Through its fermentative capacities, Saccharomyces cerevisiae was central in the development of civilisation during the Neolithic period, and the yeast remains of importance in industry and biotechnology, giving rise to bona fide domesticated populations. Here, we conduct a population genomic study of domesticated and wild populations of S. cerevisiae. Using coalescent analyses, we report that the effective population size of yeast populations decreased since the divergence with S. paradoxus. We fitted models of distributions of fitness effects to infer the rate of adaptive ( ωa ) and non-adaptive ( ωna ) non-synonymous substitutions in protein-coding genes. We report an overall limited contribution of positive selection to S. cerevisiae protein evolution, albeit with higher rates of adaptive evolution in wild compared to domesticated populations. Our analyses revealed the signature of background selection and possibly Hill-Robertson interference, as recombination was found to be negatively correlated with ωna and positively correlated with ωa . However, the effect of recombination on ωa was found to be labile, as it is only apparent after removing the impact of codon usage bias on the synonymous site frequency spectrum and disappears if we control for the correlation with ωna , suggesting that it could be an artefact of the decreasing population size. Furthermore, the rate of adaptive non-synonymous substitutions is significantly correlated with the residue solvent exposure, a relation that cannot be explained by the population's demography. Together, our results provide a detailed characterisation of adaptive mutations in protein-coding genes across S. cerevisiae populations.

Adaptation can occur at remarkably short timescales in natural populations, leading to drastic changes in phenotypes and genotype frequencies over a few generations only. The inference of demographic parameters can allow understanding how evolutionary forces interact and shape the genetic trajectories of populations during rapid adaptation. Here we propose a new Approximate Bayesian Computation (ABC) framework that couples a forward and individual-based model with temporal genetic data to disentangle genetic changes and demographic variations in a case of rapid adaptation. We test the accuracy of our inferential framework and evaluate the benefit of considering a dense versus sparse sampling. Theoretical investigations demonstrate high accuracy in both model and parameter estimations, even if a strong thinning is applied to time series data. Then, we apply our ABC inferential framework to empirical data describing the population genetic changes of the poplar rust pathogen following a major event of resistance overcoming. We successfully estimate key demographic and genetic parameters, including the proportion of resistant hosts deployed in the landscape and the level of standing genetic variation from which selection occurred. Inferred values are in accordance with our empirical knowledge of this biological system. This new inferential framework, which contrasts with coalescent-based ABC analyses, is promising for a better understanding of evolutionary trajectories of populations subjected to rapid adaptation.

Allele frequencies can shift rapidly within natural populations. Under certain conditions, repeated rapid allele frequency shifts can lead to the long-term maintenance of polymorphism. In recent years, studies of the model insect Drosophila melanogaster have suggested that this phenomenon is more common than previously believed and is often driven by some form of balancing selection, such as temporally fluctuating or sexually antagonistic selection. Here we discuss some of the general insights into rapid evolutionary change revealed by large-scale population genomic studies, as well as the functional and mechanistic causes of rapid adaptation uncovered by single-gene studies. As an example of the latter, we consider a regulatory polymorphism of the D. melanogaster fezzik gene. Polymorphism at this site has been maintained at intermediate frequency over an extended period of time. Regular observations from a single population over a period of 7 years revealed significant differences in the frequency of the derived allele and its variance across collections between the sexes. These patterns are highly unlikely to arise from genetic drift alone or from the action of sexually antagonistic or temporally fluctuating selection individually. Instead, the joint action of sexually antagonistic and temporally fluctuating selection can best explain the observed rapid and repeated allele frequency shifts. Temporal studies such as those reviewed here further our understanding of how rapid changes in selection can lead to the long-term maintenance of polymorphism as well as improve our knowledge of the forces driving and limiting adaptation in nature.

