A chickpea genetic variation map based on the sequencing of 3,366 genomes

Rajeev K. Varshney (), Manish Roorkiwal, Shuai Sun, Prasad Bajaj, Annapurna Chitikineni, Mahendar Thudi, Narendra P. Singh, Xiao Du, Hari D. Upadhyaya, Aamir W. Khan, Yue Wang, Vanika Garg, Guangyi Fan, Wallace A. Cowling, José Crossa, Laurent Gentzbittel, Kai Peter Voss-Fels, Vinod Kumar Valluri, Pallavi Sinha, Vikas K. Singh, Cécile Ben, Abhishek Rathore, Ramu Punna, Muneendra K. Singh, Bunyamin Tar’an, Chellapilla Bharadwaj, Mohammad Yasin, Motisagar S. Pithia, Servejeet Singh, Khela Ram Soren, Himabindu Kudapa, Diego Jarquín, Philippe Cubry, Lee T. Hickey, Girish Prasad Dixit, Anne-Céline Thuillet, Aladdin Hamwieh, Shiv Kumar, Amit A. Deokar, Sushil K. Chaturvedi, Aleena Francis, Réka Howard, Debasis Chattopadhyay, David Edwards, Eric Lyons, Yves Vigouroux, Ben J. Hayes, Eric Wettberg, Swapan K. Datta, Huanming Yang, Henry T. Nguyen, Jian Wang, Kadambot H. M. Siddique, Trilochan Mohapatra, Jeffrey L. Bennetzen, Xun Xu and Xin Liu ()
Additional contact information
Rajeev K. Varshney: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Manish Roorkiwal: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Shuai Sun: BGI-Qingdao, BGI-Shenzhen
Prasad Bajaj: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Annapurna Chitikineni: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Mahendar Thudi: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Narendra P. Singh: ICAR–Indian Institute of Pulses Research
Xiao Du: BGI-Qingdao, BGI-Shenzhen
Hari D. Upadhyaya: ICRISAT
Aamir W. Khan: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Yue Wang: BGI-Qingdao, BGI-Shenzhen
Vanika Garg: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Guangyi Fan: BGI-Qingdao, BGI-Shenzhen
Wallace A. Cowling: The University of Western Australia
José Crossa: International Maize and Wheat Improvement Center (CIMMYT)
Laurent Gentzbittel: Skolkovo Institute of Science and Technology
Kai Peter Voss-Fels: The University of Queensland
Vinod Kumar Valluri: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Pallavi Sinha: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Vikas K. Singh: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Cécile Ben: Skolkovo Institute of Science and Technology
Abhishek Rathore: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Ramu Punna: Cornell University
Muneendra K. Singh: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Bunyamin Tar’an: University of Saskatchewan
Chellapilla Bharadwaj: ICAR–Indian Agricultural Research Institute (IARI)
Mohammad Yasin: Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya
Motisagar S. Pithia: Junagadh Agricultural University
Servejeet Singh: Rajasthan Agricultural Research Institute (RARI)
Khela Ram Soren: ICAR–Indian Institute of Pulses Research
Himabindu Kudapa: International Crops Research Institute for the Semi-Arid Tropics (ICRISAT)
Diego Jarquín: University of Nebraska–Lincoln
Philippe Cubry: Université de Montpellier, Institut de Recherche pour le Développement (IRD)
Lee T. Hickey: The University of Queensland
Girish Prasad Dixit: ICAR–Indian Institute of Pulses Research
Anne-Céline Thuillet: Université de Montpellier, Institut de Recherche pour le Développement (IRD)
Aladdin Hamwieh: International Centre for Agricultural Research in the Dry Areas (ICARDA)
Shiv Kumar: International Centre for Agricultural Research in the Dry Areas (ICARDA)
Amit A. Deokar: University of Saskatchewan
Sushil K. Chaturvedi: Rani Lakshmi Bai Central Agricultural University
Aleena Francis: National Institute of Plant Genome Research
Réka Howard: University of Nebraska–Lincoln
Debasis Chattopadhyay: National Institute of Plant Genome Research
David Edwards: The University of Western Australia
Eric Lyons: University of Arizona
Yves Vigouroux: Université de Montpellier, Institut de Recherche pour le Développement (IRD)
Ben J. Hayes: The University of Queensland
Eric Wettberg: University of Vermont
Swapan K. Datta: University of Calcutta
Huanming Yang: BGI-Shenzhen
Henry T. Nguyen: University of Missouri
Jian Wang: BGI-Shenzhen
Kadambot H. M. Siddique: The University of Western Australia
Trilochan Mohapatra: Indian Council of Agricultural Research (ICAR)
Jeffrey L. Bennetzen: University of Georgia
Xun Xu: BGI-Shenzhen
Xin Liu: BGI-Shenzhen

Nature, 2021, vol. 599, issue 7886, 622-627

Abstract: Abstract Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources1. So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level2. Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.

Date: 2021
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DOI: 10.1038/s41586-021-04066-1

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