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.

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.

A global catalog of whole-genome diversity from 233 primate species

The rich diversity of morphology and behavior displayed across primate species provides an informative context in which to study the impact of genomic diversity on fundamental biological processes. Analysis of that diversity provides insight into long-standing questions in evolutionary and conservation biology and is urgent given severe threats these species are facing. Here, we present high-coverage whole-genome data from 233 primate species representing 86% of genera and all 16 families. This dataset was used, together with fossil calibration, to create a nuclear DNA phylogeny and to reassess evolutionary divergence times among primate clades. We found within-species genetic diversity across families and geographic regions to be associated with climate and sociality, but not with extinction risk. Furthermore, mutation rates differ across species, potentially influenced by effective population sizes. Lastly, we identified extensive recurrence of missense mutations previously thought to be human specific. This study will open a wide range of research avenues for future primate genomic research.

The landscape of tolerated genetic variation in humans and primates

Personalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.

Competition and coevolution drive the evolution and the diversification of CRISPR immunity

The diversity of resistance challenges the ability of pathogens to spread and to exploit host populations. Yet, how this host diversity evolves over time remains unclear because it depends on the interplay between intraspecific competition among host genotypes and coevolution with pathogens. Here we study experimentally the effect of coevolving phage populations on the diversification of bacterial CRISPR immunity across space and time. We demonstrate that the negative-frequency-dependent selection generated by coevolution is a powerful force that maintains host resistance diversity and selects for new resistance mutations in the host. We also find that host evolution is driven by asymmetries in competitive abilities among different host genotypes. Even if the fittest host genotypes are targeted preferentially by the evolving phages, they often escape extinctions through the acquisition of new CRISPR immunity. Together, these fluctuating selective pressures maintain diversity, but not by preserving the pre-existing host composition. Instead, we repeatedly observe the introduction of new resistance genotypes stemming from the fittest hosts in each population. These results highlight the importance of competition on the transient dynamics of host-pathogen coevolution.

From genotype to phenotype: Genetic redundancy and the maintenance of an adaptive polymorphism in the context of high gene flow

A central question in evolution is how several adaptive phenotypes are maintained within a species. Theory predicts that the genetic determination of a trait, and in particular the amounts of redundancy in the mapping of genotypes to phenotypes, mediates evolutionary outcomes of phenotypic selection. In Mediterranean wild thyme, numerous discrete chemical phenotypes (chemotypes) occur in close geographic proximity. Chemotypes are defined by the predominant monoterpene produced by individual plants in their essential oil. In this study, we analyze the ecological genetics of six chemotypes nested within two well‐established chemical families (hereafter ecotypes). Ecotypes, and chemotypes within ecotypes, are spatially segregated, and their distributions track local differences in the abiotic environment. By combining population genomic, phenotypic, and environmental data from 700 individuals, we show how the genetics of ecotype determination mediates this evolutionary response. Variation in three terpene‐synthase loci explains variation in ecotype identity, with one single locus accounting for as much as 78% of this variation. Phenotypic selection combined with low segregating genotypic redundancy of ecotypes leaves a clear footprint at the genomic level: alleles associated with ecotype identity track environmental variation despite extensive gene flow. Different chemotypes within each ecotype differentially track environmental variation. Their identity is determined by multiple loci and displays a wider range of genotypic redundancy that dilutes phenotypic selection on their characteristic alleles. Our study thus provides a novel illustration of how genetic redundancy of a phenotype modulates the ability of selection to maintain adaptive differentiation. Identifying the precise genetics of the chemical polymorphism in thyme is the next crucial step for our understanding of the origin and maintenance of a polymorphism that is present in many aromatic plants.

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.

Detection of sexually antagonistic transmission distortions in trio datasets

Sexual dimorphisms are widespread in animals and plants, for morphological as well as physiological traits. Understanding the genetic basis of sexual dimorphism and its evolution is crucial for understanding biological differences between the sexes. Genetic variants with sex‐antagonistic effects on fitness are expected to segregate in populations at the early phases of sexual dimorphism emergence. Detecting such variants is notoriously difficult, and the few genome‐scan methods employed so far have limited power and little specificity. Here, we propose a new framework to detect a signature of sexually antagonistic (SA) selection. We rely on trio datasets where sex‐biased transmission distortions can be directly tracked from parents to offspring, and identify signals of SA transmission distortions in genomic regions. We report the genomic location of six candidate regions detected in human populations as potentially under sexually antagonist selection. We find an enrichment of genes associated with embryonic development within these regions. Last, we highlight two candidate regions for SA selection in humans.

