Plant Breeding Reviews, Volume 41 [1. Auflage] 9781119414506, 1119414504, 9781119414513, 1119414512

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PLANT BREEDING REVIEWS Volume 41

PLANT BREEDING REVIEWS Volume 41

Edited by

Irwin Goldman University of Wisconsin‐Madison Wisconsin, USA

This edition first published 2018 © 2018 John Wiley & Sons, Inc. All rights reserved. No part of this publication may be reproduced, stored in a ­retrieval ­system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. The right of Irwin Goldman to be identified as the author of the editorial material in this work has been asserted in accordance with law. Registered Office(s) John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK Editorial Office 9600 Garsington Road, Oxford, OX4 2DQ, UK For details of our global editorial offices, customer services, and more information about Wiley products visit us at www.wiley.com. Wiley also publishes its books in a variety of electronic formats and by print‐on‐demand. Some content that appears in standard print versions of this book may not be available in other formats. Limit of Liability/Disclaimer of Warranty While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Library of Congress Cataloging‐in‐Publication Data Library of Congress Catalog Control Number: 83-641963 Cover Design: Wiley Cover Illustration: © browndogstudios/Gettyimages Set in 10/12pt Melior by SPi Global, Pondicherry, India

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Contents

Contributorsxiii 1. Hari Deo Upadhyaya: Plant Breeder, Geneticist and Genetic Resources ­Specialist

1

Sangam L Dwivedi Abbreviations3 I. Introduction 3 II.  Biographical Sketch 5 III. Contributions 5 A.  Genetic Resources Management and Use 6 1.  Representative Subsets 6 2.  Climate‐resilient Germplasm 8 3.  Seed Nutrient‐dense Germplasm 8 4. Bioenergy 9 5.  Germplasm Use in Breeding 9 6.  On‐farm Conservation and Use of Diversity 10 7.  Wild Relatives and Cultigen Genepool 10 8.  Gaps in Collections 12 B.  Molecular Biology and Biometrics 13 1.  Population Structure and Diversity 13 2.  Genome‐wide Association Mapping 13 3.  Candidate Genes Associated with Agronomically Useful Traits 15 4.  Ethnolinguistic Groups Shaped Sorghum Diversity in Africa15 5.  Genome Sequencing 16 C.  Groundnut Breeding 16 1.  Early Maturity 16 2.  Drought Tolerance 18 3.  Aflatoxin Resistance 18 4.  Farmers Participatory Varietal Selection 19 D.  Chickpea Breeding 20 IV.  Upadhyaya, the Man 20 v

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A. Personality B.  Educator and Leader C.  International Collaborations D. Recognition 1. Awards 2. Honours 3. Service V. Publications VI. Products A. Cultivars B. Registrations References cited and further reading

2. Crop Improvement Using Genome ­Editing

20 27 28 28 28 30 30 30 31 31 31 33

55

Nathaniel M Butler, Jiming Jiang and Robert M Stupar Abbreviations56 I. Introduction 57 II.  Conceptual Framework for Genome Editing 60 A.  Development of Sequence‐Specific Nucleases 60 1.  Early Nucleases 62 2.  Designer Nucleases 62 3.  RNA‐guided Nucleases 65 B.  DNA Repair Pathways 66 1.  Non‐homologous End‐joining 66 2.  Homologous Recombination 69 C.  Modes of Modifications 70 1.  NHEJ‐mediated Modifications 70 2.  HR‐mediated Modifications 71 III.  Plant Transformation Strategies 72 A.  Agrobacterium‐mediated Transformation 73 B.  Protoplasts and Biolistics 75 C.  Plant Viral Systems 76 IV.  Harnessing Breaks for Targeted Mutagenesis 77 A.  Detecting and Stabilizing Targeted Mutations 78 B.  Targeted Mutagenesis in Polyploids 81 V.  Precision Gene Editing via Homologous­ Recombination82 VI.  Genome Editing at the Genome Level 85 A.  Large Deletions 85 B.  Chromosomal Rearrangements 86 C.  Epigenetic Remodelling and Base Editing 87

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VII. Future Perspectives 88 A. Nuclease Decisions and Considerations 89 B.  Crop Challenges and Advantages 90 C.  Regulation of Nuclease Technology 91 Acknowledgements92 Literature Cited 92

3. Development and Commercialization of CMS Pigeonpea Hybrids

103

KB Saxena, D Sharma, and MI Vales Abbreviations 105 I. Introduction 106 II. Reproductive Cycle and Morphology of Pigeonpea 108 A. Induction of Flowering 108 B.  Maturity Range 109 C.  Flower Structure 110 D. Flowering Pattern 111 E.  Pollination and Fertilization 111 F.  Natural Cross‐pollination 112 1.  Cross‐pollinating Agents 112 2.  Extent of Out‐crossing 114 III.  Crop Production 115 A. General Agronomy 115 B.  Major Production Constraints 115 1. Diseases 115 2.  Insect Pests 117 3. Waterlogging 117 IV. Extent and Nature of Heterosis in Pigeonpea 118 V. Genetic Male Sterility‐based Hybrid Technology 119 A. Genetic Male Sterility Systems 119 B.  Heterosis in GMS‐based Hybrids 121 C. Release of the First GMS‐based Pigeonpea Hybrid 121 D. Hybrid Seed Production Technology 122 E.  Assessment of GMS‐based Hybrid Technology 123 VI. Temperature‐sensitive Male Sterility 124 VII. Cytoplasmic‐nuclear Male Sterility‐based Hybrid Technology125 A. Early Efforts to Produce CMS System 126 B.  Breakthrough in Breeding Stable CMS Systems 126 C.  Diversification of Cytoplasm 127

viii Contents

1. A1 CMS System from Cajanus sericeus (Benth. ex Bak.) van der Maesen 128 2. A2 CMS System from Cajanus scarabaeoides (L.) Thou 128 3. A3 CMS System from Cajanus volubilis (Blanco) Blanco. 128 4. A4 CMS System from Cajanus cajanifolius (Haines) Maesen 129 5. A5 CMS System from Cajanus cajan (L.) Millsp 129 6. A6 CMS System from Cajanus lineatus (W & A) van der ­Maesen 130 7. A7 CMS from Cajanus platycarpus (Benth.) van der Maesen 130 8. A8 CMS System from Cajanus reticulatus (Aiton) F. Muell 130 9. A9 CMS System from Cajanus cajan (L.) Millsp 131 D.  Effect of Pigeonpea Cytoplasm on Yield 131 E. Fertility Restoration of A4 CMS System 132 VIII.  Breeding New Hybrid Parents 133 A.  Fixing Priorities 133 B. Selection of Hybrid Parents from Germplasm and Breeding Populations 134 C. Isolation of Fertility‐Restoring Inbred Lines from Heterotic Hybrids136 D.  Breeding Dwarf Parental Lines 137 E. Breeding Determinate/Non‐determinate Parental Lines 137 F. Disease‐resistant Parental Lines 138 G.  Use of a Naked‐Eye Polymorphic Marker in Hybrid Breeding139 H.  Formation of Heterotic Groups 140 I. Inbreeding Depression 141 IX.  Application of Genomics in Breeding Hybrids 142 A.  Understanding the Molecular Genetics Basis of the A4 CMS System 143 B.  Tagging Fertility‐restoring Genes 143 C.  Assessment of Genetic Purity 144 D.  Potential Role in Breeding Two‐line Hybrids 145 X. Commercialization of Hybrid Pigeonpea Technology 146 A.  Standard Heterosis 146 1.  Early‐maturing Hybrids 146 2.  Medium‐ and Late‐maturing Hybrids 147

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ix

B.  Release of the World’s First Commercial Legume Hybrid 149 C.  Hybrid Seed Production Technology 152 D.  Economics of Hybrid Seed Production 153 XI. Outlook 154 Acknowledgements157 Literature Cited 157

4. The Evolution of Potato Breeding

169

Shelley H Jansky and David M Spooner Abbreviations170 I. Introduction 170 II.  Classification of Cultivated Potato 171 III.  Origin of the Cultivated Potato 173 IV.  Dynamics of Potato Landrace Evolution 176 V.  Origin of the European Potato 178 VI.  Nineteenth Century Potato Breeding 179 VII.  Early Twentieth Century Potato Breeding 184 VIII.  Conventional Potato Breeding 189 IX.  Late Twentieth Century Potato Breeding 191 X.  Twenty‐first Century Potato Breeding 196 A.  Is Tetraploidy Necessary for High Tuber Yield in Potato? 196 B. What are the Advantages of Moving to the  Diploid Level and Developing Inbred Lines? 198 C.  Is It Possible to Develop Diploid Inbred Lines in Potato? 200 XI. Conclusions 202 Literature Cited 203

5. Flavour Evaluation for Plant Breeders

215

JC Dawson and GK Healy Abbreviations217 I. Introduction 217 A.  Scope of the Chapter 218 B.  Justification for Rapid Sensory Methods 219 C. History 220 II.  Types of Rapid Sensory Analysis Methods 221 A.  Performance Relative to Conventional Methods 222 B.  Methods of Rapid Sensory Evaluation 224

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1.  Evaluation of Individual Product Attributes Method 1: Intensity Scales Method 2: Flash Profiling Medhod 3: Check All That Apply (CATA) 2.  Evaluation of Global Differences Method 4: Sorting Method 5: Projective Mapping 3.  Evaluation in Comparison to a Reference Method 6: Paired Comparisons Method 7: Polarized Sensory Positioning Method 8: Open‐ended Evaluations 4.  Use of Professional Experts in Evaluation C. Numbers of Assessors and Numbers of Samples for Trained, Untrained and  Expert Panels III.  Data Analysis for Rapid Sensory Methods A.  Principal Component Analysis B.  Multi‐dimensional Scaling C.  Multiple Correspondence Analysis D.  Generalized Procrustes Analysis E.  Multiple Factor Analysis IV.  Example of Using Sensory Analysis for Breeding A.  Background, Goals and Partners 1.  Participant Recruitment and Priority Setting 2.  Cultivar Trials B.  Flavour Evaluation Methods Used 1.  Evolution of Flavour Evaluation Methods 2.  Intensity Scaling Methods Used with  Crew Members 3.  Chef Projective Mapping Evaluation C.  Statistical Methodology 1.  ANOVA with Intensity Scaling Methods 2. Principal Component Analysis of Field Crew Flavour Evaluation Means 3. Multiple Factor Analysis of Chef Projective Mapping Data D. Results 1. Field Crew Flavour Evaluation with  Intensity Scaling 2.  Chef Flavour Evaluations 3.  Participant Feedback and Next Steps V. Outlook

224 224 225 226 227 227 228 230 230 231 232 232 235 236 237 237 238 239 239 241 241 241 243 243 243 244 245 246 246 246 247 247 247 250 253 254

Contents

xi

Acknowledgements256 Literature Cited 256

6. The Genetic Improvement of Black Walnut for  Timber Production

263

James R McKenna and Mark V Coggeshall Abbreviations264 I. Introduction 265 II.  Biology of Black Walnut 268 A.  Leafing Date 268 B. Flowering 268 1.  Female Flowers 269 2.  Male Flowers 270 C.  Pollen Collection 270 D.  Artificial Pollination 271 III. Breeding 272 A.  Breeding Strategies 272 B. Selection 272 C.  Age‐to‐Age Correlations 273 D. Improvement 274 E. Analysis 274 IV.  Evaluation of Heritable Traits 274 A.  Geographic Variation 274 B. Growth 275 C.  Timber Quality 275 D.  Wood Quality 276 V. Host Plant Resistance to Pathogens and Insect Pests 277 A.  Insect Resistance 277 B. Anthracnose 277 C.  Thousand Cankers Disease 278 D.  Bunch Disease – Witches Broom 278 VI. Propagation 279 A.  Seed Propagation 279 B. Grafting 280 C. Rooting 281 VII.  Plot Management 281 A.  Progeny Tests 281 B.  Clone Banks 282 C.  Seed Orchards 283 VIII.  Future Directions 283 Literature Cited 283

xii Contents

7. A Life in Horticulture and Plant Breeding: The Extraordinary C ­ ontributions of Jules Janick

291

Irwin Goldman and Rodomiro Ortiz Abbreviations292 I. Introduction 292 II.  Honors and Commendations 297 III.  Students and Teaching 297 IV.  Editorial Work 299 V.  Books and Proceedings 303 VI. Research 306 A. Patents 307 B.  Book Chapters, Reviews and Introductions 307 C.  Journal Publications 310 D.  Popular and Extension Articles 320 E.  Book Reviews 329 F.  Encyclopaedia Articles 331 VII.  Public Addresses, Invited Seminars and Speeches 332 VIII.  Service Contributions 355 IX. Epilogue 358 Literature Cited 360

Author Index Subject Index Cumulative Subject Index Cumulative Contributor Index

361 363 365 389

Contributors

Nathaniel M Butler, Department of Horticulture, University of Wisconsin, Madison, WI Mark V Coggeshall, USDA Forest Service, Northern Research Station, Hardwood Tree Improvement and Regeneration Center, West State Street, West Lafayette, IN, USA JC Dawson, Department of Horticulture, University of Wisconsin‐­ Madison, M ­ adison, WI Irwin Goldman, Department of Horticulture, University of Wisconsin‐ Madison, Madison, WI GK Healy, Department of Horticulture, University of Wisconsin‐Madison, Madison, WI Shelley H Jansky, United States Department of Agriculture – Agricultural Research Service, and University of Wisconsin, Madison, WI Jiming Jiang, Department of Horticulture, University of Wisconsin, Madison, WI Sangam L Dwivedi, International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT), Patancheru, Telangana, India James R McKenna, USDA Forest Service, Northern Research Station, Hardwood Tree Improvement and Regeneration Center, West State Street, West Lafayette, IN, USA Rodomiro Ortiz, Swedish University of Agricultural Sciences, Department of Plant Breeding, Sweden KB Saxena, International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT), Patancheru, Telangana, India D Sharma, International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT), Patancheru, Telangana, India David M Spooner, United States Department of Agriculture – Agricultural Research Service, and University of Wisconsin, Madison, WI Robert M Stupar, Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN MI Vales, Department of Horticultural Sciences, Texas A&M University, College Station, TX

xiii

1 Hari Deo Upadhyaya: Plant Breeder, Geneticist and Genetic Resources ­Specialist Sangam L Dwivedi International Crops Research Institute for the Semi‐Arid Tropics ­(ICRISAT), Patancheru, Telangana, India

ABSTRACT This chapter discusses Hari Deo Upadhyaya, a plant breeder, geneticist and genetic resources specialist, and his contributions in management and utilization of genetic resources, molecular biology and biometrics, and in groundnut breeding. Hari’s contributions in genetic resources include enriching germplasm collections; forming representative subsets in the form of core and/or mini-core collections in chickpea, groundnut, pigeonpea, pearl millet, sorghum, and six small millets; unlocking population structures, diversity and association genetics; and identifying genetically diverse and agronomically desirable germplasm accessions for use in crop breeding. The Consultative Group on International Agriculture Research (CGIAR) recognized his concept and process of forming mini-core collection as International Public Goods (IPGs) and researchers worldwide are now using mini core-collections as useful genetic resources in breeding and genomics of the aforementioned crops. A genebank manager’s role isn’t just confined to collection, maintenance, and archiving germplasm. Hari’s spirited efforts prove so and they led many to realize the abundant opportunities to mine and enhance the value of the genetic resources in crop improvement programs. As a geneticist, his seminal work on wilt resistance in chickpea laid a strong foundation for the wilt resistance breeding programs globally. His contributions as a groundnut breeder resulted in the release of 27 cultivars in 18 countries, some widely grown, and 24 elite germplasm releases with unique characteristics made available to groundnut researchers

Plant Breeding Reviews, Volume 41, First Edition. Edited by Irwin Goldman. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc. 1

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worldwide. Hari’s inimitable ability and scientific competence allowed him to collaborate with diverse groups and institutions worldwide. His scientific contributions in germplasm research and groundnut breeding have been recognized with several prestigious global awards and honors. A prolific writer and with immense passion for teaching, Hari Upadhyaya has established a school of his own for the management, evaluation and use of genetic resources for crop improvement. KEYWORDS: Breeding, Climate resilient germplasm, core and mini-core collections, crop wild relatives, cultivars, elite germplasm, farmers participatory variety selection, molecular breeding, population structure and diversity, on-farm conservation of germplasm OUTLINE ABBREVIATIONS I. INTRODUCTION II. BIOGRAPHICAL SKETCH III. CONTRIBUTIONS A. Genetic Resources Management and Use 1.  Representative Subsets 2.  Climate‐resilient Germplasm 3.  Seed Nutrient‐dense Germplasm 4.  Bioenergy 5.  Germplasm Use in Breeding 6.  On‐farm Conservation and Use of Diversity 7.  Wild Relatives and Cultigen Genepool 8.  Gaps in Collections B.  Molecular Biology and Biometrics 1.  Population Structure and Diversity 2.  Genome‐wide Association Mapping 3.  Candidate Genes Associated with Agronomically Beneficial Traits 4.  Ethnolinguistic Groups Shaped Sorghum Diversity in Africa 5.  Genome Sequencing C.  Groundnut Breeding 1.  Early Maturity 2.  Drought Tolerance 3.  Aflatoxin Resistance 4.  Farmers Participatory Varietal Selection D.  Chickpea Breeding IV. UPADHYAYA, THE MAN A.  Personality B.  Educator and Leader C.  International Collaborations D.  Recognition 1.  Awards 2.  Honours 3.  Service V. PUBLICATIONS

1.  HARI DEO UPADHYAYA

3

VI. PRODUCTS A.  Cultivars B.  Registrations REFERENCES CITED AND FURTHER READING

ABBREVIATIONS ASA CGIARC CSSA ICRISAT NARS R4D SNP

American Society of Agronomy Consultative Group on International Agricultural Research Consortium Crop Science Society of America International Crops Research Institute for Semi‐Arid Tropics National Agricultural Research Systems Research for development Single nucleotide polymorphisms

I. INTRODUCTION Hari Deo Upadhyaya, whom many of us know as Hari, has been known to me since 1980, when he joined the International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT), Patancheru, India, as a

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postdoctoral fellow in chickpea breeding. After completing his postdoctoral assignment at ICRISAT, Hari then moved for a short period to work as the Pool Officer at ‘GB Pant’ University of Agriculture and Technology (GBPUAT), Pantnagar, India, the first agricultural university established on a US ‘Land Grant’ pattern in India. He then took up a regular position at the University of Agriculture Sciences (UAS), Dharwad, India, where he worked for almost for eight years, first as a soybean breeder (as Assistant Professor), and then as the head of the oilseeds scheme and a groundnut breeder (as Associate Professor). He did a remarkable job as an oilseed breeder, and he set up and took the ­soybean and groundnut breeding programs to newer heights. In 1991, Hari returned to ICRISAT as a Senior Groundnut Breeder. In  late 1997, ICRISAT reorganized its research portfolio, and moved Hari on a part‐time basis to the Genetic Resources Unit, as part of the Crop Improvement Program. In 2002, Hari was appointed as a Principal Scientist and Head of the Genebank, ICRISAT, Patancheru, India, a position he still holds in the ‘new organizational structure’, where he has to manage the ICRISAT administrative Research for Development (R4D) portfolios with respect to management and utilization of genetic resources in crop improvement programs. Hari knows very well that greater use of germplasm in crop breeding is the way forward for better conservation and use of genetic resources, and to address food and nutritional security in the developing world. As a principal scientist (in genetic resources), Hari performed exceedingly well, while promoting the greater use of genetic resources in crop improvement. Today, the representative subsets (i.e. the core and mini‐ core collections) of the ICRISAT crops (i.e. chickpea, groundnut, pearl millet, pigeonpea, sorghum, finger millet) and small millets (i.e. barnyard millet, foxtail millet, kodo millet, little millet, proso millet) have been made available, and globally researchers are using these subsets to identify new sources of variation to support crop breeding in their respective regions. Hari’s seminal work with Rodomiro Ortiz on the process and concept of forming the mini‐core collection has been recognized as an ‘International Public Good’. Hari has published a total of 812 articles, of which 291 have undergone international peer review. These include research articles, commissioned reviews, and book chapters, and he has averaged 11.6 such articles per year, with three articles per year as first author. Twenty‐seven cultivars of groundnut that were bred by Hari are being cultivated in 18 countries in Africa and Asia. Over my long association with Hari, I have found him to be a person with the highest scientific competence and integrity, and a successful plant breeder and genebank manager. Hari’s leadership in managing

1.  HARI DEO UPADHYAYA

5

one of the largest Consultative Group on International Agricultural Research (CGIAR) Consortium genebanks is very much reflected in a recently concluded external review, when the panel remarked that ‘The ICRISAT genebank is functioning to high technical and scientific standards, and is very good in comparison with other international genebank operations. The users of the ICRISAT genebank are satisfied and appreciation of the genebank is wide spread.’

II.  BIOGRAPHICAL SKETCH Hari was born on 12th August 1953, in the small village of Shiwala, in Khair Tehsil, District Aligarh, Uttar Pradesh, India. He is the seventh of the eight children of Mr Gopi Chand Upadhyaya and Mrs Longsri Devi Upadhyaya. He passed his high school examinations (X standard) with Biology as his main subject, and got a distinction in Mathematics. Hari did a BSc (with honours) at Aligarh Muslim University, Aligarh, India, and then moved to the GB Pant University of Agriculture and Technology, Pantnagar, India, to complete his MSc and PhD, both in Plant Breeding. Hari is married to Ms Sudha, and is blessed with two sons, Abhisheik Deo and Aaditya Deo. Interestingly, neither of his sons has followed in his footsteps, as they chose Information Technology for their career path. Hari derives great strength from his wife and children in his scientific endeavours.

III. CONTRIBUTIONS Unlike traditional germplasm botanists and curators, whose vision is always centred on collection, conservation, characterization and documentation of germplasm, Hari’s basic training in plant breeding and genetics helped him to think beyond routine genebank activities, to include enhancing the value of genetic resources in the breeder’s perception. Plant breeders are often reluctant to use exotic germplasm, largely because of the fear of linkage drag, breakdown of co‐adapted gene complexes, and lengthening of the breeding cycle for the development of new cultivars. Hari strongly believes in promoting the use of germplasm in crop improvement programs, the generation and use of new knowledge (i.e. physiological, genetic, molecular) of trait expression and inheritance in applied breeding, and the sharing of breeding populations and advanced varieties, and also of knowledge, to help the global community to increase the production and productivity of staple food crops. Hari

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invested heavily to add value to the germplasm collections, and uses this in the crop breeding at ICRISAT and in the national programs globally. A.  Genetic Resources Management and Use 1.  Representative Subsets.  The use of germplasm in crop improvement programs globally is restricted due to: (i)  the large sizes of collections of many crop species; (ii)  the non‐availability of representative subsets; and (iii)  the lack of accurate and precise information on the agronomic worth of individual germplasm. Hari saw the need, as advocated by Frankel and Brown (1984) to form reduced subsets that represent the diversity of the entire collection of a given species preserved in the genebank, and he initiated work to develop representative sets for ICRISAT mandate crops and small ­millets. Using passport and characterization data and statistical tools, Hari first developed the core collections (10% of the entire collection of a species stored in the genebank) for chickpea and, later, for pigeonpea, groundnut, pearl millet, and small millets (Table 1.1). Table 1.1.  Core collections formed by Hari Deo Upadhyaya in chickpea, groundnut, pearl millet, pigeonpea, and small millets. Number of accessions used

Number of traits involved

Number of accessions in core

Pearl millet

20,766

22

2,094

Chickpea

16,991

13

1,956

Pigeonpea

12,153

14

1,290

Groundnut

14,310

14

1,704

Finger millet

5,940

14

622

Foxtail millet

1,474

23

155

Proso millet

833

20

106

Barnyard millet

736

21

89

Kodo millet

656

20

75

Little millet

460

20

56

Crop

Reference Upadhyaya et al., 2009a Upadhyaya et al., 2001a Reddy et al., 2005 Upadhyaya et al., 2003 Upadhyaya et al., 2006c Upadhyaya et al., 2008b Upadhyaya et al., 2011i Upadhyaya et al., 2014c Upadhyaya et al., 2014c Upadhyaya et al., 2014c

1.  HARI DEO UPADHYAYA

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The chickpea core collection consisted of 1,956 accessions that had been selected from 16,991 accessions (Upadhyaya et  al., 2001a). Rodomiro Ortiz, the then Director of Genetic Resources and the Enhancement Program, ICRISAT, challenged Hari and Paula Bramel (a  co‐author with Hari) about how useful the core collections were, with such large numbers of accessions for screening a desired trait for further use in breeding. After evaluating 1,956 accessions, together with controls for one season, in an augmented design, Hari concluded that it was a Herculean task to accurately and cost‐effectively generate datasets even for the core collection accessions. Hari and Rodomiro Ortiz discussed this and adopted the approach of re‐sampling the core collection to define a ‘core of the core’ or ‘mini‐core’, subset. Here, they used the evaluation data (22 morphological and agronomic traits) of the core collection (1956 accessions) and statistical theory to sample the variability to form the mini‐core collection (211 accessions) in chickpea. This represented the diversity that was present in the core collection, and also the entire collection, as shown by the similar means, variances, frequency distributions and preserved co‐adapted gene complexes, both for the core and mini‐core collections (Upadhyaya and Ortiz, 2001). Hari and Rodomiro jointly wrote a manuscript on the chickpea mini core collection, with Rodomiro as corresponding author, and submitted it to Theoretical Applied Genetics. To their surprise, exactly two weeks later, they got a response from the editor to say that the manuscript was accepted for publication. This development encouraged Hari to follow this approach, and in subsequent years, he developed mini‐core collections for other crops as well (Table 1.2). In all cases, both the core and mini‐core collections fulfilled the statistical tests for the preservation of Table 1.2.  Mini‐core collections formed by Hari Deo Upadhyaya in chickpea, groundnut, pearl millet, pigeonpea, sorghum, and small millet. Entire collection

Mini‐core number

% of entire collection

Traits used

Sorghum

22,473

242

1.08

21

Pearl millet

20,766

238

1.14

18

Chickpea

16,991

211

1.24

22

Pigeonpea

12,153

146

1.2

34

Groundnut

14,310

184

1.28

34

Finger millet

5,940

80

1.34

20

Foxtail millet

1,474

35

2.37

21

Crop

Reference Upadhyaya et al., 2009b Upadhyaya et al., 2011 l Upadhyaya and Ortiz, 2001 Upadhyaya et al., 2006e Upadhyaya et al., 2002a Upadhyaya et al., 2010c Upadhyaya et al., 2011e

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means, variances, and frequency distributions, and the co‐adapted gene complexes of the entire collections (in the case of the core collections) or core collections (in the case of the mini‐core collections). 2. Climate‐resilient Germplasm. Global warming is putting significant stress upon agricultural production and the nutritional quality of staple crops in many parts of the world. Southern Asia and Sub‐Saharan Africa will be the most adversely affected regions, due to climate change and the variability effects. ICRISAT‐mandated crops are widely grown and consumed in these regions (http://faostat.fao.org/site/567/default. aspx#ancor). The identification and use of climate‐resilient germplasm in crop breeding is the way forward to develop ‘climate‐smart’ crop cultivars. Hari adopted a two‐pronged strategy, first by working with ICRISAT researchers, and second by providing the seeds of several sets of mini‐ core collections to NARS partners and working with them to evaluate these subsets for agronomic traits, including stress tolerance. The end result was the identification of several sources of resistance to abiotic and biotic stresses in chickpea and groundnut, with some accessions combining stress resistance and tolerance in good agronomic backgrounds (Upadhyaya et  al., 2013a, 2014d). Using a similar approach, Hari and his colleagues identified a number of drought‐tolerant and salinity‐tolerant germplasm accessions in finger millet and/or foxtail millet (Krishnamurthy et al., 2014a, 2014b, 2016). Blast (Pyricularia grisea) is a devastating disease in pearl millet and finger millet, which has many pathotypes. The work of Hari and his colleagues on screening the pathogenic variability led them to identify accessions that were resistant to multiple pathotypes in pearl millet (Sharma et al., 2015), finger millet (Babu et al., 2013b, 2015) and foxtail millet (Sharma et al., 2014). Downy mildew (Sclerospora graminicola [Sacc.] Schröt) is a highly destructive and widespread d ­ isease of pearl millet, while grain mould and downy mildew (Peronosclerospora sorghi) are also important diseases of sorghum. Hari and his colleagues identified a number of accessions with resistance to multiple pathotypes in pearl millet (Sharma et al., 2015) and sorghum (Sharma et al., 2010, 2012). In addition, they identified some lines with good agronomic value, such as early maturity and resistance, and resistance and high seed/fodder yield potential, in both finger millet and pearl millet. 3. Seed Nutrient‐dense Germplasm. Widespread micronutrient malnutrition in human beings, as a result of deficiency of iron (Fe), zinc (Zn)

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and β‐carotene, has an enormous socio‐economic cost for society in the ­developing world (Stein, 2010). Hari saw the need to identify seed nutrient‐dense (i.e. Fe, Zn) germplasm to support crop breeding. ­After evaluating the mini‐core collections for two seasons, Hari identified a number of different germplasm sources with high seed Fe and/or Zn concentrations in groundnut (Upadhyaya et al., 2012d), pearl ­millet (Rai et al., 2015), sorghum (Upadhyaya et al., 2016c), finger millet (Upadhyaya et al., 2011d), and foxtail millet (Upadhyaya et al., 2011e). Finger millet and foxtail millet are rich sources of seed protein and calcium (Ca), with some accessions in both of these crops showing exceptionally high protein and Ca contents (Upadhyaya et al., 2011d, 2011e). 4. Bioenergy. Sorghum is a crop that is used for food, feed, and ­bioenergy. The stalks are rich in sugar (as measured by Brix). However, the stalk sugar content is greatly influenced by the environment and the crop stage at which the stalks are harvested. Hari evaluated the sorghum mini‐core collection accessions for stalk sugar content for two post‐rainy seasons under irrigated and drought‐stressed conditions. He found that drought stress significantly increased the mean Brix by 12–27%. A few germplasm lines had significantly greater mean Brix (14.0–15.2%), but were agronomically inferior, while some others were agronomically comparable but with similar Brix, such as IS 33844 (Brix, 12.4%) (Upadhyaya et al., 2014a). This indicated that it is possible to ­select for even higher Brix content in agronomically superior genetic background in germplasm collections. IS 33844 is the local landrace Maldandi that was collected from Maharashtra, India, and it is the most popular sorghum cultivar that is widely grown under decreasing soil moisture conditions during the rabi (post‐rainy) season in India. IS 33844 is tolerant to terminal drought and has excellent grain quality. 5.  Germplasm Use in Breeding.  Plant genetic resources are the basic raw materials for genetic progress, and they provide insurance against unforeseen threats to agricultural production. Hari firmly believes that the use of germplasm in crop improvement is one of the most sustainable ways to conserve valuable genetic resources and to broaden the genetic base of crops. Hari partnered with researchers globally to get these subsets (Tables 1–2) evaluated for stress tolerance, yield and seed nutritional traits, and collaborated with molecular biologists to dissect out the population structure and diversity in these representative ­subsets. This exercise resulted in the identification of several agronomically beneficial and genetically diverse germplasm sources that fulfil the needs of crop breeders. Armed with this valuable information, Hari

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interacted with crop breeders at ICRISAT and elsewhere, to promote the use of such germplasm in breeding programs. An analysis of the uptake of germplasm in crop improvement programs at ICRISAT showed that germplasm use has increased since the formation of the mini‐core collections in some crops. For example, there was increased use (≈15% increase) of stress‐tolerant chickpea germplasm during the 2000–2004 and 2005–2009 periods, while in recent years (i.e. 2010–2014), more emphasis (22% increase) has been on the use of germplasm that has agronomic (yield per se) and seed nutritional traits. The trend noted in groundnut was opposite: namely, more emphasis (17% increase) on the use of yield and quality‐enhancing germplasm from 2000–2004, which changed to increased (42% increase) the use of stress‐ tolerant germplasm from 2005–2009, with emphasis (46% increase) from 2010–2014 on stress tolerance, yield, and quality enhancement. All of this was possible because of the consistent efforts led by Hari and his colleagues (including those from ICRISAT and NARS countries) to use representative subsets in the identification of new sources of variation with agronomically beneficial traits, and to promote the breeders’ willingness to use new germplasm as a resource in crop breeding. 6. On‐farm Conservation and  Use of  Diversity. On‐farm conservation and evaluation of genetic resources provides farmers with the ­opportunity to select germplasm adapted to their climate conditions. In a­ ddition, it also allows evolution of new genetic variants as a result of climate change and variability effects. This facilitates greater and more rapid dissemination of promising seeds among the farming community. Hari’s collaborative work with NARS partners on the evaluation of core/mini‐core collections of finger and foxtail millets, through a project on farmers’ fields in Africa and Asia, provided the farmers with opportunities to access and appreciate the diversity of these neglected crops. Today, farmers own and cultivate some finger millet germplasm sources, such as IE 2440 and 4625 in Uganda, and IE 2872 and 4115 in Kenya, or finger millet (e.g. IE 3575, 4415, 4425, 6045, 6337) and foxtail millet (e.g. ISe 156, 1575) in India. In addition, the NARS partners from these countries have identified stress‐tolerant germplasm that they are using in breeding programs to enhance the genetic potential of these crops. 7.  Wild Relatives and Cultigen Genepool.  Wild relatives and their derivatives are sources of variation for agronomic traits, which include stress tolerance, yield, and seed quality. Wild Cicer species, and particularly those from secondary and tertiary genepools that have high levels of resistance to stress tolerance, require vernalization and/or

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extended day‐length treatments to synchronize their flowering with cultivated chickpea, for interspecific crosses. The use of vernalization and/or photoperiod response enabled Hari and his colleagues to introduce synchronized flowering into a few Cicer species, similar to that of cultivated chickpea (Sharma and Upadhyaya, 2015a). This contributes significantly not only to enhanced use of Cicer species for chickpea improvement, but also to improvements in the regeneration efficiency of Cicer species and their rapid generation turnover. Cajanus albicans (Wight & Arn.) van der Maesen is a species from the secondary genepool of pigeonpea, and it is known for the long life of its large leaves (leaflet length, 4.4–6.8  cm; leaflet width, 3.1–5.8  cm). Hence, it is an important source of animal feed in semi‐arid tropical regions. It possesses broader pods (9.6–15.0 mm) and high seed numbers (5–7 per pod), is resistant to abiotic (e.g. drought, salinity) and biotic (e.g. pod fly, pod wasp, Alternaria blight, sterility mosaic) stresses, and its high seed protein content (up to 32%) make it particularly attractive (Figure 1.1). Hari had to wait for about 500 days to see

Figure 1.1.  Cajanus albicans, a wild species from a secondary genepool with many desirable characteristics, and a potential source for gene introgression in cultivated pigeonpea.

