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Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects.

ABSTRACT: Data from C57BL/6J (B6) × DBA/2J (D2) F2 intercrosses (B6xD2 F2 ), standard and recombinant inbred strains, and heterogeneous stock mice indicate that a reciprocal (or inverse) genetic relationship exists between alcohol consumption and withdrawal severity. Furthermore, some genetic studies have detected reciprocal quantitative trait loci (QTLs) for these traits. We used a novel mouse model developed by simultaneous selection for both high alcohol consumption/low withdrawal and low alcohol consumption/high withdrawal and analyzed the gene expression and genome-wide genotypic differences.Randomly chosen third selected generation (S3 ) mice (N = 24/sex/line), bred from a B6xD2 F2 , were genotyped using the Mouse Universal Genotyping Array, which provided 2,760 informative markers. QTL analysis used a marker-by-marker strategy with the threshold for a significant log of the odds (LOD) set at 10. Gene expression in the ventral striatum was measured using the Illumina Mouse 8.2 array. Differential gene expression and the weighted gene co-expression network analysis (WGCNA) were implemented.Significant QTLs for consumption/withdrawal were detected on chromosomes (Chr) 2, 4, 9, and 12. A suggestive QTL mapped to Chr 6. Some of the QTLs overlapped with known QTLs mapped for 1 of the traits individually. One thousand seven hundred and forty-five transcripts were detected as being differentially expressed between the lines; there was some overlap with known withdrawal genes (e.g., Mpdz) located within QTL regions. WGCNA revealed several modules of co-expressed genes showing significant effects in both differential expression and intramodular connectivity; a module richly annotated with kinase-related annotations was most affected.Marked effects of selection on expression and network structure were detected. QTLs overlapping with differentially expressed genes on Chr 2 (distal) and 4 suggest that these are cis-eQTLs (Chr 2: Kif3b, Kcnq2; Chr 4: Mpdz, Snapc3). Other QTLs identified were on Chr 2 (proximal), 9, and 12. Network results point to involvement of kinase-related mechanisms and outline the need for further efforts such as interrogation of noncoding RNAs.

SUBMITTER: Metten P

PROVIDER: S-EPMC4500109 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects.

Metten Pamela P Iancu Ovidiu D OD Spence Stephanie E SE Walter Nicole A R NA Oberbeck Denesa D Harrington Christina A CA Colville Alexandre A McWeeney Shannon S Phillips Tamara J TJ Buck Kari J KJ Crabbe John C JC Belknap John K JK Hitzemann Robert J RJ

Alcoholism, clinical and experimental research 20141201 12

<h4>Background</h4>Data from C57BL/6J (B6) × DBA/2J (D2) F2 intercrosses (B6xD2 F2 ), standard and recombinant inbred strains, and heterogeneous stock mice indicate that a reciprocal (or inverse) genetic relationship exists between alcohol consumption and withdrawal severity. Furthermore, some genetic studies have detected reciprocal quantitative trait loci (QTLs) for these traits. We used a novel mouse model developed by simultaneous selection for both high alcohol consumption/low withdrawal an ...[more]

PMID: 25581648

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Project description:Purpose: Genetic factors significantly affect alcohol consumption and vulnerability to withdrawal. Some genetic models that show predisposition to severe withdrawal are also predisposed to low ethanol consumption and vice versa, even when tested independently in naïve animals. The study was undertaken to understand gene and network differences between mice selectively bred for high withdrawal/low withdrawal or low withdrawal/high consumption. Methods: Beginning with a C57BL/6J×DBA/2J F2 intercross founder population, animals were simultaneously selectively bred for both high alcohol consumption and low acute withdrawal (SOT line), or vice versa (NOT line). Using randomly chosen fourth selected generation (S4) mice (N= 18-22/sex/line), RNA-Seq was employed to assess genome-wide gene expression in the ventral striatum. The Mega-MUGA array was used to detect genome-wide genotypic differences. Differential gene expression and the weighted gene co-expression network analysis (WGCNA) were implemented. Results: The new selection of the SOT and NOT lines was similar to that reported previously (Metten et al. 2014). One thousand eight hundred and fifteen transcripts were detected as being differentially expressed between the lines. For the genes overexpressed in the SOT line there was enrichment in genes associated with cell adhesion, synapse organization and post-synaptic membrane. The genes with a cell adhesion annotation included 23 protocadherins, Mpdz & Dlg2. Genes with a postsynaptic membrane annotation included Gabrb3, Gphn, Grid1, Grin2b, Grin2c & Grm3. The genes overexpressed in the NOT line were enriched in a network module (red) with annotations associated with mitochondrial function. Several of these genes were module hub nodes and these included Nedd8, Guk1, Elof1, Ndufa8, & Atp6v1f. Conclusions: Marked effects of selection on gene expression were detected. The NOT line was characterized by the increased expression of hub nodes associated with mitochondrial function. Genes overexpressed in the SOT aligned with previous findings e.g. Colville et al. (2017) that high ethanol preference and consumption is associated with effects on cell adhesion and glutamate synaptic plasticity.