Using singleton densities to detect recent selection in Bos taurus

Many quantitative traits are subject to polygenic selection, where several genomic regions undergo small, simultaneous changes in allele frequency that collectively alter a phenotype. The widespread availability of genome data, along with novel statistical techniques, has made it easier to detect these changes. We apply one such method, the "Singleton Density Score" (SDS), to the Holstein breed of Bos taurus to detect recent selection (arising up to around 740 years ago). We identify several genes as candidates for targets of recent selection, including some relating to cell regulation, catabolic processes, neural-cell adhesion and immunity. We do not find strong evidence that three traits that are important to humans-milk protein content, milk fat content, and stature-have been subject to directional selection. Simulations demonstrate that because B. taurus recently experienced a population bottleneck, singletons are depleted so the power of SDS methods is reduced. These results inform on which genes underlie recent genetic change in B. taurus, while providing information on how polygenic selection can be best investigated in future studies.

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.

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.

Hunting for beneficial mutations: conditioning on SIFT scores when estimating the distribution of fitness effect of new mutations

The Distribution of Fitness Effects (DFE) of new mutations is a key parameter of molecular evolution. The DFE can in principle be estimated by comparing the Site Frequency Spectra (SFS) of putatively neutral and functional polymorphisms. Unfortunately the DFE is intrinsically hard to estimate, especially for beneficial mutations since these tend to be exceedingly rare. There is therefore a strong incentive to find out whether conditioning on properties of mutations that are independent of the SFS could provide additional information. In the present study, we developed a new measure based on SIFT scores. SIFT scores are assigned to nucleotide sites based on their level of conservation across a multi species alignment: the more conserved a site, the more likely mutations occurring at this site are deleterious and the lower the SIFT score. If one knows the ancestral state at a given site, one can assign a value to new mutations occurring at the site based on the change of SIFT score associated with the mutation. We called this new measure δ. We show that properties of the DFE as well as the flux of beneficial mutations across classes covary with δ and, hence, that SIFT scores are informative when estimating the fitness effect of new mutations. In particular, conditioning on SIFT scores can help to characterize beneficial mutations.

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.

Selective Sweeps Under Dominance and Inbreeding

A major research goal in evolutionary genetics is to uncover loci experiencing positive selection. One approach involves finding 'selective sweeps' patterns, which can either be 'hard sweeps' formed by de novo mutation, or 'soft sweeps' arising from recurrent mutation or existing standing variation. Existing theory generally assumes outcrossing populations, and it is unclear how dominance affects soft sweeps. We consider how arbitrary dominance and inbreeding via self-fertilization affect hard and soft sweep signatures. With increased self-fertilization, they are maintained over longer map distances due to reduced effective recombination and faster beneficial allele fixation times. Dominance can affect sweep patterns in outcrossers if the derived variant originates from either a single novel allele, or from recurrent mutation. These models highlight the challenges in distinguishing hard and soft sweeps, and propose methods to differentiate between scenarios.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

polyDFE: Inferring the Distribution of Fitness Effects and Properties of Beneficial Mutations from Polymorphism Data

The possible evolutionary trajectories a population can follow is determined by the fitness effects of new mutations. Their relative frequencies are best specified through a distribution of fitness effects (DFE) that spans deleterious, neutral, and beneficial mutations. As such, the DFE is key to several aspects of the evolution of a population, and particularly the rate of adaptive molecular evolution (α). Inference of DFE from patterns of polymorphism and divergence has been a longstanding goal of evolutionary genetics.polyDFE provides a flexible statistical framework to estimate the DFE and α from site frequency spectrum (SFS) data. Several probability distributions can be fitted to the data to model the DFE. The method also jointly estimates a series of nuisance parameters that model the effect of unknown demography as well data imperfections, in particular possible errors in polarizing SNPs. This chapter is organized as a tutorial for polyDFE. We start by briefly reviewing the concept of DFE, α, and the principles underlying the method, and then provide an example using central chimpanzees data (Tataru et al., Genetics 207(3):1103-1119, 2017; Bataillon et al., Genome Biol Evol 7(4):1122-1132, 2015) to guide the user through the different steps of an analysis: formatting the data as input to polyDFE, fitting different models, obtaining estimates of parameters uncertainty and performing statistical tests, as well as model averaging procedures to obtain robust estimates of model parameters.