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the flowering in C. albicans, and another 50–58 days to harvest the mature pods to complete the characterization data on this species. Notably, this produces partial fertile hybrids (Mallikarjuna et al., 2011 and references therein), thus, providing a potential source to broaden the cultigen genepool in pigeonpea. 8.  Gaps in Collections.  Identifying gaps in collections and enriching collections with new sources is a critical function of genebank curators. Hari’s work on gap analysis, using geo‐referenced pearl millet landraces from Asian countries (5,768 accessions), revealed parts of the Bihar, Madhya Pradesh, Maharashtra, Rajasthan, and Uttar Pradesh provinces of India as the major geographical gaps in the world collection of pearl millet at ICRISAT (Upadhyaya et al., 2010b). His similar studies involving pearl millet landraces from southern and eastern Africa (3,750 accessions), and those from west and central Africa (6,434 accessions) also allowed Hari to identify regions in Africa that were not fully represented in ICRISAT collection (i.e. central Sudan and Tanzania, eastern Botswana, west and central Zambia, eastern and central Zimbabwe, southern Mauritania, Niger and Chad and northern Benin, Ghana, and Nigeria) (Upadhyaya et al., 2009c, 2012f). Based on this gap analysis by Hari and requests from NARS partners, the ICRISAT regional genebanks in Africa organized collection missions and collected 6,625 new samples of mandate crops from west and central Africa and southern and eastern Africa regions. These, in my opinion, are important milestones achieved by Hari and his group that further enriched the germplasm collection at ICRISAT. Hari’s work further revealed that when landraces from the 5°–10°N latitude regions were grown at Patancheru, India, these flowered late and grew tall, and they also produced more tillers. Conversely, those from the 10°–15°N latitude regions had fewer tillers, but with long and thick panicles and larger seeds. Also, landraces from the 10°–15°S and 20°–25°S latitudes are good sources of resistance to bird damage (long‐ bristled panicle). Furthermore, Hari found that the landraces of the lower latitude regions (12.5 hours) and/or temperature ( 75 g). Hari strongly believes that this exceptionally large seed size trait that he recovered originated as result of cryptic genetic variation. B.  Educator and Leader Hari has an immense passion for teaching, and he can spend hours explaining the fundamentals of population genetics and the nuances of analysis and data interpretation. Hari taught a population genetics course to postgraduates at the University of Agricultural Sciences Dharwad, India; elementary genetics course to undergraduates at ‘GB Pant’ University of Agriculture and Technology, Pantnagar, India; and a

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genetics and advances in agricultural botany course at University of Agricultural Science, Dharwad, India. Hari has shown to the world that a genebank curator’s role is not only confined to collection, maintenance, and archiving germplasm, but beyond this there exist abundant opportunities to mine and enhance the value of the genetic resources in crop improvement programs. Six of his students have conducted research using mini‐core collections for their PhD theses. C.  International Collaborations Hari has the amazing ability and scientific competence to collaborate with diverse groups and institutions across continents. He collaborates both nationally and internationally with diverse groups of researchers, both from developed and developing countries. He has developed strong links with many research programs, including the University of Agricultural Sciences, the National Bureau of Plant Genetic Resources, and with the Indian Council of Agricultural Research institutions in India. He also has links with universities in the USA (Texas A&M University, College Station and University of Texas, Texas; Kansas State University, Manhattan, Kansas; Columbia University, New York; Cornell University, Ithaca, New York; University of Georgia, Athens, Georgia; Louisiana State University, Lafayette, Louisiana; University of California, Davis, California; Clemson University, Clemson, South Carolina; New Mexico State University, New Mexico), and with the University of Western Australia, Crawley, Australia, and University Hohenheim, in Germany. His collaborative research has revolved around the use of genetic and genomic resources in crop improvement, which has ranged from strengthening and managing germplasm collections and identifying trait‐specific climate‐smart germplasm through understanding the genetics, physiological, and molecular bases of trait expression and inheritance, to enriching and deriving strength from genomic sciences to enhance the use of germplasm in crop breeding at ICRISAT and elsewhere. D. Recognition 1. Awards.  Among the several awards Hari has received (Table 1.4), the most prominent include the prestigious ‘Harbhajan Singh Memorial Award’ for his outstanding contributions and great impact in the field of plant genetic resources in India, the ‘Frank N Meyer Medal’ for outstanding contributions of global significance to the conservation and use of plant genetic resources, the ‘Crop Science Research Award’, and the award for ‘International Service to Crop Science Globally’.

Table 1.4. Some of the awards and honours received by Hari Deo Upadhyaya from 2002 to 2017. Year

Award

Contribution

Awarding agency

2017

Fellow of National Academy of Agricultural Sciences Honorary Fellow of Uttar Pradesh Academy of Agricultural Sciences, India Harbhajan Singh Memorial Award

Outstanding contributions in groundnut breeding and plant genetic resources management Outstanding contribution in the Management of Biodiversity

National Academy of Agricultural Sciences, India Uttar Pradesh Academy of Agricultural Sciences, India

Biennium award for scientific excellence, leadership, outstanding contributions and great impact in the field of plant genetic resources (2013–2014) Outstanding service to crop science globally

Indian Society of Plant Genetic Resources Crop Science Society of America

Outstanding contribution to VAAS‐ICRISAT partnership in agricultural development Outstanding contribution to NARC‐ICRISAT partnership on the occasion of 40 years of NARC‐ICRISAT R4D Partner celebration Outstanding contribution to global significance of the conservation and use of plant genetic resources Outstanding contribution to crop science research of global significance Outstanding contributions to the field of plant genetic resources leading to significant growth in agriculture Outstanding contribution ‘collecting, preserving, characterizing, and distributing genetic resources of ICRISAT mandate species for use by all researchers in the world’ Outstanding contribution in devising strategy for enhanced germplasm use by mini‐core collection in dry land crops Outstanding contributions in devising strategy for enhanced germplasm use by mini‐core collection in dry land crops Jointly shared with CLL Gowda and RP Thakur for ‘Outstanding Partnership of the CGIAR Genebank Community’ Strategies for enhanced use of germplasm through improved early maturing groundnut in Asia and Africa Contribution to ‘reduction in poverty, hunger and malnutrition through sustainable increase in productivity by broadening the genetic base of crops and insuring against vulnerability to disease and pests’ Outstanding contribution to chickpea improvement Jointly awarded to chickpea team (including Hari Upadhyaya) at ICRISAT and ICARDA for outstanding contribution to chickpea improvement

Vietnam Academy of Agriculture Sciences Nepal Agriculture Research Council Crop Science Society of America

2016

2015 2014 2014

International Service in Crop Science Award Plaque of Appreciation

2014

Certification of recognition

2013

Frank N Meyer Medal

2013 2012

Crop Science Research Award Honorary Fellow of Indian Society of Plant Genetic Resources Millennium Science Award

2009

2009 2008 2006 2005

Fellow of Crop Science Society of America Fellow of American Society of Agronomy CGIAR Outstanding Science Award Doreen Mashler

2003

Millennium ICRISAT Outstanding Scientist Award

2002 2002

Doreen Mashler King Baudouin Award

Crop Science Society of America Indian Society of Plant Genetic Resources ICRISAT

Crop Science Society of America American Society of Agronomy CGIAR ICRISAT ICRISAT

ICRISAT CGIAR

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2. Honours. Hari Upadhyaya is a fellow of the Crop Science Society of America (CSSA), the American Society of Agronomy (ASA), the National Academy of Agricultural Sciences, India, and the Uttar Pradesh Academy of Agricultural Sciences, India and a member of the Fellows Committee of CSSA and ASA. He is a member of the Crop Science Research Awards Committee and the Seed Science Awards Committee of the CSSA, and Chair of the Seed Science Award and Crop Science Research Award Committees of CSSA (Table 1.4). Hari is currently an Adjunct Professor at the University of Western A ­ ustralia and at Kansas State University, Manhattan, Kansas, USA. 3. Service. As well as being Secretary of the ICRISAT Plant Materials Identification Committee (PMIC), which clears the proposals for registration of elite genetic stocks in scientific journals, Hari also serves as member of the Controlled Environment Research Advisory Committee, Institutional Biosafety Committee, and Research Committee. Hari had a critical role in seeking approval from PMIC to facilitate the release of elite lines with unique characteristics (as both germplasm and advanced varieties). The Research Committee is a very powerful committee that advices the management group on ICRISATs R4D policies and priorities to ensure ­science quality, research excellence, and consistency with the strategic, business and medium‐term plans of ICRISAT. Hari serves as Associate ­Editor of Crop Science, and has been a member of Advisory board/Editorial Board of Akdeniz Univ. J. Fac. Agric. (also known as Mediterranean Agric. Sci.), EKIN Journal of Crop Breeding and Genetics, Field Crops Research, and The Scientific World Journal. In addition, he also acts as Regional Editor of the Asian Journal of Agricultural Sciences, and Section Editor of the Journal of Semi‐Arid Tropical Agricultural Research (J. SAT Agric). V. PUBLICATIONS Hari has published a total of 812 articles, of which 291 have been in international peer‐reviewed journals, and they include journal articles, commissioned reviews, and book chapters. He has averaged 11.6 articles per year, with three articles per year as first author. Hari has co‐authored several papers that are published in journals with high impact factors. In  addition, Hari has co‐authored several commissioned reviews on ­subjects as diverse as abiotic stress tolerance and transgenes, genomics and agrobiodiversity, global warming impacts on food, nutrition, and agrobiodiversity, haploids and plant breeding, host‐plant and rhizobium genomics, landraces as source of abiotic stress adaptation, molecular

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breeding, phytochemicals and staple food crops, and ­ pre‐breeding. These have been well‐received globally by the research community. Hari’s collaborative research has generated new knowledge (i.e. trait inheritance) and materials (i.e. genetic and genomic resources) of immense value to applied plant breeding. The genebank manual ‘Managing and Enhancing the Use of Germplasm – Strategies and Methodologies’, which he co‐authored with CL Laxmipathi Gowda, is widely referred to by researchers globally to manage the genetic resources of ICRISAT mandate crops and small millets. Likewise, NARS researchers have found an Information Bulletin ‘Mini‐Core Collections for Efficient Utilization of Plant Genetic Resources in Crop Improvement Programs’ very handy for the development of similar germplasm collections in other crops. Hari has co‐edited three books, one exclusively on sorghum, and the other two on genetics and genomic resources of cereals and legumes. VI. PRODUCTS A. Cultivars As a groundnut breeder, Hari developed 27 cultivars (ICGV#) that have been released in 18 countries (Table 1.5), some with wide adaptation. For example, ICGV 86015 was released in Nepal, Niger, Pakistan, Sri  Lanka, and Vietnam; ICGV 93437 in Mozambique, South Africa, Zambia, and Zimbabwe; and ICGV 86143 in India, Vietnam, and Zambia. An early maturing (90–95 days in the rainy season), drought‐ tolerant (both mid‐season and end‐of‐season droughts) and foliar ­disease‐tolerant (rust, late leaf spot) cultivar, ICGV 91114 is becoming very popular in the Andhra Pradesh, Maharashtra, Odisha, and Telangana provinces of India (Figure 1.3). Some of the recent releases (ICGV‐SM#) from the ICRISAT Regional Program in Malawi have the distinct stamp of Hari’s selections (Table 1.5). B. Registrations Hari has registered 24 elite germplasm lines in groundnut that show agronomically beneficial traits, such as: early maturity (Nigam et al., 1995; Upadhyaya et al., 1998, 2002c, 2002d); early maturity and fresh seed dormancy (Upadhyaya et al., 1997a, 2001e); early maturity and  large seed size (Upadhyaya et al., 2005b); early maturity and lower susceptibility to rust (Upadhyaya et al., 2001d); early maturity and lower susceptible to rust and late leaf spot and tolerance to low temperature at germination (Upadhyaya et al., 2002c); early maturity

Table 1.5.  List of 27 groundnut cultivars and their local names released in 18 ­countries in Africa and Asia. Country

Variety

Country

Variety

Bangladesh

ICGV 94322 (Barichinabadam‐8) ICGV 96342 (BARI Chinabadam‐9) ICGV 96346 ICGV 86143 (BSR 1) ICGV 92195 (Pratap Mungphali‐2) ICGV 91114 (Devi) ICGV 93468 (Avtar) ICGV 00348 ICGV 00350 ICGV 00351 (Co7) ICGV 00298 R‐8808 (Apoorva) ICGV‐SM 01514 ICGV‐SM 01724 ICGV‐SM 01731

Nepal

ICGV 86015 (Jayanti)

Niger

ICGV 86015

Pakistan Philippines South Africa

ICGV 86015 (BARD 92) ICGV 00350 ICGV 93437 (Nyanda)

Sri Lanka Tanzania

ICGV 86015 (Tikiri) ICGV‐SM 01711 ICGV‐SM 01721 ICGV 95278 ICGV 86155 (Salomat) ICGV 86143 (LO5) ICGV 86015 (HL 25) ICGV 86143 (MGS 2) ICGV 93437 (Nyanda) ICGV‐SM 03517 (Wamusanga) ICGV 93437 (Nyanda) ICGV 94297 (Ilanda)

India

Malawi

Mali Mozambique

Myanmar

ICGV 86015 ICGV 93437 (Nyanda) ICGV‐SM 01513 ICGV‐SM 01514 ICGV 93382 (Sinpadetha 7) ICGV 94301 (Sinpadetha 8) ICGV 94361 (Sinpadetha 9)

Timor Leste Uzbekistan Vietnam Zambia

Zimbabwe

Figure  1.3.  ICGV 91114, an improved groundnut variety that was developed by Hari Deo Upadhyaya and shows early maturity (90 days), drought tolerance and resistance to rust and late leaf spot, which is now popularly grown in India.

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and lower ­susceptibility to peanut bud necrosis disease (Dharamraj et al., 1996); and resistance to natural seed infections, in vitro seed colonization, and with low levels of aflatoxin contamination by A flavus (Rao et al., 1995; Upadhyaya et al., 2001c). These elite germplasms/ varieties are available to researchers globally after signing the Standard Materials Transfer Agreement with ICRISAT.

REFERENCES CITED AND FURTHER READING Bailey, W.K., and R.O. Hammons (1975). Registration of Chico germplasm. Crop Science 15: 105. Diamond, J., and P. Bellwood (2003). Farmers and their languages: The first expansions. Science 300: 597–603. Dwivedi, S., K. Sahrawat, H.D. Upadhyaya, and R. Ortiz (2013). Food, nutrition and agrobiodiversity under global climate change. Advances in Agronomy 120: 1–128. Frankel, O.H., and A.H.D. Brown (1984). Plant genetic resources today: a critical appraisal. In: Holden, J.H.W., and Williams, J.T (eds). Crop genetic resources: conservation and ­evaluation, pp. 249–268. Allen and Unwin, Winchester, Massachusetts. Haware, M.P., and Y.L. Nene (1982). Races of Fusarium oxysporum f.sp. ciceri. Plant Disease 66: 809–810. ICRISAT (2014). Research Program Grain Legumes Archival Report 2012–13 (Restricted circulation). ICRISAT (2015). Research Program Grain Legumes Archival Report 2014 (Restricted circulation). Jobling, M.A., E. Hollox, M. Hurles, T. Kivisild, and C. Tyler‐Smith (2013). Human Evolutionary Genetics. 2nd edition, p. 670. Garland Science, Taylor and Francis Group, New York and London. Ketata, H., E.L. Smith, L.H. Edwards, and R.W. McNew (1976). Detection of epistasis, additive and dominance variation in winter wheat (Triticum aestivum L. em Thell.). Crop Science 16, 1–4. Kumar, J., and M.P. Haware (1982). Inheritance of resistance to wilt (Fusarium oxysporum f.sp. ciceri) in chickpea (Cicer arietinum L.). Phytopath 72: 1035–1036. Legumes Program, ICRISAT (1993). Annual Report 1992. Patancheru, A.P. 502324. India: Legumes Program, International Crops Research Institute for the Semi‐Arid Tropics. 264 pp. (Semi‐formal publication). Mallikarjuna, N., K.B. Saxena, and D.R. Jadhav (2011). Cajanus. In: Kole, C. (ed). Wild crop relatives: genomic and breeding resources, p.21–33. Berlin, Springer. Monyo, E.S., and C.L.L. Gowda (2014). Grain legumes strategies and seed roadmaps for select countries in Sub‐Saharan Africa and South Asia. Tropical Legumes II Project Report. Patancheru 502324, Telangana, India: International Crops Research Institute for the Semi‐arid Tropics (ICRISAT). ISBN 978‐92‐9066‐559‐5. Order code: BOE 062. 292 pp. Nene, Y.L., M.P. Haware, and M.V. Reddy (1978). Diagnosis of some wilt‐like disorders of chickpea (Cicer arietinum L.). ICRISAT Information Bulletin 3. ICRISAT, Patancheru 502324, AP, India. Nigam, S.N., F. Waliyar, R. Aruna, S.V. Reddy, P. Lava Kumar, P.Q. Craufurd, A.T. Diallo, B.R. Ntare, and H.D. Upadhyaya (2009). Breeding peanut for resistance to aflatoxin contamination at ICRISAT. Peanut Science 36: 42–49.

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Sehgal, J., D.K. Mandal, C. Mandal, and S. Vadivelu (1992). Agroecological regions of India. Second edition, Technical Bulletin NBSS & LUP publ 24 NBSS & LUP. Nagpur, India. Simpson, C.E., S.C. Nelson, J.L. Starr, K.E. Woodard, and O.D. Smith (1993). Registration of TxAG 6 and TxAG 7 peanut germplasm lines. Crop Science 33: 1418. Smart, J., W.C. Gregory, and M.P. Gregory (1978). The genomes of Arachis hypogaea. I. Cytogenetic studies of putative genome donors. Euphytica 27: 665–675. Stein, A.J (2010). Global impacts of human mineral nutrition. Plant and Soil 335: 113–154. Vasudeva Rao, M.J., S.N. Nigam, and A.K.S. Huda (1992). The thermal time concept as a selection criterion for earliness in peanut. Peanut Science 19: 7–10.

SELECTED PUBLICATIONS OF HARI DEO UPADHYAYA Alice, K., D. Bajaj, M.S. Saxena, S. Tripathi, H.D. Upadhyaya, C.L.L. Gowda, S. Singh, M. Jain, A.K. Tyagi, and S.K. Parida (2013). Functionally relevant microsatellite markers from chickpea transcription factor genes for efficient genotyping applications and trait association mapping. DNA Research 20: 355–373. Aruna, R., D. M. Rao, L.J. Reddy, H.D. Upadhyaya, and H.C. Sharma (2005). Inheritance of trichomes and resistance to pod borer (Helicoverpa armigera) and their association in interspecific crosses between cultivated pigeonpea (Cajanus cajan L.) and its wild relative C. scarabaeides. Euphytica 145: 247– 257. Aruna, R., D.M. Rao, S. Sivaramakrishnan, L.J. Reddy, P. Bramel, and H.D. Upadhyaya (2008). Efficiency of three DNA markers in revealing genetic variation among wild Cajanus species. Plant Genetic Resources 7: 113–121. Aruna, R., M. Rao, L.J. Reddy, S. Sivaramakrishna, and H.D. Upadhyaya (2007). Influence of pod maturity and level of domestication on biochemical components in wild and cultivated pigeonpea (Cajanus cajan). Annals of Applied Biology 151: 25–32. Babu, T.K., R. Sharma, H.D. Upadhyaya, P.N. Reddy, S.P. Deshpande, S. Senthilvel, N.D.R.K. Sarma, and R.P. Thakur (2013a). Evaluation of genetic diversity in Magnaporthe grisea populations adapted to finger millet using simple sequence repeats (SSRs) markers. Physiological and Molecular Plant Pathology 84: 10–18. Babu, T.K., R.P. Thakur, H.D. Upadhyaya, P.N. Reddy, R. Sharma, A.G. Girish, and N.D.R.K. Sarma (2013b). Resistance to blast (Magnaporthe grisea) in a mini‐core collection of finger millet germplasm. European Journal of Plant Pathology 135: 299–311. Babu, T.K., R. Sharma, R.P. Thakur, H.D. Upadhyaya, P.N. Reddy, and A.G. Girish (2015). Selection of host differentials for elucidating pathogenic variation in Magnaporthe grisea populations adapted to finger millet (Eleusine coracana (L.) Gaertn.). Plant Disease 99(12), 1784–1789. doi: http: //dx.doi.org/10.1094/PDIS‐10‐14‐1089‐RE. Bajaj, D., S. Das, HD. Upadhyaya, R. Ranjan, S. Badoni, V. Kumar, S. Tripathi, C.L.L. Gowda, S. Sharma, S. Singh, A. Tyagi, and S.K. Parida (2015a). A genome‐wide combinatorial strategy dissects complex genetic architecture of seed coat color in chickpea. Frontiers in Plant Science 6: 979. doi: 10.3389/fpls.2015.00979. Bajaj, D., M.S. Saxena, A. Kujur, S. Das, S. Badoni, S. Tripathi, H.D. Upadhyaya, C.L.L. Gowda, S. Sharma, S. Singh, A. K. Tyagi and S.K. Parida (2015b). Genome‐wide c­ onserved non‐coding microsatellite (CNMS) marker‐based integrative genetical genomics for quantitative dissection of seed weight in chickpea. Journal of Experimental Botany 66: 1271–1290. Bajaj, D., H.D. Upadhyaya, Y. Khan, S. Das, S. Badoni, T. Shree, V. Kumar, S. Tripathi, C.L.L. Gowda, S. Singh, S. Sharma, A. Tyagi, D. Chattopadhyay, and S. Parida (2015c). A combinatorial approach of comprehensive QTL‐based comparative genome mapping

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and transcript profiling identified a seed weight‐regulating candidate gene in chickpea. Nature Scientific Reports 5: 9264. doi: 10.1038/srep09264. Bajaj, D., R. Srivastava, M. Nath, S Tripathi, C. Bharadwaj, H.D. Upadhyaya, A.K. Tyagi and S.K. Parida. (2016a). EcoTILLING‐based association mapping efficiently delineates functionally relevant natural allelic variants of candidate genes governing agronomic traits in chickpea. Frontiers in Plant Science 7: 450. doi: 10.3389/fpls.2016.00450. Bajaj, D., H.D. Upadhyaya, S. Das, V. Kumar, C.L.L. Gowda, S. Sharma, A.K. Tyagi, and S.K. Parida (2016b). Identification of candidate genes for dissecting complex branch number trait in chickpea. Plant Science 245: 61–70. Barkley, N.A., H.D. Upadhyaya, L. Boshou, and C.C. Holbrook (2016). Global resources of genetic diversity in peanut. Peanuts, 67–109. http: //dx.doi.org/10.1016/ B978‐1‐63067‐038‐2.00003‐4. Billot, C., P. Ramu, S. Bouchet, J. Chantereau, M. Deu, L. Gardes, J‐L Noyer, J.‐F. Rami, R.  Rivallan, Y. Li, P. Lu, T. Wang, R.T. Folkertsma, E. Arnaud, H.D. Upadhyaya, J.‐C. Glaszmann, and C.T. Hash (2013). Massive sorghum collection genotyped with SSR markers to enhance use of global genetic resources. PLoS One 8: e59714. Bohra, A., A. Dubey, R. Saxena, P.R. Varma, K.N. Poornima, N. Kumar, A. Farmer, G. Srivani, H.D. Upadhyaya, R. Gothalwal, R. Ramareddy, D. Singh, K.B. Saxena, P.B. Kavikishor, N. Singh, C. Town, G. May, D. Cook, and R.K. Varshney (2011). Analysis of BAC‐end sequences (BESs) and development of BES‐SSR markers for genetic mapping and hybrid purity assessment in pigeonpea (Cajanus spp.) BMC Plant Biology 11: 56. http://www. biomedcentral.com/1471‐2229/11/56. Bohra, A., R.K. Varshney, N. Mallikarjuna, K.B. Saxena, H.D. Upadhyaya, and V. Isabel (2010). Harnessing the potential of crop wild relatives through genomics tools for pigeonpea improvement. Journal of Plant Biology 37: 83–98. Burow, M.D., M.G. Selvaraj, H.D. Upadhyaya, P. Ozais‐Akins, B. Guo, D.J. Bertioli, S.C. de Macedo Leal‐Bertioli, M. de C. Moretzsohn, and P.M. Guimaraes (2008). Genomics of Peanut, a Major Source of Oil and protein. In: Moore, P.H., and R. Ming (eds). Genomics of Tropical Crops, pp. 421–440. Springer, New York. Challinor, A.J., T. Wheeler, D. Hemming, and H.D. Upadhyaya (2009). Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotype adaptation to climate change. Climate Research 38: 117–127. Chen, X., H. Li, M.K. Pandey, Q. Yang, X. Wang, V. Garg, H. Li, X. Chi, D. Doddamani, Y. Hong, H.D. Upadhyaya, H. Guo, A.W. Khan, F. Zhu, X. Zhang, L. Pan, G.J. Pierce, G. Zhou, K.A.V.S. Krishnamohan, M. Chen, N. Zhong, G. Agarwal, S. Li, A.C., G. Zhang, S. Sharma, N. Chen, H. Liu, P. Janila, S. Li, M. Wang, T. Wang, J. Sun, X. Li, C. Li, M. Wang, L. Yu, S. Wen, S. Singh, Z. Yang, J. Zhao, C. Zhang, Y. Yu, J. Bi, X. Zhang, Z. Liu, A.H. Paterson, S. Wang, X. Liang, R.K. Varshney, and S. Yu (2016). Draft genome of the peanut A‐genome progenitor (Arachis duranensis) provides insights into geocarpy, oil biosynthesis and allergens. Proceedings of the National Academy of Sciences of the United States of America 113(24): 6785–6790. www.pnas.org/cgi/doi/10.1073/ pnas.1600899113. Cuevas, H., Z. Chengbo, T. Haibao, K. Prashant, D. Sayan, L. Yann, G. Zhengxiang, C.T. Hash, H.D. Upadhyaya, and A.H. Paterson (2016). The evolution of photoperiod‐insensitive flowering in sorghum, a genomic model for panicoid grasses. Molecular Biology and Evolution 33(9): 2417–2428. doi: 10.1093/molbev/msw120. Curan, A.B., E. Dulloo, P. Mathur, P. Brahmi, V. Tyagi, R.K. Tyagi, and H.D. Upadhyaya (2010). Plant genetic resources and germplasm use in India. Asian Biotechnology Development Review 12: 17–34. Das, S., H.D. Upadhyaya, D. Bajaj, A. Kujur, S. Badoni, L. Laxmi, V. Kumar, S. Tripathi, C.L.L. Gowda, S. Sharma, S. Singh, A.K. Tyagi, and S.K. Parida (2015a). Deploying

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QTL‐seq for rapid delineation of a potential candidate gene underlying major trait‐ associated QTL in chickpea. DNA Research 22: 193–203. Das S., H.D. Upadhyaya, R. Srivastava, D. Bajaj, C.L.L. Gowda, S. Sharma, and S. Singh, A.K. Tyagi, and S.K. Parida (2015b). Genome‐wide insertion‐deletion (InDel) marker discovery and genotyping for genomics‐assisted breeding applications in chickpea. DNA Research 22(5): 377–386. Dharamraj, P.S., H.D. Upadhyaya, V.K. Deshpande, B.S. Sarala, and V.B. Naragund (1996). R 8808 – A high yielding peanut bud necrosis tolerant groundnut variety. Journal of Oilseeds Research 13: 111–112. Divakara, B.N., H.D. Upadhyaya, A. Laxmi, and R. Das (2015). Identification of diverse genotypes with high oil content in Madhuca latifolia for further use in tree improvement. Journal of Forest Research 26: 369–379. Divakara, B.N., H.D. Upadhyaya, and B. Fandohan (2012). Identification and divergence studies of genotypes of Tamarindus indica (Fabaceae) with superior pod traits. International Journal of Biological and Chemical Sciences 5: 509–514. Divakara, B.N., H.D. Upadhyaya, and R. Krishnamurthy (2011). Identification and evaluation of diverse genotypes in Pongamia pinnata (L.) Pierre. for genetic improvement in seed traits. Journal of Biodiversity and Environmental Sciences 1: 179–190. Divakara, B.N., H.D. Upadhyaya, S.P. Wani, and C.L.L. Gowda (2010). Biology and genetics improvement of Jatropha curcas L: A review. Applied Energy 87: 732–742. Dwivedi, S.L., A.B. Britt, L. Tripathi, S. Sharma, H.D. Upadhyaya, and R. Ortiz (2015). Haploids: constraints and opportunities in plant breeding. Biotechnology Advances 33: 812–829. Dwivedi, S.L., C. Salvatore, M.W. Blair, H.D. Upadhyaya, A.A. Kumar, and R. Ortiz (2016a). Landrace germplasm for improving yield and abiotic stress adaptation. Trends Plant Science 21: 31–42. http: //dx.doi.org/10.1016/j.tplants.2015.10.012. Dwivedi, S.L., D.J. Bertioli, J.H. Crouch, J.F. Valls, H.D. Upadhyaya, A. Favero, M. Moretzsohn, and A.H. Paterson (2007a). Peanut. In: Kole, C. (ed.). Genome Mapping and Molecular Breeding in Plants. Volume II, Oilseeds, p. 117–151. Springer, Berlin Heidelberg. Dwivedi, S.L., E. Perotti, H.D. Upadhyaya, and R. Ortiz (2010). Sexual and apomictic plant reproduction in the genomics era: exploring the mechanisms potentially useful in crop plants. Sexual Plant Reproduction 23: 265–279. Dwivedi, S.L., E.T.L. van Bueren, S. Ceccarelli, S. Grando, H.D. Upadhyaya, and R. Ortiz. (2017) Diversifying food systems in the pursuit of sustainable food production and healthy diets. Trends in Plant Science http://dx.doi.org/10.1016/j.tplants.2017.06.011 Dwivedi, S.L., H.D. Upadhyaya, and D.M. Hegde (2005). Development of core collection using geographic information and morphological descriptors in safflower (Carthamus tinctorius L.) germplasm. Genetic Resources and Crop Evolution 52: 821–830. Dwivedi, S.L., H.D. Upadhyaya, C. Gehring, P. Subudhi, V. Bajic, and R. Ortiz (2009). Enhancing abiotic stress tolerance in cereals through breeding and transgenic interventions. Plant Breeding Reviews 33: 31–114. Dwivedi, S.L., N. Puppala, H.D. Upadhyaya, N. Manivannan, and S. Singh (2008a). Developing a core collection of peanut specific to Valencia market type. Crop Science 48: 625–632. Dwivedi, S.L., H.D. Upadhyaya, H.T. Stalker, D. Bertioli, S. Nielsen, R. Ortiz, and M.W. Blair (2008b). Enhancing crop gene pools with beneficial traits using wild relatives. Plant Breeding Reviews 30: 179– 230. Dwivedi, S.L., H.D. Upadhyaya, I.‐M. Chung, De Vita, Pasquale, S. Garcia‐Lara, D.  Guajardo‐Flores, J.A. Gutiérrez‐Uribe, S.R.O.S. Saldívar, G. Rajakumar, K.L. Sahrawat, J. Kumar, and R. Ortiz (2016). Exploiting phenylpropanoid derivatives to enhance the nutraceutical values of cereals and legumes. Frontiers in Plant Science 7: 763. doi: 10.3389/fpls.2016.00763.

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Dwivedi, S.L., H.D. Upadhyaya, S. Senthilvel, C.T. Hash, K. Fukunaga, X. Diao, D. Santra, D. Baltensperger, and M. Prasad (2012). Millets: genetic and genomic resources. Plant Breeding Reviews 35: 247–375. Dwivedi, S.L., J.H. Crouch, D.J. Mackill, Y. Xu, M.W. Blair, M. Ragot, H.D. Upadhyaya, and R. Ortiz (2007b). The molecularization of public sector crop breeding: Progress, problems and Prospects. Advances in Agronomy 95: 163–318. Dwivedi, S.L., K.L. Sahrawat, H.D. Upadhyaya, A. Mengoni, M. Galardine, M. Bazzicalupo, E.G. Biondi, M. Hungria, G. Kaschuk, M. Blair, and R. Ortiz (2014). Advances in host plant and rhizobium genomics to enhance symbiotic nitrogen fixation in grain ­legumes. Advances in Agronomy 129: 1–116. Dwivedi, S.L., K.L. Sahrawat, H.D. Upadhyaya, and R. Ortiz (2013). Food, nutrition and agro‐biodiversity under global climate change. Advances in Agronomy 120: 1–128. Dwivedi, S.L., M.W. Blair, H.D. Upadhyaya, R. Serraj, J. Balaji, H.K. Buhariwalla, R. Ortiz, and J.H. Crouch (2006). Using genomics to exploit grain legume biodiversity in crop improvement. Plant Breeding Reviews 26: 171–357. Engin, Y., H.D. Upadhyaya, and B. Uzun (2015). Molecular diagnosis to identify new sources of resistance to sclerotinia blight in groundnut (Arachis hypogaea L.). Euphytica 203: 367–374. Gadag, R.N., and H.D. Upadhyaya (1995). Heterosis in soybean (Glycine max (L.) Merrill). Indian Journal of Genetics 55: 308–314. Gadag, R.N., H.D. Upadhyaya, and J.V. Goud (1999). Genetic analysis of yield, protein, oil and other related traits in soybean. Indian Journal of Genetics 59: 487–492. Gaur, P.M., K.B. Saxena, S.N. Nigam, B.V.S. Reddy, K.N. Rai, C.L.L. Gowda, and H.D. Upadhyaya (2012). Plant breeding research at ICRISAT. In: Principles of Plant Genetics and Breeding, 2nd Edition, pp. 556–574. Wiley‐Blackwell. Glaszmann, J.C., B. Kilian, H.D. Upadhyaya, and R.K. Varshney (2010). Accessing genetic diversity for crop improvement. Current Opinion in Plant Biology 13: 167–173. Gowda, C.L.L., and H.D. Upadhyaya (2006). International crop germplasm exchange at ICRISAT. Indian Journal of Plant Genetic Resources 19: 418–427. Gowda, C.L.L., H.D. Upadhyaya, N. Dronavalli, and S. Singh (2011). Identification of large‐seeded high‐yielding stable kabuli chickpea germplasm lines for use in crop improvement. Crop Science 51: 198–209. Gowda, C.L.L., H.D. Upadhyaya, S. Sharma, R.K. Varshney, and S.L. Dwivedi (2013). Exploiting genomic resources for efficient conservation and use of chickpea, groundnut, and pigeonpea collections for crop improvement. The Plant Genome 6. doi: 10.3835/ plantgenome2013.05.0016. Gowda, C.L.L., K.B. Saxena, R.K. Srivastava, H.D. Upadhyaya, and S.N. Silim (2012). Pigeonpea: From an orphan to a leader in food legumes. In: Gepts, P., T.R. Famula, R.L. Bettinger, S.B. Brush, A.B. Damania, P.E. McGuire, and C.O. Qualset (eds). Biodiversity in Agriculture: Domestication, Evolution and Sustainability, pp. 361–373. Cambridge University Press. Gowda, C.L.L., R. Serraj, G. Srinivasan, Y.S. Chauhan, B.V.S. Reddy, K.N. Rai, P.M. Gaur, L.J. Reddy, S.L. Dwivedi, H.D. Upadhyaya, P.N. Zaidi, H.K. Rai, P. Maniselva, and N. Mallikarjuna (2009). Opportunities for improving crop‐water productivity through genetic enhancement in dry land crops. In: S.P. Wani, J. Rockstron, and T.  Oweis (eds). Rain‐fed Agriculture: Unlocking Potential, pp. 133–163. CAB International. Gowda, C.L.L., S. Ramesh, S. Chandra, and H.D. Upadhyaya (2005). Genetic basis of pod borer (Helicoverpa armigera) resistance and grain yield in desi and kabuli chickpea (Cicer arietinum L.) under unprotected conditions. Euphytica 145: 199–214.

