A high-resolution association mapping panel for the dissection of complex traits in mice

被引：251

作者：

Bennett, Brian J. ^{[1
]}

Farber, Charles R. ^{[2
,3
]}

Orozco, Luz ^{[1
]}

Kang, Hyun Min ^{[4
]}

Ghazalpour, Anatole ^{[1
]}

Siemers, Nathan ^{[5
]}

Neubauer, Michael ^{[5
]}

Neuhaus, Isaac ^{[5
]}

Yordanova, Roumyana ^{[5
]}

Guan, Bo ^{[5
]}

Truong, Amy ^{[5
]}

Yang, Wen-pin ^{[5
]}

He, Aiqing ^{[5
]}

Kayne, Paul ^{[5
]}

Gargalovic, Peter ^{[6
]}

Kirchgessner, Todd ^{[6
]}

Pan, Calvin ^{[7
]}

Castellani, Lawrence W. ^{[1
]}

Kostem, Emrah ^{[8
]}

Furlotte, Nicholas ^{[8
]}

Drake, Thomas A. ^{[9
]}

Eskin, Eleazar ^{[7
,8
]}

Lusis, Aldons J. ^{[1
,7
,10
]}

机构：

[1] Univ Calif Los Angeles, David Geffen Sch Med, Dept Med, Div Cardiol, Los Angeles, CA 90095 USA

[2] Univ Virginia, Dept Med, Dept Biochem & Mol Genet, Charlottesville, VA 22908 USA

[3] Univ Virginia, Ctr Publ Hlth Genom, Charlottesville, VA 22908 USA

[4] Univ Calif San Diego, La Jolla, CA 92093 USA

[5] Bristol Myers Squibb Co, Dept Appl Genom, Princeton, NJ 08543 USA

[6] Bristol Myers Squibb Co, Dept Atherosclerosis Drug Discovery, Princeton, NJ 08543 USA

[7] Univ Calif Los Angeles, David Geffen Sch Med, Dept Human Genet, Los Angeles, CA 90095 USA

[8] Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90095 USA

[9] Univ Calif Los Angeles, David Geffen Sch Med, Dept Pathol & Lab Med, Los Angeles, CA 90095 USA

[10] Univ Calif Los Angeles, Dept Microbiol Mol Genet & Immunol, Los Angeles, CA 90095 USA

来源：

GENOME RESEARCH | 2010年 / 20卷 / 02期

基金：

美国国家科学基金会;

关键词：

GENE-EXPRESSION; IN-SILICO; GENOMEWIDE ASSOCIATION; LIPOPROTEIN METABOLISM; COLLABORATIVE CROSS; HDL CHOLESTEROL; MOUSE; LINKAGE; POWER; LOCI;

D O I：

10.1101/gr.099234.109

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

070307 [化学生物学]; 071010 [生物化学与分子生物学];

摘要：

Systems genetics relies on common genetic variants to elucidate biologic networks contributing to complex disease-related phenotypes. Mice are ideal model organisms for such approaches, but linkage analysis has been only modestly successful due to low mapping resolution. Association analysis in mice has the potential of much better resolution, but it is confounded by population structure and inadequate power to map traits that explain less than 10% of the variance, typical of mouse quantitative trait loci (QTL). We report a novel strategy for association mapping that combines classic inbred strains for mapping resolution and recombinant inbred strains for mapping power. Using a mixed model algorithm to correct for population structure, we validate the approach by mapping over 2500 cis-expression QTL with a resolution an order of magnitude narrower than traditional QTL analysis. We also report the fine mapping of metabolic traits such as plasma lipids. This resource, termed the Hybrid Mouse Diversity Panel, makes possible the integration of multiple data sets and should prove useful for systems-based approaches to complex traits and studies of gene-by-environment interactions.

引用

页码：281 / 290

页数：10

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