Variation of the adaptive substitution rate between species and within genomes

The importance of adaptive mutations in molecular evolution is extensively debated. Recent developments in population genomics allow inferring rates of adaptive mutations by fitting a distribution of fitness effects to the observed patterns of polymorphism and divergence at sites under selection and sites assumed to evolve neutrally. Here, we summarize the current state-of-the-art of these methods and review the factors that affect the molecular rate of adaptation. Several studies have reported extensive cross-species variation in the proportion of adaptive amino-acid substitutions (α) and predicted that species with larger effective population sizes undergo less genetic drift and higher rates of adaptation. Disentangling the rates of positive and negative selection, however, revealed that mutations with deleterious effects are the main driver of this population size effect and that adaptive substitution rates vary comparatively little across species. Conversely, rates of adaptive substitution have been documented to vary substantially within genomes. On a genome-wide scale, gene density, recombination and mutation rate were observed to play a role in shaping molecular rates of adaptation, as predicted under models of linked selection. At the gene level, it has been reported that the gene functional category and the macromolecular structure substantially impact the rate of adaptive mutations. Here, we deliver a comprehensive review of methods used to infer the molecular adaptive rate, the potential drivers of adaptive evolution and how positive selection shapes molecular evolution within genes, across genes within species and between species.

Comparison of the Full Distribution of Fitness Effects of New Amino Acid Mutations Across Great Apes

The distribution of fitness effects (DFE) is central to many questions in evolutionary biology. However, little is known about the differences in DFE between closely related species. We use >9000 coding genes orthologous one-to-one across great apes, gibbons, and macaques to assess the stability of the DFE across great apes. We use the unfolded site frequency spectrum of polymorphic mutations (n = 8 haploid chromosomes per population) to estimate the DFE. We find that the shape of the deleterious DFE is strikingly similar across great apes. We confirm that effective population size (Ne ) is a strong predictor of the strength of negative selection, consistent with the nearly neutral theory. However, we also find that the strength of negative selection varies more than expected given the differences in Ne between species. Across species, mean fitness effects of new deleterious mutations covaries with Ne , consistent with positive epistasis among deleterious mutations. We find that the strength of negative selection for the smallest populations, bonobos and western chimpanzees, is higher than expected given their Ne This may result from a more efficient purging of strongly deleterious recessive variants in these populations. Forward simulations confirm that these findings are not artifacts of the way we are inferring Ne and DFE parameters. All findings are replicated using only GC-conservative mutations, thereby confirming that GC-biased gene conversion is not affecting our conclusions.

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.

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.

Patterns of Genome-Wide Nucleotide Diversity in the Gynodioecious Plant Thymus vulgaris Are Compatible with Recent Sweeps of Cytoplasmic Genes

Gynodioecy is a sexual dimorphism where females coexist with hermaphrodite individuals. In most cases, this dimorphism involves the interaction of cytoplasmic male sterility (CMS) genes and nuclear restorer genes. Two scenarios can account for how these interactions maintain gynodioecy. Either CMS genes recurrently enter populations at low frequency via mutation or migration and go to fixation unimpeded (successive sweeps), or CMS genes maintain polymorphism over evolutionary time through interactions with a nuclear restorer allele (balanced polymorphism). To distinguish between these scenarios, we used transcriptome sequencing in gynodioecious Thymus vulgaris and surveyed genome-wide diversity in 18 naturally occurring individuals sampled from populations at a local geographic scale. We contrast the amount and patterns of nucleotide diversity in the nuclear and cytoplasmic genome, and find ample diversity at the nuclear level (π = 0.019 at synonymous sites) but reduced genetic diversity and an excess of rare polymorphisms in the cytoplasmic genome relative to the nuclear genome. Our finding is incompatible with the maintenance of gynodioecy via scenarios invoking long-term balancing selection, and instead suggests the recent fixation of CMS lineages in the populations studied.

Identifying Drivers of Parallel Evolution: A Regression Model Approach

Parallel evolution, defined as identical changes arising in independent populations, is often attributed to similar selective pressures favoring the fixation of identical genetic changes. However, some level of parallel evolution is also expected if mutation rates are heterogeneous across regions of the genome. Theory suggests that mutation and selection can have equal impacts on patterns of parallel evolution; however, empirical studies have yet to jointly quantify the importance of these two processes. Here, we introduce several statistical models to examine the contributions of mutation and selection heterogeneity to shaping parallel evolutionary changes at the gene-level. Using this framework, we analyze published data from forty experimentally evolved Saccharomyces cerevisiae populations. We can partition the effects of a number of genomic variables into those affecting patterns of parallel evolution via effects on the rate of arising mutations, and those affecting the retention versus loss of the arising mutations (i.e., selection). Our results suggest that gene-to-gene heterogeneity in both mutation and selection, associated with gene length, recombination rate, and number of protein domains drive parallel evolution at both synonymous and nonsynonymous sites. While there are still a number of parallel changes that are not well described, we show that allowing for heterogeneous rates of mutation and selection can provide improved predictions of the prevalence and degree of parallel evolution.

