A systematic approach to mapping recessive disease genes in individuals from outbred populations.


Journal Article

The identification of recessive disease-causing genes by homozygosity mapping is often restricted by lack of suitable consanguineous families. To overcome these limitations, we apply homozygosity mapping to single affected individuals from outbred populations. In 72 individuals of 54 kindred ascertained worldwide with known homozygous mutations in 13 different recessive disease genes, we performed total genome homozygosity mapping using 250,000 SNP arrays. Likelihood ratio Z-scores (ZLR) were plotted across the genome to detect ZLR peaks that reflect segments of homozygosity by descent, which may harbor the mutated gene. In 93% of cases, the causative gene was positioned within a consistent ZLR peak of homozygosity. The number of peaks reflected the degree of inbreeding. We demonstrate that disease-causing homozygous mutations can be detected in single cases from outbred populations within a single ZLR peak of homozygosity as short as 2 Mb, containing an average of only 16 candidate genes. As many specialty clinics have access to cohorts of individuals from outbred populations, and as our approach will result in smaller genetic candidate regions, the new strategy of homozygosity mapping in single outbred individuals will strongly accelerate the discovery of novel recessive disease genes.

Full Text

Cited Authors

  • Hildebrandt, F; Heeringa, SF; Rüschendorf, F; Attanasio, M; Nürnberg, G; Becker, C; Seelow, D; Huebner, N; Chernin, G; Vlangos, CN; Zhou, W; O'Toole, JF; Hoskins, BE; Wolf, MTF; Hinkes, BG; Chaib, H; Ashraf, S; Schoeb, DS; Ovunc, B; Allen, SJ; Vega-Warner, V; Wise, E; Harville, HM; Lyons, RH; Washburn, J; Macdonald, J; Nürnberg, P; Otto, EA

Published Date

  • January 23, 2009

Published In

Volume / Issue

  • 5 / 1

Start / End Page

  • e1000353 -

PubMed ID

  • 19165332

Pubmed Central ID

  • 19165332

Electronic International Standard Serial Number (EISSN)

  • 1553-7404

International Standard Serial Number (ISSN)

  • 1553-7390

Digital Object Identifier (DOI)

  • 10.1371/journal.pgen.1000353


  • eng