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


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



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



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


Article Type

Research Article



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



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.



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



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


Edited by

P Kangueane






Biomedical Informatics



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.