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

The Wright–Fisher 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 Wright–Fisher 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 Wright–Fisher model, and we consider these in turn. We begin our review with the basic bi-allelic Wright–Fisher 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.

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.

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.

Analysis of large-scale next-generation sequencing datasets are finding more examples of adaptive evolution at the genomic level.

Advances in theoretical work has demonstrated how self-fertilisation affects different aspects of adaptation in these organisms, compared to outcrossers.

Current software and statistical methods do not take different mating systems into account, which risks mischaracterising the presence or strength of adaptive mutations from genome scans.

Development of new mathematical and statistical methods that explicitly consider self-fertilization and associated demographic effects will enable researchers to more accurately quantify adaptation in these organisms.

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.

Epistasis and the Structure of Fitness Landscapes: Are Experimental Fitness Landscapes Compatible with Fisher's Geometric Model?

The fitness landscape defines the relationship between genotypes and fitness in a given environment and underlies fundamental quantities such as the distribution of selection coefficient and the magnitude and type of epistasis. A better understanding of variation in landscape structure across species and environments is thus necessary to understand and predict how populations will adapt. An increasing number of experiments investigate the properties of fitness landscapes by identifying mutations, constructing genotypes with combinations of these mutations, and measuring the fitness of these genotypes. Yet these empirical landscapes represent a very small sample of the vast space of all possible genotypes, and this sample is often biased by the protocol used to identify mutations. Here we develop a rigorous statistical framework based on Approximate Bayesian Computation to address these concerns and use this flexible framework to fit a broad class of phenotypic fitness models (including Fisher's model) to 26 empirical landscapes representing nine diverse biological systems. Despite uncertainty owing to the small size of most published empirical landscapes, the inferred landscapes have similar structure in similar biological systems. Surprisingly, goodness-of-fit tests reveal that this class of phenotypic models, which has been successful so far in interpreting experimental data, is a plausible in only three of nine biological systems. More precisely, although Fisher's model was able to explain several statistical properties of the landscapes-including the mean and SD of selection and epistasis coefficients-it was often unable to explain the full structure of fitness landscapes.

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.

Inference of purifying and positive selection in three subspecies of chimpanzees (Pan troglodytes) from exome sequencing

We study genome-wide nucleotide diversity in three subspecies of extant chimpanzees using exome capture. After strict filtering, Single Nucleotide Polymorphisms and indels were called and genotyped for greater than 50% of exons at a mean coverage of 35× per individual. Central chimpanzees (Pan troglodytes troglodytes) are the most polymorphic (nucleotide diversity, θ_w = 0.0023 per site) followed by Eastern (P. t. schweinfurthii) chimpanzees (θ_w = 0.0016) and Western (P. t. verus) chimpanzees (θ_w = 0.0008). A demographic scenario of divergence without gene flow fits the patterns of autosomal synonymous nucleotide diversity well except for a signal of recent gene flow from Western into Eastern chimpanzees. The striking contrast in X-linked versus autosomal polymorphism and divergence previously reported in Central chimpanzees is also found in Eastern and Western chimpanzees. We show that the direction of selection statistic exhibits a strong nonmonotonic relationship with the strength of purifying selection S, making it inappropriate for estimating S. We instead use counts in synonymous versus nonsynonymous frequency classes to infer the distribution of S coefficients acting on nonsynonymous mutations in each subspecies. The strength of purifying selection we infer is congruent with the differences in effective sizes of each subspecies: Central chimpanzees are undergoing the strongest purifying selection followed by Eastern and Western chimpanzees. Coding indels show stronger selection against indels changing the reading frame than observed in human populations.

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.

Classical population genetics models indicate that the efficiency of selection, and hence adaptation, depends on a number of non-selective factors, such as the size of a population or the intensity of recombination. In the last 10 years, evidence has accumulated that another mechanism called GC-Biased Gene Conversion (gBGC) can interfere with selection and even mimic its effects. This phenomenon, which arises from a particularity of the recombination machinery, was first thought to be restricted to sexual eukaryotic organisms. Here, we show that this mechanism probably exists in Bacteria and has a strong impact on their genome evolution. This discovery not only explains many previously unconnected features of bacterial genome evolution, but also highlights the importance of non-adaptive evolutionary processes in Bacteria.

