Genome assembly and annotation of a Drosophila simulans strain from Madagascar

The genomic distribution of transposable elements is driven by spatially variable purifying selection

It is widely accepted that the genomic distribution of transposable elements (TEs) mainly reflects the outcome of purifying selection and insertion bias (1). Nevertheless, the relative importance of these two evolutionary forces could not be tested thoroughly. Here, we introduce an experimental system, which allows separating purifying selection from TE insertion bias. We used experimental evolution to study the TE insertion patterns in Drosophila simulans founder populations harboring 1040 insertions of an active P-element. After 10 generations at a large population size, we detected strong selection against P-element insertions. The exception were P-element insertions in genomic regions for which a strong insertion bias has been proposed (2-4). Because recurrent P-element insertions cannot explain this pattern, we conclude that purifying selection, with variable strength along the chromosomes, is the major determinant of the genomic distribution of P-elements. Genomic regions with relaxed purifying selection against P-element insertions exhibit normal levels of purifying selection against base substitutions. This suggests that different types of purifying selection operate on base substitutions and P-element insertions. Our results highlight the power of experimental evolution to understand basic evolutionary processes, which are difficult to infer from patterns of natural variation alone.

The transposition rate has little influence on the plateauing level of the P-element

The popular trap model assumes that the invasions of transposable elements (TEs) in mammals and invertebrates are stopped by piRNAs that emerge after insertion of the TE into a piRNA cluster. It remains, however, still unclear which factors influence the dynamics of TE invasions. The activity of the TE (i.e., transposition rate) is one frequently discussed key factor. Here we take advantage of the temperature-dependent activity of the P-element, a widely studied eukaryotic TE, to test how TE activity affects the dynamics of a TE invasion. We monitored P-element invasion dynamics in experimental Drosophila simulans populations at hot and cold culture conditions. Despite marked differences in transposition rates, the P-element reached very similar copy numbers at both temperatures. The reduction of the insertion rate upon approaching the copy number plateau was accompanied by similar amounts of piRNAs against the P-element at both temperatures. Nevertheless, we also observed fewer P-element insertions in piRNA clusters than expected, which is not compatible with a simple trap model. The ping-pong cycle, which degrades TE transcripts, becomes typically active after the copy number plateaued. We generated a model, with few parameters, that largely captures the observed invasion dynamics. We conclude that the transposition rate has at the most only a minor influence on TE abundance, but other factors, such as paramutations or selection against TE insertions are shaping the TE composition.

Natural variation in Drosophila shows weak pleiotropic effects

Background

Pleiotropy describes the phenomenon in which a gene affects multiple phenotypes. The extent of pleiotropy is still disputed, mainly because of issues of inadequate power of analyses. A further challenge is that empirical tests of pleiotropy are restricted to a small subset of all possible phenotypes. To overcome these limitations, we propose a new measurement of pleiotropy that integrates across many phenotypes and multiple generations to improve power.

Results

We infer pleiotropy from the fitness cost imposed by frequency changes of pleiotropic loci. Mixing Drosophila simulans populations, which adapted independently to the same new environment using different sets of genes, we show that the adaptive frequency changes have been accompanied by measurable fitness costs.

Conclusions

Unlike previous studies characterizing the molecular basis of pleiotropy, we show that many loci, each of weak effect, contribute to genome-wide pleiotropy. We propose that the costs of pleiotropy are reduced by the modular architecture of gene expression, which facilitates adaptive gene expression changes with low impact on other functions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02680-4.

Pool-GWAS on reproductive dormancy in Drosophila simulans suggests a polygenic architecture

The genetic basis of adaptation to different environments has been of long-standing interest to evolutionary biologists. Dormancy is a well-studied adaptation to facilitate overwintering. In Drosophila melanogaster, a moderate number of genes with large effects have been described, which suggests a simple genetic basis of dormancy. On the other hand, genome-wide scans for dormancy suggest a polygenic architecture in insects. In D. melanogaster, the analysis of the genetic architecture of dormancy is complicated by the presence of cosmopolitan inversions. Here, we performed a genome-wide scan to characterize the genetic basis of this ecologically extremely important trait in the sibling species of D. melanogaster, D. simulans that lacks cosmopolitan inversions. We performed Pool-GWAS in a South African D. simulans population for dormancy incidence at 2 temperature regimes (10 and 12°C, LD 10:14). We identified several genes with SNPs that showed a significant association with dormancy (P-value < 1e-13), but the overall modest response suggests that dormancy is a polygenic trait with many loci of small effect. Our results shed light on controversies on reproductive dormancy in Drosophila and have important implications for the characterization of the genetic basis of this trait.

