A Synthesis of Game Theory and Quantitative Genetic Models of Social Evolution.

Two popular approaches for modeling social evolution, evolutionary game theory and quantitative genetics, ask complementary questions but are rarely integrated. Game theory focuses on evolutionary outcomes, with models solving for evolutionarily stable equilibria, whereas quantitative genetics provides insight into evolutionary processes, with models predicting short-term responses to selection. Here we draw parallels between evolutionary game theory and interacting phenotypes theory, which is a quantitative genetic framework for understanding social evolution. First, we show how any evolutionary game may be translated into two quantitative genetic selection gradients, nonsocial and social selection, which may be used to predict evolutionary change from a single round of the game. We show that synergistic fitness effects may alter predicted selection gradients, causing changes in magnitude and sign as the population mean evolves. Second, we show how evolutionary games involving plastic behavioral responses to partners can be modeled using indirect genetic effects, which describe how trait expression changes in response to genes in the social environment. We demonstrate that repeated social interactions in models of reciprocity generate indirect effects and conversely, that estimates of parameters from indirect genetic effect models may be used to predict the evolution of reciprocity. We argue that a pluralistic view incorporating both theoretical approaches will benefit empiricists and theorists studying social evolution. We advocate the measurement of social selection and indirect genetic effects in natural populations to test the predictions from game theory and, in turn, the use of game theory models to aid in the interpretation of quantitative genetic estimates.

Evolutionary bedfellows: Reconstructing the ancestral state of autotomy and regeneration.

Some form of regeneration occurs in all lifeforms and extends from single-cell organisms to humans. The degree to which regenerative ability is distributed across different taxa, however, is harder to ascertain given the potential for phylogenetic constraint or inertia, and adaptive processes to shape this pattern. Here, we examine the phylogenetic history of regeneration in two groups where the trait has been well-studied: arthropods and reptiles. Because autotomy is often present alongside regeneration in these groups, we performed ancestral state reconstructions for both traits to more precisely assess the timing of their origins and the degree to which these traits coevolve. Using an ancestral trait reconstruction, we find that autotomy and regeneration were present at the base of the arthropod and reptile trees. We also find that when autotomy is lost it does not re-evolve easily. Lastly, we find that the distribution of regeneration is intimately connected to autotomy with the association being stronger in reptiles than in arthropods. Although these patterns suggest that decoupling autotomy and regeneration at a broad phylogenetic scale may be difficult, the available data provides useful insight into their entanglement. Ultimately, our reconstructions provide the important groundwork to explore how selection may have played a role during the loss of regeneration in specific lineages.

Some topics in theoretical population genetics: Editorial commentaries on a selection of Marc Feldman's TPB papers.

This article consists of commentaries on a selected group of papers of Marc Feldman published in Theoretical Population Biology from 1970 to the present. The papers describe a diverse set of population-genetic models, covering topics such as cultural evolution, social evolution, and the evolution of recombination. The commentaries highlight Marc Feldman's role in providing mathematically rigorous formulations to explore qualitative hypotheses, in many cases generating surprising conclusions.

The evolving landscape of imprinted genes in humans and mice: Conflict among alleles, genes, tissues, and kin.

Three recent genome-wide studies in mice and humans have produced the most definitive map to date of genomic imprinting (gene expression that depends on parental origin) by incorporating multiple tissue types and developmental stages. Here, we explore the results of these studies in light of the kinship theory of genomic imprinting, which predicts that imprinting evolves due to differential genetic relatedness between maternal and paternal relatives. The studies produce a list of imprinted genes with around 120-180 in mice and ~100 in humans. The studies agree on broad patterns across mice and humans including the complex patterns of imprinted expression at loci like Igf2 and Grb10. We discuss how the kinship theory provides a powerful framework for hypotheses that can explain these patterns. Finally, since imprinting is rare in the genome despite predictions from the kinship theory that it might be common, we discuss evolutionary factors that could favor biallelic expression.

Not just a theory--the utility of mathematical models in evolutionary biology.

Progress in science often begins with verbal hypotheses meant to explain why certain biological phenomena exist. An important purpose of mathematical models in evolutionary research, as in many other fields, is to act as "proof-of-concept" tests of the logic in verbal explanations, paralleling the way in which empirical data are used to test hypotheses. Because not all subfields of biology use mathematics for this purpose, misunderstandings of the function of proof-of-concept modeling are common. In the hope of facilitating communication, we discuss the role of proof-of-concept modeling in evolutionary biology.

