Population Genetic Framework Research Articles

Autosomal suppression of sex-ratio meiotic drive influences the dynamics of X and Y chromosome coevolution.

Sex-ratio meiotic drivers are selfish genes or gene complexes that bias the transmission of sex chromosomes resulting in skewed sex ratios. Existing theoretical models have suggested the maintenance of a four-chromosome equilibrium (with driving and standard X and suppressing and susceptible Y) in a cyclic dynamic, studies of natural populations have failed to capture this pattern. Although there are several plausible explanations for this lack of cycling, interference from autosomal suppressors has not been studied using a theoretical population genetic framework even though autosomal suppressors and Y-linked suppressors coexist in natural populations of some species. In this study, we use a simulation-based approach to investigate the influence of autosomal suppressors on the cycling of sex chromosomes. Our findings demonstrate that the presence of an autosomal suppressor can hinder the invasion of a Y-linked suppressor under some parameter space, thereby impeding the cyclic dynamics, or even the invasion of Y-linked suppression. Even when a Y-linked suppressor invades, the presence of an autosomal suppressor can prevent cycling. Our study demonstrates the potential role of autosomal suppressors in preventing sex chromosome cycling and provides insights into the conditions and consequences of maintaining both Y-linked and autosomal suppressors.

On the evolutionary origin of discrete phenotypic plasticity.

Phenotypic plasticity provides an attractive strategy for adapting to various environments, but the evolutionary mechanism of the underlying genetic system is poorly understood. We use a simple gene regulatory network model to explore how a species acquires phenotypic plasticity, particularly focusing on discrete phenotypic plasticity, which has been difficult to explain by quantitative genetic models. Our approach employs a population genetic framework that integrates the developmental process, where each individual undergoes growth to develop its phenotype, which subsequently becomes subject to selection pressures. Our model considers two alternative types of environments, with the gene regulatory network including a sensor gene that turns on and off depending on the type of environment. With this assumption, we demonstrate that the system gradually adapts by acquiring the ability to produce two distinct optimum phenotypes under two types of environments without changing genotype, resulting in phenotypic plasticity. We find that the resulting plasticity is often discrete after a lengthy period of evolution. Our results suggest that gene regulatory networks have a notable capacity to flexibly produce various phenotypes in response to environmental changes. This study also shows that the evolutionary dynamics of phenotype may differ significantly between mechanistic-based developmental models and quantitative genetics models, suggesting the utility of incorporating gene regulatory networks into evolutionary models.

Conservation genetics of the endangered California Freshwater Shrimp (Syncaris pacifica): watershed and stream networks define gene pool boundaries

Understanding genetic structure and diversity among remnant populations of rare species can inform conservation and recovery actions. We used a population genetic framework to spatially delineate gene pools and estimate gene flow and effective population sizes for the endangered California Freshwater Shrimp Syncaris pacifica. Tissues of 101 individuals were collected from 11 sites in 5 watersheds, using non-lethal tissue sampling. Single Nucleotide Polymorphism markers were developed de novo using ddRAD-seq methods, resulting in 433 unlinked loci scored with high confidence and low missing data. We found evidence for strong genetic structure across the species range. Two hierarchical levels of significant differentiation were observed: (i) five clusters (regional gene pools, FST = 0.38–0.75) isolated by low gene flow were associated with watershed limits and (ii) modest local structure among tributaries within a watershed that are not connected through direct downstream flow (local gene pools, FST = 0.06–0.10). Sampling sites connected with direct upstream-to-downstream water flow were not differentiated. Our analyses suggest that regional watersheds are isolated from one another, with very limited (possibly no) gene flow over recent generations. This isolation is paired with small effective population sizes across regional gene pools (Ne = 62.4–147.1). Genetic diversity was variable across sites and watersheds (He = 0.09–0.22). Those with the highest diversity may have been refugia and are now potential sources of genetic diversity for other populations. These findings highlight which portions of the species range may be most vulnerable to future habitat fragmentation and provide management consideration for maintaining local effective population sizes and genetic connectivity.

