Evolutionary dynamics of redundant regulatory control

Many complex regulatory processes concern tracking a constant or variable set point. Examples include temperature homeostasis, rhythmic oscillation, and the concentration of key metabolites and enzymes. Control over homeostatic or tracking phenotypes often depends on multiple, overlapping regulatory systems. In this paper, I develop a theory for the evolutionary dynamics of redundant regulatory control architecture. Prior theories analyzed the evolution of redundant control architectures by the balance between improved performance for additional redundant control weighed against the decay by germline mutation that arises in characters with overlapping function. By contrast, I argue that germline mutation is likely to be a very weak balancing force in evolutionary dynamics. Instead, I analyze the evolutionary dynamics of redundant control by a balance between the benefits of reduced tracking error and the costs of building and running the multiple control systems. In one particular mathematical model that highlights key features of evolutionary dynamics, additional redundant control reduces tracking error multiplicatively but contributes to costs additively. In that model, the performance landscape has multiple peaks of the same height, one peak for each level of redundancy and the associated optimal investment per control structure. The multipeak landscape imposes evolutionary stasis, in which control systems resist invasion by increased or decreased levels of redundancy. However, fluctuating environments likely favor a rise in redundancy over time. With greater redundancy, investment per individual control structure declines, causing a decay in the performance of each individual dimension of control. I conclude that the costs of control structures may influence regulatory architecture.     

Dynamic-module redundancy confers robustness to the gene regulatory network involved in hair patterning of Arabidopsis epidermis

Redundancy among dynamic modules is emerging as a potentially generic trait in gene regulatory networks. Moreover, module redundancy could play an important role in network robustness to perturbations. We explored the effect of dynamic-module redundancy in the networks associated to hair patterning in Arabidopsis root and leaf epidermis. Recent studies have put forward several dynamic modules belonging to these networks. We defined these modules in a discrete dynamical framework that was previously reported. Then, we addressed whether these modules are sufficient or necessary for recovering epidermal cell types and patterning. After defining two quantitative estimates of the system's robustness, we also compared the robustness of each separate module with that of a network coupling all the leaf or root modules. We found that, considering certain assumptions, all the dynamic modules proposed so far are sufficient on their own for pattern formation, but reinforce each other during epidermal development. Furthermore, we found that networks of coupled modules are more robust to perturbations than single modules. These results suggest that dynamic-module redundancy might be an important trait in gene regulatory networks and point at central questions regarding network evolution, module coupling, pattern robustness and the evolution of development.     

Redundancy and niche differentiation among the European invasive <Emphasis Type="Italic">Elodea</Emphasis> species

Community ecologists implicitly assume redundancy when they aggregate species into functional groups. But there have been remarkably few empirical efforts to investigate the accuracy of this concept in situ. The concept of redundancy could be roughly split into two components: the ecological redundancy (similar response to environmental variations involving similar ecological processes) and the functional redundancy (similar biological trait combinations shaping similar functional processes). Both types of redundancy are tested among the 3 invasive European Elodeas. In 11 sites and during two successive years 2004–2005, the cover growth rate of each Elodea species was monthly recorded. To test ecological redundancy, cover growth rates were related to a large suite of environmental variables. To test functional redundancy, 13 biological traits involved in competitive relationships were measured each month. Firstly, the redundancy hypothesis looks problematic for Elodea ernstiae. Indeed, the later possess numerous biological traits involved in light competition and niche overlap with the other Elodeas is very low. Secondly, ecological and functional redundancy can be successfully applied to Elodea canadensis and Elodea nuttallii. They share a large suite of biological traits leading to wide niche overlaps through the growing season. And the measured environmental variables do not differentially influence their growth rates, which are, in turn, controlled by a similar group of biological traits. In this way, the different invasiveness patterns of E. canadensis and E. nuttallii could be solely due to the ecological drift and their ecological dynamic could follow neutral rules.     

A Simple Model of Optimal Population Coding for Sensory Systems

A fundamental task of a sensory system is to infer information about the environment. It has long been suggested that an important goal of the first stage of this process is to encode the raw sensory signal efficiently by reducing its redundancy in the neural representation. Some redundancy, however, would be expected because it can provide robustness to noise inherent in the system. Encoding the raw sensory signal itself is also problematic, because it contains distortion and noise. The optimal solution would be constrained further by limited biological resources. Here, we analyze a simple theoretical model that incorporates these key aspects of sensory coding, and apply it to conditions in the retina. The model specifies the optimal way to incorporate redundancy in a population of noisy neurons, while also optimally compensating for sensory distortion and noise. Importantly, it allows an arbitrary input-to-output cell ratio between sensory units (photoreceptors) and encoding units (retinal ganglion cells), providing predictions of retinal codes at different eccentricities. Compared to earlier models based on redundancy reduction, the proposed model conveys more information about the original signal. Interestingly, redundancy reduction can be near-optimal when the number of encoding units is limited, such as in the peripheral retina. We show that there exist multiple, equally-optimal solutions whose receptive field structure and organization vary significantly. Among these, the one which maximizes the spatial locality of the computation, but not the sparsity of either synaptic weights or neural responses, is consistent with known basic properties of retinal receptive fields. The model further predicts that receptive field structure changes less with light adaptation at higher input-to-output cell ratios, such as in the periphery.     