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Grace, D., G. Mahuku, V. Hoffmann, C. Atherstone, H.D. Upadhyaya, and R.  Bandyopadhyay (2015). International agricultural research to reduce food risks: Case studies on aflatoxins. Food Security 7: 569–582. Gujaria, N., A. Kumar, P. Dauthal, A. Dubey, H. Pavana, A.B. Prakash, F. Andrew, B.  Mangla,T. Shah, P. Gaur, H.D. Upadhyaya, S. Bhatia, D. Cook, G. May, and R.K. Varshney (2011). Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.). Theoretical and Applied Genetics 122: 1577–1589. Halewood, M., R. Sood, R.S. Hamilton, A. Amri, I. Van der Houwe, N. Roux, D. Dumet, J. Hanson, H.D. Upadhyaya, A. Jorge, and D. Tay (2012). Changing rates of acquisition of plant genetic resources by international gene banks: setting the scene to monitor an impact of the international treaty. In: Halewood, M., I.L. Noriega, S. Louafi (eds). Crop Genetic Resources as a Global Commons Challenges in International Law and Governance, pp. 99–131. http://grpi2.wordpress.com/2012/12/11/global‐commons‐book/. Hamidou, F., P. Ratnakumar, O. Halilou, O. Mponda, T. Kapewa, E. Monyo, I. Faye, B.R. Ntare, S.N. Nigam, H.D. Upadhyaya, and V. Vadez (2012). Selection of intermittent drought tolerant lines across years and locations in the reference collection of groundnut (Arachis hypogaea L.). Field Crops Research 126: 189–199. Hay, F.R., N.R.S. Hamilton, B.J. Furman, H.D. Upadhyaya, K.N. Reddy, and S.K. Singh (2013). Cereals. In: Normah, M.N., Chin, H.F., Reed, Barbara M. (eds). Conservation of Tropical Plant Species. 2013, XIV, pp 293–315. ISBN 978‐1‐4614‐3775‐8. http://www. springer.com/978‐1‐4614‐3775‐8. Hiremath, P.J., A. Kumar, R.V. Penmetsa, A. Farmer, J.A. Schlueter, S.K. Chamarthi, A.M. Whaley, N. Carrasquilla‐Garcia, P.M. Gaur, H.D. Upadhyaya, P.B.K. Kishor, T.M. Shah, D.R. Cook, and R.K. Varshney (2012). Large‐scale development of cost‐effective SNP marker assays for diversity assessment and genetic mapping in chickpea and ­comparative mapping in legumes. Plant Biotechnology Journal 10: 716–732. Huang, L., H. Jiang, X. Ren, Y. Chen, Y. Xiao, X. Zhao, M. Tang, J. Huang, H.D. Upadhyaya, and L. Boshou (2012). Abundant microsatellite diversity and oil content in wild Arachis Species. PLoS One 7: e50002. Jorge, M.A., G. Claessens, J. Hanson, M.E. Dulloo, E. Goldberg, I. Thormann, S. Alemayehu, E. Gacheru, A. Amri, E. Benson, D. Dumet, N. Roux, P. Rudebjer, R.S. Hamilton, I. Sanchez, S. Sharma, S. Taba, H.D. Upadhyaya, and I.V.D. Houwe (2011). Knowledge sharing on best practices for managing crop genebanks. Agricultural Information Worldwide 3: 101–106. Kamala, V., M. Muraya, S.L. Dwivedi, and H.D. Upadhyaya (2014). Wild sorghums‐ Their potential use in crop improvement. In: Yi‐Hong Wang, H.D. Upadhyaya, and Chittaranjan Kole (eds). Genetics, Genomics and Breeding of Sorghum, pp. 56–89. Taylor & Francis Group. ISBN: K21635/9781482210088. Kashiwagi, J., H.D. Upadhyaya, and L. Krishnamurthy (2010). Significance and genetic diversity of SPAD chlorophyll meter reading in chickpea germplasm in the semi‐arid environments. Journal of Food Legumes 23: 99–105. Kashiwagi, J., L. Krishnamurthy, H.D. Upadhyaya, H. Krishna, S. Chandra, V. Vadez, and R. Serraj (2005). Genetic variability of drought‐avoidance root traits in the mini‐core germplasm collection of chickpea (Cicer arietinum L.). Euphytica 146: 213–222. Kashiwagi, J., L. Krishnamurthy, P.M. Gaur, H.D. Upadhyaya, R.K. Varshney, and S. Tobita (2013). Traits of relevance to improve yield under terminal drought stress in chickpea (C. arietinum L.). Field Crops Research 145: 88–95. Kashiwagi, J., L. Krishnamurthy, P.M. Gaur, S. Chandra, and H.D. Upadhyaya (2008). Estimation of gene effects of the drought avoidance root characteristics in chickpea (C. arietinum L.). Field Crops Research 105: 64–69.

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Kashiwagi, J., L. Krishnamurthy, R. Purushothaman, H.D. Upadhyaya, P.M. Gaur, C.L.L. Gowda, O. Ito, and R.K. Varshney (2015). Scope for improvement of yield under drought through the root traits in chickpea (Cicer arietinum L.). Field Crops Research 170: 47–54. Kassa, M.T., R.V. Penmetsa, N. Carrasquilla‐Garcia, B.K. Sarma, S. Datta, H.D. Upadhyaya, R.K. Varshney, E.J.B. con Wettberg, and D. Cook (2012). Genetic patterns of domestication in pigeonpea (Cajanus cajan (L.) Millsp.) and wild Cajanus relatives. PLoS One 7: e39563. Kaur, G., S. Kumar, H. Nayyar, and H.D. Upadhyaya (2008). Cold stress injury during pod‐filling in chickpea (Cicer arietinum L.): Effects on quantitative and qualitative components of seeds. Journal of Agronomy and Crop Science 194: 457–464. Khedikar, Y., M.V. C. Gowda, C. Sarvamangala, K.V. Patgar, H.D. Upadhyaya, and R.K. Varshney (2010). A QTL study on late leaf spot and rust revealed one major QTL for molecular breeding for rust resistance in groundnut (Arachis hypogaea L.) Theoretical and Applied Genetics 121: 971–984. Khera, P., H.D. Upadhyaya, M.K. Pandey, M. Roorkiwal, M. Sriswathi, P. Janila, Y. Guo, M.R. McKain, E.D. Nagy, S.J. Knapp, J. Leebens‐Mack, J.A. Conner, P. Ozias‐Akins, and R.K. Varshney (2013). Single nucleotide polymorphism–based genetic diversity in the reference set of peanut (Arachis spp.) by developing and applying cost‐effective kompetitive allele specific polymerase chain reaction genotyping assays. The Plant Genome 6. doi: 10.3835/plantgenome2013.06.0019. Khoury, C.K., N.P. Castañeda‐Alvarez, H.A. Achicanoy, C.C. Sosa, V. Bernau, M.T. Kassa, S.L. Norton, L.J.G. van der Maesen, H.D. Upadhyaya, J. Ramírez‐Villegas, A. Jarvis, and P.C. Struik (2015). Crop wild relatives of pigeonpea [Cajanus cajan (L.) Millsp.]: distributions, ex situ conservation status, and potential genetic resources for adaptation to abiotic stress. Biological Conservation 184: 259–270. Kim, D.H., M. Kashyap, A. Rathore, R.R. Das, S. Parupalli, H.D. Upadhyaya, S. Gopalakrishnan, P.M. Gaur, S. Singh, J. Kaur, M. Yasin, and R.K. Varshney (2014). Phylogenetic diversity of Mesorhizobium in chickpea. Journal of Biosciences 39: 513–517. Koppolu, R., H.D. Upadhyaya, S.L. Dwivedi, D.A. Hoisington, and R.K. Varshney (2010). Genetic relationships among seven sections of genus Arachis studied by SSR markers. BMC Plant Biology 10: 15. Doi: 10.1186/1471‐2229‐10‐15. Kottapalli, P., H.D. Upadhyaya, K.R. Kottapalli, P. Payton, S.L. Dwivedi, M. Burow, K.O. David, S. Sanogo, and N. Puppala (2011). Population structure and diversity in Valencia peanut germplasm collection. Crop Science 51: 1089–1100. Krishnamurthy, L., J. Kashiwagi, P.M. Gaur, H.D. Upadhyaya, and V. Vadez (2010). Sources of tolerance to terminal drought in the chickpea (Cicer arietinum L.) minicore germplasm. Field Crops Research 119: 322–330. Krishnamurthy, L., N.C. Turner, P. M. Gaur, H.D. Upadhyaya, K.H.M. Siddique, R.K. Varshney and V.Vadez (2011a). Consistent variation across soil types in salinity resistance of a diverse range of chickpea (Cicer arietinum L.) genotypes. Journal of Agronomy and Crop Science 197: 214–227. Krishnamurthy, L., H.D. Upadhyaya, K.B. Saxena, and V. Vadez (2011b). Variation for temporary waterlogging response within the mini core pigeonpea germplasm. Journal of Agricultural Science 150, 357–364. Krishnamurthy, L., J. Kashiwagi, S. Tobita, O. Ito, H.D. Upadhyaya, C.L.L. Gowda, P.M. Gaur, M.S. Sheshshayee, S. Singh, V. Vadez, and R.K. Varshney (2013a). Variation in carbon isotope discrimination and its relationship with harvest index in the reference collection of chickpea germplasm. Functional Plant Biology 40: 1350–1361 Krishnamurthy, L., J. Kashiwagi, H.D. Upadhyaya, C.L.L. Gowda, P.M. Gaur, S. Singh, R.  Purushothaman, and R.K. Varshney (2013b). Partitioning coefficient‐a trait that ­contributes to drought tolerance in chickpea. Field Crops Research 149: 354–365.

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Krishnamurthy, L., H.D. Upadhyaya, C.L.L. Gowda, J. Kashiwagi, R. Purushothaman, S. Singh, and V. Vadez (2014a). Large variation for salinity tolerance in the core collection of foxtail millet (Setaria italica (L.) P. Beauv.) germplasm. Crop and Pasture Science 65: 353–361. Krishnamurthy, L., H.D. Upadhyaya, R. Purushothaman, C.L.L. Gowda, J. Kashiwagi, S.L.  Dwivedi, S. Singh, and V. Vadez (2014b). The extent of variation in salinity ­tolerance of the minicore collection of finger millet (Eleusine coracana L. Gaertn.) germplasm. Plant Science 227: 51–59. Krishnamurthy, L., H.D. Upadhyaya, J. Kashiwagi, R. Purushothaman, S.L. Dwivedi, and V. Vadez (2016). Variation in drought‐tolerance components and their interrelationships in the minicore collection of finger millet germplasm. Crop Science 56(4): ­1914–1926. doi: 10.2135/cropsci2016.03.0191. Kujur, A., D. Bajaj, M.S. Saxena, S. Tripathi, H.D. Upadhyaya, CL.L. Gowda, S. Singh, A.K. Tyagi, M. Jain, and S.K. Parida (2014). An efficient and cost‐effective approach for genic microsatellite marker‐based large‐scale trait association mapping: identification of candidate genes for seed weight in chickpea. Molecular Breeding 34: 241–265. Kujur, A., D. Bajaj, H.D. Upadhyaya, S. Das, R. Ranjan, T. Shree, M.S. Saxena, S. Badoni, V. Kumar, S. Tripathi, C.L.L. Gowda, S. Sharma, S. Singh, A.K. Tyagi, and S.K. Parida (2015a). Employing genome‐wide SNP discovery and genotyping strategy to extrapolate the natural allelic diversity and domestication patterns in chickpea. Frontiers in Plant Science 6: 162. doi: 10.3389/fpls.2015.00162. Kujur, A., D. Bajaj, H.D. Upadhyaya, S. Das, R. Ranjan, T. Shree, M. Saxena, S. Badoni, V.  Kumar, S. Tripathi, C.L.L. Gowda, S. Sharma, S. Singh, A. Tyagi, and S. Parida (2015b). A genome‐wide SNP scan accelerates trait‐regulatory genomic loci identification in chickpea. Nature Scientific Reports 5: 11166 doi: 10.1038/srep11166. Kujur, A., H.D. Upadhyaya, T. Shree, D. Bajaj, S. Das, M.S. Saxena, S. Badoni, V. Kumar, S. Tripathi, C.L.L. Gowda S. Sharma, S. Singh, A. K. Tyagi, and S.K. Parida (2015c). Ultra‐high density intra‐specific genetic linkage maps accelerate identification of functionally relevant molecular tags governing important agronomic traits in chickpea. Scientific Reports 5: 9468. doi: 10.1038/srep09468. Kujur, A., H.D. Upadhyaya, D. Bajaj, C.L.L. Gowda, S. Sharma, A.K. Tyagi, and S.K. Parida (2016). Identification of candidate genes and natural allelic variants for QTLs governing plant height in chickpea. Scientific Reports 6, 27968. doi: 10.1038/srep27968. Lalitha, N., H.D. Upadhyaya, L. Krishnamurthy, J. Kashiwagi, P.B. Kavikishor, and S Singh (2015). Assessing genetic variability for root traits and identification of trait specific germplasm in chickpea (Cicer arietinum L.) reference set. Crop Science 55(5): 2034–2045. doi: 10.2135/cropsci2014.12.0847. Lasky, J.R., H.D. Upadhyaya, P. Ramu, S. Deshpande, C.T. Hash, J. Bonnette, T.E. Juenger, K. Hyma, C. Acharya, S.E. Mitchell, E.S. Buckler, Z. Brenton, S. Kresovich, and G.P. Morris (2015). Genome‐environment associations in sorghum landraces predict ­adaptive traits. Science Advances 1: e1400218. doi: 10.1126/sciadv.1400218. Mace, E.S., D.T. Phong, H.D. Upadhyaya, S. Chandra, and J.H. Crouch (2006). SSR ­analysis of cultivated groundnut (Arachis hypogaea L.) germplasm resistant to rust and late leaf spot diseases. Euphytica 152: 317–330. Mace, E.S., W. Yuejin, L. Boshou, H.D. Upadhyaya, S. Chandra, and J.H. Crouch (2007). Simple sequence repeat (SSR)‐based diversity analysis of groundnut (Arachis hypogaea L.) germplasm resistant to bacterial wilt. Plant Genetic Resources 5: 27–36. Mallikarjuna Swamy, B.P., H.D. Upadhyaya, P.V.K. Goudar, B.Y. Kullaiswamy, and S. Singh (2003). Phenotypic variation for agronomic characteristics in a groundnut core collection for Asia. Field Crops Research 84: 359–371.

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Mallikarjuna, N., S. Senthivel, D.R. Jadhav, K.B. Saxena, H.C. Sharma, H.D. Upadhyaya, A. Rathore, and R.K. Varshney (2011). Progress in utilization of Cajanus platycarpus (Benth.) Maesen in pigeonpea improvement. Plant Breeding 130: 507–514. Mallikarjuna, N., S. Srikanth, R.K. Vellanki, D.R. Jadhav, K. Das, and H.D. Upadhyaya (2012). Meiotic analysis of the hybrids between cultivated and synthetic tetraploid groundnuts. Plant Breeding 131: 135–138. Mir, R.R., R.K. Saxena, K.B. Saxena, H.D. Upadhyaya, A. Kilian, D.R Cook, and R.K. Varshney (2013). Whole‐ genome scanning for mapping determinacy in pigeonpea (Cajanus spp.). Plant Breeding 132: 472–478. Morris, G.P., P. Ramu, S.P. Deshpande, C.T. Hash, T. Shah, H.D. Upadhyaya, O. Riera‐ Lizarazu, P.J. Brown, C.B. Acharya, S.E. Mitchell, J. Harriman, J.C. Glaubitz, E.S. Buckler, and S. Kresovich (2013). Population genomic and genome‐wide association studies of agroclimatic traits in sorghum. Proceedings of the National Academy of Sciences of the United States of America 110: 453–458. Mukri, G., H.L. Nadaf, M.V.C. Gowda, R.S. Bhat, and H.D. Upadhyaya (2014). Genetic analysis for yield, nutritional and oil quality traits in RIL population of groundnut (Arachis hypogaea L.). Indian Journal of Genetics and Plant Breeding 74: 450–455. Mukri, G., H.L. Nadaf, R.S. Bhat, M.C.V. Gowda, H.D. Upadhyaya, and V. Sujay (2012). Phenotypic and molecular dissection of ICRISAT mini core collection of peanut (Arachis hypogaea L.) for high oleic acid. Plant Breeding 131: 418–422. Nayak, S.N., J. Balaji, H.D. Upadhyaya, C.T. Hash, P.B.K. Kishor, D. Chattopadhyay, L.M. Rodriquez, M.W. Blair M. Baum, K. McNally, D. This, D.A. Hoisington, and R.K. Varshney (2009). Isolation and sequence analysis of DREB2A homologues in three cereals and two legume species. Plant Science 177: 460–467. Nayyar, H., G. Kaur, S. Kumar, and H.D. Upadhyaya (2007). Low temperature effects during seed filling on chickpea genotypes (Cicer arietinum L.): Probing mechanisms affecting seed reserves and yield. Journal of Agronomy and Crop Science 193: 336–344. Nayyar, H., S. Kaur, S. Smita, and H.D. Upadhyaya (2006a). Differential sensitivity of desi (small‐seeded) and kabuli (large‐seeded) chickpea genotypes to water stress during seed filling: Effects on accumulation of seed reserve and yield. Journal of the Science of Food and Agriculture 86: 2076–2082. Nayyar, H., S. Singh, S. Kaur, S. Kumar, and H.D. Upadhyaya (2006b). Differential sensitivity of macrocarpa and microcarpa types of chickpea (Cicer arietinum L.) to water stress: Association of contrasting stress response with oxidative injury. Journal of Integrative Plant Biology 48: 1318–1329. Nigam, S.N., M.J.V. Rao, H.D. Upadhyaya, Y.L.C. Rao, and N.S. Reddy (1995). Registration of an early‐maturing peanut germplasm ICGV 86015. Crop Science 35: 1718–1719. Nigam, S.N., H.D. Upadhyaya, S. Chandra, R.C. Nageswara Rao, G.C. Wright, and A.G.S.  Reddy (2001). Gene effects for specific leaf area and harvest index in three crosses of groundnut (Arachis hypogaea). Annals of Applied Biology 139: 301–306. Nigam, S.N., F. Waliyar, R. Aruna, S.V. Reddy, P.L. Kumar, P.Q. Craufurd, A.T. Diallo, B.R.  Ntare, and H.D. Upadhyaya (2009). Breeding peanut for resistance to aflatoxin contamination at ICRISAT. Peanut Science 36: 42–49. Nirgude, M., B.B. Kalyana, Y. Shambhavi, U.M. Singh, H.D. Upadhyaya, and A. Kumar (2014). Development and molecular characterization of genic molecular markers for grain protein and calcium content in finger millet (Eleusine coracana (L.) Gaertn.) Molecular Biology Reports 41: 1189–1200. Ortiz, R., T. Ban, R. Bandyopadhyay, D. Bergvinson, K. Hell, B. James, D. Jaffers, A. Mankir, J. Murakami, P.L. Kumar, S.N. Nigam, H.D. Upadhyaya, and F. Waliyar (2008). CGIAR research for development program on mycotoxins. In: Leslie, J., R. Bandyopadhyay,

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and A. Visconti (eds). Mycotoxins: Detection Methods, Management, Public Health and Agricultural Trade, pp. 415–424. CABI Publishing, UK. Pande, S., G.K. Kishore, H.D. Upadhyaya, and J.N. Rao (2006). Identification of sources multiple disease resistance in mini‐core collection of chickpea. Plant Disease 90: 1214–1218. Pandey, M.K., B. Gautami, T. Jayakumar, M. Sriswathi, H.D. Uapdhyaya, M.V.C. Gowda, T. Radhakrishnan, D.J. Bertioli, S.J. Knapp, D.R. Cook, and R.K. Varshney (2012a). Highly informative genic and genomic SSR markers to facilitate molecular breeding in cultivated groundnut (Arachis hypogaea). Plant Breeding 131: 139–147. Pandey, M.K., E. Monyo, P. Ozias‐Akins, X. Liang, P. Guimarães, S.N. Nigam, H.D. Upadhyaya, P. Janila, X. Zhang, B. Guo, D.R. Cook, D.J. Bertioli, R. Michelmore, and R.K. Varshney (2012b). Advances in Arachis genomics for peanut improvement. Biotechnology Advances 30: 639–651. Pandey, M.K., G. Agarwal, S.M. Kale, J. Clevenger, S.N. Nayak, M. Sriswathi, A. Chitikineni, C. Chavarro, X. Chen, H.D. Upadhyaya, M.K. Vishwakarma, S. LealBertioli, X. Liang, D.J. Bertioli, B. Guo, S.A. Jackson, P. Ozias-Akins, and R.K. Varshney. (2017). Development and evaluation of a high-density genotyping ‘Axiom_Arachis’ array with 58K SNPs for accelerating genetics and breeding in groundnut. Scientific Reports 7:40577. doi: 10.1038/srep40577 Pandey, M.K., H.D. Upadhyaya, A. Rathore, V. Vadez, M.S. Sheshshayee, M. Sriswathi, M. Govil, A. Kumar, M.V.C. Gowda, S. Sharma, F. Hamidou, V.A. Kumar, P. Khera, R.S. Bhat, A.W. Khan, S. Singh, H. Li, E. Monyo, H.L. Nadaf, G. Mukri, S.A. Jackson, B.  Guo, X. Liang, and R.K. Varshney (2014). Genome wide association studies for 50 agronomic traits in peanut using the ‘reference set’ comprising 300 genotypes from 48 countries of the semi‐arid tropics of the world. PLoS One 9: e105228. Parameshwarappa, S.G., P.M. Salimath, H.D. Upadhyaya, S.S. Patil, and S.T. Kajjidoni (2011a). Genetic variability studies in minicore collections of chickpea (Cicer ­arietinum L.) under different environments. Indian Journal of Genetics Resources 24: 43–48. Parameshwarappa, S.G., P.M. Salimath, H.D. Upadhyaya, S.S. Patil, and S.T. Kajjidoni (2011b). Genetic divergence under three environments in a minicore collection of chickpea (Cicer arietinum L.). Indian Journal of Plant Genetic Resources 24: 177–185. Pattanashetti, S.K., H.D. Upadhyaya, S. Dwivedi, M. Vetriventhan, and K.N. Reddy (2015). Pearl millet. In: Mohar Singh, Upadhyaya HD (eds). Genetic and Genomic Resources for Grain Cereals Improvement, pp. 253–289. Elsevier (Academic Press). Purushothaman, R., H.D. Upadhyaya, P.M. Gaur, C.L.L. Gowda, and L. Krishnamurthy (2014). Kabuli and desi chickpeas differ in their requirement for reproductive duration. Field Crops Research 163: 24–31. Purushothaman, R., M. Thudi, L. Krishnamurthy, H.D. Upadhyaya, J. Kashiwagi, C.L.L. Gowda, and R.K. Varshney (2015). Association of mid‐reproductive stage canopy temperature depression with the molecular markers and grain yields of chickpea (Cicer arietinum L.) germplasm under terminal drought. Field Crops Research 174: 1–11. Rai, K.N., G. Velu, M. Govindaraj, H.D. Upadhyaya, A.S. Rao, H. Shivade and K.N. Reddy (2015). Iniadi pearl millet germplasm as a valuable genetic resource for high grain iron and zinc densities. Plant Genetic Resources 13: 75–82. Ramamoorthy, P., L. Krishnamurthy, H.D. Upadhyaya, V. Vadez, and R.K. Varshney. (2016). Genotypic variation in soil water use and root distribution and their Implications for drought tolerance in chickpea. Functional Plant Biology 44, 235–252. Ramu, P., C. Billot, R. Jean‐francois, S. Senthilvel, H.D. Upadhyaya, L.A. Reddy, and C.T. Hash (2013). Assessment of genetic diversity in the sorghum reference set using EST‐SSR markers. Theoretical and Applied Genetics 126: 2051–2064.

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Rao, M.J.V., H.D. Upadhyaya, V.K. Mehan, S.N. Nigam, D. McDonald, and N.S. Reddy (1995). Registration of peanut germplasm ICGV 88145 and ICGV 89104 resistant to seed infection by Aspergillus flavus. Crop Science 35: 1717. Redden, R.J., B.J. Furman, H.D. Upadhyaya, R.P.S. Pundir, C.L.L. Gowda, C.J. Coyne, and D. Enneking (2007). Biodiversity management in chickpea. In: Yadav, S.S., R.R. Redden, W. Chen, and B. Sharma (eds). Chickpea Breeding and Management, p. 355–368. Wallingford, Oxon, UK: CAB International. Reddy, L.J., H.D. Upadhyaya, C.L.L. Gowda, and S. Singh 2005). Development of core  collection in pigeonpea (Cajanus cajan (L) Millspaugh) using geographic and  qualitative morphological descriptors. Genetic Resources and Crop Evolution 52: 1049–1056. Roorkiwal, M., S.L. Sawargaonkar, A. Chitikineni, M. Thudi, R.K. Saxena, H.D. Upadhyaya, M.I. Vales, O. Riera‐Lizarazu, and R.K. Varshney (2013). Single nucleotide polymorphism genotyping for breeding and genetics applications in chickpea and pigeonpea using the BeadXpress platform. The Plant Genome 6. doi: 10.3835/plantgenome2013.05.0017. Roorkiwal, M., S.N. Nayak, M. Thudi, H.D. Upadhyaya, D. Brunel, P. Mournet, D. This, P.C. Sharma, and R.K. Varshney (2014a). Allele diversity for abiotic stress responsive candidate genes in chickpea reference set using gene based SNP markers. Frontiers in Plant Science 5: 248.doi: 10.3389/fpls.2014.00248. Roorkiwal, M., E. von Wettberg, H.D. Upadhyaya, E. Warshefsky, A. Rathore, and R.K.  Varshney (2014b). Exploring germplasm diversity to understand the domestication process in Cicer spp. using SNP and DArT markers. PLoS One 9: e102016. doi: 10.1371/journal.pone.0102016. Roorkiwal, M., M. Thudi, P.M. Gaur, H.D. Upadhyaya, N.P. Singh, and R.K. Varshney (2015). Chickpea translational genomics in the ‘whole genome’ era. Legumes Perspectives (Special issue) 7: 7–9. ISSN 2340–1559. Saha, D., R.S. Rana, L. Arya, M. Verma, M.V.C. Gowda, and H.D. Upadhyaya (2016). Genetic polymorphism among and between blast disease resistant and susceptible finger millet (Eleusine coracana L. (Gaertn.). Plant Genetic Resources 1–11. doi: 10.1017/ S1479262116000010. Saxena, R.K., E. von Wettberg, H.D. Upadhyaya, V. Sanchez, S. Songok, P. Kimurto, and R.K. Varshney (2014). Genetic diversity and demographic history of Cajanus spp. illustrated from genome‐wide SNPs. PLoS One 9: e88568. Saxena, R.K., R.V. Penmetsa, H.D. Upadhyaya, A. Kumar, N. Carrasquilla‐Garcia, J.A. Schlueter, A. Farmer, A.M. Whaley, B.K. Sarma, G.D. May, D.R. Cook, and R.K. Varshney (2012). Large‐scale development of cost‐effective single‐nucleotide polymorphism marker assays for genetic mapping in pigeonpea and comparative mapping in legumes. DNA Research 19: 449–461. Sharma, M., A. Rathore, U.N. Mangala, R. Ghosh, S. Sharma, H.D. Upadhyay, and S. Pande (2012a). New sources of resistance to Fusarium wilt and sterility mosaic disease in a mini‐core collection of pigeonpea germplasm. European Journal of Plant Pathology 133: 707–714. Sharma, R., V.P. Rao, H.D. Upadhyaya, V.G. Reddy, and R.P. Thakur (2010). Resistance to grain mold and downy mildew in a mini core collection of sorghum germplasm. Plant Disease 94: 439–444. Sharma, R., H.D. Upadhyaya, S.V. Manjunatha, V.P. Rao, and R.P. Thakur (2012). Resistance to foliar diseases in a mini‐core collection of sorghum germplasm. Plant Disease 96: 1629–1633. Sharma, R., H.D. Upadhyaya, S.V. Manjunatha, K.N. Rai, S.K. Gupta, and R.P. Thakur (2013b). Pathogenic variation in the pearl millet blast pathogen Magnaporthe grisea and identification of resistance to diverse pathotypes. Plant Disease 97: 189–195.

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Sharma, R., A.G. Girish, H.D. Upadhyaya, P. Humayun, T.K. Babu, V.P. Rao, and R.P. Thakur (2014). Identification of blast resistance in a core collection of foxtail millet germplasm. Plant Disease 98: 519–524. Sharma, R., H.D. Upadhyaya, S. Sharma, V.L. Gate, and C. Raj (2015). New sources of resistance to multiple pathotypes of Sclerospora graminicola in the pearl millet mini core germplasm collection. Crop Science 55: 1619–1628. doi: 10.2135/cropsci2014.12.0822. Sharma, S. and H.D. Upadhyaya (2015a). Vernalization and photoperiod response in annual wild Cicer Species and cultivated chickpea. Crop Science 55: 2393–2400. Sharma, S., and H.D. Upadhyaya (2015b). Pre‐breeding to expand primary genepool through introgression of genes from wild Cajanus species for pigeonpea improvement. Legume Perspectives (Special issue) 11: 19–22. Sharma, S., H.D. Upadhyaya, C.L.L. Gowda, S. Kumar, and S. Singh (2013a). Genetic analysis for seed size in three crosses of chickpea (Cicer arietinum L.). Canadian Journal of Plant Science 93: 387–395. Sharma, S., H.D. Upadhyaya, M. Roorkiwal, R.K. Varshney and C.L.L. Gowda (2013b). Chickpea. In: M. Singh, H.D. Upadhyaya, and I.S. Bisht (eds). Genetic and Genomic Resources of Grain Legume Improvement, pp. 81–112. Elsevier, London. Sharma, S., H.D. Upadhyaya, R.K. Varshney, and C.L.L. Gowda (2013d). Pre‐breeding for diversification of primary gene pool and genetic enhancement of grain legumes. Frontiers in Plant Science 4: 309. doi: 10.3389/fpls.2013.00309. Sharma, S., H.D. Upadhyaya, M. Roorkiwal, and R.K. Varshney (2016). Interspecific hybridization for chickpea (Cicer arietinum L.) improvement. In: Annaliese, S. Manson (eds). Polyploidy and Hybridization for Crop Improvement, pp. 446–471. CRC Press. Sharma, S., M.K. Pandey, H.K. Sudini, H.D. Upadhyaya, and R.K. Varshney. (2017). Harnessing genetic diversity of wild Arachis species for genetic enhancement of cultivated peanut. Crop Science 57. doi: 10.2135/cropsci2016.10.0871 Singh, M., H.D. Upadhyaya, and I.S. Bisht (2013). Introduction. In: M. Singh M., H.D. Upadhyaya and I.S. Bisht (eds). Genetic and genomic resources of grain legume Improvement, pp. 1–10. Elsevier. Sood, S., R. Khulbe, A. Gupta, P.K. Agrawal, H.D. Upadhyaya, and J.C. Bhatt (2014). Barnyard millet – a potential food and feed crop of future. Plant Breeding 134: 135–147. Sood, S., R.K. Khulbe, R.A. Kumar, P.K Agrawal, and H.D. Upadhyaya (2015). Barnyard millet global core collection evaluation in the submontane Himalayan region of India using multivariate analysis. The Crop Journal 3: 517–525. http://doi.org/10.1016/j. cj.2015.07.005. Srinivasa Rao, P., B.V.S. Reddy, N. Nagaraj, and H.D. Upadhyaya (2014). Sorghum production for diversified uses. In: Yi‐Hong Wang, H.D. Upadhyaya and Chittaranjan Kole (eds). Genetics, Genomics and Breeding of Sorghum, pp. 1–27. Taylor & Francis Group, LLC, CRC Press. Srivastava, R., D. Bajaj, K.Y. Sayal, P.K. Meher, H.D. Upadhyaya, R. Kumar, S. Tripathi, C. Bharadwaj, A.R. Rao, and S.K. Parida. (2016). Genome-wide development and deployment of informative intron-spanning and intron-length polymorphism markers for genomics-assisted breeding applications in chickpea. Plant Science 252: 374–387. doi:10.1016/j.plantsci.2016.08.013. Srivastava, R., H.D. Upadhyaya, R. Kumar, A. Daware, U. Basu, P.W. Shimray, S. Tripathi, C. Bharadwaj, A. Tyagi, and S.K. Parida. (2017). A multiple QTL-Seq strategy delineates potential genomic loci governing flowering time in chickpea. Frontiers in Plant Science doi: 10.3389/fpls.2017.01105. Sudini, H., H.D. Upadhyaya, S.V. Reddy, U.N. Mangala, A. Rathore, and K.V.K. Kumar (2015). Resistance to late leaf spot and rust diseases in ICRISAT’s mini core collection

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of peanut (Arachis hypogaea L.) Australasian Plant Pathology 44: 557–566. ISSN 0815‐3191. Thudi, M., A. Bohra, S.N. Nayak, N. Varghese, T.M. Shah, R.V. Penmetsa, T. Nepolean, S.  Gudipati, P.M. Gaur, P.L. Kulwal, H.D. Upadhyaya, P.B. KaviKishor, P. Winter, G. Kahl, C.D. Town, A. Kilian, D.R. Cook, and R.K. Varshney (2011). Novel SSR markers from BAC‐end sequences, DArT arrays and a comprehensive genetic map with 1,291 marker loci for chickpea (Cicer arietinum L.). PLoS One 6: e27275. Thudi, M., H.D. Upadhyaya, A. Rathore, P.M. Gaur, L. Krishnamurthy, M. Roorkiwal, S.N. Nayak, S.K. Chaturvedi, P.S. Basu, N.V.P.R. Gangarao, A. Fikre, P. Imurto, P.C. Sharma, M.S. Sheshashayee, S. Tobita, J. Kashiwagi, O. Ito, A. Killian, and R.K. Varshney (2014). Genetic dissection of drought and heat tolerance in chickpea through genome‐wide and candidate gene‐based association mapping approaches. PLoS One 9: e96758. Upadhyaya, H.D (2003a). Geographical patterns of variation for morphological and agronomic characteristics in the chickpea germplasm collection. Euphytica 132: 343–352. Upadhyaya, H.D (2003b). Phenotypic diversity in groundnut (Arachis hypogaea L.) core collection assessed by morphological and agronomical evaluations. Genetic Resources and Crop Evolution 50: 539–550. Upadhyaya, H.D (2005). Variability for drought resistance related traits in the mini core collection of peanut. Crop Science 45: 1432–1440. Upadhyaya, H.D (2008). Crop Germplasm and wild relatives: a source of novel variation for crop improvement. Korean Journal of Crop Science 53: 12–17. Upadhyaya H.D (2015). Establishing core collections for enhanced use of germplasm in crop improvement. Ekin Journal of Crop Breeding and Genetics 1: 1–12. Upadhyaya, H.D., and S.N. Nigam (1994). Inheritance of two components of early ­maturity in groundnut (Arachis hypogaea L.). Euphytica 78: 59–67. Upadhyaya, H.D., and S.N. Nigam (1996). Identification and inheritance of male sterility in groundnut (Arachis hypogaea L.). Euphytica 88: 227–230. Upadhyaya, H.D., and S.N. Nigam (1998). Epistasis for vegetative and reproductive traits in peanut. Crop Science 38: 44–49. Upadhyaya, H.D., and S.N. Nigam (1999a). Detection of epistasis for protein and oil ­contents and oil quality parameters in peanut. Crop Science 39: 115–118. Upadhyaya, H.D., and S.N. Nigam (1999b). Inheritance of fresh seed dormancy in peanut. Crop Science 39: 98–101. Upadhyaya, H.D., and R. Ortiz (2001). A mini core subset for capturing diversity and promoting utilization of chickpea genetic resources in crop improvement. Theoretical and Applied Genetics 102: 1292–1298. Upadhyaya, H.D., M.P. Haware, J. Kumar, and J.B. Smithson (1983a). Resistance to wilt in chickpea. I. Inheritance of late wilting in response to race 1. Euphytica 32: 447–452. Upadhyaya, H.D., J.B. Smithson, M.P. Haware, and J. Kumar (1983b). Resistance to wilt in chickpea. II. Further evidence for two genes for resistance to race 1. Euphytica 32: 749–755. Upadhyaya, H.D., K. Gopal, H.L. Nadaf, and S. Vijayakumar (1992). Combining ability studies for yield and its components in groundnut. Indian Journal of Genetics 52: 1–6. Upadhyaya, H.D., S.N. Nigam, M.J.V. Rao, A.G.S. Reddy, N. Yellaiah, and N.S. Reddy (1997a). Registration of five Spanish peanut germplasm lines with fresh seed dormancy. Crop Science 37: 1027. Upadhyaya, H.D., S.N. Nigam, M.J.V. Rao, N.S. Reddy, N. Yellaiah, and A.G.S. Reddy (1997b). Registration of ICGV 86143 peanut germplasm. Crop Science 37: 1986. Upadhyaya, H.D., S.N. Nigam, M.J.V. Rao, A.G.S. Reddy, N. Yellaiah, and N.S. Reddy (1998). Registration of early‐maturing peanut germplasm ICGV 92196, ICGV 92206, ICGV 92234 and ICGV 92243. Crop Science 38: 900–901.

