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    Proc Natl Acad Sci U S A. 2006 Apr 18;103(16):6368-73. Epub 2006 Apr 17.

    Toward understanding the genetics of alcohol drinking through transcriptome meta-analysis.

    Source

    Waggoner Center for Alcohol and Addiction Research and Sections of Neurobiology, University of Texas, Austin, TX 78712, USA.

    Abstract

    Much evidence from studies in humans and animals supports the hypothesis that alcohol addiction is a complex disease with both hereditary and environmental influences. Molecular determinants of excessive alcohol consumption are difficult to study in humans. However, several rodent models show a high or low degree of alcohol preference, which provides a unique opportunity to approach the molecular complexities underlying the genetic predisposition to drink alcohol. Microarray analyses of brain gene expression in three selected lines, and six isogenic strains of mice known to differ markedly in voluntary alcohol consumption provided >4.5 million data points for a meta-analysis. A total of 107 arrays were obtained and arranged into six experimental data sets, allowing the identification of 3,800 unique genes significantly and consistently changed between all models of high or low amounts of alcohol consumption. Several functional groups, including mitogen-activated protein kinase signaling and transcription regulation pathways, were found to be significantly overrepresented and may play an important role in establishing a high level of voluntary alcohol drinking in these mouse models. Data from the general meta-analysis was further filtered by a congenic strain microarray set, from which cis-regulated candidate genes for an alcohol preference quantitative trait locus on chromosome 9 were identified: Arhgef12, Carm1, Cryab, Cox5a, Dlat, Fxyd6, Limd1, Nicn1, Nmnat3, Pknox2, Rbp1, Sc5d, Scn4b, Tcf12, Vps11, and Zfp291 and four ESTs. The present study demonstrates the use of (i) a microarray meta-analysis to analyze a behavioral phenotype (in this case, alcohol preference) and (ii) a congenic strain for identification of cis regulation.

    PMID:
    16618939
    [PubMed - indexed for MEDLINE]
    PMCID:
    PMC1458884
    Free PMC Article

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