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

Genomic evidence for inbreeding depression and purging of deleterious genetic variation in Indian tigers

Increasing habitat fragmentation leads to wild populations becoming small, isolated, and threatened by inbreeding depression. However, small populations may be able to purge recessive deleterious alleles as they become expressed in homozygotes, thus reducing inbreeding depression and increasing population viability. We used whole-genome sequences from 57 tigers to estimate individual inbreeding and mutation load in a small-isolated and two large-connected populations in India. As expected, the small-isolated population had substantially higher average genomic inbreeding (FROH = 0.57) than the large-connected (FROH = 0.35 and FROH = 0.46) populations. The small-isolated population had the lowest loss-of-function mutation load, likely due to purging of highly deleterious recessive mutations. The large populations had lower missense mutation loads than the small-isolated population, but were not identical, possibly due to different demographic histories. While the number of the loss-of-function alleles in the small-isolated population was lower, these alleles were at higher frequencies and homozygosity than in the large populations. Together, our data and analyses provide evidence of 1) high mutation load, 2) purging, and 3) the highest predicted inbreeding depression, despite purging, in the small-isolated population. Frequency distributions of damaging and neutral alleles uncover genomic evidence that purifying selection has removed part of the mutation load across Indian tiger populations. These results provide genomic evidence for purifying selection in both small and large populations, but also suggest that the remaining deleterious alleles may have inbreeding-associated fitness costs. We suggest that genetic rescue from sources selected based on genome-wide differentiation could offset any possible impacts of inbreeding depression.

The crucial role of genome-wide genetic variation in conservation

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis.

The crucial role of genome-wide genetic variation in conservation

The unprecedented rate of extinction calls for efficient use of genetics to help conserve biodiversity. Several recent genomic and simulation-based studies have argued that the field of conservation biology has placed too much focus on conserving genome-wide genetic variation, and that the field should instead focus on managing the subset of functional genetic variation that is thought to affect fitness. Here, we critically evaluate the feasibility and likely benefits of this approach in conservation. We find that population genetics theory and empirical results show that conserving genome-wide genetic variation is generally the best approach to prevent inbreeding depression and loss of adaptive potential from driving populations toward extinction. Focusing conservation efforts on presumably functional genetic variation will only be feasible occasionally, often misleading, and counterproductive when prioritized over genome-wide genetic variation. Given the increasing rate of habitat loss and other environmental changes, failure to recognize the detrimental effects of lost genome-wide genetic variation on long-term population viability will only worsen the biodiversity crisis.

Sex differences in deleterious mutational effects in Drosophila melanogaster: combining quantitative and population genetic insights

Fitness effects of deleterious mutations can differ between females and males due to: (i) sex differences in the strength of purifying selection; and (ii) sex differences in ploidy. Although sex differences in fitness effects have important broader implications (e.g., for the evolution of sex and lifespan), few studies have quantified their scope. Those that have belong to one of two distinct empirical traditions: (i) quantitative genetics, which focusses on multi-locus genetic variances in each sex, but is largely agnostic about their genetic basis; and (ii) molecular population genetics, which focusses on comparing autosomal and X-linked polymorphism, but is poorly suited for inferring contemporary sex differences. Here, we combine both traditions to present a comprehensive analysis of female and male adult reproductive fitness among 202 outbred, laboratory-adapted, hemiclonal genomes of Drosophila melanogaster. While we find no clear evidence for sex differences in the strength of purifying selection, sex differences in ploidy generate multiple signals of enhanced purifying selection for X-linked loci. These signals are present in quantitative genetic metrics-i.e., a disproportionate contribution of the X to male (but not female) fitness variation-and population genetic metrics-i.e., steeper regressions of an allele's average fitness effect on its frequency, and proportionally less nonsynonymous polymorphism on the X than autosomes. Fitting our data to models for both sets of metrics, we infer that deleterious alleles are partially recessive. Given the often-large gap between quantitative and population genetic estimates of evolutionary parameters, our study showcases the benefits of combining genomic and fitness data when estimating such parameters.

Genomic signatures of inbreeding and mutation load in a threatened rattlesnake

Theory predicts that threatened species living in small populations will experience high levels of inbreeding that will increase their genetic load, but recent work suggests that the impact of load may be minimized by purging resulting from long-term population bottlenecks. Empirical studies that examine this idea using genome-wide estimates of inbreeding and genetic load in threatened species are limited. Here we use individual genome resequencing data to compare levels of inbreeding, levels of genetic load (estimated as mutation load) and population history in threatened Eastern massasauga rattlesnakes (Sistrurus catenatus), which exist in small isolated populations, and closely related yet outbred Western massasauga rattlesnakes (Sistrurus tergeminus). In terms of inbreeding, S. catenatus genomes had a greater number of runs of homozygosity of varying sizes, indicating sustained inbreeding through repeated bottlenecks when compared to S. tergeminus. At the species level, outbred S. tergeminus had higher genome-wide levels of mutation load in the form of greater numbers of derived deleterious mutations compared to S. catenatus, presumably due to long-term purging of deleterious mutations in S. catenatus. In contrast, mutations that escaped species-level drift effects within S. catenatus populations were in general more frequent and more often found in homozygous genotypes than in S. tergeminus, suggesting a reduced efficiency of purifying selection in smaller S. catenatus populations for most mutations. Our results support an emerging idea that the historical demography of a threatened species has a significant impact on the type of genetic load present, which impacts implementation of conservation actions such as genetic rescue.

