Demographic inference reveals African and European admixture in the North American Drosophila melanogaster population

From sub-Saharan Africa to China: Evolutionary history and adaptation of Drosophila melanogaster revealed by population genomics

Drosophila melanogaster is a widely used model organism for studying environmental adaptation. However, the genetic diversity of populations in Asia is poorly understood, leaving a notable gap in our knowledge of the global evolution and adaptation of this species. We sequenced genomes of 292 D. melanogaster strains from various ecological settings in China and analyzed them along with previously published genome sequences. We have identified six global genetic ancestry groups, despite the presence of widespread genetic admixture. The strains from China represent a unique ancestry group, although detectable differentiation exists among populations within China. We deciphered the global migration and demography of D. melanogaster, and identified widespread signals of adaptation, including genetic changes in response to insecticides. We validated the effects of insecticide resistance variants using population cage trials and deep sequencing. This work highlights the importance of population genomics in understanding the genetic underpinnings of adaptation, an effort that is particularly relevant given the deterioration of ecosystems.

Quantification and modeling of turnover dynamics of de novo transcripts in Drosophila melanogaster

Most of the transcribed eukaryotic genomes are composed of non-coding transcripts. Among these transcripts, some are newly transcribed when compared to outgroups and are referred to as de novo transcripts. De novo transcripts have been shown to play a major role in genomic innovations. However, little is known about the rates at which de novo transcripts are gained and lost in individuals of the same species. Here, we address this gap and estimate the de novo transcript turnover rate with an evolutionary model. We use DNA long reads and RNA short reads from seven geographically remote samples of inbred individuals of Drosophila melanogaster to detect de novo transcripts that are gained on a short evolutionary time scale. Overall, each sampled individual contains around 2500 unspliced de novo transcripts, with most of them being sample specific. We estimate that around 0.15 transcripts are gained per year, and that each gained transcript is lost at a rate around 5× 10-5 per year. This high turnover of transcripts suggests frequent exploration of new genomic sequences within species. These rate estimates are essential to comprehend the process and timescale of de novo gene birth.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Quantifying the fraction of new mutations that are recessive lethal

The presence and impact of recessive lethal mutations have been widely documented in diploid outcrossing species. However, precise estimates of the proportion of new mutations that are recessive lethal remain limited. Here, we evaluate the performance of Fit∂a∂i, a commonly used method for inferring the distribution of fitness effects (DFE), in the presence of lethal mutations. Using simulations, we demonstrate that in both additive and recessive cases, inference of the deleterious nonlethal portion of the DFE is minimally affected by a small proportion (<10%) of lethal mutations. Additionally, we demonstrate that while Fit∂a∂i cannot estimate the fraction of recessive lethal mutations, Fit∂a∂i can accurately infer the fraction of additive lethal mutations. Finally, as an alternative approach to estimate the proportion of mutations that are recessive lethal, we employ models of mutation-selection-drift balance using existing genomic parameters and estimates of segregating recessive lethals for humans and Drosophila melanogaster. In both species, the segregating recessive lethal load can be explained by a very small fraction (<1%) of new nonsynonymous mutations being recessive lethal. Our results refute recent assertions of a much higher proportion of mutations being recessive lethal (4%-5%), while highlighting the need for additional information on the joint distribution of selection and dominance coefficients.

Enrichment of Hard Sweeps on the X Chromosome in Drosophila melanogaster

The characteristic properties of the X chromosome, such as male hemizygosity and its unique inheritance pattern, expose it to natural selection in a way that can be different from the autosomes. Here, we investigate the differences in the tempo and mode of adaptation on the X chromosome and autosomes in a population of Drosophila melanogaster. Specifically, we test the hypothesis that due to hemizygosity and a lower effective population size on the X, the relative proportion of hard sweeps, which are expected when adaptation is gradual, compared with soft sweeps, which are expected when adaptation is rapid, is greater on the X than on the autosomes. We quantify the incidence of hard versus soft sweeps in North American D. melanogaster population genomic data with haplotype homozygosity statistics and find an enrichment of the proportion of hard versus soft sweeps on the X chromosome compared with the autosomes, confirming predictions we make from simulations. Understanding these differences may enable a deeper understanding of how important phenotypes arise as well as the impact of fundamental evolutionary parameters on adaptation, such as dominance, sex-specific selection, and sex-biased demography.

Patterns of Population Structure and Introgression Among Recently Differentiated Drosophila melanogaster Populations

Despite a century of genetic analysis, the evolutionary processes that have generated the patterns of exceptional genetic and phenotypic variation in the model organism Drosophila melanogaster remains poorly understood. In particular, how genetic variation is partitioned within its putative ancestral range in Southern Africa remains unresolved. Here, we study patterns of population genetic structure, admixture, and the spatial structuring of candidate incompatibility alleles across a global sample, including 223 new accessions, predominantly from remote regions in Southern Africa. We identify nine major ancestries, six that primarily occur in Africa and one that has not been previously described. We find evidence for both contemporary and historical admixture between ancestries, with admixture rates varying both within and between continents. For example, while previous work has highlighted an admixture zone between broadly defined African and European ancestries in the Caribbean and southeastern USA, we identify West African ancestry as the most likely African contributor. Moreover, loci showing the strongest signal of introgression between West Africa and the Caribbean/southeastern USA include several genes relating to neurological development and male courtship behavior, in line with previous work showing shared mating behaviors between these regions. Finally, while we hypothesized that potential incompatibility loci may contribute to population genetic structure across the range of D. melanogaster; these loci are, on average, not highly differentiated between ancestries. This work contributes to our understanding of the evolutionary history of a key model system, and provides insight into the partitioning of diversity across its range.

Inferring the demographic history of the North American firefly Photinus pyralis

The firefly Photinus pyralis inhabits a wide range of latitudinal and ecological niches, with populations living from temperate to tropical habitats. Despite its broad distribution, its demographic history is unknown. In this study, we modelled and inferred different demographic scenarios for North American populations of P. pyralis, which were collected from Texas to New Jersey. We used a combination of ABC techniques (for multi-population/colonization analyses) and likelihood inference (dadi, StairwayPlot2, PoMo) for single-population demographic inference, which proved useful with our RAD data. We uncovered that the most ancestral North American population lays in Texas, which further colonized the Central region of the US and more recently the North Eastern coast. Our study confidently rejects a demographic scenario where the North Eastern populations colonized more southern populations until reaching Texas. To estimate the age of divergence between of P. pyralis, which provides deeper insights into the history of the entire species, we assembled a multi-locus phylogenetic data covering the genus Photinus. We uncovered that the phylogenetic node leading to P. pyralis lies at the end of the Miocene. Importantly, modelling the demographic history of North American P. pyralis serves as a null model of nucleotide diversity patterns in a widespread native insect species, which will serve in future studies for the detection of adaptation events in this firefly species, as well as a comparison for future studies of other North American insect taxa.

