Developmental constraints vs. variational properties: How pattern formation can help to understand evolution and development

Utilizing developmental dynamics for evolutionary prediction and control

Understanding, predicting, and controlling the phenotypic consequences of genetic and environmental change is essential to many areas of fundamental and applied biology. In evolutionary biology, the generative process of development is a major source of organismal evolvability that constrains or facilitates adaptive change by shaping the distribution of phenotypic variation that selection can act upon. While the complex interactions between genetic and environmental factors during development may appear to make it impossible to infer the consequences of perturbations, the persistent observation that many perturbations result in similar phenotypes indicates that there is a logic to what variation is generated. Here, we show that a general representation of development as a dynamical system can reveal this logic. We build a framework that allows predicting the phenotypic effects of perturbations, and conditions for when the effects of perturbations of different origins are concordant. We find that this concordance is explained by two generic features of development, namely the dynamical dependence of the phenotype on itself and the fact that all perturbations must affect the developmental process to have an effect on the phenotype. We apply our theoretical framework to classical models of development and show that it can be used to predict the evolutionary response to selection using information of plasticity and to accelerate evolution in a desired direction. The framework we introduce provides a way to quantitatively interchange perturbations, opening an avenue of perturbation design to control the generation of variation.

Evo-devo beyond development: Generalizing evo-devo to all levels of the phenotypic evolution

A foundational idea of evo-devo is that morphological variation is not isotropic, that is, it does not occur in all directions. Instead, some directions of morphological variation are more likely than others from DNA-level variation and these largely depend on development. We argue that this evo-devo perspective should apply not only to morphology but to evolution at all phenotypic levels. At other phenotypic levels there is no development, but there are processes that can be seen, in analogy to development, as constructing the phenotype (e.g., protein folding, learning for behavior, etc.). We argue that to explain the direction of evolution two types of arguments need to be combined: generative arguments about which phenotypic variation arises in each generation and selective arguments about which of it passes to the next generation. We explain how a full consideration of the two types of arguments improves the explanatory power of evolutionary theory. Also see the video abstract here: https://youtu.be/Egbvma_uaKc.

Evaluating the drivers and engines of morphological diversification in the invasive gecko Hemidactylus mabouia (Moreau de Jonnès, 1818) (Squamata: Gekkonidae)

Development determines the range of possible phenotypes that can be produced and exposed to selection and has a major role in the evolutionary trajectories of species. Nevertheless, development is itself subject to evolutionary forces. Here, we describe differences at the ontogenetic and population levels in head and limb proportions of the invasive gecko Hemidactylus mabouia, to assess the developmental mechanisms and extrinsic forces associated with morphological diversification during colonization of novel habitats. We have found that allometric trajectories of most skeletal traits remain constant throughout postnatal development. Linear morphometric analysis did not find multivariate differences between ontogenetic stages or sexes. When comparing populations, our results showed that the divergence of the corresponding external measures was explained by shifts in the intercept of static allometry curves, indicating that differences arose early in development. Populations aggregated into two morphological groups that did not correspond to the groups formed on the basis of genetic structure. Using two different approaches, we found support for an adaptive hypothesis when comparing observed patterns of morphological variation with that expected under neutral evolutionary models.

Beyond genotype-phenotype maps: Toward a phenotype-centered perspective on evolution

Evolutionary biology is paying increasing attention to the mechanisms that enable phenotypic plasticity, evolvability, and extra-genetic inheritance. Yet, there is a concern that these phenomena remain insufficiently integrated within evolutionary theory. Understanding their evolutionary implications would require focusing on phenotypes and their variation, but this does not always fit well with the prevalent genetic representation of evolution that screens off developmental mechanisms. Here, we instead use development as a starting point, and represent it in a way that allows genetic, environmental and epigenetic sources of phenotypic variation to be independent. We show why this representation helps to understand the evolutionary consequences of both genetic and non-genetic phenotype determinants, and discuss how this approach can instigate future areas of empirical and theoretical research.

Genome size drives morphological evolution in organ-specific ways

Morphogenesis is an emergent property of biochemical and cellular interactions during development. Genome size and the correlated trait of cell size can influence these interactions through effects on developmental rate and tissue geometry, ultimately driving the evolution of morphology. We tested whether variation in genome and body size is related to morphological variation in the heart and liver using nine species of the salamander genus Plethodon (genome sizes 29-67 gigabases). Our results show that overall organ size is a function of body size, whereas tissue structure changes dramatically with evolutionary increases in genome size. In the heart, increased genome size is correlated with a reduction of myocardia in the ventricle, yielding proportionally less force-producing mass and greater intertrabecular space. In the liver, increased genome size is correlated with fewer and larger vascular structures, positioning hepatocytes farther from the circulatory vessels that transport key metabolites. Although these structural changes should have obvious impacts on organ function, their effects on organismal performance and fitness may be negligible because low metabolic rates in salamanders relax selective pressure on function of key metabolic organs. Overall, this study suggests large genome and cell size influence the developmental systems involved in heart and liver morphogenesis.

