"Reverse ecology" and the power of population genomics

Context matters: assessing the impacts of genomic background and ecology on microbial biosynthetic gene cluster evolution

Encoded within many microbial genomes, biosynthetic gene clusters (BGCs) underlie the synthesis of various secondary metabolites that often mediate ecologically important functions. Several studies and bioinformatics methods developed over the past decade have advanced our understanding of both microbial pangenomes and BGC evolution. In this minireview, we first highlight challenges in broad evolutionary analysis of BGCs, including delineation of BGC boundaries and clustering of BGCs across genomes. We further summarize key findings from microbial comparative genomics studies on BGC conservation across taxa and habitats and discuss the potential fitness effects of BGCs in different settings. Afterward, recent research showing the importance of genomic context on the production of secondary metabolites and the evolution of BGCs is highlighted. These studies draw parallels to recent, broader, investigations on gene-to-gene associations within microbial pangenomes. Finally, we describe mechanisms by which microbial pangenomes and BGCs evolve, ranging from the acquisition or origination of entire BGCs to micro-evolutionary trends of individual biosynthetic genes. An outlook on how expansions in the biosynthetic capabilities of some taxa might support theories that open pangenomes are the result of adaptive evolution is also discussed. We conclude with remarks about how future work leveraging longitudinal metagenomics across diverse ecosystems is likely to significantly improve our understanding on the evolution of microbial genomes and BGCs.

Beyond genes-for-behaviour: The potential for genomics to resolve long-standing questions in avian brood parasitism

Behavioural ecology by definition of its founding 'Tinbergian framework' is an integrative field, however, it lags behind in incorporating genomic methods. 'Finding the gene/s for a behaviour' is still rarely feasible or cost-effective in the wild but as we show here, genomic data can be used to address broader questions. Here we use avian brood parasitism, a model system in behavioural ecology as a case study to highlight how behavioural ecologists could use the full potential of state-of-the-art genomic tools. Brood parasite-host interactions are one of the most easily observable and amenable natural laboratories of antagonistic coevolution, and as such have intrigued evolutionary biologists for decades. Using worked examples, we demonstrate how genomic data can be used to study the causes and mechanisms of (co)evolutionary adaptation and answer three key questions for the field: (i) Where and when should brood parasitism evolve?, (ii) When and how should hosts defend?, and (iii) Will coevolution persist with ecological change? In doing so, we discuss how behavioural and molecular ecologists can collaborate to integrate Tinbergen's questions and achieve the coherent science that he promoted to solve the mysteries of nature.

Rapid Adaptation and Interspecific Introgression in the North American Crop Pest Helicoverpa zea

Insect crop pests threaten global food security. This threat is amplified through the spread of nonnative species and through adaptation of native pests to control measures. Adaptations such as pesticide resistance can result from selection on variation within a population, or through gene flow from another population. We investigate these processes in an economically important noctuid crop pest, Helicoverpa zea, which has evolved resistance to a wide range of pesticides. Its sister species Helicoverpa armigera, first detected as an invasive species in Brazil in 2013, introduced the pyrethroid-resistance gene CYP337B3 to South American H. zea via adaptive introgression. To understand whether this could contribute to pesticide resistance in North America, we sequenced 237 H. zea genomes across 10 sample sites. We report H. armigera introgression into the North American H. zea population. Two individuals sampled in Texas in 2019 carry H. armigera haplotypes in a 4 Mbp region containing CYP337B3. Next, we identify signatures of selection in the panmictic population of nonadmixed H. zea, identifying a selective sweep at a second cytochrome P450 gene: CYP333B3. We estimate that its derived allele conferred a ∼5% fitness advantage and show that this estimate explains independently observed rare nonsynonymous CYP333B3 mutations approaching fixation over a ∼20-year period. We also detect putative signatures of selection at a kinesin gene associated with Bt resistance. Overall, we document two mechanisms of rapid adaptation: the introduction of fitness-enhancing alleles through interspecific introgression, and selection on intraspecific variation.

Functional genomic diversity is correlated with neutral genomic diversity in populations of an endangered rattlesnake

Theory predicts that genetic erosion in small, isolated populations of endangered species can be assessed using estimates of neutral genetic variation, yet this widely used approach has recently been questioned in the genomics era. Here, we leverage a chromosome-level genome assembly of an endangered rattlesnake (Sistrurus catenatus) combined with whole genome resequencing data (N = 110 individuals) to evaluate the relationship between levels of genome-wide neutral and functional diversity over historical and future timescales. As predicted, we found positive correlations between genome-wide estimates of neutral genetic diversity (π) and inferred levels of adaptive variation and an estimate of inbreeding mutation load, and a negative relationship between neutral diversity and an estimate of drift mutation load. However, these correlations were half as strong for projected future levels of neutral diversity based on contemporary effective population sizes. Broadly, our results confirm that estimates of neutral genetic diversity provide an accurate measure of genetic erosion in populations of a threatened vertebrate. They also provide nuance to the neutral-functional diversity controversy by suggesting that while these correlations exist, anthropogenetic impacts may have weakened these associations in the recent past and into the future.

The evolution of anaerobic growth in Saccharomycotina yeasts

Humans rely on the ability of budding yeasts to grow without oxygen in industrial scale fermentations that produce beverages, foods, and biofuels. Oxygen is deeply woven into the energy metabolism and biosynthetic capabilities of budding yeasts. While diverse ecological habitats may provide wide varieties of different carbon and nitrogen sources for yeasts to utilize, there is no direct substitute for molecular oxygen, only a range of availability. Understanding how a small subset of budding yeasts evolved the ability to grow without oxygen could expand the set of useful species in industrial scale fermentations as well as provide insight into the cryptic field of yeast ecology. However, we still do not yet appreciate the full breadth of species that can growth without oxygen, what genes underlie this adaptation, and how these genes have evolved.

