308-23 Genome-Wide Association Mapping of Agronomic and Morphological Traits in the USDA Soybean Germplasm Collection.

Poster Number 1036

See more from this Division: C07 Genomics, Molecular Genetics & Biotechnology
See more from this Session: Genomics, Molecular Genetics & Biotechnology: I

Tuesday, November 17, 2015
Minneapolis Convention Center, Exhibit Hall BC

Nonoy Bandillo, Nebraska, University of Nebraska - Lincoln, Lincoln, NE, Juan Diego Hernandez Jarquin, Agronomy and Horticulture, University of Nebraska - Lincoln, Lincoln, NE, Qijian Song, USDA-ARS, Beltsville, MD, Perry B. Cregan, Soybean Genomics and Improvement Lab, USDA-ARS, Beltsville, MD, George Graef, University of Nebraska - Lincoln, Lincoln, NE, James Specht, Department of Agrononomy and Horticulture, University of Nebraska - Lincoln, Lincoln, NE, Aaron J Lorenz, Department of Agronomy and Horticulture, University of Nebraska - Lincoln, Lincoln, NE and Randall Nelson, 1101 W Peabody, USDA-ARS, Urbana, IL
Abstract:
The potential high mapping resolution in localizing quantitative trait loci (QTL) controlling a trait of interest is the primary advantage of genome-wide association study (GWAS) compared to linkage mapping. In this study, we demonstrate the power of the soybean germplasm collection as a new genetic resource for high-resolution mapping of multiple traits and for facilitating gene discovery. We conducted a GWAS using the collection of over 12K unique Glycine max accessions genotyped with a high-density 50K SNP chip. The phenotype we examined for GWAS can be broadly categorized into plant morphology related-traits, seed-related traits, and growth-related traits. We then determined the resolution of the causal genes controlling variation for traits whose genes have been cloned, and other genes that have been mapped as classical loci but have not yet cloned. The GWAS identified the known major genes at a high mapping resolution. Notably, the peak signals of the GWAS loci for different traits appeared near or within the known genes and/or candidate genes. Interestingly, GWAS also identified new loci at a high resolution that are attractive candidates for further studies. The GWAS results will be useful for map-based cloning of the causal genes underlying these traits and facilitate a more efficient and effective introgression of diversity contained within the collection into elite varieties for continued genetic improvement.

See more from this Division: C07 Genomics, Molecular Genetics & Biotechnology
See more from this Session: Genomics, Molecular Genetics & Biotechnology: I