Revealing cryptic spatial patterns in genetic variability by a new multivariate method

Geographical and genetic clines in Dracocephalum kotschyi X Dracocephalum oligadenium hybrids: landscape genetics and genocline analyses

Conservation and management of medicinally important plants are among the necessary tasks all over the world. The genus Dracocephalum (Lamiaceae) contains about 186 perennials, or annual herb species that have been used for their medicinal values in different parts of the world as an antihyperlipidemic, analgesic, antimicrobial, antioxidant, as well as anticancer medicine. Producing detailed data on the genetic structure of these species and their response against climate change and human landscape manipulation can be very important for conservation purposes. Therefore, the present study was performed on six geographical populations of two species in the Dracocephalum genus, namely, Dracocephalum kotschyi, and Dracocephalum oligadenium, as well as their inter-specific hybrid population. We carried out, population genetic study, landscape genetics, species modeling, and genetic cline analyses on these plants. We present here, new findings on the genetic structure of these populations, and provide data on both geographical and genetic clines, as well as morphological clines. We also identified genetic loci that are potentially adaptive to the geographical spatial features and genocide conditions. Different species distribution modeling (SDM) methods, used in this work revealed that bioclimatic variables related to the temperature and moisture, play an important role in Dracocephalum population's geographical distribution within IRAN and that due to the presence of some potentially adaptive genetic loci in the studied plants, they can survive well enough by the year 2050 and under climate change. The findings can be used for the protection of these medicinally important plant.

Genetic structure and climate niche differentiation among populations of Leopardus geoffroyi

Geoffroy's cat (Leopardus geoffroyi) is a small-sized felid native to South America. Given the species' distribution covering a wide variety of habitats, and the presence of high levels of anthropization in part of its range, it is possible that genetically differentiated groups exist and that they occupy different climatic niches. We assessed patterns of contemporary genetic diversity and structure in the species across most of its range, characterizing each inferred genetic group based on ecological niche models. We genotyped 11 microsatellites for 142 samples covering most of Geoffroy's cat distribution, and investigated patterns of genetic structure and diversity, applying spatial and nonspatial Bayesian clustering methods and a spatial principal component analysis. We created ecological niche models for each genetic cluster, evaluating whether these clusters occupy different climatic spaces and display differences in the suitability of different values of the climatic variables analyzed. We identified two genetic clusters, one in the north-northeast and the other in the south-southwest of the species' distribution. These clusters showed moderate FST values between them and differences in dispersal/genetic diversity. We found isolation-by-distance patterns globally and within each cluster. We observed lower expected heterozygosity compared with other studies and a north-south gradient in allelic richness. The southern cluster showed lower genetic variability and a more restricted climatic niche suggesting that this group is more vulnerable to the effects of the current context of climate change. Individuals from the southern genetic cluster are under different pressures, likely a product of the particularly dry habitat they occupy. Climatic variables associated with habitat suitability suggest the southern cluster has affinity for the arid and semiarid conditions present in its distribution. Conservation measures should consider the genetic structure observed and differences in climatic spaces to maintain the evolutionary potential of the species.

Dealing With Assumptions and Sampling Bias in the Estimation of Effective Population Size: A Case Study in an Amphibian Population

Accurately estimating effective population size (N e) is essential for understanding evolutionary processes and guiding conservation efforts. This study investigates N e estimation methods in spatially structured populations using a population of moor frog (Rana arvalis) as a case study. We assessed the behaviour of N e estimates derived from the linkage disequilibrium (LD) method as we changed the spatial configuration of samples. Moor frog eggs were sampled from 25 breeding patches (i.e., separate vernal ponds, ditches or parts of larger fens) within a single population, revealing an isolation-by-distance pattern and a local spatial genetic structure. Varying buffer sizes around each patch were used to examine the impact of sampling window size on the estimation of effective number of breeders (N b). Our results indicate a downward bias in LD N b estimates with increasing buffer size, suggesting an underestimation of N b. The observed bias is attributed to LD resulting from including genetically divergent individuals (mixture-LD) confounding LD due to drift. This emphasises the significance of considering even subtle spatial genetic patterns. The implications of these findings are discussed, emphasising the need to account for spatial genetic structure to accurately assess population viability and inform conservation efforts. This study contributes to our understanding of the challenges associated with N e estimation in spatially structured populations and underscores the importance of refining methodologies to address population-specific spatial dynamics for effective conservation planning and management.

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.

Large-scale assessment of genetic structure to assess risk of populations of a large herbivore to disease

Chronic wasting disease (CWD) can spread among cervids by direct and indirect transmission, the former being more likely in emerging areas. Identifying subpopulations allows the delineation of focal areas to target for intervention. We aimed to assess the population structure of white-tailed deer (Odocoileus virginianus) in the northeastern United States at a regional scale to inform managers regarding gene flow throughout the region. We genotyped 10 microsatellites in 5701 wild deer samples from Maryland, New York, Ohio, Pennsylvania, and Virginia. We evaluated the distribution of genetic variability through spatial principal component analysis and inferred genetic structure using non-spatial and spatial Bayesian clustering algorithms (BCAs). We simulated populations representing each inferred wild cluster, wild deer in each state and each physiographic province, total wild population, and a captive population. We conducted genetic assignment tests using these potential sources, calculating the probability of samples being correctly assigned to their origin. Non-spatial BCA identified two clusters across the region, while spatial BCA suggested a maximum of nine clusters. Assignment tests correctly placed deer into captive or wild origin in most cases (94%), as previously reported, but performance varied when assigning wild deer to more specific origins. Assignments to clusters inferred via non-spatial BCA performed well, but efficiency was greatly reduced when assigning samples to clusters inferred via spatial BCA. Differences between spatial BCA clusters are not strong enough to make assignment tests a reliable method for inferring the geographic origin of deer using 10 microsatellites. However, the genetic distinction between clusters may indicate natural and anthropogenic barriers of interest for management.

Population status and genetic assessment of mugger (Crocodylus palustris) in a tropical regulated river system in North India

For rewilding the depleted crocodylian populations in India, a targeted 'one-species one area' based conservation approach was adopted in the early-1970s. Suitable habitats were identified and designated as protected areas, specifically targeted to recover a particular crocodylian species. A ~ 610 km stretch of Chambal River in the Ganga River Basin was declared as National Chambal Sanctuary to restore the 'Critically Endangered' gharial (Gavialis gangeticus), where active management of mugger (Crocodylus palustris) was discouraged. In the present study, we examined the population trends, occupancy, and genetic status of mugger by conducting population monitoring and genetic assessment to understand the status of potentially competitive mugger in the Sanctuary. Our finding suggests that the mugger population has notably increased and colonised the Sanctuary. We observed a moderate level of genetic diversity in the mugger, which was relatively higher compared to the gharial in the Sanctuary. The rapid colonization of ecological generalist mugger raises concerns about potential competition with ecological specialist gharial threatening its long-term sustainability. Considering the coexistence dynamics between the species, it is essential to extend adaptive management strategies for mugger to ensure successful recovery of gharial population in the Sanctuary.

