RT Journal
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
JF Genome Research 
JO Genome Research 
YR 2010 
FD February 01 
VO 20 
IS 2 
SP 281 
OP 290 
DO 10.1101/gr.099234.109 
UL http://genome.cshlp.org/content/20/2/281.abstract 
AB 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.