yields. There evolved some less photo-sensitive varieties of both C. capsularis and C. olitorius species, which have flexibility in sowing time and can easily be accommodated in three cropping seasons. Among the less photo-sensitive varieties of tossa jute, JRO-524 and O-9897 rank at the top for their higher yield and better quality fiber. Farmers also prefer this variety for its early sowing characteristics. These varieties exclusively produce better fiber yield but produce very poor seed yield when planted in March–April as fiber crop (Hossain et al. 1994).

20.3

Flowering Pathways in Jute

The transition to flowering consists of a major phase change in the plant’s lifecycle. The production of a plant that has previously produced

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only its leaves and axillary meristems must now transit to producing bracts and floral meristem along with any change in the general axis and type of growth. This transition is referred as the vegetative-to-reproductive or floral transition and commits the plant to flower. The timing of this transition is critical, after realizing the favorable environmental conditions and endogenous signals, plants initiate flowering and vegetative meristems, producing leaves and shoots, become inflorescence meristems. In plant, this transition can be thought of as a 'decision part', it is not a random event, but occurs in response to one or several sets of potential stimuli, which differ from species to species. Environmental and endogenous signals are interpreted by multiple regulatory pathways in plants. Though several additional pathways have been integrated recently, nevertheless genetical and molecular analyses have identified four major flowering pathways, viz, the photoperiod, vernalization, autonomous, and hormonal pathways, in plants. Genome-wide analysis in jute also observed that these major four flowering pathways are functioning. Flowering-related proteins are given in Table 20.1.

20.3.1 Floral Induction in Jute by the Photoperiod Pathway Generally, photoperiodism can be defined as the response to changes in day length that enables plants to adapt to seasonal changes in their environment, except at the equator. The period of light in a given day or photoperiod is an important indication that flowering plants utilize effectively evaluate seasonal information and coordinate their reproductive development in synchrony with the external environment.

20.3.1.1 Physiology of Photoperiodism At the beginning of the twentieth century, Julien Tournois and Hans Klebs proposed independently the response of plants to the daily duration of light. However, Garner and Allard (1920) first described clearly that flowering and many other

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Md. W. Ullah and Md. S. Islam

Table 20.1 Flowering-related Proteins in Jute (Corchorus olitorius and C. capsularis) C. olitorius gene model

C. capsularis gene model

Alias

Enzyme name

COLO4_12653

CCACVL1_14183 CCACVL1_09899

AGL20

Mads-box protein agamouslike 20

COLO4_27843

CCACVL1_06450

AP1

Floral homeotic protein apetala 1

COLO4_20029

CCACVL1_09904

CAL

Transcription factor cauliflower

COLO4_23060

CCACVL1_01635

CCA1

Circadian clock-associated 1

COLO4_18994, COLO4_08017, COLO4_13201, COLO4_12998, COLO4_20602,

CCACVL1_29126, CCACVL1_23818, CCACVL1_09754, CCACVL1_19565, CCACVL1_14759, CCACVL1_23777, CCACVL1_10149, CCACVL1_16762, CCACVL1_24344, CCACVL1_16130, CCACVL1_24820, CCACVL1_16782, CCACVL1_17834, CCACVL1_07649

CO

Constans/zinc finger protein constans

COLO4_04558, COLO4_31850, COLO4_21724, COLO4_27174,

CCACVL1_15331, CCACVL1_31061, CCACVL1_31063, CCACVL1_13495, CCACVL1_03615

COP1

Constitutive photomorphogenic 1

COLO4_15872

CCACVL1_27540

CRY2

Cryptochrome 2

COLO4_07847, COLO4_34123, COLO4_13331, COLO4_26042, COLO4_19655, COLO4_05971

COLO4_34976

CCACVL1_12703

D8

Della protein dwarf 8

COLO4_18362, COLO4_09900, COLO4_09934

CCACVL1_20471, CCACVL1_06216 CCACVL1_26802

EIN3

Ethylene-insensitive 3

–

CCACVL1_18542

ELF7

Early flowering 7

COLO4_18111

CCACVL1_20711

ELF8

Early flowering 8

COLO4_34585, COLO4_23202

CCACVL1_28613, CCACVL1_22103

FCA1

Flowering time control protein

COLO4_20430

CCACVL1_10206

FLC

Flowering locus C

COLO4_34216, COLO4_21596, COLO4_09467, COLO4_26189

CCACVL1_21496, CCACVL1_02625, CCACVL1_12981, CCACVL1_09014

FLD

Lysine-specific histone demethylase 1

COLO4_03736, COLO4_07096, COLO4_10328, COLO4_09318, COLO4_31185, COLO4_31040, COLO4_07097,

CCACVL1_18029, CCACVL1_13923, CCACVL1_00340, CCACVL1_30185, CCACVL1_15912, CCACVL1_13754, CCACVL1_13131, CCACVL1_06572, CCACVL1_10315,

FLK

Flowering locus kh domain

COLO4_18615, COLO4_35360, COLO4_03739, COLO4_22942, COLO4_32403, COLO4_12431, COLO4_27374

(continued)

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Flowering Pathway of Jute Based on Genomic Data

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Table 20.1 (continued) C. olitorius gene model

C. capsularis gene model

Alias

Enzyme name

FPA

Flowering time control protein

CCACVL1_18988, CCACVL1_08658, CCACVL1_19415, CCACVL1_26646 COLO4_10090, COLO4_19705

COLO4_37292

CCACVL1_20129, CCACVL1_25230, CCACVL1_08016 CCACVL1_05824

FRI

Frigida

COLO4_34901, COLO4_11512, COLO4_09781, COLO4_36066,

CCACVL1_21527, CCACVL1_07250, CCACVL1_11274, CCACVL1_12787, CCACVL1_07252, CCACVL1_07249, CCACVL1_09437

FRL1

Frigida-like protein

COLO4_32094

CCACVL1_25746

FT

Flowering locus T

COLO4_18197, COLO4_30660

CCACVL1_20631

FVE

Wd-40 repeat protein MSI4

COLO4_13783, COLO4_13782

CCACVL1_12464

GI

Gigantea

COLO4_07998

CCACVL1_22294

LD

Luminidependens

COLO4_37264

CCACVL1_05844

LFY

Leafy-like protein

COLO4_32860

CCACVL1_31004

MYB33

Myb domain protein 33

COLO4_26280

CCACVL1_08938

PAF1

Proteasome alpha subunit F1

COLO4_05474

CCACVL1_09740

PHYA

Phytochrome A

COLO4_22907

CCACVL1_30579

PIE1

Photoperiod-independent early flowering 1

COLO4_29672

CCACVL1_11971

SPY

UDP-N-acetylglucosaminepeptide Nacetylglucosaminyltransferase

COLO4_29765, COLO4_19899

CCACVL1_12042, CCACVL1_30972

TFL1

Terminal flower 1

COLO4_36941

CCACVL1_06894

TOC1

Two-component response regulator-like aprr1

COLO4_24182, COLO4_35254, COLO4_34883, COLO4_37734

CCACVL1_18075, CCACVL1_30263

VIN3

Vernalization insensitive 3

COLO4_18151, COLO4_27437

CCACVL1_20681, CCACVL1_06714

VIP3

SKI8 Like WD40 repeatcontaining protein

COLO4_37593

CCACVL1_29931

VIP4

LEO1-like family protein

COLO4_10019, COLO4_37330, COLO4_37126

CCACVL1_24757, CCACVL1_05791

VRN2

Polycomb group protein vernalization 2

COLO4_05865, COLO4_06350

CCACVL1_00388, CCACVL1_24055, CCACVL1_25668

MIR159A

MicroRNA 159a

COLO4_08612

CCACVL1_11768, CCACVL1_25142

MIR172A

MicroRNA 172a

COLO4_34278, COLO4_15296, COLO4_36065, COLO4_21479, COLO4_36068

310

responses in plants could be accelerated either by long days or by short days, depending on the plant; this phenomenon is now termed photoperiodism. Short-day plants are plants whose flowerings are accelerated by days that are shorter than a critical day length. Long-day plants are plants those flowerings are accelerated when the daylight period exceeds a critical day length. On the other hand, day-neutral plants are plants whose flowering time is irrespective of the changes in day length. Many important crop species are potentially photoperiodic, such as rice, soybean, jute, kenaf, cotton, maize, tobacco, sunflower are short-day plants, while long-day plants include wheat, potato, grape, pea, barley (Thomas et al. 2006). According to Knott (1934), a common feature of photoperiodism seems to be that the perception of day length is a separate process from the response to photoperiod. In photoperiodical sensitive plants, either the leaves or the shoot tips are exposed to different day lengths, flowering depends on the day length given to the leaves and not to the apex. Flowering in plants occurs when signal transmitted from the leaves to the apex. Florigen, a specific flowering hormone responsible for controlling and/or triggering flowering in plants. Florigen is produced in the leaves and passing signal between leaves and response sites (Chailakhyan 1936). This concept was based on multiple experiments showing that grafting of leaves from one donor plants to a separate receptor plant could cause flowering. Both jute species are short-day plants and the critical light is being 12 h for Corchorus capsularis and 12.5 h for Corchorus olitorius (Gupta and Sen 1946; Ali 1961). The long vegetative period of jute seems to be influenced by long light periods more than any other factor (Gupta and Sen 1946). Photoperiod had the largest effect on flowering, and this effect was eventually reflected in plant height, technical height, and fiber weight (Johansen et al. 1985).

Md. W. Ullah and Md. S. Islam

20.3.1.2 Current Molecular Mechanism of Photoperiodic Flowering Pathway in Jute Changes in the length of the day provide a reliable and consistent indicator of changes in the environment. These changes give the impression of the onset of cold or rainy season and allow the plants to coordinate flowering time. Short-day plants often have a clear day length threshold, called critical day length (critical photoperiod length), after which flower formation is induced. A long-day plant, Arabidopsis thaliana, the molecular mechanisms of photoperiodic flowering are well studied and characterized. In rice, a short-day plant, such molecular mechanisms also have been well studied, particularly those that confer critical day length recognition. In Arabidopsis, various reports suggested that a candidate for florigen is FT (FLOWERING LOCUS T) gene and it is expressed in the leaf and promotes flowering at the shoot apex (Abe et al. 2005; Kardailsky et al. 1999). Latterly, it was informed that FT and its rice ortholog Hd3a (Heading date 3a) can move from leaves to the shoot apex (Corbesier et al. 2007; Kojima et al. 2002; Tamaki et al. 2007), suggesting that the FT family genes encode the florigens. A florigen gene has some characteristics, such as (i) in leaf, the florigen mRNA are induced under day length conditions; (ii) the gene products move from the leaf to the shoot apex; (iii) the gene products can induce floral organ formation at the shoot apex, (iv) and the florigens are evolutionarily and functionally conserved in different species. In long-day and short-day plants, florigen is produced under inductive long- and short-day conditions, respectively. In this manner, in leaves, the florigen mRNA levels provide critical information about the status of floral transitions. Based on physiological evidences, different models for day-length recognition have been reported. First Dr. Erwin Bünning suggested that

