A G matrix analogue to capture the cumulative effects of nongenetic inheritance

The genetic variance‐covariance ( G ) matrix describes the variances and covariances of genetic traits under strict genetic inheritance. Genetically expressed traits often influence trait expression in another via nongenetic forms of transmission and inheritance, however. The importance of non‐genetic influences on phenotypic evolution is increasingly clear, but how genetic and nongenetic inheritance interact to determine the response to selection is not well understood. Here, we use the ‘reachability matrix’ – a key analytical tool of geometric control theory – to integrate both forms of inheritance, capturing how the consequences of generation‐lagged maternal effects accumulate. Building on the classic Lande and Kirkpatrick model that showed how nongenetic (maternal) inheritance fundamentally alters the expected path of phenotypic evolution, we make novel inferences through decomposition of the reachability matrix. In particular, we quantify how nongenetic inheritance affects the distribution (orientation and shape) of ellipses of phenotypic change and how these distributions influence subsequent evolution. This interweaving of phenotypic means and variances accumulates generation by generation and is described analytically by the reachability matrix, which acts as an analogue of G when genetic and nongenetic inheritance both act.     

A unified approach to the evolutionary consequences of genetic and nongenetic inheritance

Inheritance-the influence of ancestors on the phenotypes of their descendants-translates natural selection into evolutionary change. For the past century, inheritance has been conceptualized almost exclusively as the transmission of DNA sequence variation from parents to offspring in accordance with Mendelian rules, but advances in cell and developmental biology have now revealed a rich array of inheritance mechanisms. This empirical evidence calls for a unified conception of inheritance that combines genetic and nongenetic mechanisms and encompasses the known range of transgenerational effects, including the transmission of genetic and epigenetic variation, the transmission of plastic phenotypes (acquired traits), and the effects of parental environment and genotype on offspring phenotype. We propose a unified theoretical framework based on the Price equation that can be used to model evolution under an expanded inheritance concept that combines the effects of genetic and nongenetic inheritance. To illustrate the utility and generality of this framework, we show how it can be applied to a variety of scenarios, including nontransmissible environmental noise, maternal effects, indirect genetic effects, transgenerational epigenetic inheritance, RNA-mediated inheritance, and cultural inheritance.     

Identification of candidate loci for adaptive phenotypic plasticity in natural populations of spadefoot toads

Phenotypic plasticity allows organisms to alter their phenotype in direct response to changes in the environment. Despite growing recognition of plasticity's role in ecology and evolution, few studies have probed plasticity's molecular bases—especially using natural populations. We investigated the genetic basis of phenotypic plasticity in natural populations of spadefoot toads (Spea multiplicata). Spea tadpoles normally develop into an “omnivore” morph that is favored in long‐lasting, low‐density ponds. However, if tadpoles consume freshwater shrimp or other tadpoles, they can alternatively develop (via plasticity) into a “carnivore” morph that is favored in ephemeral, high‐density ponds. By combining natural variation in pond ecology and morph production with population genetic approaches, we identified candidate loci associated with each morph (carnivores vs. omnivores) and loci associated with adaptive phenotypic plasticity (adaptive vs. maladaptive morph choice). Our candidate morph loci mapped to two genes, whereas our candidate plasticity loci mapped to 14 genes. In both cases, the identified genes tended to have functions related to their putative role in spadefoot tadpole biology. Our results thereby form the basis for future studies into the molecular mechanisms that mediate plasticity in spadefoots. More generally, these results illustrate how diverse loci might mediate adaptive plasticity.     

