The Essential Motif that wasn´t there: Topological and Lesioning Analysis of Evolved Genetic Regulatory Networks

Networks that abstractly model natural genetic regulatory networks (GRNs) are evolved to show a range of dynamical behaviors. Specifically one group was evolved to show differentiation, i.e. to be able to perform an additional behavior as compared to the original, single target behavior. These GRNs are then analyzed and compared with measures used in the biological sciences. Having huge numbers of GRNs available for not only analysis but also "metabolic" inspection, we find that evolutionary niches (target functions) do not necessarily mold network structure uniquely. Our results suggest that variability operators can have a stronger influence on network topologies than selection pressures, especially when many topologies can create similar dynamics. Furthermore, damaging the most significantly represented motif (whether in differentiating or non-differentiating GRNs) is found not to have a significantly bigger impact on function than random lesions, suggesting that particular motifs are not as important in the robust functioning of networks as might perhaps be expected