Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 200

The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.

Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen

Open access
MacLean, Oscar A., Lytras, Spyros, Weaver, Steven, Singer, Joshua B., Boni, Maciej F., Lemey, Philippe, Kosakovsky Pond, Sergei L., Robertson, David L.·2021·PLOS Biology

Abstract

Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early 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 evidence for significant positive episodic diversifying selection acting at the base of 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 these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 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. While an undiscovered “facilitating” intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human–human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pbio.3001115

Cites

20 of 20 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 20 references

Research works printed but not linked: 60

  1. AE Gorbalenya, 2020, The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2, Nature Microbiology, 536
  2. P Zhou, 2020, A pneumonia outbreak associated with a new coronavirus of probable bat origin, Nature, 579, 270, 10.1038/s41586-020-2012-7 · DOI · Paper page
  3. TTY Lam, 2020, Identifying SARS-CoV-2 related coronaviruses in Malayan pangolins, Nature, 583, 282, 10.1038/s41586-020-2169-0 · DOI · Paper page
  4. Y Guan, 2003, Isolation and characterization of viruses related to the SARS coronavirus from animals in Southern China, Science (80), 302, 276, 10.1126/science.1087139 · DOI · Paper page
  5. HD Song, 2005, Cross-host evolution of severe acute respiratory syndrome coronavirus in palm civet and human, Proc Natl Acad Sci U S A, 102, 2430, 10.1073/pnas.0409608102 · DOI · Paper page
  6. RL Graham, 2010, Reservoirs, and the Modular Spike: Mechanisms of Coronavirus Cross-Species Transmission, J Virol, 84, 3134, 10.1128/JVI.01394-09 · DOI · Paper page
  7. VD Menachery, 2020, Trypsin Treatment Unlocks Barrier for Zoonotic Bat Coronavirus Infection, J Virol, 94, e01774, 10.1128/JVI.01774-19 · DOI · Paper page
  8. KG Andersen, 2020, The proximal origin of SARS-CoV-2, Nature Medicine, 450, 10.1038/s41591-020-0820-9 · DOI · Paper page
  9. WR Gallaher, 2020, A palindromic RNA sequence as a common breakpoint contributor to copy-choice recombination in SARS-COV-2, Arch Virol, 1, 3
  10. S Lytras, 2021, Exploring the natural origins of SARS-CoV-2, bioRxiv
  11. CR Parrish, 2008, Cross-Species Virus Transmission and the Emergence of New Epidemic Diseases, Microbiol Mol Biol Rev, 72, 457, 10.1128/MMBR.00004-08 · DOI · Paper page
  12. MEJ Woolhouse, 2001, Population biology of multihost pathogens, Science
  13. XD Lin, 2017, Extensive diversity of coronaviruses in bats from China, Virology, 507, 1, 10.1016/j.virol.2017.03.019 · DOI
  14. R Verity, 2020, Estimates of the severity of coronavirus disease 2019: a model-based analysis, Lancet Infect Dis, 20, P669, 10.1016/S1473-3099(20)30243-7 · DOI · Paper page
  15. ND Grubaugh, 2020, We shouldn’t worry when a virus mutates during disease outbreaks, Nature Microbiology, 529, 10.1038/s41564-020-0690-4 · DOI · Paper page
  16. OA Maclean, 2020, No evidence for distinct types in the evolution of SARS-CoV-2, Virus Evol, 6, veaa034, 10.1093/ve/veaa034 · DOI
  17. M Kimura, 1968, Evolutionary rate at the molecular level, Nature, 217, 624, 10.1038/217624a0 · DOI · Paper page
  18. JL Geoghegan, 2018, The phylogenomics of evolving virus virulence, Nat Rev Genet, 756, 10.1038/s41576-018-0055-5 · DOI · Paper page
  19. MF Boni, 2013, Virulence attenuation during an influenza A/H5N1 pandemic, Philos Trans R Soc B Biol Sci, 368, 20120207, 10.1098/rstb.2012.0207 · DOI
  20. S Peischl, 2013, On the accumulation of deleterious mutations during range expansions, Mol Ecol, 22, 5972, 10.1111/mec.12524 · DOI · Paper page
  21. R Nielsen, 2020, Synonymous mutations and the molecular evolution of SARS-Cov-2 origins, Virus Evolution, veaa098
  22. SL Kosakovsky, 2005, Not So Different After All: A Comparison of Methods for Detecting Amino Acid Sites Under Selection, Mol Biol Evol, 22, 1208, 10.1093/molbev/msi105 · DOI · Paper page
  23. OG Pybus, 2007, Phylogenetic Evidence for Deleterious Mutation Load in RNA Viruses and Its Contribution to Viral Evolution, Mol Biol Evol, 24, 845, 10.1093/molbev/msm001 · DOI · Paper page
  24. M Anisimova, 2001, Accuracy and Power of the Likelihood Ratio Test in Detecting Adaptive Molecular Evolution, Mol Biol Evol, 18, 1585, 10.1093/oxfordjournals.molbev.a003945 · DOI · Paper page
  25. S Duchêne, 2014, Analyses of evolutionary dynamics in viruses are hindered by a time-dependent bias in rate estimates, Proc R Soc B Biol Sci, 281, 20140732, 10.1098/rspb.2014.0732 · DOI · Paper page
  26. SL Kosakovsky, 2006, GARD: a genetic algorithm for recombination detection, Bioinformatics, 22, 3096, 10.1093/bioinformatics/btl474 · DOI · Paper page
  27. SJ Anthony, 2017, Further evidence for bats as the evolutionary source of middle east respiratory syndrome coronavirus, MBio, 8, 10.1128/mBio.00373-17 · DOI · Paper page
