The strength of phenotypic selection in natural populations

Selective effect of winter weather on a songbird's morphology depends on individual sex and winter condition

Knowledge of the effect of harsh weather on the phenotypic traits of organisms is essential for understanding the environmental influence on phenotype evolution and holds implications for predicting how species respond to current climate change. For many birds, harsh weather in winter often imposes a strong selective effect on their survival, and only the individuals with certain phenotypes may survive. However, whether the selective effect on phenotype varies with winter weather conditions has been poorly investigated. Here, we explored the selective effect of winter weather on black-throated tit's (Aegithalos concinnus) morphological traits under winters with and without severe snowstorms. We found that for males, the sizes of their bills, heads and wings significantly affected their overwinter survival, but the effects varied with winter conditions. In relatively benign winters, males with smaller bill depths, smaller bill surface areas, and greater head lengths survived better; whereas, in winters with severe snowstorms, a reverse pattern was found. This phenomenon was likely driven by selection pressures from heat retention and foraging requirements, with their relative importance depending on winter conditions. Additionally, wing length was positively correlated with male survival and the relationship was stronger in harsher winters, which was probably due to longer wings' higher flight efficiency in adverse weather. By contrast, we found no correlation between morphological traits and survival in females. These results suggest a sex-specific and condition-dependent selective effect of environment on bird phenotypes, implying complicated interactions between different selection pressures and phenotype evolution.

The cliff edge model of the evolution of schizophrenia: Mathematical, epidemiological, and genetic evidence

How has schizophrenia, a condition that significantly reduces an individual's evolutionary fitness, remained common across generations and cultures? Numerous theories about the evolution of schizophrenia have been proposed, most of which are not consistent with modern epidemiological and genetic evidence. Here, we briefly review this evidence and explore the cliff edge model of schizophrenia. It suggests that schizophrenia is the extreme manifestation of a polygenic trait or a combination of traits that, within a normal range of variation, confer cognitive, linguistic, and/or social advantages. Only beyond a certain threshold, these traits precipitate the onset of schizophrenia and reduce fitness. We provide the first mathematical model of this qualitative concept and show that it requires only very weak positive selection of the underlying trait(s) to explain today's schizophrenia prevalence. This prediction, along with expectations about the effect size of schizophrenia risk alleles, are surprisingly well matched by empirical evidence. The cliff edge model predicts a dynamic change of selection of risk alleles, which explains the contradictory findings of evolutionary genetic studies.

The missing fraction problem as an episodes of selection problem

In evolutionary quantitative genetics, the missing fraction problem refers to a specific kind of bias in parameters estimated later in life that occurs when nonrandom subsets of phenotypes are missing from the population due to prior viability selection on correlated traits. The missing fraction problem thus arises when the following hold: (a) viability selection and (b) correlation between later-life traits and traits important for early-life survival. Although it is plausible that these conditions are widespread in wild populations, this problem has received little empirical attention. This may be natural: the problem could appear intractable, given that it is impossible to measure phenotypes of individuals that have previously died. However, it is not impossible to correctly measure lifetime selection, or correctly predict evolutionary trajectories, of later-life traits in the presence of the missing fraction. Two basic strategies are available. First, given phenotypic data on selected early life traits, well established but underused episodes of selection theory can yield correct values of evolutionary parameters throughout life. Second, when traits subjected to early-life viability selection are not known and/or measured, it is possible to use the genetic association of later-life traits with early-life viability to correctly infer important information about the consequences of prior viability selection for later-life traits. By carefully reviewing the basic nature of the missing fraction problem, and describing the tractable solutions to the problem, we hope that future studies will be able to be better designed to cope with the (likely pervasive) consequences of early-life viability selection.

Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these two fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we derive a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., Genome-Wide Association Studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur using analytical theory and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate this by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study of this, we re-examine an analysis testing for co-evolution of expression levels between genes across a fungal phylogeny, and show that including covariance matrix eigenvectors as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.

The evolutionary impact of childhood cancer on the human gene pool

Germline pathogenic variants associated with increased childhood mortality must be subject to natural selection. Here, we analyze publicly available germline genetic metadata from 4,574 children with cancer [11 studies; 1,083 whole exome sequences (WES), 1,950 whole genome sequences (WGS), and 1,541 gene panel] and 141,456 adults [125,748 WES and 15,708 WGS]. We find that pediatric cancer predisposition syndrome (pCPS) genes [n = 85] are highly constrained, harboring only a quarter of the loss-of-function variants that would be expected. This strong indication of selective pressure on pCPS genes is found across multiple lines of germline genomics data from both pediatric and adult cohorts. For six genes [ELP1, GPR161, VHL and SDHA/B/C], a clear lack of mutational constraint calls the pediatric penetrance and/or severity of associated cancers into question. Conversely, out of 23 known pCPS genes associated with biallelic risk, two [9%, DIS3L2 and MSH2] show significant constraint, indicating that they may monoallelically increase childhood cancer risk. In summary, we show that population genetic data provide empirical evidence that heritable childhood cancer leads to natural selection powerful enough to have significantly impacted the present-day gene pool.

Non-genetic phenotypic variability affects populations and communities in protist microcosms

Intraspecific trait variation (ITV), potentially driven by genetic and non-genetic mechanisms, can underlie variability in resource acquisition, individual fitness and ecological interactions. Impacts of ITV at higher levels of biological organizations are hence likely, but up-scaling our knowledge about ITV importance to communities and comparing its relative effects at population and community levels has rarely been investigated. Here, we tested the effects of genetic and non-genetic ITV on morphological traits in microcosms of protist communities by contrasting the effects of strains showing different ITV levels (i.e. trait averages and variance) on population growth, community composition and biomass production. We found that genetic and non-genetic ITV can lead to different effects on populations and communities across several generations. Furthermore, the effects of ITV declined across levels of biological organization: ITV directly altered population performance, with cascading but indirect consequences for community composition and biomass productivity. Overall, these results show that the drivers of ITV can have distinct effects on populations and communities, with cascading impacts on higher levels of biological organization that might mediate biodiversity-ecosystem functioning relationships.