Interactions between natural selection and recombination shape the genomic landscape of introgression

Hybridization between lineages that have not reached complete reproductive isolation appears more and more like a common phenomenon. Indeed, speciation genomics studies have now extensively shown that many species' genomes have hybrid ancestry. However, genomic patterns of introgression are often heterogeneous across the genome. In many organisms, a positive correlation between introgression levels and recombination rate has been observed. It is usually explained by the purging of deleterious introgressed material due to incompatibilities. However, the opposite relationship was observed in a North American population of Drosophila melanogaster with admixed European and African ancestry. In order to explore how directional and epistatic selection can impact the relationship between introgression and recombination, we performed forward simulations of whole D. melanogaster genomes reflecting the North American population's history. Our results revealed that the simplest models of positive selection often yield negative correlations between introgression and recombination such as the one observed in D. melanogaster. We also confirmed that incompatibilities tend to produce positive introgression-recombination correlations. And yet, we identify parameter space under each model where the predicted correlation is reversed. These findings deepen our understanding of the evolutionary forces that may shape patterns of ancestry across genomes, and they strengthen the foundation for future studies aimed at estimating genome-wide parameters of selection in admixed populations.

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

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

A Population Genomic Assessment of Three Decades of Evolution in a Natural Drosophila Population

Population genetics seeks to illuminate the forces shaping genetic variation, often based on a single snapshot of genomic variation. However, utilizing multiple sampling times to study changes in allele frequencies can help clarify the relative roles of neutral and non-neutral forces on short time scales. This study compares whole-genome sequence variation of recently collected natural population samples of Drosophila melanogaster against a collection made approximately 35 years prior from the same locality—encompassing roughly 500 generations of evolution. The allele frequency changes between these time points would suggest a relatively small local effective population size on the order of 10,000, significantly smaller than the global effective population size of the species. Some loci display stronger allele frequency changes than would be expected anywhere in the genome under neutrality—most notably the tandem paralogs Cyp6a17 and Cyp6a23, which are impacted by structural variation associated with resistance to pyrethroid insecticides. We find a genome-wide excess of outliers for high genetic differentiation between old and new samples, but a larger number of adaptation targets may have affected SNP-level differentiation versus window differentiation. We also find evidence for strengthening latitudinal allele frequency clines: northern-associated alleles have increased in frequency by an average of nearly 2.5% at SNPs previously identified as clinal outliers, but no such pattern is observed at random SNPs. This project underscores the scientific potential of using multiple sampling time points to investigate how evolution operates in natural populations, by quantifying how genetic variation has changed over ecologically relevant timescales.

Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

Molecular population genetics of Sex-lethal (Sxl) in the Drosophila melanogaster species group: a locus that genetically interacts with Wolbachia pipientis in Drosophila melanogaster

Sex-lethal (Sxl) is the sex determination switch in Drosophila, and also plays a critical role in germ-line stem cell daughter differentiation in Drosophila melanogaster. Three female-sterile alleles at Sxl in D. melanogaster were previously shown to genetically interact to varying degrees with the maternally inherited endosymbiont Wolbachia pipientis. Given this genetic interaction and W. pipientis’ ability to manipulate reproduction in Drosophila, we carried out a careful study of both the population genetics (within four Drosophila species) and molecular evolutionary analysis (across 20 Drosophila species) of Sxl. Consistent with earlier studies, we find that selective constraint has played a prominent role in Sxl’s molecular evolution within Drosophila, but we also observe patterns that suggest both episodic bursts of protein evolution and recent positive selection at Sxl. The episodic nature of Sxl’s protein evolution is discussed in light of its genetic interaction with W. pipientis.

Clinal and seasonal changes are correlated in Drosophila melanogaster natural populations

Spatial and seasonal variations in the environment are ubiquitous. Environmental heterogeneity can affect natural populations and lead to covariation between environment and allele frequencies. Drosophila melanogaster is known to harbor polymorphisms that change both with latitude and seasons. Identifying the role of selection in driving these changes is not trivial, because nonadaptive processes can cause similar patterns. Given the environment changes in similar ways across seasons and along the latitudinal gradient, one promising approach may be to look for parallelism between clinal and seasonal changes. Here, we test whether there is a genome-wide correlation between clinal and seasonal changes, and whether the pattern is consistent with selection. Allele frequency estimates were obtained from pooled samples from seven different locations along the east coast of the United States, and across seasons within Pennsylvania. We show that there is a genome-wide correlation between clinal and seasonal variations, which cannot be explained by linked selection alone. This pattern is stronger in genomic regions with higher functional content, consistent with natural selection. We derive a way to biologically interpret these correlations and show that around 3.7% of the common, autosomal variants could be under parallel seasonal and spatial selection. Our results highlight the contribution of natural selection in driving fluctuations in allele frequencies in natural fly populations and point to a shared genomic basis to climate adaptation that happens over space and time in D. melanogaster.

Low levels of genetic differentiation with isolation by geography and environment in populations of Drosophila melanogaster from across China

The fruit fly, Drosophila melanogaster, is a model species in evolutionary studies. However, population processes of this species in East Asia are poorly studied. Here we examined the population genetic structure of D. melanogaster across China. There were 14 mitochondrial haplotypes with 10 unique ones out of 23 known from around the globe. Pairwise F_ST values estimated from 15 novel microsatellites ranged from 0 to 0.11, with geographically isolated populations showing the highest level of genetic uniqueness. STRUCTURE analysis identified high levels of admixture at both the individual and population levels. Mantel tests indicated a strong association between genetic distance and geographical distance as well as environmental distance. Full redundancy analysis (RDA) showed that independent effects of environmental conditions and geography accounted for 62.10% and 31.58% of the total explained genetic variance, respectively. When geographic variables were constrained in a partial RDA analysis, the environmental variables bio2 (mean diurnal air temperature range), bio13 (precipitation of the wettest month), and bio15 (precipitation seasonality) were correlated with genetic distance. Our study suggests that demographic history, geographical isolation, and environmental factors have together shaped the population genetic structure of D. melanogaster after its introduction into China.

