The many landscapes of recombination in Drosophila melanogaster

Temporal challenges in detecting balancing selection from population genomic data

The role of balancing selection in maintaining genetic variation remains an open question in population genetics. Recent years have seen numerous studies identifying candidate loci potentially experiencing balancing selection, most predominantly in human populations. There are however numerous alternative evolutionary processes that may leave similar patterns of variation, thereby potentially confounding inference, and the expected signatures of balancing selection additionally change in a temporal fashion. Here we use forward-in-time simulations to quantify expected statistical power to detect balancing selection using both site frequency spectrum- and linkage disequilibrium-based methods under a variety of evolutionarily realistic null models. We find that whilst site frequency spectrum-based methods have little power immediately after a balanced mutation begins segregating, power increases with time since the introduction of the balanced allele. Conversely, linkage disequilibrium-based methods have considerable power whilst the allele is young, and power dissipates rapidly as the time since introduction increases. Taken together, this suggests that site frequency spectrum-based methods are most effective at detecting long-term balancing selection (>25N generations since the introduction of the balanced allele) whilst linkage disequilibrium-based methods are effective over much shorter timescales (<1N generations), thereby leaving a large time frame over which current methods have little power to detect the action of balancing selection. Finally, we investigate the extent to which alternative evolutionary processes may mimic these patterns, and demonstrate the need for caution in attempting to distinguish the signatures of balancing selection from those of both neutral processes (e.g. population structure and admixture) as well as of alternative selective processes (e.g. partial selective sweeps).

Inversions Can Accumulate Balanced Sexual Antagonism: Evidence from Simulations and Drosophila Experiments

Chromosomal inversion polymorphisms can be common, but the causes of their persistence are often unclear. We propose a model for the maintenance of inversion polymorphism, which requires that some variants contribute antagonistically to two phenotypes, one of which has negative frequency-dependent fitness. These conditions yield a form of frequency-dependent disruptive selection, favoring two predominant haplotypes segregating alleles that favor opposing antagonistic phenotypes. An inversion associated with one haplotype can reduce the fitness load incurred by generating recombinant offspring, reinforcing its linkage to the haplotype and enabling both haplotypes to accumulate more antagonistic variants than expected otherwise. We develop and apply a forward simulator to examine these dynamics under a tradeoff between survival and male display. These simulations indeed generate inversion-associated haplotypes with opposing sex-specific fitness effects. Antagonism strengthens with time, and can ultimately yield karyotypes at surprisingly predictable frequencies, with striking genotype frequency differences between sexes and between developmental stages. To test whether this model may contribute to well-studied yet enigmatic inversion polymorphisms in Drosophila melanogaster, we track inversion frequencies in laboratory crosses to test whether they influence male reproductive success or survival. We find that two of the four tested inversions show significant evidence for the tradeoff examined, with In(3R)K favoring survival and In(3L)Ok favoring male reproduction. In line with the apparent sex-specific fitness effects implied for both of those inversions, In(3L)Ok was also found to be less costly to the viability and/or longevity of males than females, whereas In(3R)K was more beneficial to female survival. Based on this work, we expect that balancing selection on antagonistically pleiotropic traits may provide a significant and underappreciated contribution to the maintenance of natural inversion polymorphism.

Acetylcholine esterase of Drosophila melanogaster: a laboratory model to explore insecticide susceptibility gene drives

BACKGROUND

One of the proposed applications of gene drives has been to revert pesticide resistant mutations back to the ancestral susceptible state. Insecticides that have become ineffective because of the rise of resistance could have reinvigorated utility and be used to suppress pest populations again, perhaps at lower application doses.

RESULTS

We have created a laboratory model for susceptibility gene drives that replaces field-selected resistant variants of the acetylcholine esterase (Ace) locus of Drosophila melanogaster with ancestral susceptible variants. We constructed a CRISPR/Cas9 homing drive and found that homing occurred in many genetic backgrounds with varying efficiencies. While the drive itself could not be homozygous, it converted resistant alleles into susceptible ones and produced recessive lethal alleles that could suppress populations. Our studies provided evidence for two distinct classes of gene drive resistance (GDR): rather than being mediated by the conventional non-homologous end-joining (NHEJ) pathway, one seemed to involve short homologous repair and the other was defined by genetic background. Additionally, we used simulations to explore a distinct application of susceptibility drives; the use of chemicals to prevent the spread of synthetic gene drives into protected areas.

CONCLUSIONS

Insecticide susceptibility gene drives could be useful tools to control pest insects however problems with particularities of target loci and GDR will need to be overcome for them to be effective. Furthermore, realistic patterns of pest dispersal and high insecticide exposure rates would be required if susceptibility were to be useful as a 'safety-switch' to prevent the unwanted spread of gene drives. © 2024 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Effects of demographic history on recombination hotspots in soybean

Recombination is the primary mechanism underlying genetic improvement in populations and allows plant breeders to create new allelic combinations for agronomic improvement. Soybean [Glycine max (L.) Merr.] has gone through multiple genetic bottlenecks that have significantly affected its genetic diversity, linkage disequilibrium, and altered allele frequencies. To investigate the impact of genetic bottlenecks on recombination hotspots in soybeans, historical recombination was studied in three soybean populations. The populations were wild soybean [Glycine soja (Sieb. and Zucc.)], landraces, and North American elite soybean cultivars that have been genotyped with the SoySNP50K BeadChip. While each population after a genetic bottleneck had an increased average haplotype block size, they did not have a significant difference in the number of hotspots between each population. Instead, the increase in observed haplotype block size is likely due to an elimination of individuals that contained historical recombination at hotspots which decreased the observed rate of recombination for the hotspot after each genetic bottleneck. Conversely, heterochromatic DNA which has an increased haplotype block size compared to euchromatic DNA had a significantly different number of hotspots but not a significant difference in the average hotspot recombination rate. Previously identified genomic motifs associated with hotspots were also associated with hotspots found in the historical populations suggesting a common mechanism. This characterization of historical recombination hotspots in soybeans provides further insights into the effect genetic bottlenecks and selection have on recombination hotspots.

Recombinant inbred line panels inform the genetic architecture and interactions of adaptive traits in Drosophila melanogaster

The distribution of allelic effects on traits, along with their gene-by-gene and gene-by-environment interactions, contributes to the phenotypes available for selection and the trajectories of adaptive variants. Nonetheless, uncertainty persists regarding the effect sizes underlying adaptations and the importance of genetic interactions. Herein, we aimed to investigate the genetic architecture and the epistatic and environmental interactions involving loci that contribute to multiple adaptive traits using two new panels of Drosophila melanogaster recombinant inbred lines (RILs). To better fit our data, we re-implemented functions from R/qtl (Broman et al. 2003) using additive genetic models. We found 14 quantitative trait loci (QTL) underlying melanism, wing size, song pattern, and ethanol resistance. By combining our mapping results with population genetic statistics, we identified potential new genes related to these traits. None of the detected QTLs showed clear evidence of epistasis, and our power analysis indicated that we should have seen at least one significant interaction if sign epistasis or strong positive epistasis played a pervasive role in trait evolution. In contrast, we did find roles for gene-by-environment interactions involving pigmentation traits. Overall, our data suggest that the genetic architecture of adaptive traits often involves alleles of detectable effect, that strong epistasis does not always play a role in adaptation, and that environmental interactions can modulate the effect size of adaptive alleles.