A mathematical framework for evo-devo dynamics

Natural selection acts on phenotypes constructed over development, which raises the question of how development affects evolution. Classic evolutionary theory indicates that development affects evolution by modulating the genetic covariation upon which selection acts, thus affecting genetic constraints. However, whether genetic constraints are relative, thus diverting adaptation from the direction of steepest fitness ascent, or absolute, thus blocking adaptation in certain directions, remains uncertain. This limits understanding of long-term evolution of developmentally constructed phenotypes. Here we formulate a general, tractable mathematical framework that integrates age progression, explicit development (i.e., the construction of the phenotype across life subject to developmental constraints), and evolutionary dynamics, thus describing the evolutionary and developmental (evo-devo) dynamics. The framework yields simple equations that can be arranged in a layered structure that we call the evo-devo process, whereby five core elementary components generate all equations including those mechanistically describing genetic covariation and the evo-devo dynamics. The framework recovers evolutionary dynamic equations in gradient form and describes the evolution of genetic covariation from the evolution of genotype, phenotype, environment, and mutational covariation. This shows that genotypic and phenotypic evolution must be followed simultaneously to yield a dynamically sufficient description of long-term phenotypic evolution in gradient form, such that evolution described as the climbing of a fitness landscape occurs in "geno-phenotype" space. Genetic constraints in geno-phenotype space are necessarily absolute because the phenotype is related to the genotype by development. Thus, the long-term evolutionary dynamics of developed phenotypes is strongly non-standard: (1) evolutionary equilibria are either absent or infinite in number and depend on genetic covariation and hence on development; (2) developmental constraints determine the admissible evolutionary path and hence which evolutionary equilibria are admissible; and (3) evolutionary outcomes occur at admissible evolutionary equilibria, which do not generally occur at fitness landscape peaks in geno-phenotype space, but at peaks in the admissible evolutionary path where "total genotypic selection" vanishes if exogenous plastic response vanishes and mutational variation exists in all directions of genotype space. Hence, selection and development jointly define the evolutionary outcomes if absolute mutational constraints and exogenous plastic response are absent, rather than the outcomes being defined only by selection. Moreover, our framework provides formulas for the sensitivities of a recurrence and an alternative method to dynamic optimization (i.e., dynamic programming or optimal control) to identify evolutionary outcomes in models with developmentally dynamic traits. These results show that development has major evolutionary effects.

Drift on holey landscapes as a dominant evolutionary process

An organism's phenotype has been shaped by evolution but the specific processes have to be indirectly inferred for most species. For example, correlations among traits imply the historical action of correlated selection and, more generally, the expression and distribution of traits is expected to be reflective of the adaptive landscapes that have shaped a population. However, our expectations about how quantitative traits-like most behaviors, physiological processes, and life-history traits-should be distributed under different evolutionary processes are not clear. Here, we show that genetic variation in quantitative traits is not distributed as would be expected under dominant evolutionary models. Instead, we found that genetic variation in quantitative traits across six phyla and 60 species (including both Plantae and Animalia) is consistent with evolution across high-dimensional "holey landscapes." This suggests that the leading conceptualizations and modeling of the evolution of trait integration fail to capture how phenotypes are shaped and that traits are integrated in a manner contrary to predictions of dominant evolutionary theory. Our results demonstrate that our understanding of how evolution has shaped phenotypes remains incomplete and these results provide a starting point for reassessing the relevance of existing evolutionary models.

Divergent preference functions generate directional selection in a jumping spider

Sexual selection has long been thought to promote speciation, but this possibility still remains a topic of controversy. Many theoretical models have been developed to understand the relationship between sexual selection and speciation, but such relationship seems complex and sexual selection has also been argued to prevent speciation in many scenarios. Here, I model for the first time the tendency of speciation due to sexual selection using realistic model parameters input collected from an existing species, the jumping spider Hasarius adansoni. I show that, even though the species has substantial female variance in preference (the model typically thought to link sexual selection to speciation), when realistic parameters are input in the model, it predicts directional selection, rather than disruptive selection. I propose that including realistic parameters in speciation models is a new tool that will help us understand how common sexual selection helps or hinders speciation in the real world.

Stabilizing selection on a plumage-based foraging adaptation: hooded warblers with average-sized white tail spots live longer

Avian flush-pursuit insectivores typically use contrasting white plumage patches in their tails or wings to startle potential prey. Although experimental evidence indicates that the extent of white has been fine-tuned by natural selection to optimize foraging performance, the hypothesis that within-population plumage variation directly influences survival or lifetime reproduction and is subject to stabilizing selection has not been tested. Here, I provide such a test using data collected as part of a 14-year study of a colour-ringed breeding population of the hooded warbler (Setophaga citrina), a migratory flush-pursuit insectivore that shows inter-individual variation in the extent of white in the tail that is highly repeatable across moults and probably heritable. As expected under stabilizing selection, warblers with average-sized white tail patches achieved significantly higher apparent long-term survival than individuals with either a lesser or greater extent of white in the tail. Evidence of stabilizing selection was especially strong in males, an observation that is probably related to pronounced sexual habitat segregation on the wintering range. My results provide infrequently observed evidence of stabilizing selection operating in a natural population, and also illustrate how stabilizing selection can act on avian plumage traits outside the context of sexual and social signalling.

Evolutionary rescue under demographic and environmental stochasticity

Populations suffer two types of stochasticity: demographic stochasticity, from sampling error in offspring number, and environmental stochasticity, from temporal variation in the growth rate. By modelling evolution through phenotypic selection following an abrupt environmental change, we investigate how genetic and demographic dynamics, as well as effects on population survival of the genetic variance and of the strength of stabilizing selection, differ under the two types of stochasticity. We show that population survival probability declines sharply with stronger stabilizing selection under demographic stochasticity, but declines more continuously when environmental stochasticity is strengthened. However, the genetic variance that confers the highest population survival probability differs little under demographic and environmental stochasticity. Since the influence of demographic stochasticity is stronger when population size is smaller, a slow initial decline of genetic variance, which allows quicker evolution, is important for population persistence. In contrast, the influence of environmental stochasticity is population-size-independent, so higher initial fitness becomes important for survival under strong environmental stochasticity. The two types of stochasticity interact in a more than multiplicative way in reducing the population survival probability. Our work suggests the importance of explicitly distinguishing and measuring the forms of stochasticity during evolutionary rescue.

Modeling heterothermic fitness landscapes in a marsupial hibernator using changes in body composition

Hibernation is an adaptive strategy that allows animals to enter a hypometabolic state, conserving energy and enhancing their fitness by surviving harsh environmental conditions. However, addressing the adaptive value of hibernation, at the individual level and in natural populations, has been challenging. Here, we applied a non-invasive technique, body composition analysis by quantitative magnetic resonance (qMR), to calculate energy savings by hibernation in a population of hibernating marsupials (Dromiciops gliroides). Using outdoor enclosures installed in a temperate rainforest, and measuring qMR periodically, we determined the amount of fat and lean mass consumed during a whole hibernation cycle. With this information, we estimated the daily energy expenditure of hibernation (DEEH) at the individual level and related to previous fat accumulation. Using model selection approaches and phenotypic selection analysis, we calculated linear (directional, β), quadratic (stabilizing or disruptive, γ) and correlational (ρ) coefficients for DEEH and fat accumulation. We found significant, negative directional selection for DEEH (βDEEH = - 0.58 ± 0.09), a positive value for fat accumulation (βFAT = 0.34 ± 0.07), and positive correlational selection between both traits (ρDEEH × FAT = 0.24 ± 0.07). Then, individuals maximizing previous fat accumulation and minimizing DEEH were promoted by selection, which is visualized by a bi-variate selection surface estimated by generalized additive models. At the comparative level, results fall within the isometric allometry known for hibernation metabolic rate in mammals. Thus, by a combination of a non-invasive technique for body composition analysis and semi-natural enclosures, we were characterized the heterothermic fitness landscape in a semi-natural population of hibernators.