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Short-day

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Long-day

Light-sensitive phase 12 h

Light-insensitive phase

(i) Bünning’s model Light-sensitive phase Various

Light-insensitive phase

(ii) External coincidence model

(iii) Internal coincidence model Fig. 20.1 Different models for day-length recognition. (i) Bünning’s model. The circadian clock set the lightsensitive phase during the second half of the day (evening and night). During the light-sensitive phase, plants perceive it as long day, when the light signal is present. (ii) The external coincidence model. In this model, the circadian clock set the light-sensitive phase, and the light signal during the light-sensitive phase is perceived as long

day as in Bünning’s model, but the light-sensitive phase is notably concise than in Bünning’s model. (iii) The internal coincidence model. The circadian clock, or circadian clock and other diurnal coexisting rhythms formed two distinct diurnal rhythms. The day length is recognized when the two rhythms overlap. Adopted by Osugi and Izawa (2014)

both light signal transduction cascades and the circadian clock are involved in the molecular recognition of day length (Fig. 20.1; Bünning, 1950). According to Bünning’s hypothesis, during the light-sensitive phase of circadian clocks, the plants recognize day length by perceiving (or not perceiving) the light. The light-sensitive phase happens during the evening and the night and corresponds to the second half of the day and by the circadian clock is reset at first morning. However, among plant species, Bünning’s model was inefficient to explain the variability in the

critical day length. Later, the ‘external coincidence model’ was proposed by Dr. Colin Pittendrigh (Fig. 20.1(ii); Pittendrigh and Minis 1964). According to this model, information about day length can provide by the light perceived during the light-sensitive phase. However, in external coincidence model, by the light stimulus, the light-sensitive phase is substantially shorter than 12 h and is entrained. Consequently, the light-sensitive phase can shift in response to the changing day length. Afterward, the ‘internal coincidence model’ was suggested by Pittendrigh

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(Fig. 20.1(iii); Pittendrigh 1966). According to this model, contribution of day-length recognition is occurred by an interaction between two differentially entrained circadian rhythms. Different studies on the molecular mechanisms support the external coincidence model. However, some other mechanisms support the internal coincidence model also. In plants, different biological processes are diurnally regulated, either by the coincidence of environmental stimuli with a specific time of the day or directly by the circadian clock. Pittendrigh (1966) proposed the ‘gating effect’ concept to explain the latter case. In this concept, when only the gate is ‘open’ then an external stimulus can be perceived. The diurnal rhythm of the gate is regulated mainly by the circadian clock, and only at a specific time of the day, the biological processes can be induced by external stimuli. In response to a given day length, the gate opening would be changed by either light-on or light-off signals, and the time of the gate opening depends on the day length at the presence of light. According to Nagano et al. (2012), when light conditions change greatly within a few hours, then the expression dynamics of many genes involved in day-length recognition and responsive to the fluctuations of the gate, the opening time is often set around dawn or dusk. The genetic nature of such gating effect may include transcription, protein abundance, or enzymatic activity at a specific time of the day. The effect of environmental factors such as photoperiod on floral induction in jute has not been adequately documented. This kind of knowledge is necessary to control the flowering process in jute. Genome-wide analysis indicates that jute has one florigen homolog gene of rice. FT gene, COLO4_32094 for Corchorus olitorius and CCACVL1_25746 for Corchorus capsularis, induces flowering under inductive short-day conditions. Jute has several CONSTANS (CO) homolog gene of rice, namely, COLO4_07847, COLO4_18994, COLO4_34123, COLO4_08017, COLO4_13331, COLO4_13201, COLO4_26042, COLO4_12998, COLO4_19655, COLO4_20602, COLO4_05971 for Corchorus olitorius and CCACVL1_29126, CCACVL1_23818, CCA

Md. W. Ullah and Md. S. Islam

CVL1_09754, CCACVL1_19565, CCACVL 1_14759, CCACVL1_23777, CCACVL1_10149, CCACVL1_16762, CCACVL1_24344, CCACV L1_16130, CCACVL1_24820, CCACVL 1_16782, CCACVL1_17834, CCACVL1_07649 for Corchorus capsularis. COLO4_32094 or CCACVL1_25746 of FT regulator control via CO or EHD1 (Early Heading Date 1) (or both). Eleven CO genes for Corchorus olitorius and 14 CO genes for Corchorus capsularis are jute homolog of the rice CO gene, which encodes a Zinc finger protein constans (Table 20.1). CO genes promote the expression of FT gene under short-day conditions but represses their expression under long-day conditions in jute (Fig. 20.2) as in rice (Kojima et al. 2002), whereas CO induces the expression of the Arabidopsis FT gene (a florigen gene in Arabidopsis) only under long-day conditions (Samach et al. 2000). In rice, Grain yield and heading date 7 (Ghd7) is a long-day-specific repressor identified through QTL mapping of plant height and grain yield traits (Yu et al. 2002; Xue et al. 2008). Introgressing a functional allele of Ghd7 from the indica rice ‘Minghui 63’ to ‘Zhenshan 97’ can cause pleiotropic phenotypes such as late flowering and increases in height, stem diameter, and yield (Yu et al. 2002; Xue et al. 2008). Ghd7 gene encodes a CO-like protein containing the B-box and CCT domains (Xue et al. 2008). Ghd7 gene inhibits flowering by suppressing the expression of Ehd1 (Xue et al. 2008). In the vascular bundle, Ghd7 is strongly expressed where Ehd1 is also expressed, providing evidence that Ghd7 functions upstream of Ehd1 (Xue et al. 2008). GIGANTEA (GI) is a specific nuclear protein and function in various physiological processes, e.g., flowering time regulation, light signaling, hypocotyl elongation, control of circadian rhythm, sucrose signaling, starch accumulation, chlorophyll accumulation, transpiration, herbicide tolerance, cold tolerance, drought tolerance, and miRNA processing. In Arabidopsis, GI controls CO, a positive regulator of FT (Fowler et al. 1999). The GI–CO–FT pathway is conserved in jute as in rice (Hayama et al. 2003). GI positively controls FT via CO and EHD1 expression at short day in jute (Fig. 20.2).

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313

Fig. 20.2 An outline of flowering pathway of jute using jute orthologs. Rice flowering pathway depicted by Andrés and Coupland (2012) was adapted for this study

20.3.2 Floral Induction in Jute by the Vernalization Pathway In plants, flowering is a critical developmental transition from vegetative to reproductive and this transition is not reversible. So, for successful reproduction, proper timing of flowering is crucial in plants. Therefore, plants have evolved several sophisticated mechanisms to incorporate changes in environmental cues, such as day length and temperature to control flowering time.

20.3.2.1 Definition of Vernalization Flowering plants can be classified into three groups, such as, annual, biennial, and perennial plants based on plants’ life cycles. Annual plants complete their life cycle within a year, whereas biennial plants usually take 2 years to complete their life cycle. Perennial plants live for more than 2 years. Vernalization is derived from the

Latin word vernus meaning ‘of the spring’, reflecting that most vernalization required winter annual and biennial plants’ flower in the spring. According to Chouard (1960), vernalization is ‘the acquisition or acceleration of the ability to flower by a chilling treatment’. By vernalization, the promotion of flowering is the result of subjecting an imbibed seed or young plant to a long period of cold. Generally, cold treatment does not initiate flower in plants but only after returning the plant to a higher temperature. Accordingly, cold temperatures do not cause plants to initiate floral primordia but create the capacity for subsequent flowering. In plants, vernalization can be facultative or obligate. In winter annual plants, facultative vernalization is required, as cold accelerates, but this is not required for flowering. On the other hand, in biennial plants, flower cannot have occurred without cold treatment and, therefore, have an obligate requirement for vernalization.

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20.3.2.2 Molecular Analysis of Vernalization Pathway in Jute Most temperate plants, including Arabidopsis, wheat (Triticum spp.), and barley (Hordeum vulgare), require prolonged exposure to cold temperatures before flowering. Since jute like as rice was domesticated in tropical regions, it does not show vernalization responses. However, it is an important adaptation for species and varieties adapted to higher latitudes, because if the temperature is unfavorable, it prevents flowering, thus protecting the delicate inflorescence meristem from cold damage. FRIGIDA (FRI) and FLOWERING LOCUS C (FLC) were discovered by the study of Arabidopsis vernalization (Sheldon et al. 1999; Johanson et al. 2000). Intensive study was conducted in Arabidopsis to understand the genetic and molecular bases of vernalization responses, and it was observed that two genes, FRI and FLC, play a vital role in preventing flowering before cold exposure (Ream et al. 2012). Those plants experiencing low temperatures suppress FLC expression and maintain its repression also when returned to warm temperatures. Downregulation of FLC expression is associated with epigenetic silencing of FLC chromatin that is altered from active to inactive (Song et al. 2012). Genome-wide analysis of jute observed that only one copy of FRI, COLO4_37292 for Corchorus olitorius and CCACVL1_05824 for Corchorus capsularis was present. Moreover, nine (COLO4_34278, COLO4_34901, COLO4_152 96, COLO4_11512, COLO4_36065, COLO 4_09781, COLO4_21479, COLO4_36066, COL O4_36068) and 7 (CCACVL1_21527, CCACV L1_07250, CCACVL1_11274, CCACVL 1_12787, CCACVL1_07252, CCACVL1_07249, CCACVL1_09437) FRL (FRIGIDA LIKE, FRL) genes were present in Corchorus olitorius and C. capsularis, respectively. In both jute genomes, we have identified the homologs of FLC gene, COLO4_20430 for Corchorus olitorius and CCACVL1_10206 for C. capsularis (Table 20.1). In Arabidopsis, molecular analysis has revealed that the presence of active FRI alleles leads to an increased level of FLC mRNA

Md. W. Ullah and Md. S. Islam

expression. This accounts for the function of FRI, as early flowering null alleles of flc are epistatic to FRI (Michaels and Amasino 2001). FRI encodes a plant-specific coiled-coil domain protein and is a member of a small group of related FRL genes (Johanson et al. 2000; Michaels et al. 2004). Activation of FRL1 (one of the FRL genes) gene is required for FRI to upregulate FLC expression, but FRL1 itself is not sufficient to delay flowering as the overexpression of FRL1 does not delay flowering in an early flowering accession (Michaels et al. 2004). FLC contributes a major role in vernalization pathway and it has a potent repressive effect on flowering time, and its ability to be downregulated by exposure to low temperatures (Sheldon et al. 1999). The initial repress in FLC expression is mediated by the VERNALIZATION INSENSITIVE 3 (VIN3) gene (Sung and Amasino 2004). It is thought that in the vernalization process, the VIN3 gene is induced by long periods of cold treatment. We have identified four (COLO4_24182, COLO4_35254, COLO4_34883, and COLO4_37734) and two (CCACVL1_18075 and CCACVL1_30263) Arabidopsis VIN3 homologous in Corchorus olitorius and in C. capsularis, respectively. In both jute genomes, the homologous of VRN2 (Polycomb group protein vernalization 2) genes, COLO4_10019, COLO4_37330, and COLO4_37126 for Corchorus olitorius and CCACVL1_24757, CCACVL1_057 91 for C. capsularis were identified. Under cold induced vernalization, both VIN3 and VRN2 repress FLC expression (Sung and Amasino 2004; Gendall et al. 2001) that also support our proposed flowering development pathway in jute (Fig. 20.3). Vernalization pathway may not response in jute, because of the tropically domesticated crop. However, adaptation is important for species and varieties in an unfavorable environment such as cold temperature to prevent flowering, thus protecting floral organ from cold injury. In Arabidopsis, cereals and other plants, vernalization requirement has been evolved independently. This variation in the conservation of different aspects of flowering-time control might be explained by the number of possible alternative targets that could confer a vernalization requirement.

