Inferences about the distribution of dominance drawn from yeast gene knockout data

Genomic and fitness consequences of a near-extinction event in the northern elephant seal

Understanding the genetic and fitness consequences of anthropogenic bottlenecks is crucial for biodiversity conservation. However, studies of bottlenecked populations combining genomic approaches with fitness data are rare. Theory predicts that severe bottlenecks deplete genetic diversity, exacerbate inbreeding depression and decrease population viability. However, actual outcomes are complex and depend on how a species' unique demography affects its genetic load. We used population genetic and veterinary pathology data, demographic modelling, whole-genome resequencing and forward genetic simulations to investigate the genomic and fitness consequences of a near-extinction event in the northern elephant seal. We found no evidence of inbreeding depression within the contemporary population for key fitness components, including body mass, blubber thickness and susceptibility to parasites and disease. However, we detected a genomic signature of a recent extreme bottleneck (effective population size = 6; 95% confidence interval = 5.0-7.5) that will have purged much of the genetic load, potentially leading to the lack of observed inbreeding depression in our study. Our results further suggest that deleterious genetic variation strongly impacted the post-bottleneck population dynamics of the northern elephant seal. Our study provides comprehensive empirical insights into the intricate dynamics underlying species-specific responses to anthropogenic bottlenecks.

Hill-Robertson interference may bias the inference of fitness effects of new mutations in highly selfing species

The accurate estimation of the distribution of fitness effects (DFE) of new mutations is critical for population genetic inference but remains a challenging task. While various methods have been developed for DFE inference using the site frequency spectrum of putatively neutral and selected sites, their applicability in species with diverse life history traits and complex demographic scenarios is not well understood. Selfing is common among eukaryotic species and can lead to decreased effective recombination rates, increasing the effects of selection at linked sites, including interference between selected alleles. We employ forward simulations to investigate the limitations of current DFE estimation approaches in the presence of selfing and other model violations, such as linkage, departures from semidominance, population structure, and uneven sampling. We find that distortions of the site frequency spectrum due to Hill-Robertson interference in highly selfing populations lead to mis-inference of the deleterious DFE of new mutations. Specifically, when inferring the distribution of selection coefficients, there is an overestimation of nearly neutral and strongly deleterious mutations and an underestimation of mildly deleterious mutations when interference between selected alleles is pervasive. In addition, the presence of cryptic population structure with low rates of migration and uneven sampling across subpopulations leads to the false inference of a deleterious DFE skewed towards effectively neutral/mildly deleterious mutations. Finally, the proportion of adaptive substitutions estimated at high rates of selfing is substantially overestimated. Our observations apply broadly to species and genomic regions with little/no recombination and where interference might be pervasive.

Whole-Genome Analyses Reveal the Distinct Taxonomic Status of the Hainan Population of Endangered Rucervus eldii and Its Conservation Implications

Eld's deer Rucervus eldii (McClelland, 1842) is an ungulate that lives in tropical lowland forests in several countries of Indochina and Hainan Island of China. Its remaining population is small and scattered, and the species is listed as an Endangered species on the IUCN Red List. The debate over the taxonomic status of the Hainan population has persisted for over a century-as an island-endemic subspecies R. e. hainanus, or an insular population of the subspecies R. e. siamensis, would have significant conservation implications. And, given the Hainan population had experienced both population bottleneck and multiple translocations in the past, conservation genomics would be a powerful tool to evaluate the genetic impacts of these events. In this study, we used conservation genomics assessment to study population differentiation and genetic diversity of R. e. siamensis in Cambodia and three Eld's deer subpopulations on Hainan Island. Based on the unique genetic profile and demographic analysis, this study corroborated previous studies using genetic markers that the Hainan Eld's deer warrants the taxonomic status of a distinct subspecies. The Hainan population exhibits a reduction in genetic diversity and an increase in the level of inbreeding when compared to the population of Cambodia. The signs of purifying selection were found against homozygous loss-of-function mutations to decrease the deleterious burden in the Hainan population. However, there was an accumulation of more deleterious missense mutations. Furthermore, significant differences in genetic diversity and level of inbreeding found among the three Hainan subpopulations indicated population isolation and suboptimal translocation strategies, which calls for urgent, coordinated, and science-based genetic management to ensure the long-term viability of the endemic subspecies hainanus. This study provides guidance for the conservation and management of Eld's deer.

The limit to evolutionary rescue depends on ploidy in yeast exposed to nystatin

The number of copies of each chromosome, or ploidy, of an organism is a major genomic factor affecting adaptation. We set out to determine how ploidy can impact the outcome of evolution, as well as the likelihood of evolutionary rescue, using short-term experiments with yeast (Saccharomyces cerevisiae) in a high concentration of the fungicide nystatin. In similar experiments using haploid yeast, the genetic changes underlying evolutionary rescue were highly repeatable, with all rescued lines containing a single mutation in the ergosterol biosynthetic pathway. All of these beneficial mutations were recessive, which led to the expectation that diploids would find alternative genetic routes to adaptation. To test this, we repeated the experiment using both haploid and diploid strains and found that diploid populations did not evolve resistance. Although diploids are able to adapt at the same rate as haploids to a lower, not fully inhibitory, concentration of nystatin, the present study suggests that diploids are limited in their ability to adapt to an inhibitory concentration of nystatin, while haploids may undergo evolutionary rescue. These results demonstrate that ploidy can tip the balance between adaptation and extinction when organisms face an extreme environmental change.

Constraining models of dominance for nonsynonymous mutations in the human genome

Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h = 0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.

Revisiting Dominance in Population Genetics

Dominance refers to the effect of a heterozygous genotype relative to that of the two homozygous genotypes. The degree of dominance of mutations for fitness can have a profound impact on how deleterious and beneficial mutations change in frequency over time as well as on the patterns of linked neutral genetic variation surrounding such selected alleles. Since dominance is such a fundamental concept, it has received immense attention throughout the history of population genetics. Early work from Fisher, Wright, and Haldane focused on understanding the conceptual basis for why dominance exists. More recent work has attempted to test these theories and conceptual models by estimating dominance effects of mutations. However, estimating dominance coefficients has been notoriously challenging and has only been done in a few species in a limited number of studies. In this review, we first describe some of the early theoretical and conceptual models for understanding the mechanisms for the existence of dominance. Second, we discuss several approaches used to estimate dominance coefficients and summarize estimates of dominance coefficients. We note trends that have been observed across species, types of mutations, and functional categories of genes. By comparing estimates of dominance coefficients for different types of genes, we test several hypotheses for the existence of dominance. Lastly, we discuss how dominance influences the dynamics of beneficial and deleterious mutations in populations and how the degree of dominance of deleterious mutations influences the impact of inbreeding on fitness.

