The Roles of Drift and Selection on Short Stamen Loss in Arabidopsis thaliana along an Elevational Gradient in the Spanish Pyrenees.

Traits that have lost function sometimes persist through evolutionary time. These traits may be maintained by a lack of standing genetic variation for the trait, if selection against the trait is weak relative to drift, or if they have a residual function. To determine the evolutionary processes shaping whether nonfunctional traits are retained or lost, we investigated short stamens in 16 populations of Arabidopsis thaliana along an elevational cline in the Spanish Pyrenees. We found a cline in short stamen number from retention of short stamens in high elevation populations to incomplete loss in low elevation populations. We did not find evidence that limited genetic variation constrains the loss of short stamens at high elevations nor evidence for divergent selection on short stamens between high and low elevations. Finally, we identified loci associated with short stamens in the Spanish Pyrenees that are different from loci associated with variation in short stamen number across latitudes from a previous study. Overall, we did not identify the evolutionary mechanisms maintaining an elevational cline in short stamen number but did identify different genetic loci underlying the variation in short stamen along similar phenotypic clines.

A spatial approach to jointly estimate Wright's neighborhood size and long-term effective population size.

Spatially continuous patterns of genetic differentiation, which are common in nature, are often poorly described by existing population genetic theory or methods that assume either panmixia or discrete, clearly definable populations. There is therefore a need for statistical approaches in population genetics that can accommodate continuous geographic structure, and that ideally use georeferenced individuals as the unit of analysis, rather than populations or subpopulations. In addition, researchers are often interested in describing the diversity of a population distributed continuously in space; this diversity is intimately linked to both the dispersal potential and the population density of the organism. A statistical model that leverages information from patterns of isolation-by-distance to jointly infer parameters that control local demography (such as Wright's neighborhood size), and the long-term effective size (Ne) of a population would be useful. Here, we introduce such a model that uses individual-level pairwise genetic and geographic distances to infer Wright's neighborhood size and long-term Ne. We demonstrate the utility of our model by applying it to complex, forward-time demographic simulations as well as an empirical dataset of the two-form bumblebee (Bombus bifarius). The model performed well on simulated data relative to alternative approaches and produced reasonable empirical results given the natural history of bumblebees. The resulting inferences provide important insights into the population genetic dynamics of spatially structured populations.

Pitfalls and windfalls of detecting demographic declines using population genetics in long-lived species.

Detecting recent demographic changes is a crucial component of species conservation and management, as many natural populations face declines due to anthropogenic habitat alteration and climate change. Genetic methods allow researchers to detect changes in effective population size (N e ) from sampling at a single timepoint. However, in species with long lifespans, there is a lag between the start of a decline in a population and the resulting decrease in genetic diversity. This lag slows the rate at which diversity is lost, and therefore makes it difficult to detect recent declines using genetic data. However, the genomes of old individuals can provide a window into the past, and can be compared to those of younger individuals, a contrast that may help reveal recent demographic declines. To test whether comparing the genomes of young and old individuals can help infer recent demographic bottlenecks, we use forward-time, individual-based simulations with varying mean individual lifespans and extents of generational overlap. We find that age information can be used to aid in the detection of demographic declines when the decline has been severe. When average lifespan is long, comparing young and old individuals from a single timepoint has greater power to detect a recent (within the last 50 years) bottleneck event than comparing individuals sampled at different points in time. Our results demonstrate how longevity and generational overlap can be both a hindrance and a boon to detecting recent demographic declines from population genomic data.

A geographic history of human genetic ancestry.

Describing the distribution of genetic variation across individuals is a fundamental goal of population genetics. In humans, traditional approaches for describing population genetic variation often rely on discrete genetic ancestry labels, which, despite their utility, can obscure the complex, multifaceted nature of human genetic history. These labels risk oversimplifying ancestry by ignoring its temporal depth and geographic continuity, and may therefore conflate notions of race, ethnicity, geography, and genetic ancestry. Here, we present a method that capitalizes on the rich genealogical information encoded in genomic tree sequences to infer the geographic locations of the shared ancestors of a sample of sequenced individuals. We use this method to infer the geographic history of genetic ancestry of a set of human genomes sampled from Europe, Asia, and Africa, accurately recovering major population movements on those continents. Our findings demonstrate the importance of defining the spatial-temporal context of genetic ancestry to describing human genetic variation and caution against the oversimplified interpretations of genetic data prevalent in contemporary discussions of race and ancestry.

