Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures

Gerald Dunn, Anthony L. Hinrichs, Sarah Bertelsen, Carol H. Jin, John S.K. Kauwe, Brian K. Suarez, Laura J. Bierut

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Background: Genetic maps based on single-nucleotide polymorphisms (SNP) are increasingly being used as an alternative to microsatellite maps. This study compares linkage results for both types of maps for a neurophysiology phenotype and for an alcohol dependence phenotype. Our analysis used two SNP maps on the Illumina and Affymetrix platforms. We also considered the effect of high linkage disequilibrium (LD) in regions near the linkage peaks by analysing a "sparse" SNP map obtained by dropping some markers in high LD with other markers in those regions. Results: The neurophysiology phenotype at the main linkage peak near 130 MB gave LOD scores of 2.76, 2.53, 3.22, and 2.68 for the microsatellite, Affymetrix, Illumina, and Illumina-sparse maps, respectively. The alcohol dependence phenotype at the main linkage peak near 101 MB gave LOD scores of 3.09, 3.69, 4.08, and 4.11 for the microsatellite, Affymetrix, Illumina, and Illumina-sparse maps, respectively. Conclusion: The linkage results were stronger overall for SNPs than for microsatellites for both phenotypes. However, LOD scores may be artificially elevated in regions of high LD. Our analysis indicates that appropriately thinning a SNP map in regions of high LD should give more accurate LOD scores. These results suggest that SNPs can be an efficient substitute for microsatellites for linkage analysis of both quantitative and qualitative phenotypes.

Original languageEnglish
Article numberS122
JournalBMC genetics
Volume6
Issue numberSUPPL.1
DOIs
StatePublished - Dec 30 2005

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