Consequences of partially recessive deleterious genetic variation for the evolution of inversions suppressing recombination between sex chromosomes1

The evolution of suppressed recombination between sex chromosomes is widely hypothesized to be driven by sexually antagonistic selection (SA), where tighter linkage between the sex-determining gene(s) and nearby SA loci is favored when it couples male-beneficial alleles to the proto-Y chromosome, and female-beneficial alleles to the proto-X. Although difficult to test empirically, the SA selection hypothesis overshadows several alternatives, including an incomplete but often-repeated "sheltering" hypothesis which suggests that expansion of the sex-linked region (SLR) reduces the homozygous expression of deleterious mutations at selected loci. Here, we use population genetic models to evaluate the consequences of partially recessive deleterious mutational variation for the evolution of otherwise neutral chromosomal inversions expanding the SLR on proto-Y chromosomes. Both autosomal and SLR-expanding inversions face a race against time: lightly-loaded inversions are initially beneficial, but eventually become deleterious as they accumulate new mutations, after which their chances of fixing become negligible. In contrast, initially unloaded inversions eventually become neutral as their deleterious load reaches the same equilibrium as non-inverted haplotypes. Despite the differences in inheritance and indirect selection, SLR-expanding inversions exhibit similar evolutionary dynamics to autosomal inversions over many biologically plausible parameter conditions. Differences emerge when the population average mutation load is quite high; in this case large autosomal inversions that are lucky enough to be mutation-free can rise to intermediate to high frequencies where selection in homozygotes becomes important (Y-linked inversions never appear as homozygous karyotypes); conditions requiring either high mutation rates, highly recessive deleterious mutations, weak selection, or a combination thereof.

Impact of whole-genome duplications on structural variant evolution in Cochlearia

Polyploidy, the result of whole-genome duplication (WGD), is a major driver of eukaryote evolution. Yet WGDs are hugely disruptive mutations, and we still lack a clear understanding of their fitness consequences. Here, we study whether WGDs result in greater diversity of genomic structural variants (SVs) and how they influence evolutionary dynamics in a plant genus, Cochlearia (Brassicaceae). By using long-read sequencing and a graph-based pangenome, we find both negative and positive interactions between WGDs and SVs. Masking of recessive mutations due to WGDs leads to a progressive accumulation of deleterious SVs across four ploidal levels (from diploids to octoploids), likely reducing the adaptive potential of polyploid populations. However, we also discover putative benefits arising from SV accumulation, as more ploidy-specific SVs harbor signals of local adaptation in polyploids than in diploids. Together, our results suggest that SVs play diverse and contrasting roles in the evolutionary trajectories of young polyploids.

Fixation times of de novo and standing beneficial variants in subdivided populations

The rate at which beneficial alleles fix in a population depends on the probability of and time to fixation of such alleles. Both of these quantities can be significantly impacted by population subdivision and limited gene flow. Here, we investigate how limited dispersal influences the rate of fixation of beneficial de novo mutations, as well as fixation time from standing genetic variation. We investigate this for a population structured according to the island model of dispersal allowing us to use the diffusion approximation, which we complement with simulations. We find that fixation may take on average fewer generations under limited dispersal than under panmixia when selection is moderate. This is especially the case if adaptation occurs from de novo recessive mutations, and dispersal is not too limited (such that approximately FST<0.2). The reason is that mildly limited dispersal leads to only a moderate increase in effective population size (which slows down fixation), but is sufficient to cause a relative excess of homozygosity due to inbreeding, thereby exposing rare recessive alleles to selection (which accelerates fixation). We also explore the effect of metapopulation dynamics through local extinction followed by recolonization, finding that such dynamics always accelerate fixation from standing genetic variation, while de novo mutations show faster fixation interspersed with longer waiting times. Finally, we discuss the implications of our results for the detection of sweeps, suggesting that limited dispersal mitigates the expected differences between the genetic signatures of sweeps involving recessive and dominant alleles.

Measuring the Efficiency of Purging by non-random Mating in Human Populations

Human populations harbor a high concentration of deleterious genetic variants. Here, we tested the hypothesis that non-random mating practices affect the distribution of these variants, through exposure in the homozygous state, leading to their purging from the population gene pool. To do so, we produced whole-genome sequencing data for two pairs of Asian populations exhibiting different alliance rules and rates of inbreeding, but with similar effective population sizes. The results show that populations with higher rates of inbred matings do not purge deleterious variants more efficiently. Purging therefore has a low efficiency in human populations, and different mating practices lead to a similar mutational load.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ∼25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

Dominance and multi-locus interaction

Dominance is usually considered a constant value that describes the relative difference in fitness or phenotype between heterozygotes and the average of homozygotes at a focal polymorphic locus. However, the observed dominance can vary with the genetic background of the focal locus. Here, alleles at other loci modify the observed phenotype through position effects or dominance modifiers that are sometimes associated with pathogen resistance, lineage, sex, or mating type. Theoretical models have illustrated how variable dominance appears in the context of multi-locus interaction (epistasis). Here, we review empirical evidence for variable dominance and how the observed patterns may be captured by proposed epistatic models. We highlight how integrating epistasis and dominance is crucial for comprehensively understanding adaptation and speciation.

Dominance reversals: the resolution of genetic conflict and maintenance of genetic variation

Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g. habitat, developmental stage, trait or sex) being dominant in that context but recessive where deleterious. This context dependence at least partially mitigates the fitness consequence of heterozygotes carrying one non-beneficial allele for their context and can result in balancing selection that maintains alternative alleles. Dominance reversals are theoretically plausible and are supported by mounting empirical evidence. Here, we highlight the importance of beneficial dominance reversals as a mechanism for the mitigation of genetic conflict and review the theory and empirical evidence for them. We identify some areas in need of further research and development and outline three methods that could facilitate the identification of antagonistic genetic variation (dominance ordination, allele-specific expression and allele-specific ATAC-Seq (assay for transposase-accessible chromatin with sequencing)). There is ample scope for the development of new empirical methods as well as reanalysis of existing data through the lens of dominance reversals. A greater focus on this topic will expand our understanding of the mechanisms that resolve genetic conflict and whether they maintain genetic variation.