Overdominant Mutations Restrict Adaptive Loss of Heterozygosity at Linked Loci

Loss of heterozygosity is a common mode of adaptation in asexual diploid populations. Because mitotic recombination frequently extends the full length of a chromosome arm, the selective benefit of loss of heterozygosity may be constrained by linked heterozygous mutations. In a previous laboratory evolution experiment with diploid yeast, we frequently observed homozygous mutations in the WHI2 gene on the right arm of Chromosome XV. However, when heterozygous mutations arose in the STE4 gene, another common target on Chromosome XV, loss of heterozygosity at WHI2 was not observed. Here, we show that mutations at WHI2 are partially dominant and that mutations at STE4 are overdominant. We test whether beneficial heterozygous mutations at these two loci interfere with one another by measuring loss of heterozygosity at WHI2 over 1,000 generations for ∼300 populations that differed initially only at STE4 and WHI2. We show that the presence of an overdominant mutation in STE4 reduces, but does not eliminate, loss of heterozygosity at WHI2. By sequencing 40 evolved clones, we show that populations with linked overdominant and partially dominant mutations show less parallelism at the gene level, more varied evolutionary outcomes, and increased rates of aneuploidy. Our results show that the degree of dominance and the phasing of heterozygous beneficial mutations can constrain loss of heterozygosity along a chromosome arm, and that conflicts between partially dominant and overdominant mutations can affect evolutionary outcomes.

The contribution of mutation and selection to multivariate quantitative genetic variance in an outbred population of Drosophila serrata

Genetic variance is not equal for all multivariate combinations of traits. This inequality, in which some combinations of traits have abundant genetic variation while others have very little, biases the rate and direction of multivariate phenotypic evolution. However, we still understand little about what causes genetic variance to differ among trait combinations. Here, we investigate the relative roles of mutation and selection in determining the genetic variance of multivariate phenotypes. We accumulated mutations in an outbred population of Drosophila serrata and analyzed wing shape and size traits for over 35,000 flies to simultaneously estimate the additive genetic and additive mutational (co)variances. This experimental design allowed us to gain insight into the phenotypic effects of mutation as they arise and come under selection in naturally outbred populations. Multivariate phenotypes associated with more (less) genetic variance were also associated with more (less) mutational variance, suggesting that differences in mutational input contribute to differences in genetic variance. However, mutational correlations between traits were stronger than genetic correlations, and most mutational variance was associated with only one multivariate trait combination, while genetic variance was relatively more equal across multivariate traits. Therefore, selection is implicated in breaking down trait covariance and resulting in a different pattern of genetic variance among multivariate combinations of traits than that predicted by mutation and drift. Overall, while low mutational input might slow evolution of some multivariate phenotypes, stabilizing selection appears to reduce the strength of evolutionary bias introduced by pleiotropic mutation.

Large-scale genomic analysis reveals the genetic cost of chicken domestication

BACKGROUND

Species domestication is generally characterized by the exploitation of high-impact mutations through processes that involve complex shifting demographics of domesticated species. These include not only inbreeding and artificial selection that may lead to the emergence of evolutionary bottlenecks, but also post-divergence gene flow and introgression. Although domestication potentially affects the occurrence of both desired and undesired mutations, the way wild relatives of domesticated species evolve and how expensive the genetic cost underlying domestication is remain poorly understood. Here, we investigated the demographic history and genetic load of chicken domestication.

RESULTS

We analyzed a dataset comprising over 800 whole genomes from both indigenous chickens and wild jungle fowls. We show that despite having a higher genetic diversity than their wild counterparts (average π, 0.00326 vs. 0.00316), the red jungle fowls, the present-day domestic chickens experienced a dramatic population size decline during their early domestication. Our analyses suggest that the concomitant bottleneck induced 2.95% more deleterious mutations across chicken genomes compared with red jungle fowls, supporting the "cost of domestication" hypothesis. Particularly, we find that 62.4% of deleterious SNPs in domestic chickens are maintained in heterozygous states and masked as recessive alleles, challenging the power of modern breeding programs to effectively eliminate these genetic loads. Finally, we suggest that positive selection decreases the incidence but increases the frequency of deleterious SNPs in domestic chicken genomes.

CONCLUSION

This study reveals a new landscape of demographic history and genomic changes associated with chicken domestication and provides insight into the evolutionary genomic profiles of domesticated animals managed under modern human selection.

Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution

Similar forms often evolve repeatedly in nature, raising long-standing questions about the underlying mechanisms. Here, we use repeated evolution in stickleback to identify a large set of genomic loci that change recurrently during colonization of freshwater habitats by marine fish. The same loci used repeatedly in extant populations also show rapid allele frequency changes when new freshwater populations are experimentally established from marine ancestors. Marked genotypic and phenotypic changes arise within 5 years, facilitated by standing genetic variation and linkage between adaptive regions. Both the speed and location of changes can be predicted using empirical observations of recurrence in natural populations or fundamental genomic features like allelic age, recombination rates, density of divergent loci, and overlap with mapped traits. A composite model trained on these stickleback features can also predict the location of key evolutionary loci in Darwin's finches, suggesting that similar features are important for evolution across diverse taxa.

Genetic load has potential in large populations but is realized in small inbred populations

Populations with higher genetic diversity and larger effective sizes have greater evolutionary capacity (i.e., adaptive potential) to respond to ecological stressors. We are interested in how the variation captured in protein-coding genes fluctuates relative to overall genomic diversity and whether smaller populations suffer greater costs due to their genetic load of deleterious mutations compared with larger populations. We analyzed individual whole-genome sequences (N = 74) from three different populations of Montezuma quail (Cyrtonyx montezumae), a small ground-dwelling bird that is sustainably harvested in some portions of its range but is of conservation concern elsewhere. Our historical demographic results indicate that Montezuma quail populations in the United States exhibit low levels of genomic diversity due in large part to long-term declines in effective population sizes over nearly a million years. The smaller and more isolated Texas population is significantly more inbred than the large Arizona and the intermediate-sized New Mexico populations we surveyed. The Texas gene pool has a significantly smaller proportion of strongly deleterious variants segregating in the population compared with the larger Arizona gene pool. Our results demonstrate that even in small populations, highly deleterious mutations are effectively purged and/or lost due to drift. However, we find that in small populations the realized genetic load is elevated because of inbreeding coupled with a higher frequency of slightly deleterious mutations that are manifested in homozygotes. Overall, our study illustrates how population genomics can be used to proactively assess both neutral and functional aspects of contemporary genetic diversity in a conservation framework while simultaneously considering deeper demographic histories.

