Genomic Insights into Honey Bee Health: Genetics of Immunity and Colony-level Traits

Abstract

Honey bees (Apis mellifera) are essential pollinators in natural and agricultural ecosystems and a key model for studying social behavior. Despite their ecological and economic importance, managed honey bee colonies have experienced persistently high mortality over the past two decades due to interacting stressors, including pests, pathogens, and environmental pressures. Recent national surveys in Canada by the Canadian Association of Professional Apiculturists and Provincial Apiarists reported winter colony losses of 39.3% during 2024–2025, substantially exceeding long-term averages, with Varroa destructor, associated viral infections, weak fall colonies, and poor queen quality identified as major contributors. At the same time, honey bees have substantial phenotypic and genetic diversity across behavioral, immune, and colony-level traits, many of which show measurable narrow-sense heritability. This standing variation provides an opportunity to investigate the genetic basis of colony resilience and immunity. Advances in next-generation sequencing have enabled genome-wide analyses of complex traits at unprecedented scale and resolution. In this dissertation, Chapter 2 establishes the applied and conceptual foundation by reviewing genomic tools for honey bee health management, including stock certification, lineage monitoring, and marker-assisted selection. Building on this framework, Chapter 3 presents a large-scale genome-wide association study (GWAS) of 1,350 colonies spanning behavioral, social, and immune traits, revealing that colony-level traits are heritable yet highly polygenic, shaped by local adaptation, and influenced by extensive pleiotropy. To connect genotype to function further in Chapter 4, protein quantitative trait locus mapping was done to identify loci and genes regulating innate immune protein abundance and pathogen resistance, finding shared loci that influence both protein expression and pathogen load. Integrating these results, Chapter 5 examines the shared genetic architecture of innate immunity, social immunity, and pathogen-associated traits using network analyses, demonstrating that robust honey bee defense is underpinned by interconnected gene networks. Finally, Chapter 6 characterizes understudied short insertion-deletion (InDel) variants and their contribution to colony-level traits, providing complementary evidence to SNP-based analyses. Overall, my dissertation identifies candidate genes, loci, and different genetic variants associated with honey bee health, immunity, and colony performance. These findings highlight key targets for future functional validation and provide a foundation for exploring how natural genetic variation can inform breeding and management strategies aimed at enhancing colony resilience.