Fast and flexible estimation of effective migration surfaces

Distinguishing species boundaries from geographic variation

In an era of unprecedented biodiversity loss, the need for standardized practices to describe biological variation is becoming increasingly important. As with all scientific endeavors, species delimitation needs to be explicit, testable, and refutable. A fundamental task in species delimitation is distinguishing within-species variation from among-species variation. Many species that are distributed across large geographic areas exhibit levels of genetic variation that are as great or greater than those that exist between well-defined sympatric species. Here, we provide a workflow to distinguish between intra- and interspecific genetic variation and apply the workflow to a taxonomically problematic group of frogs (the Rana pipiens complex, or leopard frogs) that are widely distributed across Mexico and Central America. Our workflow makes use of recent advancements that pair genome-scale datasets with model-based species delimitation methods, while emphasizing the need for positive evidence of reproductive isolation to confirm the validity of geographically contiguous species boundaries. We find that intraspecific geographic variation in widespread leopard frog species has resulted in considerable taxonomic inflation of species. Ten currently recognized species are not supported in our analyses, and we here synonymize them with previously named taxa. Furthermore, we find positive evidence for the presence of three undescribed species. In addition to proposing these taxonomic changes, we provide descriptions of the data or analyses that would be needed to refute and overturn our recommendations. We recommend that all species delimitation studies (especially of geographically variable groups) clarify what new evidence would be sufficient to change the taxonomic recommendations.

Population genomics and molecular epidemiology of wheat powdery mildew in Europe

Agricultural diseases are a major threat to sustainable food production. Yet, for many pathogens we know exceptionally little about their epidemiological and population dynamics, and this knowledge gap is slowing the development of efficient control strategies. Here we study the population genomics and molecular epidemiology of wheat powdery mildew, a disease caused by the biotrophic fungus Blumeria graminis forma specialis tritici (Bgt). We sampled Bgt across two consecutive years, 2022 and 2023, and compiled a genomic dataset of 415 Bgt isolates from 22 countries in Europe and surrounding regions. We identified a single epidemic unit in the north of Europe, consisting of a highly homogeneous population. Conversely, the south of Europe hosts smaller local populations which are less interconnected. In addition, we show that the population structure can be largely predicted by the prevalent wind patterns. We identified several loci that were under selection in the recent past, including fungicide targets and avirulence genes. Some of these loci are common between populations, while others are not, suggesting different local selective pressures. We reconstructed the evolutionary history of one of these loci, AvrPm17, coding for an effector recognized by the wheat receptor Pm17. We found evidence for a soft sweep on standing genetic variation. Multiple AvrPm17 haplotypes, which can partially escape recognition by Pm17, spread rapidly throughout the continent upon its introduction in the early 2000s. We also identified a new virulent variant, which emerged more recently and can evade Pm17 resistance altogether. Overall, we highlight the potential of genomic surveillance in resolving the evolutionary and epidemiological dynamics of agricultural pathogens, as well as in guiding control strategies.

Sweeps in space: leveraging geographic data to identify beneficial alleles in Anopheles gambiae

As organisms adapt to environmental changes, natural selection modifies the frequency of non-neutral alleles. For beneficial mutations, the outcome of this process may be a selective sweep, in which an allele rapidly increases in frequency and perhaps reaches fixation within a population. Selective sweeps have well-studied effects on patterns of local genetic variation in panmictic populations, but much less is known about the dynamics of sweeps in continuous space. In particular, because limited movement across a landscape leads to unique patterns of population structure, spatial dynamics may influence the trajectory of selected mutations. Here, we use forward-in-time, individual-based simulations in continuous space to study the impact of space on beneficial mutations as they sweep through a population. In particular, we show that selection changes the joint distribution of allele frequency and geographic range occupied by a focal allele and demonstrate that this signal can be used to identify selective sweeps. We then leverage this signal to identify in-progress selective sweeps within the malaria vector Anopheles gambiae , a species under strong selection pressure from vector control measures. By considering space, we identify multiple previously undescribed variants with potential phenotypic consequences, including mutations impacting known IR-associated genes and altering protein structure and properties. Our results demonstrate a novel signal for detecting selection in spatial population genetic data that may have implications for genomic surveillance and understanding geographic patterns of genetic variation.

Integrating Genomics and Biogeography to Unravel the Origin of a Mountain Biota: The Case of a Reptile Endemicity Hotspot in Arabia

Advances in genomics have greatly enhanced our understanding of mountain biodiversity, providing new insights into the complex and dynamic mechanisms that drive the formation of mountain biotas. These span from broad biogeographic patterns to population dynamics and adaptations to these environments. However, significant challenges remain in integrating large-scale and fine-scale findings to develop a comprehensive understanding of mountain biodiversity. One significant challenge is the lack of genomic data, especially in historically understudied arid regions where reptiles are a particularly diverse vertebrate group. In the present study, we assembled a de novo genome-wide SNP dataset for the complete endemic reptile fauna of a mountain range (19 described species with more than 600 specimens sequenced), and integrated state-of-the-art biogeographic analyses at the population, species, and community level. Thus, we provide a holistic integration of how a whole endemic reptile community has originated, diversified and dispersed through a mountain system. Our results show that reptiles independently colonized the Hajar Mountains of southeastern Arabia 11 times. After colonization, species delimitation methods suggest high levels of within-mountain diversification, supporting up to 49 deep lineages. This diversity is strongly structured following local topography, with the highest peaks acting as a broad barrier to gene flow among the entire community. Interestingly, orogenic events do not seem key drivers of the biogeographic history of reptiles in this system. Instead, past climatic events seem to have had a major role in this community assemblage. We observe an increase of vicariant events from Late Pliocene onwards, coinciding with an unstable climatic period of rapid shifts between hyper-arid and semiarid conditions that led to the ongoing desertification of Arabia. We conclude that paleoclimate, and particularly extreme aridification, acted as a main driver of diversification in arid mountain systems which is tangled with the generation of highly adapted endemicity. Overall, our study does not only provide a valuable contribution to understanding the evolution of mountain biodiversity, but also offers a flexible and scalable approach that can be reproduced into any taxonomic group and at any discrete environment.

