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Computational prediction of SARS-CoV-2 encoded miRNAs and their putative host targets
Preprint
in English
| bioRxiv
| ID: ppbiorxiv-365049
ABSTRACT
Over the past two decades, there has been a continued research on the role of small non-coding RNAs including microRNAs (miRNAs) in various diseases. Studies have shown that viruses modulate the host cellular machinery and hijack its metabolic and immune signalling pathways by miRNA mediated gene silencing. Given the immensity of coronavirus disease 19 (COVID-19) pandemic and the strong association of viral encoded miRNAs with their pathogenesis, it is important to study Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) miRNAs. To address this unexplored area, we identified 8 putative novel miRNAs from SARS-CoV-2 genome and explored their possible human gene targets. A significant proportion of these targets populated key immune and metabolic pathways such as MAPK signalling pathway, maturity-onset diabetes, Insulin signalling pathway, endocytosis, RNA transport, TGF-{beta} signalling pathway, to name a few. The data from this work is backed up by recently reported high-throughput transcriptomics datasets obtains from SARS-CoV-2 infected samples. Analysis of these datasets reveal that a significant proportion of the target human genes were down-regulated upon SARS-CoV-2 infection. The current study brings to light probable host metabolic and immune pathways susceptible to viral miRNA mediated silencing in a SARS-CoV-2 infection, and discusses its effects on the host pathophysiology.
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Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Type of study:
Prognostic study
Language:
English
Year:
2020
Document type:
Preprint