Correlational selection in the age of genomics

Interspecific selection in a diverse mycorrhizal symbiosis

Coevolution describes evolutionary change in which two or more interacting species reciprocally drive each other's evolution, potentially resulting in trait diversification and ecological speciation. Much progress has been made in analysis of its dynamics and consequences, but relatively little is understood about how coevolution works in multispecies interactions, i.e., those with diverse suites of species on one or both sides of an interaction. Interactions among plant hosts and their mutualistic ectomycorrhizal fungi (ECM) may provide an ecologically unique arena to examine the nature of selection in multispecies interactions. Using native genotypes of Monterey pine (Pinus radiata), we performed a common garden experiment at a field site that contains native stands to investigate selection from ECM fungi on pine traits. We planted seedlings from all five native populations, as well as inter-population crosses to represent intermediate phenotypes/genotypes, and measured seedling traits and ECM fungal traits to evaluate the potential for evolution in the symbiosis. We then combined field estimates of selection gradients with estimates of heritability and genetic variance-covariance matrices for multiple traits of the mutualism to determine which fungal traits drive plant fitness variation. We found evidence that certain fungal operational taxonomic units, families and species-level morphological traits by which ECM fungi acquire and transport nutrients exert selection on plant traits related to growth and allocation patterns. This work represents the first field-based, community-level study measuring multispecific coevolutionary selection in nutritional symbioses.

Rapid evolutionary change in trait correlations of single proteins

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability - the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem. We show that correlations between these traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a protein's ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

The genomic basis of nitrogen utilization efficiency and trait plasticity to improve nutrient stress tolerance in cultivated sunflower

Maintaining crop productivity is challenging as population growth, climate change, and increasing fertilizer costs necessitate expanding crop production to poorer lands whilst reducing inputs. Enhancing crops' nutrient use efficiency is thus an important goal, but requires a better understanding of related traits and their genetic basis. We investigated variation in low nutrient stress tolerance in a diverse panel of cultivated sunflower genotypes grown under high and low nutrient conditions, assessing relative growth rate (RGR) as performance. We assessed variation in traits related to nitrogen utilization efficiency (NUtE), mass allocation, and leaf elemental content. Across genotypes, nutrient limitation generally reduced RGR. Moreover, there was a negative correlation between vigor (RGR in control) and decline in RGR in response to stress. Given this trade-off, we focused on nutrient stress tolerance independent of vigor. This tolerance metric correlated with the change in NUtE, plasticity for a suite of morphological traits, and leaf element content. Genome-wide associations revealed regions associated with variation and plasticity in multiple traits, including two regions with seemingly additive effects on NUtE change. Our results demonstrate potential avenues for improving sunflower nutrient stress tolerance independent of vigor, and highlight specific traits and genomic regions that could play a role in enhancing tolerance.

Knocking down GRAMD1C expression reduces 6-OHDA-induced apoptosis in PC12 cells

Aim

To explore the differential genes in Parkinson's disease (PD) through a preliminary GEO database, and to investigate the possible mechanisms.

Materials and Methods

The PD differentially expressed genes (DEGs) were analyzed by the microarray method. Then, these DEGs were applied to KEGG and GO analyses to predict the related signaling pathways and molecular functions. Comparison of GRAMD1C expression levels in the putamen of normal and Parkinson's patients by bioinformatic analysis. PC12 cells were cultured to construct a 6-hydroxydopamine (6-OHDA)-induced Parkinson's cell model. RT-qPCR was performed to detect the efficiency of GRAMD1C siRNA. MTT assay was conducted to examine the proliferation of cells. Then, the apoptosis of each group of cells was measured by flow cytometry. Western blot was carried out to determine the expression of apoptosis-related proteins.

