Multiple-trait mapping of quantitative trait loci after selective genotyping using logistic regression

Experiments to map QTL usually measure several traits, and not uncommonly g enotype only those animals that are extreme for some trait(s). Analysis of selectively genotyped, multiple-trait data presents special problems, and m ost simple methods lead to biased estimates of the QTL effects. The use of logistic regression to estimate QTL effects is described, where the genotyp e 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 analyis i s almost equivalent to a maximum-likelihood analysis, but can be carried ou t with standard statistical packages, Analysis of a simulated half-sib expe riment 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.