Chaotic Gene Regulatory Networks Can Be Robust Against Mutations and Noise

Abstract

Robustness to mutations and noise has been shown to evolve through stabilizing selection for optimal phenotypes in model gene regulatory networks. The ability to evolve robust mutants is known to depend on the network architecture. How do the dynamical properties and state-space structures of networks with high and low robustness differ? Does selection operate on the global dynamical behavior of the networks? What kind of state-space structures are favored by selection? We provide damage propagation analysis and an extensive statistical analysis of state spaces of these model networks to show that the change in their dynamical properties due to stabilizing selection for optimal phenotypes is minor. Most notably, the networks that are most robust to both mutations and noise are highly chaotic. Certain properties of chaotic networks, such as being able to produce large attractor basins, can be useful for maintaining a stable gene-expression pattern. Our findings indicate that conventional measures of stability, such as the damage-propagation rate, do not provide much information about robustness to mutations or noise in model gene regulatory networks.

arXiv commentJTB accepted

References in corpus (12)

• Lethality and centrality in protein networks
• The large-scale organization of metabolic networks
• The Yeast Cell-Cycle Network Is Robustly Designed
• Revisiting the Edge of Chaos: Evolving Cellular Automata to Perform Computations
• Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics
• Lyapunov Exponents in Random Boolean Networks
• Function Constrains Network Architecture and Dynamics: A Case Study on the Yeast Cell Cycle Boolean Network
• Criticality in Random Threshold Networks: Annealed Approximation and Beyond
• Network growth models and genetic regulatory networks
• Evolution of Canalizing Boolean Networks
• Network Analysis of the State Space of Discrete Dynamical Systems
• Spontaneous Self-Assembly of Transcription Factor Based Gene Regulation Networks

Cited by in corpus (8)

• Perturbation propagation in random and evolved Boolean networks
• Shaping Robust System through Evolution
• Robustness Leads Close to the Edge of Chaos in Coupled Map Networks: toward the understanding of biological networks
• Evolution of regulatory networks towards adaptability and stability in a changing environment
• Coherent organization in gene regulation: a study on six networks
• Coherent regulation in yeast cell cycle network
• Robust Regulatory Networks
• Are Genetically Robust Regulatory Networks Dynamically Different from Random Ones?