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    Hum Genet. 2007 May;121(3-4):305-17. Epub 2007 Feb 27.

    Candidate SNPs for a universal individual identification panel.

    Source

    Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA.

    Abstract

    Single nucleotide polymorphisms (SNPs) are likely in the near future to have a fundamental role both in human identification and description. However, because allele frequencies can vary greatly among populations, a critical issue is the population genetics underlying calculation of the probabilities of unrelated individuals having identical multi-locus genotypes. Here we report on progress in identifying SNPs that show little allele frequency variation among a worldwide sample of 40 populations, i.e., have a low F(st), while remaining highly informative. Such markers have match probabilities that are nearly uniform irrespective of population and become candidates for a universally applicable individual identification panel applicable in forensics and paternity testing. They are also immediately useful for efficient sample identification/tagging in large biomedical, association, and epidemiologic studies. Using our previously described strategy for both identifying and characterizing such SNPs (Kidd et al. in Forensic Sci Int 164:20-32, 2006), we have now screened a total of 432 SNPs likely a priori to have high heterozygosity and low allele frequency variation and from these have selected the markers with the lowest F(st) in our set of 40 populations to produce a panel of 40 low F(st), high heterozygosity SNPs. Collectively these SNPs give average match probabilities of less than 10(-16) in most of the 40 populations and less than 10(-14) in all but one small isolated population; the range is 2.02 x 10(-17) to 1.29 x 10(-13). These 40 SNPs constitute excellent candidates for the global forensic community to consider for a universally applicable SNP panel for human identification. The relative ease with which these markers could be identified also provides a cautionary lesson for investigations of possible balancing selection.

    PMID:
    17333283
    [PubMed - indexed for MEDLINE]

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