On indirect genetic effects in structured populations

Indirect genetic effects (IGEs) occur when the phenotype of an individual, and possibly its fitness, depends, at least in part, on the genes of its social partners. The effective result is that environmental sources of phenotypic variance can themselves evolve. Simple models have shown that IGEs can alter the rate and direction of evolution for traits involved in interactions. Here we expand the applicability of the theory of IGEs to evolution in metapopulations by including nonlinear interactions between individuals and population genetic structure. Although population subdivision alone generates some dramatic and nonintuitive evolutionary dynamics for interacting phenotypes, the combination of nonlinear interactions with subdivision reveals an even greater importance of IGEs. The presence of genetic structure links the evolution of interacting phenotypes and the traits that influence their expression ("effector traits") even in the absence of genetic correlations. When nonlinear social effects occur in subdivided populations, evolutionary response is altered and can even oppose the direction expected due to direct selection. Because population genetic structure allows for multilevel selection, we also investigate the role of IGEs in determining the response to individual and group selection. We find that nonlinear social effects can cause interference between levels of selection even when they act in the same direction. In some cases, interference can be so extreme that the actual evolutionary response to multilevel selection is opposite in direction to that predicted by summing selection at each level. This theoretical result confirms empirical data that show higher levels of selection cannot be ignored even when selection acts in the same direction at all levels.     

INTERACTING PHENOTYPES AND THE EVOLUTIONARY PROCESS. III. SOCIAL EVOLUTION

Interactions among conspecifics influence social evolution through two distinct but intimately related paths. First, they provide the opportunity for indirect genetic effects (IGEs), where genes expressed in one individual influence the expression of traits in others. Second, interactions can generate social selection when traits expressed in one individual influence the fitness of others. Here, we present a quantitative genetic model of multivariate trait evolution that integrates the effects of both IGEs and social selection, which have previously been modeled independently. We show that social selection affects evolutionary change whenever the breeding value of one individual covaries with the phenotype of its social partners. This covariance can be created by both relatedness and IGEs, which are shown to have parallel roles in determining evolutionary response. We show that social selection is central to the estimation of inclusive fitness and derive a version of Hamilton's rule showing the symmetrical effects of relatedness and IGEs on the evolution of altruism. We illustrate the utility of our approach using altruism, greenbeards, aggression, and weapons as examples. Our model provides a general predictive equation for the evolution of social phenotypes that encompasses specific cases such as kin selection and reciprocity. The parameters can be measured empirically, and we emphasize the importance of considering both IGEs and social selection, in addition to relatedness, when testing hypotheses about social evolution.     

Indirect Genetic Effects and the Dynamics of Social Interactions

BackgroundIndirect genetic effects (IGEs) occur when genes expressed in one individual alter the expression of traits in social partners. Previous studies focused on the evolutionary consequences and evolutionary dynamics of IGEs, using equilibrium solutions to predict phenotypes in subsequent generations. However, whether or not such steady states may be reached may depend on the dynamics of interactions themselves.ResultsIn our study, we focus on the dynamics of social interactions and indirect genetic effects and investigate how they modify phenotypes over time. Unlike previous IGE studies, we do not analyse evolutionary dynamics; rather we consider within-individual phenotypic changes, also referred to as phenotypic plasticity. We analyse iterative interactions, when individuals interact in a series of discontinuous events, and investigate the stability of steady state solutions and the dependence on model parameters, such as population size, strength, and the nature of interactions. We show that for interactions where a feedback loop occurs, the possible parameter space of interaction strength is fairly limited, affecting the evolutionary consequences of IGEs. We discuss the implications of our results for current IGE model predictions and their limitations.     

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.     

Indirect genetic effects and the evolution of aggression in a vertebrate system

Aggressive behaviours are necessarily expressed in a social context, such that individuals may be influenced by the phenotypes, and potentially the genotypes, of their social partners. Consequently, it has been hypothesized that indirect genetic effects (IGEs) arising from the social environment will provide a major source of heritable variation on which selection can act. However, there has been little empirical scrutiny of this to date. Here we test this hypothesis in an experimental population of deer mice (Peromyscus maniculatus). Using quantitative genetic models of five aggression traits, we find repeatable and heritable differences in agonistic behaviours of focal individuals when presented with an opponent mouse. For three of the traits, there is also support for the presence of IGEs, and estimated correlations between direct and indirect genetic (rAO,F) effects were high. As a consequence, any selection for aggression in the focal individuals should cause evolution of the social environment as a correlated response. In two traits, strong positive rAO,F will cause the rapid evolution of aggression, while in a third case changes in the phenotypic mean will be constrained by negative covariance between direct and IGEs. Our results illustrate how classical analyses may miss important components of heritable variation, and show that a full understanding of evolutionary dynamics requires explicit consideration of the genetic component of the social environment.     

