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 Pratap Singh, Xiao Du, Hari D. Upadhyaya, Aamir W. Khan, Yue Wang, Vanika Garg, Guangyi Fan, Wallace A. Cowling, José Crossa, Laurent Gentzbittel, Kai P. Voss‐Fels, Vinod Kumar Valluri, Pallavi Sinha, Vikas Kumar Singh, Cécile Ben, Abhishek Rathore, Punna Ramu, Muneendra Kumar Singh, Bunyamin Tar’an, C. Bharadwaj, Mohammad Yasin, Motisagar S. Pithia, Servejeet Singh, Khela Ram Soren, Himabindu Kudapa, Diego Jarquín, Philippe Cubry, Lee T. Hickey, G. P. Dixit, Anne‐Céline Thuillet, Aladdin Hamwieh, Shiv Kumar, Amit Deokar, S. K. Chaturvedi, Aleena Francis, Réka Howard, Debasis Chattopadhyay, David Edwards, Eric Lyons, Yves Vigouroux, Ben J. Hayes, Eric von Wettberg, Swapan K. Datta, Huanming Yang, Henry T. Nguyen, Jian Wang, Kadambot H. M. Siddique, Trilochan Mohapatra, Jeffrey L. Bennetzen, Xun Xu, Xin Liu
Abstract
. 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.