The effects of sexual selection on trait divergence in a peripheral population with gene flow

The unique aspects of speciation and divergence in peripheral populations have long sparked much research. Unidirectional migration, received by some peripheral populations, can hinder the evolution of distinct differences from their founding populations. Here, we explore the effects that sexual selection, long hypothesized to drive the divergence of distinct traits used in mate choice, can play in the evolution of such traits in a partially isolated peripheral population. Using population genetic continent‐island models, we show that with phenotype matching, sexual selection increases the frequency of an island‐specific mating trait only when female preferences are of intermediate strength. We identify regions of preference strength for which sexual selection can instead cause an island‐specific trait to be lost, even when it would have otherwise been maintained at migration‐selection balance. When there are instead separate preference and trait loci, we find that sexual selection can lead to low trait frequencies or trait loss when female preferences are weak to intermediate, but that sexual selection can increase trait frequencies when preferences are strong. We also show that novel preference strengths almost universally cannot increase, under either mating mechanism, precluding the evolution of premating isolation in peripheral populations at the early stages of species divergence.     

Demographic processes shaping genetic variation

Demographic processes modulate genome-wide levels and patterns of genetic variation via impacting effective population size independently of natural selection. Such processes include the perturbation of population distributions from external events shaping habitat landscape and internal factors shaping the probability of contemporaneous alleles in a population (coalescence). Several patterns have recently emerged: spatial and temporal heterogeneity in population structure have different influences on the persistence of new mutations and genetic variation, multi-locus analyses indicate that gene flow continues to occur during speciation and the incorporation of demographic processes into models of molecular evolution and association genetics approaches has improved statistical power to detect deviations from neutral-equilibrium expectations and decreased false positive rates.     

EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS

Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation.     

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.Subject terms: Population genetics, Biological models, Population genetics     

Stochasticity in Sexual Selection Enables Divergence: Implications for Moth Pheromone Evolution

Sexual selection has long been hypothesized to lead to allopatric speciation, and one possible mechanism for this is that its interaction with stochasticity, which perturbs the trait and preference equilibria, can result in different traits being preferred in different populations. Here we specifically examine the role that stochastic changes in sexual selection strength plays in the shift of predominance between pairs of preferences and traits within a single population. We first create a single-locus null model of stochasticity during frequency dependent selection and then compare it to a two-locus population genetic model with stochastic strengths of female preferences for male traits. We find some interesting differences between the two models, primarily that in the two-locus sexual selection model shifts between preference and trait regimes occur more often with both weak and strong preferences, compared to intermediate preference strengths. We discuss the implications of our results for the evolution of pheromone blends and male responses during speciation in moths, a case that seems to match the assumptions of our model.     

Environmental fluctuations restrict eco-evolutionary dynamics in predator–prey system

Environmental fluctuations, species interactions and rapid evolution are all predicted to affect community structure and their temporal dynamics. Although the effects of the abiotic environment and prey evolution on ecological community dynamics have been studied separately, these factors can also have interactive effects. Here we used bacteria–ciliate microcosm experiments to test for eco-evolutionary dynamics in fluctuating environments. Specifically, we followed population dynamics and a prey defence trait over time when populations were exposed to regular changes of bottom-up or top-down stressors, or combinations of these. We found that the rate of evolution of a defence trait was significantly lower in fluctuating compared with stable environments, and that the defence trait evolved to lower levels when two environmental stressors changed recurrently. The latter suggests that top-down and bottom-up changes can have additive effects constraining evolutionary response within populations. The differences in evolutionary trajectories are explained by fluctuations in population sizes of the prey and the predator, which continuously alter the supply of mutations in the prey and strength of selection through predation. Thus, it may be necessary to adopt an eco-evolutionary perspective on studies concerning the evolution of traits mediating species interactions.     