Development and selective grain make plasticity 'take the lead' in adaptive evolution

BACKGROUND

Biological evolution exhibits an extraordinary capability to adapt organisms to their environments. The explanation for this often takes for granted that random genetic variation produces at least some beneficial phenotypic variation in which natural selection can act. Such genetic evolvability could itself be a product of evolution, but it is widely acknowledged that the immediate selective gains of evolvability are small on short timescales. So how do biological systems come to exhibit such extraordinary capacity to evolve? One suggestion is that adaptive phenotypic plasticity makes genetic evolution find adaptations faster. However, the need to explain the origin of adaptive plasticity puts genetic evolution back in the driving seat, and genetic evolvability remains unexplained.

RESULTS

To better understand the interaction between plasticity and genetic evolvability, we simulate the evolution of phenotypes produced by gene-regulation network-based models of development. First, we show that the phenotypic variation resulting from genetic and environmental perturbation are highly concordant. This is because phenotypic variation, regardless of its cause, occurs within the relatively specific space of possibilities allowed by development. Second, we show that selection for genetic evolvability results in the evolution of adaptive plasticity and vice versa. This linkage is essentially symmetric but, unlike genetic evolvability, the selective gains of plasticity are often substantial on short, including within-lifetime, timescales. Accordingly, we show that selection for phenotypic plasticity can be effective in promoting the evolution of high genetic evolvability.

CONCLUSIONS

Without overlooking the fact that adaptive plasticity is itself a product of genetic evolution, we show how past selection for plasticity can exercise a disproportionate effect on genetic evolvability and, in turn, influence the course of adaptive evolution.

Genetic Causation in Complex Regulatory Systems: An Integrative Dynamic Perspective

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype-phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference-making causes of phenotypes is re-examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered. This review argues that it is appropriate to treat genes as specific actual difference-makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause-and-effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes.

A highly conserved ontogenetic limb allometry and its evolutionary significance in the adaptive radiation of Anolis lizards

Diversifications often proceed along highly conserved, evolutionary trajectories. These patterns of covariation arise in ontogeny, which raises the possibility that adaptive morphologies are biased towards trait covariations that resemble growth trajectories. Here, we test this prediction in the diverse clade of Anolis lizards by investigating the covariation of embryonic growth of 13 fore- and hindlimb bones in 15 species, and compare these to the evolutionary covariation of these limb bones across 267 Anolis species. Our results demonstrate that species differences in relative limb length are established already at hatching, and are resulting from both differential growth and differential sizes of cartilaginous anlagen. Multivariate analysis revealed that Antillean Anolis share a common ontogenetic allometry that is characterized by positive allometric growth of the long bones relative to metapodial and phalangeal bones. This major axis of ontogenetic allometry in limb bones deviated from the major axis of evolutionary allometry of the Antillean Anolis and the two clades of mainland Anolis lizards. These results demonstrate that the remarkable diversification of locomotor specialists in Anolis lizards are accessible through changes that are largely independent from ontogenetic growth trajectories, and therefore likely to be the result of modifications that manifest at the earliest stages of limb development.

Evolvability and evolutionary rescue

The survival prospects of threatened species or populations can sometimes be improved by adaptive change. Such evolutionary rescue is particularly relevant when the threat comes from changing environments, or when long-term population persistence requires range expansion into new habitats. Conservation biologists are therefore often interested in whether or not populations or lineages show a disposition for adaptive evolution, that is, if they are evolvable. Here, we discuss four alternative perspectives that target different causes of evolvability and outline some of the key challenges those perspectives are designed to address. Standing genetic variation provides one familiar estimate of evolvability. Yet, the mere presence of genetic variation is often insufficient to predict if a population will adapt, or how it will adapt. The reason is that adaptive change not only depends on genetic variation, but also on the extent to which this genetic variation can be realized as adaptive phenotypic variation. This requires attention to developmental systems and how plasticity influences evolutionary potential. Finally, we discuss how a better understanding of the different factors that contribute to evolvability can be exploited in conservation practice.

On the evolution and development of morphological complexity: A view from gene regulatory networks

How does morphological complexity evolve? This study suggests that the likelihood of mutations increasing phenotypic complexity becomes smaller when the phenotype itself is complex. In addition, the complexity of the genotype-phenotype map (GPM) also increases with the phenotypic complexity. We show that complex GPMs and the above mutational asymmetry are inevitable consequences of how genes need to be wired in order to build complex and robust phenotypes during development. We randomly wired genes and cell behaviors into networks in EmbryoMaker. EmbryoMaker is a mathematical model of development that can simulate any gene network, all animal cell behaviors (division, adhesion, apoptosis, etc.), cell signaling, cell and tissues biophysics, and the regulation of those behaviors by gene products. Through EmbryoMaker we simulated how each random network regulates development and the resulting morphology (i.e. a specific distribution of cells and gene expression in 3D). This way we obtained a zoo of possible 3D morphologies. Real gene networks are not random, but a random search allows a relatively unbiased exploration of what is needed to develop complex robust morphologies. Compared to the networks leading to simple morphologies, the networks leading to complex morphologies have the following in common: 1) They are rarer; 2) They need to be finely tuned; 3) Mutations in them tend to decrease morphological complexity; 4) They are less robust to noise; and 5) They have more complex GPMs. These results imply that, when complexity evolves, it does so at a progressively decreasing rate over generations. This is because as morphological complexity increases, the likelihood of mutations increasing complexity decreases, morphologies become less robust to noise, and the GPM becomes more complex. We find some properties in common, but also some important differences, with non-developmental GPM models (e.g. RNA, protein and gene networks in single cells).

