Emergence of robustness against noise: A structural phase transition in evolved models of gene regulatory networks

Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Apr;85(4 Pt 1):041908. doi: 10.1103/PhysRevE.85.041908. Epub 2012 Apr 10.

Abstract

We investigate the evolution of Boolean networks subject to a selective pressure which favors robustness against noise, as a model of evolved genetic regulatory systems. By mapping the evolutionary process into a statistical ensemble and minimizing its associated free energy, we find the structural properties which emerge as the selective pressure is increased and identify a phase transition from a random topology to a "segregated-core" structure, where a smaller and more densely connected subset of the nodes is responsible for most of the regulation in the network. This segregated structure is very similar qualitatively to what is found in gene regulatory networks, where only a much smaller subset of genes--those responsible for transcription factors-is responsible for global regulation. We obtain the full phase diagram of the evolutionary process as a function of selective pressure and the average number of inputs per node. We compare the theoretical predictions with Monte Carlo simulations of evolved networks and with empirical data for Saccharomyces cerevisiae and Escherichia coli.

MeSH terms

  • Animals
  • Computer Simulation
  • Gene Expression Regulation / genetics*
  • Humans
  • Models, Genetic*
  • Models, Statistical*
  • Phase Transition
  • Proteome / metabolism*
  • Signal Transduction / physiology*

Substances

  • Proteome