Deep phylogenetic-based clustering analysis uncovers new and shared mutations in SARS-CoV-2 variants as a result of directional and convergent evolution

  1. Danilo Rosa Nunes
  2. Carla Torres Braconi
  3. Louisa F. Ludwig-Begall
  4. Clarice Weis Arns
  5. Ricardo Durães-Carvalho

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Abstract

Nearly two decades after the last epidemic caused by a severe acute respiratory syndrome coronavirus (SARS-CoV), newly emerged SARS-CoV-2 quickly spread in 2020 and precipitated an ongoing global public health crisis. Both the continuous accumulation of point mutations, owed to the naturally imposed genomic plasticity of SARS-CoV-2 evolutionary processes, as well as viral spread over time, allow this RNA virus to gain new genetic identities, spawn novel variants and enhance its potential for immune evasion. Here, through an in-depth phylogenetic clustering analysis of upwards of 200,000 whole-genome sequences, we reveal the presence of previously unreported and hitherto unidentified mutations and recombination breakpoints in Variants of Concern (VOC) and Variants of Interest (VOI) from Brazil, India (Beta, Eta and Kappa) and the USA (Beta, Eta and Lambda). Additionally, we identify sites with shared mutations under directional evolution in the SARS-CoV-2 Spike-encoding protein of VOC and VOI, tracing a heretofore-undescribed correlation with viral spread in South America, India and the USA. Our evidence-based analysis provides well-supported evidence of similar pathways of evolution for such mutations in all SARS-CoV-2 variants and sub-lineages. This raises two pivotal points: (i) the co-circulation of variants and sub-lineages in close evolutionary environments, which sheds light onto their trajectories into convergent and directional evolution, and (ii) a linear perspective into the prospective vaccine efficacy against different SARS-CoV-2 strains.

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  1. Version published to 10.1371/journal.pone.0268389
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    SciScore for 10.1101/2021.10.14.21264474: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    2.1 Sequence data and filtering strategy: High-coverage and complete HCoV-229E and HCoV-NL63 (alpha-CoVs), HCoV-OC43, HCoV-HKU1, MERS-CoV, SARS-CoV and SARS-CoV-2 VOC and VOI (beta-CoVs) genome sequences (≥ 29,000 bp), sampled from humans, were retrieved from the Global Initiative on Sharing Avian Influenza Data-EpiCoV (GISAID-EpiCoV) and GenBank databases at different times: February 12th (MERS-CoV, SARS-CoV and SARS-CoV-2), July 12th (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1 and SARS-CoV-2) and August 26th 2021 (SARS-CoV-2), totalling 238,990 sequences.
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    Software and Algorithms
    SentencesResources
    Next, the datasets were aligned by adding coding-sequences related to references for HCoV-229E (NC_002645.1), HCoV-NL63 (NC_005831.2), HCoV-OC43 (NC_006213.1), HCoV-HKU1 (NC_006577.2), MERS-CoV (NC_038294.1), SARS-CoV (NC_004718.3), and SARS-CoV-2 (NC_045512.2), using default settings, with the rapid calculation of full-length multiple sequence alignment of closely-related viral genomes (MAFFT v.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    The ML tree was implemented in FastTree v.
    FastTree
    suggested: (FastTree, RRID:SCR_015501)
    Evidence-based analysis through phylogenetic maximum-likelihood was then performed implementing the Datamonkey web-server and the program Hyphy v.
    Datamonkey
    suggested: (DataMonkey, RRID:SCR_010278)
    Data analyses were carried out using GraphPad Prism v. 5.01 (GraphPad Software, San Diego, California, USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Figures and data visualization were performed using the ggplot2 v.3.3.5 package in the R (RStudio v.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Final graphics were edited with the open-source software drawing tool Inkscape v.1.0.2.
    Inkscape
    suggested: (Inkscape, RRID:SCR_014479)

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    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.

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

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  3. Version published to 10.1101/2021.10.14.21264474 on medRxiv