Properties of selected mutations and genotypic landscapes under Fisher's geometric model

The fitness landscape-the mapping between genotypes and fitness-determines properties of the process of adaptation. Several small genotypic fitness landscapes have recently been built by selecting a handful of beneficial mutations and measuring fitness of all combinations of these mutations. Here, we generate several testable predictions for the properties of these small genotypic landscapes under Fisher's geometric model of adaptation. When the ancestral strain is far from the fitness optimum, we analytically compute the fitness effect of selected mutations and their epistatic interactions. Epistasis may be negative or positive on average depending on the distance of the ancestral genotype to the optimum and whether mutations were independently selected, or coselected in an adaptive walk. Simulations show that genotypic landscapes built from Fisher's model are very close to an additive landscape when the ancestral strain is far from the optimum. However, when it is close to the optimum, a large diversity of landscape with substantial roughness and sign epistasis emerged. Strikingly, small genotypic landscapes built from several replicate adaptive walks on the same underlying landscape were highly variable, suggesting that several realizations of small genotypic landscapes are needed to gain information about the underlying architecture of the fitness landscape.

Effects of new mutations on fitness: insights from models and data

The rates and properties of new mutations affecting fitness have implications for a number of outstanding questions in evolutionary biology. Obtaining estimates of mutation rates and effects has historically been challenging, and little theory has been available for predicting the distribution of fitness effects (DFE); however, there have been recent advances on both fronts. Extreme-value theory predicts the DFE of beneficial mutations in well-adapted populations, while phenotypic fitness landscape models make predictions for the DFE of all mutations as a function of the initial level of adaptation and the strength of stabilizing selection on traits underlying fitness. Direct experimental evidence confirms predictions on the DFE of beneficial mutations and favors distributions that are roughly exponential but bounded on the right. A growing number of studies infer the DFE using genomic patterns of polymorphism and divergence, recovering a wide range of DFE. Future work should be aimed at identifying factors driving the observed variation in the DFE. We emphasize the need for further theory explicitly incorporating the effects of partial pleiotropy and heterogeneity in the environment on the expected DFE.

Rates of fitness decline and rebound suggest pervasive epistasis

Unraveling the factors that determine the rate of adaptation is a major question in evolutionary biology. One key parameter is the effect of a new mutation on fitness, which invariably depends on the environment and genetic background. The fate of a mutation also depends on population size, which determines the amount of drift it will experience. Here, we manipulate both population size and genotype composition and follow adaptation of 23 distinct Escherichia coli genotypes. These have previously accumulated mutations under intense genetic drift and encompass a substantial fitness variation. A simple rule is uncovered: the net fitness change is negatively correlated with the fitness of the genotype in which new mutations appear—a signature of epistasis. We find that Fisher's geometrical model can account for the observed patterns of fitness change and infer the parameters of this model that best fit the data, using Approximate Bayesian Computation. We estimate a genomic mutation rate of 0.01 per generation for fitness altering mutations, albeit with a large confidence interval, a mean fitness effect of mutations of −0.01, and an effective number of traits nine in mutS⁻E. coli. This framework can be extended to confront a broader range of models with data and test different classes of fitness landscape models.

Selection, genome-wide fitness effects and evolutionary rates in the model legume Medicago truncatula

Sequence data for >20 000 annotated genes from 56 accessions of Medicago truncatula were used to identify potential targets of positive selection, the determinants of evolutionary rate variation and the relative importance of positive and purifying selection in shaping nucleotide diversity. Based upon patterns of intraspecific diversity and interspecific divergence, c. 50-75% of nonsynonymous polymorphisms are subject to strong purifying selection and 1% of the sampled genes harbour a signature of positive selection. Combining polymorphism with expression data, we estimated the distribution of fitness effects and found that the proportion of deleterious mutations is significantly greater for expressed genes than for genes with undetected transcripts (nonexpressed) in a previous RNA-seq experiment and greater for broadly expressed genes than those expressed in only a single tissue. Expression level is the strongest correlate of evolutionary rates at nonsynonymous sites, and despite multiple genomic features being significantly correlated with evolutionary rates, they explain less than 20% of the variation in nonsynonymous rates (dN) and <15% of the variation in either synonymous rates (dS) or dN:dS. Among putative targets of selection were genes involved in defence against pathogens and herbivores, genes with roles in mediating the relationship with rhizobial symbionts and one-third of annotated histone-lysine methyltransferases. Adaptive evolution of the methyltransferases suggests that positive selection in gene expression may have occurred through evolution of enzymes involved in epigenetic modification.

