Developmental quantitative genetic models of evolutionary change

Discussions about evolutionary change in developmental processes or morphological structures are predicated on specific quantitative genetic models whose parameters predict whether evolutionary change can occur, its relative rate and direction, and if correlated change will occur in other related and unrelated structures. The appropriate genetic model should reflect the relevant genetical and developmental biology of the organisms, yet be simple enough in its parameters so that deductions can be made and hypotheses tested. As a consequence, the choice of the most appropriate genetic model for polygenically controlled traits is a complex tissue and the eventual choice of model is often a compromise between completeness of the model and computational expediency. Herein, we discuss several developmental quantitative genetic models for the evolution of development and morphology. The models range from the classical direct effects model to complex epigenetic models. Further, we demonstrate the algebraic equivalency of the Cowley and Atchley epigenetic model and Wagner's developmental mapping model. Finally, we propose a new multivariate model for continuous growth trajectories. The relative efficacy of these various models for understanding evolutionary change in developmental and morphological traits is discussed. © 1994 Wiley-Liss, Inc.     

PERSPECTIVE: FROM MUTANTS TO MECHANISMS? ASSESSING THE CANDIDATE GENE PARADIGM IN EVOLUTIONARY BIOLOGY

The generation of mutants in model organisms by geneticists and developmental biologists over the last century has occasionally produced phenotypes that are startlingly reminiscent of those seen in other species. Such extreme mutations have generally been dismissed by evolutionary geneticists since the "modern synthesis" as irrelevant to adaptation and speciation. But only in recent years has information on the molecular bases of mutant phenotypes become widely available, and thus work on testing the relevance of such extreme mutations to the generation of phylogenetic diversity has just begun. Here we evaluate whether evolutionary mimics are, in fact, useful for pinpointing the genetic differences that distinguish morphological variants generated during evolution. Examples come from both plants and animals, and range from intraspecific to interordinal taxonomic ranges. The use of mutationally defined candidate genes to predict evolutionary mechanisms has so far been most fruitful in explaining intraspecific variants, where it has been effective in both plants and animals. In several cases these efforts were facilitated or supported by parallel results from quantitative trait loci studies, in which natural alleles controlling continuous variation in developmental model organisms were mapped to mutationally defined genes. However, despite these successes the approach's utility seems to rapidly decay as a function of phylogenetic distance. This suggests that the divergence of developmental genetic systems is great even in closely related organisms and may become intractable at larger distances. We discuss this result in the context of what it teaches us about development, the future prospects of the candidate gene approach, and the historical debate over process in micro- and macroevolution.     

Molecular tools and bumble bees: revealing hidden details of ecology and evolution in a model system

Bumble bees are a longstanding model system for studies on behaviour, ecology and evolution, due to their well‐studied social lifestyle, invaluable role as wild and managed pollinators, and ubiquity and diversity across temperate ecosystems. Yet despite their importance, many aspects of bumble bee biology have remained enigmatic until the rise of the genetic and, more recently, genomic eras. Here, we review and synthesize new insights into the ecology, evolution and behaviour of bumble bees that have been gained using modern genetic and genomic techniques. Special emphasis is placed on four areas of bumble bee biology: the evolution of eusociality in this group, population‐level processes, large‐scale evolutionary relationships and patterns, and immunity and resistance to pesticides. We close with a prospective on the future of bumble bee genomics research, as this rapidly advancing field has the potential to further revolutionize our understanding of bumble bees, particularly in regard to adaptation and resilience. Worldwide, many bumble bee populations are in decline. As such, throughout the review, connections are drawn between new molecular insights into bumble bees and our understanding of the causal factors involved in their decline. Ongoing and potential applications to bumble bee management and conservation are also included to demonstrate how genetics‐ and genomics‐enabled research aids in the preservation of this threatened group.     

