Data from: Real-time assessment of hybridization between wolves and dogs: combining non-invasive samples with ancestry informative markers
Godinho, Raquel et al. (2014), Data from: Real-time assessment of hybridization between wolves and dogs: combining non-invasive samples with ancestry informative markers, Dryad, Dataset, https://doi.org/10.5061/dryad.84ph3
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 non-invasive 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.