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Updated: Jan 10, 2026

Preparation of Virus-Enriched Inoculum for Oral Infection of Honey Bees Apis mellifera
Published on: August 26, 2020
Multi-Genome-Wide association studies provide new insights into the genetic architecture of Varroa resistance in
Peymaneh Davoodi1, Mohammad Razmkabir2
1Department of Animal Science, Faculty of Agriculture, University of Kurdistan, Sanandaj, Iran. pey.davoodi@gmail.com.
Background:
The Varroa destructor represents one of the most significant global threats to honeybee colonies. Genome-wide association studies (GWAS) play a crucial role in identifying genetic markers associated with Varroa resistance in honeybees. Six scenarios of genome-wide association studies (additive, dominance, and epistatic for each case‒control and quantitative approach) were implemented to analyze SNP markers associated with hygienic behavior in worker bees.
Results:
In additive GWAS (case‒control), 10 SNPs were identified, whereas additive GWAS (quantitative) revealed 23 SNPs. For the dominance GWAS, 2 SNPs were found in the case‒control study, and 13 SNPs were found in the quantitative analysis. Moreover, the epistatic GWAS (case‒control) identified 10 paired SNPs, and the epistasis GWAS (quantitative) revealed 13 paired SNPs associated with uncapping behavior. These scenarios, along with some overlapping findings, highlighted unique SNPs. The results demonstrate that the type of data definition and genetic model used significantly influence the identification of SNPs associated with the uncapping trait. Additionally, combining multiple methods enhances SNP detection and provides deeper insights into the genetic architecture of Varroa resistance. The identified SNPs were distributed across the genome and presented distinct features from the perspective of minor allele frequency across different models. Furthermore, enrichment analysis revealed that genes related to these SNPs are predominantly involved in pathways related to the stress response and immunity.
Conclusions:
Together, our research provides new insights into the genetics underlying varroa resistance in honeybees. By leveraging genomic data and different GWAS models, this study contributes significantly to the understanding of the genetic architecture of varroa resistance.
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