Population Genetic Models Research Articles

Tackling the Pangenome Dilemma Requires the Concerted Analysis of Multiple Population Genetic Processes.

The pangenome is the set of all genes present in a prokaryotic population. Most pangenomes contain many accessory genes of low and intermediate frequencies. Different population genetics processes contribute to the shape of these pangenomes, namely selection and fitness-independent processes such as gene transfer, gene loss, and migration. However, their relative importance is unknown and highly debated. Here, we argue that the debate around prokaryotic pangenomes arose due to the imprecise application of population genetics models. Most importantly, two different processes of horizontal gene transfer act on prokaryotic populations, which are frequently confused, despite their fundamentally different behavior. Genes acquired from distantly related organisms (termed here acquiring gene transfer) are most comparable to mutation in nucleotide sequences. In contrast, gene gain within the population (termed here spreading gene transfer) has an effect on gene frequencies that is identical to the effect of positive selection on single genes. We thus show that selection and fitness-independent population genetic processes affecting pangenomes are indistinguishable at the level of single gene dynamics. Nevertheless, population genetics processes are fundamentally different when considering the joint distribution of all accessory genes across individuals of a population. We propose that, to understand to which degree the different processes shaped pangenome diversity, the development of comprehensive models and simulation tools is mandatory. Furthermore, we need to identify summary statistics and measurable features that can distinguish between the processes, where considering the joint distribution of accessory genes across individuals of a population will be particularly relevant.

Coupling large-spatial scale larval dispersal modelling with barcoding to refine the amphi-Atlantic connectivity hypothesis in deep-sea seep mussels

In highly fragmented and relatively stable cold-seep ecosystems, species are expected to exhibit high migration rates and long-distance dispersal of long-lived pelagic larvae to maintain genetic integrity over their range. Accordingly, several species inhabiting cold seeps are widely distributed across the whole Atlantic Ocean, with low genetic divergence between metapopulations on both sides of the Atlantic Equatorial Belt (AEB, i.e. Barbados and African/European margins). Two hypotheses may explain such patterns: (i) the occurrence of present-day gene flow or (ii) incomplete lineage sorting due to large population sizes and low mutation rates. Here, we evaluated the first hypothesis using the cold seep mussels Gigantidas childressi, G. mauritanicus, Bathymodiolus heckerae and B. boomerang. We combined COI barcoding of 763 individuals with VIKING20X larval dispersal modelling at a large spatial scale not previously investigated. Population genetics supported the parallel evolution of Gigantidas and Bathymodiolus genera in the Atlantic Ocean and the occurrence of a 1-3 Million-year-old vicariance effect that isolated populations across the Caribbean Sea. Both population genetics and larval dispersal modelling suggested that contemporary gene flow and larval exchanges are possible across the AEB and the Caribbean Sea, although probably rare. When occurring, larval flow was eastward (AEB - only for B. boomerang) or northward (Caribbean Sea - only for G. mauritanicus). Caution is nevertheless required since we focused on only one mitochondrial gene, which may underestimate gene flow if a genetic barrier exists. Non-negligible genetic differentiation occurred between Barbados and African populations, so we could not discount the incomplete lineage sorting hypothesis. Larval dispersal modelling simulations supported the genetic findings along the American coast with high amounts of larval flow between the Gulf of Mexico (GoM) and the US Atlantic Margin, although the Blake Ridge population of B. heckerae appeared genetically differentiated. Overall, our results suggest that additional studies using nuclear genetic markers and population genomics approaches are needed to clarify the evolutionary history of the Atlantic bathymodioline mussels and to distinguish between ongoing and past processes.

Evolution with recombination as Gibbs sampling

This work presents a population genetic model of evolution, which includes haploid selection, mutation, recombination, and drift. The mutation-selection equilibrium can be expressed exactly in closed form for arbitrary fitness functions without resorting to diffusion approximations. Tractability is achieved by generating new offspring using n-parent rather than 2-parent recombination. While this enforces linkage equilibrium among offspring, it allows analysis of the whole population under linkage disequilibrium. We derive a general and exact relationship between fitness fluctuations and response to selection. Our assumptions allow analytical calculation of the stationary distribution of the model for a variety of non-trivial fitness functions. These results allow us to speak to genetic architecture, i.e., what stationary distributions result from different fitness functions. This paper presents methods for exactly deriving stationary states for finite and infinite populations. This method can be applied to many fitness functions, and we give exact calculations for four of these. These results allow us to investigate metastability, tradeoffs between fitness functions, and even consider error-correcting codes.

