Multipoint mapping of viability and segregation distorting loci using molecular markers

In line-crossing experiments, deviations from Mendelian segregation ratios are usually observed for some markers. We hypothesize that these deviations are caused by one or more segregation-distorting loci (SDL) linked to the markers. We develop both a maximum-likelihood (ML) method and a Bayesian me thod to map SDL using molecular markers. The ML mapping is implemented via an EM algorithm and the Bayesian method is performed via the Markov chain M onte Carlo (MCMC). The Bayesian mapping is computationally more intensive t han the ML mapping but can handle more complicated models such as multiple SDL and variable number of SDL. Both methods are applied to a set of simula ted data and real data from a cross of two Scots pine trees.