Pervasive RNA Secondary Structure in the Genomes of SARS-CoV-2 and Other Coronaviruses

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

The detection and characterization of large-scale RNA secondary structure in the genome of SARS-CoV-2 indicate an extraordinary and unsuspected degree of genome structural organization; this could be effectively visualized through a newly developed contour plotting method that displays positions, structural features, and conservation of RNA secondary structure between related viruses. Such RNA structure imposes a substantial evolutionary cost; paired sites showed greater restriction in diversity and represent a substantial additional constraint in reconstructing its molecular epidemiology. Its biological relevance arises from previously documented associations between possession of structured genomes and persistence, as documented for HCV and several other RNA viruses infecting humans and mammals. Shared properties potentially conferred by large-scale structure in SARS-CoV-2 include increasing evidence for prolonged infections and induced immune dysfunction that prevents development of protective immunity. The findings provide an additional element to cellular interactions that potentially influences the natural history of SARS-CoV-2, its pathogenicity, and its transmission.

Article activity feed

  1. SciScore for 10.1101/2020.06.17.155200: (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

    Software and Algorithms
    SentencesResources
    Statistical analysis and construction of frequency histograms used SPSS version 2
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    Results from OddPub: Thank you for sharing your data.


    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • 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.