Abstract 860: The dynamics of LINE-1 retrotransposition in cellular populations

Abstract Retrotransposons are genetic elements that have the ability to copy and paste themselves in the genome via the proteins they encode. Since the rapid growth of a retrotransposon can be highly deleterious at the organismal level, many of these genetic parasites are suppressed or have been inactivated over evolutionary time. However, the human genome still hosts the active retrotransposon LINE-1, whose aberrant expression is associated with various diseases, especially epithelial cancers. Despite these associations, a quantitative understanding of the dynamics and diversity of LINE-1 insertions in somatic tissue is lacking. In order to address this gap, we present a population dynamic model of LINE-1 retrotransposition in individual cells. Using the model, we show that at demographic equilibrium, the LINE-1 copy number distribution is broader than would be expected from classical population genetic models. We demonstrate how this broadening distorts the frequency spectrum of insertions. We compare the model's predictions to data from whole genome sequencing of individual tumor cells. Citation Format: Stephen Martis, Alexander Solovyov, Jayon Lihm, Hao Li, Benjamin Greenbaum. The dynamics of LINE-1 retrotransposition in cellular populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 860.

Reproductive Compensation and Selection among Viable Embryos Drive the Evolution of Polyembryony.

AbstractSimple polyembryony, where one gametophyte produces multiple embryos with different sires but the same maternal haplotype, is common among vascular plants. We develop an infinite-sites, forward population genetics model showing that together polyembryony's two benefits-"reproductive compensation" achieved by providing a backup for inviable embryos and the opportunity to favor the fitter of surviving embryos-can favor its evolution. Our model tests how these factors can favor the evolution of polyembryony and how these underlying benefits of polyembryony shape the genetic load under a range of biological parameters. While these two benefits are difficult to disentangle in nature, we construct variant models of polyembryony that either only include or only exclude the opportunity for reproductive compensation. We find that reproductive compensation strongly favors the evolution of polyembryony and that polyembryony is favored much more weekly in its absence, suggesting that the benefit of a backup embryo is the major force favoring polyembryony. Remarkably, we find nearly identical results in cases in which mutations impact either embryonic or postembryonic fitness (no pleiotropy) and in cases in which mutations have identical effects on embryonic and postembryonic fitness (extreme pleiotropy). Finally, we find that the consequences of polyembryony depend on its function-polyembryony results in a decrease in mean embryonic fitness when acting as a mechanism of embryo compensation and ultimately increases mean embryonic fitness when we exclude this potential benefit.

Predation drives complex eco-evolutionary dynamics in sexually selected traits

Predation plays a role in preventing the evolution of ever more complicated sexual displays, because such displays often increase an individual's predation risk. Sexual selection theory, however, omits a key feature of predation in modeling costs to sexually selected traits: Predation is density dependent. As a result of this density dependence, predator-prey dynamics should feed back into the evolution of sexual displays, which, in turn, feeds back into predator-prey dynamics. Here, we develop both population and quantitative genetic models of sexual selection that explicitly link the evolution of sexual displays with predator-prey dynamics. Our primary result is that predation can drive eco-evolutionary cycles in sexually selected traits. We also show that mechanistically modeling the cost to sexual displays as predation leads to novel outcomes such as the maintenance of polymorphism in sexual displays and alters ecological dynamics by muting prey cycles. These results suggest predation as a potential mechanism to maintain variation in sexual displays and underscore that short-term studies of sexual display evolution may not accurately predict long-run dynamics. Further, they demonstrate that a common verbal model (that predation limits sexual displays) with widespread empirical support can result in unappreciated, complex dynamics due to the density-dependent nature of predation.

Neuroblastoma arises in early fetal development and its evolutionary duration predicts outcome

Neuroblastoma, the most frequent solid tumor in infants, shows very diverse outcomes from spontaneous regression to fatal disease. When these different tumors originate and how they evolve are not known. Here we quantify the somatic evolution of neuroblastoma by deep whole-genome sequencing, molecular clock analysis and population-genetic modeling in a comprehensive cohort covering all subtypes. We find that tumors across the entire clinical spectrum begin to develop via aberrant mitoses as early as the first trimester of pregnancy. Neuroblastomas with favorable prognosis expand clonally after short evolution, whereas aggressive neuroblastomas show prolonged evolution during which they acquire telomere maintenance mechanisms. The initial aneuploidization events condition subsequent evolution, with aggressive neuroblastoma exhibiting early genomic instability. We find in the discovery cohort (n = 100), and validate in an independent cohort (n = 86), that the duration of evolution is an accurate predictor of outcome. Thus, insight into neuroblastoma evolution may prospectively guide treatment decisions.