Inferred Attractiveness: A generalized mechanism for sexual selection that can maintain variation in traits and preferences over time

Sexual selection by mate choice is a powerful force that can lead to evolutionary change, and models of why females choose particular mates are central to understanding its effects. Predominant mate choice theories assume preferences are determined solely by genetic inheritance, an assumption still lacking widespread support. Moreover, preferences often vary among individuals or populations, fail to correspond with conspicuous male traits, or change with context, patterns not predicted by dominant models. Here, we propose a new model that explains this mate choice complexity with one general hypothesized mechanism, "Inferred Attractiveness." In this model, females acquire mating preferences by observing others' choices and use context-dependent information to infer which traits are attractive. They learn to prefer the feature of a chosen male that most distinguishes him from other available males. Over generations, this process produces repeated population-level switches in preference and maintains male trait variation. When viability selection is strong, Inferred Attractiveness produces population-wide adaptive preferences superficially resembling "good genes." However, it results in widespread preference variation or nonadaptive preferences under other predictable circumstances. By casting the female brain as the central selective agent, Inferred Attractiveness captures novel and dynamic aspects of sexual selection and reconciles inconsistencies between mate choice theory and observed behavior.

Detecting natural selection in trait-trait coevolution

No phenotypic trait evolves independently of all other traits, but the cause of trait-trait coevolution is poorly understood. While the coevolution could arise simply from pleiotropic mutations that simultaneously affect the traits concerned, it could also result from multivariate natural selection favoring certain trait relationships. To gain a general mechanistic understanding of trait-trait coevolution, we examine the evolution of 220 cell morphology traits across 16 natural strains of the yeast Saccharomyces cerevisiae and the evolution of 24 wing morphology traits across 110 fly species of the family Drosophilidae, along with the variations of these traits among gene deletion or mutation accumulation lines (a.k.a. mutants). For numerous trait pairs, the phenotypic correlation among evolutionary lineages differs significantly from that among mutants. Specifically, we find hundreds of cases where the evolutionary correlation between traits is strengthened or reversed relative to the mutational correlation, which, according to our population genetic simulation, is likely caused by multivariate selection. Furthermore, we detect selection for enhanced modularity of the yeast traits analyzed. Together, these results demonstrate that trait-trait coevolution is shaped by natural selection and suggest that the pleiotropic structure of mutation is not optimal. Because the morphological traits analyzed here are chosen largely because of their measurability and thereby are not expected to be biased with regard to natural selection, our conclusion is likely general.

Beauty or function? The opposing effects of natural and sexual selection on cuticular hydrocarbons in male black field crickets

Although many theoretical models of male sexual trait evolution assume that sexual selection is countered by natural selection, direct empirical tests of this assumption are relatively uncommon. Cuticular hydrocarbons (CHCs) are known to play an important role not only in restricting evaporative water loss but also in sexual signalling in most terrestrial arthropods. Insects adjusting their CHC layer for optimal desiccation resistance is often thought to come at the expense of successful sexual attraction, suggesting that natural and sexual selection are in opposition for this trait. In this study, we sampled the CHCs of male black field crickets (Teleogryllus commodus) using solid-phase microextraction and then either measured their evaporative water loss or mating success. We then used multivariate selection analysis to quantify the strength and form of natural and sexual selection targeting male CHCs. Both natural and sexual selection imposed significant linear and stabilizing selection on male CHCs, although for very different combinations. Natural selection largely favoured an increase in the total abundance of CHCs, especially those with a longer chain length. In contrast, mating success peaked at a lower total abundance of CHCs and declined as CHC abundance increased. However, mating success did improve with an increase in a number of specific CHC components that also increased evaporative water loss. Importantly, this resulted in the combination of male CHCs favoured by natural selection and sexual selection being strongly opposing. Our findings suggest that the balance between natural and sexual selection is likely to play an important role in the evolution of male CHCs in T. commodus and may help explain why CHCs are so divergent across populations and species.

Contemporary changes in phenotypic variation, and the potential consequences for eco-evolutionary dynamics

Most studies assessing rates of phenotypic change focus on population mean trait values, whereas a largely overlooked additional component is changes in population trait variation. Theoretically, eco-evolutionary dynamics mediated by such changes in trait variation could be as important as those mediated by changes in trait means. To date, however, no study has comprehensively summarised how phenotypic variation is changing in contemporary populations. Here, we explore four questions using a large database: How do changes in trait variances compare to changes in trait means? Do different human disturbances have different effects on trait variance? Do different trait types have different effects on changes in trait variance? Do studies that established a genetic basis for trait change show different patterns from those that did not? We find that changes in variation are typically small; yet we also see some very large changes associated with particular disturbances or trait types. We close by interpreting and discussing the implications of our findings in the context of eco-evolutionary studies.

Are animal personality, body condition, physiology and structural size integrated? A comparison of species, populations and sexes, and the value of study replication

A major question in behavioural ecology is why behaviour, physiology and morphology are often integrated into syndromes. In great tits, Parus major, for example, explorative males are larger (vs. smaller) and leaner (vs. heavier) compared to less explorative individuals. Unfortunately, considerable debate exists on whether patterns found in specific studies are replicable. This debate calls for study replication among species, populations and sexes. We measured behavioural (exploration), physiological (breathing rate) and morphological traits (body mass, tarsus length, wing length, bill length) in two species (great vs. blue tits Cyanistes caeruleus), two populations (Forstenrieder Park vs. Starnberg) and two sexes (males vs. females). We then tested whether the same pattern of integration characterized all unique combinations of these three biological categories (hereafter called datasets). We used a multi-year repeated measures set-up to estimate among-individual trait correlation matrices for each dataset. We then used structural equation modelling to test for size-dependent behaviour and physiology, size-corrected (i.e. size-independent) behaviour-physiology correlations and size-corrected body mass-dependent behaviour and physiology. Finally, we used meta-analyses to test which structural paths were generally (vs. conditionally) supported (vs. unsupported). We found general and consistent support for size-dependent physiology and size-corrected body mass-dependent physiology across datasets: faster breathers were smaller but heavier for their size. Unexpectedly, condition-dependent behaviour was not supported: explorative birds were neither leaner, nor was this relationship heterogeneous across datasets. All other hypothesized patterns were dataset-specific: the covariance between size and behaviour, and between behaviour and physiology differed in sign between datasets, and both were, on average, not supported. This heterogeneity was not explained by any of our moderators: species, population or sex. The specific pattern of size- and condition-dependent physiology reported for a unique combination of species, population, and sex, thus generally predicted those in others. Patterns of size- or condition-dependent behaviour (i.e. 'personality'), or behaviour-physiology syndromes reported in specific datasets, by contrast, did not. These findings call for studies revealing the ecological background of this variation and highlight the value of study replication to help understand whether patterns of phenotypic integration reported in one study can be generalized.

