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Title: Using dominance relationship coefficients based on linkage disequilibrium and linkage with a general complex pedigree to increase mapping resolution
Contributor(s): Lee, Sang Hong  (author); Van Der Werf, Julius Herman  (author)orcid 
Publication Date: 2006
DOI: 10.1534/genetics.106.060806
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Abstract: Dominance (intra-locus allelic interactions) plays often an important role in quantitative trait variation. However, few studies about dominance in QTL mapping have been reported in outbred animal or human populations. This is because common dominance effects can be predicted mainly for many full sibs which are not often occurring in outbred or natural populations with a general pedigree. Moreover, incomplete genotypes for such a pedigree make it infeasible to estimate dominance relationship coefficients between individuals. In this study, identity by descent (IBD) coefficients are estimated based on population wide linkage disequilibrium (LD), which makes it possible to tract dominance relationships between unrelated founders. Therefore, it is possible to use dominance effects in QTL mapping without full sibs. Incomplete genotypes with complex pedigree and many markers can be efficiently dealt with a Markov chain Monte Carlo method for estimating IBD and dominance relationship matrices (DRM). It is shown by simulation that the use of DRM increases the likelihood ratio at the true QTL position, and the mapping accuracy and power with complete dominance, overdominance and recessive inheritance modes when using 200 genotyped and phenotyped individuals.
Publication Type: Journal Article
Source of Publication: Genetics, 174(2), p. 1-8
Publisher: Genetics Society of America
Place of Publication: United States of America
ISSN: 1943-2631
Fields of Research (FoR) 2008: 060412 Quantitative Genetics (incl Disease and Trait Mapping Genetics)
Socio-Economic Objective (SEO) 2008: 830311 Sheep - Wool
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Environmental and Rural Science

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