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315

Fig. 20.3 Flowering development pathway of jute

20.3.3 Floral Induction in Jute by the Autonomous Pathway After vernalization, the autonomous pathway is the second group of factors, which suppress FLC expression. Simpson (2004) described the autonomous pathway as a genetic pathway that regulates flowering time independently of photoperiod and has a role to determine FLC mRNA expression levels. To date, eight autonomous pathway genes have been identified, including FLOWERING CONTROL LOCUS A (FCA), FLOWERING LOCUS Y (FY), FPA, FVE/MIS4 (MULTICOPY SUPPRESSOR OF IRA1 4), LUMINIDEPENDENS (LD), FLOWERING LOCUS D (FLD), FLOWERING LOCUS K (FLK) and RELATIVE OF EARLY FLOWERING

6 (REF6). The genome-wide analysis in jute all autonomous pathway-related genes are present except FY and REF6 (Fig. 20.3). None of the autonomous pathway components appears to regulate one another, suggesting that this pathway is a genetically defined ‘pathway’ and not a pathway in the sense of a sequential series of biochemical changes (Simpson 2004). All autonomous pathway members repress the FLC expression (Michaels and Amasino 2001), but it is still unclear how they regulate FLC. Some autonomous members such as FCA, FPA, and FLK encode RNA-binding or RNA-processing factors, revealing that they may act to regulate FLC mRNA synthesis. However, a direct effect on FLC mRNA has not been demonstrated (Macknight et al. 1997; Schomburg et al. 2001; Lim et al. 2004). One of the autonomous

316

members, LD encodes a homeodomain protein (Lee et al., 1994) but it remains unclear what DNA target LD binds. It was observed that both FVE and FLD are required for the normal deacetylation of histone 3 and/or histone 4 at the FLC gene, they encode putative components of a histone deacetylase complex (He et al. 2003; Ausin et al. 2004). In jute, the homologous of FCA, COLO4_34585 and COLO4_23202 for Corchorus olitorius and CCACVL1_28613 and CCACVL1_22103 for C. capsularis has been identified. Two and three copies of FPA homologous were identified in Corchorus olitorius and in C. capsularis, respectively (Table 20.1). In Corchorus olitorius and in C. capsularis, two and one copies of FVE homologous were identified, respectively. In each jute genome, one and four copies of LD and FLD homologous genes were identified, respectively. Most of the copies of autonomous gene, FLK homologous were identified in Corchorus olitorius (14 copies) and in C. capsularis (13 copies), respectively (Table 20.1). All of the identified homolog of FCA, FPA, FVE, LD, FLD, and FLK in jute suppress FLC expression (Fig. 20.3) that support previous report (Michaels and Amasino 2001). The reported data suggested that the autonomous pathway genes act primarily on FLC because a mutation in the FLC gene completely suppresses the late-flowering phenotype. However, it was reported that some autonomous pathway genes are also involved in other developmental processes in plants, including seed germination (Baurle et al. 2007; Veley and Michaels 2008; Auge et al. 2018). Therefore, it is likely that there might be still unidentified functions of the autonomous pathway genes in plant developmental programs.

20.3.4 Floral Induction in Jute by the Endogenous Signal/Hormonal Pathway Plant hormones influence many diverse developmental processes ranging from seed

Md. W. Ullah and Md. S. Islam

germination to root, shoot and flower formation (McCourt 1999). The recent advances have been made in understanding the molecular basis underlying the regulation of flowering by plant hormones. In this arena, most progress has been made in model plant species such as Arabidopsis thaliana. Based on this model plant, we will have discussed the endogenous pathway-related genes in jute that were identified by genome analysis.

20.3.4.1 Gibberellic Acid (GA) The phytohormones, gibberellins are involved in plant growth and development, including seed germination, hypocotyl elongation, chlorophyll biosynthesis, and flowering induction (Yamaguchi 2008). GA signaling pathway is tightly interconnected with other hormonal signaling pathways. So, it is possible that other hormones control the flowering transition indirectly by modulating GA biosynthesis and signaling. Mutations in the genes involved in either GA biosynthesis or the GA signaling pathway result in alterations in flowering time in Arabidopsis (Blazquez et al. 1998, 2002). For example, the mutant ga1-3, which does not produce GA, fails to induce flower under short-day conditions and displays a delay in flowering under long-day conditions (Mutasa-Gottgens and Hedden 2009). GA may be act independently of the photoperiod pathway because the delayed flowering in ga1 mutants is relatively minor under long-day conditions compared to short-day conditions. Moreover, Reeves and Coupland (2001) revealed that a double mutant of ga1 with the photoperiod mutant co (constans) displays an extremely delayed flowering in long-day conditions. In jute, GA promotes flowering by promoting the expression of the floral integrators, such as LFY (LEAFY), via AGL20 (agamous-like 20) and the MYB33 (Myb domain protein 33) (Achard et al. 2004). Thus, GA-induced flowering pathways independently promote floral transition by activating the expression of floral integrators such as LFY, AGL20, and MYB33 (Fig. 20.3). 20.3.4.2 Ethylene Ethylene plays an important role throughout the entire plant life cycle, from germination and

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photomorphogenesis to senescence and fruits ripening. Ethylene signaling mutant plants is late flowering, implicating these plant growth regulators in floral signaling pathways (Ogawara et al. 2003). In both jute genome, the homologs of EIN3 (Ethylene insensitive 3) and the D8 (Della protein dwarf 8) gene were identified (Table 20.1). It was observed that ethylene represses flowering by suppressing the expression of the LFY gene, via EIN3 and the D8 (Achard et al. 2007) in jute (Fig. 20.3). Therefore, ethylene has been found to suppress flowering in jute and also observed in Xanthium pensylvanicum, Pharbitis nil, rice, Lotus and A. thaliana (Abeles 1967; Chan et al. 2013; Suge 1972; Wang et al. 2013; Wuriyanghan et al. 2009).

20.3.4.3 Abscisic Acid (ABA) ABA is a plant hormone known for its prominent role in different developmental stages and adaptation to environmental stress across the plant life cycle, which is synthesized from carotenoids. Mutants that reduce ABA biosynthesis are earlier flowering under non-inductive conditions, suggesting that ABA inhibits flowering (MartinezZapater et al. 1994). It was reported that ABA signaling mutants, abi1 (ABA insensitive 1) (Koornneef et al. 1984; Leung et al. 1997) and abi2 (ABA insensitive 2) (Koornneef et al. 1984; Leung et al. 1997) have been shown to reduce the flowering time of Arabidopsis fca-1 mutants (Chandler et al. 2000; Boss et al. 2004). MicroRNA 159 (miR159) is a core microRNA family that is conserved in ancient terrestrial plant and in modern day plant species (Axtell and Bartel 2005). It is known to post-transcriptionally regulate GAMYB-like genes and function in leaf, flower, and seed maturation (Cheng et al. 2004; Millar and Gubler 2005; Tsuji et al. 2006; Reyes and Chua 2007). Reyes and Chua (2007) revealed that ABA represses MYB33 by the accumulation of miR159 in Arabidopsis. Moreover, under short-day condition overexpression of miR159 in the Landsberg erecta ecotype of Arabidopsis reduced MYB33 transcript levels and delayed flowering (Achard et al. 2004). We have identified the homologs of miR159 in jute

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that accumulate by ABA induction and also suppress MYB33 gene expression and regulate the flowering in jute (Table 20.1 and Fig. 20.3).

20.4

Conclusions

Flowering pathways of jute in this chapter represent only a skeletal framework, which helps to understand the basic molecular mechanism of flowering regulatory networks and understanding of interacting pathways that promote flowering in response to different environmental cues. The future work will focus on understanding the biochemical function of pathway components and the process in which the signaling pathways convey information that regulates flowering in jute. The proposed pathway has given rise to opportunities for the improvement of day-neutral jute plants and widened the scope of potential applications for further development of jute yield and quality.

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319 McCourt P (1999) Genetic analysis of hormone signalling. Annu Rev Plant Physiol Plant Mol Biol 50:219–243 Michaels SD, Amasino RM (2001) Loss of FLOWERING LOCUS C activity eliminates the late-flowering phenotype of FRIGIDA and autonomous pathway mutations but not responsiveness to vernalization. Plant Cell 13:935–941 Michaels SD, Bezerra IC, Amasino RM (2004) FRIGIDA-related genes are required for the winterannual habit in Arabidopsis. Proc Natl Acad Sci USA 101:3281–3285 Millar AA, Gubler F (2005) The Arabidopsis GAMYBlike genes, MYB33 and MYB65, are microRNAregulated genes that redundantly facilitate anther development. Plant Cell 17:705–721 Mutasa-Gottgens E, Hedden P (2009) Gibberellin as a factor in floral regulatory networks. J Exp Bot 60:1979–1989 Nagano AJ, Sato Y, Mihara M, Antonio BA, Motoyama R, Itoh H et al (2012) Deciphering and prediction of transcriptome dynamics under fluctuating field conditions. Cell 151:1358–1369 Ogawara T, Higashi K, Kamada H, Ezura H (2003) Ethylene advances the transition from vegetative growth to flowering in Arabidopsis thaliana. J Plant Physiol 160:1335–1340 Osugi A and Izawa T (2014) Critical Gates in Day-Length Recognition to Control the Photoperiodic Flowering. In: Fornara F (ed) Advances in botanical research: the molecular genetics of floral transition and flower development, vol 72, pp 110–137. Elsevier, Academic Press, UK Pittendrigh CS (1966) The circadian oscillation in Drosophila pseudoobscura pupae: a model for the photoperiodic clock. Zeitschrift Fuer Pflanzenphysiologie 54:275–307 Pittendrigh CS, Minis DH (1964) The entrainment of circadian oscillations by light and their role as photoperiodic clocks. Am Nat 98:261–294 Reeves PH, Coupland G (2001) Analysis of flowering time control in Arabidopsis by comparison of double and triple mutants. Plant Physiol 126:1085–1091 Ream TS, Woods DP, Amasino RM (2012) The molecular basis of vernalization in different plant groups. Cold Spring Harb Symp Quant Biol 77:105–115 Regal PJ (1977) Ecology and evolution of flowering plant dominance. Science 196:622–629 Reyes JL, Chua NH (2007) ABA induction of miR159 controls transcript levels of two MYB factors during Arabidopsis seed germination. Plant J 49:592–606 Samach A, Onouchi H, Gold SE, Ditta GS, SchwarzSommer Z, Yanofsky MF et al (2000) Distinct roles of CONSTANS target genes in reproductive development of Arabidopsis. Science 288:1613–1616 Schomburg FM, Patton DA, Amasino MDW, RM, (2001) FPA, a gene involved in floral induction in Arabidopsis, encodes a protein containing RNA-recognition motifs. Plant Cell 13:1427–1436

320 Seo PJ, Ryu J, Kang SK, Park CM (2011) Modulation of sugar metabolism by an INDETERMINATE DOMAIN transcription factor contributes to photoperiodic flowering in Arabidopsis. Plant J 65:418–429. https://doi.org/10.1111/j.1365313X.2010.04432.x Sheldon CC, Burn JE, Perez PP, Metzger J, Edwards JA, Peacock WJ, Dennis ES (1999) The FLF MADS box gene: a repressor of flowering in Arabidopsis regulated by vernalization and methylation. Plant Cell 11:445–458 Simpson GG (2004) The autonomous pathway: epigenetic and posttranscriptional gene regulation in the control of Arabidopsis flowering time. Curr Opin Plant Biol 7:570–574 Song J, Angel A, Howard M, Dean C (2012) Vernalization—a cold-induced epigenetic switch. J Cell Sci 125:3723–3731 Song YH, Ito S, Imaizumi T (2013) Flowering time regulation: photoperiod- and temperature-sensing in leaves. Trends Plant Sci 18:575–583. https://doi.org/ 10.1016/j.tplants.2013.05.003 Suge H (1972) Inhibition of photoperiodic floral induction in Pharbitis nil by ethylene. Plant Cell Physiol 13 (6):1031–1038 Sung S, Amasino RM (2004) Vernalization in Arabidopsis thaliana is mediated by the PHD finger protein VIN3. Nature 427:159–164 Susila H, Nasim Z, Ahn JH (2018) Ambient temperatureresponsive mechanisms coordinate regulation of flowering time. Int J Mol Sci 19:3196. https://doi.org/10. 3390/ijms19103196 Tamaki S, Matsuo S, Wong HL, Yokoi S, Shimamoto K (2007) Hd3a protein is a mobile flowering signal in rice. Science 316:1033–1036 Thomas B, Carre I, Jackson S. (2006) Photoperiodism and flowering. In: Jordan B (ed) The molecular biology and biotechnology of flowering, 2nd edn. CAB International, UK, Biddles Ltd, King’s Lynn

