Final Report Summary - MODULAR NETWORKS (Topological and functional modularity in biological regulatory networks)
Summary of the project objectives
Most biological processes depend on elements organised as modules. Modularity promotes evolvability because it permits adjustment of a module without perturbing other modules. It also facilitates the origin of new combinations of modules. This projects aims at studying how modules in gene regularity circuits arise in evolution and how such modules can evolve new gene activity patterns. These new gene activity patterns have defined many evolutionary innovations throughout life's history.
Description of the work performed
First, we addressed whether network structural traits could define independent modules. We analysed gene networks for many organisms and developmental processes. Results were not conclusive, thus prohibiting the analysis of modularity through structural traits. Hence, our best option was to identify modules as sets of nodes with a significant connection density.
Next, we addressed how modularity can arise and be maintained in evolving gene regulatory networks. We ran computer simulations of the evolution of populations of gene networks, and tracked how modularity and interactions among genes change. We also analysed whether modularity facilitates the evolution of some gene activity patterns over others.
Finally, we studied how modules of gene circuits can evolve new gene activity patterns. We addressed how phenotypic plasticity, a genotype's potential to produce different phenotypes can facilitate innovation. We analysed, for many thousands of circuits, how the probability that a genotype has to produce a phenotype through plasticity affects the likelihood of reaching another genotype in which the new phenotype is genetically determined. In this manner, we show that new adaptive phenotypes may arise first through plasticity.
We also studied phenotypic variability. We used simulations of the evolution of gene network modules to study how phenotypic variability in response to either non-genetic perturbation or mutation varies in response to the robustness of a gene activity trait.
Description of the main results.
-Modularity
We simulate the evolution of gene regulatory networks to show that modularity increases after acquiring the ability to produce new additional gene expression patterns. We show that selection favours modules where genes with new functions come to lie in the same module. We also show how modularity facilitates the combination of modules to evolve new functions. Our work provides an explanation for how living beings acquire a modular organisation and why modularity facilitates the evolution of new gene activity patterns.
-Innovation and phenotypic plasticity
Several empirical observations suggest that plasticity can help to find a new adaptive phenotype. However, we do not know if such examples hint at general principles of innovation. We used a well studied model of gene circuits to show that genotypes that produce occasionally a beneficial phenotype give more easily rise to genotypes where that same phenotype is more strongly genetically determined. New adaptive phenotypes may frequently arise first as alternative phenotypes, induced by non-genetic perturbations, and then be genetically stabilised by selection. Our work suggests a widespread relationship between phenotypic plasticity and adaptive evolution in gene activity phenotypes.
-Robustness, plasticity, variability
We asked if there are traits for which non-genetic perturbation more likely results in new phenotypes. We find that populations with robust gene expression phenotypes are more likely to generate phenotypic diversity after such perturbations. The same populations produce less phenotypic variation after mutations. Our results suggest that plasticity-mediated innovation may be especially important for gene expression traits with high mutational robustness. Our work also shows how mutational robustness can increase the chances of producing a new adaptive phenotype through plasticity.
Most biological processes depend on elements organised as modules. Modularity promotes evolvability because it permits adjustment of a module without perturbing other modules. It also facilitates the origin of new combinations of modules. This projects aims at studying how modules in gene regularity circuits arise in evolution and how such modules can evolve new gene activity patterns. These new gene activity patterns have defined many evolutionary innovations throughout life's history.
Description of the work performed
First, we addressed whether network structural traits could define independent modules. We analysed gene networks for many organisms and developmental processes. Results were not conclusive, thus prohibiting the analysis of modularity through structural traits. Hence, our best option was to identify modules as sets of nodes with a significant connection density.
Next, we addressed how modularity can arise and be maintained in evolving gene regulatory networks. We ran computer simulations of the evolution of populations of gene networks, and tracked how modularity and interactions among genes change. We also analysed whether modularity facilitates the evolution of some gene activity patterns over others.
Finally, we studied how modules of gene circuits can evolve new gene activity patterns. We addressed how phenotypic plasticity, a genotype's potential to produce different phenotypes can facilitate innovation. We analysed, for many thousands of circuits, how the probability that a genotype has to produce a phenotype through plasticity affects the likelihood of reaching another genotype in which the new phenotype is genetically determined. In this manner, we show that new adaptive phenotypes may arise first through plasticity.
We also studied phenotypic variability. We used simulations of the evolution of gene network modules to study how phenotypic variability in response to either non-genetic perturbation or mutation varies in response to the robustness of a gene activity trait.
Description of the main results.
-Modularity
We simulate the evolution of gene regulatory networks to show that modularity increases after acquiring the ability to produce new additional gene expression patterns. We show that selection favours modules where genes with new functions come to lie in the same module. We also show how modularity facilitates the combination of modules to evolve new functions. Our work provides an explanation for how living beings acquire a modular organisation and why modularity facilitates the evolution of new gene activity patterns.
-Innovation and phenotypic plasticity
Several empirical observations suggest that plasticity can help to find a new adaptive phenotype. However, we do not know if such examples hint at general principles of innovation. We used a well studied model of gene circuits to show that genotypes that produce occasionally a beneficial phenotype give more easily rise to genotypes where that same phenotype is more strongly genetically determined. New adaptive phenotypes may frequently arise first as alternative phenotypes, induced by non-genetic perturbations, and then be genetically stabilised by selection. Our work suggests a widespread relationship between phenotypic plasticity and adaptive evolution in gene activity phenotypes.
-Robustness, plasticity, variability
We asked if there are traits for which non-genetic perturbation more likely results in new phenotypes. We find that populations with robust gene expression phenotypes are more likely to generate phenotypic diversity after such perturbations. The same populations produce less phenotypic variation after mutations. Our results suggest that plasticity-mediated innovation may be especially important for gene expression traits with high mutational robustness. Our work also shows how mutational robustness can increase the chances of producing a new adaptive phenotype through plasticity.