We report a meta-Genome Wide Association Study involving 73 published studies in soybean (Glycine max L. [Merr.]) covering 17,556 unique accessions, with improved statistical power for robust detection of loci associated with a broad range of traits. De novo GWAS and meta-analysis were conducted for composition traits including fatty acid and amino acid composition traits, disease resistance traits, and agronomic traits including seed yield, plant height, stem lodging, seed weight, seed mottling, seed quality, flowering timing, and pod shattering. To examine differences in detectability and test statistical power between single- and multi-environment GWAS, comparison of meta-GWAS results to those from the constituent experiments were performed. Using meta-GWAS analysis and the analysis of individual studies, we report 483 quantitative trait loci (QTL) at 393 unique loci. Using stringent criteria to detect significant marker trait associations, 66 candidate genes were identified, including 17 candidate genes for agronomic traits, 19 for seed related traits, and 33 for disease reaction traits. This study identified potentially valuable candidate genes that affect multiple traits. The success in narrowing down the genomic region for some loci through overlapping mapping results of multiple studies is a promising avenue for community-based studies and plant breeding applications.

中文翻译：

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Meta-GWAS用于大豆数量性状基因座鉴定

我们报告了一项涉及73个已发表的大豆（Glycine max L. [Merr。]）研究的全基因组广泛关联研究，涉及17,556个独特种质，具有增强的统计能力，可用于与各种性状相关的基因座的稳健检测。从头进行了GWAS和元分析，分析了包括脂肪酸和氨基酸组成特征，抗病性特征和农艺性状（包括种子产量，株高，茎秆倒伏，种子重量，种子斑驳，种子品质，开花时间，和豆荚碎裂。为了检查单环境和多环境GWAS之间的可检测性差异和测试统计能力，对meta-GWAS结果与组成实验的结果进行了比较。使用全球GWAS分析和个别研究分析，我们报告了393个唯一基因座上的483个数量性状基因座（QTL）。使用严格的标准检测显着的标记性状关联，鉴定了66个候选基因，其中包括17个农艺性状候选基因，19个种子相关性状和33个疾病反应性状。这项研究确定了可能影响多种性状的潜在有价值的候选基因。通过多次研究的重叠作图结果成功缩小某些基因座的基因组区域，是基于社区的研究和植物育种应用的有希望的途径。这项研究确定了可能影响多种性状的潜在有价值的候选基因。通过多次研究的重叠作图结果成功缩小某些基因座的基因组区域，是基于社区的研究和植物育种应用的有希望的途径。这项研究确定了可能影响多种性状的潜在有价值的候选基因。通过多次研究的重叠作图结果成功缩小某些基因座的基因组区域，是基于社区的研究和植物育种应用的有希望的途径。