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Genetics. 2014 Aug;197(4):1377-93. doi: 10.1534/genetics.114.166165. Epub 2014 Jun 11.

Identification of a QTL in Mus musculus for alcohol preference, withdrawal, and Ap3m2 expression using integrative functional genomics and precision genetics.

Author information

  • 1The Jackson Laboratory, Bar Harbor, Maine 04609.
  • 2South Plains Alcohol and Addiction Research Center, Texas Tech University Health Sciences Center Lubbock, Texas 79430-6592.
  • 3RIKEN Center for Integrative Medical Sciences (IMS), Yokohama, Kanagawa 230-0045, Japan.
  • 4Portland Alcohol Research Center, Department of Behavioral Neuroscience, Oregon Health & Science University and Veterans Affairs Medical Center, Portland, Oregon 97239.
  • 5The Jackson Laboratory, Bar Harbor, Maine 04609 elissa.chesler@jax.org.

Abstract

Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with >60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits.

KEYWORDS:

behavioral genetics; complex traits; data integration

PMID:
24923803
PMCID:
PMC4125407
DOI:
10.1534/genetics.114.166165
[PubMed - indexed for MEDLINE]
Free PMC Article
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