EVOLUTION OF PHENOTYPE–ENVIRONMENT ASSOCIATIONS BY GENETIC RESPONSES TO SELECTION AND PHENOTYPIC PLASTICITY IN A TEMPORALLY AUTOCORRELATED ENVIRONMENT

Covariation between population‐mean phenotypes and environmental variables, sometimes termed a “phenotype–environment association” (PEA), can result from phenotypic plasticity, genetic responses to natural selection, or both. PEAs can potentially provide information on the evolutionary dynamics of a particular set of populations, but this requires a full theoretical characterization of PEAs and their evolution. Here, we derive formulas for the expected PEA in a temporally fluctuating environment for a quantitative trait with a linear reaction norm. We compare several biologically relevant scenarios, including constant versus evolving plasticity, and the situation in which an environment affects both development and selection but at different time periods. We find that PEAs are determined not only by biological factors (e.g., magnitude of plasticity, genetic variation), but also environmental factors, such as the association between the environments of development and of selection, and in some cases the level of temporal autocorrelation. We also describe how a PEA can be used to estimate the relationship between an optimum phenotype and an environmental variable (i.e., the environmental sensitivity of selection), an important parameter for determining the extinction risk of populations experiencing environmental change. We illustrate this ability using published data on the predator‐induced morphological responses of tadpoles to predation risk.     

The relative importance of genetic and nongenetic inheritance in relation to trait plasticity in Callosobruchus maculatus

A trait's response to natural selection will reflect the nature of the inheritance mechanisms that mediate the transmission of variation across generations. The relative importance of genetic and nongenetic mechanisms of inheritance is predicted to be related to the degree of trait plasticity, with nongenetic inheritance playing a greater role in the cross‐generational transmission of more plastic traits. However, this prediction has never been tested. We investigated the influence of genetic effects and nongenetic parental effects in two morphological traits differing in degree of plasticity by manipulating larval diet quality within a cross‐generational split‐brood experiment using the seed beetle Callososbuchus maculatus. In line with predictions, we found that the more plastic trait (elytron length) is strongly influenced by both maternal and paternal effects whereas genetic variance is undetectable. In contrast, the less plastic trait (first abdominal sternite length) is not influenced by parental effects but exhibits abundant genetic variance. Our findings support the hypothesis that environment‐dependent parental effects may play a particularly important role in highly plastic traits and thereby affect the evolutionary response of such traits.     

SOLVING THE PARADOX OF STASIS: SQUASHED STABILIZING SELECTION AND THE LIMITS OF DETECTION

Despite the potential for rapid evolution, stasis is commonly observed over geological timescales—the so‐called “paradox of stasis.” This paradox would be resolved if stabilizing selection were common, but stabilizing selection is infrequently detected in natural populations. We hypothesize a simple solution to this apparent disconnect: stabilizing selection is hard to detect empirically once populations have adapted to a fitness peak. To test this hypothesis, we developed an individual‐based model of a population evolving under an invariant stabilizing fitness function. Stabilizing selection on the population was infrequently detected in an “empirical” sampling protocol, because (1) trait variation was low relative to the fitness peak breadth; (2) nonselective deaths masked selection; (3) populations wandered around the fitness peak; and (4) sample sizes were typically too small. Moreover, the addition of negative frequency‐dependent selection further hindered detection by flattening or even dimpling the fitness peak, a phenomenon we term “squashed stabilizing selection.” Our model demonstrates that stabilizing selection provides a plausible resolution to the paradox of stasis despite its infrequent detection in nature. The key reason is that selection “erases its traces”: once populations have adapted to a fitness peak, they are no longer expected to exhibit detectable stabilizing selection.     

THE EVOLUTION OF PHENOTYPIC CORRELATIONS AND “DEVELOPMENTAL MEMORY”

Development introduces structured correlations among traits that may constrain or bias the distribution of phenotypes produced. Moreover, when suitable heritable variation exists, natural selection may alter such constraints and correlations, affecting the phenotypic variation available to subsequent selection. However, exactly how the distribution of phenotypes produced by complex developmental systems can be shaped by past selective environments is poorly understood. Here we investigate the evolution of a network of recurrent nonlinear ontogenetic interactions, such as a gene regulation network, in various selective scenarios. We find that evolved networks of this type can exhibit several phenomena that are familiar in cognitive learning systems. These include formation of a distributed associative memory that can “store” and “recall” multiple phenotypes that have been selected in the past, recreate complete adult phenotypic patterns accurately from partial or corrupted embryonic phenotypes, and “generalize” (by exploiting evolved developmental modules) to produce new combinations of phenotypic features. We show that these surprising behaviors follow from an equivalence between the action of natural selection on phenotypic correlations and associative learning, well‐understood in the context of neural networks. This helps to explain how development facilitates the evolution of high‐fitness phenotypes and how this ability changes over evolutionary time.     