Why call it developmental bias when it is just development?

The concept of developmental constraints has been central to understand the role of development in morphological evolution. Developmental constraints are classically defined as biases imposed by development on the distribution of morphological variation.

This opinion article argues that the concepts of developmental constraints and developmental biases do not accurately represent the role of development in evolution. The concept of developmental constraints was coined to oppose the view that natural selection is all-capable and to highlight the importance of development for understanding evolution. In the modern synthesis, natural selection was seen as the main factor determining the direction of morphological evolution. For that to be the case, morphological variation needs to be isotropic (i.e. equally possible in all directions). The proponents of the developmental constraint concept argued that development makes that some morphological variation is more likely than other (i.e. variation is not isotropic), and that, thus, development constraints evolution by precluding natural selection from being all-capable.

This article adds to the idea that development is not compatible with the isotropic expectation by arguing that, in fact, it could not be otherwise: there is no actual reason to expect that development could lead to isotropic morphological variation. It is then argued that, since the isotropic expectation is untenable, the role of development in evolution should not be understood as a departure from such an expectation. The role of development in evolution should be described in an exclusively positive way, as the process determining which directions of morphological variation are possible, instead of negatively, as a process precluding the existence of morphological variation we have no actual reason to expect.

This article discusses that this change of perspective is not a mere question of semantics: it leads to a different interpretation of the studies on developmental constraints and to a different research program in evolution and development. This program does not ask whether development constrains evolution. Instead it asks questions such as, for example, how different types of development lead to different types of morphological variation and, together with natural selection, determine the directions in which different lineages evolve.

How to fit in: The learning principles of cell differentiation

Cell differentiation in multicellular organisms requires cells to respond to complex combinations of extracellular cues, such as morphogen concentrations. Some models of phenotypic plasticity conceptualise the response as a relatively simple function of a single environmental cues (e.g. a linear function of one cue), which facilitates rigorous analysis. Conversely, more mechanistic models such those implementing GRNs allows for a more general class of response functions but makes analysis more difficult. Therefore, a general theory describing how cells integrate multi-dimensional signals is lacking. In this work, we propose a theoretical framework for understanding the relationships between environmental cues (inputs) and phenotypic responses (outputs) underlying cell plasticity. We describe the relationship between environment and cell phenotype using logical functions, making the evolution of cell plasticity equivalent to a simple categorisation learning task. This abstraction allows us to apply principles derived from learning theory to understand the evolution of multi-dimensional plasticity. Our results show that natural selection is capable of discovering adaptive forms of cell plasticity associated with complex logical functions. However, developmental dynamics cause simpler functions to evolve more readily than complex ones. By using conceptual tools derived from learning theory we show that this developmental bias can be interpreted as a learning bias in the acquisition of plasticity functions. Because of that bias, the evolution of plasticity enables cells, under some circumstances, to display appropriate plastic responses to environmental conditions that they have not experienced in their evolutionary past. This is possible when the selective environment mirrors the bias of the developmental dynamics favouring the acquisition of simple plasticity functions–an example of the necessary conditions for generalisation in learning systems. These results illustrate the functional parallelisms between learning in neural networks and the action of natural selection on environmentally sensitive gene regulatory networks. This offers a theoretical framework for the evolution of plastic responses that integrate information from multiple cues, a phenomenon that underpins the evolution of multicellularity and developmental robustness.

In organisms composed of many cell types, the differentiation of cells relies on their ability to respond to complex extracellular cues, such as morphogen concentrations, a phenomenon known as cell plasticity. Although cell plasticity plays a crucial role in development and evolution, it is not clear how, and if, cell plasticity can enhance adaptation to a novel environment and/or facilitate robust developmental processes. In some models, the relationships between the environmental cues (inputs) and the phenotypic responses (outputs) are conceptualised as one-to-one (i.e. simple ‘reaction norms’); whereas the phenotype of plastic cells commonly depends on several simultaneous inputs (i.e. many-to-one, multi-dimensional reaction norms). One alternative is the use of a gene-regulatory network (GRN) models that allow for much more general responses; but this can make analysis difficult. In this work we use a theoretical framework based on logical functions and learning theory to characterize such multi-dimensional reaction norms produced by GRNs. This allows us to reveal a strong and previously unnoticed bias towards the acquisition of simple forms of cell plasticity, which increases their ability to adapt to novel environments. Recognising this bias helps us to understand when the evolution of cell plasticity will increase the ability of plastic cells to adapt to novel environments, to respond appropriately to complex extracellular cues and to enhance developmental robustness. Since this set of properties are required for the evolution of multicellularity, our approach can also contribute to our understanding of this evolutionary transition.

