Evolution of Boolean Networks: Contingency Versus Necessity in Biology

Many scientists are convinced that the Modern Synthesis – the current paradigm in evolutionary biology – needs to be expanded within the framework of an Extended Evolutionary Synthesis (EES). A major task for the EES is to provide an explanation for the origins and extant features of biological complexity. Here we address this issue, focusing our investigation on genetic network architectures, motifs, and dynamical behaviour, by developing an intuitive and essentially parameter-free evolutionary model of transcriptional regulation where the self-replicating digital organisms are Boolean networks, and where fitness is determined by their information-processing capacities. We validate our choice of fitness function by demonstrating that our evolved networks exhibit typical biological features of extant genetic regulatory networks: sparse connectivity, scale-free out-degree (within our range of measurement) and exponentially decaying indegree distributions, significant clustering, a high proportion of feed-forward loop (FFL) network motifs, a prominence of canalising logic at the promoter, plasticity, and distributed robustness to mutation. In addition, the dynamics of our evolved networks feature simple attractor cycles that are robust to perturbations and exhibit self-organised criticality. In networks evolved without gene duplications, we show that the key architectural signatures noted above are absent. Surprisingly, the canalising fraction is much higher in comparison with networks evolved with gene duplications. These results suggest network properties of extant gene networks require gene duplications in order to evolve, and that these properties undergo positive selection, where they contribute to the global stability of the networks. By demonstrating that networks evolved without gene duplications are robust and, like their scale-free counterparts, also exhibit self-organised criticality, this work highlights the interplay between contingent mechanism, such as gene duplications, and selection, in determining evolutionary outcomes.