Patterns of linkage disequilibrium between SNPs in a sardinian population isolate and the selection of markers for association studies

Andrea Angius, Fiona C L Hyland, Ivana Persico, Nicola Pirastu, Trevor Woodage, Mario Pirastu, Francisco M. De La Vega*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Objective: In isolated populations, 'background' linkage disequilibrium (LD) has been shown to extend over large genetic distances. This and their reduced environmental and genetic heterogeneity has stimulated interest in their potential for association mapping. We compared LD unit map distances with pair-wise measurements of LD in a dense single nucleotide polymorphism (SNP) set. Methods: We genotyped 771 SNPs in an 8 Mb segment of chromosome 22 on 101 individuals from the isolated village of Talana, Sardinia, and compared with outbred European populations. Results: Heterozygosity was remarkably similar in both populations. In contrast, the extent of LD observed was quite different. The decay of LD with distance is slower in the isolate. The differences in LD map lengths suggest that useful LD extends up to three times farther in the Sardinian population; smaller differences are seen with pairwise LD metrics. While LD map length slightly decreases with average relatedness, cryptic relatedness does not explain the decrease in LD map length. Haplotypes, block boundaries, and patterns of LD are similar in both populations, suggesting a shared distribution of recombination hotspots. Conclusions: About 15% fewer haplotype tagging SNPs need to be genotyped in the isolate, and possibly 70% fewer if selecting SNPs evenly spaced on the metric LD map.

Original languageEnglish
Pages (from-to)9-22
Number of pages14
JournalHuman heredity
Volume65
Issue number1
DOIs
Publication statusPublished - Oct 2007

Keywords / Materials (for Non-textual outputs)

  • Founder population
  • Haplotype
  • Isolated population
  • LDU
  • Linkage disequilibrium
  • Population isolate
  • Tagging SNPs

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