The origin, invasion history and resistance architecture of Anopheles stephensi in Africa

The invasion of Africa by the Asian urban malaria vector, Anopheles stephensi, endangers 126 million people across a rapidly urbanising continent where malaria is primarily a rural disease. Control of An. stephensi requires greater understanding of its origin, invasion dynamics, and mechanisms of widespread resistance to vector control insecticides. We present a genomic surveillance study of 551 An. stephensi sampled across the invasive and native ranges in Africa and Asia. Our findings support a hypothesis that an initial invasion from Asia to Djibouti seeded separate incursions to Sudan, Ethiopia, and Yemen before spreading inland, aided by favourable temperature, vegetation cover, and human transit conditions. Insecticide resistance in invasive An. stephensi is conferred by detoxification genes introduced from Asia. These findings, and a companion genomic data catalogue, will form the foundation of an evidence base for surveillance and management strategies for An. stephensi.

Local Selection Shaped the Diversity of European Maize Landraces

The introduction of populations to novel environments can lead to a loss of genetic diversity and the accumulation of deleterious mutations due to selection and demographic changes. We investigate how the recent introduction of maize to Europe shaped the genetic diversity and differentiation of European traditional maize populations and quantify the impact of its recent range expansion and consecutive breeding on the accumulation of genetic load. We use genome-wide genetic markers of almost 2000 individuals from 38 landraces, 155 elite breeding lines, and a large set of doubled haploid lines derived from two landraces to find extensive population structure within European maize, with landraces being highly differentiated even over short geographic distances. Yet, diversity change does not follow the continuous pattern of range expansions. Landraces maintain high genetic diversity that is distinct between populations and does not decrease along the possible expansion routes. Signals of positive selection in European landraces that overlap with selection in Asian maize suggest convergent selection during maize introductions. At the same time, environmental factors partially explain genetic differences across Europe. Consistent with the maintenance of high diversity, we find no evidence of genetic load accumulating along the maize introduction route in European maize. However, modern breeding likely purged highly deleterious alleles but accumulated genetic load in elite germplasm. Our results reconstruct the history of maize in Europe and show that landraces have maintained high genetic diversity that could reduce genetic load in the European maize breeding pools.

Jointly representing long-range genetic similarity and spatially heterogeneous isolation-by-distance

Isolation-by-distance patterns in genetic variation are a widespread feature of the geographic structure of genetic variation in many species, and many methods have been developed to illuminate such patterns in genetic data. However, long-range genetic similarities also exist, often as a result of rare or episodic long-range gene flow. Jointly characterizing patterns of isolation-by-distance and long-range genetic similarity in genetic data is an open data analysis challenge that, if resolved, could help produce more complete representations of the geographic structure of genetic data in any given species. Here, we present a computationally tractable method that identifies long-range genetic similarities in a background of spatially heterogeneous isolation-by-distance variation. The method uses a coalescent-based framework, and models long-range genetic similarity in terms of directional events with source fractions describing the fraction of ancestry at a location tracing back to a remote source. The method produces geographic maps annotated with inferred long-range edges, as well as maps of uncertainty in the geographic location of each source of long-range gene flow. We have implemented the method in a package called FEEMSmix (an extension to FEEMS from Marcus et al., 2021), and validated its implementation using simulations representative of typical data applications. We also apply this method to two empirical data sets. In a data set of over 4,000 humans (Homo sapiens) across Afro-Eurasia, we recover many known signals of long-distance dispersal from recent centuries. Similarly, in a data set of over 100 gray wolves (Canis lupus) across North America, we identify several previously unknown long-range connections, some of which were attributable to recording errors in sampling locations. Therefore, beyond identifying genuine long-range dispersals, our approach also serves as a useful tool for quality control in spatial genetic studies.

Suture zones, speciation, and evolution

In the more than 50 years since the initial conceptualization of the suture zone, little work has been done to take full advantage of the comparative capability of these geographic regions. During this time, great advances have been made in hybrid zone research that have provided invaluable insight into speciation and evolution. Hybrid zones have long been recognized to be "windows to the evolutionary process." If a single hybrid zone provides a window, then multiple hybrid zones in a suture zone can provide a panoramic view of the evolutionary process. Here, we hope to redirect attention to suture zones, bring the advances from hybrid zone research to a comparative framework, and further expand our understanding of speciation and evolution. In this review, we recount the historical discussions surrounding suture zones, briefly review what we can learn from hybrid zones, and review the comparative studies done on suture zones thus far. We also highlight the opportunities and challenges of performing research in suture zones to help guide researchers hoping to start a research project in these regions. Lastly, we propose future directions and questions for comparative research that can be done in suture zones.

The Limits of the Metapopulation: Lineage Fragmentation in a Widespread Terrestrial Salamander (Plethodon cinereus)

In vicariant species formation, divergence results primarily from periods of allopatry and restricted gene flow. Widespread species harboring differentiated, geographically distinct sublineages offer a window into what may be a common mode of species formation, whereby a species originates, spreads across the landscape, then fragments into multiple units. However, incipient lineages usually lack reproductive barriers that prevent their fusion upon secondary contact, blurring the boundaries between a single, large metapopulation-level lineage and multiple independent species. Here, we explore this model of species formation in the Eastern Red-backed Salamander (Plethodon cinereus), a widespread terrestrial vertebrate with at least 6 divergent mitochondrial clades throughout its range. Using anchored hybrid enrichment data, we applied phylogenomic and population genomic approaches to investigate patterns of divergence, gene flow, and secondary contact. Genomic data broadly match most mitochondrial groups but reveal mitochondrial introgression and extensive admixture at several contact zones. While species delimitation analyses in Bayesian Phylogenetics and Phylogeography supported 5 lineages of P. cinereus, genealogical divergence indices (gdi) were highly sensitive to the inclusion of admixed samples and the geographic representation of candidate species, with increasing support for multiple species when removing admixed samples or limiting sampling to a single locality per group. An analysis of morphometric data revealed differences in body size and limb proportions among groups, with a reduction of forelimb length among warmer and drier localities consistent with increased fossoriality. We conclude that P. cinereus is a single species, but one with highly structured component lineages of various degrees of independence.

