Identification of constrained sequence elements across 239 primate genomes.

Noncoding DNA is central to our understanding of human gene regulation and complex diseases1,2, and measuring the evolutionary sequence constraint can establish the functional relevance of putative regulatory elements in the human genome3-9. Identifying the genomic elements that have become constrained specifically in primates has been hampered by the faster evolution of noncoding DNA compared to protein-coding DNA10, the relatively short timescales separating primate species11, and the previously limited availability of whole-genome sequences12. Here we construct a whole-genome alignment of 239 species, representing nearly half of all extant species in the primate order. Using this resource, we identified human regulatory elements that are under selective constraint across primates and other mammals at a 5% false discovery rate. We detected 111,318 DNase I hypersensitivity sites and 267,410 transcription factor binding sites that are constrained specifically in primates but not across other placental mammals and validate their cis-regulatory effects on gene expression. These regulatory elements are enriched for human genetic variants that affect gene expression and complex traits and diseases. Our results highlight the important role of recent evolution in regulatory sequence elements differentiating primates, including humans, from other placental mammals.

fastDFE: Fast and Flexible Inference of the Distribution of Fitness Effects.

Estimating the distribution of fitness effects (DFE) of new mutations is of fundamental importance in evolutionary biology, ecology, and conservation. However, existing methods for DFE estimation suffer from limitations, such as slow computation speed and limited scalability. To address these issues, we introduce fastDFE, a Python-based software package, offering fast, and flexible DFE inference from site-frequency spectrum (SFS) data. Apart from providing efficient joint inference of multiple DFEs that share parameters, it offers the feature of introducing genomic covariates that influence the DFEs and testing their significance. To further simplify usage, fastDFE is equipped with comprehensive VCF-to-SFS parsing utilities. These include options for site filtering and stratification, as well as site-degeneracy annotation and probabilistic ancestral-allele inference. fastDFE thereby covers the entire workflow of DFE inference from the moment of acquiring a raw VCF file. Despite its Python foundation, fastDFE incorporates a full R interface, including native R visualization capabilities. The package is comprehensively tested and documented at fastdfe.readthedocs.io.

Recombination Facilitates Adaptive Evolution in Rhizobial Soil Bacteria.

Homologous recombination is expected to increase natural selection efficacy by decoupling the fate of beneficial and deleterious mutations and by readily creating new combinations of beneficial alleles. Here, we investigate how the proportion of amino acid substitutions fixed by adaptive evolution (α) depends on the recombination rate in bacteria. We analyze 3,086 core protein-coding sequences from 196 genomes belonging to five closely related species of the genus Rhizobium. These genes are found in all species and do not display any signs of introgression between species. We estimate α using the site frequency spectrum (SFS) and divergence data for all pairs of species. We evaluate the impact of recombination within each species by dividing genes into three equally sized recombination classes based on their average level of intragenic linkage disequilibrium. We find that α varies from 0.07 to 0.39 across species and is positively correlated with the level of recombination. This is both due to a higher estimated rate of adaptive evolution and a lower estimated rate of nonadaptive evolution, suggesting that recombination both increases the fixation probability of advantageous variants and decreases the probability of fixation of deleterious variants. Our results demonstrate that homologous recombination facilitates adaptive evolution measured by α in the core genome of prokaryote species in agreement with studies in eukaryotes.

Dioecy Is Associated with High Genetic Diversity and Adaptation Rates in the Plant Genus Silene.

About 15,000 angiosperm species (∼6%) have separate sexes, a phenomenon known as dioecy. Why dioecious taxa are so rare is still an open question. Early work reported lower species richness in dioecious compared with nondioecious sister clades, raising the hypothesis that dioecy may be an evolutionary dead-end. This hypothesis has been recently challenged by macroevolutionary analyses that detected no or even positive effect of dioecy on diversification. However, the possible genetic consequences of dioecy at the population level, which could drive the long-term fate of dioecious lineages, have not been tested so far. Here, we used a population genomics approach in the Silene genus to look for possible effects of dioecy, especially for potential evidence of evolutionary handicaps of dioecy underlying the dead-end hypothesis. We collected individual-based RNA-seq data from several populations in 13 closely related species with different sexual systems: seven dioecious, three hermaphroditic, and three gynodioecious species. We show that dioecy is associated with increased genetic diversity, as well as higher selection efficacy both against deleterious mutations and for beneficial mutations. The results hold after controlling for phylogenetic inertia, differences in species census population sizes and geographic ranges. We conclude that dioecious Silene species neither show signs of increased mutational load nor genetic evidence for extinction risk. We discuss these observations in the light of the possible demographic differences between dioecious and self-compatible hermaphroditic species and how this could be related to alternatives to the dead-end hypothesis to explain the rarity of dioecy.