Developmental structuring of phenotypic variation: A case study with a cellular automata model of ontogeny

Developmental mechanisms not only produce an organismal phenotype, but they also structure the way genetic variation maps to phenotypic variation. Here, we revisit a computational model for the evolution of ontogeny based on cellular automata, in which evolution regularly discovered two alternative mechanisms for achieving a selected phenotype, one showing high modularity, the other showing morphological integration. We measure a primary variational property of the systems, their distribution of fitness effects of mutation. We find that the modular ontogeny shows the evolution of mutational robustness and ontogenic simplification, while the integrated ontogeny does not. We discuss the wider use of this methodology on other computational models of development as well as real organisms.

Historical and philosophical perspectives on the study of developmental bias

Throughout the recent history of research at the intersection of evolution and development, notions such as developmental constraint, evolutionary novelty, and evolvability have been prominent, but the term "developmental bias" has scarcely been used. And one may even doubt whether a unique and principled definition of bias is possible. I argue that the concept of developmental bias can still play a vital scientific role by means of setting an explanatory agenda that motivates investigation and guides the formulation of integrative explanatory frameworks. Less crucial is a definition that would classify patterns of phenotypic variation and unify variational patterns involving different traits and taxa as all being "bias." Instead, what we should want is a concept that generates intellectual identity across various researchers, and that unites the diverse fields and approaches relevant to the study of developmental bias, from paleontology to behavioral biology. I point to some advantages of conducting research specifically under the label of "developmental bias," compared with employing other, more common terms such as "evolvability."

Developmental Bias and Evolution: A Regulatory Network Perspective

Phenotypic variation is generated by the processes of development, with some variants arising more readily than others-a phenomenon known as "developmental bias." Developmental bias and natural selection have often been portrayed as alternative explanations, but this is a false dichotomy: developmental bias can evolve through natural selection, and bias and selection jointly influence phenotypic evolution. Here, we briefly review the evidence for developmental bias and illustrate how it is studied empirically. We describe recent theory on regulatory networks that explains why the influence of genetic and environmental perturbation on phenotypes is typically not uniform, and may even be biased toward adaptive phenotypic variation. We show how bias produced by developmental processes constitutes an evolving property able to impose direction on adaptive evolution and influence patterns of taxonomic and phenotypic diversity. Taking these considerations together, we argue that it is not sufficient to accommodate developmental bias into evolutionary theory merely as a constraint on evolutionary adaptation. The influence of natural selection in shaping developmental bias, and conversely, the influence of developmental bias in shaping subsequent opportunities for adaptation, requires mechanistic models of development to be expanded and incorporated into evolutionary theory. A regulatory network perspective on phenotypic evolution thus helps to integrate the generation of phenotypic variation with natural selection, leaving evolutionary biology better placed to explain how organisms adapt and diversify.

Looking Beyond the Genes: The Interplay Between Signaling Pathways and Mechanics in the Shaping and Diversification of Epithelial Tissues

The core of Evo-Devo lies in the intuition that the way tissues grow during embryonic development, the way they sustain their structure and function throughout lifetime, and the way they evolve are closely linked. Epithelial tissues are ubiquitous in metazoans, covering the gut and internal branched organs, as well as the skin and its derivatives (ie, teeth). Here, we discuss in vitro, in vivo, and in silico studies on epithelial tissues to illustrate the conserved, dynamical, and complex aspects of their development. We then explore the implications of the dynamical and nonlinear nature of development on the evolution of their size and shape at the phenotypic and genetic levels. In rare cases, when the interplay between signaling and mechanics is well understood at the cell level, it is becoming clear that the structure of development leads to covariation of characters, an integration which in turn provides some predictable structure to evolutionary changes. We suggest that such nonlinear systems are prone to genetic drift, cryptic genetic variation, and context-dependent mutational effects. We argue that experimental and theoretical studies at the cell level are critical to our understanding of the phenotypic and genetic evolution of epithelial tissues, including carcinomas.

Bioattractors: dynamical systems theory and the evolution of regulatory processes

In this paper, we illustrate how dynamical systems theory can provide a unifying conceptual framework for evolution of biological regulatory systems. Our argument is that the genotype-phenotype map can be characterized by the phase portrait of the underlying regulatory process. The features of this portrait--such as attractors with associated basins and their bifurcations--define the regulatory and evolutionary potential of a system. We show how the geometric analysis of phase space connects Waddington's epigenetic landscape to recent computational approaches for the study of robustness and evolvability in network evolution. We discuss how the geometry of phase space determines the probability of possible phenotypic transitions. Finally, we demonstrate how the active, self-organizing role of the environment in phenotypic evolution can be understood in terms of dynamical systems concepts. This approach yields mechanistic explanations that go beyond insights based on the simulation of evolving regulatory networks alone. Its predictions can now be tested by studying specific, experimentally tractable regulatory systems using the tools of modern systems biology. A systematic exploration of such systems will enable us to understand better the nature and origin of the phenotypic variability, which provides the substrate for evolution by natural selection.