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.

The population genetics of ploidy change in unicellular fungi

Changes in ploidy are a significant type of genetic variation, describing the number of chromosome sets per cell. Ploidy evolves in natural populations, clinical populations, and lab experiments, particularly in fungi. Despite a long history of theoretical work on this topic, predicting how ploidy will evolve has proven difficult, as it is often unclear why one ploidy state outperforms another. Here, we review what is known about contemporary ploidy evolution in diverse fungal species through the lens of population genetics. As with typical genetic variants, ploidy evolution depends on the rate that new ploidy states arise by mutation, natural selection on alternative ploidy states, and random genetic drift. However, ploidy variation also has unique impacts on evolution, with the potential to alter chromosomal stability, the rate and patterns of point mutation, and the nature of selection on all loci in the genome. We discuss how ploidy evolution depends on these general and unique factors and highlight areas where additional experimental evidence is required to comprehensively explain the ploidy transitions observed in the field and the lab.

Negative selection on human genes underlying inborn errors depends on disease outcome and both the mode and mechanism of inheritance

Genetic variants underlying life-threatening diseases, being unlikely to be transmitted to the next generation, are gradually and selectively eliminated from the population through negative selection. We study the determinants of this evolutionary process in human genes underlying monogenic diseases by comparing various negative selection scores and an integrative approach, CoNeS, at 366 loci underlying inborn errors of immunity (IEI). We find that genes underlying autosomal dominant (AD) or X-linked IEI have stronger negative selection scores than those underlying autosomal recessive (AR) IEI, whose scores are not different from those of genes not known to be disease causing. Nevertheless, genes underlying AR IEI that are lethal before reproductive maturity with complete penetrance have stronger negative selection scores than other genes underlying AR IEI. We also show that genes underlying AD IEI by loss of function have stronger negative selection scores than genes underlying AD IEI by gain of function, while genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. These results are replicated in 1,140 genes underlying inborn errors of neurodevelopment. Finally, we propose a supervised classifier, SCoNeS, which predicts better than state-of-the-art approaches whether a gene is more likely to underlie an AD or AR disease. The clinical outcomes of monogenic inborn errors, together with their mode and mechanisms of inheritance, determine the levels of negative selection at their corresponding loci. Integrating scores of negative selection may facilitate the prioritization of candidate genes and variants in patients suspected to carry an inborn error.

Selective Interference and the Evolution of Sex

Selection acts upon genes linked together on chromosomes. This physical connection reduces the efficiency by which selection can act because, in the absence of sex, alleles must rise and fall together in frequency with the genome in which they are found. This selective interference underlies such phenomena as clonal interference and Muller’s Ratchet and is broadly termed Hill-Robertson interference. In this review, I examine the potential for selective interference to account for the evolution and maintenance of sex, discussing the positive and negative evidence from both theoretical and empirical studies, and highlight the gaps that remain.

Background Selection Does Not Mimic the Patterns of Genetic Diversity Produced by Selective Sweeps

It is increasingly evident that natural selection plays a prominent role in shaping patterns of diversity across the genome. The most commonly studied modes of natural selection are positive selection and negative selection, which refer to directional selection for and against derived mutations, respectively. Positive selection can result in hitchhiking events, in which a beneficial allele rapidly replaces all others in the population, creating a valley of diversity around the selected site along with characteristic skews in allele frequencies and linkage disequilibrium among linked neutral polymorphisms. Similarly, negative selection reduces variation not only at selected sites but also at linked sites, a phenomenon called background selection (BGS). Thus, discriminating between these two forces may be difficult, and one might expect efforts to detect hitchhiking to produce an excess of false positives in regions affected by BGS. Here, we examine the similarity between BGS and hitchhiking models via simulation. First, we show that BGS may somewhat resemble hitchhiking in simplistic scenarios in which a region constrained by negative selection is flanked by large stretches of unconstrained sites, echoing previous results. However, this scenario does not mirror the actual spatial arrangement of selected sites across the genome. By performing forward simulations under more realistic scenarios of BGS, modeling the locations of protein-coding and conserved noncoding DNA in real genomes, we show that the spatial patterns of variation produced by BGS rarely mimic those of hitchhiking events. Indeed, BGS is not substantially more likely than neutrality to produce false signatures of hitchhiking. This holds for simulations modeled after both humans and Drosophila, and for several different demographic histories. These results demonstrate that appropriately designed scans for hitchhiking need not consider BGS's impact on false-positive rates. However, we do find evidence that BGS increases the false-negative rate for hitchhiking, an observation that demands further investigation.

The Impact of Recessive Deleterious Variation on Signals of Adaptive Introgression in Human Populations

Admixture with archaic hominins has altered the landscape of genomic variation in modern human populations. Several gene regions have been identified previously as candidates of adaptive introgression (AI) that facilitated human adaptation to specific environments. However, simulation-based studies have suggested that population genetic processes other than adaptive mutations, such as heterosis from recessive deleterious variants private to populations before admixture, can also lead to patterns in genomic data that resemble AI. The extent to which the presence of deleterious variants affect the false-positive rate and the power of current methods to detect AI has not been fully assessed. Here, we used extensive simulations under parameters relevant for human evolution to show that recessive deleterious mutations can increase the false positive rates of tests for AI compared to models without deleterious variants, especially when the recombination rates are low. We next examined candidates of AI in modern humans identified from previous studies, and show that 24 out of 26 candidate regions remain significant, even when deleterious variants are included in the null model. However, two AI candidate genes, HYAL2 and HLA, are particularly susceptible to high false positive signals of AI due to recessive deleterious mutations. These genes are located in regions of the human genome with high exon density together with low recombination rate, factors that we show increase the rate of false-positives due to recessive deleterious mutations. Although the combination of such parameters is rare in the human genome, caution is warranted in such regions, as well as in other species with more compact genomes and/or lower recombination rates. In sum, our results suggest that recessive deleterious mutations cannot account for the signals of AI in most, but not all, of the top candidates for AI in humans, suggesting they may be genuine signals of adaptation.

