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.

The Potential for a Released Autosomal X-Shredder Becoming a Driving-Y Chromosome and Invasively Suppressing Wild Populations of Malaria Mosquitoes.

Sex-ratio distorters based on X-chromosome shredding are more efficient than sterile male releases for population suppression. X-shredding is a form of sex distortion that skews spermatogenesis of XY males towards the preferential transmission of Y-bearing gametes, resulting in a higher fraction of sons than daughters. Strains harboring X-shredders on autosomes were first developed in the malaria mosquito Anopheles gambiae, resulting in strong sex-ratio distortion. Since autosomal X-shredders are transmitted in a Mendelian fashion and can be selected against, their frequency in the population declines once releases are halted. However, unintended transfer of X-shredders to the Y-chromosome could produce an invasive meiotic drive element, that benefits from its biased transmission to the predominant male-biased offspring and its effective shielding from female negative selection. Indeed, linkage to the Y-chromosome of an active X-shredder instigated the development of the nuclease-based X-shredding system. Here, we analyze mechanisms whereby an autosomal X-shredder could become unintentionally Y-linked after release by evaluating the stability of an established X-shredder strain that is being considered for release, exploring its potential for remobilization in laboratory and wild-type genomes of An. gambiae and provide data regarding expression on the mosquito Y-chromosome. Our data suggest that an invasive X-shredder resulting from a post-release movement of such autosomal transgenes onto the Y-chromosome is unlikely.

Engines of change: Transposable element mutation rates are high and variable within Daphnia magna.

Transposable elements (TEs) represent a major portion of most eukaryotic genomes, yet little is known about their mutation rates or how their activity is shaped by other evolutionary forces. Here, we compare short- and long-term patterns of genome-wide mutation accumulation (MA) of TEs among 9 genotypes from three populations of Daphnia magna from across a latitudinal gradient. While the overall proportion of the genome comprised of TEs is highly similar among genotypes from Finland, Germany, and Israel, populations are distinguishable based on patterns of insertion site polymorphism. Our direct rate estimates indicate TE movement is highly variable (net rates ranging from -11.98 to 12.79 x 10-5 per copy per generation among genotypes), differing both among populations and TE families. Although gains outnumber losses when selection is minimized, both types of events appear to be highly deleterious based on their low frequency in control lines where propagation is not limited to random, single-progeny descent. With rate estimates 4 orders of magnitude higher than base substitutions, TEs clearly represent a highly mutagenic force in the genome. Quantifying patterns of intra- and interspecific variation in TE mobility with and without selection provides insight into a powerful mechanism generating genetic variation in the genome.

Evolution of genome structure in the Drosophila simulans species complex.

The rapid evolution of repetitive DNA sequences, including satellite DNA, tandem duplications, and transposable elements, underlies phenotypic evolution and contributes to hybrid incompatibilities between species. However, repetitive genomic regions are fragmented and misassembled in most contemporary genome assemblies. We generated highly contiguous de novo reference genomes for the Drosophila simulans species complex (D. simulans, D. mauritiana, and D. sechellia), which speciated ∼250,000 yr ago. Our assemblies are comparable in contiguity and accuracy to the current D. melanogaster genome, allowing us to directly compare repetitive sequences between these four species. We find that at least 15% of the D. simulans complex species genomes fail to align uniquely to D. melanogaster owing to structural divergence-twice the number of single-nucleotide substitutions. We also find rapid turnover of satellite DNA and extensive structural divergence in heterochromatic regions, whereas the euchromatic gene content is mostly conserved. Despite the overall preservation of gene synteny, euchromatin in each species has been shaped by clade- and species-specific inversions, transposable elements, expansions and contractions of satellite and tRNA tandem arrays, and gene duplications. We also find rapid divergence among Y-linked genes, including copy number variation and recent gene duplications from autosomes. Our assemblies provide a valuable resource for studying genome evolution and its consequences for phenotypic evolution in these genetic model species.

A community-maintained standard library of population genetic models.

