Mapping interacting QTL for count phenotypes using hierarchical Poisson and binomial models: an application to reproductive traits in mice

Abstract

SummaryWe proposed hierarchical Poisson and binomial models for mapping multiple interacting quantitative trait loci (QTLs) for count traits in experimental crosses. We applied our methods to two counted reproductive traits, live fetuses (LF) and dead fetuses (DF) at 17 days gestation, in an F2female mouse population. We treated observed number ofcorpora lutea(ovulation rate) as the baseline and the total trials in our Poisson and binomial models, respectively. We detected more than 10 QTLs forLFandDF, most having epistatic and pleiotropic effects. The epistatic effects were larger, involved more QTLs, and explained a larger proportion of phenotypic variance than the main effects. Our analyses revealed a complex network of multiple interacting QTLs for the reproductive traits, and increase our understanding of the genetic architecture of reproductive characters. The proposed statistical models and methods provide valuable tools for detecting multiple interacting QTLs for complex count phenotypes.