The global population of SARS-CoV-2 is composed of six major subtypes

  1. Ivair José Morais Júnior
  2. Richard Costa Polveiro
  3. Gabriel Medeiros Souza
  4. Daniel Inserra Bortolin
  5. Flávio Tetsuo Sassaki
  6. Alison Talis Martins Lima

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Abstract

The World Health Organization characterized the COVID-19 as a pandemic in March 2020, the second pandemic of the 21 st century. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-stranded RNA betacoronavirus of the family Coronaviridae . Expanding virus populations, as that of SARS-CoV-2, accumulate a number of narrowly shared polymorphisms imposing a confounding effect on traditional clustering methods. In this context, approaches that reduce the complexity of the sequence space occupied by the SARS-CoV-2 population are necessary for a robust clustering. Here, we proposed the subdivision of the global SARS-CoV-2 population into sixteen well-defined subtypes by focusing on the widely shared polymorphisms in nonstructural ( nsp 3, nsp 4, nsp 6, nsp 12, nsp 13 and nsp 14) cistrons, structural ( spike and nucleocapsid ) and accessory ( ORF8 ) genes. Six virus subtypes were predominant in the population, but all sixteen showed amino acid replacements which might have phenotypic implications. We hypothesize that the virus subtypes detected in this study are records of the early stages of the SARS-CoV-2 diversification that were randomly sampled to compose the virus populations around the world, a typical founder effect. The genetic structure determined for the SARS-CoV-2 population provides substantial guidelines for maximizing the effectiveness of trials for testing the candidate vaccines or drugs.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.14.040782: (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
    The calculation of the average number of nucleotide differences per site (nucleotide diversity, π) was conducted in DnaSP v.
    DnaSP
    suggested: (DnaSP, RRID:SCR_003067)
    The detection of polymorphic sites was conducted using PAUP* v. 4.044 and MEGA X45.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)

    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 10.1101/2020.04.14.040782 on bioRxiv