Boundary Effects Cause False Signals of Range Expansions in Population Genomic Data

Studying range expansions is central for understanding genetic variation through space and time as well as for identifying refugia and biological invasions. Range expansions are characterized by serial founder events causing clines of decreasing genetic diversity away from the center of origin and asymmetries in the two-dimensional allele frequency spectra. These asymmetries, summarized by the directionality index (ψ), are sensitive to range expansions and persist for longer than clines in genetic diversity. In continuous and finite meta-populations, genetic drift tends to be stronger at the edges of the species distribution in equilibrium populations and populations undergoing range expansions alike. Such boundary effects are expected to affect geographic patterns in genetic diversity and ψ. Here we demonstrate that boundary effects cause high false positive rates in equilibrium meta-populations when testing for range expansions. In the simulations, the absolute value of ψ (|ψ|) in equilibrium data sets was proportional to the fixation index (FST). By fitting signatures of range expansions as a function of ɛ |ψ|/FST and geographic clines in ψ, strong evidence for range expansions could be detected in data from a recent rapid invasion of the cane toad, Rhinella marina, in Australia, but not in 28 previously published empirical data sets from Australian scincid lizards that were significant for the standard range expansion tests. Thus, while clinal variation in ψ is still the most sensitive statistic to range expansions, to detect true signatures of range expansions in natural populations, its magnitude needs to be considered in relation to the overall levels of genetic structuring in the data.

A general and efficient representation of ancestral recombination graphs

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. This approach is out of step with modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalises these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

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.

Population size rescaling significantly biases outcomes of forward-in-time population genetic simulations

Simulations are an essential tool in all areas of population genetic research, used in tasks such as the validation of theoretical analysis and the study of complex evolutionary models. Forward-in-time simulations are especially flexible, allowing for various types of natural selection, complex genetic architectures, and non-Wright-Fisher dynamics. However, their intense computational requirements can be prohibitive to simulating large populations and genomes. A popular method to alleviate this burden is to scale down the population size by some scaling factor while scaling up the mutation rate, selection coefficients, and recombination rate by the same factor. However, this rescaling approach may in some cases bias simulation results. To investigate the manner and degree to which rescaling impacts simulation outcomes, we carried out simulations with different demographic histories and distributions of fitness effects using several values of the rescaling factor, Q , and compared the deviation of key outcomes (fixation times, fixation probabilities, allele frequencies, and linkage disequilibrium) between the scaled and unscaled simulations. Our results indicate that scaling introduces substantial biases to each of these measured outcomes, even at small values of Q . Moreover, the nature of these effects depends on the evolutionary model and scaling factor being examined. While increasing the scaling factor tends to increase the observed biases, this relationship is not always straightforward, thus it may be difficult to know the impact of scaling on simulation outcomes a priori. However, it appears that for most models, only a small number of replicates was needed to accurately quantify the bias produced by rescaling for a given Q . In summary, while rescaling forward-in-time simulations may be necessary in many cases, researchers should be aware of the rescaling effect's impact on simulation outcomes and consider investigating its magnitude in smaller scale simulations of the desired model(s) before selecting an appropriate value of Q .

Enrichment of hard sweeps on the X chromosome compared to autosomes in six Drosophila species

The X chromosome, being hemizygous in males, is exposed one-third of the time increasing the visibility of new mutations to natural selection, potentially leading to different evolutionary dynamics than autosomes. Recently, we found an enrichment of hard selective sweeps over soft selective sweeps on the X chromosome relative to the autosomes in a North American population of Drosophila melanogaster. To understand whether this enrichment is a universal feature of evolution on the X chromosome, we analyze diversity patterns across 6 commonly studied Drosophila species. We find an increased proportion of regions with steep reductions in diversity and elevated homozygosity on the X chromosome compared to autosomes. To assess if these signatures are consistent with positive selection, we simulate a wide variety of evolutionary scenarios spanning variations in demography, mutation rate, recombination rate, background selection, hard sweeps, and soft sweeps and find that the diversity patterns observed on the X are most consistent with hard sweeps. Our findings highlight the importance of sex chromosomes in driving evolutionary processes and suggest that hard sweeps have played a significant role in shaping diversity patterns on the X chromosome across multiple Drosophila species.

Multiple Genomic Landscapes of Recombination and Genomic Divergence in Wild Populations of House Mice-The Role of Chromosomal Fusions and Prdm9

Chromosomal fusions represent one of the most common types of chromosomal rearrangements found in nature. Yet, their role in shaping the genomic landscape of recombination and hence genome evolution remains largely unexplored. Here, we take advantage of wild mice populations with chromosomal fusions to evaluate the effect of this type of structural variant on genomic landscapes of recombination and divergence. To this aim, we combined cytological analysis of meiotic crossovers in primary spermatocytes with inferred analysis of recombination rates based on linkage disequilibrium using single nucleotide polymorphisms. Our results suggest the presence of a combined effect of Robertsonian fusions and Prdm9 allelic background, a gene involved in the formation of meiotic double strand breaks and postzygotic reproductive isolation, in reshaping genomic landscapes of recombination. We detected a chromosomal redistribution of meiotic recombination toward telomeric regions in metacentric chromosomes in mice with Robertsonian fusions when compared to nonfused mice. This repatterning was accompanied by increased levels of crossover interference and reduced levels of estimated recombination rates between populations, together with high levels of genomic divergence. Interestingly, we detected that Prdm9 allelic background was a major determinant of recombination rates at the population level, whereas Robertsonian fusions showed limited effects, restricted to centromeric regions of fused chromosomes. Altogether, our results provide new insights into the effect of Robertsonian fusions and Prdm9 background on meiotic recombination.

Population genetic simulation: Benchmarking frameworks for non-standard models of natural selection

Population genetic simulation has emerged as a common tool for investigating increasingly complex evolutionary and demographic models. Software capable of handling high-level model complexity has recently been developed, and the advancement of tree sequence recording now allows simulations to merge the efficiency and genealogical insight of coalescent simulations with the flexibility of forward simulations. However, frameworks utilizing these features have not yet been compared and benchmarked. Here, we evaluate various simulation workflows using the coalescent simulator msprime and the forward simulator SLiM, to assess resource efficiency and determine an optimal simulation framework. Three aspects were evaluated: (1) the burn-in, to establish an equilibrium level of neutral diversity in the population; (2) the forward simulation, in which temporally fluctuating selection is acting; and (3) the final computation of summary statistics. We provide typical memory and computation time requirements for each step. We find that the fastest framework, a combination of coalescent and forward simulation with tree sequence recording, increases simulation speed by over twenty times compared to classical forward simulations without tree sequence recording, although it does require six times more memory. Overall, using efficient simulation workflows can lead to a substantial improvement when modelling complex evolutionary scenarios-although the optimal framework ultimately depends on the available computational resources.

