Mineral nutrients play a crucial role in the biochemical and physiological functions of biological systems. The enhancement of seed mineral content via genetic improvement is considered as the most promising and cost-effective approach compared alternative means for meeting the dietary needs. The overall objective of this study was to perform a GWAS of mineral content (Ca, K, P and S) in seeds of a core set of 137 soybean lines that are representative of the diversity of early maturing soybeans cultivated in Canada (maturity groups 000-II). This panel of 137 soybean lines was grown in five environments (in total) and the seed mineral content was measured using a portable x-ray fluorescence (XRF) spectrometer. The association analyses were carried out using three statistical models and a set of 2.2 million SNPs obtained from a combined dataset of genotyping-by-sequencing and whole-genome sequencing. Eight QTLs significantly associated with the Ca, K, P and S content were identified by at least two of the three statistical models used (in two environments) contributing each from 17 to 31% of the phenotypic variation. A strong reproducibility of the effect of seven out these eight QTLs was observed in three other environments. In total, three candidate genes were identified involved in transport and assimilation of these mineral elements. There have been very few GWAS studies to identify QTLs associated with the mineral element content of soybean seeds. In addition to being new, the QTLs identified in this study and candidate genes will be useful for the genetic improvement of soybean nutritional quality through marker-assisted selection. Moreover, this study also provides details on the range of phenotypic variation encountered within the Canadian soybean germplasm.

中文翻译：

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控制大豆种子中矿质元素浓度的基因座的鉴定。


矿物质营养素在生物系统的生化和生理功能中发挥着至关重要的作用。与满足饮食需求的替代方法相比，通过遗传改良提高种子矿物质含量被认为是最有前途且最具成本效益的方法。本研究的总体目标是对 137 个核心大豆品系的种子中的矿物质含量（Ca、K、P 和 S）进行 GWAS，这些品系代表了加拿大种植的早熟大豆（成熟组 000）的多样性。 -II）。这组 137 个大豆品系在五种环境（总共）中生长，并使用便携式 X 射线荧光 (XRF) 光谱仪测量种子矿物质含量。使用三个统计模型和从测序基因分型和全基因组测序的组合数据集中获得的一组 220 万个 SNP 进行关联分析。所使用的三个统计模型中的至少两个（在两个环境中）鉴定出八个与 Ca、K、P 和 S 含量显着相关的 QTL，每个 QTL 贡献 17% 至 31% 的表型变异。在其他三个环境中观察到这八个 QTL 中的七个的效果具有很强的重现性。总共，确定了三个参与这些矿物元素的运输和同化的候选基因。很少有 GWAS 研究来鉴定与大豆种子矿物元素含量相关的 QTL。除了是新的之外，本研究中确定的 QTL 和候选基因还将有助于通过标记辅助选择对大豆营养品质进行遗传改良。此外，这项研究还提供了加拿大大豆种质中遇到的表型变异范围的详细信息。