Reliable Wolf-Dog Hybrid Detection in Europe Using a Reduced SNP Panel Developed for Non-Invasively Collected Samples
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Preprint
- 1 December 2020
- preprint
- Published by Springer Nature in Research Square
Abstract
BackgroundUnderstanding 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. ResultsGenotypes 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 status of individuals regarded as wolves to be 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, as migrants are increasingly more common.ConclusionsCompared to microsatellites, this method is faster to implement, economically more feasible and results are directly comparable across laboratories. The new panel is thus suitable as a new tool for wolf-dog hybrid assessments and monitoring on a continental scale.Keywords
All Related Versions
- Version 1, 2020-12-01, Research Square
- Published version: BMC Genomics, 22 (1), 1.