Ayalew Habtamu, Schapaugh William, Vuong Tri, Nguyen Henry T
Dep. of Agronomy, Kansas State Univ., Manhattan, Kansas, 66506, USA.
Division of Plant Science and Technology, Univ. of Missouri, Columbia, Missouri, 65211, USA.
Plant Genome. 2022 Dec;15(4):e20268. doi: 10.1002/tpg2.20268. Epub 2022 Oct 18.
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.
提高种子产量是大豆[Glycine max (L.) Merr.]育种的主要目标之一。鉴定影响产量的基因座并了解其遗传机制将有助于进行标记辅助性状导入。本研究在美国堪萨斯州的四个环境中,对由三个成熟组(MGs III-V)组成的541个大豆基因型的多样化群体进行了评估。关于种子产量、种子重量、抗裂性、成熟天数和株高的数据显示出显著的基因型、环境以及基因型×环境互作变异。种子产量和裂荚具有中等广义遗传力(<85%),而其他性状表现出高广义遗传力(>90%)。利用SoySNP50K iSelect BeadChip数据集通过全基因组关联研究(GWAS)鉴定显著相关的基因座。共有19个单核苷酸多态性(SNP)与种子产量显著相关。特别地,在四个环境中的至少三个环境中一致检测到位于9号和17号染色体上的两个稳定的种子产量数量性状位点(QTL)。对9号染色体上种子产量QTL周围的候选基因分析表明,一种氧结合蛋白Glyma.09G048900最接近QTL峰值。同样,Glyma.17G090200和Glyma.17G090400位于17号染色体上种子产量QTL的20 kb区域内。这些候选基因值得进一步分析,以确定其功能机制并开发用于提高种子产量的标记。