Modeling linkage disequilibrium between a polymorphic marker locus and a locus affecting complex dichotomous traits in natural populations

Linkage disequilibrium is an important topic in evolutionary and population genetics. An issue yet to be settled is the theory required to extend the linkage disequilibrium analysis to complex traits. In this study, we presen t theoretical analysis and methods for detecting or estimating linkage dise quilibrium (LD) between a polymorphic marker locus and any one of the loci affecting a complex dichotomous trait on the basis of samples randomly or s electively collected from natural populations. Statistical properties of th ese methods were investigated and their powers were compared analytically o r by use of Monte Carlo simulations. The results show that the disequilibri um may be detected with a power of 80% by using phenotypic. records and mar ker genotype when both the trait and marker variants are common (30%) and t he Ll) is relatively high (40-100% of the theoretical maximum). The maximum -likelihood approach provides accurate estimates of the model parameters as well as detection of linkage disequilibrium. The likelihood method is pref erred for its higher power and reliability in parameter estimation. The app roaches developed in this article are also compared to those for analyzing a continuously distributed quantitative trait. It is shown that a larger sa mple size is required for the dichotomous trait model to obtain the same le vel of power in detecting linkage disequilibrium as the continuous trait an alysis. Potential use of these estimates in mapping the trait locus is also discussed.