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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., (© The American Genetic Association. 2022. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The caste fate of developing female honey bee larvae is strictly socially regulated by adult nurse workers. As a result of this social regulation, nurse-expressed genes as well as larval-expressed genes may affect caste expression and evolution. We used a novel transcriptomic approach to identify genes with putative direct and indirect effects on honey bee caste development, and we subsequently studied the relative rates of molecular evolution at these caste-associated genes. We experimentally induced the production of new queens by removing the current colony queen, and we used RNA sequencing to study the gene expression profiles of both developing larvae and their caregiving nurses before and after queen removal. By comparing the gene expression profiles of queen-destined versus worker-destined larvae as well as nurses observed feeding these two types of larvae, we identified larval and nurse genes associated with caste development. Of 950 differentially expressed genes associated with caste, 82% were expressed in larvae with putative direct effects on larval caste, and 18% were expressed in nurses with putative indirect effects on caste. Estimated selection coefficients suggest that both nurse and larval genes putatively associated with caste are rapidly evolving, especially those genes associated with worker development. Altogether, our results suggest that indirect effect genes play important roles in both the expression and evolution of socially influenced traits such as caste.

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. [ABSTRACT FROM AUTHOR]

Behavioural ecologists increasingly study behavioural variation within and among individuals in conjunction, thereby integrating research on phenotypic plasticity and animal personality within a single adaptive framework. Interactions between individuals (cf. social environments) constitute a major causative factor of behavioural variation at both of these hierarchical levels. Social interactions give rise to complex ‘interactive phenotypes’ and group-level emergent properties. This type of phenotype has intriguing evolutionary implications, warranting a cohesive framework for its study. We detail here how a reaction-norm framework might be applied to usefully integrate social environment theory developed in behavioural ecology and quantitative genetics. The proposed emergent framework facilitates firm integration of social environments in adaptive research on phenotypic characters that vary within and among individuals. [ABSTRACT FROM AUTHOR]

Female mating preferences are often flexible, reflecting the social environment in which they are expressed. Associated indirect genetic effects (IGEs) can affect the rate and direction of evolutionary change, but sexual selection models do not capture these dynamics. We incorporate IGEs into quantitative genetic models to explore how variation in social environments and mate choice flexibility influence Fisherian sexual selection. The importance of IGEs is that runaway sexual selection can occur in the absence of a genetic correlation between male traits and female preferences. Social influences can facilitate the initiation of the runaway process and increase the rate of trait elaboration. Incorporating costs to choice do not alter the main findings. Our model provides testable predictions: (1) genetic covariances between male traits and female preferences may not exist, (2) social flexibility in female choice will be common in populations experiencing strong sexual selection, (3) variation in social environments should be associated with rapid sexual trait divergence, and (4) secondary sexual traits will be more elaborate than previously predicted. Allowing feedback from the social environment resolves discrepancies between theoretical predictions and empirical data, such as why indirect selection on female preferences, theoretically weak, might be sufficient for preferences to become elaborated. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Social interactions pervade all aspects of life in the social insects. Networks of interacting nestmates enable the maintenance of colony homeostasis and regulation of brood development. Artificial colony-level selection on the amount of pollen stored in honeybee colonies has produced high- and low-pollen-hoarding strains that have been used as a model system to study the genetic and physiological basis of differences in forager behavior that contribute to colony-level differences in pollen hoarding. Here we extend this model system using an interacting-phenotypes approach that explicitly studies genetic components arising from social interactions. High- and low-pollen-hoarding-strain larvae were reared in hives with high- or low-strain older larvae and high- or low-strain adult workers. The ovariole number and dry mass of focal individuals depended on interactions between the genotypes of the focal individuals and their brood and adult worker nestmates. These results show that trait expression by individual honeybee workers is modulated by the genotypic composition of the colony, indicating that individual-level phenotypes are properties of the composite "sociogenome." Thus, colony-level selection has produced strains with distinct combinations of socially interacting genes, which make up the social networks that regulate development and expressed phenotypes. [ABSTRACT FROM AUTHOR]