Applying Quantitative Genetic Methods to Primate Social Behavior

Increasingly, behavioral ecologists have applied quantitative genetic methods to investigate the evolution of behaviors in wild animal populations. The promise of quantitative genetics in unmanaged populations opens the door for simultaneous analysis of inheritance, phenotypic plasticity, and patterns of selection on behavioral phenotypes all within the same study. In this article, we describe how quantitative genetic techniques provide studies of the evolution of behavior with information that is unique and valuable. We outline technical obstacles for applying quantitative genetic techniques that are of particular relevance to studies of behavior in primates, especially those living in noncaptive populations, e.g., the need for pedigree information, non-Gaussian phenotypes, and demonstrate how many of these barriers are now surmountable. We illustrate this by applying recent quantitative genetic methods to spatial proximity data, a simple and widely collected primate social behavior, from adult rhesus macaques on Cayo Santiago. Our analysis shows that proximity measures are consistent across repeated measurements on individuals (repeatable) and that kin have similar mean measurements (heritable). Quantitative genetics may hold lessons of considerable importance for studies of primate behavior, even those without a specific genetic focus.     

Epigenetic population differentiation in field‐ and common garden‐grown Scabiosa columbaria plants

Populations often differ in phenotype and these differences can be caused by adaptation by natural selection, random neutral processes, and environmental responses. The most straightforward way to divide mechanisms that influence phenotypic variation is heritable variation and environmental‐induced variation (e.g., plasticity). While genetic variation is responsible for most heritable phenotypic variation, part of this is also caused by nongenetic inheritance. Epigenetic processes may be one of the underlying mechanisms of plasticity and nongenetic inheritance and can therefore possibly contribute to heritable differences through drift and selection. Epigenetic variation may be influenced directly by the environment, and part of this variation can be transmitted to next generations. Field screenings combined with common garden experiments will add valuable insights into epigenetic differentiation, epigenetic memory and can help to reveal part of the relative importance of epigenetics in explaining trait variation. We explored both genetic and epigenetic diversity, structure and differentiation in the field and a common garden for five British and five French Scabiosa columbaria populations. Genetic and epigenetic variation was subsequently correlated with trait variation. Populations showed significant epigenetic differentiation between populations and countries in the field, but also when grown in a common garden. By comparing the epigenetic variation between field and common garden‐grown plants, we showed that a considerable part of the epigenetic memory differed from the field‐grown plants and was presumably environmentally induced. The memory component can consist of heritable variation in methylation that is not sensitive to environments and possibly genetically based, or environmentally induced variation that is heritable, or a combination of both. Additionally, random epimutations might be responsible for some differences as well. By comparing epigenetic variation in both the field and common environment, our study provides useful insight into the environmental and genetic components of epigenetic variation.     

When to rely on maternal effects and when on phenotypic plasticity?

Existing insight suggests that maternal effects have a substantial impact on evolution, yet these predictions assume that maternal effects themselves are evolutionarily constant. Hence, it is poorly understood how natural selection shapes maternal effects in different ecological circumstances. To overcome this, the current study derives an evolutionary model of maternal effects in a quantitative genetics context. In constant environments, we show that maternal effects evolve to slight negative values that result in a reduction of the phenotypic variance (canalization). By contrast, in populations experiencing abrupt change, maternal effects transiently evolve to positive values for many generations, facilitating the transmission of beneficial maternal phenotypes to offspring. In periodically fluctuating environments, maternal effects evolve according to the autocorrelation between maternal and offspring environments, favoring positive maternal effects when change is slow, and negative maternal effects when change is rapid. Generally, the strongest maternal effects occur for traits that experience very strong selection and for which plasticity is severely constrained. By contrast, for traits experiencing weak selection, phenotypic plasticity enhances the evolutionary scope of maternal effects, although maternal effects attain much smaller values throughout. As weak selection is common, finding substantial maternal influences on offspring phenotypes may be more challenging than anticipated.     

