Evolution Of Gene Regulatory Networks Research Articles

CpG Deamination Creates Transcription Factor–Binding Sites with High Efficiency

The formation of new transcription factor–binding sites (TFBSs) has a major impact on the evolution of gene regulatory networks. Clearly, single nucleotide mutations arising within genomic DNA can lead to the creation of TFBSs. Are molecular processes inducing single nucleotide mutations contributing equally to the creation of TFBSs? In the human genome, a spontaneous deamination of methylated cytosine in the context of CpG dinucleotides results in the creation of thymine (C → T), and this mutation has the highest rate among all base substitutions. CpG deamination has been ascribed a role in silencing of transposons and induction of variation in regional methylation. We have previously shown that CpG deamination created thousands of p53-binding sites within genomic sequences of Alu transposons. Interestingly, we have defined a ∼30 bp region in Alu sequence, which, depending on a pattern of CpG deamination, can be converted to functional p53-, PAX-6-, and Myc-binding sites. Here, we have studied single nucleotide mutational events leading to creation of TFBSs in promoters of human genes and in genomic regions bound by such key transcription factors as Oct4, NANOG, and c-Myc. We document that CpG deamination events can create TFBSs with much higher efficiency than other types of mutational events. Our findings add a new role to CpG methylation: We propose that deamination of methylated CpGs constitutes one of the evolutionary forces acting on mutational trajectories of TFBSs formation contributing to variability in gene regulation.

Evolution of Gene Regulatory Networks by Fluctuating Selection and Intrinsic Constraints

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.

Algebraic connectivity may explain the evolution of gene regulatory networks

Gene expression is a result of the interplay between the structure, type, kinetics, and specificity of gene regulatory interactions, whose diversity gives rise to the variety of life forms. As the dynamic behavior of gene regulatory networks depends on their structure, here we attempt to determine structural reasons which, despite the similarities in global network properties, may explain the large differences in organismal complexity. We demonstrate that the algebraic connectivity, the smallest non-trivial eigenvalue of the Laplacian, of the directed gene regulatory networks decreases with the increase of organismal complexity, and may therefore explain the difference between the variety of analyzed regulatory networks. In addition, our results point out that, for the species considered in this study, evolution favours decreasing concentration of strategically positioned feed forward loops, so that the network as a whole can increase the specificity towards changing environments. Moreover, contrary to the existing results, we show that the average degree, the length of the longest cascade, and the average cascade length of gene regulatory networks cannot recover the evolutionary relationships between organisms. Whereas the dynamical properties of special subnetworks are relatively well understood, there is still limited knowledge about the evolutionary reasons for the already identified design principles pertaining to these special subnetworks, underlying the global quantitative features of gene regulatory networks of different organisms. The behavior of the algebraic connectivity, which we show valid on gene regulatory networks extracted from curated databases, can serve as an additional evolutionary principle of organism-specific regulatory networks.

Activation of the skeletogenic gene regulatory network in the early sea urchin embryo

The gene regulatory network (GRN) that underlies the development of the embryonic skeleton in sea urchins is an important model for understanding the architecture and evolution of developmental GRNs. The initial deployment of the network is thought to be regulated by a derepression mechanism, which is mediated by the products of the pmar1 and hesC genes. Here, we show that the activation of the skeletogenic network occurs by a mechanism that is distinct from the transcriptional repression of hesC. By means of quantitative, fluorescent whole-mount in situ hybridization, we find that two pivotal early genes in the network, alx1 and delta, are activated in prospective skeletogenic cells prior to the downregulation of hesC expression. An analysis of the upstream regulation of alx1 shows that this gene is regulated by MAPK signaling and by the transcription factor Ets1; however, these inputs influence only the maintenance of alx1 expression and not its activation, which occurs by a distinct mechanism. By altering normal cleavage patterns, we show that the zygotic activation of alx1 and delta, but not that of pmar1, is dependent upon the unequal division of vegetal blastomeres. Based on these findings, we conclude that the widely accepted double-repression model is insufficient to account for the localized activation of the skeletogenic GRN. We postulate the existence of additional, unidentified repressors that are controlled by pmar1, and propose that the ability of pmar1 to derepress alx1 and delta is regulated by the unequal division of vegetal blastomeres.

Stochasticity Versus Determinism: Consequences for Realistic Gene Regulatory Network Modelling and Evolution

Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.