Studying developmental variation with Geometric Morphometric Image Analysis (GMIA)

The ways in which embryo development can vary across individuals of a population determine how genetic variation translates into adult phenotypic variation. The study of developmental variation has been hampered by the lack of quantitative methods for the joint analysis of embryo shape and the spatial distribution of cellular activity within the developing embryo geometry. By drawing from the strength of geometric morphometrics and pixel/voxel-based image analysis, we present a new approach for the biometric analysis of two-dimensional and three-dimensional embryonic images. Well-differentiated structures are described in terms of their shape, whereas structures with diffuse boundaries, such as emerging cell condensations or molecular gradients, are described as spatial patterns of intensities. We applied this approach to microscopic images of the tail fins of larval and juvenile rainbow trout. Inter-individual variation of shape and cell density was found highly spatially structured across the tail fin and temporally dynamic throughout the investigated period.

Quantifying the impact of development on phenotypic variation and evolution

A primary goal of evolutionary biology is to identify the factors that shape phenotypic evolution. According to the theory of natural selection, phenotypic evolution occurs through the differential survival and reproduction of individuals whose traits are selectively advantageous relative to other individuals in the population. This implies that evolution by natural selection is contingent upon the distribution and magnitude of phenotypic variation among individuals, which are in turn the products of developmental processes. Development therefore has the potential to affect the trajectory and rate of phenotypic evolution. Recent research in diverse systems (e.g., mammalian teeth, cichlid skulls, butterfly wings, and marsupial limbs) supports the hypothesis that development biases phenotypic variation and evolution, but suggests that these biases might be system-specific.

On the effect of phenotypic dimensionality on adaptation and optimality

What proportion of the traits of individuals has been optimally shaped by natural selection and what has not? Here, we estimate the maximal number of those traits using a mathematical model for natural selection in multitrait organisms. The model represents the most ideal conditions for natural selection: a simple genotype-phenotype map and independent variation between traits. The model is also used to disentangle the influence of fitness functions and the number of traits, n, per se on the efficiency of natural selection. We also allow n to evolve. Our simulations show that, for all fitness functions and even in the best conditions optimal phenotypes are rarely encountered, only for n = 1, and that a large proportion of traits are always far from their optimum, specially for large n. This happens to different degrees depending on the fitness functions (additive linear, additive nonlinear, Gaussian and multiplicative). The traits that arise earlier in evolution account for a larger proportion of the absolute fitness of individuals. Thus, complex phenotypes have, in proportion, more traits that are far from optimal and the closeness to the optimum correlates with the age of the trait. Based on estimated population sizes, mutation rates and selection coefficients, we provide an upper estimation of the number of traits that can become and remain adapted by direct natural selection.

Evolution of Drosophila sex comb length illustrates the inextricable interplay between selection and variation

In spite of the diversity of possible biological forms observed in nature, a limited range of morphospace is frequently occupied for a given trait. Several mechanisms have been proposed to explain this bias in the distribution of phenotypes including selection, drift, and developmental constraints. Despite extensive work on phenotypic bias, the underlying developmental mechanisms explaining why particular regions of morphological space remain unoccupied are poorly understood. To address this issue, we studied the sex comb, a group of modified bristles used in courtship that shows marked morphological diversity among Drosophila species. In many Drosophila species including Drosophila melanogaster, the sex comb rotates 90° to a vertical position during development. Here we analyze the effect of changing D. melanogaster sex comb length on the process of rotation. We find that artificial selection changes the number of bristles per comb without a proportional change in the space available for rotation. As a result, when increasing sex comb length, rather than displaying a similar straight vertical shape observed in other Drosophila species, long sex combs bend because rotation is blocked by a neighboring row of bristles. Our results show ways in which morphologies that would be favored by natural selection are apparently impossible to achieve developmentally. These findings highlight the potential role of development in modifying selectable variation in the evolution of Drosophila sex comb length.

Mechanisms and constraints shaping the evolution of body plan segmentation

Segmentation of the major body axis into repeating units is arguably one of the major inventions in the evolution of animal body plan pattering. It is found in current day vertebrates, annelids and arthropods. Most segmented animals seem to use a clock-and-wavefront type mechanism in which oscillations emanating from a posterior growth zone become transformed into an anterior posterior sequence of segments. In contrast, few animals such as Drosophila use a complex gene regulatory hierarchy to simultaneously subdivide their entire body axis into segments. Here I discuss how in silico models simulating the evolution of developmental patterning can be used to investigate the forces and constraints that helped shape these two developmental modes. I perform an analysis of a series of previous simulation studies, exploiting the similarities and differences in their outcomes in relation to model characteristics to elucidate the circumstances and constraints likely to have been important for the evolution of sequential and simultaneous segmentation modes. The analysis suggests that constraints arising from the involved growth process and spatial patterning signal--posterior elongation producing a propagating wavefront versus a tissue wide morphogen gradient--and the evolutionary history--ancestral versus derived segmentation mode--strongly shaped both segmentation mechanisms. Furthermore, this implies that these patterning types are to be expected rather than random evolutionary outcomes and supports the likelihood of multiple parallel evolutionary origins.

