Accurate Detection of scutellata-Hybrids (Africanized Bees) Using a SNP-Based Diagnostic Assay

Area of Science:

• Genomics
• Entomology
• Animal Science

Background:

• Africanized honey bees (scutellata-hybrids) spread rapidly in the Americas, raising concerns about accidental importation via commercial trade.
• Accurate detection of scutellata-hybrids is crucial for risk mitigation and managing honey bee populations.

Purpose of the Study:

• To develop and validate a robust assay for accurately identifying scutellata-hybrids in commercial honey bee colonies.
• To assess genomic admixture patterns in North and South American honey bees.

Main Methods:

• Utilized an extensive population genomic dataset of Apis mellifera native populations.
• Developed a Single Nucleotide Polymorphism (SNP) assay with 80 markers.
• Employed machine learning classification for differentiating hybrid and non-hybrid colonies.
• Validated the assay on 1263 individuals across Canada, USA, Australia, and Brazil.

Main Results:

• The SNP assay, combined with machine learning, accurately differentiates scutellata-hybrids from non-scutellata-hybrid commercial colonies.
• A reduced SNP set of as few as 10 loci can still provide accurate identification results.
• The assay demonstrated high accuracy across diverse geographical locations.

Conclusions:

• A reliable and efficient SNP-based assay is now available for detecting scutellata-hybrids.
• This assay can aid in preventing the unintended spread of Africanized honey bees through commercial trade.
• The findings support proactive management strategies for honey bee populations globally.