The discovery of a recombinant SARS2-like CoV strain provides insights into SARS and COVID-19 pandemics

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Abstract

In December 2019, the world awoke to a new zoonotic strain of coronavirus named severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). In the present study, we identified key recombination regions and mutation sites cross the SARS-CoV-2, SARS-CoV and SARS-like CoV clusters of betacoronavirus subgroup B. Based on the analysis of these recombination events, we proposed that the Spike protein of SARS-CoV-2 may have more than one specific receptor for its function. In addition, we reported—for the first time—a recombination event of ORF8 at the whole-gene level in a bat and ultimately determined that ORF8 enhances the viral replication. In conjunction with our previous discoveries, we found that receptor binding abilities, junction furin cleavage sites (FCSs), strong first ribosome binding sites (RBSs) and enhanced ORF8 s are main factors contributing to transmission, virulence and host adaptability of CoVs. Junction FCSs and enhanced ORF8 s increase the efficiencies in viral entry into cells and replication, respectively while strong first RBSs enhance the translational initiation. The strong recombination ability of CoVs integrated these factors to generate multiple recombinant strains, two of which evolved into SARS-CoV and SARS-CoV-2 by nature selection, resulting in the SARS and COVID-19 pandemics.

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  1. SciScore for 10.1101/2020.07.22.213926: (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
    SVDetect v0.8b and SVFilter [18] were used to removed abnormal aligned reads.
    SVDetect
    suggested: (SVDetect, RRID:SCR_010812)
    Sequence alignment was performed using the Bowtie v0.12.7 software with paired-end alignment allowing 3 mismatches; mutation detection and other data processing were carried out using Perl scripts; the phylogenetic analysis was performed using MEGA v7.0.26; Statistics and plotting were conducted using the software R v2.15.3 the Bioconductor packages [23].
    Bowtie
    suggested: (Bowtie, RRID:SCR_005476)
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    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.
    • 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.