Evolution of phenotypic variance in response to a novel hot environment

Shifts in trait means are widely considered as evidence for adaptive responses, but the impact on phenotypic variance remains largely unexplored. Classic quantitative genetics provides a theoretical framework to predict how selection on phenotypic mean affects the variance. In addition to this indirect effect, it is also possible that the variance of the trait is the direct target of selection, but experimentally characterized cases are rare. Here, we studied gene expression variance of Drosophila simulans males before and after 100 generations of adaptation to a novel hot laboratory environment. In each of the two independently evolved populations, the variance of 125 and 97 genes was significantly reduced. We propose that the drastic loss in environmental complexity from nature to the laboratory may have triggered selection for reduced variance. Our observation that selection could drive changes in the variance of gene expression could have important implications for studies of adaptation processes in natural and experimental populations.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime

Background

Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

Results

Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime.

Conclusions

These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02425-9.

The Evolution of Phenotypic Plasticity in Response to Temperature Stress

Phenotypic plasticity is the ability of a single genotype to produce different phenotypes in response to environmental variation. The importance of phenotypic plasticity in natural populations and its contribution to phenotypic evolution during rapid environmental change is widely debated. Here, we show that thermal plasticity of gene expression in natural populations is a key component of its adaptation: evolution to novel thermal environments increases ancestral plasticity rather than mean genetic expression. We determined the evolution of plasticity in gene expression by conducting laboratory natural selection on a Drosophila simulans population in hot and cold environments. After more than 60 generations in the hot environment, 325 genes evolved a change in plasticity relative to the natural ancestral population. Plasticity increased in 75% of these genes, which were strongly enriched for several well-defined functional categories (e.g., chitin metabolism, glycolysis, and oxidative phosphorylation). Furthermore, we show that plasticity in gene expression of populations exposed to different temperatures is rather similar across species. We conclude that most of the ancestral plasticity can evolve further in more extreme environments.

Fitness effects for Ace insecticide resistance mutations are determined by ambient temperature

BACKGROUND

Insect pest control programs often use periods of insecticide treatment with intermittent breaks, to prevent fixing of mutations conferring insecticide resistance. Such mutations are typically costly in an insecticide-free environment, and their frequency is determined by the balance between insecticide treatment and cost of resistance. Ace, a key gene in neuronal signaling, is a prominent target of many insecticides and across several species, three amino acid replacements (I161V, G265A, and F330Y) provide resistance against several insecticides. Because temperature disturbs neuronal signaling homeostasis, we reasoned that the cost of insecticide resistance could be modulated by ambient temperature.

RESULTS

Experimental evolution of a natural Drosophila simulans population at hot and cold temperature regimes uncovered a surprisingly strong effect of ambient temperature. In the cold temperature regime, the resistance mutations were strongly counter selected (s = - 0.055), but in a hot environment, the fitness costs of resistance mutations were reduced by almost 50% (s = - 0.031). We attribute this unexpected observation to the advantage of the reduced enzymatic activity of resistance mutations in hot environments.

CONCLUSION

We show that fitness costs of insecticide resistance genes are temperature-dependent and suggest that the duration of insecticide-free periods need to be adjusted for different climatic regions to reflect these costs. We suggest that such environment-dependent fitness effects may be more common than previously assumed and pose a major challenge for modeling climate change.