Md. W. Ullah and Md. S. Islam Tsuji H, Aya K, Ueguchi-Tanaka M et al (2006) GAMYB controls different sets of genes and is differentially regulated by microRNA in aleurone cells and anthers. Plant J 47:427–444 Veley KM, Michaels SD (2008) Functional redundancy and new roles for genes of the autonomous floralpromotion pathway. Plant Physiol 147:682–695. https://doi.org/10.1104/pp.108.118927 Wahl V, Ponnu J, Schlereth A, Arrivault S, Langenecker T, Franke A, Feil R, Lunn JE, Stitt M, Schmid M (2013) Regulation of flowering by trehalose-6-phosphate signaling in Arabidopsis thaliana. Science 339:704–707. https://doi.org/10.1126/ science.1230406 Wang Q, Zhang W, Yin Z, Wen CK (2013) Rice CONSTITUTIVE TRIPLE-RESPONSE2 is involved in the ethylene-receptor signalling and regulation of various aspects of rice growth and development. J Exp Bot 64(16):4863–4875 Weigel D, Alvarez J, Smyth DR, Meyerowitz YMF, EM, (1992) Leafy controls floral meristem identity in Arabidopsis. Cell 69:843–859 Wuriyanghan H, Zhang B, Cao WH, Ma B, Lei G, Liu YF, Wei W, Wu WJ, Chen LJ, Chen HW, Cao YR, He SJ, Zhang WK, Wang XJ, Chen SY, Zhang JS (2009) The ethylene receptor ETR2 delays floral transition and affects starch accumulation in rice. Plant Cell 21(5):1473–1494 Xue W, Xing Y, Weng X, Zhao Y, Tang W, Wang L, Zhou H, Yu S, Xu C, Li X, Zhang Q (2008) Natural variation in Ghd7 is an important regulator of heading date and yield potential in rice. Nat Genet 40:761–767 Yamaguchi S (2008) Gibberellin metabolism and its regulation. Annu Rev Plant Biol 59:225–251 Yu SB, Li JX, Xu CG, Tan YF, Li XH, Zhang Q (2002) Identification of quantitative trait loci and epistatic interactions for plant height and heading date in rice. Theor Appl Genet 104:619–625

Power of Molecular Markers and Genomics Technology in Jute Breeding

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Pratik Satya, Debabrata Sarkar, Chandan Sourav Kar, Dipnarayan Saha, Subhojit Datta, Surendra Kumar Pandey, Amit Bera, and Jiban Mitra

Abstract

Molecular markers and genomic resources are integral components of current plant breeding programmes. During the past decades, genomic researches in jute predominantly focussed on the genome and transcriptome sequencing, characterization of genes, development of molecular markers, and use of these resources for linkage map construction, germplasm characterization, phylogenetic analyses, population structure analysis, and cultivar differentiation. However, their direct applications in jute breeding are limited. Major reasons for such slow progress in jute molecular breeding lie in the biological complexity of economically important traits and unusual breeding objectives that are quite different from those of other major crops. In this chapter, we first provided an introduction on jute from the viewpoint of a plant breeder identifying the major constraints in jute breeding, followed by a summary of the developments in molecular marker and genomic researches in jute, and finally identified some potential areas where the application of marker and genomics

P. Satya (&)
D. Sarkar
C. S. Kar
D. Saha
S. Datta
S. K. Pandey
A. Bera
J. Mitra ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata 700121, India

technologies can aid in developing improved genotypes for versatile future applications.

21.1

Introduction

To satisfy the growing demand of the human population, plant breeders require to develop new high-yielding cultivars adapted to specific environments, improve the quality of the economic product, introduce resistance to pests and pathogens, adjust crop ideotype to suit the changing climate, and fit/introduce crops according to the demand of the consumer. Today, plant breeding must placate the market demand by increasing productivity, product quality, and climate resilience of the crop (Brozynska et al. 2016). Ultimately, a new cultivar is only adopted by the farmers if it adds a net profit to their business of agriculture. The reproductive storage tissue (endosperm) is the major economic product for most of the major cultivated crops. As a plant has a direct physiological source–sink relationship between the food-producing organs (leaves and stem) and the reproductive/vegetative storage organ, breeding of these crops is the selection of the genotypes that channel more food to the sink. In contrast, breeding crops, where reproductive/storage sink is not the economic product is more challenging, as the plant does not have specific source–sink relationship to transfer photosynthate to the tissues of economic importance. For most of the fibre crops, the fibre

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_21

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tissue does not serve as a reproductive/storage sink, as it is a modified vascular tissue present within the bast (jute, kenaf, flax, ramie) or leaf (Agave) providing mechanical support to the stem or the leaf. To date, a direct source–sink relationship that contributes solely to fibre biosynthesis in these crops has not been established. Breeding for jute (Corchorus olitorius L. and C. capsularis L.), a bast fibre crop, therefore, is challenging and should be viewed from a perspective different from that of major crop plants. Though molecular markers and genomic resources have numerous applications in current plant breeding programmes, an in-depth understanding of the biology and economics of jute is necessary to integrate these tools in jute crop improvement. Our next challenges will be bidirectional, to design efficient and effective breeding programmes integrating existing molecular resources, and upgrade the molecular resource database of jute according to the need of nextgeneration jute-breeding programs. As this book itself describes in detail the genomic resources developed in jute, we will not reiterate the status of its genomic resources in detail in this chapter. Also, for a detailed discussion of molecular markers developed in jute please refer to Satya and Chakraborty (2015) and Sarkar et al. (2016). Rather, we will first have a relook into jute from a plant breeder’s viewpoint identifying the major challenges in jute breeding, followed by a brief update on the molecular resources for use in jute breeding, and finally, synthesize from this information, the potential applications of marker and genomic resource enriched jute breeding in coming decades.

21.2

Jute: A Short Introduction for the Plant Breeders

The jute fibre is commercially obtained from two morphologically similar species, tossa jute (Corchorus olitorius L.) and white jute (C. capsularis L.). Jute is produced primarily in India (1.77 million tonnes), Bangladesh (1.57 million tonnes), China (0.3 million tonnes), and to some extent in Nepal, Uzbekistan, Egypt, Zimbabwe,

Bhutan, Pakistan, Cambodia, Viet Nam, South Sudan, and Peru (FAOSTAT average production during 2017–19, http://www.fao.org/faostat/en/ #data). C. olitorius is the major cultivated species for producing jute fibre. However, it is consumed as leafy vegetable in many African and Asian countries. C. capsularis is grown in specific pockets in India and Bangladesh and most jute growing belts of China. The fibre-type jute genotypes are branchless/sparsely branched when grown in long day, reaching a height of 3– 5 m within 120 days, and if not harvested, flowers at 150–160 days’ age (Satya et al. 2014a). The leafy vegetable ecotype is branched, bushy (0.3–0.5 m plant height), and flowers within 35–45 days (Nyadanu et al. 2016). While the history of the fibre-type jute cultivation can be traced back at least to Medieval India, it was sporadically cultivated as a minor fibre crop in the Gangetic delta until the East India Company, in 1793, sent jute fibre to England under the name ‘pat’ for spinning, considering it as a variant of flax (Dodge 1897). The botanical identities of jute as Corchorus capsularis L. and Corchorus olitorius L. were established by Roxburgh in 1795, and in 1828, 18 tons of this fibre were first commercially exported under the name jute (Carter 1921). By 1870–71, jute export volume expanded to 3,10,000 tons, practically putting the European flax and hemp industries out of business. Large-scale cultivation of the jute crop became a steady business in the Bengal province of India, which flourished rapidly during the late nineteenth century and was a premium export earner for India during the first half of the twentieth century. The invention of synthetic fibres, partition of the Bengal province during the independence of India, and introduction of high-yielding short duration rice in jutebased cropping system caused serious damages to the production and business of jute fibre in the second half of the twentieth century. In the recent decades, jute is gradually regaining its importance not only as a fibre crop but also as vegetable, bioenergy crop, and climate-smart crop, for it is perhaps the only crop, which, by occupying one-hectare land for 4 months provides over 3 tons of natural fibre, produces 20 tonnes

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of dry biomass, consumes 15 tonnes of CO2, adds 11 tonnes of O2 and fertilizes soil by adding 4 tonnes of organic matter (Palit and Meshram 2008; Satya and Maiti 2013; Mukul and Akter 2021). Genetic improvement of jute was initiated during the early nineteenth century in India by purification of the local races, resulting in the development of pure line selections like D154 and Chinsurah Green that dominated the jute growing regions till the 1970s until the new ideotypes befitting to the jute-rice cropping systems were developed by hybridizing the C. olitorius cultivars with African landraces that can be sown early during mid-March. This reversed the early C. capsularis dominated jute cultivation practice, enabling the higher yielding shortduration C. olitorius cultivars to be cultivated over 90% of the jute area. Although C. olitorius is more productive, its fibre is coarser and contains more lignin than that of C. capsularis. Therefore, the current fibre-type jute breeding programme is dwindling over two ambitious targets, namely, the development of C. capsularis cultivars that can match the yield potential of C. olitorius and the breeding of C. olitorius cultivars that can match the fibre quality of C. capsularis. A jute ideotype combining the desirable traits of both species is a long term, yet unachieved goal in jute breeding.

21.2.1 Taxonomy and Distribution The genus Corchorus is a member of the family Malvaceae (subfamily Grewoideae) comprising approximately 40–100 species distributed throughout the tropical and subtropical regions of the world, with the highest diversity in African subtropical regions (Sinha et al. 2011). Of these, only two species, C. olitorius and C. capsularis, are cultivated. Some of the wild Corchorus species have ethnomedicinal uses (Sinha et al., 2011). Molecular studies confirmed an African origin of C. olitorius (Benor et al. 2012; Satya et al. 2014a; Sarkar et al. 2019), while the origin of C. capsularis is still debated (Zhang et al., 2019), although molecular evidence (Benor et al. 2012; Sarkar et al. 2019) and geographical

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support for an African origin of most of the wild Corchorus species (Dempsey 1975) suggest that C. capsularis might have also originated in Africa and was later domesticated in Indo-Burma region as a fibre crop.

