Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars
Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars
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DOI：
10.1007/s00122-011-1697-2
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发表时间：
2011-09
影响因子：
5.4
通讯作者：
Minghui Wang;Ning Jiang;T. Jia;Lindsey J. Leach;J. Cockram;R. Waugh;L. Ramsay;B. Thomas;
中科院分区：
文献类型：
--
作者：
Minghui Wang;Ning Jiang;T. Jia;Lindsey J. Leach;J. Cockram;R. Waugh;L. Ramsay;B. Thomas;
全基因组关联研究（GWAS）已成为研究高等植物，特别是作物重要农艺性状的一种常用方法。在这里，我们提出了一个GWAS的32个形态和10个农艺性状的615个大麦品种的基因型全基因组多态性，从最近开发的大麦寡核苷酸池检测。强的人口结构效应有关的混合抽样的基础上，季节性生长习性和穗行数是目前在这个大麦收集。在全基因组扫描中比较七种统计方法，以确定是否存在校正人群结构混淆的显著关联，结果表明，在降低假阳性率的同时保持统计功效，混合线性模型解决方案优于基因组控制，结构化关联，逐步回归控制和主成分调整。本研究报告了16个形态和9个农艺性状的显着关联，并证明了应用GWAS在高度结构化的植物样本中探索复杂性状的能力和可行性。
Genome-wide association study (GWAS) has become an obvious general approach for studying traits of agricultural importance in higher plants, especially crops. Here, we present a GWAS of 32 morphologic and 10 agronomic traits in a collection of 615 barley cultivars genotyped by genome-wide polymorphisms from a recently developed barley oligonucleotide pool assay. Strong population structure effect related to mixed sampling based on seasonal growth habit and ear row number is present in this barley collection. Comparison of seven statistical approaches in a genome-wide scan for significant associations with or without correction for confounding by population structure, revealed that in reducing false positive rates while maintaining statistical power, a mixed linear model solution outperforms genomic control, structured association, stepwise regression control and principal components adjustment. The present study reports significant associations for sixteen morphologic and nine agronomic traits and demonstrates the power and feasibility of applying GWAS to explore complex traits in highly structured plant samples.