Results

Through bioinformatics, GRAMD1C was confirmed to be one of the most significantly upregulated genes in PD. Furthermore, GRAMD1C was notably enhanced in the PD patients and 6-OHDA-induced PC12 cells. Besides, 6-OHDA stimulation significantly reduced PC12 cell proliferation, and it reverted with the GRAMD1C siRNA. Moreover, the flow cytometry results showed that knockdown of GRAMD1C could effectively reduce the high apoptosis rate of PC12 cells induced by 6-OHDA treatment. Similarly, western blot results found that 6-OHDA stimulation markedly increased the expression levels of Bax and Caspase 3Caspase 3 and decreased the Bcl-2 expression in PC12 cells, and GRAMD1C knockdown reversed these changes.

Conclusion

GRAMD1C is upregulated in PD, and may affect the PD process through the apoptotic pathway.

Genetic structure, UV-vision, wing coloration and size coincide with colour polymorphism in Fabriciana adippe butterflies

Colour polymorphisms have long served as model systems in evolutionary studies and continue to inform about processes involved in the origin and dynamics of biodiversity. Modern sequencing tools allow for evaluating whether phenotypic differences between morphs reflect genetic differentiation rather than developmental plasticity, and for investigating whether polymorphisms represent intermediate stages of diversification towards speciation. We investigated phenotypic and genetic differentiation between two colour morphs of the butterfly Fabriciana adippe using a combination of ddRAD-sequencing and comparisons of body size, colour patterns and optical properties of bright wing spots. The silvery-spotted adippe form had larger and darker wings and reflected UV light, while the yellow cleodoxa form displayed more green scales and reflected very little UV, showcasing that they constitute distinct and alternative integrated phenotypes. Genomic analyses revealed genetic structuring according to source population, and to colour morph, suggesting that the phenotypic differentiation reflects evolutionary modifications. We report 17 outlier loci associated with colour morph, including ultraviolet-sensitive visual pigment (UVRh1), which is associated with intraspecific communication and mate choice in butterflies. Together with the demonstration that the wings of the adippe (but essentially not the cleodoxa) morph reflect UV light, that UV reflectance is higher in females than males and that morphs differ in wing size, this suggests that these colour morphs might represent genetically integrated phenotypes, possibly adapted to different microhabitats. We propose that non-random mating might contribute to the differentiation and maintenance of the polymorphism.

The genomic consequences of selection across development

Understanding how natural selection drives diversification in nature has been at the forefront of biological research for over a century. The main idea is simple: natural selection favours individuals best suited to pass on their genes. However, the journey from birth to reproduction is complex as organisms experience multiple developmental stages, each influenced by genetic and environmental factors (Orr, 2009). These complexities compound even further as each stage of development might be governed by a unique underlying set of alleles and genes. In this issue of Molecular Ecology, Goebl et al. (2022) examine the role of natural selection in driving ecotypic divergence across different life history stages of the prairie sunflower Helianthus petiolaris. The authors used reciprocal transplant experiments, demographic models, and genomic sequencing to explore fitness variation across developmental stages. They show how natural selection impacts population divergence across multiple life history stages and evaluate the resulting allele frequency changes. Goebl et al. link these results to the role of chromosomal inversions, thus furthering our understanding of how ecological divergence proceeds in the face of gene flow. Below, we explore these results in detail and complement their interpretation by considering the evolution of genetic correlations amongst traits governing fitness.

Personality traits differentially affect components of reproductive success in a Neotropical poison frog

Individual reproductive success has several components, including the acquisition of mating partners, offspring production, and offspring survival until adulthood. While the effects of certain personality traits-such as boldness or aggressiveness-on single components of reproductive success are well studied, we know little about the composite and multifaceted effects behavioural traits can have on all the aspects of reproductive success. Behavioural traits positively linked to one component of reproductive success might not be beneficial for other components, and these effects may differ between sexes. We investigated the influence of boldness, aggressiveness, and exploration on the number of mating partners, mating events, and offspring surviving until adulthood in males and females of the Neotropical poison frog Allobates femoralis. Behavioural traits had different-even opposite-effects on distinct components of reproductive success in both males and females. For example, males who displayed high levels of aggressiveness and exploration (or low levels of aggressiveness and exploration) managed to attract high number of mating partners, while males with low levels of boldness, low levels of aggressiveness, and high levels of exploration had the most offspring surviving until adulthood. Our results therefore suggest correlational selection favouring particular combinations of behavioural traits.

