A framework for automated scalable designation of viral pathogen lineages from genomic data

Jakob McBroome*, Adriano de Bernardi Schneider, Cornelius Roemer, Michael T. Wolfinger, Angie S. Hinrichs, Aine Niamh O'Toole, Christopher Ruis, Yatish Turakhia, Andrew Rambaut, Russell Corbett-Detig*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets.

Original languageEnglish
Pages (from-to)550-560
Number of pages11
JournalNature Microbiology
Issue number2
Early online date5 Feb 2024
Publication statusPublished - Feb 2024

Keywords / Materials (for Non-textual outputs)

  • Animals
  • Horses/genetics
  • Phylogeny
  • Encephalitis Virus, Venezuelan Equine/genetics
  • Genomics
  • Base Sequence
  • Genome, Viral
  • SARS-CoV-2/genetics
  • Zika Virus/genetics
  • Zika Virus Infection


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