Sweepstakes reproduction facilitates rapid adaptation in highly fecund populations.

Adaptation enables natural populations to survive in a changing environment. Understanding the mechanics of adaptation is therefore crucial for learning about the evolution and ecology of natural populations. We focus on the impact of random sweepstakes on selection in highly fecund haploid and diploid populations partitioned into two genetic types, with one type conferring selective advantage. For the diploid populations, we incorporate various dominance mechanisms. We assume that the populations may experience recurrent bottlenecks. In random sweepstakes, the distribution of individual recruitment success is highly skewed, resulting in a huge variance in the number of offspring contributed by the individuals present in any given generation. Using computer simulations, we investigate the joint effects of random sweepstakes, recurrent bottlenecks and dominance mechanisms on selection. In our framework, bottlenecks allow random sweepstakes to have an effect on the time to fixation, and in diploid populations, the effect of random sweepstakes depends on the dominance mechanism. We describe selective sweepstakes that are approximated by recurrent sweeps of strongly beneficial allelic types arising by mutation. We demonstrate that both types of sweepstakes reproduction may facilitate rapid adaptation (as defined based on the average time to fixation of a type conferring selective advantage conditioned on fixation of the type). However, whether random sweepstakes cause rapid adaptation depends also on their interactions with bottlenecks and dominance mechanisms. Finally, we review a case study in which a model of recurrent sweeps is shown to essentially explain population genomic data from Atlantic cod.

Recommendations for improving statistical inference in population genomics.

The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.

Soft selective sweeps: Addressing new definitions, evaluating competing models, and interpreting empirical outliers.

The ability to accurately identify and quantify genetic signatures associated with soft selective sweeps based on patterns of nucleotide variation has remained controversial. We here provide counter viewpoints to recent publications in PLOS Genetics that have argued not only for the statistical identifiability of soft selective sweeps, but also for their pervasive evolutionary role in both Drosophila and HIV populations. We present evidence that these claims owe to a lack of consideration of competing evolutionary models, unjustified interpretations of empirical outliers, as well as to new definitions of the processes themselves. Our results highlight the dangers of fitting evolutionary models based on hypothesized and episodic processes without properly first considering common processes and, more generally, of the tendency in certain research areas to view pervasive positive selection as a foregone conclusion.

The classical hitchhiking model with continuous mutational pressure and purifying selection.

Detecting selective sweeps driven by strong positive selection and localizing the targets of selection in the genome play a major role in modern population genetics and genomics. Most of these analyses are based on the classical model of genetic hitchhiking proposed by Maynard Smith and Haigh (1974, Genetical Research, 23, 23). Here, we consider extensions of the classical two-locus model. Introducing mutation at the strongly selected site, we analyze the conditions under which soft sweeps may arise. We identify a new parameter (the ratio of the beneficial mutation rate to the selection coefficient) that characterizes the occurrence of multiple-origin soft sweeps. Furthermore, we quantify the hitchhiking effect when the polymorphism at the linked locus is not neutral but maintained in a mutation-selection balance. In this case, we find a smaller relative reduction of heterozygosity at the linked site than for a neutral polymorphism. In our analysis, we use a semi-deterministic approach; i.e., we analyze the frequency process of the beneficial allele in an infinitely large population when its frequency is above a certain threshold; however, for very small frequencies in the initial phase after the onset of selection we rely on diffusion theory.

Rapid Evolutionary Adaptation in Response to Selection on Quantitative Traits.

Evolutionary adaptation after sudden environmental changes can occur very rapidly. The mechanisms facilitating rapid adaptation range from strong positive directional selection leading to large shifts in the allele frequencies at a few loci (selective sweeps) to polygenic selection causing small changes in allele frequencies at many loci. In addition, combinations of these two extreme mechanisms may also result in fast evolution. In recent years, following reports of new case studies of rapid adaptation, population genetic models have been proposed to explain these observations. In these models, the role of the major selective forces (positive directional and stabilizing selection) is highlighted as well as the genetic architecture of quantitative traits. Furthermore, the factors limiting the speed of adaptation are analyzed, in particular, the effects of random genetic drift and demography due to finite population size.

Demographic analyses of a new sample of haploid genomes from a Swedish population of Drosophila melanogaster.

