Mapping epistatic quantitative trait loci

Abstract

Background: How to map quantitative trait loci (QTL) with epistasis efficiently and reliably has been a persistentproblem for QTL mapping analysis. There are a number of difficulties for studying epistatic QTL. Linkage can impose asignificant challenge for finding epistatic QTL reliably. If multiple QTL are in linkage and have interactions, searchingfor QTL can become a very delicate issue. A commonly used strategy that performs a two-dimensional genome scanto search for a pair of QTL with epistasis can suffer from low statistical power and also may lead to false identificationdue to complex linkage disequilibrium and interaction patterns.Results: To tackle the problem of complex interaction of multiple QTL with linkage, we developed a three-stagesearch strategy. In the first stage, main effect QTL are searched and mapped. In the second stage, epistatic QTL thatinteract significantly with other identified QTL are searched. In the third stage, new epistatic QTL are searched in pairs.This strategy is based on the consideration that most genetic variance is due to the main effects of QTL. Thus by firstmapping those main-effect QTL, the statistical power for the second and third stages of analysis for mapping epistaticQTL can be maximized. The search for main effect QTL is robust and does not bias the search for epistatic QTL due to agenetic property associated with the orthogonal genetic model that the additive and additive by additive variancesare independent despite of linkage. The model search criterion is empirically and dynamically evaluated by using ascore-statistic based resampling procedure. We demonstrate through simulations that the method has good powerand low false positive in the identification of QTL and epistasis.Conclusion: This method provides an effective and powerful solution to map multiple QTL with complex epistaticpattern. The method has been implemented in the user-friendly computer software Windows QTL Cartographer. Thiswill greatly facilitate the application of the method for QTL mapping data analysis.