The genome-wide meiotic recombination landscape in ciliates and its implications for crossover regulation and genome evolution

Meiotic recombination is essential for sexual reproduction and its regulation has been extensively studied in many taxa. However, genome-wide recombination landscape has not been reported in ciliates and it remains unknown how it is affected by the unique features of ciliates: the synaptonemal complex (SC)-independent meiosis and the nuclear dimorphism. Here, we show the recombination landscape in the model ciliate Tetrahymena thermophila by analyzing single-nucleotide polymorphism datasets from 38 hybrid progeny. We detect 1021 crossover (CO) events (35.8 per meiosis), corresponding to an overall CO rate of 9.9 cM/Mb. However, gene conversion by non-crossover is rare (1.03 per meiosis) and not biased towards G or C alleles. Consistent with the reported roles of SC in CO interference, we find no obvious sign of CO interference. CO tends to occur within germ-soma common genomic regions and many of the 44 identified CO hotspots localize at the centromeric or subtelomeric regions. Gene ontology analyses show that CO hotspots are strongly associated with genes responding to environmental changes. We discuss these results with respect to how nuclear dimorphism has potentially driven the formation of the observed recombination landscape to facilitate environmental adaptation and the sharing of machinery among meiotic and somatic recombination.

Polygenic response of sex chromosomes to sexual antagonism

Sexual antagonism occurs when males and females differ in their phenotypic fitness optima but are constrained in their evolution to these optima because of their shared genome. The sex chromosomes, which have distinct evolutionary "interests" relative to the autosomes, are theorized to play an important role in sexually antagonistic conflict. However, the evolutionary responses of sex chromosomes and autosomes have usually been considered independently, that is, via contrasting the response of a gene located on either an X chromosome or an autosome. Here, we study the coevolutionary response of the X chromosome and autosomes to sexually antagonistic selection acting on a polygenic phenotype. We model a phenotype initially under stabilizing selection around a single optimum, followed by a sudden divergence of the male and female optima. We find that, in the absence of dosage compensation, the X chromosome promotes evolution toward the female optimum, inducing coevolutionary male-biased responses on the autosomes. Dosage compensation obscures the female-biased interests of the X, causing it to contribute equally to male and female phenotypic change. We further demonstrate that fluctuations in an adaptive landscape can generate prolonged intragenomic conflict and accentuate the differential responses of the X and autosomes to this conflict.

The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.

IntroUNET: Identifying introgressed alleles via semantic segmentation

A growing body of evidence suggests that gene flow between closely related species is a widespread phenomenon. Alleles that introgress from one species into a close relative are typically neutral or deleterious, but sometimes confer a significant fitness advantage. Given the potential relevance to speciation and adaptation, numerous methods have therefore been devised to identify regions of the genome that have experienced introgression. Recently, supervised machine learning approaches have been shown to be highly effective for detecting introgression. One especially promising approach is to treat population genetic inference as an image classification problem, and feed an image representation of a population genetic alignment as input to a deep neural network that distinguishes among evolutionary models (i.e. introgression or no introgression). However, if we wish to investigate the full extent and fitness effects of introgression, merely identifying genomic regions in a population genetic alignment that harbor introgressed loci is insufficient-ideally we would be able to infer precisely which individuals have introgressed material and at which positions in the genome. Here we adapt a deep learning algorithm for semantic segmentation, the task of correctly identifying the type of object to which each individual pixel in an image belongs, to the task of identifying introgressed alleles. Our trained neural network is thus able to infer, for each individual in a two-population alignment, which of those individual's alleles were introgressed from the other population. We use simulated data to show that this approach is highly accurate, and that it can be readily extended to identify alleles that are introgressed from an unsampled "ghost" population, performing comparably to a supervised learning method tailored specifically to that task. Finally, we apply this method to data from Drosophila, showing that it is able to accurately recover introgressed haplotypes from real data. This analysis reveals that introgressed alleles are typically confined to lower frequencies within genic regions, suggestive of purifying selection, but are found at much higher frequencies in a region previously shown to be affected by adaptive introgression. Our method's success in recovering introgressed haplotypes in challenging real-world scenarios underscores the utility of deep learning approaches for making richer evolutionary inferences from genomic data.

Novel Insights into the Landscape of Crossover and Noncrossover Events in Rhesus Macaques (Macaca mulatta)

Meiotic recombination landscapes differ greatly between distantly and closely related taxa, populations, individuals, sexes, and even within genomes; however, the factors driving this variation are yet to be well elucidated. Here, we directly estimate contemporary crossover rates and, for the first time, noncrossover rates in rhesus macaques (Macaca mulatta) from four three-generation pedigrees comprising 32 individuals. We further compare these results with historical, demography-aware, linkage disequilibrium-based recombination rate estimates. From paternal meioses in the pedigrees, 165 crossover events with a median resolution of 22.3 kb were observed, corresponding to a male autosomal map length of 2,357 cM-approximately 15% longer than an existing linkage map based on human microsatellite loci. In addition, 85 noncrossover events with a mean tract length of 155 bp were identified-similar to the tract lengths observed in the only other two primates in which noncrossovers have been studied to date, humans and baboons. Consistent with observations in other placental mammals with PRDM9-directed recombination, crossover (and to a lesser extent noncrossover) events in rhesus macaques clustered in intergenic regions and toward the chromosomal ends in males-a pattern in broad agreement with the historical, sex-averaged recombination rate estimates-and evidence of GC-biased gene conversion was observed at noncrossover sites.

Enrichment of hard sweeps on the X chromosome compared to autosomes in six Drosophila species

The X chromosome, being hemizygous in males, is exposed one third of the time increasing the visibility of new mutations to natural selection, potentially leading to different evolutionary dynamics than autosomes. Recently, we found an enrichment of hard selective sweeps over soft selective sweeps on the X chromosome relative to the autosomes in a North American population of Drosophila melanogaster. To understand whether this enrichment is a universal feature of evolution on the X chromosome, we analyze diversity patterns across six commonly studied Drosophila species. We find an increased proportion of regions with steep reductions in diversity and elevated homozygosity on the X chromosome compared to autosomes. To assess if these signatures are consistent with positive selection, we simulate a wide variety of evolutionary scenarios spanning variations in demography, mutation rate, recombination rate, background selection, hard sweeps, and soft sweeps, and find that the diversity patterns observed on the X are most consistent with hard sweeps. Our findings highlight the importance of sex chromosomes in driving evolutionary processes and suggest that hard sweeps have played a significant role in shaping diversity patterns on the X chromosome across multiple Drosophila species.

