Detection of reciprocal quantitative trait loci for acute ethanol withdrawal and ethanol consumption in heterogeneous stock mice.
ABSTRACT Previous studies have suggested that there is an inverse genetic relationship between ethanol consumption (two-bottle choice, continuous access) and ethanol withdrawal (e.g., Metten et al., Behav Brain Res 95:113-122, 1998a).
The current study used short-term selective breeding from heterogeneous stock (HS) animals to examine this relationship. The primary goal of the current study was to determine if reciprocal quantitative trait loci (QTLs) could be found in the selectively bred lines. The advantage of detecting QTLs in HS animals is that it is possible to extract a haplotype signature for the QTL, which in turn can be used to narrow the number of candidate genes generated from gene expression and sequence databases (see, e.g., Hitzemann et al., Mamm Genome 14:733-747, 2003).
Seven reciprocal QTLs were detected on chromosomes (Chr) 1 (two), 3, 6, 11, 16, and 17 that exceeded the nominal LOD threshold of 10; genetic drift, which occurs during selection, dramatically increases the LOD threshold. The proximal Chr 1 QTL was examined in some detail. The haplotype structure of the QTL was such that the LP/J allele was associated with low withdrawal and high consumption. The QTL appears to be located in a gene-poor region between 170 and 173 Mbp. Based on available sequence data, two plausible candidate genes emerge-Nos1ap and Atf6alpha.
The data presented here confirm some aspects of the negative genetic relationship between acute ethanol withdrawal and ethanol consumption. The QTL data point to the potential involvement of NO signaling and/or the unfolded protein response.
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ABSTRACT: BACKGROUND: Heterogeneous stock (HS/NPT) mice have been used to create lines selectively bred in replicate for elevated drinking in the dark (DID). Both selected lines routinely reach a blood ethanol (EtOH) concentration (BEC) of 1.00 mg/ml or greater at the end of the 4-hour period of access in Day 2. The mechanisms through which genetic differences influence DID are currently unclear. Therefore, the current study examines the transcriptome, the first stage at which genetic variability affects neurobiology. Rather than focusing solely on differential expression (DE), we also examine changes in the ways that gene transcripts collectively interact with each other, as revealed by changes in coexpression patterns. METHODS: Naïve mice (N = 48/group) were genotyped using the Mouse Universal Genotyping Array, which provided 3,683 informative markers. Quantitative trait locus (QTL) analysis used a marker-by-marker strategy with the threshold for a significant logarithm of odds (LOD) set at 10.6. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene coexpression network analysis (WGCNA) were implemented largely as described elsewhere. RESULTS: Significant QTLs for elevated BECs after DID were detected on chromosomes 4, 14, and 16; the latter 2 were associated with gene-poor regions. None of the QTLs overlapped with known QTLs for EtOH preference drinking. Ninety-four transcripts were detected as being differentially expressed in both selected lines versus HS controls; there was no overlap with known preference genes. The WGCNA revealed 2 modules as showing significant effects of both selections on intramodular connectivity. A number of genes known to be associated with EtOH phenotypes (e.g., Gabrg1, Glra2, Grik1, Npy2r, and Nts) showed significant changes in connectivity. CONCLUSIONS: We found marked and consistent effects of selection on coexpression patterns; DE changes were more modest and less concordant. The QTLs and differentially expressed genes detected here are distinct from the preference phenotype. This is consistent with behavioral data and suggests that the DID and preference phenotypes are markedly different genetically.Alcoholism Clinical and Experimental Research 03/2013; · 3.31 Impact Factor
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ABSTRACT: The National Institute on Alcohol Abuse and Alcoholism (NIAAA) was founded 40 years ago to help elucidate the biological underpinnings of alcohol dependence, including the potential contribution of genetic factors. Twin, adoption, and family studies conclusively demonstrated that genetic factors account for 50 to 60 percent of the variance in risk for developing alcoholism. Case-control studies and linkage analyses have helped identify DNA variants that contribute to increased risk, and the NIAAA-sponsored Collaborative Studies on Genetics of Alcoholism (COGA) has the expressed goal of identifying contributing genes using state-of-the-art genetic technologies. These efforts have ascertained several genes that may contribute to an increased risk of alcoholism, including certain variants encoding alcohol-metabolizing enzymes and neurotransmitter receptors. Genome-wide association studies allowing the analysis of millions of genetic markers located throughout the genome will enable discovery of further candidate genes. In addition to these human studies, genetic animal models of alcohol's effects and alcohol use have greatly advanced our understanding of the genetic basis of alcoholism, resulting in the identification of quantitative trait loci and allowing for targeted manipulation of candidate genes. Novel research approaches-for example, into epigenetic mechanisms of gene regulation-also are under way and undoubtedly will further clarify the genetic basis of alcoholism.Alcohol research & health: the journal of the National Institute on Alcohol Abuse and Alcoholism 01/2010; 33(1):64-75. · 0.58 Impact Factor