Under-dominance constrains the evolution of negative autoregulation in diploids

Alexander J Stewart, Robert M Seymour, Andrew Pomiankowski, Max Reuter

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)
2 Downloads (Pure)


Regulatory networks have evolved to allow gene expression to rapidly track changes in the environment as well as to buffer perturbations and maintain cellular homeostasis in the absence of change. Theoretical work and empirical investigation in Escherichia coli have shown that negative autoregulation confers both rapid response times and reduced intrinsic noise, which is reflected in the fact that almost half of Escherichia coli transcription factors are negatively autoregulated. However, negative autoregulation is rare amongst the transcription factors of Saccharomyces cerevisiae. This difference is surprising because E. coli and S. cerevisiae otherwise have similar profiles of network motifs. In this study we investigate regulatory interactions amongst the transcription factors of Drosophila melanogaster and humans, and show that they have a similar dearth of negative autoregulation to that seen in S. cerevisiae. We then present a model demonstrating that this striking difference in the noise reduction strategies used amongst species can be explained by constraints on the evolution of negative autoregulation in diploids. We show that regulatory interactions between pairs of homologous genes within the same cell can lead to under-dominance--mutations which result in stronger autoregulation, and decrease noise in homozygotes, paradoxically can cause increased noise in heterozygotes. This severely limits a diploid's ability to evolve negative autoregulation as a noise reduction mechanism. Our work offers a simple and general explanation for a previously unexplained difference between the regulatory architectures of E. coli and yeast, Drosophila and humans. It also demonstrates that the effects of diploidy in gene networks can have counter-intuitive consequences that may profoundly influence the course of evolution.

Original languageEnglish
Article numbere1002992
Number of pages12
JournalPLoS Computational Biology
Issue number3
Publication statusPublished - 21 Mar 2013


  • Animals
  • Binding Sites
  • Diploidy
  • Drosophila melanogaster
  • Escherichia coli/genetics
  • Evolution, Molecular
  • Gene Expression Regulation
  • Gene Regulatory Networks
  • Homeostasis
  • Humans
  • Models, Genetic
  • Molecular Dynamics Simulation
  • Monte Carlo Method
  • Mutation
  • Saccharomyces cerevisiae/genetics
  • Transcription Factors/genetics


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