Allelic gene conversion softens selective sweeps

The prominence of positive selection, in which beneficial mutations are favored by natural selection and rapidly increase in frequency, is a subject of intense debate. Positive selection can result in selective sweeps, in which the haplotype(s) bearing the adaptive allele "sweep" through the population, thereby removing much of the genetic diversity from the region surrounding the target of selection. Two models of selective sweeps have been proposed: classical sweeps, or "hard sweeps", in which a single copy of the adaptive allele sweeps to fixation, and "soft sweeps", in which multiple distinct copies of the adaptive allele leave descendants after the sweep. Soft sweeps can be the outcome of recurrent mutation to the adaptive allele, or the presence of standing genetic variation consisting of multiple copies of the adaptive allele prior to the onset of selection. Importantly, soft sweeps will be common when populations can rapidly adapt to novel selective pressures, either because of a high mutation rate or because adaptive alleles are already present. The prevalence of soft sweeps is especially controversial, and it has been noted that selection on standing variation or recurrent mutations may not always produce soft sweeps. Here, we show that the inverse is true: selection on single-origin de novo mutations may often result in an outcome that is indistinguishable from a soft sweep. This is made possible by allelic gene conversion, which "softens" hard sweeps by copying the adaptive allele onto multiple genetic backgrounds, a process we refer to as a "pseudo-soft" sweep. We carried out a simulation study examining the impact of gene conversion on sweeps from a single de novo variant in models of human, Drosophila, and Arabidopsis populations. The fraction of simulations in which gene conversion had produced multiple haplotypes with the adaptive allele upon fixation was appreciable. Indeed, under realistic demographic histories and gene conversion rates, even if selection always acts on a single-origin mutation, sweeps involving multiple haplotypes are more likely than hard sweeps in large populations, especially when selection is not extremely strong. Thus, even when the mutation rate is low or there is no standing variation, hard sweeps are expected to be the exception rather than the rule in large populations. These results also imply that the presence of signatures of soft sweeps does not necessarily mean that adaptation has been especially rapid or is not mutation limited.

The effects of mutation and recombination rate heterogeneity on the inference of demography and the distribution of fitness effects

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavour; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modelled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination prior to utilizing population genomic data to quantify the effects of genetic drift (i.e., as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modelled in downstream inference.

Inferring multi-locus selection in admixed populations

Admixture, the exchange of genetic information between distinct source populations, is thought to be a major source of adaptive genetic variation. Unlike mutation events, which periodically generate single alleles, admixture can introduce many selected alleles simultaneously. As such, the effects of linkage between selected alleles may be especially pronounced in admixed populations. However, existing tools for identifying selected mutations within admixed populations only account for selection at a single site, overlooking phenomena such as linkage among proximal selected alleles. Here, we develop and extensively validate a method for identifying and quantifying the individual effects of multiple linked selected sites on a chromosome in admixed populations. Our approach numerically calculates the expected local ancestry landscape in an admixed population for a given multi-locus selection model, and then maximizes the likelihood of the model. After applying this method to admixed populations of Drosophila melanogaster and Passer italiae, we found that the impacts between linked sites may be an important contributor to natural selection in admixed populations. Furthermore, for the situations we considered, the selection coefficients and number of selected sites are overestimated in analyses that do not consider the effects of linkage among selected sites. Our results imply that linkage among selected sites may be an important evolutionary force in admixed populations. This tool provides a powerful generalized method to investigate these crucial phenomena in diverse populations.

Female meiotic drive shapes the distribution of rare inversion polymorphisms in Drosophila melanogaster

In all species, new chromosomal inversions are constantly being formed by spontaneous rearrangement and then stochastically eliminated from natural populations. In Drosophila, when new chromosomal inversions overlap with a preexisting inversion in the population, their rate of elimination becomes a function of the relative size, position, and linkage phase of the gene rearrangements. These altered dynamics result from complex meiotic behavior wherein overlapping inversions generate asymmetric dyads that cause both meiotic drive/drag and segmental aneuploidy. In this context, patterns in rare inversion polymorphisms of a natural population can be modeled from the fundamental genetic processes of forming asymmetric dyads via crossing-over in meiosis I and preferential segregation from asymmetric dyads in meiosis II. Here, a mathematical model of crossover-dependent female meiotic drive is developed and parameterized with published experimental data from Drosophila melanogaster laboratory constructs. This mechanism is demonstrated to favor smaller, distal inversions and accelerate the elimination of larger, proximal inversions. Simulated sampling experiments indicate that the paracentric inversions directly observed in natural population surveys of D. melanogaster are a biased subset that both maximizes meiotic drive and minimizes the frequency of lethal zygotes caused by this cytogenetic mechanism. Incorporating this form of selection into a population genetic model accurately predicts the shift in relative size, position, and linkage phase for rare inversions found in this species. The model and analysis presented here suggest that this weak form of female meiotic drive is an important process influencing the genomic distribution of rare inversion polymorphisms.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

An empirical test of the estimation of historical effective population size using Drosophila melanogaster

The availability of a large number of high-density markers (SNPs) allows the estimation of historical effective population size (Ne ) from linkage disequilibrium between loci. A recent refinement of methods to estimate historical Ne from the recent past has been shown to be rather accurate with simulation data. The method has also been applied to real data for numerous species. However, the simulation data cannot encompass all the complexities of real genomes, and the performance of any estimation method with real data is always uncertain, as the true demography of the populations is not known. Here, we carried out an experimental design with Drosophila melanogaster to test the method with real data following a known demographic history. We used a population maintained in the laboratory with a constant census size of about 2800 individuals and subjected the population to a drastic decline to a size of 100 individuals. After a few generations, the population was expanded back to the previous size and after a few further generations again expanded to twice the initial size. Estimates of historical Ne were obtained with the software GONE both for autosomal and X chromosomes from samples of 17 individuals sequenced for the whole genome. Estimates of the historical effective size were able to infer the patterns of changes that occurred in the populations showing generally good performance of the method. We discuss the limitations of the method and the application of the software carried out so far.

Genomes from historical Drosophila melanogaster specimens illuminate adaptive and demographic changes across more than 200 years of evolution

The ability to perform genomic sequencing on long-dead organisms is opening new frontiers in evolutionary research. These opportunities are especially notable in the case of museum collections, from which countless documented specimens may now be suitable for genomic analysis-if data of sufficient quality can be obtained. Here, we report 25 newly sequenced genomes from museum specimens of the model organism Drosophila melanogaster, including the oldest extant specimens of this species. By comparing historical samples ranging from the early 1800s to 1933 against modern-day genomes, we document evolution across thousands of generations, including time periods that encompass the species' initial occupation of northern Europe and an era of rapidly increasing human activity. We also find that the Lund, Sweden population underwent local genetic differentiation during the early 1800s to 1933 interval (potentially due to drift in a small population) but then became more similar to other European populations thereafter (potentially due to increased migration). Within each century-scale time period, our temporal sampling allows us to document compelling candidates for recent natural selection. In some cases, we gain insights regarding previously implicated selection candidates, such as ChKov1, for which our inferred timing of selection favors the hypothesis of antiviral resistance over insecticide resistance. Other candidates are novel, such as the circadian-related gene Ahcy, which yields a selection signal that rivals that of the DDT resistance gene Cyp6g1. These insights deepen our understanding of recent evolution in a model system, and highlight the potential of future museomic studies.

