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The cell cycle is a series of events leading to DNA duplication followed by the division of cell content to form two daughter cells. The cell cycle progresses in four stages—the cell increases in size (gap 1 or G1-phase), duplicates its DNA (synthesis or S-phase), prepares to divide (gap 2 or G2-phase), and divides (mitosis or M-phase).
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The cell cycle is an organized set of events that leads the cell to divide into two daughter cells, each containing chromosomes identical to the parent cell. It is the cell cycle that leads to the formation of an entire organism from a single-cell zygote. Besides, cell division also functions in the renewal or repair of tissues in adult multicellular eukaryotes. For example, in the bone marrow, the stem cells divide to form new blood cells. Although essential for several functions, cell...
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Analysis of Cell Cycle Position in Mammalian Cells
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Model-based inference of cell cycle dynamics captures alterations of the DNA replication programme.

Adolfo Alsina1,2, Marco Fumasoni1, Pablo Sartori1

  • 1Gulbenkian Institute for Molecular Medicine, Oeiras, Lisbon, Portugal.

Plos Computational Biology
|October 14, 2025
PubMed
Summary

We developed RepliFlow, a new method to analyze cell cycle dynamics using DNA content data from flow cytometry. This approach quantifies cell cycle phase lengths and DNA replication changes in various species.

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Area of Science:

  • Molecular Biology
  • Cell Biology
  • Biophysics

Background:

  • The eukaryotic cell cycle requires precise orchestration; dysregulation is linked to diseases.
  • Quantitative analysis of cell cycle progression is crucial for understanding cellular health and disease.
  • Existing methods for cell cycle analysis can be complex or species-specific.

Purpose of the Study:

  • To develop a model-based approach, RepliFlow, for inferring cell cycle dynamics from flow cytometry data.
  • To enable quantitative analysis of DNA replication dynamics alongside cell cycle phase lengths.
  • To provide a species-agnostic framework for scalable cell cycle analysis.

Main Methods:

  • Development of RepliFlow, a model-based computational approach.
  • Application to flow cytometry data measuring DNA content in asynchronous cell populations.
  • Validation against established methods, including nucleotide incorporation assays.

Main Results:

  • RepliFlow accurately infers cell cycle phase lengths and DNA replication dynamics.
  • The method is species-agnostic and robust, comparable to more complex analyses.
  • A minimal DNA replication model was proposed to link population-level data to microscopic observables.

Conclusions:

  • RepliFlow offers a scalable and versatile framework for analyzing cell cycle dynamics.
  • This approach facilitates the characterization of alterations in DNA replication programs.
  • The findings advance quantitative cell biology and disease research.