Migration promotes mutator alleles in subdivided populations

Mutator alleles that elevate the genomic mutation rate may invade nonrecombining populations by hitchhiking with beneficial mutations. Mutators have been repeatedly observed to take over adapting laboratory populations and have been found at high frequencies in both microbial pathogen and cancer populations in nature. Recently, we have shown that mutators are only favored by selection in sufficiently large populations and transition to being disfavored as population size decreases. This population size‐dependent sign inversion in selective effect suggests that population structure may also be an important determinant of mutation rate evolution. Although large populations may favor mutators, subdividing such populations into sufficiently small subpopulations (demes) might effectively inhibit them. On the other hand, migration between small demes that otherwise inhibit hitchhiking may promote mutator fixation in the whole metapopulation. Here, we use stochastic, agent‐based simulations and evolution experiments with the yeast Saccharomyces cerevisiae to show that mutators can, indeed, be favored by selection in subdivided metapopulations composed of small demes connected by sufficient migration. In fact, we show that population structure plays a previously unsuspected role in promoting mutator success in subdivided metapopulations when migration is rare.     

sOAR: a tool for modelling optimal animal life‐history strategies in cyclic environments

Periodic environments determine the life cycle of many animals across the globe and the timing of important life history events, such as reproduction and migration. These adaptive behavioural strategies are complex and can only be fully understood (and predicted) within the framework of natural selection in which species adopt evolutionary stable strategies. We present sOAR, a powerful and user‐friendly implementation of the well‐established framework of optimal annual routine modelling. It allows determining optimal animal life history strategies under cyclic environmental conditions using stochastic dynamic programming. It further includes the simulation of population dynamics under the optimal strategy. sOAR provides an important tool for theoretical studies on the behavioural and evolutionary ecology of animals. It is especially suited for studying bird migration. In particular, we integrated options to differentiate between costs of active and passive flight into the optimal annual routine modelling framework, as well as options to consider periodic wind conditions affecting flight energetics. We provide an illustrative example of sOAR where food supply in the wintering habitat of migratory birds significantly alters the optimal timing of migration. sOAR helps improving our understanding of how complex behaviours evolve and how behavioural decisions are constrained by internal and external factors experienced by the animal. Such knowledge is crucial for anticipating potential species’ response to global environmental change.     

Sexual signal loss in field crickets maintained despite strong sexual selection favoring singing males

Evolutionary biologists commonly seek explanations for how selection drives the emergence of novel traits. Although trait loss is also predicted to occur frequently, few contemporary examples exist. In Hawaii, the Pacific field cricket (Teleogryllus oceanicus) is undergoing adaptive sexual signal loss due to natural selection imposed by eavesdropping parasitoids. Mutant male crickets (“flatwings”) cannot sing. We measured the intensity of sexual selection on wing phenotype in a wild population. First, we surveyed the relative abundance of flatwings and “normal‐wings” (nonmutants) on Oahu. Then, we bred wild‐mated females’ offspring to determine both female genotype with respect to the flatwing mutation and the proportion of flatwing males that sired their offspring. We found evidence of strong sexual selection favoring the production of song: females were predominantly homozygous normal‐wing, their offspring were sired disproportionately by singing males, and at the population level, flatwing males became less common following a single sexual selection event. We report a selection coefficient describing the total (pre‐ and postcopulatory) sexual selection favoring normal‐wing males in nature. Given the maintenance of the flatwing phenotype in Hawaii in recent years, this substantial sexual selection additionally suggests an approximate strength of opposing natural selection that favors silent males.     

The Effects of Stabilizing and Directional Selection on Phenotypic and Genotypic Variation in a Population of RNA Enzymes

The distribution of variation in a quantitative trait and its underlying distribution of genotypic diversity can both be shaped by stabilizing and directional selection. Understanding either distribution is important, because it determines a population’s response to natural selection. Unfortunately, existing theory makes conflicting predictions about how selection shapes these distributions, and very little pertinent experimental evidence exists. Here we study a simple genetic system, an evolving RNA enzyme (ribozyme) in which a combination of high throughput genotyping and measurement of a biochemical phenotype allow us to address this question. We show that directional selection, compared to stabilizing selection, increases the genotypic diversity of an evolving ribozyme population. In contrast, it leaves the variance in the phenotypic trait unchanged.     