Targeted recombination of homologous chromosomes using CRISPR-Cas9

CRISPR mutagenesis is an efficient way to disrupt specific target genes in many model organisms. We previously devised a targeted CRISPR recombination method to generate intragenic recombinants of alleles in Drosophila. Here, we assessed the applicability of CRISPR targeting-induced recombination to different genetic loci. We compared the ectopic recombination rates in the male germline by CRISPR targeting at two neighboring genetic loci within the genomic region that consists of the repressed chromatin domain of the Lobe gene, and the transcriptionally active domain of PRAS40. Targeting around the transcription initiation of PRAS40 resulted in higher recombination rates of homologous chromosomes than targeting at the Lobe intron. Based on the efficient homologous recombination by CRISPR targeting observed around transcriptionally active loci, we further investigated targeted recombination between P-elements that are inserted at different genomic locations. Male recombination by CRISPR targeting of P-elements located proximally and distally to the ebony gene produced recombinants deficient for the intervening region of ebony transcription. Taken together, we suggest that targeted homologous recombination by CRISPR targeting may have specific genetic applications, such as generation of allelic combinations or chromosomal variations.

Mitonuclear interactions shape both direct and parental effects of diet on fitness and involve a SNP in mitoribosomal 16s rRNA

Nutrition is a primary determinant of health, but responses to nutrition vary with genotype. Epistasis between mitochondrial and nuclear genomes may cause some of this variation, but which mitochondrial loci and nutrients participate in complex gene-by-gene-by-diet interactions? Furthermore, it remains unknown whether mitonuclear epistasis is involved only in the immediate responses to changes in diet, or whether mitonuclear genotype might modulate sensitivity to variation in parental nutrition, to shape intergenerational fitness responses. Here, in Drosophila melanogaster, we show that mitonuclear epistasis shapes fitness responses to variation in dietary lipids and amino acids. We also show that mitonuclear genotype modulates the parental effect of dietary lipid and amino acid variation on offspring fitness. Effect sizes for the interactions between diet, mitogenotype, and nucleogenotype were equal to or greater than the main effect of diet for some traits, suggesting that dietary impacts cannot be understood without first accounting for these interactions. Associating phenotype to mtDNA variation in a subset of populations implicated a C/T polymorphism in mt:lrRNA, which encodes the 16S rRNA of the mitochondrial ribosome. This association suggests that directionally different responses to dietary changes can result from variants on mtDNA that do not change protein coding sequence, dependent on epistatic interactions with variation in the nuclear genome.

The role of recombination landscape in species hybridisation and speciation

It is now well recognised that closely related species can hybridize and exchange genetic material, which may promote or oppose adaptation and speciation. In some cases, interspecific hybridisation is very common, making it surprising that species identity is preserved despite active gene exchange. The genomes of most eukaryotic species are highly heterogeneous with regard to gene density, abundance of repetitive DNA, chromatin compactisation etc, which can make certain genomic regions more prone or more resistant to introgression of genetic material from other species. Heterogeneity in local recombination rate underpins many of the observed patterns across the genome (e.g. actively recombining regions are typically gene rich and depleted for repetitive DNA) and it can strongly affect the permeability of genomic regions to interspecific introgression. The larger the region lacking recombination, the higher the chance for the presence of species incompatibility gene(s) in that region, making the entire non- or rarely recombining block impermeable to interspecific introgression. Large plant genomes tend to have highly heterogeneous recombination landscape, with recombination frequently occurring at the ends of the chromosomes and central regions lacking recombination. In this paper we review the relationship between recombination and introgression in plants and argue that large rarely recombining regions likely play a major role in preserving species identity in actively hybridising plant species.

The fitness of an introgressing haplotype changes over the course of divergence and depends on its size and genomic location

The genomic era has made clear that introgression, or the movement of genetic material between species, is a common feature of evolution. Examples of both adaptive and deleterious introgression exist in a variety of systems. What is unclear is how the fitness of an introgressing haplotype changes as species diverge or as the size of the introgressing haplotype changes. In a simple model, we show that introgression may more easily occur into parts of the genome which have not diverged heavily from a common ancestor. The key insight is that alleles from a shared genetic background are likely to have positive epistatic interactions, increasing the fitness of a larger introgressing block. In regions of the genome where few existing substitutions are disrupted, this positive epistasis can be larger than incompatibilities with the recipient genome. Further, we show that early in the process of divergence, introgression of large haplotypes can be favored more than introgression of individual alleles. This model is consistent with observations of a positive relationship between recombination rate and introgression frequency across the genome; however, it generates several novel predictions. First, the model suggests that the relationship between recombination rate and introgression may not exist, or may be negative, in recently diverged species pairs. Furthermore, the model suggests that introgression that replaces existing derived variation will be more deleterious than introgression at sites carrying ancestral variants. These predictions are tested in an example of introgression in Drosophila melanogaster, with some support for both. Finally, the model provides a potential alternative explanation to asymmetry in the direction of introgression, with expectations of higher introgression from rapidly diverged populations into slowly evolving ones.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Teaser Text

Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.

The fine-scale recombination rate variation and associations with genomic features in a butterfly

Recombination is a key molecular mechanism that has profound implications on both micro- and macroevolutionary processes. However, the determinants of recombination rate variation in holocentric organisms are poorly understood, in particular in Lepidoptera (moths and butterflies). The wood white butterfly (Leptidea sinapis) shows considerable intraspecific variation in chromosome numbers and is a suitable system for studying regional recombination rate variation and its potential molecular underpinnings. Here, we developed a large whole-genome resequencing data set from a population of wood whites to obtain high-resolution recombination maps using linkage disequilibrium information. The analyses revealed that larger chromosomes had a bimodal recombination landscape, potentially caused by interference between simultaneous chiasmata. The recombination rate was significantly lower in subtelomeric regions, with exceptions associated with segregating chromosome rearrangements, showing that fissions and fusions can have considerable effects on the recombination landscape. There was no association between the inferred recombination rate and base composition, supporting a limited influence of GC-biased gene conversion in butterflies. We found significant but variable associations between the recombination rate and the density of different classes of transposable elements, most notably a significant enrichment of short interspersed nucleotide elements in genomic regions with higher recombination rate. Finally, the analyses unveiled significant enrichment of genes involved in farnesyltranstransferase activity in recombination coldspots, potentially indicating that expression of transferases can inhibit formation of chiasmata during meiotic division. Our results provide novel information about recombination rate variation in holocentric organisms and have particular implications for forthcoming research in population genetics, molecular/genome evolution, and speciation.

Variation in mutation, recombination, and transposition rates in Drosophila melanogaster and Drosophila simulans

The rates of mutation, recombination, and transposition are core parameters in models of evolution. They impact genetic diversity, responses to ongoing selection, and levels of genetic load. However, even for key evolutionary model species such as Drosophila melanogaster and Drosophila simulans, few estimates of these parameters are available, and we have little idea of how rates vary between individuals, sexes, or populations. Knowledge of this variation is fundamental for parameterizing models of genome evolution. Here, we provide direct estimates of mutation, recombination, and transposition rates and their variation in a West African and a European population of D. melanogaster and a European population of D. simulans Across 89 flies, we observe 58 single-nucleotide mutations, 286 crossovers, and 89 transposable element (TE) insertions. Compared to the European D. melanogaster, we find the West African population has a lower mutation rate (1.67 × 10-9 site-1 gen-1 vs. 4.86 × 10-9 site-1 gen-1) and a lower transposition rate (8.99 × 10-5 copy-1 gen-1 vs. 23.36 × 10-5 copy-1 gen-1), but a higher recombination rate (3.44 cM/Mb vs. 2.06 cM/Mb). The European D. simulans population has a similar mutation rate to European D. melanogaster, but a significantly higher recombination rate and a lower, but not significantly different, transposition rate. Overall, we find paternal-derived mutations are more frequent than maternal ones in both species. Our study quantifies the variation in rates of mutation, recombination, and transposition among different populations and sexes, and our direct estimates of these parameters in D. melanogaster and D. simulans will benefit future studies in population and evolutionary genetics.