Benchmarking the performance of Pool-seq SNP callers using simulated and real sequencing data

Population genomics is a fast-developing discipline with promising applications in a growing number of life sciences fields. Advances in sequencing technologies and bioinformatics tools allow population genomics to exploit genome-wide information to identify the molecular variants underlying traits of interest and the evolutionary forces that modulate these variants through space and time. However, the cost of genomic analyses of multiple populations is still too high to address them through individual genome sequencing. Pooling individuals for sequencing can be a more effective strategy in Single Nucleotide Polymorphism (SNP) detection and allele frequency estimation because of a higher total coverage. However, compared to individual sequencing, SNP calling from pools has the additional difficulty of distinguishing rare variants from sequencing errors, which is often avoided by establishing a minimum threshold allele frequency for the analysis. Finding an optimal balance between minimizing information loss and reducing sequencing costs is essential to ensure the success of population genomics studies. Here, we have benchmarked the performance of SNP callers for Pool-seq data, based on different approaches, under different conditions, and using computer simulations and real data. We found that SNP callers performance varied for allele frequencies up to 0.35. We also found that SNP callers based on Bayesian (SNAPE-pooled) or maximum likelihood (MAPGD) approaches outperform the two heuristic callers tested (VarScan and PoolSNP), in terms of the balance between sensitivity and FDR both in simulated and sequencing data. Our results will help inform the selection of the most appropriate SNP caller not only for large-scale population studies but also in cases where the Pool-seq strategy is the only option, such as in metagenomic or polyploid studies.

A Likelihood Approach for Uncovering Selective Sweep Signatures from Haplotype Data

Selective sweeps are frequent and varied signatures in the genomes of natural populations, and detecting them is consequently important in understanding mechanisms of adaptation by natural selection. Following a selective sweep, haplotypic diversity surrounding the site under selection decreases, and this deviation from the background pattern of variation can be applied to identify sweeps. Multiple methods exist to locate selective sweeps in the genome from haplotype data, but none leverages the power of a model-based approach to make their inference. Here, we propose a likelihood ratio test statistic T to probe whole-genome polymorphism data sets for selective sweep signatures. Our framework uses a simple but powerful model of haplotype frequency spectrum distortion to find sweeps and additionally make an inference on the number of presently sweeping haplotypes in a population. We found that the T statistic is suitable for detecting both hard and soft sweeps across a variety of demographic models, selection strengths, and ages of the beneficial allele. Accordingly, we applied the T statistic to variant calls from European and sub-Saharan African human populations, yielding primarily literature-supported candidates, including LCT, RSPH3, and ZNF211 in CEU, SYT1, RGS18, and NNT in YRI, and HLA genes in both populations. We also searched for sweep signatures in Drosophila melanogaster, finding expected candidates at Ace, Uhg1, and Pimet. Finally, we provide open-source software to compute the T statistic and the inferred number of presently sweeping haplotypes from whole-genome data.

Detection of hard and soft selective sweeps from Drosophila melanogaster population genomic data

Whether hard sweeps or soft sweeps dominate adaptation has been a matter of much debate. Recently, we developed haplotype homozygosity statistics that (i) can detect both hard and soft sweeps with similar power and (ii) can classify the detected sweeps as hard or soft. The application of our method to population genomic data from a natural population of Drosophila melanogaster (DGRP) allowed us to rediscover three known cases of adaptation at the loci Ace, Cyp6g1, and CHKov1 known to be driven by soft sweeps, and detected additional candidate loci for recent and strong sweeps. Surprisingly, all of the top 50 candidates showed patterns much more consistent with soft rather than hard sweeps. Recently, Harris et al. 2018 criticized this work, suggesting that all the candidate loci detected by our haplotype statistics, including the positive controls, are unlikely to be sweeps at all and that instead these haplotype patterns can be more easily explained by complex neutral demographic models. They also claim that these neutral non-sweeps are likely to be hard instead of soft sweeps. Here, we reanalyze the DGRP data using a range of complex admixture demographic models and reconfirm our original published results suggesting that the majority of recent and strong sweeps in D. melanogaster are first likely to be true sweeps, and second, that they do appear to be soft. Furthermore, we discuss ways to take this work forward given that most demographic models employed in such analyses are necessarily too simple to capture the full demographic complexity, while more realistic models are unlikely to be inferred correctly because they require a large number of free parameters.

Population Genomics on the Fly: Recent Advances in Drosophila

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field.

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

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

Genomic Analysis of European Drosophila melanogaster Populations Reveals Longitudinal Structure, Continent-Wide Selection, and Previously Unknown DNA Viruses

Genetic variation is the fuel of evolution, with standing genetic variation especially important for short-term evolution and local adaptation. To date, studies of spatiotemporal patterns of genetic variation in natural populations have been challenging, as comprehensive sampling is logistically difficult, and sequencing of entire populations costly. Here, we address these issues using a collaborative approach, sequencing 48 pooled population samples from 32 locations, and perform the first continent-wide genomic analysis of genetic variation in European Drosophila melanogaster. Our analyses uncover longitudinal population structure, provide evidence for continent-wide selective sweeps, identify candidate genes for local climate adaptation, and document clines in chromosomal inversion and transposable element frequencies. We also characterize variation among populations in the composition of the fly microbiome, and identify five new DNA viruses in our samples.

Learning the properties of adaptive regions with functional data analysis

Identifying regions of positive selection in genomic data remains a challenge in population genetics. Most current approaches rely on comparing values of summary statistics calculated in windows. We present an approach termed SURFDAWave, which translates measures of genetic diversity calculated in genomic windows to functional data. By transforming our discrete data points to be outputs of continuous functions defined over genomic space, we are able to learn the features of these functions that signify selection. This enables us to confidently identify complex modes of natural selection, including adaptive introgression. We are also able to predict important selection parameters that are responsible for shaping the inferred selection events. By applying our model to human population-genomic data, we recapitulate previously identified regions of selective sweeps, such as OCA2 in Europeans, and predict that its beneficial mutation reached a frequency of 0.02 before it swept 1,802 generations ago, a time when humans were relatively new to Europe. In addition, we identify BNC2 in Europeans as a target of adaptive introgression, and predict that it harbors a beneficial mutation that arose in an archaic human population that split from modern humans within the hypothesized modern human-Neanderthal divergence range.

Light dependent courtship behavior in Drosophila simulans and D. melanogaster

Differences in courtship signals and perception are well-known among Drosophila species. One such described difference is the dependency on light, and thus presumably vision, for copulation success. Many studies have described a difference in light-dependent copulation success between D. melanogaster and D. simulans, identifying D. simulans as a light-dependent species, and D. melanogaster as a light-independent one. However, many of these studies use assays of varying design and few strains to represent the entire species. Here, we attempt to better characterize this purported difference using 11 strains of each species, paired by collection location, in behavioral assays conducted at two different exposure times. We show that, while there is a species-wide difference in magnitude of light-dependent copulation success, D. melanogaster copulation success is, on average, still impaired in the dark at both exposure times we measured. Additionally, there is significant variation in strain-specific ability to copulate in the dark in both species across two different exposure times. We find that this variation correlates strongly with longitude in D. melanogaster, but not in D. simulans. We hypothesize that differences in species history and demography may explain behavioral variation. Finally, we use courtship assays to show that light-dependent copulation success in one D. simulans strain is driven in part by both males and females. We discuss potential differences in courtship signals and/or signal importance between these species and potential for further comparative studies for functional characterization.