  28. G Dudas, 2016, MERS-CoV recombination: implications about the reservoir and potential for adaptation, Virus Evol, 2, vev023, 10.1093/ve/vev023 · DOI
  29. MC Wong, 2020, Evidence of recombination in coronaviruses implicating pangolin origins of nCoV-2019, bioRxiv
  30. MD Smith, 2015, Less Is More: An Adaptive Branch-Site Random Effects Model for Efficient Detection of Episodic Diversifying Selection, Mol Biol Evol, 32, 1342, 10.1093/molbev/msv022 · DOI · Paper page
  31. SR Wisotsky, 2020, Synonymous Site-to-Site Substitution Rate Variation Dramatically Inflates False Positive Rates of Selection Analyses: Ignore at Your Own Peril, Mol Biol Evol, 37, 2430, 10.1093/molbev/msaa037 · DOI
  32. J Felsenstein, 1996, A Hidden Markov Model Approach to Variation Among Sites in Rate of Evolution, Mol Biol Evol, 13, 93, 10.1093/oxfordjournals.molbev.a025575 · DOI · Paper page
  33. D Forni, 2016, Extensive Positive Selection Drives the Evolution of Nonstructural Proteins in Lineage C Betacoronaviruses, J Virol, 90, 3627, 10.1128/JVI.02988-15 · DOI
  34. A Lucaci, 2020, Extra base hits: widespread empirical support for instantaneous multiple-nucleotide changes, bioRxiv
  35. Y Konno, 2020, SARS-CoV-2 ORF3b Is a Potent Interferon Antagonist Whose Activity Is Increased by a Naturally Occurring Elongation Variant, Cell Rep, 108185, 10.1016/j.celrep.2020.108185 · DOI · Paper page
  36. P Simmonds, 2020, →U Hypermutation in the Genomes of SARS-CoV-2 and Other Coronaviruses: Causes and Consequences for Their Short- and Long-Term Evolutionary Trajectories, mSphere, 5, e00408, 10.1128/mSphere.00408-20 · DOI · Paper page
  37. Nicola De Maio, 2020, Virological
  38. A Venkat, 2018, Multinucleotide mutations cause false inferences of lineage-specific positive selection, Nat Ecol Evol
  39. BD Greenbaum, 2008, Patterns of Evolution and Host Gene Mimicry in Influenza and Other RNA Viruses, PLoS Pathog, 4, e1000079, 10.1371/journal.ppat.1000079 · DOI · Paper page
  40. KN Bishop, 2004, APOBEC-mediated editing of viral RNA, Science (80-), 305, 645, 10.1126/science.1100658 · DOI · Paper page
  41. D Kmiec, 2020, CpG frequency in the 5’ third of the env gene determines sensitivity of primary HIV-1 strains to the zinc-finger antiviral protein, MBio, 11, 10.1128/mBio.02903-19 · DOI
  42. DD Pollock, 2020, Viral CpG deficiency provides no evidence that dogs were intermediate hosts for SARS-CoV-2, Mol Biol Evol, 37, 2706, 10.1093/molbev/msaa178 · DOI
  43. S Lytras, 2020, Synonymous Dinucleotide Usage: A Codon-Aware Metric for Quantifying Dinucleotide Representation in Viruses, Viruses, 12, 462, 10.3390/v12040462 · DOI
  44. P Bastide, 2018, Inference of Adaptive Shifts for Multivariate Correlated Traits, Syst Biol, 67, 662, 10.1093/sysbio/syy005 · DOI
  45. H Zhou, 2020, Novel Bat Coronavirus Closely Related to SARS-CoV-2 Contains Natural Insertions at the S1/S2 Cleavage Site of the Spike Protein, Curr Biol, 30, 1, 10.1016/j.cub.2020.09.030 · DOI
  46. MA Suchard, 2018, Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10, Virus Evol, 4, vey016, 10.1093/ve/vey016 · DOI · Paper page
  47. J Lee, 2020, No Evidence of Coronaviruses or Other Potentially Zoonotic Viruses in Sunda pangolins (Manis javanica) Entering the Wildlife Trade via Malaysia, Ecohealth, 17, 406, 10.1007/s10393-020-01503-x · DOI
  48. EC Holmes, 2003, Error thresholds and the constraints to RNA virus evolution, Trends Microbiol
  49. L Van Dorp, 2020, Recurrent mutations in SARS-CoV-2 genomes isolated from mink point to rapid host-adaptation, bioRxiv
  50. N Wang, 2018, Virol Sin, 104
  51. H Li, 2019, Human-animal interactions and bat coronavirus spillover potential among rural residents in Southern China, Biosaf Heal, 1, 84, 10.1016/j.bsheal.2019.10.004 · DOI
  52. DE Anderson, 2020, Lack of cross-neutralization by SARS patient sera towards SARS-CoV-2, Emerg Microbes Infect, 9, 900, 10.1080/22221751.2020.1761267 · DOI
  53. A Stamatakis, 2014, RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies, Bioinforma Appl, 30, 1312, 10.1093/bioinformatics/btu033 · DOI · Paper page
  54. SR Wisotsky, Synonymous site-to-site substitution rate variation dramatically inflates false positive rates of selection analyses: ignore at your own peril, Mol Biol Evol
  55. SL Kosakovsky Pond, 2019, HyPhy 2.5-A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies, Mol Biol Evol, 37, 295, 10.1093/molbev/msz197 · DOI · Paper page
  56. D Charif, 2007, Structural Approaches to Sequence Evolution, 207, 10.1007/978-3-540-35306-5_10 · DOI · Paper page
  57. WH Li, 1993, Unbiased estimation of the rates of synonymous and nonsynonymous substitution, Journal of Molecular Evolution, 96, 10.1007/BF02407308 · DOI · Paper page
  58. DP Martin, 2015, RDP4: Detection and analysis of recombination patterns in virus genomes, Virus Evol, 1, vev003, 10.1093/ve/vev003 · DOI · Paper page
  59. M Worobey, 2014, Rambaut A. A synchronized global sweep of the internal genes of modern avian influenza virus, Nature, 508, 254, 10.1038/nature13016 · DOI · Paper page
  60. DL Ayres, 2019, BEAGLE 3: Improved Performance, Scaling, and Usability for a High-Performance Computing Library for Statistical Phylogenetics, Syst Biol, 68, 1052, 10.1093/sysbio/syz020 · DOI · Paper page

