# Evolution of gene regulatory networks by means of selection and random genetic drift

## TL;DR

This paper explores how gene regulatory networks evolve through natural selection and random genetic drift using a new simulation framework.

## Contribution

The study introduces EvoNET, a simulation framework that evaluates GRN evolution with variable mutation fitness and phenotypic selection.

## Key findings

- GRN evolution is influenced by both random genetic drift and natural selection.
- The study confirms the impact of mutations on GRN robustness.
- Phenotypic maturation affects evolutionary outcomes in GRNs.

## Abstract

The evolution of a population by means of genetic drift and natural selection operating on a gene regulatory network (GRN) of an individual has not been scrutinized in depth. Thus, the relative importance of various evolutionary forces and processes on shaping genetic variability in GRNs is understudied. In this study, we implemented a simulation framework, called EvoNET, that simulates forward-in-time the evolution of GRNs in a population. The fitness effect of mutations is not constant, rather fitness of each individual is evaluated on the phenotypic level, by measuring its distance from an optimal phenotype. Each individual goes through a maturation period, where its GRN may reach an equilibrium, thus deciding its phenotype. Afterwards, individuals compete to produce the next generation. We examine properties of the GRN evolution, such as robustness against the deleterious effect of mutations and the role of genetic drift. We are able to confirm previous hypotheses regarding the effect of mutations and we provide new insights on the interplay between random genetic drift and natural selection.