P-element invasion fuels molecular adaptation in laboratory populations of Drosophila melanogaster

Transposable elements (TEs) are mobile genetic parasites that frequently invade new host genomes through horizontal transfer. Invading TEs often exhibit a burst of transposition, followed by reduced transposition rates as repression evolves in the host. We recreated the horizontal transfer of P-element DNA transposons into a Drosophila melanogaster host and followed the expansion of TE copies and evolution of host repression in replicate laboratory populations reared at different temperatures. We observed that while populations maintained at high temperatures rapidly go extinct after TE invasion, those maintained at lower temperatures persist, allowing for TE spread and the evolution of host repression. We also surprisingly discovered that invaded populations experienced recurrent insertion of P-elements into a specific long non-coding RNA, lncRNA:CR43651, and that these insertion alleles are segregating at unusually high frequency in experimental populations, indicative of positive selection. We propose that, in addition to driving the evolution of repression, transpositional bursts of invading TEs can drive molecular adaptation.

Lessons from the meiotic recombination landscape of the ZMM deficient budding yeast Lachancea waltii

Meiotic recombination is a driving force for genome evolution, deeply characterized in a few model species, notably in the budding yeast Saccharomyces cerevisiae. Interestingly, Zip2, Zip3, Zip4, Spo16, Msh4, and Msh5, members of the so-called ZMM pathway that implements the interfering meiotic crossover pathway in S. cerevisiae, have been lost in Lachancea yeast species after the divergence of Lachancea kluyveri from the rest of the clade. In this context, after investigating meiosis in L. kluyveri, we determined the meiotic recombination landscape of Lachancea waltii. Attempts to generate diploid strains with fully hybrid genomes invariably resulted in strains with frequent whole-chromosome aneuploidy and multiple extended regions of loss of heterozygosity (LOH), which mechanistic origin is so far unclear. Despite the lack of multiple ZMM pro-crossover factors in L. waltii, numbers of crossovers and noncrossovers per meiosis were higher than in L. kluyveri but lower than in S. cerevisiae, for comparable genome sizes. Similar to L. kluyveri but opposite to S. cerevisiae, L. waltii exhibits an elevated frequency of zero-crossover bivalents. Lengths of gene conversion tracts for both crossovers and non-crossovers in L. waltii were comparable to those observed in S. cerevisiae and shorter than in L. kluyveri despite the lack of Mlh2, a factor limiting conversion tract size in S. cerevisiae. L. waltii recombination hotspots were not shared with either S. cerevisiae or L. kluyveri, showing that meiotic recombination hotspots can evolve at a rather limited evolutionary scale within budding yeasts. Finally, L. waltii crossover interference was reduced relative to S. cerevisiae, with interference being detected only in the 25 kb distance range. Detection of positive inference only at short distance scales in the absence of multiple ZMM factors required for interference-sensitive crossovers in other systems likely reflects interference between early recombination precursors such as DSBs.

Bait-ER: A Bayesian method to detect targets of selection in Evolve-and-Resequence experiments

For over a decade, experimental evolution has been combined with high-throughput sequencing techniques. In so-called Evolve-and-Resequence (E&R) experiments, populations are kept in the laboratory under controlled experimental conditions where their genomes are sampled and allele frequencies monitored. However, identifying signatures of adaptation in E&R datasets is far from trivial, and it is still necessary to develop more efficient and statistically sound methods for detecting selection in genome-wide data. Here, we present Bait-ER - a fully Bayesian approach based on the Moran model of allele evolution to estimate selection coefficients from E&R experiments. The model has overlapping generations, a feature that describes several experimental designs found in the literature. We tested our method under several different demographic and experimental conditions to assess its accuracy and precision, and it performs well in most scenarios. Nevertheless, some care must be taken when analysing trajectories where drift largely dominates and starting frequencies are low. We compare our method with other available software and report that ours has generally high accuracy even for trajectories whose complexity goes beyond a classical sweep model. Furthermore, our approach avoids the computational burden of simulating an empirical null distribution, outperforming available software in terms of computational time and facilitating its use on genome-wide data. We implemented and released our method in a new open-source software package that can be accessed at https://doi.org/10.5281/zenodo.7351736.

Identification of sex chromosomes and primary sex ratio in the small hive beetle, a worldwide parasite of honey bees

BACKGROUND

The small hive beetle (SHB), Aethina tumida, has emerged as a worldwide threat to honey bees in the past two decades. These beetles harvest nest resources, feed on larval bees, and ultimately spoil nest resources with gelatinous slime together with the fungal symbiont Kodamaea ohmeri.

RESULTS

Here, we present the first chromosome-level genome assembly for the SHB. With a 99.1% representation of conserved (BUSCO) arthropod genes, this resource enables the study of chemosensory, digestive, and detoxification traits critical for SHB success and possible control. We use this annotated assembly to characterize features of SHB sex chromosomes and a female-skewed primary sex ratio. We also found chromosome fusion and a lower recombination rate in sex chromosomes than in autosomes.

CONCLUSIONS

Genome-enabled insights will clarify the traits that allowed this beetle to exploit hive resources successfully and will be critical for determining the causes of observed sex ratio asymmetries.

GADMA2: more efficient and flexible demographic inference from genetic data

BACKGROUND

Inference of complex demographic histories is a source of information about events that happened in the past of studied populations. Existing methods for demographic inference typically require input from the researcher in the form of a parameterized model. With an increased variety of methods and tools, each with its own interface, the model specification becomes tedious and error-prone. Moreover, optimization algorithms used to find model parameters sometimes turn out to be inefficient, for instance, by being not properly tuned or highly dependent on a user-provided initialization. The open-source software GADMA addresses these problems, providing automatic demographic inference. It proposes a common interface for several likelihood engines and provides global parameters optimization based on a genetic algorithm.

RESULTS

Here, we introduce the new GADMA2 software and provide a detailed description of the added and expanded features. It has a renovated core code base, new likelihood engines, an updated optimization algorithm, and a flexible setup for automatic model construction. We provide a full overview of GADMA2 enhancements, compare the performance of supported likelihood engines on simulated data, and demonstrate an example of GADMA2 usage on 2 empirical datasets.

CONCLUSIONS

We demonstrate the better performance of a genetic algorithm in GADMA2 by comparing it to the initial version and other existing optimization approaches. Our experiments on simulated data indicate that GADMA2's likelihood engines are able to provide accurate estimations of demographic parameters even for misspecified models. We improve model parameters for 2 empirical datasets of inbred species.

