2024
A phylogenetics and variant calling pipeline to support SARS-CoV-2 genomic epidemiology in the UK
Colquhoun R, O’Toole Á, Hill V, McCrone J, Yu X, Nicholls S, Poplawski R, Whalley T, Groves N, Ellaby N, Loman N, Connor T, Rambaut A. A phylogenetics and variant calling pipeline to support SARS-CoV-2 genomic epidemiology in the UK. Virus Evolution 2024, 10: veae083. PMID: 39493537, PMCID: PMC11529618, DOI: 10.1093/ve/veae083.Peer-Reviewed Original ResearchSARS-CoV-2 genome sequencesSARS-CoV-2 genomeGlobal phylogenetic contextCOVID-19 Genomics UKCOG-UKVariant callingGenome sequencePhylogenetic contextGenomic epidemiologyGenomic surveillanceSARS-CoV-2Public health decision makingHealth decision makingGenomeSequenceSARS-CoV-2 pandemicPhylogeneticallyUnited KingdomQuality controlDecision makingCOVID-19Increasing amount
2021
Progress and challenges in virus genomic epidemiology
Hill V, Ruis C, Bajaj S, Pybus O, Kraemer M. Progress and challenges in virus genomic epidemiology. Trends In Parasitology 2021, 37: 1038-1049. PMID: 34620561, DOI: 10.1016/j.pt.2021.08.007.Peer-Reviewed Original ResearchConceptsGenomic dataSource of genomic dataDecreasing costs of genome sequencingCost of genome sequencingViral genome datasetGenome sequencePathogen genomesGenomic datasetsGenomic epidemiologySpatial scale of transmissionTransmission patternsSpatial scalesScale of transmissionGenomeAssociated metadataPathogensSequenceDisease transmissionGeneration and transmission of interlineage recombinants in the SARS-CoV-2 pandemic
Jackson B, Boni M, Bull M, Colleran A, Colquhoun R, Darby A, Haldenby S, Hill V, Lucaci A, McCrone J, Nicholls S, O’Toole Á, Pacchiarini N, Poplawski R, Scher E, Todd F, Webster H, Whitehead M, Wierzbicki C, Consortium T, Loman N, Connor T, Robertson D, Pybus O, Rambaut A. Generation and transmission of interlineage recombinants in the SARS-CoV-2 pandemic. Cell 2021, 184: 5179-5188.e8. PMID: 34499854, PMCID: PMC8367733, DOI: 10.1016/j.cell.2021.08.014.Peer-Reviewed Original ResearchConceptsLocations of recombination breakpointsLineage-defining mutationsMultiple independent originsSets of mutationsSingle-nucleotide polymorphismsGenomic locationsInterlineage recombinationRecombination breakpointsParental virusRecombinant virusesB.1.1.7 variant of concernTransmission advantageGenomeVariant of concernSpike regionB.1.1.7 variantMutationsSequenced casesB.1.1.7VirusRecombinationSARS-CoV-2 virusTransmission clustersSARS-CoV-2Non-B.Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool
O’Toole Á, Scher E, Underwood A, Jackson B, Hill V, McCrone J, Colquhoun R, Ruis C, Abu-Dahab K, Taylor B, Yeats C, du Plessis L, Maloney D, Medd N, Attwood S, Aanensen D, Holmes E, Pybus O, Rambaut A. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evolution 2021, 7: veab064. PMID: 34527285, PMCID: PMC8344591, DOI: 10.1093/ve/veab064.Peer-Reviewed Original ResearchSARS-CoV-2 genomic dataSARS-CoV-2 genome sequencesPhylogenetic assignmentGenome sequenceGenomics communityGenomic dataPangolin toolOutbreak lineageGenomic epidemiologyVirus genomeLineagesTransmission lineagesGenomePangolinsSARS-CoV-2Nomenclature schemeComputational toolsVirusPangoSequenceSevere acute respiratory syndromeAcute respiratory syndromeCLIMB-COVID: continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance
Nicholls S, Poplawski R, Bull M, Underwood A, Chapman M, Abu-Dahab K, Taylor B, Colquhoun R, Rowe W, Jackson B, Hill V, O’Toole Á, Rey S, Southgate J, Amato R, Livett R, Gonçalves S, Harrison E, Peacock S, Aanensen D, Rambaut A, Connor T, Loman N. CLIMB-COVID: continuous integration supporting decentralised sequencing for SARS-CoV-2 genomic surveillance. Genome Biology 2021, 22: 196. PMID: 34210356, PMCID: PMC8247108, DOI: 10.1186/s13059-021-02395-y.Peer-Reviewed Original Research
2020
Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2
Lemey P, Hong S, Hill V, Baele G, Poletto C, Colizza V, O’Toole Á, McCrone J, Andersen K, Worobey M, Nelson M, Rambaut A, Suchard M. Accommodating individual travel history and unsampled diversity in Bayesian phylogeographic inference of SARS-CoV-2. Nature Communications 2020, 11: 5110. PMID: 33037213, PMCID: PMC7547076, DOI: 10.1038/s41467-020-18877-9.Peer-Reviewed Original ResearchConceptsBayesian phylogeographic inferencePhylogeographic inferenceSARS-CoV-2 genomeIndividual travel history dataImpact of sampling biasTravel history dataGenomic samplesPhylogeographic analysisSARS-CoV-2Sampling effortPosterior predictive accuracyUndersampled locationsGenomeVirus migrationSpatiotemporal biasesSpread of SARS-CoV-2Sampling biasTransmission hypothesisSampling locationsIndividual's travel historyLineagesVirus spreadDiversityGenomic Epidemiology of SARS-CoV-2 in Guangdong Province, China
Lu J, du Plessis L, Liu Z, Hill V, Kang M, Lin H, Sun J, François S, Kraemer M, Faria N, McCrone J, Peng J, Xiong Q, Yuan R, Zeng L, Zhou P, Liang C, Yi L, Liu J, Xiao J, Hu J, Liu T, Ma W, Li W, Su J, Zheng H, Peng B, Fang S, Su W, Li K, Sun R, Bai R, Tang X, Liang M, Quick J, Song T, Rambaut A, Loman N, Raghwani J, Pybus O, Ke C. Genomic Epidemiology of SARS-CoV-2 in Guangdong Province, China. Cell 2020, 181: 997-1003.e9. PMID: 32359424, PMCID: PMC7192124, DOI: 10.1016/j.cell.2020.04.023.Peer-Reviewed Original ResearchConceptsGenetic diversity of SARS-CoV-2Combination of metagenomic sequencingDiversity of SARS-CoV-2Genomic epidemiology of SARS-CoV-2Genetic diversityAmplicon approachPhylogenetic analysisMetagenomic sequencingPhylogenetic clusteringChina’s most populous province,Genetic variationEpidemiology of SARS-CoV-2Genomic epidemiologyIndependent introductionsSARS-CoV-2Molecular epidemiologyMolecular surveillanceGenomeLocal transmission chainsTransmission chainCentral ChinaSequenceSARS-CoV-2 infectionGuangdong Province