Metagenomic Discovery of "Candidatus Parvarchaeales"-Related Lineages Sheds Light on Adaptation and Diversification from Neutral-Thermal to Acidic-Mesothermal Environments

"Candidatus Parvarchaeales" microbes, representing a DPANN archaeal group with limited metabolic potential and reliance on hosts for their growth, were initially found in acid mine drainage (AMD). Due to the lack of representatives, however, their ecological roles and adaptation to extreme habitats such as AMD as well as how they diverge across the lineage remain largely unexplored. By applying genome-resolved metagenomics, 28 Parvarchaeales-associated metagenome-assembled genomes (MAGs) representing two orders and five genera were recovered. Among them, we identified three new genera and proposed the names "Candidatus Jingweiarchaeum," "Candidatus Haiyanarchaeum," and "Candidatus Rehaiarchaeum," with the former two belonging to a new order, "Candidatus Jingweiarchaeales." Further analyses of the metabolic potentials revealed substantial niche differentiation between Jingweiarchaeales and Parvarchaeales. Jingweiarchaeales may rely on fermentation, salvage pathways, partial glycolysis, and the pentose phosphate pathway (PPP) for energy conservation reservation, while the metabolic potentials of Parvarchaeales might be more versatile. Comparative genomic analyses suggested that Jingweiarchaeales favor habitats with higher temperatures and that Parvarchaeales are better adapted to acidic environments. We further revealed that the thermal adaptation of these lineages, especially Haiyanarchaeum, might rely on genomic features such as the usage of specific amino acids, genome streamlining, and hyperthermophile featured genes such as rgy. Notably, the adaptation of Parvarchaeales to acidic environments was possibly driven by horizontal gene transfer (HGT). The reconstruction of ancestral states demonstrated that both may have originated from thermal and neutral environments and later spread to mesothermal and acidic environments. These evolutionary processes may also be accompanied by adaptation to oxygen-rich environments via HGT. IMPORTANCE "Candidatus Parvarchaeales" microbes may represent a lineage uniquely distributed in extreme environments such as AMD and hot springs. However, little is known about the strategies and processes of how they adapted to these extreme environments. By the discovery of potential new order-level lineages, "Ca. Jingweiarchaeales," and in-depth comparative genomic analysis, we unveiled the functional differentiation of these lineages. Furthermore, we show that the adaptation of these lineages to high-temperature and acidic environments was driven by different strategies, with the former relying more on genomic characteristics such as genome streamlining and amino acid compositions and the latter relying more on the acquisition of genes associated with acid tolerance. Finally, by the reconstruction of the ancestral states of the optimal growth temperature (OGT) and isoelectric point (pI), we showed the potential evolutionary process of Parvarchaeales-related lineages with regard to the shift from the high-temperature environment of their common ancestors to low-temperature (potentially acidic) environments.

Genome-phenotype-environment associations identify signatures of selection in a panmictic population of threespine stickleback

Adaptive genetic divergence occurs when selection imposed by the environment causes the genomic component of the phenotype to differentiate. However, genomic signatures of natural selection are usually identified without information on which trait is responding to selection by which selective agent(s). Here, we integrate whole-genome sequencing with phenomics and measures of putative selective agents to assess the extent of adaptive divergence in threespine stickleback occupying the highly heterogeneous lake Mývatn, NE Iceland. We find negligible genome wide divergence, yet multiple traits (body size, gill raker structure and defence traits) were divergent along known ecological gradients (temperature, predatory bird densities and water depth). SNP based heritability of all measured traits was high (h²  = 0.42-0.65), indicating adaptive potential for all traits. Environment-association analyses further identified thousands of loci putatively involved in selection, related to genes linked to, for instance, neuron development and protein phosphorylation. Finally, we found that loci linked to water depth were concurrently associated with pelvic spine length variation - supporting the conclusion that divergence in pelvic spine length occurred in the face of gene flow. Our results suggest that whilst there is substantial genetic variation in the traits measured, phenotypic divergence of Mývatn stickleback is mostly weakly associated with environmental gradients, potentially as a result of substantial gene flow. Our study illustrates the value of integrative studies that combine genomic assays of multivariate trait variation with landscape genomics.

Genome sequencing and resequencing identified three horizontal gene transfers and uncovered the genetic mechanism on the intraspecies adaptive evolution of Gastrodia elata Blume

Horizontal gene transfer is a rare and useful genetic mechanism in higher plants. Gastrodia elata Blume (GE) (Orchidaceae), well known as traditional medicinal material in East Asia, adopts a heterotrophic lifestyle, thus being considered to be more prone to horizontal gene transfer (HGT). GE is a "polytypic species" that currently comprised of five recognized forms according to the plant morphology. G. elata Blume forma elata (GEE) and G. elata Bl.f.glauca (GEG) are two common forms that naturally grow in different habitats with difference in altitude and latitude. G. elata Bl.f.viridis (GEV) often occurs sporadically in cultivated populations of GEE and GEG. However, the genetic relationships and genetic mechanism underpinned the divergent ecological adaptations of GEE and GEG have not been revealed. Here, we assembled a chromosome-level draft genome of GEE with 1.04 Gb. Among predicted 17,895 protein coding genes, we identified three HGTs. Meanwhile, we resequenced 10 GEE accessions, nine GEG accessions, and 10 GEV accessions, and identified two independent genetic lineages: GEG_pedigree (GEG individuals and GEV individuals collected from GEG populations) and GEE_pedigree (GEE individuals and GEV individuals collected from GEE populations), which strongly support the taxonomic status of GEE and GEG as subspecies, not as different forms. In highly differentiated genomic regions of GEE_pedigree and GEG_pedigree, three chalcone synthase-encoding genes and one Phox/Bem1p (PB1) domain of encoding Auxin (AUX)/Indoleacetic acid (IAA) were identified in selection sweeping genome regions, which suggested that differentiation between GEE_pedigree and GEG_pedigree was promoted by the selection of genes related to photoresponse and growth and development. Overall, this new genome would be helpful for breeding and utilization of GE and the new findings would deepen the understanding about ecological adaptation and evolution of GE.

