Abstract
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. Hum Mutat 32:345–353, 2011. © 2011 Wiley-Liss, Inc.
Highlights
Autosomal recessive mutations are involved in Mendelian diseases and probably a small proportion of cases of complex diseases
The HF2 for this region was calculated as described in Materials and Methods and the P-value for this parameter was estimated according to the null distribution derived from the best regions in the control individuals
The results clearly demonstrated the superiority of HF2 in evaluating regions derived from recent common ancestry compared to evaluations based on physical size of the homozygous regions
Summary
Autosomal recessive mutations are involved in Mendelian diseases and probably a small proportion of cases of complex diseases. Detecting such mutations holds much promise in improving our understanding of disease mechanism and gene function. The power of detection is lower for recessive mutations in most situations compared to autosomal dominant ones, because usually the number of affected is small in a family. The relationship between parents can be remote and unknown, and the common ancestor is untraceable. Detection of such regions of recent common ancestry requires development of novel methods
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