Recurrent mutation in the ancestry of a rare variant.

Recurrent mutation produces multiple copies of the same allele which may be co-segregating in a population. Yet, most analyses of allele-frequency or site-frequency spectra assume that all observed copies of an allele trace back to a single mutation. We develop a sampling theory for the number of latent mutations in the ancestry of a rare variant, specifically a variant observed in relatively small count in a large sample. Our results follow from the statistical independence of low-count mutations, which we show to hold for the standard neutral coalescent or diffusion model of population genetics as well as for more general coalescent trees. For populations of constant size, these counts are distributed like the number of alleles in the Ewens sampling formula. We develop a Poisson sampling model for populations of varying size and illustrate it using new results for site-frequency spectra in an exponentially growing population. We apply our model to a large data set of human SNPs and use it to explain dramatic differences in site-frequency spectra across the range of mutation rates in the human genome.

Drones Do Not Drift between Nests in a Wild Population of Apis cerana.

The modes through which individuals disperse prior to reproduction has important consequences for gene flow in populations. In honey bees (Apis sp.), drones (males) reproduce within a short flight range of their natal nest, leaving and returning each afternoon within a narrow mating window. Drones are assumed to return to their natal nests as they depend on workers to feed them. However, in apiaries, drones are reported to regularly make navigation errors and return to a non-natal nest, where they are accepted and fed by unrelated workers. If such a "drone drift" occurred in wild populations, it could facilitate some further degree of dispersal for males, particularly if drones drift into host nests some distance away from their natal nest. Here, we investigated whether drone drift occurs in an invasive population of the Asian honey bee (Apis cerana). Based on the genotypes of 1462 drones from 19 colonies, we found only a single drone that could be considered a candidate drifter (~0.07%). In three other colonies, drones whose genotypes differed from the inferred queen were best explained by recent queen turnover or worker-laying. We concluded that drone drift in this population is low at best, and A. cerana drones either rarely make navigation errors in wild populations or are not accepted into foreign nests when they do so. We therefore confirm that drone dispersal distance is limited to the distance of daily drone flights from natal nests, a key assumption of both colony density estimates based on sampling of drone congregation areas and population genetic models of gene flow in honey bees.

Genome Scan of Rice Landrace Populations Collected Across Time Revealed Climate Changes’ Selective Footprints in the Genes Network Regulating Flowering Time

Analyses of the genetic bases of plant adaptation to climate changes, using genome-scan approaches, are often conducted on natural populations, under hypothesis of out-crossing reproductive regime. We report here on a study based on diachronic sampling (1980 and 2011) of the autogamous crop species, Oryza sativa and Oryza glaberrima, in the tropical forest and the Sudanian savannah of West Africa. First, using historical meteorological data we confirmed changes in temperatures (+ 1 °C on average) and rainfall regime (less predictable and reduced amount) in the target areas. Second, phenotyping the populations for phenology, we observed significantly earlier heading time in the 2010 samples. Third, implementing two genome-scan methods (one of which specially developed for selfing species) on genotyping by sequencing genotypic data of the two populations, we detected 31 independent selection footprints. Gene ontology analysis detected significant enrichment of these selection footprints in genes involved in reproductive processes. Some of them bore known heading time QTLs and genes, including OsGI, Hd1 and OsphyB. This rapid adaptive evolution, originated from subtle changes in the standing variation in genetic network regulating heading time, did not translate into predominance of multilocus genotypes, as it is often the case in selfing plants, and into notable selective sweeps. The high adaptive potential observed results from the multiline genetic structure of the rice landraces, and the rather large and imbricated genetic diversity of the rice meta-population at the farm, the village and the region levels, that hosted the adaptive variants in multiple genetic backgrounds before the advent of the environmental selective pressure. Our results illustrate the evolution of in situ diversity through processes of human and natural selection, and provide a model for rice breeding and cultivars deployment strategies aiming resilience to climate changes. It also calls for further development of population genetic models for adaptation of plant populations to environmental changes. To our best knowledge, this is the first study dealing with climate-changes’ selective footprint in crops.

