Detection of potential new SARS-CoV-2 Gamma-related lineage in Tocantins shows the spread and ongoing evolution of P.1 in Brazil

  1. U.J.B. Souza
  2. R.N. Santos
  3. A. Belmok
  4. F.L. Melo
  5. J.D. Galvão
  6. S.B. Damasceno
  7. T.C.V. Rezende
  8. M.S. Andrade
  9. B.M. Ribeiro
  10. J.C. Ribeiro Junior
  11. R.F. Carvalho
  12. I.G.C. Santos
  13. M.S. Oliveira
  14. F.R. Spilki
  15. F.S. Campos

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Abstract

After more than a year of the pandemic situation of COVID-19, the United Kingdom (UK), South Africa, and Brazil became the epicenter of new lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Variants of Concern (VOCs) were identified through a continuous genomic surveillance global effort, the B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), and P.1 (Gamma) harboring a constellation set of mutations. This research aims to: (i) report the predominance of the Gamma (P.1) lineage presenting the epidemiological situation of the SARS-CoV-2 genomic surveillance at the state of Tocantins, and (ii) describe the emergence of possible new mutations and viral variants with the potential new lineage (P1-related) represented by 8 genomes from the Tocantins harboring the mutation L106F in ORF3a. At the moment, 6,687 SARS-CoV-2 genomes from GISAID carry this mutation. The whole-genome sequencing has an important role in understanding the evolution and genomic diversity of SARS-CoV-2, thus, the continuous monitoring will help in the control measures and restrictions imposed by the secretary of health of the state to prevent the spread of variants.

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    SciScore for 10.1101/2021.06.30.450617: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsIRB: The study was approved by the Ethics Committee (33202820.7.1001.5348).
    Sex as a biological variablePatients were aged between 01 and 80 years old, being 54.2% men and 45.8% women.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    2.1.2 [16] under the Generalized Time Reversible GRT model of nucleotide substitution with empirical base frequencies (+F) and invariable sites (+I), as selected by the ModelFinder software.
    ModelFinder
    suggested: None
    The final dataset consisting of 851 was aligned using MAFFT v.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    A Maximum Likelihood tree was generated using IQ-TREE v.
    IQ-TREE
    suggested: (IQ-TREE, RRID:SCR_017254)

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.06.30.450617v1 on bioRxiv