Ultrafast Sample Placement on Existing Trees (UShER) Empowers Real-Time Phylogenetics for the SARS-CoV-2 Pandemic

Abstract

As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering a new era of “genomic contact tracing” – that is, using viral genome sequences 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 improves the speed of phylogenetic placement of new samples and data visualization by orders of magnitude, making it possible to complete the placements under real-time constraints. Our method also provides the key ingredient for maintaining a fully-updated reference phylogeny. We make these tools available to the research community through the UCSC 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 laboratories worldwide.Software AvailabilityUSHER is available to users through the UCSC Genome Browser at https://genome.ucsc.edu/cgi-bin/hgPhyloPlace. The source code and detailed instructions on how to compile and run UShER are available from https://github.com/yatisht/usher.

Sequencing the pandemic: rapid and high-throughput processing and analysis of COVID-19 clinical samples for 21st century public health

“…For retrospective studies, time can allow for more robust phylogenetic analyses including smart subsamplers 35 , such as NextStrain 17 and other commonly used phylogenetic tools; however their employment can significantly add time to a rapid response. The UShER tool 34 , which can rapidly place genomes onto an existing SARS-CoV-2 phylogenetic tree, can greatly speed-up the final analysis. Parsing the output of UShER generates a subset of public genomes that are phylogenetically close to the samples of interest.…”

“…For subsequent, more sophisticated phylogenetic analyses, phylogenetic trees were constructed in NextStrain 17 , with genomes from GISAID subsampled by uploading our genomes of interest to the UCSC UShER (UShER: Ultrafast Sample placement on Existing tRee) tool 34 , identifying relevant genomes (those most related to our genomes of interest), and further reducing that set of genomes when necessary with genome-sampler 35 .…”

Mutation rates and selection on synonymous mutations in SARS-CoV-2

“…The low mutation rate observed in SARS-CoV-2 makes parsimony an efficient and reliable approach to infer mutational histories [ 56 ]. However, phylogenetic inference from large SARS-CoV-2 datasets is difficult due to elevated computational demand and phylogenetic uncertainty [ 43 ], and we cannot exclude the presence of errors in our phylogenetic tree, and therefore in our mutational history.…”

A missense variant effect prediction and annotation resource for SARS-CoV-2

“…Viral phosphosites were integrated from Bouhaddou et al (2020). Variant frequencies across all samples up to February 2021 were calculated from a sequence alignment of over 235,900 public SARS-CoV-2 sequences (Lanfear and Mansfield, 2020;Turakhia et al, 2020). Sequences are dominated by samples from the UK (75.0%) and USA (14.4%), meaning frequencies mostly reflect these regions.…”