Constraining models of dominance for nonsynonymous mutations in the human genome

Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h=0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.

Gametic selection favours polyandry and selfing

Competition among pollen or sperm (gametic selection) can cause evolution. Mating systems shape the intensity of gametic selection by determining the competitors involved, which can in turn cause the mating system itself to evolve. We model the bidirectional relationship between gametic selection and mating systems, focusing on variation in female mating frequency (monandry-polyandry) and self-fertilisation (selfing-outcrossing). First, we find that monandry and selfing both reduce the efficiency of gametic selection in removing deleterious alleles. This means that selfing can increase mutation load, in contrast to cases without gametic selection where selfing purges deleterious mutations and decreases mutation load. Second, we explore how mating systems evolve via their effect on gametic selection. By manipulating gametic selection, polyandry can evolve to increase the fitness of the offspring produced. However, this indirect advantage of post-copulatory sexual selection is weak and is likely to be overwhelmed by any direct fitness effects of mating systems. Nevertheless, gametic selection can be potentially decisive for selfing evolution because it significantly reduces inbreeding depression, which favours selfing. Thus, the presence of gametic selection could be a key factor driving selfing evolution.

Schrödinger's yeast: the challenge of using transformation to compare fitness among Saccharomyces cerevisiae that differ in ploidy or zygosity

How the number of genome copies modifies the effect of random mutations remains poorly known. In yeast, researchers have investigated these effects for knock-out or other large-effect mutations, but have not accounted for differences at the mating-type locus. We set out to compare fitness differences among strains that differ in ploidy and/or zygosity using a panel of spontaneously arising mutations acquired in haploid yeast from a previous study. To ensure no genetic differences, even at the mating-type locus, we embarked on a series of transformations, which first sterilized and then temporarily introduced plasmid-borne mating types. Despite these attempts to equalize the haplotypes, fitness variation introduced during transformation swamped the differences among the original mutation-accumulation lines. While colony size looked normal, we observed a bi-modality in the maximum growth rate of our transformed yeast and determined that many of the slow growing lines were respiratory deficient ("petite"). Not previously reported, we found that yeast that were TID1/RDH54 knockouts were less likely to become petite. Even for lines with the same petite status, however, we found no correlation in fitness between the two replicate transformations performed. These results pose a challenge for any study using transformation to measure the fitness effect of genetic differences among strains. By attempting to hold haplotypes constant, we introduced more mutations that overwhelmed our ability to measure fitness differences between the genetic states. In this study, we transformed over one hundred different lines of yeast, using two independent transformations, and found that this common laboratory procedure can cause large changes to the microbe studied. Our study provides a cautionary tale of the need to use multiple transformants in fitness assays.

Using Computational Simulations to Model Deleterious Variation and Genetic Load in Natural Populations

AbstractDeleterious genetic variation is abundant in wild populations, and understanding the ecological and conservation implications of such variation is an area of active research. Genomic methods are increasingly used to quantify the impacts of deleterious variation in natural populations; however, these approaches remain limited by an inability to accurately predict the selective and dominance effects of mutations. Computational simulations of deleterious variation offer a complementary tool that can help overcome these limitations, although such approaches have yet to be widely employed. In this perspective article, we aim to encourage ecological and conservation genomics researchers to adopt greater use of computational simulations to aid in deepening our understanding of deleterious variation in natural populations. We first provide an overview of the components of a simulation of deleterious variation, describing the key parameters involved in such models. Next, we discuss several approaches for validating simulation models. Finally, we compare and validate several recently proposed deleterious mutation models, demonstrating that models based on estimates of selection parameters from experimental systems are biased toward highly deleterious mutations. We describe a new model that is supported by multiple orthogonal lines of evidence and provide example scripts for implementing this model (https://github.com/ckyriazis/simulations_review).

Adaptation to the High-Arctic island environment despite long-term reduced genetic variation in Svalbard reindeer

Typically much smaller in number than their mainland counterparts, island populations are ideal systems to investigate genetic threats to small populations. The Svalbard reindeer (Rangifer tarandus platyrhynchus) is an endemic subspecies that colonized the Svalbard archipelago ca. 6,000-8,000 years ago and now shows numerous physiological and morphological adaptations to its arctic habitat. Here, we report a de-novo chromosome-level assembly for Svalbard reindeer and analyze 133 reindeer genomes spanning Svalbard and most of the species' Holarctic range, to examine the genomic consequences of long-term isolation and small population size in this insular subspecies. Empirical data, demographic reconstructions, and forward simulations show that long-term isolation and high inbreeding levels may have facilitated the reduction of highly deleterious-and to a lesser extent, moderately deleterious-variation. Our study indicates that long-term reduced genetic diversity did not preclude local adaptation to the High Arctic, suggesting that even severely bottlenecked populations can retain evolutionary potential.

The Contribution of Mutation to Variation in Temperature-Dependent Sprint Speed in Zebrafish, Danio rerio

AbstractThe contribution of new mutations to phenotypic variation and the consequences of this variation for individual fitness are fundamental concepts for understanding genetic variation and adaptation. Here, we investigated how mutation influenced variation in a complex trait in zebrafish, Danio rerio. Typical of many ecologically relevant traits in ectotherms, swimming speed in fish is temperature dependent, with evidence of adaptive evolution of thermal performance. We chemically induced novel germline point mutations in males and measured sprint speed in their sons at six temperatures (between 16°C and 34°C). Heterozygous mutational effects on speed were strongly positively correlated among temperatures, resulting in statistical support for only a single axis of mutational variation, reflecting temperature-independent variation in speed (faster-slower mode). These results suggest pleiotropic effects on speed across different temperatures; however, spurious correlations arise via linkage or heterogeneity in mutation number when mutations have consistent directional effects on each trait. Here, mutation did not change mean speed, indicating no directional bias in mutational effects. The results contribute to emerging evidence that mutations may predominantly have synergistic cross-environment effects, in contrast to conditionally neutral or antagonistic effects that underpin thermal adaptation. We discuss several aspects of experimental design that may affect resolution of mutations with nonsynergistic effects.

