Non-invasive genetic monitoring involving citizen science enables reconstruction of current pack dynamics in a re-establishing wolf population.

BACKGROUND: Carnivores are re-establishing in many human-populated areas, where their presence is often contentious. Reaching consensus on management decisions is often hampered by a dispute over the size of the local carnivore population. Understanding the reproductive dynamics and individual movements of the carnivores can provide support for management decisions, but individual-level information can be difficult to obtain from elusive, wide-ranging species. Non-invasive genetic sampling can yield such information, but makes subsequent reconstruction of population history challenging due to incomplete population coverage and error-prone data. Here, we combine a collaborative, volunteer-based sampling scheme with Bayesian pedigree reconstruction to describe the pack dynamics of an establishing grey wolf (Canis lupus) population in south-west Finland, where wolf breeding was recorded in 2006 for the first time in over a century. RESULTS: Using DNA extracted mainly from faeces collected since 2008, we identified 81 individual wolves and assigned credible full parentages to 70 of these and partial parentages to a further 9, revealing 7 breeding pairs. Individuals used a range of strategies to obtain breeding opportunities, including dispersal to established or new packs, long-distance migration and inheriting breeding roles. Gene flow occurred between all packs but inbreeding events were rare. CONCLUSIONS: These findings demonstrate that characterizing ongoing pack dynamics can provide detailed, locally-relevant insight into the ecology of contentious species such as the wolf. Involving various stakeholders in data collection makes these results more likely to be accepted as unbiased and hence reliable grounds for management decisions.

Fish scales and SNP chips: SNP genotyping and allele frequency estimation in individual and pooled DNA from historical samples of Atlantic salmon (Salmo salar).

BACKGROUND: DNA extracted from historical samples is an important resource for understanding genetic consequences of anthropogenic influences and long-term environmental change. However, such samples generally yield DNA of a lower amount and quality, and the extent to which DNA degradation affects SNP genotyping success and allele frequency estimation is not well understood. We conducted high density SNP genotyping and allele frequency estimation in both individual DNA samples and pooled DNA samples extracted from dried Atlantic salmon (Salmo salar) scales stored at room temperature for up to 35 years, and assessed genotyping success, repeatability and accuracy of allele frequency estimation using a high density SNP genotyping array. RESULTS: In individual DNA samples, genotyping success and repeatability was very high (> 0.973 and > 0.998, respectively) in samples stored for up to 35 years; both increased with the proportion of DNA of fragment size > 1000 bp. In pooled DNA samples, allele frequency estimation was highly repeatable (Repeatability = 0.986) and highly correlated with empirical allele frequency measures (Mean Adjusted R2 = 0.991); allele frequency could be accurately estimated in > 95% of pooled DNA samples with a reference group of at least 30 individuals. SNPs located in polyploid regions of the genome were more sensitive to DNA degradation: older samples had lower genotyping success at these loci, and a larger reference panel of individuals was required to accurately estimate allele frequencies. CONCLUSIONS: SNP genotyping was highly successful in degraded DNA samples, paving the way for the use of degraded samples in SNP genotyping projects. DNA pooling provides the potential for large scale population genetic studies with fewer assays, provided enough reference individuals are also genotyped and DNA quality is properly assessed beforehand. We provide recommendations for future studies intending to conduct high-throughput SNP genotyping and allele frequency estimation in historical samples.