Allele fixation in a dynamic metapopulation: Founder effects vs refuge effects

The fixation of mutant alleles has been studied with models assuming various spatial population structures. In these models, the structure of the metapopulation that we call the “landscape” (number, size and connectivity of subpopulations) is often static. However, natural populations are subject to repetitive population size variations, fragmentation and secondary contacts at different spatiotemporal scales due to geological, climatic and ecological processes. In this paper, we examine how such dynamic landscapes can alter mutant fixation probability and time to fixation. We consider three stochastic landscape dynamics: (i) the population is subject to repetitive bottlenecks, (ii) to the repeated alternation of fragmentation and fusion of demes with a constant population carrying capacity, (iii) idem with a variable carrying capacity. We show by deriving a variance, a coalescent and a harmonic mean population effective size, and with simulations that these landscape dynamics generate repetitive founder effects which counteract selection, thereby decreasing the fixation probability of an advantageous mutant but accelerate fixation when it occurs. For models (ii) and (iii), we also highlight an antagonistic “refuge effect” which can strongly delay mutant fixation. The predominance of either founder effects or refuge effects determines the time to fixation and mainly depends on the characteristic time scales of the landscape dynamics.     

Further remarks on Darwinian selection and “altruism”

In a recent note, Maynard Smith (Theor. Pop. Biol., in press) has claimed that there are certain difficulties in applying the method developed by us (Theor. Pop. Biol.14, 268–280) which incorporates the evolution of altruism into the population genetic theory of frequency-dependent selection. Of the four examples presented by Maynard Smith, the case of alarm calls was shown to have a natural expression in our multiplicative framework, and to produce conclusions different from those expected under the usual additive assumptions. We show here that the examples of the sterile worker, and of parental care are both simply expressible in terms of our conditional probability approach. The fourth example, the case of incest taboos, will be discussed elsewhere. Using Maynard Smith's examples important differences between the results for the additive and multiplicative fitness constructions are revealed. It is concluded that the heuristic approach using “inclusive fitness” offers no substantive advantages over exact population genetic modelling.     

Efficient use of a 'dead-end' GA 5' splice site in the human fibroblast growth factor receptor genes

We have investigated use of a conserved non-canonical GA 5' splice site present in vertebrate fibroblast growth factor receptor (FGFR) genes. Despite previous studies suggesting that GA at the beginning of an intron is incompatible with splicing, we observe efficient utilization of this splice site for human FGFR1 gene constructs. We show that use of the GA splice site is dependent on both a conventional splice site six nucleotides upstream and sequence elements within the downstream intron. Furthermore, our results are consistent with competition between the tandem 5' splice sites being mediated by U6 snRNP, rather than U1 snRNP. Thus the GA 5' splice site represents an extension of the adjacent conventional 5' splice site, the first natural example of such a composite 5' splice site.     

Spatial Ultimatum Games, collaborations and the evolution of fairness

It is often the case that individuals in a social group can perform certain tasks (such as hunting, for example) more efficiently if they collaborate with other individuals than if they act alone. In such situations one is necessarily faced with the problem of how the resource obtained as the result of such a collaboration should be divided among the collaborating individuals. If one of the individuals in the collaboration is in a position (through its dominance rank, for example) to impose a particular division of the resource on the other members of the collaboration then we show that an evolutionary dilemma arises which prevents such collaborations being evolutionarily stable. This dilemma, which is closely related to the well-known Ultimatum Game, results from the fact that in such situations natural selection favours individuals who, if dominant, offer smaller and smaller shares of the resource to the others and, if subdominant, will accept lower and lower offers. We also show, however, that this dilemma is naturally resolved in a spatially structured population with selection favouring the evolution of a fair division of the resource and consequently ensuring the evolutionary stability of collaborations of this type.     