Combining population genetics and demographical approaches in evolutionary studies of plant mating systems

The striking amount of variation in the mating systems of higher plants has stimulated fruitful research by both ecologists and population geneticists. Historically, these two schools of thought have developed independent theoretical treatments and empirical approaches to account for the evolution of such diversity. We highlight the approach adopted by each field. Population geneticists have developed an approach centred on gene properties of individuals and their role on the evolution of self-fertilisation (transmission rules and the deleterious role of mutations), while ecologists have mostly focused on demographic properties of self-fertilisation (seed production, colonisation ability of selfers). As a result, the two approaches sometimes use conflicting notions of fitness. The recent empirical advances on inbreeding depression, a topic typically motivated by population genetic questions, have emphasized the need to adopt a demographical perspective for fitness. In this paper, we suggest generalizing this approach in mating system evolution and we expect further improvements by integrating demographic and genetics perspectives.     

Nemo: an evolutionary and population genetics programming framework

Nemo is an individual-based, genetically explicit and stochastic population computer program for the simulation of population genetics and life-history trait evolution in a metapopulation context. It comes as both a C++ programming framework and an executable program file. Its object-oriented programming design gives it the flexibility and extensibility needed to implement a large variety of forward-time evolutionary models. It provides developers with abstract models allowing them to implement their own life-history traits and life-cycle events. Nemo offers a large panel of population models, from the Island model to lattice models with demographic or environmental stochasticity and a variety of already implemented traits (deleterious mutations, neutral markers and more), life-cycle events (mating, dispersal, aging, selection, etc.) and output operators for saving data and statistics. It runs on all major computer platforms including parallel computing environments. AVAILABILITY: The source code, binaries and documentation are available under the GNU General Public License at http://nemo2.sourceforge.net.     

The effect of phenotypic variation on metapopulation persistence

Demographic stochasticity (due to the probabilistic nature of the birth–death process) and demographic heterogeneity (between-individual differences in demographic parameters) have long been seen as factors affecting extinction risk. While demographic stochasticity can be independent of underlying species traits, demographic heterogeneity may strongly depend on phenotypic variation. However, how phenotypic variation can affect extinction risk is largely unknown. Here, I develop a stochastic metapopulation model that takes into account the effects of demographic stochasticity and phenotypic variation in the traits controlling colonization rates to assess what the effect of phenotypic variation may be on the persistence of the metapopulation. Although phenotypic variation can lead to a decrease in metapopulation persistence under some conditions, it also may lead to an increase in persistence whenever phenotypic mismatch—or the distance between the optimal trait value and the population mean—is large. This mismatch can in turn arise from a variety of ecological and evolutionary reasons, including weak selection or a recent history of invasion. Last, the effect of phenotypic variation has a deterministic component on colonization rates, and a stochastic component on persistence through colonization rates, but both are important to understand the overall effect. These results have important implications for the conservation of threatened species and management practices that may historically have overlooked phenotypic variation as unimportant noise around mean values of interest.     

A population genetics model for multiple quantitative traits exhibiting pleiotropy and epistasis

We study a population genetics model of an organism with a genome of L(tot)loci that determine the values of T quantitative traits. Each trait is controlled by a subset of L loci assigned randomly from the genome. There is an optimum value for each trait, and stabilizing selection acts on the phenotype as a whole to maintain actual trait values close to their optima. The model contains pleiotropic effects (loci can affect more than one trait) and epistasis in fitness. We use adaptive walk simulations to find high-fitness genotypes and to study the way these genotypes are distributed in sequence space. We then simulate the evolution of haploid and diploid populations on these fitness landscapes and show that the genotypes of populations are able to drift through sequence space despite stabilizing selection on the phenotype. We study the way the rate of drift and the extent of the accessible region of sequence space is affected by mutation rate, selection strength, population size, recombination rate, and the parameters L and T that control the landscape shape. There are three regimes of the model. If LTL(tot), there are many small peaks that can be spread over a wide region of sequence space. Compensatory neutral mutations are important in the population dynamics in this case.     

