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RESEARCH ARTICLE
Year : 2017  |  Volume : 54  |  Issue : 2  |  Page : 131-138

Identification and characterization of differentially expressed genes from human microglial cell samples infected with Japanese encephalitis virus


Biomedical Informatics Centre, ICMR-Regional Medical Research Centre, Chandrasekharpur, Odisha, India

Correspondence Address:
Namita Mahapatra
Scientist 'F', Biomedical Informatics Centre, ICMR-Regional Medical Research Centre, Chandrasekharpur, Nandankanan Road, Bhubaneswar-751023, Odisha
India
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Source of Support: None, Conflict of Interest: None


PMID: 28748833

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Background & objectives: Limited studies have been reported on Japanese encephalitis (JE) with reference to microarray data analysis. The present study involved an in silico approach for identification and characterization of differentially expressed genes in human microglial cell (CHME3) samples, infected with P20778 strain of Japanese encephalitis virus (JEV). Methods: Gene expression data (GSE57330) belonging to mRNA expression profile of CHME3 cells infected with JEV, was downloaded from the gene expression omnibus (GEO) database, processed and normalized by robust multichip averaging (RMA) method using affy packages of R. The Bayes method was used to correct multiple testing. The log fold change (logFC > 1) and p< 0.05 were used as cut-off to identify differentially expressed genes (DEGs). The newly identified hub genes were set at the centre for construction of protein-protein interaction network using search tool for the retrieval of interacting genes/proteins (STRING) database considering human genome as reference. Gene ontology and pathway enrichment analysis of the hub gene and its associated genes were performed using STRING and DAVID tool. Results: Microarray data analysis revealed that STAT1 gene was down-regulated during JEV infection. STAT1 gene was found to interact with tyrosine protein kinase family members, and showed strong interaction with JAK1 and JAK2 genes. Interpretation & conclusion: The identified transcription factors and the binding sites in the promoter region of STAT1 gene might act as potential drug targets in near future.


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