Social competition as a driver of phenotype–environment correlations: implications for ecology and evolution

While it is universally recognised that environmental factors can cause phenotypic trait variation via phenotypic plasticity, the extent to which causal processes operate in the reverse direction has received less consideration. In fact individuals are often active agents in determining the environments, and hence the selective regimes, they experience. There are several important mechanisms by which this can occur, including habitat selection and niche construction, that are expected to result in phenotype–environment correlations (i.e. non-random assortment of phenotypes across heterogeneous environments). Here we highlight an additional mechanism – intraspecific competition for preferred environments – that may be widespread, and has implications for phenotypic evolution that are currently underappreciated. Under this mechanism, variation among individuals in traits determining their competitive ability leads to phenotype–environment correlation; more competitive phenotypes are able to acquire better patches. Based on a concise review of the empirical evidence we argue that competition-induced phenotype–environment correlations are likely to be common in natural populations before highlighting the major implications of this for studies of natural selection and microevolution. We focus particularly on two central issues. First, competition-induced phenotype–environment correlation leads to the expectation that positive feedback loops will amplify phenotypic and fitness variation among competing individuals. As a result of being able to acquire a better environment, winners gain more resources and even better phenotypes – at the expense of losers. The distinction between individual quality and environmental quality that is commonly made by researchers in evolutionary ecology thus becomes untenable. Second, if differences among individuals in competitive ability are underpinned by heritable traits, competition results in both genotype–environment correlations and an expectation of indirect genetic effects (IGEs) on resource-dependent life-history traits. Theory tells us that these IGEs will act as (partial) constraints, reducing the amount of genetic variance available to facilitate evolutionary adaptation. Failure to recognise this will lead to systematic overestimation of the adaptive potential of populations. To understand the importance of these issues for ecological and evolutionary processes in natural populations we therefore need to identify and quantify competition-induced phenotype–environment correlations in our study systems. We conclude that both fundamental and applied research will benefit from an improved understanding of when and how social competition causes non-random distribution of phenotypes, and genotypes, across heterogeneous environments.     

HOW TO MEASURE INDIRECT GENETIC EFFECTS: THE CONGRUENCE OF TRAIT-BASED AND VARIANCE-PARTITIONING APPROACHES

Indirect genetic effects (IGEs), which occur when phenotypic expression in one individual is influenced by genes in another conspecific individual, may have a drastic effect on evolutionary response to selection. General evolutionary models of IGEs have been developed using two distinct theoretical frameworks derived from maternal effects theory. The first framework is trait-based and focuses on how phenotypes are influenced by specific traits in a social partner, with the strength of interactions defined by the matrix Ψ. The second framework partitions total genetic variance into components representing direct effects, indirect effects, and the covariance between them, without identifying specific social traits responsible for IGEs. The latter framework has been employed more commonly by empiricists because the methods for estimating variance components are relatively straightforward. Here, we show how these two theoretical frameworks are related to each other and derive equations that can be used to translate between them. This translation leads to a generalized method that can be used to estimate Ψ via standard quantitative genetic breeding designs or pedigrees from natural populations. This method can be used in a very general set of circumstances and is widely applicable to all IGEs, including maternal effects and other interactions among relatives.     

Genetic Color Morphs in the Eastern Mosquitofish Experience Different Social Environments in the Wild and Laboratory

The social environment of an animal is an especially interesting component of its environment because it can be shaped by both genetic and non‐genetic variation among social partners. Indirect genetic effects (IGEs) are those created when genetic variation in social partners contributes to variation in an individual's phenotype; a potentially common form of IGE occurs when the expression of a behavioral phenotype depends on the particular genotypic combination of interacting individuals. Although IGEs can profoundly affect individual‐ and group‐level fitness, population dynamics, and even community structure, understanding their importance is complicated by two inherent challenges: (1) identifying individuals with genetic differences in social interactions that can contribute to IGEs and (2) characterizing natural social interactions that potentially involve IGEs. As a first step toward addressing both these challenges in the same system, we investigated social interactions involving genetically distinct male color morphs in the poeciliid fish Gambusia holbrooki under natural and laboratory conditions. Previous work indicates that melanic (M) and silver (S) males differ in social behavior and in how conspecifics respond to them, suggesting the potential for IGEs. We used a combination of live and video recording of social groups in two natural populations and in the laboratory to determine the potential for IGEs to contribute to behavioral variation in this species. We found that M males had more social partners, and especially more female social partners than did S males, in nature and in the laboratory. These results suggest that both direct and indirect genetic effects have the potential to play a role in the expression and evolution of social behavior in G. holbrooki.     

