A unified formal framework for developmental andevolutionary change in gene regulatory network models

TL;DR

This paper introduces a unified Boolean model framework that captures both developmental and evolutionary changes in gene regulatory networks, allowing for the study of phenotypic evolution over multiple timescales.

Contribution

It extends existing Boolean models to include evolutionary processes, linking development and evolution within a single formal framework, and incorporates gene duplication as an evolutionary mechanism.

Findings

Phenotypes are represented as macrostates, possibly corresponding to multiple attractors.

Gene duplication events can control phenotype realization and lead to new regulatory structures.

The framework maintains network controllability, enabling control theory applications in development and evolution.

Abstract

The two most fundamental processes describing change in biology, development and evolu-tion, occur over drastically different timescales, difficult to reconcile within a unified framework. Development involves temporal sequences of cell states controlled by hierarchies of regulatory structures. It occurs over the lifetime of a single individual, and is associated to the gene expression level change of a given genotype. Evolution, by contrast entails genotypic change through the acquisition/loss of genes and changes in the network topology of interactions among genes. It involves the emergence of new, environmentally selected phenotypes over the lifetimes of many individuals. Here we present a model of regulatory network evolution that accounts for both timescales. We extend the framework of Boolean models of gene regulatory networks (GRN)-currently only applicable to describing development to include evolutionary processes. As opposed to one-to-one maps to specific attractors, we identify the phenotypes of the cells as the relevant macrostates of the GRN. A phenotype may now correspond to multiple attractors, and its formal definition no longer requires a fixed size for the genotype. This opens the possibility for a quantitative study of the phenotypic change of a genotype, which is itself changing over evolutionary timescales. We show how the realization of specific phenotypes can be controlled by gene duplication events (used here as an archetypal evolutionary event able to change the genotype), and how successive events of gene duplication lead to new regulatory structures via selection. At the same time, we show that our generalized framework does not inhibit network controllability and the possibility for network control theory to describe epigenetic signaling during development.