Computation of identity by descent probabilities conditional on DNA markers via a Monte Carlo Markov Chain method

The accurate estimation of the probability of identity by descent (IBD) at loci or genome positions of interest is paramount to the genetic study of q uantitative and disease resistance traits. We present a Monte Carlo Markov Chain method to compute IBD probabilities between individuals conditional o n DNA markers and on pedigree information. The IBDs can be obtained in a co mpletely general pedigree at any genome position of interest, and all marke r and pedigree information available is used. The method can be split into two steps at each iteration. First, phases are sampled using current genoty pic configurations of relatives and second, crossover events are simulated conditional on phases. Internal track is kept of all founder origins and cr ossovers such that the IBD probabilities averaged over replicates are rapid ly obtained. We illustrate the method with some examples. First, we show th at all pedigree information should be used to obtain line origin probabilit ies in F2 crosses. Second, the distribution of genetic relationships betwee n half and full sibs is analysed in both simulated data and in real data fr om an F2 cross in pigs.