Using multivariate genetic modeling to detect pleiotropic quantitative trait loci

Abstract

Large numbers of sibling pairs or other relatives are needed to detect linkage between a quantitative trait locus (QTL) and a marker, especially if the variance of the QTL is low relative to the total phenotypic variance of the trait. One strategy to increase the power to detect linkage is to reduce the environmental variance in the trait under analysis. This approach was explored by carrying out a series of simulation studies in which multivariate observations were used to estimate individual genotypic values at a QTL, that pleiotropically affected more than one trait. Simulations for different QTL allele frequencies with a completely informative marker showed that the power to detect the QTL increased substantially when estimates of individual genotypic values at the QTL were used in the linkage analysis instead of phenotypic observations. An advantage of this approach is that, rather than employing phenotypic selection, individuals with extreme genotypes may be selected when ascertaining a sample of extreme families.