Assessment and implications of linkage disequilibrium in genome-wide single-nucleotide polymorphism and microsatellite panels

Authors

  • Ellen L. Goode,

    Corresponding author
    1. Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, Minnesota
    • Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN 55905
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  • Gail P. Jarvik

    1. Division of Medical Genetics, University of Washington Medical Center, and Department of Genome Sciences, University of Washington, Seattle, Washington
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Abstract

Linkage disequilibrium (LD) between markers is more likely to exist in dense genome-wide single-nucleotide polymorphism (SNP) panels than in microsatellite panels. As part of Genetic Analysis Workshop 14 (GAW14), the extent of LD in the Illumina linkage panel III and the Affymetrix Genechip® 10 K mapping array was assessed, using data from the Collaborative Study on the Genetics of Alcoholism (COGA). The impact of LD on linkage results was examined in COGA and simulated data, and characteristics of SNPs were assessed for their ability to detect population substructure and predict haplotypes. The authors of the papers summarized here observed greater LD in the Affymetrix than in the Illumina panel, possibly due to increased marker density in the Affymetrix panel, and found greater LD on chromosome X than on the autosomes. Simulation analyses suggest that intermarker LD can cause an upward bias in linkage statistics; however, the impact of LD on linkage analysis depends on the proportion of ungenotyped founders and the extent of LD. No large effect of LD on linkage peaks was observed in COGA analyses. In addition, the papers summarized here found that SNPs with high minor allele frequencies were the most informative compared with microsatellites for the detection of population substructure, and that SNPs in higher LD, and small numbers of SNPs, were the most reliable for haplotype prediction. As ease of genotyping continues to increase, study design and SNP selection for linkage and association studies (including genome-wide association studies) will be improved with consideration of LD in the particular populations studied. Genet. Epidemiol. 29(Suppl. 1):S72–S76, 2005. © 2005 Wiley-Liss, Inc.

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