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Highly fecund natural populations characterized by high early mortality abound, yet our knowledge about their recruitment dynamics is somewhat rudimentary. This knowledge gap has implications for our understanding of genetic variation, population connectivity, local adaptation, and the resilience of highly fecund populations. The concept of sweepstakes reproductive success, which posits a considerable variance and skew in individual reproductive output, is key to understanding the distribution of individual reproductive success. However, it still needs to be determined whether highly fecund organisms reproduce through sweepstakes and, if they do, the relative roles of neutral and selective sweepstakes. Here, we use coalescent-based statistical analysis of population genomic data to show that selective sweepstakes likely explain recruitment dynamics in the highly fecund Atlantic cod. We show that the Kingman coalescent (modelling no sweepstakes) and the Xi-Beta coalescent (modelling random sweepstakes), including complex demography and background selection, do not provide an adequate fit for the data. The Durrett-Schweinsberg coalescent, in which selective sweepstakes result from recurrent and pervasive selective sweeps of new mutations, offers greater explanatory power. Our results show that models of sweepstakes reproduction and multiple-merger coalescents are relevant and necessary for understanding genetic diversity in highly fecund natural populations. These findings have fundamental implications for understanding the recruitment variation of fish stocks and general evolutionary genomics of high-fecundity organisms.

Testing hypotheses of a coevolutionary key innovation reveals a complex suite of traits involved in defusing the mustard oil bomb

Coevolutionary interactions are responsible for much of the Earth's biodiversity, with key innovations driving speciation bursts on both sides of the interaction. One persistent question is whether macroevolutionary traits identified as key innovations accurately predict functional performance and selection dynamics within species, as this necessitates characterizing their function, investigating their fitness consequences, and exploring the selection dynamics acting upon them. Here, we used CRISPR-Cas9 mediating nonhomologous end joining (NHEJ) in the butterfly species Pieris brassicae to knock out and directly assess the function and fitness impacts of nitrile specifier protein (NSP) and major allergen (MA). These are two closely related genes that facilitate glucosinolate (GSL) detoxification capacity, which is a key innovation in mustard feeding Pierinae butterflies. We find NSP and MA are both required for survival on plants containing GSLs, with expression differences arising in response to variable GSL profiles, concordant with detoxification performance. Importantly, this concordance was only observed when using natural host plants, likely reflecting the complexity of how these enzymes interact with natural plant variation in GSLs and myrosinases. Finally, signatures of positive selection for NSP and MA were detected across Pieris species, consistent with these genes' importance in recent coevolutionary interactions. Thus, the war between these butterflies and their host plants involves more than the mere presence of chemical defenses and detoxification mechanisms, as their regulation and activation represent key components of complex interactions. We find that inclusion of these dynamics, in ecologically relevant assays, is necessary for coevolutionary insights in this system and likely others.

Yeasts from temperate forests

Yeasts are ubiquitous in temperate forests. While this broad habitat is well-defined, the yeasts inhabiting it and their life cycles, niches, and contributions to ecosystem functioning are less understood. Yeasts are present on nearly all sampled substrates in temperate forests worldwide. They associate with soils, macroorganisms, and other habitats, and no doubt contribute to broader ecosystem-wide processes. Researchers have gathered information leading to hypotheses about yeasts' niches and their life cycles based on physiological observations in the laboratory as well as genomic analyses, but the challenge remains to test these hypotheses in the forests themselves. Here we summarize the habitat and global patterns of yeast diversity, give some information on a handful of well-studied temperate forest yeast genera, discuss the various strategies to isolate forest yeasts, and explain temperate forest yeasts' contributions to biotechnology. We close with a summary of the many future directions and outstanding questions facing researchers in temperate forest yeast ecology. Yeasts present an exciting opportunity to better understand the hidden world of microbial ecology in this threatened and global habitat.

Detecting selection in low-coverage high-throughput sequencing data using principal component analysis

BACKGROUND

Identification of selection signatures between populations is often an important part of a population genetic study. Leveraging high-throughput DNA sequencing larger sample sizes of populations with similar ancestries has become increasingly common. This has led to the need of methods capable of identifying signals of selection in populations with a continuous cline of genetic differentiation. Individuals from continuous populations are inherently challenging to group into meaningful units which is why existing methods rely on principal components analysis for inference of the selection signals. These existing methods require called genotypes as input which is problematic for studies based on low-coverage sequencing data.

MATERIALS AND METHODS

We have extended two principal component analysis based selection statistics to genotype likelihood data and applied them to low-coverage sequencing data from the 1000 Genomes Project for populations with European and East Asian ancestry to detect signals of selection in samples with continuous population structure.

RESULTS

Here, we present two selections statistics which we have implemented in the PCAngsd framework. These methods account for genotype uncertainty, opening for the opportunity to conduct selection scans in continuous populations from low and/or variable coverage sequencing data. To illustrate their use, we applied the methods to low-coverage sequencing data from human populations of East Asian and European ancestries and show that the implemented selection statistics can control the false positive rate and that they identify the same signatures of selection from low-coverage sequencing data as state-of-the-art software using high quality called genotypes.

CONCLUSION

We show that selection scans of low-coverage sequencing data of populations with similar ancestry perform on par with that obtained from high quality genotype data. Moreover, we demonstrate that PCAngsd outperform selection statistics obtained from called genotypes from low-coverage sequencing data without the need for ad-hoc filtering.

