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High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression
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Stochastic variation: from single cells to superorganisms.

Maria L Kilfoil1, Paul Lasko, Ehab Abouheif

  • 1Department of Biology and Developmental Biology Research Initiative, McGill University, 1205 Avenue Docteur Penfield, Montréal, Québec H3A 1B1, Canada.

HFSP Journal
|June 2, 2010
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Stochasticity, or randomness, in gene expression and cellular processes creates phenotypic variation. This random variation influences development and reproduction, even in complex systems like ant colonies, impacting evolution.

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Area of Science:

  • Molecular Biology
  • Developmental Biology
  • Evolutionary Biology

Background:

  • Phenotypic variation often does not directly correlate with an organism's genetic makeup (genotype).
  • While genetic and environmental factors are known influences, random fluctuations in gene expression (stochasticity) also contribute to phenotypic differences.

Purpose of the Study:

  • To explore how cellular physical properties and probabilistic biochemical reactions introduce noise into gene expression.
  • To examine how stochastic events initiate and become fixed during multicellular organism development.
  • To investigate the role of stochasticity in social insect reproduction.

Main Methods:

  • Review of recent research on cellular noise and gene expression.
  • Analysis of developmental processes involving stochastic initiation and fixation.
  • Case study on social insect reproduction.

Main Results:

  • Cellular physical properties and probabilistic reactions are sources of noise in gene expression.
  • Stochastic decisions can initiate key developmental events in multicellular organisms.
  • A similar stochastic mechanism may regulate reproduction in social insects.

Conclusions:

  • Stochasticity impacts biological processes from the molecular to the colony level.
  • Randomness is a significant, yet often overlooked, factor in phenotypic variation and evolution.
  • Understanding stochasticity is crucial for a comprehensive view of biological systems.