АНАЛИЗ УСТОЙЧИВОСТИ В МОДЕЛИРОВАНИИ ЭВОЛЮЦИОННЫХ ПРОЦЕССОВ

The paper considers mathematical models of the evolution of new biological species from a common ancestor, depending on the adaptability to the environment in the presence of a particular trait in the genotype. Equations describing the change in the number of individuals with dominant and recessive traits, taking into account their fertility, are presented. The calculation of the time for which the population of the species consumes vital environmental resources has also been made. Within the framework of this model, the growth rate of the population in conditions of a shortage of a food source is investigated. A mathematical model of the population growth of the species, the limits of applicability and methods of its continuation using equations describing the factor of population decline due to sudden changes in the environment are presented and described. The article presents criteria for the applicability of critical points of one mathematical model as initial conditions for another. The results of the calculations can be used in the framework of population genetics, as well as for environmental studies. On their basis, it is possible to make assumptions about the possibility of further evolutionary development of a biological species.

Fitness Effects of Phenotypic Mutations at Proteome-Scale Reveal Optimality of Translation Machinery.

Errors in protein translation can lead to non-genetic, phenotypic mutations, including amino acid misincorporations. While phenotypic mutations can increase protein diversity, the systematic characterization of their proteome-wide frequencies and their evolutionary impact has been lacking. Here, we developed a mechanistic model of translation errors to investigate how selection acts on protein populations produced by amino acid misincorporations. We fitted the model to empirical observations of misincorporations obtained from over a hundred mass spectrometry datasets of E. coli and S. cerevisiae. We found that on average 20% to 23% of proteins synthesized in the cell are expected to harbor at least one amino acid misincorporation, and that deleterious misincorporations are less likely to occur. Combining misincorporation probabilities and the estimated fitness effects of amino acid substitutions in a population genetics framework, we found 74% of mistranslation events in E. coli and 94% in S. cerevisiae to be neutral. We further show that the set of available synonymous tRNAs is subject to evolutionary pressure, as the presence of missing tRNAs would increase codon-anticodon cross-reactivity and misincorporation error rates. Overall, we find that the translation machinery is likely optimal in E. coli and S. cerevisiae and that both local solutions at the level of codons and a global solution such as the tRNA pool can mitigate the impact of translation errors. We provide a framework to study the evolutionary impact of codon-specific translation errors and a method for their proteome-wide detection across organisms and conditions.

Highland islands: assessing gene flow among populations of an aquatic highland endemic

Abstract A variety of hierarchical gene flow models have been proposed to explain the distribution of genetic variation in aquatic environments. These models, including the Stream Hierarchy (SH), Death Valley (DV), Headwater (HW), and Widespread Gene flow (WG) models, provide testable hypotheses that focus on the degree of within-basin or within-stream network connectivity and an organism’s dispersal abilities. We tested these models using Tlaloc hildebrandi (Profundulidae, Cyprinodontiformes), a freshwater fish endemic to the highlands of the Grijalva and Usumacinta River basins in southern Mexico. Data from ultraconserved elements (UCEs) showed that although T. hildebrandi was recovered as monophyletic, the sub-basins were not. We generated single nucleotide polymorphisms from the UCEs to analyse the data in a population genetic framework. These results differed between analyses such that two (STRUCTURE analysis) or three (DAPC analysis) genetic groupings were recovered. Overall, the results of this study provide support for the SH model. Some individuals from the Jataté sub-basin, however, conformed to the HW model, due to historical connections among headwater streams and rivers of the Jataté and Amarillo–Chenalhó clades/clusters. The greatest degree of gene flow has occurred from the Grijlava to the Usumacinta basins, two geographically proximate basins that have been hypothesized to have had previous connections.

Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life.

How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing.

Mitochondrial sequence data reveal population structure within Pustulosa pustulosa.