Purging of highly deleterious mutations through severe bottlenecks in Alpine ibex

Human activity has caused dramatic population declines in many wild species. The resulting bottlenecks have a profound impact on the genetic makeup of a species with unknown consequences for health. A key genetic factor for species survival is the evolution of deleterious mutation load, but how bottleneck strength and mutation load interact lacks empirical evidence. We analyze 60 complete genomes of six ibex species and the domestic goat. We show that historic bottlenecks rather than the current conservation status predict levels of genome-wide variation. By analyzing the exceptionally well-characterized population bottlenecks of the once nearly extinct Alpine ibex, we find genomic evidence of concurrent purging of highly deleterious mutations but accumulation of mildly deleterious mutations. This suggests that recolonization bottlenecks induced both relaxed selection and purging, thus reshaping the landscape of deleterious mutation load. Our findings highlight that even populations of ~1000 individuals can accumulate mildly deleterious mutations. Conservation efforts should focus on preventing population declines below such levels to ensure long-term survival of species.

Although there is extensive theory predicting the effects of population bottlenecks on mutation load, there is little empirical evidence from recent bottlenecks. Here, Grossen et al. compare the consequences of population bottlenecks in six ibex species for genome-wide variation and mutation load.

Estimation of population genetic parameters using an EM algorithm and sequence data from experimental evolution populations

MOTIVATION

Evolve and resequence (E&R) experiments show promise in capturing real-time evolution at genome-wide scales, enabling the assessment of allele frequency changes SNPs in evolving populations and thus the estimation of population genetic parameters in the Wright-Fisher model (WF) that quantify the selection on SNPs. Currently, these analyses face two key difficulties: the numerous SNPs in E&R data and the frequent unreliability of estimates. Hence, a methodology for efficiently estimating WF parameters is needed to understand the evolutionary processes that shape genomes.

RESULTS

We developed a novel method for estimating WF parameters (EMWER), by applying an expectation maximization algorithm to the Kolmogorov forward equation associated with the WF model diffusion approximation. EMWER was used to infer the effective population size, selection coefficients and dominance parameters from E&R data. Of the methods examined, EMWER was the most efficient method for selection strength estimation in multi-core computing environments, estimating both selection and dominance with accurate confidence intervals. We applied EMWER to E&R data from experimental Drosophila populations adapting to thermally fluctuating environments and found a common selection affecting allele frequency of many SNPs within the cosmopolitan In(3R)P inversion. Furthermore, this application indicated that many of beneficial alleles in this experiment are dominant.

AVAILABILITY AND IMPLEMENTATION

Our C++ implementation of 'EMWER' is available at https://github.com/kojikoji/EMWER.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mating system impacts the genetic architecture of adaptation to heterogeneous environments

Self-fertilisation has consequences for variation across the genome as it reduces effective population size, effect recombination rates and pollen flow, with implications for local adaptation. We conducted simulations of divergent stabilising selection on a quantitative trait with drift, pollen flow, mutation, recombination and different outcrossing rates. We quantified trait divergence and the genetic architecture of adaptation. We conducted an F_ST outlier analysis to identify candidate loci and quantified the impact of mating system on detectability. Selfing promoted trait divergence mainly through reductions in pollen flow. Moreover, trait architecture became more diffuse with selfing. Average effect size of trait loci was lower, while the number of loci, and their clustering distance increased. The genetic architecture of selfers was also more diffuse than outcrossers for equivalent migration rates. However, when deleterious alleles were included, architectures became more concentrated in selfers, likely to be because of reductions in population size caused by mutational meltdown and impacts of background selection on N_e . Our simulations demonstrate that mating system has important impacts on adaptive divergence of traits and the genetic landscape underlying that divergence. Selfing has a significant effect on detectability of regions of the genome important for adaptation because of neutral divergence and diffuse trait architecture.

Thinking About the Evolution of Complex Traits in the Era of Genome-Wide Association Studies

Many traits of interest are highly heritable and genetically complex, meaning that much of the variation they exhibit arises from differences at numerous loci in the genome. Complex traits and their evolution have been studied for more than a century, but only in the last decade have genome-wide association studies (GWASs) in humans begun to reveal their genetic basis. Here, we bring these threads of research together to ask how findings from GWASs can further our understanding of the processes that give rise to heritable variation in complex traits and of the genetic basis of complex trait evolution in response to changing selection pressures (i.e., of polygenic adaptation). Conversely, we ask how evolutionary thinking helps us to interpret findings from GWASs and informs related efforts of practical importance.

Effect of partial selfing and polygenic selection on establishment in a new habitat

This article analyzes how partial selfing in a large source population influences its ability to colonize a new habitat via the introduction of a few founder individuals. Founders experience inbreeding depression due to partially recessive deleterious alleles as well as maladaptation to the new environment due to selection on a large number of additive loci. I first introduce a simplified version of the inbreeding history model to characterize mutation‐selection balance in a large, partially selfing source population under selection involving multiple nonidentical loci. I then use individual‐based simulations to study the eco‐evolutionary dynamics of founders establishing in the new habitat under a model of hard selection. The study explores how selfing rate shapes establishment probabilities of founders via effects on both inbreeding depression and adaptability to the new environment, and also distinguishes the effects of selfing on the initial fitness of founders from its effects on the long‐term adaptive response of the populations they found. A high rate of (but not complete) selfing is found to aid establishment over a wide range of parameters, even in the absence of mate limitation. The sensitivity of the results to assumptions about the nature of polygenic selection is discussed.