Selection on weapon allometry in the wild

Allometry is the scaling relationship between a trait and body size. This relationship can often explain considerable morphological variation within and among species. Nevertheless, much remains unknown about the factors that underlie allometric patterns. For example, when different allometric relationships are observed amongst closely related species, these differences are regularly considered to be products of selection. However, directional selection on allometry (particularly the slope) has rarely been tested and observed in natural populations. Here, we investigate selection on the scaling relationship between weapon size and body size (i.e., weapon allometry) in a wild population of giant mesquite bugs, Pachylis neocalifornicus (previously Thasus neocalifornicus). Males in this species use their weapons (enlarged femurs) to compete with one another over access to resources and females. We found that large males with relatively large weapons successfully secured access to mates. However, we also found that small males with relatively small weapons could access mates as well. These two patterns together can increase the allometric slope of the sexually selected weapon, suggesting a straightforward process by which the allometric slope can evolve.

Different mechanisms underpin the decline in growth of anchovies and sardines of the Bay of Biscay

Declines in individuals' growth in exploited fish species are generally attributed to evolutionary consequences of size-selective fishing or to plastic responses due to constraints set by changing environmental conditions dampening individuals' growth. However, other processes such as growth compensation and non-directional selection can occur and their importance on the overall phenotypic response of exploited populations has largely been ignored. Using otolith growth data collected in European anchovy and sardine of the Bay of Biscay (18 cohorts from 2000 to 2018), we parameterized the breeder's equation to determine whether declines in size-at-age in these species were due to an adaptive response (i.e. related to directional or non-directional selection differentials within parental cohorts) or a plastic response (i.e. related to changes in environmental). We found that growth at age-0 in anchovy declined between parents and their offspring when biomass increased and the selective disappearance of large individuals was high in parents. Therefore, an adaptive response probably occurred in years with high fishing effort and the large increase in biomass after the collapse of this stock maintained this adaptive response subsequently. In sardine offspring, higher growth at age-0 was associated with increasing biomass between parents and offspring, suggesting a plastic response to a bottom-up process (i.e. a change in food quantity or quality). Parental cohorts in which selection favoured individuals with high growth compensation produced offspring high catch up growth rates, which may explain the smaller decline in growth in sardine relative to anchovy. Finally, on non-directional selection differentials were not significantly related to the changes in growth at age-0 and growth compensation at age-1 in both species. Although anchovy and sardine have similar ecologies, the mechanisms underlying the declines in their growth are clearly different. The consequences of the exploitation of natural populations could be long lasting if density-dependent processes follow adaptive changes.

The long-lasting legacy of reproduction: lifetime reproductive success shapes expected genetic contributions of humans after 10 generations

An individual's lifetime reproductive success (LRS) measures its realized genetic contributions to the next generation, but how well does it predict this over longer periods? Here we use human genealogical data to estimate expected individual genetic contributions (IGC) and quantify the degree to which LRS, relative to other fitness proxies, predicts IGC over longer periods. This allows an identification of the life-history stages that are most important in shaping variation in IGC. We use historical genealogical data from two non-isolated local populations in Switzerland to estimate the stabilized IGC for 2230 individuals approximately 10 generations after they were born. We find that LRS explains 30% less variation in IGC than the best predictor of IGC, the number of grandoffspring. However, albeit less precise than the number of grandoffspring, we show that LRS does provide an unbiased prediction of IGC. Furthermore, it predicts IGC better than lifespan, and accounting for offspring survival to adulthood does not improve the explanatory power. Overall, our findings demonstrate the value of human genealogical data to evolutionary biology and suggest that reproduction-more than lifespan or offspring survival-impacts the long-term genetic contributions of historic humans, even in a population with appreciable migration.

A polygenic basis for birth weight in a wild population of red deer (Cervus elaphus)

The genetic architecture of traits under selection has important consequences for the response to selection and potentially for population viability. Early QTL mapping studies in wild populations have reported loci with large effect on trait variation. However, these results are contradicted by more recent genome-wide association analyses, which strongly support the idea that most quantitative traits have a polygenic basis. This study aims to re-evaluate the genetic architecture of a key morphological trait, birth weight, in a wild population of red deer (Cervus elaphus), using genomic approaches. A previous study using 93 microsatellite and allozyme markers and linkage mapping on a kindred of 364 deer detected a pronounced QTL on chromosome 21 explaining 29% of the variance in birth weight, suggesting that this trait is partly controlled by genes with large effects. Here, we used data for more than 2,300 calves genotyped at >39,000 SNP markers and two approaches to characterise the genetic architecture of birth weight. First, we performed a genome-wide association (GWA) analysis, using a genomic relatedness matrix to account for population structure. We found no SNPs significantly associated with birth weight. Second, we used genomic prediction to estimate the proportion of variance explained by each SNP and chromosome. This analysis confirmed that most genetic variance in birth weight was explained by loci with very small effect sizes. Third, we found that the proportion of variance explained by each chromosome was slightly positively correlated with its size. These three findings highlight a highly polygenic architecture for birth weight, which contradicts the previous QTL study. These results are probably explained by the differences in how associations are modelled between QTL mapping and GWA. Our study suggests that models of polygenic adaptation are the most appropriate to study the evolutionary trajectory of this trait.

