A single-nucleotide polymorphism-based approach for rapid and cost-effective genetic wolf monitoring in Europe based on noninvasively collected samples.

Noninvasive genetics based on microsatellite markers has become an indispensable tool for wildlife monitoring and conservation research over the past decades. However, microsatellites have several drawbacks, such as the lack of standardisation between laboratories and high error rates. Here, we propose an alternative single-nucleotide polymorphism (SNP)-based marker system for noninvasively collected samples, which promises to solve these problems. Using nanofluidic SNP genotyping technology (Fluidigm), we genotyped 158 wolf samples (tissue, scats, hairs, urine) for 192 SNP loci selected from the Affymetrix v2 Canine SNP Array. We carefully selected an optimised final set of 96 SNPs (and discarded the worse half), based on assay performance and reliability. We found rates of missing data in this SNP set of <10% and genotyping error of ~1%, which improves genotyping accuracy by nearly an order of magnitude when compared to published data for other marker types. Our approach provides a tool for rapid and cost-effective genotyping of noninvasively collected wildlife samples. The ability to standardise genotype scoring combined with low error rates promises to constitute a major technological advancement and could establish SNPs as a standard marker for future wildlife monitoring.

Real-time assessment of hybridization between wolves and dogs: combining noninvasive samples with ancestry informative markers.

Wolves and dogs provide a paradigmatic example of the ecological and conservation implications of hybridization events between wild and domesticated forms. However, our understanding of such implications has been traditionally hampered by both high genetic similarity and the difficulties in obtaining tissue samples (TS), which limit our ability to assess ongoing hybridization events. To assess the occurrence and extension of hybridization in a pack of wolf-dog hybrids in northwestern Iberia, we compared the power of 52 nuclear markers implemented on TS with a subset of 13 ancestry informative markers (AIMs) typed in noninvasive samples (NIS). We demonstrate that the 13 AIMs are as accurate as the 52 markers that were chosen without regard to the power to differentiate between wolves and dogs, also having the advantage of being rapidly screened on NIS. The efficiency of AIMs significantly outperformed ten random sets of similar size and an additional commercial set of 18 markers. Bayesian clustering analysis implemented on AIMs and NIS identified nine hybrids, two wolves and two dogs. Four hybrids were unambiguously assigned to F1xWolf backcrosses. Our approach (AIMs + NIS) overcomes previous difficulties related to sample availability and informative power of markers, allowing a quick identification of wolf-dog hybrids in the first phases of hybridization episodes. This provides managers with a reliable tool to evaluate hybridization and estimate the success of their actions. This approach may be easily adapted for other pairs of wild/domesticated species, thus improving our understanding of the introgression of domestication genes into natural populations.