Removal of alleles by genome editing (RAGE) against deleterious load

BACKGROUND

In this paper, we simulate deleterious load in an animal breeding program, and compare the efficiency of genome editing and selection for decreasing it. Deleterious variants can be identified by bioinformatics screening methods that use sequence conservation and biological prior information about protein function. However, once deleterious variants have been identified, how can they be used in breeding?

RESULTS

We simulated a closed animal breeding population that is subject to both natural selection against deleterious load and artificial selection for a quantitative trait representing the breeding goal. Deleterious load was polygenic and was due to either codominant or recessive variants. We compared strategies for removal of deleterious alleles by genome editing (RAGE) to selection against carriers. When deleterious variants were codominant, the best strategy for prioritizing variants was to prioritize low-frequency variants. When deleterious variants were recessive, the best strategy was to prioritize variants with an intermediate frequency. Selection against carriers was inefficient when variants were codominant, but comparable to editing one variant per sire when variants were recessive.

CONCLUSIONS

Genome editing of deleterious alleles reduces deleterious load, but requires the simultaneous editing of multiple deleterious variants in the same sire to be effective when deleterious variants are recessive. In the short term, selection against carriers is a possible alternative to genome editing when variants are recessive. Our results suggest that, in the future, there is the potential to use RAGE against deleterious load in animal breeding.

Measuring intolerance to mutation in human genetics

In numerous applications, from working with animal models to mapping the genetic basis of human disease susceptibility, knowing whether a single disrupting mutation in a gene is likely to be deleterious is useful. With this goal in mind, a number of measures have been developed to identify genes in which protein-truncating variants (PTVs), or other types of mutations, are absent or kept at very low frequency in large population samples-genes that appear 'intolerant' to mutation. One measure in particular, the probability of being loss-of-function intolerant (pLI), has been widely adopted. This measure was designed to classify genes into three categories, null, recessive and haploinsufficient, on the basis of the contrast between observed and expected numbers of PTVs. Such population-genetic approaches can be useful in many applications. As we clarify, however, they reflect the strength of selection acting on heterozygotes and not dominance or haploinsufficiency.

Understanding the Hidden Complexity of Latin American Population Isolates

Most population isolates examined to date were founded from a single ancestral population. Consequently, there is limited knowledge about the demographic history of admixed population isolates. Here we investigate genomic diversity of recently admixed population isolates from Costa Rica and Colombia and compare their diversity to a benchmark population isolate, the Finnish. These Latin American isolates originated during the 16th century from admixture between a few hundred European males and Amerindian females, with a limited contribution from African founders. We examine whole-genome sequence data from 449 individuals, ascertained as families to build mutigenerational pedigrees, with a mean sequencing depth of coverage of approximately 36×. We find that Latin American isolates have increased genetic diversity relative to the Finnish. However, there is an increase in the amount of identity by descent (IBD) segments in the Latin American isolates relative to the Finnish. The increase in IBD segments is likely a consequence of a very recent and severe population bottleneck during the founding of the admixed population isolates. Furthermore, the proportion of the genome that falls within a long run of homozygosity (ROH) in Costa Rican and Colombian individuals is significantly greater than that in the Finnish, suggesting more recent consanguinity in the Latin American isolates relative to that seen in the Finnish. Lastly, we find that recent consanguinity increased the number of deleterious variants found in the homozygous state, which is relevant if deleterious variants are recessive. Our study suggests that there is no single genetic signature of a population isolate.

Deleterious variation shapes the genomic landscape of introgression

While it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how gene flow affects and is affected by the dynamics of deleterious variation. Here we use population genetic simulations to examine how gene flow impacts deleterious variation under a variety of demographic scenarios, mating systems, dominance coefficients, and recombination rates. Our results show that admixture between populations can temporarily reduce the genetic load of smaller populations and cause increases in the frequency of introgressed ancestry, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. Together, these factors lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30–75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models of admixture include both demography and deleterious variation before invoking other mechanisms to explain unusual patterns of genetic variation.

Individuals from distinct populations sometimes will produce fertile offspring and will exchange genetic material in a process called hybridization. Genomes of hybrid individuals often show non-random patterns of hybrid ancestry across the genome, where some regions have a high frequency of ancestry from the second population and other regions have less. Typically, this pattern has been attributed to adaptive introgression, where beneficial genetic variants are passed from one population to the other, or to genomic incompatibilities between these distinct species. However, other mechanisms could lead to these heterogeneous patterns of ancestry in hybrids. Here we use simulations to investigate whether deleterious mutations affect the patterns of introgressed ancestry across genomes. We show that when ancestry from a larger population is added to a smaller population, the ancestry from the larger population dramatically increases in frequency because it carries fewer deleterious mutations. This occurs even in the absence of beneficial mutations in either population. Additionally, we show that differences in sex chromosome evolution relative to autosomes, or differences in mating system, can affect patterns of introgression in similar ways. Our study argues that deleterious mutations should be included in population genetic models used to identify unusual regions of the genome that appear to be under selection in hybrids.

The interaction between sex-specific selection and local adaptation in species without separate sexes

Local adaptation in hermaphrodite species can be based on a variety of fitness components, including survival, as well as both female and male sex-functions within individuals. When selection via female and male fitness components varies spatially (e.g. due to environmental heterogeneity), local adaptation will depend, in part, on variation in selection through each fitness component, and the extent to which genetic trade-offs between sex-functions maintain genetic variation necessary for adaptation. Local adaptation will also depend on the hermaphrodite mating system because self-fertilization alters several key factors influencing selection and the maintenance of genetic variance underlying trade-offs between the sex-functions (sexually antagonistic polymorphism). As a first step to guide intuition regarding sex-specific adaptation in hermaphrodites, we develop a simple theoretical model incorporating the essential features of hermaphrodite mating and adaptation in a spatially heterogeneous environment, and explore the interaction between sex-specific selection, self-fertilization and local adaptation. Our results suggest that opportunities for sex-specific local adaptation in hermaphrodites depend strongly on the extent of self-fertilization and inbreeding depression. Using our model as a conceptual framework, we provide a broad overview of the literature on sex-specific selection and local adaptation in hermaphroditic plants and animals, emphasizing promising future directions in light of our theoretical predictions.This article is part of the theme issue 'Linking local adaptation with the evolution of sex differences'.

