How different types of pattern formation mechanisms affect the evolution of form and development

Here we investigate how development and evolution can affect each other by exploring what kind of phenotypic variation is produced by different types of developmental mechanisms. A limited number of developmental mechanisms are capable of pattern formation in development. Two main types have been identified. In morphodynamic mechanisms, induction events and morphogenetic processes, such as simple growth, act at the same time. In morphostatic mechanisms, induction events happen before morphogenetic mechanisms, and thus growth cannot influence the induction of a pattern. We present a study of the variational properties of these developmental mechanisms that can help to understand how and why a developmental mechanism may become involved in the evolution and development of a particular morphological structure. Using existing models of pattern formation in teeth, an extensive simulation analysis of the phenotypic variation produced by different types of developmental mechanisms is performed. The studied properties include the amount and diversity of the phenotypic variation produced, the complexity of the phenotypic variation produced, and the relationship between phenotype and genotype. These variational properties are so different between different types of mechanisms that the relative involvement of these types of mechanisms in evolutionary innovation and in different stages of development can be estimated. In addition, type of mechanism affects the tempo and mode of morphological evolution. These results suggest that the basic principles by which development is organized can influence the likelihood of morphological evolution.     

Evolvability and robustness in a complex signalling circuit

Biological systems at various levels of organisation exhibit robustness, as well as phenotypic variability or evolvability, the ability to evolve novel phenotypes. We still know very little about the relationship between robustness and phenotypic variability at levels of organisation beyond individual macromolecules, and especially for signalling circuits. Here, we examine multiple alternate topologies of the Saccharomyces cerevisiae target-of-rapamycin (TOR) signalling circuit, in order to understand the circuit's robustness and phenotypic variability. We consider each of the topological variants a genotype, a set of alternative interactions between TOR circuit components. Two genotypes are neighbours in genotype space if they can be reached from each other by a single small genetic change. Each genotype (topology) has a signalling phenotype, which we define via the concentration trajectories of key signalling molecules. We find that the circuits we study can produce almost 300 different phenotypes. The number of genotypes with a given phenotype varies very widely among these phenotypes. Some phenotypes have few associated genotypes. Others have many genotypes that form genotype networks extending far through genotype space. A minority of phenotypes accounts for the vast majority of genotypes. Importantly, we find that these phenotypes tend to have large genotype networks, greater robustness and a greater ability to produce novel phenotypes. Thus, over a broad range of phenotypic robustness, robustness facilitates phenotypic variability in our study system. Our observations show parallels to studies on macromolecules, suggesting that similar principles might govern robustness and phenotypic variability in biological systems. Our approach points a way towards mapping genotype spaces in complex circuitry, and it exposes some challenges such mapping faces.     

Evolution in a changing environment: a case study with great tit fledging mass

Heritable phenotypic traits under significant and consistent directional selection often fail to show the expected evolutionary response. A potential explanation for this contradiction is that because environmental conditions change constantly, environmental change can mask an evolutionary response to selection. We combined an "animal model" analysis with 36 years of data from a long-term study of great tits (Parus major) to explore selection on and evolution of a morphological trait: body mass at fledging. We found significant heritability of this trait, but despite consistent positive directional selection on both the phenotypic and the additive genetic component of body mass, the population mean phenotypic value declined rather than increased over time. However, the mean breeding value for body mass at fledging increased over time, presumably in response to selection. We show that the divergence between the response to selection observed at the levels of genotype and phenotype can be explained by a change in environmental conditions over time, that is, related both to increased spring temperature before breeding and elevated population density. Our results support the suggestion that measuring phenotypes may not always give a reliable impression of evolutionary trajectories and that understanding patterns of phenotypic evolution in nature requires an understanding of how the environment has itself changed.     

Synthetic circuits reveal how mechanisms of gene regulatory networks constrain evolution

Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe—a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.     

PHENOTYPIC PLASTICITY AND EPIGENETIC MARKING: AN ASSESSMENT OF EVIDENCE FOR GENETIC ACCOMMODATION

The relationship between genotype (which is inherited) and phenotype (the target of selection) is mediated by environmental inputs on gene expression, trait development, and phenotypic integration. Phenotypic plasticity or epigenetic modification might influence evolution in two general ways: (1) by stimulating evolutionary responses to environmental change via population persistence or by revealing cryptic genetic variation to selection, and (2) through the process of genetic accommodation, whereby natural selection acts to improve the form, regulation, and phenotypic integration of novel phenotypic variants. We provide an overview of models and mechanisms for how such evolutionary influences may be manifested both for plasticity and epigenetic marking. We point to promising avenues of research, identifying systems that can best be used to address the role of plasticity in evolution, as well as the need to apply our expanding knowledge of genetic and epigenetic mechanisms to our understanding of how genetic accommodation occurs in nature. Our review of a wide variety of studies finds widespread evidence for evolution by genetic accommodation.     