What does the distribution of fitness effects of new mutations reflect? Insights from plants.

The distribution of fitness effects (DFE) of new mutations plays a central role in molecular evolution. It is therefore crucial to be able to estimate it accurately from genomic data and to understand the factors that shape it. After a rapid overview of available methods to characterize the fitness effects of mutations, we review what is known on the factors affecting them in plants. Available data indicate that life history traits (e.g. mating system and longevity) have a major effect on the DFE. By contrast, the impact of demography within species appears to be more limited. These results remain to be confirmed, and methods to estimate the joint evolution of demography, life history traits, and the DFE need to be developed.

Ongoing decline in insect-pollinated plants across Danish grasslands.

Loss of habitat, eutrophication and reduced grazing intensity are known drivers of landscape-level changes in plant species composition; however, consequences of the massive decline in insect abundance are still to be understood. Pollinator decline can reduce seed set in plants relying on insects for successful reproduction. This may result in a reduced recruitment of insect-pollinated plant species with associated changes in species composition. So far, large-scale studies addressing this issue have relied on few data points-typically consisting of 'historic' records of numbers of insect-pollinated plants compared to present-day records. Such comparisons can provide information as to whether the diversity of insect-pollinated plants has changed, but not whether the process is still ongoing. Here, we use nationwide monitoring data of plant species richness in Danish grasslands from the period 2004-2014, covering 244 grassland sites and encompassing more than 790 flowering plant species. We show an ongoing decrease in insect-pollinated, but not wind-pollinated, plant species across different habitat types. In both dry calcareous and Nardus grasslands, loss of insect-pollinated plants was greatest at sites with low grazing intensity. However, insect-pollinated plants also declined from sites with higher grazing intensity, and plants requiring more specialized insect pollination tended to decline most. In addition to changes in plant diversity driven by land-use intensification, loss of pollinators may also play a role in reducing the richness of insect-pollinated plants. Ongoing reduction in floral richness could further increase the threat to insects relying on these plants as a food source.

The Evolutionary Interplay between Adaptation and Self-Fertilization.

Genome-wide surveys of nucleotide polymorphisms, obtained from next-generation sequencing, have uncovered numerous examples of adaptation in self-fertilizing organisms, especially regarding changes to climate, geography, and reproductive systems. Yet existing models for inferring attributes of adaptive mutations often assume idealized outcrossing populations, which risks mischaracterizing properties of these variants. Recent theoretical work is emphasizing how various aspects of self-fertilization affects adaptation, yet empirical data on these properties are lacking. We review theoretical and empirical studies demonstrating how self-fertilization alters the process of adaptation, illustrated using examples from current sequencing projects. We propose ideas for how future research can more accurately quantify aspects of adaptation in self-fertilizers, including incorporating the effects of standing variation, demographic history, and polygenic adaptation.

polyDFEv2.0: testing for invariance of the distribution of fitness effects within and across species.

SUMMARY: Distribution of fitness effects (DFE) of mutations can be inferred from site frequency spectrum (SFS) data. There is mounting interest to determine whether distinct genomic regions and/or species share a common DFE, or whether evidence exists for differences among them. polyDFEv2.0 fits multiple SFS datasets at once and provides likelihood ratio tests for DFE invariance across datasets. Simulations show that testing for DFE invariance across genomic regions within a species requires models accounting for distinct sources of heterogeneity (chance and genuine difference in DFE) underlying differences in SFS data in these regions. Not accounting for this will result in the spurious detection of DFE differences. AVAILABILITY AND IMPLEMENTATION: polyDFEv2.0 is implemented in C and is accompanied by a series of R functions that facilitate post-processing of the output. It is available as source code and compiled binaries under a GNU General Public License v3.0 from https://github.com/paula-tataru/polyDFE. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Microbial community assembly and evolution in subseafloor sediment.

