Disequilibrium likelihoods for fine-scale mapping of a rare allele

Genetic linkage studies based on pedigree data have lim-ited resolution, because of the relatively small number of segregations. Disequilibrium mapping, which uses population associations to infer the location of a disease mutation, provides one possible strategy for narrowing the candidate region. The coalescent process provides a model for the ancestry of a sample of disease alleles, and recombination events between disease locus and marker may be placed on this ancestral phylogeny. These events define the recombinant classes, the sets of sampled dis-ease copies descending from the meiosis at which a given recombination occurred. We show how Monte Carlo generation of the recombinant classes leads to a linkage likelihood for fine-scale mapping from disease haplo-types. We compare single-marker disequilibrium map-ping with interval-disequilibrium mapping and discuss how the approach may be extended to multipoint-dis-equilibrium mapping. The method and its properties are illustrated with an example of simulated data, con-structed to be typical of fine-scale mapping of a rare disease in the Japanese population. The method can take into account known features of population history, such as changing patterns of population growth