Genomic haplotype blocks may not accurately reflect spatial variation in historic recombination intensity

Koen J F Verhoeven, Katy L Simonsen

Research output: Contribution to journal/periodicalArticleScientificpeer-review

8 Citations (Scopus)

Abstract

Recently, genomic data have revealed a "block-like" structure of haplotype diversity on human chromosomes. This structure is anticipated to facilitate gene mapping studies, because strong associations among loci within a block may allow haplotype variation to be tagged with a limited number of markers. But its usefulness to mapping efforts depends on the consistency of the block structure within and among populations, which in turn depends on how the block structure arises. Recombination hot spots are generally thought to underlie the block structure, but haplotype blocks can also develop stochastically under random recombination, in which case the block structure will show limited consistency among populations. Using coalescent models, which we upscaled to simulate the evolution of haplotypes with many markers at fixed distances, we show that the relationship between block boundaries and historic recombination intensity may be surprisingly weak. The majority of historic recombinations do not leave a footprint in present-day linkage disequilibrium patterns, and the block structure is sensitive to factors that affect the timing of recombination relative to marker mutation events in the genealogy, such as marker frequency bias and historic population size changes. Our results give insight into the potential of stochastic events to affect haplotype block structure, which can limit the usefulness of the block structure to mapping studies.

Original languageEnglish
Pages (from-to)735-40
Number of pages6
JournalMolecular Biology and Evolution
Volume22
Issue number3
DOIs
Publication statusPublished - Mar 2005
Externally publishedYes

Keywords

  • Animals
  • Genetic Variation
  • Haplotypes
  • Humans
  • Linkage Disequilibrium
  • Models, Genetic
  • Recombination, Genetic

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