Veterinary medicine and science · 2026
Leave-One-Chromosome-Out Association Testing Decodes Uncapping Behaviour in Honeybees During Varroa destructor Infestation.
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Davoodi Peymaneh, Razmkabir Mohammad
Аннотация
BACKGROUND: Uncapping behaviour of Varroa‑infested brood cells is a critical social‑immunity mechanism in honeybees, enabling colonies to detect and remove parasitized brood. This trait reduces mite reproduction and pathogen transmission and is increasingly recognized as a valuable phenotypic marker for breeding Varroa‑resistant colonies.
OBJECTIVES: This study aimed to identify robust genomic markers associated with uncapping behaviour by applying a statistically rigorous GWAS framework that overcomes the potential inflated associations and limited resolution of earlier fixed‑model approaches.
METHODS: Genome‑wide association analyses were performed using linear and logistic mixed models within a leave‑one‑chromosome‑out (MLM‑LOCO) design on Affymetrix 44K single-nucleotide polymorphism (SNP) array data. This framework explicitly accounted for population structure and relatedness, thereby improving model accuracy and reducing false‑positive signals.
RESULTS: Both linear and logistic models identified seven loci each, with substantial overlap between approaches. Across analyses, three SNPs and nine genes consistently emerged as strong candidate genomic markers for uncapping behaviour in response to Varroa infestation. These genes encompass diverse biological functions, including immune defence, epithelial integrity, vesicle trafficking, sensory perception, metabolism, RNA regulation, stress response, and apoptosis, underscoring the complex molecular architecture underlying this behavioural trait.
CONCLUSIONS: The MLM‑LOCO approach provided enhanced statistical power and eliminated inflated associations observed in fixed‑effect models, yielding a reliable set of candidate loci. These findings establish a solid genomic foundation for selective breeding of Varroa‑resistant colonies and contribute to long‑term strategies for sustainable apiculture and improved pollinator health.
OBJECTIVES: This study aimed to identify robust genomic markers associated with uncapping behaviour by applying a statistically rigorous GWAS framework that overcomes the potential inflated associations and limited resolution of earlier fixed‑model approaches.
METHODS: Genome‑wide association analyses were performed using linear and logistic mixed models within a leave‑one‑chromosome‑out (MLM‑LOCO) design on Affymetrix 44K single-nucleotide polymorphism (SNP) array data. This framework explicitly accounted for population structure and relatedness, thereby improving model accuracy and reducing false‑positive signals.
RESULTS: Both linear and logistic models identified seven loci each, with substantial overlap between approaches. Across analyses, three SNPs and nine genes consistently emerged as strong candidate genomic markers for uncapping behaviour in response to Varroa infestation. These genes encompass diverse biological functions, including immune defence, epithelial integrity, vesicle trafficking, sensory perception, metabolism, RNA regulation, stress response, and apoptosis, underscoring the complex molecular architecture underlying this behavioural trait.
CONCLUSIONS: The MLM‑LOCO approach provided enhanced statistical power and eliminated inflated associations observed in fixed‑effect models, yielding a reliable set of candidate loci. These findings establish a solid genomic foundation for selective breeding of Varroa‑resistant colonies and contribute to long‑term strategies for sustainable apiculture and improved pollinator health.