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Dynamics extracted from fixed cells reveal feedback linking cell growth to cell cycle
Open accessAbstract
Biologists have long been concerned about what constrains variation in cell size, but progress in this field has been slow and stymied by experimental limitations. Here we describe a new method, ergodic rate analysis (ERA), that uses single-cell measurements of fixed steady-state populations to accurately infer the rates of molecular events, including rates of cell growth. ERA exploits the fact that the number of cells in a particular state is related to the average transit time through that state. With this method, it is possible to calculate full time trajectories of any feature that can be labelled in fixed cells, for example levels of phosphoproteins or total cellular mass. Using ERA we find evidence for a size-discriminatory process at the G1/S transition that acts to decrease cell-to-cell size variation.
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“Thus, the large variation induced by the cell cycle in some scRNA-seq experiments may conceal other important sources of biological variation101, especially cellular differentiation processes137,141,151,152.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [141]
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“More recent studies have begun to determine regulatory circuit topology beyond pairwise interaction.”
From Revealing the vectors of cellular identity with single-cell genomics (2016) · cites this paper as [141]
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Additional file 5 of Short cell cycle duration is a phenotype of human epidermal stem cells
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Additional file 1 of Short cell cycle duration is a phenotype of human epidermal stem cells
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Additional file 2 of Short cell cycle duration is a phenotype of human epidermal stem cells
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Additional file 4 of Short cell cycle duration is a phenotype of human epidermal stem cells
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Additional file 6 of Short cell cycle duration is a phenotype of human epidermal stem cells
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Metadata
- Authors
- Kafri, R., Levy, J., Ginzberg, M. B., Oh, S., Lahav, G., & Kirschner, M. W.
- Affiliations
- Harvard University (US)
- University of Ottawa (CA)
- Corresponding author
- Kirschner, Marc W.
- Venue
- Nature
- Published
- 2013-02
- Volume
- 494
- Issue
- 7438
- Pages
- 480-483
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3730528
- OpenAlex
- W2087252982
- Cited by
- 232
- References
- 11
- Citations by year
- 2026: 9 · 2025: 11 · 2024: 13 · 2023: 10 · 2022: 21 · 2021: 12 · 2020: 23 · 2019: 18 · 2018: 18 · 2017: 31 · 2016: 15 · 2015: 24 · 2014: 20 · 2013: 7
- FWCI
- 9.80
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM083303, R01GM026875, GM 26875)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Microtubule and mitosis dynamics
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
- Keywords
- cell size control, cell growth rate, cell cycle, G1/S transition, single-cell measurement, transit time
- MeSH terms
- Cell Count, Cell Cycle, Cell Line, Cycloheximide, Dimethyl Sulfoxide, HeLa Cells, Humans, Leupeptins, Phosphoproteins, G1 Phase, S Phase, Sirolimus, Feedback, Physiological, Cell Size, Cell Proliferation, Single-Cell Analysis
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