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A genome-wide association study of 23 agronomic traits in Chinese wheat landraces

机译:中国小麦实体中23例农艺性状的基因组关联研究

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Uncovering the genetic basis of agronomic traits in wheat landraces is important for ensuring global food security via the development of improved varieties. Here, 723 wheat landraces from 10 Chinese agro-ecological zones were evaluated for 23 agronomic traits in six environments. All accessions could be clustered into five subgroups based on phenotypic data via discriminant function analysis, which was highly consistent with genotypic classification. A genome-wide association study was conducted for these traits using 52 303 DArT-seq markers to identify marker-trait associations and candidate genes. Using both the general linear model and the mixed linear model, 149 significant markers were identified for 21 agronomic traits based on best linear unbiased prediction values. Considering the linkage disequilibrium decay distance in this study, significant markers within 10 cM were combined as a quantitative trait locus (QTL), with a total of 29 QTL identified for 15 traits. Of these, five QTL for heading date, flag leaf width, peduncle length, and thousand kernel weight had been reported previously. Twenty-five candidate genes associated with significant markers were identified. These included the known vernalization genes VRN-B1 and vrn-B3 and the photoperiod response genes Ppd and PRR. Overall, this study should be helpful in elucidating the underlying genetic mechanisms of complex agronomic traits and performing marker-assisted selection in wheat.
机译:揭示小麦地球菌农艺性状的遗传基础对于通过改进品种的发展来确保全球粮食安全是重要的。在这里,在六种环境中评估了来自10家中国农业生态区的723个小麦样力。通过判别函数分析,可以基于表型数据组聚集成五个亚组,这与基因型分类高度一致。使用52 303次达特-SEQ标记对这些性状进行基因组 - 宽的关联研究,以鉴定标记性关联和候选基因。使用一般线性模型和混合线性模型,基于最佳线性无偏的预测值,鉴定了149个显着标记的21种农艺性状。考虑到该研究中的连锁不平衡衰减距离,将10cm内的显着标记作为定量性状基因座(QTL)组合,共有29 QTL鉴定为15个特征。其中,先前已经报道了五个QTL用于标题日,标志叶宽度,花梗长度和千内核重量。确定了与重要标记相关的二十五个候选基因。这些包括已知的vernalizate基因VRN-B1和VRN-B3以及PHD和PRR的光周期反应基因。总体而言,该研究应有助于阐明复杂的农艺性状的潜在遗传机制,并在小麦中进行标记辅助选择。

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