Cargando…

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

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Dunn, Gerald, Hinrichs, Anthony L, Bertelsen, Sarah, Jin, Carol H, Kauwe, John SK, Suarez, Brian K, Bierut, Laura J
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866815/
https://www.ncbi.nlm.nih.gov/pubmed/16451580
http://dx.doi.org/10.1186/1471-2156-6-S1-S122
_version_ 1782133336181833728
author Dunn, Gerald
Hinrichs, Anthony L
Bertelsen, Sarah
Jin, Carol H
Kauwe, John SK
Suarez, Brian K
Bierut, Laura J
author_facet Dunn, Gerald
Hinrichs, Anthony L
Bertelsen, Sarah
Jin, Carol H
Kauwe, John SK
Suarez, Brian K
Bierut, Laura J
author_sort Dunn, Gerald
collection PubMed
description 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.
format Text
id pubmed-1866815
institution National Center for Biotechnology Information
language English
publishDate 2005
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-18668152007-05-11 Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures Dunn, Gerald Hinrichs, Anthony L Bertelsen, Sarah Jin, Carol H Kauwe, John SK Suarez, Brian K Bierut, Laura J BMC Genet Proceedings 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. BioMed Central 2005-12-30 /pmc/articles/PMC1866815/ /pubmed/16451580 http://dx.doi.org/10.1186/1471-2156-6-S1-S122 Text en Copyright © 2005 Dunn et al; licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Dunn, Gerald
Hinrichs, Anthony L
Bertelsen, Sarah
Jin, Carol H
Kauwe, John SK
Suarez, Brian K
Bierut, Laura J
Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
title Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
title_full Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
title_fullStr Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
title_full_unstemmed Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
title_short Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
title_sort microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1866815/
https://www.ncbi.nlm.nih.gov/pubmed/16451580
http://dx.doi.org/10.1186/1471-2156-6-S1-S122
work_keys_str_mv AT dunngerald microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures
AT hinrichsanthonyl microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures
AT bertelsensarah microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures
AT jincarolh microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures
AT kauwejohnsk microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures
AT suarezbriank microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures
AT bierutlauraj microsatellitesversussinglenucleotidepolymorphismsinlinkageanalysisforquantitativeandqualitativemeasures