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

Authors :
Varshney RK
Roorkiwal M
Sun S
Bajaj P
Chitikineni A
Thudi M
Singh NP
Du X
Upadhyaya HD
Khan AW
Wang Y
Garg V
Fan G
Cowling WA
Crossa J
Gentzbittel L
Voss-Fels KP
Valluri VK
Sinha P
Singh VK
Ben C
Rathore A
Punna R
Singh MK
Tar'an B
Bharadwaj C
Yasin M
Pithia MS
Singh S
Soren KR
Kudapa H
Jarquín D
Cubry P
Hickey LT
Dixit GP
Thuillet AC
Hamwieh A
Kumar S
Deokar AA
Chaturvedi SK
Francis A
Howard R
Chattopadhyay D
Edwards D
Lyons E
Vigouroux Y
Hayes BJ
von Wettberg E
Datta SK
Yang H
Nguyen HT
Wang J
Siddique KHM
Mohapatra T
Bennetzen JL
Xu X
Liu X
Source :
Nature [Nature] 2021 Nov; Vol. 599 (7886), pp. 622-627. Date of Electronic Publication: 2021 Nov 10.
Publication Year :
2021

Abstract

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources <superscript>1</superscript> . So far, few chickpea (Cicer arietinum) germplasm accessions have been characterized at the genome sequence level <superscript>2</superscript> . 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.<br /> (© 2021. The Author(s).)

Details

Language :
English
ISSN :
1476-4687
Volume :
599
Issue :
7886
Database :
MEDLINE
Journal :
Nature
Publication Type :
Academic Journal
Accession number :
34759320
Full Text :
https://doi.org/10.1038/s41586-021-04066-1