MODELING PHENOTYPIC PLASTICITY IN GROWTH TRAJECTORIES: A STATISTICAL FRAMEWORK

Phenotypic plasticity, that is multiple phenotypes produced by a single genotype in response to environmental change, has been thought to play an important role in evolution and speciation. Historically, knowledge about phenotypic plasticity has resulted from the analysis of static traits measured at a single time point. New insight into the adaptive nature of plasticity can be gained by an understanding of how organisms alter their developmental processes in a range of environments. Recent advances in statistical modeling of functional data and developmental genetics allow us to construct a dynamic framework of plastic response in developmental form and pattern. Under this framework, development, genetics, and evolution can be synthesized through statistical bridges to better address how evolution results from phenotypic variation in the process of development via genetic alterations.     

Expanding population edges: theories,traits, and trade‐offs

Recent patterns of global change have highlighted the importance of understanding the dynamics and mechanisms of species range shifts and expansions. Unique demographic features, spatial processes, and selective pressures can result in the accumulation and evolution of distinctive phenotypic traits at the leading edges of expansions. We review the characteristics of expanding range margins and highlight possible mechanisms for the appearance of phenotypic differences between individuals at the leading edge and core of the range. The development of life history traits that increase dispersal or reproductive ability is predicted by theory and supported with extensive empirical evidence. Many examples of rapid phenotypic change are associated with trade‐offs that may influence the persistence of the trait once expansion ends. Accounting for the effects of edge phenotypes and related trade‐offs could be critical for predicting the spread of invasive species and population responses to climate change.     

Evolution and development — the nematode vulva as a case study

To understand how morphological characters change during evolution, we need insight into the evolution of developmental processes. Comparative developmental approaches that make use of our fundamental understanding of development in certain model organisms have been initiated for different animal systems and flowering plants. Nematodes provide a useful experimental system with which to investigate the genetic and molecular alterations underlying evolutionary changes of cell fate specification in development, by comparing different species to the genetic model system Caenorhabditis elegans. In this review, I will first discuss the different types of evolutionary alterations seen at the cellular level by focusing mainly on the analysis of vulva development in different species. The observed alterations involve changes in cell lineage, cell migration and cell death, as well as induction and cell competence. I then describe a genetic approach in the nematode Pristionchus pacificus that might identify those genetic and molecular processes that cause evolutionary changes of cell fate specification.     

Developmental processes regulate craniofacial variation in disease and evolution

Variation in development mediates phenotypic differences observed in evolution and disease. Although the mechanisms underlying phenotypic variation are still largely unknown, recent research suggests that variation in developmental processes may play a key role. Developmental processes mediate genotype–phenotype relationships and consequently play an important role regulating phenotypes. In this review, we provide an example of how shared and interacting developmental processes may explain convergence of phenotypes in spliceosomopathies and ribosomopathies. These data also suggest a shared pathway to disease treatment. We then discuss three major mechanisms that contribute to variation in developmental processes: genetic background (gene–gene interactions), gene–environment interactions, and developmental stochasticity. Finally, we comment on evolutionary alterations to developmental processes, and the evolution of disease buffering mechanisms.     

Developmental interactions and the constituents of quantitative variation

Development is the process by which genotypes are transformed into phenotypes. Consequently, development determines the relationship between allelic and phenotypic variation in a population and, therefore, the patterns of quantitative genetic variation and covariation of traits. Understanding the developmental basis of quantitative traits may lead to insights into the origin and evolution of quantitative genetic variation, the evolutionary fate of populations, and, more generally, the relationship between development and evolution. Herein, we assume a hierarchical, modular structure of trait development and consider how epigenetic interactions among modules during ontogeny affect patterns of phenotypic and genetic variation. We explore two developmental models, one in which the epigenetic interactions between modules result in additive effects on character expression and a second model in which these epigenetic interactions produce nonadditive effects. Using a phenotype landscape approach, we show how changes in the developmental processes underlying phenotypic expression can alter the magnitude and pattern of quantitative genetic variation. Additive epigenetic effects influence genetic variances and covariances, but allow trait means to evolve independently of the genetic variances and covariances, so that phenotypic evolution can proceed without changing the genetic covariance structure that determines future evolutionary response. Nonadditive epigenetic effects, however, can lead to evolution of genetic variances and covariances as the mean phenotype evolves. Our model suggests that an understanding of multivariate evolution can be considerably enriched by knowledge of the mechanistic basis of character development.     

Back and forth between cell fate specification and movement during vertebrate gastrulation

Animal body plan arises during gastrulation and organogenesis by the coordination of inductive events and cell movements. Several signaling pathways, such as BMP, FGF, Hedgehog, Nodal, and Wnt have well-recognized instructive roles in cell fate specification during vertebrate embryogenesis. Growing evidence indicates that BMP, Nodal, and FGF signaling also regulate cell movements, and that they do so through mechanisms distinct from those that specify cell fates. Moreover, pathways controlling cell movements can also indirectly influence cell fate specification by regulating dimensions and relative positions of interacting tissues. The current challenge is to delineate the molecular mechanisms via which the major signaling pathways regulate cell fate specification and movements, and how these two processes are coordinated to ensure normal development.     