Estimation of 2Nes from temporal allele frequency data

We develop a new method for estimating effective population sizes, Ne, and selection coefficients, s, from time-series data of allele frequencies sampled from a single diallelic locus. The method is based on calculating transition probabilities, using a numerical solution of the diffusion process, and assuming independent binomial sampling from this diffusion process at each time point. We apply the method in two example applications. First, we estimate selection coefficients acting on the CCR5-delta 32 mutation on the basis of published samples of contemporary and ancient human DNA. We show that the data are compatible with the assumption of s = 0, although moderate amounts of selection acting on this mutation cannot be excluded. In our second example, we estimate the selection coefficient acting on a mutation segregating in an experimental phage population. We show that the selection coefficient acting on this mutation is approximately 0.43.     

Eco-evolutionary dynamics in Pacific salmon

Increasing acceptance of the idea that evolution can proceed rapidly has generated considerable interest in understanding the consequences of ongoing evolutionary change for populations, communities and ecosystems. The nascent field of 'eco-evolutionary dynamics' considers these interactions, including reciprocal feedbacks between evolution and ecology. Empirical support for eco-evolutionary dynamics has emerged from several model systems, and we here present some possibilities for diverse and strong effects in Pacific salmon (Oncorhynchus spp.). We specifically focus on the consequences that natural selection on body size can have for salmon population dynamics, community (bear-salmon) interactions and ecosystem process (fluxes of salmon biomass between habitats). For example, we find that shifts in body size because of selection can alter fluxes across habitats by up to 11% compared with ecological (that is, numerical) effects. More generally, we show that selection within a generation can have large effects on ecological dynamics and so should be included within a complete eco-evolutionary framework.     

Developmental plasticity and evolutionary explanations

Developmental plasticity looks like a promising bridge between ecological and developmental perspectives on evolution. Yet, there is no consensus on whether plasticity is part of the explanation for adaptive evolution or an optional “add‐on” to genes and natural selection. Here, we suggest that these differences in opinion are caused by differences in the simplifying assumptions, and particular idealizations, that enable evolutionary explanation. We outline why idealizations designed to explain evolution through natural selection prevent an understanding of the role of development, and vice versa. We show that representing plasticity as a reaction norm conforms with the idealizations of selective explanations, which can give the false impression that plasticity has no explanatory power for adaptive evolution. Finally, we use examples to illustrate why evolutionary explanations that include developmental plasticity may in fact be more satisfactory than explanations that solely refer to genes and natural selection.     

Resource-aware taxon selection for maximizing phylogenetic diversity

Phylogenetic diversity (PD) is a useful metric for selecting taxa in a range of biological applications, for example, bioconservation and genomics, where the selection is usually constrained by the limited availability of resources. We formalize taxon selection as a conceptually simple optimization problem, aiming to maximize PD subject to resource constraints. This allows us to take into account the different amounts of resources required by the different taxa. Although this is a computationally difficult problem, we present a dynamic programming algorithm that solves it in pseudo-polynomial time. Our algorithm can also solve many instances of the Noah's Ark Problem, a more realistic formulation of taxon selection for biodiversity conservation that allows for taxon-specific extinction risks. These instances extend the set of problems for which solutions are available beyond previously known greedy-tractable cases. Finally, we discuss the relevance of our results to real-life scenarios.     

Sex and evolutionary stability

We study evolutionary games in which the rest points of the evolutionary dynamic cluster in connected components, focusing on what we call the Resource Game as a canonical example. The long-term outcome in such games can depend critically on second-order forces that were excluded from the evolutionary dynamics because they are typically insignificant compared with selection pressures. We show that the influence of second-order forces on long-term outcomes can depend on whether the reproduction underlying the evolutionary dynamics is sexual or asexual. An implication is that care is needed in adopting the convenience of an asexual model when examining the behavior of a sexual population in games with nontrivial components of rest points.     

Haplotype-based inference of the distribution of fitness effects

Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some nonequilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.     

