How the replication and transcription complex functions in jumping transcription of SARS-CoV-2

  1. Jianguang Liang
  2. Jinsong Shi
  3. Shunmei Chen
  4. Guangyou Duan
  5. Fan Yang
  6. Zhi Cheng
  7. Xin Li
  8. Jishou Ruan
  9. Dong Mi
  10. Shan Gao

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Abstract

Background

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although unprecedented efforts are underway to develop therapeutic strategies against this disease, scientists have acquired only a little knowledge regarding the structures and functions of the CoV replication and transcription complex (RTC) and 16 non-structural proteins, named NSP1-16.

Results

In the present study, we proposed a two-route model to answer how the RTC functions in the jumping transcription of CoVs. The key step leading to this model was that the motif AAACH for METTL3 recognition flanking the transcription regulatory sequence (TRS) motif was discovered to determine the m6A methylation of SARS-CoV-2 RNAs, by reanalyzing public Nanopore RNA-seq data. As the most important finding, TRS hairpins were reported for the first time to interpret NSP15 cleavage, RNA methylation of CoVs and their association at the molecular level. In addition, we reported canonical TRS motifs of all CoVs to prove the importance of our findings.

Conclusions

The main conclusions are: (1) TRS hairpins can be used to identify recombination regions in CoV genomes; (2) RNA methylation of CoVs participates in the determination of the RNA secondary structures by affecting the formation of base pairing; and (3) The eventual determination of the CoV RTC global structure needs to consider METTL3 in the experimental design. Our findings enrich fundamental knowledge in the field of gene expression and its regulation, providing a crucial basis for future studies.

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  1. ScreenIT

    SciScore for 10.1101/2021.02.17.431652: (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
    Statistics and plotting were conducted using the software R v2.15.3 with the Bioconductor packages [19].
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)

    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 10.1101/2021.02.17.431652 on bioRxiv