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

This article suggests that apparent disagreements between the concept of developmental constraints and neo-Darwinian views on morphological evolution can disappear by using a different conceptualization of the interplay between development and selection. A theoretical framework based on current evolutionary and developmental biology and the concepts of variational properties, developmental patterns and developmental mechanisms is presented. In contrast with existing paradigms, the approach in this article is specifically developed to compare developmental mechanisms by the morphological variation they produce and the way in which their functioning can change due to genetic variation. A developmental mechanism is a gene network, which is able to produce patterns in space though the regulation of some cell behaviour (like signalling, mitosis, apoptosis, adhesion, etc.). The variational properties of a developmental mechanism are all the pattern transformations produced under different initial and environmental conditions or IS-mutations. IS-mutations are DNA changes that affect how two genes in a network interact, while T-mutations are mutations that affect the topology of the network itself. This article explains how this new framework allows predictions not only about how pattern formation affects variation, and thus phenotypic evolution, but also about how development evolves by replacement between pattern formation mechanisms. This article presents testable inferences about the evolution of the structure of development and the phenotype under different selective pressures. That is what kind of pattern formation mechanisms, in which relative temporal order, and which kind of phenotypic changes, are expected to be found in development.     

Multivariate Phenotypic Divergence Due to the Fixation of Beneficial Mutations in Experimentally Evolved Lineages of a Filamentous Fungus

The potential for evolutionary change is limited by the availability of genetic variation. Mutations are the ultimate source of new alleles, yet there have been few experimental investigations of the role of novel mutations in multivariate phenotypic evolution. Here, we evaluated the degree of multivariate phenotypic divergence observed in a long-term evolution experiment whereby replicate lineages of the filamentous fungus Aspergillus nidulans were derived from a single genotype and allowed to fix novel (beneficial) mutations while maintained at two different population sizes. We asked three fundamental questions regarding phenotypic divergence following approximately 800 generations of adaptation: (1) whether divergence was limited by mutational supply, (2) whether divergence proceeded in relatively many (few) multivariate directions, and (3) to what degree phenotypic divergence scaled with changes in fitness (i.e. adaptation). We found no evidence that mutational supply limited phenotypic divergence. Divergence also occurred in all possible phenotypic directions, implying that pleiotropy was either weak or sufficiently variable among new mutations so as not to constrain the direction of multivariate evolution. The degree of total phenotypic divergence from the common ancestor was positively correlated with the extent of adaptation. These results are discussed in the context of the evolution of complex phenotypes through the input of adaptive mutations.     

Cultural and biological evolutionary processes, selection for a trait under complex transmission.

We consider the evolution of a trait, which is under both genetic and phenotypic transmission. An individual is always born in one state but can be converted to the other before reaching adulthood. If the conversion takes place by a learning process, the native state is called “unskilled,” and that acquired by learning is called “skilled.” If phenotypic conversion takes place by way of infection, the native state is uninfected, and can be converted to infected. Native and converted phenotypes may be subject to selection; acquiring a skill may lead to selective advantage of skilled versus unskilled, while contracting a disease may involve a selective disadvantage. Conversion probability is a function of the parental phenotypes. In some of our models we assume that only one parent has teaching ability (or transmits the disease) and in others we consider more general situations. The probability of learning (or of taking the disease) may be determined by the individual's genotype. A diallelic locus is considered. The evolution of the genotypes and the phenotypes is studied in a variety of situations. Equilibria, and in a few simple cases the dynamics of the phenotypes and genotypes in the population are given. The usual equilibrium for heterozygote advantage is found to depend, in the present case, on the parameters of the learning process. Oscillatory equilibria and more than one stable equilibrium can exist in certain circumstances. Even in the absence of genotypic differences for the conversion probability gene frequencies may change.     

How fast is fast? Eco‐evolutionary dynamics and rates of change in populations and phenotypes

It is increasingly recognized that evolution may occur in ecological time. It is not clear, however, how fast evolution – or phenotypic change more generally – may be in comparison with the associated ecology, or whether systems with fast ecological dynamics generally have relatively fast rates of phenotypic change. We developed a new dataset on standardized rates of change in population size and phenotypic traits for a wide range of species and taxonomic groups. We show that rates of change in phenotypes are generally no more than 2/3, and on average about 1/4, the concurrent rates of change in population size. There was no relationship between rates of population change and rates of phenotypic change across systems. We also found that the variance of both phenotypic and ecological rates increased with the mean across studies following a power law with an exponent of two, while temporal variation in phenotypic rates was lower than in ecological rates. Our results are consistent with the view that ecology and evolution may occur at similar time scales, but clarify that only rarely do populations change as fast in traits as they do in abundance.