The era of the ARG: An introduction to ancestral recombination graphs and their significance in empirical evolutionary genomics.

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

The era of the ARG: an empiricist's guide to ancestral recombination graphs.

In the presence of recombination, the evolutionary relationships between a set of sampled genomes cannot be described by a single genealogical tree. Instead, the genomes are related by a complex, interwoven collection of genealogies formalized in a structure called an ancestral recombination graph (ARG). An ARG extensively encodes the ancestry of the genome(s) and thus is replete with valuable information for addressing diverse questions in evolutionary biology. Despite its potential utility, technological and methodological limitations, along with a lack of approachable literature, have severely restricted awareness and application of ARGs in empirical evolution research. Excitingly, recent progress in ARG reconstruction and simulation have made ARG-based approaches feasible for many questions and systems. In this review, we provide an accessible introduction and exploration of ARGs, survey recent methodological breakthroughs, and describe the potential for ARGs to further existing goals and open avenues of inquiry that were previously inaccessible in evolutionary genomics. Through this discussion, we aim to more widely disseminate the promise of ARGs in evolutionary genomics and encourage the broader development and adoption of ARG-based inference.

Functional genomic diversity is correlated with neutral genomic diversity in populations of an endangered rattlesnake.

Theory predicts that genetic erosion in small, isolated populations of endangered species can be assessed using estimates of neutral genetic variation, yet this widely used approach has recently been questioned in the genomics era. Here, we leverage a chromosome-level genome assembly of an endangered rattlesnake (Sistrurus catenatus) combined with whole genome resequencing data (N = 110 individuals) to evaluate the relationship between levels of genome-wide neutral and functional diversity over historical and future timescales. As predicted, we found positive correlations between genome-wide estimates of neutral genetic diversity (π) and inferred levels of adaptive variation and an estimate of inbreeding mutation load, and a negative relationship between neutral diversity and an estimate of drift mutation load. However, these correlations were half as strong for projected future levels of neutral diversity based on contemporary effective population sizes. Broadly, our results confirm that estimates of neutral genetic diversity provide an accurate measure of genetic erosion in populations of a threatened vertebrate. They also provide nuance to the neutral-functional diversity controversy by suggesting that while these correlations exist, anthropogenetic impacts may have weakened these associations in the recent past and into the future.

A spatial approach to jointly estimate Wright's neighborhood size and long-term effective population size.

Spatially continuous patterns of genetic differentiation, which are common in nature, are often poorly described by existing population genetic theory or methods that assume panmixia or discrete, clearly definable populations. There is therefore a need for statistical approaches in population genetics that can accommodate continuous geographic structure, and that ideally use georeferenced individuals as the unit of analysis, rather than populations or subpopulations. In addition, researchers are often interested describing the diversity of a population distributed continuously in space, and this diversity is intimately linked to the dispersal potential of the organism. A statistical model that leverages information from patterns of isolation-by-distance to jointly infer parameters that control local demography (such as Wright's neighborhood size), and the long-term effective size (Ne) of a population would be useful. Here, we introduce such a model that uses individual-level pairwise genetic and geographic distances to infer Wright's neighborhood size and long-term Ne. We demonstrate the utility of our model by applying it to complex, forward-time demographic simulations as well as an empirical dataset of the Red Sea clownfish (Amphiprion bicinctus). The model performed well on simulated data relative to alternative approaches and produced reasonable empirical results given the natural history of clownfish. The resulting inferences provide important insights into the population genetic dynamics of spatially structure populations.

Importance of timely metadata curation to the global surveillance of genetic diversity.

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome-scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n = 440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data-sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.

