Mapping quantitative trait loci for complex binary traits in outbred populations.

Abstract

Complex binary traits have a dichotomous phenotypic expression but do not show a simple Mendelian segregation ratio. These traits are considered to be jointly controlled by the actions of several genes and a random environmental effect. The binary phenotype and the underlying factor are assumed to be linked through a threshold model. The underlying factor, referred to as the liability, is treated as a regular but unobservable quantitative character. Mapping quantitative trait loci (QTL) can be performed directly on the liability. Methods of QTL mapping for the liability of a complex binary trait have been well developed in line-crossing experiments. However, such a method is not available in outbred populations which usually consist of many independent pedigrees (families). In this study, we develop a method to analyse jointly multiple families of an outbred population. The method is developed based on a fixed-model approach, i.e. the QTL effects, rather than the variance, are estimated and tested. After the test, the estimated effects are then converted into a single estimate of the QTL variance by taking into consideration errors in the estimated effects. The QTL effects and variance-covariance matrix of the estimates are obtained by a fast Fisher-scoring method. Monte Carlo simulations show that the method is not only powerful but also generates very accurate estimates of QTL variances.