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Phenotypic plasticity, if adaptive, may allow species to counter the detrimental effects of extreme conditions, but the infrequent occurrence of extreme environments and/or their restriction to low-quality habitats within a species range means that they exert little direct selection on reaction norms. Plasticity could, therefore, be maladaptive under extreme environments, unless genetic correlations are strong between extreme and non-extreme environmental states, and the optimum phenotype changes smoothly with the environment. Empirical evidence suggests that populations and species from more variable environments show higher levels of plasticity that might preadapt them to extremes, but genetic variance for plastic responses can also be low, and genetic variation may not be expressed for some classes of traits under extreme conditions. Much of the empirical literature on plastic responses to extremes has not yet been linked to ecologically relevant conditions, such as asymmetrical fluctuations in the case of temperature extremes. Nevertheless, evolved plastic responses are likely to be important for natural and agricultural species increasingly exposed to climate extremes, and there is an urgent need to collect empirical information and link this to model predictions. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events'.

Genetic correlations between traits can concentrate genetic variance into fewer phenotypic dimensions that can bias evolutionary trajectories along the axis of greatest genetic variance and away from optimal phenotypes, constraining the rate of evolution. If genetic correlations limit adaptation, rapid adaptive divergence between multiple contrasting environments may be difficult. However, if natural selection increases the frequency of rare alleles after colonization of new environments, an increase in genetic variance in the direction of selection can accelerate adaptive divergence. Here, we explored adaptive divergence of an Australian native wildflower by examining the alignment between divergence in phenotype mean and divergence in genetic variance among four contrasting ecotypes. We found divergence in mean multivariate phenotype along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with much of the divergence in phenotype among ecotypes associated with changes in trait combinations containing substantial levels of genetic variance. Overall, our results suggest that natural selection can alter the distribution of genetic variance underlying phenotypic traits, increasing the amount of genetic variance in the direction of natural selection and potentially facilitating rapid adaptive divergence during an adaptive radiation.

Some genes have repeatedly been found to control diverse adaptations in a wide variety of organisms. Such gene reuse reveals not only the diversity of phenotypes these unique genes control but also the composition of developmental gene networks and the genetic routes available to and taken by organisms during adaptation. However, the causes of gene reuse remain unclear. A small number of large-effect Mendelian loci control a huge diversity of mimetic butterfly wing color patterns, but reasons for their reuse are difficult to identify because the genetic basis of mimicry has primarily been studied in two systems with correlated factors: female-limited Batesian mimicry in Papilio swallowtails (Papilionidae) and non-sex-limited Müllerian mimicry in Heliconius longwings (Nymphalidae). Here, we break the correlation between phylogenetic relationship and sex-limited mimicry by identifying loci controlling female-limited mimicry polymorphism Hypolimnas misippus (Nymphalidae) and non-sex-limited mimicry polymorphism in Papilio clytia (Papilionidae). The Papilio clytia polymorphism is controlled by the genome region containing the gene cortex, the classic P supergene in Heliconius numata, and loci controlling color pattern variation across Lepidoptera. In contrast, female-limited mimicry polymorphism in Hypolimnas misippus is associated with a locus not previously implicated in color patterning. Thus, although many species repeatedly converged on cortex and its neighboring genes over 120 My of evolution of diverse color patterns, female-limited mimicry polymorphisms each evolved using a different gene. Our results support conclusions that gene reuse occurs mainly within ∼10 My and highlight the puzzling diversity of genes controlling seemingly complex female-limited mimicry polymorphisms.

Evolutionary biology has struggled to explain the coexistence of two basic observations: Genetic variation is found in almost all traits in the presence of strong natural and sexual selection in natural populations. These two observations are in direct conflict as such selection should deplete genetic variation. Furthermore, the presence of genetic variation in a trait, and selection acting on that trait, is often not sufficient for the trait to respond to selection. Here, we bring together geometric perspectives on mutation, selection, and genetic variation and show how the perceived incompatibility between these two observations is a consequence of taking a trait-by-trait approach to the multivariate problem of genetic variation and selection. We conclude that the simultaneous presence of widespead genetic variation in, and strong selection on, individual traits indicates that substantial multivariate genetic constraints are likely to be present in natural populations.

Males and females share most of their genomes, and differences between the sexes can therefore not evolve through sequence divergence in protein coding genes. Sexual dimorphism is instead restricted to occur through sex-specific expression and splicing of gene products. Evolution of sexual dimorphism through these mechanisms should, however, also be constrained when the sexes share the genetic architecture for regulation of gene expression. Despite these obstacles, sexual dimorphism is prevalent in the animal kingdom and commonly evolves rapidly. Here, we ask whether the genetic architecture of gene expression is plastic and easily molded by sex-specific selection, or if sexual dimorphism evolves rapidly despite pervasive genetic constraint. To address this question, we explore the relationship between the intersexual genetic correlation for gene expression (rMF), which captures how independently genes are regulated in the sexes, and the evolution of sex-biased gene expression. Using transcriptome data from Drosophila melanogaster, we find that most genes have a high rMF and that genes currently exposed to sexually antagonistic selection have a higher average rMF than other genes. We further show that genes with a high rMF have less pronounced sex-biased gene expression than genes with a low rMF within D. melanogaster and that the strength of the rMF in D. melanogaster predicts the degree to which the sex bias of a gene’s expression has changed between D. melanogaster and six other species in the Drosophila genus. In sum, our results show that a shared genome constrains both short- and long-term evolution of sexual dimorphism.

