Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection

dc.contributor.author Demirci, Muserref Duygu Sacar
dc.contributor.author Adan, Aysun
dc.contributor.authorID 0000-0003-2012-0598 en_US
dc.contributor.department AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Moleküler Biyoloji ve Genetik Bölümü en_US
dc.date.accessioned 2021-01-16T12:04:07Z
dc.date.available 2021-01-16T12:04:07Z
dc.date.issued 2020 en_US
dc.description.abstract MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression found in more than 200 diverse organisms. Although it is still not fully established if RNA viruses could generate miRNAs, there are examples of miRNA like sequences from RNA viruses with regulatory functions. In the case of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there are several mechanisms that would make miRNAs impact the virus, like interfering with viral replication, translation and even modulating the host expression. In this study, we performed a machine learning based miRNA prediction analysis for the SARS-CoV-2 genome to identify miRNA-like hairpins and searched for potential miRNA-based interactions between the viral miRNAs and human genes and human miRNAs and viral genes. Overall, 950 hairpin structured sequences were extracted from the virus genome and based on the prediction results, 29 of them could be precursor miRNAs. Targeting analysis showed that 30 viral mature miRNA-like sequences could target 1,367 different human genes. PANTHER gene function analysis results indicated that viral derived miRNA candidates could target various human genes involved in crucial cellular processes including transcription, metabolism, defense system and several signaling pathways such as Wnt and EGFR signalings. Protein class-based grouping of targeted human genes showed that host transcription might be one of the main targets of the virus since 96 genes involved in transcriptional processes were potential targets of predicted viral miRNAs. For instance, basal transcription machinery elements including several components of human mediator complex (MED1, MED9, MED 12L, MED 19), basal transcription factors such as TAF4, TAF5, TAF7L and site-specific transcription factors such as STATI were found to be targeted. In addition, many known human miRNAs appeared to be able to target viral genes involved in viral life cycle such as S, M, N, E proteins and ORF lab, ORF3a, ORF8, ORF7a and ORF10. Considering the fact that miRNA-based therapies have been paid attention, based on the findings of this study, comprehending mode of actions of miRNAs and their possible roles during SARS-CoV-2 infections could create new opportunities for the development and improvement of new therapeutics. en_US
dc.identifier.issn 2167-8359
dc.identifier.other PubMed ID: 32547891
dc.identifier.uri https://hdl.handle.net/20.500.12573/435
dc.identifier.volume Volume: 8 en_US
dc.language.iso eng en_US
dc.publisher PEERJ INC, 341-345 OLD ST, THIRD FLR, LONDON, EC1V 9LL, ENGLAND en_US
dc.relation.isversionof 10.7717/peerj.9369 en_US
dc.relation.journal PEERJ en_US
dc.relation.publicationcategory Makale - Ulusal Hakemli Dergi - Başka Kurum Yazarı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject SARS-CoV-2 en_US
dc.subject MicroRNA en_US
dc.subject COVID19 en_US
dc.subject Host-virus interaction en_US
dc.title Computational analysis of microRNA-mediated interactions in SARS-CoV-2 infection en_US
dc.type article en_US

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