Evolutionarily stable strategy analysis and its links to demography and genetics through invasion fitness.

Evolutionarily stable strategy (ESS) analysis pioneered by Maynard Smith and Price took off in part because it often does not require explicit assumptions about the genetics and demography of a population in contrast to population genetic models. Though this simplicity is useful, it obscures the degree to which ESS analysis applies to populations with more realistic genetics and demography: for example, how does ESS analysis handle complexities such as kin selection, group selection and variable environments when phenotypes are affected by multiple genes? In this paper, I review the history of the ESS concept and show how early uncertainty about the method lead to important mathematical theory linking ESS analysis to general population genetic models. I use this theory to emphasize the link between ESS analysis and the concept of invasion fitness. I give examples of how invasion fitness can measure kin selection, group selection and the evolution of linked modifier genes in response to variable environments. The ESSs in these examples depend crucially on demographic and genetic parameters, which highlights how ESS analysis will continue to be an important tool in understanding evolutionary patterns as new models address the increasing abundance of genetic and long-term demographic data in natural populations. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

The effectiveness of pseudomagic traits in promoting premating isolation.

Upon the secondary contact of populations, speciation with gene flow is greatly facilitated when the same pleiotropic loci are both subject to divergent ecological selection and induce non-random mating, leading to loci with this fortuitous combination of functions being referred to as 'magic trait' loci. We use a population genetics model to examine whether 'pseudomagic trait' complexes, composed of physically linked loci fulfilling these two functions, are as efficient in promoting premating isolation as magic traits. We specifically measure the evolution of choosiness, which controls the strength of assortative mating. We show that, surprisingly, pseudomagic trait complexes, and to a lesser extent also physically unlinked loci, can lead to the evolution of considerably stronger assortative mating preferences than do magic traits, provided polymorphism at the involved loci is maintained. This is because assortative mating preferences are generally favoured when there is a risk of producing maladapted recombinants, as occurs with non-magic trait complexes but not with magic traits (since pleiotropy precludes recombination). Contrary to current belief, magic traits may not be the most effective genetic architecture for promoting strong premating isolation. Therefore, distinguishing between magic traits and pseudomagic trait complexes is important when inferring their role in premating isolation. This calls for further fine-scale genomic research on speciation genes.

A population genetics theory for piRNA-regulated transposable elements

Transposable elements (TEs) are self-reproducing selfish DNA sequences that can invade the genome of virtually all living species. Population genetics models have shown that TE copy numbers generally reach a limit, either because the transposition rate decreases with the number of copies (transposition regulation) or because TE copies are deleterious, and thus purged by natural selection. Yet, recent empirical discoveries suggest that TE regulation may mostly rely on piRNAs, which require a specific mutational event (the insertion of a TE copy in a piRNA cluster) to be activated — the so-called TE regulation “trap model”. We derived new population genetics models accounting for this trap mechanism, and showed that the resulting equilibria differ substantially from previous expectations based on a transposition–selection equilibrium. We proposed three sub-models, depending on whether or not genomic TE copies and piRNA cluster TE copies are selectively neutral or deleterious, and we provide analytical expressions for maximum and equilibrium copy numbers, as well as cluster frequencies for all of them. In the full neutral model, the equilibrium is achieved when transposition is completely silenced, and this equilibrium does not depend on the transposition rate. When genomic TE copies are deleterious but not cluster TE copies, no long-term equilibrium is possible, and active TEs are eventually eliminated after an active incomplete invasion stage. When all TE copies are deleterious, a transposition–selection equilibrium exists, but the invasion dynamics is not monotonic, and the copy number peaks before decreasing. Mathematical predictions were in good agreement with numerical simulations, except when genetic drift and/or linkage disequilibrium dominates. Overall, the trap-model dynamics appeared to be substantially more stochastic and less repeatable than traditional regulation models.

The evolution of suppressed recombination between sex chromosomes and the lengths of evolutionary strata.