Toward an Evolutionarily Appropriate Null Model: Jointly Inferring Demography and Purifying Selection

The question of the relative evolutionary roles of adaptive and nonadaptive processes has been a central debate in population genetics for nearly a century. While advances have been made in the theoretical development of the underlying models, and statistical methods for estimating their parameters from large-scale genomic data, a framework for an appropriate null model remains elusive. A model incorporating evolutionary processes known to be in constant operation, genetic drift (as modulated by the demographic history of the population) and purifying selection, is lacking. Without such a null model, the role of adaptive processes in shaping within- and between-population variation may not be accurately assessed. Here, we investigate how population size changes and the strength of purifying selection affect patterns of variation at "neutral" sites near functional genomic components. We propose a novel statistical framework for jointly inferring the contribution of the relevant selective and demographic parameters. By means of extensive performance analyses, we quantify the utility of the approach, identify the most important statistics for parameter estimation, and compare the results with existing methods. Finally, we reanalyze genome-wide population-level data from a Zambian population of Drosophila melanogaster, and find that it has experienced a much slower rate of population growth than was inferred when the effects of purifying selection were neglected. Our approach represents an appropriate null model, against which the effects of positive selection can be assessed.

Recurrent Collection of Drosophila melanogaster from Wild African Environments and Genomic Insights into Species History

A long-standing enigma concerns the geographic and ecological origins of the intensively studied vinegar fly, Drosophila melanogaster. This globally distributed human commensal is thought to originate from sub-Saharan Africa, yet until recently, it had never been reported from undisturbed wilderness environments that could reflect its precommensal niche. Here, we document the collection of 288 D. melanogaster individuals from multiple African wilderness areas in Zambia, Zimbabwe, and Namibia. The presence of D. melanogaster in these remote woodland environments is consistent with an ancestral range in southern-central Africa, as opposed to equatorial regions. After sequencing the genomes of 17 wilderness-collected flies collected from Kafue National Park in Zambia, we found reduced genetic diversity relative to town populations, elevated chromosomal inversion frequencies, and strong differences at specific genes including known insecticide targets. Combining these genomes with existing data, we probed the history of this species' geographic expansion. Demographic estimates indicated that expansion from southern-central Africa began ∼10,000 years ago, with a Saharan crossing soon after, but expansion from the Middle East into Europe did not begin until roughly 1,400 years ago. This improved model of demographic history will provide an important resource for future evolutionary and genomic studies of this key model organism. Our findings add context to the history of D. melanogaster, while opening the door for future studies on the biological basis of adaptation to human environments.

Contemporary Demographic Reconstruction Methods Are Robust to Genome Assembly Quality: A Case Study in Tasmanian Devils

Reconstructing species’ demographic histories is a central focus of molecular ecology and evolution. Recently, an expanding suite of methods leveraging either the sequentially Markovian coalescent (SMC) or the site-frequency spectrum has been developed to reconstruct population size histories from genomic sequence data. However, few studies have investigated the robustness of these methods to genome assemblies of varying quality. In this study, we first present an improved genome assembly for the Tasmanian devil using the Chicago library method. Compared with the original reference genome, our new assembly reduces the number of scaffolds (from 35,975 to 10,010) and increases the scaffold N90 (from 0.101 to 2.164 Mb). Second, we assess the performance of four contemporary genomic methods for inferring population size history (PSMC, MSMC, SMC++, Stairway Plot), using the two devil genome assemblies as well as simulated, artificially fragmented genomes that approximate the hypothesized demographic history of Tasmanian devils. We demonstrate that each method is robust to assembly quality, producing similar estimates of Ne when simulated genomes were fragmented into up to 5,000 scaffolds. Overall, methods reliant on the SMC are most reliable between ∼300 generations before present (gbp) and 100 kgbp, whereas methods exclusively reliant on the site-frequency spectrum are most reliable between the present and 30 gbp. Our results suggest that when used in concert, genomic methods for reconstructing species’ effective population size histories 1) can be applied to nonmodel organisms without highly contiguous reference genomes, and 2) are capable of detecting independently documented effects of historical geological events.

Life-History Evolution and the Genetics of Fitness Components in Drosophila melanogaster

Life-history traits or "fitness components"-such as age and size at maturity, fecundity and fertility, age-specific rates of survival, and life span-are the major phenotypic determinants of Darwinian fitness. Analyzing the evolution and genetics of these phenotypic targets of selection is central to our understanding of adaptation. Due to its simple and rapid life cycle, cosmopolitan distribution, ease of maintenance in the laboratory, well-understood evolutionary genetics, and its versatile genetic toolbox, the "vinegar fly" Drosophila melanogaster is one of the most powerful, experimentally tractable model systems for studying "life-history evolution." Here, I review what has been learned about the evolution and genetics of life-history variation in D. melanogaster by drawing on numerous sources spanning population and quantitative genetics, genomics, experimental evolution, evolutionary ecology, and physiology. This body of work has contributed greatly to our knowledge of several fundamental problems in evolutionary biology, including the amount and maintenance of genetic variation, the evolution of body size, clines and climate adaptation, the evolution of senescence, phenotypic plasticity, the nature of life-history trade-offs, and so forth. While major progress has been made, important facets of these and other questions remain open, and the D. melanogaster system will undoubtedly continue to deliver key insights into central issues of life-history evolution and the genetics of adaptation.

The Demographic History of African Drosophila melanogaster

As one of the most commonly utilized organisms in the study of local adaptation, an accurate characterization of the demographic history of Drosophila melanogaster remains as an important research question. This owes both to the inherent interest in characterizing the population history of this model organism, as well as to the well-established importance of an accurate null demographic model for increasing power and decreasing false positive rates in genomic scans for positive selection. Although considerable attention has been afforded to this issue in non-African populations, less is known about the demographic history of African populations, including from the ancestral range of the species. While qualitative predictions and hypotheses have previously been forwarded, we here present a quantitative model fitting of the population history characterizing both the ancestral Zambian population range as well as the subsequently colonized west African populations, which themselves served as the source of multiple non-African colonization events. We here report the split time of the West African population at 72 kya, a date corresponding to human migration into this region as well as a period of climatic changes in the African continent. Furthermore, we have estimated population sizes at this split time. These parameter estimates thus represent an important null model for future investigations in to African and non-African D. melanogaster populations alike.