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.

Predicting the future

Experiments on worms suggest that a statistical measure called the G matrix can accurately predict how phenotypes will adapt to a novel environment over multiple generations.

Selection and the direction of phenotypic evolution

Predicting adaptive phenotypic evolution depends on invariable selection gradients and on the stability of the genetic covariances between the component traits of the multivariate phenotype. We describe the evolution of six traits of locomotion behavior and body size in the nematode Caenorhabditis elegans for 50 generations of adaptation to a novel environment. We show that the direction of adaptive multivariate phenotypic evolution can be predicted from the ancestral selection differentials, particularly when the traits were measured in the new environment. Interestingly, the evolution of individual traits does not always occur in the direction of selection, nor are trait responses to selection always homogeneous among replicate populations. These observations are explained because the phenotypic dimension with most of the ancestral standing genetic variation only partially aligns with the phenotypic dimension under directional selection. These findings validate selection theory and suggest that the direction of multivariate adaptive phenotypic evolution is predictable for tens of generations.

Interaction between mutation type and gene pleiotropy drives parallel evolution in the laboratory

What causes evolution to be repeatable is a fundamental question in evolutionary biology. Pleiotropy, i.e. the effect of an allele on multiple traits, is thought to enhance repeatability by constraining the number of available beneficial mutations. Additionally, pleiotropy may promote repeatability by allowing large fitness benefits of single mutations via adaptive combinations of phenotypic effects. Yet, this latter evolutionary potential may be reaped solely by specific types of mutations able to realize optimal combinations of phenotypic effects while avoiding the costs of pleiotropy. Here, we address the interaction of gene pleiotropy and mutation type on evolutionary repeatability in a meta-analysis of experimental evolution studies with Escherichia coli. We hypothesize that single nucleotide polymorphisms (SNPs) are principally able to yield large fitness benefits by targeting highly pleiotropic genes, whereas indels and structural variants (SVs) provide smaller benefits and are restricted to genes with lower pleiotropy. By using gene connectivity as proxy for pleiotropy, we show that non-disruptive SNPs in highly pleiotropic genes yield the largest fitness benefits, since they contribute more to parallel evolution, especially in large populations, than inactivating SNPs, indels and SVs. Our findings underscore the importance of considering genetic architecture together with mutation type for understanding evolutionary repeatability. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Eco-Evolutionary Consequences of Dispersal Syndromes during Colonization in a Passerine Bird

AbstractIn most animal species, dispersing individuals possess phenotypic attributes that mitigate the costs of colonization and/or increase settlement success in new areas (dispersal syndromes). This phenotypic integration likely affects population dynamics and the direction of selection, but data are lacking for natural populations. Using an approach that combines population dynamics, quantitative genetics, and phenotypic selection analyses, we reveal the existence of dispersal syndromes in a pied flycatcher (Ficedula hypoleuca) population in the Netherlands: immigrants were larger, tended to have darker plumage, bred earlier, and produced larger clutches than local recruits, and some of these traits were genetically correlated. Over time, the phenotypic profile of the population gradually changed: each generation advanced arrival and breeding and exhibited longer wings as a result of direct and indirect selection on these correlated traits. Although phenotypic attributes of immigrants were favored by selection during the early phase of colonization, observed phenotypic changes were similar for immigrants and local recruits. We propose that immigrants facilitated initial population establishment but that temporal changes likely resulted from climate change-induced large-scale selection. This study highlights that newly established populations are of nonrandom composition and that phenotypic architecture affects evolutionary population trajectories.

