High Resolution Association Mapping of Quantitative Trait Loci, A Population Based Approach

In this paper, population based regression models are proposed for high resolution linkage disequilibrium mapping of quantitative trait loci (QTL). Two regression models, "genotype effect model" and "additive effect model", are proposed to model the association between the markers and the trait locus. The marker can be either di-allelic or multi-allelic. If only one marker is used, the method is similar to a classical setting by Nielsen and Weir, and the "additive effect model" is equivalent to Haplotype Trend Regression (HTR) method by Zaykin et al. If two/multiple marker data with phase ambiguity are used in the analysis, the proposed models can be used to analyze the data directly. By analytical formulae, we show that the "genotype effect model" can be used to model the additive and dominance 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 simulation study, we show that the two models have reasonable type I error rates for a dataset of moderate sample size. The non-centrality parameter approximations of F-test statistics are derived to make power calculation and comparison. By simulation study, it is found that the non-centrality parameter approximations of F-test statistics work very well. Using the non-centrality parameter approximations, we compare the power of the two models with that of the HTR. In addition, simulation study is performed to make comparison based on the haplotype frequencies of 10 SNPs of angiotensin-1 converting enzyme (ACE) genes.

Key Words: Haplotype, QTL, linkage disequilibrium mapping

Online ISS 1091-6490
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