The genomic footprint of whaling and isolation in fin whale populations

Twentieth century industrial whaling pushed several species to the brink of extinction, with fin whales being the most impacted. However, a small, resident population in the Gulf of California was not targeted by whaling. Here, we analyzed 50 whole-genomes from the Eastern North Pacific (ENP) and Gulf of California (GOC) fin whale populations to investigate their demographic history and the genomic effects of natural and human-induced bottlenecks. We show that the two populations diverged ~16,000 years ago, after which the ENP population expanded and then suffered a 99% reduction in effective size during the whaling period. In contrast, the GOC population remained small and isolated, receiving less than one migrant per generation. However, this low level of migration has been crucial for maintaining its viability. Our study exposes the severity of whaling, emphasizes the importance of migration, and demonstrates the use of genome-based analyses and simulations to inform conservation strategies.

Human deleterious mutation rate implies high fitness variance, with declining mean fitness compensated by rarer beneficial mutations of larger effect

Each new human has an expected Ud = 2 - 10 new deleterious mutations. This deluge of deleterious mutations cannot all be purged, and therefore accumulate in a declining fitness ratchet. Using a novel simulation framework designed to efficiently handle genome-wide linkage disequilibria across many segregating sites, we find that rarer, beneficial mutations of larger effect are sufficient to compensate fitness declines due to the fixation of many slightly deleterious mutations. Drift barrier theory posits a similar asymmetric pattern of fixations to explain ratcheting genome size and complexity, but in our theory, the cause is Ud > 1 rather than small population size. In our simulations, Ud ~2 - 10 generates high within-population variance in relative fitness; two individuals will typically differ in fitness by 15-40%. Ud ~2 - 10 also slows net adaptation by ~13%-39%. Surprisingly, fixation rates are more sensitive to changes in the beneficial than the deleterious mutation rate, e.g. a 10% increase in overall mutation rate leads to faster adaptation; this puts to rest dysgenic fears about increasing mutation rates due to rising paternal age.

Influence of the mutation load on the genomic composition of hybrids between outcrossing and self-fertilizing species

Hybridization is a natural process whereby two diverging evolutionary lineages reproduce and create offspring of mixed ancestry. Differences in mating systems (e.g., self-fertilization and outcrossing) are expected to affect the direction and extent of hybridization and introgression in hybrid zones. Among other factors, selfers and outcrossers are expected to differ in their mutation loads. This has been studied both theoretically and empirically; however, conflicting predictions have been made on the effects mutation loads of parental species with different mating systems can have on the genomic composition of hybrids. Here, we develop a multi-locus, selective model to study how the different mutation load built up in selfers and outcrossers as a result of selective interference and homozygosity impact the long-term genetic composition of hybrid populations. Notably, our results emphasize that genes from the parental population with lesser mutation load get rapidly overrepresented in hybrid genomes, regardless of the hybrids own mating system. When recombination tends to be more important than mutation, outcrossers' genomes tend to be of higher quality and prevail. When recombination rates are low, however, selfers' genomes may reach higher quality than outcrossers' genomes and prevail in the hybrids. Taken together, these results provide concrete insights into one of the multiple factors influencing hybrid genome ancestry and introgression patterns in hybrid zones containing species with different mating systems.

Purging due to self-fertilization does not prevent accumulation of expansion load

As species expand their geographic ranges, colonizing populations face novel ecological conditions, such as new environments and limited mates, and suffer from evolutionary consequences of demographic change through bottlenecks and mutation load accumulation. Self-fertilization is often observed at species range edges and, in addition to countering the lack of mates, is hypothesized as an evolutionary advantage against load accumulation through increased homozygosity and purging. We study how selfing impacts the accumulation of genetic load during range expansion via purging and/or speed of colonization. Using simulations, we disentangle inbreeding effects due to demography versus due to selfing and find that selfers expand faster, but still accumulate load, regardless of mating system. The severity of variants contributing to this load, however, differs across mating system: higher selfing rates purge large-effect recessive variants leaving a burden of smaller-effect alleles. We compare these predictions to the mixed-mating plant Arabis alpina, using whole-genome sequences from refugial outcrossing populations versus expanded selfing populations. Empirical results indicate accumulation of expansion load along with evidence of purging in selfing populations, concordant with our simulations, suggesting that while purging is a benefit of selfing evolving during range expansions, it is not sufficient to prevent load accumulation due to range expansion.

Environmental variance in male mating success modulates the positive versus negative impacts of sexual selection on genetic load

Sexual selection on males is predicted to increase population fitness, and delay population extinction, when mating success negatively covaries with genetic load across individuals. However, such benefits of sexual selection could be counteracted by simultaneous increases in genome-wide drift resulting from reduced effective population size caused by increased variance in fitness. Resulting fixation of deleterious mutations could be greatest in small populations, and when environmental variation in mating traits partially decouples sexual selection from underlying genetic variation. The net consequences of sexual selection for genetic load and population persistence are therefore likely to be context dependent, but such variation has not been examined. We use a genetically explicit individual-based model to show that weak sexual selection can increase population persistence time compared to random mating. However, for stronger sexual selection such positive effects can be overturned by the detrimental effects of increased genome-wide drift. Furthermore, the relative strengths of mutation-purging and drift critically depend on the environmental variance in the male mating trait. Specifically, increasing environmental variance caused stronger sexual selection to elevate deleterious mutation fixation rate and mean selection coefficient, driving rapid accumulation of drift load and decreasing population persistence times. These results highlight an intricate balance between conflicting positive and negative consequences of sexual selection on genetic load, even in the absence of sexually antagonistic selection. They imply that environmental variances in key mating traits, and intrinsic genetic drift, should be properly factored into future theoretical and empirical studies of the evolution of population fitness under sexual selection.

Digest: Few new mutations are recessive lethal

When a new mutation arises, what is the probability that it is recessive lethal? Wade et al. find that fewer than 1% of nonsynonymous mutations in humans and Drosophila melanogaster are recessive lethal. The authors show that methods based on site frequency spectrum (SFS) analyses, though generally robust in their estimations of the nonlethal distribution of fitness effects (DFE), are unable to accurately estimate the fraction of recessive lethal mutations.