A Whole-Genome Scan for Association with Invasion Success in the Fruit Fly Drosophila suzukii Using Contrasts of Allele Frequencies Corrected for Population Structure

Evidence is accumulating that evolutionary changes are not only common during biological invasions but may also contribute directly to invasion success. The genomic basis of such changes is still largely unexplored. Yet, understanding the genomic response to invasion may help to predict the conditions under which invasiveness can be enhanced or suppressed. Here, we characterized the genome response of the spotted wing drosophila Drosophila suzukii during the worldwide invasion of this pest insect species, by conducting a genome-wide association study to identify genes involved in adaptive processes during invasion. Genomic data from 22 population samples were analyzed to detect genetic variants associated with the status (invasive versus native) of the sampled populations based on a newly developed statistic, we called C2, that contrasts allele frequencies corrected for population structure. We evaluated this new statistical framework using simulated data sets and implemented it in an upgraded version of the program BayPass. We identified a relatively small set of single-nucleotide polymorphisms that show a highly significant association with the invasive status of D. suzukii populations. In particular, two genes, RhoGEF64C and cpo, contained single-nucleotide polymorphisms significantly associated with the invasive status in the two separate main invasion routes of D. suzukii. Our methodological approaches can be applied to any other invasive species, and more generally to any evolutionary model for species characterized by nonequilibrium demographic conditions for which binary covariables of interest can be defined at the population level.

Signatures of optimal codon usage in metabolic genes inform budding yeast ecology

Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GALactose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter-species that have yet to be cultured in the lab or have only been identified by genomic material.

Neurospora from Natural Populations: Population Genomics Insights into the Life History of a Model Microbial Eukaryote

The ascomycete filamentous fungus Neurospora crassa played a historic role in experimental biology and became a model system for genetic research. Stimulated by a systematic effort to collect wild strains initiated by Stanford geneticist David Perkins, the genus Neurospora has also become a basic model for the study of evolutionary processes, speciation, and population biology. In this chapter, we will first trace the history that brought Neurospora into the era of population genomics. We will then cover the major contributions of population genomic investigations using Neurospora to our understanding of microbial biogeography and speciation, and review recent work using population genomics and genome-wide association mapping that illustrates the unique potential of Neurospora as a model for identifying the genetic basis of (potentially adaptive) phenotypes in filamentous fungi. The advent of population genomics has contributed to firmly establish Neurospora as a complete model system and we hope our review will entice biologists to include Neurospora in their research.

Contrasting patterns of local adaptation along climatic gradients between a sympatric parasitic and autotrophic tree species

Sympatric tree species are subject to similar climatic drivers, posing a question as to whether they display comparable adaptive responses. However, no study has explicitly examined local adaptation of co-occurring parasitic and autotrophic plant species to the abiotic environment. Here we test the hypotheses that a generalist parasitic tree would display a weaker signal of selection and that genomic variation would associate with fewer climatic variables (particularly precipitation) but have similar spatial patterns to a sympatric autotrophic tree species. To test these hypotheses, we collected samples from 17 sites across the range of two tree species, the hemiparasite Nuytsia floribunda (n = 264) and sympatric autotroph Melaleuca rhaphiophylla (n = 272). We obtained 5,531 high-quality genome-wide single nucleotide polymorphisms (SNPs) for M. rhaphiophylla and 6,727 SNPs for N. floribunda using DArTseq genome scan technology. Population differentiation and environmental association approaches were used to identify signals of selection. Generalized dissimilarly modelling was used to detect climatic and spatial patterns of local adaptation across climatic gradients. Overall, 322 SNPs were identified as putatively adaptive for the autotroph, while only 57 SNPs were identified for the parasitic species. We found genomic variation to associate with different sets of bioclimatic variables for each species, with precipitation relatively less important for the parasite. Spatial patterns of predicted adaptive variability were different and indicate that co-occurring species with disparate life history traits may not respond equally to selective pressures (i.e., temperature and precipitation). Together, these findings provide insight into local adaptation of sympatric parasitic and autotrophic tree species to abiotic environments.

Evaluating Population Genomic Candidate Genes Underlying Flowering Time in Arabidopsis thaliana Using T-DNA Insertion Lines

Population genomic scans have emerged as a powerful tool to detect regions of the genome that are potential targets of selection. Despite the success of genomic scans in identifying novel lists of loci potentially underlying adaptation, few studies proceed to validate the function of these candidate genes. In this study, we used transfer-DNA (T-DNA) insertion lines to evaluate the effects of 27 candidate genes on flowering time in North American accessions of Arabidopsis thaliana. We compared the flowering time of T-DNA insertion lines that knock out the function of a candidate gene obtained from population genomic studies to a wild type under long- and short-day conditions. We also did the same for a collection of randomly chosen genes that had not been identified as candidates. We validated the well-known effect of long-day conditions in accelerating flowering time and found that gene disruption caused by insertional mutagenesis tends to delay flowering. Surprisingly, we found that knockouts in random genes were just as likely to produce significant phenotypic effects as knockouts in candidate genes. T-DNA insertions at a handful of candidate genes that had previously been identified as outlier loci showed significant delays in flowering time under both long and short days, suggesting that they are promising candidates for future investigation.

Predicting the optimal growth temperatures of prokaryotes using only genome derived features

MOTIVATION

Optimal growth temperature is a fundamental characteristic of all living organisms. Knowledge of this temperature is central to the study of a prokaryote, the thermal stability and temperature dependent activity of its genes, and the bioprospecting of its genome for thermally adapted proteins. While high throughput sequencing methods have dramatically increased the availability of genomic information, the growth temperatures of the source organisms are often unknown. This limits the study and technological application of these species and their genomes. Here, we present a novel method for the prediction of growth temperatures of prokaryotes using only genomic sequences.

RESULTS

By applying the reverse ecology principle that an organism's genome includes identifiable adaptations to its native environment, we can predict a species' optimal growth temperature with an accuracy of 5.17°C root-mean-square error and a coefficient of determination of 0.835. The accuracy can be further improved for specific taxonomic clades or by excluding psychrophiles. This method provides a valuable tool for the rapid calculation of organism growth temperature when only the genome sequence is known.