Evolutionarily unstable fitness maxima and stable fitness minima of continuous traits

Summary We present models of adaptive change in continuous traits for the following situations: (1) adaptation of a single trait within a single population in which the fitness of a given individual depends on the population's mean trait value as well as its own trait value; (2) adaptation of two (or more) traits within a single population; (3) adaptation in two or more interacting species. We analyse a dynamic model of these adaptive scenarios in which the rate of change of the mean trait value is an increasing function of the fitness gradient (i.e. the rate of increase of individual fitness with the individual's trait value). Such models have been employed in evolutionary game theory and are often appropriate both for the evolution of quantitative genetic traits and for the behavioural adjustment of phenotypically plastic traits. The dynamics of the adaptation of several different ecologically important traits can result in characters that minimize individual fitness and can preclude evolution towards characters that maximize individual fitness. We discuss biological circumstances that are likely to produce such adaptive failures for situations involving foraging, predator avoidance, competition and coevolution. The results argue for greater attention to dynamical stability in models of the evolution of continuous traits.     

The evolution of genetic architectures underlying quantitative traits

In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in quantitative trait loci mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher''s blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here, we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions with qualitative trends in the genetics of human traits, and with systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis for traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.     

An evolutionary quantitative genetics model for phenotypic (co)variances under limited dispersal,with an application to socially synergistic traits

Darwinian evolution consists of the gradual transformation of heritable traits due to natural selection and the input of random variation by mutation. Here, we use a quantitative genetics approach to investigate the coevolution of multiple quantitative traits under selection, mutation, and limited dispersal. We track the dynamics of trait means and of variance–covariances between traits that experience frequency‐dependent selection. Assuming a multivariate‐normal trait distribution, we recover classical dynamics of quantitative genetics, as well as stability and evolutionary branching conditions of invasion analyses, except that due to limited dispersal, selection depends on indirect fitness effects and relatedness. In particular, correlational selection that associates different traits within‐individuals depends on the fitness effects of such associations between‐individuals. We find that these kin selection effects can be as relevant as pleiotropy for the evolution of correlation between traits. We illustrate this with an example of the coevolution of two social traits whose association within‐individuals is costly but synergistically beneficial between‐individuals. As dispersal becomes limited and relatedness increases, associations between‐traits between‐individuals become increasingly targeted by correlational selection. Consequently, the trait distribution goes from being bimodal with a negative correlation under panmixia to unimodal with a positive correlation under limited dispersal.     

Pleiotropy and the low cost of individual traits promote cooperation

The evolution of cooperation is thought to be promoted by pleiotropy, whereby cooperative traits are coregulated with traits that are important for personal fitness. However, this hypothesis faces a key challenge: what happens if mutation targets a cooperative trait specifically rather than the pleiotropic regulator? Here, we explore this question with the bacterium Pseudomonas aeruginosa, which cooperatively digests complex proteins using elastase. We empirically measure and theoretically model the fate of two mutants—one missing the whole regulatory circuit behind elastase production and the other with only the elastase gene mutated—relative to the wild‐type (WT). We first show that, when elastase is needed, neither of the mutants can grow if the WT is absent. And, consistent with previous findings, we show that regulatory gene mutants can grow faster than the WT when there are no pleiotropic costs. However, we find that mutants only lacking elastase production do not outcompete the WT, because the individual cooperative trait has a low cost. We argue that the intrinsic architecture of molecular networks makes pleiotropy an effective way to stabilize cooperative evolution. Although individual cooperative traits experience loss‐of‐function mutations, these mutations may result in weak benefits, and need not undermine the protection from pleiotropy.     

