Evolution of Gene Regulatory Networks by Fluctuating Selection and Intrinsic Constraints

Abstract

Various characteristics of complex gene regulatory networks (GRNs) have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution.

ncDNA and drift drive binding site accumulation

“…For instance, properties such as robustness, modularity, redundancy, complexity, and evolvability can be measured by pathway connectivity and have been argued to convey adaptive value to the individual [4,16-18]. A recent study invoked fluctuating phenotypic selection to explain the evolution of scale-free distributions and pathway complexity [19]. However, whether adaptation can operate uniformly on the genome scale to have consistent effect on regulatory complexity is an open debate [20,21].…”

Neutral forces acting on intragenomic variability shape the Escherichia coli regulatory network topology

“…However, it has been shown that when subjecting CRNs to the various neutral evolutionary forces and tracing their trajectory in time, many of these topological patterns may simply arise spontaneously due to the forces of mutation, recombination, gene duplication, and genetic drift (10, 12). These studies call into question arguments that were made in favor of adaptive explanations for the emergence and conservation of CRN properties (8,(13)(14)(15) and identify important parameters that may significantly affect the evolution of CRNs from a neutral perspective. Specifically (12), they highlighted the role that promoter length, binding-site size, and population size may play in forming certain topological patterns known as motifs.…”

“…In particular, an important insight into improving the quantifiability of neutral trends is that promoter length and the spontaneous gain and loss rates of TF binding sites (TFBS) vary substantially within a genome and that reducing each distribution to one value potentially eclipses important emergent properties and structure at the network level. Previous work assumed all promoters were the same length (10,12,15,16), whereas the current work incorporates variability in promoter lengths. Finally, by subjecting a population of individuals whose genotypes are thus constructed to nonadaptive forces of evolution, we provide a simulation framework for generating data corresponding to a null model of only neutral forces.…”

Systems Evolutionary Biology of Waddington’s Canalization and Genetic Assimilation

“…Iwasaki, Tsuda, and Kawata developed an individual-based approach to the GRN modeling [37, 38]. The GRN of each individual had both phenotypic and regulatory genes, each gene was composed of a cis-regulatory region and a coding region, and a cis-regulatory region was composed of cis-sites for specific transcription factors.…”

“…In contrast, simple GRNs have mutational robustness only because of their small mutational target size. Iwasaki and co-authors found that the level of CGVs in a population was mainly determined by the order (weighted size) of GRNs and concluded that the outgrowth of GRNs and adaptation to new environments are mutually facilitating, resulting in sustainable evolvability [37]. …”