Strong evidence for positive and negative correlational selection revealed by recreating ancestral variation

The study of adaptation helps explain biodiversity and predict future evolution. Yet the process of adaptation can be difficult to observe due to limited phenotypic variation in contemporary populations. Furthermore, the scarcity of male fitness estimates has made it difficult to both understand adaptation and evaluate sexual conflict hypotheses. We addressed both issues in our study of two anther position traits in wild radish (Raphanus raphanistrum): anther exsertion (long filament - corolla tube lengths) and anther separation (long - short filament lengths). These traits affect pollination efficiency and are particularly interesting due to the unusually high correlations among their component traits. We measured selection through male and female fitness on wild radish plants from populations artificially selected to recreate ancestral variation in each anther trait. We found little evidence for conflicts between male and female function. We found strong evidence for stabilizing selection on anther exsertion and disruptive selection on anther separation, indicating positive and negative correlational selection on the component traits. Intermediate levels of exsertion are likely an adaptation to best contact small bees. The function of anther separation is less clear, but future studies might investigate pollen placement on pollinators and compare species possessing multiple stamen types.

Genetic architecture of multiple mutualisms and mating system in Turnera ulmifolia

Plants often associate with multiple arthropod mutualists. These partners provide important services to their hosts, but multiple interactions can constrain a plant's ability to respond to complex, multivariate selection. Here, we quantified patterns of genetic variance and covariance among rewards for pollination, biotic defence and seed dispersal mutualisms in multiple populations of Turnera ulmifolia to better understand how the genetic architecture of multiple mutualisms might influence their evolution. We phenotyped plants cultivated from 17 Jamaican populations for several mutualism and mating system-related traits. We then fit genetic variance-covariance (G) matrices for the island metapopulation and the five largest individual populations. At the metapopulation level, we observed significant positive genetic correlations among stigma-anther separation, floral nectar production and extrafloral nectar production. These correlations have the potential to significantly constrain or facilitate the evolution of multiple mutualisms in T. ulmifolia and suggest that pollination, seed dispersal and defence mutualisms do not evolve independently. In particular, we found that positive genetic correlations between floral and extrafloral nectar production may help explain their stable coexistence in the face of physiological trade-offs and negative interactions between pollinators and ant bodyguards. Locally, we found only small differences in G among our T. ulmifolia populations, suggesting that geographic variation in G may not shape the evolution of multiple mutualisms.

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

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.

Sexual repurposing of juvenile aposematism in locusts

The same signal can convey different information across an animal’s lifetime. High-density desert locusts avoid predation as juveniles by exhibiting striking warning coloration, which honestly advertises their unpalatability relative to their camouflaged, low-density conspecifics. Here, we show that by reusing their youthful “don’t touch me” yellow color upon sexual maturation, high-density adult male locusts also advertise unprofitability, but in this case to fellow amorous males. This three-way (developmental stage, population density, sex) control of a single carotenoid-binding protein toward multiple adaptive outcomes makes it an exciting model system for unravelling the molecular evolution of an animal signal.

Adaptive plasticity requires an integrated suite of functional responses to environmental variation, which can include social communication across life stages. Desert locusts (Schistocerca gregaria) exhibit an extreme example of phenotypic plasticity called phase polyphenism, in which a suite of behavioral and morphological traits differ according to local population density. Male and female juveniles developing at low population densities exhibit green- or sand-colored background-matching camouflage, while at high densities they show contrasting yellow and black aposematic patterning that deters predators. The predominant background colors of these phenotypes (green/sand/yellow) all depend on expression of the carotenoid-binding “Yellow Protein” (YP). Gregarious (high-density) adults of both sexes are initially pinkish, before a YP-mediated yellowing reoccurs upon sexual maturation. Yellow color is especially prominent in gregarious males, but the reason for this difference has been unknown since phase polyphenism was first described in 1921. Here, we use RNA interference to show that gregarious male yellowing acts as an intrasexual warning signal, which forms a multimodal signal with the antiaphrodisiac pheromone phenylacetonitrile (PAN) to prevent mistaken sexual harassment from other males during scramble mating in a swarm. Socially mediated reexpression of YP thus adaptively repurposes a juvenile signal that deters predators into an adult signal that deters undesirable mates. These findings reveal a previously underappreciated sexual dimension to locust phase polyphenism, and promote locusts as a model for investigating the relative contributions of natural versus sexual selection in the evolution of phenotypic plasticity.

