OBJECTIVE: The purpose of this study was to fine map previously identified quantitative trait loci affecting atherosclerosis in mice using association analysis. METHODS AND RESULTS: We recently showed that high-resolution association analysis using common inbred strains of mice is feasible if corrected for population structure. To use this approach for atherosclerosis, which requires a sensitizing mutation, we bred human apolipoprotein B-100 transgenic mice with 22 different inbred strains to produce F1 heterozygotes. Mice carrying the dominant transgene were tested for association with high-density single nucleotide polymorphism maps. Here, we focus on high-resolution mapping of the previously described atherosclerosis 30 locus on chromosome 1. Compared with the previous linkage analysis, association improved the resolution of the atherosclerosis 30 locus by more than an order of magnitude. Using expression quantitative trait locus analysis, we identified one of the genes in the region, desmin, as a strong candidate. CONCLUSIONS: Our high-resolution mapping approach accurately identifies and fine maps known atherosclerosis quantitative trait loci. These results suggest that high-resolution genome-wide association analysis for atherosclerosis is feasible in mice.
OBJECTIVE: The purpose of this study was to fine map previously identified quantitative trait loci affecting atherosclerosis in mice using association analysis. METHODS AND RESULTS: We recently showed that high-resolution association analysis using common inbred strains of mice is feasible if corrected for population structure. To use this approach for atherosclerosis, which requires a sensitizing mutation, we bred humanapolipoprotein B-100transgenic mice with 22 different inbred strains to produce F1 heterozygotes. Mice carrying the dominant transgene were tested for association with high-density single nucleotide polymorphism maps. Here, we focus on high-resolution mapping of the previously described atherosclerosis 30 locus on chromosome 1. Compared with the previous linkage analysis, association improved the resolution of the atherosclerosis 30 locus by more than an order of magnitude. Using expression quantitative trait locus analysis, we identified one of the genes in the region, desmin, as a strong candidate. CONCLUSIONS: Our high-resolution mapping approach accurately identifies and fine maps known atherosclerosis quantitative trait loci. These results suggest that high-resolution genome-wide association analysis for atherosclerosis is feasible in mice.
Authors: Hayes M Dansky; Pei Shu; M Donavan; Jill Montagno; Deborah L Nagle; John S Smutko; Natalie Roy; S Whiteing; Judith Barrios; T J McBride; Jonathan D Smith; Geoffrey Duyk; Jan L Breslow; Karen J Moore Journal: Genetics Date: 2002-04 Impact factor: 4.562
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Authors: Veronica V Colinayo; Jian-Hua Qiao; Xuping Wang; Kelly L Krass; Eric Schadt; Aldons J Lusis; Thomas A Drake Journal: Mamm Genome Date: 2003-07 Impact factor: 2.957
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Authors: Jill C Gregory; Jennifer A Buffa; Elin Org; Zeneng Wang; Bruce S Levison; Weifei Zhu; Matthew A Wagner; Brian J Bennett; Lin Li; Joseph A DiDonato; Aldons J Lusis; Stanley L Hazen Journal: J Biol Chem Date: 2014-12-30 Impact factor: 5.157
Authors: Diana M Shih; Zeneng Wang; Richard Lee; Yonghong Meng; Nam Che; Sarada Charugundla; Hannah Qi; Judy Wu; Calvin Pan; J Mark Brown; Thomas Vallim; Brian J Bennett; Mark Graham; Stanley L Hazen; Aldons J Lusis Journal: J Lipid Res Date: 2014-11-06 Impact factor: 5.922
Authors: Elaine M Smolock; Dietrich E Machleder; Vyacheslav A Korshunov; Bradford C Berk Journal: Arterioscler Thromb Vasc Biol Date: 2013-02-28 Impact factor: 8.311
Authors: Brian J Bennett; Thomas Q de Aguiar Vallim; Zeneng Wang; Diana M Shih; Yonghong Meng; Jill Gregory; Hooman Allayee; Richard Lee; Mark Graham; Rosanne Crooke; Peter A Edwards; Stanley L Hazen; Aldons J Lusis Journal: Cell Metab Date: 2013-01-08 Impact factor: 27.287
Authors: Sabrina H Spiezio; Lynn M Amon; Timothy S McMillen; Cynthia M Vick; Barbara A Houston; Mark Caldwell; Kayoko Ogimoto; Gregory J Morton; Elizabeth A Kirk; Michael W Schwartz; Joseph H Nadeau; Renée C LeBoeuf Journal: Mamm Genome Date: 2014-07-08 Impact factor: 2.957