Bivariate combined linkage and association mapping of quantitative trait loci
Bivariate combined linkage and association mapping of quantitative trait loci
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DOI：
10.1002/gepi.20313
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发表时间：
2008-07-01
影响因子：
2.1
通讯作者：
Fan, Ruzong
中科院分区：
文献类型：
--
作者：
Jung, Jeesun;Zhong, Ming;Fan, Ruzong
本文基于家系和群体数据的结合，提出了双变量/多变量方差成分模型，用于定量性状位点（QTL）的高分辨率联合连锁和关联定位。假设一个数量性状位点位于对多个数量性状具有多效性作用的染色体区域。在该区域，多个标记如单核苷酸多态性被分型。提出了“基因型效应模型”和“加性效应模型”两种回归模型来模拟标记与性状位点之间的关联。连锁信息，即QTL与标记之间的重组分数，在方差和协方差矩阵中建模。通过解析公式表明，“基因型效应模型”可以同时模拟加性效应和显性效应；“加性效应模型”只考虑加性效应。在这两个模型的基础上，提出了f检验统计量来检验QTL与标记之间的相关性。通过分析功率分析，我们表明二元模型比单变量模型更强大。对于中等规模的样本，所提出的模型导致正确的I型错误率；所以这些模型是相当稳健的。以the North American rheumatoid arthritis Consortium， Problem 2， genetic Analysis Workshop 15的数据为例，应用该方法分析类风湿关节炎的遗传遗传，验证了二元模型的优势。
In this paper, bivariate/multivariate variance component models are proposed for high-resolution combined linkage and association mapping of quantitative trait loci (QTL), based on combinations of pedigree and population data. Suppose that a quantitative trait locus is located in a chromosome region that exerts pleiotropic effects on multiple quantitative traits. In the region, multiple markers such as single nucleotide polymorphisms are typed. Two regression models, "genotype effect model" and "additive effect model", are proposed to model the association between the markers and the trait locus. The linkage information, i.e., recombination fractions between the QTL and the markers, is modeled in the variance and covariance matrix. By analytical formulae, we show that the "genotype effect model" can be used to model the additive and dominant effects simultaneously; the "additive effect model" only takes care of additive effect. Based on the two models, F-test statistics are proposed to test association between the QTL and markers. By analytical power analysis, we show that bivariate models can be more powerful than univariate models. For moderate-sized samples, the proposed models lead to correct type I error rates; and so the models are reasonably robust. As a practical example, the method is applied to analyze the genetic inheritance of rheumatoid arthritis for the data of The North American Rheumatoid Arthritis Consortium, Problem 2, Genetic Analysis Workshop 15, which confirms the advantage of the proposed bivariate models.