White Paper: An Integrated Perspective on the Causes of Hypometric Metabolic Scaling in Animals

Larger animals studied during ontogeny, across populations, or across species, usually have lower mass-specific metabolic rates than smaller animals (hypometric scaling). This pattern is usually observed regardless of physiological state (e.g. basal, resting, field, maximally-active). The scaling of metabolism is usually highly correlated with the scaling of many life history traits, behaviors, physiological variables, and cellular/molecular properties, making determination of the causation of this pattern challenging. For across-species comparisons of resting and locomoting animals (but less so for across populations or during ontogeny), the mechanisms at the physiological and cellular level are becoming clear. Lower mass-specific metabolic rates of larger species at rest are due to a) lower contents of expensive tissues (brains, liver, kidneys), and b) slower ion leak across membranes at least partially due to membrane composition, with lower ion pump ATPase activities. Lower mass-specific costs of larger species during locomotion are due to lower costs for lower-frequency muscle activity, with slower myosin and Ca++ ATPase activities, and likely more elastic energy storage. The evolutionary explanation(s) for hypometric scaling remain(s) highly controversial. One subset of evolutionary hypotheses relies on constraints on larger animals due to changes in geometry with size; for example, lower surface-to-volume ratios of exchange surfaces may constrain nutrient or heat exchange, or lower cross-sectional areas of muscles and tendons relative to body mass ratios would make larger animals more fragile without compensation. Another subset of hypotheses suggests that hypometric scaling arises from biotic interactions and correlated selection, with larger animals experiencing less selection for mass-specific growth or neurolocomotor performance. A additional third type of explanation comes from population genetics. Larger animals with their lower effective population sizes and subsequent less effective selection relative to drift may have more deleterious mutations, reducing maximal performance and metabolic rates. Resolving the evolutionary explanation for the hypometric scaling of metabolism and associated variables is a major challenge for organismal and evolutionary biology. To aid progress, we identify some variation in terminology use that has impeded cross-field conversations on scaling. We also suggest that promising directions for the field to move forward include: 1) studies examining the linkages between ontogenetic, population-level, and cross-species allometries, 2) studies linking scaling to ecological or phylogenetic context, 3) studies that consider multiple, possibly interacting hypotheses, and 4) obtaining better field data for metabolic rates and the life history correlates of metabolic rate such as lifespan, growth rate and reproduction.

Where do we stand with the covariation framework in primate societies?

Comparative study of the social systems of macaques has revealed correlated variations between species in multiple social traits such as the asymmetry of dominance relationships, preferential treatment of kin, patterns of aggression and reconciliation, modes of socialization, and access to food resources. Macaques can be classified on a scale of four categories of social styles, ranging from the least to the most tolerant species. This led to the development of the covariation framework, which addresses the constraints responsible for the linkages between social traits, and their consequences on the evolution of primate social systems. Decades of research have provided a wealth of information that supports, complements, expands, or challenges the covariation framework. In this article, I review this body of knowledge and consider covariation in its two aspects, that is, as a pattern and as a hypothesis. I first consider the extent to which social styles can be invariant, the strength of correlations between traits, and the possible extension of the framework to nonhuman primates other than macaques. I then discuss how to formulate hypotheses, identify sources of linkage between traits, make predictions about the effects of social constraints, assess the tolerance dimension of social styles, and consider the breaking of linkages between traits. Whereas socioecological studies aim to understand how adaptation to the ecological environment determines the shape of social systems, the covariation framework is a complementary research program that seeks to unravel the internal processes that restrict or channel change in social behavior.

Beyond genotype-phenotype maps: Toward a phenotype-centered perspective on evolution

Evolutionary biology is paying increasing attention to the mechanisms that enable phenotypic plasticity, evolvability, and extra-genetic inheritance. Yet, there is a concern that these phenomena remain insufficiently integrated within evolutionary theory. Understanding their evolutionary implications would require focusing on phenotypes and their variation, but this does not always fit well with the prevalent genetic representation of evolution that screens off developmental mechanisms. Here, we instead use development as a starting point, and represent it in a way that allows genetic, environmental and epigenetic sources of phenotypic variation to be independent. We show why this representation helps to understand the evolutionary consequences of both genetic and non-genetic phenotype determinants, and discuss how this approach can instigate future areas of empirical and theoretical research.

