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Title

Genomic profiling of Nipah virus using NGS driven RNA-Seq expression data

Authors

Md. Zakiul Hassan1†, Md. Shakil Ahmed1†*, Md. Marufuzzaman Khan2, Mohammad Ahsan Uddin3, Fahmida Chowdhury1, Md. Kamruzzaman4

 

Affiliation

1Infectious Diseases Division, icddr,b (International Centre for Diarrheal Disease Research, Bangladesh), Dhaka, Bangladesh; 2Department of Public Health, The University of Tennessee, Knoxville, Tennessee, USA; 3Department of Statistics, University of Dhaka, Dhaka, Bangladesh; 4Institute of Bangladesh Studies, University of Rajshahi, Rajshahi, Bangladesh

 

Email

Md. Shakil Ahmed - Email: md.shakil@icddrb.org; †Contributed equally; *Corresponding author

 

Article Type

Research Article

 

Date

Received December 28, 2019; Revised December 31, 2019; Accepted December 31, 2019; Published December 31, 2019

 

Abstract

Nipah virus (NiV) is an ssRNA, enveloped paramyxovirus in the genus Henipaveridae with a case fatality rate >70%. We analyzed the NGS RNA-Seq gene expression data of NiV to detect differentially expressed genes (DEGs) using the statistical R package limma. We used the Cytoscape, Ensembl, and STRING tools to construct the gene-gene interaction tree, phylogenetic gene tree and protein-protein interaction networks towards functional annotation. We identified 2707 DEGs (p-value <0.05) among 54359 NiV genes. The top-up and down-regulated DEGs were EPST1, MX1, IFIT3, RSAD2, OAS1, OASL, CMPK2 and SLFN13, SPAC977.17 using log2FC criteria with optimum threshold 1.0. The top 20 up-regulated gene-gene interaction trees showed no significant association between Nipah and Tularemia virus. Similarly, the top 20 down-regulated genes of neither Ebola nor Tularemia virus showed an association with the Nipah virus. Hence, we document the top-up and down-regulated DEGs for further consideration as biomarkers and candidates for vaccine or drug design against Nipah virus to combat infection.

 

Keywords

Nipah virus, NGS RNA-Seq, limma, Phylogenetic gene tree, Protein-protein interaction network

 

Citation

Hassan et al. Bioinformation 15(12): 853-862 (2019)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.