Importancia de la curación oportuna de metadatos para la vigilancia mundial de la diversidad genética Resumen La diversidad genética intraespecífica representa un nivel fundamental, pero a la vez subvalorado de la biodiversidad. La diversidad genética puede indicar la resiliencia de una especie ante el clima cambiante, por lo que su medición es relevante para muchos objetivos de la política de conservación mundial y nacional. Muchos estudios producen una gran cantidad de datos sobre la diversidad a nivel genético de las poblaciones silvestres, aunque la mayoría (87%) no incluye los metadatos espaciales y temporales asociados para que sean reutilizados en los programas de monitoreo o para reconocer la soberanía de las naciones o los pueblos indígenas. Realizamos un "datatón" distribuido para cuantificar la disponibilidad de estos metadatos faltantes y para probar la hipótesis que supone que esta disponibilidad se deteriora con el tiempo. También trabajamos para reparar los metadatos faltantes al extraerlos de los artículos asociados publicados, los repositorios en línea y la comunicación directa con los autores. Iniciamos con 838 candidatos de conjuntos de datos genómicos (representación reducida y genoma completo) tomados de la colaboración internacional para la base de datos de secuencias de nucleótidos y determinamos que 561 incluían en su mayoría muestras tomadas de poblaciones silvestres. Restauramos con éxito los metadatos espaciotemporales en el 78% de estos 561 conjuntos de datos (n = 440 conjuntos de datos con información sobre 45,105 individuos de 762 especies en 17 filos). El análisis de los artículos y los repositorios virtuales fue mucho más productivo que contactar a los 351 autores, quienes tuvieron un 45% de respuesta a nuestros correos. En general, el 23% de nuestras consultas descubrieron metadatos útiles. La probabilidad de recuperar metadatos espaciotemporales declinó de manera significativa conforme incrementó la antigüedad del conjunto de datos. Hubo una disminución anual del 13.5% en los metadatos asociados con los artículos publicados y los repositorios virtuales y hasta una disminución anual del 22% en los metadatos que sólo estaban disponibles mediante la comunicación con los autores. Este rápido deterioro en la disponibilidad de los metadatos, duplicado en estudios de otros tipos de datos biológicos, debería motivar la pronta actualización de las políticas del intercambio de datos y las prácticas de los investigadores para asegurar que en las ciencias de la conservación no se pierda para siempre el contexto valioso proporcionado por los metadatos.

Modeling the Evolution of Rates of Continuous Trait Evolution.

Rates of phenotypic evolution vary markedly across the tree of life, from the accelerated evolution apparent in adaptive radiations to the remarkable evolutionary stasis exhibited by so-called "living fossils." Such rate variation has important consequences for large-scale evolutionary dynamics, generating vast disparities in phenotypic diversity across space, time, and taxa. Despite this, most methods for estimating trait evolution rates assume rates vary deterministically with respect to some variable of interest or change infrequently during a clade's history. These assumptions may cause underfitting of trait evolution models and mislead hypothesis testing. Here, we develop a new trait evolution model that allows rates to vary gradually and stochastically across a clade. Further, we extend this model to accommodate generally decreasing or increasing rates over time, allowing for flexible modeling of "early/late bursts" of trait evolution. We implement a Bayesian method, termed "evolving rates" (evorates for short), to efficiently fit this model to comparative data. Through simulation, we demonstrate that evorates can reliably infer both how and in which lineages trait evolution rates varied during a clade's history. We apply this method to body size evolution in cetaceans, recovering substantial support for an overall slowdown in body size evolution over time with recent bursts among some oceanic dolphins and relative stasis among beaked whales of the genus Mesoplodon. These results unify and expand on previous research, demonstrating the empirical utility of evorates. [cetacea; macroevolution; comparative methods; phenotypic diversity; disparity; early burst; late burst].

Genetic isolation by distance underlies colour pattern divergence in red-eyed treefrogs (Agalychnis callidryas).

Investigating the spatial distribution of genetic and phenotypic variation can provide insights into the evolutionary processes that shape diversity in natural systems. We characterized patterns of genetic and phenotypic diversity to learn about drivers of colour-pattern diversification in red-eyed treefrogs (Agalychnis callidryas) in Costa Rica. Along the Pacific coast, red-eyed treefrogs have conspicuous leg colour patterning that transitions from orange in the north to purple in the south. We measured phenotypic variation of frogs, with increased sampling at sites where the orange-to-purple transition occurs. At the transition zone, we discovered the co-occurrence of multiple colour-pattern morphs. To explore possible causes of this variation, we generated a single nucleotide polymorphism data set to analyse population genetic structure, measure genetic diversity and infer the processes that mediate genotype-phenotype dynamics. We investigated how patterns of genetic relatedness correspond to individual measures of colour pattern along the coast, including testing for the role of hybridization in geographic regions where orange and purple phenotypic groups co-occur. We found no evidence that colour-pattern polymorphism in the transition zone arose through recent hybridization. Instead, a strong pattern of genetic isolation by distance indicates that colour-pattern variation was either retained through other processes such as ancestral colour polymorphisms or ancient secondary contact, or else it was generated by novel mutations. We found that phenotype changes along the Pacific coast more than would be expected based on genetic divergence and geographic distance alone. Combined, our results suggest the possibility of selective pressures acting on colour pattern at a small geographic scale.

