RNA‐Seq Analysis of Genetic and Transcriptome Network Effects of Dual‐Trait Selection for Ethanol Preference and Withdrawal Using SOT and NOT Genetic Models

Abstract

Background: Genetic 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 na€ ıve animals.Methods: Beginning with a C57BL/6J 9 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).Results: The 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.Conclusions: Marked 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.

On the Use of Heterogeneous Stock Mice to Map Transcriptomes Associated With Excessive Ethanol Consumption

“…Regardless of how one deals with the relatedness issue(s), it would seem that independent replication should be a convincing solution to the problem. For QTLs associated with ethanol preference and derived from B6xD2 crosses, replication has worked extremely well (79)(80)(81). However, replication in HS animals does not appear to be straightforward.…”

“…However, for ethanol preference, we do have data that gets very close to this issue (see below). For those unfamiliar with alcohol preference research, selection from B6xD2 intercross animals and/or data collected from BXD RI strains has yielded remarkably consistent preference results for almost 30 years [see e.g., (79)(80)(81)].…”

“…Keeping the Colville et al (61,82) data in perspective, we turn to Kozell et al (81). Beginning with a B6xD2 F2 intercross founder population, these authors selectively bred for both high alcohol consumption and low acute withdrawal (SOT line), or vice versa (NOT line).…”

Alcohol Dependence in Rats Is Associated with Global Changes in Gene Expression in the Central Amygdala

“…Perturbation-induced gene expression serves as a sensitive measure of changes in cell functions, and numerous studies have used transcriptome profiling to investigate the mechanisms underlying brain plasticity and brain pathology [ 8 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Alcohol causes widespread changes in gene expression in the brain [ 31 , 39 , 42 , 43 , 44 , 45 , 46 , 47 , 48 ], some of which contribute to the development of AUD.…”

“…Perturbation-induced gene expression serves as a sensitive measure of changes in cell functions, and numerous studies have used transcriptome profiling to investigate the mechanisms underlying brain plasticity and brain pathology [ 8 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ]. Alcohol causes widespread changes in gene expression in the brain [ 31 , 39 , 42 , 43 , 44 , 45 , 46 , 47 , 48 ], some of which contribute to the development of AUD. Because AUD is a complex disease, with various brain circuits playing particular roles at different stages of AUD progression, it is important to determine alcohol-induced molecular changes across brain regions, AUD stages and animal models.…”