Cooperation, conformity, and the coevolutionary problem of trait associations.

In large scale social systems, coordinated or cooperative outcomes become difficult because encounters between kin or repeated encounters between friends are infrequent. Even punishment of noncooperators does not entirely alleviate the dilemma. One important mechanism for achieving cooperative outcomes in such social systems is conformist bias where individuals copy the behavior performed by the majority of their group mates. Conformist bias enhances group competition by both stabilizing behaviors within groups and increasing variance between groups. Due to this group competition effect, conformist bias is thought to have been an important driver of human social complexity and cultural diversity. However, conformist bias only evolves indirectly through associations with other traits, and I show that such associations are more difficult to obtain than previously expected. Specifically, I show that initial measures of population structure must be strong in order for a strong association between conformist bias and cooperative behaviors (cooperation and costly punishment) to evolve and for these traits to reach high frequencies. Additionally, the required initial level of association does not evolve de novo in simulations run over long timescales. This suggests that the coevolution of cooperative behaviors and conformist bias alone may not explain the high levels of cooperation within human groups, though conformist bias may still play an important role in combination with other social and demographic forces.

Social evolution and genetic interactions in the short and long term.

The evolution of social traits remains one of the most fascinating and feisty topics in evolutionary biology even after half a century of theoretical research. W.D. Hamilton shaped much of the field initially with his 1964 papers that laid out the foundation for understanding the effect of genetic relatedness on the evolution of social behavior. Early theoretical investigations revealed two critical assumptions required for Hamilton's rule to hold in dynamical models: weak selection and additive genetic interactions. However, only recently have analytical approaches from population genetics and evolutionary game theory developed sufficiently so that social evolution can be studied under the joint action of selection, mutation, and genetic drift. We review how these approaches suggest two timescales for evolution under weak mutation: (i) a short-term timescale where evolution occurs between a finite set of alleles, and (ii) a long-term timescale where a continuum of alleles are possible and populations evolve continuously from one monomorphic trait to another. We show how Hamilton's rule emerges from the short-term analysis under additivity and how non-additive genetic interactions can be accounted for more generally. This short-term approach reproduces, synthesizes, and generalizes many previous results including the one-third law from evolutionary game theory and risk dominance from economic game theory. Using the long-term approach, we illustrate how trait evolution can be described with a diffusion equation that is a stochastic analogue of the canonical equation of adaptive dynamics. Peaks in the stationary distribution of the diffusion capture classic notions of convergence stability from evolutionary game theory and generally depend on the additive genetic interactions inherent in Hamilton's rule. Surprisingly, the peaks of the long-term stationary distribution can predict the effects of simple kinds of non-additive interactions. Additionally, the peaks capture both weak and strong effects of social payoffs in a manner difficult to replicate with the short-term approach. Together, the results from the short and long-term approaches suggest both how Hamilton's insight may be robust in unexpected ways and how current analytical approaches can expand our understanding of social evolution far beyond Hamilton's original work.

Demography, kinship, and the evolving theory of genomic imprinting.

Genomic imprinting is the differential expression of an allele based on the parent of origin. Recent transcriptome-wide evaluations of the number of imprinted genes reveal complex patterns of imprinted expression among developmental stages and cell types. Such data demand a comprehensive evolutionary framework in which to understand the effect of natural selection on imprinted gene expression. We present such a framework for how asymmetries in demographic parameters and fitness effects can lead to the evolution of genomic imprinting and place recent theoretical advances in this framework. This represents a modern interpretation of the kinship theory, is well suited to studying populations with complex social interactions, and provides predictions which can be tested with forthcoming transcriptomic data. To understand the intricate phenotypic patterns that are emerging from the recent deluge of data, future investigations of genomic imprinting will require integrating evolutionary theory, transcriptomic data, developmental and functional genetics, and natural history.

Linked selection and the evolution of altruism in family-structured populations.

