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2000
Volume 6, Issue 4
  • ISSN: 2666-7967
  • E-ISSN: 2666-7975

Abstract

Purpose

To identify significant genes responsible for altering immune response in viral infections, including SARS, H1N1, Influenza, and Rhinovirus, as there are no previous studies that have analyzed these viral infections together.

Methods

Viral infection datasets pertaining to SARS, H1N1, Influenza, and Rhinovirus were obtained from the NCBI Gene Expression Omnibus. We have used three GEO datasets with accession numbers: GSE47962, GSE48466, and GSE71766. The Differentially Expressed Genes (DEG’s) were identified from each of the datasets, and then common DEGs were extracted. Protein-Protein-Interaction (PPI) network was constructed for the common DEGs obtained in all the virus datasets. Finally, we analyzed the PPI network to identify the hub genes that have high interconnectivity with other genes. The significantly enriched pathways are reported.

Results

By performing the comparative analysis, we identified 463 common DEG’s among the viral infection datasets under study. The highly interconnected PPI network constructed from these genes contained 3396 edges with an average node degree of 14.7 and an average local clustering coefficient of 0.406. There were 51 nodes with degree>50. The highest interconnected node, STAT1 had degree 113.

Conclusion

STAT 1 gene is identified as the most significant hub gene related to the immune response in all four viral infections, including SARS, H1N1, Influenza, and Rhinovirus. Its trivial role is already known in different viral infections, but being most significant in the four viruses together is a novel finding. It is thus identified as a central gene that is a potential therapeutic drug and vaccine target for viral infections.

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Comparative Transcriptomic Analysis of SARS, H1N1, Influenza, and Rhinovirus to Identify Significant Genes Involved in Altering Immune Response
Coronaviruses 6, E090724231753 (2025); https://doi.org/10.2174/0126667975300308240703050733
/content/journals/covid/10.2174/0126667975300308240703050733
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  • Article Type:     Research Article
Keyword(s): COVID-19; GEO; H1N1; influenza; limma; PPI; SARS; STAT 1

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