An empirical evaluation of the estimation of inbreeding depression from molecular markers under suboptimal conditions

Inbreeding depression (ID), the reduction in fitness due to inbreeding, is typically measured by the regression of the phenotypic values of individuals for a particular trait on their corresponding inbreeding coefficients (F). While genealogical records can provide these coefficients, they may be unavailable or incomplete, making molecular markers a useful alternative. The power to detect ID and its accuracy depend on the variation of F values of individuals, the sample sizes available, and the accuracy in the estimation of individual fitness traits and F values. In this study, we used Drosophila melanogaster to evaluate the effectiveness of molecular markers in estimating ID under suboptimal conditions. We generated two sets of 100 pairs of unrelated individuals from a large panmictic population and mated them for two generations to produce non-inbred and unrelated individuals (F = 0) and inbred individuals (full-sib progeny; F = 0.25). Using these expected genealogical F values, we calculated inbreeding depression for two fitness-related traits, pupae productivity and competitive fitness. We then sequenced the males from 17 non-inbred pairs and 17 inbred pairs to obtain their genomic inbreeding coefficients and estimate ID for the two traits. The scenario assumed was rather restrictive in terms of estimation of ID because: (1) the individuals belonged to the same generation of a large panmictic population, leading to low variation in individual F coefficients; (2) the sample sizes were small; and (3) the traits measured depended on both males and females while only males were sequenced. Despite the challenging conditions of our study, we found that molecular markers provided estimates of ID that were comparable to those obtained from simple pedigree estimations with larger sample sizes. The results therefore suggest that genomic measures of inbreeding are useful to provide estimates of inbreeding depression even under very challenging scenarios.

Quantifying the fraction of new mutations that are recessive lethal

The presence and impact of recessive lethal mutations have been widely documented in diploid outcrossing species. However, precise estimates of the proportion of new mutations that are recessive lethal remain limited. Here, we evaluate the performance of Fit∂a∂i, a commonly used method for inferring the distribution of fitness effects (DFE), in the presence of lethal mutations. Using simulations, we demonstrate that in both additive and recessive cases, inference of the deleterious nonlethal portion of the DFE is minimally affected by a small proportion (<10%) of lethal mutations. Additionally, we demonstrate that while Fit∂a∂i cannot estimate the fraction of recessive lethal mutations, Fit∂a∂i can accurately infer the fraction of additive lethal mutations. Finally, as an alternative approach to estimate the proportion of mutations that are recessive lethal, we employ models of mutation-selection-drift balance using existing genomic parameters and estimates of segregating recessive lethals for humans and Drosophila melanogaster. In both species, the segregating recessive lethal load can be explained by a very small fraction (<1%) of new nonsynonymous mutations being recessive lethal. Our results refute recent assertions of a much higher proportion of mutations being recessive lethal (4%-5%), while highlighting the need for additional information on the joint distribution of selection and dominance coefficients.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, s het . Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

Demographic history and genomic consequences of 10,000 generations of isolation in a wild mammal

Increased human activities caused the isolation of populations in many species-often associated with genetic depletion and negative fitness effects. The effects of isolation are predicted by theory, but long-term data from natural populations are scarce. We show, with full genome sequences, that common voles (Microtus arvalis) in the Orkney archipelago have remained genetically isolated from conspecifics in continental Europe since their introduction by humans over 5,000 years ago. Modern Orkney vole populations are genetically highly differentiated from continental conspecifics as a result of genetic drift processes. Colonization likely started on the biggest Orkney island and vole populations on smaller islands were gradually split off, without signs of secondary admixture. Despite having large modern population sizes, Orkney voles are genetically depauperate and successive introductions to smaller islands resulted in further reduction of genetic diversity. We detected high levels of fixation of predicted deleterious variation compared with continental populations, particularly on smaller islands, yet the fitness effects realized in nature are unknown. Simulations showed that predominantly mildly deleterious mutations were fixed in populations, while highly deleterious mutations were purged early in the history of the Orkney population. Relaxation of selection overall due to benign environmental conditions on the islands and the effects of soft selection may have contributed to the repeated, successful establishment of Orkney voles despite potential fitness loss. Furthermore, the specific life history of these small mammals, resulting in relatively large population sizes, has probably been important for their long-term persistence in full isolation.

Inferring the mode and strength of ongoing selection

Genome sequence data are no longer scarce. The UK Biobank alone comprises 200,000 individual genomes, with more on the way, leading the field of human genetics toward sequencing entire populations. Within the next decades, other model organisms will follow suit, especially domesticated species such as crops and livestock. Having sequences from most individuals in a population will present new challenges for using these data to improve health and agriculture in the pursuit of a sustainable future. Existing population genetic methods are designed to model hundreds of randomly sampled sequences but are not optimized for extracting the information contained in the larger and richer data sets that are beginning to emerge, with thousands of closely related individuals. Here we develop a new method called trio-based inference of dominance and selection (TIDES) that uses data from tens of thousands of family trios to make inferences about natural selection acting in a single generation. TIDES further improves on the state of the art by making no assumptions regarding demography, linkage, or dominance. We discuss how our method paves the way for studying natural selection from new angles.

Using inbreeding to test the contribution of non-additive genetic effects to additive genetic variance: a case study in Drosophila serrata

Additive genetic variance, V_A, is the key parameter for predicting adaptive and neutral phenotypic evolution. Changes in demography (e.g. increased close-relative inbreeding) can alter V_A, but how they do so depends on the (typically unknown) gene action and allele frequencies across many loci. For example, V_A increases proportionally with the inbreeding coefficient when allelic effects are additive, but smaller (or larger) increases can occur when allele frequencies are unequal at causal loci with dominance effects. Here, we describe an experimental approach to assess the potential for dominance effects to deflate V_A under inbreeding. Applying a powerful paired pedigree design in Drosophila serrata, we measured 11 wing traits on half-sibling families bred via either random or sibling mating, differing only in homozygosity (not allele frequency). Despite close inbreeding and substantial power to detect small V_A, we detected no deviation from the expected additive effect of inbreeding on genetic (co)variances. Our results suggest the average dominance coefficient is very small relative to the additive effect, or that allele frequencies are relatively equal at loci affecting wing traits. We outline the further opportunities for this paired pedigree approach to reveal the characteristics of V_A, providing insight into historical selection and future evolutionary potential.