Phenotypic assortment mediates the effect of social selection in a wild beetle population

Social interactions often have major fitness consequences, but little is known about how specific interacting phenotypes affect the strength of natural selection. Social influences on the evolutionary process can be assessed using a multilevel selection approach that partitions the effects of social partner phenotypes on fitness (referred to as social or group selection) from those of the traits of a focal individual (nonsocial or individual selection). To quantify the contribution of social selection to total selection affecting a trait, the patterns of phenotypic association among interactants must also be considered. We estimated selection gradients on male body size in a wild population of forked fungus beetles (Bolitotherus cornutus). We detected positive nonsocial selection and negative social selection on body size operating through differences in copulation success, indicating that large males with small social partners had highest fitness. In addition, we found that, in low-density demes, the phenotypes of focal individuals were negatively correlated with those of their social partners. This pattern reversed the negative effect of group selection on body size and led to stronger positive selection for body size. Our results demonstrate multilevel selection in nature and stress the importance of considering social selection whenever conspecific interactions occur nonrandomly.     

Indirect genetic effects and kin recognition: estimating IGEs when interactions differ between kin and strangers

Social interactions among individuals are widespread, both in natural and domestic populations. As a result, trait values of individuals may be affected by genes in other individuals, a phenomenon known as indirect genetic effects (IGEs). IGEs can be estimated using linear mixed models. The traditional IGE model assumes that an individual interacts equally with all its partners, whether kin or strangers. There is abundant evidence, however, that individuals behave differently towards kin as compared with strangers, which agrees with predictions from kin-selection theory. With a mix of kin and strangers, therefore, IGEs estimated from a traditional model may be incorrect, and selection based on those estimates will be suboptimal. Here we investigate whether genetic parameters for IGEs are statistically identifiable in group-structured populations when IGEs differ between kin and strangers, and develop models to estimate such parameters. First, we extend the definition of total breeding value and total heritable variance to cases where IGEs depend on relatedness. Next, we show that the full set of genetic parameters is not identifiable when IGEs differ between kin and strangers. Subsequently, we present a reduced model that yields estimates of the total heritable effects on kin, on non-kin and on all social partners of an individual, as well as the total heritable variance for response to selection. Finally we discuss the consequences of analysing data in which IGEs depend on relatedness using a traditional IGE model, and investigate group structures that may allow estimation of the full set of genetic parameters when IGEs depend on kin.     

The joint effects of kin, multilevel selection and indirect genetic effects on response to genetic selection

Kin and levels-of-selection models are common approaches for modelling social evolution. Indirect genetic effect (IGE) models represent a different approach, specifying social effects on trait values rather than fitness. We investigate the joint effect of relatedness, multilevel selection and IGEs on response to selection. We present a measure for the degree of multilevel selection, which is the natural partner of relatedness in expressions for response. Response depends on both relatedness and the degree of multilevel selection, rather than only one or the other factor. Moreover, response is symmetric in relatedness and the degree of multilevel selection, indicating that both factors have exactly the same effect. Without IGEs, the key parameter is the product of relatedness and the degree of multilevel selection. With IGEs, however, multilevel selection without relatedness can explain evolution of social traits. Thus, next to relatedness and multilevel selection, IGEs are a key element in the genetical theory of social evolution.     

EXPERIMENTAL EVIDENCE FOR THE EVOLUTION OF INDIRECT GENETIC EFFECTS: CHANGES IN THE INTERACTION EFFECT COEFFICIENT,PSI (Ψ), DUE TO SEXUAL SELECTION

Indirect genetics effects (IGEs)—when the genotype of one individual affects the phenotypic expression of a trait in another—may alter evolutionary trajectories beyond that predicted by standard quantitative genetic theory as a consequence of genotypic evolution of the social environment. For IGEs to occur, the trait of interest must respond to one or more indicator traits in interacting conspecifics. In quantitative genetic models of IGEs, these responses (reaction norms) are termed interaction effect coefficients and are represented by the parameter psi (Ψ). The extent to which Ψ exhibits genetic variation within a population, and may therefore itself evolve, is unknown. Using an experimental evolution approach, we provide evidence for a genetic basis to the phenotypic response caused by IGEs on sexual display traits in Drosophila serrata. We show that evolution of the response is affected by sexual but not natural selection when flies adapt to a novel environment. Our results indicate a further mechanism by which IGEs can alter evolutionary trajectories—the evolution of interaction effects themselves.     