The idea that sex differences in selection drive the evolution of suppressed recombination between sex chromosomes is well developed in population genetics. Yet, despite a now classic body of theory, empirical evidence that sexually antagonistic selection drives the evolution of recombination arrest remains equivocal and alternative hypotheses underdeveloped. Here, we investigate whether the length of "evolutionary strata" formed by chromosomal inversions (or other large-effect recombination modifiers) expanding the non-recombining sex-linked region (SLR) on sex chromosomes can be informative of how selection influenced their fixation. We develop population genetic models to show how the length of an SLR-expanding inversion, and the presence of partially recessive deleterious mutational variation, affect the fixation probability of three different classes of inversions: (1) intrinsically neutral, (2) directly beneficial (i.e., due to breakpoint or positional effects), and (3) those capturing sexually antagonistic (SA) loci. Our models indicate that neutral inversions, and those capturing an SA locus in linkage disequilibrium with the ancestral SLR, will exhibit a strong fixation bias toward small inversions; while unconditionally beneficial inversions, and those capturing a genetically unlinked SA locus, will favor fixation of larger inversions. The footprint of evolutionary stratum size left behind by different selection regimes is strongly influenced by parameters affecting the deleterious mutation load, the physical position of the ancestral SLR, and the distribution of new inversion lengths.

Learning by Population Genetics and Matrix Riccati Equation

A model of learning as a generalization of the Eigen's quasispecies model in population genetics is introduced. Eigen's model is considered as a matrix Riccati equation. The error catastrophe in the Eigen's model (when the purifying selection becomes ineffective) is discussed as the divergence of the Perron-Frobenius eigenvalue of the Riccati model in the limit of large matrices. A known estimate for the Perron-Frobenius eigenvalue provides an explanation for observed patterns of genomic evolution. We propose to consider the error catastrophe in Eigen's model as an analog of overfitting in learning theory; this gives a criterion for the presence of overfitting in learning.

A simulation-based approach to evaluating population structure in non-equilibrial populations

The standard null model of panmixia used to test for population subdivision is based on a set of assumptions that can be violated given recent events likely to result in non-equilibrial genetic composition coupled with the complex life histories of many species. Bowhead whales (Balaena mysticetus) represent such a species. Bowhead whales also have a well-documented history of severe commercial harvest in the recent past which would be expected to leave a population out of genetic equilibrium. They also have a very long life span, overlapping generations, and age and sex-structured migrations. In addition, samples come from whales killed in a hunt known to be non-random with respect to size at different whaling villages. Sampling of such a population could lead to erroneous conclusions regarding population structure, which could have real consequences for aboriginal whaling. To better interpret the results of standard population genetic analyses, an individual-based model of bowhead whale population dynamics and genetics was created using the R package rmetasim. The model re-created as closely as possible all aspects of the demography, genetics, and whaling history of bowhead whales. Simulated datasets were generated by sampling from the simulated population in a way that matched the age, sex and geographic distribution of empirically collected samples. The empirical bowhead datasets were compared to null distributions generated from the simulated datasets for a variety of genetic analyses. The analysis indicates that the empirical genetic data sampled from the Bering-ChukchiBeaufort (BCB) stock of bowhead whales are more consistent with the model of a population with the same whaling history and demographic composition as BCB whales than they are with a single, randomly-mating population in genetic equilibrium under a standard Wright-Fisher model. Additionally, it was demonstrated that by failing to account for the unique features of the population dynamics of the species, standard tests of genetic differentiation based on panmixia may produce misleading results. The approach outlined will likely prove useful for evaluating population structure in other species likely to be out of equilibrium.

The effect of mutation subtypes on the allele frequency spectrum and population genetics inference.

Population genetics has adapted as technological advances in next-generation sequencing have resulted in an exponential increase of genetic data. A common approach to efficiently analyze genetic variation present in large sequencing data is through the allele frequency spectrum, defined as the distribution of allele frequencies in a sample. While the frequency spectrum serves to summarize patterns of genetic variation, it implicitly assumes mutation types (A→C vs C→T) as interchangeable. However, mutations of different types arise and spread due to spatial and temporal variation in forces such as mutation rate and biased gene conversion that result in heterogeneity in the distribution of allele frequencies across sites. In this work, we explore the impact of this simplification on multiple aspects of population genetic modeling. As a site's mutation rate is strongly affected by flanking nucleotides, we defined a mutation subtype by the base pair change and adjacent nucleotides (e.g. AAA→ATA) and systematically assessed the heterogeneity in the frequency spectrum across 96 distinct 3-mer mutation subtypes using n = 3556 whole-genome sequenced individuals of European ancestry. We observed substantial variation across the subtype-specific frequency spectra, with some of the variation being influenced by molecular factors previously identified for single base mutation types. Estimates of model parameters from demographic inference performed for each mutation subtype's AFS individually varied drastically across the 96 subtypes. In local patterns of variation, a combination of regional subtype composition and local genomic factors shaped the regional frequency spectrum across genomic regions. Our results illustrate how treating variants in large sequencing samples as interchangeable may confound population genetic frameworks and encourages us to consider the unique evolutionary mechanisms of analyzed polymorphisms.