Lineage-specific transcription factors and the evolution of gene regulatory networks

Nature is replete with examples of diverse cell types, tissues and body plans, forming very different creatures from genomes with similar gene complements. However, while the genes and the structures of proteins they encode can be highly conserved, the production of those proteins in specific cell types and at specific developmental time points might differ considerably between species. A full understanding of the factors that orchestrate gene expression will be essential to fully understand evolutionary variety. Transcription factor (TF) proteins, which form gene regulatory networks (GRNs) to act in cooperative or competitive partnerships to regulate gene expression, are key components of these unique regulatory programs. Although many TFs are conserved in structure and function, certain classes of TFs display extensive levels of species diversity. In this review, we highlight families of TFs that have expanded through gene duplication events to create species-unique repertoires in different evolutionary lineages. We discuss how the hierarchical structures of GRNs allow for flexible small to large-scale phenotypic changes. We survey evidence that explains how newly evolved TFs may be integrated into an existing GRN and how molecular changes in TFs might impact the GRNs. Finally, we review examples of traits that evolved due to lineage-specific TFs and species differences in GRNs.

PlnTFDB: updated content and new features of the plant transcription factor database

The Plant Transcription Factor Database (PlnTFDB; http://plntfdb.bio.uni-potsdam.de/v3.0/) is an integrative database that provides putatively complete sets of transcription factors (TFs) and other transcriptional regulators (TRs) in plant species (sensu lato) whose genomes have been completely sequenced and annotated. The complete sets of 84 families of TFs and TRs from 19 species ranging from unicellular red and green algae to angiosperms are included in PlnTFDB, representing >1.6 billion years of evolution of gene regulatory networks. For each gene family, a basic description is provided that is complemented by literature references, and multiple sequence alignments of protein domains. TF or TR gene entries include information of expressed sequence tags, 3D protein structures of homologous proteins, domain architecture and cross-links to other computational resources online. Moreover, the different species in PlnTFDB are linked to each other by means of orthologous genes facilitating cross-species comparisons.

Rapid Sequence Evolution of Transcription Factors Controlling Neuron Differentiation in Caenorhabditis

Whether phenotypic evolution proceeds predominantly through changes in regulatory sequences is a controversial issue in evolutionary genetics. Ample evidence indicates that the evolution of gene regulatory networks via changes in cis-regulatory sequences is an important determinant of phenotypic diversity. However, recent experimental work suggests that the role of transcription factor (TF) divergence in developmental evolution may be underestimated. In order to help understand what levels of constraints are acting on the coding sequence of developmental regulatory genes, evolutionary rates were investigated among 48 TFs required for neuronal development in Caenorhabditis elegans. Allelic variation was then sampled for 28 of these genes within a population of the related species Caenorhabditis remanei. Neuronal TFs are more divergent, both within and between species, than structural genes. TFs affecting different neuronal classes are under different levels of selective constraints. The regulatory genes controlling the differentiation of chemosensory neurons evolve particularly fast and exhibit higher levels of within- and between-species nucleotide variation than TFs required for the development of several neuronal classes and TFs required for motorneuron differentiation. The TFs affecting chemosensory neuron development are also more divergent than chemosensory genes expressed in the neurons they differentiate. These results illustrate that TFs are not as highly constrained as commonly thought and suggest that the role of divergence in developmental regulatory genes during the evolution of gene regulatory networks requires further attention.

Replaying the Evolutionary Tape: Biomimetic Reverse Engineering of Gene Networks

In this paper, we suggest a new approach for reverse engineering gene regulatory networks, which consists of using a reconstruction process that is similar to the evolutionary process that created these networks. The aim is to integrate prior knowledge into the reverse-engineering procedure, thus biasing the search toward biologically plausible solutions. To this end, we propose an evolutionary method that abstracts and mimics the natural evolution of gene regulatory networks. Our method can be used with a wide range of nonlinear dynamical models. This allows us to explore novel model types such as the log-sigmoid model introduced here. We apply the biomimetic method to a gold-standard dataset from an in vivo gene network. The obtained results won a reverse engineering competition of the second DREAM conference (Dialogue on Reverse Engineering Assessments and Methods 2007, New York, NY).

