Robustness Can Evolve Gradually in Complex Regulatory Gene Networks with Varying Topology

By Stefano Ciliberti, Olivier C. Martin, Andreas Wagner. PLoS Comput. Biol., 2007

381 citations recorded by the source corpus.

The topology of cellular circuits (the who-interacts-with-whom) is key to understand their robustness to both mutations and noise. The reason is that many biochemical parameters driving circuit behavior vary extensively and are thus not fine-tuned. Existing work in this area asks to what extent the function of any one given circuit is robust. But is high robustness truly remarkable, or would it be expected for many circuits of similar topology? And how can high robustness come about through gradual Darwinian evolution that changes circuit topology gradually, one interaction at a time? We here ask these questions for a model of transcriptional regulation networks, in which we explore millions of different network topologies. Robustness to mutations and noise are correlated in these networks. They show a skewed distribution, with a very small number of networks being vastly more robust than the rest. All networks that attain a given gene expression state can be organized into a graph whose nodes are networks that differ in their topology. Remarkably, this graph is connected and can be easily traversed by gradual changes of network topologies. Thus, robustness is an evolvable property. This connectedness and evolvability of robust networks may be a general organizational principle of biological networks. In addition, it exists also for RNA and protein structures, and may thus be a general organizational principle of all biological systems.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/16aff53ac0061dd00017abab28e3e9cc9bda53b3

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Citations in the corpus

Survival of the sparsest: robust gene networks are parsimonious (2008, methodology): “…reported using more densely connected networks (Wagner, 1996; Siegal and Bergman, 2002; Bergman and Siegal, 2003; Masel, 2004; Azevedo et al, 2006; Ciliberti et al, 2007a, b; & 2008 EMBO and Nature Publishing Group Molecular Systems Biology 2008 1 Molecular Systems Biology 4; Article number 213;…”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “…bridging positions) driving disease-specific network traffic are preferred targets of the network influence strategy (Kitano, 2004a, 2004b, 2007; Ciliberti et al., 2007; Antal et al., 2009; Hase et al., 2009; Zanzoni et al., 2009; Fliri et al., 2010; Cornelius et al., 2011; Farkas et al., 2011;…”
Robustness and evolvability: a paradox resolved (2008, background): “This connectedness also suggests evolvability, because many new phenotypes might be produced by single mutations if a phenotype has many different genotypes that adopt it (Huynen 1996; Ciliberti et al. 2007b; Sumedha et al. 2007).”
Hierarchical Network Structure Promotes Dynamical Robustness (2014, background): “[20] Stefano Ciliberti, Olivier C Martin, and Andreas Wagner.”