Stability of SARS-CoV-2 phylogenies

Abstract

The SARS-CoV-2 pandemic has led to unprecedented, nearly real-time genetic tracing due to the rapid community sequencing response. Researchers immediately leveraged these data to infer the evolutionary relationships among viral samples and to study key biological questions, including whether host viral genome editing and recombination are features of SARS-CoV-2 evolution. This global sequencing effort is inherently decentralized and must rely on data collected by many labs using a wide variety of molecular and bioinformatic techniques. There is thus a strong possibility that systematic errors associated with lab—or protocol—specific practices affect some sequences in the repositories. We find that some recurrent mutations in reported SARS-CoV-2 genome sequences have been observed predominantly or exclusively by single labs, co-localize with commonly used primer binding sites and are more likely to affect the protein-coding sequences than other similarly recurrent mutations. We show that their inclusion can affect phylogenetic inference on scales relevant to local lineage tracing, and make it appear as though there has been an excess of recurrent mutation or recombination among viral lineages. We suggest how samples can be screened and problematic variants removed, and we plan to regularly inform the scientific community with our updated results as more SARS-CoV-2 genome sequences are shared ( https://virological.org/t/issues-with-sars-cov-2-sequencing-data/473 and https://virological.org/t/masking-strategies-for-sars-cov-2-alignments/480 ). We also develop tools for comparing and visualizing differences among very large phylogenies and we show that consistent clade- and tree-based comparisons can be made between phylogenies produced by different groups. These will facilitate evolutionary inferences and comparisons among phylogenies produced for a wide array of purposes. Building on the SARS-CoV-2 Genome Browser at UCSC, we present a toolkit to compare, analyze and combine SARS-CoV-2 phylogenies, find and remove potential sequencing errors and establish a widely shared, stable clade structure for a more accurate scientific inference and discourse.

References 79

1. 1.

   NCBI Staff. NCBI Insights: INSDC Statement on SARS-CoV-2 sequence data sharing during COVID-19. 17 Aug 2020 [cited 26 Aug 2020]. Available: https://ncbiinsights.ncbi.nlm.nih.gov/2020/08/17/insdc-covid-data-sharing/

   Not in our library

2. 2.

   Maurano MT, Ramaswami S, Westby G, Zappile P, Dimartino D, Shen G, et al Sequencing identifies multiple, early introductions of SARS-CoV2 to New York City Region.

   Not in our library10.1101/2020.04.15.20064931

3. 3.
   Genomic surveillance reveals multiple introductions of SARS-CoV-2 into Northern California · 2020

   No notice
4. 4.

   Zhang Y-Z, Holmes EC. A Genomic Perspective on the Origin and Emergence of SARS-CoV-2. Cell. 2020;181:223–227.

   Not in our library10.1016/j.cell.2020.03.035

5. 5.

   Bal A, Destras G, Gaymard A, Bouscambert-Duchamp M, Valette M, Escuret V, et al Molecular characterization of SARS-CoV-2 in the first COVID-19 cluster in France reveals an amino-acid deletion in nsp2 (Asp268Del).

   Not in our library10.1016/j.cmi.2020.03.020

6. 6.

   Grubaugh ND, Ladner JT, Lemey P, Pybus OG, Rambaut A, Holmes EC, et al Tracking virus outbreaks in the twenty-first century. Nat Microbiol. 2019;4:10–19.

   Not in our library10.1038/s41564-018-0296-2

7. 7.

   Yi H. 2019 novel coronavirus is undergoing active recombination. Clin Infect Dis. 2020

   Not in our library10.1093/cid/ciaa219

8. 8.

   Chaw S-M, Tai J-H, Chen S-L, Hsieh C-H, Chang S-Y, Yeh S-H, et al The origin and underlying driving forces of the SARS-CoV-2 outbreak.

   Not in our library10.1186/s12929-020-00665-8

9. 9.

   van Dorp L, Acman M, Richard D, Shaw LP, Ford CE, Ormond L, et al Emergence of genomic diversity and recurrent mutations in SARS-CoV-2. Infection, Genetics and Evolution. 2020 p. 104351

   Not in our library10.1016/j.meegid.2020.104351

10. 10.

