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Quantitative fate mapping: A general framework for analyzing progenitor state dynamics via retrospective lineage barcoding.
Fang, Weixiang; Bell, Claire M; Sapirstein, Abel; Asami, Soichiro; Leeper, Kathleen; Zack, Donald J; Ji, Hongkai; Kalhor, Reza.
Afiliação
  • Fang W; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 2120
  • Bell CM; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
  • Sapirstein A; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology,
  • Asami S; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
  • Leeper K; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
  • Zack DJ; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Ba
  • Ji H; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA. Electronic address: hji@jhu.edu.
  • Kalhor R; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205
Cell ; 185(24): 4604-4620.e32, 2022 11 23.
Article em En | MEDLINE | ID: mdl-36423582
ABSTRACT
Natural and induced somatic mutations that accumulate in the genome during development record the phylogenetic relationships of cells; whether these lineage barcodes capture the complex dynamics of progenitor states remains unclear. We introduce quantitative fate mapping, an approach to reconstruct the hierarchy, commitment times, population sizes, and commitment biases of intermediate progenitor states during development based on a time-scaled phylogeny of their descendants. To reconstruct time-scaled phylogenies from lineage barcodes, we introduce Phylotime, a scalable maximum likelihood clustering approach based on a general barcoding mutagenesis model. We validate these approaches using realistic in silico and in vitro barcoding experiments. We further establish criteria for the number of cells that must be analyzed for robust quantitative fate mapping and a progenitor state coverage statistic to assess the robustness. This work demonstrates how lineage barcodes, natural or synthetic, enable analyzing progenitor fate and dynamics long after embryonic development in any organism.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Desenvolvimento Embrionário Tipo de estudo: Observational_studies / Prognostic_studies Idioma: En Revista: Cell Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Desenvolvimento Embrionário Tipo de estudo: Observational_studies / Prognostic_studies Idioma: En Revista: Cell Ano de publicação: 2022 Tipo de documento: Article