The explosion in population genomic data demands ever more complex modes of analysis, and increasingly, these analyses depend on sophisticated simulations. Recent advances in population genetic simulation have made it possible to simulate large and complex models, but specifying such models for a particular simulation engine remains a difficult and error-prone task. Computational genetics researchers currently re-implement simulation models independently, leading to inconsistency and duplication of effort. This situation presents a major barrier to empirical researchers seeking to use simulations for power analyses of upcoming studies or sanity checks on existing genomic data. Population genetics, as a field, also lacks standard benchmarks by which new tools for inference might be measured. Here, we describe a new resource, stdpopsim, that attempts to rectify this situation. Stdpopsim is a community-driven open source project, which provides easy access to a growing catalog of published simulation models from a range of organisms and supports multiple simulation engine backends. This resource is available as a well-documented python library with a simple command-line interface. We share some examples demonstrating how stdpopsim can be used to systematically compare demographic inference methods, and we encourage a broader community of developers to contribute to this growing resource.

Predicting the Landscape of Recombination Using Deep Learning.

Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here, we describe recombination landscape estimation using recurrent neural networks (ReLERNN), a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, although largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in natural Drosophila populations.

Butterfly abundance declines over 20 years of systematic monitoring in Ohio, USA.

Severe insect declines make headlines, but they are rarely based on systematic monitoring outside of Europe. We estimate the rate of change in total butterfly abundance and the population trends for 81 species using 21 years of systematic monitoring in Ohio, USA. Total abundance is declining at 2% per year, resulting in a cumulative 33% reduction in butterfly abundance. Three times as many species have negative population trends compared to positive trends. The rate of total decline and the proportion of species in decline mirror those documented in three comparable long-term European monitoring programs. Multiple environmental changes such as climate change, habitat degradation, and agricultural practices may contribute to these declines in Ohio and shift the makeup of the butterfly community by benefiting some species over others. Our analysis of life-history traits associated with population trends shows an impact of climate change, as species with northern distributions and fewer annual generations declined more rapidly. However, even common and invasive species associated with human-dominated landscapes are declining, suggesting widespread environmental causes for these trends. Declines in common species, although they may not be close to extinction, will have an outsized impact on the ecosystem services provided by insects. These results from the most extensive, systematic insect monitoring program in North America demonstrate an ongoing defaunation in butterflies that on an annual scale might be imperceptible, but cumulatively has reduced butterfly numbers by a third over 20 years.

Patterns of transposable element variation and clinality in Drosophila.

Natural populations often exist in spatially diverse environments and may experience variation in the strength and targets of natural selection across their ranges. Drosophila provides an excellent opportunity to study the effects of spatially varying selection in natural populations, as both Drosophila melanogaster and Drosophila simulans live across a wide range of environments in North America. Here, we characterize patterns of variation in transposable elements (TEs) from six populations of D. melanogaster and nine populations of D. simulans sampled from multiple latitudes across North America. We find a nearly twofold excess of TEs in D. melanogaster relative to D. simulans, with this difference largely driven by TEs segregating at the lowest and highest allele frequencies. We find no effect of latitude on either total TE abundance or average TE allele frequencies in either species. Moreover, we show that, as a class of mutations, the most common patterns of TE variation do not coincide with the sampled latitudinal gradient, nor are they consistent with local adaptation acting on environmental differences found in the most extreme latitudes. We also do not find a cline in ancestry for North American D. melanogaster-for either TEs or single nucleotide polymorphisms-suggesting a limited role for demography in shaping patterns of TE variation. Though we find little evidence for widespread clinality among TEs in Drosophila, this does not necessarily imply a limited role for TEs in adaptation. We discuss the need for improved models of adaptation to large-scale environmental heterogeneity, and how these might be applied to TEs.

Genome-Wide Estimates of Transposable Element Insertion and Deletion Rates in Drosophila Melanogaster.

