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Genome-wide association mapping of three important traits using bread wheat elite breeding populations

机译:利用面包小麦优良育种群体对三个重要性状进行全基因组关联映射

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摘要

The exponential development of molecular markers enables a more effective study of the genetic architecture of traits of economic importance, like test weight in wheat (Triticum aestivum L.), for which a high value is desired by most end-users. The association mapping (AM) method now allows more precise exploration of the entire genome. AM requires populations with substantial genetic variability of the traits of interest. The breeding lines at the end of a selection cycle, characterized for numerous traits, represent a potentially useful population for AM studies. Using three elite line populations, selected by several breeders and genotyped with about 2,500 Diversity Arrays Technology markers, several associations were identified between these markers and test weight, grain yield and heading date. To minimize spurious associations, we compared the general linear model and mixed linear model (MLM), which adjust for population structure and kinship differently. The MLM model with the kinship matrix was the most efficient. Finally, elite lines from several breeding programs had sufficient genetic variability to allow for the mapping of several chromosomal regions involved in the variation of three important traits.
机译:分子标记物的指数发展使人们能够更有效地研究具有经济重要性的性状的遗传结构,例如小麦的容重(大多数小麦的最终用户希望获得较高的价值)。现在,关联映射(AM)方法可以更精确地探索整个基因组。 AM需要具有感兴趣性状的显着遗传变异的种群。选择周期结束时的育种系具有许多特征,代表了AM研究的潜在有用种群。使用由数个育种者选择并用约2,500个多样性阵列技术标记进行基因分型的三个优良品系种群,在这些标记与测试重量,谷物产量和抽穗期之间确定了几种关联。为了最大程度地减少虚假关联,我们比较了一般线性模型和混合线性模型(MLM),它们对人口结构和亲属关系的调整不同。具有亲属关系矩阵的MLM模型效率最高。最后,来自几个育种计划的优良品系具有足够的遗传变异性,可以绘制出涉及三个重要性状变异的几个染色体区域的图谱。

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