TY  - JOUR
A1  - Bennett, Brian J.
A1  - Farber, Charles R.
A1  - Orozco, Luz
A1  - Min Kang, Hyun
A1  - Ghazalpour, Anatole
A1  - Siemers, Nathan
A1  - Neubauer, Michael
A1  - Neuhaus, Isaac
A1  - Yordanova, Roumyana
A1  - Guan, Bo
A1  - Truong, Amy
A1  - Yang, Wen-pin
A1  - He, Aiqing
A1  - Kayne, Paul
A1  - Gargalovic, Peter
A1  - Kirchgessner, Todd
A1  - Pan, Calvin
A1  - Castellani, Lawrence W.
A1  - Kostem, Emrah
A1  - Furlotte, Nicholas
A1  - Drake, Thomas A.
A1  - Eskin, Eleazar
A1  - Lusis, Aldons J.
T1  - A high-resolution association mapping panel for the dissection of complex traits in mice
Y1  - 2010/02/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 281 
EP  - 290 
DO  - 10.1101/gr.099234.109 
VL  - 20 
IS  - 2 
UR  - http://genome.cshlp.org/content/20/2/281.abstract 
N2  - 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. 
ER  -