Natural selection. II. Developmental variability and evolutionary rate

The origin of novel traits in cancer

The traditional view of cancer emphasizes a genes-first process. Novel cancer traits arise by genetic mutations that spread to drive phenotypic change. However, recent data support a phenotypes-first process in which nonheritable cellular variability creates novel traits that later become heritably stabilized by genetic and epigenetic changes. Single-cell measurements reinforce the idea that phenotypes lead genotypes, showing how cancer evolution follows normal developmental plasticity and creates novel traits by recombining parts of different cellular developmental programs. In parallel, studies in evolutionary biology also support a phenotypes-first process driven by developmental plasticity and developmental recombination. These advances in cancer research and evolutionary biology mutually reinforce a revolution in our understanding of how cells and organisms evolve novel traits in response to environmental challenges.

Twenty years on from Developmental Plasticity and Evolution: middle-range theories and how to test them

In Developmental Plasticity and Evolution, Mary-Jane West-Eberhard argued that the developmental mechanisms that enable organisms to respond to their environment are fundamental causes of adaptation and diversification. Twenty years after publication of this book, this once so highly controversial claim appears to have been assimilated by a wealth of studies on 'plasticity-led' evolution. However, we suggest that the role of development in explanations for adaptive evolution remains underappreciated in this body of work. By combining concepts of evolvability from evolutionary developmental biology and quantitative genetics, we outline a framework that is more appropriate to identify developmental causes of adaptive evolution. This framework demonstrates how experimental and comparative developmental biology and physiology can be leveraged to put the role of plasticity in evolution to the test.

Heterogeneity in maternal mRNAs within clutches of eggs in response to thermal stress during the embryonic stage

BACKGROUND

The origin of variation is of central interest in evolutionary biology. Maternal mRNAs govern early embryogenesis in many animal species, and we investigated the possibility that heterogeneity in maternal mRNA provisioning of eggs can be modulated by environmental stimuli.

RESULTS

We employed two sibling species of the ascidian Ciona, called here types A and B, that are adapted to different temperature regimes and can be hybridized. Previous study showed that hybrids using type B eggs had higher susceptibility to thermal stress than hybrids using type A eggs. We conducted transcriptome analyses of multiple single eggs from crosses using eggs of the different species to compare the effects of maternal thermal stress on heterogeneity in egg provisioning, and followed the effects across generations. We found overall decreases of heterogeneity of egg maternal mRNAs associated with maternal thermal stress. When the eggs produced by the F1 AB generation were crossed with type B sperm and the progeny ('ABB' generation) reared unstressed until maturation, the overall heterogeneity of the eggs produced was greater in a clutch from an individual with a heat-stressed mother compared to one from a non-heat-stressed mother. By examining individual genes, we found no consistent overall effect of thermal stress on heterogeneity of expression in genes involved in developmental buffering. In contrast, heterogeneity of expression in signaling molecules was directly affected by thermal stress.

CONCLUSIONS

Due to the absence of batch replicates and variation in the number of reads obtained, our conclusions are very limited. However, contrary to the predictions of bet-hedging, the results suggest that maternal thermal stress at the embryo stage is associated with reduced heterogeneity of maternal mRNA provision in the eggs subsequently produced by the stressed individual, but there is then a large increase in heterogeneity in eggs of the next generation, although itself unstressed. Despite its limitations, our study presents a proof of concept, identifying a model system, experimental approach and analytical techniques capable of providing a significant advance in understanding the impact of maternal environment on developmental heterogeneity.