Heritability Estimation Approaches Utilizing Genome-Wide Data

Prior to the development of genome-wide arrays and whole genome sequencing technologies, heritability estimation mainly relied on the study of related individuals. Over the past decade, various approaches have been developed to estimate SNP-based narrow-sense heritability (h SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ ) in unrelated individuals. These latter approaches use either individual-level genetic variations or summary results from genome-wide association studies (GWAS). Recently, several studies compared these approaches using extensive simulations and empirical datasets. However, sparse information on hands-on training necessitates revisiting these approaches from the perspective of a stepwise guide for practical applications. Here, we provide an overview of the commonly used SNP-heritability estimation approaches utilizing genome-wide array, imputed or whole genome data from unrelated individuals, or summary results. We not only discuss these approaches based on their statistical concepts, utility, advantages, and limitations, but also provide step-by-step protocols to apply these approaches. For illustration purposes, we estimateh SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ of height and BMI utilizing individual-level data from The Northern Finland Birth Cohort (NFBC) and summary results from the Genetic Investigation of ANthropometric Traits (GIANT;) consortium. We present this review as a template for the researchers who estimate and use heritability in their studies and as a reference for geneticists who develop or extend heritability estimation approaches. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: GREML (GCTA) Alternate Protocol 1: Stratified GREML Basic Protocol 2: LDAK Alternate Protocol 2: Stratified LDAK Basic Protocol 3: Threshold GREML Basic Protocol 4: LD score (LDSC) regression Basic Protocol 5: SumHer.

Gene expression differentials driven by mass rearing and artificial selection in black soldier fly colonies

The micro-evolutionary forces that shape genetic diversity during domestication have been assessed in many plant and animal systems. However, the impact of these processes on gene expression, and consequent functional adaptation to artificial environments, remains under-investigated. In this study, whole-transcriptome dynamics associated with the early stages of domestication of the black soldier fly (BSF), Hermetia illucens, were assessed. Differential gene expression (DGE) was evaluated in relation to (i) generational time within the cultured environment (F2 vs. F3), and (ii) two selection strategies [no artificial selective pressure (NS); and selection for greater larval mass (SEL)]. RNA-seq was conducted on 5th instar BSF larvae (n = 36), representing equal proportions of the NS (F2 = 9; F3 = 9) and SEL (F2 = 9; F3 = 9) groups. A multidimensional scaling plot revealed greater gene expression variability within the NS and F2 subgroups, while the SEL group clustered separately with lower levels of variation. Comparisons between generations revealed 898 differentially expressed genes (DEGs; FDR-corrected p < 0.05), while between selection strategies, 213 DEGs were observed (FDR-corrected p < 0.05). Enrichment analyses revealed that metabolic, developmental, and defence response processes were over-expressed in the comparison between F2 and F3 larvae, while metabolic processes were the main differentiating factor between NS and SEL lines. This illustrates the functional adaptations that occur in BSF colonies across generations due to mass rearing; as well as highlighting genic dynamics associated with artificial selection for production traits that might inform future selective breeding strategies.

Adaptability of Bony Armor Elements of the Threespine Stickleback Gasterosteus aculeatus (Teleostei: Gasterosteidae): Ecological and Evolutionary Insights from Symmetry Analyses

Differentiation in the defensive armor of the threespine stickleback, Gasterosteus aculeatus, is caused by predator-driven divergent selection. Most studies considered armor traits related to swimming behavior, hence combining pre- and post-capture responses to gape-limited predators. Here, we focus exclusively on the defensive complex (DC), the post-capture predator defense. This complex consists of a series of bony elements surrounding the anterior part of the abdomen. Relaxation from predation pressure not only drives reduction of bony elements but is also expected to increase asymmetry in the DC. To test this hypothesis, we used four Austrian freshwater populations that differed distinctly in the formation of the DC. We found significant left–right asymmetries in the DC in the population with a distinctly reduced DC and, surprisingly, also in the population with a significantly enhanced DC. These populations occur in vastly different habitats (stream and lake) characterized by distinct regimes of gape-limited predators (none vs. many). Apparently, both a shift to very low and very high pressure by gape-limited predators can boost asymmetry. We conclude that greater asymmetries in the two populations at the opposite ends of the predatory gradient result from an ongoing process of adaptation to decreased or increased environmental stress.

Addressing prey naivety in native mammals by accelerating selection for antipredator traits

Harnessing natural selection to improve conservation outcomes is a recent concept in ecology and evolutionary biology and a potentially powerful tool in species conservation. One possible application is the use of natural selection to improve antipredator responses of mammal species that are threatened by predation from novel predators. We investigated whether long-term exposure of an evolutionary naïve prey species to a novel predator would lead to phenotypic changes in a suite of physical and behavioral traits. We exposed a founder population of 353 burrowing bettongs (Bettongia lesueur) to feral cats (Felis catus) over 5 years and compared the physical and behavioral traits of this population (including offspring) to a control (non-predator exposed) population. We used selection analysis to investigate whether changes in the traits of bettongs were likely due to phenotypic plasticity or natural selection. We also quantified selection in both populations before and during major population crashes caused by drought (control) and high predation pressure (predator-exposed). Results showed that predator-exposed bettongs had longer flight initiation distances, larger hind feet, and larger heads than control bettongs. Trait divergence began soon after exposure and continued to intensify over time for flight initiation distance and hind foot length relative to control bettongs. Selection analysis found indicators of selection for larger hind feet and longer head length in predator-exposed populations. Results of a common garden experiment showed that the progeny of predator-exposed bettongs had larger feet than control bettongs. Results suggest that long-term, low-level exposure of naïve prey to novel predators can drive phenotypic changes that may assist with future conservation efforts.

How development affects evolution

Natural selection acts on developmentally constructed phenotypes, but how does development affect evolution? This question prompts a simultaneous consideration of development and evolution. However, there has been a lack of general mathematical frameworks mechanistically integrating the two, which may have inhibited progress on the question. Here, we use a new mathematical framework that mechanistically integrates development into evolution to analyse how development affects evolution. We show that, while selection pushes genotypic and phenotypic evolution up the fitness landscape, development determines the admissible evolutionary pathway, such that evolutionary outcomes occur at path peaks rather than landscape peaks. Changes in development can generate path peaks, triggering genotypic or phenotypic diversification, even on constant, single-peak landscapes. Phenotypic plasticity, niche construction, extra-genetic inheritance, and developmental bias alter the evolutionary path and hence the outcome. Thus, extra-genetic inheritance can have permanent evolutionary effects by changing the developmental constraints, even if extra-genetically acquired elements are not transmitted to future generations. Selective development, whereby phenotype construction points in the adaptive direction, may induce adaptive or maladaptive evolution depending on the developmental constraints. Moreover, developmental propagation of phenotypic effects over age enables the evolution of negative senescence. Overall, we find that development plays a major evolutionary role.

