Evidence of recombination in coronaviruses implicating pangolin origins of nCoV-2019

  1. Matthew C. Wong
  2. Sara J. Javornik Cregeen
  3. Nadim J. Ajami
  4. Joseph F. Petrosino

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Abstract

A novel coronavirus (nCoV-2019) was the cause of an outbreak of respiratory illness detected in Wuhan, Hubei Province, China in December of 2019. Genomic analyses of nCoV-2019 determined a 96% resemblance with a coronavirus isolated from a bat in 2013 (RaTG13); however, the receptor binding motif (RBM) of these two genomes share low sequence similarity. This divergence suggests a possible alternative source for the RBM coding sequence in nCoV-2019. We identified high sequence similarity in the RBM between nCoV-2019 and a coronavirus genome reconstructed from a viral metagenomic dataset from pangolins possibly indicating a more complex origin for nCoV-2019.

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  1. ScreenIT

    SciScore for 10.1101/2020.02.07.939207: (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
    Data used in the study: Viral metagenomic datasets of hosts that could potentially harbor coronaviruses were downloaded from the NCBI BioProject database.
    NCBI BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)
    Sequence homology plots were visualized using R version 3.6.211 and the ggplot2 visualization package12.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    The RBM segments as well as the Pro-Arg-Arg-Ala (PRRA) amino acid insertion region were excised from the full genome and pairwise aligned on NCBI using blastn and blastx.
    blastx
    suggested: (BLASTX, RRID:SCR_001653)
    Multiple alignments of the both these regions were done using MAFFT v7.31313 and visualized with MEGAX v10.1.714.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    MEGAX
    suggested: None

    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: We detected the following sentences addressing limitations in the study:
    The main limitations of this analysis are the lack of additional viral datasets arising from pangolins or the availability of coronavirus genomes isolated from pangolins that could be used for multiple genome alignments with nCoV-2019. In addition, the current analysis only focuses on the spike protein of nCoV-2019 without exploring additional recombination events that may lead to changes in host tropism. Nonetheless, the identification of a possible recombination event in the host-receptor binding protein of nCoV-2019, suggesting an intermediate host, supports a call for continuous surveillance of species known to be infected by this group of viruses, including pangolins, as well as all small mammals sold in such wet markets as the Huanan Seafood Wholesale Market in Wuhan to better understand and characterize zoonotic transmission events.

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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 10.1101/2020.02.07.939207v1 on bioRxiv