mRNA changes in nucleus accumbens related to methamphetamine addiction in mice

Li Zhu1,2, Jiaqi Li1,2, Nan Dong1,2

  • 1College of Forensic Medicine, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, 710061, PR China.

Scientific Reports
|November 22, 2016
PubMed

Insights

Methamphetamine (METH) alters gene expression and splicing in the mouse brain, impacting synaptic plasticity and metabolism. These changes, driven by non-coding RNAs, may underlie METH addiction.

Area of Science:

  • Neuroscience
  • Molecular Biology
  • Genomics

Background:

  • Methamphetamine (METH) is a psychostimulant causing addiction.
  • METH alters microRNA (miRNA) and long non-coding RNA (lncRNA) expression in the nucleus accumbens.
  • These non-coding RNA changes suggest METH impacts post-transcriptional regulation.

Purpose of the Study:

  • To identify mRNA expression and alternative splicing alterations in the mouse nucleus accumbens after METH exposure.
  • To correlate METH-induced mRNA changes with known non-coding RNA alterations.
  • To elucidate the role of non-coding RNAs in METH's effects on the transcriptome.

Main Methods:

  • Strand-specific RNA sequencing (ssRNA-Seq) was used to analyze gene expression and splicing.
  • Differential gene expression analysis identified METH-responsive mRNAs.
  • Bioinformatic analysis correlated mRNA changes with miRNA and lncRNA targets.

Main Results:

  • METH significantly altered the expression of 2171 mRNAs involved in synaptic plasticity, mitochondrial energy metabolism, and immune response.
  • 309 and 589 differentially expressed mRNAs were predicted as targets of miRNAs and lncRNAs, respectively.
  • METH treatment reduced mRNA alternative splicing, with 818 METH-specific splicing events identified.

Conclusions:

  • METH addiction may result from altered miRNA and lncRNA expression, leading to changes in mRNA splicing and expression.
  • The study reveals a METH-modified nucleus accumbens transcriptome.
  • Identified non-coding RNA-mRNA interaction networks offer insights into METH addiction mechanisms.

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