How differing modes of non‐genetic inheritance affect population viability in fluctuating environments

Different modes of non‐genetic inheritance are expected to affect population persistence in fluctuating environments. We here analyse Caenorhabditis elegans density‐independent per capita growth rate time series on 36 populations experiencing six controlled sequences of challenging oxygen level fluctuations across 60 generations, and parameterise competing models of non‐genetic inheritance in order to explain observed dynamics. Our analysis shows that phenotypic plasticity and anticipatory maternal effects are sufficient to explain growth rate dynamics, but that a carryover model where ‘epigenetic’ memory is imperfectly transmitted and might be reset at each generation is a better fit to the data. We further find that this epigenetic memory is asymmetric since it is kept for longer when populations are exposed to the more challenging environment. Our analysis suggests that population persistence in fluctuating environments depends on the non‐genetic inheritance of phenotypes whose expression is regulated across multiple generations.     

Drift versus selection as drivers of phenotypic divergence at small spatial scales: The case of Belgjarskógur threespine stickleback

Divergence in phenotypic traits is facilitated by a combination of natural selection, phenotypic plasticity, gene flow, and genetic drift, whereby the role of drift is expected to be particularly important in small and isolated populations. Separating the components of phenotypic divergence is notoriously difficult, particularly for multivariate phenotypes. Here, we assessed phenotypic divergence of threespine stickleback (Gasterosteus aculeatus) across 19 semi‐interconnected ponds within a small geographic region (~7.5 km²) using comparisons of multivariate phenotypic divergence (PST), neutral genetic (FST), and environmental (EST) variation. We found phenotypic divergence across the ponds in a suite of functionally relevant phenotypic traits, including feeding, defense, and swimming traits, and body shape (geometric morphometric). Comparisons of PSTs with FSTs suggest that phenotypic divergence is predominantly driven by neutral processes or stabilizing selection, whereas phenotypic divergence in defensive traits is in accordance with divergent selection. Comparisons of population pairwise PSTs with ESTs suggest that phenotypic divergence in swimming traits is correlated with prey availability, whereas there were no clear associations between phenotypic divergence and environmental difference in the other phenotypic groups. Overall, our results suggest that phenotypic divergence of these small populations at small geographic scales is largely driven by neutral processes (gene flow, drift), although environmental determinants (natural selection or phenotypic plasticity) may play a role.     

QUANTITATIVE GENETICS OF BRYOZOAN PHENOTYPIC EVOLUTION. III. PHENOTYPIC PLASTICITY AND THE MAINTENANCE OF GENETIC VARIATION

Cheilostome bryozoan species show long-term morphologic stasis, implying stabilizing selection sustained for millions of years, but nevertheless retain significant heritable variation in traits of skeletal morphology. The possible role of within-genotype (within-colony) phenotypic variability in preserving genetic diversity was analyzed using breeding data for two species of Stylopoma from sites along 110 km of the Caribbean coast of Panama. Variation among zooids within colonies accounts for nearly two-thirds of the phenotypic variance on average, increases with environmental heterogeneity, and includes significant genotype-environment interaction. Thus, within-colony variability apparently represents phenotypic plasticity, at least some of which is heritable, rather than random “developmental noise.” Almost all of the among-colonies component of phenotypic variance is accounted for by additive genetic differences in trait means, suggesting that within-colony plasticity includes virtually all of the environmental component of phenotypic variance in these populations of Stylopoma. Thus, heritable within-colony plasticity could play a significant part in maintaining genetic diversity in cheilostomes, but it is also possible that rates of polygenic mutation alone are sufficient to balance the effects of selection.     

Plasticity,memory and the adaptive landscape of the genotype

The adaptive value of epigenetic inheritance systems is investigated in a simple mathematical framework. These systems enable the environmentally induced phenotypes to be transmitted between generations. The frequencies of the different epigenetic variants are determined by the plasticity and the efficiency of transmission (called memory). Plasticity and memory are genetically determined. This paper studies the evolution of a quantitative character, its plasticity and memory, on the adaptive landscape. Due to the dual inheritance of the character, selection acts on two levels: on the phenotypes of the same genotype, and on the different genotypes. Plasticity generates the raw material, and memory increases the strength of phenotypic selection. If the character is far from the peak of the landscape, then dual inheritance of the character can be advantageous for the genotype. Near the peak it is more favourable to suppress phenotypic variation. This would lead to genetic assimilation.     

