The evolution of gene regulatory networks

2018-10-30Advances in molecular and developmental biology have lead to the understanding that many phenotypic traits are the product of many interacting genes, often in the form of gene regulatory networks. As such, much effort has been expended to understand both the function and evolution of such networks or otherwise to elucidate the genotype-phenotype map. Asking about the function or evolution of a gene, removed from its context, in the functioning of such a network, is a fruitful exercise, however, much information and understanding is lost, as a gene’s context can significantly influence its behavior. This view motivates the discipline of systems biology, which intends to study genes in context. This discipline also typically involves the application of quantitative methods, sometimes absent or underdeveloped in other approaches, to model or simulate system dynamics. In this dissertation I explore topics in the domain of evolutionary systems biology, in Part I by studying the evolution of a computational model of a biological system, and in Part II by developing and applying a theoretical framework of system evolution to study species formation, and next to study the evolution of system topology and complexity. ❧ Part I: The Gap Gene Regulatory Network ❧ Cis-regulatory sequences are often composed of many low-affinity transcription factor binding sites. Determining the evolutionary and functional importance of regulatory sequence composition is impeded without a detailed knowledge of the genotype-phenotype map. I simulate the evolution of regulatory sequences involved in Drosophila melanogaster embryo segmentation during early development. Natural selection evaluates gene expression dynamics produced by a computational model of the developmental network. I observe a dramatic decrease in the total number of transcription factor binding sites through the course of evolution. Despite a decrease in average sequence binding energies through time, the regulatory sequences tend towards organizations containing increased high affinity transcription factor binding sites. Additionally, the binding energies of separate sequence segments demonstrate ubiquitous mutual correlations through time. Fewer than 10% of initial TFBSs are maintained throughout the entire simulation, deemed 'core' sites. These sites have increased functional importance as assessed under wild-type conditions and their binding energy distributions are highly conserved. Furthermore, TFBSs within close proximity of core sites exhibit increased longevity, reflecting functional regulatory interactions with core sites. In response to elevated mutational pressure, evolution tends to sample regulatory sequence organizations with fewer, albeit on average, stronger functional transcription factor binding sites. These organizations are also shaped by the regulatory interactions among core binding sites with sites in their local vicinity. ❧ Part II: Evolutionary System Theory ❧ Even if a species' phenotype does not change over evolutionary time, the underlying mechanism may change, as distinct molecular pathways can realize identical phenotypes. Here I use linear system theory to explore the consequences of this idea, describing how a gene network underlying a conserved phenotype evolves, as the genetic drift of small changes to these molecular pathways cause a population to explore the set of mechanisms with identical phenotypes. To do this, I model an organism’s internal state as a linear system of differential equations for which the environment provides input and the phenotype is the output, in which context there exists an exact characterization of the set of all mechanisms that give the same input–output relationship. This characterization implies that selectively neutral directions in genotype space should be common and that the evolutionary exploration of these distinct but equivalent mechanisms can lead to the reproductive incompatibility of independently evolving populations. This evolutionary exploration, or system drift, proceeds at a rate proportional to the amount of intrapopulation genetic variation divided by the effective population size (Nₑ). At biologically reasonable parameter values this process can lead to substantial interpopulation incompatibility, and thus speciation, in fewer than Nₑ generations. This model also naturally predicts Haldane's rule, thus providing another possible explanation of why heterogametic hybrids tend to be disrupted more often than homogametes during the early stages of speciation. ❧ Many biological systems, such as gene regulatory networks, appear to be highly complex. The necessity of such complexity is not clear, and may be the consequence of non-adaptive and chance processes. Here I apply system theory to study the evolution of complexity in gene regulatory networks. I show that network complexity, as defined by the addition of superfluous molecular components, can increase under neutral conditions within a specific parameter space, where the addition and deletion rates of de novo genes is nearly equivalent. Under a broader set of circumstances, networks may increase in complexity by recruiting existing and available genes, or as a consequence of system drift among multiple, simultaneously active, biological systems; the total number of genes may not increase, but the number of genes underlying a given trait does. I further suggest that in addition to a neutral complexity ratchet, selection and consolidation of biological systems may lead to the appearance of gratuitously complex systems, despite actually simplifying system architecture on a larger scale