Mutation load dynamics during environmentally-driven range shifts

The fitness of spatially expanding species has been shown to decrease over time and space, but specialist species tracking their changing environment and shifting their range accordingly have been little studied. We use individual-based simulations and analytical modeling to compare the impact of range expansions and range shifts on genetic diversity and fitness loss, as well as the ability to recover fitness after either a shift or expansion. We find that the speed of a shift has a strong impact on fitness evolution. Fastest shifts show the strongest fitness loss per generation, but intermediate shift speeds lead to the strongest fitness loss per geographic distance. Range shifting species lose fitness more slowly through time than expanding species, however, their fitness measured at equal geographic distances from the source of expansion can be considerably lower. These counter-intuitive results arise from the combination of time over which selection acts and mutations enter the system. Range shifts also exhibit reduced fitness recovery after a geographic shift and may result in extinction, whereas range expansions can persist from the core of the species range. The complexity of range expansions and range shifts highlights the potential for severe consequences of environmental change on species survival.

Gene expression drives the evolution of dominance

Dominance is a fundamental concept in molecular genetics and has implications for understanding patterns of genetic variation, evolution, and complex traits. However, despite its importance, the degree of dominance in natural populations is poorly quantified. Here, we leverage multiple mating systems in natural populations of Arabidopsis to co-estimate the distribution of fitness effects and dominance coefficients of new amino acid changing mutations. We find that more deleterious mutations are more likely to be recessive than less deleterious mutations. Further, this pattern holds across gene categories, but varies with the connectivity and expression patterns of genes. Our work argues that dominance arises as a consequence of the functional importance of genes and their optimal expression levels.

Dominance is difficult to measure in natural populations as it is confounded with fitness. Here, Huber et al. developed a new approach to co-estimate dominance and selection coefficients, and found that the observed relationship is best fit by a new model of dominance based on gene expression level.

It's not magic - Hsp90 and its effects on genetic and epigenetic variation

Canalization, or phenotypic robustness in the face of environmental and genetic perturbation, is an emergent property of living systems. Although this phenomenon has long been recognized, its molecular underpinnings have remained enigmatic until recently. Here, we review the contributions of the molecular chaperone Hsp90, a protein that facilitates the folding of many key regulators of growth and development, to canalization of phenotype - and de-canalization in times of stress - drawing on studies in eukaryotes as diverse as baker's yeast, mouse ear cress, and blind Mexican cavefish. Hsp90 is a hub of hubs that interacts with many so-called 'client proteins,' which affect virtually every aspect of cell signaling and physiology. As Hsp90 facilitates client folding and stability, it can epistatically suppress or enable the expression of genetic variants in its clients and other proteins that acquire client status through mutation. Hsp90's vast interaction network explains the breadth of its phenotypic reach, including Hsp90-dependent de novo mutations and epigenetic effects on gene regulation. Intrinsic links between environmental stress and Hsp90 function thus endow living systems with phenotypic plasticity in fluctuating environments. As environmental perturbations alter Hsp90 function, they also alter Hsp90's interaction with its client proteins, thereby re-wiring networks that determine the genotype-to-phenotype map. Ensuing de-canalization of phenotype creates phenotypic diversity that is not simply stochastic, but often has an underlying genetic basis. Thus, extreme phenotypes can be selected, and assimilated so that they no longer require environmental stress to manifest. In addition to acting on standing genetic variation, Hsp90 perturbation has also been linked to increased frequency of de novo variation and several epigenetic phenomena, all with the potential to generate heritable phenotypic change. Here, we aim to clarify and discuss the multiple means by which Hsp90 can affect phenotype and possibly evolutionary change, and identify their underlying common feature: at its core, Hsp90 interacts epistatically through its chaperone function with many other genes and their gene products. Its influence on phenotypic diversification is thus not magic but rather a fundamental property of genetics.

Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations

Heterosis, the superiority of hybrids over their parents for quantitative traits, represents a crucial issue in plant and animal breeding as well as evolutionary biology. Heterosis has given rise to countless genetic, genomic and molecular studies, but has rarely been investigated from the point of view of systems biology. We hypothesized that heterosis is an emergent property of living systems resulting from frequent concave relationships between genotypic variables and phenotypes, or between different phenotypic levels. We chose the enzyme-flux relationship as a model of the concave genotype-phenotype (GP) relationship, and showed that heterosis can be easily created in the laboratory. First, we reconstituted in vitro the upper part of glycolysis. We simulated genetic variability of enzyme activity by varying enzyme concentrations in test tubes. Mixing the content of "parental" tubes resulted in "hybrids," whose fluxes were compared to the parental fluxes. Frequent heterotic fluxes were observed, under conditions that were determined analytically and confirmed by computer simulation. Second, to test this model in a more realistic situation, we modeled the glycolysis/fermentation network in yeast by considering one input flux, glucose, and two output fluxes, glycerol and acetaldehyde. We simulated genetic variability by randomly drawing parental enzyme concentrations under various conditions, and computed the parental and hybrid fluxes using a system of differential equations. Again we found that a majority of hybrids exhibited positive heterosis for metabolic fluxes. Cases of negative heterosis were due to local convexity between certain enzyme concentrations and fluxes. In both approaches, heterosis was maximized when the parents were phenotypically close and when the distributions of parental enzyme concentrations were contrasted and constrained. These conclusions are not restricted to metabolic systems: they only depend on the concavity of the GP relationship, which is commonly observed at various levels of the phenotypic hierarchy, and could account for the pervasiveness of heterosis.

