Genetics, Vol. 151, 885-894, February 1999, Copyright © 1999

Multiple-Trait Mapping of Quantitative Trait Loci After Selective Genotyping Using Logistic Regression

John M. Henshalla and Michael E. Goddarda
a Animal Genetics and Breeding Unit, University of New England, Armidale, New South Wales 2351, Australia

Corresponding author: John M. Henshall, Animal Genetics and Breeding Unit, The University of New England, Armidale, NSW 2351, Australia., jhenshal{at}metz.une.edu.au (E-mail)

Communicating editor: C. HALEY

Experiments to map QTL usually measure several traits, and not uncommonly genotype only those animals that are extreme for some trait(s). Analysis of selectively genotyped, multiple-trait data presents special problems, and most simple methods lead to biased estimates of the QTL effects. The use of logistic regression to estimate QTL effects is described, where the genotype is treated as the dependent variable and the phenotype as the independent variable. In this way selection on phenotype does not bias the results. If normally distributed errors are assumed, the logistic-regression analysis is almost equivalent to a maximum-likelihood analysis, but can be carried out with standard statistical packages. Analysis of a simulated half-sib experiment shows that logistic regression can estimate the effect and position of a QTL without bias and confirms the increased power achieved by multiple-trait analysis.




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