Testing optimality with experimental evolution: lysis time in a bacteriophage

Optimality models collapse the vagaries of genetics into simple trade-offs to calculate phenotypes expected to evolve by natural selection. Optimality approaches are commonly criticized for this neglect of genetic details, but resolution of this disagreement has been difficult. The importance of genetic details may be tested by experimental evolution of a trait for which an optimality model exists and in which genetic details can be studied. Here we evolved lysis time in bacteriophage T7, a virus of Escherichia coli. Lysis time is equivalent to the age of reproduction in an organism that reproduces once and then dies. Delaying lysis increases the number of offspring but slows generation time, and this trade-off renders the optimum sensitive to environmental conditions: earlier lysis is favored when bacterial hosts are dense, later lysis is favored when hosts are sparse. In experimental adaptations, T7 evolved close to the optimum in conditions favoring early lysis but not in conditions favoring late lysis. One of the late lysis adaptations exhibited no detectable phenotypic evolution despite genetic evolution; the other evolved only partly toward the expected optimum. Overall, the lysis time of the adapted phages remained closer to their starting values than predicted by the model. From the perspective of the optimality model, the experimental conditions were expected to select changes only along the postulated trade-off, but a trait outside the trade-off evolved as well. Evidence suggests that the model's failure ultimately stems from a violation of the trade-off, rather than a paucity of mutations.     

FUNCTIONAL GENETIC DIVERGENCE IN HIGH CO2 ADAPTED EMILIANIA HUXLEYI POPULATIONS

Predicting the impacts of environmental change on marine organisms, food webs, and biogeochemical cycles presently relies almost exclusively on short‐term physiological studies, while the possibility of adaptive evolution is often ignored. Here, we assess adaptive evolution in the coccolithophore Emiliania huxleyi, a well‐established model species in biological oceanography, in response to ocean acidification. We previously demonstrated that this globally important marine phytoplankton species adapts within 500 generations to elevated CO₂. After 750 and 1000 generations, no further fitness increase occurred, and we observed phenotypic convergence between replicate populations. We then exposed adapted populations to two novel environments to investigate whether or not the underlying basis for high CO₂‐adaptation involves functional genetic divergence, assuming that different novel mutations become apparent via divergent pleiotropic effects. The novel environment “high light” did not reveal such genetic divergence whereas growth in a low‐salinity environment revealed strong pleiotropic effects in high CO₂ adapted populations, indicating divergent genetic bases for adaptation to high CO₂. This suggests that pleiotropy plays an important role in adaptation of natural E. huxleyi populations to ocean acidification. Our study highlights the potential mutual benefits for oceanography and evolutionary biology of using ecologically important marine phytoplankton for microbial evolution experiments.     

The interaction of sexually and naturally selected traits in the adaptive radiations of cichlid fishes

The question of how genetic variation translates into organismal diversity has puzzled biologists for decades. Despite recent advances in evolutionary and developmental genetics, the mechanisms that underlie adaptation, diversification and evolutionary innovation remain largely unknown. The exceptionally diverse species flocks of cichlid fishes are textbook examples of adaptive radiation and explosive speciation and emerge as powerful model systems to study the genetic basis of animal diversification. East Africa's hundreds of endemic cichlid species are akin to a natural mutagenesis screen and differ greatly not only in ecologically relevant (hence naturally selected) characters such as mouth morphology and body shape, but also in sexually selected traits such as coloration. One of the most fascinating aspects of cichlid evolution is the frequent occurrence of evolutionary parallelisms, which has led to the question whether selection alone is sufficient to produce these parallel morphologies, or whether a developmental or genetic bias has influenced the direction of diversification. Here, I review fitness-relevant traits that could be responsible for the cichlids' evolutionary success and assess whether these were shaped by sexual or natural selection. I then focus on the interaction and the relative importance of sexual vs. natural selection in cichlid evolution. Finally, I discuss what is currently known about the genes underlying the morphogenesis of adaptively relevant traits and highlight the importance of the forthcoming cichlid genomes in the quest of the genetic basis of diversification in this group.     

What paths do advantageous alleles take during short‐term evolutionary change?

Combining experimental evolution with whole‐genome resequencing is a promising new strategy for investigating the dynamics of evolutionary change. Published studies that have resequenced laboratory‐selected populations of sexual organisms have typically focused on populations sampled at the end of an evolution experiment. These studies have attempted to associate particular alleles with phenotypic change and attempted to distinguish between different theoretical models of adaptation. However, neither the population used to initiate the experiment nor multiple time points sampled during the evolutionary trajectory are generally available for examination. In this issue of Molecular Ecology, Orozco‐terWengel et al. (2012) take a significant step forward by estimating genome‐wide allele frequencies at the start, 15 generations into and at the end of a 37‐generation Drosophila experimental evolution study. The authors identify regions of the genome that have responded to laboratory selection and describe the temporal dynamics of allele frequency change. They identify two common trajectories for putatively adaptive alleles: alleles either gradually increase in frequency throughout the entire 37 generations or alleles plateau at a new frequency by generation 15. The identification of complex trajectories of alleles under selection contributes to a growing body of literature suggesting that simple models of adaptation, whereby beneficial alleles arise and increase in frequency unimpeded until they become fixed, may not adequately describe short‐term response to selection.     