Population history and admixture of the Fulani people from the Sahel

The Fulani people, one of the most important pastoralist groups in sub-Saharan Africa, are still largely underrepresented in population genomic research. They speak a Niger-Congo language called Fulfulde or Pulaar and live in scattered locations across the Sahel/Savannah belt, from the Atlantic Ocean to Lake Chad. According to historical records, their ancestors spread from Futa Toro in the Middle Senegal Valley to Futa-Jallon in Guinea and then eastward into the Sahel belt over the past 1,500 years. However, the earlier history of this traditionally pastoral population has not been well studied. To uncover the genetic structure and ancestry of this widespread population, we gathered genome-wide genotype data from 460 individuals across 18 local Fulani populations, along with comparative data from both modern and ancient worldwide populations. This represents a comprehensive geographically wide-scaled genome-wide study of the Fulani. We revealed a genetic component closely associated with all local Fulani populations, suggesting a shared ancestral component possibly linked to the beginning of African pastoralism in the Green Sahara. Comparison to ancient DNA results also identified the presence of an ancient Iberomaurusian-associated component across all Fulani groups, providing additional insights into their deep genetic history. Additionally, our genetic data indicate a later Fulani expansion from the western to the eastern Sahel, characterized by a clinal pattern and admixture with several other African populations north of the equator.

Genomic Insights Into Red Squirrels in Scotland Reveal Loss of Heterozygosity Associated With Extreme Founder Effects

Remnant populations of endangered species often have complex demographic histories associated with human impact. This can present challenges for conservation as populations modified by human activity may require bespoke management. The Eurasian red squirrel, Sciurus vulgaris (L., 1758), is endangered in the UK. Scotland represents a key stronghold, but Scottish populations have been subjected to intense anthropogenic influence, including widespread extirpations, reintroductions and competition from an invasive species. This study examined the genetic legacy of these events through low coverage whole-genome resequencing of 106 red squirrels. Previously undetected patterns of population structure and gene flow were uncovered. One offshore island, four mainland Scottish populations, and a key east-coast migration corridor were observed. An abrupt historical population bottleneck, related to extreme founder effects, has led to a severe and prolonged depression in genome-wide heterozygosity, which is amongst the lowest reported for any species. Current designated red squirrel conservation stronghold locations do not encompass all existing diversity. These findings highlight the genetic legacies of past anthropogenic influence on long-term diversity in endangered taxa. Continuing management interventions and regular genetic monitoring are recommended to safeguard and improve future diversity.

The structure of the environment influences the patterns and genetics of local adaptation

Environmental heterogeneity can lead to spatially varying selection, which can, in turn, lead to local adaptation. Population genetic models have shown that the pattern of environmental variation in space can strongly influence the evolution of local adaptation. In particular, when environmental variation is highly autocorrelated in space local adaptation will more readily evolve. However, there have been few attempts to test this prediction empirically or characterize the consequences it would have for the genetic architecture underlying local adaptation. In this study, I analyze a large-scale provenance trial conducted on lodgepole pine and find suggestive evidence that spatial autocorrelation in environmental variation is related to the strength of local adaptation that has evolved in that species. Motivated by those results, I use simulations to model local adaptation to different spatial patterns of environmental variation. The simulations confirm that local adaptation is expected to increase with the degree of spatial autocorrelation in the selective environment, but also show that highly heterogeneous environments are more likely to exhibit high variation in local adaptation, a result not previously described. I find that the spatial pattern of environmental variation influences the genetic architectures underlying local adaptation. In highly autocorrelated environments, the genetic architecture of local adaptation tends to be composed of high-frequency alleles with small phenotypic effects. In weakly autocorrelated environments, locally adaptive alleles may have larger phenotypic effects but are present at lower frequencies across species' ranges and experience more evolutionary turnover. Overall, this work emphasizes the profound importance that the spatial pattern of selection can have on the evolution of local adaptation and how spatial autocorrelation should be considered when formulating hypotheses in ecological and genetic studies.

Endangered Pinto/Northern Abalone (Haliotis kamtschatkana) are Panmictic Across Their 3700 km Range Along the Pacific Coast of North America

Connectivity is integral to the dynamics of metapopulations through dispersal and gene flow, and understanding these processes is essential for guiding conservation efforts. Abalone, broadcast-spawning marine snails associated with shallow rocky habitats, have experienced widespread declines, and all seven North American species are threatened. We investigated the connectivity and population genomics of pinto/northern abalone (Haliotis kamtschatkana), the widest-ranging of abalone species. We employed reduced representation sequencing (RADseq) to generate single nucleotide polymorphism (SNP) data, assessing population connectivity and potential adaptive variation at 12 locations across the full range from Alaska to Mexico. Despite depleted populations, our analysis of over 6000 SNPs across nearly 300 individuals revealed that pinto abalone maintains a high genetic diversity with no evidence of a genetic bottleneck. Neutral population structure and isolation by distance were extremely weak, indicating panmixia across the species' range (global F ST = 0.0021). Phylogenetic analysis, principal components analysis, and unsupervised clustering methods all supported a single genetic population. However, slight population differentiation was noted in the Salish Sea and Inside Passage regions, with evidence for higher barriers to dispersal relative to outer coastal areas. This north-central region may also represent the species' ancestral range based on relatively low population-specific F ST values; the northern and southern extremes of the range likely represent range expansions. Outlier analysis did not identify consensus loci implicated in adaptive variation, suggesting limited adaptive differentiation. Our study sheds light on the evolutionary history and contemporary gene flow of this threatened species, providing key insights for conservation strategies, particularly in sourcing broodstock for ongoing restoration efforts.

