Multivariate analysis of a genome-wide association study in dairy cattle
Multivariate analysis of a genome-wide association study in dairy cattle
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DOI：
10.3168/jds.2009-2980
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发表时间：
2010-08-01
影响因子：
3.5
通讯作者：
Goddard, M. E.
中科院分区：
文献类型：
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作者：
Bolormaa, S.;Pryce, J. E.;Goddard, M. E.
将多性状全基因组关联研究（GWAS）分析与单性状GWAS分析进行比较，以发现并随后验证与奶牛性状相关的遗传标记（单核苷酸多态性；SNP）。在1个荷斯坦种群中发现了SNP关联，并在由比发现种群和泽西种群中年轻的公牛组成的荷斯坦种群中得到了验证。使用的多变量方法是主成分分析和一系列双变量分析。使用多性状GWAS检测关联的统计能力等于或优于最佳单性状GWAS。在单性状分析中未发现的多变量方法中发现了额外的SNP关联；这是在没有增加错误发现率的情况下实现的。通过多变量分析，在影响澳大利亚选择指数的QTL中发现了4种常见的多效型。这些模式可以解释为QTL对1个或多个乳成分的主要影响和对其他成分的次要影响。多变量分析似乎并没有增加QTL定位的精度。
Multiple-trait genome-wide association study (GWAS) analyses were compared with single-trait GWAS for power to discover and subsequently validate genetic markers (single nucleotide polymorphisms; SNP) associated with dairy traits. The SNP associations were discovered in 1 Holstein population and validated in both a Holstein population consisting of bulls younger than those in the discovery population and a Jersey population. The multivariate methods used were a principal component analysis and a series of bivariate analyses. The statistical power of detecting associations using multiple-trait GWAS was as good as or better than that of the best single-trait GWAS. Additional SNP associations were found with the multivariate methods that had not been discovered in the single-trait analyses; this was achieved without an increase in the false discovery rate. From the multivariate analysis, 4 common pleiotropic patterns were identified among the putative quantitative trait loci (QTL) affecting the Australian selection index. These patterns could be interpreted as a primary effect of the putative QTL on 1 or more milk components and secondary effects on other components. The multivariate analysis did not appear to increase the precision with which putative QTL were mapped.