Genomic changes underlying repeated niche shifts in an adaptive radiation

In adaptive radiations, single lineages rapidly diversify by adapting to many new niches. Little is known yet about the genomic mechanisms involved, that is, the source of genetic variation or genomic architecture facilitating or constraining adaptive radiation. Here, we investigate genomic changes associated with repeated invasion of many different freshwater niches by threespine stickleback in the Haida Gwaii archipelago, Canada, by resequencing single genomes from one marine and 28 freshwater populations. We find 89 likely targets of parallel selection in the genome that are enriched for old standing genetic variation. In contrast to theoretical expectations, their genomic architecture is highly dispersed with little clustering. Candidate genes and genotype-environment correlations match the three major environmental axes predation regime, light environment, and ecosystem size. In a niche space with these three dimensions, we find that the more divergent a new niche from the ancestral marine habitat, the more loci show signatures of parallel selection. Our findings suggest that the genomic architecture of parallel adaptation in adaptive radiation depends on the steepness of ecological gradients and the dimensionality of the niche space.

Evolutionary trade-offs between heat and cold tolerance limit responses to fluctuating climates

The evolutionary potential of species to cope with short-term temperature fluctuations during reproduction is critical to predicting responses to future climate change. Despite this, vertebrate research has focused on reproduction under high or low temperatures in relatively stable temperate climates. Here, we characterize the genetic basis of reproductive thermal tolerance to temperature fluctuations in the ostrich, which lives in variable environments in tropical and subtropical Africa. Both heat and cold tolerance were under selection and heritable, indicating the potential for evolutionary responses to mean temperature change. However, we found evidence for a negative, genetic correlation between heat and cold tolerance that should limit the potential for adaptation to fluctuating temperatures. Genetic constraints between heat and cold tolerance appear a crucial, yet underappreciated, factor influencing responses to climate change.

The influence of genetic architecture on responses to selection under drought in rice

Accurately predicting responses to selection is a major goal in biology and important for successful crop breeding in changing environments. However, evolutionary responses to selection can be constrained by such factors as genetic and cross‐environment correlations, linkage, and pleiotropy, and our understanding of the extent and impact of such constraints is still developing. Here, we conducted a field experiment to investigate potential constraints to selection for drought resistance in rice (Oryza sativa) using phenotypic selection analysis and quantitative genetics. We found that traits related to drought response were heritable, and some were under selection, including selection for earlier flowering, which could allow drought escape. However, patterns of selection generally were not opposite under wet and dry conditions, and we did not find individual or closely linked genes that influenced multiple traits, indicating a lack of evidence that antagonistic pleiotropy, linkage, or cross‐environment correlations would constrain selection for drought resistance. In most cases, genetic correlations had little influence on responses to selection, with direct and indirect selection largely congruent. The exception to this was seed mass under drought, which was predicted to evolve in the opposite direction of direct selection due to correlations. Because of this indirect effect on selection on seed mass, selection for drought resistance was not accompanied by a decrease in seed mass, and yield increased with fecundity. Furthermore, breeding lines with high fitness and yield under drought also had high fitness and yield under wet conditions, indicating that there was no evidence for a yield penalty on drought resistance. We found multiple genes in which expression influenced both water use efficiency (WUE) and days to first flowering, supporting a genetic basis for the trade‐off between drought escape and avoidance strategies. Together, these results can provide helpful guidance for understanding and managing evolutionary constraints and breeding stress‐resistant crops.

