Evolution of gene regulatory networks: Robustness as an emergent property of evolution

Arun Krishnan, Masaru Tomita, Alessandro Giuliani

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Although much work has been done in elucidating the transcriptional regulatory network, the underlying mechanisms that have possibly influenced the evolution of these GRNs are still debatable. We have developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs. We observed that robustness evolves along with the networks as an emergent property even in the absence of specific selective pressure towards more robust systems. In addition, robustness was independent of the selective pressure, input types or the initial starting populations. We also observed the existence of multiple genotypes giving rise to the same phenotype in accordance with the theoretical view that natural selection operates on phenotypes thereby accommodating variation in the genotype by fixing those changes that are phenotype-neutral. This study gives a proof-of-concept of the fact that robustness is an emergent property of GRNs as well as of the degeneracy of the network topology/function relationship analogous to the sequence/structure problem in proteins.

Original languageEnglish
Pages (from-to)2170-2186
Number of pages17
JournalPhysica A: Statistical Mechanics and its Applications
Volume387
Issue number8-9
DOIs
Publication statusPublished - 2008 Mar 15

Keywords

  • Computational biology
  • Gene expression regulation
  • Networks

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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