Neuronal Function and Dopamine Signaling Evolve at High Temperature in Drosophila

Neuronal activity is temperature sensitive and affects behavioral traits important for individual fitness, such as locomotion and courtship. Yet, we do not know enough about the evolutionary response of neuronal phenotypes in new temperature environments. Here, we use long-term experimental evolution of Drosophila simulans populations exposed to novel temperature regimes. Here, we demonstrate a direct relationship between thermal selective pressure and the evolution of neuronally expressed molecular and behavioral phenotypes. Several essential neuronal genes evolve lower expression at high temperatures and higher expression at low temperatures, with dopaminergic neurons standing out by displaying the most consistent expression change across independent replicates. We functionally validate the link between evolved gene expression and behavioral changes by pharmacological intervention in the experimentally evolved D. simulans populations as well as by genetically triggered expression changes of key genes in D. melanogaster. As natural temperature clines confirm our results for Drosophila and Anopheles populations, we conclude that neuronal dopamine evolution is a key factor for temperature adaptation.

Rapid sex-specific adaptation to high temperature in Drosophila

The pervasive occurrence of sexual dimorphism demonstrates different adaptive strategies of males and females. While different reproductive strategies of the two sexes are well-characterized, very little is known about differential functional requirements of males and females in their natural habitats. Here, we study the impact environmental change on the selection response in both sexes. Exposing replicated Drosophila populations to a novel temperature regime, we demonstrate sex-specific changes in gene expression, metabolic and behavioral phenotypes in less than 100 generations. This indicates not only different functional requirements of both sexes in the new environment but also rapid sex-specific adaptation. Supported by computer simulations we propose that altered sex-biased gene regulation from standing genetic variation, rather than new mutations, is the driver of rapid sex-specific adaptation. Our discovery of environmentally driven divergent functional requirements of males and females has important implications-possibly even for gender aware medical treatments.

A Deep Learning Approach for Detecting Copy Number Variation in Next-Generation Sequencing Data

Copy number variants (CNV) are associated with phenotypic variation in several species. However, properly detecting changes in copy numbers of sequences remains a difficult problem, especially in lower quality or lower coverage next-generation sequencing data. Here, inspired by recent applications of machine learning in genomics, we describe a method to detect duplications and deletions in short-read sequencing data. In low coverage data, machine learning appears to be more powerful in the detection of CNVs than the gold-standard methods of coverage estimation alone, and of equal power in high coverage data. We also demonstrate how replicating training sets allows a more precise detection of CNVs, even identifying novel CNVs in two genomes previously surveyed thoroughly for CNVs using long read data.

RaGOO: fast and accurate reference-guided scaffolding of draft genomes

We present RaGOO, a reference-guided contig ordering and orienting tool that leverages the speed and sensitivity of Minimap2 to accurately achieve chromosome-scale assemblies in minutes. After the pseudomolecules are constructed, RaGOO identifies structural variants, including those spanning sequencing gaps. We show that RaGOO accurately orders and orients 3 de novo tomato genome assemblies, including the widely used M82 reference cultivar. We then demonstrate the scalability and utility of RaGOO with a pan-genome analysis of 103 Arabidopsis thaliana accessions by examining the structural variants detected in the newly assembled pseudomolecules. RaGOO is available open source at https://github.com/malonge/RaGOO .

DNA Motifs Are Not General Predictors of Recombination in Two Drosophila Sister Species

Meiotic recombination is crucial for chromosomal segregation and facilitates the spread of beneficial and removal of deleterious mutations. Recombination rates frequently vary along chromosomes and Drosophila melanogaster exhibits a remarkable pattern. Recombination rates gradually decrease toward centromeres and telomeres, with a dramatic impact on levels of variation in natural populations. Two close sister species, Drosophila simulans and Drosophila mauritiana do not only have higher recombination rates but also exhibit a much more homogeneous recombination rate that only drops sharply very close to centromeres and telomeres. Because certain sequence motifs are associated with recombination rate variation in D. melanogaster, we tested whether the difference in recombination landscape between D. melanogaster and D. simulans can be explained by the genomic distribution of recombination rate–associated sequence motifs. We constructed the first high-resolution recombination map for D. simulans based on 189 haplotypes from a natural D. simulans population and searched for short sequence motifs linked with higher than average recombination in both sister species. We identified five consensus motifs significantly associated with higher than average chromosome-wide recombination rates in at least one species and present in both. Testing fine resolution associations between motif density and recombination, we found strong and positive associations genome-wide over a range of scales in D. melanogaster, while the results were equivocal in D. simulans. Despite the strong association in D. melanogaster, we did not find a decreasing density of these short-repeat motifs toward centromeres and telomeres. We conclude that the density of recombination-associated repeat motifs cannot explain the large-scale recombination landscape in D. melanogaster, nor the differences to D. simulans. The strong association seen for the sequence motifs in D. melanogaster likely reflects their impact influencing local differences in recombination rates along the genome.