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Upadhyaya, H.D., P.J. Bramel, and S. Singh (2001a). Development of a chickpea core ­subset using geographic distribution and quantitative traits. Crop Science 41: 206–210. Upadhyaya, H.D., M.E. Ferguson, and P.J. Bramel (2001b). Status of the Arachis germplasm collection at ICRISAT. Peanut Science 28: 89–96. Upadhyaya, H.D., S.N. Nigam, V.K. Mehan, A.G.S. Reddy, and N. Yellaiah (2001c). Registration of Aspergillus flavus seed infection resistant peanut germplasm ICGV 91278, ICGV 91283 and ICGV 91284. Crop Science 41: 599–600. Upadhyaya, H.D., S.N. Nigam, S. Pande, A.G.S. Reddy, and N. Yellaiah (2001d). Registration of an early‐maturing moderately resistant to rust peanut germplasm ICGV 94361. Crop Science 41: 598–599. Upadhyaya, H.D., S.N. Nigam, A.G.S. Reddy, and N. Yellaiah (2001e). Registration of early‐ maturing fresh seed dormant peanut germplasm ICGV 93470. Crop Science 41: 597–598. Upadhyaya, H.D., S.N. Nigam, and S. Singh (2001f). Evaluation of groundnut core collection to identify sources of tolerance to low temperature at germination. Indian Journal of Plant Genetic Resources 14: 165–167. Upadhyaya, H.D., P.J. Bramel, R. Ortiz, and S. Singh (2002a). Developing a mini core of peanut for utilization of genetic resources. Crop Science 42: 2150–2156. Upadhyaya, H.D., P.J. Bramel, R. Ortiz, and S. Singh (2002b). Geographical pattern of  diversity for morphological and agronomic traits in the groundnut germplasm collection. Euphytica 128: 191–204.. Upadhyaya, H.D., S.N. Nigam, A.G.S. Reddy, and N. Yellaiah (2002c). Registration of early‐maturing, rust, late leaf spot and low temperature tolerant peanut germplasm line ICGV 92267. Crop Science 42: 2220–2221. Upadhyaya, H.D., S.N. Nigam, A.G.S. Reddy, and N. Yellaiah (2002d). Registration of early‐maturing peanut germplasm ICGV 93382. Crop Science 42: 2221. Upadhyaya, H.D., R. Ortiz, P.J. Bramel‐Cox, and S. Singh (2002e). Phenotypic diversity for morphological and agronomic characteristics in chickpea core collection. Euphytica 123: 333–342 Upadhyaya, H.D., R. Ortiz, P.J. Bramel, and S. Singh (2003). Development of a groundnut core collection using taxonomical, geographical and morphological descriptors. Genetic Resources and Crop Evolution 50: 139–148. Upadhyaya, H.D., B.P. Mallikarjuna Swamy, P.V.K. Goudar, B.Y. Kullaiswamy, and S. Singh (2005a). Identification of diverse groundnut germplasm through multi‐environment evaluation of a core Collection for Asia. Field Crops Research 93: 293–299. Upadhyaya, H.D., S.N. Nigam, A.G.S. Reddy, and N. Yellaiah (2005b). Early‐maturing, large‐seeded and high‐yielding groundnut varieties ICGV 96466, ICGV 96468 and ICGV 96469. SAT eJournal 1.ejournal.icrisat.org. Upadhyaya, H.D., R.P.S. Pundir, C.L.L. Gowda, and S. Singh (2005c). Geographical pattern of diversity for qualitative and quantitative traits in pigeonpea germplasm collection. Plant Genetic Resources 3: 331–352. Upadhyaya, H.D., B.J. Furman, S.L. Dwivedi, S.M. Udupa, C.L.L. Gowda, M. Baum, J.H. Crouch, H.K. Buhariwalla, and S. Singh (2006a). Development of a composite collection for mining germplasm possessing allelic variation for beneficial traits in chickpea. Plant Genetic Resources 4: 13–19. Upadhyaya, H.D., C.L.L. Gowda, H.K. Buhariwalla, and J.H. Crouch (2006b). Efficient use of crop germplasm resources: identifying useful germplasm for crop improvement through core and mini core collections and molecular marker approaches. Plant Genetic Resources 4: 25–35. Upadhyaya, H.D., C.L.L. Gowda, R.P.S. Pundir, V.G. Reddy, and S. Singh (2006c). Development of core subset of finger millet germplasm using geographical origin and data on 14 quantitative traits. Genetic Resources and Crop Evolution 53: 679–685.

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Upadhyaya, H.D., S. Kumar, C.L.L. Gowda, and S. Singh (2006d). Two major genes for seed size in chickpea (Cicer arietinum L.). Euphytica 147: 311–315. Upadhyaya, H.D., L.J. Reddy, C.L.L. Gowda, K.N. Reddy, and S. Singh (2006e). Development of a mini core subset for enhanced and diversified utilization of pigeonpea germplasm resources. Crop Science 46: 2127–2132. Upadhyaya, H.D., L.J. Reddy, C.L.L. Gowda, and S. Singh (2006f). Identification of diverse groundnut germplasm: Sources of early‐maturity in a core collection. Field Crops Research 97: 261–271. Upadhyaya, H.D., S.L. Dwivedi, C.L.L. Gowda, and S. Singh (2007a). Identification of diverse germplasm lines for agronomic traits in a chickpea (Cicer arietinum L.) core collection for use in crop improvement. Field Crops Research 100: 320–326. Upadhyaya, H.D., K.N. Reddy, C.L.L. Gowda, M.I. Ahmed, and S. Singh (2007b). Agroecological patterns of diversity in pearl millet (Pennisetum glaucum (L.) R. Br.) germplasm from India. Plant Genetic Resources 20: 178–185. Upadhyaya, H.D., K.N. Reddy, C.L.L. Gowda, and S.N. Silim (2007c). Patterns of diversity in pigeonpea (Cajanus cajan (L.) Millsp.) germplasm collected from different elevations in Kenya. Genetic Resources and Crop Evolution 54: 1787–1795. Upadhyaya, H.D., K.N. Reddy, C.L.L. Gowda, and S. Singh (2007d). Phenotypic diversity in pigeonpea (Cajanus cajan (L.) core collection. Genetic Resources and Crop Evolution 54: 1167–1184. Upadhyaya, H.D., P.M. Salimath, C.L.L. Gowda, and S. Singh (2007e). New early‐maturing germplasm lines for utilization in chickpea improvement. Euphytica 157: 195–208. Upadhyaya, H.D., S.L. Dwivedi, M. Baum, R.K. Varshney, S.M. Udupa, C.L.L. Gowda, D. Hoisington, and S. Singh (2008a). Genetic structure, diversity and allelic richness in composite collection and reference set in chickpea (Cicer arietinum L.). BMC Plant Biology 8: 106. http://www.biomedcentral.com/1471‐2229/8/106. Upadhyaya, H.D., R.P.S. Pundir, C.L.L. Gowda, V.G. Reddy, and S. Singh (2008b). Establishing a core collection of foxtail millet to enhance utilization of germplasm of an underutilized crop. Plant Genetic Resources 7: 177–184. Upadhyaya, H.D., C.L.L. Gowda, K.N. Reddy, and S. Singh (2009a). Augmenting the pearl millet core collection for enhancing germplasm utilization in crop improvement. Crop Science 49: 573–580. Upadhyaya, H.D., R.P.S. Pundir, S.L. Dwivedi, C.L.L. Gowda, V.G. Reddy, and S. Singh (2009b). Developing a mini core collection of sorghum for diversified utilization of germplasm. Crop Science 49: 1769–1780. Upadhyaya, H.D., K.N. Reddy, M.I. Ahmed, C.L.L. Gowda, and B.I.G. Haussmann (2009c). Identification of geographical gaps in the pearl millet germplasm conserved at ICRISAT genebank from West and Central Africa. Plant Genetic Resources 8: 45–51. Upadhyaya, H.D., L.J. Reddy, S.L. Dwivedi, C.L.L. Gowda, and S. Singh (2009d). Phenotypic diversity in cold‐tolerant peanut (Arachis hypogaea L.) germplasm. Euphytica 165: 279–291. Upadhyaya, H.D., K.N. Reddy, C.L.L Gowda, and S. Singh (2010a). Identification and evaluation of vegetable type pigeonpea (Cajanus cajan (L.) Millsp.) in the world germplasm collection at ICRISAT Genebank. Plant Genetic Resources 8: 162–170. Upadhyaya, H.D., K.N. Reddy, M Irshad, and C.L.L. Gowda (2010b). Identification of gaps in pearl millet germplasm from Asia conserved at the ICRISAT genebank. Plant Genetic Resources 8: 267–276. Upadhyaya, H.D., S. Sharma, B. Ramulu, R. Bhattacharjee, C.L.L. Gowda, V.G. Reddy, and S. Singh (2010c). Variation for qualitative and quantitative traits and identification

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of  trait‐specific sources in new sorghum germplasm. Crop and Pasture Science 61: 609–618. Upadhyaya, H.D., N.D.R.K Sarma, C.R. Ravishankar, T. Albrecht, Y. Narasimhudu, S.K. Singh, S.K. Varshney, V.G. Reddy, S. Singh, S.L. Dwivedi, N. Wanyera, C.O.A. Oduori, M.A. Mgonja, D.B. Kisandu, H.K. Parzies, and C.L.L. Gowda (2010d). Developing a  minicore collection in finger millet using multilocation data. Crop Science 50: 1924–1931. Upadhyaya, H.D., N. Dronavalli, C.L.L. Gowda, and S. Singh (2011a). Identification and  evaluation of chickpea germplasm for tolerance to heat stress. Crop Science 51: 2079–2094. Upadhyaya, H.D., S.L. Dwivedi, M. Ambrose, N. Ellis, J. Berger, P. Smýkal, D. Debouck, G. Duc, D. Dumet, A. Flavell, S.K. Sharma, N. Mallikarjuna, and C.L.L. Gowda (2011b). Legume genetic resources: management, diversity assessment, and utilization in crop improvement. Euphytica 180: 27–47. Upadhyaya, H.D., S.L. Dwivedi, H.L. Nadaf, and S. Singh (2011c). Phenotypic diversity and identification of wild Arachis accessions with useful agronomic and nutritional traits. Euphytica 182: 103–115. Upadhyaya, H.D., S. Ramesh, S. Sharma, S.K. Singh, S.K. Varshney, N.D.R.K. Sharma, C.R. Ravishanker, Y. Narasimhudu, V.G. Reddy, K.L. Sahrawat, T.N. Dhanalakshmi, M.A. Mgonja, H.K. Parzies, C.L.L. Gowda, and S. Singh (2011d). Genetic diversity for grain nutrients contents in a core collection of finger millet [Eleusine coracana (L.) Gaertn.] germplasm. Field Crops Research 21: 42–52. Upadhyaya, H.D., C.R. Ravishankar, Y. Narasimhudu, N.D.R.K. Sarma, S.K. Singh, S.K. Varshney, V.G. Reddy, S. Singh, H.K. Parzies, S.L. Dwivedi, H.L. Nadaf, K.L. Sahrawat, and C.L.L. Gowda (2011e). Identification of trait‐specific germplasm and developing a mini core collection for efficient use of foxtail millet genetic resources in crop improvement. Field Crops Research 124: 459–467. Upadhyaya, H.D., K.N. Reddy, S. Sharma, R.K. Varshney, R. Bhattacharjee, S. Singh, and C.L.L. Gowda (2011f). Pigeonpea composite collection and identification of germplasm in crop improvement programmes. Plant Genetic Resources 9: 97–108. Upadhyaya, H.D., S. Sharma, and S.L. Dwivedi (2011 g). Arachis. In: Kole, C. (ed). Wild Crop Relatives: Genomics and Breeding Resources, Legume Crops and Forages, pp. 1–19. Springer Publisher. Upadhyaya, H.D., S. Sharma, and C.L.L. Gowda (2011 h). Major genes with additive effects for seed size in kabuli chickpea (Cicer arietinum L.). Journal of Genetics 90: 479–482. Upadhyaya, H.D., S. Sharma, C.L.L. Gowda, V.G. Reddy, and S. Singh (2011i). Developing proso millet (Panicum miliaceum L.) core collection using geographic and morpho‐ agronomic data. Crop and Pasture Science 62: 383–389. Upadhyaya, H.D., S. Sharma, S. Singh, and M. Singh (2011j). Inheritance of drought resistance related traits in two crosses of groundnut (Arachis hypogaea L.). Euphytica 177: 55–66. Upadhyaya, H.D., M. Thudi, N. Dronavalli, N. Gujaria, S. Singh, S. Sharma, and R.K. Varshney (2011 k). Genomic tools and germplasm diversity for chickpea improvement. Plant Genetic Resources 9: 45–58. Upadhyaya, H.D., D. Yadav, K.N. Reddy, C.L.L. Gowda, and S. Singh (2011 l). Development of pearl millet minicore collection for enhanced utilization of germplasm. Crop Science 51: 217–223. Upadhyaya, H.D., N. Dronavalli, C.L. L. Gowda, and S. Singh (2012a). Mini core collections for enhanced utilization of genetic resources in crop improvement. Indian Journal of Plant Genetic Resources 25: 111–124.

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Upadhyaya, H.D., J. Kashiwagi, R.K. Varshney, P.M. Gaur, K.B. Saxena, L. Krishnamurthy, C.L.L. Gowda, R.P.S. Pundir, S.K. Chaturvedi, P.S. Vasu, and I.P. Singh (2012b). Phenotyping chickpeas and pigeonpeas for adaptation to drought. Front. Plant Physiol. 3: 179. doi: 10.3389/fphys.2012.00179. Upadhyaya, H.D., G. Mukri, H.L. Nadaf, and S. Singh (2012c). Variability and stability analysis for nutritional traits in the mini core collection of peanut. Crop Science 52: 168–178. Upadhyaya, H.D., D. Naresh, S. Singh, and S.L. Dwivedi (2012d). Variability and stability for kernel iron and zinc contents in the ICRISAT mini core collection of peanut. Crop Science 52: 2628–2637. Upadhyaya, H.D., K.N. Reddy, M.I. Ahmed, N. Dronavalli, and C.L.L. Gowda (2012e). Latitudinal variation and distribution of photoperiod and temperature sensitivity for flowering in the world collection of pearl millet germplasm at ICRISAT genebank. Plant Genetic Resources 10: 59–69. Upadhyaya, H.D., K.N. Reddy, M.I. Ahamed, and C.L.L. Gowda (2012f). Identification of gaps in pearl millet germplasm from East and Southern Africa conserved at the ICRISAT genebank. Plant Genetic Resources 10: 202–213. Upadhyaya, H.D., W. Yi‐Hong, S. Sharma, and S. Singh (2012g). Association mapping of height and maturity across five environments using the sorghum mini core collection. Genome 55: 471–479. Upadhyaya, H.D., Y.‐H. Wang, S. Sharma, S. Singh, and K.H. Hasenstein (2012h). SSR markers linked to kernel weight and tiller number in sorghum identified by association mapping. Euphytica 187: 401–410 Upadhyaya, H.D., N. Dronavalli, S.L. Dwivedi, J. Kashiwagi, L. Krishnamurthy, S. Pande, H.C. Sharma, V. Vadez, S. Singh, R.K. Varshney, and C.L.L. Gowda (2013a). Mini core collection as a resource to identify new sources of variation. Crop Science 53: 2506–2517. Upadhyaya, H.D., K.N. Reddy, R.P.S. Pundir, S. Singh, C.L.L. Gowda, and M.I. Ahmed (2013b). Diversity and geographical gaps in Cajanus scarabaeoides (L.) Thou. germplasm conserved at the ICRISAT genebank. Plant Genetic Resources 11: 3–14. Upadhyaya, H.D., K.N. Reddy, D.V.S.S.R. Sastry, and C.L.L. Gowda (2013c). The wild genepool of pigeonpea at ICRISAT genebank – Status and distribution. Indian Journal of Plant Genetic Resources 26: 193–201. Upadhyaya, H.D., K.N. Reddy, S. Singh, and C.L.L. Gowda (2013d). Phenotypic diversity in Cajanus species and identification of promising sources for agronomic traits and seed protein content. Genetic Resources and Crop Evolution 60: 639–659. Upadhyaya, H.D., S. Sharma, K.N. Reddy, R. Saxena, R.K. Varshney, and C.L. Laxmipathi Gowda (2013e). Pigeonpea. In: Singh M., H.D. Upadhyaya and I.S. Bisht (eds). Genetic and genomic resources of grain legume Improvement, pp. 181–202. Elsevier, USA. ISBN: 978‐0‐12‐397935‐3. Upadhyaya, H.D., Y.‐H. Wang, C.L.L. Gowda, and S. Sharma (2013f). Association mapping of maturity and plant height using SNP markers with the sorghum mini core collection. Theoretical and Applied Genetics 126: 2003–2015. Upadhyaya, H.D., Y.‐H. Wang, R. Sharma, and S. Sharma (2013g). Identification of genetic markers linked to anthracnose resistance in sorghum using association analysis. Theoretical and Applied Genetics 126: 1649–1657. Upadhyaya, H.D., Y.‐H. Wang, R. Sharma, and S. Sharma (2013h). SNP markers linked to leaf rust and grain mold resistance in sorghum. Molecular Breeding 32: 451–462. Upadhyaya, H.D., S.L. Dwivedi, P. Ramu, S.K. Singh, and S. Singh (2014a). Genetic variability and effect of post‐flowering drought on stalk sugar content in sorghum mini core collection. Crop Science 54: 2120–2130.

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Upadhyaya, H.D., S.L. Dwivedi, S. Sharma, N. Lalitha, S. Singh, R.K. Varshney, and C.L.L. Gowda (2014b). Enhancement of the use and impact of germplasm in crop improvement. Plant Genetic Resources 12(S1): S155–S159. Upadhyaya, H.D., S.L. Dwivedi, S.K. Singh, S. Singh, M. Vetriventhan, and S. Sharma (2014c). Forming core collections in barnyard, kodo, and little millets using morpho‐ agronomic descriptors. Crop Science 54: 2673–2682. Upadhyaya, H.D., S.L. Dwivedi, V. Vadez, F. Hamidou, S. Singh, R.K. Varshney, and B. Liao (2014d). Multiple resistant and nutritionally dense germplasm identified from mini core collection in peanut. Crop Science 54: 679–693. Upadhyaya, H.D., K.N. Reddy, S. Singh, C.L.L. Gowda, M.I. Ahmed, and V. Kumar (2014e). Diversity and gaps in Pennisetum glaucum subsp. monodii (Maire) Br. germplasm conserved at the ICRISAT genebank. Plant Genetic Resources 12: 226–235. Upadhyaya, H.D., K.N. Reddy, S. Singh, C.L.L. Gowda, M.I. Ahmed, and S. Ramachandran (2014f). Latitudinal patterns of diversity in the world collection of pearl millet landraces at the ICRISAT genebank. Plant Genetic Resources 12: 91–102. Upadhyaya, H.D., K.N. Reddy, S. Singh, M.I. Ahmed, V. Kumar, and S. Ramachandran (2014g). Geographical gaps and diversity in Deenanath grass (Pennisetum pedicellatumTrin.) germplasm conserved at the ICRISAT genebank. Indian Journal of Plant Genetic Resources 27: 93–101. Upadhyaya, H.D., S. Sharma, and S.L. Dwivedi (2014h). Genetic resources, diversity and association mapping in peanut. In: N. Mallikarjuna, and R.K. Varshney (eds). Genetics, Genomics and Breeding of Peanuts, p. 13–36. Science Publishers/CRC Press, Boca Raton, FL, USA. Upadhyaya, H.D., D. Bajaj, S. Das, M.S. Saxena, S. Badoni, V. Kumar, S. Tripathi, C.L.L Gowda, S. Sharma, A.K. Tyagi, and S.K. Parida (2015a). A genome‐scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea. Plant Molecular Biology 89(4–5): 403–20. doi: 10.1007/s11103‐015‐0377‐z. Upadhyaya, H.D., K.N. Reddy, M.I. Ahmed, C.L.L. Gowda, and M.T. Reddy (2015b). Identification of gaps in pigeonpea germplasm from East and Southern Africa conserved at the ICRISAT genebank. Indian Journal of Plant Genetic Resources 28: 180–188. Upadhyaya, H.D., K.N. Reddy, S. Ramachandran, V. Kumar, S. Singh, M.T. Reddy, and M.I. Ahmed (2015c). Status and genetic diversity in the pigeonpea germplasm from Caribbean and Central American at the ICRISAT genebank. Plant Genetic Resources 13(3), 247–255. doi: http: //dx.doi.org/10.1017/s1479262114000987. Upadhyaya, H.D., K.N. Reddy, S. Sharma, S.L. Dwivedi. and S. Ramachandran (2015d). Enhancing the value of genetic resources for use in pigeonpea improvement. Legumes Perspectives (Special issue) 7: 13–16. Upadhyaya, H.D., Vetriventhan M, S.L. Dwivedi, S.K. Pattanashetti, and S.K. Singh (2015e). Proso, little, barnyard, and kodo millet. In: Singh, M., and Upadhyaya HD (eds). Genetic and Genomic Resources for Grain Cereals Improvement, pp. 321–343. Elsevier (Academic Press). Upadhyaya, H.D., M. Vetriventhan, S. P. Deshpande, S. Sivasubramani, J.G. Wallace, E. S. Buckler, C.T. Hash, and P. Ramu (2015f). Population genetics and structure of a global foxtail millet germplasm collection. The Plant Genome 8(3): 1–13. doi: 10.3835/ plantgenome2015.07.0054. Upadhyaya, H.D., D. Bajaj, N. Laxmi, S. Das, V. Kumar, C.L.L Gowda, S. Sharma, A. Tyagi, and S.K. Parida (2016a). Genome‐wide scans for delineation of candidate genes regulating seed‐protein content in chickpea. Frontiers in Plant Science 7: 302. doi: 10.3389/ fpls.2016.00302.

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Upadhyaya, H.D, D. Bajaj, S. Das, V. Kumar, C.L.L. Gowda, S. Sharma, and S.K. Parida (2016b). Genetic dissection of seed‐iron and zinc concentrations in chickpea. Scientific Reports 6: 24050. doi: 10.1038/srep24050. Upadhyaya, H.D., S.L. Dwivedi, S. Singh, K.L. Sahrawat, and S.K. Singh (2016c). Genetic variation and post flowering drought effects on seed iron and zinc in ICRISAT sorghum mini core collection. Crop Science 56: 374–384. Upadhyaya, H.D., S.L. Dwivedi, Y.‐H. Wang, and M. Vetriventhan (2016d). Sorghum genetic resources. In: Prasad, V., and I. Ciampitti (eds). Sorghum: State of the Art and Future Perspectives. Am. Soc. Agron. and the Crop Science Soc. America. doi: 10.2134/ agronmonogr58.2014.0056.5. Upadhyaya, H.D., K.N. Reddy, M.I. Ahmad, S. Ramchandran, V. Kumar, and S. Singh (2016e). Characterization and genetic potential of African pearl millet named landraces conserved at the ICRISAT Genebank. Plant Genetic Resources. doi: 10.1017/S1479262116000113. Upadhyaya, H.D., Y.‐H. Wang, D.V.S.S.R. Sastry, S.L. Dwivedi, P.V.V. Prasad, A.M. Burrell, R.R. Klein, G.P. Morris, and P.E. Klein (2016f). Association mapping of germinability and seedling vigor in sorghum under controlled low temperature conditions. Genome 59: 137–145. Upadhyaya, H.D., K.N. Reddy, M. Vetriventhan, M. Gumma Murali Krishna. I. Ahmed, M.  T. Reddy and S. K. Singh (2016g). Status, genetic diversity and gaps in sorghum germplasm from South Asia conserved at ICRISAT genebank. Plant Genetic Resources 1–12. doi: 10.1017/S147926211600023X. Upadhyaya H.D., K.N. Reddy, S. Ramachandran, V. Kumar and Irshad Ahmed M (2016h). Adaptation pattern and genetic potential of Indian pearl millet named landraces ­conserved at the ICRISAT genebank. Indian Journal of Plant Genetic Resources. doi 10.5958/0976. Upadhyaya, H.D., D. Bajaj, R, Srivastava, A. Daware, U. Basu, S. Tripathi, C. Bharadwaj, A.K. Tyagi, and S.K. Parida. (2017). Genetic dissection of plant growth habit in chickpea. Functional and Integrative Genomics DOI 10.1007/s10142-017-0566-8. Upadhyaya, H. D., S. L. Dwivedi, M. Vetriventhan, L. Krishnamurthy, and S. K. Singh. (2017). Post-flowering drought tolerance using managed stress trials, adjustment to flowering, and mini core collection in sorghum. Crop Science. 57:310–321. doi:10.2135/ cropsci2016.04.0280. Vadez, V., C.T. Hash, S.M.H. Rizvi, F.R. Bidinger, K. Banttee, K.K. Sharma, J.M. Devi, P.  Bhatnagar‐Mathur, J. Kashiwagi, L. Krishnamurthy, D. Hoisington, R.K. Varshney, P.M. Gaur, S.N. Nigam, R. Aruna, and H.D. Upadhyaya (2007a). The scope of gene technology in improving drought tolerance in crops. In: Serageldin, I., and E. Masood (eds). Changing lives, Edition: 41, p. 323–334. Publisher: Biblioteca Alexandrina. Vadez, V., L. Krishnamurthy, R. Serraj, P.M. Gaur, H.D. Upadhyaya, D.A. Hoisington, R.K. Varshney, N.C. Turner, and K.H.M. Siddique (2007b). Large variation for salinity tolerance in chickpea is explained by differences in sensitivity at reproductive stage. Field Crops Research 104: 123–129. Vadez, V., L. Krishnamurthy, C.T. Hash, H.D. Upadhyaya, and A.K. Borrell (2011). Yield, transpiration efficiency, and water‐use variations and their interrelationships in the sorghum reference collection. Crop and Pasture Science 62: 645–655. Varshney, R.K., R.V. Penmetsa, S. Dutta, P.L. Kulwal, R.K. Saxena, S. Datta, T.R Sharma, B. Rosen, N. Carrasquilla‐Garcia, A.D. Farmer, A. Dubey, K.B. Saxena, J. Gao, B. Fakrudin, M.N. Singh, B.P. Singh, K.B. Wanjari, M. Yuan, R.K. Srivastava, A. Kilian, H.D. Upadhyaya, N. Mallikarjuna, C.D. Town, G.E. Bruening, G. He, G.D. May, R.  McCombie, S.A. Jackson, N.K. Singh, and D.R. Cook (2010). Pigeonpea genomics initiative (PGI): an international effort to improve crop productivity of pigeonpea (Cajanus cajan L.). Molecular Breeding 26: 393–408.

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Varshney, R.K., D.A. Hoisington, H.D. Upadhyaya, P.M. Gaur, S.N. Nigam, K.B. Saxena, V. Vadez, S. Bhatia, R. Aruna, M.V.C. Gowda, and N.K. Singh (2007). Molecular genetics and breeding of grain legume crops for the semi‐arid tropics. In: Varshney, R.K., and R. Tuberosa, (eds). Genomics Assisted Crop Improvement. Vol. 2, Genomics Applications in Crops, p. 207–241. Springer. Varshney, R.K., K. Himabindu, M. Roorkiwal, M. Thudi, M.K. Pandey, R.K. Saxena, S.K. Chamarthi, S.M. Mohan, N. Mallikarjuna, H.D. Upadhyaya, P.M. Gaur, L. Krishnamurthy, K.B. Saxena, S.N. Nigam, and S. Pande (2012a). Advances in genetics and molecular breeding of three legume crops of semi‐arid tropics using next‐generation sequencing and high‐throughput genotyping technologies. Journal of Biosciences 37: 811–820. Varshney, R.K., W. Chen, Y. Li, A.K. Bharti, R.K. Saxena, J.A. Schlueter, M.T.A. Donoghue, S. Azam, G. Fan, A.M. Whaley, A.D. Farmer, J. Sheridan, A. Iwata, R. Tuteja, R.V. Penmetsa, W. Wu, H.D. Upadhyaya, S.‐P.Yang, T. Shah, K.B. Saxena, T. Michael, W.R McCombie, B. Yang, G. Zhang, H. Yang, J. Wang, C. Spillane, D.R. Cook, G.D. May, X. Xu, and S.A. Jackson (2012b). Draft genome sequence of pigeonpea (Cajanus cajan), an orphan legume crop of resource‐poor farmers. Nature Biotechnology 30: 83–89. Varshney, R.K., C. Song, R.K. Saxena, S. Azam, S. Yu, A.G. Sharpe, S. Cannon, J. Baek, B.D. Rosen, B. Tar’an, T. Millan, X. Zhang, L.D. Ramsay, A. Iwata, Y. Wang, W. Nelson, A.D. Farmer, P.M. Gaur, C. Soderlund, R.V. Penmetsa, C. Xu, A.K. Bharti, W. He, P. Winter, S. Zhao, J.K. Hane, N. Carrasquilla‐Garcia, J.A. Condie, H.D. Upadhyaya, M.‐C. Luo, M.  Thudi, C.L.L. Gowda, N.P. Singh, J. Lichtenzveig, K.K. Gali, J. Rubio, N. Nadarajan, J. Dolezel, K.C. Bansal, X. Xu, D. Edwards, G. Zhang, G. Kahl, J. Gil, K.B. Singh, S.K. Datta, S.A. Jackson, J. Wang, and D.R. Cook (2013). Draft genome sequence of chickpea (Cicer arietinum) provides a resource for trait improvement. Nature Biotechnology 31: 240–248. Varshney, R.K., M. Thudi, H.D. Upadhyaya, S.L. Dwivedi, S. Udupa, B. Furman, M. Baum, and D. Hoisington (2014). SSR kit to study genetic diversity in chickpea (Cicer arietinum L.). Plant Genetic Resources 12(S1): S118–S120. Varshney, R.K., R.K. Saxena, H.D. Upadhyaya, A.W. Khan, O. Yu, C. Kim, A. Rathore, D. Seon, J. Kim, S. An, V. Kumar, G. Anuradha, K. Yamini, W. Zhang, S Muniswamy, B. Kim, R. V. Penmetsa, E. von Wettberg, and S.K. Datta. (2017). Whole genome resequencing of 292 pigeonpea accessions identifies genomic regions associated with domestication and agronomic traits. Nature Genetics doi:10.1038/ng.3872. Vetriventhan, M., H.D. Upadhyaya, C.R. Anandakumar, S. Senthilvel, H.K. Parzies, A. Bharathi, R.K. Varshney, and C.L.L. Gowda (2012). Assessing genetic diversity, allelic richness and genetic relationship among races in ICRISAT foxtail millet core collection. Plant Genetic Resources 10: 214–223. Vetriventhan, M., H.D. Upadhyaya, C.R. Anandakumar, S. Senthilvel, R.K. Varshney, and H.K. Parizies (2013). Population structure and linkage disequilibrium of ICRISAT foxtail millet (Setaria italica (L.) P. Beauv.) core collection. Euphytica 196: 423–435. Vetriventhan, M., H.D. Upadhyaya, S.L. Dwivedi, S.K. Pattanashetti, and S.K. Singh (2015). Finger and foxtail millets. In: Singh, M., and Upadhyaya HD (eds). Genetic and Genomic Resources for Grain Cereals Improvement, pp. 291–319. Academic Press, Elsevier. Waliyar, F., K.V.K. Kumar, M. Diallo, A. Traore, U.N. Mangala, H.D. Upadhyaya, and H.  Sudini (2016). Resistance to pre‐harvest aflatoxin contamination in ICRISAT’s groundnut mini core collection. European Journal of Plant Pathology 145(4): 901–913. doi 10.1007/s10658‐016‐0879‐9. Wallace, J.G., H.D. Upadhyaya, M. Vetriventhan, E.S. Buckler, C.T. Hash, and P. Ramu (2015). The genetic makeup of a global barnyard millet germplasm collection. The Plant Genome 8(01): 01–07. doi: 10.3835/plantgenome2014.10.0067. Wang, Y.‐H., P. Bible, R. Loganantharaj, and H.D. Upadhyaya (2012). Identification of SSR markers associated with height using pool‐based genome‐wide association mapping in sorghum. Molecular Breeding 30: 281–292.

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Wang, Y.‐H., H.D. Upadhyaya, A.M. Burrell, S.M.E. Sahraeian, R.R. Klein, and P.E. Klein (2013). Genetic structure and linkage disequilibrium in a diverse, representative ­collection of the C4 model plant, Sorghum bicolor. G3: Genes, Genomes, Genetics 3: 783–793. Wang, Y.‐H., H.D. Upadhyaya, and I. Dweikat (2015). Sorghum. In: Singh, M., and Upadhyaya, H.D. (eds). Genetic and Genomic Resources for Grain Cereals Improvement, pp. 227–251. Academic Press, Elsevier. Westengen, O.T., M.A. Okongo, L. Onek, T. Berg, H.D. Upadhyaya, S. Birkeland, S.D.K. Khalsa, H. Kristoffer, K.H. Ring, N.C. Stenseth, and A.K. Brysting (2014). Ethnolinguistic structuring of sorghum genetic diversity in Africa and the role of local seed systems. Proceedings of the National Academy of Sciences of the United States of America 111: 14100–14105. William, E., H.D. Upadhyaya, and A.I. Malik (2014). Salinity. In: Jackson, M., B. Ford‐ Lloyd and M. Parry (eds). Plant Genetic Resources and Climate Change – a 21st Century Perspective, pp. 236–250. CABI International. Yang, S.Y., R.K. Saxena, P.L. Kulwal, G.J. Ash, A. Dubey, J.D.I. Harper, H.D. Upadhyaya, R. Gothalwal, A. Kilian, and R.K. Varshney (2011). The first genetic map of pigeonpea based on Diversity Arrays Technology (DArT) markers. Journal of Genetics 90: 103–109. Yol, E., H.D. Upadhyaya, B. Uzun (2016). Identification of rust resistance in groundnut by using validated SSR marker. Euphytica 210(3): 405–411. doi: 10.1007/s10681‐016‐1705‐3.

Genebank Manual Upadhyaya, H.D., and C.L.L. Gowda (2009). Managing and enhancing the use of germplasm  – strategies and methodologies. Technical manual no 10, Patancheru 502324, Andhra Pradesh, India: International Crops Research Institute for the Semi‐Arid Tropics, pp. 236.

Information Bulletins Pande, S., H.D. Upadhyaya, Narayana Rao, L.L. Reddy, and P. Parhasarathy Rao (2005). Promotion of integrated disease management of ICGV 91114, a dual purpose, early maturing groundnut variety for rain‐fed areas. Information Bulletin no. 68, Patancheru 502324, Telangana, India: International Crops Research Institute for the Semi‐Arid Tropics. pp. 28. Upadhyaya, H.D., R.P.S. Pundir, S.L. Dwivedi, and C.L.L. Gowda (2009). Mini core collections for efficient utilization of plant genetic resources in crop improvement programs. Information Bulletin no 78. Patancheru 502324, Andhra Pradesh, India: International Crops Research Institute for the Semi‐Arid Tropics, pp. 52.

Books Edited Singh, M., H.D. Upadhyaya, and I.S. Bisht, (eds. 2013). Genetic and Genomic Resources of Grain Legume Improvement. 302 pages. Elsevier, London, UK. Singh, M., and H.D. Upadhyaya (eds, 2015). Genetic and Genomic Resources for Grain Cereals Improvement. Elsevier Science Publishing Company Incorporated. 384 pages. Wang, Y.‐H., H.D. Upadhyaya, and C. Kole (eds, 2014). Genetics, Genomics and Breeding of Sorghum. 366 pages. Taylor & Francis Group, Boca Raton, FL, USA.

