Bees are important global pollinators that play a vital role in maintaining ecosystems and supporting global food production. They also exhibit a diversity of social organization, making them ideal model organisms for studying the evolution of sociality in animals. Recent advancements in genome sequencing have enabled researchers to address longstanding questions about the evolution of social behaviour in bees, particularly in the relatively few species that exhibit complex social structures, such as Apis. Whole genome phylogenies have enhanced our understanding of the complex evolutionary history of bees, providing a foundation for studying the evolution of specific traits, including eusociality. Recent transcriptomic and alternative splicing studies have advanced our understanding of how gene regulation and expression patterns contribute to behavioural plasticity, caste differentiation, and the emergence of social complexity. Comparative genomics across a range of bees with varying social behaviours has aided our understanding of the genomic features associated with social evolution and has shed light on its molecular underpinnings. Genomic approaches like GWAS and population genomic comparisons, combined with advanced sequencing technologies, have revolutionized the study of bee evolution, social behaviour, and environmental interactions. Pollen metabarcoding and environmental DNA (eDNA) techniques are now being used to quantify the intricate and complex interactions between bees and the plants they visit, and to identify other environmental factors, including pathogens that impact bee health. Additionally, techniques like museomics (using DNA from museum specimens) and broader genomic approaches have been instrumental in revealing how bees have been affected by anthropogenic changes. These tools offer valuable insights into population genetics, conservation biology, and the impact of environmental changes on bee populations. These advancements both provide critical insights into the molecular basis of eusociality and species adaptation and offer valuable tools for addressing the urgent challenges facing bee conservation due to anthropogenic change. By leveraging these genomic approaches, researchers can inform strategies for the preservation and sustainable management of bee populations worldwide.

Abstract Maintaining honey bee health in crop production systems is increasingly difficult because worker bees encounter multiple chemical and biological pressures from pesticides and pathogens. How these field-realistic pressures affect molecular physiology across functionally distinct tissues remains poorly understood. Here, we tested whether tissue-resolved proteomics could separate stable tissue-specific patterns from crop-associated molecular changes. To do this, we profiled abdomen, gut, and head proteomes from honey bees collected across four Canadian crop ecosystems over two consecutive years, and integrated these data with pesticide-residue and pathogen-load measurements. Proteomic variation was structured by both tissue identity and crop environment. Tissue-specific proteomic profiles were characterized across samples, whereas crop-associated effects were detected in both years and were stronger in 2021, the second year of the study. Tissue-specific enrichment and network analyses linked the abdomen to lipid catabolism and ubiquitin-proteasome proteostasis, the gut to central carbon metabolism, membrane transport, vesicle trafficking, and cytoskeletal organization, and the head to neurosensory and mitochondrial functions, together with amino-sugar metabolism and vesicle-associated quality-control modules. Among the measured pesticide residues, boscalid was the most reproducible chemical correlate of proteomic variation, with the strongest signal in the gut. Cross-year validation associated boscalid exposure with reduced abundance of gut proteins involved in mitochondrial metabolism, protein quality control, vesicle trafficking, nutrient transport, and biosynthetic pathways. Additionally, integrated proteome-transcriptome-microbiome factor analysis further identified gut-centered components associated with measured stressor variables and linked protein-level variation to coordinated transcriptomic and microbial shifts. Independent-year validation showed that compact crop-associated protein signatures detected in 2020 were also present in 2021. Together, these results show that honey bee tissues maintain stable proteomic identities while showing tissue- and year-specific responses to pesticide and pathogen pressures encountered in crop ecosystems. The gut proteome may specifically provide a sensitive molecular indicator of pesticide-associated perturbation under field conditions.

In this response to comments by Heneberg (2026) on our recent review, "The evolution of bees: insights from 'omic studies," we continue the scientific conversation about evidence linking RNA regulatory mechanisms to phenotypic traits. We acknowledge that studies connecting small noncoding RNAs and alternative splicing to social behavior phenotypes are largely correlational and should be interpreted with an appropriate level of caution. At the same time, we suggest that such findings may still offer valuable insights, given the hypothesized importance of regulatory mechanisms in social evolution and the substantial body of work in model organisms demonstrating causal links between these processes and phenotypic change.

ABSTRACT Environmental DNA (eDNA) has the potential to provide a rapid and non‐invasive screening approach for both honey bee health and foraging behavior. Here, we use eDNA carried in the air within honey bee colonies to analyze fine‐scale temporal patterns of foraging and microbial health, across both seasonal and diel scales. We identified nearly 100 genera of plants and more than 700 bacteria and fungi genera, including the core honey bee gut microbiome almost consistently detected in all samples. We detected wild, ornamental and cultivated plants supporting existing literature on honey bee generalist foraging behavior in urban environments. While overall richness of plant and microbiome remained stable throughout the active season (May to September), plant community composition varied significantly across months, likely reflecting seasonal turnover in local floral resources. At a finer diel scale, nor plant or microbiome richness and composition showed a significant day‐night differences, despite a trend of higher microbiome richness at night, potentially reflecting the accumulation of diverse microbiota from plants brought back in the hive by returning foragers and increased activity within the hive. These results demonstrate how airborne eDNA collected inside the bee hive can provide information on bee health and measure ecological data on a fine temporal scale to provide novel insights into bee ecology.