Heterogeneous patterns of heterozygosity loss in isolated populations of the threatened eastern barred bandicoot (Perameles gunnii)

Identifying and analysing isolated populations is critical for conservation. Isolation can make populations vulnerable to local extinction due to increased genetic drift and inbreeding, both of which should leave imprints of decreased genome-wide heterozygosity. While decreases in heterozygosity among populations are frequently investigated, fewer studies have analysed how heterozygosity varies among individuals, including whether heterozygosity varies geographically along lines of discrete population structure or with continuous patterns analogous to isolation by distance. Here we explore geographical patterns of differentiation and individual heterozygosity in the threatened eastern barred bandicoot (Perameles gunnii) in Tasmania, Australia, using genomic data from 85 samples collected between 2008 and 2011. Our analyses identified two isolated demes undergoing significant genetic drift, and several areas of fine-scale differentiation across Tasmania. We observed discrete genetic structures across geographical barriers and continuous patterns of isolation by distance, with little evidence of recent or historical migration. Using a recently developed analytical pipeline for estimating autosomal heterozygosity, we found individual heterozygosities varied within demes by up to a factor of two, and demes with low-heterozygosity individuals also still contained those with high heterozygosity. Spatial interpolation of heterozygosity scores clarified these patterns and identified the isolated Tasman Peninsula as a location where low-heterozygosity individuals were more common than elsewhere. Our results provide novel insights into the relationship between isolation-driven genetic structure and local heterozygosity patterns. These may help improve translocation efforts, by identifying populations in need of assistance, and by providing an individualised metric for identifying source animals for translocation.

Studies on genetic diversity, gene flow and landscape genetic in Avicennia marina: Spatial PCA, Random Forest, and phylogeography approaches

Mangrove forests grow in coastal areas, lagoons, estuaries, and deltas and form the main vegetation in tidal and saline wetlands. Due to the mankind activities and also changes in climate, these forests face degradations and probably extinction in some areas. Avicennia marina is one of the most distributed mangrove species throughout the world. The populations of A. marina occur in a limited region in southern parts of Iran. Very few genetic and spatial analyses are available on these plants from our country. Therefore, the present study was planned to provide detailed information on Avicennia marina populations with regard to genetic diversity, gene flow versus genetic isolation, effects of spatial variables on connectivity and structuring the genetic content of trees populations and also identifying adaptive genetic regions in respond too spatial variables. We used SCoT molecular markers for genetic analyses and utilized different computational approaches for population genetics and landscapes analyses. The results of present study showed a low to moderate genetic diversity in the studied populations and presence of significant Fst values among them. Genetic fragmentation was also observed within each province studied. A limited gene flow was noticed among neighboring populations within a particular province. One population was almost completely isolated from the gene flow with other populations and had peculiar genetic content.Spatial PCA analysis revealed both significant global and local genetic structuring in the studied populations. Spatial variables like humidity, longitude and altitude were the most important spatial features affecting genetic structure in these populations.

Move it or lose it: Predicted effects of culverts and population density on Mojave desert tortoise (Gopherus agassizii) connectivity

Roadways and railways can reduce wildlife movements across landscapes, negatively impacting population connectivity. Connectivity may be improved by structures that allow safe passage across linear barriers, but connectivity could be adversely influenced by low population densities. The Mojave desert tortoise is threatened by habitat loss, fragmentation, and population declines. The tortoise continues to decline as disturbance increases across the Mojave Desert in the southwestern United States. While underground crossing structures, like hydrological culverts, have begun receiving attention, population density has not been considered in tortoise connectivity. Our work asks a novel question: How do culverts and population density affect connectivity and potentially drive genetic and demographic patterns? To explore the role of culverts and population density, we used agent-based spatially explicit forward-in-time simulations of gene flow. We constructed resistance surfaces with a range of barriers to movement and representative of tortoise habitat with anthropogenic disturbance. We predicted connectivity under variable population densities. Simulations were run for 200 non-overlapping generations (3400 years) with 30 replicates using 20 microsatellite loci. We evaluated population genetic structure and diversity and found that culverts would not entirely negate the effects of linear barriers, but gene flow improved. Our results also indicated that density is important for connectivity. Low densities resulted in declines regardless of the landscape barrier scenario (> 75% population census size, > 97% effective population size). Results from our simulation using current anthropogenic disturbance predicted decreased population connectivity over time. Genetic and demographic effects were detectable within five generations (85 years) following disturbance with estimated losses in effective population size of 69%. The pronounced declines in effective population size indicate this could be a useful monitoring metric. We suggest management strategies that improve connectivity, such as roadside fencing tied to culverts, conservation areas in a connected network, and development restricted to disturbed areas.

Genetic data visualization using literature text-based neural networks: Examples associated with myocardial infarction

Data visualization is critical to unraveling hidden information from complex and high-dimensional data. Interpretable visualization methods are critical, especially in the biology and medical fields, however, there are limited effective visualization methods for large genetic data. Current visualization methods are limited to lower-dimensional data and their performance suffers if there is missing data. In this study, we propose a literature-based visualization method to reduce high-dimensional data without compromising the dynamics of the single nucleotide polymorphisms (SNP) and textual interpretability. Our method is innovative because it is shown to (1) preserves both global and local structures of SNP while reducing the dimension of the data using literature text representations, and (2) enables interpretable visualizations using textual information. For performance evaluations, we examined the proposed approach to classify various classification categories including race, myocardial infarction event age groups, and sex using several machine learning models on the literature-derived SNP data. We used visualization approaches to examine clustering of data as well as quantitative performance metrics for the classification of the risk factors examined above. Our method outperformed all popular dimensionality reduction and visualization methods for both classification and visualization, and it is robust against missing and higher-dimensional data. Moreover, we found it feasible to incorporate both genetic and other risk information obtained from literature with our method.

Spatial genetic structure of 2009 H1N1 pandemic influenza established as a result of interaction with human populations in mainland China

Identifying the spatial patterns of genetic structure of influenza A viruses is a key factor for understanding their spread and evolutionary dynamics. In this study, we used phylogenetic and Bayesian clustering analyses of genetic sequences of the A/H1N1pdm09 virus with district-level locations in mainland China to investigate the spatial genetic structure of the A/H1N1pdm09 virus across human population landscapes. Positive correlation between geographic and genetic distances indicates high degrees of genetic similarity among viruses within small geographic regions but broad-scale genetic differentiation, implying that local viral circulation was a more important driver in the formation of the spatial genetic structure of the A/H1N1pdm09 virus than even, countrywide viral mixing and gene flow. Geographic heterogeneity in the distribution of genetic subpopulations of A/H1N1pdm09 virus in mainland China indicates both local to local transmission as well as broad-range viral migration. This combination of both local and global structure suggests that both small-scale and large-scale population circulation in China is responsible for viral genetic structure. Our study provides implications for understanding the evolution and spread of A/H1N1pdm09 virus across the population landscape of mainland China, which can inform disease control strategies for future pandemics.

Non-random mating within an Island rookery of Hawaiian hawksbill turtles: demographic discontinuity at a small coastline scale

Hawksbill sea turtles (Eretmochelys imbricata) from the Hawaiian archipelago form a small and genetically isolated population, consisting of only a few tens of individuals breeding annually. Most females nest on the island of Hawai'i, but little is known about the demographics of this rookery. This study used genetic relatedness, inferred from 135 microhaplotype markers, to determine breeding sex-ratios, estimate female nesting frequency and assess relationships between individuals nesting on different beaches. Samples were collected during the 2017 nesting season and final data included 13 nesting females and 1002 unhatched embryos, salvaged from 41 nests, of which 13 had no observed mother. Results show that most females used a single nesting beach laying 1-5 nests each. From female and offspring alleles, the paternal genotypes of 12 breeding males were reconstructed and many showed high relatedness to their mates. Pairwise relatedness of offspring revealed one instance of polygyny but otherwise suggested a 1 : 1 breeding-sex ratio. Relatedness analysis and spatial-autocorrelation of genotypes indicate that turtles from different nesting areas do not regularly interbreed, suggesting that strong natal homing tendencies in both sexes result in non-random mating across the study area. Complexes of nearby nesting beaches also showed unique patterns of inbreeding across loci, further indicating that Hawaiian hawksbill turtles have demographically discontinuous nesting populations separated by only tens of km.

A high-throughput KASP assay provides insights into the evolution of multiple resistant mutations in populations of the two-spotted spider mite Tetranychus urticae across China

BACKGROUND

The two-spotted spider mite (TSSM), Tetranychus urticae (Acari: Tetranychidae), is a cosmopolitan phytophagous pest in agriculture and horticulture. It has developed resistance to many acaricides by target-site mutations. Understanding the status and evolution of resistant mutations in the field is essential for resistance management. Here, we applied a high-throughput Kompetitive allele-specific polymerase chain reaction (KASP) method for detecting six mutations conferring resistance to four acaricides of the TSSM. We genotyped 3274 female adults of TSSM from 43 populations collected across China in 2017, 2020, and 2021.

RESULTS

The KASP genotyping of 24 testing individuals showed 99% agreement with Sanger sequencing results. KASP assays showed that most populations had a high frequency of mutations conferring avermectin (G314D and G326E) and pyridaben (H92R) resistance. The frequency of mutation conferring bifenazate (A269V and G126S) and etoxazole (I1017F) resistance was relatively low. Multiple mutations were common in the TSSM, with 70.2% and 24.6% of individuals having 2-6 and 7-10 of 10 possible resistant alleles, respectively. No loci were linked in most populations among the six mutations, indicating the development of multiple resistance is mainly by independent selection. However, G314D and I1017F on the nuclear genome deviated from Hardy-Weinberg equilibrium in most populations, indicating significant selective pressure on TSSM populations by acaricides or fitness cost of the mutations in the absence of acaricide selection.

CONCLUSION

Our study revealed that the high frequency of TSSMs evolved multiple resistant mutations in population and individual levels by independent selection across China, alarming for managing multiple-acaricides resistance. © 2023 Society of Chemical Industry.

Genetic Diversity and Population Structure Assessed Using Microsatellite (SSR) Markers from Relict Populations of Nuphar pumila (Nymphaeaceae)

The genus Nuphar (Nymphaeaceae) comprises aquatic plant species inhabiting freshwater bodies of the Northern hemisphere temperate regions known as yellow water-lilies. Nuphar lutea and N. pumila are the only representatives in the European continent and present different ecologies: the former is a widespread generalist, while the latter is restricted to northern latitudes or high-altitudes due to its requirements for colder and oligotrophic waters. The Central Europe mountainous areas, the Massif Central (France) and the Cantabrian Mountains (north Iberian Peninsula) harbor relict isolated N. pumila populations endangered by eutrophication and hybridization with N. lutea. We aim to detect hybridization processes in the Massif Central and Cantabrian Mountains populations and compare the genetic diversity of N. pumila in the relict populations of Central Europe by using microsatellite (SSR) markers. No evidence of hybridization was found in the Iberian population, whereas the admixture between N. pumila and N. lutea in the Massif Central populations could be due to hybridization or ancient introgression. Our current knowledge would benefit from genetic diversity studies focusing on both species throughout their distributional range. The Iberian and Massif Central N. pumila populations were genetically distinct, representing two different clusters from other relict populations, with low genetic diversity and a genetic boundary within Central Europe.

Landscape genetics identifies barriers to Natterjack toad metapopulation dispersal

Habitat fragmentation and loss reduce population size and connectivity, which imperils populations. Functional connectivity is key for species persistence in human-modified landscapes. To inform species conservation management, we investigated spatial genetic structure, gene flow and inferred dispersal between twelve breeding sites of the Natterjack toad (Bufo calamita); regionally Red-Listed as Endangered in Ireland. Spatial genetic structure was determined using both Bayesian and non-Bayesian clustering analysis of 13 polymorphic microsatellite loci genotyping 247 individuals. We tested the influence of geographic distance, climate, habitat, geographical features, and anthropogenic pressure on pairwise genetic distances between breeding sites using Isolation-by-distance and Isolation-by-resistance based on least-cost path and circuit theory models of functional connectivity. There was clear spatial structuring with genetic distances increasing with geographic distance. Gene flow was best explained by Isolation-by-resistance models with coniferous forestry plantations, bog, marsh, moor and heath, scrub, anthropogenic presence (Human Influence Index) and rivers (riparian density) identified as habitats with high resistance to gene flow while metapopulation connectivity was enhanced by coastal habitats (beaches, sand dunes and salt marshes) and coastal grassland. Despite substantial declines in census numbers over the past 15 years and its regional status as Endangered, the Natterjack toad population in Ireland retains high genetic diversity. If declines continue, maintaining habitat connectivity to prevent genetic erosion by management of coastal grasslands, pond construction and assisted migration through translocation will be increasingly important.

Genetic diversity and structure of a recent fish invasion: Tench (Tinca tinca) in eastern North America

Introduced and geographically expanding populations experience similar eco-evolutionary challenges, including founder events, genetic bottlenecks, and novel environments. Theory predicts that reduced genetic diversity resulting from such phenomena limits the success of introduced populations. Using 1900 SNPs obtained from restriction-site-associated DNA sequencing, we evaluated hypotheses related to the invasion history and connectivity of an invasive population of Tench (Tinca tinca), a Eurasian freshwater fish that has been expanding geographically in eastern North America for three decades. Consistent with the reported history of a single introduction event, our findings suggest that multiple introductions from distinct genetic sources are unlikely as Tench had a small effective population size (~114 [95% CI = 106-123] individuals), no strong population subdivision across time and space, and evidence of a recent genetic bottleneck. The large genetic neighbourhood size (220 km) and weak within-population genetic substructure suggested high connectivity across the invaded range, despite the relatively large area occupied. There was some evidence for a small decay in genetic diversity as the species expanded northward, but not southward, into new habitats. As eradicating the species within a ~112 km radius would be necessary to prevent recolonization, eradicating Tench is likely not feasible at watershed-and possibly local-scales. Management should instead focus on reducing abundance in priority conservation areas to mitigate adverse impacts. Our study indicates that introduced populations can thrive and exhibit relatively high levels of genetic diversity despite severe bottlenecks (<1.5% of the ancestral effective population size) and suggests that landscape heterogeneity and population demographics can generate variability in spatial patterns of genetic diversity within a single range expansion.

Blind recovery of sources for multivariate space-time random fields

With advances in modern worlds technology, huge datasets that show dependencies in space as well as in time occur frequently in practice. As an example, several monitoring stations at different geographical locations track hourly concentration measurements of a number of air pollutants for several years. Such a dataset contains thousands of multivariate observations, thus, proper statistical analysis needs to account for dependencies in space and time between and among the different monitored variables. To simplify the consequent multivariate spatio-temporal statistical analysis it might be of interest to detect linear transformations of the original observations that result in straightforward interpretative, spatio-temporally uncorrelated processes that are also highly likely to have a real physical meaning. Blind source separation (BSS) represents a statistical methodology which has the aim to recover so-called latent processes, that exactly meet the former requirements. BSS was already successfully used in sole temporal and sole spatial applications with great success, but, it was not yet introduced for the spatio-temporal case. In this contribution, a reasonable and innovative generalization of BSS for multivariate space-time random fields (stBSS), under second-order stationarity, is proposed, together with two space-time extensions of the well-known algorithms for multiple unknown signals extraction (stAMUSE) and the second-order blind identification (stSOBI) which solve the formulated problem. Furthermore, symmetry and separability properties of the model are elaborated and connections to the space-time linear model of coregionalization and to the classical principal component analysis are drawn. Finally, the usefulness of the new methods is shown in a thorough simulation study and on a real environmental application.

Spatially aware dimension reduction for spatial transcriptomics

Spatial transcriptomics are a collection of genomic technologies that have enabled transcriptomic profiling on tissues with spatial localization information. Analyzing spatial transcriptomic data is computationally challenging, as the data collected from various spatial transcriptomic technologies are often noisy and display substantial spatial correlation across tissue locations. Here, we develop a spatially-aware dimension reduction method, SpatialPCA, that can extract a low dimensional representation of the spatial transcriptomics data with biological signal and preserved spatial correlation structure, thus unlocking many existing computational tools previously developed in single-cell RNAseq studies for tailored analysis of spatial transcriptomics. We illustrate the benefits of SpatialPCA for spatial domain detection and explores its utility for trajectory inference on the tissue and for high-resolution spatial map construction. In the real data applications, SpatialPCA identifies key molecular and immunological signatures in a detected tumor surrounding microenvironment, including a tertiary lymphoid structure that shapes the gradual transcriptomic transition during tumorigenesis and metastasis. In addition, SpatialPCA detects the past neuronal developmental history that underlies the current transcriptomic landscape across tissue locations in the cortex.

Evolutionary dynamics inform management interventions of a hanging garden obligate, Carex specuicola

Uncovering the historical and contemporary processes shaping rare species with complex distributions is of growing importance due to threats such as habitat destruction and climate change. Species restricted to specialized, patchy habitat may persist by virtue of life history characteristics facilitating ongoing gene flow and dispersal, but they could also reflect the remnants of formerly widespread, suitable habitat that existed during past climate regimes. If formerly widespread species did not rely upon traits facilitating high dispersibility to persist, contemporary populations could be at high risk of extirpation or extinction. Fortunately, genomic investigations provide an opportunity to illuminate such alternative scenarios while simultaneously offering guidance for future management interventions. Herein, we test the role of these mechanisms in shaping patterns of genomic diversity and differentiation across a highly restricted and rare ecosystem: desert hanging gardens. We focus on Carex specuicola (Cyperaceae), a hanging garden obligate narrowly distributed in the Four Corners region of the southwestern United States that is listed as Threatened under the United States Endangered Species Act. Population structure and diversity analyses reveal that hanging garden populations are shaped by strong genetic drift, but that individuals in gardens are occasionally more closely related to individuals at other gardens than to individuals within the same garden. Similarly, gardens separated by long geographic distances may contain individuals that are more closely related compared to individuals in gardens separated by short geographic distances. Demographic modeling supports historical gene flow between some contemporary garden pairs, which is corroborated by low estimates of inbreeding coefficients and recent divergence times. As such, multiple lines of evidence support dispersal and gene flow across C. specuicola populations at both small and large spatial scales, indicating that even if C. specuicola was formerly more widespread, it may be well suited to persist in hanging gardens so long as suitable habitat remains available. Analyses like those demonstrated herein may be broadly applicable for understanding the short- and long-term evolutionary processes influencing rare species, and especially those having complex distributions across heterogeneous landscapes.

Development of Genomic Resources in Mexican Bursera (Section: Bullockia: Burseraceae): Genome Assembly, Annotation, and Marker Discovery for Three Copal Species

Bursera comprises ~100 tropical shrub and tree species, with the center of the species diversification in Mexico. The genomic resources developed for the genus are scarce, and this has limited the study of the gene flow, local adaptation, and hybridization dynamics. In this study, based on ~155 million Illumina paired-end reads per species, we performed a de novo genome assembly and annotation of three Bursera species of the Bullockia section: Bursera bipinnata, Bursera cuneata, and Bursera palmeri. The total lengths of the genome assemblies were 253, 237, and 229 Mb for B. cuneata, B. palmeri, and B. bipinnata, respectively. The assembly of B. palmeri retrieved the most complete and single-copy BUSCOs (87.3%) relative to B. cuneata (86.5%) and B. bipinnata (76.6%). The ab initio gene prediction recognized between 21,000 and 32,000 protein-coding genes. Other genomic features, such as simple sequence repeats (SSRs), were also detected. Using the de novo genome assemblies as a reference, we identified single-nucleotide polymorphisms (SNPs) for a set of 43 Bursera individuals. Moreover, we mapped the filtered reads of each Bursera species against the chloroplast genomes of five Burseraceae species, obtaining consensus sequences ranging from 156 to 160 kb in length. Our work contributes to the generation of genomic resources for an important but understudied genus of tropical-dry-forest species.

Evaluation and comparison of unsupervised methods for the extraction of spatial patterns from mass spectrometry imaging data (MSI)

For the extraction of spatially important regions from mass spectrometry imaging (MSI) data, different clustering methods have been proposed. These clustering methods are based on certain assumptions and use different criteria to assign pixels into different classes. For high-dimensional MSI data, the curse of dimensionality also limits the performance of clustering methods which are usually overcome by pre-processing the data using dimension reduction techniques. In summary, the extraction of spatial patterns from MSI data can be done using different unsupervised methods, but the robust evaluation of clustering results is what is still missing. In this study, we have performed multiple simulations on synthetic and real MSI data to validate the performance of unsupervised methods. The synthetic data were simulated mimicking important spatial and statistical properties of real MSI data. Our simulation results confirmed that K-means clustering with correlation distance and Gaussian Mixture Modeling clustering methods give optimal performance in most of the scenarios. The clustering methods give efficient results together with dimension reduction techniques. From all the dimension techniques considered here, the best results were obtained with the minimum noise fraction (MNF) transform. The results were confirmed on both synthetic and real MSI data. However, for successful implementation of MNF transform the MSI data requires to be of limited dimensions.

Large-scale and small-scale population genetic structure of the medically important gastropod species Bulinus truncatus (Gastropoda, Heterobranchia)

BACKGROUND

Gastropod snails remain strongly understudied, despite their important role in transmitting parasitic diseases. Knowledge of their distribution and population dynamics increases our understanding of the processes driving disease transmission. We report the first study to use high-throughput sequencing (HTS) to elucidate the population genetic structure of the hermaphroditic snail Bulinus truncatus (Gastropoda, Heterobranchia) on a regional (17-150 km) and inter-regional (1000-5400 km) scale. This snail species acts as an intermediate host of Schistosoma haematobium and Schistosoma bovis, which cause human and animal schistosomiasis respectively.

METHODS

Bulinus truncatus snails were collected in Senegal, Cameroon, Egypt and France and identified through DNA barcoding. A single-end genotyping-by-sequencing (GBS) library, comprising 87 snail specimens from the respective countries, was built and sequenced on an Illumina HiSeq 2000 platform. Reads were mapped against S. bovis and S. haematobium reference genomes to identify schistosome infections, and single nucleotide polymorphisms (SNPs) were scored using the Stacks pipeline. These SNPs were used to estimate genetic diversity, assess population structure and construct phylogenetic trees of B. truncatus.

RESULTS

A total of 10,750 SNPs were scored and used in downstream analyses. The phylogenetic analysis identified five clades, each consisting of snails from a single country but with two distinct clades within Senegal. Genetic diversity was low in all populations, reflecting high selfing rates, but varied between locations due to habitat variability. Significant genetic differentiation and isolation by distance patterns were observed at both spatial scales, indicating that gene flow is not strong enough to counteract the effects of population bottlenecks, high selfing rates and genetic drift. Remarkably, the population genetic differentiation on a regional scale (i.e. within Senegal) was as large as that between populations on an inter-regional scale. The blind GBS technique was able to pick up parasite DNA in snail tissue, demonstrating the potential of HTS techniques to further elucidate the role of snail species in parasite transmission.

CONCLUSIONS

HTS techniques offer a valuable toolbox to further investigate the population genetic patterns of intermediate schistosome host snails and the role of snail species in parasite transmission.

New strategies for characterizing genetic structure in wide-ranging, continuously distributed species: A Greater Sage-grouse case study

Characterizing genetic structure across a species’ range is relevant for management and conservation as it can be used to define population boundaries and quantify connectivity. Wide-ranging species residing in continuously distributed habitat pose substantial challenges for the characterization of genetic structure as many analytical methods used are less effective when isolation by distance is an underlying biological pattern. Here, we illustrate strategies for overcoming these challenges using a species of significant conservation concern, the Greater Sage-grouse (Centrocercus urophasianus), providing a new method to identify centers of genetic differentiation and combining multiple methods to help inform management and conservation strategies for this and other such species. Our objectives were to (1) describe large-scale patterns of population genetic structure and gene flow and (2) to characterize genetic subpopulation centers across the range of Greater Sage-grouse. Samples from 2,134 individuals were genotyped at 15 microsatellite loci. Using standard STRUCTURE and spatial principal components analyses, we found evidence for four or six areas of large-scale genetic differentiation and, following our novel method, 12 subpopulation centers of differentiation. Gene flow was greater, and differentiation reduced in areas of contiguous habitat (eastern Montana, most of Wyoming, much of Oregon, Nevada, and parts of Idaho). As expected, areas of fragmented habitat such as in Utah (with 6 subpopulation centers) exhibited the greatest genetic differentiation and lowest effective migration. The subpopulation centers defined here could be monitored to maintain genetic diversity and connectivity with other subpopulation centers. Many areas outside subpopulation centers are contact zones where different genetic groups converge and could be priorities for maintaining overall connectivity. Our novel method and process of leveraging multiple different analyses to find common genetic patterns provides a path forward to characterizing genetic structure in wide-ranging, continuously distributed species.

How Geography and Climate Shaped the Genomic Diversity of Italian Local Cattle and Sheep Breeds

Simple Summary

In this paper, we study the inter-relationships among geography, climate, and genetics in Italian local cattle and sheep breeds. In terms of genetic diversity, geography (latitude and longitude) appears to play a larger role in sheep (26.4%) than that in cattle (13.8%). Once geography is accounted for, 10.1% of cattle genomic diversity and 13.3% of that of sheep are attributable to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher predomestication genetic variability together with biological and productive specializations. The climate alone seems to have had less impact on the current genetic diversity in both species even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Abstract

Understanding the relationships among geography, climate, and genetics is increasingly important for animal farming and breeding. In this study, we examine these inter-relationships in the context of local cattle and sheep breeds distributed along the Italian territory. To this aim, we used redundancy analysis on genomic data from previous projects combined with geographical coordinates and corresponding climatic data. The effect of geographic factors (latitude and longitude) was more important in sheep (26.4%) than that in cattle (13.8%). Once geography had been partialled out of analysis, 10.1% of cattle genomic diversity and 13.3% of that of sheep could be ascribed to climatic effects. Stronger geographic effects in sheep can be related to a combination of higher pre-domestication genetic variability together with biological and productive specificities. Climate alone seems to have had less impact on current genetic diversity in both species, even if climate and geography are greatly confounded. Results confirm that both species are the result of complex evolutionary histories triggered by interactions between human needs and environmental conditions.

Spatial Variation of Acanthophlebia cruentata (Ephemeroptera), a Mayfly Endemic to Te Ika-a-Māui—North Island of Aotearoa, New Zealand

Simple Summary

Patterns of variation within a widespread species can provide evidence of population history. Adjacent stable populations with gene flow show clinal genetic divergence forming a pattern of isolation by distance. Populations that have grown due to an increase in potential habitat such as forest cover since the last glacial maximum will have low genetic variation showing patterns of range expansion. The mayfly Acanthophlebia cruentata of Aotearoa, New Zealand, is widespread in streams of North Island but absent from the cooler South Island. Mayfly nymphs are restricted to streams but adults fly, facilitating gene flow among catchments. We detected higher genetic diversity at lower latitudes of this mayfly’s range compared to most of its distribution, concordant with predictions of limited forest cover in New Zealand during Pleistocene glacial periods. A signature of recent range expansion was observed in the higher latitudes. Despite initial observation suggesting mayfly size correlated with latitude, we found sex, elevation and sampling date were significant predictors of size, and some size variation is also explained by three regional groups based on haplotype distribution.

Abstract

The mayfly Acanthophlebia cruentata of Aotearoa, New Zealand, is widespread in Te Ika-a-Māui North Island streams, but has never been collected from South Island despite land connection during the last glacial maximum. Population structure of this mayfly might reflect re-colonisation after volcanic eruptions in North Island c1800 years ago, climate cycling or conceal older, cryptic diversity. We collected population samples from 33 locations to estimate levels of population genetic diversity and to document phenotypic variation. Relatively low intraspecific haplotype divergence was recorded among mitochondrial cytb sequences from 492 individuals, but these resolved three geographic-haplotype regions (north, west, east). We detected a signature of isolation by distance at low latitudes (north) but evidence of recent population growth in the west and east. We did not detect an effect of volcanic eruptions but infer range expansion into higher latitudes from a common ancestor during the last glacial period. As judged from wing length, both sexes of adult mayflies were larger at higher elevation and we found that haplotype region was also a significant predictor of Acanthophlebia cruentata size. This suggests that our mitochondrial marker is concordant with nuclear genetic differences that might be explained by founder effect during range expansion.

Genome-scale phylogeography resolves the native population structure of the Asian longhorned beetle, Anoplophora glabripennis (Motschulsky)

Human-assisted movement has allowed the Asian longhorned beetle (ALB, Anoplophora glabripennis (Motschulsky)) to spread beyond its native range and become a globally regulated invasive pest. Within its native range of China and the Korean peninsula, human-mediated dispersal has also caused cryptic translocation of insects, resulting in population structure complexity. Previous studies used genetic methods to detangle this complexity but were unable to clearly delimit native populations which is needed to develop downstream biosurveillance tools. We used genome-wide markers to define historical population structure in native ALB populations and contemporary movement between regions. We used genotyping-by-sequencing to generate 6102 single-nucleotide polymorphisms (SNPs) and amplicon sequencing to genotype 53 microsatellites. In total, we genotyped 712 individuals from ALB's native distribution. We observed six distinct population clusters among native ALB populations, with a clear delineation between northern and southern groups. Most of the individuals from South Korea were distinct from populations in China. Our results also indicate historical divergence among populations and suggest limited large-scale admixture, but we did identify a restricted number of cases of contemporary movement between regions. We identified SNPs under selection and describe a clinal allele frequency pattern in a missense variant associated with glycerol kinase, an important enzyme in the utilization of an insect cryoprotectant. We further demonstrate that small numbers of SNPs can assign individuals to geographic regions with high probability, paving the way for novel ALB biosurveillance tools.

Visual Parameter Selection for Spatial Blind Source Separation

Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameters involves navigating two large and interdependent parameter spaces, while also taking into account prior knowledge of the physical reality represented by the data. To support analysts in this process, we developed a visual analytics prototype. We evaluated it with experts in visualization, SBSS, and geochemistry. Our evaluations show that our interactive prototype allows to define complex and realistic parameter settings efficiently, which was so far impractical. Settings identified by a non-expert led to remarkable and surprising insights for a domain expert. Therefore, this paper presents important first steps to enable the use of a promising analysis method for spatial multivariate data.

Maize dispersal patterns associated with different types of endosperm and migration of indigenous groups in lowland South America

BACKGROUND AND AIMS

The lowlands of South America appear to be remarkably important in the evolutionary history of maize, due to new evidence that suggests that maize dispersed from Mexico and arrived in this region in a state of partial domestication. This study aimed to identify dispersal patterns of maize genetic diversity in this part of the continent.

METHODS

A total of 170 maize accessions were characterized with 4398 single nucleotide polymorphisms (SNPs) and analysed to determine if maize dispersal was associated with types of endosperm and indigenous language families.

KEY RESULTS

Four genetic groups were identified in the discriminant analysis of principal components and five groups in the cluster analysis (neighbour-joining method). The groups were structured according to the predominance of endosperm types (popcorn, floury, flint/semi-flint). Spatial principal component analysis of genetic variation suggests different dispersal patterns for each endosperm type and can be associated with hypotheses of expansions of different indigenous groups.

CONCLUSIONS

From a possible origin in Southwestern Amazonia, different maize dispersal routes emerged: (1) towards Northern Amazonia, which continued towards the Caatinga and south-eastern Atlantic Forest (Floury); (2) towards Southern Brazil, passing through the Cerrado and Southern Atlantic Forest reaching the Pampa region (Floury); and (3) along the Atlantic Coast, following Tupi movements originating from two separate expansions: one (Tupinamba) from north to south, and the other (Guarani) in the opposite direction, from south to north (flint, floury and popcorn).

Genetic Characterization by SSR Markers of a Comprehensive Wine Grape Collection Conserved at Rancho de la Merced (Andalusia, Spain)

The IFAPA research center “Rancho de la Merced” (Jerez, Spain) hosts one of the oldest and most diverse grapevine germplasm repositories in Europe, and is aimed at providing feasible solutions to deal with any agronomic trait by exploring its genetic variability and by means of association and Deoxyribonucleic Acid (DNA) editing studies. In this work, we focused on a wine and dual-use grapevine subcollection that consists of 930 accessions. Genetic analysis allowed to identify 521 unique genotypes. After comparing them with several databases, matches were found for 476 genetic profiles while the remaining 45 have not been previously described. Combination with clustering analysis suggested a total pool of 481 Vitis vinifera accessions that included some table cultivars. Several synonymies, homonymies and mislabeling have also been detected. Structure analysis allowed identifying six clusters according to eco-geographic cultivation areas and one additional group including non-vinifera accessions. Diversity analysis pointed out that Spanish Mediterranean varieties are genetically closer to oriental genotypes than to European varieties typical of oceanic and continental climates. The origin of Spanish varieties is discussed in depth considering our data and previous studies. Analysis of molecular variance partition confirmed a well-structured germplasm, although differentiation among groups had a much lower effect on genetic variability than differences within groups, which are strongly related to a very high heterozygosity. A core collection that covers all allele richness is proposed. It is constituted of about 13% of total accessions, and each cluster inferred by structure analysis is represented.

Population differentiation and intraspecific genetic admixture in two Eucryptorrhynchus weevils (Coleoptera: Curculionidae) across northern China

Increasing damage of pests in agriculture and forestry can arise both as a consequence of changes in local species and through the introduction of alien species. In this study, we used population genetics approaches to examine population processes of two pests of the tree-of-heaven trunk weevil (TTW), Eucryptorrhynchus brandti (Harold) and the tree-of-heaven root weevil (TRW), E. scrobiculatus (Motschulsky) on the tree-of-heaven across their native range of China. We analyzed the population genetics of the two weevils based on ten highly polymorphic microsatellite markers. Population genetic diversity analysis showed strong population differentiation among populations of each species, with F ST ranges from 0.0197 to 0.6650 and from -0.0724 to 0.6845, respectively. Populations from the same geographic areas can be divided into different genetic clusters, and the same genetic cluster contained populations from different geographic populations, pointing to dispersal of the weevils possibly being human-mediated. Redundancy analysis showed that the independent effects of environment and geography could account for 93.94% and 29.70% of the explained genetic variance in TTW, and 41.90% and 55.73% of the explained genetic variance in TRW, respectively, indicating possible impacts of local climates on population genetic differentiation. Our study helps to uncover population genetic processes of these local pest species with relevance to control methods.

Lack of Genetic Structure Among Populations of Striped Flea Beetle Phyllotreta striolata (Coleoptera: Chrysomelidae) Across Southern China

The striped flea beetle (SFB) Phyllotreta striolata (Fabricius) (Coleoptera: Chrysomelidae) is a major pest of cruciferous vegetables in southern China. The population diversity and genetic structure of SFB are unknown. Here, we assembled a draft genome for the SFB and characterized the distribution of microsatellites. Then, we developed 12 novel microsatellite markers across the genome. We used a segment of the cox1 gene and newly developed microsatellite markers to genotype the genetic diversity of SFB across southern China. There were 44 mitochondrial haplotypes in the SFB populations, with haplotype 2 as the most widespread. The population genetic differentiation was very low, indicated by FST-values (&lt;0.05 except for Guangxi population with other populations based on cox1), high gene flow (4.10 and 44.88 of cox1 and microsatellite, respectively) and Principal Coordinate Analysis across all populations. Mantel test showed genetic distance in SFB was significantly associated with geographic distance based on microsatellites (R2 = 0.2373, P = 0.014) while result based on cox1 (R2 = 0.0365, P = 0.155) showed no significant difference. The phylogenetic analysis did not find any geographically related clades among all haplotypes. Analyses based on microsatellites showed a lack of population genetic structure among all populations. Our study provides a foundation for the future understanding of the ecology and evolution of SFB and its management.

Environmental differences explain subtle yet detectable genetic structure in a widespread pollinator

BACKGROUND

The environment is a strong driver of genetic structure in many natural populations, yet often neglected in population genetic studies. This may be a particular problem in vagile species, where subtle structure cannot be explained by limitations to dispersal. Consequently, these species might falsely be considered quasi-panmictic and hence potentially mismanaged. A species this might apply to, is the buff-tailed bumble bee (Bombus terrestris), an economically important and widespread pollinator, which is considered to be quasi-panmictic at mainland continental scales. Here we aimed to (i) quantify genetic structure in 21+ populations of the buff-tailed bumble bee, sampled throughout two Eastern European countries, and (ii) analyse the degree to which structure is explained by environmental differences, habitat permeability and geographic distance. Using 12 microsatellite loci, we characterised populations of this species with Fst analyses, complemented by discriminant analysis of principal components and Bayesian clustering approaches. We then applied generalized dissimilarity modelling to simultaneously assess the informativeness of geographic distance, habitat permeability and environmental differences among populations in explaining divergence.

RESULTS

Genetic structure of the buff-tailed bumble bee quantified by means of Fst was subtle and not detected by Bayesian clustering. Discriminant analysis of principal components suggested insignificant but still noticeable structure that slightly exceeded estimates obtained through Fst analyses. As expected, geographic distance and habitat permeability were not informative in explaining the spatial pattern of genetic divergence. Yet, environmental variables related to temperature, vegetation and topography were highly informative, explaining between 33 and 39% of the genetic variation observed.

CONCLUSIONS

In contrast to previous studies reporting quasi-panmixia in continental populations of this species, we demonstrated the presence of subtle population structure related to environmental heterogeneity. Environmental data proved to be highly useful in unravelling the drivers of genetic structure in this vagile and opportunistic species. We highlight the potential of including these data to obtain a better understanding of population structure and the processes driving it in species considered to be quasi-panmictic.

Hybrid zone of a tree in a Cerrado/Atlantic Forest ecotone as a hotspot of genetic diversity and conservation

The Cerrado, the largest Neotropical savanna, and the Brazilian Atlantic Forest form large ecotonal areas where savanna and forest habitats occupy adjacent patches with closely related species occurring side by side, providing opportunities for hybridization. Here, we investigated the evolutionary divergence between the savanna and forest ecotypes of the widely distributed tree Plathymenia reticulata (n = 233 individuals). Genetic structure analysis of P. reticulata was congruent with the recognition of two ecotypes, whose divergence captured the largest proportion of genetic variance in the data (F CT = 0.222 and F ST = 0.307). The ecotonal areas between the Cerrado and the Atlantic Forest constitute a hybrid zone in which a diversity of hybrid classes was observed, most of them corresponding to second-generation hybrids (F2) or backcrosses. Gene flow occurred mainly toward the forest ecotype. The genetic structure was congruent with isolation by environment, and environmental correlates of divergence were identified. The observed pattern of high genetic divergence between ecotypes may reflect an incipient speciation process in P. reticulata. The low genetic diversity of the P. reticulata forest ecotype indicate that it is threatened in areas with high habitat loss on Atlantic Forest. In addition, the high divergence from the savanna ecotype suggests it should be treated as a different unit of management. The high genetic diversity found in the ecotonal hybrid zone supports the view of ecotones as important areas for the origin and conservation of biodiversity in the Neotropics.

Evidence of spatial genetic structure in a snow leopard population from Gansu, China

Understanding the spatial structure of genetic diversity provides insights into a populations' genetic status and enables assessment of its capacity to counteract the effects of genetic drift. Such knowledge is particularly scarce for the snow leopard, a conservation flagship species of Central Asia mountains. Focusing on a snow leopard population in the Qilian mountains of Gansu Province, China, we characterised the spatial genetic patterns by incorporating spatially explicit indices of diversity and multivariate analyses, based on different inertia levels of Principal Component Analysis (PCA). We compared two datasets differing in the number of loci and individuals. We found that genetic patterns were significantly spatially structured and were characterised by a broad geographical division coupled with a fine-scale cline of differentiation. Genetic admixture was detected in two adjoining core areas characterised by higher effective population size and allelic diversity, compared to peripheral localities. The power to detect significant spatial relationships depended primarily on the number of loci, and secondarily on the number of PCA axes. Spatial patterns and indices of diversity highlighted the cryptic structure of snow leopard genetic diversity, likely driven by its ability to disperse over large distances. In combination, the species' low allelic richness and large dispersal ability result in weak genetic differentiation related to major geographical features and isolation by distance. This study illustrates how cryptic genetic patterns can be investigated and analysed at a fine spatial scale, providing insights into the spatially variable isolation effects of both geographic distance and landscape resistance.

Landscape and climatic features drive genetic differentiation processes in a South American coastal plant

BACKGROUND

Historical and ecological processes shape patterns of genetic diversity in plant species. Colonization to new environments and geographical landscape features determine, amongst other factors, genetic diversity within- and differentiation between-populations. We analyse the genetic diversity and population structure of Calibrachoa heterophylla to infer the influence of abiotic landscape features on the level of gene flow in this coastal species of the South Atlantic Coastal Plain.

RESULTS

The C. heterophylla populations located on early-deposited coastal plain regions show higher genetic diversity than those closer to the sea. The genetic differentiation follows a pattern of isolation-by-distance. Landscape features, such as water bodies and wind corridors, and geographical distances equally explain the observed genetic differentiation, whereas the precipitation seasonality exhibits a strong signal for isolation-by-environment in marginal populations. The estimated levels of gene flow suggest that marginal populations had restricted immigration rates enhancing differentiation.

CONCLUSIONS

Topographical features related to coastal plain deposition history influence population differentiation in C. heterophylla. Gene flow is mainly restricted to nearby populations and facilitated by wind fields, albeit without any apparent influence of large water bodies. Furthermore, differential rainfall regimes in marginal populations seem to promote genetic differentiation.

King or royal family? Testing for species boundaries in the King Cobra, Ophiophagus hannah (Cantor, 1836), using morphology and multilocus DNA analyses

In widespread species, the diverse ecological conditions in which the populations occur, and the presence of many potential geographical barriers through their range are expected to have created ample opportunities for the evolution of distinct, often cryptic lineages. In this work, we tested for species boundaries in one such widespread species, the king cobra, Ophiophagus hannah (Cantor, 1836), a largely tropical elapid snake distributed across the Oriental realm. Based on extensive geographical sampling across most of the range of the species, we initially tested for candidate species (CS) using Maximum-Likelihood analysis of mitochondrial genes. We then tested the resulting CS using both morphological data and sequences of three single-copy nuclear genes. We used snapclust to determine the optimal number of clusters in the nuclear dataset, and Bayesian Phylogenetics and Phylogeography (BPP) to test for likely species status. We used non-metric multidimensional scaling (nMDS) analysis for discerning morphological separation. We recovered four independently evolving, geographically separated lineages that we consider Confirmed Candidate Species: (1) Western Ghats lineage; (2) Indo-Chinese lineage (3) Indo-Malayan lineage; (4) Luzon Island lineage, in the Philippine Archipelago. We discuss patterns of lineage divergence, particularly in the context of low morphological divergence, and the conservation implications of recognizing several endemic king cobra lineages.

Genetic analyses reveal demographic decline and population differentiation in an endangered social carnivore, Asiatic wild dog

Deforestation and agricultural intensification have resulted in an alarming change in the global land cover over the past 300 years, posing a threat to species conservation. Dhole is a monophyletic, social canid and, being an endangered and highly forest-dependent species, is more prone to the loss of favorable habitat in the Anthropocene. We determined the genetic differentiation and demographic history of dhole across the tiger reserves of Maharashtra using the microsatellite data of 305 individuals. Simulation-based analyses revealed a 77-85% decline in the major dhole sub-populations. Protected areas have provided refuge to the historically declining dhole population resulting in clustering with strong genetic structure in the remnant dhole population. The historical population decline coincides with the extreme events in the landscape over the past 300 years. The study highlights the pattern of genetic differentiation and diversity of a highly forest-dependent species which can be associated with the loss of forest cover outside tiger reserves. It also warrants attention to develop conservation plans for the remnant surviving population of dholes in India.

Genetic differentiation in an endangered and strongly philopatric, migrant shorebird

Background

Populations living in fragmented habitats may suffer from loss of genetic variation and reduced between-patch dispersal, which are processes that can result in genetic differentiation. This occurs frequently in species with reduced mobility, whereas genetic differentiation is less common among mobile species such as migratory birds. The high dispersal capacity in the latter species usually allows for gene flow even in fragmented landscapes. However, strongly philopatric behaviour can reinforce relative isolation and the degree of genetic differentiation. The Southern Dunlin (Calidris alpina schinzii) is a philopatric, long-distance migratory shorebird and shows reduced dispersal between isolated breeding patches. The endangered population of the Southern Dunlin breeding at the Baltic Sea has suffered from habitat deterioration and fragmentation of coastal meadows. We sampled DNA across the entire population and used 12 polymorphic microsatellite loci to examine whether the environmental changes have resulted in genetic structuring and loss of variation.

Results

We found a pattern of isolation-by-distance across the whole Baltic population and genetic differentiation between local populations, even within the southern Baltic. Observed heterozygosity was lower than expected throughout the range and internal relatedness values were positive indicating inbreeding.

Conclusions

Our results provide long-term, empirical evidence for the theoretically expected links between habitat fragmentation, population subdivision, and gene flow. They also demonstrate a rare case of genetic differentiation between populations of a long-distance migratory species. The Baltic Southern Dunlin differs from many related shorebird species that show near panmixia, reflecting its philopatric life history and the reduced connectivity of its breeding patches. The results have important implications as they suggest that reduced connectivity of breeding habitats can threaten even long-distance migrants if they show strong philopatry during breeding. The Baltic Southern Dunlin warrants urgent conservation efforts that increase functional connectivity and gene flow between breeding areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01855-0.

Multiscale patterns of isolation by ecology and fine-scale population structure in Texas bobcats

Patterns of spatial genetic variation can be generated by a variety of ecological processes, including individual preferences based on habitat. These ecological processes act at multiple spatial and temporal scales, generating scale-dependent effects on gene flow. In this study, we focused on bobcats (Lynx rufus), a highly mobile, generalist felid that exhibits ecological and behavioral plasticity, high abundance, and broad connectivity across much of their range. However, bobcats also show genetic differentiation along habitat breaks, a pattern typically observed in cases of isolation-by-ecology (IBE). The IBE observed in bobcats is hypothesized to occur due to habitat-biased dispersal, but it is unknown if this occurs at other habitat breaks across their range or at what spatial scale IBE becomes most apparent. Thus, we used a multiscale approach to examine isolation by ecology (IBE) patterns in bobcats (Lynx rufus) at both fine and broad spatial scales in western Texas. We genotyped 102 individuals at nine microsatellite loci and used partial redundancy analysis (pRDA) to test if a suite of landscape variables influenced genetic variation in bobcats. Bobcats exhibited a latitudinal cline in population structure with a spatial signature of male-biased dispersal, and no clear barriers to gene flow. Our pRDA tests revealed high genetic similarity in similar habitats, and results differed by spatial scale. At the fine spatial scale, herbaceous rangeland was an important influence on gene flow whereas mixed rangeland and agriculture were significant at the broad spatial scale. Taken together, our results suggests that complex interactions between spatial-use behavior and landscape heterogeneity can create non-random gene flow in highly mobile species like bobcats. Furthermore, our results add to the growing body of data highlighting the importance of multiscale study designs when assessing spatial genetic structure.

No leading-edge effect in North Atlantic harbor porpoises: Evolutionary and conservation implications

Understanding species responses to past environmental changes can help forecast how they will cope with ongoing climate changes. Harbor porpoises are widely distributed in the North Atlantic and were deeply impacted by the Pleistocene changes with the split of three subspecies. Despite major impacts of fisheries on natural populations, little is known about population connectivity and dispersal, how they reacted to the Pleistocene changes, and how they will evolve in the future. Here, we used phylogenetics, population genetics, and predictive habitat modeling to investigate population structure and phylogeographic history of the North Atlantic porpoises. A total of 925 porpoises were characterized at 10 microsatellite loci and one quarter of the mitogenome (mtDNA). A highly divergent mtDNA lineage was uncovered in one porpoise off Western Greenland, suggesting that a cryptic group may occur and could belong to a recently discovered mesopelagic ecotype off Greenland. Aside from it and the southern subspecies, spatial genetic variation showed that porpoises from both sides of the North Atlantic form a continuous system belonging to the same subspecies (Phocoena phocoena phocoena). Yet, we identified important departures from random mating and restricted dispersal forming a highly significant isolation by distance (IBD) at both mtDNA and nuclear markers. A ten times stronger IBD at mtDNA compared with nuclear loci supported previous evidence of female philopatry. Together with the lack of spatial trends in genetic diversity, this IBD suggests that migration-drift equilibrium has been reached, erasing any genetic signal of a leading-edge effect that accompanied the predicted recolonization of the northern habitats freed from Pleistocene ice. These results illuminate the processes shaping porpoise population structure and provide a framework for designing conservation strategies and forecasting future population evolution.

An overview of current population genomics methods for the analysis of whole-genome resequencing data in eukaryotes

Characterizing the population history of a species and identifying loci underlying local adaptation is crucial in functional ecology, evolutionary biology, conservation and agronomy. The constant improvement of high-throughput sequencing techniques has facilitated the production of whole genome data in a wide range of species. Population genomics now provides tools to better integrate selection into a historical framework, and take into account selection when reconstructing demographic history. However, this improvement has come with a profusion of analytical tools that can confuse and discourage users. Such confusion limits the amount of information effectively retrieved from complex genomic data sets, and impairs the diffusion of the most recent analytical tools into fields such as conservation biology. It may also lead to redundancy among methods. To address these isssues, we propose an overview of more than 100 state-of-the-art methods that can deal with whole genome data. We summarize the strategies they use to infer demographic history and selection, and discuss some of their limitations. A website listing these methods is available at www.methodspopgen.com.

Spatial familial networks to infer demographic structure of wild populations

In social species, reproductive success and rates of dispersal vary among individuals resulting in spatially structured populations. Network analyses of familial relationships may provide insights on how these parameters influence population-level demographic patterns. These methods, however, have rarely been applied to genetically derived pedigree data from wild populations.Here, we use parent-offspring relationships to construct familial networks from polygamous boreal woodland caribou (Rangifer tarandus caribou) in Saskatchewan, Canada, to inform recovery efforts. We collected samples from 933 individuals at 15 variable microsatellite loci along with caribou-specific primers for sex identification. Using network measures, we assess the contribution of individual caribou to the population with several centrality measures and then determine which measures are best suited to inform on the population demographic structure. We investigate the centrality of individuals from eighteen different local areas, along with the entire population.We found substantial differences in centrality of individuals in different local areas, that in turn contributed differently to the full network, highlighting the importance of analyzing networks at different scales. The full network revealed that boreal caribou in Saskatchewan form a complex, interconnected familial network, as the removal of edges with high betweenness did not result in distinct subgroups. Alpha, betweenness, and eccentricity centrality were the most informative measures to characterize the population demographic structure and for spatially identifying areas of highest fitness levels and family cohesion across the range. We found varied levels of dispersal, fitness, and cohesion in family groups. Synthesis and applications: Our results demonstrate the value of different network measures in assessing genetically derived familial networks. The spatial application of the familial networks identified individuals presenting different fitness levels, short- and long-distance dispersing ability across the range in support of population monitoring and recovery efforts.