Unionid mussels are among the most imperiled group of organisms in North America, and Pustulosa pustulosa is a freshwater species with a relatively wide latitudinal distribution that extends from southern Ontario, Canada, to Texas, USA. Considerable morphological and geographic variation in the genus Pustulosa (formerly Cyclonaias) has led to uncertainty over species boundaries, and recent studies have suggested revisions to species-level classifications by synonymizing C. aurea, C. houstonensis, C. mortoni, and C. refulgens with C. pustulosa (currently P. pustulosa). Owing to its wide range and shallow phylogenetic differentiation, we analyzed individuals of P. pustulosa using mitochondrial DNA sequence data under a population genetics framework. We included 496 individuals, which were comprised of 166 samples collected during this study and 330 additional sequences retrieved from GenBank. Pairwise ΦST measures based on ND1 data suggested there may be up to five major geographic groups present within P. pustulosa. Genetic differentiation between regions within Texas was higher compared to populations from the Mississippi and Great Lakes populations, which may reflect differences in historical connectivity. Mitochondrial sequence data also revealed varying demographic histories for each major group suggesting each geographic region has also experienced differential population dynamics in the past. Future surveys should consider exploring variation within species after phylogeographic delimitation has been performed. In this study, we begin to address this need for freshwater mussels via the P. pustulosa system.

Opisthorchis viverrini Life Cycle, Distribution, Systematics, and Population Genetics.

Opisthorchis viverrini plays a key role as the carcinogenic liver fluke causing bile duct cancer in Southeast Asia. A comprehensive understanding of its life cycle, distribution, systematics, and population genetics is critically important as they underpin the effective development and establishment of future prevention and control programs that center on opisthorchiasis and cholangiocarcinoma. This chapter provides detailed information concerning the basic biology and updated information of O. viverrini related to its host life cycle, transmission route via raw, partially cooked or fermented freshwater cyprinid fish, endemic areas, and the discovery of new foci. Previous sequential studies over the last two decades on the phylogenetic and systematic relationships, genetic variation, and population genetics of O. viverrini as well as its snail intermediate host Bithynia spp. are presented and discussed, which have led to the currently known complex species level systematics and population genetics framework of this host-parasite system. Additionally, further directions for comprehensive research are suggested to provide a more complete understanding of liver fluke, O. viverrini-related cholangiocarcinoma.

Utilizing a Population-Genetic Framework to Test for Gene-Environment Interactions between Zebrafish Behavior and Chemical Exposure.

Individuals within genetically diverse populations display broad susceptibility differences upon chemical exposures. Understanding the role of gene-environment interactions (GxE) in differential susceptibility to an expanding exposome is key to protecting public health. However, a chemical's potential to elicit GxE is often not considered during risk assessment. Previously, we've leveraged high-throughput zebrafish (Danio rerio) morphology screening data to reveal patterns of potential GxE effects. Here, using a population genetics framework, we apportioned variation in larval behavior and gene expression in three different PFHxA environments via mixed-effect modeling to assess significance of GxE term. We estimated the intraclass correlation (ICC) between full siblings from different families using one-way random-effects model. We found a significant GxE effect upon PFHxA exposure in larval behavior, and the ICC of behavioral responses in the PFHxA exposed population at the lower concentration was 43.7%, while that of the control population was 14.6%. Considering global gene expression data, a total of 3746 genes showed statistically significant GxE. By showing evidence that heritable genetics are directly affecting gene expression and behavioral susceptibility of individuals to PFHxA exposure, we demonstrate how standing genetic variation in a heterogeneous population such as ours can be leveraged to test for potential GxE.

High-throughput RNA sequencing and genetic structure studies of turnip mosaic virus infecting black and yellow mustard revealing emergence of world-B3 pathotype in India.

To study the evolution and host expansion of a TuMV for the first time in India using molecular population genetic framework. Here, we decipher the complete genome sequences of two TuMV world-B3 strains infecting yellow and black mustard in India through high-throughput RNA sequencing subjecting ribosomal RNA depleted mRNA isolated from leaves exhibiting puckering and mosaic symptoms with 100% incidence and high severity in the experimental field. The viral genomes of the two isolates were 9817 and 9829 nucleotides long. They featured two open reading frames (ORFs), one of which encoded a polyprotein comprised of 3164 amino acids and the other of which encoded a PIPO protein of 62 amino acids. The two TuMV strains from New Delhi region shared identity with the world-B pathotype and subpathotype world B3 showcasing its emergence first time in South Asia. In contrast, other isolates reported previously from South Asia were all Asian-BR pathotypes. According to our knowledge, this is the first instance of TuMV association with black mustard naturally. Their geographical prevalence justifies a lower degree of genetic differentiation and higher rate of gene flow calculated between the world-B and Asian-BR pathotypes. This study provides insights on population structuring, expansions and evolution, level of genetic heterogeneity and variability of worldwide prevalent isolates of TuMV which will further aid in understanding virus epidemiology and help prevent losses.

