De novo SNP discovery in the Scandinavian brown bear (Ursus arctos)

Fine scale genetics reveals the subtle negative effects of roads on an endangered bat

The effective management of species with small and fragmented populations requires an in-depth understanding of how the effects of human-induced habitat disturbance shape the structure and gene flow at fine spatial scales. Identification of putative environmental barriers that affect individual exchange among subpopulations is imperative to prevent extinction risks. Here, we investigated how landscape affects the gene flow and relatedness structure of a population of the endangered lesser horseshoe bat (Rhinolophus hipposideros). We also assessed the effects of sexbiased dispersal on genetic relatedness. We genotyped 287 bat samples collected across southern Portugal and developed resistance surfaces for landscape variables hypothesized to affect gene flow. Then, we used spatially explicit models to fit relatedness distance through the resistance surfaces. We found genetic evidence of sex-biased dispersal and identified a significant fine scale structuring in the relatedness regarding females, the philopatric sex. Males displayed uniform levels of relatedness throughout the landscape. The results indicated less relatedness between the female´ from roosts located on proximity of roads than in roosts away from roads. Also, when analysing the sexes together the relatedness on roosts separated by highway were subtly less related in comparison to those occurring on the same side. Roads seem to be major shapers of the contemporary population structure of females, regardless of being relatively recent structures in the landscape. Furthermore, the relatedness patterns detected suggested that high tree density among roosts and continuity of forest patches in broader surrounding areas, promotes the relatedness among individuals. Landscape heterogeneity among roosts slightly decreases genetic relatedness. Nevertheless, those relationships are still weak, suggesting that population structuring driven by those factors is slowly ongoing. Thus, effective management measures should focus on issues for promoting safe road passages and suitable habitat corridors, allowing for the exchange of individuals and gene flow among lesser horseshoe bat roosts.

Phylogeography of ancient and modern brown bears from eastern Eurasia

The brown bear (Ursus arctos) is an iconic carnivoran species of the Northern Hemisphere. Its population history has been studied extensively using mitochondrial markers, which demonstrated signatures of multiple waves of migration, arguably connected with glaciation periods. Among Eurasian brown bears, Siberian populations remain understudied. We have sequenced complete mitochondrial genomes of four ancient (~4.5-40 kya) bears from South Siberia and 19 modern bears from South Siberia and the Russian Far East. Reconstruction of phylogenetic relationships between haplotypes and evaluation of modern population structure have demonstrated that all the studied samples belong to the most widespread Eurasian clade 3. One of the ancient haplotypes takes a basal position relative to the whole of clade 3; the second is basal to the haplogroup 3a (the most common subclade), and two others belong to clades 3a1 and 3b. Modern Siberian bears retain at least some of this diversity; apart from the most common haplogroup 3a, we demonstrate the presence of clade 3b, which was previously found mainly in mainland Eurasia and Northern Japan. Our findings highlight the importance of South Siberia as a refugium for northern Eurasian brown bears and further corroborate the hypothesis of several waves of migration in the Pleistocene.

De novo discovery of SNPs for genotyping endangered sun parakeets (Aratinga solstitialis) in Guyana

Parrots (Psittaciformes) are among the most endangered groups of birds today and remain threatened by habitat loss and exploitation for the live bird trade. Under such conditions, reliable and non-invasive monitoring techniques are crucial for successful conservation measures. In this study, we developed a panel of 86 high quality SNPs for genotyping endangered sun parakeets (Aratinga solstitialis) in Guyana, which form one of the last known breeding populations of this South American species in the wild. Genotyping was tested on different types of samples (blood, feathers, feces, beak and cloacal swabs). While blood performed best, feathers and feces also yielded reliable results and could thus be used as non-invasive sources of DNA for future population monitoring. Discriminant Analysis of Principal Components (DAPC) on genotypes revealed that Guyanese sun parakeets clustered separately from other psittacine species as well as conspecifics from a captive population. A priori known first-order kinships were also adequately detected by the SNP panel. Using a series of experimental contaminations, we found that contamination from other psittacine species and slight contamination (~ 10%) from conspecifics did not prevent successful genotyping and recognition of individuals. We show that instances of higher conspecific contamination (~ 50%) can be detected through an increased level of heterozygosity that falls outside the distribution of uncontaminated samples.

Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

The genomic era has led to an unprecedented increase in the availability of genome-wide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of noninvasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucleotide polymorphism (SNP) panels applicable for microfluidic genotyping of degraded DNA samples, such as faeces or hairs. We demonstrate how microfluidic SNP panels can be optimized to efficiently monitor European wildcat (Felis silvestris S.) populations. We show how panels can be set up in a modular fashion to accommodate informative markers for relevant population genetics questions, such as individual identification, hybridization assessment and the detection of population structure. We discuss various aspects regarding the implementation of reduced SNP panels and provide a framework that will allow both molecular ecologists and practitioners to help bridge the gap between genomics and applied wildlife conservation.

Applying genomic data in wildlife monitoring: Development guidelines for genotyping degraded samples with reduced single nucleotide polymorphism panels

The genomic era has led to an unprecedented increase in the availability of genome-wide data for a broad range of taxa. Wildlife management strives to make use of these vast resources to enable refined genetic assessments that enhance biodiversity conservation. However, as new genomic platforms emerge, problems remain in adapting the usually complex approaches for genotyping of noninvasively collected wildlife samples. Here, we provide practical guidelines for the standardized development of reduced single nucleotide polymorphism (SNP) panels applicable for microfluidic genotyping of degraded DNA samples, such as faeces or hairs. We demonstrate how microfluidic SNP panels can be optimized to efficiently monitor European wildcat (Felis silvestris S.) populations. We show how panels can be set up in a modular fashion to accommodate informative markers for relevant population genetics questions, such as individual identification, hybridization assessment and the detection of population structure. We discuss various aspects regarding the implementation of reduced SNP panels and provide a framework that will allow both molecular ecologists and practitioners to help bridge the gap between genomics and applied wildlife conservation.

Use of molecular data in zoo and aquarium collection management: Benefits, challenges, and best practices

The global zoo and aquarium community widely recognizes that its animal collections and cooperative breeding programs are facing a sustainability crisis. It has become commonly accepted that numerous priority species cannot be maintained unless new management strategies are adopted. While molecular data have the potential to greatly improve management across a range of scenarios, they have been generally underutilized by the zoo and aquarium community. This failure to effectively apply molecular data to collection management has been due, in part, to a paucity of resources within the community on which to base informed decisions about when the use of such data is appropriate and what steps are necessary to successfully integrate data into management. Here, we identify three broad areas of inquiry where molecular data can inform management: 1) taxonomic identification; 2) incomplete or unknown pedigrees; and 3) hereditary disease. Across these topics, we offer a discussion of the advantages, limitations, and considerations for applying molecular data to ex situ animal populations in a style accessible to zoo and aquarium professionals. Ultimately, we intend for this compiled information to serve as a resource for the community to help ensure that molecular projects directly and effectively benefit the long-term persistence of ex situ populations.

Targeted resequencing of coding DNA sequences for SNP discovery in nonmodel species

Targeted capture coupled with high-throughput sequencing can be used to gain information about nuclear sequence variation at hundreds to thousands of loci. Divergent reference capture makes use of molecular data of one species to enrich target loci in other (related) species. This is particularly valuable for nonmodel organisms, for which often no a priori knowledge exists regarding these loci. Here, we have used targeted capture to obtain data for 809 nuclear coding DNA sequences (CDS) in a nonmodel organism, the Eurasian lynx Lynx lynx, using baits designed with the help of the published genome of a related model organism (the domestic cat Felis catus). Using this approach, we were able to survey intraspecific variation at hundreds of nuclear loci in L. lynx across the species' European range. A large set of biallelic candidate SNPs was then evaluated using a high-throughput SNP genotyping platform (Fluidigm), which we then reduced to a final 96 SNP-panel based on assay performance and reliability; validation was carried out with 100 additional Eurasian lynx samples not included in the SNP discovery phase. The 96 SNP-panel developed from CDS performed very successfully in the identification of individuals and in population genetic structure inference (including the assignment of individuals to their source population). In keeping with recent studies, our results show that genic SNPs can be valuable for genetic monitoring of wildlife species.