Genomic Underpinnings of Population Persistence in Isle Royale Moose

Island ecosystems provide natural laboratories to assess the impacts of isolation on population persistence. However, most studies of persistence have focused on a single species, without comparisons to other organisms they interact with in the ecosystem. The case study of moose and gray wolves on Isle Royale allows for a direct contrast of genetic variation in isolated populations that have experienced dramatically differing population trajectories over the past decade. Whereas the Isle Royale wolf population recently declined nearly to extinction due to severe inbreeding depression, the moose population has thrived and continues to persist, despite having low genetic diversity and being isolated for ∼120 years. Here, we examine the patterns of genomic variation underlying the continued persistence of the Isle Royale moose population. We document high levels of inbreeding in the population, roughly as high as the wolf population at the time of its decline. However, inbreeding in the moose population manifests in the form of intermediate-length runs of homozygosity suggestive of historical inbreeding and purging, contrasting with the long runs of homozygosity observed in the smaller wolf population. Using simulations, we confirm that substantial purging has likely occurred in the moose population. However, we also document notable increases in genetic load, which could eventually threaten population viability over the long term. Overall, our results demonstrate a complex relationship between inbreeding, genetic diversity, and population viability that highlights the use of genomic datasets and computational simulation tools for understanding the factors enabling persistence in isolated populations.

Genetic complementation fosters evolvability in complex fitness landscapes

The ability of natural selection to optimize traits depends on the topology of the genotype-fitness map (fitness landscape). Epistatic interactions produce rugged fitness landscapes, where adaptation is constrained by the presence of low-fitness intermediates. Here, we used simulations to explore how evolvability in rugged fitness landscapes is influenced by genetic complementation, a process whereby different sequence variants mutually compensate for their deleterious mutations. We designed our model inspired by viral populations, in which genetic variants are known to interact frequently through coinfection. Our simulations indicate that genetic complementation enables a more efficient exploration of rugged fitness landscapes. Although this benefit may be undermined by genetic parasites, its overall effect on evolvability remains positive in populations that exhibit strong relatedness between interacting sequences. Similar processes could operate in contexts other than viral coinfection, such as in the evolution of ploidy.

Disentangling the genetic consequences of demographic change

Quantifying the impact of human activity on the capacity of populations to persist is paramount to conservation biology, as numerous species and populations have already been driven to or beyond the brink of extinction. Those populations that persist are often a sobering example of the evolutionary power of human-disturbance, such as the loss of tusks in African elephants resulting from ivory harvesting (Campbell-Staton et al., 2021) and rapid life-history evolution in northern Atlantic cod in response to fisheries (Olsen et al., 2004). These evolutionary responses reflect a delicate interplay between demographic and selective processes (e.g., evolutionary rescue: Bell & Gonzalez, 2009; Gomulkiewicz & Holt, 1995), both of which can modify genetic variation for fitness. While quantifying fitness remains a difficult challenge, generalizable insights into the evolutionary consequences of population collapse can be provided in systems with independent demographic shifts in response to human activity. Unfortunately, such was the case for sea otter populations across its range in the 18th and 19th centuries, where the fur-trade had catastrophic, range-wide effects on sea otter (Enhydra lutris) populations. In a From the Cover article in this issue of Molecular Ecology, Beichman et al. (2022) combine a population genomic spatiotemporal data set and theoretical simulations not only to quantify past demographic change in response to sea otter exploitation, but also to understand the consequences of population collapse on species persistence.

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.

Severe inbreeding, increased mutation load and gene loss-of-function in the critically endangered Devils Hole pupfish

Small populations with limited range are often threatened by inbreeding and reduced genetic diversity, which can reduce fitness and exacerbate population decline. One of the most extreme natural examples is the Devils Hole pupfish (Cyprinodon diabolis), an iconic and critically endangered species with the smallest known range of any vertebrate. This species has experienced severe declines in population size over the last 30 years and suffered major bottlenecks in 2007 and 2013, when the population shrunk to 38 and 35 individuals, respectively. Here, we analysed 30 resequenced genomes of desert pupfishes from Death Valley, Ash Meadows and surrounding areas to examine the genomic consequences of small population size. We found extremely high levels of inbreeding (FROH = 0.34-0.81) and an increased amount of potentially deleterious genetic variation in the Devils Hole pupfish as compared to other species, including unique, fixed loss-of-function alleles and deletions in genes associated with sperm motility and hypoxia. Additionally, we successfully resequenced a formalin-fixed museum specimen from 1980 and found that the population was already highly inbred prior to recent known bottlenecks. We thus document severe inbreeding and increased mutation load in the Devils Hole pupfish and identify candidate deleterious variants to inform management of this conservation icon.

Modeling minimum viable population size with multiple genetic problems of small populations

An important goal for conservation is to define minimum viable population (MVP) sizes for long-term persistence of a species. There is increasing evidence of the role of genetics in population extinction; thus, conservation practitioners are starting to consider the effects of deleterious mutations (DM), in particular the effects of inbreeding depression on fitness. We sought to develop methods to account for genetic problems other than inbreeding depression in MVP estimates, quantify the effect of the interaction of multiple genetic problems on MVP sizes, and find ways to reduce the arbitrariness of time and persistence probability thresholds in MVP analyses. To do so, we developed ecoevolutionary quantitative models to track population size and levels of genetic diversity. We assumed a biallelic multilocus genome with loci under single or multiple, interacting genetic forces. We included mutation-selection-drift balance (for loci with DM) and 3 forms of balancing selection for loci for which variation is lost through genetic drift. We defined MVP size as the lowest population size that avoids an ecoevolutionary extinction vortex. For populations affected by only balancing selection, MVP size decreased rapidly as mutation rates increased. For populations affected by mutation-selection-drift balance, the MVP size increased rapidly. In addition, MVP sizes increased rapidly as the number of loci increased under the same or different selection mechanisms until even arbitrarily large populations could not survive. In the case of fixed number of loci under selection, interaction of genetic problems did not always increase MVP sizes. To further enhance understanding about interaction of genetic problems, there is need for more empirical studies to reveal how different genetic processes interact in the genome.

