Haplotype fine mapping by evolutionary trees

To refine the location of a disease gene within the bounds provided by link age analysis, many scientists use the pattern of linkage disequilibrium bet ween the disease allele and alleles at nearby markers. We describe a method that seeks to refine location by analysis of "disease" and "normal" haplot ypes, thereby using multivariate information about linkage disequilibrium. Under the assumption that the disease mutation occurs in a specific gap bet ween adjacent markers, the method first combines parsimony and likelihood t o build an evolutionary tree of disease haplotypes, with each node (haploty pe) separated, by a single mutational or recombinational step, from its par ent. If required, latent nodes (unobserved haplotypes) are incorporated to complete the tree. Once the tree is built, its likelihood is computed from probabilities of mutation and recombination. When each gap between adjacent markers is evaluated in this fashion and these results are combined with p rior information, they yield a posterior probability distribution to guide the search for the disease mutation. We show, by evolutionary simulations, that an implementation of these methods, called "FineMap," yields substanti al refinement and excellent coverage for the true location of the disease m utation. Moreover, by analysis of hereditary hemochromatosis haplotypes, we show that FineMap can be robust to genetic heterogeneity.