European and African natural populations of Drosophila melanogaster have been the focus of several studies aiming at inferring demographic and adaptive processes based on genetic variation data. However, in these analyses little attention has been given to gene flow between African and European samples. Here we present a dataset consisting of 14 fully sequenced haploid genomes sampled from a natural population from the northern species range (Umeå, Sweden). We co-analyzed this new data with an African population to compare the likelihood of several competing demographic scenarios for European and African populations and show that gene flow improves the fit of demographic models to data.

Polygenic Adaptation in a Population of Finite Size.

Polygenic adaptation in response to selection on quantitative traits has become an important topic in evolutionary biology. Here we review the recent literature on models of polygenic adaptation. In particular, we focus on a model that includes mutation and both directional and stabilizing selection on a highly polygenic trait in a population of finite size (thus experiencing random genetic drift). Assuming that a sudden environmental shift of the fitness optimum occurs while the population is in a stochastic equilibrium, we analyze the adaptation of the trait to the new optimum. When the shift is not too large relative to the equilibrium genetic variance and this variance is determined by loci with mostly small effects, the approach of the mean phenotype to the optimum can be approximated by a rapid exponential process (whose rate is proportional to the genetic variance). During this rapid phase the underlying changes to allele frequencies, however, may depend strongly on genetic drift. While trait-increasing alleles with intermediate equilibrium frequencies are dominated by selection and contribute positively to changes of the trait mean (i.e., are aligned with the direction of the optimum shift), alleles with low or high equilibrium frequencies show more of a random dynamics, which is expected when drift is dominating. A strong effect of drift is also predicted for population size bottlenecks. Our simulations show that the presence of a bottleneck results in a larger deviation of the population mean of the trait from the fitness optimum, which suggests that more loci experience the influence of drift.

Important role of genetic drift in rapid polygenic adaptation.

We analyzed a model to determine the factors that facilitate or limit rapid polygenic adaptation. This model includes population genetic terms of mutation and both directional and stabilizing selection on a highly polygenic trait in a diploid population of finite size. First, we derived the equilibrium distribution of the allele frequencies of the multilocus model by diffusion approximation. This formula describing the equilibrium allele frequencies as a mutation-selection-drift balance was examined by computer simulation using parameter values inferred for human height, a well-studied polygenic trait. Second, assuming that a sudden environmental shift of the fitness optimum occurs while the population is in equilibrium, we analyzed the adaptation of the trait to the new optimum. The speed at which the trait mean approaches the new optimum increases with the equilibrium genetic variance. Thus, large population size and/or large mutation rate may facilitate rapid adaptation. Third, the contribution of an individual locus i to polygenic adaptation depends on the compound parameter γ i p i 0 q i 0 , where γ i is the effect size, p i 0 the equilibrium frequency of the trait-increasing allele of this locus, and q i 0 = 1 - p i 0 . Thus, only loci with large values of this parameter contribute coherently to polygenic adaptation. Given that mutation rates are relatively small, this is more likely in large populations, in which the effects of drift are limited.

Neutral genomic signatures of host-parasite coevolution.

BACKGROUND: Coevolution is a selective process of reciprocal adaptation in hosts and parasites or in mutualistic symbionts. Classic population genetics theory predicts the signatures of selection at the interacting loci of both species, but not the neutral genome-wide polymorphism patterns. To bridge this gap, we build an eco-evolutionary model, where neutral genomic changes over time are driven by a single selected locus in hosts and parasites via a simple biallelic gene-for-gene or matching-allele interaction. This coevolutionary process may lead to cyclic changes in the sizes of the interacting populations. RESULTS: We investigate if and when these changes can be observed in the site frequency spectrum of neutral polymorphisms from host and parasite full genome data. We show that changes of the host population size are too smooth to be observable in its polymorphism pattern over the course of time. Conversely, the parasite population may undergo a series of strong bottlenecks occurring on a slower relative time scale, which may lead to observable changes in a time series sample. We also extend our results to cases with 1) several parasites per host accelerating relative time, and 2) multiple parasite generations per host generation slowing down rescaled time. CONCLUSIONS: Our results show that time series sampling of host and parasite populations with full genome data are crucial to understand if and how coevolution occurs. This model provides therefore a framework to interpret and draw inference from genome-wide polymorphism data of interacting species.

Interspecific Gene Exchange Introduces High Genetic Variability in Crop Pathogen.

