Free Access
Genet. Sel. Evol.
Volume 37, Number 1, January-February 2005
Page(s) 83 - 103
Genet. Sel. Evol. 37 (2005) 83-103
DOI: 10.1051/gse:2004037

Use of the EM algorithm to detect QTL affecting multiple-traits in an across half-sib family analysis

R.J. Kerra, G.M. McLachlanb and J.M. Henshallc

a  Animal Genetics and Breeding Unit, University of New England, Armidale 2351, Australia
b  Department of Mathematics, University of Queensland, Brisbane 4072, Australia
c  CSIRO Division of Livestock Industries, Australia

(Received 30 October 2003; accepted 17 August 2004 )

Abstract - QTL detection experiments in livestock species commonly use the half-sib design. Each male is mated to a number of females, each female producing a limited number of progeny. Analysis consists of attempting to detect associations between phenotype and genotype measured on the progeny. When family sizes are limiting experimenters may wish to incorporate as much information as possible into a single analysis. However, combining information across sires is problematic because of incomplete linkage disequilibrium between the markers and the QTL in the population. This study describes formulæ for obtaining MLEs via the expectation maximization (EM) algorithm for use in a multiple-trait, multiple-family analysis. A model specifying a QTL with only two alleles, and a common within sire error variance is assumed. Compared to single-family analyses, power can be improved up to fourfold with multi-family analyses. The accuracy and precision of QTL location estimates are also substantially improved. With small family sizes, the multi-family, multi-trait analyses reduce substantially, but not totally remove, biases in QTL effect estimates. In situations where multiple QTL alleles are segregating the multi-family analysis will average out the effects of the different QTL alleles.

Key words: QTL / EM algorithm / interval mapping / half-sib families

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© INRA, EDP Sciences 2004