Genome‐wide association analysis identified consistent QTL for seed yield in a soybean diversity panel tested across multiple environments

• Published in: The plant genome Vol. 15; no. 4; pp. e20268 - n/a
• Main Authors: Ayalew, Habtamu, Schapaugh, William, Vuong, Tri, Nguyen, Henry T.
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01-12-2022; Wiley
• Subjects: Association analysis; Chromosome 17; Chromosome 9; Data analysis; Discriminant analysis; Genes; Genetic diversity; Genome-Wide Association Study; Genomes; Genotype & phenotype; Genotype-environment interactions; Glycine max; Glycine max - genetics; Heritability; Plant Breeding; Plant introductions; Polymorphism; Principal components analysis; Productivity; Quantitative Trait Loci; Seeds; Seeds - genetics; Single-nucleotide polymorphism; Soybeans
• ISSN: 1940-3372; 1940-3372
• DOI: 10.1002/tpg2.20268

Improving seed yield is one of the main targets of soybean [Glycine max (L.) Merr.] breeding. Identification of loci that influence productivity and understanding their genetic mechanism will help marker‐assisted trait introgression. The present study evaluated a diverse panel of 541 soybean genotypes consisting of three maturity groups (MGs III–V) in four environments in Kansas, U.S. Data on seed yield, seed weight, shattering resistance, days to maturity, and plant height showed significant genotype, environmental, and genotype × environment interaction variations. Seed yield and shattering had moderate broad‐sense heritability (<85%), while the rest of the traits showed high broad‐sense heritability (>90%). The SoySNP50K iSelect BeadChip dataset was used to identify significantly associated loci via genome‐wide association studies (GWAS). A total of 19 single‐nucleotide polymorphisms (SNPs) were significantly associated with seed yield. Particularly, two stable seed yield quantitative trait loci (QTL) on chromosomes 9 and 17 were consistently detected in at least three out of four environments. Candidate gene analysis surrounding seed yield QTL on chromosome 9 showed that Glyma.09G048900, an oxygen binding protein, was the closest to the QTL peak. Similarly, Glyma.17G090200 and Glyma.17G090400 were within 20‐kb region of the seed yield QTL on chromosome 17. The candidate genes warrant further analysis to determine their functional mechanisms and develop markers for seed yield improvement.
Core Ideas
The four Kansas locations commonly used to test soybean breeding materials showed significant G × E interactions.
Consistent seed yield QTL identified on Gm09 and Gm17 based on a multi‐environment data analyses.
The closest candidate genes to the seed yield QTL on Gm09 and Gm17 were oxygen and heme binding proteins.