As it happens: current directions in experimental evolution

Recent decades have seen a significant rise in studies in which evolution is observed and analysed directly-as it happens-under replicated, controlled conditions. Such 'experimental evolution' approaches offer a degree of resolution of evolutionary processes and their underlying genetics that is difficult or even impossible to achieve in more traditional comparative and retrospective analyses. In principle, experimental populations can be monitored for phenotypic and genetic changes with any desired level of replication and measurement precision, facilitating progress on fundamental and previously unresolved questions in evolutionary biology. Here, we summarize 10 invited papers in which experimental evolution is making significant progress on a variety of fundamental questions. We conclude by briefly considering future directions in this very active field of research, emphasizing the importance of quantitative tests of theories and the emerging role of genome-wide re-sequencing.

Contrasted patterns of selective pressure in three recent paralogous gene pairs in the Medicago genus (L.)

Background

Gene duplications are a molecular mechanism potentially mediating generation of functional novelty. However, the probabilities of maintenance and functional divergence of duplicated genes are shaped by selective pressures acting on gene copies immediately after the duplication event. The ratio of non-synonymous to synonymous substitution rates in protein-coding sequences provides a means to investigate selective pressures based on genic sequences. Three molecular signatures can reveal early stages of functional divergence between gene copies: change in the level of purifying selection between paralogous genes, occurrence of positive selection, and transient relaxed purifying selection following gene duplication. We studied three pairs of genes that are known to be involved in an interaction with symbiotic bacteria and were recently duplicated in the history of the Medicago genus (Fabaceae). We sequenced two pairs of polygalacturonase genes (Pg11-Pg3 and Pg11a-Pg11c) and one pair of auxine transporter-like genes (Lax2-Lax4) in 17 species belonging to the Medicago genus, and sought for molecular signatures of differentiation between copies.

Results

Selective histories revealed by these three signatures of molecular differentiation were found to be markedly different between each pair of paralogs. We found sites under positive selection in the Pg11 paralogs while Pg3 has mainly evolved under purifying selection. The most recent paralogs examined Pg11a and Pg11c, are both undergoing positive selection and might be acquiring new functions. Lax2 and Lax4 paralogs are both under strong purifying selection, but still underwent a temporary relaxation of purifying selection immediately after duplication.

Conclusions

This study illustrates the variety of selective pressures undergone by duplicated genes and the effect of age of the duplication. We found that relaxation of selective constraints immediately after duplication might promote adaptive divergence.

"Ménage à trois": the presence/absence of thyme shapes the mutualistic interaction between the host plant Medicago truncatula (Fabaceae) and its symbiotic bacterium Sinorhizobium meliloti

The long-term maintenance of specialized mutualisms remains an evolutionary puzzle. Recent focus has been on factors governing the stability of these mutualisms, including sanctions by the host, partner choice, and coevolutionary constraint, that is, the genetic correlation (r(G)) between fitness of both partners. So far these studies have been typically carried out in a single environment. Here, we ask if the genetic correlation between fitness of the host plant Medicago truncatula (Fabaceae) and its bacterial symbiont Sinorhizobium meliloti is affected by the presence/absence of a monoterpene (carvacrol) leached into the soil by Thymus vulgaris-a common plant of the Mediterranean vegetation, often co-occuring with Medicago. We show that the presence of carvacrol in the soil dramatically affects fitness of the rhizobial partner and increases the magnitude of r(G) between plant and rhizobia fitness (r(G) = 0.02 ± 0.05 vs. r(G) = 0.57 ± 0.02). This finding emphasizes the importance of heterogeneity in the biotic environment for understanding the evolution of species interactions.

Purifying selection and molecular adaptation in the genome of Verminephrobacter, the heritable symbiotic bacteria of earthworms