Adaptive dynamics under development-based genotype-phenotype maps

It is not known whether natural selection can encounter any given phenotype that can be produced by genetic variation. There has been a long-lasting debate about the processes that limit adaptation and, consequently, about how well adapted phenotypes are. Here we examine how development may affect adaptation, by decomposing the genotype-fitness map-the association between each genotype and its fitness-into two: one mapping genotype to phenotype by means of a computational model of organ development, and one mapping phenotype to fitness. In the map of phenotype and fitness, the fitness of each individual is based on the similarity between realized morphology and optimal morphology. We use three different simulations to map phenotype to fitness, and these differ in the way in which similarity is calculated: similarity is calculated for each trait (in terms of each cell position individually), for a large or a small number of phenotypic landmarks (the 'many-traits' and 'few-traits' phenotype-fitness maps), and by measuring the overall surface roughness of morphology (the 'roughness' phenotype-fitness map). Evolution is simulated by applying the genotype-phenotype map and one phenotype-fitness map to each individual in the population, as well as random mutation and drift. We show that the complexity of the genotype-phenotype map prevents substantial adaptation in some of the phenotype-fitness maps: sustained adaptation is only possible using 'roughness' or 'few-traits' phenotype-fitness maps. The results contribute developmental understanding to the long-standing question of which aspects of phenotype can be effectively optimized by natural selection.

The inheritance of process: a dynamical systems approach

A central unresolved problem of evolutionary biology concerns the way in which evolution at the genotypic level relates to the evolution of phenotypes. This genotype-phenotype map involves developmental and physiological processes, which are complex and not well understood. These processes co-determine the rate and direction of adaptive change by shaping the distribution of phenotypic variability on which selection can act. In this study, we argue-expanding on earlier ideas by Goodwin, Oster, and Alberch-that an explicit treatment of this map in terms of dynamical systems theory can provide an integrated understanding of evolution and development. We describe a conceptual framework, which demonstrates how development determines the probability of possible phenotypic transitions-and hence the evolvability of a biological system. We use a simple conceptual model to illustrate how the regulatory dynamics of the genotype-phenotype map can be passed on from generation to generation, and how heredity itself can be treated as a dynamic process. Our model yields explanations for punctuated evolutionary dynamics, the difference between micro- and macroevolution, and for the role of the environment in major phenotypic transitions. We propose a quantitative research program in evolutionary developmental systems biology-combining experimental methods with mathematical modeling-which aims at elaborating our conceptual framework by applying it to a wide range of evolving developmental systems. This requires a large and sustained effort, which we believe is justified by the significant potential benefits of an extended evolutionary theory that uses dynamic molecular genetic data to reintegrate development and evolution.

Life's attractors : understanding developmental systems through reverse engineering and in silico evolution

We propose an approach to evolutionary systems biology which is based on reverse engineering of gene regulatory networks and in silico evolutionary simulations. We infer regulatory parameters for gene networks by fitting computational models to quantitative expression data. This allows us to characterize the regulatory structure and dynamical repertoire of evolving gene regulatory networks with a reasonable amount of experimental and computational effort. We use the resulting network models to identify those regulatory interactions that are conserved, and those that have diverged between different species. Moreover, we use the models obtained by data fitting as starting points for simulations of evolutionary transitions between species. These simulations enable us to investigate whether such transitions are random, or whether they show stereotypical series of regulatory changes which depend on the structure and dynamical repertoire of an evolving network. Finally, we present a case study-the gap gene network in dipterans (flies, midges, and mosquitoes)-to illustrate the practical application of the proposed methodology, and to highlight the kind of biological insights that can be gained by this approach.

Dynamic network-based epistasis analysis: boolean examples

In this article we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the inference of gene regulatory networks. Here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson, epistasis is defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus (herein, classical epistasis). Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct inference of gene interaction topologies is hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our article complements previous accounts, not only by focusing on the implications of the hierarchical and single-path assumption, but also by demonstrating the importance of considering temporal dynamics, and specifically introducing the usefulness of Boolean network models and also reviewing some key properties of network approaches.

Variation, variability, and the origin of the avian endocranium: insights from the anatomy of Alioramus altai (Theropoda: Tyrannosauroidea)

The internal braincase anatomy of the holotype of Alioramus altai, a relatively small-bodied tyrannosauroid from the Late Cretaceous of Mongolia, was studied using high-resolution computed tomography. A number of derived characters strengthen the diagnosis of this taxon as both a tyrannosauroid and a unique, new species (e.g., endocranial position of the gasserian ganglion, internal ramification of the facial nerve). Also present are features intermediate between the basal theropod and avialan conditions that optimize as the ancestral condition for Coelurosauria—a diverse group of derived theropods that includes modern birds. The expression of several primitive theropod features as derived character states within Tyrannosauroidea establishes previously unrecognized evolutionary complexity and morphological plasticity at the base of Coelurosauria. It also demonstrates the critical role heterochrony may have played in driving patterns of endocranial variability within the group and potentially reveals stages in the evolution of neuroanatomical development that could not be inferred based solely on developmental observations of the major archosaurian crown clades. We discuss the integration of paleontology with variability studies, especially as applied to the nature of morphological transformations along the phylogenetically long branches that tend to separate the crown clades of major vertebrate groups.

