Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny

Nature Methods, vol. 23, pp. 653–662

Abstract

The SARS-CoV-2 genome occupies a unique place in infection biology - it is the most highly sequenced genome on earth (making up over 20% of public sequencing datasets) with fine scale information on sampling date and geography, and has been subject to unprecedented intense analysis. As a result, these phylogenetic data are an incredibly valuable resource for science and public health. However, the vast majority of the data was sequenced by tiling amplicons across the full genome, with amplicon schemes that changed over the pandemic as mutations in the viral genome interacted with primer binding sites. In combination with the disparate set of genome assembly workflows and lack of consistent quality control (QC) processes, the current genomes have many systematic errors that have evolved with the virus and amplicon schemes. These errors have significant impacts on the phylogeny, and therefore over the last few years, many thousands of hours of researchers time has been spent in "eyeballing" trees, looking for artefacts, and then patching the tree. Given the huge value of this dataset, we therefore set out to reprocess the complete set of public raw sequence data in a rigorous amplicon-aware manner, and build a cleaner phylogeny. Here we provide a global tree of 4,471,579 samples, built from a consistently assembled set of high quality consensus sequences from all available public data as of June 2024, viewable at https://viridian.taxonium.org. Each genome was constructed using a novel assembly tool called Viridian (https://github.com/iqbal-lab-org/viridian), developed specifically to process amplicon sequence data, eliminating artefactual errors and mask the genome at low quality positions. We provide simulation and empirical validation of the methodology, and quantify the improvement in the phylogeny. We hope the tree, consensus sequences and Viridian will be a valuable resource for researchers.

Authors 7

1. Gillian Rodger

   University of Oxford

   Affiliation as printed

   Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK

   Nuffield Department of Medicine, University of Oxford, Oxford, UK

2. Sheila Lumley

   John Radcliffe Hospital · University of Oxford

   Affiliation as printed

   Department of Infectious Diseases and Microbiology, John Radcliffe Hospital, Oxford, UK

   Nuffield Department of Medicine, University of Oxford, Oxford, UK

3. Hermione J. Webster

   University of Oxford

   Affiliation as printed

   Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK

   Nuffield Department of Medicine, University of Oxford, Oxford, UK

4. Maija Lappalainen

   University of Helsinki · Helsinki University Hospital · Hospital District of Helsinki and Uusimaa

   Affiliation as printed

   HUS Diagnostic Center, Clinical Microbiology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

5. Gavin Robert Screaton

   University of Oxford

   Affiliation as printed

   Nuffield Department of Medicine, University of Oxford, Oxford, UK

6. Teemu Smura

   University of Helsinki

   Affiliation as printed

   Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland

   Department of Virology, University of Helsinki, Helsinki, Finland

7. Houriiyah Tegally

   Stellenbosch University

   Affiliation as printed

   Centre for Epidemic Response and Innovation (CERI), Stellenbosch University, Stellenbosch, South Africa