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.

Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster

Experimental evolution combined with whole-genome sequencing (evolve and resequence (E&R)) is a powerful approach to study the adaptive architecture of selected traits. Nevertheless, so far the focus has been on the selective response triggered by a single stressor. Building on the highly parallel selection response of founder populations with reduced variation, we evaluated how the presence of a second stressor affects the genomic selection response. After 20 generations of adaptation to laboratory conditions at either 18°C or 29°C, strong genome-wide selection signatures were observed. Only 38% of the selection signatures can be attributed to laboratory adaptation (no difference between temperature regimes). The remaining selection responses are either caused by temperature-specific effects, or reflect the joint effects of temperature and laboratory adaptation (same direction, but the magnitude differs between temperatures). The allele frequency changes resulting from the combined effects of temperature and laboratory adaptation were more extreme in the hot environment for 83% of the affected genomic regions-indicating widespread synergistic effects of the two stressors. We conclude that E&R with reduced genetic variation is a powerful approach to study genome-wide fitness consequences driven by the combined effects of multiple environmental factors.

Variation in fine-scale recombination rate in temperature-evolved Drosophila melanogaster populations in response to selection

Meiotic recombination plays a critical evolutionary role in maintaining fitness in response to selective pressures due to changing environments. Variation in recombination rate has been observed amongst and between species and populations and within genomes across numerous taxa. Studies have demonstrated a link between changes in recombination rate and selection, but the extent to which fine-scale recombination rate varies between evolved populations during the evolutionary period in response to selection is under active research. Here, we utilize a set of 3 temperature-evolved Drosophila melanogaster populations that were shown to have diverged in several phenotypes, including recombination rate, based on the temperature regime in which they evolved. Using whole-genome sequencing data from these populations, we generated linkage disequilibrium-based fine-scale recombination maps for each population. With these maps, we compare recombination rates and patterns among the 3 populations and show that they have diverged at fine scales but are conserved at broader scales. We further demonstrate a correlation between recombination rates and genomic variation in the 3 populations. Lastly, we show variation in localized regions of enhanced recombination rates, termed warm spots, between the populations with these warm spots and associated genes overlapping areas previously shown to have diverged in the 3 populations due to selection. These data support the existence of recombination modifiers in these populations which are subject to selection during evolutionary change.

impMKT: the imputed McDonald and Kreitman test, a straightforward correction that significantly increases the evidence of positive selection of the McDonald and Kreitman test at the gene level

The McDonald and Kreitman test is one of the most powerful and widely used methods to detect and quantify recurrent natural selection in DNA sequence data. One of its main limitations is the underestimation of positive selection due to the presence of slightly deleterious variants segregating at low frequencies. Although several approaches have been developed to overcome this limitation, most of them work on gene pooled analyses. Here, we present the imputed McDonald and Kreitman test (impMKT), a new straightforward approach for the detection of positive selection and other selection components of the distribution of fitness effects at the gene level. We compare imputed McDonald and Kreitman test with other widely used McDonald and Kreitman test approaches considering both simulated and empirical data. By applying imputed McDonald and Kreitman test to humans and Drosophila data at the gene level, we substantially increase the statistical evidence of positive selection with respect to previous approaches (e.g. by 50% and 157% compared with the McDonald and Kreitman test in Drosophila and humans, respectively). Finally, we review the minimum number of genes required to obtain a reliable estimation of the proportion of adaptive substitution (α) in gene pooled analyses by using the imputed McDonald and Kreitman test compared with other McDonald and Kreitman test implementations. Because of its simplicity and increased power to detect recurrent positive selection on genes, we propose the imputed McDonald and Kreitman test as the first straightforward approach for testing specific evolutionary hypotheses at the gene level. The software implementation and population genomics data are available at the web-server imkt.uab.cat.

HUGE pipeline to measure temporal genetic variation in Drosophila suzukii populations for genetic biocontrol applications

Understanding the fine-scale genome sequence diversity that exists within natural populations is important for developing models of species migration, temporal stability, and range expansion. For invasive species, agricultural pests, and disease vectors, sequence diversity at specific loci in the genome can impact the efficacy of next-generation genetic biocontrol strategies. Here we describe a pipeline for haplotype-resolution genetic variant discovery and quantification from thousands of Spotted Wing Drosophila (Drosophila suzukii, SWD) isolated at two field sites in the North-Central United States (Minnesota) across two seasons. We observed highly similar single nucleotide polymorphism (SNP) frequencies at each genomic location at each field site and year. This supports the hypotheses that SWD overwinters in Minnesota, is annually populated by the same source populations or a combination of both theories. Also, the stable genetic structure of SWD populations allows for the rational design of genetic biocontrol technologies for population suppression.

Gene flow biases population genetic inference of recombination rate

Accurate estimates of the rate of recombination are key to understanding a host of evolutionary processes as well as the evolution of the recombination rate itself. Model-based population genetic methods that infer recombination rates from patterns of linkage disequilibrium in the genome have become a popular method to estimate rates of recombination. However, these linkage disequilibrium-based methods make a variety of simplifying assumptions about the populations of interest that are often not met in natural populations. One such assumption is the absence of gene flow from other populations. Here, we use forward-time population genetic simulations of isolation-with-migration scenarios to explore how gene flow affects the accuracy of linkage disequilibrium-based estimators of recombination rate. We find that moderate levels of gene flow can result in either the overestimation or underestimation of recombination rates by up to 20–50% depending on the timing of divergence. We also find that these biases can affect the detection of interpopulation differences in recombination rate, causing both false positives and false negatives depending on the scenario. We discuss future possibilities for mitigating these biases and recommend that investigators exercise caution and confirm that their study populations meet assumptions before deploying these methods.

Meiotic crossover interference: Methods of analysis and mechanisms of action

Segregation of chromosomes during meiosis, to form haploid gametes from diploid precursor cells, requires in most species formation of crossovers physically connecting homologous chromosomes. Along with sister chromatid cohesion, crossovers allow tension to be generated when chromosomes begin to segregate; tension signals that chromosome movement is proceeding properly. But crossovers too close to each other might result in less sister chromatid cohesion and tension and thus failed meiosis. Interference describes the non-random distribution of crossovers, which occur farther apart than expected from independence. We discuss both genetic and cytological methods of assaying crossover interference and models for interference, whose molecular mechanism remains to be elucidated. We note marked differences among species.

Species-specific chromatin landscape determines how transposable elements shape genome evolution

Transposable elements (TEs) are selfish genetic parasites that increase their copy number at the expense of host fitness. The ‘success’, or genome-wide abundance, of TEs differs widely between species. Deciphering the causes for this large variety in TE abundance has remained a central question in evolutionary genomics. We previously proposed that species-specific TE abundance could be driven by the inadvertent consequences of host-direct epigenetic silencing of TEs—the spreading of repressive epigenetic marks from silenced TEs into adjacent sequences. Here, we compared this TE-mediated local enrichment of repressive marks, or ‘the epigenetic effect of TEs’, in six species in the Drosophila melanogaster subgroup to dissect step-by-step the role of such effect in determining genomic TE abundance. We found that TE-mediated local enrichment of repressive marks is prevalent and substantially varies across and even within species. While this TE-mediated effect alters the epigenetic states of adjacent genes, we surprisingly discovered that the transcription of neighboring genes could reciprocally impact this spreading. Importantly, our multi-species analysis provides the power and appropriate phylogenetic resolution to connect species-specific host chromatin regulation, TE-mediated epigenetic effects, the strength of natural selection against TEs, and genomic TE abundance unique to individual species. Our findings point toward the importance of host chromatin landscapes in shaping genome evolution through the epigenetic effects of a selfish genetic parasite.