A two level mutation-selection model of cultural evolution and diversity

Cultural evolution is a complex process that can happen at several levels. At the level of individuals in a population, each human bears a set of cultural traits that he or she can transmit to its offspring (vertical transmission) or to other members of his or her society (horizontal transmission). The relative frequency of a cultural trait in a population or society can thus increase or decrease with the relative reproductive success of its bearers (individual's level) or the relative success of transmission (called the idea's level). This article presents a mathematical model on the interplay between these two levels. The first aim of this article is to explore when cultural evolution is driven by the idea's level, when it is driven by the individual's level and when it is driven by both. These three possibilities are explored in relation to (a) the amount of interchange of cultural traits between individuals, (b) the selective pressure acting on individuals, (c) the rate of production of new cultural traits, (d) the individual's capacity to remember cultural traits and to the population size. The aim is to explore the conditions in which cultural evolution does not lead to a better adaptation of individuals to the environment. This is to contrast the spread of fitness-enhancing ideas, which make individual bearers better adapted to the environment, to the spread of "selfish" ideas, which spread well simply because they are easy to remember but do not help their individual bearers (and may even hurt them). At the same time this article explores in which conditions the adaptation of individuals is maximal. The second aim is to explore how these factors affect cultural diversity, or the amount of different cultural traits in a population. This study suggests that a larger interchange of cultural traits between populations could lead to cultural evolution not improving the adaptation of individuals to their environment and to a decrease of cultural diversity.

Ontogenetic convergence and evolution of foot morphology in European cave salamanders (Family: Plethodontidae)

BACKGROUND

A major goal in evolutionary biology is to understand the evolution of phenotypic diversity. Both natural and sexual selection play a large role in generating phenotypic adaptations, with biomechanical requirements and developmental mechanisms mediating patterns of phenotypic evolution. For many traits, the relative importance of selective and developmental components remains understudied.

RESULTS

We investigated ontogenetic trajectories of foot morphology in the eight species of European plethodontid cave salamander to test the hypothesis that adult foot morphology was adapted for climbing. Using geometric morphometrics and other approaches, we found that developmental patterns in five species displayed little morphological change during growth (isometry), where the extensive interdigital webbing in adults was best explained as the retention of the juvenile morphological state. By contrast, three species exhibited significant allometry, with an increase in interdigital webbing during growth. Phylogenetic analyses revealed that multiple evolutionary transitions between isometry and allometry of foot webbing have occurred in this lineage. Allometric parameters of foot growth were most similar to those of a tropical species previously shown to be adapted for climbing. Finally, interspecific variation in adult foot morphology was significantly reduced as compared to variation among juveniles, indicating that ontogenetic convergence had resulted in a common adult foot morphology across species.

CONCLUSIONS

The results presented here provide evidence of a complex history of phenotypic evolution in this clade. The common adult phenotype exhibited among species reveals that selection plays an important part in generating patterns of foot diversity in the group. However, developmental trajectories arriving at this common morphology are distinct; with some species displaying developmental stasis (isometry), while others show an increase in foot webbing during growth. Thus, multiple developmental solutions exist to the same evolutionary challenge. Our findings underscore the importance of examining morphological adaptations from multiple perspectives, and emphasize that both selective hypotheses and developmental processes must be considered for a more comprehensive understanding of phenotypic evolution.

Looking at the origin of phenotypic variation from pattern formation gene networks

This article critically reviews some widespread views about the overall functioning of development. Special attention is devoted to views in developmental genetics about the superstructure of developmental gene networks. According to these views gene networks are hierarchic and multilayered. The highest layers partition the embryo in large coarse areas and control downstream genes that subsequently subdivide the embryo into smaller and smaller areas. These views are criticized on the bases of developmental and evolutionary arguments. First, these views, although detailed at the level of gene identities, do not incorporate morphogenetic mechanisms nor do they try to explain how morphology changes during development. Often, they assume that morphogenetic mechanisms are subordinate to cell signaling events. This is in contradiction to the evidence reviewed herein. Experimental evidence on pattern formation also contradicts the view that developmental gene networks are hierarchically multilayered and that their functioning is decodable from promoter analysis. Simple evolutionary arguments suggest that, indeed, developmental gene networks tend to be non-hierarchic. Re-use leads to extensive modularity in gene networks while developmental drift blurs this modularity. Evolutionary opportunism makes developmental gene networks very dependent on epigenetic factors.