Genetic redundancy fuels polygenic adaptation in Drosophila

The genetic architecture of adaptive traits is of key importance to predict evolutionary responses. Most adaptive traits are polygenic-i.e., result from selection on a large number of genetic loci-but most molecularly characterized traits have a simple genetic basis. This discrepancy is best explained by the difficulty in detecting small allele frequency changes (AFCs) across many contributing loci. To resolve this, we use laboratory natural selection to detect signatures for selective sweeps and polygenic adaptation. We exposed 10 replicates of a Drosophila simulans population to a new temperature regime and uncovered a polygenic architecture of an adaptive trait with high genetic redundancy among beneficial alleles. We observed convergent responses for several phenotypes-e.g., fitness, metabolic rate, and fat content-and a strong polygenic response (99 selected alleles; mean s = 0.059). However, each of these selected alleles increased in frequency only in a subset of the evolving replicates. We discerned different evolutionary paradigms based on the heterogeneous genomic patterns among replicates. Redundancy and quantitative trait (QT) paradigms fitted the experimental data better than simulations assuming independent selective sweeps. Our results show that natural D. simulans populations harbor a vast reservoir of adaptive variation facilitating rapid evolutionary responses using multiple alternative genetic pathways converging at a new phenotypic optimum. This key property of beneficial alleles requires the modification of testing strategies in natural populations beyond the search for convergence on the molecular level.

A 24 h Age Difference Causes Twice as Much Gene Expression Divergence as 100 Generations of Adaptation to a Novel Environment

Gene expression profiling is one of the most reliable high-throughput phenotyping methods, allowing researchers to quantify the transcript abundance of expressed genes. Because many biotic and abiotic factors influence gene expression, it is recommended to control them as tightly as possible. Here, we show that a 24 h age difference of Drosophilasimulans females that were subjected to RNA sequencing (RNA-Seq) five and six days after eclosure resulted in more than 2000 differentially expressed genes. This is twice the number of genes that changed expression during 100 generations of evolution in a novel hot laboratory environment. Importantly, most of the genes differing in expression due to age introduce false positives or negatives if an adaptive gene expression analysis is not controlled for age. Our results indicate that tightly controlled experimental conditions, including precise developmental staging, are needed for reliable gene expression analyses, in particular in an evolutionary framework.

A Large Panel of Drosophila simulans Reveals an Abundance of Common Variants

The rapidly expanding availability of large NGS data sets provides an opportunity to investigate population genetics at an unprecedented scale. Drosophila simulans is the sister species of the model organism Drosophila melanogaster, and is often presumed to share similar demographic history. However, previous population genetic and ecological work suggests very different signatures of selection and demography. Here, we sequence a new panel of 170 inbred genotypes of a North American population of D. simulans, a valuable complement to the DGRP and other D. melanogaster panels. We find some unexpected signatures of demography, in the form of excess intermediate frequency polymorphisms. Simulations suggest that this is possibly due to a recent population contraction and selection. We examine the outliers in the D. simulans genome determined by a haplotype test to attempt to parse the contribution of demography and selection to the patterns observed in this population. Untangling the relative contribution of demography and selection to genomic patterns of variation is challenging, however, it is clear that although D. melanogaster was thought to share demographic history with D. simulans different forces are at work in shaping genomic variation in this population of D. simulans.

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

BACKGROUND

Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation.

RESULTS

To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements reveal extensive metabolic rewiring after only approximately 60 generations in a hot environment. Analysis of genome-wide polymorphisms identifies two interacting selection targets, Sestrin and SNF4Aγ, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation.

CONCLUSIONS

Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4Aγ also exhibits clinal variation in various Drosophila species, we suggest that this large-effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.

