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

• Published in: Molecular ecology resources Vol. 15; no. 2; pp. 295 - 305
• Main Authors: Kraus, Robert H. S., vonHoldt, Bridgett, Cocchiararo, Berardino, Harms, Verena, Bayerl, Helmut, Kühn, Ralph, Förster, Daniel W., Fickel, Jörns, Roos, Christian, Nowak, Carsten
• Format: Journal Article
• Language: English
• Published: England Blackwell Publishing Ltd 01.03.2015; Wiley Subscription Services, Inc
• Subjects: Animals; Canis lupus; conservation; Costs and Cost Analysis; Europe; genetic monitoring; Genotyping Techniques - economics; Genotyping Techniques - methods; Polymorphism; Polymorphism, Single Nucleotide; scat sampling; single-nucleotide polymorphism; single-nucleotide polymorphism chip; Time Factors; wildlife management; Wolves - classification; Wolves - genetics; Europe; genetic monitoring; wildlife management; conservation; scat sampling; single-nucleotide polymorphism chip; single-nucleotide polymorphism; Canis lupus
• ISSN: 1755-098X; 1755-0998
• DOI: 10.1111/1755-0998.12307

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.