Fine mapping and expression of candidate genes within the chromosome 10 QTL region of the high and low alcohol-drinking rats

Self Cite

The objective of this study was to detect changes in gene expression in the ventral tegmental area (VTA) following repeated excessive binge-like (‘loss-of-control’) alcohol drinking by alcohol-preferring (P) rats. Adult female P rats (n = 7) were given concurrent access to 10, 20, and 30% EtOH for 4 1-hour sessions daily for 10 weeks followed by 2 cycles of 2 weeks of abstinence and 2 weeks of EtOH access. Rats were sacrificed by decapitation 3 hours after the 4th daily EtOH-access session at the end of the second 2-week relapse period. A water-control group of female P rats (n = 8) was also sacrificed. RNA was prepared from micro-punch samples of the VTA from individual rats; analyses were conducted with Affymetrix Rat 230.2 GeneChips. Ethanol intakes were 1.2–1.7 g/kg per session, resulting in blood levels > 200 mg% at the end of the 4th session. There were 211 unique named genes that significantly differed (FDR = 0.1) between the water and EtOH groups. Bioinformatics analyses indicated alterations in a) transcription factors that reduced excitation-coupled transcription and promoted excitotoxic neuronal damage involving clusters of genes associated with Nfkbia, Fos, and Srebf1, b) genes that reduced cholesterol and fatty acid synthesis, and increased protein degradation, and c) genes involved in cell-to-cell interactions and regulation of the actin cytoskeleton. Among the named genes, there were 62 genes that showed differences between alcohol-naïve P and non-preferring (NP) rats, with 43 of the genes changing toward NP-like expression levels following excessive binge-like drinking in the P rats. These genes are involved in a pro-inflammatory response, and enhanced response to glucocorticoids and steroid hormones. Overall, the results of this study indicate that the repeated excessive binge-like alcohol drinking can change the expression of genes that may alter neuronal function in several ways, some of which may be deleterious.

“…In addition, there were no genes in common between the present study (Table 1) and the candidate genes within the chromosome 10 QTL (Bice et al, 2010). …”

Section: Discussionmentioning

confidence: 67%

Changes in gene expression within the ventral tegmental area following repeated excessive binge-like alcohol drinking by alcohol-preferring (P) rats

McBride

Kimpel

McClintick

et al. 2013

Self Cite

“…Previous studies have evaluated whether any of the specific phenotypes mapped back to the location of the differentially expressed genes in their respective group (Bice et al, 2010, 2006; Carhuatanta, Shea, Herman, & Jankord, 2014; Cook et al, 2015; Overall et al, 2009; Palmer, Lessov-Schlaggar, Ponder, McKinnon, & Phillips, 2006; Porcu et al, 2011; Urquhart et al, 2016). However, in the present study, only one phenotype mapped back to the location of a gene that was correlated with it: Cnot6l from the RSE vs. NOE group.…”

Section: Resultsmentioning

confidence: 99%

Analyses of differentially expressed genes after exposure to acute stress, acute ethanol, or a combination of both in mice

Baker

Zhou

et al. 2017

Alcohol abuse is a complex disorder, which is confounded by other factors, including stress. In the present study, we examined gene expression in the hippocampus of BXD recombinant inbred mice after exposure to ethanol (NOE), stress (RSS), and the combination of both (RSE). Mice were given an intra-peritoneal (i.p.) injection of 1.8 g/kg ethanol or saline, and subsets of both groups were exposed to acute restraint stress for 15 min or controls. Gene expression in the hippocampus was examined using microarray analysis. Genes that were significantly (p < 0.05, q < 0.1) differentially expressed were further evaluated. Bioinformatic analyses were predominantly performed using tools available at GeneNetwork. org, and included gene ontology, presence of cis-regulation or polymorphisms, phenotype correlations, and principal component analyses. Comparisons of differential gene expression between groups showed little overlap. Gene Ontology demonstrated distinct biological processes in each group with the combined exposure (RSE) being unique from either the ethanol (NOE) or stress (RSS) group, suggesting that the interaction between these variables is mediated through diverse molecular pathways. This supports the hypothesis that exposure to stress alters ethanol-induced gene expression changes and that exposure to alcohol alters stress-induced gene expression changes. Behavior was profiled in all groups following treatment, and many of the differentially expressed genes are correlated with behavioral variation within experimental groups. Interestingly, in each group several genes were correlated with the same phenotype, suggesting that these genes are the potential origins of significant genetic networks. The distinct sets of differentially expressed genes within each group provide the basis for identifying molecular networks that may aid in understanding the complex interactions between stress and ethanol, and potentially provide relevant therapeutic targets. Using Ptp4a1, a candidate gene underlying the quantitative trait locus for several of these phenotypes, and network analyses, we show that a large group of differentially expressed genes in the NOE group are highly interrelated, some of which have previously been linked to alcohol addiction or alcohol-related phenotypes.

“…Present probe sets were analyzed for enrichment in regions of established rat QTLs for alcohol consumption in P × NP (Bice et al, 1998; Carr et al, 1998, 2007; Foroud et al, 2002) and HAD × LAD replicates (Bice et al, 2010; Carr et al, 2003; Foroud et al, 2003) using the methodology of Gene Set Enrichment Analysis (GSEA) (Subramanian et al, 2005) accompanied by linear modeling (Oron et al, 2008) with the Bioconductor packages GSEABase (R package version 1.17.1) and GSEAlm (R package version 1.15.0). For the across line-pairs analysis, the same linear model was used, as described above for the ANOVA analysis, and GSEA was conducted using the statistic for the ethanol consumption phenotype factor.…”

Section: Methodsmentioning

confidence: 99%

Gene expression within the extended amygdala of 5 pairs of rat lines selectively bred for high or low ethanol consumption

McBride

Kimpel

McClintick

et al. 2013

Self Cite

The objectives of this study were to determine innate differences in gene expression in 2 regions of the extended amygdala between 5 different pairs of lines of male rats selectively bred for high or low ethanol consumption: a) alcohol-preferring (P) vs. alcohol-non-preferring (NP) rats, b) high-alcohol-drinking (HAD) vs. low-alcohol-drinking (LAD) rats (replicate line-pairs 1 and 2), c) ALKO alcohol (AA) vs. nonalcohol (ANA) rats, and d) Sardinian alcohol-preferring (sP) vs. Sardinian alcohol-nonpreferring (sNP) rats, and then to determine if these differences are common across the line-pairs. Microarray analysis revealed up to 1,772 unique named genes in the nucleus accumbens shell (AcbSh) and 494 unique named genes in the central nucleus of the amygdala (CeA) that significantly differed [False Discovery Rate (FDR) = 0.10; fold-change at least 1.2] in expression between the individual line-pairs. Analysis using Gene Ontology (GO) and Ingenuity Pathways information indicated significant categories and networks in common for up to 3 or 4 line-pairs, but not for all 5 line-pairs. However, there were almost no individual genes in common within these categories and networks. ANOVAs of the combined data for the 5 line-pairs indicated 1,014 and 731 significant (p < 0.01) differences in expression of named genes in the AcbSh and CeA, respectively. There were 4–6 individual named genes that significantly differed across up to 3 line-pairs in both regions; only 1 gene (Gsta4 in the CeA) differed in as many as 4 line-pairs. Overall, the findings suggest that a) some biological categories or networks (e.g., cell-to-cell signaling, cellular stress response, cellular organization, etc.) may be in common for subsets of line-pairs within either the AcbSh or CeA, and b) regulation of different genes and/or combinations of multiple biological systems may be contributing to the disparate alcohol drinking behaviors of these line-pairs.