Molecular dissection of a natural transposable element invasion

The first tracking of the dynamics of a natural invasion by a transposable element (TE) provides unprecedented details on the establishment of host defense mechanisms against TEs. We captured a D. simulans population at an early stage of a P-element invasion and studied the spread of the TE in replicated experimentally evolving populations kept under hot and cold conditions. We analyzed the factors controlling the invasion by NGS, RNA-FISH, and gonadal dysgenesis assays. Under hot conditions, the P-element spread rapidly for 20 generations, but no further spread was noted later on. This plateauing of the invasion was mediated by the rapid emergence of P-element-specific piRNAs. Under cold conditions, we observed a lower expression of the P-element and a slower emergence of the piRNA defense, resulting in a three times slower invasion that continued beyond 40 generations. We conclude that the environment is a major factor determining the evolution of TEs in their host.

Maximum Likelihood Implementation of an Isolation-with-Migration Model for Three Species

We develop a maximum likelihood (ML) method for estimating migration rates between species using genomic sequence data. A species tree is used to accommodate the phylogenetic relationships among three species, allowing for migration between the two sister species, while the third species is used as an out-group. A Markov chain characterization of the genealogical process of coalescence and migration is used to integrate out the migration histories at each locus analytically, whereas Gaussian quadrature is used to integrate over the coalescent times on each genealogical tree numerically. This is an extension of our early implementation of the symmetrical isolation-with-migration model for three species to accommodate arbitrary loci with two or three sequences per locus and to allow asymmetrical migration rates. Our implementation can accommodate tens of thousands of loci, making it feasible to analyze genome-scale data sets to test for gene flow. We calculate the posterior probabilities of gene trees at individual loci to identify genomic regions that are likely to have been transferred between species due to gene flow. We conduct a simulation study to examine the statistical properties of the likelihood ratio test for gene flow between the two in-group species and of the ML estimates of model parameters such as the migration rate. Inclusion of data from a third out-group species is found to increase dramatically the power of the test and the precision of parameter estimation. We compiled and analyzed several genomic data sets from the Drosophila fruit flies. Our analyses suggest no migration from D. melanogaster to D. simulans, and a significant amount of gene flow from D. simulans to D. melanogaster, at the rate of ~0.02 migrant individuals per generation. We discuss the utility of the multispecies coalescent model for species tree estimation, accounting for incomplete lineage sorting and migration.

High rate of translocation-based gene birth on the Drosophila Y chromosome

Using a powerful method that uses inexpensive short reads to detect Y-linked transfers, we show that gene traffic onto the Drosophila Y chromosome is 10 times more frequent than previously thought and includes the first Y-linked retrocopies discovered in these taxa. All 25 identified Y-linked gene transfers were relatively young (<1 million years old), although most appear to be pseudogenes because only three of these transfers show signs of purifying selection. Our method provides compelling evidence that the Drosophila Y chromosome is a highly challenging and dynamic genetic environment that is capable of rapidly diverging between species and promises to reveal fundamental insights into Y chromosome evolution across many taxa.

The Y chromosome is a unique genetic environment defined by a lack of recombination and male-limited inheritance. The Drosophila Y chromosome has been gradually acquiring genes from the rest of the genome, with only seven Y-linked genes being gained over the past 63 million years (0.12 gene gains per million years). Using a next-generation sequencing (NGS)-powered genomic scan, we show that gene transfers to the Y chromosome are much more common than previously suspected: at least 25 have arisen across three Drosophila species over the past 5.4 million years (1.67 per million years for each lineage). The gene transfer rate is significantly lower in Drosophila melanogaster than in the Drosophila simulans clade, primarily due to Y-linked retrotranspositions being significantly more common in the latter. Despite all Y-linked gene transfers being evolutionarily recent (<1 million years old), only three showed evidence for purifying selection (ω ≤ 0.14). Thus, although the resulting Y-linked functional gene acquisition rate (0.25 new genes per million years) is double the longer-term estimate, the fate of most new Y-linked genes is defined by rapid degeneration and pseudogenization. Our results show that Y-linked gene traffic, and the molecular mechanisms governing these transfers, can diverge rapidly between species, revealing the Drosophila Y chromosome to be more dynamic than previously appreciated. Our analytical method provides a powerful means to identify Y-linked gene transfers and will help illuminate the evolutionary dynamics of the Y chromosome in Drosophila and other species.