Polygenic adaptation dynamics in large, finite populations

Although many phenotypic traits are determined by a large number of genetic variants, how a polygenic trait adapts in response to a change in the environment is not completely understood. In the framework of diffusion theory, we study the steady state and the adaptation dynamics of a large but finite population evolving under stabilizing selection and symmetric mutations when selection and mutation are moderately large. We find that in the stationary state, the allele frequency distribution at a locus is unimodal if its effect size is below a threshold effect and bimodal otherwise; these results are the stochastic analog of the deterministic ones where the stable allele frequency becomes bistable when the effect size exceeds a threshold. It is known that following a sudden shift in the phenotypic optimum, in an infinitely large population, selective sweeps at a large-effect locus are prevented and adaptation proceeds exclusively via subtle changes in the allele frequency; in contrast, we find that the chance of sweep is substantially enhanced in large, finite populations and the allele frequency at a large-effect locus can reach a high frequency at short times even for small shifts in the phenotypic optimum.

Assortative mating for reproductive timing affects population recruitment and resilience in a quantitative genetic model

Quantitative models that simulate the inheritance and evolution of fitness-linked traits offer a method for predicting how environmental or anthropogenic perturbations can affect the dynamics of wild populations. Random mating between individuals within populations is a key assumption of many such models used in conservation and management to predict the impacts of proposed management or conservation actions. However, recent evidence suggests that non-random mating may be underestimated in wild populations and play an important role in diversity-stability relationships. Here we introduce a novel individual-based quantitative genetic model that incorporates assortative mating for reproductive timing, a defining attribute of many aggregate breeding species. We demonstrate the utility of this framework by simulating a generalized salmonid lifecycle, varying input parameters, and comparing model outputs to theoretical expectations for several eco-evolutionary, population dynamic scenarios. Simulations with assortative mating systems resulted in more resilient and productive populations than those that were randomly mating. In accordance with established ecological and evolutionary theory, we also found that decreasing the magnitude of trait correlations, environmental variability, and strength of selection each had a positive effect on population growth. Our model is constructed in a modular framework so that future components can be easily added to address pressing issues such as the effects of supportive breeding, variable age structure, differential selection by sex or age, and fishery interactions on population growth and resilience. With code published in a public Github repository, model outputs may easily be tailored to specific study systems by parameterizing with empirically generated values from long-term ecological monitoring programs.

Selective effects of a short transient environmental fluctuation on a natural population

Natural populations experience continuous and often transient changes of environmental conditions. These in turn may result in fluctuating selection pressures leading to variable demographic and evolutionary population responses. Rapid adaptation as short-term response to a sudden environmental change has in several cases been attributed to polygenic traits, but the underlying genomic dynamics and architecture are poorly understood. In this study, we took advantage of a natural experiment in an insect population of the non-biting midge Chironomus riparius by monitoring genome-wide allele frequencies before and after a cold snap event. Whole genome pooled sequencing of time series samples revealed 10 selected haplotypes carrying ancient polymorphisms, partially with signatures of balancing selection. By constantly cold exposing genetically variable individuals in the laboratory, we could demonstrate with whole genome resequencing (i) that among the survivors, the same alleles rose in frequency as in the wild, and (ii) that the identified variants additively predicted fitness (survival time) of its bearers. Finally, by simultaneously sequencing the genome and the transcriptome of cold exposed individuals we could tentatively link some of the selected SNPs to the cis- and trans-regulation of genes and pathways known to be involved in cold response of insects, such as cytochrome P450 and fatty acid metabolism. Altogether, our results shed light on the strength and speed of selection in natural populations and the genomic architecture of its underlying polygenic trait. Population genomic time series data thus appear as promising tool for measuring the selective tracking of fluctuating selection in natural populations.

The opportunity for selection: A slippery concept in ecology and evolution

Natural selection can only occur if individuals differ in fitness. For this reason, the variance in relative fitness has been equated with the 'opportunity for selection' ( I ), which has a long, albeit somewhat controversial, history. In this paper we discuss the use/misuse of I and related metrics in evolutionary ecology. The opportunity is only realised if some fraction of I is caused by trait variation. Thus, I > 0 does not imply that selection is occurring, as sometimes erroneously assumed, because all fitness variation could be independent of phenotype. The selection intensity on any given trait cannot exceed I , but this upper limit will never be reached because (a) stochastic factors always affect fitness, and (b) there might be multiple traits under selection. The expected magnitude of the stochastic component of I is negatively correlated with mean fitness. Uncertainty in realised I is also larger when mean fitness or population/sample size are low. Variation in I across time or space thus can be dominated (or solely driven) by variation in the strength of demographic stochasticity. We illustrate these points using simulations and empirical data from a population study on great tits Parus major. Our analysis shows that the scope for fecundity selection in the great tits is substantially higher when using annual number of recruits as the fitness measure, rather than fledglings or eggs, even after adjusting for the dependence of I on mean fitness. This suggests nonrandom survival of juveniles across families between life stages. Indeed, previous work on this population has shown that offspring recruitment is often nonrandom with respect to clutch size and laying date of parents, for example. We conclude that one cannot make direct inferences about selection based on fitness data alone. However, examining variation in ∆ I F (the opportunity for fecundity selection adjusted for mean fitness) across life stages, years or environments can offer clues as to when/where fecundity selection might be strongest, which can be useful for research planning and experimental design.

Maternal effects do not resolve the paradox of stasis in birth weight in a wild red deer populaton

In natural populations, quantitative traits seldom show short-term evolution at the rate predicted by evolutionary models. Resolving this "paradox of stasis" is a key goal in evolutionary biology, as it directly challenges our capacity to predict evolutionary change. One particularly promising hypothesis to explain the lack of evolutionary responses in a key offspring trait, body weight, is that positive selection on juveniles is counterbalanced by selection against maternal investment in offspring growth, given that reproduction is costly for the mothers. Here, we used data from one of the longest individual-based studies of a wild mammal population to test this hypothesis. We first showed that despite positive directional selection on birth weight, and heritable variation for this trait, no genetic change has been observed for birth weight over the past 47 years in the study population. Contrarily to our expectation, we found no evidence of selection against maternal investment in birth weight-if anything, selection favors mothers that produce large calves. Accordingly, we show that genetic change in birth weight over the study period is actually lower than that predicted from models including selection on maternal performance; ultimately our analysis here only deepens rather than resolves the paradox of stasis.

