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Noise minimization in eukaryotic gene expression.

Hunter B Fraser1, Aaron E Hirsh, Guri Giaever

  • 1Department of Molecular and Cell Biology, University of California, Berkeley, USA. hunter@ocf.berkeley.edu

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This summary is machine-generated.

Organisms minimize random fluctuations, or noise, in protein production for essential genes. This study reveals that controlling gene expression noise is biologically relevant and subject to natural selection for organismal fitness.

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Genetics

Background:

  • Organisms possess mechanisms to regulate protein production rates.
  • Protein production can exhibit stochastic fluctuations, known as "noise."
  • Previous studies explored transcription/translation rates and protein level noise in model organisms.

Purpose of the Study:

  • To determine if stochasticity in protein expression is biologically relevant across most genes.
  • To investigate if random noise in protein production rates affects organismal fitness.
  • To test the hypothesis that organisms are sensitive to protein level variations in essential and complex-forming genes.

Main Methods:

  • Utilized an experimentally validated model of stochastic gene expression in Saccharomyces cerevisiae.
  • Estimated protein production noise for nearly all yeast genes.
  • Correlated noise levels with gene essentiality and involvement in multiprotein complexes.

Main Results:

  • Essential genes and genes encoding subunits of multiprotein complexes exhibit lower protein production noise.
  • Confirmed the prediction that noise is reduced for critical protein-coding genes.
  • Demonstrated a correlation between reduced noise and biological importance.

Conclusions:

  • Noise in gene expression is a biologically significant variable.
  • Stochasticity in protein production is generally detrimental to organismal fitness.
  • The control of gene expression noise is a target of natural selection.