Experimental evolution of a pheromone signal

Sexual signals are important in speciation, but understanding their evolution is complex as these signals are often composed of multiple, genetically interdependent components. To understand how signals evolve, we thus need to consider selection responses in multiple components and account for the genetic correlations among components. One intriguing possibility is that selection changes the genetic covariance structure of a multicomponent signal in a way that facilitates a response to selection. However, this hypothesis remains largely untested empirically. In this study, we investigate the evolutionary response of the multicomponent female sex pheromone blend of the moth Heliothis subflexa to 10 generations of artificial selection. We observed a selection response of about three‐quarters of a phenotypic standard deviation in the components under selection. Interestingly, other pheromone components that are biochemically and genetically linked to the components under selection did not change. We also found that after the onset of selection, the genetic covariance structure diverged, resulting in the disassociation of components under selection and components not under selection across the first two genetic principle components. Our findings provide rare empirical support for an intriguing mechanism by which a sexual signal can respond to selection without possible constraints from indirect selection responses.

Allometric conservatism in the evolution of bird beaks

Evolution can involve periods of rapid divergent adaptation and expansion in the range of diversity, but evolution can also be relatively conservative over certain timescales due to functional, genetic‐developmental, and ecological constraints. One way in which evolution may be conservative is in terms of allometry, the scaling relationship between the traits of organisms and body size. Here, we investigate patterns of allometric conservatism in the evolution of bird beaks with beak size and body size data for a representative sample of over 5000 extant bird species within a phylogenetic framework. We identify clades in which the allometric relationship between beak size and body size has remained relatively conserved across species over millions to tens of millions of years. We find that allometric conservatism is nonetheless punctuated by occasional shifts in the slopes and intercepts of allometric relationships. A steady accumulation of such shifts through time has given rise to the tremendous diversity of beak size relative to body size across birds today. Our findings are consistent with the Simpsonian vision of macroevolution, with evolutionary conservatism being the rule but with occasional shifts to new adaptive zones.

Detecting patterns of correlational selection with sampling error: A simulation study

The adoption of a multivariate perspective of selection implies the existence of multivariate adaptive peaks and pervasive correlational selection that promotes co-adaptation between traits. However, to test for the ubiquity of correlational selection in nature, we must first have a sense of how well can we estimate multivariate nonlinear selection (i.e., the γ-matrix) in the face of sampling error. To explore the sampling properties of estimated γ-matrices, we simulated inidividual traits and fitness under a wide range of sample sizes, using different strengths of correlational selection and of stabilizing selection, combined with different number of traits under selection, different amounts of residual variance in fitness, and distinct patterns of selection. We then ran nonlinear regressions with these simulated datasets to simulate γ-matrices after adding random error to individual fitness. To test how well could we detect the imposed pattern of correlational selection at different sample sizes, we measured the similarity between simulated and imposed γ-matrices. We show that detection of the pattern of correlational selection is highly dependent on the total strength of selection on traits and on the amount of residual variance in fitness. Minimum sample size needs to be at least 500 to precisely estimate the pattern of correlational selection. Furthermore, a pattern of selection in which different sets of traits contribute to different functions is the easiest to diagnose, even when using a large number of traits (10 traits), but with sample sizes in the order of 1000 individuals. Consequently, we recommend working with sets of traits from distinct functional complexes and fitness proxies less prone to effects of environmental and demographic stochasticity to test for correlational selection with lower sample sizes.

The genetic basis of the root economics spectrum in a perennial grass

Construction economics of plant roots exhibit predictable relationships with root growth, death, and nutrient uptake strategies. Plant taxa with inexpensively constructed roots tend to more precisely explore nutrient hotspots than do those with costly constructed roots but at the price of more frequent tissue turnover. This trade-off underlies an acquisitive to conservative continuum in resource investment, described as the "root economics spectrum (RES)." Yet the adaptive role and genetic basis of RES remain largely unclear. Different ecotypes of switchgrass (Panicum virgatum) display root features exemplifying the RES, with costly constructed roots in southern lowland and inexpensively constructed roots in northern upland ecotypes. We used an outbred genetic mapping population derived from lowland and upland switchgrass ecotypes to examine the genetic architecture of the RES. We found that absorptive roots (distal first and second orders) were often "deciduous" in winter. The percentage of overwintering absorptive roots was decreased by northern upland alleles compared with southern lowland alleles, suggesting a locally-adapted conservative strategy in warmer and acquisitive strategy in colder regions. Relative turnover of absorptive roots was genetically negatively correlated with their biomass investment per unit root length, suggesting that the key trade-off in framing RES is genetically facilitated. We also detected strong genetic correlations among root morphology, root productivity, and shoot size. Overall, our results reveal the genetic architecture of multiple traits that likely impacts the evolution of RES and plant aboveground-belowground organization. In practice, we provide genetic evidence that increasing switchgrass yield for bioenergy does not directly conflict with enhancing its root-derived carbon sequestration.