21.2.2 Botany and Ideotype The jute fibre is produced from fibre-type ecotypes of two closely related but sexually isolated annual diploid species C. capsularis L. (white jute, 2n = 14) and C. olitorius L. (tossa jute, 2n = 14). Both the species are similar in appearance but can be distinguished easily from their pod shape and taste of leaves. C. olitorius is more vigorous in growth and has an elongated (*5 cm) pod, while C. capsularis has a round (*1 cm diameter) pod. The leaves of C. capsularis taste bitter when chewed. The two species have slightly different adaptations; C. capsularis with more tolerance to waterlogging is suitable for low-lying areas, whereas C. olitorius grows well on up- and medium lands and has a higher tolerance to drought stress (Maiti et al. 2017). C. olitorius is the principal cultivated jute crop occupying over 90% of the area. The fibre of C. capsularis is comparatively finer with less lignin (10–13%) but has lower strength than that of C. olitorius. The fibre-type ecotypes of both the species do not flower or produce branches under long day, but profuse branching with numerous flowers can be seen under short day. The wildtype C. olitorius exhibit photo-insensitivity to a certain extent, producing flower and seed throughout the year in tropical locations, particularly peninsular India (Sarkar et al. 2019).

21.2.3 Biology of the Economic Product Jute fibre, the principal economic product of the jute plant, is formed in the secondary phloem of the stem, surrounding the woody xylem core in a tapering wedge-like fashion (Kundu et al. 2012). The fibre bundles occupy a significant part of the phloem tissue (30–40%) thereby limiting the

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potential of phloem transport, which is again a challenging issue for jute breeders. An increase in the fibre content in the bast will invariably impede phloem transport, thereby negatively affecting the growth and development of the plant, which, in turn, will reduce the total fibre production in that plant. Therefore, improving the fibre yield by increasing the fibre: bast volume may not be a practical breeding objective. Jute breeders, therefore, have resorted to increasing the fibre yield by making the stem taller and thicker by selecting genotypes based on plant height and basal diameter. A plant taller than the height of the present cultivars (4–5 m) would require a more robust root system for withstanding the wind pressure and stormy weather that prevail in the monsoon season (June–July) during the active growth phase of jute. Moreover, such jute cultivars may not be suitable for growing jute in loose sandy loam soil, due to poorer root adherence. A sturdy root system with the ability to withstand powerful stormy weather is an important, yet neglected trait in the current jute breeding programme. In addition, planting density, a non-heritable determinant also affects fibre yield and quality (Johansen et al. 1985). The pattern of fibre development in jute is also different from other bast fibre crops like flax and ramie. In flax, fibre maturity period (deposition of cellulosic material in the fibre cell wall) starts after completion of the fibre development phase (growth and elongation of the cell), and fibre is formed in the primary phloem. Therefore, in a growing flax plant, fibre maturation takes place in the middle and the basal region of the stem, while new fibre cells form in the apical region of the stem. In contrast, fibre development in jute is both longitudinal and radial, i.e., at a given time, fibre development and fibre maturation take place throughout the plant (Maiti et al. 2017). The basal region of the stem, therefore, has fibre cells, some of which are actively growing, some exhibiting both growth and maturity, and others who have completed growth but cellulosic materials are being deposited. Such complex growth pattern indeed makes tissue-specific genetic engineering of fibre-related traits quite

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challenging. Chemically, the fibre is lignocellulosic, containing 70–75% cellulose, 10–15% lignin, and 12–15% hemicellulose. Each fibre cell (ultimate fibre) is a longitudinal rod (2–5 mm long, 0.01–0.025 mm wide), with the outer surface being polygonal instead of cylindrical, with tapering end. The fibre cells are grouped into fibre bundles (30–60 cells per bundle) that are held together by the interaction of lignin and pectin (Satya et al. 2021). These bundles are joined together end to end to form the technical fibre length (1500–3500 mm) that runs throughout the bast tissue. When the fibre is spun, it breaks into pieces of spinnable technical fibre length (150– 360 mm), which is the final product.

21.2.4 Genetics of Economically Important Traits The history of genetic analysis in jute can be traced back to 1912 when Burkil and Finlow first reported a monogenic inheritance of stem pigmentation. Later, several grades of pigmentations were reported to be controlled by complex inheritance mechanisms, including multiple alleles, modifier genes, regulatory genes, and quantitative inheritance (Basak 1993). Although stem pigmentation is an important character for cultivar identification, it has little economic importance, as both pigmented and nonpigmented cultivars can be high-yielding. The major domestication-related traits in jute are tall plant, non-shattering pod, non-branching plant type under long day and absence of flowering under long day. Transition to the non-shattering pod from the shattering pod is a common sign of domestication of major crops. Several germplasm accessions of jute are shattering type, but the cultivars have non-shattering pods. Nonshattering habit is dominant over shattering habit, with monogenic inheritance. Most of the economic characters in jute are controlled by quantitative gene action. Several mating designs, including line x tester, diallel and triallel were used to partition the genetic variance into additive and dominance components. Heritability of fibre yield is very low in C. olitorius (4–38%)

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and is controlled more by dominance gene action (Basak 1993). Furthermore, extreme variability in the heritability of fibre yield (9–90%) was noted for C. capsularis (Basak 1993), suggesting that direct selection for fibre yield would be ineffective. The contribution of plant height and basal diameter in fibre yield was first conclusively described by Ghosh and Patel (Maiti and Chakravarty 1977). Some other characters such as biomass, internode length, and node number have a good correlation with fibre yield. Plant height is also controlled by both additive and dominant gene actions. However, wide variation in its heritability (12–81%) was observed in different studies, depending on the number of parents, mating designs, and approaches for data analysis (Basak 1993). Zhang et al. (2019) also listed the heritability of 11 quantitative characters that ranged from 26.3 to 94.3%. A moderate heritability of 59% was observed for plant height. Since jute has to fit the rice-based cropping system in India and Bangladesh, some farmers tend to sow jute seed early (1st fortnight of March) to accommodate transplanting of rice in mid-June. As jute flowers under short day, early sowing in March often results in early flowering and branching of the young plant, a condition often termed as ‘premature flowering’ (Kumar and Palve 2002; Begam and Kumar 2014), a misnomer, since jute crop do not mature during its cultivation and the term ‘maturity’ is inappropriate for jute (Basak 1993). A more appropriate term for this condition should be ‘earliness in flowering’, a measurable quantitative trait (number of plants flowered in a crop stand). Earliness in flowering reduces fibre yield and deteriorates fibre quality by producing knotty fibre at branch points. C. capsularis cultivars exhibit an absence of earliness in flowering when sown in early March in the Indian subcontinent, while C. olitorius cultivars show variable (3–80%) earliness in flowering. Absence/reduction in earliness of flowering is a desirable trait in current jute breeding programmes. Several studies showed that this trait is influenced more by epistatic and dominant gene actions, with a moderate (61%) heritability (Basak 1993).

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21.2.5 Breeding Methods Fibre yield and fibre quality are the major traits targeted in jute breeding programmes. Since the estimation of fibre content requires the harvesting of the plant at the vegetative stage, direct selection for fibre yield cannot be performed in a breeding programme based on single plant selection. Two component characters, plant height and base diameter are extensively used in jute-breeding programmes. In a strict pedigree selection-based breeding programme, the plants are grown in long day and allowed to complete the vegetative phase, so that the breeder can select the best progeny based on plant height and basal diameter, and then the selected lines are allowed to complete the reproductive phase to harvest seed of the selected lines. In such a case, the seed-to-seed maturity period extends over 180 days as sowing is done in April–May. An alternate option is to practice bulking at early segregating generations with no apparent selection, followed by single plant selection at later generations. In such a case, a shorter growth cycle (seed to seed maturity 120 days) can be achieved by raising the plant in short-day conditions. Under tropical environment, jute flowers in long-day condition, which allows the breeders to expedite the breeding programme by growing two generations in a year. However, under such conditions, selection for fibre yield or its component characters cannot be practised as the plants produce profuse branches and flower very early. A shuttle breeding scheme by growing jute at subtropical locations of Eastern India and tropical locations of Southern India is often utilized in the Indian jute-breeding programmes. To introduce new variation in the breeding population, mutation breeding has been successfully adopted resulting in development of many mutant cultivars (KOM 62, JRC-7447, Bidhan Rupali and JROB-2). A number of mutants maintained in the Indian germplasm repository contain important traits such as low lignin, high base diameter, long fibre wedge, and more fibre cells (Kundu et al. 2012; Satya et al. 2014b).

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Constraints to Genetic Improvement of Jute

21.3.1 Recent Domestication Most of the crop plants were domesticated over 10,000 years ago. Almost all of these are cultivated over large areas in different ecology for at least the past 2,000 years. In contrast, the fibre-type ecotype of jute was domesticated only in the eastern regions of Indian subcontinent around 2000 years ago and has been put under large-scale cultivation only about 220–240 years ago in colonial India. Within such a small timeframe jute area grew from a few hundred hectares to about 0.2 million hectares, most of the area being occupied by a few mega cultivars (Yang et al. 2018). Therefore, the modernday jute cultivars have not undergone through a long phase of domestication process, and only a small fraction of cultivar variability was retained during rapid expansion of cultivation. Consequently, many undesirable alleles, which have been filtered during long domestication processes in other crops, might not have been removed from the jute genome. However, a number of domesticationrelated traits, such as shattering pod, branching habit, and dwarf stature, were selected against during its short and sporadic cultivation period, indicating that jute is, at least, a semi-domesticated crop. Furthermore, due to its high economic importance, leading fibre-type cultivars of jute were introduced and tested for domestication in many countries including Europe, South East Asia, China, USA, Brazil, and Australia within the past 300 years (Satya et al. 2014a).

21.3.2 Low Genetic Diversity Average genetic diversity in the jute cultivars varies between 2.2 and 13.8% (Rana et al. 2013). Several estimates revealed low to moderate allelic polymorphism and low genetic diversity in jute (Benor et al. 2012; Satya et al. 2014a; Sarkar et al. 2019). A more detailed account of marker polymorphism in jute is presented in Sect. 21.5.3. Such low allelic polymorphism is a major constraint in

constructing robust genetic map, identification of QTLs and marker-assisted selection, thereby limiting the applications of molecular markers and genomic resources in jute breeding.

21.3.3 Depletion of Natural Genetic Variation Due to Unique Cultivation Practice Typically, jute crop is harvested before reproductive maturity to obtain fibre but a cultivar’s genetic identity is maintained through sexual reproduction. Therefore, jute has to be grown twice, first for fibre production under long day and then for seed production under short day. India and Bangladesh are the two major producers of jute contributing over 90% of the World’s jute production. Till 1950–1960, jute was grown only once in a year as a sole crop in these countries spanning a duration of 160–175 days (from April–May to August–September). Farmers used to harvest jute during flowering and early pod formation stage leaving a portion of the crop for seed production, allowing some scope for natural selection and maintenance of landrace variability. During green revolution, the development of short-duration high-yielding rice cultivars led to the adoption of jute-followed-by-rice cropping sequence in jute growing regions of India and Bangladesh. This led to a drastic reduction of growth duration of the jute crop (110–120 days, April–July), as rice transplanting starts in the months of June–July. Although jute breeders were able to develop shorter duration cultivars that could match the yield potential of the old longer duration cultivars, the practice of preserving self-seed by the jute farmers practically stopped in India. Till 1980s, Chinsurah Green and D154 were the major cultivated varieties in India, which were then replaced by JRO-524, JRO878, JRO7835, and JRC-321, respectively. Presently, JRO-524 occupies about 30% of jute area in India, being replaced largely by another cultivar JRO-204 (60% area). Only a few varieties of jute are grown in Bangladesh, of which JRO-524, O-4, and O-9897 are principally cultivated (Satya

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and Maiti 2013). About 90% of jute seed is imported by Bangladesh from India, which indicates that most of the jute area in Bangladesh might be under a single cultivar (cv. JRO-524) (Saha 2013; USAID EAT Report, 2014; Islam and Uddin, 2019). Similarly, only a few major cultivars (C. capsularis—D154, Lubinyuanguo, Yueyuan 1, JRC-212 and C46; C. olitorius— Guangfengchangguo, Kuanyechangguo, Bachang 4, Maliyeshengchangguo) have been cultivated during the last century in China (Zhang et al. 2019). A separate cultivation practice to grow only elite jute cultivars as seed crop started in the Southern and Western states of India, which till date supplies the seed for bulk of the World’s jute crop. Within 15–20 years, most long-duration cultivars/landraces disappeared completely from farmers’ field, which radically crumbled the natural gene pool of jute. Today, although jute is grown over 1.4 million ha land worldwide, not a single natural mutation in jute crop advances to the next generation, eliminating any chance of natural selection. Practically, the only genetic variability left in the fibre-type ecotypes of jute is confined to few countryspecific germplasm repositories and some jute plants sporadically distributed in nature, most of which escaped from cultivation and are under the process of un-domestication.