AVAILABILITY AND IMPLEMENTATION

Source code, genomes analyzed and features calculated are available at: https://github.com/DavidBSauer/OGT_prediction.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A multiscale approach to detect selection in nonmodel tree species: Widespread adaptation despite population decline in Taxus baccata L

Detecting the molecular basis of local adaptation and identifying selective drivers is still challenging in nonmodel species. The use of purely population genetic approaches is limited by some characteristics of genetic systems, such as pleiotropy and polygenic control, and parallel evidence from phenotypic-based experimental comparisons is required. In long-lived organisms, the detection of selective pressures might also be precluded by evolutionary lag times in response to the environment. Here, we used the English yew to showcase an example of a multiscale integrative approach in a nonmodel species with limited plant and genomic resources. We combined information from two independent sources, phenotypes in a common environment and genomic data in natural populations, to investigate the signature of selection. Growth differences among populations in a common environment, and phenological patterns of both shoot elongation and male strobili maturation, were associated with climate clines, providing evidence for local adaptation and guiding us in the selection of populations for genomic analyses. We used information on over 25,000 SNPs from c. 1,200 genes to infer the demographic history and to test for molecular signatures of selection at different levels: SNP, gene, and biological pathway. Our results confirmed an overall demographic history of population decline, but we also found evidence for putative local adaptation at the molecular level. We identified or confirmed several candidate genes for positive and negative selection in forest trees, including the pseudo-response regulator 7 (PRR7), an essential component of the circadian clock in plants. In addition, we successfully tested an approach to detect polygenic adaptation in biological pathways, allowing us to identify the flavonoid biosynthesis pathway as a candidate stress-response pathway that deserves further attention in other plants. Finally, our study contributes to the emerging view that explaining contemporary standing genetic variation requires considering adaptation to past climates, especially for long-lived trees.

Linking genotype to phenotype to identify genetic variation relating to host susceptibility in the mountain pine beetle system

Identifying genetic variants responsible for phenotypic variation under selective pressure has the potential to enable productive gains in natural resource conservation and management. Despite this potential, identifying adaptive candidate loci is not trivial, and linking genotype to phenotype is a major challenge in contemporary genetics. Many of the population genetic approaches commonly used to identify adaptive candidates will simultaneously detect false positives, particularly in nonmodel species, where experimental evidence is seldom provided for putative roles of the adaptive candidates identified by outlier approaches. In this study, we use outcomes from population genetics, phenotype association, and gene expression analyses as multiple lines of evidence to validate candidate genes. Using lodgepole and jack pine as our nonmodel study species, we analyzed 17 adaptive candidate loci together with 78 putatively neutral loci at 58 locations across Canada (N > 800) to determine whether relationships could be established between these candidate loci and phenotype related to mountain pine beetle susceptibility. We identified two candidate loci that were significant across all population genetic tests, and demonstrated significant changes in transcript abundance in trees subjected to wounding or inoculation with the mountain pine beetle fungal associate Grosmannia clavigera. Both candidates are involved in central physiological processes that are likely to be invoked in a trees response to stress. One of these two candidate loci showed a significant association with mountain pine beetle attack status in lodgepole pine. The spatial distribution of the attack-associated allele further coincides with other indicators of susceptibility in lodgepole pine. These analyses, in which population genetics was combined with laboratory and field experimental validation approaches, represent first steps toward linking genetic variation to the phenotype of mountain pine beetle susceptibility in lodgepole and jack pine, and provide a roadmap for more comprehensive analyses.

Within species expressed genetic variability and gene expression response to different temperatures in the rotifer Brachionus calyciflorus sensu stricto

Genetic divergence is impacted by many factors, including phylogenetic history, gene flow, genetic drift, and divergent selection. Rotifers are an important component of aquatic ecosystems, and genetic variation is essential to their ongoing adaptive diversification and local adaptation. In addition to coding sequence divergence, variation in gene expression may relate to variable heat tolerance, and can impose ecological barriers within species. Temperature plays a significant role in aquatic ecosystems by affecting species abundance, spatio-temporal distribution, and habitat colonization. Recently described (formerly cryptic) species of the Brachionus calyciflorus complex exhibit different temperature tolerance both in natural and in laboratory studies, and show that B. calyciflorus sensu stricto (s.s.) is a thermotolerant species. Even within B. calyciflorus s.s., there is a tendency for further temperature specializations. Comparison of expressed genes allows us to assess the impact of stressors on both expression and sequence divergence among disparate populations within a single species. Here, we have used RNA-seq to explore expressed genetic diversity in B. calyciflorus s.s. in two mitochondrial DNA lineages with different phylogenetic histories and differences in thermotolerance. We identify a suite of candidate genes that may underlie local adaptation, with a particular focus on the response to sustained high or low temperatures. We do not find adaptive divergence in established candidate genes for thermal adaptation. Rather, we detect divergent selection among our two lineages in genes related to metabolism (lipid metabolism, metabolism of xenobiotics).

Host-parasite interactions and ecology of the malaria parasite-a bioinformatics approach

Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.

Evolution: The Genetics of Milk Champagne Yeast

A newly characterized group of budding yeast found in fermented milk drinks in West and Central Asia far outshines its relatives in the ability to use galactose, a milk sugar byproduct.

The Neutral Theory in Light of Natural Selection

In this perspective, we evaluate the explanatory power of the neutral theory of molecular evolution, 50 years after its introduction by Kimura. We argue that the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality. The ubiquity of adaptive variation both within and between species means that a more comprehensive theory of molecular evolution must be sought.