Epigenetic inheritance and plasticity: The responsive germline

Developmental plasticity, the capacity of a single genotype to give rise to different phenotypes, affects evolutionary dynamics by influencing the rate and direction of phenotypic change. It is based on regulatory changes in gene expression and gene products, which are partially controlled by epigenetic mechanisms. Plasticity involves not just epigenetic changes in somatic cells and tissues; it can also involve changes in germline cells. Germline epigenetic plasticity increases evolvability, the capacity to generate heritable, selectable, phenotypic variations, including variations that lead to novel functions. I discuss studies that show that some complex adaptive responses to new challenges are mediated by germline epigenetic processes, which can be transmitted over variable number of generations, and argue that the heritable variations that are generated epigenetically have an impact on both small-scale and large-scale aspects of evolution. First, I review some recent ecological studies and models that show that germline (gametic) epigenetic inheritance can lead to cumulative micro-evolutionary changes that are rapid and semi-directional. I suggest that “priming” and “epigenetic learning” may be of special importance in generating heritable, fine-tuned adaptive responses in populations. Second, I consider work showing how genomic and environmental stresses can also lead to epigenome repatterning, and produce changes that are saltational.     

Genetic evolution,plasticity, and bet‐hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model

Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet‐hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations.     

GENERALISTS,SPECIALISTS, AND THE EVOLUTION OF PHENOTYPIC PLASTICITY IN SYMPATRIC POPULATIONS OF DISTINCT SPECIES

The evolution of phenotypic plasticity is studied in a model with two reproductively isolated “species” in a coarse-grained environment, consisting of two types of habitats. A quantitative genetic model for selection was constructed, in which habitats differ in the optimal value for a focal trait, and with random dispersal among habitats. The main interest was to study the effects of different selection regimes. Three cases were investigated: (1) without any limits to plasticity; (2) without genetic variation for plasticity; and (3) with a fitness cost for phenotypically plastic reactions. In almost all cases a generalist strategy to exploit both habitats emerged. Without any limits to plasticity, optimal adaptive reactions evolved. Without any genetic variation for plasticity, a compromise strategy with an intermediate, fixed phenotype evolved, whereas in the presence of costs a plastic compromise between the demands of the habitats and the costs associated with plasticity was found. Specialization and phenotypic differentiation was only found when selection within habitats was severe and optimal phenotypes for different habitats were widely different. Under soft selection (local regulation of population numbers in each habitat) the specialists coexisted; under hard selection (global regulation of population numbers) one specialist outcompeted the other. The prevalent evolutionary outcome of compromises rather than specialization implies that costs or constraints are not necessarily detectable as local adaptation in transplantation or translocation experiments.     

Roles of maternal effects in maintaining genetic variation: Maternal storage effect

Understanding the maintenance of genetic variation remains a central challenge in evolutionary biology. Recent empirical studies suggest the importance of temporally varying selection, as allele frequencies have been found to fluctuate substantially in the wild. However, previous theory suggests that the conditions for the maintenance of genetic variation under temporally fluctuating selection are quite restrictive. Using mathematical models, we demonstrate that maternal genetic effects, whereby maternal genotypes affect offspring phenotypes, can facilitate the maintenance of polymorphism in temporally varying environments. Maternal effects result in mismatches between genotypes and phenotypes, thereby buffering the influence of selection on allele frequency. This decreases the magnitude of allele‐frequency fluctuations and creates conditions for the maintenance of variation when selection causes fluctuations. Therefore, maternal effects may result in a temporal storage effect (“maternal storage effect”). On the other hand, when selection does not cause fluctuations (e.g., linear negative frequency‐dependent selection), maternal genetic effects moderate the relative importance of selection compared to genetic drift and promote stochastic allele extinction in finite populations. Thus, maternal effects can play an important role in the maintenance of polymorphism, but the direction of the effect depends on the nature of selection.