2 Crop Improvement Using Genome ­Editing Nathaniel M Butler and Jiming Jiang Department of Horticulture, University of Wisconsin, Madison, WI Robert M Stupar Department of Agronomy and Plant Genetics, University of ­Minnesota, St. Paul, MN

ABSTRACT Genome editing is a rapidly developing field of genetic engineering that allows precise modification of the genome. Genome editing is enabled by localizing sequence‐specific nuclease (SSN) and sequence‐specific effector (SSE) proteins to specific regions of the genome, and inducing DNA damage or modifying nucleotides or histone marks, respectively. SSN technology has been the driving force behind the advancement of genome editing, with clustered, regularly interspaced, short palindromic repeats/CRISPR‐associated system (CRISPR/ Cas) standing as the dominant technology. Nevertheless, challenges exist for applying genome editing to crop species. This chapter reviews the mechanisms underlying genome editing, the ­reagents and plant transformation systems that enable genome editing, and strategies for targeted mutagenesis and gene targeting in crop species, as well as perspective applications for genome editing for large‐scale modifications and commercial applications in agriculture. This information aims to extend the benefits of genome editing to more crop species and accelerate plant breeding efforts. KEYWORDS: Genetic engineering; gene targeting; sequence-specific nuclease; targeted mutagenesis; plant transformation; CRISPR/Cas; TALENs; gene editing

Plant Breeding Reviews, Volume 41, First Edition. Edited by Irwin Goldman. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc. 55

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OUTLINE ABBREVIATIONS I. INTRODUCTION II. CONCEPTUAL FRAMEWORK FOR GENOME EDITING A.  Development of Sequence‐Specific Nucleases 1.  Early Nucleases 2.  Designer Nucleases 3.  RNA‐guided Nucleases B.  DNA Repair Pathways 1.  Non‐homologous End‐joining 2.  Homologous Recombination C.  Modes of Modifications 1.  NHEJ‐mediated Modifications 2.  HR‐mediated Modifications III. PLANT TRANSFORMATION STRATEGIES A.  Agrobacterium‐mediated Transformation B.  Protoplasts and Biolistics C.  Plant Viral Systems IV. HARNESSING BREAKS FOR TARGETED MUTAGENESIS A.  Detecting and Stabilizing Targeted Mutations B.  Targeted Mutagenesis in Polyploids V. PRECISION GENE EDITING VIA HOMOLOGOUS RECOMBINATION VI. GENOME EDITING AT THE GENOME LEVEL A.  Large Deletions B.  Chromosomal Rearrangements C.  Epigenetic Remodelling and Base Editing VII. FUTURE PERSPECTIVES A.  Nuclease Decisions and Considerations B.  Crop Challenges and Advantages C.  Regulation of Nuclease Technology ACKNOWLEDGEMENTS LITERATURE CITED

ABBREVIATIONS ALS Acetolactate synthase aNHEJ Alternative non‐homologous end‐joining BeYDV Bean yellow dwarf virus bp Base pair CAPS Cleaved amplified polymorphic sequences CHiP Chromatin immunoprecipitation cNHEJ Canonically non‐homologous end‐joining CRISPR/Cas Clustered regularly interspaced short palindromic repeats/CRISPR‐associated system

2.  Crop Improvement Using Genome ­Editing

dCas9 Dead Cas9 DCL1 Dicer‐like 1 DSB Double‐strand break EMS Ethyl methanesulfonate EPSPS 5‐enolpyruvylshikimate‐2‐phosphate synthase FAD2 Fatty acid desaturase 2 GFP Green fluorescent protein GUS β‐glucuronidase GVR Geminivirus replicon HR Homologous recombination Indel Insertion‐deletion kb Kilo‐base miRNA Micro RNA MLO Mildew‐resistance locus Mutant X generation Mx NGS Next‐generation sequencing NHEJ Non‐homologous end‐joining ODM Oligonucleotide‐directed mutagenesis PAM Protospacer adjacent motif QTL Quantitative trait loci R genes Resistance genes Rep Replicase RVD Repeat variable diresidue SDSA Synthesis‐dependent strand annealing sgRNA Single‐guide RNA SSA Single‐strand annealing SSB Single‐strand break SSE Sequence‐specific effector SSN Sequence‐specific nuclease T7E1 T7 endonuclease 1 TALEN Transcription activator‐like effector nuclease TRV Tobacco rattle virus Tx Transgenic X generation VIGS Virus‐induced gene silencing ZFN Zinc finger nuclease I. INTRODUCTION ‘Knowledge of the laws of mutation will probably lead to the artificial ­production of mutations at will, and thus the creation of completely new properties in plants and animals. And if one can form improved, higher

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yielding and more beautiful cultivated strains by the selection method, then perhaps someday one will also be able to produce permanently better species of cultivated plants and animals by mastery of mutations.’ Hugo de Vries (1901)

The above statement from founding geneticist Hugo de Vries recalls a human desire to purposely modify genetic traits in domesticated ­species, dating back to the rediscovery of Mendel’s laws of heredity. Numerous seminal discoveries developing this concept originated in the subsequent decades of the 20th century, including the development of random mutagenesis technologies, the identification of DNA as the molecule of heredity, the advent of molecular genetics and gene cloning, and the establishment of genetic transformation methods capable of transporting genes from one species to another. More recent breakthroughs in the 21st century, however, have begun more fully to realize this vision portrayed by de Vries, and has manifested as advances in the field of genome editing. Genome editing, also known as genome engineering or gene editing, describes a suite of techniques that enable the targeted modification of DNA or epigenetic DNA modifications in a host genome. These technological advances have drawn a tremendous amount of attention, so that the most cutting‐edge genome editing methods, such as clustered regularly interspaced short palindromic repeats/CRISPR‐associated system (CRISPR/Cas) and transcription activator‐like effector nucleases (TALENs), are being recognized in the news as well as leading scientific journals (e.g. Travis, 2015). The advancement of sequence‐specific nuclease technology, and CRISPR/Cas in particular, has garnered a great deal of interest and enthusiasm towards genome editing in crop species. It is tempting to consider genome editing as analogous to pre‐ existing technologies used in crop genetic engineering and breeding (e.g. chemical/ionizing mutagenesis or genetic engineering). In reality, genome editing goes beyond existing technologies by enabling modification of the genome with higher efficiency and increased precision. Seven types of targeted DNA sequence changes can currently be made using genome editing methodology (Table  2.1). These include changes that convey a loss of gene function, a change in gene function, or establishment of novel function. In most examples, the products of genome editing are similar to those that could be developed by spontaneous or induced mutation. However, the important distinction is that the sequence changes made using genome editing can be specified to a discrete genomic region, rather than identified in collections of natural or induced mutants with genome‐wide mutations. The precision of genome editing allows sequence changes to be made

Table 2.1.

Applications of genome editing.

Desired modification

Modification type

Typical DNA repair pathway utilized

Modification outcomes

Most analogous to:

Targeted DNA substitution Targeted small DNA insertion or deletion Targeted gene insertion

Gene targeting Gene targeting

HR HR

Change of gene function Change of gene function

Gene targeting

NHEJ or HR

Targeted frame‐shift mutation

Targeted mutagenesis

NHEJ

Introduction of new gene with novel function Loss of gene function

Chemical mutagenesis Ionizing radiation or chemical mutagenesis Stable transformation

Large targeted deletion, duplication, inversion, or translocation

Genome‐wide modification

NHEJ

Targeted DNA methylation or histone modification Targeted DNA deamination

Epigenetic modification

(none)

Loss of function to single or multiple genes; change of gene dosage Change of gene function

Base editing

(none)

Change of gene function

Ionizing radiation or chemical mutagenesis Ionizing radiation mutagenesis

Methylation and histone modification mutants Ionizing radiation or chemical mutagenesis

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without altering the genetic background, in contrast to traditional genome‐wide mutagenesis platforms. Some applications allow specification of exact DNA sequence within a specified region. This includes facilitating the insertion of codons within specific genes or transgenes within specific regions of the genome, for ‘transgene stacking’ in genetically linked configurations. Hence, these attributes make genome editing technology attractive to researchers attempting to improve germplasm by modifying existing alleles, stabilizing transgene expression, and simplifying transgene breeding schemes. Still, with respect to de Vries’s prescient statement above, how will the ability to control DNA sequence alterations more precisely affect the way humans breed crops and animals? More specifically, for the sake of this review, what can genome editing do for crop improvement? The recent tsunami in sequence‐specific nuclease technology is, no doubt, the driving force behind the progress genome editing has made, but how do these exciting technologies work and how can they be applied to crop species? The present chapter provides a conceptual framework for genome editing (Section II), plant transformation technologies and vector systems used to deliver sequence‐specific nucleases and other genome editing reagents (Section III), approaches to targeted mutagenesis and targeted gene replacement (Sections IV and V, respectively), how sequence‐specific nucleases and effector proteins can be used to make other genome editing modifications (Section VI), and other topics related to genome editing, including regulations and public responses (Section VII). The field of genome editing is rapidly developing, and much of the potential impact it will make on agriculture has yet to be seen. This chapter aims to capture important topics related to genome editing for crop improvement using current examples, while emphasizing major milestones and areas for improvement.

II.  CONCEPTUAL FRAMEWORK FOR GENOME EDITING A.  Development of Sequence‐Specific Nucleases Genome editing is an approach to genetic engineering that employs DNA repair mechanisms to introduce modifications within specific regions of the genome. Genome editing is made possible by the action of sequence‐specific nucleases (SSNs) (Table 2.2), oligonucleotides and other molecules capable of binding DNA in a sequence‐specific manner (Lee et al., 2015; Sauer et al., 2016). Although early techniques using

Table 2.2. Sequence‐specific nucleases used for genome editing. Name

Nuclease type

Nuclease domain

Specificity (base pair)

Type of break (DSBs or SSBs)

Ease of development

Homing endonuclease Compact TALENs (cTALENs) Zinc finger nucleases (ZFNs) TALENs

Natural endonuclease Synthetic endonuclease

variable I‐TevI

14–40 bp 12–31 bp

DSBs DSBs or SSBs

Difficult Moderate

Synthetic endonuclease

FokI

12–36 bp

DSBs

Difficult

Synthetic endonuclease

FokI

24–62 bp

DSBs

Moderate

CRISPR/Cas FokI‐dCas9

RNA‐guided endonuclease RNA‐guided endonuclease

Cas9 (HNH, RuvC) FokI

17–20 bp 34–40 bp

DSBs DSBs

Easy Moderate

Cas9 nickase

RNA‐guided endonuclease

Cas9 (D10A or H840A)

34–40 bp

DSBs or SSBs

Easy

References Stoddard, 2011 Beurdeley et al., 2013 Kim et al., 1996 Christian et al., 2010 Jinek et al., 2012 Guilinger et al., 2014 Ran et al., 2013a

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oligonucleotides (known as oligonucleotide‐directed mutagenesis or ODM) have been successful, the focus of current technological advancements has been with developing SSNs. 1. Early Nucleases. The first class of SSNs used for genome editing was based on restriction endonucleases, called homing endonucleases or meganucleases (Figure 2.1). Homing endonucleases have combined functional domains capable of both binding DNA specifically and making double‐strand breaks (DSBs) (Stoddard, 2011). Most homing endonucleases are used in their native forms and are restricted to 14–40 base pair (bp) target DNA sequences. I‐SceI, for example, is one of the first homing endonucleases isolated from yeast (Siegl et  al., 2010). I‐SceI is known to target the 18 bp sequence (TAGGGATAACAGGGTAAT), and has been expressed in microbe, plant and animal cells to make DSBs. The ability of I‐SceI to function across biological kingdoms is not typical of all homing endonucleases, since most homing endonucleases vary in activity, depending on their host environment (Stoddard, 2005). For this reason, homing endonucleases have been isolated from plant species for uses in plant genome editing (Takeuchi et al., 2011). For example, I‐CreI, which targets the 22 bp sequence (CAAAACGTCGTGAGACAGTTTG), was isolated from Chlamydomonas reinhardtii (green algae), and has been successfully used to induce DSBs in a number of other plant species (Antunes et  al., 2012; Gao et al., 2010; Jurica et al., 1998). Not surprisingly, the uppermost limitation of using homing endonucleases is the limited number of DNA sequences that can be targeted based on available homing endonucleases. This limitation of using homing endonucleases has  been overcome by protein engineering techniques, but these methods are very technical and time consuming (Thyme et al., 2013). Instead, another restriction enzyme, FokI, has been the focus of developing subsequent classes of SSNs. 2.  Designer Nucleases.  The complication of using homing endonucleases, such as I‐SceI and I‐CreI, is the reliance on a combined domain responsible for both DNA binding and nuclease activity (Stoddard, 2011). This central feature of homing endonucleases ties DNA binding to nuclease activity, and results in great variation in overall activity across biological systems (Grizot et al., 2011). However, the restriction endonuclease, FokI overcomes this complication by having separable DNA binding and nuclease domains (Li et  al., 1992). This important feature allows the FokI nuclease domain to be fused to virtually any

Homing endonuclease (meganuclease)

Zinc finger nuclease (ZFN)

14–40 bp

6–18 bp

Transcription activatorlike effector nuclease (TALEN)

CRISPR/CRISPR-associated systems (CRISPR/Cas)

Compact TALEN (cTALEN) nickase

(CRISPR/Cas nickase) 12–31 bp

17–20 bp

Figure 2.1.  Sequence‐specific nuclease (SSN) platforms and variations used for genome editing. Homing endonucleases (meganucleases) are natural endonucleases with multifunctional domains, capable of binding double‐strand DNA targets and making double‐stranded breaks (DSBs; paired scissors). Zinc finger nucleases (ZFNs) are synthetic nucleases composed of assembled zinc finger DNA binding domains (black hexagons) and the FokI nuclease domain (grey trapezoids). Transcription activator‐like effector nucleases (TALENs) are synthetic nucleases composed of assembled TAL effector DNA binding domains (black boxes) and the FokI nuclease. Clustered regularly interspaced short palindromic repeats/CRISPR‐associated system (CRISPR/Cas) is a RNA‐guided endonuclease system employing the Cas9 nuclease (grey circle), with RuvC and HNH nuclease domains and a single‐guide RNA to guide Cas9 to DNA targets. Modification of Cas9 where RuvC or HNH nuclease domain activity is eliminated results in creation of D10A and H840A CRISPR/Cas nickases, respectively capable of producing single‐strand breaks (SSBs; single scissors). Replacement of the TALEN FokI nuclease domain with the I‐Tev nuclease domain results a compact TALEN (cTALEN) nickase capable of creating SSBs. Target DNA recognition lengths are in base pairs (bp).

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DNA binding protein, thus creating so‐called ‘designer nucleases’ (Kim and Chandrasegaran, 1994) (Figure 2.1). Another important feature of FokI is that it requires dimerization before cleavage will occur (Bitinaite et al., 1998). Modifications of the FokI nuclease domain allowed this characteristic to be exploited by requiring two versions of the FokI nuclease domain, each fused to a different DNA binding protein, to dimerize before cleavage will occur (Miller et al., 2007). The obligate heterodimeric nature of the modified FokI nuclease improves specificity by requiring two DNA binding proteins to bind adjacent sites before DNA cleavage will occur (Szczepek et al., 2007). The power of this nuclease design was first demonstrated with zinc finger nucleases (ZFNs), and set a precedent for future designer nucleases (Miller et al., 2011; Tsai et al., 2014). ZFNs are a fusion of the zinc finger DNA‐binding domain with the FokI nuclease (Figure 2.1). The zinc fingers that make up the zinc finger DNA‐binding domain are capable of binding three bp, each giving DNA recognition sequences ranging from 6 to 18 bp (Choo and Isalan, 2000). Early experiments showed that ZFNs created with the wild‐type FokI nuclease caused varying degrees of toxicity when expressed in cell cultures (Pruett‐Miller et al., 2008; Ramirez et al., 2008). This toxicity was putatively due to excessive ZFN cleaving of similar DNA sequences across the genome, called ‘off‐targeting’. To improve ZFN specificity, the heterodimeric FokI nuclease was fused to two zinc finger domains targeting adjacent DNA sequences (Miller et  al., 2007; Szczepek et  al., 2007). This strategy of requiring two ZFNs to bind before cleavage would occur improved DNA specificity, reduced toxicity, and was crucial for the success of ZFNs for genome editing in higher eukaryotes, which have large genomes and provide more opportunity for off‐targeting and excessive cleavage (Petolino, 2015; Urnov et al., 2010). However, many genes and genomic intervals of interest cannot be targeted by ZFNs, due to the context‐dependence of zinc finger domains and the requirement of designing ZFNs to target triplet DNA sequences. An alternative DNA binding protein with more flexible DNA recognition properties, known as transcription activator‐ like effector (TALE) proteins, was subsequently adapted for use in this designer nuclease system, and accelerated the pace of genome editing research. TALE proteins were discovered in the plant pathogen Xanthomas ssp. as agents of infection, having the ability to target specific DNA sequences (Boch et al., 2009; Moscou and Bogdanove, 2009). TALE proteins include a domain that binds DNA through the action of tandem repeats, which independently interact with nucleotides of target DNA

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via interactions with each repeat’s so‐called repeat variable diresidue (RVD) (Bogdanove and Voytas, 2011) (Figure 2.1). Each RVD interacts with its conjugate nucleotide through different interactions, ranging from hydrogen bonds to van der Waal contacts, and with different affinities (Sun and Zhao, 2013). Similarities in RVD‐nucleotide interactions results in RVDs having affinities for one or more nucleotides, with varying degrees of strength. For example, the four most commonly used RVDs, ‘HD, NN, NG, and NI’ primarily recognize ‘C, G/A, T, A,’ respectively. The RVD ‘NN’ recognizes both ‘G’ and ‘A’, since both nucleotides share similar hydrogen bond interactions with ‘NN’, but result in relatively strong affinities due to the use of hydrogen bond interactions. On the other hand, RVDs ‘NG’ and ‘NI’ rely on van der Waal contacts to bind their conjugate nucleotides and have relatively weaker affinities. By assembling repeats with different RVDs, an engineered TALE DNA binding domain is capable of targeting new sequence with ‘one‐ to‐one’ modularity (Čermák et al., 2011). This is in contrast to ZFNs, which bind DNA in triplets and are most effective in certain combinations (Sander et al., 2011). Furthermore, 12–31 repeats can be incorporated within a single TALE DNA binding domain, exceeding the target length limitations of ZFNs (Čermák et al., 2011). Similar strategies using the heterodimeric FokI nuclease were applied to the TALE DNA binding domain, creating TALENs (Christian et al., 2010). Soon after the creation of TALENs, a completely new class of SSNs, based on the microbial clustered regularly interspaced short palindromic repeats/CRISPR‐associated system (CRISPR/Cas), caused a paradigm shift in genome editing technologies. 3.  RNA‐guided Nucleases.  CRISPR/Cas is a powerful SSN technology that uses a guide RNA to direct a nuclease to specific DNA sequences for cleavage (Hsu et al., 2014; Jinek et al., 2012). The advantage of CRISPR/Cas over previous SSN technologies is the use of a single nuclease, called Cas9, to target virtually any sequence containing a required protospacer adjacent motif (PAM) (Figure 2.1). Cas9 and other Cas9‐like proteins target DNA by complexing with a single‐guide RNA (sgRNA) that has been engineered using 17–20 bp of sequence upstream of a PAM (Ran et al., 2013b). Once the sgRNA has complexed with Cas9 and base paired with its target DNA, Cas9 is allowed to cleave each strand of the double strand DNA using two different nuclease domains – RuvC and HNH (Jinek et al., 2014; Nishimasu et al., 2014). The use of a single nuclease in this system allows Cas9 to be optimized for different biological systems and it can be used for so‐called

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‘multiplexing’, where multiple sgRNA are expressed simultaneously and allow targeting of different sequences (Cong et al., 2013). This differs from previous designer nuclease platforms, which required nucleases to be designed for each new target and expressed individually. Furthermore, since each nuclease domain cleaves a different strand of the target DNA, Cas9 can be modified by disrupting the nuclease activity of either domain and creating a so‐called ‘nickase’, capable of generating single strand breaks (SSBs) (Ran et al., 2013a). The robust nature of the Cas9 nuclease and the mechanism of RNA‐ guided recognition have been demonstrated in a surge of studies where CRISPR/Cas has been applied to virtually every biological kingdom (Sternberg and Doudna, 2015). The ability of CRISPR/Cas and other SSN technologies to make targeted breaks in DNA is undeniable, but how can these technologies be harnessed to make specific modifications within the genome? B.  DNA Repair Pathways DNA repair is an essential element of genome editing. The breaks induced by SSNs force living cells either to fix the breaks or perish (Manova and Gruszka, 2015). An excess of breaks across the genome will overwhelm the cell and cause toxicity, so concentrating breaks to specific regions of the genome is vital both for making modifications efficiently, and for allowing modified cells to survive and divide. SSNs enable breaks to be concentrated in higher eukaryotes by recognizing DNA sequences that are unique within the genome (typically at least 10 bp), and have a low tolerance for recognizing similar sequences within the genome (off‐targets) (Carroll, 2014). The use of specific SSNs minimizes the opportunity for excessive off‐targeting, and is critical to control toxicity, so that modified cells can be grown and regenerated. The DNA repair pathways used to repair breaks in plants and other higher eukaryotes varies, depending on tissue‐type and  developmental stage but largely fall within two categories  – non‐homologous end‐joining and homologous recombination. 1.  Non‐homologous End‐joining.  Non‐homologous end‐joining (NHEJ) is the preferred DNA repair pathway in most plant cells, and can result in error‐prone, low‐fidelity repair (Puchta, 2005). The lack of a homologous DNA template during NHEJ results in various sequence modifications at the break site, and can result in insertion‐deletions ranging up to 1 kilobase (kb) in size (Manova and Gruszka, 2015; Figure 2.2). Sequencing of NHEJ repaired sites has revealed the use of short repeats

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lonizing radiation Chemical Cellular processes

Sequencespecific “nickases”

Sequencespecific nucleases

Oxidative damage Chemical Cellular processes

Single strand breaks (SSBs, “nicks”)

Double strand breaks (DSBs)

Repair template Non-homologous endjoining (NHEJ)

Canonically NHEJ Alternative NHEJ (cNHEJ) (aNHEJ)

Targeted mutagenesis

Homologous recombination (HR)

Single-strand annealing (SSA)

Synthesis-dependent strand annealing (SDSA)

Gene targeting

Figure  2.2.  DNA damage and DNA repair pathways used for genome editing. DNA damage, in the form of double‐strand breaks (DSBs) and single‐strand breaks (SSBs or ‘nicks’), underlie most applications of genome editing. DNA damage can originate both from natural (ionizing radiation, chemical, cellular processes, and oxidative damage) and synthetic (sequence‐specific nucleases and ‘nickases’) sources, and typically results in random or directed DNA damage, respectively. DSBs are a severe form of DNA damage, which induce a strong DNA repair response, primarily of the non‐homologous end‐joining (NHEJ) pathway (thick arrow). SSBs, or ‘nicks’, are a less severe form of DNA damage, but can stimulate the homologous recombination (HR) pathway (thin arrow), or can be directed to an adjacent region to induce DSBs and NHEJ. NHEJ follows two sub‐pathways, called canonically NHEJ (cNHEJ) or alternative NHEJ (aNHEJ), for low‐fidelity repair and loss or gain of sequence at the break site and frame‐shift mutations (Targeted mutagenesis). A sub‐pathway of HR, called single‐strand annealing (SSA), can also result in loss of sequence and frame‐shift mutations in the form of targeted mutagenesis. An alternative HR sub‐pathway, called synthesis‐dependent strand annealing (SDSA), uses a DNA repair ­template (Repair template) to repair both SSBs and DSBs, and is capable of introducing new sequence at the break site with high fidelity (grey stars), resulting in so‐called gene targeting. Gene targeting is the most useful form of genome editing but is least preferred in most plant cells, compared with other sub‐pathways of DNA repair.

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or microhomology near the break site to re‐join the break (Qi et  al., 2013b). For example, a break site in between two ‘TCAA’ sequences might be collapsed following NHEJ repair, resulting in a deletion of the region spanning the two sequences and a single ‘TCAA’ at the break site. Interestingly, the size of deletions resulting from NHEJ repair are larger in plants with smaller genomes, such as Arabidopsis thaliana (Arabidopsis), compared with the smaller deletions in plants with larger genomes, such as tobacco (Nicotiana tabacum) (Puchta, 2005). This observation suggests that the mechanisms of NHEJ repair might have influenced the evolution of genome size in plant species, and possibly in other higher eukaryotes. The mechanisms of NHEJ repair currently follow a canonically NHEJ (cNHEJ) sub‐pathway or the alternative NHEJ (aNHEJ) sub‐pathway (Figure  2.2). cNHEJ is highly conserved across biological kingdoms, and has been implicated to act during T‐DNA integration (Salomon and Puchta, 1998; Tzfira et al., 2003; Vaghchhipawala et al., 2012). cNHEJ is initiated by the Ku70/Ku80 heterodimer binding the end of each broken strand and forming a ring structure, which both brings the ends together and prevents their degradation (Manova and Gruszka, 2015). Subsequent steps allow correct phosphorylation and hydroxylation of each broken end and DNA ligation by ligase IV/XRCC4, XLF, PARP3, and APLF proteins for end‐joining. On the other hand, aNHEJ involves creation of 3’ single strands on the ends of each broken strand, trimming of the single strands, and re‐joining based on microhomologies near the break site. The formation of 3’ single strands, trimming and re‐joining, all introduce opportunities for sequence loss at the break site and can be highly mutagenic. The contribution of these two sub‐ pathways is thought to account for the majority of break site repairs in living plant cells, but can be modified by altering the components of each sub‐pathway. Knock‐out mutants of NHEJ components have provided insight on NHEJ repair, as well as opportunities to control DNA repair for genome editing applications. The major components of cNHEJ, namely Ku70, Ku80 and ligase IV, have been knocked out in model species, such as Arabidopsis, and have demonstrated reduced efficiency of cNHEJ and increased sensitivity to DSBs (Li et  al., 2005; Nishizawa‐Yokoi et  al., 2012; Qi et  al., 2013b; Nishizawa‐Yokoi et  al., 2016). Interestingly, ku70, ku80 and ligIV mutants in Arabidopsis have no major growth defects or in viability. Validation of these findings in other species, such as rice (Oryza sativa) suggests that such mutants could be used to suppress cNHEJ and promote other DNA repair pathways, such as homologous recombination (Endo et al., 2016).

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2. Homologous Recombination. Homologous recombination (HR) is a less frequently used DNA repair pathway in most plant cells, but typically results in error‐free, high‐fidelity repair (Puchta, 2005). The major distinction with HR, compared with NHEJ, is the use of a DNA repair template which shares sequence similarity or homology with the break site and is used to repair the break (Figure 2.2). HR between break sites and non‐allelic, repetitive sequence regions of the genome can result in rearrangements in plants with large genomes, and may explain why NHEJ is the preferred pathway in most plant cells (Manova and Gruszka, 2015). Nevertheless, the preference for HR or NHEJ cannot be overly simplified, since both pathways can be employed to repair a single break (Puchta and Fauser, 2013b). For example, NHEJ might be initiated with loss of sequence at the broken ends, and HR used to repair the break. This is putatively due to an overlap in factors controlling both pathways, and sequence features available at the break site. HR in somatic tissues occurs mostly in S and G2 phase cells, and is carried out through the single‐strand annealing (SSA) sub‐pathway and synthesis‐dependent strand annealing (SDSA) sub‐pathway (Puchta and Fauser, 2013b; Figure  2.2). SSA is analogous to the aNHEJ sub‐ pathway in the use of homologous sequences on either side of the break site, and 3’ single strand overhangs to re‐join the broken ends. In contrast to aNHEJ, SSA is mediated by the RAD52 protein, which recruits factors to create the 3’ single strand ends, resection of the single strands ends in which non‐complementary sequence is removed, gap filling of the single strand ends by DNA polymerase, and sealing of the break by DNA ligase I (Manova and Gruszka, 2015). Similar to aNHEJ, SSA is typically mutagenic or non‐conservative, and results in deletion of sequences that separate regions of homology. For this reason, SSA is the preferred pathway in repetitive regions of the genome, and is thought to be involved in the collapse of transposon‐ rich regions (Puchta, 2005). The use of a DNA repair template on the same strand as the break also makes SSA more efficient than SDSA, and is repaired at efficiencies comparable to NHEJ (Puchta et al., 1996). SDSA is the least efficient DNA repair pathway in most plant cells, but has the most potential for genome editing (Puchta and Fauser, 2013b; Figure 2). SDSA relies on the invasion of a homologous, double‐ stranded repair template with a 3’ single strand, originating from the break site that is extended and resected during repair (Manova and Gruszka, 2015). Processing and invasion of the 3’ break site is thought to be mediated by the RAD51 protein by recruitment of other factors, such as the BRCA2 protein which is responsible for formation of the invading 3’ single strand. The 3’ single strand invades the double‐stranded

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repair template, base pairing with complementary sequence and forming a D‐loop structure. The invading strand is then extended up to the homology with the other end of the break site, and resection of the D‐loop occurs. The break is then re‐joined through NHEJ, since the extended invading strand does not share homology with the other end of the break. The use of a separate DNA repair template allows an opportunity for complete conservation of sequence, incorporation of new sequence, or loss of specific sequence at the break site. Interestingly, ectopic or allelic homologous templates are rarely used for SDSA repair, and instead rely on sequences on the same chromosome or sister chromatid that is closer in proximity (Vu et al., 2014). C.  Modes of Modifications The creation of either SSBs or DSBs in the presence or absence of homologous sequence provides an opportunity to make a variety of sequence‐specific modifications (Puchta and Fauser, 2013b; Table 2.1). Most SSNs create DSBs which will employ either NHEJ and HR pathways, with a strong preference for NHEJ or SSA HR pathways. This approach is useful if sequence loss at the break site can be tolerated, or sequence disruption is desired. However, variations of certain homing endonucleases or CRISPR/Cas proteins, such as I‐TevI and Cas9 nickase, respectively, will allow formation of, primarily, SSBs, and recruitment of, primarily, the SDSA HR pathway (Davis and Maizels, 2011; Figure 2.1). This is an important strategy if sequence loss at the break site cannot be tolerated, and minimal sequence disruption is desired. The combination of different types of breaks and repair templates allows SSNs to direct virtually any type of modification to a specific genomic region. 1. NHEJ‐mediated Modifications. NHEJ‐mediated modifications are the most commonly used for genome editing, primarily because most SSNs will induce DSBs, which invoke a strong NHEJ response (Puchta and Fauser, 2013b; Figure 2.2). The types of modifications made using NHEJ are almost always deleterious or ‘loss‐of‐function’; however, NHEJ can be used for directed mutagenesis and ‘gain‐of‐function’ mutations as well (Budhagatapalli et al., 2015). Creating new gain‐of‐function mutations has traditionally been carried out using other sources of DNA damage that cause genome‐wide mutations, such as chemical treatments (e.g. ethyl methanesulfonate (EMS)) or ionizing radiation (e.g. gamma rays), with the hope that new mutations fall within useful genes.

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However, these methods are time‐consuming and result in extensive changes in the genetic background (off‐target effects) (Mba, 2013). The ability of SSNs to guide NHEJ to specific regions of the genome permits a number of modifications to be made, ranging from targeted mutations within a single gene to entire gene removal, with much higher efficiency compared with genome‐wide mutagenesis (Puchta and Fauser, 2013b; Table 2.1). The number of possible NHEJ modifications was extended with the development of CRISPR/Cas (Hsu et al., 2014). Previous SSNs, such as TALENs or ZFNs are limited to the sequences they are designed to target, and are primarily used to induce targeted insertion‐deletion ­ (indel) mutations within the coding sequences of genes (Curtin et al., 2012). CRISPR/Cas is also capable of targeted mutagenesis using indel mutations, but can target an entire gene family or network of genes via multiplexing, without the need for a shared target sequence (Baltes and Voytas, 2014). This allows simultaneous ‘knock‐out’ of potentially redundant genes or genes acting in a particular pathway (Li et al., 2016). Since cNHEJ is the preferred sub‐pathway, small deletions (ranging up to 1 kb) are typical of indel mutations and, in some cases, small insertions (typically 100 bp or less) (Manova and Gruszka, 2015). To increase specificity, Cas9 nickases have been developed that have D10A or H840A point mutations in the RuvC and HNH nuclease domains, respectively (Fauser et  al., 2014). A single Cas9 nickase can be used with a pair of sgRNAs capable of binding opposite strands of the target sequence, and separated by 5–50 bp with the ‘PAM sites out’. This approach has been successful in maintaining NHEJ mutagenesis efficiencies and indels spanning the two sgRNAs. A similar approach can be used with the wild‐type Cas9 to make deletions spanning up to 10 kb and possibly more (Zhou et al., 2014). 2. HR‐mediated Modifications. HR‐mediated modifications are less commonly used for genome editing, primarily due to the strong preference for NHEJ repair and the difficulty of supplying a readily available repair template (Puchta and Fauser, 2013a; Figure 2.2). The difficulty of supporting favourable conditions for HR is justified by its utility to incorporate virtually any sequence near a break site (Table  2.1). The exception to this tendency is with SSA repair, which allows deletions to be formed between repetitive sequences with high efficiency (Puchta et al., 1993). The length of homology needed at either end of the break site for SSA repair varies, but typically ranges from 100–500 bp. SSA repair typically does not leave indel ‘scars’ from NHEJ, and can be used to reduce repetitive sequence within a gene while maintaining

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the gene’s coding sequence. The high‐fidelity nature of SSA has been exploited in SSA‐based reporter systems, which incorporate the target sequence of a SSN between a tandem repeat within the coding sequence of a reporter, such as GUS or GFP (Zhang et  al., 2013). The high ­efficiency of SSN repair reflects the efficiency of the SSN to make a DSBs and, in turn, provides information about the efficacy of the SSN. The limitation of SSA repair to make deletions spanning repeats has limited its use for genome editing, and has allowed SDSA repair to gain more focus. SDSA repair was the first DNA repair pathway exploited for the purpose of genetic engineering and is the least efficient in most plant cells (Puchta and Fauser, 2013a). Early attempts at SDSA repair in plants, called gene targeting or gene conversion, were conducted by introducing exogenous DNA templates to protoplasts, and relying on chance invasion of the DNA template by the target sequence for HR to occur (Paszkowski and Saul, 1986; Paszkowski et al., 1988). Selection markers are typically included in the DNA repair templates, to facilitate selection of the gene targeting events. It was estimated that one in every 105 to 106 transfected cells became gene targeting events (Wright et al., 2005). The use of SSNs to induce DSBs at the target site improved gene targeting efficiencies to approximately one in every 103 transfected ­ cells, or by approximately two orders of magnitude. More recently, experiments have been conducted using the Cas9 nickase to form SSBs in the transcribed strand of a SDSA reporter system (Fauser et al., 2014). When compared to the wild‐type Cas9, the Cas9 nickase improved the rates of gene targeting approximately 2.75‐fold. The use of the Cas9 nickase for inducing SSBs is a powerful approach to promoting SDSA repair, and suppressing NHEJ repair by avoiding the use of DSBs. III.  PLANT TRANSFORMATION STRATEGIES The main limitation of applying genome editing or any other genetic engineering technology to crop species is the ability to delivery DNA, RNA or protein to living cells, and regenerate new plants (Barampuram and Zhang, 2011). Important tools in plant transformation, including Agrobacterium and plant viral systems, are actively being developed in the public sector to deliver genome editing reagents (Ali et al., 2015; Baltes et al., 2014; Marton et al., 2010). In the private sector, considerable effort has been devoted to developing so‐called transient methods of plant transformation, such as the use of protoplasts and particle

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biolistics that are capable of delivering genome editing reagents without falling under US government regulations (Clasen et  al., 2016; Sauer et al., 2016; Waltz, 2012). Regardless of the technique, all these plant transformation tools are potentially useful, and should be considered, depending on the crop of interest and the desired outcome (Table 2.3). A.  Agrobacterium‐mediated Transformation Agrobacterium is by far the most commonly used method for delivering genome editing or any other genetic engineering reagents to plant cells (Barampuram and Zhang, 2011). Agrobacterium‐mediated transformation protocols have been developed for a number of crop species and are efficient in most cases. The use of Agrobacterium for delivery of genome editing reagents, such as SSNs and DNA repair templates, has both advantages and disadvantages. The advantage of using Agrobacterium is the ability to efficiently transform and regenerate plant materials, using both Agrobacterium tumefaciens and Agrobacterium rhizogenes, and the greatest disadvantage is the reduced copy number of T‐DNA integration for SDSA repair. Agrobacterium tumefaciens is routine for most crops, but regeneration of modified plants can be a lengthy process for some crop species, such as poplar (Populus tomentosa) and soybeans (Glycine max). This is problematical when different SSNs, and DNA repair templates need to be tested for a particular target sequence, but this issue can be overcome by using ‘Agro‐infiltration’ or ‘hairy root’ transformation (Jacobs et  al., 2015; Nekrasov et  al., 2013). Agro‐infiltration is used with A. tumefaciens to deliver SSNs and DNA repair templates to living leaf materials. This approach is particularly useful in tobacco (Nicotiana tabacum) or Nicotiana benthamiana, and would need to be used in conjunction with a SSA or SDSA reporter system for testing sequences and reagents from other species (Zhang et al., 2013). Whole plants carrying the modified events have also been regenerated from Agro‐ infiltrated plant materials in a number of cases, demonstrating the utility of this system for delivering genome editing reagents (Baltes et al., 2014; Nekrasov et al., 2013). Alternatively, Agrobacterium rhizogenes can be used as part of the so‐called ‘hairy root’ transformation system (Ron et  al., 2014). Hairy roots provide advantages over regenerated whole plants, since they are easy to use with common reporter systems, such as GUS or GFP, they grow quickly, and they can be sampled and propagated in the dark as root clones (Curtin et al., 2011; Jacobs et al., 2015). Disarmed strains of A. rhizogenes can also be used for whole plant transformation, similar

Table 2.3.

Plant transformation systems used for genome editing.

