In silico identification of conserved cis -acting RNA elements in the SARS-CoV-2 genome

  1. Bader Y. Alhatlani

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Abstract

Aim

The aim of this study was to computationally predict conserved RNA sequences and structures known as cis -acting RNA elements (CREs) located within the SARS-CoV-2 genome.

Materials & methods

Bioinformatics tools were used to analyse and predict cis -acting regulatory elements by obtaining viral sequences from available databases.

Results

Computational analysis prediction revealed the presence of RNA stem-loop structures within the 3’ end of the ORF1ab region that are analogous to the previously identified SARS-CoV genomic packaging signals. Alignment-based RNA secondary structures prediction of the 5’ end of the SARS-CoV-2 genome identified also conserved CREs.

Conclusion

These CREs could be used as potential targets for a vaccine and/or antiviral therapeutics developments; however, further studies would be required to confirm their roles in the SARS-CoV-2 life cycle.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.23.167916: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.06.23.167916 on bioRxiv