Thematic Layers of Genomic Susceptibility for Conservation Monitoring

Population genomics has great potential to inform applied conservation management and associated policy. However, the bioinformatic analyses and interpretation of population genomic datasets can be daunting and difficult to convey to nonspecialists, including on-the-ground conservationists that work with many state, federal and international agencies. We think that individual population genomic metrics of interest can be interpolated and ultimately distilled into thematic GIS layers that represent spatiotemporal genomic potential (or conversely, susceptibility) in conservation monitoring. As examples relevant to ongoing conservation efforts, we use introgressive hybridisation and individual heterozygosity to illustrate a conceptual approach for mapping population genomic susceptibility. The general framework of thematic layers could be extended to integrate key genomic metrics (e.g., runs of homozygosity and genomic load) that are relevant to many conservation efforts.

Population Genomic Scans for Natural Selection and Demography

Uncovering the fundamental processes that shape genomic variation in natural populations is a primary objective of population genetics. These processes include demographic effects such as past changes in effective population size or gene flow between structured populations. Furthermore, genomic variation is affected by selection on nonneutral genetic variants, for example, through the adaptation of beneficial alleles or balancing selection that maintains genetic variation. In this article, we discuss the characterization of these processes using population genetic models, and we review methods developed on the basis of these models to unravel the underlying processes from modern population genomic data sets. We briefly discuss the conditions in which these approaches can be used to infer demography or identify specific nonneutral genetic variants and cases in which caution is warranted. Moreover, we summarize the challenges of jointly inferring demography and selective processes that affect neutral variation genome-wide.

Estimation of spatial demographic maps from polymorphism data using a neural network

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity-by-descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN.

The genetic legacy of the Quaternary ice ages for West Palearctic butterflies

The interplay between geographic barriers and climatic oscillations over the past 2.6 million years structured genetic variation at the continental scale. The genetic legacy of the Quaternary ice ages (GLQ) hypothesis outlines this phenomenon for Europe, but a comprehensive data-driven assessment is lacking. Using innovative genetic landscape methods, we model the GLQ in the West Palearctic based on 31,653 Cytochrome c oxidase subunit 1 (COI) sequences from 494 butterfly species and three functional traits. Seven distinct bioregions with varying levels of genetic endemicity emerge, revealing a latitudinal gradient in variation that confirms the "southern richness, northern purity" hypothesis. Through shift from case studies to a comparative approach, we objectively identify the main glacial refugia, colonization routes, and barriers to dispersal. Our findings offer a quantitative model of the GLQ across Europe, North Africa, and neighboring Asia, with broader applicability to other taxa and potentially scalable to encompass life on Earth.

Variation in spatial population structure in the Anopheles gambiae species complex

Anopheles gambiae, Anopheles coluzzii, and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of these closely related species, including the extent to which populations are connected by gene flow, is essential for understanding how vector control implemented in one location might indirectly affect vector populations in other locations. Here, we assessed the population structure of each species based on a combined data set of publicly available and newly processed whole-genome sequences. The data set included single nucleotide polymorphisms from whole genomes of 2,410 individual mosquitoes sampled from 128 locations across 19 African countries. We found that A. gambiae sampled from several countries in West and Central Africa showed low genetic differentiation from each other according to principal components analysis (PCA) and ADMIXTURE modeling. Using Estimated Effective Migration Surfaces (EEMS), we showed that this low genetic differentiation indicates high effective migration rates for A. gambiae across this region. Outside of this region, we found eight groups of sampling locations from Central, East, and Southern Africa for which A. gambiae showed higher genetic differentiation, and lower effective migration rates, between each other and the West/Central Africa group. These results indicate that the barriers to and corridors for migration between populations of A. gambiae differ across the geographical range of this malaria vector species. Using the same methods, we found higher genetic differentiation and lower migration rates between populations of A. coluzzii in West and Central Africa than for A. gambiae in the same region. In contrast, we found lower genetic differentiation and higher migration rates between populations of A. arabiensis in Tanzania, compared to A. gambiae in the same region. These differences between A. gambiae, A. coluzzii, and A. arabiensis indicate that migration barriers and corridors may vary, even between very closely related species. Overall, our results demonstrate that migration rates vary both within and between species of Anopheles mosquitoes, presumably based on species-specific responses to the ecological or environmental conditions that may impede or facilitate migration, and the geographical patterns of these conditions across the landscape. Together with previous findings, this study provides robust evidence that migration rates between populations of malaria vectors depend on the ecological context, which should be considered when planning surveillance of vector populations, monitoring for insecticide resistance, and evaluating interventions.

Recurrent hybridization and gene flow shaped Norway and Siberian spruce evolutionary history over multiple glacial cycles

Most tree species underwent cycles of contraction and expansion during the Quaternary. These cycles led to an ancient and complex genetic structure that has since been affected by extensive gene flow and by strong local adaptation. The extent to which hybridization played a role in this multi-layered genetic structure is important to be investigated. To study the effect of hybridization on the joint population genetic structure of two dominant species of the Eurasian boreal forest, Picea abies and P. obovata, we used targeted resequencing and obtained around 480 K nuclear SNPs and 87 chloroplast SNPs in 542 individuals sampled across most of their distribution ranges. Despite extensive gene flow and a clear pattern of Isolation-by-Distance, distinct genetic clusters emerged, indicating the presence of barriers and corridors to migration. Two cryptic refugia located in the large hybrid zone between the two species played a critical role in shaping their current distributions. The two species repeatedly hybridized during the Pleistocene and the direction of introgression depended on latitude. Our study suggests that hybridization helped both species to overcome main shifts in their distribution ranges during glacial cycles and highlights the importance of considering whole species complex instead of separate entities to retrieve complex demographic histories.

