High affinity of host human microRNAs to SARS-CoV-2 genome: An in silico analysis

宿主人类microRNA与SARS-CoV-2基因组的高亲和力:一项计算机模拟分析

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Abstract

BACKGROUND: Coronavirus disease 2019 (COVID-19) caused by a novel betacoronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has attracted top health concerns worldwide within a few months after its appearance. Since viruses are highly dependent on the host small RNAs (microRNAs) for their replication and propagation, in this study, top miRNAs targeting SARS-CoV-2 genome and top miRNAs targeting differentially expressed genes (DEGs) in lungs of patients infected with SARS-CoV-2, were predicted. METHODS: All human mature miRNA sequences were acquired from miRBase database. MiRanda tool was used to predict the potential human miRNA binding sites on the SARS-CoV-2 genome. EdgeR identified differentially expressed genes (DEGs) in response to SARS-CoV-2 infection from GEO147507 data. Gene Set Enrichment Analysis (GSEA) and DEGs annotation analysis were performed using ToppGene and Metascape tools. RESULTS: 160 miRNAs with a perfect matching in the seed region were identified. Among them, there was 15 miRNAs with more than three binding sites and 12 miRNAs with a free energy binding of -29 kCal/Mol. MiR-29 family had the most binding sites (11 sites) on the SARS-CoV-2 genome. MiR-21 occupied four binding sites and was among the top miRNAs that targeted up-regulated DEGs. In addition to miR-21, miR-16, let-7b, let-7e, and miR-146a were the top miRNAs targeting DEGs. CONCLUSION: Collectively, more experimental studies especially miRNA-based studies are needed to explore detailed molecular mechanisms of SARS-CoV-2 infection. Moreover, the role of DEGs including STAT1, CCND1, CXCL-10, and MAPKAPK2 in SARS-CoV-2 should be investigated to identify the similarities and differences between SARS-CoV-2 and other respiratory viruses.

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