Natural selection in the evolution of SARS-CoV-2 in bats, not humans, created a highly capable human pathogen

  1. Oscar A. MacLean
  2. Spyros Lytras
  3. Steven Weaver
  4. Joshua B. Singer
  5. Maciej F. Boni
  6. Philippe Lemey
  7. Sergei L. Kosakovsky Pond
  8. David L. Robertson

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Abstract

RNA viruses are proficient at switching host species, and evolving adaptations to exploit the new host’s cells efficiently. Surprisingly, SARS-CoV-2 has apparently required no significant adaptation to humans since the start of the COVID-19 pandemic, with no observed selective sweeps since genome sampling began. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses . In contrast, our analysis detects significant positive episodic diversifying selection acting on the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in ancestral hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor ∼1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. Collectively our results demonstrate the progenitor of SARS-CoV-2 was capable of near immediate human-human transmission as a consequence of its adaptive evolutionary history in bats, not humans.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.28.122366: (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
    The protein sequences of the non-recombinant regions SARS-CoV-2, SARS-CoV-1 and 67 closely related viruses with non-human hosts (bats and pangolins; Supplementary Table 6) were aligned using MAFFT version 7 (L-INS-i)54.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Phylogenies for each codon alignment were inferred using RAxML with a GTR+G nucleotide substitution model55.
    RAxML
    suggested: (RAxML, RRID:SCR_006086)
    All selection analyses were performed in the HyPhy software package v.2.5.1456
    HyPhy
    suggested: (HyPhy, RRID:SCR_016162)
    Time-measured evolutionary histories for NRR1 and NRR2 were inferred using a Bayesian approach, implemented through the Markov chain Monte Carlo (MCMC) framework available in BEAST 1.1048.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    We used the BEAGLE library v362 to increase computational performance.
    BEAGLE
    suggested: (BEAGLE, RRID:SCR_001789)
    Trees were summarized as maximum clade credibility (MCC) trees using TreeAnnotator and visualized using FigTree.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    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 10.1101/2020.05.28.122366v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.05.28.122366: (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
    To search for signatures of positive selection in the phylogenetic tree of the current SARS-CoV-2 outbreak we ran the Bayesian FUBAR software from the HyPhy package27,28 .
    HyPhy
    suggested: (HyPhy, SCR_016162)
    The protein sequences of the non-recombinant regions SARS-CoV-2 , SARSCoV-1 and 67 closely related viruses with non-human hosts ( bats and pangolins ) were aligned using MAFFT version 7 ( L-INS-i)52 .
    MAFFT
    suggested: (MAFFT, SCR_011811)
    Phylogenies for each codon alignment were inferred using RAxML with a GTR+Γ model49 .
    RAxML
    suggested: (RAxML, SCR_006086)

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.05.28.122366v1 on bioRxiv