    Li Y, Wang Y, Qiu Y, Gong Z, Deng L, Pan M, et al SARS-CoV-2 Spike Glycoprotein Receptor Binding Domain is Subject to Negative Selection with Predicted Positive Selection Mutations.

    Not in our library10.1101/2020.05.04.077842

11. 11.

    Victorovich KV, Rajanish G, Aleksandrovna KT, Krishna KS, Nicolaevich SA, Vitoldovich PV. Translation-associated mutational U-pressure in the first ORF of SARS-CoV-2 and other coronaviruses.

    Not in our library10.3389/fmicb.2020.559165

12. 12.

    Zehender G, Lai A, Bergna A, Meroni L, Riva A, Balotta C, et al GENOMIC CHARACTERISATION AND PHYLOGENETIC ANALYSIS OF SARS-COV-2 IN ITALY.

    Not in our library10.1101/2020.03.15.20032870

13. 13.

    Gardy JL, Loman NJ. Towards a genomics-informed, real-time, global pathogen surveillance system. Nat Rev Genet. 2018;19:9–20.

    Not in our library10.1038/nrg.2017.88

14. 14.
    Evolving geographic diversity in SARS-CoV2 and in silico analysis of replicating enzyme 3CLpro targeting repurposed drug candidates · 2020

    Not checked
15. 15.

    Adebali O, Bircan A, Circi D, Islek B, Kilinc Z, Selcuk B, et al Phylogenetic Analysis of SARS-CoV-2 Genomes in Turkey.

    Not in our library10.3906/biy-2005-35

16. 16.

    Hadfield J, Megill C, Bell SM, Huddleston J, Potter B, Callender C, et al Nextstrain: real-time tracking of pathogen evolution. Bioinformatics. 2018 pp. 4121–4123.

    Not in our library10.1093/bioinformatics/bty407

17. 17.
    nextflu: real-time tracking of seasonal influenza virus evolution in humans · 2015

    No notice
18. 18.

    Rambaut A, Holmes EC, Hill V, O’Toole Á, McCrone JT, Ruis C, et al A dynamic nomenclature proposal for SARS-CoV-2 to assist genomic epidemiology.

    Not in our library10.1038/s41564-020-0770-5

19. 19.

    Mavian C, Marini S, Prosperi M, Salemi M. A snapshot of SARS-CoV-2 genome availability up to 30th March, 2020 and its implications.

    Not in our library10.1101/2020.04.01.020594

20. 20.

    Fountain-Jones NM, Appaw RC, Carver S, Didelot X, Volz EM, Charleston M. Emerging phylogenetic structure of the SARS-CoV-2 pandemic. bioRxiv. 2020 p. 202005.19.103846.

    Not in our library10.1101/2020.05.19.103846

21. 21.

    Bogner P, Capua I, Lipman DJ, Cox NJ. A global initiative on sharing avian flu data. Nature. 2006 pp. 981–981.

    Not in our library10.1038/442981a

22. 22.

    Rayko M, Komissarov A. Quality control of low-frequency variants in SARS-CoV-2 genomes.

    Not in our library10.1101/2020.04.26.062422

23. 23.

    Akther S, Bezrucenkovas E, Sulkow B, Panlasigui C. CoV Genome Tracker: tracing genomic footprints of Covid-19 pandemic. bioRxiv. 2020 Available: https://www.biorxiv.org/content/10.1101/2020.04.10.036343v1.abstract

    Not in our library

24. 24.

    DeMaio N, Walker C, Borges R, Weilguny L, Slodkowicz G, Goldman N. Issues with SARS-CoV-2 sequencing data. In: Virological [Internet]. 5 5 2020 [cited 13 May 2020]. Available: http://virological.org/t/issues-with-sars-cov-2-sequencing-data/473

    Not in our library

25. 25.

    Freeman TM, Genomics England Research Consortium, Wang D, Harris J. Genomic loci susceptible to systematic sequencing bias in clinical whole genomes. Genome Res. 2020;30: 415–426.

