Gender-Specific Effects of Selection for Drinking in the Dark on the Network Roles of Coding and Noncoding RNAs

Ovidiu Iancu, Alex M. Colville, Beth Wilmot, Robert Searles, Priscila Darakjian, Christina Zheng, Shannon McWeeney, Sunita Kawane, John Jr Crabbe, Pamela Metten, Denesa Oberbeck, Robert Hitzemann

Research output: Contribution to journalArticle

Abstract

Background: Transcriptional differences between heterogeneous stock mice and high drinking-in-the-dark selected mouse lines have previously been described based on microarray technology coupled with network-based analysis. The network changes were reproducible in 2 independent selections and largely confined to 2 distinct network modules; in contrast, differential expression appeared more specific to each selected line. This study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of noncoding RNA (ncRNA); we additionally evaluate sex-specific transcriptional effects of selection. Methods: Naïve mice (N = 24/group and sex) were utilized for gene expression analysis in the ventral striatum; the transcriptome was sequenced with the Illumina HiSeq platform. Differential gene expression and the weighted gene co-expression network analysis were implemented largely as described elsewhere, resulting in the identification of genes that change expression level or (co)variance structure. Results: Across both sexes, we detect selection effects on the extracellular matrix and synaptic signaling, although the identity of individual genes varies. A majority of nc RNAs cluster in a single module of relatively low density in both the male and female network. The most strongly differentially expressed transcript in both sexes was Gm22513, a small nuclear RNA with unknown function. Associated with selection, we also found a number of network hubs that change edge strength and connectivity. At the individual gene level, there are many sex-specific effects; however, at the annotation level, results are more concordant. Conclusions: In addition to demonstrating sex-specific effects of selection on the transcriptome, the data point to the involvement of extracellular matrix genes as being associated with the binge drinking phenotype.

Original languageEnglish (US)
Pages (from-to)1454-1465
Number of pages12
JournalAlcoholism: Clinical and Experimental Research
Volume42
Issue number8
DOIs
StatePublished - Aug 1 2018

Fingerprint

Untranslated RNA
Drinking
Genes
Gene Expression
Transcriptome
Gene expression
Extracellular Matrix
Sex Preselection
Genetic Transcription
RNA
Technology
Binge Drinking
Small Nuclear RNA
Transcription
Microarrays
Electric network analysis
Phenotype

Keywords

  • Alcohol
  • Binge
  • Differential Network Analysis
  • Drinking in the Dark
  • Mouse
  • Noncoding RNA
  • Selective Breeding
  • Sex-Specific Effects

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Toxicology
  • Psychiatry and Mental health

Cite this

Gender-Specific Effects of Selection for Drinking in the Dark on the Network Roles of Coding and Noncoding RNAs. / Iancu, Ovidiu; Colville, Alex M.; Wilmot, Beth; Searles, Robert; Darakjian, Priscila; Zheng, Christina; McWeeney, Shannon; Kawane, Sunita; Crabbe, John Jr; Metten, Pamela; Oberbeck, Denesa; Hitzemann, Robert.

In: Alcoholism: Clinical and Experimental Research, Vol. 42, No. 8, 01.08.2018, p. 1454-1465.

Research output: Contribution to journalArticle

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AU - Iancu, Ovidiu

AU - Colville, Alex M.

AU - Wilmot, Beth

AU - Searles, Robert

AU - Darakjian, Priscila

AU - Zheng, Christina

AU - McWeeney, Shannon

AU - Kawane, Sunita

AU - Crabbe, John Jr

AU - Metten, Pamela

AU - Oberbeck, Denesa

AU - Hitzemann, Robert

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N2 - Background: Transcriptional differences between heterogeneous stock mice and high drinking-in-the-dark selected mouse lines have previously been described based on microarray technology coupled with network-based analysis. The network changes were reproducible in 2 independent selections and largely confined to 2 distinct network modules; in contrast, differential expression appeared more specific to each selected line. This study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of noncoding RNA (ncRNA); we additionally evaluate sex-specific transcriptional effects of selection. Methods: Naïve mice (N = 24/group and sex) were utilized for gene expression analysis in the ventral striatum; the transcriptome was sequenced with the Illumina HiSeq platform. Differential gene expression and the weighted gene co-expression network analysis were implemented largely as described elsewhere, resulting in the identification of genes that change expression level or (co)variance structure. Results: Across both sexes, we detect selection effects on the extracellular matrix and synaptic signaling, although the identity of individual genes varies. A majority of nc RNAs cluster in a single module of relatively low density in both the male and female network. The most strongly differentially expressed transcript in both sexes was Gm22513, a small nuclear RNA with unknown function. Associated with selection, we also found a number of network hubs that change edge strength and connectivity. At the individual gene level, there are many sex-specific effects; however, at the annotation level, results are more concordant. Conclusions: In addition to demonstrating sex-specific effects of selection on the transcriptome, the data point to the involvement of extracellular matrix genes as being associated with the binge drinking phenotype.

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