Scots pine - panmixia and the elusive signal of genetic adaptation

Scots pine is the foundation species of diverse forested ecosystems across Eurasia and displays remarkable ecological breadth, occurring in environments ranging from temperate rainforests to arid tundra margins. Such expansive distributions can be favored by various demographic and adaptive processes and the interactions between them. To understand the impact of neutral and selective forces on genetic structure in Scots pine, we conducted range-wide population genetic analyses on 2321 trees from 202 populations using genotyping-by-sequencing, reconstructed the recent demography of the species and examined signals of genetic adaptation. We found a high and uniform genetic diversity across the entire range (global FST 0.048), no increased genetic load in expanding populations and minor impact of the last glacial maximum on historical population sizes. Genetic-environmental associations identified only a handful of single-nucleotide polymorphisms significantly linked to environmental gradients. The results suggest that extensive gene flow is predominantly responsible for the observed genetic patterns in Scots pine. The apparent missing signal of genetic adaptation is likely attributed to the intricate genetic architecture controlling adaptation to multi-dimensional environments. The panmixia metapopulation of Scots pine offers a good study system for further exploration into how genetic adaptation and plasticity evolve under gene flow and changing environment.

Isolation by environment and its consequences for range shifts with global change: Landscape genomics of the invasive plant common tansy

Invasive species are a growing global economic and ecological problem. However, it is not well understood how environmental factors mediate invasive range expansion. In this study, we investigated the recent and rapid range expansion of common tansy across environmental gradients in Minnesota, USA. We densely sampled individuals across the expanding range and performed reduced representation sequencing to generate a dataset of 3071 polymorphic loci for 176 individuals. We used non-spatial and spatially explicit analyses to determine the relative influences of geographic distance and environmental variation on patterns of genomic variation. We found no evidence for isolation by distance but strong evidence for isolation by environment, indicating that environmental factors may have modulated patterns of range expansion. Land use classification and soils were particularly important variables related to population structure although they operated on different spatial scales; land use classification was related to broad-scale patterns and soils were related to fine-scale patterns. All analyses indicated a distinctive genetic cluster in the most recently invaded portion of the range. Individuals from the far northwestern range margin were separated from the remainder of the range by reduced migration, which was associated with environmental resistance. This portion of the range was invaded primarily in the last 15 years. Ecological niche models also indicated that this cluster was associated with the expansion of the niche. While invasion is often assumed to be primarily influenced by dispersal limitation, our results suggest that ongoing invasion and range shifts with climate change may be strongly affected by environmental heterogeneity.

Estimation of spatial demographic maps from polymorphism data using a neural network

A fundamental goal in population genetics is to understand how variation is arrayed over natural landscapes. From first principles we know that common features such as heterogeneous population densities and barriers to dispersal should shape genetic variation over space, however there are few tools currently available that can deal with these ubiquitous complexities. Geographically referenced single nucleotide polymorphism (SNP) data are increasingly accessible, presenting an opportunity to study genetic variation across geographic space in myriad species. We present a new inference method that uses geo-referenced SNPs and a deep neural network to estimate spatially heterogeneous maps of population density and dispersal rate. Our neural network trains on simulated input and output pairings, where the input consists of genotypes and sampling locations generated from a continuous space population genetic simulator, and the output is a map of the true demographic parameters. We benchmark our tool against existing methods and discuss qualitative differences between the different approaches; in particular, our program is unique because it infers the magnitude of both dispersal and density as well as their variation over the landscape, and it does so using SNP data. Similar methods are constrained to estimating relative migration rates, or require identity by descent blocks as input. We applied our tool to empirical data from North American grey wolves, for which it estimated mostly reasonable demographic parameters, but was affected by incomplete spatial sampling. Genetic based methods like ours complement other, direct methods for estimating past and present demography, and we believe will serve as valuable tools for applications in conservation, ecology, and evolutionary biology. An open source software package implementing our method is available from https://github.com/kr-colab/mapNN .

Pushed waves, trailing edges, and extreme events: Eco-evolutionary dynamics of a geographic range shift in the owl limpet, Lottia gigantea

As climatic variation re-shapes global biodiversity, understanding eco-evolutionary feedbacks during species range shifts is of increasing importance. Theory on range expansions distinguishes between two different forms: "pulled" and "pushed" waves. Pulled waves occur when the source of the expansion comes from low-density peripheral populations, while pushed waves occur when recruitment to the expanding edge is supplied by high-density populations closer to the species' core. How extreme events shape pushed/pulled wave expansion events, as well as trailing-edge declines/contractions, remains largely unexplored. We examined eco-evolutionary responses of a marine invertebrate (the owl limpet, Lottia gigantea) that increased in abundance during the 2014-2016 marine heatwaves near the poleward edge of its geographic range in the northeastern Pacific. We used whole-genome sequencing from 19 populations across >11 degrees of latitude to characterize genomic variation, gene flow, and demographic histories across the species' range. We estimated present-day dispersal potential and past climatic stability to identify how contemporary and historical seascape features shape genomic characteristics. Consistent with expectations of a pushed wave, we found little genomic differentiation between core and leading-edge populations, and higher genomic diversity at range edges. A large and well-mixed population in the northern edge of the species' range is likely a result of ocean current anomalies increasing larval settlement and high-dispersal potential across biogeographic boundaries. Trailing-edge populations have higher differentiation from core populations, possibly driven by local selection and limited gene flow, as well as high genomic diversity likely as a result of climatic stability during the Last Glacial Maximum. Our findings suggest that extreme events can drive poleward range expansions that carry the adaptive potential of core populations, while also cautioning that trailing-edge extirpations may threaten unique evolutionary variation. This work highlights the importance of understanding how both trailing and leading edges respond to global change and extreme events.