    Not in our library10.1101/gr.255349.119

26. 26.
    No evidence for increased transmissibility from recurrent mutations in SARS-CoV-2 · 2020

    No notice
27. 27.

    Korber B, Fischer WM, Gnanakaran S, Yoon H, Theiler J, Abfalterer W, et al Spike mutation pipeline reveals the emergence of a more transmissible form of SARS-CoV-2.

    Not in our library10.1101/2020.04.29.069054

28. 28.
    SARS-CoV-2 within-host diversity and transmission · 2021

    No notice
29. 29.

    Banerjee AK, Begum F, Ray U. Mutation Hot Spots in Spike Protein of COVID-19.

    Not in our library10.20944/preprints202004.0281.v1

30. 30.

    Laamarti M, Alouane T, Kartti S, Chemao-Elfihri MW, Hakmi M, Essabbar A, et al Large scale genomic analysis of 3067 SARS-CoV-2 genomes reveals a clonal geo-distribution and a rich genetic variations of hotspots mutations.

    Not in our library10.1371/journal.pone.0240345

31. 31.

    Wang C, Liu Z, Chen Z, Huang X, Xu M, He T, et al The establishment of reference sequence for SARS-CoV-2 and variation analysis. Journal of Medical Virology. 2020 pp. 667–674.

    Not in our library10.1002/jmv.25762

32. 32.

    Wang Y, Mao J-M, Wang G-D, Qiu Z, Yao Q, Chen K-P. Human SARS-CoV-2 has evolved to reduce CG dinucleotide in its open reading frames.

    Not in our library10.1038/s41598-020-69342-y

33. 33.

    Wen F, Yu H, Guo J, Li Y, Luo K, Huang S. Identification of the hyper-variable genomic hotspot for the novel coronavirus SARS-CoV-2. J Infect. 2020

    Not in our library10.1016/j.jinf.2020.02.027

34. 34.
    Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant · 2020

    No notice
35. 35.
    Evolutionary Trajectory for the Emergence of Novel Coronavirus SARS-CoV-2 · 2020

    No notice
36. 36.

    Wertheim JO. A Glimpse Into the Origins of Genetic Diversity in the Severe Acute Respiratory Syndrome Coronavirus 2. Clinical Infectious Diseases. 2020

    Not in our library10.1093/cid/ciaa213

37. 37.

    Vasilarou M, Alachiotis N, Garefalaki J, Beloukas A, Pavlidis P. Population genomics insights into the recent evolution of SARS-CoV-2.

    Not in our library10.1101/2020.04.21.054122

38. 38.

    Ou J, Zhou Z, Dai R, Zhang J, Lan W, Zhao S, et al Emergence of RBD mutations in circulating SARS-CoV-2 strains enhancing the structural stability and human ACE2 receptor affinity of the spike protein. bioRxiv. 2020 p. 202003.15.991844.

    Not in our library10.1101/2020.03.15.991844

39. 39.

    Sashittal P, Luo Y, Peng J, El-Kebir M. Characterization of SARS-CoV-2 viral diversity within and across hosts. bioRxiv. 2020 p. 202005.07.083410.

    Not in our library10.1101/2020.05.07.083410

40. 40.

    Velazquez-Salinas L, Zarate S, Eberl S, Gladue DP, Novella I, Borca MV. Positive selection of ORF3a and ORF8 genes drives the evolution of SARS-CoV-2 during the 2020 COVID-19 pandemic.

    Not in our library10.3389/fmicb.2020.550674

41. 41.

    Brianna SC, Paskov K, Stockham N, J-Y J, Varma M, Washington P, et al Common Microdeletions in SARS-CoV-2 Sequences. In: Virological [Internet]. 15 5 2020 [cited 16 May 2020]. Available: http://virological.org/t/common-microdeletions-in-sars-cov-2-sequences/485

    Not in our library

42. 42.

