|RAJENDRAN, KARTHIKA - Vellore Institute Of Technology, Vit|
|Coyne, Clarice - Clare|
|ZHENG, PING - Washington State University|
|SAHA, GOPESH - Washington State University|
|MAIN, DORRIE - Washington State University|
|AMIN, NURUL - Washington State University|
|MA, YU - Washington State University|
|KISHA, THEODORE - Retired ARS Employee|
|BETT, KIRSTIN - University Of Saskatchewan|
|KUMAR AGRAWAL, SHIV - International Center For Agricultural Research In The Dry Areas (ICARDA)|
Submitted to: Plant Genetic Resources: Characterization and Utilization
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/5/2021
Publication Date: 7/7/2021
Citation: Rajendran, K., Coyne, C.J., Zheng, P., Saha, G., Main, D., Amin, N., Ma, Y., Kisha, T.J., Bett, K., Kumar Agrawal, S., McGee, R.J. 2021. Genetic diversity and GWAS of agronomic traits using an ICARDA lentil (Lens culinaris Medik.) Reference Plus collection. Plant Genetic Resources. 1-10. https://doi.org/10.1017/S147926212100006X.
Interpretive Summary: Lentil is an important protein crop. It has high demand in both domestic and international markets and the demand is expected to increase in the near future due to rapid population growth and plant protein market. But the narrow genetic base of cultivated lentil poses a serious barrier towards developing cultivars for future needs. Integration of genetic sequencing with conventional breeding approaches would help to alleviate bottlenecks by improving selection efficiency and accelerating the breeding process in developing improved cultivars. Lentil plant genetic resources hold the genetic diversity needed for crop improvement. We completed skim sequencing of a collection of lentil lines collected from around the world and used the data to identify regions of interest controlling important crop traits.
Technical Abstract: Genotyping of lentil plant genetic resources holds the promise to increase the identification and utilization of genetic diversity for crop improvement. The ICARDA lentil reference set plus collection of 176 accessions was genotyped using genotyping-by-sequencing and 22,555 SNPs were identified after filtering for 50% missing data. The population structure was investigated using STRUCTURE (K=3) and principle component analysis. The two methods were in concordance. Genome wide association analysis (GWAS) using the filtered SNP set and ICARDA historical phenotypic data identified putative markers for several agronomic traits including days to first flower, seeds per pod, seed weight and days to maturity. This SNP genotype resource and seed of the accessions are available to the research community interested in exploring the ICARDA reference set plus collection using GWAS.