An empirical approach for reliable microsatellite genotyping of wolf DNA from multiple noninvasive sources

Wildlife management and conservation take advantage of the possibility to study free-living populations by collecting and analysing noninvasive samples. Nevertheless, the commonly adopted approaches, aimed at preventing results being affected by genotyping errors, considerably limit the applicability of noninvasive genotyping. An empirical approach is presented for achieving a reliable data set of wolf (Canis lupus) genotypes from multiple sources of DNA collected in a monitored population. This method relies on the relationship between sample quality and amplification outcome, which is ultimately related to the occurrence of typing errors (allelic dropout, false alleles). After DNA extraction, templates are amplified once at each locus and a conservative rating system (Q-score) is adopted to define the quality of single-locus amplifications. A significant relationship was found between quality scores and error rate (ER) (r 2=0.982). Thus it was possible to predict the chance a genotype has of being affected by errors on the basis of its Q-score. Genotypes not reaching a satisfactory confidence level can either be replicated to become reliable or excluded from the data set. Accordingly, in the present case study, 48-73% of all single-locus and 51-53% of all multilocus (ML) genotypes reached a sufficient (99 and 95%, respectively) reliability level after a single amplification per locus. Despite the possible decrease in overall yield, this method could provide a good compromise between accuracy in genotyping and effectiveness in screening large data sets for long-term or large-scale population surveys. However, to achieve complete and reliable data sets, replicated amplifications are necessary for those samples and loci providing poor results.