Bacterial and archaeal communities inhabiting the subsurface seabed live under strong energy limitation and have growth rates that are orders of magnitude slower than laboratory-grown cultures. It is not understood how subsurface microbial communities are assembled and whether populations undergo adaptive evolution or accumulate mutations as a result of impaired DNA repair under such energy-limited conditions. Here we use amplicon sequencing to explore changes of microbial communities during burial and isolation from the surface to the >5,000-y-old subsurface of marine sediment and identify a small core set of mostly uncultured bacteria and archaea that is present throughout the sediment column. These persisting populations constitute a small fraction of the entire community at the surface but become predominant in the subsurface. We followed patterns of genome diversity with depth in four dominant lineages of the persisting populations by mapping metagenomic sequence reads onto single-cell genomes. Nucleotide sequence diversity was uniformly low and did not change with age and depth of the sediment. Likewise, there was no detectable change in mutation rates and efficacy of selection. Our results indicate that subsurface microbial communities predominantly assemble by selective survival of taxa able to persist under extreme energy limitation.

What drives parallel evolution?: How population size and mutational variation contribute to repeated evolution.

Parallel evolution is the repeated evolution of the same phenotype or genotype in evolutionarily independent populations. Here, we use evolve-and-resequence experiments with bacteria and yeast to dissect the drivers of parallel evolution at the gene level. A meta-analysis shows that parallel evolution is often rare, but there is a positive relationship between population size and the probability of parallelism. We present a modeling approach to estimate the contributions of mutational and selective heterogeneity across a genome to parallel evolution. We show that, for two experiments, mutation contributes between ∼10 and 45%, respectively, of the variation associated with selection. Parallel evolution cannot, therefore, be interpreted as a phenomenon driven by selection alone; it must also incorporate information on heterogeneity in mutation rates along the genome. More broadly, the work discussed here helps lay the groundwork for a more sophisticated, empirically grounded theory of parallel evolution.

Statistical Inference in the Wright-Fisher Model Using Allele Frequency Data.

The Wright­Fisher model provides an elegant mathematical framework for understanding allele frequency data. In particular, the model can be used to infer the demographic history of species and identify loci under selection. A crucial quantity for inference under the Wright­Fisher model is the distribution of allele frequencies (DAF). Despite the apparent simplicity of the model, the calculation of the DAF is challenging. We review and discuss strategies for approximating the DAF, and how these are used in methods that perform inference from allele frequency data. Various evolutionary forces can be incorporated in the Wright­Fisher model, and we consider these in turn. We begin our review with the basic bi-allelic Wright­Fisher model where random genetic drift is the only evolutionary force. We then consider mutation, migration, and selection. In particular, we compare diffusion-based and moment-based methods in terms of accuracy, computational efficiency, and analytical tractability. We conclude with a brief overview of the multi-allelic process with a general mutation model.

The fitness landscape of the codon space across environments.

Fitness landscapes map the relationship between genotypes and fitness. However, most fitness landscape studies ignore the genetic architecture imposed by the codon table and thereby neglect the potential role of synonymous mutations. To quantify the fitness effects of synonymous mutations and their potential impact on adaptation on a fitness landscape, we use a new software based on Bayesian Monte Carlo Markov Chain methods and re-estimate selection coefficients of all possible codon mutations across 9 amino acid positions in Saccharomyces cerevisiae Hsp90 across 6 environments. We quantify the distribution of fitness effects of synonymous mutations and show that it is dominated by many mutations of small or no effect and few mutations of larger effect. We then compare the shape of the codon fitness landscape across amino acid positions and environments, and quantify how the consideration of synonymous fitness effects changes the evolutionary dynamics on these fitness landscapes. Together these results highlight a possible role of synonymous mutations in adaptation and indicate the potential mis-inference when they are neglected in fitness landscape studies.

Overestimation of the adaptive substitution rate in fluctuating populations.

Estimating the proportion of adaptive substitutions (α) is of primary importance to uncover the determinants of adaptation in comparative genomic studies. Several methods have been proposed to estimate α from patterns polymorphism and divergence in coding sequences. However, estimators of α can be biased when the underlying assumptions are not met. Here we focus on a potential source of bias, i.e. variation through time in the long-term population size (N) of the considered species. We show via simulations that ancient demographic fluctuations can generate severe overestimations of α, and this is irrespective of the recent population history.