    Ramazzotti D, Angaroni F, Maspero D, Gambacorti-Passerini C, Antoniotti M, Graudenzi A, et al Characterization of intra-host SARS-CoV-2 variants improves phylogenomic reconstruction and may reveal functionally convergent mutations.

    Not in our library10.1101/2020.04.22.044404

43. 43.

    Dellicour S, Durkin K, Hong SL, Vanmechelen B, Martí-Carreras J, Gill MS, et al A phylodynamic workflow to rapidly gain insights into the dispersal history and dynamics of SARS-CoV-2 lineages.

    Not in our library10.1101/2020.05.05.078758

44. 44.

    Morel B, Barbera P, Czech L, Bettisworth B, Hübner L, Lutteropp S, et al Phylogenetic analysis of SARS-CoV-2 data is difficult. bioRxiv. 2020

    Not in our library10.1101/2020.08.05.239046

45. 45.

    Rice AM, Morales AC, Ho AT, Mordstein C, Mühlhausen S, Watson S, et al Evidence for strong mutation bias towards, and selection against, T/U content in SARS-CoV2: implications for attenuated vaccine design.

    Not in our library10.1101/2020.05.11.088112

46. 46.
    Extreme Genomic CpG Deficiency in SARS-CoV-2 and Evasion of Host Antiviral Defense · 2020

    No notice
47. 47.

    Fitch WM. Toward Defining the Course of Evolution: Minimum Change for a Specific Tree Topology. Systematic Zoology. 1971 p. 406

    Not in our library10.2307/2412116

48. 48.

    Sankoff D. Minimal Mutation Trees of Sequences. SIAM Journal on Applied Mathematics. 1975 pp. 35–42.

    Not in our library10.1137/0128004

49. 49.
    Rampant C→U Hypermutation in the Genomes of SARS-CoV-2 and Other Coronaviruses: Causes and Consequences for Their Short- and Long-Term Evolutionary Trajectories · 2020

    No notice
50. 50.

    Bishop KN, Holmes RK, Sheehy AM, Malim MH. APOBEC-mediated editing of viral RNA. Science. 2004;305:645

    Not in our library10.1126/science.1100658

51. 51.

    Giorgio SD, Di Giorgio S, Martignano F, Torcia MG, Mattiuz G, Conticello SG. Evidence for host-dependent RNA editing in the transcriptome of SARS-CoV-2.

    Not in our library10.1126/sciadv.abb5813

52. 52.
    Analysis of error profiles in deep next-generation sequencing data · 2019

    No notice
53. 53.
    Evaluation of genomic high-throughput sequencing data generated on Illumina HiSeq and Genome Analyzer systems · 2011

    No notice
54. 54.
    Nanopore sequencing and assembly of a human genome with ultra-long reads · 2018

    No notice
55. 55.
    Challenges and opportunities in estimating viral genetic diversity from next-generation sequencing data · 2012

    No notice
56. 56.

    Kugelman JR, Wiley MR, Nagle ER, Reyes D, Pfeffer BP, Kuhn JH, et al Error baseline rates of five sample preparation methods used to characterize RNA virus populations. PLoS One. 2017;12:e0171333

    Not in our library10.1371/journal.pone.0171333

57. 57.

    Orton RJ, Wright CF, Morelli MJ, King DJ, Paton DJ, King DP, et al Distinguishing low frequency mutations from RT-PCR and sequence errors in viral deep sequencing data. BMC Genomics. 2015;16:229

    Not in our library10.1186/s12864-015-1456-x

58. 58.

    McElroy K, Thomas T, Luciani F. Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions. Microb Inform Exp. 2014;4:1

    Not in our library10.1186/2042-5783-4-1

59. 59.
    IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era · 2020

    No notice
60. 60.

    Hoang DT, Chernomor O, von Haeseler A, Minh BQ, Vinh LS. UFBoot2: Improving the Ultrafast Bootstrap Approximation. Mol Biol Evol. 2018;35:518–522.

    Not in our library10.1093/molbev/msx281

61. 61.

    Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, et al The variant call format and VCFtools. Bioinformatics. 2011;27:2156–2158.

