Runs of Homozygosity in European Populations

  • McQuillan R
  • Leutenegger A
  • Abdel-Rahman R
 et al. 
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Abstract

Estimating individual genome-wide autozygosity is important both in the identification of recessive disease variants via homozygosity mapping and in the investigation of the effects of genome-wide homozygosity on traits of biomedical importance. Approaches have tended to involve either single-point estimates or rather complex multipoint methods of inferring individual autozygosity, all on the basis of limited marker data. Now, with the availability of high-density genome scans, a multipoint, observational method of estimating individual autozygosity is possible. Using data from a 300,000 SNP panel in 2618 individuals from two isolated and two more-cosmopolitan populations of European origin, we explore the potential of estimating individual autozygosity from data on runs of homozygosity (ROHs). Termed Froh, this is defined as the proportion of the autosomal genome in runs of homozygosity above a specified length. Mean Frohdistinguishes clearly between subpopulations classified in terms of grandparental endogamy and population size. With the use of good pedigree data for one of the populations (Orkney), Frohwas found to correlate strongly with the inbreeding coefficient estimated from pedigrees (r = 0.86). Using pedigrees to identify individuals with no shared maternal and paternal ancestors in five, and probably at least ten, generations, we show that ROHs measuring up to 4 Mb are common in demonstrably outbred individuals. Given the stochastic variation in ROH number, length, and location and the fact that ROHs are important whether ancient or recent in origin, approaches such as this will provide a more useful description of genomic autozygosity than has hitherto been possible. © 2008 The American Society of Human Genetics.

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Authors

  • Anne-Louise LeuteneggerInstitut national de la santé et de la recherche médicale, Genetic Variation and Human Diseases Lab (U946)

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  • Ruth McQuillan

  • Rehab Abdel-Rahman

  • Christopher S. Franklin

  • Marijana Pericic

  • Lovorka Barac-Lauc

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