Homozygosity mapping on a single patient-identification of homozygous regions of recent common ancestry by using population data

Homozygosity mapping has played an important role in detecting recessive mutations using families of consanguineous marriages. However, detection of regions identical and homozygosity by descent (HBD) when family data are not available, or when relationships are unknown, is still a challenge. Making use of population data from high-density SNP genotyping may allow detection of regions HBD from recent common founders in singleton patients without genealogy information. We report a novel algorithm that detects such regions by estimating the population haplotype frequencies (HF) for an entire homozygous region. We also developed a simulation method to evaluate the probability of HBD and linkage to disease for a homozygous region by examining the best regions in unaffected controls from the host population. The method can be applied to diseases of Mendelian inheritance but can also be extended to complex diseases to detect rare founder mutations that affect a very small number of patients using either multiplex families or sporadic cases. Testing of the method on both real cases (singleton affected) and simulated data demonstrated its superb sensitivity and robustness under genetic heterogeneity.