Understanding the relative contributions of ecological and evolutionary processes to the structuring of ecological communities is needed to improve our ability to predict how communities may respond to future changes in an increasingly human-modified world. Metabarcoding methods make it possible to gather population genetic data for all species within a community, unlocking a new axis of data to potentially unveil the origins and maintenance of biodiversity at local scales. Here, we present a new eco-evolutionary simulation model for investigating community assembly dynamics using metabarcoding data. The model makes joint predictions of species abundance, genetic variation, trait distributions and phylogenetic relationships under a wide range of parameter settings (e.g. high speciation/low dispersal or vice versa) and across a range of community states, from pristine and unmodified to heavily disturbed. We first demonstrate that parameters governing metacommunity and local community processes leave detectable signatures in simulated biodiversity data axes. Next, using a simulation-based machine learning approach we show that neutral and non-neutral models are distinguishable and that reasonable estimates of several model parameters within the local community can be obtained using only community-scale genetic data, while phylogenetic information is required to estimate those describing metacommunity dynamics. Finally, we apply the model to soil microarthropod metabarcoding data from the Troodos mountains of Cyprus, where we find that communities in widespread forest habitats are structured by neutral processes, while high-elevation and isolated habitats act as an abiotic filter generating non-neutral community structure. We implement our model within the ibiogen R package, a package dedicated to the investigation of island, and more generally community-scale, biodiversity using community-scale genetic data.

Oceanic islands are characterized by conditions that favour diversification into endemic lineages that can be very different from their mainland counterparts. This can be the result of fast phenotypic divergence due to drift or the result of slower adaptation to local conditions. This uniqueness can obscure their evolutionary history. Here we used morphological, stable isotope, genetic and genomic data to characterize common quails (Coturnix coturnix) in the Azores archipelago and assess the divergence from neighbouring common quail populations. Historical documents suggested that these quails could have a recent origin associated with the arrival of humans in the last centuries. Our results show that Azorean quails constitute a well-differentiated lineage with small size and dark throat pigmentation that has lost the migratory ability and that diverged from mainland quail lineages more than 0.8 mya, contrary to the notion of a recent human-mediated arrival. Even though some Azorean quails carry an inversion that affects 115 Mbp of chromosome 1 and that has been associated with the loss of the migratory behaviour in other common quail populations, half of the analysed individuals do not have that inversion and still do not migrate. The long coexistence and evolution in isolation in the Azores of two chromosomal variants (with and without the inversion) is best explained by balancing selection. Thus, a unique and long evolutionary history led to the island endemic that we know today, C. c. conturbans.

Humans have profoundly impacted the distribution of plant and animal species over thousands of years. The most direct example of these effects is human-mediated movement of individuals, either through translocation of individuals within their range or through the introduction of species to new habitats. While human involvement may be suspected in species with obvious range disjunctions, it can be difficult to detect natural versus human-mediated dispersal events for populations at the edge of a species' range, and this uncertainty muddles how we understand the evolutionary history of populations and broad biogeographical patterns. Studies combining genetic data with archaeological, linguistic and historical evidence have confirmed prehistoric examples of human-mediated dispersal; however, it is unclear whether these methods can disentangle recent dispersal events, such as species translocated by European colonizers during the past 500 years. We use genomic DNA from historical museum specimens and historical records to evaluate three hypotheses regarding the timing and origin of Northern Bobwhites (Colinus virginianus) in Cuba, whose status as an endemic or introduced population has long been debated. We discovered that bobwhites from southern Mexico arrived in Cuba between the 12th and 16th centuries, followed by the subsequent introduction of bobwhites from the southeastern USA to Cuba between the 18th and 20th centuries. These dates suggest the introduction of bobwhites to Cuba was human-mediated and concomitant with Spanish colonial shipping routes between Veracruz, Mexico and Havana, Cuba during this period. Our results identify endemic Cuban bobwhites as a genetically distinct population born of hybridization between divergent, introduced lineages.

