Multi-Genome-Wide Association Study and Novel Gene Identification in Korean Soybean Using a 391 Core Collection

A large amount of genome information has been accumulated in soybean [Glycine max (Merr.) L.] by the development of high-throughput genotyping technology and therefore, genome-wide association studies (GWAS) become feasible to identify associations between genomic variation and quantitative/qualitative traits. Here, we provide the information about current progress in soybean GWAS study using core collection, which was constructed using 391 soybean varieties. The 180K Axiom® Soybean Genotyping Array was employed to obtain the genome-wide variation information. Multiple traits collected from the core collection accessions were used to evaluate the power of GWAS using GAPIT, and its potential capability to identify the novel genes/QTLs. First, to confirm the accuracy of proposed GWAS, agronomic phenotypes with well-known genes/QTLs, such as flowering time or hypocotyl color, were tested. The result showed that precise location of previously reported genes/QTLs (e.g., GIGANTEA homologos, GIa, for flowering time) were detected. In sequence, secondary metabolite profiling data were employed to identify the novel genes/QTLs. Using soybean seeds, three phenotypes from non-targeted secondary metabolites profiling by 500MHz NMR, DPPH radical scavenging assay, and the NMR peaks, which were correlated to antioxidant activity, were used for GWAS. The analysis result shows that SNPs associated with both the well-known and novel unknown compounds can be identified. Our results suggested that GWAS in soybean genomics could provide opportunity to discover the novel genes/Qtls. Those genetic information could be used for improvement of plant modeling, which would support different forms including agricultural practices including organic farming as well as climate change adaptation.