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Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean

机译:用GBS-GWA方法识别八个农艺性状的诊断与QTL映射在大豆豆章中的验证

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摘要

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sitesx2years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.
机译:大豆是人类消费食用油和蛋白质的主要来源,以及动物饲料。了解大豆不同特征的遗传基础将为改善这种作物的育种策略提供重要见解。进行了一种基因组协会研究(GWAS),以加速分子育种,以改善大豆豆类农艺性状。用于逐序列(GBS)方法用于为304个短季大豆线的面板提供致密的基因组标记覆盖(> 47000 snps)。在六种环境下表现出八个特征的表现出来的139条线的子集,表现出八个特征(3个位点x2years)。标记覆盖证明,足以确保所知的基因之间的高度显着关联(花,海洛姆和青春期)和侧翼SNP。还鉴定了与更复杂的特征(成熟,植物高度,种子重,种子油和蛋白质)相关的一个和八种基因组基因座之间。重要的是,这些GWAS基因座中的大多数位于由先前报告的定量性状基因座(QTL)鉴定的基因组区域内,用于这些性状。在某些情况下,报告的QTL也被额外的QTL映射成功地验证了一步。该研究表明,集成GBS和GWA可以用作典型额向映射的强大互补方法,用于解剖豆豆中的复杂性状。

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