Literature DB >> 30102956

Abnormalities in Prefrontal Cortical Gene Expression Profiles Relevant to Schizophrenia in MK-801-Exposed C57BL/6 Mice.

Jialu Zhao1, Xu Liu1, Chunyue Huo2, Tian Zhao1, Haihong Ye3.   

Abstract

MK-801, a non-competitive NMDA receptor (NMDAR) antagonist, disturbs NMDAR function in rodents and induces psychological and behavioral changes similar to schizophrenia (SCZ). However, the effects of MK-801 treatment on gene expression are largely unknown. Here we performed RNA-sequencing on the prefrontal cortex of MK-801-exposed male mice in order to analyze gene expression and co-expression patterns related to SCZ and to identify mechanisms that underlie the molecular etiology of this disorder. Transcriptome analysis revealed that the differentially expressed genes were more often associated with biological processes that included postsynaptic transmission, immune system process, response to external stimulus and hemostasis. In order to extract comprehensive biological information, we used an approach for biclustering, called FABIA, to simultaneously cluster transcriptomic data across genes and conditions. When combined with analyses using DAVID and STRING databases, we found that co-expression patterns were altered in synapse-related genes and genes central to the mitochondrial network. Abnormal co-expression of genes mediating synaptic vesicle cycling could disturb release, uptake and reuptake of glutamate, and the perturbation in co-expression patterns for mitochondrial respiratory chain complexes was extensive. Our study supports the hypothesis that research using MK-801-exposed male mice as an animal model of SCZ offers important insights into the pathogenesis of SCZ.
Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  RNA-seq; biclustering; mitochondrion; synapse

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Year:  2018        PMID: 30102956     DOI: 10.1016/j.neuroscience.2018.07.046

Source DB:  PubMed          Journal:  Neuroscience        ISSN: 0306-4522            Impact factor:   3.590


  3 in total

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3.  A comparison of transcriptome analysis methods with reference genome.

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  3 in total

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