GC-Content evolution in bacterial genomes: the biased gene conversion hypothesis expands.

The characterization of functional elements in genomes relies on the identification of the footprints of natural selection. In this quest, taking into account neutral evolutionary processes such as mutation and genetic drift is crucial because these forces can generate patterns that may obscure or mimic signatures of selection. In mammals, and probably in many eukaryotes, another such confounding factor called GC-Biased Gene Conversion (gBGC) has been documented. This mechanism generates patterns identical to what is expected under selection for higher GC-content, specifically in highly recombining genomic regions. Recent results have suggested that a mysterious selective force favouring higher GC-content exists in Bacteria but the possibility that it could be gBGC has been excluded. Here, we show that gBGC is probably at work in most if not all bacterial species. First we find a consistent positive relationship between the GC-content of a gene and evidence of intra-genic recombination throughout a broad spectrum of bacterial clades. Second, we show that the evolutionary force responsible for this pattern is acting independently from selection on codon usage, and could potentially interfere with selection in favor of optimal AU-ending codons. A comparison with data from human populations shows that the intensity of gBGC in Bacteria is comparable to what has been reported in mammals. We propose that gBGC is not restricted to sexual Eukaryotes but also widespread among Bacteria and could therefore be an ancestral feature of cellular organisms. We argue that if gBGC occurs in bacteria, it can account for previously unexplained observations, such as the apparent non-equilibrium of base substitution patterns and the heterogeneity of gene composition within bacterial genomes. Because gBGC produces patterns similar to positive selection, it is essential to take this process into account when studying the evolutionary forces at work in bacterial genomes.

Can the experimental evolution programme help us elucidate the genetic basis of adaptation in nature?

There have been a variety of approaches taken to try to characterize and identify the genetic basis of adaptation in nature, spanning theoretical models, experimental evolution studies and direct tests of natural populations. Theoretical models can provide formalized and detailed hypotheses regarding evolutionary processes and patterns, from which experimental evolution studies can then provide important proofs of concepts and characterize what is biologically reasonable. Genetic and genomic data from natural populations then allow for the identification of the particular factors that have and continue to play an important role in shaping adaptive evolution in the natural world. Further to this, experimental evolution studies allow for tests of theories that may be difficult or impossible to test in natural populations for logistical and methodological reasons and can even generate new insights, suggesting further refinement of existing theories. However, as experimental evolution studies often take place in a very particular set of controlled conditions--that is simple environments, a small range of usually asexual species, relatively short timescales--the question remains as to how applicable these experimental results are to natural populations. In this review, we discuss important insights coming from experimental evolution, focusing on four key topics tied to the evolutionary genetics of adaptation, and within those topics, we discuss the extent to which the experimental work compliments and informs natural population studies. We finish by making suggestions for future work in particular a need for natural population genomic time series data, as well as the necessity for studies that combine both experimental evolution and natural population approaches.

A replicated climate change field experiment reveals rapid evolutionary response in an ecologically important soil invertebrate.

Whether species can respond evolutionarily to current climate change is crucial for the persistence of many species. Yet, very few studies have examined genetic responses to climate change in manipulated experiments carried out in natural field conditions. We examined the evolutionary response to climate change in a common annelid worm using a controlled replicated experiment where climatic conditions were manipulated in a natural setting. Analyzing the transcribed genome of 15 local populations, we found that about 12% of the genetic polymorphisms exhibit differences in allele frequencies associated to changes in soil temperature and soil moisture. This shows an evolutionary response to realistic climate change happening over short-time scale, and calls for incorporating evolution into models predicting future response of species to climate change. It also shows that designed climate change experiments coupled with genome sequencing offer great potential to test for the occurrence (or lack) of an evolutionary response.

One size fits all? Direct evidence for the heterogeneity of genetic drift throughout the genome.

