Specialization Can Drive the Evolution of Modularity

Abstract

Organismal development and many cell biological processes are organized in a modular fashion, where regulatory molecules form groups with many interactions within a group and few interactions between groups. Thus, the activity of elements within a module depends little on elements outside of it. Modularity facilitates the production of heritable variation and of evolutionary innovations. There is no consensus on how modularity might evolve, especially for modules in development. We show that modularity can increase in gene regulatory networks as a byproduct of specialization in gene activity. Such specialization occurs after gene regulatory networks are selected to produce new gene activity patterns that appear in a specific body structure or under a specific environmental condition. Modules that arise after specialization in gene activity comprise genes that show concerted changes in gene activities. This and other observations suggest that modularity evolves because it decreases interference between different groups of genes. Our work can explain the appearance and maintenance of modularity through a mechanism that is not contingent on environmental change. We also show how modularity can facilitate co-option, the utilization of existing gene activity to build new gene activity patterns, a frequent feature of evolutionary innovations.

Morphological change in machines accelerates the evolution of robust behavior

“…This dynamic has been observed in biological organisms (39) as well as in computational models (24,40,41). Further it has been argued that, through genetic assimilation, this developmental robustness can lead to higher evolvability (42) in biological organisms: Genetic robustness can eventually supplant developmental robustness (43).…”

“…Robustness can arise as a result of modularity (23), but no increased structural (24) or functional (25) modularity was detected in the controllers evolved within the morphologically changing A B C D Fig. 3.…”

Morphological Modularity Can Enable the Evolution of Robot Behavior to Scale Linearly with the Number of Environmental Features

“…Lipson et al (2002) showed that environmental change can be a catalyst for the evolution of modularity. That work was followed by experiments in which non-embodied Boolean networks (Espinosa-Soto and Wagner, 2010) or neural networks (Kashtan and Alon, 2005;Clune et al, 2013) were evolved to perform various tasks. The tasks and fitness functions were chosen in such a way as to favor networks that computed partial results using separate genetic or neural modules; changes to the fitness function over evolutionary time favored networks that could rapidly change how those partial results were combined.…”

“…Espinosa-Soto and Wagner (2010) accomplished this by formulating a biased mutation operator that favors low in-degree network nodes. Clune et al (2013) used a multi-objective approach, in which one objective was to minimize the number of edges in the network.…”

Synthetic Biology: opportunities for Chilean bioindustry and education

“…This is because biological systems naturally exploit some level of modularity (Hartwell et al, 1999). Functional modularity can be identifi ed at the molecular level (Grunberg andSerrano, 2010, Khalil et al, 2012), metabolic level (Alon, 2006) and developmental level (von Dassow et al, 2000;Espinosa-Soto and Wagner, 2010;Gallois et al, 2004, Niehrs andMeinhardt, 2002;Davidson, 2010). This modular organization has been suggested to be an adaptive trait that facilitates evolutionary exploration by allowing rewiring of existing higher level building blocks that perform modular biological functions (Hartwell et al, 1999;Lipson, 2007Kashtan and Alon, 2005).…”