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GWAS Analysis and QTL Identification of Fiber Quality Traits and Yield Components in Upland Cotton Using Enriched High-Density SNP Markers

机译:利用丰富的高密度SNP标记进行陆地棉GWAS分析和QTL鉴定纤维品质性状和产量构成要素

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摘要

It is of great importance to identify quantitative trait loci (QTL) controlling fiber quality traits and yield components for future marker-assisted selection (MAS) and candidate gene function identifications. In this study, two kinds of traits in 231 F6:8 recombinant inbred lines (RILs), derived from an intraspecific cross between Xinluzao24, a cultivar with elite fiber quality, and Lumianyan28, a cultivar with wide adaptability and high yield potential, were measured in nine environments. This RIL population was genotyped by 122 SSR and 4729 SNP markers, which were also used to construct the genetic map. The map covered 2477.99 cM of hirsutum genome, with an average marker interval of 0.51 cM between adjacent markers. As a result, a total of 134 QTLs for fiber quality traits and 122 QTLs for yield components were detected, with 2.18–24.45 and 1.68–28.27% proportions of the phenotypic variance explained by each QTL, respectively. Among these QTLs, 57 were detected in at least two environments, named stable QTLs. A total of 209 and 139 quantitative trait nucleotides (QTNs) were associated with fiber quality traits and yield components by four multilocus genome-wide association studies methods, respectively. Among these QTNs, 74 were detected by at least two algorithms or in two environments. The candidate genes harbored by 57 stable QTLs were compared with the ones associated with QTN, and 35 common candidate genes were found. Among these common candidate genes, four were possibly “pleiotropic.” This study provided important information for MAS and candidate gene functional studies.
机译:识别控制纤维质量性状和产量成分的定量性状基因座(QTL)对于将来的标记辅助选择(MAS)和候选基因功能鉴定非常重要。在这项研究中,对231 F6:8重组自交系(RILs)的两种性状进行了测量,该系来自具有优良纤维品质的品种新芦枣24和适应性强,高产潜力的品种Lumianyan28之间的种内杂交在九种环境中。该RIL群体由122个SSR和4729个SNP标记进行了基因分型,这些标记也用于构建遗传图谱。该图覆盖了hirsutum基因组的2477.99 cM,相邻标记之间的平均标记间隔为0.51 cM。结果,共检测到134个纤维品质性状的QTL和122个产量性状的QTL,每个QTL解释的表型差异的比例分别为2.18–24.45和1.68–28.27%。在这些QTL中,至少在两个环境中检测到57个,称为稳定QTL。通过四种多基因组全基因组关联研究方法,分别将总共209和139个定量性状核苷酸(QTN)与纤维品质性状和产量构成因素相关联。在这些QTN中,至少有两种算法或在两种环境中检测到74种。将57个稳定的QTL所具有的候选基因与QTN相关的候选基因进行了比较,发现了35个常见的候选基因。在这些常见候选基因中,有四个可能是“多效性”。该研究为MAS和候选基因功能研究提供了重要信息。

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