A clinal polymorphism in the insulin signaling transcription factor foxo contributes to life-history adaptation in Drosophila

A fundamental aim of adaptation genomics is to identify polymorphisms that underpin variation in fitness traits. In Drosophila melanogaster, latitudinal life-history clines exist on multiple continents and make an excellent system for dissecting the genetics of adaptation. We have previously identified numerous clinal single-nucleotide polymorphism in insulin/insulin-like growth factor signaling (IIS), a pathway known from mutant studies to affect life history. However, the effects of natural variants in this pathway remain poorly understood. Here we investigate how two clinal alternative alleles at foxo, a transcriptional effector of IIS, affect fitness components (viability, size, starvation resistance, fat content). We assessed this polymorphism from the North American cline by reconstituting outbred populations, fixed for either the low- or high-latitude allele, from inbred DGRP lines. Because diet and temperature modulate IIS, we phenotyped alleles across two temperatures (18°C, 25°C) and two diets differing in sugar source and content. Consistent with clinal expectations, the high-latitude allele conferred larger body size and reduced wing loading. Alleles also differed in starvation resistance and expression of insulin-like receptor, a transcriptional target of FOXO. Allelic reaction norms were mostly parallel, with few GxE interactions. Together, our results suggest that variation in IIS makes a major contribution to clinal life-history adaptation.

Demographic History of the Human Commensal Drosophila melanogaster

The cohabitation of Drosophila melanogaster with humans is nearly ubiquitous. Though it has been well established that this fly species originated in sub-Saharan Africa, and only recently has spread globally, many details of its swift expansion remain unclear. Elucidating the demographic history of D. melanogaster provides a unique opportunity to investigate how human movement might have impacted patterns of genetic diversity in a commensal species, as well as providing neutral null models for studies aimed at identifying genomic signatures of local adaptation. Here, we use whole-genome data from five populations (Africa, North America, Europe, Central Asia, and the South Pacific) to carry out demographic inferences, with particular attention to the inclusion of migration and admixture. We demonstrate the importance of these parameters for model fitting and show that how previous estimates of divergence times are likely to be significantly underestimated as a result of not including them. Finally, we discuss how human movement along early shipping routes might have shaped the present-day population structure of D. melanogaster.

Genome-wide sexually antagonistic variants reveal long-standing constraints on sexual dimorphism in fruit flies

The evolution of sexual dimorphism is constrained by a shared genome, leading to ‘sexual antagonism’, in which different alleles at given loci are favoured by selection in males and females. Despite its wide taxonomic incidence, we know little about the identity, genomic location, and evolutionary dynamics of antagonistic genetic variants. To address these deficits, we use sex-specific fitness data from 202 fully sequenced hemiclonal Drosophila melanogaster fly lines to perform a genome-wide association study (GWAS) of sexual antagonism. We identify approximately 230 chromosomal clusters of candidate antagonistic single nucleotide polymorphisms (SNPs). In contradiction to classic theory, we find no clear evidence that the X chromosome is a hot spot for sexually antagonistic variation. Characterising antagonistic SNPs functionally, we find a large excess of missense variants but little enrichment in terms of gene function. We also assess the evolutionary persistence of antagonistic variants by examining extant polymorphism in wild D. melanogaster populations and closely related species. Remarkably, antagonistic variants are associated with multiple signatures of balancing selection across the D. melanogaster distribution range and in their sister species D. simulans, indicating widespread and evolutionarily persistent (about 1 million years) genomic constraints on the evolution of sexual dimorphism. Based on our results, we propose that antagonistic variation accumulates because of constraints on the resolution of sexual conflict over protein coding sequences, thus contributing to the long-term maintenance of heritable fitness variation.

This study characterises antagonistic loci across the genome of the fruit fly Drosophila melanogaster, finding them to be preferentially associated with variation in coding sequences and to be selectively maintained across worldwide populations of D. melanogaster, and even its sister species D. simulans.

Population-specific dynamics and selection patterns of transposable element insertions in European natural populations

Transposable elements (TEs) are ubiquitous sequences in genomes of virtually all species. While TEs have been investigated for several decades, only recently we have the opportunity to study their genome-wide population dynamics. Most of the studies so far have been restricted either to the analysis of the insertions annotated in the reference genome or to the analysis of a limited number of populations. Taking advantage of the European Drosophila population genomics consortium (DrosEU) sequencing data set, we have identified and measured the dynamics of TEs in a large sample of European Drosophila melanogaster natural populations. We showed that the mobilome landscape is population-specific and highly diverse depending on the TE family. In contrast with previous studies based on SNP variants, no geographical structure was observed for TE abundance or TE divergence in European populations. We further identified de novo individual insertions using two available programs and, as expected, most of the insertions were present at low frequencies. Nevertheless, we identified a subset of TEs present at high frequencies and located in genomic regions with a high recombination rate. These TEs are candidates for being the target of positive selection, although neutral processes should be discarded before reaching any conclusion on the type of selection acting on them. Finally, parallel patterns of association between the frequency of TE insertions and several geographical and temporal variables were found between European and North American populations, suggesting that TEs can be potentially implicated in the adaptation of populations across continents.

Evolutionary insights from large scale resequencing datasets in Drosophila melanogaster

Drosophila melanogaster has long been used as an evolutionary model system. Its small genome size, well-annotated genome, and ease of sampling, also makes it a choice species for genome resequencing studies. Hundreds of genomic samples from populations worldwide are available and are currently being used to tackle a wide range of evolutionary questions. In this review, we focused on three insights that have increased our understanding of the evolutionary history of this species, and that have implications for the study of evolutionary processes in other species as well. Because of technical limitations, most of the studies so far have focused on SNP variants. However, long-read sequencing techniques should allow us in the near future to include other type of genomic variants that also influence genome evolution.

On the unfounded enthusiasm for soft selective sweeps II: Examining recent evidence from humans, flies, and viruses

Since the initial description of the genomic patterns expected under models of positive selection acting on standing genetic variation and on multiple beneficial mutations—so-called soft selective sweeps—researchers have sought to identify these patterns in natural population data. Indeed, over the past two years, large-scale data analyses have argued that soft sweeps are pervasive across organisms of very different effective population size and mutation rate—humans, Drosophila, and HIV. Yet, others have evaluated the relevance of these models to natural populations, as well as the identifiability of the models relative to other known population-level processes, arguing that soft sweeps are likely to be rare. Here, we look to reconcile these opposing results by carefully evaluating three recent studies and their underlying methodologies. Using population genetic theory, as well as extensive simulation, we find that all three examples are prone to extremely high false-positive rates, incorrectly identifying soft sweeps under both hard sweep and neutral models. Furthermore, we demonstrate that well-fit demographic histories combined with rare hard sweeps serve as the more parsimonious explanation. These findings represent a necessary response to the growing tendency of invoking parameter-heavy, assumption-laden models of pervasive positive selection, and neglecting best practices regarding the construction of proper demographic null models.