21.3.4 Limited Wild Gene Pool With a gradual decline in allelic variation in the species gene pool, plant breeders have resorted to crop wild relatives for the introduction of new alleles, but difficulty in interspecific hybridization and linkage drag have limited the use of wild Corchorus in jute breeding. Attempts to develop successful fertile progeny from interspecific hybridization of the two cultivated species are unsuccessful due to strong sexual incompatibility of the two species (Sinha et al. 2011; Sarkar et al., 2016). Among the wild Corchorus species, C. aestuans shows moderate cross-compatibility with C. olitorius. One such progeny, RS-6 showed resistance to stem rot disease (Mandal et al., 2021). Based on cross-compatibility and

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DNA marker polymorphism, C. aestuans is considered to be the closest progenitor of C. olitorius. However, often the wild progenitor(s) from which a cultivated crop has originated are lost during evolution. Given the low recovery of sexually fertile progenies between C. olitorius and C. aestuans, existence of intermediate progenitor(s) seems probable. Reports on utilization of other wild species like C. pseudo-olitorius, C. tridens, and C. trilocularis and their use in jute breeding are rare. Moreover, the two cultivated species are sexually incompatible, and even if such hybrids are obtained, they are morphologically similar to the female parent (mostly C. olitorius, as reports of successful hybridization using C. capsularis as female parent are rare) (Islam and Rashid, 1960; Swaminathan and Iyer, 1961).

21.3.5 Low Harvest Index For the grain crops, the harvest index is the ratio of the grain harvested to the ratio of total biomass at that stage. As these plants have attained reproductive maturity and are almost dry, here the harvest index is the ratio of harvested dry biomass to the total dry biomass, thereby providing a rough estimation of the proportion of photosynthate that was translocated to the sink (grain) to the photosynthate utilized to construct the whole plant. In crops like rice and wheat, harvest index is around 60%, indicating 60% of the photosynthate is translocated to the grain. Improving harvest index, thus, is a major target in reproductive-trait-centric breeding programmes. Conversely, jute crop is harvested when the plant is fully green, before the onset of reproductive phase. The ratio of fibre extracted to the crop biomass present in the field at that time (total green biomass) can be considered as a harvest index for jute, which is a meagre 6–7% in case of jute. As the fibre development is a component of vegetative growth, the partitioning of photosynthate towards apical meristematic growth (that increases plant height) and towards lignocellulosic fibre cell development and maturity throughout the bast tissue is an important determinant of fibre yield. If more photosynthate

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is driven towards apical growth, the plant will be taller but the fibre cells will be thinner. On the other hand, if more photosynthate is used to synthesize the fibre cells, apical meristematic growth will be negatively affected thereby making the plant dwarf. It seems that the jute plant itself has imposed a biological limitation on the harvest index of fibre yield.

21.3.6 Low Heritability and Response to Selection The fibre yield and its component characters in jute like plant height, basal diameter, fibre to stick ratio have low heritability and are influenced more by dominance and epistatic gene actions (see Sect. 21.2.4). Direct selection for these traits would have low response to selection and low genetic gain. Mukul and Akter (2021), after observing low genotypic coefficient of variation and low genetic advance for fibre yield, plant height and base diameter also commented that there is a very low opportunity to improve these characters by selection.

21.3.7 The Dilemma of Lignin In contrast to other plant fibres like cotton and ramie (>90% cellulose), or flax and hemp (63– 85% cellulose, 10–17% hemicellulose, 3–5% lignin and 5–10% pectin), the presence of high lignin (13–17%) distinguishes jute fibre, making lignin a key target trait in jute breeding. In woody plants, including some fibre plants like flax and ramie, lignin is deposited mainly in the woody xylem. However, for jute and kenaf, lignin is deposited both in the xylem and the phloem, albeit the concentration being more in xylem (25%). Jute, therefore, has inherent physiological and biochemical pathways directing lignin biosynthesis in the fibre cells. Breeding for low lignin has been a long-standing objective in jute research, with little success due to limited genetic resources, difficulty in chemical estimation of lignin and low response to selection. Since lignin is more difficult to degrade

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than pectin or hemicellulose, microbial degradation of jute to separate the fibre from the bast is a much slower process in comparison with flax. Moreover, current chemical or enzymatic treatments that work well for flax are inefficient to separate the jute fibres from other bast tissues due to the presence of high lignin. This makes water retting an indispensable component of jute cultivation, while flax can be retted in air containing high moisture (dew retting). Since lignin is deposited in the growing fibre cell along with cellulose deposition in jute (Kundu et al. 2012; Satya et al. 2021), physical separation of lignin from the cellulose in jute fibre is difficult, if not impossible. In contrast, lignin deposition in flax is limited to the middle lamella between the fibre cells, while cellulose deposition continues in the fibre cell wall (Gorshkova et al. 2000). Breeding for low-lignin jute, therefore, has to be targeted by blocking the lignin biosynthesis rather than by relying on post-harvest enzymatic lignin removal techniques. In addition, jute lignin contains a higher syringal:guiacol ratio (S:G::2:1) than wood lignin (S:G::1:1.4), making it more difficult for microbial or chemical degradation than hardwood lignin (del Rio et al. 2009). This, one hand, improves the durability of the fibre but makes it less suitable for textile applications.

21.3.8 Low Heterosis, NonSynchronous Flowering, and Absence of Pollen Control Mechanism Heterosis or the phenotypic superiority of the hybrid has been exploited in several crops to increase the productivity of the crop. Since jute fibre is vegetative, luxuriance or heterosis for vegetative vigour is expected to enhance fibre yield. Fibre yield and its component characters are also influenced more by dominance gene action, which makes exploitation of heterosis a potential avenue for increasing fibre yield. However, Basak and Dana (1971) reported negligible/negative heterosis for plant height, base diameter and node number in three crosses of C. olitorius. Other studies also reported

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negative/low heterosis for plant height and base diameter in C. capsularis, and moderate heterosis for fibre yield (Palve 2003), non-significant heterosis for plant height, base diameter and fibre yield (Bhattacharya et al. 2016) and low heterosis for fibre strength (Chaudhury and Sasmal 1992). In addition, non-synchronous flowering, moderate outcrossing (12–17% in C. olitorius), and absence of any effective male sterility system are major impediments for the exploitation of heterosis in jute.

21.4

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and genomic resources is being extensively utilized in current plant breeding programmes of major crops like rice, maize and cotton (Ray and Satya 2014). Application of the ubiquitous markers like RAPD and ISSR that do not require sequence information started in 2002, followed by development of sequence-specific markers like SSR, InDel, and SNP in the next decade. However, investment in molecular research in jute lagged behind that of other major crops. Delayed developments in marker technology and genomic resources coupled with inherent biological problems associated with the crop deferred proper utilization of molecular resources in jute breeding. Table 21.1 provides a summary of the various molecular markers developed in jute. In addition, several other marker systems developed in other species have been exploited in jute for molecular genetic analyses, such as start codon targeted markers (SCoT), genic markers (peroxidase and phenylalanine ammonia-lyase), and random markers.

Molecular Markers and Genomic Resources in Jute

21.4.1 Molecular Markers While classical breeding has produced the most successful cultivars worldwide, next-generation plant breeding armed with molecular markers Table 21.1 Status of molec(ular markers developed in jute Type of marker

Species

Genomic resource used

Distribution in genome

Number of markers developed

Reference

Genomic SSR

C. olitorius

Microsatelliteenriched genomic libraries

Repeat-rich genomic region

2,469

Mir et al. (2009)

Genomic SSR

C. olitorius

Microsatelliteenriched genomic libraries

Repeat-rich genomic region

399

Das et al. (2012)

EST-SSR

C. capsularis

Transcriptome

Genic

1,906

Zhang et al. (2015) Satya et al. (2017)

Genic SSR

C. capsularis

Transcriptome

Genic

12,772

Pathway-specificGenic SSR

C. capsularis

Transcriptome

Phenylpropanoid-pathway genes; genes involved in fibre development

39, 14

TF-SSR

C. capsularis

Transcriptome

Regulatory genes

457

Genic SSR

C. capsularis

Transcriptome

Genic

4,509 (907 within ORF sequence)

Saha et al. (2017) (continued)

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Table 21.1 (continued) Type of marker

Species

Genomic resource used

Distribution in genome

Number of markers developed

Reference

Genomic SSR

C. capsularis

Genome sequence

Throughout genome

1,53,242

Yao et al. (2019

cpSSR

C. olitorius/ C. capsularis

Chloroplast genome

Chloroplast genome

66

Fang et al. (2021)

InDel

C. capsularis

Transcriptome

Genic

4,815

Zhang et al. (2017)

C. olitorius/ C. capsularis

Genome sequence

Throughout genome

51,172

Yang et al. (2018)

C. olitorius/ C. capsularis

Chloroplast genome

Chloroplast genome

294

Fang et al. (2021)

C. capsularis

Expressed sequence tags

Throughout genome

43,335

Biswas et al. (2015)

C. olitorius/ C. capsularis

Transcriptome

Genic

3,11,906 in 12 samples

Yang et al. (2018)

C. olitorius/ C. capsularis

Chloroplast genome

Genic/non-transcribing

2417

Fang et al. (2021)

Corchorus spp.

Transcriptome

Genic

67,567

Tao et al. (2020)

C. olitorius

Genomic

Restriction site-associated genomic region

503

Kundu et al. (2012)

C. olitorius

Genomic

Restriction site-associated genomic region

1115

Sarkar et al. (2019)

Specific locus amplified fragment (SLAF)

C. capsularis

Restriction enzyme digested library

Genomic region

69,446

Tao et al. (2017)

AFLP

C. olitorius/ C. capsularis

Genomic library

Restriction site-associated genomic region

9,092 (C. capsularis) 8,856 (C. olitorius)

Das et al. (2011)

Cleaved amplified polymorphic sequence (CAPS)

Corchorus spp.

Transcriptome

Designed from SNP

26

Tao et al. (2020)

SNP

RAD-SNP

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Table 21.2 Status of genomic resources developed in jute

Genome

C. capsularis

C. olitorius

Reference

Nuclear genome–2 Chloroplast genome–1

Nuclear genome–1 Chloroplast genome–1

Islam et al. (2017); Sarkar et al. (2017); Fang et al. (2021)

Transcriptome (SRA)

See Chap. 15 for details

Transcriptome (TSA)

4

–

Chakaraborty et al. (2015); Satya et al. (2018)

miRNA/siRNA

9 5

227

Islam et al. (2015); Dey et al. (2016); Ahmed et al. (2021)

Linkage maps

1

3

Das et al. (2012); Topdar et al. (2013); Kundu et al. (2012); Tao et al. (2017)

Reconstructed pathways

Phenylpropanoid, lignin, fibre development, anthocyanin

Do

Chakaraborty et al. (2015); Islam et al. (2017); Satya et al. (2021)

21.4.2 Genomic Resources in Jute Detailed descriptions of different genomic resources developed in jute are provided throughout the preceding chapters of this book. Sarkar et al. (2016) also provided a concise and informative review on jute genomics. Hence, to avoid repetitions, only an indicative summary of genomic resources developed in jute is outlined in Table 21.2.