Broken Ring Speciation in California Mygalomorph Spiders (Nemesiidae, Calisoga)

AbstractIdealized ring species, with approximately continuous gene flow around a geographic barrier but singular reproductive isolation at a ring terminus, are rare in nature. A broken ring species model preserves the geographic setting and fundamental features of an idealized model but accommodates varying degrees of gene flow restriction over complex landscapes through evolutionary time. Here we examine broken ring species dynamics in Calisoga spiders, which, like the classic ring species Ensatina salamanders, are distributed around the Central Valley of California. Using nuclear and mitogenomic data, we test key predictions of common ancestry, ringlike biogeography, biogeographic timing, population connectivity, and terminal overlap. We show that a ring complex of populations shares a single common ancestor, and from an ancestral area in the Sierra Nevada mountains, two distributional and phylogenomic arms encircle the Central Valley. Isolation by distance occurs along these distributional arms, although gene flow restriction is also evident. Where divergent lineages meet in the South Coast Ranges, we find rare lineage sympatry, without evidence for nuclear gene flow and with clear evidence for morphological and ecological divergence. We discuss general insights provided by broken ring species and how such a model could be explored and extended in other systems and future studies.

Evaluating evidence for co-geography in the Anopheles-Plasmodium host-parasite system

The often tight association between parasites and their hosts means that under certain scenarios, the evolutionary histories of the two species can become closely coupled both through time and across space. Using spatial genetic inference, we identify a potential signal of common dispersal patterns in the Anopheles gambiae and Plasmodium falciparum host-parasite system as seen through a between-species correlation of the differences between geographic sampling location and geographic location predicted from the genome. This correlation may be due to coupled dispersal dynamics between host and parasite but may also reflect statistical artifacts due to uneven spatial distribution of sampling locations. Using continuous-space population genetics simulations, we investigate the degree to which uneven distribution of sampling locations leads to bias in prediction of spatial location from genetic data and implement methods to counter this effect. We demonstrate that while algorithmic bias presents a problem in inference from spatio-genetic data, the correlation structure between A. gambiae and P. falciparum predictions cannot be attributed to spatial bias alone and is thus likely a genetic signal of co-dispersal in a host-parasite system.

Genomic diversity and structure of a Neotropical microendemic fig tree

Genetic diversity is a key component of evolution, and unraveling factors that promote genetic differentiation in space and time is a central question in evolutionary biology. One of the most diverse and ecologically important tree genera in tropical forests worldwide is Ficus (Moraceae). It has been suggested that, given the great dispersal capacity of pollinating fig wasps (Chalcidoidea; Agaonidae), the spatial genetic structure, particularly in monoecious fig species, should be weak. However, no studies have addressed the factors that determine the genetic structure of Ficus species in regions of high geological, geographic, and climatic complexity, such as the Mexican Transition Zone. Using nuclear single nucleotide polymorphisms (5311 SNPs) derived from low-coverage whole genomes and 17 populations, we analyzed the population genomics of Ficus pringlei to characterize neutral and adaptive genetic variation and structure and its association with geographic barriers such as the Trans-Mexican Volcanic Belt, environmental heterogeneity, and wind connectivity. From genomic data of 71 individuals, high genetic diversity, and the identification of three genomic lineages were recorded (North, South, and Churumuco). The results suggest that genetic variation is primarily determined by climatic heterogeneity. Ficus pringlei populations from the north and south of the Trans-Mexican Volcanic Belt also exhibited minimal genetic differentiation (F ST = 0.021), indicating that this mountain range may not act as an insurmountable barrier to gene flow. Wind connectivity is also highlighted in structuring putative adaptive genetic variation, underscoring the intricate complexity of the various factors influencing genetic variation in the species. This study provides information on the possible mechanisms underlying the genetic variation of endemic species of the tropical dry forest of Western Mexico, such as F. pringlei.

Genomic Tools in Biological Invasions: Current State and Future Frontiers

Human activities are accelerating rates of biological invasions and climate-driven range expansions globally, yet we understand little of how genomic processes facilitate the invasion process. Although most of the literature has focused on underlying phenotypic correlates of invasiveness, advances in genomic technologies are showing a strong link between genomic variation and invasion success. Here, we consider the ability of genomic tools and technologies to (i) inform mechanistic understanding of biological invasions and (ii) solve real-world issues in predicting and managing biological invasions. For both, we examine the current state of the field and discuss how genomics can be leveraged in the future. In addition, we make recommendations pertinent to broader research issues, such as data sovereignty, metadata standards, collaboration, and science communication best practices that will require concerted efforts from the global invasion genomics community.

The genetic legacy of the expansion of Bantu-speaking peoples in Africa

The expansion of people speaking Bantu languages is the most dramatic demographic event in Late Holocene Africa and fundamentally reshaped the linguistic, cultural and biological landscape of the continent1-7. With a comprehensive genomic dataset, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we contribute insights into this expansion that started 6,000-4,000 years ago in western Africa. We genotyped 1,763 participants, including 1,526 Bantu speakers from 147 populations across 14 African countries, and generated whole-genome sequences from 12 Late Iron Age individuals8. We show that genetic diversity amongst Bantu-speaking populations declines with distance from western Africa, with current-day Zambia and the Democratic Republic of Congo as possible crossroads of interaction. Using spatially explicit methods9 and correlating genetic, linguistic and geographical data, we provide cross-disciplinary support for a serial-founder migration model. We further show that Bantu speakers received significant gene flow from local groups in regions they expanded into. Our genetic dataset provides an exhaustive modern-day African comparative dataset for ancient DNA studies10 and will be important to a wide range of disciplines from science and humanities, as well as to the medical sector studying human genetic variation and health in African and African-descendant populations.

slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes

One of the goals of population genetics is to understand how evolutionary forces shape patterns of genetic variation over time. However, because populations evolve across both time and space, most evolutionary processes also have an important spatial component, acting through phenomena such as isolation by distance, local mate choice, or uneven distribution of resources. This spatial dimension is often neglected, partly due to the lack of tools specifically designed for building and evaluating complex spatio-temporal population genetic models. To address this methodological gap, we present a new framework for simulating spatially-explicit genomic data, implemented in a new R package called slendr (www.slendr.net), which leverages a SLiM simulation back-end script bundled with the package. With this framework, the users can programmatically and visually encode spatial population ranges and their temporal dynamics (i.e., population displacements, expansions, and contractions) either on real Earth landscapes or on abstract custom maps, and schedule splits and gene-flow events between populations using a straightforward declarative language. Additionally, slendr can simulate data from traditional, non-spatial models, either with SLiM or using an alternative built-in coalescent msprime back end. Together with its R-idiomatic interface to the tskit library for tree-sequence processing and analysis, slendr opens up the possibility of performing efficient, reproducible simulations of spatio-temporal genomic data entirely within the R environment, leveraging its wealth of libraries for geospatial data analysis, statistics, and visualization. Here, we present the design of the slendr R package and demonstrate its features on several practical example workflows.

Evaluating evidence for co-geography in the Anopheles-Plasmodium host-parasite system

The often tight association between parasites and their hosts means that under certain scenarios, the evolutionary histories of the two species can become closely coupled both through time and across space. Using spatial genetic inference, we identify a potential signal of common dispersal patterns in the Anopheles gambiae and Plasmodium falciparum host-parasite system as seen through a between-species correlation of the differences between geographic sampling location and geographic location predicted from the genome. This correlation may be due to coupled dispersal dynamics between host and parasite, but may also reflect statistical artifacts due to uneven spatial distribution of sampling locations. Using continuous-space population genetics simulations, we investigate the degree to which uneven distribution of sampling locations leads to bias in prediction of spatial location from genetic data and implement methods to counter this effect. We demonstrate that while algorithmic bias presents a problem in inference from spatio-genetic data, the correlation structure between A. gambiae and P. falciparum predictions cannot be attributed to spatial bias alone, and is thus likely a genetic signal of co-dispersal in a host-parasite system.

Eurasian back-migration into Northeast Africa was a complex and multifaceted process

Recent studies have identified Northeast Africa as an important area for human movements during the Holocene. Eurasian populations have moved back into Northeastern Africa and contributed to the genetic composition of its people. By gathering the largest reference dataset to date of Northeast, North, and East African as well as Middle Eastern populations, we give new depth to our knowledge of Northeast African demographic history. By employing local ancestry methods, we isolated the Non-African parts of modern-day Northeast African genomes and identified the best putative source populations. Egyptians and Sudanese Copts bore most similarities to Levantine populations whilst other populations in the region generally had predominantly genetic contributions from the Arabian peninsula rather than Levantine populations for their Non-African genetic component. We also date admixture events and investigated which factors influenced the date of admixture and find that major linguistic families were associated with the date of Eurasian admixture. Taken as a whole we detect complex patterns of admixture and diverse origins of Eurasian admixture in Northeast African populations of today.

Population genetic structure and hybrid zone analyses for species delimitation in the Japanese toad (Bufo japonicus)

Hybridization following secondary contact may produce different outcomes depending on the extent to which genetic diversity and reproductive barriers have accumulated during isolation. The Japanese toad, Bufo japonicus, is distributed on the main islands of Japan. In the present study, we applied multiplexed inter-simple sequence repeat genotyping by sequencing to achieve the fine-scale resolution of the genetic cluster in B. j. japonicus and B. j. formosus. We also elucidated hybridization patterns and gene flow degrees across contact zones between the clusters identified. Using SNP data, we found four genetic clusters in B. j. japonicus and B. j. formosus and three contact zones of the cluster pairs among these four clusters. The two oldest diverged lineages, B. j. japonicus and B. j. formosus, formed a narrow contact zone consistent with species distinctiveness. Therefore, we recommend that these two subspecies be elevated to the species level. In contrast, the less diverged pairs of two clusters in B. j. japonicus and B. j. formosus, respectively, admixed over a hundred kilometers, suggesting that they have not yet developed strong reproductive isolation and need to be treated as conspecifics. These results will contribute to resolving taxonomic confusion in Japanese toads.

Fine-scale sampling uncovers the complexity of migrations in 5th-6th century Pannonia

As the collapse of the Western Roman Empire accelerated during the 4th and 5th centuries, arriving "barbarian" groups began to establish new communities in the border provinces of the declining (and eventually former) empire. This was a time of significant cultural and political change throughout not only these border regions but Europe as a whole.1,2 To better understand post-Roman community formation in one of these key frontier zones after the collapse of the Hunnic movement, we generated new paleogenomic data for a set of 38 burials from a time series of three 5th century cemeteries3,4,5 at Lake Balaton, Hungary. We utilized a comprehensive sampling approach to characterize these cemeteries along with data from 38 additional burials from a previously published mid-6th century site6 and analyzed them alongside data from over 550 penecontemporaneous individuals.7,8,9,10,11,12,13,14,15,16,17,18,19 The range of genetic diversity in all four of these local burial communities is extensive and wider ranging than penecontemporaneous Europeans sequenced to date. Despite many commonalities in burial customs and demography, we find that there were substantial differences in genetic ancestry between the sites. We detect evidence of northern European gene flow into the Lake Balaton region. Additionally, we observe a statistically significant association between dress artifacts and genetic ancestry among 5th century genetically female burials. Our analysis shows that the formation of early Medieval communities was a multifarious process even at a local level, consisting of genetically heterogeneous groups.

Where to draw the line? Expanding the delineation of conservation units to highly mobile taxa

Conservation units (CUs) are an essential tool for maximizing evolutionary potential and prioritizing areas across a species' range for protection when implementing conservation and management measures. However, current workflows for identifying CUs on the basis of neutral and adaptive genomic variation largely ignore information contained in patterns of isolation by distance (IBD), frequently the primary signal of population structure in highly mobile taxa, such as birds, bats, and marine organisms with pelagic larval stages. While individuals located on either end of a species' distribution may exhibit clear genetic, phenotypic, and ecological differences, IBD produces subtle changes in allele frequencies across space, making it difficult to draw clear boundaries for conservation purposes in the absence of discrete population structure. Here, we highlight potential pitfalls that arise when applying common methods for delineating CUs to continuously distributed organisms and review existing methods for detecting subtle breakpoints in patterns of IBD that can indicate barriers to gene flow in highly mobile taxa. In addition, we propose a new framework for identifying CUs in all organisms, including those characterized by continuous genomic differentiation, and suggest several possible ways to harness the information contained in patterns of IBD to guide conservation and management decisions.

Dispersal inference from population genetic variation using a convolutional neural network

The geographic nature of biological dispersal shapes patterns of genetic variation over landscapes, making it possible to infer properties of dispersal from genetic variation data. Here, we present an inference tool that uses geographically distributed genotype data in combination with a convolutional neural network to estimate a critical population parameter: the mean per-generation dispersal distance. Using extensive simulation, we show that our deep learning approach is competitive with or outperforms state-of-the-art methods, particularly at small sample sizes. In addition, we evaluate varying nuisance parameters during training-including population density, demographic history, habitat size, and sampling area-and show that this strategy is effective for estimating dispersal distance when other model parameters are unknown. Whereas competing methods depend on information about local population density or accurate inference of identity-by-descent tracts, our method uses only single-nucleotide-polymorphism data and the spatial scale of sampling as input. Strikingly, and unlike other methods, our method does not use the geographic coordinates of the genotyped individuals. These features make our method, which we call "disperseNN," a potentially valuable new tool for estimating dispersal distance in nonmodel systems with whole genome data or reduced representation data. We apply disperseNN to 12 different species with publicly available data, yielding reasonable estimates for most species. Importantly, our method estimated consistently larger dispersal distances than mark-recapture calculations in the same species, which may be due to the limited geographic sampling area covered by some mark-recapture studies. Thus genetic tools like ours complement direct methods for improving our understanding of dispersal.

Evolutionary Genetics and Admixture in African Populations

As the ancestral homeland of our species, Africa contains elevated levels of genetic diversity and substantial population structure. Importantly, African genomes are heterogeneous: They contain mixtures of multiple ancestries, each of which have experienced different evolutionary histories. In this review, we view population genetics through the lens of admixture, highlighting how multiple demographic events have shaped African genomes. Each of these historical vignettes paints a recurring picture of population divergence followed by secondary contact. First, we give a brief overview of genetic variation in Africa and examine deep population structure within Africa, including the evidence of ancient introgression from archaic "ghost" populations. Second, we describe the genetic legacies of admixture events that have occurred during the past 10,000 years. This includes gene flow between different click-speaking Khoe-San populations, the stepwise spread of pastoralism from eastern to southern Africa, multiple migrations of Bantu speakers across the continent, as well as admixture from the Middle East and Europe into the Sahel region and North Africa. Furthermore, the genomic signatures of more recent admixture can be found in the Cape Peninsula and throughout the African diaspora. Third, we highlight how natural selection has shaped patterns of genetic variation across the continent, noting that gene flow provides a potent source of adaptive variation and that selective pressures vary across Africa. Finally, we explore the biomedical implications of population structure in Africa on health and disease and call for more ethically conducted studies of genetic variation in Africa.

Biogeographic inferences across spatial and evolutionary scales

The field of biogeography unites landscape genetics and phylogeography under a common conceptual framework. Landscape genetics traditionally focuses on recent-time, population-based, spatial genetics processes at small geographical scales, while phylogeography typically investigates deep past, lineage- and species-based processes at large geographical scales. Here, we evaluate the link between landscape genetics and phylogeographical methods using the western fence lizard (Sceloporus occidentalis) as a model species. First, we conducted replicated landscape genetics studies across several geographical scales to investigate how population genetics inferences change depending on the spatial extent of the study area. Then, we carried out a phylogeographical study of population structure at two evolutionary scales informed by inferences derived from landscape genetics results to identify concordance and conflict between these sets of methods. We found significant concordance in landscape genetics processes at all but the largest geographical scale. Phylogeographical results indicate major clades are restricted to distinct river drainages or distinct hydrological regions. At a more recent timescale, we find minor clades are restricted to single river canyons in the majority of cases, while the remainder of river canyons include samples from at most two clades. Overall, the broad-scale pattern implicating stream and river valleys as key features linking populations in the landscape genetics results, and high degree of clade specificity within major topographic subdivisions in the phylogeographical results, is consistent. As landscape genetics and phylogeography share many of the same objectives, synthesizing theory, models and methods between these fields will help bring about a better understanding of ecological and evolutionary processes structuring genetic variation across space and time.

Demographic and Selection Histories of Populations Across the Sahel/Savannah Belt

The Sahel/Savannah belt harbors diverse populations with different demographic histories and different subsistence patterns. However, populations from this large African region are notably under-represented in genomic research. To investigate the population structure and adaptation history of populations from the Sahel/Savannah space, we generated dense genome-wide genotype data of 327 individuals-comprising 14 ethnolinguistic groups, including 10 previously unsampled populations. Our results highlight fine-scale population structure and complex patterns of admixture, particularly in Fulani groups and Arabic-speaking populations. Among all studied Sahelian populations, only the Rashaayda Arabic-speaking population from eastern Sudan shows a lack of gene flow from African groups, which is consistent with the short history of this population in the African continent. They are recent migrants from Saudi Arabia with evidence of strong genetic isolation during the last few generations and a strong demographic bottleneck. This population also presents a strong selection signal in a genomic region around the CNR1 gene associated with substance dependence and chronic stress. In Western Sahelian populations, signatures of selection were detected in several other genetic regions, including pathways associated with lactase persistence, immune response, and malaria resistance. Taken together, these findings refine our current knowledge of genetic diversity, population structure, migration, admixture and adaptation of human populations in the Sahel/Savannah belt and contribute to our understanding of human history and health.