La investigación de la distribución espacial de la variación genética y fenotípica puede proporcionar información sobre los procesos evolutivos que dan forma a la diversidad en los sistemas naturales. Caracterizamos patrones de diversidad genética y fenotípica para conocer los impulsores de la diversificación de patrones de color en ranas con ojos rojos (Agalychnis callidryas) en Costa Rica. A lo largo de la costa del Pacífico, las ranas con ojos rojos tienen un patrón de color llamativo en las patas que cambia de naranja en el norte a púrpura en el sur. Medimos la variación fenotípica de las ranas en los sitios del Pacífico, con un mayor muestreo en los sitios donde ocurre la transición de naranja a púrpura. En la zona de transición, descubrimos la co-ocurrencia de múltiples morfos de patrones de color. Para explorar las posibles causas de esta variación, generamos un conjunto de datos SNP con secuenciación RAD para analizar la estructura genética de la población, medir la diversidad genética e inferir los procesos que median la dinámica genotipo-fenotipo. Investigamos cómo los patrones de parentesco genético se corresponden con medidas individuales de patrón de color a lo largo de la costa, incluidas las pruebas del papel de la hibridación en regiones geográficas donde coexisten grupos fenotípicos naranja y morado. No encontramos evidencia de que el polimorfismo del patrón de color en la zona de transición surgiera a través de una hibridación o introgresión reciente. En cambio, un fuerte patrón de aislamiento genético por distancia indica que la variación del patrón de color se retuvo a través de otros procesos, como los polimorfismos de color ancestrales, el contacto secundario antiguo o la generada por mutaciones novedosas. Descubrimos que el fenotipo de color cambia a lo largo de la costa del Pacífico más de lo que se esperaría solo por la divergencia genética y la distancia geográfica. Combinados, nuestros resultados sugieren la posibilidad de que las presiones selectivas actúen sobre el patrón de color a pequeña escala geográfica.

Poor data stewardship will hinder global genetic diversity surveillance.

Genomic data are being produced and archived at a prodigious rate, and current studies could become historical baselines for future global genetic diversity analyses and monitoring programs. However, when we evaluated the potential utility of genomic data from wild and domesticated eukaryote species in the world's largest genomic data repository, we found that most archived genomic datasets (86%) lacked the spatiotemporal metadata necessary for genetic biodiversity surveillance. Labor-intensive scouring of a subset of published papers yielded geospatial coordinates and collection years for only 33% (39% if place names were considered) of these genomic datasets. Streamlined data input processes, updated metadata deposition policies, and enhanced scientific community awareness are urgently needed to preserve these irreplaceable records of today's genetic biodiversity and to plug the growing metadata gap.

Broad Concordance in the Spatial Distribution of Adaptive and Neutral Genetic Variation across an Elevational Gradient in Deer Mice.

When species are continuously distributed across environmental gradients, the relative strength of selection and gene flow shape spatial patterns of genetic variation, potentially leading to variable levels of differentiation across loci. Determining whether adaptive genetic variation tends to be structured differently than neutral variation along environmental gradients is an open and important question in evolutionary genetics. We performed exome-wide population genomic analysis on deer mice sampled along an elevational gradient of nearly 4,000 m of vertical relief. Using a combination of selection scans, genotype-environment associations, and geographic cline analyses, we found that a large proportion of the exome has experienced a history of altitude-related selection. Elevational clines for nearly 30% of these putatively adaptive loci were shifted significantly up- or downslope of clines for loci that did not bear similar signatures of selection. Many of these selection targets can be plausibly linked to known phenotypic differences between highland and lowland deer mice, although the vast majority of these candidates have not been reported in other studies of highland taxa. Together, these results suggest new hypotheses about the genetic basis of physiological adaptation to high altitude, and the spatial distribution of adaptive genetic variation along environmental gradients.

Neo-darwinism still haunts evolutionary theory: A modern perspective on Charlesworth, Lande, and Slatkin (1982).