"Bet hedging" against climate change in developing and adult animals: roles for stochastic gene expression, phenotypic plasticity, epigenetic inheritance and adaptation

Animals from embryos to adults experiencing stress from climate change have numerous mechanisms available for enhancing their long-term survival. In this review we consider these options, and how viable they are in a world increasingly experiencing extreme weather associated with climate change. A deeply understood mechanism involves natural selection, leading to evolution of new adaptations that help cope with extreme and stochastic weather events associated with climate change. While potentially effective at staving off environmental challenges, such adaptations typically occur very slowly and incrementally over evolutionary time. Consequently, adaptation through natural selection is in most instances regarded as too slow to aid survival in rapidly changing environments, especially when considering the stochastic nature of extreme weather events associated with climate change. Alternative mechanisms operating in a much shorter time frame than adaptation involve the rapid creation of alternate phenotypes within a life cycle or a few generations. Stochastic gene expression creates multiple phenotypes from the same genotype even in the absence of environmental cues. In contrast, other mechanisms for phenotype change that are externally driven by environmental clues include well-understood developmental phenotypic plasticity (variation, flexibility), which can enable rapid, within-generation changes. Increasingly appreciated are epigenetic influences during development leading to rapid phenotypic changes that can also immediately be very widespread throughout a population, rather than confined to a few individuals as in the case of favorable gene mutations. Such epigenetically-induced phenotypic plasticity can arise rapidly in response to stressors within a generation or across a few generations and just as rapidly be "sunsetted" when the stressor dissipates, providing some capability to withstand environmental stressors emerging from climate change. Importantly, survival mechanisms resulting from adaptations and developmental phenotypic plasticity are not necessarily mutually exclusive, allowing for classic "bet hedging". Thus, the appearance of multiple phenotypes within a single population provides for a phenotype potentially optimal for some future environment. This enhances survival during stochastic extreme weather events associated with climate change. Finally, we end with recommendations for future physiological experiments, recommending in particular that experiments investigating phenotypic flexibility adopt more realistic protocols that reflect the stochastic nature of weather.

Exploring the expanse between theoretical questions and experimental approaches in the modern study of evolvability

Despite several decades of computational and experimental work across many systems, evolvability remains on the periphery with regards to its status as a widely accepted and regularly applied theoretical concept. Here we propose that its marginal status is partly a result of large gaps between the diverse but disconnected theoretical treatments of evolvability and the relatively narrower range of studies that have tested it empirically. To make this case, we draw on a range of examples-from experimental evolution in microbes, to molecular evolution in proteins-where attempts have been made to mend this disconnect. We highlight some examples of progress that has been made and point to areas where synthesis and translation of existing theory can lead to further progress in the still-new field of empirical measurements of evolvability.

Evolution of phenotypic fluctuation under host-parasite interactions

Robustness and plasticity are essential features that allow biological systems to cope with complex and variable environments. In a constant environment, robustness, i.e., insensitivity of phenotypes, is expected to increase, whereas plasticity, i.e., the changeability of phenotypes, tends to diminish. Under a variable environment, existence of plasticity will be relevant. The robustness and plasticity, on the other hand, are related to phenotypic variances. As phenotypic variances decrease with the increase in robustness to perturbations, they are expected to decrease through the evolution. However, in nature, phenotypic fluctuation is preserved to a certain degree. One possible cause for this is environmental variation, where one of the most important “environmental” factors will be inter-species interactions. As a first step toward investigating phenotypic fluctuation in response to an inter-species interaction, we present the study of a simple two-species system that comprises hosts and parasites. Hosts are expected to evolve to achieve a phenotype that optimizes fitness. Then, the robustness of the corresponding phenotype will be increased by reducing phenotypic fluctuations. Conversely, plasticity tends to evolve to avoid certain phenotypes that are attacked by parasites. By using a dynamic model of gene expression for the host, we investigate the evolution of the genotype-phenotype map and of phenotypic variances. If the host–parasite interaction is weak, the fittest phenotype of the host evolves to reduce phenotypic variances. In contrast, if there exists a sufficient degree of interaction, the phenotypic variances of hosts increase to escape parasite attacks. For the latter case, we found two strategies: if the noise in the stochastic gene expression is below a certain threshold, the phenotypic variance increases via genetic diversification, whereas above this threshold, it is increased mediated by noise-induced phenotypic fluctuation. We examine how the increase in the phenotypic variances caused by parasite interactions influences the growth rate of a single host, and observed a trade-off between the two. Our results help elucidate the roles played by noise and genetic mutations in the evolution of phenotypic fluctuation and robustness in response to host–parasite interactions.

