SNPs selected by information content outperform randomly selected microsatellite loci for delineating genetic identification and introgression in the endangered dark European honeybee (Apis mellifera mellifera)
The honeybee (Apis mellifera) has been threatened by multiple factors including pests and pathogens, pesticidesand loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the geneticintegrity of the native A. m. mellifera (M-lineage) is endangered due to trading and intensive queen breeding withcommercial subspecies of eastern European ancestry (C-lineage). Effective conservation actions require reliablemolecular tools to identify pure-bred A. m. mellifera colonies. Microsatellites have been preferred for identificationof A. m. mellifera stocks across conservation centres. However, owing to high throughput, easy transferabilitybetween laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolvingpower of a widely utilized microsatellite set to detect structure and introgression with that of different sets that com-bine a variable number of SNPs selected for their information content and genomic proximity to the microsatelliteloci. Contrary to every SNP data set, microsatellites did not discriminate between the two lineages in the PCA space.Mean introgression proportions were identical across the two marker types, although at the individual level,microsatellites’ performance was relatively poor at the upper range of Q-values, a result reflected by their lower pre-cision. Our results suggest that SNPs are more accurate and powerful than microsatellites for identification of A. m.mellifera colonies, especially when they are selected by information content.