Effective population size (Ne) is a central parameter in population and conservation genetics. It measures the magnitude of genetic drift, rates of accumulation of inbreeding in a population, and it conditions the efficacy of selection. It is often assumed that a single Ne can account for the evolution of genomes. However, recent work provides indirect evidence for heterogeneity in Ne throughout the genome. We study this by examining genome-wide diversity in the Danish Holstein cattle breed. Using the differences in allele frequencies over a single generation, we directly estimated Ne among autosomes and smaller windows within autosomes. We found statistically significant variation in Ne at both scales. However, no correlation was found between the detected regional variability in Ne, and proxies for the intensity of linked selection (local recombination rate, gene density), or the presence of either past strong selection or current artificial selection on traits of economic value. Our findings call for further caution regarding the wide applicability of the Ne concept for understanding quantitatively processes such as genetic drift and accumulation of consanguinity in both natural and managed populations.

Extensive X-linked adaptive evolution in central chimpanzees.

Surveying genome-wide coding variation within and among species gives unprecedented power to study the genetics of adaptation, in particular the proportion of amino acid substitutions fixed by positive selection. Additionally, contrasting the autosomes and the X chromosome holds information on the dominance of beneficial (adaptive) and deleterious mutations. Here we capture and sequence the complete exomes of 12 chimpanzees and present the largest set of protein-coding polymorphism to date. We report extensive adaptive evolution specifically targeting the X chromosome of chimpanzees with as much as 30% of all amino acid replacements being adaptive. Adaptive evolution is barely detectable on the autosomes except for a few striking cases of recent selective sweeps associated with immunity gene clusters. We also find much stronger purifying selection than observed in humans, and in contrast to humans, we find that purifying selection is stronger on the X chromosome than on the autosomes in chimpanzees. We therefore conclude that most adaptive mutations are recessive. We also document dramatically reduced synonymous diversity in the chimpanzee X chromosome relative to autosomes and stronger purifying selection than for the human X chromosome. If similar processes were operating in the human-chimpanzee ancestor as in central chimpanzees today, our results therefore provide an explanation for the much-discussed reduction in the human-chimpanzee divergence at the X chromosome.

Distribution of fitness effects among beneficial mutations before selection in experimental populations of bacteria.

The extent to which a population diverges from its ancestor through adaptive evolution depends on variation supplied by novel beneficial mutations. Extending earlier work, recent theory makes two predictions that seem to be robust to biological details: the distribution of fitness effects among beneficial mutations before selection should be (i) exponential and (ii) invariant, meaning it is always exponential regardless of the fitness rank of the wild-type allele. Here we test these predictions by assaying the fitness of 665 independently derived single-step mutations in the bacterium Pseudomonas fluorescens across a range of environments. We show that the distribution of fitness effects among beneficial mutations is indistinguishable from an exponential despite marked variation in the fitness rank of the wild type across environments. These results suggest that the initial step in adaptive evolution--the production of novel beneficial mutants from which selection sorts--is very general, being characterized by an approximately exponential distribution with many mutations of small effect and few of large effect. We also document substantial variation in the pleiotropic costs of antibiotic resistance, a result that may have implications for strategies aimed at eliminating resistant pathogens in animal and human populations.

The making of a new pathogen: insights from comparative population genomics of the domesticated wheat pathogen Mycosphaerella graminicola and its wild sister species.

The fungus Mycosphaerella graminicola emerged as a new pathogen of cultivated wheat during its domestication ~11,000 yr ago. We assembled 12 high-quality full genome sequences to investigate the genetic footprints of selection in this wheat pathogen and closely related sister species that infect wild grasses. We demonstrate a strong effect of natural selection in shaping the pathogen genomes with only ~3% of nonsynonymous mutations being effectively neutral. Forty percent of all fixed nonsynonymous substitutions, on the other hand, are driven by positive selection. Adaptive evolution has affected M. graminicola to the highest extent, consistent with recent host specialization. Positive selection has prominently altered genes encoding secreted proteins and putative pathogen effectors supporting the premise that molecular host-pathogen interaction is a strong driver of pathogen evolution. Recent divergence between pathogen sister species is attested by the high degree of incomplete lineage sorting (ILS) in their genomes. We exploit ILS to generate a genetic map of the species without any crossing data, document recent times of species divergence relative to genome divergence, and show that gene-rich regions or regions with low recombination experience stronger effects of natural selection on neutral diversity. Emergence of a new agricultural host selected a highly specialized and fast-evolving pathogen with unique evolutionary patterns compared with its wild relatives. The strong impact of natural selection, we document, is at odds with the small effective population sizes estimated and suggest that population sizes were historically large but likely unstable.