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Clonal dynamics of surface-driven growing tissues.

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Tissue growth modes, whether surface- or bulk-driven, can be determined by analyzing the size distribution of progeny from genetically traced cells. This method offers new insights into tissue development and disease.

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Area of Science:

  • Developmental Biology
  • Cell Biology
  • Biophysics

Background:

  • Tissue self-organization into complex structures requires coordinated cell behavior.
  • Understanding tissue growth mechanisms is crucial for developmental biology and cancer research.
  • Distinguishing between surface-driven and bulk-driven tissue growth in vivo is challenging.

Purpose of the Study:

  • To develop a method for inferring the mode of tissue growth (surface vs. bulk) in vivo.
  • To link genetic tracing data to underlying cellular growth dynamics.
  • To provide a framework for analyzing clone size distributions in developmental processes.

Main Methods:

  • Analytical derivation of clone size distributions under simplified conditions (negligible migration and cell death).
  • Agent-based stochastic sampling simulations to test theoretical predictions.
  • Analysis of the characteristic power-law form of clone size distributions.

Main Results:

  • The size distribution of progeny from marked cells reflects the mode of tissue growth.
  • Surface-driven growth results in a clone size distribution following a power-law.
  • The exponent of the power law is determined by tissue surface fluctuations.

Conclusions:

  • Genetic tracing experiments can reveal the mode of tissue growth in vivo.
  • The derived clone size distribution provides a novel biomarker for tissue growth dynamics.
  • This approach has implications for understanding normal tissue development and aberrant growth in diseases like cancer.