Issue |
Genet. Sel. Evol.
Volume 35, Number 6, November-December 2003
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Page(s) | 605 - 622 | |
DOI | https://doi.org/10.1051/gse:2003042 |
DOI: 10.1051/gse:2003042
A comparison of bivariate and univariate QTL mapping in livestock populations
Peter Sørensen, Mogens Sandø Lund, Bernt Guldbrandtsen, Just Jensen and Daniel SorensenDanish Institute of Agricultural Sciences, Department of Animal Breeding and Genetics, Research Centre Foulum, PO Box 50, 8830 Tjele, Denmark
(Received 22 April 2002; accepted 6 March 2003)
Abstract
This study presents a multivariate, variance component-based QTL
mapping model implemented via restricted maximum likelihood
(REML). The method was applied to investigate bivariate and univariate
QTL mapping analyses, using simulated data. Specifically, we report
results on the statistical power to detect a QTL and on the precision
of parameter estimates using univariate and bivariate approaches. The
model and methodology were also applied to study the effectiveness of
partitioning the overall genetic correlation between two traits into a
component due to many genes of small effect, and one due to the
QTL. It is shown that when the QTL has a pleiotropic effect on two
traits, a bivariate analysis leads to a higher statistical power of
detecting the QTL and to a more precise estimate of the QTL's map
position, in particular in the case when the QTL has a small effect on
the trait. The increase in power is most marked in cases where the
contributions of the QTL and of the polygenic components to the
genetic correlation have opposite signs. The bivariate REML analysis
can successfully partition the two components contributing to the
genetic correlation between traits.
Key words: multivariate / QTL mapping / livestock
Correspondence and reprints: Peter Sørensen pso@genetics.agrsci.dk
© INRA, EDP Sciences 2003