Transformation system

Mode of delivery

Transient or stable

Expression level

Transformed material

Ease of use

References

Agrobacterium tumefaciens Agro‐infiltration Agrobacterium rhizogenes

T‐DNA T‐DNA T‐DNA

Stable Transient Stable

Low Moderate Low

Easy Moderate Easy

Barton et al., 1983 Schöb et al., 1997 Chilton et al., 1982

Tobacco rattle virus (TRV) Geminivirus replicon (GVR) Particle bombardment

T‐DNA T‐DNA Plasmid

High Moderate High

Moderate Easy Moderate

Ratcliff et al., 1999 Mor et al., 2003 Klein et al., 1987

Protoplasts

Plasmid

Transient Transient Stable and transient Transient

Whole plant Leaf sector ‘Hairy roots’ or whole plant Leaf sector Whole plant Whole plant

High

Protoplasts

Difficult

Damm et al., 1989

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to A. tumefaciens, if the target crop species is recalcitrant to A. tumefaciens (Veena and Taylor, 2007). A number of reports in soybean have demonstrated the use of the A. rhizogenes hairy root system for evaluating SSNs, and it is easy to imagine this approach being applied to other crops that are difficult to regenerate (Cai et al., 2015; Jacobs et al., 2015; Du et al., 2016). Interestingly, chimerism is minimal among examined root clones, suggesting that whole plants derived from these root clones could hold stable mono‐ or biallelic SSN modifications. B.  Protoplasts and Biolistics Protoplasts and particle bombardment are useful techniques for genome editing, for the ability to rapidly transform plant materials with genome editing reagents and assess their efficiency (Svitashev et  al., 2015; Zhang et  al., 2013). The direct introduction of excessive amounts of DNA, RNA or protein originating from SSNs or DNA repair templates is a powerful approach to elicit DNA repair and detect modifications (Woo et al., 2015; Zhang et al., 2016). For this reason, the first examples of genome editing were carried out using protoplasts (Puchta and Fauser, 2013a). Protoplasts provide an additional advantage for genome editing by supporting a high percentage of transfected cells, compared with Agrobacterium or particle bombardment (Zhang et al., 2013). This is an important feature, since most modifications made using genome editing do not confer a trait for selection, and unmodified cells can cause excessive background for detecting modifications and regenerating modified events. Protoplasts have been used for both NHEJ and HR modification in monocots and dicots, but are particularly useful for SDSA repair since excessive DNA template can be made available (Davey et al., 2005). The efficiency of genome editing modifications in protoplasts can be staggering, but the ability to regenerate protoplasts to whole plants is crop‐specific, and success rates can be highly variable among different labs. Particle bombardment combines the advantages of high delivery volume of protoplasts with the ability to regenerate typical of ­ Agrobacterium (Barampuram and Zhang, 2011). Similar to protoplasts, direct delivery of genome editing reagents to plant cells without relying on T‐DNA integration provides an opportunity to transiently express SSNs and deliver high volumes of DNA template for SDSA repair (Shukla et al., 2009; Svitashev et al., 2015). Transient expression can be particularly useful for genome editing, since genome editing reagents are only needed to trigger DNA repair and incorporate ­modifications.

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Persistent action of SSNs and integration of repair ­templates may cause excessive toxicity or off‐targeting, but can be counteracted by ‘segregating out’ integrated transgenes (Wang et al., 2014). Transient expression using protoplasts or particle bombardment also allows modified events to potentially fall outside of US regulations, which can be advantageous for commercial development (Wolt et al., 2015). C.  Plant Viral Systems Plant viral systems are capable of complementing an Agrobacterium‐ mediated transformation system by improving expression of SSNs, and increasing DNA repair template copy number (Ali et al., 2015; Baltes et al., 2014). Plant viruses, such as the tobacco rattle virus (TRV) and bean yellow dwarf virus (BeYDV), have been modified for use in plant biotechnology. These tools have recently been further developed for uses in genome editing and have proven their utility (Table 2.3). TRV is an RNA‐virus originally developed for virus‐induced gene silencing (VIGS) but it has more recently been used to express small SSNs and sgRNAs (Ali et al., 2015). TRV has a bipartite genome made up of two RNAs – RNA1 and RNA2 – that can be delivered to plant tissues on a T‐DNA using Agrobacterium‐mediated transformation. RNA2 can be modified to carry the sequence of a small SSN, such as a ZFN, homing endonuclease or sgRNA for CRISPR/Cas. The ability of the TRV to deliver sgRNAs has proven to be a powerful approach to NHEJ‐based modifications, providing the ability to target multiple sequences by delivering multiple viruses carrying sgRNAs. The high replication of the virus in the plant cell nucleus facilitates efficient NHEJ modification, which can be further supported by development of a Cas9‐expressing line. The use of TRV for delivering sgRNA has been demonstrated in N. benthamiana, but could also be applied to other species. BeYDV is a DNA‐virus originally developed for high expression of heterologous proteins in plant explants and cell cultures (Zhang and Mason, 2006). The DNA genome of BeYDV and other geminiviruses provides a unique opportunity for supplying a DNA template for SDSA repair (Baltes et al., 2014). Once introduced into the plant cell, BeYDV and other geminiviruses replicate to a high copy number within the nucleus, creating a geminivirus replicon (GVR), and are available for SDSA repair. Improving DNA repair template availability is important for SDSA repair, since it is thought to be the limiting factor using Agrobacterium delivery. GVRs are also capable of expressing proteins, such as SSNs, although expression of SSNs on GVRs has not shown improvements in NHEJ or HR repair (Baltes et al., 2014; Butler et al.,

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2016; Čermák et al., 2015). GVRs have been shown to enhance SDSA efficiencies five‐fold, compared with conventional T‐DNA delivery (Baltes et al., 2014). This enhancement in SDSA repair is the result of both DNA repair template availability on the GVR and the pleiotropic effects of a geminivirus trans‐acting factor called Rep/RepA. Rep/RepA is implicated to interact with a number of plant host proteins, including those involved in cell cycling that could stimulate transformed cells to enter the S‐phase, thus providing the DNA replication machinery needed for GVR replication and improving regeneration. This transition to the S‐phase most likely supports more efficient SDSA repair, and contributes to the enhanced effect that GVRs have on SDSA repair. Furthermore, integration of the T‐DNA carrying GVR components is inefficient, and can act as a transient method for expressing genome editing reagents (Butler et al., 2015; Čermák et al., 2015). This is useful in polyploid crops that cannot be crossed or selfed to remove integrated genome editing reagents. GVRs have been used successfully in tobacco, potato (Solanum tuberosum), tomato (Solanum lycopersicum), N. benthaminana and Arabidopsis, and have great potential in other crop species (Baltes et al., 2014; Butler et al., 2015; Čermák et al., 2015). IV.  HARNESSING BREAKS FOR TARGETED MUTAGENESIS Previous sections have described the most straightforward method for developing a targeted ‘loss‐of‐function’ mutation in a plant species. This form of targeted mutagenesis involves expressing SSNs in plant cells to generate DSBs at a specific sequence, and then allowing the plant’s natural NHEJ pathway to introduce frame‐shift mutations during the DSB repair. Previous reviews have extensively tabulated lists of noteworthy studies in which targeted mutations have been developed in crop plant species (e.g. Baltes and Voytas, 2014; Bortesi and Fischer, 2015; Weeks et al., 2016). Many of the major technological breakthroughs in plant genome editing have come from studies of protoplasts or somatic cells (e.g. transformed hairy roots) that cannot be passed to the next generation. Therefore, it is important to distinguish between these studies and those that generated whole plants with heritable DNA sequences changes. For most crop species, observing heritable targeted sequence alterations is considerably slower and more challenging (and clearly more valuable to breeders) than demonstrating proof‐of‐concept alterations in somatic cells. Thus, in this section, we have focused primarily

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on studies that have accomplished heritable sequence changes, as these demonstrate a more complete assessment of the feasibility of these technologies in a given species. A.  Detecting and Stabilizing Targeted Mutations Heritable loss‐of‐function mutations have been developed for several crop species, including genes targeted for methodological proof of concept, insight into biological processes, and agriculturally relevant and/ or market‐driven traits (e.g. Marton et al., 2010; Djukanovic et al., 2013; Haun et al., 2014; Wang et al., 2014; Curtin et al., 2015; Clasen et al., 2016). There are other examples in which creative utility of NHEJ mutagenesis has been used at DNA sequences that do not encode proteins. In one such example, the successful mutation of a promoter sequence in a rice sucrose‐efflux transporter gene disrupted the effector protein binding site normally used by the bacteria Xanthomonas oryzae to promote pathogen survival and virulence (Li et al., 2012). This mutation thus enhanced resistance to the pathogen, effectively creating a gain‐of‐function disease resistance locus based on the targeted mutation. While generating such events depends on the efficiency of SSN delivery and activity, detecting such events is a relatively efficient process, based on molecular and/or phenotypic markers. For proof of concept studies, mutagenesis of genes that encode visual markers (e.g. GUS or GFP) or selective markers (e.g. herbicide or antibiotic resistance) can be measured phenotypically to gauge the mutagenesis efficacy. This can be accomplished either by making functional genes non‐functional, or by making non‐functional genes functional. More commonly, however, the genes of interest are endogenous plant genes that will not exhibit an obvious phenotype in the first generation. This is particularly true for self‐pollinating species, where most endogenous genes are homozygous, and it therefore requires homozygous or biallelic mutations to confer a loss‐of‐function phenotype. In these cases, molecular assays can be developed to screen large numbers of individuals, to identify mutations at the targeted loci. There are two popular approaches for screening de novo mutations among a population of plants exposed to a SSN. The first approach, known as Cleaved Amplified Polymorphic Sequences (CAPS), involves identifying a restriction enzyme site at the targeted locus. The central idea is that PCR products from wild‐type and mutated sequences can be digested by the restriction enzymes, and differentiated by fragment analysis (e.g. agarose electrophoresis). Amplicons from homozygous

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wild‐type individuals will carry sequences that are fully digested by the enzyme, while amplicons from homozygous mutant individuals will be fully resistant to digestion (and heterozygous individuals will exhibit both digested and undigested products). Furthermore, CAPS markers can be an effective diagnostic tool to test the efficacy of specific SSNs. For example, pools of cells from hairy roots or protoplast cultures can be screened using enrichment CAPS assays. Enrichment CAPS is a modified protocol, wherein the genomic DNA sample is pre‐digested with the restriction enzyme prior to PCR amplification. The purpose of the pre‐digestion is to cut the wild‐type sequences prior to amplification, so that mutated sequences will be enriched in the sample and will, therefore, be preferentially amplified. Following the pre‐digestion and the amplification, the resulting amplicon is digested again and analyzed by fragment analysis. If a SSN is generating any type of de novo mutations at even trace levels, those novel sequences should be revealed by the enrichment PCR experiments. The CAPS method is effective for identifying novel sequence changes at specific sites, and it can distinguish homozygous wild‐type, homozygous mutant, and heterozygous individuals. However, the method requires additional bench time, due to the one or two restriction digestion reactions. More importantly, not all desired sites are amenable to CAPS analysis, as they may not possess a unique restriction digestion site, or the researcher may be interested in screening for alleles along a larger sequence tract than can be covered by one or a small number of restriction enzymes. In these cases, the user may opt for a PCR heteroduplex‐based mutation screening method. In this method, the extracted DNA is subjected to PCR, as with CAPS. However, the heteroduplex method leverages the melting and reannealing properties of the DNA to screen for mutations. PCR amplicons from individuals heterozygous for the desired mutation (heterozygotes are common in T0 or first generation SSN plants) will re‐anneal, with some strands forming a ‘bubble’, where the wild‐type and mutated strands fail to properly pair. There are two different ways to reveal the amplicons with such bubbles. First, mismatch‐specific DNA endonucleases, such as CEL I or T7 endonuclease 1, can be used to digest heteroduplexed DNA, such that the wild‐type (uncut) and heteroduplexed (cut) DNA can be distinguished by fragment analysis on standard agarose gels. Alternatively, the amplicons can be directly run on polyacrylamide gels to distinguish the banding patterns of wild‐type and heteroduplexed DNA (Zhu et  al., 2014). At first glance, it would appear that homozygous

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wild‐type and homozygous mutations may not be distinguished by this method, as differential DNA banding requires heteroduplex PCR products. However, as demonstrated by Zhu et al. (2014), wild‐type DNA can be spiked in as a control for the reactions, such that homozygous mutated individuals will form heteroduplexes with the control, while wild‐type DNA will properly anneal with the control. Relative to CAPS, the main advantage of the heteroduplex method is that the PCR products may not have to undergo digestion, and mutations do not have to be located within a defined restriction enzyme recognition site. This, therefore, adds flexibility to target site selection, as restriction sites do not have to be factored into the decision. Screening for mutations can begin in the initial generation of mutagenesis. For species that require SSN transformation, screening may commence in the T0 generation. Depending on the promoter used to drive the SSN transgene, it is possible that mutations may be chimeric throughout the plant, and some mutations that are found in somatic cells may not be transmitted to the next generation. Therefore, the progeny (e.g. T1 plants) from putatively positive plants should be screened again for novel mutations. Ideally, plants will be identified in this generation that harbour at least one mutated allele and no longer carry any transgenic sequences. However, if there are no stable mutations identified, it may still be possible to identify transgenic plants with active SSN that may generate de novo mutations in the subsequent generations (e.g. T2 or beyond). Figure  2.3 provides a visual depiction of potential scenarios that might emerge at the targeted sequence and the transgene itself following SSN transformation. This figure demonstrates the complex combinations that can occur at these respective loci across generations, and the need for reliable methods to genotype these outcomes. The figure also demonstrates the complexity of appropriately naming each generation, given the potential segregation of transgenes and mutations. We propose that the first generation in which a transgene or mutation emerges should be referred to as the ‘zeroth’ generation (e.g. the initial transgenic plant, if successfully mutated, would be considered generation T0M0). Plants that lose the transgene via segregation in subsequent generations would only be named as mutants (MX), and those that lose a heterozygous mutation via segregation in subsequent generations but maintain the transgene would only be designated as transgenic (TX). While the example in Figure 2.3 depicts scenarios for targeted NHEJ applications, one can easily imagine how this diagram would directly translate to other genome editing applications (e.g. site‐directed gene insertion; see Table 2.1 for others). Given these general guidelines and

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CRISPR is transformed and target is mutated Subsequent generations segregate for CRISPR and mutations

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Figure 2.3.  Possible modes of inheritance for SSNs and targeted modifications. In this example, a selfing crop species (line ‘Inbred A’) is stably transformed with a CRISPR/ Cas9 transgene that targets a specific mutation, and the desired genotype is a homozygous mutated line with no transgene. The transgene and the target locus are unlinked, permitting independent segregation of the two loci. The subscript accompanying each letter represents the number of generations, since the introduction of the transgene (‘T’) or induction of a mutation (‘M’). Solid lines represent direct descent from the previous generation, while dashed lines represent multiple generations. Individuals with fixed states (no longer segregating) are shown in rectangles (undesired genotypes) or circles (desired genotypes). Individuals not within rectangles or circles are heterozygous for at least one locus, or still capable of generating new mutations (i.e. carrying the transgene in the heterozygous or homozygous state). The diagram does not show all possible outcomes, but instead represents several possible scenarios that illustrate the complexity of tracking the two segregating loci and recovering the desired plant.

considerations described above, the optimal screening strategy for any given experiment depends on numerous important details, including the mating system of the plant species, the method of SSN introduction, and the preferred zygosity of the resulting mutant. B.  Targeted Mutagenesis in Polyploids One other major consideration for developing and detecting targeted mutations in plant species is ploidy. The scenario described in the previous section is most easily applied to diploid species where mutation for one allele is desired. However, the plant kingdom is replete with polyploid and paleopolyploid species, and the major crop species are no exception. Polyploid and paleopolyploid genomes contain numerous duplicated genes, often termed homologues or paralogues (depending on the origin and mechanism of gene duplication).

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Therefore, the ability to confer a desired phenotype may not only depend on successful mutagenesis and recovery of homozygous mutated alleles, but may also require the successful recovery of homozygous mutated alleles of multiple duplicated genes. Fortunately, genome editing tools enable simultaneous mutagenesis of duplicated genes, either by targeting conserved sites between paralogues using any SSN platform (Curtin et al., 2011; Wang et al., 2014) or multiplexing multiple sites specifically with the CRISPR platform (Cong et al., 2013; Lowder et al., 2015). A clean example of the importance of mutating paralogues to confer a phenotype was recently demonstrated for a duplicated pair of genes involved in the microRNA (miRNA) processing pathway of soybean (a paleopolyploid species). ZFNs were used to mutagenize each of two Dicer‐Like 1 (DCL1) genes, known as DCL1a and DCL1b (Curtin et al., 2015). As single homozygous mutants, each plant demonstrated normal growth with no perceptible phenotype. However, when these mutations were combined into a homozygous double‐mutant plant, developmental and molecular phenotypes were severely altered, resulting in plants that could not grow beyond the seedling stage. The necessity and utility of paralogue mutagenesis has also been demonstrated in agriculturally relevant traits. One study utilized a single TALEN to confer enhance powdery mildew resistance in hexaploid wheat (Triticum aestivum) by simultaneously mutating three homologous genes encoding MILDEW‐RESISTANCE LOCUS (MLO) proteins (Wang et al., 2014). Similarly, a single TALEN was used to mutate paralogous fatty acid desaturase 2 (FAD2) genes in soybean (Haun et al., 2014). Homozygous single mutations for either of the paralogues did not result in a mutant phenotype. The homozygous double‐mutant, however, exhibited a desirable high oleic acid seed composition phenotype. These examples illustrate how polyploidy and duplicate gene retention can influence the success and failure of genome editing strategies for plant improvement. The ability to mutate genes at will is not enough; one must also understand genome structure and accurately predict the phenotypic outcome of both independent single mutations and multi‐genic mutations. V. PRECISION GENE EDITING VIA HOMOLOGOUS ­RECOMBINATION The previous section highlighted the power of generating new mutations by using SSNs to stimulate DSBs that are repaired by the NHEJ pathway. This strategy allows the user to pre‐define the genomic location in

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which a mutation will occur. However, the strategy has been mostly limited to inducing loss‐of‐function frameshift mutations, as the researcher cannot specify the exact DNA sequence changes that occur at the targeted locus when using the NHEJ pathway. Researchers interested in specifying both the location and exact DNA sequence change can attempt to utilize the SDSA HR repair pathway to edit the DSB region following SSN activity, a process that is oftentimes referred to as ‘gene targeting’. The molecular mechanisms underlying the HR pathway and how it can be used to repair DSB have been comprehensively reviewed in recent literature (e.g. Steinert et  al., 2016). Therefore we will, instead, focus this section on the genome editing outcomes that can be generated in plants using this mechanism. Genome editing using HR requires the SSN to be introduced along with a DNA ‘repair template’ that specifies the DNA sequence that will repair the DSB. This repair template typically consists of a desired sequence to repair the DSB, surrounded on either side by homologous sequences that match the sequence tracts adjacent to the DSB region. The homologous flanking sequences can be used as a repair template for the DSB, thereby escorting the desired sequence change into the genomic interval. When properly executed, HR‐mediated repair with a repair template empowers the researcher to insert a specific DNA sequence alteration or novel DNA sequence (e.g. a transgene) into a specific chromosomal position. In Table  2.1, three types of DNA sequence changes are listed as potential HR introductions, including DNA base substitutions, small DNA insertions or deletions (presumably in‐frame), and targeted gene insertions. As with targeted mutagenesis, in many crops species it is considerably easier to achieve gene editing HR events in somatic cells, while recovery of heritable whole‐plant events are more difficult. Nonetheless, there have been some seminal studies that have used HR to introduce heritable sequence changes at an endogenous gene or reporter gene in crop species. For example, HR‐mediated repair of ZFN‐induced breaks of reporter and endogenous genes have been demonstrated in tobacco (Wright et al., 2005; Townsend et al., 2009); targeted non‐synonymous substitutions of endogenous genes SuRA and SuRB conferred resistance to certain herbicides. Subsequently, HR‐mediated repair of TALEN‐ induced breaks was used to introduce mutations that altered the amino acids encoded in these same tobacco genes (Zhang et al., 2013). More recently, HR‐mediated repair of CRISPR/Cas‐induced DSBs have been demonstrated in crop systems. One study introduced herbicide resistance into flax by targeting non‐synonymous point mutations into EPSPS genes (Sauer et  al., 2016). Similarly, herbicide resistance

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was introduced into maize (Zea mays) by targeting point mutations into the acetolactate synthase 2 gene (Svitashev et al., 2015). There has been considerable interest in using HR (and NHEJ) to target transgenes into a specific locus. Shukla et al. (2009) demonstrated this technology in maize, by targeting an herbicide resistance gene to an inositol‐1,3,4,5,6‐pentakisphosphate gene using HR‐mediated repair of a ZFN‐induced DSB. Similar targeting of transgene insertion sites has been demonstrated in other crop species using other SSNs; examples include recent reports of TALEN‐induced HR events in tomato (Čermák et al., 2015), and CRISPR‐induced HR events in soybean (Haun et al., 2014), maize (Svitashev et al., 2015) and tomato (Čermák et al., 2015). It is also noteworthy that targeted insertion events have also been reported using NHEJ mechanisms in species such as tobacco (Nicotiana tabacum) (Chilton and Que, 2003) and wheat (Wang et al., 2014). There have also been efforts to use HR to generate molecular stacks of multiple linked transgenes at a single locus. A single locus containing multiple transgenes is preferable to multiple unlinked transgenes, as it facilitates breeding applications. Years of work have been devoted towards developing recombinase‐based systems to generate transgenic molecular stacks (reviewed by Srivastava and Thomson, 2016). However, recent work indicates that SSNs can also be utilized to stack transgenes. One such study used a ZFN‐induced DSB to target a transgene integration event adjacent to another transgene in maize (Ainley et al., 2013). In this case, the design of the initial transgene included a ‘landing pad’ sequence, with homologous surrounding sequences that could be recognized by the ZFN and repair template, respectively. Similar work was performed in stacking a second transgene adjacent to an initial event in cotton using a meganuclease (D’Halluin et al., 2013). Undoubtedly, creative methodologies (e.g. Kumar et al., 2016) will continue to be developed to facilitate transgene molecular stacking using SSNs. Given the relative power of HR‐mediated repair, it may be surprising that there are not more examples of this method being successfully applied in plants. However, previous work indicates that the plant DSB repair processes in somatic cells overwhelmingly prefer the NHEJ pathway over HR pathways, which may explain the infrequent observation of HR‐mediated events. Researchers have recently reported some progress in increasing the frequency of HR‐mediated pathways in plants. For example, in planta, gene targeting has been enhanced by designing repair templates with SSN sites flanking the HR template, such that stably transformed templates can become extrachromosomal following SSN activity, and more frequently find the target locus to initiate repair (Schiml et al., 2014).

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Other approaches to increase HR frequency have included expressing HR‐related genes from bacteria or yeast in plants, or mutating specific plant genes that repress the HR pathway (Shaked et  al., 2005; Endo et  al., 2006; Even‐Faitelson et  al., 2011; Kwon et  al., 2012; Qi et  al., 2013b; Endo et al., 2016). Finally, recent studies found that increasing the abundance of repair template sequences available for repair by stimulating rolling circle replication in the cell or particle bombardment could increase rates of HR editing (Baltes et  al., 2014; Čermák et  al., 2015; Sun et  al., 2016). Given the power of HR‐mediated DSB repair for gene editing, it is likely that technological breakthroughs will continue in the future, further facilitating the use of this technology in plants. VI.  GENOME EDITING AT THE GENOME LEVEL The opportunity to target nucleases and effector proteins to specific regions of the genome allows modifications to be made at both the genome and epigenome‐scale (Hsu et al., 2014; Jankele and Svoboda, 2014). Versatile platforms, such as CRISPR/Cas, extend this opportunity by allowing multiple genomic regions to be targeted simultaneously (called multiplexing), and employing a single targeting protein (i.e. Cas9), which can be modified to perform an array functions (Hsu et al., 2014). The ability to make large‐scale modifications in the genome may facilitate control of complex traits not possible through modification of sequence in individual loci (Cong et al., 2013). These possibilities are already being implemented in mammalian systems, and are just beginning to be explored in crop species. A.  Large Deletions The ability to generate large deletions (1 kb or more) in an important genomic region can be used in both genetic and breeding studies to assess or modify the function of a gene or cluster of genes within a locus. Large deletions can be generated by simultaneously targeting SSNs to either end of the desired deletion region and employing NHEJ repair (Ran et al., 2013b) (Table 2.1). One or more SSNs may be used to generate large deletions, depending on SSN design and the nature of the target site. For example, an early study in Arabidopsis used ZFNs to create large deletions in resistance (R) gene clusters by designing the ZFNs to target conserved regions of the R genes (Qi et al., 2013a). This allowed a single ZFN to bind and cleave either end of the large deletion

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without the need of a second SSN. This strategy of using of a conserved target site may also be used to introduce large deletions within other repetitive sequence, such as transposons, or to remove transgenes. The advent of CRISPR/Cas has provided new opportunities for creating large deletions without the need to identify conserved sequence within target sites or express multiple SSNs. Single‐guide RNAs can be designed to target sequences spanning a desired large deletion site, and expressed simultaneously with Cas9 to introduce large deletions (Ran et al., 2013b). The ability to express more than two sgRNAs allows multiple loci to be targeted for creating large deletions within a single event (Standage‐Beier et al., 2015). The use of CRISPR/Cas for creating large deletions in plants has been demonstrated in a number of studies, including a study in rice where a 245 kb large deletion was created in T0 plants (Zhou et al., 2014). Future studies will need to be conducted to determine the stability of such large deletions in later generations, and whether large deletions can be used to remove genes within quantitative trait loci (QTL) for the purposes of fine mapping. B.  Chromosomal Rearrangements The creation of DSBs across the genome provides the opportunity for chromosomal rearrangements. Chromosomal rearrangements occur through NHEJ repair of DSBs introduced on different sister chromatids (duplications), the same chromosome (inversions), or different chromosomes (translocations) (Gorbunova and Levy, 1999). A combination of rearrangements is typical of a single event. For example, in order for a duplication to occur, a chromosomal region is deleted in one sister chromatid and is duplicated in the other. The magnitude of chromosomal rearrangements induces large genotypic changes in an individual, ranging from disease to speciation (Gorbunova and Levy, 1999). The use of genome editing to create chromosomal rearrangement has been most studied in mammalian systems, where SSNs have been expressed in cell cultures and chromosomal rearrangements have been studied using PCR and next‐generation sequencing (NGS) (Brunet et al., 2009; Egli et al., 2004; Lee et al., 2012; Maddalo et al., 2014; Piganeau et al., 2013). Such studies have highlighted the genome‐wide effects of expressing SSNs and the possibility of off‐target effects. The opportunity to harness chromosomal rearrangements in plants has been demonstrated in Arabidopsis and rice, providing information about how future studies may be conducted (Liang et al., 2016; Qi et al., 2013a).

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In the Arabdiopsis study, two ZFNs were targeted to separate genes within a gene cluster and expressed simultaneously in protoplasts. Induction of DSBs within each gene resulted in inversion of the sequence separating the two DSBs and re‐ligation. The inversion event could be detect using PCR primers spanning each target site and appeared to be stable. However, the frequency of inversions was 0.05%, whereas large deletions were much more prevalent. The frequency of inversions reported in this study was likely limited by the efficiency of the ZFNs used to induce the DSBs and the length spanning the DSBs. In the rice study, CRISPR/Cas9 was used, and the frequency of inversions in whole plants was 8.70%. However, only one of the nine paired sgRNA combinations separated by 312 bp yielded inversion events, demonstrating the importance of SSN efficiency and inversion sequence length for generating chromosomal rearrangements (Liang et al., 2016). The increasing availability of plant genomes and rapid development of comparative genomics is improving our understanding of chromosomal rearrangements in plants, and could provide the basis for using chromosomal rearrangements for crop improvement in the future (Baltes and Voytas, 2014). This includes preventing outcrossing of modified crop species and altering the inheritance of important loci. C.  Epigenetic Remodelling and Base Editing The focus of crop genetic and breeding efforts has, historically, been to make genetic changes that control important traits and are inherited in a Mendelian fashion. However, non‐Mendelian genetic changes, such as changes in methylation and histone modifications, can also affect expression of important traits (Kawashima and Berger, 2014). The use of so‐called ‘epialleles’ could be applied in plant breeding to control expression of important genes that are inherited in a non‐Mendelian fashion. Integration of bisulfite sequencing and chromatin immunoprecipitation (ChIP) data with next‐generation transcriptome sequencing is revealing the important role that epigenetic marks play in plant gene regulation and development (Baulcombe and Dean, 2014). Such epigenetic information has already made a significant impact in human genetics, through projects such as ENCODE, and is being validated using genome editing tools (ENCODE Consortium, 2012). The original intent of developing SSNs was to direct a nuclease to a specific region of the genome and trigger DNA repair mechanisms. However, SSNs with separable DNA binding and nuclease domains, such as ZFNs, TALENs and CRISPR/Cas allow for the replacement of

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nuclease domains with other effector domains, such as transcriptional activators, methylases, or acetylases, and epigenetic control of specific genomic regions (Hsu et  al., 2014; Jankele and Svoboda, 2014). Deaminases, such as cytidine deaminases, can also be used as effector domains that convert cytosine to uracil, a base with characteristics similar to thymine (Komor et al., 2016). The use of deminases and other similar effector proteins allows modification of specific nucleotides independent of DNA damage, and provides new opportunities for base editing in plant species. The development of sequence‐specific effector (SSE) proteins for epigenetic remodelling has been enabled by highly characterized transcription factor activation domains, such as VP64, and DNA and histone methylases and acetylases, as well as demethylases and deacetylases (Puchta, 2015). These highly characterized effector domains are fused to the DNA‐binding domains of ZFNs and TALENs, or to a nuclease‐inactivated (‘dead’) form of Cas9, called dCas9. The use of dCas9 has proven to be particularly effective, due to the ability to express different dCas9‐like protein‐effector fusions in combination with their respective sgRNAs. This approach allows many different loci to be modified with different epigenetic marks, and needs to express only a limited number of dCas9 effector fusion proteins. The efficiency of the dCas9 effector fusions to perform transcriptional activation and repression has been demonstrated in plants but, unlike in mammalian systems, epigenetic remodelling of DNA or histones has not yet been demonstrated (Puchta, 2015). VII.  FUTURE PERSPECTIVES The rapid development of SSN technology has ushered in a new era of genetic engineering that is providing potent tools for crop improvement. The ability to direct DSBs or effector proteins to discrete regions of the genome allows modification of sequence, ranging from a single nucleotide to epigenetic remodelling or rearrangement of entire chromosomes, respectively. These tools have already demonstrated their utility to manipulate the sequence of plant genomes, and are making future synthetic biology more of inevitability than a possibility. However, practical decisions must be made about which SSNs and other genome editing reagents should be used for a particular experiment, and whether genome editing is feasible in a given crop species. Furthermore, commercialization of resulting genome editing events must be considered, and if any restrictions for commercialization exist under the current regulatory framework.

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A.  Nuclease Decisions and Considerations SSN technology has been improving over time, but accomplishes a constant goal of creating DSBs. The question of ‘which nuclease is the best’ can be answered when considering a few factors. First, can the SSNs under consideration be expressed efficiently in the target cell type and be localized to the nucleus? The factor of nuclease expression and localization is commonly overlooked in plant genome editing studies, and is addressed by simply looking at the efficiency of the SSN in transient or stable transformation experiments. However, SSN expression and localization may be an issue for some crop species, since some SSNs are more effective than others (Osakabe and Osakabe, 2015). For example, CRISPR/Cas has been demonstrated in more crop species than any other SSN, even though it was developed most recently (Bortesi and Fischer, 2015). The varying efficiency of nucleases in different plant systems is likely affected by other factors, such as different SSN mechanisms and the nature of target sequences, but it can be better assessed by ensuring proper SSN expression and localization. Second, is the specificity of the SSNs important? Many approaches have been developed to improve SSN specificity and reduce so‐called off‐targeting (Cornu et  al., 2008; Doench et  al., 2016; Lee et  al., 2016; Quétier, 2015). The most popular method to reduce off‐targeting is the use of two SSNs which require dimerization before a DSBs is formed (Bitinaite et al., 1998; Figure 2.1). This approach uses a heterodimeric FokI nuclease and is standard for ZFNs and TALENs (Miller et al., 2007, 2011). For this reason, and the fact that TALENs are capable of recognizing larger target sites, TALENs are thought to be more specific than other SSN platforms in general. However, Cas9 used for CRISPR/Cas has also been modified to employ the FokI nuclease, which requires Cas9 to bind two adjacent target sites before cleavage will occur (Guilinger et  al., 2014; Tsai et  al., 2014). This approach, and other modifications that allow Cas9 to act as a ‘nickase’ or have less of an affinity for DNA, have been successful for improving specificity (Ran et al., 2013a). Other approaches have been used with CRISPR/Cas to improve specificity, including tethering Cas9 to another DNA binding protein, truncation of the sgRNA, fusion to FokI to create a dimeric Cas9, and engineering of high‐fidelity mismatch‐sensitive Cas9 variants (Bolukbasi et al., 2015; Fu et al., 2014; Guilinger et al., 2014; Kleinstiver et al., 2016; Slaymaker et al., 2016). Nevertheless, the use of these variations of CRISPR/Cas may complicate experiments, and can compromise efficiency for specificity. Lastly, does the SSN target site include features useful for detection? This is the most practical factor to consider, since targeted mutations

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must be detected to assess SSN efficiency, and can be the desired ­outcome. Early SSNs, such as homing endonucleases and ZFN, are much more restrictive in what target sites can be used and what sequence features can be included (Stoddard, 2011). At minimum, unique sequences should be present on either side of the target site to allow PCR amplification of the target site, and should be assayed for targeted mutations using an electrophoresis‐based assay (see Section IV; Vouillot et al., 2015). ZFNs and TALENs improved on previous SSNs by allowing identification of restriction enzyme sites within identified TALEN or ZFN cleavage sites for CAPS detection using design software (Booher and Bogdanove, 2014). The use of a CAPS assay for detection versus a heteroduplex‐based assay is preferred, especially in polyploids, since PCR enrichment can be used for samples with excessive wild‐type background, and targeted mutations can be cloned and tracked across generations (Butler et  al., 2015; Wang et  al., 2014). CRISPR/Cas further improves on identifying useful target sites by allowing more flexibility and potential for incorporation of a restriction enzyme site immediately upstream of the PAM motif (Ran et  al., 2013b). For this reason, CRISPR/Cas is likely the most useful nuclease for the purposes of detection. B.  Crop Challenges and Advantages Crop species present unique challenges and opportunities for genome editing compared to model plant species. The model species, Arabidopsis and rice, are diploid, self‐compatibility species with available reference genomes, and are highly amenable to plant transformation (Arabidopsis Sequencing Consortium, 2000; International Rice Genome Sequencing Project, 2005). The diploid nature of most model species facilitates detection of targeted modifications without excessive wild‐type alleles present in polyploid crop species (Comai, 2005). Self‐compatibility has proven to be a key attribute of model species, since primary events are typically somatic chimeras for targeted mutations, and require a germline generation to stabilize targeted modifications (Butler et al., 2015; Wang et al., 2014). Availability of a  high‐quality reference genome common for model species also ­facilitates their use for genome editing by identifying members of gene families and potential off‐target sites when designing nuclease reagents (Belhaj et al., 2013). Outcrossing or clonally propagated crop species, such as potato, cassava (Manihot esculenta Crantz), and sweet potato (Ipomoea batatas) provide unique challenges for genome editing, since

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most varieties lack self‐compatibility, high‐quality reference genomes and can be d ­ ifficult to transform. These attributes are available in some crop species, but may pose significant challenges if absent for genome editing experiments. Despite the potential challenges, crop species present significant opportunities for genome editing. Crop species have evolved an array of critical agricultural traits that are not present in model species (Morrell et al., 2011). The function of genes controlling agricultural traits, such as yield and herbicide resistance, has been investigated in plant models, but is best studied in individual crop species (Ronald, 2014). For example, the ACETOLACTATE SYNTHASE (ALS) gene in potato was recently modified using genome editing and was shown to confer reduced susceptibility to certain herbicides (Butler et al., 2016). The ALS gene was originally characterized in model species, but has shown to have variable effects on herbicide resistance in different crop backgrounds (Jander et al., 2003; Lee et al., 1988; Newhouse et al., 1991; Sathasivan et al., 1991). The application of genome editing in crop species will accelerate the study of agricultural traits, by allowing genes identified in model species to be studied in crop genetic backgrounds. The lack of genetic resources, such as mutant collections in crop species, has also hindered the study and development of agriculturally important traits, but could be used for both genetic and breeding purposes (Parry et al., 2009). The application of genome editing technologies in crop species could provide such genetic resources in specific crop backgrounds, and facilitate translation of information originating in model species to crop species (Khatodia et  al., 2016; Xiong et  al., 2015). The potential of genome editing for crop improvement is far reaching, but significant challenges exist for regulating genome editing technology in agriculture. C.  Regulation of Nuclease Technology The use of SSNs to make genome modifications in crop species poses a significant challenge for regulators around the world. Most genome editing modifications, such as those resulting from NHEJ, can be recreated in nature and can be difficult to distinguish (Figure  2.2). This poses a significant challenge not only to regulators concerned with the safety of these events, but also companies who are interested in tracking the events through production. Efforts are already under way to incorporate genome editing concepts into existing regulatory framework and to give definitions to genome editing events in the USA (Jones, 2015; Ledford, 2016).