A long-standing debate in evolutionary biology revolves around the role of selective vs. stochastic processes in driving molecular evolution and shaping genetic variation. With the advent of genomics, genome-wide polymorphism data have been utilized to characterize these processes, with a major interest in describing the fraction of genomic variation shaped by positive selection. These genomic scans were initially focused around a hard sweep model, in which selection acts upon rare, newly arising beneficial mutations. Recent years have seen the description of sweeps occurring from both standing and rapidly recurring beneficial mutations, collectively known as soft sweeps. However, common to both hard and soft sweeps is the difficulty in distinguishing these effects from neutral demographic patterns, and disentangling these processes has remained an important field of study within population genetics. Despite this, there is a recent and troubling tendency to neglect these demographic considerations, and to naively fit sweep models to genomic data. Recent realizations of such efforts have resulted in the claim that soft sweeps play a dominant role in shaping genomic variation and in driving adaptation across diverse branches of the tree of life. Here, we reanalyze these findings and demonstrate that a more careful consideration of neutral processes results in highly differing conclusions.

Demographic histories and genetic diversity across pinnipeds are shaped by human exploitation, ecology and life-history

A central paradigm in conservation biology is that population bottlenecks reduce genetic diversity and population viability. In an era of biodiversity loss and climate change, understanding the determinants and consequences of bottlenecks is therefore an important challenge. However, as most studies focus on single species, the multitude of potential drivers and the consequences of bottlenecks remain elusive. Here, we combined genetic data from over 11,000 individuals of 30 pinniped species with demographic, ecological and life history data to evaluate the consequences of commercial exploitation by 18th and 19th century sealers. We show that around one third of these species exhibit strong signatures of recent population declines. Bottleneck strength is associated with breeding habitat and mating system variation, and together with global abundance explains much of the variation in genetic diversity across species. Overall, bottleneck intensity is unrelated to IUCN status, although the three most heavily bottlenecked species are endangered. Our study reveals an unforeseen interplay between human exploitation, animal biology, demographic declines and genetic diversity.

Historical hunting has caused documented declines in pinnipeds, but the extent to which hunting caused genetic bottlenecks among species was unknown. Here, the authors show evidence of severe bottlenecks in several pinniped species, particularly those that breed on land.

Genome-wide patterns of local adaptation in Western European Drosophila melanogaster natural populations

Signatures of spatially varying selection have been investigated both at the genomic and transcriptomic level in several organisms. In Drosophila melanogaster, the majority of these studies have analyzed North American and Australian populations, leading to the identification of several loci and traits under selection. However, several studies based mainly in North American populations showed evidence of admixture that likely contributed to the observed population differentiation patterns. Thus, disentangling demography from selection might be challenging when analyzing these populations. European populations could help identify loci under spatially varying selection provided that no recent admixture from African populations would have occurred. In this work, we individually sequence the genome of 42 European strains collected in populations from contrasting environments: Stockholm (Sweden) and Castellana Grotte (Southern Italy). We found low levels of population structure and no evidence of recent African admixture in these two populations. We thus look for patterns of spatially varying selection affecting individual genes and gene sets. Besides single nucleotide polymorphisms, we also investigated the role of transposable elements in local adaptation. We concluded that European populations are a good dataset to identify candidate loci under spatially varying selection. The analysis of the two populations sequenced in this work in the context of all the available D. melanogaster data allowed us to pinpoint genes and biological processes likely to be relevant for local adaptation. Identifying and analyzing populations with low levels of population structure and admixture should help to disentangle selective from non-selective forces underlying patterns of population differentiation in other species as well.

Estimating the Timing of Multiple Admixture Pulses During Local Ancestry Inference

Admixture, the mixing of genetically distinct populations, is increasingly recognized as a fundamental biological process. One major goal of admixture analyses is to estimate the timing of admixture events. Whereas most methods today can only detect the most recent admixture event, here, we present coalescent theory and associated software that can be used to estimate the timing of multiple admixture events in an admixed population. We extensively validate this approach and evaluate the conditions under which it can successfully distinguish one- from two-pulse admixture models. We apply our approach to real and simulated data of Drosophila melanogaster We find evidence of a single very recent pulse of cosmopolitan ancestry contributing to African populations, as well as evidence for more ancient admixture among genetically differentiated populations in sub-Saharan Africa. These results suggest our method can quantify complex admixture histories involving genetic material introduced by multiple discrete admixture pulses. The new method facilitates the exploration of admixture and its contribution to adaptation, ecological divergence, and speciation.

Deleterious variation shapes the genomic landscape of introgression

While it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how gene flow affects and is affected by the dynamics of deleterious variation. Here we use population genetic simulations to examine how gene flow impacts deleterious variation under a variety of demographic scenarios, mating systems, dominance coefficients, and recombination rates. Our results show that admixture between populations can temporarily reduce the genetic load of smaller populations and cause increases in the frequency of introgressed ancestry, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. Together, these factors lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30–75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models of admixture include both demography and deleterious variation before invoking other mechanisms to explain unusual patterns of genetic variation.

Individuals from distinct populations sometimes will produce fertile offspring and will exchange genetic material in a process called hybridization. Genomes of hybrid individuals often show non-random patterns of hybrid ancestry across the genome, where some regions have a high frequency of ancestry from the second population and other regions have less. Typically, this pattern has been attributed to adaptive introgression, where beneficial genetic variants are passed from one population to the other, or to genomic incompatibilities between these distinct species. However, other mechanisms could lead to these heterogeneous patterns of ancestry in hybrids. Here we use simulations to investigate whether deleterious mutations affect the patterns of introgressed ancestry across genomes. We show that when ancestry from a larger population is added to a smaller population, the ancestry from the larger population dramatically increases in frequency because it carries fewer deleterious mutations. This occurs even in the absence of beneficial mutations in either population. Additionally, we show that differences in sex chromosome evolution relative to autosomes, or differences in mating system, can affect patterns of introgression in similar ways. Our study argues that deleterious mutations should be included in population genetic models used to identify unusual regions of the genome that appear to be under selection in hybrids.