Moving past the challenges and misconceptions in urban adaptation research

Although the field of urban evolutionary ecology has recently expanded, much progress has been made in identifying adaptations that arise as a result of selective pressures within these unique environments. However, as studies within urban environments have rapidly increased, researchers have recognized that there are challenges and opportunities in characterizing urban adaptation. Some of these challenges are a consequence of increased direct and indirect human influence, which compounds long-recognized issues with research on adaptive evolution more generally. In this perspective, we discuss several common research challenges to urban adaptation related to (1) methodological approaches, (2) trait-environment relationships and the natural history of organisms, (3) agents and targets of selection, and (4) habitat heterogeneity. Ignoring these challenges may lead to misconceptions and further impede our ability to draw conclusions regarding evolutionary and ecological processes in urban environments. Our goal is to first shed light on the conceptual challenges of conducting urban adaptation research to help avoid the propagation of these misconceptions. We further summarize potential strategies to move forward productively to construct a more comprehensive picture of urban adaptation, and discuss how urban environments also offer unique opportunities and applications for adaptation research.

Molecular Regulation and Evolution of Redox Homeostasis in Photosynthetic Machinery

The recent advances in plant biology have significantly improved our understanding of reactive oxygen species (ROS) as signaling molecules in the redox regulation of complex cellular processes. In plants, free radicals and non-radicals are prevalent intra- and inter-cellular ROS, catalyzing complex metabolic processes such as photosynthesis. Photosynthesis homeostasis is maintained by thiol-based systems and antioxidative enzymes, which belong to some of the evolutionarily conserved protein families. The molecular and biological functions of redox regulation in photosynthesis are usually to balance the electron transport chain, photosystem II, photosystem I, mesophyll and bundle sheath signaling, and photo-protection regulating plant growth and productivity. Here, we review the recent progress of ROS signaling in photosynthesis. We present a comprehensive comparative bioinformatic analysis of redox regulation in evolutionary distinct photosynthetic cells. Gene expression, phylogenies, sequence alignments, and 3D protein structures in representative algal and plant species revealed conserved key features including functional domains catalyzing oxidation and reduction reactions. We then discuss the antioxidant-related ROS signaling and important pathways for achieving homeostasis of photosynthesis. Finally, we highlight the importance of plant responses to stress cues and genetic manipulation of disturbed redox status for balanced and enhanced photosynthetic efficiency and plant productivity.

Compiling forty years of guppy research to investigate the factors contributing to (non)parallel evolution

Examples of parallel evolution have been crucial for our understanding of adaptation via natural selection. However, strong parallelism is not always observed even in seemingly similar environments where natural selection is expected to favour similar phenotypes. Leveraging this variation in parallelism within well-researched study systems can provide insight into the factors that contribute to variation in adaptive responses. Here we analyse the results of 36 studies reporting 446 average trait values in Trinidadian guppies, Poecilia reticulata, from different predation regimes. We examine how the extent of predator-driven phenotypic parallelism is influenced by six factors: sex, trait type, rearing environment, ecological complexity, evolutionary history, and time since colonization. Analyses show that parallel evolution in guppies is highly variable and weak on average, with only 24.7% of the variation among populations being explained by predation regime. Levels of parallelism appeared to be especially weak for colour traits, and parallelism decreased with increasing complexity of evolutionary history (i.e., when estimates of parallelism from populations within a single drainage were compared to estimates of parallelism from populations pooled between two major drainages). Suggestive - but not significant - trends that warrant further research include interactions between the sexes and different trait categories. Quantifying and accounting for these and other sources of variation among evolutionary 'replicates' can be leveraged to better understand the extent to which seemingly similar environments drive parallel and nonparallel aspects of phenotypic divergence.

Topographically distinct adaptive landscapes for teeth, skeletons, and size explain the adaptive radiation of Carnivora (Mammalia)

Models of adaptive radiation were originally developed to explain the early, rapid appearance of distinct modes of life within diversifying clades. Phylogenetic tests of this hypothesis have yielded limited support for temporally declining rates of phenotypic evolution across diverse clades, but the concept of an adaptive landscape that links form to fitness, while also crucial to these models, has received more limited attention. Using methods that assess the temporal accumulation of morphological variation and estimate the topography of the underlying adaptive landscape, I found evidence of an early partitioning of mandibulo-dental morphological variation in Carnivora (Mammalia) that occurs on an adaptive landscape with multiple peaks, consistent with classic ideas about adaptive radiation. Although strong support for this mode of adaptive radiation is present in traits related to diet, its signal is not present in body mass data or for traits related to locomotor behavior and substrate use. These findings suggest that adaptive radiations may occur along some axes of ecomorphological variation without leaving a signal in others and that their dynamics are more complex than simple univariate tests might suggest.

Multivariate selection and the making and breaking of mutational pleiotropy

The role of mutations have been subject to many controversies since the formation of the Modern Synthesis of evolution in the early 1940ties. Geneticists in the early half of the twentieth century tended to view mutations as a limiting factor in evolutionary change. In contrast, natural selection was largely viewed as a “sieve” whose main role was to sort out the unfit but which could not create anything novel alone. This view gradually changed with the development of mathematical population genetics theory, increased appreciation of standing genetic variation and the discovery of more complex forms of selection, including balancing selection. Short-term evolutionary responses to selection are mainly influenced by standing genetic variation, and are predictable to some degree using information about the genetic variance–covariance matrix (G) and the strength and form of selection (e. g. the vector of selection gradients, β). However, predicting long-term evolution is more challenging, and requires information about the nature and supply of novel mutations, summarized by the mutational variance–covariance matrix (M). Recently, there has been increased attention to the role of mutations in general and M in particular. Some evolutionary biologists argue that evolution is largely mutation-driven and claim that mutation bias frequently results in mutation-biased adaptation. Strong similarities between G and M have also raised questions about the non-randomness of mutations. Moreover, novel mutations are typically not isotropic in their phenotypic effects and mutational pleiotropy is common. Here I discuss the evolutionary origin and consequences of mutational pleiotropy and how multivariate selection directly shapes G and indirectly M through changed epistatic relationships. I illustrate these ideas by reviewing recent literature and models about correlational selection, evolution of G and M, sexual selection and the fitness consequences of sexual antagonism.

The short-term, genome-wide effects of indirect selection deserve study: A response to Charlesworth and Jensen (2022)

We recently published a paper quantifying the genome-wide consequences of natural selection, including the effects of indirect selection due to the correlation of genetic regions (neutral or selected) with directly selected regions (Gompert et al., 2022). In their critique of our paper, Charlesworth and Jensen (2022) make two main points: (i) indirect selection is equivalent to hitchhiking and thus well documented (i.e., our results are not novel) and (ii) that we do not demonstrate the source of linkage disequilibrium (LD) between SNPs and the Mel-Stripe locus in the Timema cristinae experiment we analyse. As we discuss in detail below, neither of these are substantial criticisms of our work.

