This track shows recombination breakpoints inferred by the RIPPLES software from a phylogenetic tree of 1.6 million SARS-CoV-2 sequences, described by Thurakia et al, Nature 2022.
The track is in "density" mode by default, it shows the density of recombinated
sequences per nucleotide. By deactivating the "Density plot" checkbox on the configuration
page, all recombinations can be shown.
From Thurakia et al, Nature 2022: "We developed a new method for detecting recombination in pandemic-scale
phylogenies, Recombination Inference using Phylogenetic PLacEmentS, RIPPLES. Because recombination
violates the central assumption of many phylogenetic methods, that is, that a single evolutionary
history is shared across the genome, recombinant lineages arising from diverse genomes will often
be found on 'long branches', which result from accommodating the divergent evolutionary histories
of the two parental haplotypes. Note that as long as recombination is relatively uncommon,
phylogenetic inference is expected to remain accurate even when branch lengths are artifactually
expanded. RIPPLES exploits that signal by first identifying long branches on a comprehensive
SARS-CoV-2 mutation-annotated tree. RIPPLES then exhaustively breaks the potential recombinant
sequence into distinct segments and replaces each onto a global phylogeny using maximum parsimony.
RIPPLES reports the two parental nodes-hereafter termed donor and acceptor-that result in the
highest parsimony score improvement relative to the original placement on the global phylogeny. Our
approach therefore leverages phylogenetic signals for each parental lineage and the spatial
correlation of markers along the genome. We establish significance using a null model conditioned
on the inferred site-specific rates of de novo mutation."
You can download the bigBed file underlying this track (primers) from our
The data can be explored interactively with the Table Browser
or the Data Integrator. The data can also be
accessed from scripts through our API.
Thanks to Bryan Thornlow for sharing the data.
Turakhia Y, Thornlow B, Hinrichs A, McBroome J, Ayala N, Ye C, Smith K, De Maio N, Haussler D,
Lanfear R et al.
Pandemic-scale phylogenomics reveals the SARS-CoV-2 recombination landscape.
Nature. 2022 Sep;609(7929):994-997.
PMID: 35952714; PMC: PMC9519458