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dc.contributor.authorWerner, Ben_US
dc.contributor.authorCase, Jen_US
dc.contributor.authorWilliams, MJen_US
dc.contributor.authorChkhaidze, Ken_US
dc.contributor.authorTemko, Den_US
dc.contributor.authorFernández-Mateos, Jen_US
dc.contributor.authorCresswell, GDen_US
dc.contributor.authorNichol, Den_US
dc.contributor.authorCross, Wen_US
dc.contributor.authorSpiteri, Ien_US
dc.contributor.authorHuang, Wen_US
dc.contributor.authorTomlinson, IPMen_US
dc.contributor.authorBarnes, CPen_US
dc.contributor.authorGraham, TAen_US
dc.contributor.authorSottoriva, Aen_US
dc.date.accessioned2020-03-02T09:57:15Z
dc.date.issued2020-02-25en_US
dc.identifier.citationNature communications, 2020, 11 (1), pp. 1035 - ?en_US
dc.identifier.issn2041-1723en_US
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3519
dc.identifier.eissn2041-1723en_US
dc.identifier.doi10.1038/s41467-020-14844-6en_US
dc.description.abstractBoth normal tissue development and cancer growth are driven by a branching process of cell division and mutation accumulation that leads to intra-tissue genetic heterogeneity. However, quantifying somatic evolution in humans remains challenging. Here, we show that multi-sample genomic data from a single time point of normal and cancer tissues contains information on single-cell divisions. We present a new theoretical framework that, applied to whole-genome sequencing data of healthy tissue and cancer, allows inferring the mutation rate and the cell survival/death rate per division. On average, we found that cells accumulate 1.14 mutations per cell division in healthy haematopoiesis and 1.37 mutations per division in brain development. In both tissues, cell survival was maximal during early development. Analysis of 131 biopsies from 16 tumours showed 4 to 100 times increased mutation rates compared to healthy development and substantial inter-patient variation of cell survival/death rates.en_US
dc.formatElectronicen_US
dc.format.extent1035 - ?en_US
dc.languageengen_US
dc.language.isoengen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.subjectBrainen_US
dc.subjectNeuronsen_US
dc.subjectHumansen_US
dc.subjectNeoplasmsen_US
dc.subjectBayes Theoremen_US
dc.subjectReproducibility of Resultsen_US
dc.subjectCell Divisionen_US
dc.subjectHematopoiesisen_US
dc.subjectCell Survivalen_US
dc.subjectGenetic Heterogeneityen_US
dc.subjectModels, Geneticen_US
dc.subjectSingle-Cell Analysisen_US
dc.subjectMutation Rateen_US
dc.subjectMutation Accumulationen_US
dc.subjectWhole Genome Sequencingen_US
dc.titleMeasuring single cell divisions in human tissues from multi-region sequencing data.en_US
dc.typeJournal Article
dcterms.dateAccepted2020-01-29en_US
rioxxterms.versionofrecord10.1038/s41467-020-14844-6en_US
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0en_US
rioxxterms.licenseref.startdate2020-02-25en_US
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfNature communicationsen_US
pubs.issue1en_US
pubs.notesNo embargoen_US
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Evolutionary Genomics & Modelling
pubs.publication-statusPublisheden_US
pubs.volume11en_US
pubs.embargo.termsNo embargoen_US
icr.researchteamEvolutionary Genomics & Modellingen_US
dc.contributor.icrauthorSottoriva, Andreaen_US
dc.contributor.icrauthorSpiteri Sagastume, Mariaen_US


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