Project description:BackgroundGenetic factors significantly affect alcohol consumption and vulnerability to withdrawal. Furthermore, some genetic models showing predisposition to severe withdrawal are also predisposed to low ethanol (EtOH) consumption and vice versa, even when tested independently in naïve animals.MethodsBeginning with a C57BL/6J × DBA/2J F2 intercross founder population, animals were simultaneously selectively bred for both high alcohol consumption and low acute withdrawal (SOT line), or vice versa (NOT line). Using randomly chosen fourth selected generation (S4) mice (N = 18-22/sex/line), RNA-Seq was employed to assess genome-wide gene expression in ventral striatum. The MegaMUGA array was used to detect genome-wide genotypic differences. Differential gene expression and the weighted gene co-expression network analysis were implemented as described elsewhere (Genes Brain Behav 16, 2017, 462).ResultsThe new selection of the SOT and NOT lines was similar to that reported previously (Alcohol Clin Exp Res 38, 2014, 2915). One thousand eight hundred and sixteen transcripts were detected as differentially expressed between the lines. For genes more highly expressed in the SOT line, there was enrichment in genes associated with cell adhesion, synapse organization, and postsynaptic membrane. The genes with a cell adhesion annotation included 23 protocadherins, Mpdz and Dlg2. Genes with a postsynaptic membrane annotation included Gabrb3, Gphn, Grid1, Grin2b, Grin2c, and Grm3. The genes more highly expressed in the NOT line were enriched in a network module (red) with annotations associated with mitochondrial function. Several of these genes were module hub nodes, and these included Nedd8, Guk1, Elof1, Ndufa8, and Atp6v1f.ConclusionsMarked effects of selection on gene expression were detected. The NOT line was characterized by higher expression of hub nodes associated with mitochondrial function. Genes more highly expressed in the SOT aligned with previous findings, for example, Colville and colleagues (Genes Brain Behav 16, 2017, 462) that both high EtOH preference and consumption are associated with effects on cell adhesion and glutamate synaptic plasticity.

Project description:Long lasting abusive consumption, dependence, and withdrawal are characteristic features of alcohol use disorders (AUD). Mechanistically, persistent changes in gene expression are hypothesized to contribute to brain adaptations leading to ethanol toxicity and AUD. We employed repeated chronic intermittent ethanol (CIE) exposure by vapor chamber as a mouse model to simulate the cycles of ethanol exposure and withdrawal commonly seen with AUD. This model has been shown to induce progressive ethanol consumption in rodents. Brain CIE-responsive expression networks were identified by microarray analysis across five regions of the mesolimbic dopamine system and extended amygdala with tissue harvested from 0-hours to 7-days following CIE. Weighted Gene Correlated Network Analysis (WGCNA) was used to identify gene networks over-represented for CIE-induced temporal expression changes across brain regions. Differential gene expression analysis showed that long-lasting gene regulation occurred 7-days after the final cycle of ethanol exposure only in prefrontal cortex (PFC) and hippocampus. Across all brain regions, however, ethanol-responsive expression changes occurred mainly within the first 8-hours after removal from ethanol. Bioinformatics analysis showed that neuroinflammatory responses were seen across multiple brain regions at early time-points, whereas co-expression modules related to neuroplasticity, chromatin remodeling, and neurodevelopment were seen at later time-points and in specific brain regions (PFC or HPC). In PFC a module containing Bdnf was identified as highly CIE responsive in a biphasic manner, with peak changes at 0 hours and 5 days following CIE, suggesting a possible role in mechanisms underlying long-term molecular and behavioral response to CIE. Bioinformatics analysis of this network and several other modules identified Let-7 family microRNAs as potential regulators of gene expression changes induced by CIE. Our results suggest a complex temporal and regional pattern of widespread gene network responses involving neuroinflammatory and neuroplasticity related genes as contributing to physiological and behavioral responses to chronic ethanol.

Project description:We previously identified a region on chromosome 1 that harbor quantitative trait loci (QTLs) with large effects on alcohol withdrawal risk using both chronic and acute models in mice. Here, using newly created and existing QTL interval-specific congenic (ISC) models, we report the first evidence that this region harbors two distinct alcohol withdrawal QTLs (Alcw11and Alcw12), which underlie 13% and 3-6%, respectively, of the genetic variance in alcohol withdrawal severity measured using the handling-induced convulsion. Our results also precisely localize Alcw11 and Alcw12 to discreet chromosome regions (syntenic with human 1q23.1-23.3) that encompass a limited number of genes with validated genotype-dependent transcript expression and/or non-synonymous sequence variation that may underlie QTL phenotypic effects. ISC analyses also implicate Alcw11and Alcw12 in withdrawal-induced anxiety-like behavior, representing the first evidence for their broader roles in alcohol withdrawal beyond convulsions; but detect no evidence for Alcw12 involvement in ethanol conditioned place preference (CPP) or consumption. Our data point to high-quality candidates for Alcw12, including genes involved in mitochondrial respiration, spatial buffering, and neural plasticity, and to Kcnj9 as a high-quality candidate for Alcw11. Our studies are the first to show, using two null mutant models on different genetic backgrounds, that Kcnj9-/- mice demonstrate significantly less severe alcohol withdrawal than wildtype littermates using acute and repeated exposure paradigms. We also demonstrate that Kcnj9-/- voluntarily consume significantly more alcohol (20%, two-bottle choice) than wildtype littermates. Taken together with evidence implicating Kcnj9 in ethanol CPP, our results support a broad role for this locus in ethanol reward and withdrawal phenotypes. In summary, our results demonstrate two distinct chromosome 1 QTLs that significantly affect risk for ethanol withdrawal, and point to their distinct unique roles in alcohol reward phenotypes.

Dataset Information

Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects.

Publications

Dual-trait selection for ethanol consumption and withdrawal: genetic and transcriptional network effects.

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