Chaining Distinct Tasks Drives The Evolution of Modularity

I introduce a novel method for evolving modularity in gene regulatory networks. Like previous models of modular evolu-tion, it relies on selecting networks to perform a task consist-ing of distinct sub-tasks, with the aim of producing modules that perform these sub-tasks. Whilst existing models struc-ture these sub-tasks in parallel and then combine the out-put, this model chains sub-tasks together, so they must be performed one after another. This task structure resembles the selective constraints undergone in multicellular evolution, where genetic networks must (a) integrate multiple cues to es-tablish what environment they are in, and (b) express a pattern of gene activity on the basis of this environment. I show that the modules produced in these networks exhibit the hallmarks of modularity: existing modules can change independently o