Genetics of dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.     

Evolutionary quantitative genetics of nonlinear developmental systems

In quantitative genetics, the effects of developmental relationships among traits on microevolution are generally represented by the contribution of pleiotropy to additive genetic covariances. Pleiotropic additive genetic covariances arise only from the average effects of alleles on multiple traits, and therefore the evolutionary importance of nonlinearities in development is generally neglected in quantitative genetic views on evolution. However, nonlinearities in relationships among traits at the level of whole organisms are undeniably important to biology in general, and therefore critical to understanding evolution. I outline a system for characterizing key quantitative parameters in nonlinear developmental systems, which yields expressions for quantities such as trait means and phenotypic and genetic covariance matrices. I then develop a system for quantitative prediction of evolution in nonlinear developmental systems. I apply the system to generating a new hypothesis for why direct stabilizing selection is rarely observed. Other uses will include separation of purely correlative from direct and indirect causal effects in studying mechanisms of selection, generation of predictions of medium‐term evolutionary trajectories rather than immediate predictions of evolutionary change over single generation time‐steps, and the development of efficient and biologically motivated models for separating additive from epistatic genetic variances and covariances.     

A multivariate test of evolutionary constraints for thermal tolerance in Drosophila melanogaster

Exposure to extreme temperatures is increasingly likely to impose strong selection on many organisms in their natural environments. The ability of organisms to adapt to such selective pressures will be determined by patterns of genetic variation and covariation. Despite increasing interest in thermal adaptation, few studies have examined the extent to which the genetic covariance between traits might constrain thermal responses. Furthermore, it remains unknown whether sex‐specific genetic architectures will constrain responses to climatic selection. We used a paternal half‐sibling breeding design to examine whether sex‐specific genetic architectures and genetic covariances between traits might constrain evolutionary responses to warming climates in a population of Drosophila melanogaster. Our results suggest that the sexes share a common genetic underpinning for heat tolerance as indicated by a strong positive inter‐sexual genetic correlation. Further, we found no evidence in either of the sexes that genetic trade‐offs between heat tolerance and fitness will constrain responses to thermal selection. Our results suggest that neither trade‐offs, nor sex‐specific genetics, will significantly constrain an evolutionary response to climatic warming, at least in this population of D. melanogaster.     

The evolution and evolutionary consequences of marginal thermostability in proteins

When we seek to explain the characteristics of living systems in their evolutionary context, we are often interested in understanding how and why certain properties arose through evolution, and how these properties then affected the continuing evolutionary process. This endeavor has been assisted by the use of simple computational models that have properties characteristic of natural living systems but allow simulations over evolutionary timescales with full transparency. We examine a model of the evolution of a gene under selective pressure to code for a protein that exists in a prespecified folded state at a given growth temperature. We observe the emergence of proteins with modest stabilities far below those possible with the model, with a denaturation temperature tracking the simulation temperature, despite the absence of selective pressure for such marginal stability. This demonstrates that neither observations of marginally stable proteins, nor even instances where increased stability interferes with function, provide evidence that marginal stability is an adaptation. Instead the marginal stability is the result of a balance between predominantly destabilizing mutations and selection that shifts depending on effective population size. Even if marginal stability is not an adaptation, the natural tendency of proteins toward marginal stability, and the range of stabilities that occur during evolution, may have significant effect on the evolutionary process.     

Evolution of the capacity to evolve

Abstract During the past two decades, the fields of molecular biology and genetics have enabled study of far broader and more detailed aspects of evolutionary change than were possible when the evolutionary synthesis was elaborated in the mid‐twentieth century. The capacity for complete sequencing of both genes and proteins of all groups of organisms provide, simultaneously, the means to determine both the patterns and processes of evolution throughout the history of life. Increased knowledge of the genome documents the changing nature of its composition, mode of transmission, and the nature of the units of selection. Advances in evolutionary developmental biology demonstrate the conservation of genetic elements throughout multicellular organisms, and explain how control of the timing, position and nature of their expression has produced the extraordinary diversity of living plants and animals. The next generation of evolutionary biologists will benefit greatly from the increased integration of these new fields of research with those that are currently emphasized in the standard textbooks and journals.     