All the instructions required for life are encoded in the set of DNA present in a cell. It therefore seems natural to think that every bit of this genetic information should serve the organism. And yet most species carry parasitic ‘transposable’ sequences, or transposons, whose only purpose is to multiply and insert themselves at other positions in the genome.

It is possible for cells to suppress these selfish elements. Chemical marks can be deposited onto the DNA to temporarily ‘silence’ transposons and prevent them from being able to move and replicate. However, this sometimes comes at a cost: the repressive chemical modifications can spread to nearby genes that are essential for the organism and perturb their function.

Strangely, the prevalence of transposons varies widely across the tree of life. These sequences form the majority of the genome of certain species – in fact, they represent about half of the human genetic information. But their abundance is much lower in other organisms, forming a measly 6% of the genome of puffer fish for instance. Even amongst fruit fly species, the prevalence of transposable elements can range between 2% and 25%. What explains such differences?

Huang et al. set out to examine this question through the lens of transposon silencing, systematically comparing how this process impacts nearby regions in six species of fruit flies. This revealed variations in the strength of the side effects associated with transposon silencing, resulting in different levels of perturbation on neighbouring genes. A stronger impact was associated with the species having fewer transposons in its genome, suggesting that an evolutionary pressure is at work to keep the abundance of transposons at a low level in these species. Further analyses showed that the genes which determine how silencing marks are distributed may also be responsible for the variations in the impact of transposon silencing. They could therefore be the ones driving differences in the abundance of transposons between species.

Overall, this work sheds light on the complex mechanisms shaping the evolution of genomes, and it may help to better understand how transposons are linked to processes such as aging and cancer.

Assortative mating enhances postzygotic barriers to gene flow via ancestry bundling

Hybridization and subsequent genetic introgression are now known to be common features of the histories of many species, including our own. Following hybridization, selection often purges introgressed DNA genome-wide. While assortative mating can limit hybridization in the first place, it is also known to play an important role in postzygotic selection against hybrids and, thus, the purging of introgressed DNA. However, this role is usually thought of as a direct one: a tendency for mates to be conspecific reduces the sexual fitness of hybrids, reducing the transmission of introgressed ancestry. Here, we explore a second, indirect role of assortative mating as a postzygotic barrier to gene flow. Under assortative mating, parents covary in their ancestry, causing ancestry to be "bundled" in their offspring and later generations. This bundling effect increases ancestry variance in the population, enhancing the efficiency with which postzygotic selection purges introgressed DNA. Using whole-genome simulations, we show that the bundling effect can comprise a substantial portion of mate choice's overall effect as a postzygotic barrier to gene flow. We then derive a simple method for estimating the impact of the bundling effect from standard metrics of assortative mating. Applying this method to data from a diverse set of hybrid zones, we find that the bundling effect increases the purging of introgressed DNA by between 1.2-fold (in a baboon system with weak assortative mating) and 14-fold (in a swordtail system with strong assortative mating). Thus, assortative mating's bundling effect contributes substantially to the genetic isolation of species.

Turning coldspots into hotspots: targeted recruitment of axis protein Hop1 stimulates meiotic recombination in Saccharomyces cerevisiae

The DNA double strand breaks (DSBs) that initiate meiotic recombination are formed in the context of the meiotic chromosome axis, which in Saccharomyces cerevisiae contains a meiosis-specific cohesin isoform and the meiosis-specific proteins Hop1 and Red1. Hop1 and Red1 are important for DSB formation; DSB levels are reduced in their absence and their levels, which vary along the lengths of chromosomes, are positively correlated with DSB levels. How axis protein levels influence DSB formation and recombination remains unclear. To address this question, we developed a novel approach that uses a bacterial ParB-parS partition system to recruit axis proteins at high levels to inserts at recombination coldspots where Hop1 and Red1 levels are normally low. Recruiting Hop1 markedly increased DSBs and homologous recombination at target loci, to levels equivalent to those observed at endogenous recombination hotspots. This local increase in DSBs did not require Red1 or the meiosis-specific cohesin component Rec8, indicating that, of the axis proteins, Hop1 is sufficient to promote DSB formation. However, while most crossovers at endogenous recombination hotspots are formed by the meiosis-specific MutLγ resolvase, crossovers that formed at an insert locus were only modestly reduced in the absence of MutLγ, regardless of whether or not Hop1 was recruited to that locus. Thus, while local Hop1 levels determine local DSB levels, the recombination pathways that repair these breaks can be determined by other factors, raising the intriguing possibility that different recombination pathways operate in different parts of the genome.

Emerging mechanisms and roles of meiotic crossover repression at centromeres

Crossover events during recombination in meiosis are essential for generating genetic diversity as well as crucial to allow accurate chromosomal segregation between homologous chromosomes. Spatial control for the distribution of crossover events along the chromosomes is largely a tightly regulated process and involves many facets such as interference, repression as well as assurance, to make sure that not too many or too few crossovers are generated. Repression of crossover events at the centromeres is a highly conserved process across all species tested. Failure to inhibit such recombination events can result in chromosomal mis-segregation during meiosis resulting in aneuploid gametes that are responsible for infertility or developmental disorders such as Down's syndrome and other trisomies in humans. In the past few decades, studies to understand the molecular mechanisms behind this repression have shown the involvement of a multitude of factors ranging from the centromere-specific proteins such as the kinetochore to the flanking pericentric heterochromatin as well as DNA double-strand break repair pathways. In this chapter, we review the different mechanisms of pericentric repression mechanisms known till date as well as highlight the importance of understanding this regulation in the context of chromosomal segregation defects. We also discuss the clinical implications of dysregulation of this process, especially in human reproductive health and genetic diseases.

The evaluation of Bcftools mpileup and GATK HaplotypeCaller for variant calling in non-human species

Identification of genetic variations is a central part of population and quantitative genomics studies based on high-throughput sequencing data. Even though popular variant callers such as Bcftools mpileup and GATK HaplotypeCaller were developed nearly 10 years ago, their performance is still largely unknown for non-human species. Here, we showed by benchmark analyses with a simulated insect population that Bcftools mpileup performs better than GATK HaplotypeCaller in terms of recovery rate and accuracy regardless of mapping software. The vast majority of false positives were observed from repeats, especially for GATK HaplotypeCaller. Variant scores calculated by GATK did not clearly distinguish true positives from false positives in the vast majority of cases, implying that hard-filtering with GATK could be challenging. These results suggest that Bcftools mpileup may be the first choice for non-human studies and that variants within repeats might have to be excluded for downstream analyses.