Improving sustainable crop protection using population genetics concepts.

Growing genetically resistant plants allows pathogen populations to be controlled and reduces the use of pesticides. However, pathogens can quickly overcome such resistance. In this context, how can we achieve sustainable crop protection? This crucial question has remained largely unanswered despite decades of intense debate and research effort. In this study, we used a bibliographic analysis to show that the research field of resistance durability has evolved into three subfields: (1) "plant breeding" (generating new genetic material), (2) "molecular interactions" (exploring the molecular dialogue governing plant-pathogen interactions) and (3) "epidemiology and evolution" (explaining and forecasting of pathogen population dynamics resulting from selection pressure[s] exerted by resistant plants). We argue that this triple split of the field impedes integrated research progress and ultimately compromises the sustainable management of genetic resistance. After identifying a gap among the three subfields, we argue that the theoretical framework of population genetics could bridge this gap. Indeed, population genetics formally explains the evolution of all heritable traits, and allows genetic changes to be tracked along with variation in population dynamics. This provides an integrated view of pathogen adaptation, in particular via evolutionary-epidemiological feedbacks. In this Opinion Note, we detail examples illustrating how such a framework can better inform best practices for developing and managing genetically resistant cultivars.

Emergent evolutionary forces in spatial models of luminal growth and their application to the human gut microbiota

The genetic composition of the gut microbiota is constantly reshaped by ecological and evolutionary forces. These strain-level dynamics are challenging to understand because they depend on complex spatial growth processes that take place within a host. Here we introduce a population genetic framework to predict how stochastic evolutionary forces emerge from simple models of microbial growth in spatially extended environments like the intestinal lumen. Our framework shows how fluid flow and longitudinal variation in growth rate combine to shape the frequencies of genetic variants in simulated fecal samples, yielding analytical expressions for the effective generation times, selection coefficients, and rates of genetic drift. We find that over longer timescales, the emergent evolutionary dynamics can often be captured by well-mixed models that lack explicit spatial structure, even when there is substantial spatial variation in species-level composition. By applying these results to the human colon, we find that continuous fluid flow and simple forms of wall growth alone are unlikely to create sufficient bottlenecks to allow large fluctuations in mutant frequencies within a host. We also find that the effective generation times may be significantly shorter than expected from traditional average growth rate estimates. Our results provide a starting point for quantifying genetic turnover in spatially extended settings like the gut microbiota and may be relevant for other microbial ecosystems where unidirectional fluid flow plays an important role.

Inversion invasions: when the genetic basis of local adaptation is concentrated within inversions in the face of gene flow.

Across many species where inversions have been implicated in local adaptation, genomes often evolve to contain multiple, large inversions that arise early in divergence. Why this occurs has yet to be resolved. To address this gap, we built forward-time simulations in which inversions have flexible characteristics and can invade a metapopulation undergoing spatially divergent selection for a highly polygenic trait. In our simulations, inversions typically arose early in divergence, captured standing genetic variation upon mutation, and then accumulated many small-effect loci over time. Under special conditions, inversions could also arise late in adaptation and capture locally adapted alleles. Polygenic inversions behaved similarly to a single supergene of large effect and were detectable by genome scans. Our results show that characteristics of adaptive inversions found in empirical studies (e.g. multiple large, old inversions that are FST outliers, sometimes overlapping with other inversions) are consistent with a highly polygenic architecture, and inversions do not need to contain any large-effect genes to play an important role in local adaptation. By combining a population and quantitative genetic framework, our results give a deeper understanding of the specific conditions needed for inversions to be involved in adaptation when the genetic architecture is polygenic. This article is part of the theme issue 'Genomic architecture of supergenes: causes and evolutionary consequences'.