Discovery of SNPs for individual identification by reduced representation sequencing of moose (Alces alces)

Monitoring of wild animal populations is challenging, yet reliable information about population processes is important for both management and conservation efforts. Access to molecular markers, such as SNPs, enables population monitoring through genotyping of various DNA sources. We have developed 96 high quality SNP markers for individual identification of moose (Alces alces), an economically and ecologically important top-herbivore in boreal regions. Reduced representation libraries constructed from 34 moose were high-throughput de novo sequenced, generating nearly 50 million read pairs. About 50 000 stacks of aligned reads containing one or more SNPs were discovered with the Stacks pipeline. Several quality criteria were applied on the candidate SNPs to find markers informative on the individual level and well representative for the population. An empirical validation by genotyping of sequenced individuals and additional moose, resulted in the selection of a final panel of 86 high quality autosomal SNPs. Additionally, five sex-specific SNPs and five SNPs for sympatric species diagnostics are included in the panel. The genotyping error rate was 0.002 for the total panel and probability of identities were low enough to separate individuals with high confidence. Moreover, the autosomal SNPs were highly informative also for population level analyses. The potential applications of this SNP panel are thus many including investigations of population size, sex ratios, relatedness, reproductive success and population structure. Ideally, SNP-based studies could improve today’s population monitoring and increase our knowledge about moose population dynamics.

A SNP resource for studying North American moose

Background: Moose ( Alces alces) colonized the North American continent from Asia less than 15,000 years ago, and spread across the boreal forest regions of Canada and the northern United States (US).  Contemporary populations have low genetic diversity, due either to low number of individuals in the original migration (founder effect), and/or subsequent population bottlenecks in North America.  Genetic tests based on informative single nucleotide polymorphism (SNP) markers are helpful in forensic and wildlife conservation activities, but have been difficult to develop for moose, due to the lack of a reference genome assembly and whole genome sequence (WGS) data. Methods:  WGS data were generated for four individual moose from the US states of Alaska, Idaho, Wyoming, and Vermont with minimum and average genome coverage depths of 14- and 19-fold, respectively.  Cattle and sheep reference genomes were used for aligning sequence reads and identifying moose SNPs. Results:  Approximately 11% and 9% of moose WGS reads aligned to cattle and sheep genomes, respectively.  The reads clustered at genomic segments, where sequence identity between these species was greater than 95%.  In these segments, average mapped read depth was approximately 19-fold.  Sets of 46,005 and 36,934 high-confidence SNPs were identified from cattle and sheep comparisons, respectively, with 773 and 552 of those having minor allele frequency of 0.5 and conserved flanking sequences in all three species.  Among the four moose, heterozygosity and allele sharing of SNP genotypes were consistent with decreasing levels of moose genetic diversity from west to east.  A minimum set of 317 SNPs, informative across all four moose, was selected as a resource for future SNP assay design. Conclusions:  All SNPs and associated information are available, without restriction, to support development of SNP-based tests for animal identification, parentage determination, and estimating relatedness in North American moose.

Genetic substructure and admixture as important factors in linkage disequilibrium-based estimation of effective number of breeders in recovering wildlife populations

The number of effective breeders (Nb ) and effective population size (Ne ) are population parameters reflective of evolutionary potential, susceptibility to stochasticity, and viability. We have estimated these parameters using the linkage disequilibrium-based approach with LDNE through the latest phase of population recovery of the brown bears (Ursus arctos) in Finland (1993-2010; N = 621). This phase of the recovery was recently documented to be associated with major changes in genetic composition. In particular, differentiation between the northern and the southern genetic cluster declined rapidly within 1.5 generations. Based on this, we have studied effects of the changing genetic structure on Nb and Ne , by comparing estimates for whole Finland with the estimates for the two genetic clusters. We expected a potentially strong relationship between estimate sizes and genetic differentiation, which should disappear as the population recovers and clusters merge. Consistent with this, our estimates for whole Finland were lower than the sum of the estimates of the two genetic clusters and both approaches produced similar estimates in the end. Notably, we also found that admixed genotypes strongly increased the estimates. In all analyses, our estimates for Ne were larger than Nb and likely reflective for brown bears of the larger region of Finland and northwestern Russia. Conclusively, we find that neglecting genetic substructure may lead to a massive underestimation of Nb and Ne . Our results also suggest the need for further empirical analysis focusing on individuals with admixed genotypes and their potential high influence on Nb and Ne .