The Modern Synthesis (or "Neo-Darwinism"), which arose out of the reconciliation of Darwin's theory of natural selection and Mendel's research on genetics, remains the foundation of evolutionary theory. However, since its inception, it has been a lightning rod for criticism, which has ranged from minor quibbles to complete dismissal. Among the most famous of the critics was Stephen Jay Gould, who, in 1980, proclaimed that the Modern Synthesis was "effectively dead." Gould and others claimed that the action of natural selection on random mutations was insufficient on its own to explain patterns of macroevolutionary diversity and divergence, and that new processes were required to explain findings from the fossil record. In 1982, Charlesworth, Lande, and Slatkin published a response to this critique in Evolution, in which they argued that Neo-Darwinism was indeed sufficient to explain macroevolutionary patterns. In this Perspective for the 75th Anniversary of the Society for the Study of Evolution, we review Charlesworth et al. in its historical context and provide modern support for their arguments. We emphasize the importance of microevolutionary processes in the study of macroevolutionary patterns. Ultimately, we conclude that punctuated equilibrium did not represent a major revolution in evolutionary biology - although debate on this point stimulated significant research and furthered the field - and that Neo-Darwinism is alive and well.

Stepping into the past to conserve the future: Archived skin swabs from extant and extirpated populations inform genetic management of an endangered amphibian.

Moving animals on a landscape through translocations and reintroductions is an important management tool used in the recovery of endangered species, particularly for the maintenance of population genetic diversity and structure. Management of imperiled amphibian species rely heavily on translocations and reintroductions, especially for species that have been brought to the brink of extinction by habitat loss, introduced species, and disease. One striking example of amphibian declines and associated management efforts is in California's Sequoia and Kings Canyon National Parks with the mountain yellow-legged frog species complex (Rana sierrae/muscosa). Mountain yellow-legged frogs have been extirpated from more than 93% of their historic range, and limited knowledge of their population genetics has made long-term conservation planning difficult. To address this, we used 598 archived skin swabs from both extant and extirpated populations across 48 lake basins to generate a robust Illumina-based nuclear amplicon data set. We found that samples grouped into three main genetic clusters, concordant with watershed boundaries. We also found evidence for historical gene flow across watershed boundaries with a north-to-south axis of migration. Finally, our results indicate that genetic diversity is not significantly different between populations with different disease histories. Our study offers specific management recommendations for imperiled mountain yellow-legged frogs and, more broadly, provides a population genetic framework for leveraging minimally invasive samples for the conservation of threatened species.

Genomic and Fitness Consequences of Genetic Rescue in Wild Populations.

Gene flow is an enigmatic evolutionary force because it can limit adaptation but may also rescue small populations from inbreeding depression [1-3]. Several iconic examples of genetic rescue-increased population growth caused by gene flow [4, 5]-have reversed population declines [6, 7]. However, concerns about outbreeding depression and maladaptive gene flow limit the use of human-mediated gene flow in conservation [8, 9]. Rescue effects of immigration through demographic and/or genetic mechanisms have received theoretical and empirical support, but studies that monitor initial and long-term effects of gene flow on individuals and populations in the wild are lacking. Here, we used individual-based mark-recapture, multigenerational pedigrees, and genomics to test the demographic and evolutionary consequences of manipulating gene flow in two isolated, wild Trinidadian guppy populations. Recipient and source populations originated from environments with different predation, flow, and resource regimes [10]. We documented 10-fold increases in population size following gene flow and found that, on average, hybrids lived longer and reproduced more than residents and immigrants. Despite overall genomic homogenization, alleles potentially associated with local adaptation were not entirely swamped by gene flow. Our results suggest that genetic rescue was caused not just by increasing individual genetic diversity, rather new genomic variation from immigrants combined with alleles from the recipient population resulted in highly fit hybrids and subsequent increases in population size. Contrary to the classic view of maladaptive gene flow, our study reveals conditions under which immigration can produce long-term fitness benefits in small populations without entirely swamping adaptive variation.

Physiological and genomic evidence that selection on the transcription factor Epas1 has altered cardiovascular function in high-altitude deer mice.

Evolutionary adaptation to extreme environments often requires coordinated changes in multiple intersecting physiological pathways, but how such multi-trait adaptation occurs remains unresolved. Transcription factors, which regulate the expression of many genes and can simultaneously alter multiple phenotypes, may be common targets of selection if the benefits of induced changes outweigh the costs of negative pleiotropic effects. We combined complimentary population genetic analyses and physiological experiments in North American deer mice (Peromyscus maniculatus) to examine links between genetic variation in transcription factors that coordinate physiological responses to hypoxia (hypoxia-inducible factors, HIFs) and multiple physiological traits that potentially contribute to high-altitude adaptation. First, we sequenced the exomes of 100 mice sampled from different elevations and discovered that several SNPs in the gene Epas1, which encodes the oxygen sensitive subunit of HIF-2α, exhibited extreme allele frequency differences between highland and lowland populations. Broader geographic sampling confirmed that Epas1 genotype varied predictably with altitude throughout the western US. We then discovered that Epas1 genotype influences heart rate in hypoxia, and the transcriptomic responses to hypoxia (including HIF targets and genes involved in catecholamine signaling) in the heart and adrenal gland. Finally, we used a demographically-informed selection scan to show that Epas1 variants have experienced a history of spatially varying selection, suggesting that differences in cardiovascular function and gene regulation contribute to high-altitude adaptation. Our results suggest a mechanism by which Epas1 may aid long-term survival of high-altitude deer mice and provide general insights into the role that highly pleiotropic transcription factors may play in the process of environmental adaptation.

