Genome-wide computational prediction of miRNAs in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) revealed target genes involved in pulmonary vasculature and antiviral innate immunity

对严重急性呼吸综合征冠状病毒2 (SARS-CoV-2) 进行全基因组计算预测,揭示了参与肺血管系统和抗病毒先天免疫的靶基因。

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Abstract

The current outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China threatened humankind worldwide. The coronaviruses contains the largest RNA genome among all other known RNA viruses, therefore the disease etiology can be understood by analyzing the genome sequence of SARS-CoV-2. In this study, we used an ab-intio based computational tool VMir to scan the complete genome of SARS-CoV-2 to predict pre-miRNAs. The potential pre-miRNAs were identified by ViralMir and mature miRNAs were recognized by Mature Bayes. Additionally, predicted mature miRNAs were analysed against human genome by miRDB server to retrieve target genes. Besides that we also retrieved GO (Gene Ontology) terms for pathways, functions and cellular components. We predicted 26 mature miRNAs from genome of SARS-CoV-2 that targets human genes involved in pathways like EGF receptor signaling, apoptosis signaling, VEGF signaling, FGF receptor signaling. Gene enrichment tool analysis and substantial literature evidences suggests role of genes like BMPR2 and p53 in pulmonary vasculature and antiviral innate immunity respectively. Our findings may help research community to understand virus pathogenesis.

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