Knowing the rate at which transposable elements (TEs) insert and delete is critical for understanding their role in genome evolution. We estimated spontaneous rates of insertion and deletion for all known, active TE superfamilies present in a set of Drosophila melanogaster mutation-accumulation (MA) lines using whole genome sequence data. Our results demonstrate that TE insertions far outpace TE deletions in D. melanogaster. We found a significant effect of background genotype on TE activity, with higher rates of insertions in one MA line. We also found significant rate heterogeneity between the chromosomes, with both insertion and deletion rates elevated on the X relative to the autosomes. Further, we identified significant associations between TE activity and chromatin state, and tested for associations between TE activity and other features of the local genomic environment such as TE content, exon content, GC content, and recombination rate. Our results provide the most detailed assessment of TE mobility in any organism to date, and provide a useful benchmark for both addressing theoretical predictions of TE dynamics and for exploring large-scale patterns of TE movement in D. melanogaster and other species.

The Roles of Compensatory Evolution and Constraint in Aminoacyl tRNA Synthetase Evolution.

Mitochondrial protein translation requires interactions between transfer RNAs encoded by the mitochondrial genome (mt-tRNAs) and mitochondrial aminoacyl tRNA synthetase proteins (mt-aaRS) encoded by the nuclear genome. It has been argued that animal mt-tRNAs have higher deleterious substitution rates relative to their nuclear-encoded counterparts, the cytoplasmic tRNAs (cyt-tRNAs). This dynamic predicts elevated rates of compensatory evolution of mt-aaRS that interact with mt-tRNAs, relative to aaRS that interact with cyt-tRNAs (cyt-aaRS). We find that mt-aaRS do evolve at significantly higher rates (exemplified by higher dN and dN/dS) relative to cyt-aaRS, across mammals, birds, and Drosophila. While this pattern supports a model of compensatory evolution, the level at which a gene is expressed is a more general predictor of protein evolutionary rate. We find that gene expression level explains 10-56% of the variance in aaRS dN/dS, and that cyt-aaRS are more highly expressed in addition to having lower dN/dS values relative to mt-aaRS, consistent with more highly expressed genes being more evolutionarily constrained. Furthermore, we find no evidence of positive selection acting on either class of aaRS protein, as would be expected under a model of compensatory evolution. Nevertheless, the signature of faster mt-aaRS evolution persists in mammalian, but not bird or Drosophila, lineages after controlling for gene expression, suggesting some additional effect of compensatory evolution for mammalian mt-aaRS. We conclude that gene expression is the strongest factor governing differential amino acid substitution rates in proteins interacting with mitochondrial versus cytoplasmic factors, with important differences in mt-aaRS molecular evolution among taxonomic groups.

Revisiting classic clines in Drosophila melanogaster in the age of genomics.

Adaptation to spatially varying environments has been studied for decades, but advances in sequencing technology are now enabling researchers to investigate the landscape of genetic variation underlying this adaptation genome wide. In this review we highlight some of the decades-long research on local adaptation in Drosophila melanogaster from well-studied clines in North America and Australia. We explore the evidence for parallel adaptation and identify commonalities in the genes responding to clinal selection across continents as well as discussing instances where patterns differ among clines. We also investigate recent studies utilizing whole-genome data to identify clines in D. melanogaster and several other systems. Although connecting segregating genomic variation to variation in phenotypes and fitness remains challenging, clinal genomics is poised to increase our understanding of local adaptation and the selective pressures that drive the extensive phenotypic diversity observed in nature.

Drosophila suzukii: the genetic footprint of a recent, worldwide invasion.

Native to Asia, the soft-skinned fruit pest Drosophila suzukii has recently invaded the United States and Europe. The eastern United States represents the most recent expansion of their range, and presents an opportunity to test alternative models of colonization history. Here, we investigate the genetic population structure of this invasive fruit fly, with a focus on the eastern United States. We sequenced six X-linked gene fragments from 246 individuals collected from a total of 12 populations. We examine patterns of genetic diversity within and between populations and explore alternative colonization scenarios using approximate Bayesian computation. Our results indicate high levels of nucleotide diversity in this species and suggest that the recent invasions of Europe and the continental United States are independent demographic events. More broadly speaking, our results highlight the importance of integrating population structure into demographic models, particularly when attempting to reconstruct invasion histories. Finally, our simulation results illustrate the general challenge in reconstructing invasion histories using genetic data and suggest that genome-level data are often required to distinguish among alternative demographic scenarios.