Dissecting the basis of novel trait evolution in a radiation with widespread phylogenetic discordance

Phylogenetic analyses of trait evolution can provide insight into the evolutionary processes that initiate and drive phenotypic diversification. However, recent phylogenomic studies have revealed extensive gene tree-species tree discordance, which can lead to incorrect inferences of trait evolution if only a single species tree is used for analysis. This phenomenon-dubbed "hemiplasy"-is particularly important to consider during analyses of character evolution in rapidly radiating groups, where discordance is widespread. Here, we generate whole-transcriptome data for a phylogenetic analysis of 14 species in the plant genus Jaltomata (the sister clade to Solanum), which has experienced rapid, recent trait evolution, including in fruit and nectar colour, and flower size and shape. Consistent with other radiations, we find evidence for rampant gene tree discordance due to incomplete lineage sorting (ILS) and to introgression events among the well-supported subclades. As both ILS and introgression increase the probability of hemiplasy, we perform several analyses that take discordance into account while identifying genes that might contribute to phenotypic evolution. Despite discordance, the history of fruit colour evolution in Jaltomata can be inferred with high confidence, and we find evidence of de novo adaptive evolution at individual genes associated with fruit colour variation. In contrast, hemiplasy appears to strongly affect inferences about floral character transitions in Jaltomata, and we identify candidate loci that could arise either from multiple lineage-specific substitutions or standing ancestral polymorphisms. Our analysis provides a generalizable example of how to manage discordance when identifying loci associated with trait evolution in a radiating lineage.

Hybrids and horizontal transfer: introgression allows adaptive allele discovery

Evolution has devised countless remarkable solutions to diverse challenges. Understanding the mechanistic basis of these solutions provides insights into how biological systems can be subtly tweaked without maladaptive consequences. The knowledge gained from illuminating these mechanisms is equally important to our understanding of fundamental evolutionary mechanisms as it is to our hopes of developing truly rational plant breeding and synthetic biology. In particular, modern population genomic approaches are proving very powerful in the detection of candidate alleles for mediating consequential adaptations that can be tested functionally. Especially striking are signals gained from contexts involving genetic transfers between populations, closely related species, or indeed between kingdoms. Here we discuss two major classes of these scenarios, adaptive introgression and horizontal gene flow, illustrating discoveries made across kingdoms.

Sources of Fungal Genetic Variation and Associating It with Phenotypic Diversity

The first eukaryotic genome to be sequenced was fungal, and there continue to be more sequenced genomes in the kingdom Fungi than in any other eukaryotic kingdom. Comparison of these genomes reveals many sources of genetic variation, from single nucleotide polymorphisms to horizontal gene transfer and on to changes in the arrangement and number of chromosomes, not to mention endofungal bacteria and viruses. Population genomics shows that all sources generate variation all the time and implicate natural selection as the force maintaining genome stability. Variation in wild populations is a rich resource for associating genetic variation with phenotypic variation, whether through quantitative trait locus mapping, genome-wide association studies, or reverse ecology. Subjects of studies associating genetic and phenotypic variation include model fungi, e.g., Saccharomyces and Neurospora, but pioneering studies have also been made with fungi pathogenic to plants, e.g., Pyricularia (= Magnaporthe), Zymoseptoria, and Fusarium, and to humans, e.g., Coccidioides, Cryptococcus, and Candida.

Metabolic evolution and the self-organization of ecosystems

Metabolism mediates the flow of matter and energy through the biosphere. We examined how metabolic evolution shapes ecosystems by reconstructing it in the globally abundant oceanic phytoplankter Prochlorococcus To understand what drove observed evolutionary patterns, we interpreted them in the context of its population dynamics, growth rate, and light adaptation, and the size and macromolecular and elemental composition of cells. This multilevel view suggests that, over the course of evolution, there was a steady increase in Prochlorococcus' metabolic rate and excretion of organic carbon. We derived a mathematical framework that suggests these adaptations lower the minimal subsistence nutrient concentration of cells, which results in a drawdown of nutrients in oceanic surface waters. This, in turn, increases total ecosystem biomass and promotes the coevolution of all cells in the ecosystem. Additional reconstructions suggest that Prochlorococcus and the dominant cooccurring heterotrophic bacterium SAR11 form a coevolved mutualism that maximizes their collective metabolic rate by recycling organic carbon through complementary excretion and uptake pathways. Moreover, the metabolic codependencies of Prochlorococcus and SAR11 are highly similar to those of chloroplasts and mitochondria within plant cells. These observations lead us to propose a general theory relating metabolic evolution to the self-amplification and self-organization of the biosphere. We discuss the implications of this framework for the evolution of Earth's biogeochemical cycles and the rise of atmospheric oxygen.

Continental-level population differentiation and environmental adaptation in the mushroom Suillus brevipes

Recent advancements in sequencing technology allowed researchers to better address the patterns and mechanisms involved in microbial environmental adaptation at large spatial scales. Here we investigated the genomic basis of adaptation to climate at the continental scale in Suillus brevipes, an ectomycorrhizal fungus symbiotically associated with the roots of pine trees. We used genomic data from 55 individuals in seven locations across North America to perform genome scans to detect signatures of positive selection and assess whether temperature and precipitation were associated with genetic differentiation. We found that S. brevipes exhibited overall strong population differentiation, with potential admixture in Canadian populations. This species also displayed genomic signatures of positive selection as well as genomic sites significantly associated with distinct climatic regimes and abiotic environmental parameters. These genomic regions included genes involved in transmembrane transport of substances and helicase activity potentially involved in cold stress response. Our study sheds light on large-scale environmental adaptation in fungi by identifying putative adaptive genes and providing a framework to further investigate the genetic basis of fungal adaptation.

