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

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 queen...

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Bibliographic Details
Published in:Ecology and evolution 2024-11, Vol.14 (11), p.e70554-n/a
Main Authors: Dogantzis, Kathleen A., Patel, Harshilkumar, Rose, Stephen, Conflitti, Ida M., Dey, Alivia, Tiwari, Tanushree, Chapman, Nadine C., Kadri, Samir M., Patch, Harland M., Muli, Elliud M., Alqarni, Abdulaziz S., Allsopp, Michael H., Zayed, Amro
Format: Article
Language:English
Subjects:
Africanized honey bee
Apis mellifera
Applied Ecology
Assaying
Beekeeping
Bees
biomonitoring
Classification
Colonies
Datasets
Defensive behavior
Entomology
Genetics Notes
Genomes
Genomics
Honey
Hybrids
Machine learning
Mitochondrial DNA
Population
Population Genetics
Populations
Queens
Risk reduction
Single-nucleotide polymorphism
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Summary: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. Africanized bees continue to pose a threat to the apiculture industry in North America. Our genetic assay when coupled with machine learning demonstrates high accuracy in correctly classifying target samples.
ISSN:2045-7758
2045-7758
DOI:10.1002/ece3.70554