GeNESiS: gene network evolution simulation software

BackgroundThere has been a lot of interest in recent years focusing on the modeling and simulation of Gene Regulatory Networks (GRNs). However, the evolutionary mechanisms that give rise to GRNs in the first place are still largely unknown. In an earlier work, we developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs.ResultsIn this work, we present a parallel software package, GeNESiS for the modeling and simulation of the evolution of gene regulatory networks (GRNs). The software models the process of gene regulation through a combination of finite-state and stochastic models. The evolution of GRNs is then simulated by means of a genetic algorithm with the network connections represented as binary strings. The software allows users to simulate the evolution under varying selective pressures and starting conditions. We believe that the software provides a way for researchers to understand the evolutionary behavior of populations of GRNs.ConclusionWe believe that GeNESiS will serve as a useful tool for scientists interested in understanding the evolution of gene regulatory networks under a range of different conditions and selective pressures. Such modeling efforts can lead to a greater understanding of the network characteristics of GRNs.

Analysis of Gene Regulatory Networks in the Mammalian Circadian Rhythm

Circadian rhythm is fundamental in regulating a wide range of cellular, metabolic, physiological, and behavioral activities in mammals. Although a small number of key circadian genes have been identified through extensive molecular and genetic studies in the past, the existence of other key circadian genes and how they drive the genomewide circadian oscillation of gene expression in different tissues still remains unknown. Here we try to address these questions by integrating all available circadian microarray data in mammals. We identified 41 common circadian genes that showed circadian oscillation in a wide range of mouse tissues with a remarkable consistency of circadian phases across tissues. Comparisons across mouse, rat, rhesus macaque, and human showed that the circadian phases of known key circadian genes were delayed for 4–5 hours in rat compared to mouse and 8–12 hours in macaque and human compared to mouse. A systematic gene regulatory network for the mouse circadian rhythm was constructed after incorporating promoter analysis and transcription factor knockout or mutant microarray data. We observed the significant association of cis-regulatory elements: EBOX, DBOX, RRE, and HSE with the different phases of circadian oscillating genes. The analysis of the network structure revealed the paths through which light, food, and heat can entrain the circadian clock and identified that NR3C1 and FKBP/HSP90 complexes are central to the control of circadian genes through diverse environmental signals. Our study improves our understanding of the structure, design principle, and evolution of gene regulatory networks involved in the mammalian circadian rhythm.

Opsins and cell fate in the Drosophila Bolwig organ: tricky lessons in homology inference

The Drosophila Bolwig organs are small photoreceptor bundles that facilitate the phototactic behavior of the larva. Comparative literature suggests that these highly reduced visual organs share evolutionary ancestry with the adult compound eye. A recent molecular genetic study produced the first detailed account of the mechanisms controlling differential opsin expression and photoreceptor subtype determination in these enigmatic eyes of the Drosophila larva. Here, the evolutionary implications are examined, taking into account the dynamic diversification of opsin genes and the spatial regulation of opsin homolog expression in other insects. It is concluded that, consistent with their common evolutionary roots, the Drosophila larval and adult eyes use the same mechanisms for the regulation of opsin expression and photoreceptor cell fate specification. Strikingly, the structurally highly derived Bolwig organs retained a more ancestral state of opsin expression and regulation. Inconspicuous in size, the Drosophila larval eyes deliver useful lessons in the reconstruction of homology between neuronal cell types with gene expression data, and on the conservative nature of gene regulatory network evolution during the emergence of novel organs from ancestral templates.

ReAlignerV: Web-based genomic alignment tool with high specificity and robustness estimated by species-specific insertion sequences

BackgroundDetecting conserved noncoding sequences (CNSs) across species highlights the functional elements. Alignment procedures combined with computational prediction of transcription factor binding sites (TFBSs) can narrow down key regulatory elements. Repeat masking processes are often performed before alignment to mask insertion sequences such as transposable elements (TEs). However, recently such TEs have been reported to influence the gene regulatory network evolution. Therefore, an alignment approach that is robust to TE insertions is meaningful for finding novel conserved TFBSs in TEs.ResultsWe constructed a web server 'ReAlignerV' for complex alignment of genomic sequences. ReAlignerV returns ladder-like schematic alignments that integrate predicted TFBSs and the location of TEs. It also provides pair-wise alignments in which the predicted TFBS sites and their names are shown alongside each sequence. Furthermore, we evaluated false positive aligned sites by focusing on the species-specific TEs (SSTEs), and found that ReAlignerV has a higher specificity and robustness to insertions for sequences having more than 20% TE content, compared to LAGAN, AVID, MAVID and BLASTZ.ConclusionReAlignerV can be applied successfully to TE-insertion-rich sequences without prior repeat masking, and this increases the chances of finding regulatory sequences hidden in TEs, which are important sources of the regulatory network evolution. ReAlignerV can be accessed through and downloaded from .