Genome analyses have revealed a profound role of hybridization and introgression in the evolution of many eukaryote lineages, including fungi. The impact of recurrent introgression on fungal evolution however remains elusive. Here, we analyzed signatures of introgression along the genome of the fungal wheat pathogen Zymoseptoria tritici. We applied a comparative population genomics approach, including genome data from five Zymoseptoria species, to characterize the distribution and composition of introgressed regions representing segments with an exceptional haplotype pattern. These regions are found throughout the genome, comprising 5% of the total genome and overlapping with > 1,000 predicted genes. We performed window-based phylogenetic analyses along the genome to distinguish regions which have a monophyletic or nonmonophyletic origin with Z. tritici sequences. A majority of nonmonophyletic windows overlap with the highly variable regions suggesting that these originate from introgression. We verified that incongruent gene genealogies do not result from incomplete lineage sorting by comparing the observed and expected length distribution of haplotype blocks resulting from incomplete lineage sorting. Although protein-coding genes are not enriched in these regions, we identify 18 that encode putative virulence determinants. Moreover, we find an enrichment of transposable elements in these regions implying that hybridization may contribute to the horizontal spread of transposable elements. We detected a similar pattern in the closely related species Zymoseptoria ardabiliae, suggesting that hybridization is widespread among these closely related grass pathogens. Overall, our results demonstrate a significant impact of recurrent hybridization on overall genome evolution of this important wheat pathogen.

The de Novo Reference Genome and Transcriptome Assemblies of the Wild Tomato Species Solanum chilense Highlights Birth and Death of NLR Genes Between Tomato Species.

Wild tomato species, like Solanum chilense, are important germplasm resources for enhanced biotic and abiotic stress resistance in tomato breeding. S. chilense also serves as a model to study adaptation of plants to drought and the evolution of seed banks. The absence of a well-annotated reference genome in this compulsory outcrossing, very diverse species limits in-depth studies on the genes involved.We generated ∼134 Gb of DNA and 157 Gb of RNA sequence data for S chilense, which yielded a draft genome with an estimated length of 914 Mb, encoding 25,885 high-confidence predicted gene models, which show homology to known protein-coding genes of other tomato species. Approximately 71% of these gene models are supported by RNA-seq data derived from leaf tissue samples. Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis of predicted gene models retrieved 93.3% of BUSCO genes. To further verify the genome annotation completeness and accuracy, we manually inspected the NLR resistance gene family and assessed its assembly quality. We find subfamilies of NLRs unique to S. chilense Synteny analysis suggests significant degree of the gene order conservation between the S. chilense, S. lycopersicum and S. pennellii genomesWe generated the first genome and transcriptome sequence assemblies for the wild tomato species Solanum chilense and demonstrated their value in comparative genomics analyses. These data are an important resource for studies on adaptation to biotic and abiotic stress in Solanaceae, on evolution of self-incompatibility and for tomato breeding.

Decreased Temperature Sensitivity of Vestigial Gene Expression in Temperate Populations of Drosophilamelanogaster.

Drosophila melanogaster recently spread from its tropical origin in Africa and became a cosmopolitan species that has adapted to a wide range of different thermal environments, including temperate climates. An important limiting factor of temperate climates has probably been their low and varying temperatures. The transcriptional output of genes can vary across temperatures, which might have been detrimental while settling in temperate environments. The reduction of temperature-sensitive expression of functionally important genes to ensure consistent levels of gene expression might have been relevant while adapting to such environments. In this study, we focus on the gene vestigial (vg) whose product is a key factor in wing development. We provide evidence that temperature-sensitivity of vg has been buffered in populations from temperate climates. We investigated temperature-sensitivity of vg gene expression in six natural populations, including four temperate populations (three from Europe and one from high-altitude Africa), and two tropical populations from the ancestral species range. All temperate populations exhibited a lower degree of temperature-induced expression plasticity than the tropical populations.

Selective Sweeps.

For almost 20 years, many inference methods have been developed to detect selective sweeps and localize the targets of directional selection in the genome. These methods are based on population genetic models that describe the effect of a beneficial allele (e.g., a new mutation) on linked neutral variation (driven by directional selection from a single copy to fixation). Here, I discuss these models, ranging from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and emphasize the important role of demography and population structure in data analysis. In the past 10 years, soft sweeps that may arise after an environmental change from directional selection on standing variation have become a focus of population genetic research. In contrast to selective sweeps, they are caused by beneficial alleles that were neutrally segregating in a population before the environmental change or were present at a mutation-selection balance in appreciable frequency.

The importance of the Neutral Theory in 1968 and 50 years on: A response to Kern and Hahn 2018.

