Testing a new SNP-chip on the Alpine and Apennine brown bear (Ursus arctos) populations using non-invasive samples

A reduced SNP panel to trace gene flow across southern European wolf populations and detect hybridization with other Canis taxa

Intra- and inter-specific gene flow are natural evolutionary processes. However, human-induced hybridization is a global conservation concern across taxa, and the development of discriminant genetic markers to differentiate among gene flow processes is essential. Wolves (Canis lupus) are affected by hybridization, particularly in southern Europe, where ongoing recolonization of historic ranges is augmenting gene flow among divergent populations. Our aim was to provide diagnostic canid markers focused on the long-divergent Iberian, Italian and Dinaric wolf populations, based on existing genomic resources. We used 158 canid samples to select a panel of highly informative single nucleotide polymorphisms (SNPs) to (i) distinguish wolves in the three regions from domestic dogs (C. l. familiaris) and golden jackals (C. aureus), and (ii) identify their first two hybrid generations. The resulting 192 SNPs correctly identified the five canid groups, all simulated first-generation (F1) hybrids (0.482 ≤ Q_i ≤ 0.512 between their respective parental groups) and all first backcross (BC1) individuals (0.723 ≤ Q_i ≤ 0.827 to parental groups). An assay design and test with invasive and non-invasive canid samples performed successfully for 178 SNPs. By separating natural population admixture from inter-specific hybridization, our reduced panel can help advance evolutionary research, monitoring, and timely conservation management.

Testing the effectiveness of genetic monitoring using genetic non-invasive sampling

Effective conservation requires accurate data on population genetic diversity, inbreeding, and genetic structure. Increasingly, scientists are adopting genetic non-invasive sampling (gNIS) as a cost-effective population-wide genetic monitoring approach. gNIS has, however, known limitations which may impact the accuracy of downstream genetic analyses. Here, using high-quality single nucleotide polymorphism (SNP) data from blood/tissue sampling of a free-ranging koala population (n = 430), we investigated how the reduced SNP panel size and call rate typical of genetic non-invasive samples (derived from experimental and field trials) impacts the accuracy of genetic measures, and also the effect of sampling intensity on these measures. We found that gNIS at small sample sizes (14% of population) can provide accurate population diversity measures, but slightly underestimated population inbreeding coefficients. Accurate measures of internal relatedness required at least 33% of the population to be sampled. Accurate geographic and genetic spatial autocorrelation analysis requires between 28% and 51% of the population to be sampled. We show that gNIS at low sample sizes can provide a powerful tool to aid conservation decision-making and provide recommendations for researchers looking to apply these techniques to free-ranging systems.

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.

Genomic approaches to identify hybrids and estimate admixture times in European wildcat populations

The survival of indigenous European wildcat (Felis silvestris silvestris) populations can be locally threatened by introgressive hybridization with free-ranging domestic cats. Identifying pure wildcats and investigating the ancestry of admixed individuals becomes thus a conservation priority. We analyzed 63k cat Single Nucleotide Polymorphisms (SNPs) with multivariate, Bayesian and gene-search tools to better evaluate admixture levels between domestic and wild cats collected in Europe, timing and ancestry proportions of their hybrids and backcrosses, and track the origin (wild or domestic) of the genomic blocks carried by admixed cats, also looking for possible deviations from neutrality in their inheritance patterns. Small domestic ancestry blocks were detected in the genomes of most admixed cats, which likely originated from hybridization events occurring from 6 to 22 generations in the past. We identified about 1,900 outlier coding genes with excess of wild or domestic ancestry compared to random expectations in the admixed individuals. More than 600 outlier genes were significantly enriched for Gene Ontology (GO) categories mainly related to social behavior, functional and metabolic adaptive processes (wild-like genes), involved in cognition and neural crest development (domestic-like genes), or associated with immune system functions and lipid metabolism (parental-like genes). These kinds of genomic ancestry analyses could be reliably applied to unravel the admixture dynamics in European wildcats, as well as in other hybridizing populations, in order to design more efficient conservation plans.