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The factors used to define a genome editing event may determine the degree of regulatory scrutiny applied (Wolt et al., 2015). Such factors used for defining genome editing events may include the DNA repair mechanism employed, any new DNA sequence engineered into the event, and characteristics of the engineered phenotype. The DNA repair mechanism employed may also be particularly important, since NHEJ results in a low‐fidelity modification of the target site, analogous to random mutagenesis, while HR results in a high‐fidelity modification of the target site and can be capable of introducing ‘unnatural’ sequence. The presence or absence of transgenic sequence or genome editing reagents within the genome of a modified event is capable of triggering USDA‐APHIS regulation in the USA, but can be overcome by creation of ‘null‐segregates’ which have segregated out such sequence through selfing or genetic cross (Camacho et al., 2014). The use of null‐segregates, as well as other events which do not use Agrobacterium or sequence originating from ‘plant pests’, have already been successful in achieving non‐regulated status in the USA, but may be reconsidered following revisions currently being made to the US regulatory framework (Jones, 2015). Furthermore, traits common to early genome editing events, such as herbicide resistance, may draw extra attention from regulators due to their potential impacts on the environment. The overlap that genome editing shares with natural variation suggests that regulators should shift focus to the ‘product’ from the ‘process’ in which genetically engineered crops are currently regulated (Carroll et al., 2016). ACKNOWLEDGEMENTS Funding for this chapter was provided by the National Science Foundation Postdoctoral Research Fellowship in Biology under Grant No. 1523876. LITERATURE CITED Ainley, W.M., L. Sastry‐Dent, M.E. Welter, et al. (2013). Trait stacking via targeted genome editing. Plant Biotechnology Journal 11: 1126–1134. Ali, Z.A. Abul‐faraj, L. Li, N. Ghosh, M. Piatek, A. Mahjoub, et al. (2015). Efficient virus‐ mediated genome editing in plants using the CRISPR/Cas9 system. Molecular Plant 8: 1288–1291. Antunes, M.S., J.J. Smith, D. Jantz, and J.I. Medford (2012). Targeted DNA excision in Arabidopsis by a re‐engineered homing endonuclease. BMC Biotechnology 12: 1–12.

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Szczepek, M., V. Brondani, J. Büchel, L. Serrano, D.J. Segal, T. and Cathomen (2007). Structure‐based redesign of the dimerization interface reduces the toxicity of zinc‐finger nucleases. Nature Biotechnology 25: 786–793. Takeuchi, R., A.R. Lambert, A.N.‐S. Mak, K. Jacoby, R.J. Dickson, G.B. Gloor, et al. (2011). Tapping natural reservoirs of homing endonucleases for targeted gene modification. PNAS 108: 13077–13082. Thyme, S. B., S.J.S. Boissel, S. Arshiya Quadri, T. Nolan, D.A. Baker, R.U. Park, et  al. (2013). Reprogramming homing endonuclease specificity through computational design and directed evolution. Nucleic Acids Research 42: 2564–2576. Townsend, J.A., D.A. Wright, R.J. Winfrey, F. Fu, M.L. Maeder, J.K. Joung, and D.F. Voytas (2009). High‐frequency modification of plant genes using engineered zinc‐finger nucleases. Nature 459: 442–445. Travis, J (2015). Making the cut. Science 350: 1456–1457. Tsai, S. Q., N. Wyvekens, C. Khayter, J.A. Foden, V. Thapar, D. Reyon, et  al. (2014). Dimeric CRISPR RNA‐guided FokI nucleases for highly specific genome editing. Nature Biotechnology 32: 569–576. Tzfira, T., L. Frankman, M. Vaidya, and V. Citovsky (2003). Site‐specific integration of Agrobacterium tumefaciens T‐DNA via double‐stranded intermediates. Plant Physiology 133: 1011–1023. Urnov, F. D., E.J. Rebar, M.C. Holmes, H.S. Zhang, and P.D. Gregory (2010). Genome editing with engineered zinc finger nucleases. Nature Reviews 11: 636–646. Vaghchhipawala, Z. E., B. Vasudevan, S. Lee, M.R. Morsy, and K.S. Mysore (2012). Agrobacterium may delay plant nonhomologous end‐joining DNA repair via XRCC4 to favor T‐DNA integration. Plant Cell 24: 4110–4123. Veena, V., and C.G. Taylor (2007). Agrobacterium rhizogenes: recent developments and  promising applications. In Vitro Cellular & Developmental Biology  –  Plant 43: 383–403. Vouillot, L., A. Thelie, and N. Pollet (2015). Comparison of T7E1 and surveyor mismatch cleavage assays to detect mutations triggered by engineered nucleases. G3 5: 407–415. Vu, G. T. H., H.X. Cao, K. Watanabe, G. Hensel, F.R. Blattner, J. Kumlehn, et al. (2014). Repair of site‐specific DNA double‐strand breaks in barley occurs via diverse pathways primarily involving the sister chromatid. Plant Cell 26: 2156–2167. Waltz, E. (2012). Tiptoeing around transgenics. Nature Biotechnology 30: 215–217. Wang, Y., X. Cheng, Q. Shan, Y. Zhang, J. Liu, C. Gao, et al. (2014). Simultaneous editing of three homoeoalleles in hexaploid bread wheat confers heritable resistance to powdery mildew. Nature Biotechnology 32: 947–951. Weeks, D. P., M.H. Spalding, and B. Yang (2016). Use of designer nucleases for targeted gene and genome editing in plants. Plant Biotechnology Journal 14: 483–495. Wolt, J. D., K. Wang, and B. Yang (2015). The regulatory status of genome‐edited crops. Plant Biotechnology Journal 14: 510–518. Woo, J.W., J. Kim, S.I. Kwon, et al. (2015). DNA‐free genome editing in plants with preassembled CRISPR‐Cas9 ribonucleoproteins. Nature Biotechnology 33: 1162–1164. Wright, D. A, J.A. Townsend, R.J. Winfrey, P.A. Irwin, J. Rajagopal, P.M. Lonosky, et al. (2005). High‐frequency homologous recombination in plants mediated by zinc‐finger nucleases. The Plant Journal 44: 693–705. Xiong, J.‐S., J. Ding, and Y. Li (2015). Genome‐editing technologies and their potential application in horticultural crop breeding. Horticulture Research 2: 15019. Zhang, X., and H. Mason (2006). Bean Yellow Dwarf Virus replicons for high‐level transgene expression in transgenic plants and cell cultures. Biotechnology and Bioengineering 93: 271–279.

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Zhang, Y., F. Zhang, X. Li, J.A. Baller, Y. Qi, C.G. Starker, et  al. (2013). Transcription activator‐like effector nucleases enable efficient plant genome engineering. Plant ­ Physiology 161: 20–27. Zhang, Y., Z. Liang, Y. Zong, Y. Wang, J. Liu, K. Chen, J.‐L. Qiu, and C. Gao (2016). Efficient and transgene‐free genome editing in wheat through transient expression of CRISPR/Cas9 DNA or RNA. Nature Communications 7: 12617. Zhou, H., B.B. Liu, D.P. Weeks, M.H. Spalding, and B. Yang (2014). Large chromosomal deletions and heritable small genetic changes induced by CRISPR/Cas9 in rice. Nucleic Acids Research 42: 1–12. Zhu, X., Y. Xu, S. Yu, L. Lu, M. Ding, J. Cheng, et  al. (2014). An efficient genotyping method for genome‐modified animals and human cells generated with CRISPR/Cas9 system. Scientific Reports 4: 6420.

3 Development and Commercialization of CMS Pigeonpea Hybrids KB Saxena and D Sharma International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT), Patancheru, Telangana, India MI Vales Department of Horticultural Sciences, Texas A&M University, College Station, TX

ABSTRACT The role of heterosis in enhancing productivity in food crops is well known. Legume breeders have not been able, however, to take advantage of this genetic phenomenon for a long time, due to biological restrictions, such as the requirement of high seeding rate and the inability to produce large quantities of F1 hybrid seed. Recently, in pigeonpea (Cajanus cajan (L.) Millsp.), a breakthrough has been realized with the development and marketing of the world’s first legume hybrid, ICPH 2671. The key for this achievement was breeding and using a stable cytoplasmic nuclear male sterility (CMS) system obtained from the cross between C. cajanifolius, a wild relative of pigeonpea, and the cultivated type. The inherent partial natural out‐crossing of pigeonpea was knitted with this CMS system to facilitate economically‐viable large‐scale hybrid seed production. These developments provided opportunities to overcome the historic stagnant low yield (0.6–0.8 t ha–1) through heterosis breeding. Among hundreds of hybrid combinations tested, a cross between ICPA 2043 and ICPL 87119 (=ICPR 2671), designated as ICPH 2671, was the most promising, with >40% yield superiority (reaching yields above 3 t ha–1) over the prevalent cultivar ‘Maruti’, in multi‐location, multi‐year, on‐station trials, as well as on‐farm evaluations. The outstanding performance of ICPH 2671 led to its release in 2010 as the first medium duration commercial pigeonpea hybrid in India. Subsequently, two additional pigeonpea hybrids, ICPH 3762 and ICPH 2740 were also released Plant Breeding Reviews, Volume 41, First Edition. Edited by Irwin Goldman. © 2018 John Wiley & Sons, Inc. Published 2018 by John Wiley & Sons, Inc. 103

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for commercial cultivation in India in 2014 and 2015, respectively. According to recent estimates, in 2015 the CMS‐based pigeonpea hybrids were grown over 150,000 hectares in central and southern India. In this review, we summarize the research efforts that led to the milestone of developing the first commercial hybrid in food legumes. KEYWORDS: Cajanus cajan; cytoplasmic nuclear male sterility; heterosis; host plant resistance; hybrid seed production; pulses; legumes; yield. OUTLINE ABBREVIATIONS I.  INTRODUCTION II.  REPRODUCTIVE CYCLE AND MORPHOLOGY OF PIGEONPEA A.  Induction of Flowering B.  Maturity Range C.  Flower Structure D.  Flowering Pattern E.  Pollination and Fertilization F.  Natural Cross‐pollination 1.  Cross‐pollinating Agents 2.  Extent of Out‐crossing III.  CROP PRODUCTION A.  General Agronomy B.  Major Production Constraints 1.  Diseases 2.  Insect Pests 3.  Waterlogging IV.  EXTENT AND NATURE OF HETEROSIS IN PIGEONPEA V.  GENETIC MALE STERILITY‐BASED HYBRID TECHNOLOGY A.  Genetic Male Sterility Systems B.  Heterosis in GMS‐based Hybrids C.  Release of the First GMS‐based Pigeonpea Hybrid D.  Hybrid Seed Production Technology E.  Assessment of GMS‐based Hybrid Technology VI.  TEMPERATURE‐SENSITIVE MALE STERILITY VII.  CYTOPLASMIC NUCLEAR MALE STERILITY‐BASED HYBRID TECHNOLOGY A.  Early Efforts to Produce CMS System B.  Breakthrough in Breeding Stable CMS Systems C.  Diversification of Cytoplasm 1.  A1 CMS System from Cajanus sericeus (Benth. ex Bak.) van der Maesen 2.  A2 CMS System from Cajanus scarabaeoides (L.) Thou 3.  A3 CMS System from Cajanus volubilis (Blanco) Blanco

3.  DEVELOPMENT AND COMMERCIALIZATION 4.  A4 CMS System from Cajanus cajanifolius (Haines) Maesen 5.  A5 CMS System from Cajanus cajan (L.) Millsp 6.  A6 CMS System from Cajanus lineatus (W & A) van der Maesen 7.  A7 CMS from Cajanus platycarpus (Benth.) van der Maesen 8.  A8 CMS System from Cajanus reticulatus (Aiton) F. Muell 9.  A9 CMS System from Cajanus cajan (L.) Millsp D.  Effect of Pigeonpea Cytoplasm on Yield E.  Fertility Restoration of A4 CMS System VIII.  BREEDING NEW HYBRID PARENTS A.  Fixing Priorities B.  Selection of Hybrid Parents from Germplasm and Breeding Populations C.  Isolation of Fertility Restoring Inbred Lines from Heterotic Hybrids D.  Breeding Dwarf Parental Lines E.  Breeding Determinate/Non‐determinate Parental Lines F.  Disease‐resistant Parental Lines G.  Use of a Naked‐eye Polymorphic Marker in Hybrid Breeding H.  Formation of Heterotic Groups I.  Inbreeding Depression IX.  APPLICATION OF GENOMICS IN BREEDING HYBRIDS A.  Understanding the Molecular Genetics Basis of the A4 CMS System B.  Tagging Fertility‐restoring Genes C.  Assessment of Genetic Purity D.  Potential Role in Breeding Two‐line Hybrids X.  COMMERCIALIZATION OF HYBRID PIGEONPEA TECHNOLOGY A.  Standard Heterosis 1.  Early Maturing Hybrids 2.  Medium‐ and Late‐maturing Hybrids B.  Release of the World’s First Commercial Legume Hybrid C.  Hybrid Seed Production Technology D.  Economics of Hybrid Seed Production XI.  OUTLOOK ACKNOWLEDGEMENTS LITERATURE CITED

ABBREVIATIONS ATP adenosine triphosphate BC backcross CMS/CGMS cytoplasmic nuclear/genetic male sterility DES Directorate of Economics and Statistics DV daily value

105

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FAO Food and Agriculture Organization on the United Nations GMS genetic male sterility ICAR Indian Council of Agricultural Research ICRISAT International Crops Research Institute for the Semi‐ Arid Tropics Mb megabase pair mRNA messenger ribonucleic acid ORF open reading frame Person. commun. personal communication QTL quantitative trait loci rpm revolutions per minute SSR simple sequence repeat TGMS temperature‐sensitive male sterility system USDA United States Department of Agriculture I. INTRODUCTION Most farmers in the developing world earn their livelihoods from small land holdings using subsistence level agricultural systems. In those areas, malnutrition is spreading fast, mainly due to a steady decline in the availability of protein‐rich foods (NIN, 2010). Several factors, including expanding family size, limited growth in the production of protein‐rich pulses, and escalating prices, are contributing to this ­problem (Shalendra et al., 2013). In this context, pigeonpea (Cajanus cajan (L.) Millsp.) is a nutritious legume rich in carbohydrates (62.8 g per 100 g of raw mature grain, 21% DV), fibre (15 g per 100 g, 60% DV), protein (22 g per 100 g, 43% DV, containing the important amino acids methionine, lysine and tryptophan), vitamins (Thiamine 43% of DV, Folate 114% of DV), minerals (manganese 90% of DV, magnesium 46% of DV and phosphorus 37% of DV) and low fat (1.5 g per 100, 2% of DV) (USDA‐ARS National Nutrient Database). It is highly appreciated in the semi‐arid tropics, due to its resilience and role in subsistence agricultural systems. It grows well under diverse environments, cropping systems and it has capacity to tolerate various biotic and abiotic stresses. In rural settings, pigeonpea is considered a multi‐purpose crop; it is used as food (fresh as vegetable and dry as processed split peas), fodder, feed, fuel wood, and even construction material (Saxena, 2008; Saxena et  al., 2010b). Besides these benefits, the cultivation of this environmentally friendly crop also helps in improving general soil health (composition and structure) by providing around 40 kg ha–1of residual

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Table 3.1.  Area, production, and grain yield of the main pigeonpea growing countries. Area (000 ha)

Production (000 t)

Asia India Myanmar Nepal

5,602 611 17

3,290 575 16

587 940 965

Africa Kenya Malawi Tanzania Uganda Congo

276 81 250 33 11

274 34 248 13 7

994 420 990 406 636

Caribbean Dominican Republic Haiti

23 110

24 90

1,066 814

7,033

4,890

695

Country

Global

Yield (kg ha–1)

Source: http://www.faostat3.fao.org. Reproduced with permission of Food and Agriculture Organization of the United Nations (FAOSTAT), 2017.

nitrogen, releasing soil‐bound phosphorus, adding organic matter, and facilitating water infiltration. Considering these advantages, pigeonpea has become an important crop of the tropics and sub‐tropics of Asia, Africa, and South America. According to FAOSTAT (2017), the estimated globally‐sown pigeonpea area is around 7.03 million ha with a total production of 4.89 million t, and average yield of 0.695 t ha–1. India has the largest (75%) share of the global pigeonpea production area (Table 3.1). According to DES (2015), the national production of 3.29 million t is insufficient to meet the domestic requirements and about 500,000 t of pigeonpea are imported annually from Myanmar and Africa. Pigeonpea has been under cultivation for more than 3,500 years, but some botanists believe it is far from true domestication, because it still carries certain survival and evolutionary traits of its wild ancestors, such as perennial growth habit, poor harvest index, deep root system, natural out‐crossing, ability to recover from various stresses, and shattering of mature pods. Genetic improvement of this crop began in India in 1931 at the Imperial Agricultural Research Institute, Pusa (Bihar), with pure line selection within phenotypically promising landraces for simply inherited traits, with enhanced focus on disease resistance and plant type. Subsequently, the Indian Council of Agricultural Research (ICAR) launched a long‐term ‘All India Coordinated Pigeonpea Improvement Programme’ to develop high‐yielding cultivars and their production

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technology for different regions. This endeavour led to the release of over 100 cultivars (Singh et al., 2005) through pedigree selection from among and within landraces and breeding populations. A perusal of these cultivars revealed that, although significant advances were made with respect to earliness, plant type, seed type, and resistance to diseases, their on‐farm yield remained stagnant (0.6–0.8 t ha–1), which has been a matter of concern for decades. Partial out‐crossing of pigeonpea could s­ omewhat explain the lack of success in increasing grain yield, despite releasing new promising cultivars over time. Certain important traits (such as host plant resistance to pathogens) in commercial cultivars can be easily lost when farmers save seed (a mix of selfing and out‐crossing) for the next season. Efforts to preserve cultivar identity, recently popularized, include the implementation of the concept of One Village One Variety, which guarantees physical separation between cultivars. Green et al. (1981) reviewed global pigeonpea improvement programs, and concluded that ‘Almost all the traditional breeding methods of self‐pollinated crops were tried by pigeonpea breeders, but without ­significant gains in its productivity.’ Moreover, Khan (1973) ­proposed the use of partial natural out‐crossing in breeding high yielding pigeonpea populations. Onim (1981) used this approach in Kenya, and obtained encouraging results with 2% yield gain in each cycle of  selection. However, despite the encouraging results, this breeding approach failed to take off. Hence, pedigree breeding has remained the preferred pigeonpea breeding method in India and elsewhere. The discovery of male sterility systems, and the existence of partial natural out‐crossing in pigeonpea, encouraged breeders both at the International Crops Research Institute for the Semi‐Arid Tropics (ICRISAT, Patancheru, Telangana, India) and ICAR to explore the possibility of developing hybrids in this food legume. Overall, these developments generated a lot of optimism among breeders towards breaking the decades‐old productivity barrier in pigeonpea. In this review article, we summarize the breeding and seed production research efforts that led to the milestone of developing the first commercial hybrid in food legumes, and we also discuss the potential role of pigeonpea hybrids in achieving food and nutritional security in the semi‐arid tropics. II.  REPRODUCTIVE CYCLE AND MORPHOLOGY OF PIGEONPEA A.  Induction of Flowering By nature, most pigeonpea landraces are of long duration, highly ­photoperiod sensitive, and short‐lived (4–5 years) perennials. In such

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l­andraces, the induction of flowering takes place at the onset of short days (around ten hours of light). This photoperiod requirement restricts their adaptation between 15–35° latitudes. Breeders s­ uccessfully bred short‐duration cultivars that exhibited relatively less sensitivity to day length. Wallis et al. (1981) demonstrated that pigeonpea earliness was closely related to photoperiod insensitivity. The less sensitive genotypes produce less biomass, show wide adaptation (up to 45° latitude), and provide flexible sowing date options (Saxena, 2008). Saxena et al. (1981) found three dominant genes that controlled the photoperiod reaction and were expressed in hierarchical order (Ps3>Ps2>Ps1), with ps1ps1, being the earliest to flower and the least photoperiod sensitive. At ICRISAT photoperiod sensitive genotypes flowered under a ten‐hour photoperiod and continued flowering even under relatively longer (14 hours) days. B.  Maturity Range Pigeonpea shows continuous variation for maturity, from < 90 to >250 days. This range has allowed farmers to choose the cultivars best suited to their local agro‐ecological conditions and production systems. For practical purposes, four broad maturity groups have been recognized in India. These are: extra‐short/early (91–120 days), short/early (121–150 days), medium (161–200 days), and long/late (>250 days). Recently, Vales et al. (2012) bred pigeonpea genotypes that matured in < 90 days at ICRISAT. These super‐early types are useful in diversifying pigeonpea cultivation in the areas characterized by a short growing season or low temperature, such as high latitudes and ­altitudes. Furthermore, to assist breeders in planning and selection, they established 11 maturity groups in pigeonpea (Table 3.2). From the adaptation and commercial points of view, medium duration pigeonpea occupies the larger area (65%) followed by the long ­duration group (30%). These two groups are invariably cultivated as intercrops with short‐aged cereals or pulses. In contrast, the early types are typically cultivated under high density and pure stands in cropping systems that alternate cereals and legumes, and occupy 90% of these belonged to pigeonpea. In Kenya, Onim (1981) reported that also Xylocopa spp. ­(carpenter bee) and Bombus spp. (bumble bee) affected cross‐pollination in pigeonpea. Brar et  al. (1992) and Verma and Sandhu (1995) reported that M. lanata, A. dorsata, and Xylocopa spp. were responsible for cross‐ pollinating pigeonpea in Ludhiana (India). Similarly, Zeng‐Hong et al. (2011) also observed that in Yuanmou (China) Megachile spp., Xylocopa spp., and Apinea spp. actively participated in the collection and transfer of pollen grains to effect cross‐pollination. Onim (1979, 1981) reported very high levels (>70%) of natural out‐ crossing in Kenya. They also observed that each insect visit to pigeonpea flowers lasted from 15–55 seconds. Zheng‐Hong et  al. (2011) reported that the pollinating insects were more frequent on male fertile plants, with a mean of 4.8 visits 10 minutes–1, compared with male ­sterile counterparts recording 2.8 visits 10 minutes–1. They attributed that this behaviour of the pollinators was due to differences in the ­production of: (i)  chemicals such as flavone and flavonol; (ii)  nectar; (iii)  some specific scent emitted by pollen grains. They further reported that even with 50% fewer insect visitations, the male sterile plants produced cross‐pollinated yield (384 g plant–1), similar to that of more frequently visited fertile plants (357 g plant–1). They also concluded that, for good pod seed set on the male sterile plants, a very high level of insect activity was not essential to produce reasonably good quantities of hybrid seed in the production plots. An experiment conducted by ICRISAT in Patancheru during the 2010 and 2011 seasons showed that seed production of a male sterile line (A × B) outdoors using net houses containing Apis mellifera bee hives was unacceptably low (800 kg ha–1 and reaching ≈ 1,200 kg ha–1 when sequential planting (three weekly plantings) was used). The controlled system (net houses containing beehives) had the potential to

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­ roduce pure seed of fertile plants (>1,000 kg ha–1 of B lines), but p not the seed on the male sterile plants. Thus, it could be recommended for producing seed of fertile parental lines and varieties, but not for maintenance of the A parent (A × B) or hybrid seed (A × R) (Vales, unpubl.). 2.  Extent of Out‐crossing.  Natural out‐crossing in pigeonpea was first recorded by Howard et al. (1919). A review on this subject by Saxena et al. (1990) revealed a large variation (0–70%) in the extent of natural out‐crossing in all the pigeonpea growing sites. The primary factor responsible for the variation in out‐crossing is the population of insect pollinators in a particular field during the flowering period. Besides this, there are some biological and physical factors that also influence cross‐pollination in pigeonpea. The genotypic variability in floral morphology, such as the presence of wrapped flowers (Byth et  al., 1982), cleistogamy (Saxena et  al., 1993) and the quantity of nectar produced (Zeng‐Hong et al., 2011) also affect insect activity and degree of cross‐pollination. Factors such as extended period of stigma receptivity (Dalvi and Saxena, 2009) and competitive advantage of foreign pollen in germination (Onim et al., 1979), pollen tube growth (Dutta and Deb, 1970), and fertilization (Reddy and Mishra, 1981) have also been reported to encourage cross‐ pollination in this species. Bhatia et al. (1981) observed that the density of pollinating insects is the key factor for cross‐pollination in a particular field. Other factors influencing out‐crossing were: (i)  direction and velocity of wind; (ii)  habitat of production plots; (iii)  general weather conditions (dry or rainy days); (iv)  general health of the crop. Under such circumstances, it is logical to expect that these factors will not be uniform across locations and, hence, the outcome with respect to natural out‐crossing will be site‐specific. In view of the potential dangers of out‐crossing, the production of genetically pure seed needs special skills and planning in artificial means of selfing, or the use of adequate isolation is necessary. Small quantities of selfed seed are generally produced by enclosing branches (part or full) or whole plants before the flowers open, using muslin cloth bags of different sizes. For producing medium quantities (10–20 kg)

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of  selfed seed, small net houses (nylon nets attached to fixed metal frames) are used. The production of larger quantities of pure seed is done in field plots isolated by at least 500 m from other pigeonpea fields. III.  CROP PRODUCTION A.  General Agronomy Traditional pigeonpea cultivars are known to excel under subsistence agriculture. Under heavy soils or higher latitudes (27–30° N), long duration (>250 days) cultivars are adapted whereas, at lower latitudes (12–25° N), medium maturing (161–200 days) genotypes are grown. Interestingly, both of these types are cultivated with short‐aged cereals as intercrop under rain‐fed conditions, and require similar agronomy. In contrast, the early maturing group is always cultivated as a high‐ density sole crop. The plants of this group have small canopy and ­produce less biomass; hence, the crop is sown under high densities (up to 300,000 plants ha–1) to allow mechanical cultivation of pigeonpea and save labour. The late maturing cultivars are grown at densities of around 45,000 plants ha–1. In general, pigeonpea is susceptible to waterlogging, so selection of well drained fields is essential. The crop does not respond to phosphate fertilizers, but an initial dose (20 kg ha–1 N) of nitrogen helps by boosting its initial slow seedling growth. The plants are nodulated with a cowpea group of bacteria. All of the three groups are equally susceptible to insects, particularly Helicoverpa armigera and Maruca testulalis pod borers, so chemical control of insects is essential in order to minimize damage. D. Sharma (ICRISAT, person. commun.) demonstrated that the productivity of early, medium, and late maturity group genotypes is comparable and that, under optimum crop management practices and conducive environment, each group can produce about 2–3 t ha–1 of seed yield. B.  Major Production Constraints 1. Diseases. Pigeonpea plants and seeds are known to encounter the invasion of over 100 pathogens, but only a few of them cause economic losses. Among these, some diseases, such as Phytophthora, Alternaria blight, bitches broom, phoma canker, and leaf spots are site‐ or environment‐specific. Considering the global importance, Fusarium

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wilt and sterility mosaic virus are widespread diseases, and each year cause huge losses. From a hybrid breeding point of view, only these two diseases have been considered for discussion. According to Kannaiyan et al. (1984), the estimated combined annual losses due to these diseases in India were worth US$ 113 million while, in Africa, wilt losses were US$ 5 million. Wilt, caused by Fusarium udum Butler, is a soil‐borne fungal ­disease found in most pigeonpea growing areas of Asia and Africa. Butler (1908) was the first to report this disease from India. The symptoms of the disease (wilting) usually appear during the flowering and podding stage of the plant, when carbohydrate depletion occurs in the roots and stem, and the affected plants die quickly without producing any seed. Yield losses due to this disease can be up to 100%. The f­ungus multiplies and remains viable in the soil for at least three years or more and, consequently, it appears year after year. Likewise, the cultivation of susceptible cultivars increases inoculum in the fields. The chemical control of this disease is expensive and not very ­effective. Hence, the use of genetic resistance has been given high priority both in Asia and Africa. Studies on the genetics of resistance to Fusarium wilt have shown the presence of two genes: one dominant and another recessive. Both genes impart resistance to the disease and segregate independently. In the literature, perhaps for this reason, depending on the parents used in crosses, reports on multiple genes (Pal, 1934), two complementary genes (Shaw, 1936), single dominant gene (Joshi, 1957), and single recessive gene (Odeny et al., 2009) controlling the resistance to Fusarium wilt are available. Saxena et  al. (2012) confirmed the presence of both genes in a single study. Races of the pathogen for Fusarium wilt in pigeonpea remain unclear (Tiwari and Dhar, 2011). The second most important disease of pigeonpea is sterility mosaic virus, which is transmitted by an eriophyid mite (Aceria cajani). Alam (1931) and Mitra (1931) were the first to document its occurrence in India. Its incidence in farmers’ fields varies from 0 up to 100%. Its  infection can occur at any stage of growth, but the tender leaves emerging from seedlings or regenerated plant growth are first infected. The disease spreads quickly, as the viruliferous mites can be airborne, and the direction of wind can spread the disease up to 2 km (Reddy et al., 1990). The genetics of resistance to sterility mosaic disease is complex. Its  inheritance is affected by undefined interactions among the host  plant, mite, and virus, and parental lines used in crosses.

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These  interactions affect the symptoms of the disease. Singh et  al. (1983) reported that the resistance to sterility mosaic disease was ­controlled by four independent non‐allelic genes. Of these, two each were dominant and recessive. They further mentioned that, for a plant to express resistance reaction, the presence of one dominant and one recessive gene is essential. Sharma et al. (1984) found that two alleles, one dominant and one recessive, controlled the immunity to disease; the tolerance reaction was attributed to the presence of a single recessive gene. Srinivas et al. (1997) found the that the resistance was recessive in some crosses but dominant in others, and it was isolate‐ specific. Ganapathy et al. (2012) reported monogenic recessive resistance in one cross, and non‐allelic digenic with complementary epistasis in another cross. For sterility mosaic, three prevalent isolates have been described: Hyderabad, Bangalore, and Coimbatore. The presence of different ­isolates makes the understanding of the resistance more challenging. 2.  Insect Pests.  Among insects, pod borers (Helicoverpa armigera and Maruca testulalis) and pod fly (Melanogromyza obtusa) cause severe losses to the pigeonpea crop. However, due to the absence of any reliable source of genetic resistance, conventional breeding to improve insect resistance has not been undertaken, and the incorporating of Bt genes is being pursued by ICRISAT (Sharma et al., 2008) and ICAR (Ramu et al., 2011). 3. Waterlogging. Among the abiotic stresses that affect pigeonpea productivity, waterlogging is the second most important constraint ­after drought. There is no success with respect to breeding drought tolerant cultivars in pigeonpea but, with the development of an ­ ­effective waterlogging screening technology (Chauhan et  al., 1997), research on resistance breeding was started. Sultana et  al. (2013) screened in excess of 400 pigeonpea germplasm and identified a number of waterlogging tolerant genotypes. Saxena and Tikle (2015) reported that, among the tolerant genotypes, 100 were fertility restorers and 26 maintainers of A4 male sterility system. This finding facilitated the breeder’s job. Since the resistance to waterlogging is controlled by a single dominant gene (Perera et al., 2001; Sarode et al., 2007), its incorporation in the productive hybrid parents is relatively easy and resource‐efficient. Some of the male sterile lines, such as ICPA 2092, ICPA 2078, and ICPA 2098, are productive, resistant to wilt and sterility mosaic disease, good combiners, and produce high yielding hybrids, but they are

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highly susceptible to waterlogging. Potential A‐ lines can be crossed directly with waterlogging‐tolerant restorers in order to develop ­waterlogging‐tolerant pigeonpea hybrids. Considering the seriousness of this constraint and the need to breed high‐yielding hybrids adapted to temporary waterlogging conditions, breeding of new tolerant hybrid parents (A, B, R) is essential for the long‐term stability and wide adaptability of hybrids. IV.  EXTENT AND NATURE OF HETEROSIS IN PIGEONPEA The literature on heterosis in pigeonpea is limited. The first report on this aspect was published by Solomon et al. (1957). They reported that a single cross hybrid recorded 24.5% heterosis over the better parent for seed yield. Recent reviews on this aspect by Sawargaonkar (2011), Kyu (2011), Wanjari and Rathod (2012) and Mudaraddi (2015) revealed that, in over 50 publications, the heterobeltiosis for seed yield was ­significant, but with a wide range. The development of genetic (GMS) and cytoplasmic (CMS) male sterility systems triggered a change in the reporting of heterosis. Most researchers, keeping in view its practical application, used ‘standard heterosis’ (superiority over best cultivar used as check) as an indicator of hybrid vigour. Both the GMS‐ and CMS‐based hybrids demonstrated the presence of significant heterosis that led to the release of hybrid (details in subsequent sections). Saxena et al. (2005b) reported over 50% standard heterosis in the first set of CMS‐based experimental hybrids, while Kandalkar (2007) recorded up to 156% standard heterosis for grain yield. Subsequently, Dheva et al. (2009), Kumar et al. (2009, 2012), Shoba and Balan (2010), Gupta et al. (2011), Mudaraddi and Saxena (2012), Gedam et  al. (2013), Saxena et  al. (2013a; 2014b; 2014c), Pandey et  al. (2013), Patel and Tikka (2014), Yamanura et  al. (2014), Patil et al. (2014), and Ajay et al. (2015) also recorded highly ­significant levels (>20%) of standard heterosis in CMS‐based hybrids in pigeonpea. Mhasal et al. (2015) reported 18% and 34% superiority over the most popular cultivars of central and south India, ‘Tara’ and ‘Asha’, respectively. From most studies on heterosis in pigeonpea, it was concluded that: (1)  the range of reported standard heterosis was large (up to 156%); (2)  genotype × environment interactions played an important role in the expression of hybrid vigour;

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(3)  in some instances, genetic diversity was related to hybrid vigour, but it was not a rule; (4)   heterosis started expressing from germination and continued ­thereafter; (5)  in most cases, the heterosis for seed yield was associated with hybrid vigour for plant biomass, height, number of secondary branches, and number of pods plant–1 and, in some cases, with seed size and seeds pod–1. V.  GENETIC MALE STERILITY‐BASED HYBRID TECHNOLOGY Kolreuter (1763) is credited with having recorded the first ever naturally occurring male sterile plants with impaired anthers. About 175 years later, Stephens (1937) in sorghum, and Jones and Emsweller (1937) in onions, demonstrated the use of male sterility in hybrid seed production. Subsequently, plant breeders and geneticists began research to understand various aspects of male sterility such as its variants, processes of its origin and development, stability and uses in crop improvement in various plant species. The origin of male sterility in plants is attributed to mutations that ­generally occur naturally, but it can also be induced through the application of different physical or chemical mutagens. Besides these, the male sterility system can also be bred through wide hybridization and selection. For its effective utilization in plant breeding, it is essential that the individuals with altered male sterility retain their female fertility intact. In pigeonpea, on the basis of their genetic control, the male sterility systems are classified into genetic (GMS), cytoplasmic‐nuclear (CMS), or temperature‐sensitive (TGMS). Of these, so far, only the CMS system has been explored to breed commercial hybrids (Saxena et al., 2010c). A.  Genetic Male Sterility Systems Genetic male sterility (GMS) has been reported in over 150 plant species, both in the dicots and also the monocots (Kaul, 1988). In most cases, GMS is independent of any cytoplasmic or environment factors, and it is controlled by recessive nuclear gene(s) but, in odd cases, dominant genetic control is also reported. In nature, GMS arises due to mutation of the male fertility nuclear gene to its recessive form. In the self‐pollinated crops, such mutants are invariably lost but, in out‐crossed or partially  out‐crossed species, they are preserved in heterozygote form.