While genomic erosion is common among intracellular symbionts, patterns of genome evolution in heritable extracellular endosymbionts remain elusive. We study vertically transmitted extracellular endosymbionts (Verminephrobacter, Betaproteobacteria) that form a beneficial, species-specific, and evolutionarily old (60–130 Myr) association with earthworms. We assembled a draft genome of Verminephrobacter aporrectodeae and compared it with the genomes of Verminephrobacter eiseniae and two nonsymbiotic close relatives (Acidovorax). Similar to V. eiseniae, the V. aporrectodeae genome was not markedly reduced in size and showed no A–T bias. We characterized the strength of purifying selection (ω = dN/dS) and codon usage bias in 876 orthologous genes. Symbiont genomes exhibited strong purifying selection (ω = 0.09 ± 0.07), although transition to symbiosis entailed relaxation of purifying selection as evidenced by 50% higher ω values and less codon usage bias in symbiont compared with reference genomes. Relaxation was not evenly distributed among functional gene categories but was overrepresented in genes involved in signal transduction and cell envelope biogenesis. The same gene categories also harbored instances of positive selection in the Verminephrobacter clade. In total, positive selection was detected in 89 genes, including also genes involved in DNA metabolism, tRNA modification, and TonB-dependent iron uptake, potentially highlighting functions important in symbiosis. Our results suggest that the transition to symbiosis was accompanied by molecular adaptation, while purifying selection was only moderately relaxed, despite the evolutionary age and stability of the host association. We hypothesize that biparental transmission of symbionts and rare genetic mixing during transmission can prevent genome erosion in heritable symbionts.

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.

Genomic determinants of protein evolution and polymorphism in Arabidopsis

Recent results from Drosophila suggest that positive selection has a substantial impact on genomic patterns of polymorphism and divergence. However, species with smaller population sizes and/or stronger population structure may not be expected to exhibit Drosophila-like patterns of sequence variation. We test this prediction and identify determinants of levels of polymorphism and rates of protein evolution using genomic data from Arabidopsis thaliana and the recently sequenced Arabidopsis lyrata genome. We find that, in contrast to Drosophila, there is no negative relationship between nonsynonymous divergence and silent polymorphism at any spatial scale examined. Instead, synonymous divergence is a major predictor of silent polymorphism, which suggests variation in mutation rate as the main determinant of silent variation. Variation in rates of protein divergence is mainly correlated with gene expression level and breadth, consistent with results for a broad range of taxa, and map-based estimates of recombination rate are only weakly correlated with nonsynonymous divergence. Variation in mutation rates and the strength of purifying selection seem to be major drivers of patterns of polymorphism and divergence in Arabidopsis. Nevertheless, a model allowing for varying negative and positive selection by functional gene category explains the data better than a homogeneous model, implying the action of positive selection on a subset of genes. Genes involved in disease resistance and abiotic stress display high proportions of adaptive substitution. Our results are important for a general understanding of the determinants of rates of protein evolution and the impact of selection on patterns of polymorphism and divergence.

Molecular adaptation in flowering and symbiotic recognition pathways: insights from patterns of polymorphism in the legume Medicago truncatula

Background

We studied patterns of molecular adaptation in the wild Mediterranean legume Medicago truncatula. We focused on two phenotypic traits that are not functionally linked: flowering time and perception of symbiotic microbes. Phenology is an important fitness component, especially for annual plants, and many instances of molecular adaptation have been reported for genes involved in flowering pathways. While perception of symbiotic microbes is also integral to adaptation in many plant species, very few reports of molecular adaptation exist for symbiotic genes. Here we used data from 57 individuals and 53 gene fragments to quantify the overall strength of both positive and purifying selection in M. truncatula and asked if footprints of positive selection can be detected at key genes of rhizobia recognition pathways.

Results

We examined nucleotide variation among 57 accessions from natural populations in 53 gene fragments: 5 genes involved in nitrogen-fixing bacteria recognition, 11 genes involved in flowering, and 37 genes used as control loci. We detected 1757 polymorphic sites yielding an average nucleotide diversity (pi) of 0.003 per site. Non-synonymous variation is under sizable purifying selection with 90% of amino-acid changing mutations being strongly selected against. Accessions were structured in two groups consistent with geographical origins. Each of these two groups harboured an excess of rare alleles, relative to expectations of a constant-sized population, suggesting recent population expansion. Using coalescent simulations and an approximate Bayesian computation framework we detected several instances of genes departing from selective neutrality within each group and showed that the polymorphism of two nodulation and four flowering genes has probably been shaped by recent positive selection.

Conclusion

We quantify the intensity of purifying selection in the M. truncatula genome and show that putative footprints of natural selection can be detected at different time scales in both flowering and symbiotic pathways.

Insertion and deletion processes in recent human history

Background

Although insertions and deletions (indels) account for a sizable portion of genetic changes within and among species, they have received little attention because they are difficult to type, are alignment dependent and their underlying mutational process is poorly understood. A fundamental question in this respect is whether insertions and deletions are governed by similar or different processes and, if so, what these differences are.

