Abstract:
Hybrid populations of Africanized honey bees (scutellata‐hybrids), notable for their defensive behaviour, have spread rapidly throughout South and North America since their unintentional introduction. Although their migration has slowed, the large‐scale trade and movement of honey bee queens and colonies raise concern over the accidental importation of scutellata‐hybrids to previously unoccupied areas. Therefore, developing an accurate and robust assay to detect scutellata‐hybrids is an important first step toward mitigating risk. Here, we used an extensive population genomic dataset to assess the genomic composition of Apis mellifera native populations and patterns of genetic admixture in North and South American commercial honey bees. We used this dataset to develop a SNP assay, where 80 markers, combined with machine learning classification, can accurately differentiate between scutellata‐hybrids and non‐scutellata‐hybrid commercial colonies. The assay was validated on 1263 individuals from colonies located in Canada, the United States, Australia and Brazil. Notably, we demonstrate that using a reduced SNP set of as few as 10 loci can still provide accurate results.