Assessing SNP genotyping of noninvasively collected wildlife samples using microfluidic arrays

Noninvasively collected samples are a common source of DNA in wildlife genetic studies. Currently, single nucleotide polymorphism (SNP) genotyping using microfluidic arrays is emerging as an easy-to-use and cost-effective methodology. Here we assessed the performance of microfluidic SNP arrays in genotyping noninvasive samples from grey wolves, European wildcats and brown bears, and we compared results with traditional microsatellite genotyping. We successfully SNP-genotyped 87%, 80% and 97% of the wolf, cat and bear samples, respectively. Genotype recovery was higher based on SNPs, while both marker types identified the same individuals and provided almost identical estimates of pairwise differentiation. We found that samples for which all SNP loci were scored had no disagreements across the three replicates (except one locus in a wolf sample). Thus, we argue that call rate (amplification success) can be used as a proxy for genotype quality, allowing the reduction of replication effort when call rate is high. Furthermore, we used cycle threshold values of real-time PCR to guide the choice of protocols for SNP amplification. Finally, we provide general guidelines for successful SNP genotyping of degraded DNA using microfluidic technology.

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.

Conservation priorities for endangered Indian tigers through a genomic lens

Tigers have lost 93% of their historical range worldwide. India plays a vital role in the conservation of tigers since nearly 60% of all wild tigers are currently found here. However, as protected areas are small (<300 km² on average), with only a few individuals in each, many of them may not be independently viable. It is thus important to identify and conserve genetically connected populations, as well as to maintain connectivity within them. We collected samples from wild tigers (Panthera tigris tigris) across India and used genome-wide SNPs to infer genetic connectivity. We genotyped 10,184 SNPs from 38 individuals across 17 protected areas and identified three genetically distinct clusters (corresponding to northwest, southern and central India). The northwest cluster was isolated with low variation and high relatedness. The geographically large central cluster included tigers from central, northeastern and northern India, and had the highest variation. Most genetic diversity (62%) was shared among clusters, while unique variation was highest in the central cluster (8.5%) and lowest in the northwestern one (2%). We did not detect signatures of differential selection or local adaptation. We highlight that the northwest population requires conservation attention to ensure persistence of these tigers.

Wolf population genetics in Europe: a systematic review, meta-analysis and suggestions for conservation and management

The grey wolf (Canis lupus) is an iconic large carnivore that has increasingly been recognized as an apex predator with intrinsic value and a keystone species. However, wolves have also long represented a primary source of human-carnivore conflict, which has led to long-term persecution of wolves, resulting in a significant decrease in their numbers, genetic diversity and gene flow between populations. For more effective protection and management of wolf populations in Europe, robust scientific evidence is crucial. This review serves as an analytical summary of the main findings from wolf population genetic studies in Europe, covering major studies from the 'pre-genomic era' and the first insights of the 'genomics era'. We analyse, summarize and discuss findings derived from analyses of three compartments of the mammalian genome with different inheritance modes: maternal (mitochondrial DNA), paternal (Y chromosome) and biparental [autosomal microsatellites and single nucleotide polymorphisms (SNPs)]. To describe large-scale trends and patterns of genetic variation in European wolf populations, we conducted a meta-analysis based on the results of previous microsatellite studies and also included new data, covering all 19 European countries for which wolf genetic information is available: Norway, Sweden, Finland, Estonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Germany, Belarus, Russia, Italy, Croatia, Bulgaria, Bosnia and Herzegovina, Greece, Spain and Portugal. We compared different indices of genetic diversity in wolf populations and found a significant spatial trend in heterozygosity across Europe from south-west (lowest genetic diversity) to north-east (highest). The range of spatial autocorrelation calculated on the basis of three characteristics of genetic diversity was 650-850 km, suggesting that the genetic diversity of a given wolf population can be influenced by populations up to 850 km away. As an important outcome of this synthesis, we discuss the most pressing issues threatening wolf populations in Europe, highlight important gaps in current knowledge, suggest solutions to overcome these limitations, and provide recommendations for science-based wolf conservation and management at regional and Europe-wide scales.