The evolutionary dynamics of evolvability in a gene network model

Evolvability, the ability of populations to adapt, has recently emerged as a major unifying concept in biology. Although the study of evolvability offers new insights into many important biological questions, the conceptual bases of evolvability, and the mechanisms of its evolution, remain controversial. We used simulated evolution of a model of gene network dynamics to test the contentious hypothesis that natural selection can favour high evolvability, in particular in sexual populations. Our results conclusively demonstrate that fluctuating natural selection can increase the capacity of model gene networks to adapt to new environments. Detailed studies of the evolutionary dynamics of these networks establish a broad range of validity for this result and quantify the evolutionary forces responsible for changes in evolvability. Analysis of the genotype-phenotype map of these networks also reveals mechanisms connecting evolvability, genetic architecture and robustness. Our results suggest that the evolution of evolvability can have a pervasive influence on many aspects of organisms.

Evolution in biological and nonbiological systems under different mechanisms of generation and inheritance

The majority of definitions of life and evolution include the notion that part of an organism has to be copied to its offspring and that this includes some form of coded information. This article presents the thesis that this conception is too restrictive and that evolution can occur in systems in which there is no copy of information between generations. For that purpose, this article introduces a new set of concepts and a theoretical framework that is designed to be equally applicable to the study of the evolution of biological and nonbiological systems. In contrast to some theoretical approaches in evolution, like neo-Darwinism, the approach presented here is not focused on the transmission and change of hereditary information that can be copied (like in the case of DNA). Instead, multiple mechanisms by which a system can generate offspring (with and without copying) and by which information in it affects the structure and evolution of its offspring are considered. The first part of this article describes in detail these new concepts. The second part of this article discusses how these concepts are directly applicable to the diversity of systems that can evolve. The third part introduces hypotheses concerning (1) how different mechanisms of generation and inheritance can arise from each other during evolution, and (2) how the existence of several inheritance mechanisms in an organism can affect its evolution.

Maternal control of pattern formation inXenopus laevis

We review the essential role of maternal factors in pattern formation for Xenopus laevis, focusing on VegT, Vg1, and Wnt11. Results from loss of function experiments demonstrate a clear requirement for these genes in germ layer specification, dorsal-ventral axis formation, and convergence extension. We also discuss these genes in the broader context of metazoan development, exploring whether and how their functions in the X. laevis model organism may or may not be conserved in other species. Wnt11 signaling in particular provides a classic example where understanding context in development is crucial to understanding function. Genomic sequencing, gene expression, and functional screening data that are becoming available in more species are providing invaluable aid to decoding and modeling signaling pathways. More work is needed to develop a comprehensive catalog of the Wnt signaling, T-box, and TGF-beta genes in metazoans both near and far in evolutionary distance. We finally discuss some specific experimental and modeling efforts that will be needed to understand the behavior of these signaling networks in vivo so that we can interpret these critical pathways in an evolutionary framework.

On the origins of morphological disparity and its diverse developmental bases

It has been repeatedly claimed that morphological novelties are an unresolved problem in evolutionary theory. Several definitions of novelty exist but most emphasize that novelties imply qualitative changes on the phenotype and not the quantitative gradual changes favored in the neo-Darwinian approach to evolutionary theory. This article discusses how the concept of novelty is used to describe aspects of morphological evolution that are not satisfactorily explained under the modern synthesis. In this article, it is suggested that there is a repertoire of morphological changes rather than two discrete qualitatively different types of morphological change. How these different types of morphological changes can be understood from the diversity of developmental mechanisms existing in animal development is explored. Specifically, it is proposed that animal morphology and its variation can be understood from the spatial patterns produced by a set of basic developmental mechanisms and their combination. Some specific examples of these kinds of morphologic changes are explained.

Function, ontogeny and canalization of shape variance in the primate scapula

Primates have shoulders adapted to a wide range of locomotor functions from terrestrial pronograde quadrupedalism to highly arboreal suspensory behaviours. The shape of the scapula tightly follows these functional differences. Previous analyses of primate postcrania, including the scapula, indicate that quadrupedal monkeys are less variable than non-quadrupeds. It was previously suggested that this difference was due to a relationship between the strength of stabilizing selection and the functional demands of the upper limb. Here it is shown that intraspecific scapular shape variance is highly correlated with the degree of committed quadrupedalism. Primates that engage in frequent suspensory behaviours (e.g. apes and ateline monkeys) average twice the amount of shape variance as quadrupeds (e.g. Old World monkeys and Saimiri). Because this difference in intraspecific shape variance is apparent in infants and does not increase or decrease appreciably over ontogeny, it is not likely that differences in postnatal growth, neuromuscular control or environmental factors such as habitat structure/composition are the primary contributors to differences in adult shape variance. Instead variance in embryonic factors that affect the shape/size of the scapula or epigenetic factors associated with muscle attachments are more likely candidates. In particular, the heterogeneous functional demands of the non-quadrupedal shoulder probably reduce the stringency of stabilizing selection, resulting in the persistence into adulthood of increased amounts of embryonically generated scapular shape variance.