A phylogeny-based metric for estimating changes in transmissibility from recurrent mutations in SARS-CoV-2

  1. Damien Richard
  2. Liam P Shaw
  3. Rob Lanfear
  4. Russell Corbett-Detig
  5. Angie Hinrichs
  6. Jakob McBroome
  7. Yatish Turakhia
  8. Mislav Acman
  9. Christopher J Owen
  10. Cedric CS Tan
  11. Lucy van Dorp
  12. François Balloux

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019 and spread globally to cause the COVID-19 pandemic. Despite the constant accumulation of genetic variation in the SARS-CoV-2 population, there was little evidence for the emergence of significantly more transmissible lineages in the first half of 2020. Starting around November 2020, several more contagious and possibly more virulent ‘Variants of Concern’ (VoCs) were reported in various regions of the world. These VoCs share some mutations and deletions that haven arisen recurrently in distinct genetic backgrounds. Here, we build on our previous work modelling the association of mutations to SARS-CoV-2 transmissibility and characterise the contribution of individual recurrent mutations and deletions to estimated viral transmissibility. We then assess how patterns of estimated transmissibility in all SARS-CoV-2 clades have varied over the course of the COVID-19 pandemic by summing transmissibility estimates for all individual mutations carried by any sequenced genome analysed. Such an approach recovers the Delta variant (21A) as the most transmissible clade currently in circulation, followed by the Alpha variant (20I). By assessing transmissibility over the time of sampling, we observe a tendency for estimated transmissibility within clades to slightly decrease over time in most clades. Although subtle, this pattern is consistent with the expectation of a decay in transmissibility in mainly non-recombining lineages caused by the accumulation of weakly deleterious mutations. SARS-CoV-2 remains a highly transmissible pathogen, though such a trend could conceivably play a role in the turnover of different global viral clades observed over the pandemic so far.

Caveats

  • This work is not about the severity of disease. We do not analyse the severity of disease. We do not present any evidence that SARS-CoV-2 has decreased in severity.

  • Lineage replacement dynamics are affected by many factors. The trend we recover for a decrease in inferred transmissibility of a clade over time is a small effect. We caution against over-interpretation. This result would not affect the management of the SARS-CoV-2 pandemic: for example, we make no claims about any impact on the efficacy of particular non-pharmaceutical interventions (NPIs).

  • Our phylogeny-based method to infer changes in estimated transmissibility due to recurrent mutations and deletions makes a number of simplifying assumptions. These may not all be valid. The consistent trend for the slight decrease we report might be due to an as-yet-unidentified systematic bias.

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  1. Version published to 10.1101/2021.05.06.442903v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.05.06.442903: (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

    Software and Algorithms
    SentencesResources
    We applied HomoplasyFinder v0.0.0.969 to this alignment and the GISAID Audacity tree to quantify the number of independent emergences of all mutations and deletions considered and to identify the parental node of every recurrent mutation/deletion in the dataset.
    HomoplasyFinder
    suggested: (HomoplasyFinder, RRID:SCR_017300)
    Influence of phylogenetic misplacement and sample representation on CEGA estimates: Given recurrent mutations may be observed due to poor phylogenetic placement of accessions, we assessed the influence of phylogenetic uncertainty on the CEGA scores recovered.
    CEGA
    suggested: (Geom-matching SRC, RRID:SCR_018424)

    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.

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  3. Version published to 10.1101/2021.05.06.442903v1 on bioRxiv