Inferring Continuous and Discrete Population Genetic Structure Across Space.

A classic problem in population genetics is the characterization of discrete population structure in the presence of continuous patterns of genetic differentiation. Especially when sampling is discontinuous, the use of clustering or assignment methods may incorrectly ascribe differentiation due to continuous processes (e.g., geographic isolation by distance) to discrete processes, such as geographic, ecological, or reproductive barriers between populations. This reflects a shortcoming of current methods for inferring and visualizing population structure when applied to genetic data deriving from geographically distributed populations. Here, we present a statistical framework for the simultaneous inference of continuous and discrete patterns of population structure. The method estimates ancestry proportions for each sample from a set of two-dimensional population layers, and, within each layer, estimates a rate at which relatedness decays with distance. This thereby explicitly addresses the "clines versus clusters" problem in modeling population genetic variation, and remedies some of the overfitting to which nonspatial models are prone. The method produces useful descriptions of structure in genetic relatedness in situations where separated, geographically distributed populations interact, as after a range expansion or secondary contact. We demonstrate the utility of this approach using simulations and by applying it to empirical datasets of poplars and black bears in North America.

Partitioning the effects of isolation by distance, environment, and physical barriers on genomic divergence between parapatric threespine stickleback.

Genetic divergence between populations is shaped by a combination of drift, migration, and selection, yielding patterns of isolation-by-distance (IBD) and isolation-by-environment (IBE). Unfortunately, IBD and IBE may be confounded when comparing divergence across habitat boundaries. For instance, parapatric lake and stream threespine stickleback (Gasterosteus aculeatus) may have diverged due to selection against migrants (IBE), or mere spatial separation (IBD). To quantitatively partition the strength of IBE and IBD, we used recently developed population genetic software (BEDASSLE) to analyze partial genomic data from three lake-stream clines on Vancouver Island. We find support for IBD within each of three outlet streams (unlike prior studies of lake-stream stickleback). In addition, we find evidence for IBE (controlling for geographic distance): the genetic effect of habitat is equivalent to geographic separation of ∼1.9 km of IBD. Remarkably, of our three lake-stream pairs, IBE is strongest where migration between habitats is easiest. Such microgeographic genetic divergence would require exceptionally strong divergent selection, which multiple experiments have failed to detect. Instead, we propose that nonrandom dispersal (e.g., habitat choice) contributes to IBE. Supporting this conclusion, we show that the few migrants between habitats are a nonrandom subset of the phenotype distribution of the source population.

A Spatial Framework for Understanding Population Structure and Admixture.

Geographic patterns of genetic variation within modern populations, produced by complex histories of migration, can be difficult to infer and visually summarize. A general consequence of geographically limited dispersal is that samples from nearby locations tend to be more closely related than samples from distant locations, and so genetic covariance often recapitulates geographic proximity. We use genome-wide polymorphism data to build "geogenetic maps," which, when applied to stationary populations, produces a map of the geographic positions of the populations, but with distances distorted to reflect historical rates of gene flow. In the underlying model, allele frequency covariance is a decreasing function of geogenetic distance, and nonlocal gene flow such as admixture can be identified as anomalously strong covariance over long distances. This admixture is explicitly co-estimated and depicted as arrows, from the source of admixture to the recipient, on the geogenetic map. We demonstrate the utility of this method on a circum-Tibetan sampling of the greenish warbler (Phylloscopus trochiloides), in which we find evidence for gene flow between the adjacent, terminal populations of the ring species. We also analyze a global sampling of human populations, for which we largely recover the geography of the sampling, with support for significant histories of admixture in many samples. This new tool for understanding and visualizing patterns of population structure is implemented in a Bayesian framework in the program SpaceMix.