|YAN, LONG - Hebei Academy Of Agriculture & Forestry|
|HOFMANN, NICOLLE - Oregon Health & Science University|
|FERREIRA, MARCIO - Embrapa|
|SONG, BAOHUA - University Of North Carolina|
|JIANG, GUOLIANG - Virginia State University|
|REN, SHUXIN - Virginia State University|
|Quigley, Charles - Chuck|
|CREGAN, PERRY - Retired ARS Employee|
Submitted to: Biomed Central (BMC) Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/4/2017
Publication Date: 7/12/2017
Citation: Yan, L., Hofmann, N., Li, S., Ferreira, M., Song, B., Jiang, G., Ren, S., Quigley, C.V., Fickus, E.W., Cregan, P., Song, Q. 2017. Identification of QTL with large effect on seed weight in a selective population of soybean with genome-wide association and fixation index analyses. Biomed Central (BMC) Genomics. 18:529. https://doi.org/10.1186/s12864-017-3922-0.
Interpretive Summary: Soybean seed weight contributes to yield, but seed weight also has a downstream influence on the production of soybean-based foods like sprouts, edamame, sauce, natto and miso. In this study, we selected seed lines with extremely large and small seed weights that could normally grow and mature at Beltsville, MD. We then examined DNA regions to find gene differences that might explain the large effect on seed weight. Genetic and statistical analyses determined six regions in the soybean DNA genome that contributed to large seed weight difference between the two lines. These DNA regions were then searched in 3,753 different soybean lines. This approach helped differentiate between real DNA differences and random differences. In the end, we identified genetic regions in soybean DNA linked to controlling seed weight. The findings are expected to help geneticists and breeders in government agencies, universities, and private institutes develop new soybeans with greater weight and yield.
Technical Abstract: Our objective was to identify candidate QTL that had a large effect on seed weight using a selective population through GWAS and fixation index analysis. A selective population was previously used for the identification of QTL in linkage analysis of bi-parental RIL populations in plant species, but limited in GWAS. We selected 166 accessions with large or small seed and could normally grow at the same location. The accessions were evaluated for seed weight in the field for two years and characterized with the SoySNP50K BeadChip containing >42,000 SNPs. Of the 17 SNPs on six chromosomes that were significantly associated with seed weight in two years, eight on chromosome 4 or 17 had significant Fst values between the large and small seed sub-populations. The average effect of the significant SNPs varied from 8.1 g to 12.0 g/100 seeds. We also identified haplotypes in three haplotype blocks with significant and large effects on seed weight and these were validated in a panel with 3753 accessions. This study highlighted the usefulness of selective genotyping populations for the identification of QTL with large effects on seed weight in soybean, and will help geneticists and breeders to more efficiently identify major QTL controlling other traits. We identified major regions and haplotypes that control seed weight differences in soybean, which will facilitate the identification of genes regulating this important trait.