Genome composition and phylogeny of microbes predict their co-occurrence in the environment

The genomic information of microbes is a major determinant of their phenotypic properties, yet it is largely unknown to what extent ecological associations between different species can be explained by their genome composition. To bridge this gap, this study introduces two new genome-wide pairwise measures of microbe-microbe interaction. The first (genome content similarity index) quantifies similarity in genome composition between two microbes, while the second (microbe-microbe functional association index) summarizes the topology of a protein functional association network built for a given pair of microbes and quantifies the fraction of network edges crossing organismal boundaries. These new indices are then used to predict co-occurrence between reference genomes from two 16S-based ecological datasets, accounting for phylogenetic relatedness of the taxa. Phylogenetic relatedness was found to be a strong predictor of ecological associations between microbes which explains about 10% of variance in co-occurrence data, but genome composition was found to be a strong predictor as well, it explains up to 4% the variance in co-occurrence when all genomic-based indices are used in combination, even after accounting for evolutionary relationships between the species. On their own, the metrics proposed here explain a larger proportion of variance than previously reported more complex methods that rely on metabolic network comparisons. In summary, results of this study indicate that microbial genomes do indeed contain detectable signal of organismal ecology, and the methods described in the paper can be used to improve mechanistic understanding of microbe-microbe interactions.

It is still unknown to what extent ecological associations between microbes, as measured by co-occurrence of different taxa in 16S rRNA surveys, can be explained, or predicted, using composition and structure of microbial genomes alone. Here I introduce two new genome-wide, pairwise indices for quantifying the propensity of microbial species to interact with each other. The first measure quantifies similarity in genome composition between two microbes. The second measure summarizes the topology of a protein functional association network built for a given pair of microbes and quantifies the fraction of network edges crossing organismal boundaries. I then study the ability of two newly proposed and two previously reported indices to explain variation in microbial co-occurrence. All four measures are significantly correlated with co-occurrence of microbes even when accounting for evolutionary relationships between the species. One of the newly developed indices outperforms previously proposed ones and explains up to 3.5% of the variance in co-occurrence. In summary, the indices described here are able to detect ecological associations between species using only their genomic information; however, additional methods are needed to provide more reliable genomic tools for microbial ecology.

"Islands of Divergence" in the Atlantic Cod Genome Represent Polymorphic Chromosomal Rearrangements

In several species genetic differentiation across environmental gradients or between geographically separate populations has been reported to center at "genomic islands of divergence," resulting in heterogeneous differentiation patterns across genomes. Here, genomic regions of elevated divergence were observed on three chromosomes of the highly mobile fish Atlantic cod (Gadus morhua) within geographically fine-scaled coastal areas. The "genomic islands" extended at least 5, 9.5, and 13 megabases on linkage groups 2, 7, and 12, respectively, and coincided with large blocks of linkage disequilibrium. For each of these three chromosomes, pairs of segregating, highly divergent alleles were identified, with little or no gene exchange between them. These patterns of recombination and divergence mirror genomic signatures previously described for large polymorphic inversions, which have been shown to repress recombination across extensive chromosomal segments. The lack of genetic exchange permits divergence between noninverted and inverted chromosomes in spite of gene flow. For the rearrangements on linkage groups 2 and 12, allelic frequency shifts between coastal and oceanic environments suggest a role in ecological adaptation, in agreement with recently reported associations between molecular variation within these genomic regions and temperature, oxygen, and salinity levels. Elevated genetic differentiation in these genomic regions has previously been described on both sides of the Atlantic Ocean, and we therefore suggest that these polymorphisms are involved in adaptive divergence across the species distributional range.

Secondary contact and local adaptation contribute to genome-wide patterns of clinal variation in Drosophila melanogaster

Populations arrayed along broad latitudinal gradients often show patterns of clinal variation in phenotype and genotype. Such population differentiation can be generated and maintained by both historical demographic events and local adaptation. These evolutionary forces are not mutually exclusive and can in some cases produce nearly identical patterns of genetic differentiation among populations. Here, we investigate the evolutionary forces that generated and maintain clinal variation genome-wide among populations of Drosophila melanogaster sampled in North America and Australia. We contrast patterns of clinal variation in these continents with patterns of differentiation among ancestral European and African populations. Using established and novel methods we derive here, we show that recently derived North America and Australia populations were likely founded by both European and African lineages and that this hybridization event likely contributed to genome-wide patterns of parallel clinal variation between continents. The pervasive effects of admixture mean that differentiation at only several hundred loci can be attributed to the operation of spatially varying selection using an FST outlier approach. Our results provide novel insight into the well-studied system of clinal differentiation in D. melanogaster and provide a context for future studies seeking to identify loci contributing to local adaptation in a wide variety of organisms, including other invasive species as well as temperate endemics.

Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates

In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier.inra.fr/CBGP/software/baypass/.

Microbial Speciation

What are species? How do they arise? These questions are not easy to answer and have been particularly controversial in microbiology. Yet, for those microbiologists studying environmental questions or dealing with clinical issues, the ability to name and recognize species, widely considered the fundamental units of ecology, can be practically useful. On a more fundamental level, the speciation problem, the focus here, is more mechanistic and conceptual. What is the origin of microbial species, and what evolutionary and ecological mechanisms keep them separate once they begin to diverge? To what extent are these mechanisms universal across diverse types of microbes, and more broadly across the entire the tree of life? Here, we propose that microbial speciation must be viewed in light of gene flow, which defines units of genetic similarity, and of natural selection, which defines units of phenotype and ecological function. We discuss to what extent ecological and genetic units overlap to form cohesive populations in the wild, based on recent evolutionary modeling and population genomics studies. These studies suggest a continuous "speciation spectrum," which microbial populations traverse in different ways depending on their balance of gene flow and natural selection.

