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In silico discovery of gene-coding variants in murine quantitative trait loci using strain-specific genome sequence databases

Kriste E Marshall1, Elizabeth L Godden1, Fan Yang1, Sonya Burgers1, Kari J Buck2 and James M Sikela1*

Author Affiliations

1 Department of Pharmacology and Human Medical Genetics Program, University of Colorado Health Sciences Center, Denver CO 80262, USA

2 Department of Behavioral Neuroscience and Portland Alcohol Research Center, Oregon Health & Science University and VA Medical Center, Portland, OR 97201, USA

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Genome Biology 2002, 3:research0078-research0078.9  doi:10.1186/gb-2002-3-12-research0078

Published: 27 November 2002



The identification of genes underlying complex traits has been aided by quantitative trait locus (QTL) mapping approaches, which in turn have benefited from advances in mammalian genome research. Most recently, whole-genome draft sequences and assemblies have been generated for mouse strains that have been used for a large fraction of QTL mapping studies. Here we show how such strain-specific mouse genome sequence databases can be used as part of a high-throughput pipeline for the in silico discovery of gene-coding variations within murine QTLs. As a test of this approach we focused on two QTLs on mouse chromosomes 1 and 13 that are involved in physical dependence on alcohol.


Interstrain alignment of sequences derived from the relevant mouse strain genome sequence databases for 199 QTL-localized genes spanning 210,020 base-pairs of coding sequence identified 21 genes with different coding sequences for the progenitor strains. Several of these genes, including four that exhibit strong phenotypic links to chronic alcohol withdrawal, are promising candidates to underlie these QTLs.


This approach has wide general utility, and should be applicable to any of the several hundred mouse QTLs, encompassing over 60 different complex traits, that have been identified using strains for which relatively complete genome sequences are available.