Much research on the evolution of altruism via kin selection, group selection, and reciprocity focuses on the role of a single locus or quantitative trait. Very few studies have explored how linked selection, or selection at loci neighboring an altruism locus, impacts the evolution of altruism. While linked selection can decrease the efficacy of selection at neighboring loci, it might have other effects including promoting selection for altruism by increasing relatedness in regions of low recombination. Here, we used population genetic simulations to study how negative selection at linked loci, or background selection, affects the evolution of altruism. When altruism occurs between full siblings, we found that background selection interfered with selection on the altruistic allele, increasing its fixation probability when the altruistic allele was disfavored and reducing its fixation when the allele was favored. In other words, background selection has the same effect on altruistic genes in family-structured populations as it does on other, nonsocial, genes. This contrasts with prior research showing that linked selective sweeps can favor the evolution of cooperation, and we discuss possibilities for resolving these contrasting results.

Stochastic stability and the evolution of coordination in spatially structured populations.

Animals can often coordinate their actions to achieve mutually beneficial outcomes. However, this can result in a social dilemma when uncertainty about the behavior of partners creates multiple fitness peaks. Strategies that minimize risk ("risk dominant") instead of maximizing reward ("payoff dominant") are favored in economic models when individuals learn behaviors that increase their payoffs. Specifically, such strategies are shown to be "stochastically stable" (a refinement of evolutionary stability). Here, we extend the notion of stochastic stability to biological models of continuous phenotypes at a mutation-selection-drift balance. This allows us to make a unique prediction for long-term evolution in games with multiple equilibria. We show how genetic relatedness due to limited dispersal and scaled to account for local competition can crucially affect the stochastically-stable outcome of coordination games. We find that positive relatedness (weak local competition) increases the chance the payoff dominant strategy is stochastically stable, even when it is not risk dominant. Conversely, negative relatedness (strong local competition) increases the chance that strategies evolve that are neither payoff nor risk dominant. Extending our results to large multiplayer coordination games we find that negative relatedness can create competition so extreme that the game effectively changes to a hawk-dove game and a stochastically stable polymorphism between the alternative strategies evolves. These results demonstrate the usefulness of stochastic stability in characterizing long-term evolution of continuous phenotypes: the outcomes of multiplayer games can be reduced to the generic equilibria of two-player games and the effect of spatial structure can be analyzed readily.

Evolutionarily stable strategy analysis and its links to demography and genetics through invasion fitness.

Evolutionarily stable strategy (ESS) analysis pioneered by Maynard Smith and Price took off in part because it often does not require explicit assumptions about the genetics and demography of a population in contrast to population genetic models. Though this simplicity is useful, it obscures the degree to which ESS analysis applies to populations with more realistic genetics and demography: for example, how does ESS analysis handle complexities such as kin selection, group selection and variable environments when phenotypes are affected by multiple genes? In this paper, I review the history of the ESS concept and show how early uncertainty about the method lead to important mathematical theory linking ESS analysis to general population genetic models. I use this theory to emphasize the link between ESS analysis and the concept of invasion fitness. I give examples of how invasion fitness can measure kin selection, group selection and the evolution of linked modifier genes in response to variable environments. The ESSs in these examples depend crucially on demographic and genetic parameters, which highlights how ESS analysis will continue to be an important tool in understanding evolutionary patterns as new models address the increasing abundance of genetic and long-term demographic data in natural populations. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

Behavioral responses in structured populations pave the way to group optimality.

An unresolved controversy regarding social behaviors is exemplified when natural selection might lead to behaviors that maximize fitness at the social-group level but are costly at the individual level. Except for the special case of groups of clones, we do not have a general understanding of how and when group-optimal behaviors evolve, especially when the behaviors in question are flexible. To address this question, we develop a general model that integrates behavioral plasticity in social interactions with the action of natural selection in structured populations. We find that group-optimal behaviors can evolve, even without clonal groups, if individuals exhibit appropriate behavioral responses to each other's actions. The evolution of such behavioral responses, in turn, is predicated on the nature of the proximate behavioral mechanisms. We model a particular class of proximate mechanisms, prosocial preferences, and find that such preferences evolve to sustain maximum group benefit under certain levels of relatedness and certain ecological conditions. Thus, our model demonstrates the fundamental interplay between behavioral responses and relatedness in determining the course of social evolution. We also highlight the crucial role of proximate mechanisms such as prosocial preferences in the evolution of behavioral responses and in facilitating evolutionary transitions in individuality.

A theory for the evolution of other-regard integrating proximate and ultimate perspectives.