Plasticity and phenotypic variability induced by internal or external perturbations are common features of biological systems. However, under evolution for given environmental conditions, phenotypic variability is not advantageous, because it leads to the deviation from the fittest state. This has been demonstrated by previous laboratory and computer experiments. As a possible origin for the remnant phenotypic variance, we investigated the role of host–parasite interactions such as those between bacteria and phages. Different parasite-types attack hosts of certain phenotypes. Through numerical simulations of the evolution of the host genotype–phenotype mapping, we found that hosts increase phenotypic variation by increasing phenotypic fluctuations if the interaction is sufficiently strong. Depending on the degree of noise in gene expression dynamics, there are two distinct strategies for increasing phenotypic variances: stochasticity in gene expression or genetic variances. The former strategy, which can work over a faster time scale, leads to a decline in fitness, whereas the latter reduces the robustness of the fitted state. Our results provide insights into how phenotypic variances are preserved and how hosts can escape being attacked by parasites whose genes mutate to adapt to changes in parasites. These two host strategies, which depend on internal and external conditions, can be verified experimentally via the transcriptome analysis of microorganisms.

Plasticity via feedback reduces the cost of developmental instability

Costs of plasticity are thought to have important physiological and evolutionary consequences. A commonly predicted cost to plasticity is that plastic genotypes are likely to suffer from developmental instability. Adaptive plasticity requires that the developing organism can in some way sense what environment it is in or how well it is performing in that environment. These two information pathways—an “environmental signal” or a “performance signal” that indicates how well a developing phenotype matches the optimum in the current environment—can differ in their consequences for the organism and its evolution. Here, we consider how developmental instability might emerge as a side‐effect of these two distinct mechanisms. Because a performance cue allows a regulatory feedback loop connecting a trait to a feedback signal, we hypothesized that plastic genotypes using a performance signal would be more developmentally robust compared to those using a purely environmental signal. Using a numerical model of a network of gene interactions, we show that plasticity comes at a cost of developmental instability when the plastic response is mediated via an environmental signal, but not when it is mediated via a performance signal. We also show that a performance signal mechanism can evolve even in a constant environment, leading to genotypes preadapted for plasticity to novel environments even in populations without a history of environmental heterogeneity.

Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Nongenetic phenotypic variation can either speed up or slow down adaptive evolution. We show that it can speed up evolution in environments where available carbon and energy sources change over time. To this end, we use an experimentally validated model of Escherichia coli growth on two alternative carbon sources, glucose and acetate. On the superior carbon source (glucose), all cells achieve high growth rates, while on the inferior carbon source (acetate) only a small fraction of the population manages to initiate growth. Consequently, populations experience a bottleneck when the environment changes from the superior to the inferior carbon source. Growth on the inferior carbon source depends on a circuit under the control of a transcription factor that is repressed in the presence of the superior carbon source. We show that noise in the expression of this transcription factor can increase the probability that cells start growing on the inferior carbon source. In doing so, it can decrease the severity of the bottleneck and increase mean population fitness whenever this fitness is low. A modest amount of noise can also enhance the fitness effects of a beneficial allele that increases the fraction of a population initiating growth on acetate. Additionally, noise can protect this allele from extinction, accelerate its spread, and increase its likelihood of going to fixation. Central to the adaptation-enhancing principle we identify is the ability of noise to mitigate population bottlenecks, particularly in environments that fluctuate periodically. Because such bottlenecks are frequent in fluctuating environments, and because periodically fluctuating environments themselves are common, this principle may apply to a broad range of environments and organisms.