Evolutionary interactions between thermal ecology and sexual selection

Thermal ecology and mate competition are both pervasive features of ecological adaptation. A surge of recent work has uncovered the diversity of ways in which temperature affects mating interactions and sexual selection. However, the potential for thermal biology and reproductive ecology to evolve together as organisms adapt to their thermal environment has been underappreciated. Here, we develop a series of hypotheses regarding (1) not only how thermal ecology affects mating system dynamics, but also how mating dynamics can generate selection on thermal traits; and (2) how the thermal consequences of mate competition favour the reciprocal co-adaptation of thermal biology and sexual traits. We discuss our hypotheses in the context of both pre-copulatory and post-copulatory processes. We also call for future work integrating experimental and phylogenetic comparative approaches to understand evolutionary feedbacks between thermal ecology and sexual selection. Overall, studying reciprocal feedbacks between thermal ecology and sexual selection may be necessary to understand how organisms have adapted to the environments of the past and could persist in the environments of the future.

Plasticity in female timing may explain earlier breeding in a North American songbird

Many species have shifted their breeding phenology in response to climate change. Identifying the magnitude of phenological shifts and whether climate-mediated selection drives these shifts is key for determining species' resilience to climate change. Birds are a strong model for studying phenological shifts due to numerous long-term research studies; however, generalities pertaining to drivers of phenological shifts will emerge only as we add study species that differ in life history and geography. We investigated 32 years of reproductive timing in a non-migratory population of dark-eyed juncos (Junco hyemalis). We predicted that plasticity in reproductive timing would allow females to breed earlier in warmer springs. We also predicted that selection would favour earlier breeding and asked whether the temperatures throughout the breeding season would predict the strength of selection. To test these predictions, we examined temporal changes in the annual median date for reproductive onset (i.e., first egg date) and we used a sliding window analysis to identify spring temperatures driving these patterns. Next, we explored plasticity in reproductive timing and asked whether selection favoured earlier breeding. Lastly, we used a sliding window analysis to identify the time during the breeding season that temperature was most associated with selection favouring earlier breeding. First egg dates occurred earlier over time and strongly covaried with April temperatures. Further, individual females that bred in more than one year, typically bred earlier in warmer Aprils, exhibiting plastic responses to April temperature. We also found significant overall selection favouring earlier breeding (i.e., higher relative fitness with earlier first egg dates) and variation in selection for earlier breeding over time. However, temperature across diverse climatic windows did not predict the strength of selection. Our findings provide further evidence for the role of phenotypic plasticity in shifting phenology in response to earlier springs. We also provide evidence for the role of selection favouring earlier breeding, regardless of temperature, thus setting the stage for adaptive changes in female breeding phenology. We suggest for multi-brooded birds that advancing first egg dates likely increases the length of the breeding season, and therefore, reproductive success.

Analytical results for directional and quadratic selection gradients for log-linear models of fitness functions

Log-linear models are widely used for assessing determinants of fitness in empirical studies, for example, in determining how reproductive output depends on trait values or environmental conditions. Similarly, theoretical works of fitness and natural selection employ log-linear models, often with a negative quadratic term, generating Gaussian fitness functions. However, in the specific application of regression-based analysis of natural selection, such models are rarely employed. Rather, OLS regression is the predominant means of assessing the form of natural selection. OLS regressions allow specific evolutionary quantitative parameters, selection gradients, to be estimated, and benefit from the fact that the associated statistical models are easily applied. We examine whether selection gradients can be directly expressed in terms of the coefficients of models using exponential fitness functions with linear or quadratic arguments. Such models can be easily fitted with generalized linear models (GLMs). The expressions we obtain coincide with those for Gaussian functions, but relax the major constraint that the (log) fitness function is concave (downwardly curved). Additionally these results lead to univariate and multivariate analyses of both linear and quadratic selection that potentially incorporate pragmatic and interpretable models of fitness functions, where the parameters can be related analytically to selection gradients, and that can be operationalized using widely available statistical tools.

The ontogeny of selection on genetic diversity in harvester ants

Selection may favour traits throughout an individual's lifetime or at a particular life stage. In many species of social insects, established colonies that are more genetically diverse outperform less diverse colonies with respect to a variety of traits that contribute to fitness, but whether selection favours high diversity in small colonies is unknown. We tested the hypothesis that selection favours genetically diverse colonies during the juvenile period using a multi-year field experiment with the harvester ant, Pogonomyrmex occidentalis. We used controlled matings to generate colonies that varied in genetic diversity and transplanted them into the field. We monitored their survival for seven (the 2015 cohort, n = 149) and six (the 2016 cohort, n = 157) years. Genetically more diverse colonies had greater survival, resulting in significant viability selection. However, in both cohorts survival was not influenced by genetic diversity until colonies were three years old. We suggest that changes in their internal organization enabled colonies to use the benefits of multiple genotypes, and discuss possible mechanisms that can generate this pattern.

Population differentiation of polygenic score predictions under stabilizing selection

Given the many small-effect loci uncovered by genome-wide association studies (GWAS), polygenic scores have become central to genomic medicine, and have found application in diverse settings including evolutionary studies of adaptation. Despite their promise, polygenic scores have been found to suffer from limited portability across human populations. This at first seems in conflict with the observation that most common genetic variation is shared among populations. We investigate one potential cause of this discrepancy: stabilizing selection on complex traits. Counterintuitively, while stabilizing selection constrains phenotypic evolution, it accelerates the loss and fixation of alleles underlying trait variation within populations (GWAS loci). Thus even when populations share an optimum phenotype, stabilizing selection erodes the variance contributed by their shared GWAS loci, such that predictions from GWAS in one population explain less of the phenotypic variation in another. We develop theory to quantify how stabilizing selection is expected to reduce the prediction accuracy of polygenic scores in populations not represented in GWAS samples. In addition, we find that polygenic scores can substantially overstate average genetic differences of phenotypes among populations. We emphasize stabilizing selection around a common optimum as a useful null model to connect patterns of allele frequency and polygenic score differentiation. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Decomposing phenotypic skew and its effects on the predicted response to strong selection

The major frameworks for predicting evolutionary change assume that a phenotype's underlying genetic and environmental components are normally distributed. However, the predictions of these frameworks may no longer hold if distributions are skewed. Despite this, phenotypic skew has never been decomposed, meaning the fundamental assumptions of quantitative genetics remain untested. Here we demonstrate that the substantial phenotypic skew in the body size of juvenile blue tits (Cyanistes caeruleus) is driven by environmental factors. Although skew had little impact on our predictions of selection response in this case, our results highlight the impact of skew on the estimation of inheritance and selection. Specifically, the nonlinear parent-offspring regressions induced by skew, alongside selective disappearance, can strongly bias estimates of heritability. The ubiquity of skew and strong directional selection on juvenile body size imply that heritability is commonly overestimated, which may in part explain the discrepancy between predicted and observed trait evolution.