The interval of linkage disequilibrium (LD) detected with microsatellite and SNP markers in chromosomes of Finnish populations with different histories. Varilo, T., Paunio, T., Parker, A., Perola, M., Meyer, J., Terwilliger, J., D., & Peltonen, L. Hum Mol Genet, 12(1):51-59, 2003.
The interval of linkage disequilibrium (LD) detected with microsatellite and SNP markers in chromosomes of Finnish populations with different histories [pdf]Paper  abstract   bibtex   
Linkage disequilibrium (LD) has been an efficient tool for fine mapping of monogenic disease genes in population isolates. Its usefulness for identification of predisposing loci for common, polygenic diseases has been challenged on the basis of anticipated allelic and locus heterogeneity. We compared the extent of LD among marker loci in Finnish subpopulations with divergent but well-characterized histories. One study sample represents the early settlement Finnish population, descended from two immigration events 4,000 and 2,000 years ago. The second sample represents the geographically large late settlement region, populated 15 generations ago by several small immigrant groups from the early settlement region. The third is a restricted regional subpopulation in northeastern Finland which was founded 12 generations ago by 39 immigrant families from the late settlement region. We genotyped 243 microsatellite markers and 68 single nucleotide polymorphisms (SNPs) on chromosomes 1q and 5q. The genealogy of the families from the early (n=16) and late settlements (n=54) and the isolated settlement (n=54) was studied in detail back to the 1800s. Microsatellite data revealed greater LD in the young, founder subpopulation than was seen in either of the older populations. Observed linkage disequilibrium correlated not only with physical distance between markers but also with the information content of the markers. Using biallelic SNP markers, significant LD could only be detected up to 0.1 cM. Our results demonstrate the complexity of the concept of 'detectable LD' and emphasize the importance of understanding population history when designing a strategy for disease gene mapping.

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