Social runaway: Fisherian elaboration (or reduction) of socially selected traits via indirect genetic effects

Our understanding of the evolutionary stability of socially selected traits is dominated by sexual selection models originating with R. A. Fisher, in which genetic covariance arising through assortative mating can trigger exponential, runaway trait evolution. To examine whether nonreproductive, socially selected traits experience similar dynamics—social runaway—when assortative mating does not automatically generate a covariance, we modeled the evolution of socially selected badge and donation phenotypes incorporating indirect genetic effects (IGEs) arising from the social environment. We establish a social runaway criterion based on the interaction coefficient, ψ , which describes social effects on badge and donation traits. Our models make several predictions. (1) IGEs can drive the original evolution of altruistic interactions that depend on receiver badges. (2) Donation traits are more likely to be susceptible to IGEs than badge traits. (3) Runaway dynamics in nonsexual, social contexts can occur in the absence of a genetic covariance. (4) Traits elaborated by social runaway are more likely to involve reciprocal, but nonsymmetrical, social plasticity. Models incorporating plasticity to the social environment via IGEs illustrate conditions favoring social runaway, describe a mechanism underlying the origins of costly traits, such as altruism, and support a fundamental role for phenotypic plasticity in rapid social evolution.     

Quantitative genetic versions of Hamilton's rule with empirical applications

Hamilton''s theory of inclusive fitness revolutionized our understanding of the evolution of social interactions. Surprisingly, an incorporation of Hamilton''s perspective into the quantitative genetic theory of phenotypic evolution has been slow, despite the popularity of quantitative genetics in evolutionary studies. Here, we discuss several versions of Hamilton''s rule for social evolution from a quantitative genetic perspective, emphasizing its utility in empirical applications. Although evolutionary quantitative genetics offers methods to measure each of the critical parameters of Hamilton''s rule, empirical work has lagged behind theory. In particular, we lack studies of selection on altruistic traits in the wild. Fitness costs and benefits of altruism can be estimated using a simple extension of phenotypic selection analysis that incorporates the traits of social interactants. We also discuss the importance of considering the genetic influence of the social environment, or indirect genetic effects (IGEs), in the context of Hamilton''s rule. Research in social evolution has generated an extensive body of empirical work focusing—with good reason—almost solely on relatedness. We argue that quantifying the roles of social and non-social components of selection and IGEs, in addition to relatedness, is now timely and should provide unique additional insights into social evolution.     

Complex genotype interactions influence social fitness during the developmental phase of the social amoeba Dictyostelium discoideum

When individuals interact, phenotypic variation can be partitioned into direct genetic effects (DGEs) of the individuals’ own genotypes, indirect genetic effects (IGEs) of their social partners’ genotypes and epistatic interactions between the genotypes of interacting individuals (‘genotype‐by‐genotype (G×G) epistasis’). These components can all play important roles in evolutionary processes, but few empirical studies have examined their importance. The social amoeba Dictyostelium discoideum provides an ideal system to measure these effects during social interactions and development. When starved, free‐living amoebae aggregate and differentiate into a multicellular fruiting body with a dead stalk that holds aloft viable spores. By measuring interactions among a set of natural strains, we quantify DGEs, IGEs and G×G epistasis affecting spore formation. We find that DGEs explain most of the phenotypic variance (57.6%) whereas IGEs explain a smaller (13.3%) but highly significant component. Interestingly, G×G epistasis explains nearly a quarter of the variance (23.0%), highlighting the complex nature of genotype interactions. These results demonstrate the large impact that social interactions can have on development and suggest that social effects should play an important role in developmental evolution in this system.     