Social selection acts on behavior and body mass but does not contribute to the total selection differential in eastern chipmunks

Through social interactions, phenotypes of conspecifics can affect an individual's fitness, resulting in social selection. Social selection is assumed to represent a strong and dynamic evolutionary force that can act with or in opposition to natural selection. Few studies, however, have estimated social selection and its contribution to total selection in the wild. We estimated natural and social selection gradients on exploration, docility, and body mass, and their contribution to selection differentials, in a wild eastern chipmunk population (Tamias striatus). We applied trait-based multiple regression models derived from classical phenotypic selection analyses, which allowed us to include several social partners (i.e., neighbors). We detected social selection gradients on female docility and male body mass, indicating that female with docile neighbors and males with large neighbors had lower fitness. In both sexes, social selection gradients varied with the season. However, we found no phenotypic assortment or disassortment for the studied traits. Social selection gradients, therefore, did not contribute to total selection differentials, and natural selection alone could drive phenotypic changes. Evaluating the factors that drive the evolution of the covariance between interacting phenotypes is necessary to understand the role of social selection as an evolutionary force.     

Can natural selection favour altruism between species?

Darwin suggested that the discovery of altruism between species would annihilate his theory of natural selection. However, it has not been formally shown whether between‐species altruism can evolve by natural selection, or why this could never happen. Here, we develop a spatial population genetic model of two interacting species, showing that indiscriminate between species helping can be favoured by natural selection. We then ask if this helping behaviour constitutes altruism between species, using a linear‐regression analysis to separate the total action of natural selection into its direct and indirect (kin selected) components. We show that our model can be interpreted in two ways, as either altruism within species, or altruism between species. This ambiguity arises depending on whether or not we treat genes in the other species as predictors of an individual's fitness, which is equivalent to treating these individuals as agents (actors or recipients). Our formal analysis, which focuses upon evolutionary dynamics rather than agents and their agendas, cannot resolve which is the better approach. Nonetheless, because a within‐species altruism interpretation is always possible, our analysis supports Darwin's suggestion that natural selection does not favour traits that provide benefits exclusively to individuals of other species.     

Evolutionary graph theory: breaking the symmetry between interaction and replacement

We study evolutionary dynamics in a population whose structure is given by two graphs: the interaction graph determines who plays with whom in an evolutionary game; the replacement graph specifies the geometry of evolutionary competition and updating. First, we calculate the fixation probabilities of frequency dependent selection between two strategies or phenotypes. We consider three different update mechanisms: birth-death, death-birth and imitation. Then, as a particular example, we explore the evolution of cooperation. Suppose the interaction graph is a regular graph of degree h, the replacement graph is a regular graph of degree g and the overlap between the two graphs is a regular graph of degree l. We show that cooperation is favored by natural selection if b/c>hg/l. Here, b and c denote the benefit and cost of the altruistic act. This result holds for death-birth updating, weak-selection and large population size. Note that the optimum population structure for cooperators is given by maximum overlap between the interaction and the replacement graph (g=h=l), which means that the two graphs are identical. We also prove that a modified replicator equation can describe how the expected values of the frequencies of an arbitrary number of strategies change on replacement and interaction graphs: the two graphs induce a transformation of the payoff matrix.     

Ecological theatre and the evolutionary game: how environmental and demographic factors determine payoffs in evolutionary games

In the standard approach to evolutionary games and replicator dynamics, differences in fitness can be interpreted as an excess from the mean Malthusian growth rate in the population. In the underlying reasoning, related to an analysis of “costs” and “benefits”, there is a silent assumption that fitness can be described in some type of units. However, in most cases these units of measure are not explicitly specified. Then the question arises: are these theories testable? How can we measure “benefit” or “cost”? A natural language, useful for describing and justifying comparisons of strategic “cost” versus “benefits”, is the terminology of demography, because the basic events that shape the outcome of natural selection are births and deaths. In this paper, we present the consequences of an explicit analysis of births and deaths in an evolutionary game theoretic framework. We will investigate different types of mortality pressures, their combinations and the possibility of trade-offs between mortality and fertility. We will show that within this new approach it is possible to model how strictly ecological factors such as density dependence and additive background fitness, which seem neutral in classical theory, can affect the outcomes of the game. We consider the example of the Hawk–Dove game, and show that when reformulated in terms of our new approach new details and new biological predictions are produced.