Understanding patterns of diversity across macro (e.g. species-level) and micro (e.g. molecular-level) scales can shed light on community function and stability by elucidating the abiotic and biotic drivers of diversity within ecological communities. We examined the relationships among taxonomic and genetic metrics of diversity in freshwater mussels (Bivalvia: Unionidae), an ecologically important and species-rich group in the southeastern United States. Using quantitative community surveys and reduced-representation genome sequencing across 22 sites in seven rivers and two river basins, we surveyed 68 mussel species and sequenced 23 of these species to characterize intrapopulation genetic variation. We tested for the presence of species diversity-abundance correlations (i.e. the more-individuals hypothesis, MIH), species-genetic diversity correlations (SGDCs) and abundance-genetic diversity correlations (AGDCs) across all sites to evaluate relationships between different metrics of diversity. Sites with greater cumulative multispecies density (a standardized metric of abundance) had a greater number of species, consistent with the MIH hypothesis. Intrapopulation genetic diversity was strongly associated with the density of most species, indicating the presence of AGDCs. However, there was no consistent evidence for SGDCs. Although sites with greater overall densities of mussels had greater species richness, sites with higher genetic diversity did not always exhibit positive correlations with species richness, suggesting that there are spatial and evolutionary scales at which the processes influencing community-level diversity and intraspecific diversity differ. Our work reveals the importance of local abundance as indicator (and possibly a driver) of intrapopulation genetic diversity.

The speed of population adaptation to changing biotic and abiotic environments is determined by the interaction between genetic drift, positive selection and linkage effects. Many marine species (fish, crustaceans), invertebrates and pathogens of humans and crops, exhibit sweepstakes reproduction characterized by the production of a very large amount of offspring (fecundity phase) from which only a small fraction may survive to the next generation (viability phase). Using stochastic simulations, we investigate whether the occurrence of sweepstakes reproduction affects the efficiency of a positively selected unlinked locus, and thus, the speed of adaptation since fecundity and/or viability have distinguishable consequences on mutation rate, probability and fixation time of advantageous alleles. We observe that the mean number of mutations at the next generation is always the function of the population size, but the variance increases with stronger sweepstakes reproduction when mutations occur in the parents. On the one hand, stronger sweepstakes reproduction magnifies the effect of genetic drift thus increasing the probability of fixation of neutral allele and decreasing that of selected alleles. On the other hand, the time to fixation of advantageous (as well as neutral) alleles is shortened by stronger sweepstakes reproduction. Importantly, fecundity and viability selection exhibit different probabilities and times to fixation of advantageous alleles under intermediate and weak sweepstakes reproduction. Finally, alleles under both strong fecundity and viability selection display a synergistic efficiency of selection. We conclude that measuring and modelling accurately fecundity and/or viability selection are crucial to predict the adaptive potential of species with sweepstakes reproduction.

A main goal of evolutionary biology is to understand the genetic basis of adaptive evolution. Although the genes that underlie some adaptive phenotypes are now known, the molecular pathways and regulatory mechanisms mediating the phenotypic effects of those genes often remain a black box. Unveiling this black box is necessary to fully understand the genetic basis of adaptive phenotypes, and to understand why particular genes might be used during phenotypic evolution. Here, we investigated which genes and regulatory mechanisms are mediating the phenotypic effects of the Eda haplotype, a locus responsible for the loss of lateral plates and changes in the sensory lateral line of freshwater threespine stickleback (Gasterosteus aculeatus) populations. Using a combination of RNAseq and a cross design that isolated the Eda haplotype on a fixed genomic background, we found that the Eda haplotype affects both gene expression and alternative splicing of genes related to bone development, neuronal development and immunity. These include genes in conserved pathways, like the BMP, netrin and bradykinin signalling pathways, known to play a role in these biological processes. Furthermore, we found that differentially expressed and differentially spliced genes had different levels of connectivity and expression, suggesting that these factors might influence which regulatory mechanisms are used during phenotypic evolution. Taken together, these results provide a better understanding of the mechanisms mediating the effects of an important adaptive locus in stickleback and suggest that alternative splicing could be an important regulatory mechanism mediating adaptive phenotypes.