Give and Take: Effects of Genetic Admixture on Mutation Load in Endangered Florida Panthers

Genetic admixture is a biological event inherent to genetic rescue programs aimed at the long-term conservation of endangered wildlife. Although the success of such programs can be measured by the increase in genetic diversity and fitness of subsequent admixed individuals, predictions supporting admixture costs to fitness due to the introduction of novel deleterious alleles are necessary. Here, we analyzed nonsynonymous variation from conserved genes to quantify and compare levels of mutation load (i.e., proportion of deleterious alleles and genotypes carrying these alleles) among endangered Florida panthers and non-endangered Texas pumas. Specifically, we used canonical (i.e., non-admixed) Florida panthers, Texas pumas, and F1 (canonical Florida x Texas) panthers dating from a genetic rescue program and Everglades National Park panthers with Central American ancestry resulting from an earlier admixture event. We found neither genetic drift nor selection significantly reduced overall proportions of deleterious alleles in the severely bottlenecked canonical Florida panthers. Nevertheless, the deleterious alleles identified were distributed into a disproportionately high number of homozygous genotypes due to close inbreeding in this group. Conversely, admixed Florida panthers (either with Texas or Central American ancestry) presented reduced levels of homozygous genotypes carrying deleterious alleles but increased levels of heterozygous genotypes carrying these variants relative to canonical Florida panthers. Although admixture is likely to alleviate the load of standing deleterious variation present in homozygous genotypes, our results suggest introduced novel deleterious alleles (temporarily present in heterozygous state) in genetically rescued populations could potentially be expressed in subsequent generations if their effective sizes remain small.

Octopaminergic/tyraminergic Tdc2 neurons regulate biased sperm usage in female Drosophila melanogaster

In polyandrous internally fertilizing species, a multiply-mated female can use stored sperm from different males in a biased manner to fertilize her eggs. The female's ability to assess sperm quality and compatibility is essential for her reproductive success, and represents an important aspect of postcopulatory sexual selection. In Drosophila melanogaster, previous studies demonstrated that the female nervous system plays an active role in influencing progeny paternity proportion, and suggested a role for octopaminergic/tyraminergic Tdc2 neurons in this process. Here, we report that inhibiting Tdc2 neuronal activity causes females to produce a higher-than-normal proportion of first-male progeny. This difference is not due to differences in sperm storage or release, but instead is attributable to the suppression of second-male sperm usage bias that normally occurs in control females. We further show that a subset of Tdc2 neurons innervating the female reproductive tract is largely responsible for the progeny proportion phenotype that is observed when Tdc2 neurons are inhibited globally. On the contrary, overactivation of Tdc2 neurons does not further affect sperm storage and release or progeny proportion. These results suggest that octopaminergic/tyraminergic signaling allows a multiply-mated female to bias sperm usage, and identify a new role for the female nervous system in postcopulatory sexual selection.

Consequences of partially recessive deleterious genetic variation for the evolution of inversions suppressing recombination between sex chromosomes

The evolution of suppressed recombination between sex chromosomes is widely hypothesized to be driven by sexually antagonistic selection (SA), where tighter linkage between the sex-determining gene(s) and nearby SA loci is favored when it couples male-beneficial alleles to the proto-Y chromosome, and female-beneficial alleles to the proto-X. Despite limited empirical evidence, the SA selection hypothesis overshadows several alternatives, including an incomplete but often-repeated "sheltering hypothesis" that suggests that expansion of the sex-linked region (SLR) reduces homozygous expression of partially recessive deleterious mutations at selected loci. Here, we use population genetic models to evaluate the consequences of deleterious mutational variation for the evolution of neutral chromosomal inversions expanding the SLR on proto-Y chromosomes. We find that SLR-expanding inversions face a race against time: lightly loaded inversions are initially beneficial, but eventually become deleterious as they accumulate new mutations, and must fix before this window of opportunity closes. The outcome of this race is strongly influenced by inversion size, the mutation rate, and the dominance coefficient of deleterious mutations. Yet, small inversions have elevated fixation probabilities relative to neutral expectations for biologically plausible parameter values. Our results demonstrate that deleterious genetic variation can plausibly drive recombination suppression in small steps and would be most consistent with empirical patterns of small evolutionary strata or gradual recombination arrest.

Dominance shifts increase the likelihood of soft selective sweeps

Genetic models of adaptation to a new environment have typically assumed that the alleles involved maintain a constant fitness dominance across the old and new environments. However, theories of dominance suggest that this should often not be the case. Instead, the alleles involved should frequently shift from recessive deleterious in the old environment to dominant beneficial in the new environment. Here, we study the consequences of these expected dominance shifts for the genetics of adaptation to a new environment. We find that dominance shifts increase the likelihood that adaptation occurs from standing variation, and that multiple alleles from the standing variation are involved (a soft selective sweep). Furthermore, we find that expected dominance shifts increase the haplotypic diversity of selective sweeps, rendering soft sweeps more detectable in small genomic samples. In cases where an environmental change threatens the viability of the population, we show that expected dominance shifts of newly beneficial alleles increase the likelihood of evolutionary rescue and the number of alleles involved. Finally, we apply our results to a well-studied case of adaptation to a new environment: the evolution of pesticide resistance at the Ace locus in Drosophila melanogaster. We show that, under reasonable demographic assumptions, the expected dominance shift of resistant alleles causes soft sweeps to be the most frequent outcome in this case, with the primary source of these soft sweeps being the standing variation at the onset of pesticide use, rather than recurrent mutation thereafter.

Purging of deleterious burden in the endangered Iberian lynx

SignificanceThe dynamics of deleterious variation under contrasting demographic scenarios remain poorly understood in spite of their relevance in evolutionary and conservation terms. Here we apply a genomic approach to study differences in the burden of deleterious alleles between the endangered Iberian lynx (Lynx pardinus) and the widespread Eurasian lynx (Lynx lynx). Our analysis unveils a significantly lower deleterious burden in the former species that should be ascribed to genetic purging, that is, to the increased opportunities of selection against recessive homozygotes due to the inbreeding caused by its smaller population size, as illustrated by our analytical predictions. This research provides theoretical and empirical evidence on the evolutionary relevance of genetic purging under certain demographic conditions.

Gene surfing of underdominant alleles promotes formation of hybrid zones

The distribution of genetic diversity over geographical space has long been investigated in population genetics and serves as a useful tool to understand evolution and history of populations. Within some species or across regions of contact between two species, there are instances where there is no apparent ecological determinant of sharp changes in allele frequencies or divergence. To further understand these patterns of spatial genetic structure and potential species divergence, we model the establishment of clines that occur due to the surfing of underdominant alleles during range expansions. We provide analytical approximations for the fixation probability of underdominant alleles at expansion fronts and demonstrate that gene surfing can lead to clines in one-dimensional range expansions. We extend these results to multiple loci via a mixture of analytical theory and individual-based simulations. We study the interaction between the strength of selection against heterozygotes, migration rates, and local recombination rates on the formation of stable hybrid zones. Clines created by surfing at different loci can attract each other and align after expansion, if they are sufficiently close in space and in terms of recombination distance. Our findings suggest that range expansions can set the stage for parapatric speciation due to the alignment of multiple selective clines, even in the absence of ecologically divergent selection. This article is part of the theme issue 'Species' ranges in the face of changing environments (part I)'.