Plasticity leaves a phenotypic signature during local adaptation

Phenotypic responses to a novel or extreme environment are initially plastic, only later to be followed by genetic change. Whether or not environmentally induced phenotypes are sufficiently recurrent and fit to leave a signature in adaptive evolution is debated. Here, we analyze multivariate data from 34 plant reciprocal transplant studies to test: (1) if plasticity is an adaptive source of developmental bias that makes locally adapted populations resemble the environmentally induced phenotypes of ancestors; and (2) if plasticity, standing phenotypic variation and genetic divergence align during local adaptation. Phenotypic variation increased marginally in foreign environments but, as predicted, the direction of ancestral plasticity was generally well aligned with the phenotypic difference between locally adapted populations, making plasticity appear to "take the lead" in adaptive evolution. Plastic responses were sometimes more extreme than the phenotypes of locally adapted plants, which can give the impression that plasticity and evolutionary adaptation oppose each other; however, environmentally induced and locally adapted phenotypes were rarely misaligned. Adaptive fine‐tuning of phenotypes—genetic accommodation—did not fall along the main axis of standing phenotypic variation or the direction of plasticity, and local adaptation did not consistently modify the direction or magnitude of plasticity. These results suggest that plasticity is a persistent source of developmental bias that shapes how plant populations adapt to environmental change, even when plasticity does not constrain how populations respond to selection.

Animal learning as a source of developmental bias

As a form of adaptive plasticity that allows organisms to shift their phenotype toward the optimum, learning is inherently a source of developmental bias. Learning may be of particular significance to the evolutionary biology community because it allows animals to generate adaptively biased novel behavior tuned to the environment and, through social learning, to propagate behavioral traits to other individuals, also in an adaptively biased manner. We describe several types of developmental bias manifest in learning, including an adaptive bias, historical bias, origination bias, and transmission bias, stressing that these can influence evolutionary dynamics through generating nonrandom phenotypic variation and/or nonrandom environmental states. Theoretical models and empirical data have established that learning can impose direction on adaptive evolution, affect evolutionary rates (both speeding up and slowing down responses to selection under different conditions) and outcomes, influence the probability of populations reaching global optimum, and affect evolvability. Learning is characterized by highly specific, path-dependent interactions with the (social and physical) environment, often resulting in new phenotypic outcomes. Consequently, learning regularly introduces novelty into phenotype space. These considerations imply that learning may commonly generate plasticity first evolution.

Every which way? On predicting tumor evolution using cancer progression models

Successful prediction of the likely paths of tumor progression is valuable for diagnostic, prognostic, and treatment purposes. Cancer progression models (CPMs) use cross-sectional samples to identify restrictions in the order of accumulation of driver mutations and thus CPMs encode the paths of tumor progression. Here we analyze the performance of four CPMs to examine whether they can be used to predict the true distribution of paths of tumor progression and to estimate evolutionary unpredictability. Employing simulations we show that if fitness landscapes are single peaked (have a single fitness maximum) there is good agreement between true and predicted distributions of paths of tumor progression when sample sizes are large, but performance is poor with the currently common much smaller sample sizes. Under multi-peaked fitness landscapes (i.e., those with multiple fitness maxima), performance is poor and improves only slightly with sample size. In all cases, detection regime (when tumors are sampled) is a key determinant of performance. Estimates of evolutionary unpredictability from the best performing CPM, among the four examined, tend to overestimate the true unpredictability and the bias is affected by detection regime; CPMs could be useful for estimating upper bounds to the true evolutionary unpredictability. Analysis of twenty-two cancer data sets shows low evolutionary unpredictability for several of the data sets. But most of the predictions of paths of tumor progression are very unreliable, and unreliability increases with the number of features analyzed. Our results indicate that CPMs could be valuable tools for predicting cancer progression but that, currently, obtaining useful predictions of paths of tumor progression from CPMs is dubious, and emphasize the need for methodological work that can account for the probably multi-peaked fitness landscapes in cancer.

