A Population Structure and Genome-Wide Association Analysis on the USDA Soybean Germplasm Collection

Population structure analyses and genome-wide association studies (GWAS) conducted on crop germplasm collections provide valuable information on the frequency and distribution of alleles governing economically important traits. The value of these analyses is substantially enhanced when the accession numbers can be increased from ~1,000 to ~10,000 or more. In this research, we conducted the first comprehensive analysis of population structure on the collection of 14,000 soybean accessions [Glycine max (L.) Merr. and G. soja Siebold & Zucc.] using a 50KSNP chip. Accessions originating from Japan were relatively homogenous and distinct from the Korean accessions. As a whole, both Japanese and Korean accessions diverged from the Chinese accessions. The ancestry of founders of the American accessions derived mostly from two Chinese subpopulations, which reflects the composition of the American accessions as a whole. A 12,000 accession GWAS conducted on seed protein and oil is the largest reported to date in plants and identified single nucleotide polymorphisms (SNPs) with strong signals on chromosomes 20 and 15. A chromosome 20 region previously reported to be important for protein and oil content was further narrowed and now contains only three plausible candidate genes. The haplotype effects show a strong negative relationship between oil and protein at this locus, indicating negative pleiotropic effects or multiple closely linked loci in repulsion phase linkage. The vast majority of accessions carry the haplotype allele conferring lower protein and higher oil. Our results provide a fuller understanding of the distribution of genetic variation contained within the USDA soybean collection and how it relates to phenotypic variation for economically important traits. Soybean is an important crop worldwide and a major source of protein and oil for human food, animal feed, and industrial products (Wilson, 2008). The percentages of protein and oil content, while influenced by both genotype and environment, typically average ~40 and ~20%, respectively. Increasing the relative oil content in soybean seed is complicated by its high negative correlation to protein content (Brummer et al., 1997; Burton, 1987; Clemente and Cahoon, 2009; Cober and Voldeng, 2000; Wilcox, 1998) caused by either pleiotropic effects or linkage (Chung et al., 2003). Moreover, total seed yield is often negatively correlated with seed protein, although the correlation is weaker than that between protein and oil (Chung et al., 2003). Dissecting the genetic bases underlying seed oil and protein content, and eventually recombining them in desired genetic backgrounds, continues to be a challenge to soybean breeders. Given the importance of oil and protein content, the genes or quantitative trait loci (QTL) underlying these traits have undergone intensive investigations (Bolon et al., 2010; Chung et al., 2003; Hwang et al., 2014; Vaughn et al., 2014). However, most of what we know about the Published in The Plant Genome 8 doi: 10.3835/plantgenome2015.04.0024 © Crop Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA An open-access publication All rights reserved. N. Bandillo, D. Jarquin, J. Specht, and A. Lorenz, Dep. of Agronomy & Horticulture, Keim Hall, Univ. of Nebraska–Lincoln, Lincoln, NE 68583-0915; Q. Song and P. Cregan, Soybean Genomics and Improvement Lab., Beltsville Agricultural Research Center, Beltsville, MD 20705; R. Nelson, USDA–ARS, Soybean/Maize Germplasm, Pathology, and Genetics Research Unit, 1101 W. Peabody Dr., Urbana, IL 61801-0000. Received 19 Apr. 2015. Accepted 23 June 2015. *Corresponding author ([email protected]). Abbreviations: CV, cross-validation; FaST-LMM, Factored Spectrally Transformed Linear Mixed Model; GRIN, Germplasm Resources Information Network; GWA, genome-wide association; GWAS, genome-wide association studies; kb, kilobase; LD, linkage disequilibrium; LG, linkage group; MAF, minor allele frequency; Mb, megabase; MG, maturity group; QTL, quantitative trait loci; SNP, single nucleotide polymorphism; SP, subpopulation. Published November 6, 2015