The genome‐centric concept: resynthesis of evolutionary theory

Modern biology has been heavily influenced by the gene‐centric concept. Paradoxically, this very concept – on which bioresearch is based – is challenged by the success of gene‐based research in terms of explaining evolutionary theory. To overcome this major roadblock, it is essential to establish new theories, to not only solve the key puzzles presented by the gene‐centric concept, but also to provide a conceptual framework that allows the field to grow. This paper discusses a number of paradoxes and illustrates how they can be addressed by the genome‐centric concept in order to further resynthesize evolutionary theory. In particular, methodological breakthroughs that analyze genome evolution are discussed. The multiple interactions among different levels of a complex system provide the key to understanding the relationship between self‐organization and natural selection. Darwinian natural selection applies to the biological level due to its unique genetic and heterogeneous features, but does not simply or directly apply to either the lower non‐living level or higher intellectual society level. At the complex bio‐system level, the genome context (the entire package of genes and their genomic physical relationship or genomic topology), not the individual genes, defines the system and serves as the principle selection platform for evolution.     

Social traits,social networks and evolutionary biology

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals’ network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group‐level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic effects) provides the potential to understand how entire networks of social interactions in populations influence phenotypes and predict how these traits may evolve. By theoretical integration of social network analysis and quantitative genetics, we hope to identify areas of compatibility and incompatibility and to direct research efforts towards the most promising areas. Continuing this synthesis could provide important insights into the evolution of traits expressed in a social context and the evolutionary consequences of complex and nuanced social phenotypes.     

Darwinian adaptation,population genetics and the streetcar theory of evolution

 This paper investigates the problem of how to conceive a robust theory of phenotypic adaptation in non-trivial models of evolutionary biology. A particular effort is made to develop a foundation of this theory in the context of n-locus population genetics. Therefore, the evolution of phenotypic traits is considered that are coded for by more than one gene. The potential for epistatic gene interactions is not a priori excluded. Furthermore, emphasis is laid on the intricacies of frequency-dependent selection. It is first discussed how strongly the scope for phenotypic adaptation is restricted by the complex nature of ‘reproduction mechanics’ in sexually reproducing diploid populations. This discussion shows that one can easily lose the traces of Darwinism in n-locus models of population genetics. In order to retrieve these traces, the outline of a new theory is given that I call ‘streetcar theory of evolution’. This theory is based on the same models that geneticists have used in order to demonstrate substantial problems with the ‘adaptationist programme’. However, these models are now analyzed differently by including thoughts about the evolutionary removal of genetic constraints. This requires consideration of a sufficiently wide range of potential mutant alleles and careful examination of what to consider as a stable state of the evolutionary process. A particular notion of stability is introduced in order to describe population states that are phenotypically stable against the effects of all mutant alleles that are to be expected in the long-run. Surprisingly, a long-term stable state can be characterized at the phenotypic level as a fitness maximum, a Nash equilibrium or an ESS. The paper presents these mathematical results and discusses – at unusual length for a mathematical journal – their fundamental role in our current understanding of evolution. Received 22 April 1994; received in revised form 10 July 1995     

Rapid climate change and the rate of adaptation: insight from experimental quantitative genetics

CONTENTS: Summary 752 I. Introduction 752 II. Will migration be enough? 753 III. Can adaptation proceed fast enough? 754 IV. Fitness links demographic and evolutionary processes 755 V. Experimental studies: what do they tell us and how can we improve them? 756 VI. Predicting evolutionary change based on genetic variation and natural selection 757 VII. The chronosequence approach 758 VIII. Resurrection of ancestral propagules 759 IX. The mean and variance in fitness, a link between genetics and demography 760 X. Conclusions 762 Acknowledgements 762 References 762 SUMMARY: Evolution proceeds unceasingly in all biological populations. It is clear that climate-driven evolution has molded plants in deep time and within extant populations. However, it is less certain whether adaptive evolution can proceed sufficiently rapidly to maintain the fitness and demographic stability of populations subjected to exceptionally rapid contemporary climate change. Here, we consider this question, drawing on current evidence on the rate of plant range shifts and the potential for an adaptive evolutionary response. We emphasize advances in understanding based on theoretical studies that model interacting evolutionary processes, and we provide an overview of quantitative genetic approaches that can parameterize these models to provide more meaningful predictions of the dynamic interplay between genetics, demography and evolution. We outline further research that can clarify both the adaptive potential of plant populations as climate continues to change and the role played by ongoing adaptation in their persistence.     