A recent article reassessing the Neutral Theory of Molecular Evolution claims that it is no longer as important as is widely believed. The authors argue that "the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality." Claiming that "the neutral theory has been overwhelmingly rejected," they propose instead that natural selection is the major force shaping both between-species divergence and within-species variation. Although this is probably a minority view, it is important to evaluate such claims carefully in the context of current knowledge, as inaccuracies can sometimes morph into an accepted narrative for those not familiar with the underlying science. We here critically examine and ultimately reject Kern and Hahn's arguments and assessment, and instead propose that it is now abundantly clear that the foundational ideas presented five decades ago by Kimura and Ohta are indeed correct.

Dopamine Modulates Homeostatic Excitatory Synaptic Plasticity of Immature Dentate Granule Cells in Entorhino-Hippocampal Slice Cultures.

Homeostatic plasticity mechanisms maintain neurons in a stable state. To what extent these mechanisms are relevant during the structural and functional maturation of neural tissue is poorly understood. To reveal developmental changes of a major homeostatic plasticity mechanism, i.e., homeostatic excitatory synaptic plasticity, we analyzed 1-week- and 4-week-old entorhino-hippocampal slice cultures and investigated the ability of immature and mature dentate granule cells (GCs) to express this form of plasticity. Our experiments demonstrate that immature GCs are capable of adjusting their excitatory synaptic strength in a compensatory manner at early postnatal stages, i.e., in 1-week-old preparations, as is the case for mature GCs. This ability of immature dentate GCs is absent in 4-week-old slice cultures. Further investigations into the signaling pathways reveal an important role of dopamine (DA), which prevents homeostatic synaptic up-scaling of immature GCs in young cultures, whereas it does not affect immature and mature GCs in 4-week-old preparations. Together, these results disclose the ability of immature GCs to express homeostatic synaptic plasticity during early postnatal development. They hint toward a novel role of dopaminergic signaling, which may gate activity-dependent changes of newly born neurons by blocking homeostasis.

Signatures of natural selection in abiotic stress-responsive genes of Solanum chilense.

Environmental conditions are strong selective forces, which may influence adaptation and speciation. The wild tomato species Solanum chilense, native to South America, is exposed to a range of abiotic stress factors. To identify signatures of natural selection and local adaptation, we analysed 16 genes involved in the abiotic stress response and compared the results to a set of reference genes in 23 populations across the entire species range. The abiotic stress-responsive genes are characterized by elevated nonsynonymous nucleotide diversity and divergence. We detected signatures of positive selection in several abiotic stress-responsive genes on both the population and species levels. Local adaptation to abiotic stresses is particularly apparent at the boundary of the species distribution in populations from coastal low-altitude and mountainous high-altitude regions.

Evolution of highly fecund haploid populations.

We consider a model of viability selection in a highly fecund haploid population with sweepstakes reproduction. We use simulations to estimate the time until the allelic type with highest fitness has reached high frequency in a finite population. We compare the time between two reproduction modes of high and low fecundity. We also consider the probability that the allelic type with highest fitness is lost from the population before reaching high frequency. Our simulation results indicate that highly fecund populations can evolve faster (in some cases much faster) than populations of low fecundity. However, high fecundity and sweepstakes reproduction also confer much higher risk of losing the allelic type with highest fitness from the population by chance. The impact of selection on driving alleles to high frequency varies depending on the trait value conferring highest fitness; in some cases the effect of selection can hardly be detected.

T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells.

Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.

Modes of Rapid Polygenic Adaptation.

Many experimental and field studies have shown that adaptation can occur very rapidly. Two qualitatively different modes of fast adaptation have been proposed: selective sweeps wherein large shifts in the allele frequencies occur at a few loci and evolution via small changes in the allele frequencies at many loci. Although the first process has been thoroughly investigated within the framework of population genetics, the latter is based on quantitative genetics and is much less understood. Here we summarize results from our recent theoretical studies of a quantitative genetic model of polygenic adaptation that makes explicit reference to population genetics to bridge the gap between the two frameworks. Our key results are that polygenic adaptation may be a rapid process and can proceed via subtle or dramatic changes in the allele frequency depending on the sizes of the phenotypic effects relative to a threshold value. We also discuss how the signals of polygenic selection may be detected in the genome. Although powerful methods are available to identify signatures of selective sweeps at loci controlling quantitative traits, the development of statistical tests for detecting small shifts of allele frequencies at quantitative trait loci is still in its infancy.