Although much previous work describes evolutionary mechanisms that promote or stabilize different social behaviors, we still have little understanding of the factors that drive animal behavior proximately. Here we present a modeling approach to answer this question. Our model rests on motivations to achieve objectives as the proximate determinants of behavior. We develop a two-tiered framework by first modeling the dynamics of a social interaction at the behavioral time scale and then find the evolutionarily stable objectives that result from the outcomes these dynamics produce. We use this framework to ask whether "other-regarding" motivations, which result from a kind of nonselfish objective, can evolve when individuals are engaged in a social interaction that entails a conflict between their material payoffs. We find that, at the evolutionarily stable state, individuals can be other-regarding in that they are motivated to increase their partners' payoff as well as their own. In contrast to previous theories, we find that such motivations can evolve because of their direct effect on fitness and do not require kin selection or a special group structure. We also derive general conditions for the evolutionary stability of other-regarding motivations. Our conditions indicate that other-regarding motivations are more likely to evolve when social interactions and behavioral objectives are both synergistic.

Bet-hedging in innate and adaptive immune systems.

Immune system evolution is shaped by the fitness costs and trade-offs associated with mounting an immune response. Costs that arise mainly as a function of the magnitude of investment, including energetic and immunopathological costs, are well-represented in studies of immune system evolution. Less well considered, however, are the costs of immune cell plasticity and specialization. Hosts in nature encounter a large diversity of microbes and parasites that require different and sometimes conflicting immune mechanisms for defense, but it takes precious time to recognize and correctly integrate signals for an effective polarized response. In this perspective, we propose that bet-hedging can be a viable alternative to plasticity in immune cell effector function, discuss conditions under which bet-hedging is likely to be an advantageous strategy for different arms of the immune system, and present cases from both innate and adaptive immune systems that suggest bet-hedging at play.

How demography, life history, and kinship shape the evolution of genomic imprinting.

How phenomena like helping, dispersal, or the sex ratio evolve depends critically on demographic and life-history factors. One phenotype that is of particular interest to biologists is genomic imprinting, which results in parent-of-origin-specific gene expression and thus deviates from the predictions of Mendel's rules. The most prominent explanation for the evolution of genomic imprinting, the kinship theory, originally specified that multiple paternity can cause the evolution of imprinting when offspring affect maternal resource provisioning. Most models of the kinship theory do not detail how population subdivision, demography, and life history affect the evolution of imprinting. In this work, we embed the classic kinship theory within an island model of population structure and allow for diverse demographic and life-history features to affect the direction of selection on imprinting. We find that population structure does not change how multiple paternity affects the evolution of imprinting under the classic kinship theory. However, if the degree of multiple paternity is not too large, we find that sex-specific migration and survival and generation overlap are the primary factors determining which allele is silenced. This indicates that imprinting can evolve purely as a result of sex-related asymmetries in the demographic structure or life history of a species.

Environmentally Mediated Social Dilemmas.

By consuming and producing environmental resources, organisms inevitably change their habitats. The consequences of such environmental modifications can be detrimental or beneficial not only to the focal organism but also to other organisms sharing the same environment. Social evolution theory has been very influential in studying how social interactions mediated by public 'goods' or 'bads' evolve by emphasizing the role of spatial structure. The environmental dimensions driving these interactions, however, are typically abstracted away. We propose here a new, environment-mediated taxonomy of social behaviors where organisms are categorized by their production or consumption of environmental factors that can help or harm others in the environment. We discuss microbial examples of our classification and highlight the importance of environmental intermediates more generally.

Sex-specific viability, sex linkage and dominance in genomic imprinting.

Genomic imprinting is a phenomenon by which the expression of an allele at a locus depends on the parent of origin. Two different two-locus evolutionary models are presented in which a second locus modifies the imprinting status of the primary locus, which is under differential selection in males and females. In the first model, a modifier allele that imprints the primary locus invades the population when the average dominance coefficient among females and males is >12 and selection is weak. The condition for invasion is always heavily contingent upon the extent of dominance. Imprinting is more likely in the sex experiencing weaker selection only under some parameter regimes, whereas imprinting by either sex is equally likely under other regimes. The second model shows that a modifier allele that induces imprinting will increase when imprinting has a direct selective advantage. The results are not qualitatively dependent on whether the modifier locus is autosomal or X linked.