Genetics, Vol. 177, 2361-2377, December 2007, Copyright © 2007
doi:10.1534/genetics.107.081299

Mapping Quantitative Trait Loci From a Single-Tail Sample of the Phenotype Distribution Including Survival Data

Mikko J. Sillanpää*,1 and Fabian Hoti*,{dagger}

* Department of Mathematics and Statistics, University of Helsinki, FIN-00014 Helsinki, Finland and {dagger} National Public Health Institute, Department of Vaccines, FIN-00300 Helsinki, Finland

1 Corresponding author: Department of Mathematics and Statistics, P.O. Box 68, University of Helsinki, FIN-00014 Helsinki, Finland.
E-mail: mjs{at}rolf.helsinki.fi

A new effective Bayesian quantitative trait locus (QTL) mapping approach for the analysis of single-tail selected samples of the phenotype distribution is presented. The approach extends the affected-only tests to single-tail sampling with quantitative traits such as the log-normal survival time or censored/selected traits. A great benefit of the approach is that it enables the utilization of multiple-QTL models, is easy to incorporate into different data designs (experimental and outbred populations), and can potentially be extended to epistatic models. In inbred lines, the method exploits the fact that the parental mating type and the linkage phases (haplotypes) are known by definition. In outbred populations, two-generation data are needed, for example, selected offspring and one of the parents (the sires) in breeding material. The idea is to statistically (computationally) generate a fully complementary, maximally dissimilar, observation for each offspring in the sample. Bayesian data augmentation is then used to sample the space of possible trait values for the pseudoobservations. The benefits of the approach are illustrated using simulated data sets and a real data set on the survival of F2 mice following infection with Listeria monocytogenes.