Spatiotemporal dynamics and genome-wide association genome-wide association analysis of desiccation tolerance in Drosophila melanogaster

Water availability is a major environmental challenge to a variety of terrestrial organisms. In insects, desiccation tolerance varies predictably over spatial and temporal scales and is an important physiological determinant of fitness in natural populations. Here, we examine the dynamics of desiccation tolerance in North American populations of Drosophila melanogaster using: (a) natural populations sampled across latitudes and seasons; (b) experimental evolution in field mesocosms over seasonal time; (c) genome-wide associations to identify SNPs/genes associated with variation for desiccation tolerance; and (d) subsequent analysis of patterns of clinal/seasonal enrichment in existing pooled sequencing data of populations sampled in both North America and Australia. A cline in desiccation tolerance was observed, for which tolerance exhibited a positive association with latitude; tolerance also varied predictably with culture temperature, demonstrating a significant degree of thermal plasticity. Desiccation tolerance evolved rapidly in field mesocosms, although only males showed differences in desiccation tolerance between spring and autumn collections from natural populations. Water loss rates did not vary significantly among latitudinal or seasonal populations; however, changes in metabolic rates during prolonged exposure to dry conditions are consistent with increased tolerance in higher latitude populations. Genome-wide associations in a panel of inbred lines identified twenty-five SNPs in twenty-one loci associated with sex-averaged desiccation tolerance, but there is no robust signal of spatially varying selection on genes associated with desiccation tolerance. Together, our results suggest that desiccation tolerance is a complex and important fitness component that evolves rapidly and predictably in natural populations.

Impacts of Recurrent Hitchhiking on Divergence and Demographic Inference in Drosophila

In species with large population sizes such as Drosophila, natural selection may have substantial effects on genetic diversity and divergence. However, the implications of this widespread nonneutrality for standard population genetic assumptions and practices remain poorly resolved. Here, we assess the consequences of recurrent hitchhiking (RHH), in which selective sweeps occur at a given rate randomly across the genome. We use forward simulations to examine two published RHH models for D. melanogaster, reflecting relatively common/weak and rare/strong selection. We find that unlike the rare/strong RHH model, the common/weak model entails a slight degree of Hill-Robertson interference in high recombination regions. We also find that the common/weak RHH model is more consistent with our genome-wide estimate of the proportion of substitutions fixed by natural selection between D. melanogaster and D. simulans (19%). Finally, we examine how these models of RHH might bias demographic inference. We find that these RHH scenarios can bias demographic parameter estimation, but such biases are weaker for parameters relating recently diverged populations, and for the common/weak RHH model in general. Thus, even for species with important genome-wide impacts of selective sweeps, neutralist demographic inference can have some utility in understanding the histories of recently diverged populations.

Population admixture can enhance establishment success of the introduced biological control agent Cryptolaemus montrouzieri

Background

Introduced biological control agents have opportunities of population admixture through multiple introductions in the field. However, the importance of population admixture for their establishment success often remains unclear. Previous studies based on genetic markers have suggested a history of population admixture in the predatory ladybird Cryptolaemus montrouzieri Mulsant in China.

Results

We tested whether population admixture may lead to fitness changes under laboratory conditions. We first found no mating barrier or strong bias between two parental populations, despite their differences in genetics and phenotypes. Then, our experimental evidence supported the hypothesis that admixed populations have a higher potential of establishment success, due to their superior reproductive ability, and hunger and cold tolerance inherited from one of the parental populations.

Conclusions

We suggest that population admixture can be a breeding method to improve the performance of biological control agents, particularly when used in a classical biological control approach, but that consequences for potential invasiveness need to be considered.

Negative selection in humans and fruit flies involves synergistic epistasis

Negative selection against deleterious alleles produced by mutation influences within-population variation as the most pervasive form of natural selection. However, it is not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis should produce negative linkage disequilibrium between deleterious alleles and, therefore, an underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function alleles in eight independent data sets from human and fly populations. Thus, selection against rare protein-disrupting alleles is characterized by synergistic epistasis, which may explain how human and fly populations persist despite high genomic mutation rates.

Variation in the Intensity of Selection on Codon Bias over Time Causes Contrasting Patterns of Base Composition Evolution in Drosophila

Four-fold degenerate coding sites form a major component of the genome, and are often used to make inferences about selection and demography, so that understanding their evolution is important. Despite previous efforts, many questions regarding the causes of base composition changes at these sites in Drosophila remain unanswered. To shed further light on this issue, we obtained a new whole-genome polymorphism data set from D. simulans. We analyzed samples from the putatively ancestral range of D. simulans, as well as an existing polymorphism data set from an African population of D. melanogaster. By using D. yakuba as an outgroup, we found clear evidence for selection on 4-fold sites along both lineages over a substantial period, with the intensity of selection increasing with GC content. Based on an explicit model of base composition evolution, we suggest that the observed AT-biased substitution pattern in both lineages is probably due to an ancestral reduction in selection intensity, and is unlikely to be the result of an increase in mutational bias towards AT alone. By using two polymorphism-based methods for estimating selection coefficients over different timescales, we show that the selection intensity on codon usage has been rather stable in D. simulans in the recent past, but the long-term estimates in D. melanogaster are much higher than the short-term ones, indicating a continuing decline in selection intensity, to such an extent that the short-term estimates suggest that selection is only active in the most GC-rich parts of the genome. Finally, we provide evidence for complex evolutionary patterns in the putatively neutral short introns, which cannot be explained by the standard GC-biased gene conversion model. These results reveal a dynamic picture of base composition evolution.

Inferring Demographic History Using Two-Locus Statistics

Population demographic history may be learned from contemporary genetic variation data. Methods based on aggregating the statistics of many single loci into an allele frequency spectrum (AFS) have proven powerful, but such methods ignore potentially informative patterns of linkage disequilibrium (LD) between neighboring loci. To leverage such patterns, we developed a composite-likelihood framework for inferring demographic history from aggregated statistics of pairs of loci. Using this framework, we show that two-locus statistics are more sensitive to demographic history than single-locus statistics such as the AFS. In particular, two-locus statistics escape the notorious confounding of depth and duration of a bottleneck, and they provide a means to estimate effective population size based on the recombination rather than mutation rate. We applied our approach to a Zambian population of Drosophila melanogaster Notably, using both single- and two-locus statistics, we inferred a substantially lower ancestral effective population size than previous works and did not infer a bottleneck history. Together, our results demonstrate the broad potential for two-locus statistics to enable powerful population genetic inference.

Molecular Population Genetics

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data.