Cited by

See all 200

Metadata

Authors
MacLean, O. A., Lytras, S., Weaver, S., Singer, J. B., Boni, M. F., Lemey, P., Kosakovsky Pond, S. L., & Robertson, D. L.
Venue
PLOS Biology
Published
2021-03-12
Volume
19
Issue
3
Pages
e3001115
ISSN
  • 1544-9173 (ISSN-L)
  • 1545-7885
OpenAlex
W3135415606
Cited by
200
References
20
FWCI
12.73
Type
journal article
Language
en
Open access
gold
Funders
  • Medical Research Council (MC_UU_1201412)
  • Wellcome Trust (220977/Z/20/Z, 206369/Z/17/Z, 206298/Z/17/Z)
  • National Institutes of Health (R01 AI134384, NIH/NIAID Center of Excellence in Influenza Research and Surveillance contract (HHS N272201400007C))
  • National Science Foundation (2027196)
  • European Research Council (725422-ReservoirDOCS)
  • European Union's Horizon 2020 project MOOD (874850)
  • Research Foundation - Flanders (G066215N, G0D5117N and G0B9317N)
  • Bill and Melinda Gates Foundation (INV-005517)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen. https://app.cochat.ai/papers/10.1371/journal.pbio.3001115
The paper
MacLean, O. A., Lytras, S., Weaver, S., Singer, J. B., Boni, M. F., Lemey, P., Kosakovsky Pond, S. L., & Robertson, D. L. (2021). Natural selection in the evolution of SARS-CoV-2 in bats created a generalist virus and highly capable human pathogen. PLOS Biology. https://doi.org/10.1371/journal.pbio.3001115

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.