Pedigree linkage disequilibrium mapping of quantitative trait loci
Pedigree linkage disequilibrium mapping of quantitative trait loci
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DOI：
10.1038/sj.ejhg.5201301
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发表时间：
2005-02-01
影响因子：
5.2
通讯作者：
Jung, JS
中科院分区：
文献类型：
--
作者：
Fan, RZ;Spinka, C;Jung, JS
在本文中，我们建议使用任何大小的家系和任何类型的亲属进行联合高分辨率连锁不平衡(LD)和利用方差分量模型进行数量性状座位(QTL)的连锁定位。可以同时使用两个或多个标记来建模与性状轨迹的关联，而不是在分析中一次使用一个标记。该方法可以在建模中使用两个或多个标记来提供统一的结果。这可能会避免逐个标记单独分析不同结果的复杂情况。这些模型同时包含了链接信息和LD信息。LD的量度用均值系数建模，链接信息用方差-协方差矩阵建模。利用解析公式计算回归系数，将遗传效应分解为加性分量和显性分量。给出了LD测试统计量的非中心性参数近似，以进行功率计算。分析了功率误码率和第I类误码率，并通过解析公式和仿真验证了该方法的优点。与Fulker和Abecsis等人的家庭间关联和家庭内关联(AbAw)方法相比，本文提出的方法显然更有效。应用该方法研究了血管紧张素转换酶基因多态性与循环血管紧张素转换酶水平的关系，结果优于‘AbAw’法。此外，I/D和4656(CT)3/2两个标记可以在0.01显著水平上完全解释与性状基因座的关联，这为ACE数据提供了唯一的结果。
In this paper, we propose to use pedigrees of any size and any types of relatives in joint high-resolution linkage disequilibrium (LD) and linkage mapping of quantitative trait loci (QTL) by variance component models. Two or multiple markers can be simultaneously used in modeling association with the trait locus, instead of using one marker a time in the analysis. The proposed method can provide a unified result by using two or multiple markers in the modeling. This may avoid the complications of different results obtained from the separate analysis of marker by marker. The models simultaneously incorporate both linkage and LD information. The measures of LD are modeled by mean coefficients, and linkage information is modeled by variance-covariance matrix. Using analytical formulas to calculate the regression coefficients, the genetic effects are shown to be decomposed into additive and dominance components. The noncentrality parameter approximations of test statistics of LD are provided to make power calculations. Power and type I error rates are explored to investigate the merit of the proposed method by both the analytical formulas and simulations. Comparing with the association between-family and association within-family ('AbAw') approach of Fulker and Abecasis et al, it is evident that the method proposed in this article is more powerful. The method is applied to investigate the relation between polymorphisms in the angiotensin 1-converting enzyme ( ACE) genes and circulating ACE levels, with a better result than that of the 'AbAw' approach. Moreover, two markers I/D and 4656(CT)3/2 can fully interpret association with the trait locus at a 0.01 significance level, which provides a unique result for the ACE data.