Drosophila simulans: A Species with Improved Resolution in Evolve and Resequence Studies

The combination of experimental evolution with high-throughput sequencing of pooled individuals—i.e., evolve and resequence (E&R)—is a powerful approach to study adaptation from standing genetic variation under controlled, replicated conditions. Nevertheless, E&R studies in Drosophila melanogaster have frequently resulted in inordinate numbers of candidate SNPs, particularly for complex traits. Here, we contrast the genomic signature of adaptation following ∼60 generations in a novel hot environment for D. melanogaster and D. simulans. For D. simulans, the regions carrying putatively selected loci were far more distinct, and thus harbored fewer false positives, than those in D. melanogaster. We propose that species without segregating inversions and higher recombination rates, such as D. simulans, are better suited for E&R studies that aim to characterize the genetic variants underlying the adaptive response.

Suitability of Different Mapping Algorithms for Genome-Wide Polymorphism Scans with Pool-Seq Data

The cost-effectiveness of sequencing pools of individuals (Pool-Seq) provides the basis for the popularity and widespread use of this method for many research questions, ranging from unraveling the genetic basis of complex traits, to the clonal evolution of cancer cells. Because the accuracy of Pool-Seq could be affected by many potential sources of error, several studies have determined, for example, the influence of sequencing technology, the library preparation protocol, and mapping parameters. Nevertheless, the impact of the mapping tools has not yet been evaluated. Using simulated and real Pool-Seq data, we demonstrate a substantial impact of the mapping tools, leading to characteristic false positives in genome-wide scans. The problem of false positives was particularly pronounced when data with different read lengths and insert sizes were compared. Out of 14 evaluated algorithms novoalign, bwa mem and clc4 are most suitable for mapping Pool-Seq data. Nevertheless, no single algorithm is sufficient for avoiding all false positives. We show that the intersection of the results of two mapping algorithms provides a simple, yet effective, strategy to eliminate false positives. We propose that the implementation of a consistent Pool-Seq bioinformatics pipeline, building on the recommendations of this study, can substantially increase the reliability of Pool-Seq results, in particular when libraries generated with different protocols are being compared.

Ancestral population reconstitution from isofemale lines as a tool for experimental evolution

Experimental evolution is a powerful tool to study adaptation under controlled conditions. Laboratory natural selection experiments mimic adaptation in the wild with better‐adapted genotypes having more offspring. Because the selected traits are frequently not known, adaptation is typically measured as fitness increase by comparing evolved populations against an unselected reference population maintained in a laboratory environment. With adaptation to the laboratory conditions and genetic drift, however, it is not clear to what extent such comparisons provide unbiased estimates of adaptation. Alternatively, ancestral variation could be preserved in isofemale lines that can be combined to reconstitute the ancestral population. Here, we assess the impact of selection on alleles segregating in newly established Drosophila isofemale lines. We reconstituted two populations from isofemale lines and compared them to two original ancestral populations (AP) founded from the same lines shortly after collection. No significant allele frequency changes could be detected between both AP and simulations showed that drift had a low impact compared to Pool‐Seq‐associated sampling effects. We conclude that laboratory selection on segregating variation in isofemale lines is too weak to have detectable effects, which validates ancestral population reconstitution from isofemale lines as an unbiased approach for measuring adaptation in evolved populations.

Hybrid Dysgenesis in Drosophila simulans Associated with a Rapid Invasion of the P-Element

In a classic example of the invasion of a species by a selfish genetic element, the P-element was horizontally transferred from a distantly related species into Drosophila melanogaster. Despite causing ‘hybrid dysgenesis’, a syndrome of abnormal phenotypes that include sterility, the P-element spread globally in the course of a few decades in D. melanogaster. Until recently, its sister species, including D. simulans, remained P-element free. Here, we find a hybrid dysgenesis-like phenotype in the offspring of crosses between D. simulans strains collected in different years; a survey of 181 strains shows that around 20% of strains induce hybrid dysgenesis. Using genomic and transcriptomic data, we show that this dysgenesis-inducing phenotype is associated with the invasion of the P-element. To characterize this invasion temporally and geographically, we survey 631 D. simulans strains collected on three continents and over 27 years for the presence of the P-element. We find that the D. simulans P-element invasion occurred rapidly and nearly simultaneously in the regions surveyed, with strains containing P-elements being rare in 2006 and common by 2014. Importantly, as evidenced by their resistance to the hybrid dysgenesis phenotype, strains collected from the latter phase of this invasion have adapted to suppress the worst effects of the P-element.