Evolutionary tracking is determined by differential selection on demographic rates and density dependence

Recent ecological forecasts predict that ~25% of species worldwide will go extinct by 2050. However, these estimates are primarily based on environmental changes alone and fail to incorporate important biological mechanisms such as genetic adaptation via evolution. Thus, environmental change can affect population dynamics in ways that classical frameworks can neither describe nor predict. Furthermore, often due to a lack of data, forecasting models commonly describe changes in population demography by summarizing changes in fecundity and survival concurrently with the intrinsic growth rate (r). This has been shown to be an oversimplification as the environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). This differential pressure may alter population response to density, in each demographic rate, further diluting the information combined to produce r. Thus, when we consider the potential for persistence via adaptive evolution, populations with the same r can have different abilities to persist amidst environmental change. Therefore, we cannot adequately forecast population response to climate change without accounting for demography and selection on density dependence. Using a continuous‐time Markov chain model to describe the stochastic dynamics of the logistic model of population growth and allow for trait evolution via mutations arising during birth events, we find persistence via evolutionary tracking more likely when environmental change alters birth rather than the death rate. Furthermore, species that evolve responses to changes in the strength of density dependence due to environmental change are less vulnerable to extinction than species that undergo selection independent of population density. By incorporating these key demographic considerations into our predictive models, we can better understand how species will respond to climate change.     

Identification of major quantitative trait loci underlying floral pollination syndrome divergence in Penstemon

Distinct floral pollination syndromes have emerged multiple times during the diversification of flowering plants. For example, in western North America, a hummingbird pollination syndrome has evolved more than 100 times, generally from within insect-pollinated lineages. The hummingbird syndrome is characterized by a suite of floral traits that attracts and facilitates pollen movement by hummingbirds, while at the same time discourages bee visitation. These floral traits generally include large nectar volume, red flower colour, elongated and narrow corolla tubes and reproductive organs that are exerted from the corolla. A handful of studies have examined the genetic architecture of hummingbird pollination syndrome evolution. These studies find that mutations of relatively large effect often explain increased nectar volume and transition to red flower colour. In addition, they suggest that adaptive suites of floral traits may often exhibit a high degree of genetic linkage, which could facilitate their fixation during pollination syndrome evolution. Here, we explore these emerging generalities by investigating the genetic basis of floral pollination syndrome divergence between two related Penstemon species with different pollination syndromes—bee-pollinated P. neomexicanus and closely related hummingbird-pollinated P. barbatus. In an F₂ mapping population derived from a cross between these two species, we characterized the effect size of genetic loci underlying floral trait divergence associated with the transition to bird pollination, as well as correlation structure of floral trait variation. We find the effect sizes of quantitative trait loci for adaptive floral traits are in line with patterns observed in previous studies, and find strong evidence that suites of floral traits are genetically linked. This linkage may be due to genetic proximity or pleiotropic effects of single causative loci. Interestingly, our data suggest that the evolution of floral traits critical for hummingbird pollination was not constrained by negative pleiotropy at loci that show co-localization for multiple traits.     

The Interaction between Selection,Demography and Selfing and How It Affects Population Viability

Population extinction due to the accumulation of deleterious mutations has only been considered to occur at small population sizes, large sexual populations being expected to efficiently purge these mutations. However, little is known about how the mutation load generated by segregating mutations affects population size and, eventually, population extinction. We propose a simple analytical model that takes into account both the demographic and genetic evolution of populations, linking population size, density dependence, the mutation load, and self-fertilisation. Analytical predictions were found to be relatively good predictors of population size and probability of population viability when verified using an explicit individual based stochastic model. We show that initially large populations do not always reach mutation-selection balance and can go extinct due to the accumulation of segregating deleterious mutations. Population survival depends not only on the relative fitness and demographic stochasticity, but also on the interaction between the two. When deleterious mutations are recessive, self-fertilisation affects viability non-monotonically and genomic cold-spots could favour the viability of outcrossing populations.     