Genetic variation of putative myokine signaling is dominated by biological sex and sex hormones.

Skeletal muscle plays an integral role in coordinating physiological homeostasis, where signaling to other tissues via myokines allows for coordination of complex processes. Here, we aimed to leverage natural genetic correlation structure of gene expression both within and across tissues to understand how muscle interacts with metabolic tissues. Specifically, we performed a survey of genetic correlations focused on myokine gene regulation, muscle cell composition, cross-tissue signaling, and interactions with genetic sex in humans. While expression levels of a majority of myokines and cell proportions within skeletal muscle showed little relative differences between males and females, nearly all significant cross-tissue enrichments operated in a sex-specific or hormone-dependent fashion; in particular, with estradiol. These sex- and hormone-specific effects were consistent across key metabolic tissues: liver, pancreas, hypothalamus, intestine, heart, visceral, and subcutaneous adipose tissue. To characterize the role of estradiol receptor signaling on myokine expression, we generated male and female mice which lack estrogen receptor α specifically in skeletal muscle (MERKO) and integrated with human data. These analyses highlighted potential mechanisms of sex-dependent myokine signaling conserved between species, such as myostatin enriched for divergent substrate utilization pathways between sexes. Several other putative sex-dependent mechanisms of myokine signaling were uncovered, such as muscle-derived tumor necrosis factor alpha (TNFA) enriched for stronger inflammatory signaling in females compared to males and GPX3 as a male-specific link between glycolytic fiber abundance and hepatic inflammation. Collectively, we provide a population genetics framework for inferring muscle signaling to metabolic tissues in humans. We further highlight sex and estradiol receptor signaling as critical variables when assaying myokine functions and how changes in cell composition are predicted to impact other metabolic organs.

Does a complex life cycle affect adaptation to environmental change? Genome-informed insights for characterizing selection across complex life cycle.

Complex life cycles, in which discrete life stages of the same organism differ in form or function and often occupy different ecological niches, are common in nature. Because stages share the same genome, selective effects on one stage may have cascading consequences through the entire life cycle. Theoretical and empirical studies have not yet generated clear predictions about how life cycle complexity will influence patterns of adaptation in response to rapidly changing environments or tested theoretical predictions for fitness trade-offs (or lack thereof) across life stages. We discuss complex life cycle evolution and outline three hypotheses—ontogenetic decoupling, antagonistic ontogenetic pleiotropy and synergistic ontogenetic pleiotropy—for how selection may operate on organisms with complex life cycles. We suggest a within-generation experimental design that promises significant insight into composite selection across life cycle stages. As part of this design, we conducted simulations to determine the power needed to detect selection across a life cycle using a population genetic framework. This analysis demonstrated that recently published studies reporting within-generation selection were underpowered to detect small allele frequency changes (approx. 0.1). The power analysis indicates challenging but attainable sampling requirements for many systems, though plants and marine invertebrates with high fecundity are excellent systems for exploring how organisms with complex life cycles may adapt to climate change.

Positive selection on mitochondria may eliminate heritable microbes from arthropod populations.

Diverse eukaryotic taxa carry facultative heritable symbionts, microbes that are passed from mother to offspring. These symbionts are coinherited with mitochondria, and selection favouring either new symbionts, or new symbiont variants, is known to drive loss of mitochondrial diversity as a correlated response. More recently, evidence has accumulated of episodic directional selection on mitochondria, but with currently unknown consequences for symbiont evolution. We therefore employed a population genetic mean field framework to model the impact of selection on mitochondrial DNA (mtDNA) upon symbiont frequency for three generic scenarios of host–symbiont interaction. Our models predict that direct selection on mtDNA can drive symbionts out of the population where a positively selected mtDNA mutation occurs initially in an individual that is uninfected with the symbiont, and the symbiont is initially at low frequency. When, by contrast, the positively selected mtDNA mutation occurs in a symbiont-infected individual, the mutation becomes fixed and in doing so removes symbiont variation from the population. We conclude that the molecular evolution of symbionts and mitochondria, which has previously been viewed from a perspective of selection on symbionts driving the evolution of a neutral mtDNA marker, should be reappraised in the light of positive selection on mtDNA.

