The effective size of the Icelandic population and the prospects for LD mapping: inference from unphased microsatellite markers

Eur J Hum Genet. 2006 Sep;14(9):1044-53. doi: 10.1038/sj.ejhg.5201669. Epub 2006 May 31.


Characterizing the extent of linkage disequilibrium (LD) in the genome is a pre-requisite for association mapping studies. Patterns of LD also contain information about the past demography of populations. In this study, we focus on the Icelandic population where LD was investigated in 12 regions of approximately 15 cM using regularly spaced microsatellite loci displaying high heterozygosity. A total of 1753 individuals were genotyped for 179 markers. LD was estimated using a composite disequilibrium measure based on unphased data. LD decreases with distance in all 12 regions and more LD than expected by chance can be detected over approximately 4 cM in our sample. Differences in the patterns of decrease of LD with distance among genomic regions were mostly due to two regions exhibiting, respectively, higher and lower proportions of pairs in LD than average within the first 4 cM. We pooled data from all regions, except these two and summarized patterns of LD by computing the proportion of pairs of loci exhibiting significant LD (at the 5% level) as a function of distance. We compared observed patterns of LD with simulated data sets obtained under scenarios with varying demography and intensity of recombination. We show that unphased data allow to make inferences on scaled recombination rates from patterns of LD. Patterns of LD in Iceland suggest a genome-wide scaled recombination rate of rho* = 200 (130-330) per cM (or an effective size of roughly 5000), in the low range of estimates recently reported in three populations from the HapMap project.

MeSH terms

  • Biological Evolution
  • Female
  • Genetics, Population*
  • Human Genome Project
  • Humans
  • Iceland
  • Linkage Disequilibrium*
  • Male
  • Microsatellite Repeats*
  • Polymorphism, Single Nucleotide
  • Population Density
  • Recombination, Genetic