Nature MethodsBioinformaticsPeer-reviewed journal article
Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny
Martin HuntiD, Angie S. HinrichsiD, Daniel AndersoniD, Lily KarimiD, Bethany L. DearloveiD, Jeff KnaggsiD, Bede ConstantinidesiD, Philip William FowleriD, Gillian RodgeriD, Teresa StreetiD, Sheila LumleyiD, Hermione J. WebsteriD, Theo SandersoniD, Christopher RuisiD, Benjamin KotzeniD, Nicola de MaioiD, Lucas N. Amenga-Etego, Dominic S. Y. AmuzuiD, Martin Avaro, Gordon A. AwandareiD, Reuben Ayivor-DjanieiD, Timothy BarkhamiD, Matthew BashtoniD, Elizabeth M. Batty, Yaw BediakoiD, , Djin-Ye Oh
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.
- organism: virus
- assay: whole-genome sequencing
- research focus: phylogenetics / evolution
- approach: statistical model
- approach: simulation
- Citations
- 19
- FWCI
- 16.53
- Field percentile
- top 1%
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