21.5

Application of Molecular Markers for Genetic Improvement of Jute

Various molecular markers have been used to assess genetic diversity and population structure in jute. Objective wise, these studies may be categorized as—(i) identification of heterotic groups for breeding, (ii) determination of genetic relatedness of cultivars and landraces, (iii) characterization of germplasm accessions, (iv) phylogenetic analysis to investigate the origin of jute, (v) population structure analysis, and (vi) estimation of cross-species transferability for their further use in jute genetics and breeding.

21.5.1 Identification of Heterotic Genetic Groups Genetic diversity of the parents holds the key to the heterotic nature and segregation behaviour of a breeding population. Hybridization of distantly related parents may also help to reduce linkage drag and increase allelic variability by creating new allelic combinations. Initial marker polymorphism studies based on RAPD had a small sample size but indicated the potential of marker technology applications in jute (Hossain et al. 2002; Qi et al. 2003). Cluster analysis of 49 jute (22 C. capsularis, 29 C. olitorius) Indian accessions based on 7 chloroplast-SSR (cpSSR) and 10 AFLP markers clearly distinguished the two species, identifying more groups for C. olitorius than C. capsularis (Basu et al. 2004). This study also identified a landrace, Red Glossy Seed (RG) as the most diverse accession. Another study on the diversity of Indian jute cultivars using RAPD, STMS and ISSR markers indicated very low variability among the cultivars, particularly in C. capsularis (Roy et al. 2006). Based on sequence-related amplified polymorphism (SRAP) markers, JRC 698, JRC 7447, TJ 40, S19, and JRO 3690 were found more diverse

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compared with rest of the cultivars (Rana et al. 2013). A pool of 60 mutant genotypes present in the Indian germplasm collection was characterized by Satya et al. (2014b) using 13 morphological parameters and 24 SSR markers. Their study revealed high SSR diversity identifying six clusters, but the correlation of distance matrices based on morphological descriptors and molecular markers was non-significant, signifying that judicious use of morphological and molecular variability should be practised for the selection of parents in the breeding programme. Nag et al. (2018) reported maximum diversity between CIN-018 and Padma in case of C. capsularis and between OIJ-165 and JRO-524 in case of C. olitorius, suggesting hybridization between these genotypes would generate maximum variability. They also predicted that a cross-combination between OIJ-248 and CIN-119 might be useful for developing successful interspecific hybrids between the two species.

21.5.2 Genetic Relation of Cultivars and Landraces As jute is considered to be recently domesticated, a low genetic diversity is expected between the landraces and the cultivars. Roy et al. (2006) observed that the average similarity between the germplasm and the cultivars was 50–55% and suggested selection might have been responsible for such difference. Basu et al. (2016) also noted that the cultivars, landraces and wild Corchorus species formed distant organelle genetic groups. They also noted that the fibre-type cultivars of C. capsularis were found to be more related to the wild Corchorus species than the landraces, suggesting that the fibre-type cultivars were genetically isolated, being originated in Africa. Molecular makers also help to determine the genetic identity of cultivars of dubious or unknown origin. By using population structure analyses and phylogenetic studies, Yang et al. (2018) could assign 221 accessions of unknown geographic origin to population-I (155) and population-II (66). The cultivars had much less

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gene diversity (He = 0.28) than the wild germplasm (He = 0.36), but landraces had gene diversity (He = 0.30) similar to that of the cultivars.

21.5.3 Germplasm Characterization Assessment of genetic diversity in germplasm collection is a routine activity that helps to devise strategies for exploration and collection of new germplasm, identify diverse phylogenetic groups and develop core collections, determine the origin of unassigned accessions, examine extent of diversity in the existing collection, identify duplicate accessions and predict shift in gene pool of the germplasm collection over time. The earliest report on the variability of jute germplasm using molecular markers (Hossain et al. 2002) made a preliminary investigation on RAPD variability in nine jute varieties from three countries and 12 local accessions using 29 primers. Following this, a number of studies have attempted for characterization of germplasm collections in India, Bangladesh, China, and Africa. However, many of the germplasm collections in these countries include accessions from several countries, thus these may be considered as global germplasm collection. The Indian germplasm collection has been well characterized using various molecular marker systems. The number of genotypes examined in these studies ranged from 49 (Basu et al. 2004) to 292 (Banerjee et al. 2012). Most of these studies could distinguish the C. capsularis accession from the C. olitorius accessions. However, Mir et al. (2009) noted that two C. olitorius genotypes, OIJ-102 and OIJ-103 were clustered with C. capsularis, indicating possibility of admixture or horizontal gene transfer. Their study indicated low genetic diversity (PIC = 0.23) in Indian germplasm collection. Banerjee et al. (2012) evaluated 152 genotypes of C. capsularis and 140 genotypes of C. olitorius using 172 SSRs carrying 596 alleles. They also observed low polymorphism (PIC = 0.2) for both the species and also noticed that some genotypes of C. olitorius

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were grouped with C. capsularis and vice versa. Satya et al. (2014b) studied molecular diversity and population structure of 78 C. olitorius, 4 C. capsularis, and 28 wild Corchorus accessions using peroxidase gene (POG) markers, phenylalanine ammonia lyase gene (PALG) markers and SSR identifying five distinct genetic groups that separated the Indian and African C. olitorius accessions. Using organelle genome-specific markers, Basu et al. (2016) evaluated 160 jute genotypes, revealing five groups in C. capsularis and three groups in C. olitorius. Nag et al. (2018) assessed diversity in 65 C. capsularis and 33 C. olitorius genotypes using 15 ISSR and five SSR markers. Of these, 58 accessions were germplasm collections including 16 natural mutants, while the rest were cultivars. They reported that the genetic variability between the cultivars and landraces was higher in case of C. capsularis. Relatively fewer attempts have been made to characterize the jute germplasm collection in Bangladesh. Ghosh et al (2014) evaluated 63 accessions from 10 countries using six SSR and 12 AFLP markers recording a moderate PIC for both C. capsularis (0.43) and C. olitorius (0.45). Two distinct clusters for the two cultivated species were identified in the dendogram. Evaluation of the Chinese jute germplasm collection started a little late, but considerable progress has been made during a short period. Zhang et al. (2015) evaluated 58 accessions from eight countries using 28 SSR primers. The SSR genotyping distinguished the two species and revealed moderate variability (PIC = 0.5) in this collection. Yang et al. (2018) genotyped a total of 453 accessions of C. olitorius, including landraces and cultivars, using 39 SSR markers. They found that the African (Kenyan) accessions had the maximum gene diversity (He = 0.33) and PIC (0.27). A set of global collections (101 accessions) were evaluated by Benor et al. (2012) using morpholmetric and AFLP analyses, revealing low genetic diversity within species. The African population contained higher diversity than the Asian population. However, the set did not include any accession for India, where the fibre-type jute was domesticated.

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21.5.4 Molecular Phylogeny of Jute Despite several studies, the origin, progenitor(s) and relationship of the two cultivated jute species are still debated. Previously, based on geographical distribution, C. olitorius was considered to be originated in Africa, while two probable origins of C. capsularis, Indo-Burma and China were accepted. Quite a number of molecular studies have been attempted to solve the origin and the progenitor(s) of the two cultivated jute species. Initial dominant markerbased studies (Roy et al. 2006) supported the geographical pattern-based suggestions. Based on higher mean genome size variation in African accessions than the Asian accessions (Benor et al. 2011) and AFLP diversity (Benor et al. 2012), Africa was suggested as the centre of origin of C. olitorius. However, whether C. olitorius was domesticated as a fibre crop in Africa before its introduction in India remained unsolved. Recently, the relationship of 225 germplasm accessions was examined by RADseq by Sarkar et al. (2019), discovering a higher genetic diversity in the Indian population compared to African and Asian population, and within India identified a South Indian population most distinct from the African population, suggesting peninsular India as a secondary centre of origin of C. olitorius. The fibre-type population grown in East India was least differentiated from the African types, indicating multiple introductions of C. olitorius in India. Higher order taxonomy of Corchorus has been resolved by both marker-based and gene sequence-based phylogenetic studies. Most of the studies using molecular markers included a few wild Corchorus species identifying C. aestuans as the closest relative of C. olitorius (Sarkar et al. 2016). Conversely, Saha et al. (2017) identified C. urticifolius as the closest relative of C. olitorius based on SSR diversity, which supports previous morphological diversity-based inference that C. olitorius might have been originated from crossing between C. aestuans and C. urticifolius (Maity and Dutta 2008). On the other hand, quantitative karyotype analysis identified

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C. fascicularis and C. pseudo-olitorius as the closest wild relatives of C. olitorius, while C. pseudo-capsularis was the closest to C. capsularis (Saha et al. 2014). A ribosomal DNA-based phylogeny of 144 accessions of 47 species (Benor 2018) identified C. pseudocapsularis as the closest relative of C. capsularis, followed by C. africanas. On the other hand, C. orinocensis and C. pilosus were close relatives of C. olitorius; C. aestuans being separated in a distant clade.

21.5.5 Population Structure Analysis Population structure analysis identified subpopulations within a population based on shared genetic variations. It is an essential component of population genetic analysis to identify geographically and evolutionary isolated groups, resolve ancestry, determine the association between a marker and a phenotype (association mapping), and for genome-wide association analysis (Pritchard et al. 2000; Alhusian and Hafez 2018). Banerjee et al. (2012) claimed to conduct population structure analysis in jute but did not use any specific structure analysis method in their study. A comparative structural classification of jute was first generated by Satya et al. (2014a) using genic and SSR markers. They identified 3–5 structural groups in a population of 82 accessions of cultivated and 28 accessions of wild Corchorus species using both admixture and non-admixture models. The C. olitorius population was subdivided into four subpopulations, of which the first subpopulation contained three clusters differentiating the fibre-type cultivars, germplasm, and mutant genotypes. Zhang et al. (2015) classified 159 jute accessions in two structural groups specific to two species and further subdivided the C. capsularis group into two subgroups. An organelle marker-based population structure analysis was attempted by Basu et al. (2016) using the Bayesian Markov Chain Monte Carlo algorithm and Non-Bayesian recollection algorithm that generated seven and eight structural groups, respectively, in a population of 168 Corchorus accessions. Based on a

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closer association of C. capsularis structural groups with the wild Corchorus species they suggested that C. capsularis evolved earlier than C. olitorius. Sarkar et al. (2019) conducted exhaustive population structure analysis of 225 jute accessions using RAD-SNP following Bayesian structure analysis, sparse non-negative matrix factorization and discriminant analysis of principal components. They identified two ancestral groups, Indian and African, each carrying four subpopulations. The structural analysis conclusively proved an African origin of C. olitorius and identified a secondary centre of origin for C. olitorius in peninsular India.

21.5.6 Cross-Species Transferability A few studies have been conducted in the crossspecies transferability of markers in jute. Satya et al. (2014a) successfully used rice POG markers as well as PALG markers from tomato to identify structural groups and establish the relation of cultivated and wild Corchorus species. The SSR markers developed from C. capsularis amplifies well in C. olitorius (Satya et al. 2017) Genic SSR markers developed from jute have been found to show high cross-species transferability to other Corchorus species (Saha et al. 2017). The jute SSRs were also found to show high confamiliar transferability, exhibiting 81.81% and 41.04% cross-transferability across genera and tribes of Malvaceae (Satya et al. 2016).