Background Despite numerous molecular and computational advances, roughly half of patients with a rare disease remain undiagnosed after exome or genome sequencing. A particularly challenging barrier to diagnosis is identifying variants that cause deleterious alternative splicing at intronic or exonic loci outside of canonical donor or acceptor splice sites. Results Several existing tools predict the likelihood that a genetic variant causes alternative splicing. We sought to extend such methods by developing a new metric that aids in discerning whether a genetic variant leads to deleterious alternative splicing. Our metric combines genetic variation in the Genome Aggregate Database with alternative splicing predictions from SpliceAI to compare observed and expected levels of splice-altering genetic variation. We infer genic regions with significantly less splice-altering variation than expected to be constrained. The resulting model of regional splicing constraint captures differential splicing constraint across gene and exon categories, and the most constrained genic regions are enriched for pathogenic splice-altering variants. Building from this model, we developed ConSpliceML. This ensemble machine learning approach combines regional splicing constraint with multiple per-nucleotide alternative splicing scores to guide the prediction of deleterious splicing variants in protein-coding genes. ConSpliceML more accurately distinguishes deleterious and benign splicing variants than state-of-the-art splicing prediction methods, especially in “cryptic” splicing regions beyond canonical donor or acceptor splice sites. Conclusion Integrating a model of genetic constraint with annotations from existing alternative splicing tools allows ConSpliceML to prioritize potentially deleterious splice-altering variants in studies of rare human diseases.

Phenotypic plasticity can either hinder or promote adaptation to novel environments. Recent studies that have quantified alignments between plasticity, genetic variation, and divergence propose that such alignments may reflect constraints that bias future evolutionary trajectories. Here, we emphasize that such alignments may themselves be a result of natural selection and do not necessarily indicate constraints on adaptation. We estimated developmental plasticity and broad sense genetic covariance matrices (G) among damselfly populations situated along a latitudinal gradient in Europe. Damselflies were reared at photoperiod treatments that simulated the seasonal time constraints experienced at northern (strong constraints) and southern (relaxed constraints) latitudes. This allowed us to partition the effects of (1) latitude, (2) photoperiod, and (3) environmental novelty on G and its putative alignment with adaptive plasticity and divergence. Environmental novelty and latitude did not affect G, but photoperiod did. Photoperiod increased evolvability in the direction of observed adaptive divergence and developmental plasticity when G was assessed under strong seasonal time constraints at northern (relative to southern) photoperiod. Because selection and adaptation under time constraints is well understood in Lestes damselflies, our results suggest that natural selection can shape the alignment between divergence, plasticity, and evolvability.

The latitudinal herbivory defense hypothesis (LHDH) postulates that the prevalence of species interactions, including herbivory, is greater at lower latitudes, leading to selection for increased levels of plant defense. While latitudinal defense clines may be caused by spatial variation in herbivore pressure, optimal defense theory predicts that clines could also be caused by ecogeographic variation in the cost of defense. For instance, allocation of resources to defense may not increase plant fitness when growing seasons are short and plants must reproduce quickly. Here we use a common garden experiment to survey genetic variation for constitutive and induced phenylpropanoid glycoside (PPG) concentrations across 35 Mimulus guttatus populations over a ∼13° latitudinal transect. Our sampling regime is unique among studies of the LHDH in that it allows us to disentangle the effects of growing season length from those of latitude, temperature, and elevation. For five of the seven PPGs surveyed, we find associations between latitude and plant defense that are robust to population structure. However, contrary to the LHDH, only two PPGs were found at higher levels in low latitude populations, and total PPG concentrations were higher at higher latitudes. PPG levels are strongly correlated with growing season length, with higher levels of PPGs in plants from areas with longer growing seasons. Further, flowering time is positively correlated with the concentration of nearly all PPGs, suggesting that there may be a strong trade-off between development time and defense production. Our results reveal that ecogeographic patterns in plant defense may reflect variation in the cost of producing defense compounds in addition to variation in herbivore pressure. Thus, the biogeographic pattern predicted by the LHDH may not be accurate because the underlying factors driving variation in defense, in this case, growing season length, are not always associated with latitude in the same manner. Given these results, we conclude that LHDH cannot be interpreted without considering life history, and we recommend that future work on the LHDH move beyond solely testing the core LHDH prediction and place greater emphasis on isolating agents of selection that generate spatial variation in defense and herbivore pressure.

Background One of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as “genetic constraint”. Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes. Methods We aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues. Results We identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism. Conclusions Grouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.

Melanin is the most widespread pigment in organisms. Melanin-based coloration has been repeatedly observed to be associated with the same traits and in the same direction in different vertebrate and insect species. However, whether any factors that are common to different taxa account for the repeated evolution of melanin-phenotype associations remains unclear. We propose to approach this question from the perspective of convergent and parallel evolution to clarify to what extent different species have evolved the same associations owing to a shared genetic basis and being subjected to similar selective pressures. Our current understanding of the genetic basis of melanin-phenotype associations allows for both convergent and parallel evolution, but this understanding is still limited. Further research is needed to clarify the generality and interdependencies of the different proposed mechanisms (supergenes, pleiotropy based on hormones, or neural crest cells). The general ecological scenarios whereby melanin-based coloration is under selection—protection from ultraviolet radiation, thermoregulation in cold environments, or as a signal of social status—offer a good opportunity to study how melanin-phenotype associations evolve. Reviewing these scenarios shows that some traits associated with melanin-based coloration might be selected together with coloration by also favoring adaptation but that other associated traits might impede adaptation, which may be indicative of genetic constraints. We therefore encourage further research on the relative roles that selection and genetic constraints play in shaping multiple melanin-phenotype associations. Placed into a phylogenetic context, this will help clarify to what extent these associations result from convergent or parallel evolutionary processes and why melanin-phenotype associations are so common across the tree of life.