Estimating population size using single-nucleotide polymorphism-based pedigree data

Reliable population estimates are an important aspect of sustainable wildlife management and conservation but can be difficult to obtain for rare and elusive species. Here, we test a new census method based on pedigree reconstruction recently developed by Creel and Rosenblatt (2013). Using a panel of 96 single-nucleotide polymorphisms (SNPs), we genotyped fecal samples from two Swedish brown bear populations for pedigree reconstruction. Based on 433 genotypes from central Sweden (CS) and 265 from northern Sweden (NS), the population estimates (N = 630 for CS, N = 408 for NS) fell within the 95% CI of the official estimates. The precision and accuracy improved with increasing sampling intensity. Like genetic capture-mark-recapture methods, this method can be applied to data from a single sampling session. Pedigree reconstruction combined with noninvasive genetic sampling may thus augment population estimates, particularly for rare and elusive species for which sampling may be challenging.

Single nucleotide polymorphism-based dispersal estimates using noninvasive sampling

Quantifying dispersal within wild populations is an important but challenging task. Here we present a method to estimate contemporary, individual-based dispersal distance from noninvasively collected samples using a specialized panel of 96 SNPs (single nucleotide polymorphisms). One main issue in conducting dispersal studies is the requirement for a high sampling resolution at a geographic scale appropriate for capturing the majority of dispersal events. In this study, fecal samples of brown bear (Ursus arctos) were collected by volunteer citizens, resulting in a high sampling resolution spanning over 45,000 km² in Gävleborg and Dalarna counties in Sweden. SNP genotypes were obtained for unique individuals sampled (n = 433) and subsequently used to reconstruct pedigrees. A Mantel test for isolation by distance suggests that the sampling scale was appropriate for females but not for males, which are known to disperse long distances. Euclidean distance was estimated between mother and offspring pairs identified through the reconstructed pedigrees. The mean dispersal distance was 12.9 km (SE 3.2) and 33.8 km (SE 6.8) for females and males, respectively. These results were significantly different (Wilcoxon’s rank-sum test: P-value = 0.02) and are in agreement with the previously identified pattern of male-biased dispersal. Our results illustrate the potential of using a combination of noninvasively collected samples at high resolution and specialized SNPs for pedigree-based dispersal models.

Consequences of a demographic bottleneck on genetic structure and variation in the Scandinavian brown bear

The Scandinavian brown bear went through a major decline in population size approximately 100 years ago, due to intense hunting. After being protected, the population subsequently recovered and today numbers in the thousands. The genetic diversity in the contemporary population has been investigated in considerable detail, and it has been shown that the population consists of several subpopulations that display relatively high levels of genetic variation. However, previous studies have been unable to resolve the degree to which the demographic bottleneck impacted the contemporary genetic structure and diversity. In this study, we used mitochondrial and microsatellite DNA markers from pre- and postbottleneck Scandinavian brown bear samples to investigate the effect of the bottleneck. Simulation and multivariate analysis suggested the same genetic structure for the historical and modern samples, which are clustered into three subpopulations in southern, central and northern Scandinavia. However, the southern subpopulation appears to have gone through a marked change in allele frequencies. When comparing the mitochondrial DNA diversity in the whole population, we found a major decline in haplotype numbers across the bottleneck. However, the loss of autosomal genetic diversity was less pronounced, although a significant decline in allelic richness was observed in the southern subpopulation. Approximate Bayesian computations provided clear support for a decline in effective population size during the bottleneck, in both the southern and northern subpopulations. These results have implications for the future management of the Scandinavian brown bear because they indicate a recent loss in genetic diversity and also that the current genetic structure may have been caused by historical ecological processes rather than recent anthropogenic persecution.