Methodology/Principal Findings

We use published resequencing data from Seattle SNPs and NIEHS human polymorphism databases to construct a genomewide data set of short polymorphic insertions and deletions in the human genome (n = 6228). We contrast these patterns of polymorphism with insertions and deletions fixed in the same regions since the divergence of human and chimpanzee (n = 10546). The macaque genome is used to resolve all indels into insertions and deletions. We find that the ratio of deletions to insertions is greater within humans than between human and chimpanzee. Deletions segregate at lower frequency in humans, providing evidence for deletions being under stronger purifying selection than insertions. The insertion and deletion rates correlate with several genomic features and we find evidence that both insertions and deletions are associated with point mutations. Finally, we find no evidence for a direct effect of the local recombination rate on the insertion and deletion rate.

Conclusions/Significance

Our data strongly suggest that deletions are more deleterious than insertions but that insertions and deletions are otherwise generally governed by the same genomic factors.

The properties of adaptive walks in evolving populations of fungus

The rarity of beneficial mutations has frustrated efforts to develop a quantitative theory of adaptation. Recent models of adaptive walks, the sequential substitution of beneficial mutations by selection, make two compelling predictions: adaptive walks should be short, and fitness increases should become exponentially smaller as successive mutations fix. We estimated the number and fitness effects of beneficial mutations in each of 118 replicate lineages of Aspergillus nidulans evolving for approximately 800 generations at two population sizes using a novel maximum likelihood framework, the results of which were confirmed experimentally using sexual crosses. We find that adaptive walks do indeed tend to be short, and fitness increases become smaller as successive mutations fix. Moreover, we show that these patterns are associated with a decreasing supply of beneficial mutations as the population adapts. We also provide empirical distributions of fitness effects among mutations fixed at each step. Our results provide a first glimpse into the properties of multiple steps in an adaptive walk in asexual populations and lend empirical support to models of adaptation involving selection towards a single optimum phenotype. In practical terms, our results suggest that the bulk of adaptation is likely to be accomplished within the first few steps.

A comparative view of the evolution of grasses under domestication

Crop grasses were among the first plants to be domesticated c. 12,000 yr ago, and they still represent the main staple crops for humans. During domestication, as did many other crops, grasses went through dramatic genetic and phenotypic changes. The recent massive increase in genomic data has provided new tools to investigate the genetic basis and consequences of domestication. Beyond the genetics of domestication, many aspects of grass biology, including their phylogeny and developmental biology, are also increasingly well studied, offering a unique opportunity to analyse the domestication process in a comparative way. Taking such a comparative point of view, we review the history of domesticated grasses and how domestication affected their phenotypic and genomic diversity. Considering recent theoretical developments and the accumulation of genetic data, we revisit more specifically the role of mating systems in the domestication process. We close by suggesting future directions for the study of domestication in grasses.

Adaptive evolution of the symbiotic gene NORK is not correlated with shifts of rhizobial specificity in the genus Medicago

Background

The NODULATION RECEPTOR KINASE (NORK) gene encodes a Leucine-Rich Repeat (LRR)-containing receptor-like protein and controls the infection by symbiotic rhizobia and endomycorrhizal fungi in Legumes. The occurrence of numerous amino acid changes driven by directional selection has been reported in this gene, using a limited number of messenger RNA sequences, but the functional reason of these changes remains obscure. The Medicago genus, where changes in rhizobial associations have been previously examined, is a good model to test whether the evolution of NORK is influenced by rhizobial interactions.

Results

We sequenced a region of 3610 nucleotides (encoding a 392 amino acid-long region of the NORK protein) in 32 Medicago species. We confirm that positive selection in NORK has occurred within the Medicago genus and find that the amino acid positions targeted by selection occur in sites outside of solvent-exposed regions in LRRs, and other sites in the N-terminal region of the protein. We tested if branches of the Medicago phylogeny where changes of rhizobial symbionts occurred displayed accelerated rates of amino acid substitutions. Only one branch out of five tested, leading to M. noeana, displays such a pattern. Among other branches, the most likely for having undergone positive selection is not associated with documented shift of rhizobial specificity.

Conclusion

Adaptive changes in the sequence of the NORK receptor have involved the LRRs, but targeted different sites than in most previous studies of LRR proteins evolution. The fact that positive selection in NORK tends not to be associated to changes in rhizobial specificity indicates that this gene was probably not involved in evolving rhizobial preferences. Other explanations (e.g. coevolutionary arms race) must be tested to explain the adaptive evolution of NORK.