In silico investigation of potential COVID-19-associated microRNA signatures


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Asfa S. S., Okmen D., PAVLOPOULOU A.

CUKUROVA MEDICAL JOURNAL, vol.49, no.1, pp.170-180, 2024 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 49 Issue: 1
  • Publication Date: 2024
  • Doi Number: 10.17826/cumj.1415977
  • Journal Name: CUKUROVA MEDICAL JOURNAL
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Academic Search Premier, Directory of Open Access Journals, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.170-180
  • Keywords: bioinformatics, COVID-19 infection- associated genes, antiviral microRNAs, protein-protein interactions, gene set enrichment analysis, microRNA- gene network
  • Dokuz Eylül University Affiliated: No

Abstract

Purpose: The global pandemic COVID-19, caused by the coronavirus SARS-CoV-2, is persistent despite the increasing vaccination rates, with new cases being reported per week. MicroRNAs, that is, non -coding RNA species that regulate gene expression at the post -transcriptional level, play a pivotal role in the SARS-CoV-2 life cycle, pathophysiology and host's anticoronaviral responses. The objective of this study was the in silico discovery of functionally associated miRNAs that likely co -regulate COVID-19-related genes Materials and Methods: In the present study, an integrative bioinformatics approach was employed, including database searching, gene set enrichment analysis, network -based and microRNA target prediction methods, towards the discovery of epigenetic determinants of COVID-19. Results: An intricate microRNA-target gene network was constructed, and a set of 8 highly interacting microRNAs, that potentially co -target and co -regulate key COVID-19related genes, was detected. These miRNAs and their corresponding genes are likely involved in the host's response to SARS-CoV-2 infection. Conclusion: The 8 functionally associated miRNAs could constitute a signature for COVID-19 diagnosis.