The causes of evolvability and their evolution

Evolvability is the ability of a biological system to produce phenotypic variation that is both heritable and adaptive. It has long been the subject of anecdotal observations and theoretical work. In recent years, however, the molecular causes of evolvability have been an increasing focus of experimental work. Here, we review recent experimental progress in areas as different as the evolution of drug resistance in cancer cells and the rewiring of transcriptional regulation circuits in vertebrates. This research reveals the importance of three major themes: multiple genetic and non-genetic mechanisms to generate phenotypic diversity, robustness in genetic systems, and adaptive landscape topography. We also discuss the mounting evidence that evolvability can evolve and the question of whether it evolves adaptively.

The reach of gene-culture coevolution in animals

Culture (behaviour based on socially transmitted information) is present in diverse animal species, yet how it interacts with genetic evolution remains largely unexplored. Here, we review the evidence for gene-culture coevolution in animals, especially birds, cetaceans and primates. We describe how culture can relax or intensify selection under different circumstances, create new selection pressures by changing ecology or behaviour, and favour adaptations, including in other species. Finally, we illustrate how, through culturally mediated migration and assortative mating, culture can shape population genetic structure and diversity. This evidence suggests strongly that animal culture plays an important evolutionary role, and we encourage explicit analyses of gene-culture coevolution in nature.

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.

Links between evolutionary processes and phenotypic robustness in microbes

The costs and benefits of random phenotypic heterogeneity in microbes have been vigorously debated and experimental tested for decades; yet, this conversation is largely independent from discussion of phenotypic robustness in other disciplines. In this review I connect microbial examples of stochasticity with studies on the ecological and population-genetic consequences of phenotypic variability. These topics illustrate the complexity of selection pressures on phenotypic robustness and provide inspiration that this complexity can be parsed with theoretical advances and the experimental power of microbial systems.

Puzzles in modern biology. V. Why are genomes overwired?

Many factors affect eukaryotic gene expression. Transcription factors, histone codes, DNA folding, and noncoding RNA modulate expression. Those factors interact in large, broadly connected regulatory control networks. An engineer following classical principles of control theory would design a simpler regulatory network. Why are genomes overwired? Neutrality or enhanced robustness may lead to the accumulation of additional factors that complicate network architecture. Dynamics progresses like a ratchet. New factors get added. Genomes adapt to the additional complexity. The newly added factors can no longer be removed without significant loss of fitness. Alternatively, highly wired genomes may be more malleable. In large networks, most genomic variants tend to have a relatively small effect on gene expression and trait values. Many small effects lead to a smooth gradient, in which traits may change steadily with respect to underlying regulatory changes. A smooth gradient may provide a continuous path from a starting point up to the highest peak of performance. A potential path of increasing performance promotes adaptability and learning. Genomes gain by the inductive process of natural selection, a trial and error learning algorithm that discovers general solutions for adapting to environmental challenge. Similarly, deeply and densely connected computational networks gain by various inductive trial and error learning procedures, in which the networks learn to reduce the errors in sequential trials. Overwiring alters the geometry of induction by smoothing the gradient along the inductive pathways of improving performance. Those overwiring benefits for induction apply to both natural biological networks and artificial deep learning networks.

Phenotypic heterogeneity promotes adaptive evolution

Genetically identical cells frequently display substantial heterogeneity in gene expression, cellular morphology and physiology. It has been suggested that by rapidly generating a subpopulation with novel phenotypic traits, phenotypic heterogeneity (or plasticity) accelerates the rate of adaptive evolution in populations facing extreme environmental challenges. This issue is important as cell-to-cell phenotypic heterogeneity may initiate key steps in microbial evolution of drug resistance and cancer progression. Here, we study how stochastic transitions between cellular states influence evolutionary adaptation to a stressful environment in yeast Saccharomyces cerevisiae. We developed inducible synthetic gene circuits that generate varying degrees of expression stochasticity of an antifungal resistance gene. We initiated laboratory evolutionary experiments with genotypes carrying different versions of the genetic circuit by exposing the corresponding populations to gradually increasing antifungal stress. Phenotypic heterogeneity altered the evolutionary dynamics by transforming the adaptive landscape that relates genotype to fitness. Specifically, it enhanced the adaptive value of beneficial mutations through synergism between cell-to-cell variability and genetic variation. Our work demonstrates that phenotypic heterogeneity is an evolving trait when populations face a chronic selection pressure. It shapes evolutionary trajectories at the genomic level and facilitates evolutionary rescue from a deteriorating environmental stress.