The role of indirect genetic effects in the evolution of interacting reproductive behaviors in the burying beetle,Nicrophorus vespilloides

Social interactions can give rise to indirect genetic effects (IGEs), which occur when genes expressed in one individual affect the phenotype of another individual. The evolutionary dynamics of traits can be altered when there are IGEs. Sex often involves indirect effects arising from first‐order (current) or second‐order (prior) social interactions, yet IGEs are infrequently quantified for reproductive behaviors. Here, we use experimental populations of burying beetles that have experienced bidirectional selection on mating rate to test for social plasticity and IGEs associated with focal males mating with a female either without (first‐order effect) or with (second‐order effect) prior exposure to a competitor, and resource defense behavior (first‐order effect). Additive IGEs were detected for mating rate arising from (first‐order) interactions with females. For resource defense behavior, a standard variance partitioning analysis provided no evidence of additive genetic variance—either direct or indirect. However, behavior was predicted by focal size relative to that of the competitor, and size is also heritable. Assuming that behavior is causally dependent on relative size, this implies that both DGEs and IGEs do occur (and may potentially interact). The relative contribution of IGEs may differ among social behaviors related to mating which has consequences for the evolutionary trajectories of multivariate traits.     

Social effects for locomotion vary between environments in Drosophila melanogaster females

Despite strong purifying or directional selection, variation is ubiquitous in populations. One mechanism for the maintenance of variation is indirect genetic effects (IGEs), as the fitness of a given genotype will depend somewhat on the genes of its social partners. IGEs describe the effect of genes in social partners on the expression of the phenotype of a focal individual. Here, we ask what effect IGEs, and variation in IGEs between abiotic environments, has on locomotion in Drosophila. This trait is known to be subject to intralocus sexually antagonistic selection. We estimate the coefficient of interaction, Ψ, using six inbred lines of Drosophila. We found that Ψ varied between abiotic environments, and that it may vary across among male genotypes in an abiotic environment specific manner. We also found evidence that social effects of males alter the value of a sexually dimorphic trait in females, highlighting an interesting avenue for future research into sexual antagonism. We conclude that IGEs are an important component of social and sexual interactions and that they vary between individuals and abiotic environments in complex ways, with the potential to promote the maintenance of phenotypic variation.     

Sexual selection and interacting phenotypes in experimental evolution: a study of Drosophila pseudoobscura mating behavior

Sexual selection requires social interactions, particularly between the sexes. When trait expression is influenced by social interactions, such traits are called interacting phenotypes and only recently have the evolutionary consequences of interacting phenotypes been considered. Here we investigated how variation in relative fitness, or the opportunity for sexual selection, affected the evolutionary trajectories of interacting phenotypes. We used experimentally evolved populations of the naturally promiscuous Drosophila pseudoobscura , in which the numbers of potential interactions between the sexes, and therefore relative fitness, were manipulated by altering natural levels of female promiscuity. We considered two different mating interactions between the sexes: mating speed and copulation duration. We investigated the evolutionary trajectories of means and (co)variances ( P ) and also the influence of genetic drift on the evolutionary response of these interactions. Our sexual selection treatments did not affect the means of either mating speed or copulation duration, but they did affect P . We found that the means of both traits differed among replicates within each selection treatment whereas the P s did not. Changes as a consequence of genetic drift were excluded. Our results show that although variable potential strengths of sexual interactions influence the evolution of interacting phenotypes, the influence may be nonlinear.     

Community heritability measures the evolutionary consequences of indirect genetic effects on community structure

The evolutionary analysis of community organization is considered a major frontier in biology. Nevertheless, current explanations for community structure exclude the effects of genes and selection at levels above the individual. Here, we demonstrate a genetic basis for community structure, arising from the fitness consequences of genetic interactions among species (i.e., interspecific indirect genetic effects or IIGEs). Using simulated and natural communities of arthropods inhabiting North American cottonwoods (Populus), we show that when species comprising ecological communities are summarized using a multivariate statistical method, nonmetric multidimensional scaling (NMDS), the resulting univariate scores can be analyzed using standard techniques for estimating the heritability of quantitative traits. Our estimates of the broad-sense heritability of arthropod communities on known genotypes of cottonwood trees in common gardens explained 56-63% of the total variation in community phenotype. To justify and help interpret our empirical approach, we modeled synthetic communities in which the number, intensity, and fitness consequences of the genetic interactions among species comprising the community were explicitly known. Results from the model suggest that our empirical estimates of broad-sense community heritability arise from heritable variation in a host tree trait and the fitness consequences of IGEs that extend from tree trait to arthropods. When arthropod traits are heritable, interspecific IGEs cause species interactions to change, and community evolution occurs. Our results have implications for establishing the genetic foundations of communities and ecosystems.