Some genes perform necessary organismal functions, others hijack the cellular machinery to replicate themselves, potentially harming the host in the process. These ‘selfish genes’ can spread through genomes and species; as a result, eukaryotic genomes are typically saddled with large amounts of parasitic DNA. Here, we chronicle the surprisingly rapid global spread of a selfish transposable element through a close relative of the genetic model, Drosophila melanogaster. We see that, as it spreads, the transposable element is associated with damaging effects, including sterility, but that the flies quickly adapt to the negative consequences of the transposable element.

Tempo and Mode of Transposable Element Activity in Drosophila

The evolutionary dynamics of transposable element (TE) insertions have been of continued interest since TE activity has important implications for genome evolution and adaptation. Here, we infer the transposition dynamics of TEs by comparing their abundance in natural D. melanogaster and D. simulans populations. Sequencing pools of more than 550 South African flies to at least 320-fold coverage, we determined the genome wide TE insertion frequencies in both species. We suggest that the predominance of low frequency insertions in the two species (>80% of the insertions have a frequency <0.2) is probably due to a high activity of more than 58 families in both species. We provide evidence for 50% of the TE families having temporally heterogenous transposition rates with different TE families being affected in the two species. While in D. melanogaster retrotransposons were more active, DNA transposons showed higher activity levels in D. simulans. Moreover, we suggest that LTR insertions are mostly of recent origin in both species, while DNA and non-LTR insertions are older and more frequently vertically transmitted since the split of D. melanogaster and D. simulans. We propose that the high TE activity is of recent origin in both species and a consequence of the demographic history, with habitat expansion triggering a period of rapid evolution.

The impact of library preparation protocols on the consistency of allele frequency estimates in Pool-Seq data

Sequencing pools of individuals (Pool‐Seq) is a cost‐effective method to determine genome‐wide allele frequency estimates. Given the importance of meta‐analyses combining data sets, we determined the influence of different genomic library preparation protocols on the consistency of allele frequency estimates. We found that typically no more than 1% of the variation in allele frequency estimates could be attributed to differences in library preparation. Also read length had only a minor effect on the consistency of allele frequency estimates. By far, the most pronounced influence could be attributed to sequence coverage. Increasing the coverage from 30‐ to 50‐fold improved the consistency of allele frequency estimates by at least 27%. We conclude that Pool‐Seq data can be easily combined across different library preparation methods, but sufficient sequence coverage is key to reliable results.

The recent invasion of natural Drosophila simulans populations by the P-element

The P-element is one of the best understood eukaryotic transposable elements. It invaded Drosophila melanogaster populations within a few decades but was thought to be absent from close relatives, including Drosophila simulans. Five decades after the spread in D. melanogaster, we provide evidence that the P-element has also invaded D. simulans. P-elements in D. simulans appear to have been acquired recently from D. melanogaster probably via a single horizontal transfer event. Expression data indicate that the P-element is processed in the germ line of D. simulans, and genomic data show an enrichment of P-element insertions in putative origins of replication, similar to that seen in D. melanogaster. This ongoing spread of the P-element in natural populations provides a unique opportunity to understand the dynamics of transposable element spread and the associated piwi-interacting RNAs defense mechanisms.

Combining experimental evolution with next-generation sequencing: a powerful tool to study adaptation from standing genetic variation

Evolve and resequence (E&R) is a new approach to investigate the genomic responses to selection during experimental evolution. By using whole genome sequencing of pools of individuals (Pool-Seq), this method can identify selected variants in controlled and replicable experimental settings. Reviewing the current state of the field, we show that E&R can be powerful enough to identify causative genes and possibly even single-nucleotide polymorphisms. We also discuss how the experimental design and the complexity of the trait could result in a large number of false positive candidates. We suggest experimental and analytical strategies to maximize the power of E&R to uncover the genotype-phenotype link and serve as an important research tool for a broad range of evolutionary questions.