A hot topic: the genetics of adaptation to geothermal vents in Mimulus guttatus

Identifying the individual loci and mutations that underlie adaptation to extreme environments has long been a goal of evolutionary biology. However, finding the genes that underlie adaptive traits is difficult for several reasons. First, because many traits and genes evolve simultaneously as populations diverge, it is difficult to disentangle adaptation from neutral demographic processes. Second, finding the individual loci involved in any trait is challenging given the respective limitations of quantitative and population genetic methods. In this issue of Molecular Ecology, Hendrick et al. (2016) overcome these difficulties and determine the genetic basis of microgeographic adaptation between geothermal vent and nonthermal populations of Mimulus guttatus in Yellowstone National Park. The authors accomplish this by combining population and quantitative genetic techniques, a powerful, but labour‐intensive, strategy for identifying individual causative adaptive loci that few studies have used (Stinchcombe & Hoekstra 2008 ). In a previous common garden experiment (Lekberg et al. 2012), thermal M. guttatus populations were found to differ from their closely related nonthermal neighbours in various adaptive phenotypes including trichome density. Hendrick et al. (2016) combine quantitative trait loci (QTL) mapping, population genomic scans for selection and admixture mapping to identify a single genetic locus underlying differences in trichome density between thermal and nonthermal M. guttatus. The candidate gene, R2R3 MYB, is homologous to genes involved in trichome development across flowering plants. The major trichome QTL, Tr14, is also involved in trichome density differences in an independent M. guttatus population comparison (Holeski et al. 2010) making this an example of parallel genetic evolution.     

Biogeography of species richness gradients: linking adaptive traits,demography and diversification

Here we review how adaptive traits contribute to the emergence and maintenance of species richness gradients through their influence on demographic and diversification processes. We start by reviewing how demographic dynamics change along species richness gradients. Empirical studies show that geographical clines in population parameters and measures of demographic variability are frequent along latitudinal and altitudinal gradients. Demographic variability often increases at the extremes of regional species richness gradients and contributes to shape these gradients. Available studies suggest that adaptive traits significantly influence demographic dynamics, and set the limits of species distributions. Traits related to thermal tolerance, resource use, phenology and dispersal seem to play a significant role. For many traits affecting demography and/or diversification processes, complex mechanistic approaches linking genotype, phenotype and fitness are becoming progressively available. In several taxa, species can be distributed along adaptive trait continuums, i.e. a main axis accounting for the bulk of inter‐specific variation in some correlated adaptive traits. It is shown that adaptive trait continuums can provide useful mechanistic frameworks to explain demographic dynamics and diversification in species richness gradients. Finally, we review the existence of sequences of adaptive traits in phylogenies, the interactions of adaptive traits and community context, the clinal variation of traits across geographical gradients, and the role of adaptive traits in determining the history of dispersal and diversification of clades. Overall, we show that the study of demographic and evolutionary mechanisms that shape species richness gradients clearly requires the explicit consideration of adaptive traits. To conclude, future research lines and trends in the field are briefly outlined.     

Demographic history of the trace metal hyperaccumulator Noccaea caerulescens (J. Presl and C. Presl) F. K. Mey. in Western Europe

Noccaea caerulescens (Brassicaceae) is a major pseudometallophyte model for the investigation of the genetics and evolution of metal hyperaccumulation in plants. We studied the population genetics and demographic history of this species to advance the understanding of among‐population differences in metal hyperaccumulation and tolerance abilities. Sampling of seven to 30 plants was carried out in 62 sites in Western Europe. Genotyping was carried out using a combination of new chloroplast and nuclear neutral markers. A strong genetic structure was detected, allowing the definition of three genetic subunits. Subunits showed a good geographic coherence. Accordingly, distant metallicolous populations generally belonged to distinct subunits. Approximate Bayesian computation analysis of demographic scenarios among subunits further supported a primary isolation of populations from the southern Massif Central prior to last glacial maximum, whereas northern populations may have derived during postglacial recolonization events. Estimated divergence times among subunits were rather recent in comparison with the species history, but certainly before the establishment of anthropogenic metalliferous sites. Our results suggest that the large‐scale genetic structure of N. caerulescens populations pre‐existed to the local adaptation to metalliferous sites. The population structure of quantitative variation for metal‐related adaptive traits must have established independently in isolated gene pools. However, features of the most divergent genetic unit (e.g. extreme levels of Cd accumulation observed in previous studies) question the putative relationships between adaptive evolution of metal‐related traits and subunits isolation. Finally, admixture signals among distant metallicolous populations suggest a putative role of human activities in facilitating long‐distance genetic exchanges.