Geographical analysis of diapause inducibility in European Drosophila melanogaster populations

Seasonal overwintering in insects represents an adaptation to stressful environments and in European Drosophila melanogaster females, low temperatures and short photoperiods can induce an ovarian diapause. Diapause may represent a recent (<15Ky) adaptation to the colonisation of temperate Europe by D. melanogaster from tropical sub-Saharan Africa, because African D. melanogaster and the sibling species D. simulans, have been reported to fail to undergo diapause. Over the past few centuries, D. melanogaster have also invaded North America and Australia, and eastern populations on both continents show a predictable latitudinal cline in diapause induction. In Europe however, a new diapause-enhancing timeless allele, ls-tim, is observed at high levels in southern Italy (∼80%), where it appears to have arisen and has spread throughout the continent with a frequency of ∼20% in Scandinavia. Given the phenotype of ls-tim and its geographical distribution, we might predict that it would work against any latitudinal cline in diapause induction within Europe. Indeed we reveal that any latitudinal cline for diapause in Europe is very weak, as predicted by ls-tim frequencies. In contrast, we determine ls-tim frequencies in North America and observe that they would be expected to strengthen the latitudinal pattern of diapause. Our results reveal how a newly arisen mutation, can, via the stochastic nature of where it initially arose, blur an otherwise adaptive geographical pattern.

On the Long-term Stability of Clines in Some Metabolic Genes in Drosophila melanogaster

Very little information exists for long-term changes in genetic variation in natural populations. Here we take the unique opportunity to compare a set of data for SNPs in 15 metabolic genes from eastern US collections of Drosophila melanogaster that span a large latitudinal range and represent two collections separated by 12 to 13 years. We also expand this to a 22-year interval for the Adh gene and approximately 30 years for the G6pd and Pgd genes. During these intervals, five genes showed a statistically significant change in average SNP allele frequency corrected for latitude. While much remains unchanged, we see five genes where latitudinal clines have been lost or gained and two where the slope significantly changes. The long-term frequency shift towards a southern favored Adh S allele reported in Australia populations is not observed in the eastern US over a period of 21 years. There is no general pattern of southern-favored or northern-favored alleles increasing in frequency across the genes. This observation points to the fluid nature of some allelic variation over this time period and the action of selective responses or migration that may be more regional than uniformly imposed across the cline.

Parallel Evolution of Cold Tolerance within Drosophila melanogaster

Drosophila melanogaster originated in tropical Africa before expanding into strikingly different temperate climates in Eurasia and beyond. Here, we find elevated cold tolerance in three distinct geographic regions: beyond the well-studied non-African case, we show that populations from the highlands of Ethiopia and South Africa have significantly increased cold tolerance as well. We observe greater cold tolerance in outbred versus inbred flies, but only in populations with higher inversion frequencies. Each cold-adapted population shows lower inversion frequencies than a closely-related warm-adapted population, suggesting that inversion frequencies may decrease with altitude in addition to latitude. Using the FST-based "Population Branch Excess" statistic (PBE), we found only limited evidence for parallel genetic differentiation at the scale of ∼4 kb windows, specifically between Ethiopian and South African cold-adapted populations. And yet, when we looked for single nucleotide polymorphisms (SNPs) with codirectional frequency change in two or three cold-adapted populations, strong genomic enrichments were observed from all comparisons. These findings could reflect an important role for selection on standing genetic variation leading to "soft sweeps". One SNP showed sufficient codirectional frequency change in all cold-adapted populations to achieve experiment-wide significance: an intronic variant in the synaptic gene Prosap. Another codirectional outlier SNP, at senseless-2, had a strong association with our cold trait measurements, but in the opposite direction as predicted. More generally, proteins involved in neurotransmission were enriched as potential targets of parallel adaptation. The ability to study cold tolerance evolution in a parallel framework will enhance this classic study system for climate adaptation.

A Hidden Markov Model Approach for Simultaneously Estimating Local Ancestry and Admixture Time Using Next Generation Sequence Data in Samples of Arbitrary Ploidy

Admixture-the mixing of genomes from divergent populations-is increasingly appreciated as a central process in evolution. To characterize and quantify patterns of admixture across the genome, a number of methods have been developed for local ancestry inference. However, existing approaches have a number of shortcomings. First, all local ancestry inference methods require some prior assumption about the expected ancestry tract lengths. Second, existing methods generally require genotypes, which is not feasible to obtain for many next-generation sequencing projects. Third, many methods assume samples are diploid, however a wide variety of sequencing applications will fail to meet this assumption. To address these issues, we introduce a novel hidden Markov model for estimating local ancestry that models the read pileup data, rather than genotypes, is generalized to arbitrary ploidy, and can estimate the time since admixture during local ancestry inference. We demonstrate that our method can simultaneously estimate the time since admixture and local ancestry with good accuracy, and that it performs well on samples of high ploidy-i.e. 100 or more chromosomes. As this method is very general, we expect it will be useful for local ancestry inference in a wider variety of populations than what previously has been possible. We then applied our method to pooled sequencing data derived from populations of Drosophila melanogaster on an ancestry cline on the east coast of North America. We find that regions of local recombination rates are negatively correlated with the proportion of African ancestry, suggesting that selection against foreign ancestry is the least efficient in low recombination regions. Finally we show that clinal outlier loci are enriched for genes associated with gene regulatory functions, consistent with a role of regulatory evolution in ecological adaptation of admixed D. melanogaster populations. Our results illustrate the potential of local ancestry inference for elucidating fundamental evolutionary processes.

Effects of Linked Selective Sweeps on Demographic Inference and Model Selection

The availability of large-scale population genomic sequence data has resulted in an explosion in efforts to infer the demographic histories of natural populations across a broad range of organisms. As demographic events alter coalescent genealogies, they leave detectable signatures in patterns of genetic variation within and between populations. Accordingly, a variety of approaches have been designed to leverage population genetic data to uncover the footprints of demographic change in the genome. The vast majority of these methods make the simplifying assumption that the measures of genetic variation used as their input are unaffected by natural selection. However, natural selection can dramatically skew patterns of variation not only at selected sites, but at linked, neutral loci as well. Here we assess the impact of recent positive selection on demographic inference by characterizing the performance of three popular methods through extensive simulation of data sets with varying numbers of linked selective sweeps. In particular, we examined three different demographic models relevant to a number of species, finding that positive selection can bias parameter estimates of each of these models-often severely. We find that selection can lead to incorrect inferences of population size changes when none have occurred. Moreover, we show that linked selection can lead to incorrect demographic model selection, when multiple demographic scenarios are compared. We argue that natural populations may experience the amount of recent positive selection required to skew inferences. These results suggest that demographic studies conducted in many species to date may have exaggerated the extent and frequency of population size changes.