The Fisher process of sexual selection with the coevolution of preference strength.

Sexual selection has a rich history of mathematical models that consider why preferences favor one trait phenotype over another (for population genetic models) or what specific trait value is preferred (for quantitative genetic models). Less common is exploration of the evolution of choosiness or preference strength: i.e., by how much a trait is preferred. We examine both population and quantitative genetic models of the evolution of preferences, specifically developing "baseline models" of the evolution of preference strength during the Fisher process. Using a population genetic approach, we find selection for stronger and stronger preferences when trait variation is maintained by mutation. However, this force is quite weak and likely to be swamped by drift in moderately-sized populations. In a quantitative genetic model, unimodal preferences will generally not evolve to be increasingly strong without bounds when male traits are under stabilizing viability selection, but evolve to extreme values when viability selection is directional. Our results highlight that different shapes of fitness and preference functions lead to qualitatively different trajectories for preference strength evolution ranging from no evolution to extreme evolution of preference strength.

Conformity and anti-conformity in a finite population

Conformist and anti-conformist cultural transmission have been studied both empirically, in several species, and theoretically, with population genetic models. Building upon standard, infinite-population models (IPMs) of conformity, we introduce finite-population models (FPMs) and study them via simulation and a diffusion approximation. In previous IPMs of conformity, offspring observe the variants of n adult role models, where n is often three. Numerical simulations show that while the short-term behavior of the FPM with n=3 role models is well approximated by the IPM, stable polymorphic equilibria of the IPM become effective equilibria of the FPM at which the variation persists prior to fixation or loss, and which produce plateaus in curves for fixation probabilities and expected times to absorption. In the FPM with n=5 role models, the population may switch between two effective equilibria, which is not possible in the IPM, or may cycle between frequencies that are not effective equilibria, which is possible in the IPM. In all observed cases of ‘equilibrium switching’ and ‘cycling’ in the FPM, model parameters exceed O(1/N), required for the diffusion approximation, resulting in an over-estimation of the actual times to absorption. However, in those cases with n=5 role models that have one effective equilibrium and stable fixation states, even if conformity coefficients exceed O(1/N), the diffusion approximation matches closely the numerical simulations of the FPM. This suggests that the robustness of the diffusion approximation depends not only on the magnitudes of coefficients, but also on the qualitative behavior of the conformity model.

Strong, Recent Selective Sweeps Reshape Genetic Diversity in Freshwater Bivalve Megalonaias nervosa.

Freshwater Unionid bivalves have recently faced ecological upheaval through pollution, barriers to dispersal, harvesting, and changes in fish-host prevalence. Currently, over 70% of species in North America are threatened, endangered or extinct. To characterize the genetic response to recent selective pressures, we collected population genetic data for one successful bivalve species, Megalonaias nervosa. We identify megabase-sized regions that are nearly monomorphic across the population, signals of strong, recent selection reshaping diversity across 73 Mb total. These signatures of selection are greater than is commonly seen in population genetic models. We observe 102 duplicate genes with high dN/dS on terminal branches among regions with sweeps, suggesting that gene duplication is a causative mechanism of recent adaptation in M. nervosa. Genes in sweeps reflect functional classes important for Unionid survival, including anticoagulation genes important for fish host parasitization, detox genes, mitochondria management, and shell formation. We identify sweeps in regions with no known functional impacts, suggesting mechanisms of adaptation that deserve greater attention in future work on species survival. In contrast, polymorphic transposable elements (TEs) appear to be detrimental and underrepresented among regions with sweeps. TE site frequency spectra are skewed toward singleton variants, and TEs among regions with sweeps are present at low frequency. Our work suggests that duplicate genes are an essential source of genetic novelty that has helped this species succeed in environments where others have struggled. These results suggest that gene duplications deserve greater attention in non-model population genomics, especially in species that have recently faced sudden environmental challenges.