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Inferring epigenetic dynamics from kin correlations.

Sahand Hormoz1, Nicolas Desprat2, Boris I Shraiman3

  • 1Kavli Institute for Theoretical Physics and.

Proceedings of the National Academy of Sciences of the United States of America
|April 23, 2015
PubMed
Summary
This summary is machine-generated.

Researchers developed a new method to infer cell dynamics from phenotype correlations using genealogical data. This approach reveals how cell states change over time and across generations, applicable to various biological systems.

Keywords:
Bethe latticeconformal symmetrycorrelation functionsstochastic dynamics

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Area of Science:

  • Cellular dynamics
  • Systems biology
  • Genetics

Background:

  • Phenotypic heterogeneity in cell populations arises from intrinsic stochastic processes.
  • Epigenetic transmission of cellular states during division creates correlations among related cells.
  • Understanding these correlations requires knowledge of cell lineage and transition rates.

Purpose of the Study:

  • To develop an inference method for extracting probabilistic descriptions of cellular phenotypic dynamics.
  • To analyze phenotype correlations as a function of kinship in a genealogical tree model.
  • To validate the method using Pyoverdine dynamics in Pseudomonas aeruginosa.

Main Methods:

  • Modeling phenotypic dynamics on a genealogical tree.
  • Defining an inference method based on phenotype correlations and kinship.
  • Testing the method on bacterial colony data.

Main Results:

  • The inference method successfully extracts approximate probabilistic descriptions of phenotypic dynamics.
  • Phenotypic dynamics on the genealogical tree exhibit approximate conformal symmetry.
  • This conformal symmetry is characteristic of critical behavior in physical systems.

Conclusions:

  • The developed method provides a powerful tool for studying cellular dynamics using lineage information.
  • The findings suggest a link between cellular phenotypic dynamics and concepts from critical phenomena in physics.
  • The approach is broadly applicable to any system where genealogical data is available.