Genome-wide association study and genomic selection for plant height, maturity, seed weight, and yield in soybean

BackgroundSoybean [Glycine max (L.) Merr.] is a legume of great interest worldwide. Enhancing genetic gain for agronomic traits via molecular approaches has been long considered as the main task for soybean breeders and geneticists. The objectives of this study were to conduct a genome-wide association study (GWAS) for these traits and identify SNP markers associated with the four traits, and to assess genomic selection (GS) accuracy.Results A total of 250 soybean accessions were evaluated for maturity, plant height, seed weight, and yield over three years. This panel was genotyped with a total of 10,259 high quality SNPs postulated from genotyping by sequencing (GBS). Population structure was inferred using STRUCTURE 2.3.4, GWAS was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model, and GS was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that: a total of 20, 31, 37, 31, and 23 SNPs were significantly associated with the average 3-year data for maturity, plant height, seed weight, and yield, respectively; some significant SNPs were mapped into previously described loci (E2, E4, and Dt1) affecting maturity and plant height in soybean and a new locus mapped on chromosome 20 was significantly associated with plant height; Glyma.10g228900, Glyma.19g200800, Glyma.09g196700, and Glyma.09g038300 were candidate genes found in the vicinity of the top or the second best SNP (if no annotated genes found close the top one) for maturity, plant height, seed weight, and yield, respectively; a 11.5-Mb region of chromosome 10 was associated with both seed weight and yield; and GS accuracy was trait-, year-, and population structure-dependent.Conclusions The SNP markers identified from this study for plant height, maturity, seed weight and yield can be used to improve the four agronomic traits in soybean through marker-assisted selection (MAS) and GS in breeding programs. After validation, the candidate genes can be transferred to new cultivars using the linked SNP markers through MAS. The high GS accuracy has confirmed that the four agronomic traits can be selected in molecular breeding through GS.