Reliable wolf-dog hybrid detection in Europe using a reduced SNP panel developed for non-invasively collected samples

Background: Understanding the processes that lead to hybridization of wolves and dogs is of scientific and management importance, particularly over large geographical scales, as wolves can disperse great distances. However, a method to efficiently detect hybrids in routine wolf monitoring is lacking. Microsatellites offer only limited resolution due to the low number of markers showing distinctive allele frequencies between wolves and dogs. Moreover, calibration across laboratories is time-consuming and costly. In this study, we selected a panel of 96 ancestry informative markers for wolves and dogs, derived from the Illumina CanineHD Whole-Genome BeadChip (174K). We designed very short amplicons for genotyping on a microfluidic array, thus making the method suitable also for non-invasively collected samples.

Results: Genotypes based on 93 SNPs from wolves sampled throughout Europe, purebred and non-pedigree dogs, and suspected hybrids showed that the new panel accurately identifies parental individuals, first-generation hybrids and first-generation backcrosses to wolves, while second- and third-generation backcrosses to wolves were identified as advanced hybrids in almost all cases. Our results support the hybrid identity of suspect individuals and the non-hybrid status of individuals regarded as wolves. We also show the adequacy of these markers to assess hybridization at a European-wide scale and the importance of including samples from reference populations.

Conclusions: We showed that the proposed SNP panel is an efficient tool for detecting hybrids up to the third-generation backcrosses to wolves across Europe. Notably, the proposed genotyping method is suitable for a variety of samples, including non-invasive and museum samples, making this panel useful for wolf-dog hybrid assessments and wolf monitoring at both continental and different temporal scales.

Methods
Part of the data is genotyped with microfluidic 96.96 Dynamic Arrays™ (Fluidigm Corp., South San Francisco, USA) using the 93 SNP panel developed in the corresponding article. The remaining part of the data is genotyped with CanineHD Whole-Genome BeadChip microarray (Illumina, Inc., San Diego, California, USA) and the 93 SNPs genotypes are extracted from the larger dataset.