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Dataset . 2020
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2020
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Dataset . 2020
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Data sets for Perspective: SARS-CoV-2's potential mechanism of regulating cellular responses through depletion of specific host miRNAs

Authors: Rafal Bartoszewski; Michal Dabrowski; Bogdan Jakiela; Sadis Matalon; Kevin Harrod; Marek Sanak; James F. Collawn;

Data sets for Perspective: SARS-CoV-2's potential mechanism of regulating cellular responses through depletion of specific host miRNAs

Abstract

Using a bioinformatic analysis of human miRNA potential interactions with the SARS-CoV-2’s genome, we examined the potential miRNA target sites in 7 coronavirus genomes that include SARS-CoV-2, MERS-CoV, SARS-CoV, and 4 non-pathogenic coronaviruses. (Data Set 1). Our approach was to examine and compare 3 pathogenic and 4 non-pathogenic strains of HCoVs. The HCoVs' RNA genomes of pathogenic strains were SARS-CoV-2 (NC_045512.2), SARS-CoV (NC_004718.3), MERS-CoV (NC_019843.3). The non-pathogenic strains were HCoV-OC43 (KU131570.1), HCoV-229E (NC_002645.1), HCoV-HKU1 (KF686346.1), and HCoV-NL63 (NC_005831.2). These coronaviruses were tested against the set of 896 confident mature human miRNA sequences that were obtained from the miRBbase v2.21 using the RNA22 v2 microRNA target discovery tool web-server. In order to reduce the false discovery rate of the MTS predictions, the most strict parameters were applied to the default computation workflow using a specificity of 92% versus a sensitivity of 22%. In Data set 2, using the miRDIP database with only top 1% of the most probable targets considered, we analyzed the potential targets of miRNA that could be bound to either the pathogenic, the non-pathogenic or both groups of HCoVs. In Data set 3, using miRNAFold webserver we identified 10 pre-miRNA sequences in the SARS-CoV-2 RNA sequence that could potentially enter the human RNAi pathway. The graphical summary of our working hypothesis is provided in the graphical abstract.

Keywords

MERS-CoV, coronaviruses, MTSs, COVID-19, SARS-CoV

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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