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Table 3.3.  Distinctive characteristics of genetic male sterility (GMS) systems reported over time in pigeonpea. Breakdown stage –

z

– Tetrad – Pre‐meiotic Pre‐meiotic Pre‐meiotic – – – – –

Distinctive information

Genotype

Reference

Linked with female ­sterility Variable pollen sterility Translucent anthers Linked with obcordate leaf Sparse pollen production Photoperiod insensitive Arrow‐head anthers Single recessive gene Linked to obcordate leaf Single recessive gene Single dominant gene Rudimentary anthers

–

Deshmukh (1959)

– ms1ms1 –

Reddy et al. (1977) Reddy et al. (1978) Venkateshwarlu et al. (1981)

– – ms2ms2 – – – – ms3ms3

Saxena et al. (1981) Dundas et al. (1982) Saxena et al. (1983) Gupta and Faris (1983) Pandey et al. (1994) Verulkar and Singh (1997) Wanjari et al. (2000) Saxena and Kumar (2001)

 Not reported

z

In  pigeonpea, during the period extending from 1959–2001, a total of 12  GMS systems were reported (Table  3.3). With the exception of one (translucent anthers), the rest were chance selections. Deshmukh (1959) reported the first spontaneous male sterile mutant in pigeonpea. This mutant also carried severe female sterility, and was lost in the same season. Reddy et al. (1977) made a deliberate search for male sterility in 7,216 germplasm accessions at ICRISAT genebank, and selected 75 male sterile plants from different accessions. Among these, six selections had fully developed translucent anthers and had no pollen grains. This male sterility was found to be controlled by a single recessive gene (Reddy et  al., 1978), which was later used in hybrid breeding. Subsequently, in Australia, two sources of male sterility were also reported: a natural photoperiod‐insensitive mutant (Dundas et al., 1982); and a GMS mutant detected in the breeding line B15B (Saxena et al., 1983). Gupta and Faris (1983) reported the identification of 11 male‐sterile plants in a breeding population, while Venkateshwarlu et  al. (1981) and  Pandey et  al. (1994) reported GMS systems that were linked to characteristic obcordate leaves. Verulkar and Singh (1997) reported another recessive male sterile mutant in a population of ­cultivar UPAS 120. Wanjari et al. (2000) recorded the first case of a

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dominant gene controlling male sterility within an inter‐specific progeny. Saxena and Kumar (2001) reported a GMS mutant that was selected from an inbred cultivar, ICPL 85010. This trait was found to be controlled by a single recessive gene that  was non‐allelic to the other reported cases of GMS. A case of sparse pollen production caused by partial collapse of microsporogenesis was also reported by Saxena et al. (1981). Different studies related to microsporogenesis of GMS sources revealed that male sterility occurred due to pre‐ or post‐meiotic breakdown of pollen mother cells (PMCs). In hybrid breeding, only the translucent anthers‐type GMS system (Reddy et al., 1978) was used, and the others remained of academic interest. This male sterility was found to be highly stable and was used in the early stages of hybrid breeding at ICRISAT and ICAR. Under field conditions, the male sterile plants ­produced a good number of pods through natural out‐crossing, and this  encouraged breeders to accelerate research efforts towards the development of hybrid technology in pigeonpea. B.  Heterosis in GMS‐based Hybrids For the first five years, only 53 experimental hybrids were developed using the original GMS source (Reddy et al., 1978). Of these, only ten hybrids exhibited standard heterosis (20–40%). By 1990, a few improved GMS lines were bred and, in the next eight years, 203 hybrid combinations were assessed, and all of these hybrids exhibited > 20% standard heterosis. Of these, 80 hybrids recorded above 40% superiority over the best control, and 46 hybrids exhibited more than 80% standard heterosis (Table 3.4). This information was useful and demonstrated that, in a pulse crop like pigeonpea, exploitable heterosis is available. C.  Release of the First GMS‐based Pigeonpea Hybrid Since no ­commercial hybrid has ever been bred before in food legumes, the release of the world’s first pigeonpea GMS hybrid, ICPH 8, in 1991 (Saxena et  al., 1992) was considered a major technological achievement. This hybrid was developed at ICRISAT by crossing a GMS line (MS Prabhat DT) with a fertile inbred line ICPL 161. Evaluation of this hybrid in 100 yield trials under different agro‐ecological conditions showed that ICPH 8 was superior to the control cultivar UPAS 120 by 35%. In the on‐farm trials conducted in two Indian states, ICPH 8

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Table 3.4.  Summary of standard heterosisz (%) reported in genetic male sterile‐based experimental hybrids produced at ICRISAT in the early phases. GMS hybrid (no.) Standard heterosis Years 1977–1981 1990–1998 Total (no.) Hybrids (%)

 100%

Total

43 0 43 17

10 77 87 34

0 80 80 31

0 46 46 18

53 203 256

 Superiority over the best cultivar Source: ICRISAT.

z

Table 3.5.  Standard heterosis of genetic male sterile pigeonpea hybrids belonging to early and medium maturity, released across India in the 1990s. Name

Originating Maturity Year centre State

Zone

Control

ICPH 8 PPH 4 CoH 1 CoH 2 AKPH 4104 AKPH 2022

Early Early Early Early Early Medium

Central North West South South Central Central

UPAS 120 UPAS 120 VBN1 Co 1 BDN 2 BSMR 736

1991 1994 1994 1997 1997 1998

ICRISAT Ludhiana Coimbatore Coimbatore Akola Akola

Telangana Punjab Tamil Nadu Tamil Nadu Maharashtra Maharashtra

Heterosisz (%) 31 32 32 35 35 64

 In relation to the best local control Source: IIPR, Kanpur, India.

z

demonstrated 20–30% superiority over the national control (Saxena et  al., 1992). Subsequently, five additional GMS‐based hybrids were also released by the Indian National Agriculture Research System (Table 3.5). These included PPH 4 (32% heterosis), CoH 1 (32% heterosis), CoH 2 (35% heterosis), AKPH 4104 (35% heterosis), and AKPH 2022 (64% heterosis). D.  Hybrid Seed Production Technology In order to develop effective and economical field plot techniques for large‐scale seed production of GMS hybrid, various row (male : female) ratios and population densities were tested. A combination of one male and six female rows, and 60,000 plants ha–1, gave the best results with hybrid seed yields of 0.6 to 0.8 t ha–1. Roguing of male fertile plants

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within the segregating female rows was the key factor in hybrid seed production. The first few floral buds that appeared on each plant were examined, and the male‐fertile segregants were rogued out before their flowers opened. This was a time‐bound roguing operation, and needed great attention. If the roguing were delayed for some reason, then the  quality of the hybrid seed would be adversely affected, due to cross‐pollination. Since pigeonpea is perennial in nature, flowering of the male‐sterile plants continues for relatively more time until optimum pod load on each plant is achieved (Sheldrake, 1979). To ensure pollen availability for an extended duration, and more hybrid yield, the flowers and young pods from the male parent were removed periodically, which was a labour‐intensive and inefficient activity and economically unviable. E.  Assessment of GMS‐based Hybrid Technology In field crops, where hybrid seed requirement is high, the GMS‐based hybrid technology did not attract seed producers. The main problem was associated with the maintenance of genetic purity of female parent and hybrid seed; its implementation leads to high production cost. The manual roguing of 50% of the fertile plants within the female rows posed practical difficulties in large‐scale seed production as it was a difficult, time‐bound and labour‐intensive field operation. The large‐scale seed production of GMS hybrid seed was not grower‐ friendly. In spite of high seed demand, none of the GMS‐based hybrid could reach farmers. ICRISAT was aware of this potential constraint before launching the GMS‐based hybrid breeding program, but continued with it to understand the degree of difficulty in seed production. The seeding rate (@ 5–10 kg ha–1) was not very high, and each male sterile plant could produce 350–500 g of hybrid seed. Another issue that needed answering in developing the hybrid technology was to know to what extent the partial natural out‐crossing was sufficient to produce large quantities of hybrid seed under natural conditions. Besides this, even more important was the need to generate information on the nature and quantum of heterosis in this pulse. In fact, the information generated from working on GMS‐based hybrids turned out to be useful when the CMS system was bred. The investment on GMS hybrid technology paid off handsomely because, in breeding CMS‐based hybrids, the GMS system was replaced by the CMS system and the outputs came faster.

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VI.  TEMPERATURE‐SENSITIVE MALE STERILITY The effect of different environmental factors on the expression of genes controlling male sterility or fertility has been well documented in various plant species (Kaul, 1988). Such specific effects, in terms of conversion of male sterility to fertility and vice versa were reported in both GMS and CMS systems. These natural events were considered to be only of academic interest until Yuan (1987), Sun et al. (1989) and Lu et al. (1994) demonstrated the utility of a temperature‐sensitive male sterility system (TGMS) in commercial hybrid rice breeding in China. Levings et  al. (1980) hypothesized that loss of some cytoplasmic, rather than nuclear, genetic factor is responsible for the reversion of male sterility to male fertility. Small et al. (1988) showed that no DNA loss was associated with the reversion of male sterility. Overall, the conversion of male sterility to fertility and its reversal is a complex genetic phenomenon, and more research is required at genomic and physiological levels to understand it better. Recent success in breeding a TGMS (Saxena, 2014; Saxena and Mudaraddi, 2015) has opened up similar options to breed pigeonpea hybrids. In this system, when a given TGMS line is sown under low (25°C) temperature regime, it will remain male sterile (Table  3.6), and it can be used to produce hybrid seed with assistance from insect pollinators. The large‐scale seed production involving TGMS lines will require two different sites, with distinct temperature requirements, during crop Table 3.6.  Number of sterile/fertile plants recorded in temperature‐sensitive male sterile (TSMS) selections planted under an insect‐proof net at ICRISAT, Patancheru (17°N), India. The plants were male‐sterile at temperatures above 25°C (could be used to produce hybrids). The same plants became fully fertile at temperatures below 24°C (produced self‐pollinated seed of the maternal line). September (>25 °C) Selection name Envs S‐1 Envs S‐2 Envs S‐3 Envs S‐5

November ( 75% success rate. In this method, four or five fully grown but unopened floral buds of F1 hybrid plants were examined for pollen load between 11 am and 3 pm on a clear‐sky day. It was further observed that the genotypes with high pollen load had good pod set and perhaps carried both the Rf genes, while plants with sparse pollen resulted in very poor pod set on selfing, and likely had a single Rf gene. VIII.  BREEDING NEW HYBRID PARENTS A.  Fixing Priorities In order to set up breeding criteria to select parental lines and hybrids, it is necessary to take into consideration the needs of local farmers in specific target regions, and to identify and give relative weight to their priorities. In India, there are several agro‐ecological zones and multiple interests related with pigeonpea (variation for maturity, plant type, use, etc.). A parallel analysis applies to other pigeonpea growing areas in the world. Hence, it is important to perform a situation analysis about the target environment, considering the preferred or prevalent production systems (crop rotations, crop windows), how the seed is managed, soil type, moisture availability during the cropping season, weather (temperature, precipitation, evapotranspiration), geographical coordinates (latitude, longitude, altitude), photoperiod, length of the season, prevalent biotic and abiotic stresses, preferred growth habit, plant type, maturity class, available germplasm base, seed market class (vegetable vs. dry seed), use (food, feed, fodder, fuel), preferred seed morphology (size, colour) and quality, as it relates to the use of pigeonpea for the fresh or processing markets. This will be a huge exercise, requiring considerable resources. The immediate objective in hybrid breeding is to significantly enhance the productivity in a stable fashion, in combination with tolerance or resistance to biotic and abiotic stresses, in the context of the local needs and priorities. These efforts would contribute to increase crop productivity, better health and nutrition, crop diversification, environmental protection and economic growth. In a dynamic hybrid breeding program, the development of elite inbred lines (parents) at regular intervals is essential to produce new hybrids with greater yield and adaptation. Besides high per se performance, the parents should also have high combining ability, stability

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across environments, and key market‐driven traits. Such lines can either be bred or selected from the available germplasm and genetic stock. The popular methods used for breeding inbred lines in the self‐ pollinated crops are generally also followed, to develop new parental lines with emphasis on diversity at nuclear level. The logical steps involved in this program are selection of parents, development and screening of segregating populations and, finally, selection and evaluation of inbred offspring with desirable traits. In pigeonpea, the selection efficiency is always threatened by partial natural out‐crossing in the preceding generation. Therefore, breeders should take precautions to minimize the incidence of out‐crossing in the breeding plots. In the following sections, we discuss some strategies to diversify the nuclear base of the fertility restorers. B. Selection of Hybrid Parents from Germplasm and Breeding Populations The primary gene pool of pigeonpea contains over 20,000 accessions in the genebanks of ICRISAT and ICAR. These resources harbour tremendous genetic variability that can be used for mining the traits of interest. Keeping in mind the limitations of physical and financial resources, the diversification efforts in the breeding program should be implemented in a step‐by‐step manner. To start this activity, it is essential to choose stable A‐lines, such as ICPA 2039, ICPA 2043 and ICPA 2092, accompanied by their high per se performance, high general combining ability, dominant gene for wilt resistance, desirable seed traits (size, shape and colour), and adaptation to the target locations. These A‐lines should be crossed with about 100 testers. The selection of testers should also be done scientifically, considering the objectives, target cropping system and environment, heterotic grouping, and genetic diversity. In addition to germplasm collections, the list of ­testers can also involve, among other bred‐germplasm sources, old or new ­cultivars and advanced breeding lines. The latter should be given priority over the unexplored germplasm, due to their high yield potential and adaptation. Saxena et al. (2014a) launched a broad‐based hybrid parent‐breeding program at ICRISAT by crossing 503 testers with different A4 CMS lines. The testers included advanced breeding (F5 onwards) lines, released cultivars and germplasm, representing diverse pedigree and origin. The  evaluation of the resultant hybrids for their fertility restoration revealed that, in this lot, there were 26 male sterility maintainers and

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179 fertility restorers, which represented good variability with respect to key traits. The remaining 296 hybrids were segregated for different proportions for fertile and sterile plants. In another attempt to breed new maintainers and restorers, a targeted breeding program involving 35 inbred testers and three A‐lines were identified. The criteria for selection were growth habit and plant type (non‐determinate and semi‐spreading), maturity (early and medium), seed size (8–14 g 100 seeds–1), seed colour (white or brown), seed shape (round or oval), resistance to wilt and sterility mosaic diseases, and their origin. The parental lines also included eight known restorers. The crosses were made in a line × tester mating design, and 105 hybrid combinations were produced. Based on the F1 phenotype, the hybrid progenies were classified into fertile/ restorers (33), sterile/maintainers (4) and segregating types (68). Interestingly, the frequency of restorers and maintainers was similar to that recorded earlier with 503 testers. For developing new A‐lines, the F1 hybrids showing male sterility should be selected and backcrossed to the same parent. At the same time the pollinator line needs to be maintained by selfing. It has been observed at ICRISAT that, compared with bulk pollinations, if the backcrosses are made on a plant‐to‐plant basis, then the male sterility stabilizes rapidly. Similarly, for identifying new fertility restorers, the F1 hybrids exhibiting full pollen fertility and good pollen load should be identified, their pollen parent should be selected, and selfed seed should be produced for reconfirmation. Such male parents should be maintained in the purest possible form. The information generated at ICRISAT indicated that in pigeonpea germplasm the alleles responsible for male fertility/sterility are distributed randomly. Further, it was also noted that a greater proportion of germplasm suffered from intra‐accession variability for male sterility/ fertility. Hence, the prospect of using A4 cytoplasm in hybrid breeding is promising. A perusal of the fertility restoring and male sterility maintaining lines showed a significant variation for important yield contributing traits, such as, flowering, maturity, seed size, seed colour, plant height and disease resistance (Table 3.8). This provides ample opportunities for selecting hybrid parents of choice. Saxena and Tikle (2015) listed hybrid parents which  will likely ­produce hybrids with tolerance against stresses like ­waterlogging and host plant resistance to pathogens, besides various a­gronomic and market‐driven traits. They identified six male sterility maintainers ­ and  27 fertility restorers that were found tolerant to waterlogging and  were highly resistant to both wilt and sterility mosaic d ­ iseases.

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Table 3.8.  Phenotypic variation observed for important traits among pigeonpea ­fertility restorers (R lines) and maintainers (B lines) used to produce cytoplasmic male sterile (CMS) hybrids. Trait Days to 50% flowering Days to 75% maturity Plant height (cm) 100‐seed weight (g) Fusarium wilt (%) Sterility mosaic (%)

Restorers (n = 210)

Maintainers (n = 30)

50–158 100–241 70–288 6–18 0–100 0–100

53–167 98–287 70–290 5–19 0–100 0–100

Source: Saxena (Saxena, 2014). Reproduced with permission of ICRISAT.

These parental lines can be used to breed pigeonpea hybrids with stable performance for the areas prone to waterlogging and these ­ diseases. C. Isolation of Fertility‐Restoring Inbred Lines from Heterotic Hybrids Additive and non‐additive genetic variation affect grain yield in pigeonpea (Mudaraddi, 2015; Sawargaonkar, 2011; Sharma and Dwivedi, 1995; Saxena and Sharma, 1990). Theoretically, part of this variation can be fixed in some inbreds, by accumulating desirable alleles with additive effects through pedigree selection. For this exercise, the best possible heterotic hybrid combinations should be selected for subsequent pedigree selection, to obtain new inbred lines. Such improved inbreds can be used directly as inbred cultivars, or can form good parental materials for the development of new hybrids. At ICRISAT, a similar exercise was carried out in a GMS‐based pigeonpea hybrid ICPH 8, and some of the derivative inbred lines achieved 70–75% of seed yield produced by the hybrid (Saxena et al., 1992). In another attempt, the improved inbred lines selected from hybrid IPH 487 were used as new hybrid parents (KB Saxena (person. commun.)), and these produced the high‐yielding hybrid ICPH 3762 that was released for cultivation. Selection of inbred lines from heterotic hybrids requires the elimination of male sterile plants within early generation segregating populations, so a large F2 population is required to enable good segregation and selection. Also, in each cycle, special care should be taken to protect the selected individuals from unwanted cross‐pollination by selfing one branch of the selected plants with a muslin cloth bag.

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D.  Breeding Dwarf Parental Lines In pigeonpea, popular cultivars achieve a height of over 250 cm at flowering, and the hybrids grow even taller by a margin of 20–30%, which increases the difficulty of managing pod borer insects and harvesting. To find a genetic solution to this problem, a search for genetic dwarf types was made (Saxena and Sharma, 1995). Two dwarfing sources (D1 and D6), with condensed primary branches and growing up to only 100–120 cm,were identified. This trait, controlled by a single recessive gene, is being transferred into good hybrid parents. So far, the breeding efforts to develop productive dwarf male sterile genotypes have been unsuccessful. Once such A‐lines are available, their insect management will be easier and production of seed will be simplified. In this type of genetic materials, the maintenance of purity will also be easier, because any off‐type among the dwarf types will be tall, and can be rogued easily before flowering. E.  Breeding Determinate/Non‐determinate Parental Lines There are two recognized growth habits in pigeonpea: determinate (caused by a single recessive gene); and non‐determinate (dominant gene). In the determinate type, the branches and main stem terminate in a reproductive bud, and this restricts plant growth after the flowering is induced. Consequently, the plants remain compact, short, produce fewer pods, and less yield per plant, and high plant population per unit area is essential for optimizing productivity. These types are also suitable for mechanized high input cropping systems. The non‐determinate types, in contrast, are tall, spreading and have numerous secondary and tertiary branches. On an individual plant basis, the non‐determinate plants produce a large number of pods and give more grain yield. These types are best suited for subsistence agriculture and, in all the pigeonpea growing countries, most of the cultivars are of non‐determinate growth habit. In these types, flowering is non‐synchronous, and partial recovery from insect damage is possible. At present, all of the three released medium duration CMS pigeonpea hybrids are non‐determinate in growth habit. In the early maturing group, both determinate and non‐determinate hybrids have been bred, with similar degrees of hybrid vigour. Some elite hybrids have demonstrated 30–80% standard heterosis (Saxena et al., 2014c). A range of parental lines is available in both the plant types (Saxena et al., 2014a), and this provides ample opportunities to

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the national programs to breed hybrids for their areas of interest. In the medium and long maturity groups, only non‐determinate types are cultivated. In this group, many parental lines, with different trait combinations and high yielding hybrids, such as ICPH 2671, 2740 and 3762, are available. Hence, it will always remain a high‐priority group of materials. F.  Disease‐resistant Parental Lines Since both Fusarium wilt and sterility mosaic virus are major yield reducers in most pigeonpea growing areas, the strategy has been to breed hybrids carrying resistance to both diseases. To start this program, all the known fertility restorers and maintainers of A4 CMS system were screened for host plant resistance to both diseases simultaneously, and this program was implemented using the screening technology developed by Nene et al. (1981). In this field‐oriented screening, high levels of both the inoculums were maintained. Fusarium udum inoculum was sustained at 5 × 106 spores m–2 in soil by ploughing chopped wilted plants every year for over decades. For sterility mosaic virus screening, the spreading‐row technique was used. Every test and susceptible control seedling growing in the nursery was inoculated by stapling a heavily mite‐ and virus‐ loaded leaf. This allowed quick migration of mites that carried sterility mosaic virus. This method provided no chance of escape from the two diseases. Test material was sown for screening, along with a highly susceptible control (one each for the two diseases) at regular intervals, to monitor the effectiveness of inoculum. Host plant resistance to wilt and sterility mosaic is often controlled by recessive genes (Saxena and Sharma, 1990). Restorers and maintainers exhibiting resistance to both the diseases were selected for breeding hybrids, especially in the medium maturity group (Reddy et al., 1990; Saxena et al., 2014a; Saxena and Tikle, 2015). Recently, Saxena et  al. (2012) reported the presence of a dominant gene for resistance to Fusarium wilt, and this has eased the process of breeding wilt‐resistant hybrids. This gene has now been transferred to some A‐/B‐ lines; and it will now allow the production of wilt‐resistant hybrids from cross‐combinations involving both resistant A‐ x resistant R‐ and resistant A‐ x susceptible R‐ lines. A number of fertility restorer and maintainer lines have been reported to carry the dual resistance (Saxena et  al., 2014c), and these are being used to produce new high‐yielding, disease‐resistant hybrids. Pyramiding

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of disease resistant genes should be beneficial for the long‐term maintenance of disease resistance, despite possible changes in the pathogens. Additional new sources of resistance to Fusarium wilt and sterility mosaic disease found in the pigeonpea mini‐core collection (Sharma et al., 2012) should be useful to the pigeonpea hybrid breeding program. G.  Use of a Naked‐Eye Polymorphic Marker in Hybrid Breeding ‘Obcordate leaf’ is a distinctive morphological marker, and rare in occurrence. It is easy to identify by the naked eye, and is thus also known as a ‘naked‐eye polymorphic marker’. This marker is controlled by a single recessive gene (Saxena et al., 2011b). This trait has been found quite stable across environments, and expresses within 3–4 weeks from ­sowing. It has been shown to be a great tool to ensure purity of parental lines and hybrids, by testing true identity with minimum resources. At ICRISAT, this marker has already been incorporated into A‐/B‐ lines through backcrossing. In the obcordate A‐lines, any out‐crossed ‘off‐type’ plant with dominant normal (lanceolate) leaves can be rogued out easily at seedling stage, and the genetic purity of the female parent can be maintained easily and economically. Likewise, when a restorer line (normal leaves) is crossed to an A‐line having obcordate leaves, all the true hybrid plants will have normal leaves, and any plant within the hybrid population with obcordate leaves will be due to selfing (from pollen shedder) in the preceding generation. Such plants can be detected easily, to assist in determining seed ­quality of the hybrid. The limitation of this approach is that any ­outcrossed plant in the hybrid population, arising due to pollination from any other line with normal leaves, cannot be detected. Thus, the seed production of hybrids should be done with appropriate isolation distance. The newly developed A‐/B‐ lines with obcordate leaves have recently been used in developing new hybrid combinations at ICRISAT. Some of the lines, such as ICPA 2203, 2204 and 2208, have high combining ability (Patil et al., 2014). These hybrids yielded 35–60% standard heterosis, and two of them were free from wilt and sterility mosaic diseases (Table 3.9). All the hybrids had normal lanceolate leaves and few contaminated plants (250 days to maturity) pigeonpea types have a strict short day photoperiod requirement for the induction of flowering. This restricts their adaptation to areas where the day length is about ten hours. The adoption of this group is limited to deep soils with high moisture holding capacity, and occupies a large area. In this group, the potential of hybrids is also high, but not much research has  been carried out with respect to the exploitation of heterosis.

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Some hybrids, such as ICPH 2307 (2.9 t ha–1, 53% heterosis), ICPH 2306 (2.6 t ha–1, 39% heterosis), and ICPH 2896 (2.6 t ha–1, 38% heterosis), hold promise (Table 3.11). B.  Release of the World’s First Commercial Legume Hybrid The first commercial CMS‐based pigeonpea hybrid, ICPH 2671, was produced by crossing a restorer line, ICPL 87119, designated as ‘ICPR 2671’, with a male sterile line, ICPA 2043. The hybrid has non‐determinate growth, is medium maturing (164–184 days), is tall (210–226 cm) and has profuse branching. It is highly resistant to wilt and sterility mosaic diseases. ICPH 2671, by virtue of its greater root mass and depth, also recovers easily from short spells of drought. The hybrid has also demonstrated high survival (88%) under waterlogging. In multi‐location trials conducted from 2005–2008, the mean yield of ICPH 2671 ranged from 2–2.7 t ha–1 and, on average, it recorded 35% superiority over the check cultivar Maruti (2 t ha–1) (Table 3.12) in the ‘All India Coordinated Trials’. In 1,829 pre‐release on‐farm trials, conducted by ICRISAT and ICAR in five provinces and using farmers’ cultural practices, the hybrid ICPH 2671 (1.4 t ha–1) produced 52% more than the local check (954 kg ha–1). In the state of Maharashtra, the largest number (782) of trials were ­conducted, and ICPH 2671 produced 35% more yield than the check cultivar Maruti (Table  3.13). Considering its overall performance, the hybrid ICPH 2671 was released for general cultivation in the state of Madhya Pradesh in 2010 (Saxena et al., 2013a). This hybrid matched well with the popular cultivar ‘Asha’ in various seed quality, de‐hulling, and organoleptic parameters (Sawargaonkar, 2011).

Table 3.12.  Yield and standard heterosis of the cytoplasmic male sterile medium ­maturity pigeonpea hybrid ICPH 2671 in comparison with cultivar Maruti, planted across India in multi‐location trials from 2005–2008. Yield (kg ha−1) Year 2005 2006 2007 2008 Mean

Locations (no.) 5 5 11 22

ICPH 2671

Control

Standard heterosis (%)

3,138** 2,694** 2,702* 2,022* 2,639

1,855 2,066 2,140 1,746 1,952

69 30 26 16 35

*,**– significantly different from the control variety at p < 0.05 and p < 0.01%, respectively

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Table 3.13.  Yield of medium maturity cytoplasmic male sterile pigeonpea hybrid ICPH 2671 and popular cultivar Maruti recorded from on‐farm trials spread over four states in India in 2008 and 2009.

State Maharashtra Andhra Pradesh Jharkhand Madhya Pradesh Mean

Range for yield (kg ha–1)

Mean yield (kg ha–1)

Farmers (no.)

Hybrid

Control

Hybrid

Control

Standard heterosis (%)

782 399 288 360

760–4,000 701–2,900 934–2,850 1,111–3,358

660–2,900 458–2,100 784–2,222 890–3,000

969 1,411 1,460 1,940 1,445

717 907 864 1,326 954

35 56 69 46 52

Source: NGOs and ICRISAT.

Figure  3.2.  Medium duration non‐determinate pigeonpea CMS hybrid ICPH 2740 at podding stage. Jalgaon, Maharashtra, India.

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After the release of ICPH 2671, two more pigeonpea hybrids ICPH 3762 and ICPH 2740 (Figure  3.2) were also released in India. Their yield advantage over popular cultivars was above 40% in most farmers’ fields (Tables  3.14 and 3.15). According to recent estimates, in 2015, CMS‐based pigeonpea hybrids were grown on over 150,000 hectares in central and southern India. With a conservative estimate of 25% hybrid yield advantage, the replacement of inbred cultivars with hybrids will add about 30,000 tons of additional grain to the national pigeonpea production. The productivity levels recorded by the three hybrids were extremely encouraging, and it is expected that large‐scale adoption could lead to a breakthrough in the national production and productivity of pigeonpea in India. Expansion of pigeonpea hybrids to other areas is also encouraging (i.e. Myanmar (Kyu et al., 2011)).

Table 3.14.  Yield and standard heterosis of medium maturity cytoplasmic male sterile pigeonpea hybrid ICPH 3762 and popular cultivar Asha obtained from on‐farm trials conducted in four districts of Odisha, India, in 2013. Yield (kg ha–1) District (in Odisha)

Farmers (no.)

Kalahandi Rayagarh Naupada Boudh Bolangir Mean

72 28 21 12 11

Hybrid

Control

Standard heterosis (%)

2,000 2,290 1,734 803 1,804 1,726

803 695 1,230 662 676 813

149 229 41 21 167 112

Source: Courtesy of Dr. K. B. Saxena.

Table 3.15.  Yield and standard heterosis of medium maturity cytoplasmic male sterile pigeonpea hybrid ICPH 2740 and popular cultivar Asha obtained from on‐farm trials conducted in four states in India from 2009 to 2011.

State Maharashtra Andhra Pradesh Gujarat Madhya Pradesh Mean

Farmers (no.) 230 47 40 13

Yield (kg ha–1) Hybrid

Control

1,525 1,999 1,633 1,874 1,758

975 1,439 1,209 1,217 1,210

Source: Saxena (2016). Reproduced with permission of Indian Journal of Genetics.

Standard heterosis (%) 56 39 35 54 45

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C.  Hybrid Seed Production Technology Standard recommended field isolation distances for seed production of pigeonpea CMS hybrids have not yet been established. Even for inbred cultivars, recommendation for certified seed production have not been standardized, and several options have been suggested. These include, 100 m (Tunwar and Singh, 1988), 180 to 360 m (Ariyanayagam, 1976), 200 m (Agarwal, 1980), and 300 m (Faris, 1985). Based on the information from different research stations in India, ICRISAT recommended an isolation distance of 500 m for the production of both certified as well as breeder seed of pigeonpea hybrids (Saxena, 2006) and, so far, the results are encouraging. Another important consideration in selecting isolation plots is their natural habitat. It has been observed that seed production plots located closer to wild bushes, fruit or other flowering trees, and small natural or artificial water bodies give the best pod setting on the male sterile plants. It is believed that such conditions are conducive for harbouring and survival of the insects responsible for cross‐pollination. In addition to site selection, the adoption of efficient field plot techniques is also important for optimizing hybrid yields. The main focus in designing the field layout should be to make fresh pollen available for as long as possible. This will ensure more visits of the pollinating insects, to enhance pod setting on male sterile plants. A row ratio of four females : one male is recommended (Saxena, 2006) for the seed production of A‐lines, as well as hybrids. The two released hybrids ICPH 2671 and ICPH 2470 were chosen for on‐farm seed production (A × R) in four states and, on average, the yields ranged between 1,000–1,500 kg ha–1. The seed production program organized in the state of Madhya Pradesh (Table  3.16) showed that this state has excellent ecology, conducive for hybrid pigeonpea

Table 3.16.  Main areas in India suited for cytoplasmic male sterile pigeonpea hybrid seed production (A × R) based on accomplished yields in farmers’ fields, 2008–09. State

Mean yield Locations (kg ha–1)

Madhya Pradesh

6

2,055

Andhra Pradesh

5

1,255

Gujarat

3

1,558

Mean

1,623

Main recommended Yield in recommended areas areas (kg ha–1) Tikamgarh, Seoni, Indore Nizamabad, Medak, Medchal Dhagandra, Vadali, Halvad

2,602 1,404 1,558 1,855

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seed production, and it has the potential to become a hub for hybrid seed production in pigeonpea. Seed storage is also critical, and needs fair attention to avoid losses caused by bruchid (Callosobruchus maculatus). Bruchid infestation often leads to seed quality deterioration, including physical damage and germination. Vales et  al. (2014) reported that the use of Purdue Improved Cowpea Storage bags significantly reduced bruchid damage, and also preserved germination of pigeonpea seeds. In pigeonpea, raising two crops in a year for field oriented grow‐out quality testing is not possible, due to long generation turnover time. Alternatively, a genomics approach based on SSR was developed and implemented at ICRISAT to carry out quality tests (RK (Saxena et al., 2010)). This technology has so far been established for three pigeonpea hybrids, ICPH 2671, ICPH 2740 and ICPH 2438. These assays can be used for reliable assessment of hybrid seed purity within the commercial seed lots of the hybrids. Since commercial application of this technology includes a large number of seed samples, an alternative cost‐effective approach, involving single nucleotide polymorphism (SNP), has also been developed. D.  Economics of Hybrid Seed Production M.K. Saxena et  al. (2011) estimated that the total production cost of hybrid ICPH 2671 seed on one hectare plot was Rs 26,395 (US$ 1 = Rs 66 on 2015.12.24), excluding the rental value of land. From this plot, a total of 1,440 kg hybrid seed was produced, which yielded net profits of Rs 70,000 ha–1. Using these estimates, the hybrid seed cost at farm gate was Rs.18.85 (= US$ 0.29) kg–1, which is 20–25% higher (due to more labour and seed cost) than that of inbred cultivars. The production statistics of hybrid pigeonpea are comparable with other hybrid field crops (Singhal, 2013), and this will raise the confidence of seed producers in opting for hybrid pigeonpea seed business. In farmers’ fields, a grain yield of 2–3 t ha–1 by cultivating a hybrid crop is not uncommon, with estimated net production advantage of 1–1.2 t ha–1 over the local cultivars. With this level of productivity from the cultivation of hybrids, farmers will fetch an additional 30–50% profit (Rs 40,000–75,000 (= US$ 605–1,135) ha–1). It has been also observed that many farmers have opted for modern production technologies, and consider agriculture as a challenging but potentially profitable business. The attractive market prices and high demand have encouraged them to invest and reap more profits from pigeonpea. During the on‐farm promotion of hybrids during the past three years, a number of such farmers recorded exceptionally high yields (up to 4.5 t ha–1) from

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hybrids, with 40–50% superiority over the control, leading to additional profits. These yields were obtained under well‐drained fields with irrigation and good fertilization, weed and insect management. To take advantage of this technology on a large scale, the availability of sufficient quantities of quality hybrid seed is the number one prerequisite. A seed‐to‐seed ratio of 1 : 200/300 for pigeonpea hybrids means that hybrid seed can be obtained with a little effort, and a productive seed chain can be established to address seed requirements. Overall, pigeonpea CMS hybrid technology has reached a mature stage, and can be compared with other crops as far as their levels of realized standard heterosis, hybrid (A × R) seed yields and profitability are concerned. To meet the current domestic demand, India annually imports about 500,000 t of pigeonpea (DES, 2015), and the authors believe that with 30–40% yield advantage, this deficit can be reduced gradually with increased adoption of hybrids.

XI. OUTLOOK Hybrid seed technology was conceptualized and flourished in the USA in the early part of the 20th century, and the first crop to benefit from this breakthrough was maize. Gradually, this technology reached farmers’ fields, as its large‐scale and economically viable hybrid seed production technology evolved. Initially, de‐tasseling (physical removal of male reproductive parts from female rows) and wind pollination were used for producing hybrid seed. Subsequently, male sterility systems were incorporated into the female parents, and this made hybrid seed production much easier and economical. The impact of hybrid technology in combating global hunger has been immense. The six‐fold increase in maize yields in the USA (Troyer, 1991) can easily be attributed to breeding and adoption of high yielding hybrids. Similarly, in China, the adoption of rice hybrids has enhanced the mean crop productivity by three folds. Significant yield gains associated with the exploitation of hybrid vigour have also been recorded in other crops, such as sorghum, pearl millet, cotton, sunflower, safflower, caster, and various vegetables and fruits. The benefits of hybrid technology, however, have eluded legume crops. Male sterility systems exist in various food legumes (Table 3.17). The principal aspects precluding the production of hybrids in ­legumes are: low pollen movement from the male to female (low out‐ crossing rates), due mainly to flower morphology and/or low participation of insect pollinators; unstable male‐sterility systems; and scarcity of good maintainers and restorers. These aspects have limited the

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Table 3.17.  Better parent heterosis for yield, male sterility systems, and out‐crossing rates recorded in several food legumes. Crop common name

Scientific name

Black gram Chickpea Common bean Cowpea Faba beans Lentil Mung bean Pea Pigeonpea

Vigna mungo L. Cicer arietinum L. Phaseolus vulgaris L. Vigna unguiculata L. Vicia faba L. Lens culinaris Medik. Vigna radiata L. Pisum sativum L. Cajanus cajan (L.) Millsp.

Soybean

Glycine max L.

Better parent heterosis for Male sterility Out‐crossingx yieldz (%) systemy (%)