    Not in our library10.1093/bioinformatics/btr330

62. 62.

    Fernandes JD, Hinrichs AS, Clawson H, Gonzalez JN, Lee BT, Nassar LR, et al The UCSC SARS-CoV-2 Genome Browser.

    Not in our library10.1038/s41588-020-0700-8

63. 63.

    Sanjuán R, Nebot MR, Chirico N, Mansky LM, Belshaw R. Viral Mutation Rates. Journal of Virology. 2010 pp. 9733–9748.

    Not in our library10.1128/jvi.00694-10

64. 64.

    Bogdanowicz D, Giaro K, Wróbel B. TreeCmp: Comparison of Trees in Polynomial Time. Evolutionary Bioinformatics. 2012 p. EBO.S9657.

    Not in our library10.4137/ebo.s9657

65. 65.

    Malafiejska A. New scalable measure for comparing phylogenetic trees. 2008 1st International Conference on Information Technology. 2008.

    Not in our library10.1109/inftech.2008.4621645

66. 66.

    Kendall M, Eldholm V, Colijn C. Comparing phylogenetic trees according to tip label categories.

    Not in our library10.1101/251710

67. 67.

    Nye TMW. Trees of Trees: An Approach to Comparing Multiple Alternative Phylogenies. Systematic Biology. 2008 pp. 785–794.

    Not in our library10.1080/10635150802424072

68. 68.

    Bogdanowicz D. Comparing phylogenetic trees using a minimum weight perfect matching. 2008 1st International Conference on Information Technology. 2008.

    Not in our library10.1109/inftech.2008.4621680

69. 69.

    Robinson DF, Foulds LR. Comparison of phylogenetic trees. Mathematical Biosciences. 1981 pp. 131–147.

    Not in our library10.1016/0025-5564(81)90043-2

70. 70.

    Huson DH, Scornavacca C. Dendroscope 3: an interactive tool for rooted phylogenetic trees and networks. Syst Biol. 2012;61:1061–1067.

    Not in our library10.1093/sysbio/sys062

71. 71.

    Revell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods in Ecology and Evolution. 2012 pp. 217–223.

    Not in our library10.1111/j.2041-210x.2011.00169.x

72. 72.

    Sukumaran J, Holder MT. DendroPy: a Python library for phylogenetic computing. Bioinformatics. 2010;26:1569–1571.

    Not in our library10.1093/bioinformatics/btq228

73. 73.

    Hodcroft EB, Hadfield J, Neher RA, Bedford T. Year-letter Genetic Clade Naming for SARS-CoV-2 on Nextstain.org. In: Virological [Internet]. 2 6 2020 [cited 8 Jun 2020]. Available: https://virological.org/t/year-letter-genetic-clade-naming-for-sars-cov-2-on-nextstain-org/498

    Not in our library

74. 74.
    An integrated national scale SARS-CoV-2 genomic surveillance network · 2020

    No notice
75. 75.

    Margush T, McMorris FR. Consensus n-trees. Bulletin of Mathematical Biology. 1981 pp. 239–244.

    Not in our library10.1007/bf02459446

76. 76.
    GISAID: Global initiative on sharing all influenza data – from vision to reality · 2017

    No notice
77. 77.
    GISAID: Global initiative on sharing all influenza data – from vision to reality · 2017

    No notice
78. 78.

    Vinh NX, Epps J, Bailey J. Information theoretic measures for clusterings comparison. Proceedings of the 26th Annual International Conference on Machine Learning-ICML ‘09. 2009.

    Not in our library10.1145/1553374.1553511

79. 79.

    Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–274.

    Not in our library10.1093/molbev/msu300

Cited by papers we hold 4

• A pseudovirus system enables deep mutational scanning of the full SARS-CoV-2 spike · 2023
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• Fitness effects of mutations to SARS-CoV-2 proteins · 2023
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• Pandemic-scale phylogenomics reveals the SARS-CoV-2 recombination landscape · 2022
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• Mutation Rates and Selection on Synonymous Mutations in SARS-CoV-2 · 2021
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