Similar Efficacies of Selection Shape Mitochondrial and Nuclear Genes in Both Drosophila melanogaster and Homo sapiens

Deleterious mutations contribute to polymorphism even when selection effectively prevents their fixation. The efficacy of selection in removing deleterious mitochondrial mutations from populations depends on the effective population size (N_e) of the mitochondrial DNA and the degree to which a lack of recombination magnifies the effects of linked selection. Using complete mitochondrial genomes from Drosophila melanogaster and nuclear data available from the same samples, we reexamine the hypothesis that nonrecombining animal mitochondrial DNA harbor an excess of deleterious polymorphisms relative to the nuclear genome. We find no evidence of recombination in the mitochondrial genome, and the much-reduced level of mitochondrial synonymous polymorphism relative to nuclear genes is consistent with a reduction in N_e. Nevertheless, we find that the neutrality index, a measure of the excess of nonsynonymous polymorphism relative to the neutral expectation, is only weakly significantly different between mitochondrial and nuclear loci. This difference is likely the result of the larger proportion of beneficial mutations in X-linked relative to autosomal loci, and we find little to no difference between mitochondrial and autosomal neutrality indices. Reanalysis of published data from Homo sapiens reveals a similar lack of a difference between the two genomes, although previous studies have suggested a strong difference in both species. Thus, despite a smaller N_e, mitochondrial loci of both flies and humans appear to experience similar efficacies of purifying selection as do loci in the recombining nuclear genome.

Positive selection in development and growth rate regulation genes involved in species divergence of the genus Radix

Background

Life history traits like developmental time, age and size at maturity are directly related to fitness in all organisms and play a major role in adaptive evolution and speciation processes. Comparative genomic or transcriptomic approaches to identify positively selected genes involved in species divergence can help to generate hypotheses on the driving forces behind speciation. Here we use a bottom-up approach to investigate this hypothesis by comparative analysis of orthologous transcripts of four closely related European Radix species.

Results

Snails of the genus Radix occupy species specific distribution ranges with distinct climatic niches, indicating a potential for natural selection driven speciation based on ecological niche differentiation. We then inferred phylogenetic relationships among the four Radix species based on whole mt-genomes plus 23 nuclear loci. Three different tests to infer selection and changes in amino acid properties yielded a total of 134 genes with signatures of positive selection. The majority of these genes belonged to the functional gene ontology categories “reproduction” and “genitalia” with an overrepresentation of the functions “development” and “growth rate”.

Conclusions

We show here that Radix species divergence may be primarily enforced by selection on life history traits such as (larval-) development and growth rate. We thus hypothesise that life history differences may confer advantages under the according climate regimes, e.g., species occupying warmer and dryer habitats might have a fitness advantage with fast developing susceptible life stages, which are more tolerant to habitat desiccation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-015-0434-x) contains supplementary material, which is available to authorized users.

A population genomic scan in Chorthippus grasshoppers unveils previously unknown phenotypic divergence

Understanding the genetics of speciation and the processes that drive it is a central goal of evolutionary biology. Grasshoppers of the Chorthippus species group differ strongly in calling song (and corresponding female preferences) but are exceedingly similar in other characteristics such as morphology. Here, we performed a population genomic scan on three Chorthippus species (Chorthippus biguttulus, C. mollis and C. brunneus) to gain insight into the genes and processes involved in divergence and speciation in this group. Using an RNA-seq approach, we examined functional variation between the species by calling SNPs for each of the three species pairs and using FST -based approaches to identify outliers. We found approximately 1% of SNPs in each comparison to be outliers. Between 37% and 40% of these outliers were nonsynonymous SNPs (as opposed to a global level of 17%) indicating that we recovered loci under selection. Among the outliers were several genes that may be involved in song production and hearing as well as genes involved in other traits such as food preferences and metabolism. Differences in food preferences between species were confirmed with a behavioural experiment. This indicates that multiple phenotypic differences implicating multiple evolutionary processes (sexual selection and natural selection) are present between the species.

A Genome Scan for Genes Underlying Microgeographic-Scale Local Adaptation in a Wild Arabidopsis Species

Adaptive divergence at the microgeographic scale has been generally disregarded because high gene flow is expected to disrupt local adaptation. Yet, growing number of studies reporting adaptive divergence at a small spatial scale highlight the importance of this process in evolutionary biology. To investigate the genetic basis of microgeographic local adaptation, we conducted a genome-wide scan among sets of continuously distributed populations of Arabidopsis halleri subsp. gemmifera that show altitudinal phenotypic divergence despite gene flow. Genomic comparisons were independently conducted in two distinct mountains where similar highland ecotypes are observed, presumably as a result of convergent evolution. Here, we established a de novo reference genome and employed an individual-based resequencing for a total of 56 individuals. Among 527,225 reliable SNP loci, we focused on those showing a unidirectional allele frequency shift across altitudes. Statistical tests on the screened genes showed that our microgeographic population genomic approach successfully retrieve genes with functional annotations that are in line with the known phenotypic and environmental differences between altitudes. Furthermore, comparison between the two distinct mountains enabled us to screen out those genes that are neutral or adaptive only in either mountain, and identify the genes involved in the convergent evolution. Our study demonstrates that the genomic comparison among a set of genetically connected populations, instead of the commonly-performed comparison between two isolated populations, can also offer an effective screening for the genetic basis of local adaptation.

New opportunities at the wild frontier

A better understanding of the natural history of model organisms will increase their value as model systems and also keep them at the forefront of research.

DOI:http://dx.doi.org/10.7554/eLife.06956.001

The fascinating and secret wild life of the budding yeast S. cerevisiae

The budding yeast Saccharomyces cerevisiae has been used in laboratory experiments for over a century and has been instrumental in understanding virtually every aspect of molecular biology and genetics. However, it wasn't until a decade ago that the scientific community started to realise how little was known about this yeast's ecology and natural history, and how this information was vitally important for interpreting its biology. Recent large-scale population genomics studies coupled with intensive field surveys have revealed a previously unappreciated wild lifestyle of S. cerevisiae outside the restrictions of human environments and laboratories. The recent discovery that Chinese isolates harbour almost twice as much genetic variation as isolates from the rest of the world combined suggests that Asia is the likely origin of the modern budding yeast.

DOI:http://dx.doi.org/10.7554/eLife.05835.001

Soft shoulders ahead: spurious signatures of soft and partial selective sweeps result from linked hard sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of "soft shoulders" underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.