Genomewide association analysis in diverse inbred mice: Power and population structure

Phillip McClurg, Jeff Janes, Chunlei Wu, David L. Delano, John R. Walker, Serge Batalov, Joseph S. Takahashi, Kazuhiro Shimomura, Akira Kohsaka, Joseph Bass, Tim Wiltshire, Andrew I. Su*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

66 Scopus citations


The discovery of quantitative trait loci (QTL) in model organisms has relied heavily on the ability to perform controlled breeding to generate genotypic and phenotypic diversity. Recently, we and others have demonstrated the use of an existing set of diverse inbred mice (referred to here as the mouse diversity panel, MDP) as a QTL mapping population. The use of the MDP population has many advantages relative to traditional F2 mapping populations, including increased phenotypic diversity, a higher recombination frequency, and the ability to collect genotype and phenotype data in community databases. However, these methods are complicated by population structure inherent in the MDP and the lack of an analytical framework to assess statistical power. To address these issues, we measured gene expression levels in hypothalamus across the MDP. We then mapped these phenotypes as quantitative traits with our association algorithm, resulting in a large set of expression QTL (eQTL). We utilized these eQTL, and specifically cis-eQTL, to develop a novel nonparametric method for association analysis in structured populations like the MDP. These eQTL data confirmed that the MDP is a suitable mapping population for QTL discovery and that eQTL results can serve as a gold standard for relative measures of statistical power.

Original languageEnglish (US)
Pages (from-to)675-683
Number of pages9
Issue number1
StatePublished - May 2007

ASJC Scopus subject areas

  • General Medicine


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