4.8 Article

Ultrafast Sample placement on Existing tRees (UShER) enables real-time phylogenetics for the SARS-CoV-2 pandemic

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NATURE GENETICS
卷 53, 期 6, 页码 809-+

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NATURE PORTFOLIO
DOI: 10.1038/s41588-021-00862-7

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资金

  1. Schmidt Futures Foundation [SF 857]
  2. NIH [5R01HG010485, R35GM128932]
  3. Alfred P. Sloan Foundation Fellowship [T32HG008345, F31HG010584]
  4. National Human Genome Research Institute [5U41HG002371-19]
  5. Center for Information Technology Research in the Interest of Society [2020-0000000020]
  6. University of California Office of the President Emergency COVID-19 Research Seed Fund [R00RG2456]
  7. European Molecular Biology Laboratory
  8. Australian Research Council [DP200103151]
  9. Chan Zuckerberg Initiative grant
  10. Australian Research Council [DP200103151] Funding Source: Australian Research Council

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UShER is an efficient method that aids in real-time analysis of viral evolution during the COVID-19 pandemic by facilitating the addition of new SARS-CoV-2 genome sequences onto the existing phylogeny. The unprecedented accumulation of viral genome sequences is leading to a new era of 'genomic contact tracing' using viral genomes to trace local transmission dynamics. UShER addresses the challenge of placing new sequences onto the already large viral phylogeny, thus improving the speed of phylogenetic placement and data visualization for real-time contact tracing.
Ultrafast Sample placement on Existing tRees (UShER) is an efficient method that facilitates the addition of new SARS-CoV-2 genome sequences onto the existing phylogeny, aiding in real-time analysis of viral evolution during the COVID-19 pandemic. As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering in a new era of 'genomic contact tracing'-that is, using viral genomes to trace local transmission dynamics. However, because the viral phylogeny is already so large-and will undoubtedly grow many fold-placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach greatly improves the speed of phylogenetic placement of new samples and data visualization, making it possible to complete the placements under the constraints of real-time contact tracing. Thus, our method addresses an important need for maintaining a fully updated reference phylogeny. We make these tools available to the research community through the University of California Santa Cruz SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for SARS-CoV-2 specifically for laboratories worldwide.

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