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). (26th December 2016)

• Record Type: Journal Article
• Authors: Muñoz, Irene; Henriques, Dora; Jara, Laura; Johnston, J. Spencer; Chávez‐Galarza, Julio; De La Rúa, Pilar; Pinto, M. Alice
• Is Part Of: Molecular ecology resources. Volume 17:Number 4(2017:Jul.)
• Page Start: 783
• Page End: 795
• Publication Date: 2016-12-26
• Subjects: Apis mellifera mellifera -- dark European honeybee -- honeybee conservation -- introgression -- microsatellites -- SNPs; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.12637
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: The honeybee ( Apis mellifera ) has been threatened by multiple factors including pests and pathogens, pesticides and loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the genetic integrity of the native A. m. mellifera (M‐lineage) is endangered due to trading and intensive queen breeding with commercial subspecies of eastern European ancestry (C‐lineage). Effective conservation actions require reliable molecular tools to identify pure‐bred A. m. mellifera colonies. Microsatellites have been preferred for identification of A. m. mellifera stocks across conservation centres. However, owing to high throughput, easy transferability between laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolving power of a widely utilized microsatellite set to detect structure and introgression with that of different sets that combine a variable number of SNPs selected for their information content and genomic proximity to the microsatellite loci. 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 precision. 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.