Population Genomics of Herbicide Resistance: Adaptation via Evolutionary Rescue

The evolution of herbicide resistance in weed populations is a highly replicated example of adaptation surmounting the race against extinction, but the factors determining its rate and nature remain poorly understood. Here, we explore theory and empirical evidence for the importance of population genetic parameters-including effective population size, dominance, mutational target size, and gene flow-in influencing the probability and mode of herbicide resistance adaptation and its variation across species. We compiled data on the number of resistance mutations across populations for 79 herbicide-resistant species. Our findings are consistent with theoretical predictions that self-fertilization reduces resistance adaptation from standing variation within populations, but increases independent adaptation across populations. Furthermore, we provide evidence for a ploidy-mating system interaction that may reflect trade-offs in polyploids between increased effective population size and greater masking of beneficial mutations. We highlight the power of population genomic approaches to provide insights into the evolutionary dynamics of herbicide resistance with important implications for understanding the limits of adaptation.

A population genetic interpretation of GWAS findings for human quantitative traits

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes-notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10-3.

Bioinformatically predicted deleterious mutations reveal complementation in the interior spruce hybrid complex

BACKGROUND

Mutation load is expected to be reduced in hybrids via complementation of deleterious alleles. While local adaptation of hybrids confounds phenotypic tests for reduced mutation load, it may be possible to assess variation in load by analyzing the distribution of putatively deleterious alleles. Here, we use this approach in the interior spruce (Picea glauca x P. engelmannii) hybrid complex, a group likely to suffer from high mutation load and in which hybrids exhibit local adaptation to intermediate conditions. We used PROVEAN to bioinformatically predict whether non-synonymous alleles are deleterious, based on conservation of the position and abnormality of the amino acid change.

RESULTS

As expected, we found that predicted deleterious alleles were at lower average allele frequencies than alleles not predicted to be deleterious. We were unable to detect a phenotypic effect on juvenile growth rate of the many rare alleles predicted to be deleterious. Both the proportion of alleles predicted to be deleterious and the proportion of loci homozygous for predicted deleterious alleles were higher in P. engelmannii (Engelmann spruce) than in P. glauca (white spruce), due to higher diversity and frequencies of rare alleles in Engelmann. Relative to parental species, the proportion of alleles predicted to be deleterious was intermediate in hybrids, and the proportion of loci homozygous for predicted deleterious alleles was lowest.

CONCLUSION

Given that most deleterious alleles are recessive, this suggests that mutation load is reduced in hybrids due to complementation of deleterious alleles. This effect may enhance the fitness of hybrids.

The interplay of demography and selection during maize domestication and expansion

BACKGROUND

The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes.

RESULTS

We investigate these processes using high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize, and four wild teosinte individuals (Zea mays ssp. parviglumis). Genome-wide demographic analyses reveal that maize experienced pronounced declines in effective population size due to both a protracted domestication bottleneck and serial founder effects during post-domestication spread, while parviglumis in the Balsas River Valley experienced population growth. The domestication bottleneck and subsequent spread led to an increase in deleterious alleles in the domesticate compared to the wild progenitor. This cost is particularly pronounced in Andean maize, which has experienced a more dramatic founder event compared to other maize populations. Additionally, we detect introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico, Guatemala, and the southwestern USA, which reduces the prevalence of deleterious alleles likely due to the higher long-term effective population size of teosinte.

CONCLUSIONS

These findings underscore the strong interaction between historical demography and the efficiency of selection and illustrate how domesticated species are particularly useful for understanding these processes. The landscape of deleterious alleles and therefore evolutionary potential is clearly influenced by recent demography, a factor that could bear importantly on many species that have experienced recent demographic shifts.

The interplay of demography and selection during maize domestication and expansion

BACKGROUND

The history of maize has been characterized by major demographic events, including population size changes associated with domestication and range expansion, and gene flow with wild relatives. The interplay between demographic history and selection has shaped diversity across maize populations and genomes.

RESULTS

We investigate these processes using high-depth resequencing data from 31 maize landraces spanning the pre-Columbian distribution of maize, and four wild teosinte individuals (Zea mays ssp. parviglumis). Genome-wide demographic analyses reveal that maize experienced pronounced declines in effective population size due to both a protracted domestication bottleneck and serial founder effects during post-domestication spread, while parviglumis in the Balsas River Valley experienced population growth. The domestication bottleneck and subsequent spread led to an increase in deleterious alleles in the domesticate compared to the wild progenitor. This cost is particularly pronounced in Andean maize, which has experienced a more dramatic founder event compared to other maize populations. Additionally, we detect introgression from the wild teosinte Zea mays ssp. mexicana into maize in the highlands of Mexico, Guatemala, and the southwestern USA, which reduces the prevalence of deleterious alleles likely due to the higher long-term effective population size of teosinte.

CONCLUSIONS

These findings underscore the strong interaction between historical demography and the efficiency of selection and illustrate how domesticated species are particularly useful for understanding these processes. The landscape of deleterious alleles and therefore evolutionary potential is clearly influenced by recent demography, a factor that could bear importantly on many species that have experienced recent demographic shifts.

A two-locus model of selection in autotetraploids: Chromosomal gametic disequilibrium and selection for an adaptive epistatic gene combination

In this paper, we present a two-locus model of selection for an autotetraploid population. We also investigate a measure of disequilibrium that occurs between homologous chromosomes in the diploid gametes of autotetraploids, namely chromosomal gametic disequilibrium. We apply the model and measure of disequilibrium to compare how an adaptive epistatic gene combination is inherited and selected for in an autotetraploid versus diploid population. Autotetraploids are expected to have higher genomic mutation and recombination rates relative to diploids, due to a greater ploidy level. These two processes can work in opposition in terms of selection for adaptive epistatic gene combinations. While a higher genomic mutation rate can generate the alleles that confer an epistatic combination more quickly, a higher recombination rate is expected to break the combination down more quickly. We show that chromosomal gametic disequilibrium in autotetraploids can potentially compensate for less linkage disequilibrium in autotetraploids. We also explore how double reduction affects the inheritance of and selection for an epistatic gene combination. Over all, our analysis provides theoretical evidence that adaptive epistatic combinations can be selected for more efficiently in autotetraploids versus diploids. This may provide insight into empirical work that finds epistasis has a role in causing population differentiation between autotetraploid plant populations.

Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize

Deleterious alleles have long been proposed to play an important role in patterning phenotypic variation and are central to commonly held ideas explaining the hybrid vigor observed in the offspring of a cross between two inbred parents. We test these ideas using evolutionary measures of sequence conservation to ask whether incorporating information about putatively deleterious alleles can inform genomic selection (GS) models and improve phenotypic prediction. We measured a number of agronomic traits in both the inbred parents and hybrids of an elite maize partial diallel population and re-sequenced the parents of the population. Inbred elite maize lines vary for more than 350,000 putatively deleterious sites, but show a lower burden of such sites than a comparable set of traditional landraces. Our modeling reveals widespread evidence for incomplete dominance at these loci, and supports theoretical models that more damaging variants are usually more recessive. We identify haplotype blocks using an identity-by-decent (IBD) analysis and perform genomic prediction analyses in which we weigh blocks on the basis of complementation for segregating putatively deleterious variants. Cross-validation results show that incorporating sequence conservation in genomic selection improves prediction accuracy for grain yield and other fitness-related traits as well as heterosis for those traits. Our results provide empirical support for an important role for incomplete dominance of deleterious alleles in explaining heterosis and demonstrate the utility of incorporating functional annotation in phenotypic prediction and plant breeding.

Heritable Micro-environmental Variance Covaries with Fitness in an Outbred Population of Drosophila serrata

The genetic basis of stochastic variation within a defined environment, and the consequences of such micro-environmental variance for fitness are poorly understood . Using a multigenerational breeding design in Drosophila serrata, we demonstrated that the micro-environmental variance in a set of morphological wing traits in a randomly mating population had significant additive genetic variance in most single wing traits. Although heritability was generally low (<1%), coefficients of additive genetic variance were of a magnitude typical of other morphological traits, indicating that the micro-environmental variance is an evolvable trait. Multivariate analyses demonstrated that the micro-environmental variance in wings was genetically correlated among single traits, indicating that common mechanisms of environmental buffering exist for this functionally related set of traits. In addition, through the dominance genetic covariance between the major axes of micro-environmental variance and fitness, we demonstrated that micro-environmental variance shares a genetic basis with fitness, and that the pattern of selection is suggestive of variance-reducing selection acting on micro-environmental variance.

Estimating the selective effects of heterozygous protein-truncating variants from human exome data

The dispensability of individual genes for viability has interested generations of geneticists. For some genes it is essential to maintain two functional chromosomal copies, while others may tolerate the loss of one or both copies. Exome sequence data from 60,706 individuals provide sufficient observations of rare protein truncating variants (PTVs) to make genome-wide estimates of selection against heterozygous loss of gene function. The cumulative frequency of rare deleterious PTVs is primarily determined by the balance between incoming mutations and purifying selection rather than genetic drift. This enables the estimation of the genome-wide distribution of selection coefficients for heterozygous PTVs and corresponding Bayesian estimates for individual genes. The strength of selection can discriminate the severity, age of onset, and mode of inheritance in Mendelian exome sequencing cases. We find that genes under the strongest selection are enriched in embryonic lethal mouse knockouts, putatively cell-essential genes, Mendelian disease genes, and regulators of transcription. Screening by essentiality, we find a large set of genes under strong selection that likely have critical function but have not yet been extensively annotated in published literature.

A Temporal Perspective on the Interplay of Demography and Selection on Deleterious Variation in Humans

When mutations have small effects on fitness, population size plays an important role in determining the amount and nature of deleterious genetic variation. The extent to which recent population size changes have impacted deleterious variation in humans has been a question of considerable interest and debate. An emerging consensus is that the Out-of-Africa bottleneck and subsequent growth events have been too short to cause meaningful differences in genetic load between populations; though changes in the number and average frequencies of deleterious variants have taken place. To provide more support for this view and to offer additional insight into the divergent evolution of deleterious variation across populations, we numerically solve time-inhomogeneous diffusion equations and study the temporal dynamics of the frequency spectra in models of population size change for modern humans. We observe how the response to demographic change differs by the strength of selection, and we then assess whether similar patterns are observed in exome sequence data from 33,370 and 5203 individuals of non-Finnish European and West African ancestry, respectively. Our theoretical results highlight how even simple summaries of the frequency spectrum can have complex responses to demographic change. These results support the finding that some apparent discrepancies between previous results have been driven by the behaviors of the precise summaries of deleterious variation. Further, our empirical results make clear the difficulty of inferring slight differences in frequency spectra using recent next-generation sequence data.

Local Adaptation Interacts with Expansion Load during Range Expansion: Maladaptation Reduces Expansion Load

The biotic and abiotic factors that facilitate or hinder species range expansions are many and complex. We examine the impact of two genetic processes and their interaction on fitness at expanding range edges: local maladaptation resulting from the presence of an environmental gradient and expansion load resulting from increased genetic drift at the range edge. Results from spatially explicit simulations indicate that the presence of an environmental gradient during range expansion reduces expansion load; conversely, increasing expansion load allows only locally adapted populations to persist at the range edge. Increased maladaptation reduces the speed of range expansion, resulting in less genetic drift at the expanding front and more immigration from the range center, therefore reducing expansion load at the range edge. These results may have ramifications for species being forced to shift their ranges because of climate change or other anthropogenic changes. If rapidly changing climate leads to faster expansion as populations track their shifting climatic optima, populations may suffer increased expansion load beyond previous expectations.