Evolution of gene regulatory networks: Robustness as an emergent property of evolution

Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Although much work has been done in elucidating the transcriptional regulatory network, the underlying mechanisms that have possibly influenced the evolution of these GRNs are still debatable. We have developed a framework to analyze the effect of objective functions, input types and starting populations on the evolution of GRNs with a specific emphasis on the robustness of evolved GRNs.We observed that robustness evolves along with the networks as an emergent property even in the absence of specific selective pressure towards more robust systems. In addition, robustness was independent of the selective pressure, input types or the initial starting populations. We also observed the existence of multiple genotypes giving rise to the same phenotype in accordance with the theoretical view that natural selection operates on phenotypes thereby accommodating variation in the genotype by fixing those changes that are phenotype-neutral.This study gives a proof-of-concept of the fact that robustness is an emergent property of GRNs as well as of the degeneracy of the network topology/function relationship analogous to the sequence/structure problem in proteins.

Structure and evolution of gene regulatory networks in microbial genomes

With the availability of genome sequences for hundreds of microbial genomes, it has become possible to address several questions from a comparative perspective to understand the structure and function of regulatory systems, at least in model organisms. Recent studies have focused on topological properties and the evolution of regulatory networks and their components. Our understanding of natural networks is paving the way to embedding synthetic regulatory systems into organisms, allowing us to expand the natural diversity of living systems to an extent we had never before anticipated.

Housekeeping genes tend to show reduced upstream sequence conservation

Mammalian housekeeping genes show significantly lower promoter sequence conservation, especially upstream of position -500 with respect to the transcription start site, than genes expressed in a subset of tissues.

Response to Comment on "Gene Regulatory Networks and the Evolution of Animal Body Plans"

Contrary to Coyne's assertions, our paper did not advocate a macromutational innovation of phyla but considered the consequences of the introduction of developmental constraints for the evolution of gene regulatory networks based on recent empirical studies of gene regulatory networks.

Evolving beyond perfection: an investigation of the effects of long-term evolution on fractal gene regulatory networks

This paper continues a theme of exploring algorithms based on principles of biological development for tasks such as pattern generation, machine learning and robot control. Previous work has investigated the use of genes expressed as fractal proteins to enable greater evolvability of gene regulatory networks (GRNs). Here, the evolution of such GRNs is investigated further to determine whether evolution exhibits natural tendencies towards efficiency and graceful degradation of developmental programs. Experiments where “perfect” GRNs are evolved for a further thousand generations without the addition of any further selection pressure, confirm this hypothesis. After further evolution, the perfect GRNs operate in a more efficient manner (using fewer proteins) and show an improved ability to function correctly with missing genes. When the algorithm is applied to applications (e.g. robot control) this equates to efficient and fault-tolerant controllers.

Evolution of a polymorphic regulatory element in interferon-gamma through transposition and mutation.

Mammalian transposable elements have intrinsic regulatory elements that can activate neighboring genes, and it is speculated that they can also carry extrinsic transactivating DNA sequences to new genomic locations. We have identified a polymorphic segment of the human interferon-gamma promoter region where two adjacent binding sites for NF-kappaB and NFAT originated from the insertion of an Alu element approximately 22-34 MYA. Both binding sites lie outside the Alu consensus sequence but within the boundaries of the insertion, suggesting that this segment of DNA was comobilized when the Alu element moved from another part of the genome. Sequence comparisons and examination of DNA-protein interactions across nine different primate species indicate that the inserted sequence contained the intact NFAT binding site, whereas the ability to bind NF-kappaB evolved through a series of mutations after the insertion. These observations are consistent with the notion that retropseudogenes can comobilize intact regulatory sequences to new locations and thereby influence the evolution of gene regulatory networks; however, the extent to which such events have shaped the evolution of gene regulation remains unknown.

A New Factor in Evolution

A New Factor in Evolution