A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages

  1. Simon Dellicour
  2. Keith Durkin
  3. Samuel L Hong
  4. Bert Vanmechelen
  5. Joan Martí-Carreras
  6. Mandev S Gill
  7. Cécile Meex
  8. Sébastien Bontems
  9. Emmanuel André
  10. Marius Gilbert
  11. Conor Walker
  12. Nicola De Maio
  13. Nuno R Faria
  14. James Hadfield
  15. Marie-Pierre Hayette
  16. Vincent Bours
  17. Tony Wawina-Bokalanga
  18. Maria Artesi
  19. Guy Baele
  20. Piet Maes

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Abstract

Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement.

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  1. Version published to 10.1093/molbev/msaa284
  2. Version published to 10.1101/2020.05.05.078758v5 on bioRxiv
  3. Version published to 10.1101/2020.05.05.078758v4 on bioRxiv
  4. Version published to 10.1101/2020.05.05.078758v3 on bioRxiv
  5. ScreenIT

    SciScore for 10.1101/2020.05.05.078758: (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
    Sequencing was carried out on a MinION sequencer using R9.4.1 flow cells and MinKNOW 2.0 software.
    MinKNOW
    suggested: None
    We then cleaned the alignment by manually trimming the 5’ and 3’ untranslated regions (RefSeq NC_045512.2) and gap-only sites.
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    This model configuration was selected as the best GTR model using IQ-TREE?
    IQ-TREE
    suggested: (IQ-TREE, RRID:SCR_017254)
    Preliminary discrete phylogeographic analysis: We performed a preliminary phylogeographic analysis using the discrete diffusion model12 implemented in the software package BEAST 1.1014.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    While new viral genomes are sequenced and released daily, a limitation could paradoxically arise from the non-accessibility of associated metadata. Indeed, without sufficiently precise data about the geographic origin of each genome, it is not feasible to perform a spatially-explicit phylogeographic inference. In the same way that viral genomes are deposited in databases like GISAID, metadata should also be made available to enable comprehensive epidemiological investigations with a similar approach as we presented here.

    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

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  6. Version published to 10.1101/2020.05.05.078758v2 on bioRxiv
  7. Version published to 10.1101/2020.05.05.078758v1 on bioRxiv