Disentangling genetic and epigenetic determinants of ultrafast adaptation

A major rationale for the advocacy of epigenetically mediated adaptive responses is that they facilitate faster adaptation to environmental challenges. This motivated us to develop a theoretical–experimental framework for disclosing the presence of such adaptation‐speeding mechanisms in an experimental evolution setting circumventing the need for pursuing costly mutation–accumulation experiments. To this end, we exposed clonal populations of budding yeast to a whole range of stressors. By growth phenotyping, we found that almost complete adaptation to arsenic emerged after a few mitotic cell divisions without involving any phenotypic plasticity. Causative mutations were identified by deep sequencing of the arsenic‐adapted populations and reconstructed for validation. Mutation effects on growth phenotypes, and the associated mutational target sizes were quantified and embedded in data‐driven individual‐based evolutionary population models. We found that the experimentally observed homogeneity of adaptation speed and heterogeneity of molecular solutions could only be accounted for if the mutation rate had been near estimates of the basal mutation rate. The ultrafast adaptation could be fully explained by extensive positive pleiotropy such that all beneficial mutations dramatically enhanced multiple fitness components in concert. As our approach can be exploited across a range of model organisms exposed to a variety of environmental challenges, it may be used for determining the importance of epigenetic adaptation‐speeding mechanisms in general.     

Parallel adaptation to climate above the 35th parallel

Independent or parallel evolution of similar traits is key to understanding the genetics and limitations of adaptation. Adaptation from the same genetic changes in different populations defines parallel evolution. Such genetic changes can derive from standing ancestral variation or de novo mutations and excludes instances of adaptive introgression. In this issue of Molecular Ecology, Walden et al.(2020) investigate the scale of parallel climate adaptation from standing genetic variation between two North American Arabidopsis lyrata lineages, each formed by a distinct evolutionary history during the last glacial cycle. By identifying adaptive variants correlated with three ecologically significant climatic gradients, they show that instead of the same genetic variants or even genes, parallel evolution is only observed at the level of biological processes. The evolution of independent adaptive variants to climate in two genetically close lineages is explained by their different post‐glacial demographic histories. Separate glacial refugia and strong population bottlenecks were probably sufficient to change the landscape of shared allele frequencies, hindering the possibility of parallel evolution.     

Epigenetics in natural animal populations

Phenotypic plasticity is an important mechanism for populations to buffer themselves from environmental change. While it has long been appreciated that natural populations possess genetic variation in the extent of plasticity, a surge of recent evidence suggests that epigenetic variation could also play an important role in shaping phenotypic responses. Compared with genetic variation, epigenetic variation is more likely to have higher spontaneous rates of mutation and a more sensitive reaction to environmental inputs. In our review, we first provide an overview of recent studies on epigenetically encoded thermal plasticity in animals to illustrate environmentally‐mediated epigenetic effects within and across generations. Second, we discuss the role of epigenetic effects during adaptation by exploring population epigenetics in natural animal populations. Finally, we evaluate the evolutionary potential of epigenetic variation depending on its autonomy from genetic variation and its transgenerational stability. Although many of the causal links between epigenetic variation and phenotypic plasticity remain elusive, new data has explored the role of epigenetic variation in facilitating evolution in natural populations. This recent progress in ecological epigenetics will be helpful for generating predictive models of the capacity of organisms to adapt to changing climates.     

Population genomics of eusocial insects: the costs of a vertebrate‐like effective population size

The evolution of reproductive division of labour and social life in social insects has lead to the emergence of several life‐history traits and adaptations typical of larger organisms: social insect colonies can reach masses of several kilograms, they start reproducing only when they are several years old, and can live for decades. These features and the monopolization of reproduction by only one or few individuals in a colony should affect molecular evolution by reducing the effective population size. We tested this prediction by analysing genome‐wide patterns of coding sequence polymorphism and divergence in eusocial vs. noneusocial insects based on newly generated RNA‐seq data. We report very low amounts of genetic polymorphism and an elevated ratio of nonsynonymous to synonymous changes – a marker of the effective population size – in four distinct species of eusocial insects, which were more similar to vertebrates than to solitary insects regarding molecular evolutionary processes. Moreover, the ratio of nonsynonymous to synonymous substitutions was positively correlated with the level of social complexity across ant species. These results are fully consistent with the hypothesis of a reduced effective population size and an increased genetic load in eusocial insects, indicating that the evolution of social life has important consequences at both the genomic and population levels.