Development of Genomic Resources of Lentil for Gene Discovery Controlling Economic Traits Using Association Mapping in Germplasm Collections
2013 Annual Report
1a.Objectives (from AD-416):
Development of genomic resources for lentil for gene discovery controlling economic traits using association mapping in germplasm collections.
1b.Approach (from AD-416):
The project will genotype a representative lentil core collection of 200 germplasm lines we have assembled at Pullman, with a 1536 SNP (single nucleotide polymorphism) genotyping assay developed by University of Saskatchewan, according to published criteria and in consultation with the ADOR. Illumina GoldenGate based genotyping developed by University of Saskatchewan and the collaborative genotyping represents substantial savings over a stand alone project. This collaboration will allow ARS Pullman to gain genomics technologies, foster integration into an international consortium in lentil genomics, and identify specific follow on research avenues of interest to lentil breeding in the Pacific Northwest production area.
This progress contributes to the Objective 2 of the parental project: “Conduct genetic characterizations and phenotypic evaluations of genetic resources of the preceding crops and related wild species for priority genetic and agronomic traits”. We have completed the genotyping of the USDA lentil core collection (~192 accessions of cultivated and wild lentil) using a 1536 single nucleotide polymorphism (SNP) genotyping assay. Principle findings are described in brief below.
Genomic DNA was prepared from a diverse collection of lentil germplasm accessions assembled in Pullman, Washington, and shipped to the University of Saskatchewan. Accessions were genotyped for 1536 SNPs using an Illumina GoldenGate assay developed by the University of Saskatchewan. One thousand five hundred and thirty-six SNPs were called on 192 accessions for a total of 294,912 genotype data points. The processed SNP genotype data will be used in genome-wide association studies (GWAS) of economically important traits such as seed mineral nutrient concentrations and others for marker-trait association using the software TASSEL. A manuscript is in preparation to further report the findings of this Specific Cooperator Agreement.