Functional overlap and regulatory links shape genetic interactions between signaling pathways

To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.     

Thermal noise and biological information

Thermal noise limits the efficiency of all information-handling systems. This principle, which is a routine consideration in electronics, is just as fundamental to the handling of highly specific information by living organisms. The rapid basal turnover rates of cells and intracellular proteins and the high energy consumption of regulatory organs, previously unaccounted for, can be explained to a large extent by the need to compensate for the steady loss of essential information due to thermal noise.     

Interplay between gene expression noise and regulatory network architecture

Complex regulatory networks orchestrate most cellular processes in biological systems. Genes in such networks are subject to expression noise, resulting in isogenic cell populations exhibiting cell-to-cell variation in protein levels. Increasing evidence suggests that cells have evolved regulatory strategies to limit, tolerate or amplify expression noise. In this context, fundamental questions arise: how can the architecture of gene regulatory networks generate, make use of or be constrained by expression noise? Here, we discuss the interplay between expression noise and gene regulatory network at different levels of organization, ranging from a single regulatory interaction to entire regulatory networks. We then consider how this interplay impacts a variety of phenomena, such as pathogenicity, disease, adaptation to changing environments, differential cell-fate outcome and incomplete or partial penetrance effects. Finally, we highlight recent technological developments that permit measurements at the single-cell level, and discuss directions for future research.     

Regulatory genes in the ancestral chordate genomes

Changes or innovations in gene regulatory networks for the developmental program in the ancestral chordate genome appear to be a major component in the evolutionary process in which tadpole-type larvae, a unique characteristic of chordates, arose. These alterations may include new genetic interactions as well as the acquisition of new regulatory genes. Previous analyses of the Ciona genome revealed that many genes may have emerged after the divergence of the tunicate and vertebrate lineages. In this paper, we examined this possibility by examining a second non-vertebrate chordate genome. We conclude from this analysis that the ancient chordate included almost the same repertory of regulatory genes, but less redundancy than extant vertebrates, and that approximately 10% of vertebrate regulatory genes were innovated after the emergence of vertebrates. Thus, refined regulatory networks arose during vertebrate evolution mainly as preexisting regulatory genes multiplied rather than by generating new regulatory genes. The inferred regulatory gene sets of the ancestral chordate would be an important foundation for understanding how tadpole-type larvae, a unique characteristic of chordates, evolved.     

Functional redundancy patterns reveal non-random assembly rules in a species-rich marine assemblage

The relationship between species and the functional diversity of assemblages is fundamental in ecology because it contains key information on functional redundancy, and functionally redundant ecosystems are thought to be more resilient, resistant and stable. However, this relationship is poorly understood and undocumented for species-rich coastal marine ecosystems. Here, we used underwater visual censuses to examine the patterns of functional redundancy for one of the most diverse vertebrate assemblages, the coral reef fishes of New Caledonia, South Pacific. First, we found that the relationship between functional and species diversity displayed a non-asymptotic power-shaped curve, implying that rare functions and species mainly occur in highly diverse assemblages. Second, we showed that the distribution of species amongst possible functions was significantly different from a random distribution up to a threshold of ～90 species/transect. Redundancy patterns for each function further revealed that some functions displayed fast rates of increase in redundancy at low species diversity, whereas others were only becoming redundant past a certain threshold. This suggested non-random assembly rules and the existence of some primordial functions that would need to be fulfilled in priority so that coral reef fish assemblages can gain a basic ecological structure. Last, we found little effect of habitat on the shape of the functional-species diversity relationship and on the redundancy of functions, although habitat is known to largely determine assemblage characteristics such as species composition, biomass, and abundance. Our study shows that low functional redundancy is characteristic of this highly diverse fish assemblage, and, therefore, that even species-rich ecosystems such as coral reefs may be vulnerable to the removal of a few keystone species.     

Caspases and cancer

Evasion of apoptosis is considered to be one of the hallmarks of human cancers. This cell death modality is executed by caspases and several upstream regulatory factors, which direct their proteolytic activity, have been defined as either tumor suppressors or oncogenes. Often these regulatory factors, in addition to being potent apoptosis inducers, function in cell survival or repair signaling pathways in response to cellular stress. Thus, loss of function in a distinct regulatory mechanism does not necessarily mean that tumor formation is due to apoptosis malfunction resulting from insufficient caspase activation. Although each caspase has been assigned a distinct role in apoptosis, some redundancy with respect to their regulatory functions and substrate recognition is evident. Jointly, these proteases could be considered to possess solid tumor suppressor function, but what is the evidence that deregulation of specific caspases per se induces inappropriate cell survival, leading to enhanced tumorigenic potential? This question will be addressed in this review, which covers basic molecular mechanisms derived from in vitro analyses and emphasizes new insights that have emerged from in vivo and clinical studies.     

The impact of measurement errors in the identification of regulatory networks

Background  

There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise.