Assessing polar bear (Ursus maritimus) population structure in the Hudson Bay region using SNPs

Empirical landscape genetic comparison of single nucleotide polymorphisms and microsatellites in three arid-zone mammals with high dispersal capacity

Landscape genetics is increasingly transitioning away from microsatellites, with single nucleotide polymorphisms (SNPs) providing increased resolution for detecting patterns of spatial-genetic structure. This is particularly pertinent for research in arid-zone mammals due to challenges associated with unique life history traits, such as boom-bust population dynamics and long-distance dispersal capacities. Here, we provide a case study comparing SNPs versus microsatellites for testing three explicit landscape genetic hypotheses (isolation-by-distance, isolation-by-barrier, and isolation-by-resistance) in a suite of small, arid-zone mammals in the Pilbara region of Western Australia. Using clustering algorithms, Mantel tests, and linear mixed effects models, we compare functional connectivity between genetic marker types and across species, including one marsupial, Ningaui timealeyi, and two native rodents, Pseudomys chapmani and P. hermannsburgensis. SNPs resolved subtle genetic structuring not detected by microsatellites, particularly for N. timealeyi where two genetic clusters were identified. Furthermore, stronger signatures of isolation-by-distance and isolation-by-resistance were detected when using SNPs, and model selection based on SNPs tended to identify more complex resistance surfaces (i.e., composite surfaces of multiple environmental layers) in the best-performing models. While we found limited evidence for physical barriers to dispersal across the Pilbara for all species, we found that topography, substrate, and soil moisture were the main environmental drivers shaping functional connectivity. Our study demonstrates that new analytical and genetic tools can provide novel ecological insights into arid landscapes, with potential application to conservation management through identifying dispersal corridors to mediate the impacts of ongoing habitat fragmentation in the region.

Linking genetic, morphological, and behavioural divergence between inland island and mainland deer mice

The island syndrome hypothesis (ISH) stipulates that, as a result of local selection pressures and restricted gene flow, individuals from island populations should differ from individuals within mainland populations. Specifically, island populations are predicted to contain individuals that are larger, less aggressive, more sociable, and that invest more in their offspring. To date, tests of the ISH have mainly compared oceanic islands to continental sites, and rarely smaller spatial scales such as inland watersheds. Here, using a novel set of genome-wide SNP markers in wild deer mice (Peromyscus maniculatus) we conducted a genomic assessment of predictions underlying the ISH in an inland riverine island system: analysing island-mainland population structure, and quantifying heritability of phenotypes thought to underlie the ISH. We found clear genomic differentiation between the island and mainland populations and moderate to high marker-based heritability estimates for overall variation in traits previously found to differ in line with the ISH between mainland and island locations. F_ST outlier analyses highlighted 12 loci associated with differentiation between mainland and island populations. Together these results suggest that the island populations examined are on independent evolutionary trajectories, the traits considered have a genetic basis (rather than phenotypic variation being solely due to phenotypic plasticity). Coupled with the previous results showing significant phenotypic differentiation between the island and mainland groups in this system, this study suggests that the ISH can hold even on a small spatial scale.

Sea ice reduction drives genetic differentiation among Barents Sea polar bears

Loss of Arctic sea ice owing to climate change is predicted to reduce both genetic diversity and gene flow in ice-dependent species, with potentially negative consequences for their long-term viability. Here, we tested for the population-genetic impacts of reduced sea ice cover on the polar bear (Ursus maritimus) sampled across two decades (1995-2016) from the Svalbard Archipelago, Norway, an area that is affected by rapid sea ice loss in the Arctic Barents Sea. We analysed genetic variation at 22 microsatellite loci for 626 polar bears from four sampling areas within the archipelago. Our results revealed a 3-10% loss of genetic diversity across the study period, accompanied by a near 200% increase in genetic differentiation across regions. These effects may best be explained by a decrease in gene flow caused by habitat fragmentation owing to the loss of sea ice coverage, resulting in increased inbreeding of local polar bears within the focal sampling areas in the Svalbard Archipelago. This study illustrates the importance of genetic monitoring for developing adaptive management strategies for polar bears and other ice-dependent species.

Are tissue samples obtained via remote biopsy useful for fatty acid-based diet analyses in a free-ranging carnivore?

Fundamental knowledge on free-ranging animals has been obtained through capture-based studies; however, these may be logistically intensive, financially expensive, and potentially inconsistent with local cultural values. Genetic mark–recapture using remote tissue sampling has emerged as a less invasive alternative to capture-based population surveys but provides fewer opportunities to collect samples and measurements for broader ecological studies. We compared lipid content, fatty acid (FA) composition, and diet estimates from adipose tissue of polar bears (Ursus maritimus) obtained from two collection methods: remote biopsies (n = 138) sampled from helicopters and hunter-collected tissue (n = 499) from bears harvested in Davis Strait and Gulf of Boothia, Nunavut, 2010 – 2018. Lipid content of adipose tissue was lower in remote biopsies than harvest samples likely because remote biopsies removed only the outermost layer of subcutaneous tissue, rather than the more metabolically dynamic innermost tissue obtained from harvest samples. In contrast, FA composition was similar between the two collection methods with relatively small proportional differences in individual FAs. For diet estimates in Davis Strait, collection method was not a predictor of prey contribution to diet. In Gulf of Boothia, collection method was a predictor for some prey types, but the differences were relatively minor; the rank order of prey types was similar (e.g., ringed seal; Pusa hispida was consistently the primary prey in diets) and prey proportions differed by < 6% between the collection methods. Results from both methods showed that diets varied by geographic area, season, year, age class, and sex. Our study demonstrates that adipose tissue from remote biopsy provides reliable estimates of polar bear diet based on FA analysis and can be used to monitor underlying ecological changes in Arctic marine food webs.

The design and application of a 50 K SNP chip for a threatened Aotearoa New Zealand passerine, the hihi

Next-generation sequencing has transformed the fields of ecological and evolutionary genetics by allowing for cost-effective identification of genome-wide variation. Single nucleotide polymorphism (SNP) arrays, or "SNP chips", enable very large numbers of individuals to be consistently genotyped at a selected set of these identified markers, and also offer the advantage of being able to analyse samples of variable DNA quality. We used reduced representation restriction-aided digest sequencing (RAD-seq) of 31 birds of the threatened hihi (Notiomystis cincta; stitchbird) and low-coverage whole genome sequencing (WGS) of 10 of these birds to develop an Affymetrix 50 K SNP chip. We overcame the limitations of having no hihi reference genome and a low quantity of sequence data by separate and pooled de novo assembly of each of the 10 WGS birds. Reads from all individuals were mapped back to these de novo assemblies to identify SNPs. A subset of RAD-seq and WGS SNPs were selected for inclusion on the chip, prioritising SNPs with the highest quality scores whose flanking sequence uniquely aligned to the zebra finch (Taeniopygia guttata) genome. Of the 58,466 SNPs manufactured on the chip, 72% passed filtering metrics and were polymorphic. By genotyping 1,536 hihi on the array, we found that SNPs detected in multiple assemblies were more likely to successfully genotype, representing a cost-effective approach to identify SNPs for genotyping. Here, we demonstrate the utility of the SNP chip by describing the high rates of linkage disequilibrium in the hihi genome, reflecting the history of population bottlenecks in the species.

Role of individual dispersal in genetic resilience in fluctuating populations of the gray-sided vole Myodes rufocanus

Population densities of the gray-sided vole Myodes rufocanus fluctuate greatly within and across years in Japan. Here, to investigate the role of individual dispersal in maintaining population genetic diversity, we examined how genetic diversity varied during fluctuations in density by analyzing eight microsatellite loci in voles sampled three times per year for 5 years, using two fixed trapping grids (approximately 0.5 ha each). At each trapping session, all captured voles at each trapping grid were removed. The STRUCTURE program was used to analyze serially collected samples to examine how population crashes were related to temporal variability, based on local-scale genetic compositions in each population. In total, 461 and 527 voles were captured at each trapping grid during this study. The number of voles captured during each trapping session (i.e., vole density) varied considerably at both grids. Although patterns in fluctuations were not synchronized between grids, the peak densities were similar. At both grids, the mean allele number recorded at each trapping session was strongly, positively, and nonlinearly correlated with density. STRUCTURE analyses revealed that the proportions of cluster compositions among individuals at each grid differed markedly before and after the crash phase, implying the long-distance dispersal of voles from remote areas at periods of low density. The present results suggest that, in gray-sided vole populations, genetic diversity varies with density largely at the local scale; in contrast, genetic variation in a metapopulation is well-preserved at the regional scale due to the density-dependent dispersal behaviors of individuals. By influencing the dispersal patterns of individuals, fluctuations in density affect metapopulation structure spatially and temporally, while the levels of genetic diversity are preserved in a metapopulation.

SambaR: An R package for fast, easy and reproducible population-genetic analyses of biallelic SNP data sets

SNP data sets can be used to infer a wealth of information about natural populations, including information about their structure, genetic diversity, and the presence of loci under selection. However, SNP data analysis can be a time-consuming and challenging process, not in the least because at present many different software packages are needed to execute and depict the wide variety of mainstream population-genetic analyses. Here, we present SambaR, an integrative and user-friendly R package which automates and simplifies quality control and population-genetic analyses of biallelic SNP data sets. SambaR allows users to perform mainstream population-genetic analyses and to generate a wide variety of ready to publish graphs with a minimum number of commands (less than 10). These wrapper commands call functions of existing packages (including adegenet, ape, LEA, poppr, pcadapt and StAMPP) as well as new tools uniquely implemented in SambaR. We tested SambaR on online available SNP data sets and found that SambaR can process data sets of over 100,000 SNPs and hundreds of individuals within hours, given sufficient computing power. Newly developed tools implemented in SambaR facilitate optimization of filter settings, objective interpretation of ordination analyses, enhance comparability of diversity estimates from reduced representation library SNP data sets, and generate reduced SNP panels and structure-like plots with Bayesian population assignment probabilities. SambaR facilitates rapid population genetic analyses on biallelic SNP data sets by removing three major time sinks: file handling, software learning, and data plotting. In addition, SambaR provides a convenient platform for SNP data storage and management, as well as several new utilities, including guidance in setting appropriate data filters. The SambaR source script, manual and example data set are distributed through GitHub: https://github.com/mennodejong1986/SambaR.

The influence of a priori grouping on inference of genetic clusters: simulation study and literature review of the DAPC method

Inference of genetic clusters is a key aim of population genetics, sparking development of numerous analytical methods. Within these, there is a conceptual divide between finding de novo structure versus assessment of a priori groups. Recently developed, Discriminant Analysis of Principal Components (DAPC), combines discriminant analysis (DA) with principal component (PC) analysis. When applying DAPC, the groups used in the DA (specified a priori or described de novo) need to be carefully assessed. While DAPC has rapidly become a core technique, the sensitivity of the method to misspecification of groups and how it is being empirically applied, are unknown. To address this, we conducted a simulation study examining the influence of a priori versus de novo group designations, and a literature review of how DAPC is being applied. We found that with a priori groupings, distance between genetic clusters reflected underlying F_ST. However, when migration rates were high and groups were described de novo there was considerable inaccuracy, both in terms of the number of genetic clusters suggested and placement of individuals into those clusters. Nearly all (90.1%) of 224 studies surveyed used DAPC to find de novo clusters, and for the majority (62.5%) the stated goal matched the results. However, most studies (52.3%) omit key run parameters, preventing repeatability and transparency. Therefore, we present recommendations for standard reporting of parameters used in DAPC analyses. The influence of groupings in genetic clustering is not unique to DAPC, and researchers need to consider their goal and which methods will be most appropriate.

Canadian polar bear population structure using genome-wide markers

Predicting the consequences of environmental changes, including human-mediated climate change on species, requires that we quantify range-wide patterns of genetic diversity and identify the ecological, environmental, and historical factors that have contributed to it. Here, we generate baseline data on polar bear population structure across most Canadian subpopulations (n = 358) using 13,488 genome-wide single nucleotide polymorphisms (SNPs) identified with double-digest restriction site-associated DNA sequencing (ddRAD). Our ddRAD dataset showed three genetic clusters in the sampled Canadian range, congruent with previous studies based on microsatellites across the same regions; however, due to a lack of sampling in Norwegian Bay, we were unable to confirm the existence of a unique cluster in that subpopulation. These data on the genetic structure of polar bears using SNPs provide a detailed baseline against which future shifts in population structure can be assessed, and opportunities to develop new noninvasive tools for monitoring polar bears across their range.

Genome-Wide Assessment of Diversity and Divergence Among Extant Galapagos Giant Tortoise Species

Genome-wide assessments allow for fuller characterization of genetic diversity, finer-scale population delineation, and better detection of demographically significant units to guide conservation compared with those based on "traditional" markers. Galapagos giant tortoises (Chelonoidis spp.) have long provided a case study for how evolutionary genetics may be applied to advance species conservation. Ongoing efforts to bolster tortoise populations, which have declined by 90%, have been informed by analyses of mitochondrial DNA sequence and microsatellite genotypic data, but could benefit from genome-wide markers. Taking this next step, we used double-digest restriction-site associated DNA sequencing to collect genotypic data at >26000 single nucleotide polymorphisms (SNPs) for 117 individuals representing all recognized extant Galapagos giant tortoise species. We then quantified genetic diversity, population structure, and compared results to estimates from mitochondrial DNA and microsatellite loci. Our analyses detected 12 genetic lineages concordant with the 11 named species as well as previously described structure within one species, C. becki. Furthermore, the SNPs provided increased resolution, detecting admixture in 4 individuals. SNP-based estimates of diversity and differentiation were significantly correlated with those derived from nuclear microsatellite loci and mitochondrial DNA sequences. The SNP toolkit presented here will serve as a resource for advancing efforts to understand tortoise evolution, species radiations, and aid conservation of the Galapagos tortoise species complex.

Geographical assignment of polar bears using multi-element isoscapes

Wide-ranging apex predators are among the most challenging of all fauna to conserve and manage. This is especially true of the polar bear (Ursus maritimus), an iconic predator that is hunted in Canada and threatened by global climate change. We used combinations of stable isotopes (¹³C,¹⁵N,²H,¹⁸O) in polar bear hair from > 1000 individuals, sampled from across much of the Canadian Arctic and sub-Arctic, to test the ability of stable isotopic profiles to ‘assign’ bears to (1) predefined managed subpopulations, (2) subpopulations defined by similarities in stable isotope values using quadratic discriminant analysis, and (3) spatially explicit, isotopically distinct clusters derived from interpolated (i.e. ‘kriged’) isotopic landscapes, or ‘isoscapes’, using the partitioning around medoids algorithm. A four-isotope solution provided the highest overall assignment accuracies (~80%) to pre-existing management subpopulations with accuracy rates ranging from ~30–99% (median = 64%). Assignment accuracies of bears to hierarchically clustered ecological groups based on isotopes ranged from ~64–99%. Multivariate assignment to isotopic clusters resulted in highest assignment accuracies of 68% (33–77%), 84% (47–96%) and 74% (53–85%) using two, three and four stable isotope groups, respectively. The resulting spatial structure inherent in the multiple stable isotopic compositions of polar bear tissues is a powerful forensic tool that will, in this case, contribute to the conservation and management of this species. Currently, it is unclear what is driving these robust isotopic patterns and future research is needed to evaluate the processes behind the pattern. Nonetheless, our isotopic approach can be further applied to other apex mammalian predators under threat, such as the large felids, providing that isotopic structure occurs throughout their range.

Comparing Pool-seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost-effective sequencing approaches, namely Pool-seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping-by-sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool-seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool-seq data showed F ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F ST estimates, indicating that individual-based approaches provided more congruent results than Pool-seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost-effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.

Assessing polar bear (Ursus maritimus) population structure in the Hudson Bay region using SNPs

Defining subpopulations using genetics has traditionally used data from microsatellite markers to investigate population structure; however, single‐nucleotide polymorphisms (SNPs) have emerged as a tool for detection of fine‐scale structure. In Hudson Bay, Canada, three polar bear (Ursus maritimus) subpopulations (Foxe Basin (FB), Southern Hudson Bay (SH), and Western Hudson Bay (WH)) have been delineated based on mark–recapture studies, radiotelemetry and satellite telemetry, return of marked animals in the subsistence harvest, and population genetics using microsatellites. We used SNPs to detect fine‐scale population structure in polar bears from the Hudson Bay region and compared our results to the current designations using 414 individuals genotyped at 2,603 SNPs. Analyses based on discriminant analysis of principal components (DAPC) and STRUCTURE support the presence of four genetic clusters: (i) Western—including individuals sampled in WH, SH (excluding Akimiski Island in James Bay), and southern FB (south of Southampton Island); (ii) Northern—individuals sampled in northern FB (Baffin Island) and Davis Strait (DS) (Labrador coast); (iii) Southeast—individuals from SH (Akimiski Island in James Bay); and (iv) Northeast—individuals from DS (Baffin Island). Population structure differed from microsatellite studies and current management designations demonstrating the value of using SNPs for fine‐scale population delineation in polar bears.