Genetic load and extinction in peripheral populations: the roles of migration, drift and demographic stochasticity

We analyse how migration from a large mainland influences genetic load and population numbers on an island, in a scenario where fitness-affecting variants are unconditionally deleterious, and where numbers decline with increasing load. Our analysis shows that migration can have qualitatively different effects, depending on the total mutation target and fitness effects of deleterious variants. In particular, we find that populations exhibit a genetic Allee effect across a wide range of parameter combinations, when variants are partially recessive, cycling between low-load (large-population) and high-load (sink) states. Increased migration reduces load in the sink state (by increasing heterozygosity) but further inflates load in the large-population state (by hindering purging). We identify various critical parameter thresholds at which one or other stable state collapses, and discuss how these thresholds are influenced by the genetic versus demographic effects of migration. Our analysis is based on a 'semi-deterministic' analysis, which accounts for genetic drift but neglects demographic stochasticity. We also compare against simulations which account for both demographic stochasticity and drift. Our results clarify the importance of gene flow as a key determinant of extinction risk in peripheral populations, even in the absence of ecological gradients. This article is part of the theme issue 'Species' ranges in the face of changing environments (part I)'.

Dominance can increase genetic variance after a population bottleneck: a synthesis of the theoretical and empirical evidence

Drastic reductions in population size, or population bottlenecks, can lead to a reduction in additive genetic variance and adaptive potential. Genetic variance for some quantitative genetic traits, however, can increase after a population reduction. Empirical evaluations of quantitative traits following experimental bottlenecks indicate that non-additive genetic effects, including both allelic dominance at a given locus and epistatic interactions among loci, may impact the additive variance contributed by alleles that ultimately influences phenotypic expression and fitness. The dramatic effects of bottlenecks on overall genetic diversity have been well studied, but relatively little is known about how dominance and demographic events like bottlenecks can impact additive genetic variance. Herein, we critically examine how the degree of dominance among alleles affects additive genetic variance after a bottleneck. We first review and synthesize studies that document the impact of empirical bottlenecks on dominance variance. We then extend earlier work by elaborating on two theoretical models that illustrate the relationship between dominance and the potential increase in additive genetic variance immediately following a bottleneck. Furthermore, we investigate the parameters that influence the maximum level of genetic variation (associated with adaptive potential) after a bottleneck, including the number of founding individuals. Finally, we validated our methods using forward-time population genetic simulations of loci with varying dominance and selection levels. The fate of non-additive genetic variation following bottlenecks could have important implications for conservation and management efforts in a wide variety of taxa, and our work should help contextualize future studies (e.g., epistatic variance) in population genomics.

Deleterious Mutations Accumulate Faster in Allopolyploid than Diploid Cotton (Gossypium) and Unequally between Subgenomes

Whole genome duplication (polyploidization) is among the most dramatic mutational processes in nature, so understanding how natural selection differs in polyploids relative to diploids is an important goal. Population genetics theory predicts that recessive deleterious mutations accumulate faster in allopolyploids than diploids due to the masking effect of redundant gene copies, but this prediction is hitherto unconfirmed. Here, we use the cotton genus (Gossypium), which contains seven allopolyploids derived from a single polyploidization event 1-2 million years ago, to investigate deleterious mutation accumulation. We use two methods of identifying deleterious mutations at the nucleotide and amino acid level, along with whole-genome resequencing of 43 individuals spanning six allopolyploid species and their two diploid progenitors, to demonstrate that deleterious mutations accumulate faster in allopolyploids than in their diploid progenitors. We find that, unlike what would be expected under models of demographic changes alone, strongly deleterious mutations show the biggest difference between ploidy levels, and this effect diminishes for moderately and mildly deleterious mutations. We further show that the proportion of nonsynonymous mutations that are deleterious differs between the two co-resident subgenomes in the allopolyploids, suggesting that homoeologous masking acts unequally between subgenomes. Our results provide a genome-wide perspective on classic notions of the significance of gene duplication that likely are broadly applicable to allopolyploids, with implications for our understanding of the evolutionary fate of deleterious mutations. Finally, we note that some measures of selection (e.g. dN/dS, πN/πS) may be biased when species of different ploidy levels are compared.

Overcoming constraints on the detection of recessive selection in human genes from population frequency data

The identification of genes that evolve under recessive natural selection is a long-standing goal of population genetics research that has important applications to the discovery of genes associated with disease. We found that commonly used methods to evaluate selective constraint at the gene level are highly sensitive to genes under heterozygous selection but ubiquitously fail to detect recessively evolving genes. Additionally, more sophisticated likelihood-based methods designed to detect recessivity similarly lack power for a human gene of realistic length from current population sample sizes. However, extensive simulations suggested that recessive genes may be detectable in aggregate. Here, we offer a method informed by population genetics simulations designed to detect recessive purifying selection in gene sets. Applying this to empirical gene sets produced significant enrichments for strong recessive selection in genes previously inferred to be under recessive selection in a consanguineous cohort and in genes involved in autosomal recessive monogenic disorders.

Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species

About 50 y ago, Crow and Kimura [An Introduction to Population Genetics Theory (1970)] and Ohta and Kimura [Genet. Res. 22, 201-204 (1973)] laid the foundations of conservation genetics by predicting the relationship between population size and genetic marker diversity. This work sparked an enormous research effort investigating the importance of population dynamics, in particular small population size, for population mean performance, population viability, and evolutionary potential. In light of a recent perspective [J. C. Teixeira, C. D. Huber, Proc. Natl. Acad. Sci. U.S.A. 118, 10 (2021)] that challenges some fundamental assumptions in conservation genetics, it is timely to summarize what the field has achieved, what robust patterns have emerged, and worthwhile future research directions. We consider theory and methodological breakthroughs that have helped management, and we outline some fundamental and applied challenges for conservation genetics.