Ancient Introgression Between Distantly Related White Oaks (Quercus sect. Quercus) Shows Evidence of Climate-Associated Asymmetric Gene Exchange.

Ancient introgression can be an important source of genetic variation that shapes the evolution and diversification of many taxa. Here, we estimate the timing, direction, and extent of gene flow between two distantly related oak species in the same section (Quercus sect. Quercus). We estimated these demographic events using genotyping by sequencing data, which generated 25 702 single nucleotide polymorphisms for 24 individuals of California scrub oak (Quercus berberidifolia) and 23 individuals of Engelmann oak (Quercus engelmannii). We tested several scenarios involving gene flow between these species using the diffusion approximation-based population genetic inference framework and model-testing approach of the Python package DaDi. We found that the most likely demographic scenario includes a bottleneck in Q. engelmannii that coincides with asymmetric gene flow from Q. berberidifolia into Q. engelmannii. Given that the timing of this gene flow coincides with the advent of a Mediterranean-type climate in the California Floristic Province, we propose that changing precipitation patterns and seasonality may have favored the introgression of climate-associated genes from the endemic into the non-endemic California oak.

Extreme value theory as a framework for understanding mutation frequency distribution in cancer genomes.

Currently, the population dynamics of preclonal cancer cells before clonal expansion of tumors has not been sufficiently addressed thus far. By focusing on preclonal cancer cell population as a Darwinian evolutionary system, we formulated and analyzed the observed mutation frequency among tumors (MFaT) as a proxy for the hypothesized sequence read frequency and beneficial fitness effect of a cancer driver mutation. Analogous to intestinal crypts, we assumed that sample donor patients are separate culture tanks where proliferating cells follow certain population dynamics described by extreme value theory (EVT). To validate this, we analyzed three large-scale cancer genome datasets, each harboring > 10000 tumor samples and in total involving > 177898 observed mutation sites. We clarified the necessary premises for the application of EVT in the strong selection and weak mutation (SSWM) regime in relation to cancer genome sequences at scale. We also confirmed that the stochastic distribution of MFaT is likely of the Fréchet type, which challenges the well-known Gumbel hypothesis of beneficial fitness effects. Based on statistical data analysis, we demonstrated the potential of EVT as a population genetics framework to understand and explain the stochastic behavior of driver-mutation frequency in cancer genomes as well as its applicability in real cancer genome sequence data.

Strongly deleterious mutations are a primary determinant of extinction risk due to inbreeding depression.

Human‐driven habitat fragmentation and loss have led to a proliferation of small and isolated plant and animal populations with high risk of extinction. One of the main threats to extinction in these populations is inbreeding depression, which is primarily caused by recessive deleterious mutations becoming homozygous due to inbreeding. The typical approach for managing these populations is to maintain high genetic diversity, increasingly by translocating individuals from large populations to initiate a “genetic rescue.” However, the limitations of this approach have recently been highlighted by the demise of the gray wolf population on Isle Royale, which declined to the brink of extinction soon after the arrival of a migrant from the large mainland wolf population. Here, we use a novel population genetic simulation framework to investigate the role of genetic diversity, deleterious variation, and demographic history in mediating extinction risk due to inbreeding depression in small populations. We show that, under realistic models of dominance, large populations harbor high levels of recessive strongly deleterious variation due to these mutations being hidden from selection in the heterozygous state. As a result, when large populations contract, they experience a substantially elevated risk of extinction after these strongly deleterious mutations are exposed by inbreeding. Moreover, we demonstrate that, although genetic rescue is broadly effective as a means to reduce extinction risk, its effectiveness can be greatly increased by drawing migrants from small or moderate‐sized source populations rather than large source populations due to smaller populations harboring lower levels of recessive strongly deleterious variation. Our findings challenge the traditional conservation paradigm that focuses on maximizing genetic diversity in small populations in favor of a view that emphasizes minimizing strongly deleterious variation. These insights have important implications for managing small and isolated populations in the increasingly fragmented landscape of the Anthropocene.