Multidimensional divergent selection, local adaptation, and speciation

Divergent selection applied to one or more traits drives local adaptation and may lead to ecological speciation. Divergent selection on many traits might be termed "multidimensional" divergent selection. There is a commonly held view that multidimensional divergent selection is likely to promote local adaptation and speciation to a greater extent than unidimensional divergent selection. We disentangle the core concepts underlying dimensionality as a property of the environment, phenotypes, and genome. In particular, we identify a need to separate the overall strength of selection and the number of loci affected from dimensionality per se, and to distinguish divergence dimensionality from dimensionality of stabilizing selection. We then critically scrutinize this commonly held view that multidimensional selection promotes speciation, re-examining the evidence base from theory, experiments, and nature. We conclude that the evidence base is currently weak and generally suffers from confounding of possible causal effects. Finally, we propose several mechanisms by which multidimensional divergent selection and related processes might influence divergence, both as a driver and as a barrier.

Epithelial Cell Transformation and Senescence as Indicators of Genome Aging: Current Advances and Unanswered Questions

The recent advances in deciphering the human genome allow us to understand and evaluate the mechanisms of human genome age-associated transformations, which are largely unclear. Genome sequencing techniques assure comprehensive mapping of human genetics; however, understanding of gene functional interactions, specifically of time/age-dependent modifications, remain challenging. The age of the genome is defined by the sum of individual (inherited) and acquired genomic traits, based on internal and external factors that impact ontogenesis from the moment of egg fertilization and embryonic development. The biological part of genomic age opens a new perspective for intervention. The discovery of single cell-based mechanisms for genetic change indicates the possibility of influencing aging and associated disease burden, as well as metabolism. Cell populations with transformed genetic background were shown to serve as the origin of common diseases during extended life expectancy (superaging). Consequently, age-related cell transformation leads to cancer and cell degeneration (senescence). This article aims to describe current advances in the genomic mechanisms of senescence and its role in the spatiotemporal spread of epithelial clones and cell evolution.

Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology

For centuries, ecologists and evolutionary biologists have used images such as drawings, paintings and photographs to record and quantify the shapes and patterns of life. With the advent of digital imaging, biologists continue to collect image data at an ever-increasing rate. This immense body of data provides insight into a wide range of biological phenomena, including phenotypic diversity, population dynamics, mechanisms of divergence and adaptation, and evolutionary change. However, the rate of image acquisition frequently outpaces our capacity to manually extract meaningful information from images. Moreover, manual image analysis is low-throughput, difficult to reproduce, and typically measures only a few traits at a time. This has proven to be an impediment to the growing field of phenomics – the study of many phenotypic dimensions together. Computer vision (CV), the automated extraction and processing of information from digital images, provides the opportunity to alleviate this longstanding analytical bottleneck. In this review, we illustrate the capabilities of CV as an efficient and comprehensive method to collect phenomic data in ecological and evolutionary research. First, we briefly review phenomics, arguing that ecologists and evolutionary biologists can effectively capture phenomic-level data by taking pictures and analyzing them using CV. Next we describe the primary types of image-based data, review CV approaches for extracting them (including techniques that entail machine learning and others that do not), and identify the most common hurdles and pitfalls. Finally, we highlight recent successful implementations and promising future applications of CV in the study of phenotypes. In anticipation that CV will become a basic component of the biologist’s toolkit, our review is intended as an entry point for ecologists and evolutionary biologists that are interested in extracting phenotypic information from digital images.