Phenotypic heterogeneity of genetically identical cells can generate nonheritable variation in a population. Is this heterogeneity favorable for microbes? In a changing environment, the answer is a definite yes. While scholars have argued that stochastically generated variation precedes genetic changes and thereby facilitate the evolution of complex traits, this idea has remained disputed, not least because of the shortage of experimental studies. We address this long-standing and controversial issue by integrating synthetic biology, laboratory experimental evolution, and genomic analyses. We explicitly tested the mechanisms whereby phenotypic heterogeneity may promote evolvability. Our work demonstrates that phenotypic heterogeneity facilitates evolutionary rescue from deteriorating environmental stress by generating individuals with exceptionally high fitness. Remarkably, elevated phenotypic heterogeneity evolves as a direct response to stress and thereby it promotes evolution of rare combinations of mutations. These results indicate that phenotypic heterogeneity might have an important role in the evolution of key innovations.

Puzzles in modern biology. II. Language, cancer and the recursive processes of evolutionary innovation

Human language emerged abruptly. Diverse body forms evolved suddenly. Seed-bearing plants spread rapidly. How do complex evolutionary innovations arise so quickly? Resolving alternative claims remains difficult. The great events of the past happened a long time ago. Cancer provides a model to study evolutionary innovation. A tumor must evolve many novel traits to become an aggressive cancer. I use what we know or could study about cancer to describe the key processes of innovation. In general, evolutionary systems form a hierarchy of recursive processes. Those recursive processes determine the rates at which innovations are generated, spread and transmitted. I relate the recursive processes to abrupt evolutionary innovation.

Rethinking phenotypic plasticity and its consequences for individuals, populations and species

Much research has been devoted to identify the conditions under which selection favours flexible individuals or genotypes that are able to modify their growth, development and behaviour in response to environmental cues, to unravel the mechanisms of plasticity and to explore its influence on patterns of diversity among individuals, populations and species. The consequences of developmental plasticity and phenotypic flexibility for the performance and ecological success of populations and species have attracted a comparatively limited but currently growing interest. Here, I re-emphasize that an increased understanding of the roles of plasticity in these contexts requires a 'whole organism' (rather than 'single trait') approach, taking into consideration that organisms are integrated complex phenotypes. I further argue that plasticity and genetic polymorphism should be analysed and discussed within a common framework. I summarize predictions from theory on how phenotypic variation stemming from developmental plasticity and phenotypic flexibility may affect different aspects of population-level performance. I argue that it is important to distinguish between effects associated with greater interindividual phenotypic variation resulting from plasticity, and effects mediated by variation among individuals in the capacity to express plasticity and flexibility as such. Finally, I claim that rigorous testing of predictions requires methods that allow for quantifying and comparing whole organism plasticity, as well as the ability to experimentally manipulate the level of and capacity for developmental plasticity and phenotypic flexibility independent of genetic variation.

Neurogenomic mechanisms of social plasticity

Group-living animals must adjust the expression of their social behaviour to changes in their social environment and to transitions between life-history stages, and this social plasticity can be seen as an adaptive trait that can be under positive selection when changes in the environment outpace the rate of genetic evolutionary change. Here, we propose a conceptual framework for understanding the neuromolecular mechanisms of social plasticity. According to this framework, social plasticity is achieved by rewiring or by biochemically switching nodes of a neural network underlying social behaviour in response to perceived social information. Therefore, at the molecular level, it depends on the social regulation of gene expression, so that different genomic and epigenetic states of this brain network correspond to different behavioural states, and the switches between states are orchestrated by signalling pathways that interface the social environment and the genotype. Different types of social plasticity can be recognized based on the observed patterns of inter- versus intra-individual occurrence, time scale and reversibility. It is proposed that these different types of social plasticity rely on different proximate mechanisms at the physiological, neural and genomic level.

