Analysis of genetic structure in a panel of elite wheat varieties and relevance for association mapping
Analysis of genetic structure in a panel of elite wheat varieties and relevance for association mapping
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DOI：
10.1007/s00122-011-1621-9
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发表时间：
2011-09-01
影响因子：
5.4
通讯作者：
Praud, Sebastien
中科院分区：
文献类型：
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作者：
Le Couviour, Fabien;Faure, Sebastien;Praud, Sebastien
近几十年来，随着品种间杂交选育的加强，优良小麦种质形成了非常复杂的遗传结构。然而，随着资源管理和新的遗传决定因素绘图统计工具（如关联研究）的发展，用小组和集合精确描述这种结构变得越来越重要。在这项研究中，我们调查了195个西欧优良小麦品种的遗传结构，使用最近发展的高通量分子标记筛选方法。在观察到微卫星和多样性阵列技术标记都能有效地估计面板的结构后，我们使用了不同的互补方法（遗传距离，主成分分析），表明品种被地理来源（法国，德国和英国）和育种历史分开，证实了植物育种对小麦种质结构的影响。此外，通过分析三个表型性状表现出显着的平均差异，各组（株高，抽穗期和芒），并通过使用标记与这些性状的主基因（Ppd-D1，Rht-B1，Rht-D1和B1），我们发现，对于每个性状，有一个特定的最佳Q矩阵作为协变量在关联检验。
During the last decades, with the intensification of selection and breeding using crosses between varieties, a very complex genetic structure was shaped in the elite wheat germplasm. However, precise description of this structure with panels and collections is becoming more and more crucial with the development of resource management and new statistical tools for mapping genetic determinants (e.g. association studies). In this study, we investigated the genetic structure of 195 Western European elite wheat varieties using the recent development of high throughput screening methods for molecular markers. After observing that both microsatellites and Diversity Array Technology markers are efficient to estimate the structure of the panel, we used different complementary approaches (Genetic distances, principal component analysis) that showed that the varieties are separated by geographical origin (France, Germany and UK) and also by breeding history, confirming the impact of plant breeding on the wheat germplasm structure. Moreover, by analysing three phenotypic traits presenting significant average differences across groups (plant height, heading date and awnedness), and by using markers linked to major genes for these traits (Ppd-D1, Rht-B1, Rht-D1 and B1), we showed that for each trait, there is a specific optimal Q matrix to use as a covariate in association tests.