Genomic variations of SARS-CoV-2 suggest multiple outbreak sources of transmission

  1. Liangsheng Zhang
  2. Jian-Rong Yang
  3. Zhenguo Zhang
  4. Zhenguo Lin

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Abstract

We examined 169 genomes of SARS-CoV-2 and found that they can be classified into two major genotypes, Type I and Type II. Type I can be further divided into Type IA and IB. Our phylogenetic analysis showed that the Type IA resembles the ancestral SARS-CoV-2 most. Type II was likely evolved from Type I and predominant in the infections. Our results suggest that Type II SARS-CoV-2 was the source of the outbreak in the Wuhan Huanan market and it was likely originated from a super-spreader. The outbreak caused by the Type I virus should have occurred somewhere else, because the patients had no direct link to the market. Furthermore, by analyzing three genomic sites that distinguish Type I and Type II strains, we found that synonymous changes at two of the three sites confer higher protein translational efficiencies in Type II strains than in Type I strains, which might explain why Type II strains are predominant, implying that Type II is more contagious (transmissible) than Type I. These findings could be valuable for the current epidemic prevention and control.

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  1. ScreenIT

    SciScore for 10.1101/2020.02.25.20027953: (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
    Alignment of the complete genome sequences and that of BatCoV RaTG13 was carried out by MAFFT [4].
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    We inferred the phylogeny of the SARS-CoV-2 isolates based on the variable sites using the maximum likelihood (ML) method by FastTree [6].
    FastTree
    suggested: (FastTree, RRID:SCR_015501)
    The tRNA Adaptation Index (tAI), an indicator of codon translational efficiency, was computed using the tool Bio::CUA (https://metacpan.org/release/Bio-CUA), and the numbers of human tRNA genes for each codon (used for computing tAI) were downloaded from http://gtrnadb.ucsc.edu.
    Bio::CUA
    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: 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 10.1101/2020.02.25.20027953 on medRxiv