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.     

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.     

Mother’s curse and indirect genetic effects: Do males matter to mitochondrial genome evolution?

Maternal inheritance of mitochondrial DNA (mtDNA) was originally thought to prevent any response to selection on male phenotypic variation attributable to mtDNA, resulting in a male‐biased mtDNA mutation load (“mother's curse”). However, the theory underpinning this claim implicitly assumes that a male's mtDNA has no effect on the fitness of females he comes into contact with. If such “mitochondrially encoded indirect genetics effects” (mtIGEs) do in fact exist, and there is relatedness between the mitochondrial genomes of interacting males and females, male mtDNA‐encoded traits can undergo adaptation after all. We tested this possibility using strains of Drosophila melanogaster that differ in their mtDNA. Our experiments indicate that female fitness is influenced by the mtDNA carried by males that the females encounter, which could plausibly allow the mitochondrial genome to evolve via kin selection. We argue that mtIGEs are probably common, and that this might ameliorate or exacerbate mother's curse.     

Kin Selection in Primate Groups

Altruism poses a problem for evolutionary biologists because natural selection is not expected to favor behaviors that are beneficial to recipients, but costly to actors. The theory of kin selection, first articulated by Hamilton (1964), provides a solution to the problem. Hamilton's well-known rule (br > c) provides a simple algorithm for the evolution of altruism via kin selection. Because kin recognition is a crucial requirement of kin selection, it is important to know whether and how primates can recognize their relatives. While conventional wisdom has been that primates can recognize maternal kin, but not paternal kin, this view is being challenged by new findings. The ability to recognize kin implies that kin selection may shape altruistic behavior in primate groups. I focus on two cases in which kin selection is tightly woven into the fabric of social life. For female baboons, macaques, and vervets maternal kinship is an important axis of social networks, coalitionary activity, and dominance relationships. Detailed studies of the patterning of altruistic interactions within these species illustrate the extent and limits of nepotism in their social lives. Carefully integrated analyses of behavior, demography, and genetics among red howlers provide an independent example of how kin selection shapes social organization and behavior. In red howlers, kin bonds shape the life histories and reproductive performance of both males and female. The two cases demonstrate that kin selection can be a powerful source of altruistic activity within primate groups. However, to fully assess the role of kin selection in primate groups, we need more information about the effects of kinship on the patterning of behavior across the Primates and accurate information about paternal kin relationships.     

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.     

RESTRICTED MIGRATION AND THE EVOLUTION OF ALTRUISM

A suggestion that limited migration, i.e., population viscosity, should favor the evolution of altruism has been challenged by recent kin selection models explicitly incorporating restricted migration. It is demonstrated that these models compound two distinct elements of population structure, spatial-genotypic variation and density regulation. These two characteristics are often determined by distinct biological processes. While they may be linked under certain circumstances, this is not invariably true. A simple modification of the migration system employed in these studies decouples migration and population regulation thus favoring inter-group selection. At least in some cases, restricted migration will facilitate the evolution of altruism.