Integration of viral transcriptome sequencing with structure and sequence motifs predicts novel regulatory elements in SARS-CoV-2

  1. Brian J. Cox

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

In the last twenty years, three separate coronaviruses have left their typical animal hosts and became human pathogens. An area of research interest is coronavirus transcription regulation that uses an RNA-RNA mediated template-switching mechanism. It is not known how different transcriptional stoichiometries of each viral gene are generated. Analysis of SARS-CoV-2 RNA sequencing data from whole RNA transcriptomes identified TRS dependent and independent transcripts. Integration of transcripts and 5’-UTR sequence motifs identified that the pentaloop and the stem-loop 3 were also located upstream of spliced genes. TRS independent transcripts were detected as likely non-polyadenylated. Additionally, a novel conserved sequence motif was discovered at either end of the TRS independent splice junctions. While similar both SARS viruses generated similar TRS independent transcripts they were more abundant in SARS-CoV-2. TRS independent gene regulation requires investigation to determine its relationship to viral pathogenicity.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.24.169144: (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
    Related sequences were found using the NCBI BLAST tool(Johnson et al., 2008).
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    Data were visualized using ggplot2(Wickham, 2009).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Bam files were sorted and indexed using samtools.
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)

    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.
    • 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.

  2. Version published to 10.1101/2020.06.24.169144v1 on bioRxiv