Individual differences in behavioural plasticities

Interest in individual differences in animal behavioural plasticities has surged in recent years, but research in this area has been hampered by semantic confusion as different investigators use the same terms (e.g. plasticity, flexibility, responsiveness) to refer to different phenomena. The first goal of this review is to suggest a framework for categorizing the many different types of behavioural plasticities, describe examples of each, and indicate why using reversibility as a criterion for categorizing behavioural plasticities is problematic. This framework is then used to address a number of timely questions about individual differences in behavioural plasticities. One set of questions concerns the experimental designs that can be used to study individual differences in various types of behavioural plasticities. Although within-individual designs are the default option for empirical studies of many types of behavioural plasticities, in some situations (e.g. when experience at an early age affects the behaviour expressed at subsequent ages), 'replicate individual' designs can provide useful insights into individual differences in behavioural plasticities. To date, researchers using within-individual and replicate individual designs have documented individual differences in all of the major categories of behavioural plasticities described herein. Another important question is whether and how different types of behavioural plasticities are related to one another. Currently there is empirical evidence that many behavioural plasticities [e.g. contextual plasticity, learning rates, IIV (intra-individual variability), endogenous plasticities, ontogenetic plasticities) can themselves vary as a function of experiences earlier in life, that is, many types of behavioural plasticity are themselves developmentally plastic. These findings support the assumption that differences among individuals in prior experiences may contribute to individual differences in behavioural plasticities observed at a given age. Several authors have predicted correlations across individuals between different types of behavioural plasticities, i.e. that some individuals will be generally more plastic than others. However, empirical support for most of these predictions, including indirect evidence from studies of relationships between personality traits and plasticities, is currently sparse and equivocal. The final section of this review suggests how an appreciation of the similarities and differences between different types of behavioural plasticities may help theoreticians formulate testable models to explain the evolution of individual differences in behavioural plasticities and the evolutionary and ecological consequences of individual differences in behavioural plasticities.

Group selection as behavioral adaptation to systematic risk

Despite many compelling applications in economics, sociobiology, and evolutionary psychology, group selection is still one of the most hotly contested ideas in evolutionary biology. Here we propose a simple evolutionary model of behavior and show that what appears to be group selection may, in fact, simply be the consequence of natural selection occurring in stochastic environments with reproductive risks that are correlated across individuals. Those individuals with highly correlated risks will appear to form "groups", even if their actions are, in fact, totally autonomous, mindless, and, prior to selection, uniformly randomly distributed in the population. This framework implies that a separate theory of group selection is not strictly necessary to explain observed phenomena such as altruism and cooperation. At the same time, it shows that the notion of group selection does captures a unique aspect of evolution-selection with correlated reproductive risk-that may be sufficiently widespread to warrant a separate term for the phenomenon.

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.

Phenotypic plasticity in nematodes: Evolutionary and ecological significance

Model systems, including C. elegans, have been successfully studied to understand the genetic control of development. A genotype's phenotype determines its evolutionary fitness in natural environments, which are typically harsh, heterogeneous and dynamic. Phenotypic plasticity, the process by which one genome can produce different phenotypes in response to the environment, allows genotypes to better match their phenotype to their environment. Phenotypic plasticity is rife among nematodes, seen both as differences among life-cycles stages, perhaps best exemplified by parasitic nematodes, as well as developmental choices, such as shown by the C. elegans dauer/non-dauer developmental choice. Understanding the genetic basis of phenotypically plastic traits will probably explain the function of many genes whose function still remains unclear. Understanding the adaptive benefits of phenotypically plastic traits requires that we understand how plasticity differs among genotypes, and the effects of this in diverse, different environments.