21.6

Potential Applications of Markers and Genomic Resources in Jute Breeding

Due to delayed development and slow progress in marker and genomic researches in jute, direct applications of large-scale genomics in plant breeding like genomic selection, marker-assisted QTL introgression and allele mining from germplasm resources are limited. Despite a small research community and limited investment in molecular breeding of jute, considerable progress

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has been made in marker development and their utilization in germplasm characterization, identification of heterotic parental lines, genetic structure analysis of germplasm and linkage map construction. In the coming decades, with changing breeding objectives, we need to focus on some of the following research areas to address the future need for jute breeding.

21.6.1 Genomics-Assisted Jute Germplasm Research Limitation of germplasm variability is a serious concern in jute breeding. Since the fibre-type cultivars are well characterized and contain limited genetic diversity (Satya et al. 2014a; Sarkar et al. 2019), genomic-information-based germplasm collection should be emphasized in jute. The planned expansion of the existing collection requires assessment of genomic variability in the germplasm collection, followed by germplasm exchange and new germplasm collection particularly from the centre of origin and diversity. While Africa is the primary centre of origin of C. olitorius, more detailed investigations of the African accessions are required to identify the microcentres so that germplasm collection efforts can be concentrated in the areas of maximum genetic diversity. The recent identification of a secondary centre of origin of C. olitorius in Southern India (Sarkar et al. 2019) also necessitates strategic collection from this habitat. Similarly, primary centre and microcenters of origin for C. capsularis should be unequivocally established for strategic collection of C. capsularis germplasm. A large size of germplasm collection necessitates core collection development for its efficient use in plant breeding programmes (Frankel 1984). However, compared with major crops where total germplasm holding ranges from 0.1– 0.8 million (Wambugu et al. 2018), the size of the jute germplasm collection is much smaller (50,000) of SSR markers have been identified from transcriptome sequence databases, some of which have been linked with specific biochemical pathways (Zhang et al. 2015; Satya et al. 2017; Saha et al. 2017). Despite their unique locations within expressed genes, these markers currently remain unutilized. A high-density PCR-based marker enriched genetic map integrating SSR and SNP markers, with QTLs for major traits incorporated would give more choice to the breeders to select the appropriate genotyping systems.

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21.6.4 Use of New Breeding Techniques (NBTs) New plant breeding techniques (NBTs) (Lusser et al. 2012) are a collection of genetic modification tools that arose due to ban/directives on the cultivation of GM crops in various countries, particularly in European Union. According to a European Union (EU) working group on NBT, these include agroinfiltration, cisgenics, grafting on GM-rootstock, oligonucleotide-directed mutagenesis (ODM), site-directed mutagenesis like zinc finger nuclease (ZFN) or technology, RNA-dependent DNA methylation and reverse breeding (Holme et al. 2019). The improved genotype may have a new DNA fragment introduced (new gene), may have its DNA modified (targeted mutagenesis), or may not have any foreign DNA in the final product. A detailed description of these technologies is beyond the scope of this chapter. Interested readers can refer to Schaart et al. (2016) for a concise review. Whatever may be the approach, targeted introduction/mutagenesis of the genomic region requires specific knowledge on the gene sequence targeted for modification. The jute genomic resources are enriched with information on specific genes and pathways, which may be utilized in near future for the exploitation of NBTs in jute. Unlike food crops, jute is a nonedible economic product, which means that the regulatory directives on jute products will be less stringent than on food crops. Despite such advantages, the application of these techniques in jute has not been realized particularly due to its low in vitro regeneration potential. Recent successes in the introduction of new genes through agroinfiltration (Majumder et al. 2018) bring promise to the use of NBTs in jute.

21.6.5 Decoding Epigenetic Controls of Traits Phenotypic expression in jute is highly influenced by the environment in which it is grown, which has limited its cultivation in the hot and humid ecology of the Indian subcontinent for the

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past centuries. The introduction of jute as a fibre crop in many countries was not successful due to its specific environmental requirement. High environmental variation is one of the major reasons for low heritability and response to selection in jute. While genetic, environmental, and their interactions are major determinants of phenotypic expression, the role of epigenetic variation in jute has not yet been examined. Epigenomic controls of plant development, stem elongation, flowering, and biotic stress resistance in crop plants are well documented (Zhao et al. 2020). To decipher the extent of epigenetic control in jute, a comprehensive epigenomic landscape map of the jute would be very helpful in targeting specific traits for genetic improvement through epigenetic modification.

21.6.6 Deciphering Interaction of Cellulose, Hemicellulose, Pectin, and Lignin The physical properties of plant fibres are largely dependent on the chemical composition of the fibre and the interaction of the component molecules. Since the three major components of jute fibre are cellulose, lignin and hemicellulose, an in-depth understanding of biosynthesis and in vivo interactions of these molecules are extremely important to design new applications for jute fibre. For example, the softness of a fabric depends largely on the moisture absorption capacity, which, in turn, depends on the free hydroxyl groups present on the surface of the fibre that interacts with the water molecules. A fabric with more hemicellulose content has higher free hydroxyl groups and, therefore, shows more softness under elevated atmospheric moisture, which is a desirable property for textile applications (Engelund et al. 2013). On the contrary, lignin contains the lowest amount of free hydroxyl groups, so a lignin-rich fibre like jute would lack the desired softness. Pectin, on the other hand, helps in the integration of fibre bundles in jute by interacting with extracellular lignin (Satya et al. 2021). The presence of high

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rhamnogalacturonan in jute pectin ensures stronger adherence of the fibre bundles (Satya et al. 2021). By using transcriptomics, Chakraborty et al. (2015) deciphered the lignin biosynthesis pathways identifying the genes for critical enzymes, while Islam et al. (2017) and Satya et al. (2021) unravelled the fibre biosynthesis pathways and pectin biosynthesis pathways, respectively, all of which can serve as valuable resources to modulate the chemical composition of jute fibre according to the requirement of the industry.

21.6.7 Breeding for Novel Phytochemicals and Nutritional Value Though fibre is the main economic product of jute, it is also cultivated as a major leafy vegetable in several African (Côte d’Ivoire, Benin, Nigeria, Cameroon, Sudan, Kenya, Uganda, and Zimbabwe) and Asian (India, Bangladesh, Japan, Thailand, Indonesia, Malaysia) countries (Benor et al., 2010; Fondio and Grubben 2011). The jute leaf is a highly nutritious vegetable being rich in calcium, magnesium, iron, anti-oxidants, and phenolics (Choudhary et al. 2013; Nyadanu et al. 2016). Consumption of jute leaf as a vegetable is perhaps older than its use as fibre crop, as it is mentioned in Bible, old Jewish literature and Egyptian transcripts. Little emphasis has been given in jute breeding to identify suitable ideotypes for jute as vegetables, although the fibretype jute Indian jute cultivars are rich in iron, bcarotene, anti-oxidants, and flavonoids (Choudhary et al. 2013; Nyadanu et al. 2016). To facilitate the application of genomic resources and molecular markers, Satya et al. (2017) developed 39 SSR markers from the key genes of the phenylpropanoid biosynthesis pathways and 137 SSR markers from the regulatory genes known for their role in modulation of phenylpropanoid biosynthesis pathways (WRKY, MYB, MYB-related, bHLH and zinc finger transcription factors). These markers will be useful resources for genetic mapping of traits of medicinal value such as phenolic content, anti-

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oxidant activity, flavonoid content and anthocyanin content, thereby helping in markerassisted selection of these traits. In addition, the phenolics and flavonoids play crucial roles in biotic and abiotic stress tolerance. Some of these SSRs are, therefore, potential candidates for marker-assisted resistance breeding. Finally, the gene- and pathway information needs to be integrated with high-throughput metabolomics data, allowing the selection of improved genotypes containing specific phytochemicals.

21.6.8 Establishing Potential of Jute as Bioenergy and Ecosystems Service Crop Apart from its economic importance as fibre and vegetable crop, a new economic use for jute is emerging as a renewable bioenergy crop to supply the growing demand for alternate energy and green fuels (Satya and Maiti 2013). Kenaf, a fibre crop having a similar chemical constitution as jute, is already being utilized in various diversified sectors including the production of bioenergy and biofuel. A well-managed jute crop can produce high biomass (green: 40–60 t/ha; dry: 10–25 t/ha) within a short period of growth duration (120 days), assuring the supply of a large volume of biomass at very low cost. In addition, waste jute sticks can also serve as an alternate source of value-added energy (Sarakar and Wang 2020). The composition of whole jute biomass (42.5% cellulose, 12.2% hemicellulose, and 31.58% lignin) and high reducing sugar production potential under saccharification suggests that jute can be suitable for biofuel production (Singh et al. 2020). Breeding for higher cellulose content in jute is gaining momentum to reduce the lignin content not only in the fibre but also in the whole biomass. Genomic information developed in jute on the biosynthesis of major cellular carbohydrate polymers such as cellulose, hemicellulose, and pectin as well as pathways for biosynthesis of lignin will be very useful for molecular breeding for developing high bioenergy producing jute varieties with altered

P. Satya et al.

cellulose and lignin quality and structures. To accelerate genetic improvement for high biomass jute crops, identification of QTLs for vegetative developmental processes, particularly leaf development, stem elongation, high photosynthesis, high cellulose, and low lignin should be targeted. In addition, high biomass crops like jute and kenaf are also valuable for ‘ecosystems service’, which include reduction of greenhouse gases, improve air quality, the addition of nitrogen to the soil by leaf litter, and phytoremediation of heavy metals. Molecular breeding for these traits using advanced genomics technologies is gaining rapid momentum for other bioenergy crops (Allwright and Taylor 2016). The jute sector, therefore, should drive forward to harness the potential of jute as a bioenergy and ecosystems service crop, which will usher a new era for jute, making it a ‘golden energy’ crop from ‘golden fibre crop’.

21.7

Conclusion

The developments in the identification of new robust molecular markers are expected to drive genetic improvement in jute allowing breeders more control over phenotypic variance. While molecular markers have been extensively used in diversity and population structure analysis, routine application of molecular markers in jute breeding is still awaited due to slow progress in linkage mapping. Recent developments in genome sequencing, characterization of genomics resources and development of genic markers are expected to generate robust markers linked with principal traits for marker-assisted selection. Identification and mapping of SNP makers need to be prioritized for their application in genomic selection. Overall, molecular markers would have to be strategically used in new jute breeding programmes to address critical problems like increasing fibre productivity, developing cultivars adapted to early sowing, modulation of fibre chemistry, biological solution to water-retting, breeding for novel phytochemicals, increasing biomass conversion efficiency and develop ideotypes for better ecosystems service.

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Correction to: Jute Genome Sequencing: An Indian Initiative Nagendra Kumar Singh and Debabrata Sarkar

Correction to: Chapter “Jute Genome Sequencing: An Indian Initiative” in: L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_10 The original version of the book was inadvertently published without two references and an incorrect caption for Fig 10.3, in Chapter 10. Some minor corrections in the text have also been incorporated in that chapter. The erratum chapter has been updated with the changes.

The updated version of this chapter can be found at https://doi.org/10.1007/978-3-030-91163-8_10

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 L. Zhang et al. (eds.), The Jute Genome, Compendium of Plant Genomes, https://doi.org/10.1007/978-3-030-91163-8_22

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