Genetic and nongenetic determinants of cell growth variation assessed by high-throughput microscopy

In microbial populations, growth initiation and proliferation rates are major components of fitness and therefore likely targets of selection. We used a high-throughput microscopy assay, which enables simultaneous analysis of tens of thousands of microcolonies, to determine the sources and extent of growth rate variation in the budding yeast (Saccharomyces cerevisiae) in different glucose environments. We find that cell growth rates are regulated by the extracellular concentration of glucose as proposed by Monod (1949), but that significant heterogeneity in growth rates is observed among genetically identical individuals within an environment. Yeast strains isolated from different geographic locations and habitats differ in their growth rate responses to different glucose concentrations. Inheritance patterns suggest that the genetic determinants of growth rates in different glucose concentrations are distinct. In addition, we identified genotypes that differ in the extent of variation in growth rate within an environment despite nearly identical mean growth rates, providing evidence that alleles controlling phenotypic variability segregate in yeast populations. We find that the time to reinitiation of growth (lag) is negatively correlated with growth rate, yet this relationship is strain-dependent. Between environments, the respirative activity of individual cells negatively correlates with glucose abundance and growth rate, but within an environment respirative activity and growth rate show a positive correlation, which we propose reflects differences in protein expression capacity. Our study quantifies the sources of genetic and nongenetic variation in cell growth rates in different glucose environments with unprecedented precision, facilitating their molecular genetic dissection.

Hypoxia tolerance of common sole juveniles depends on dietary regime and temperature at the larval stage: evidence for environmental conditioning

An individual's environmental history may have delayed effects on its physiology and life history at later stages in life because of irreversible plastic responses of early ontogenesis to environmental conditions. We chose a marine fish, the common sole, as a model species to study these effects, because it inhabits shallow marine areas highly exposed to environmental changes. We tested whether temperature and trophic conditions experienced during the larval stage had delayed effects on life-history traits and resistance to hypoxia at the juvenile stage. We thus examined the combined effect of global warming and hypoxia in coastal waters, which are potential stressors to many estuarine and coastal marine fishes. Elevated temperature and better trophic conditions had a positive effect on larval growth and developmental rates; warmer larval temperature had a delayed positive effect on body mass and resistance to hypoxia at the juvenile stage. The latter suggests a lower oxygen demand of individuals that had experienced elevated temperatures during larval stages. We hypothesize that an irreversible plastic response to temperature occurred during early ontogeny that allowed adaptive regulation of metabolic rates and/or oxygen demand with long-lasting effects. These results could deeply affect predictions about impacts of global warming and eutrophication on marine organisms.

Baldwin effect under multipeaked fitness landscapes: phenotypic fluctuation accelerates evolutionary rate

Phenotypic fluctuations and plasticity can generally affect the course of evolution, a process known as the Baldwin effect. Several studies have recast this effect and claimed that phenotypic plasticity accelerates evolutionary rate (the Baldwin expediting effect); however, the validity of this claim is still controversial. In this study, we investigate the evolutionary population dynamics of a quantitative genetic model under a multipeaked fitness landscape, in order to evaluate the validity of the effect. We provide analytical expressions for the evolutionary rate and average population fitness. Our results indicate that under a multipeaked fitness landscape, phenotypic fluctuation always accelerates evolutionary rate, but it decreases the average fitness. As an extreme case of the trade-off between the rate of evolution and average fitness, phenotypic fluctuation is shown to accelerate the error catastrophe, in which a population fails to sustain a high-fitness peak. In the context of our findings, we discuss the role of phenotypic plasticity in adaptive evolution.

Nonheritable cellular variability accelerates the evolutionary processes of cancer

Recent cancer studies emphasize that genetic and heritable epigenetic changes drive the evolutionary rate of cancer progression and drug resistance. We discuss the ways in which nonheritable aspects of cellular variability may significantly increase evolutionary rate. Nonheritable variability arises by stochastic fluctuations in cells and by physiological responses of cells to the environment. New approaches to drug design may be required to control nonheritable variability and the evolution of resistance to chemotherapy.