Summary The honey bee ( Apis mellifera ) gut microbiome plays a central role in host health, yet its variation across agricultural landscapes remains poorly resolved. This study investigates how major environmental stressors, particularly pesticide exposure and RNA virus loadings, shape the honey bee gut microbiome in a large-scale field study conducted across Canada, spanning diverse agroecosystems from British Columbia to Quebec. We identify consistent associations between specific bacterial taxa and major RNA viruses, including enrichment of Serratia marcescens with SBV and depletion of Bombella intestini with BQCV. Pesticide exposure is likewise linked to reproducible shifts in key microbial taxa. Together, these findings reveal that interacting stressors jointly shape the bee gut microbiome and enable prediction of microbiome responses in agroecosystems. Highlights Distinct associations identified between gut bacteria and major bee RNA viruses (BQCV, SBV, LSV, IAPV) Pesticide exposure is linked to reproducible shifts in key microbial taxa Combined virus–pesticide effects form coordinated clusters that predict microbiome variation and specific bacterial responses Integrated modeling demonstrates that environmental stressors can jointly explain microbiome structure beyond crop effects Graphical abstract Schematic overview of potential links between pesticide exposure and RNA virus infection and their effects on the bee gut bacterial community. Solid arrows indicate associations supported by the present study, whereas dashed arrows indicate hypothesized or unresolved interactions. Associations between the presence of specific bee RNA viruses (left) or pesticide residues (right) and changes in the relative abundance of particular gut taxa (pink ↑, increased; blue ↓, decreased). The pesticide subtype is indicated by the icon in the cell (leaf - herbicide, hyphae - fungicide and insect - insecticide). Several bacterial taxa showed reproducible associations with specific viral or pesticide variables, including Bombella intestini, Serratia marcescens, Melissococcus plutonius, Paenibacillus alvei, Apibacter sp. wkB309, and Gilliamella sp. A7. Abbreviations: BQCV Black queen cell virus; LSV, Lake Sinai virus; SBV, Sacbrood virus; IAPV, Israeli acute paralysis virus. (p/n/b) indicate the sample matrix in which the pesticide was detected, namely pollen, nectar, and bee tissue, respectively.

Reproductive division of labour is a defining feature of eusocial insect societies, yet the relative roles of queen and brood signals in shaping the physiology of nestmates remain unresolved. In honey bees ( Apis mellifera ), workers typically remain sterile in the presence of a fertile queen and developing brood. Here we disentangle queen- and brood-derived effects by assessing physiology of workers from colonies with all combinations of queen and brood presence and absence. Queenlessness and broodlessness promoted worker ovary activation additively, with broodlessness exerting a significantly stronger effect. Workers with activated ovaries produced more queen-like pheromone profiles with elevated levels of 9-oxo-( E )-2-decenoic acid and 9-hydroxydec-( E )-2-enoic acid. Proteomic and transcriptomic analyses revealed a profound impact of broodlessness that was partially reversed by concordant queenlessness, consistent with a return to a more typical physiological status as worker reproduction initiates and pheromonal signalling is partially restored. Broodlessness, both alone and in combination with queenlessness, enhanced worker immunocompetence and led to a > 10-fold reduction in adult viral load. These findings collectively identify brood as a central regulator of worker physiology that coordinates reproduction, pheromone signaling, and immunity, revealing a previously underappreciated link between social environment and immunological defense.

ABSTRACT Environmental DNA (eDNA) refers to genetic material collected from the environment and not directly from an organism. eDNA is best known as a tool in aquatic ecology but has been found associated with almost every substrate examined including soils, surfaces, and riding around on other animals. The collection of eDNA from air is one of the most recent advances and has been used to monitor a variety of organisms, including plants, animals, and microorganisms. Current evidence suggests a high turnover rate providing a recent signal for the presence of DNA associated with an organism. Here, we test whether material carried in air can be collected from honey bee hives to evaluate recent foraging behavior and colony health. We sampled air using purpose built “bee safe” air filters operating for 5–6 h at each colony. We successfully recovered plant, fungal and microbial DNA from the air within hives over a 3‐week pilot period. From these data we identified the core honey bee microbiome and plant interaction data representing foraging behavior. We calculated beta diversity to estimate the effects of apiary sites and sampling date on data recovery. We observed that variance in ITS data was influenced by sampling date. Given that honey bees are generalist pollinators our ability to detect temporal signals in associated plant sequence data suggest this method opens new avenues into the ecological analysis of short term foraging behavior at the colony level. In comparison variance in microbial 16S sequencing data was more influenced by sampling location. As the assessment of colony health needs to be localized, spatial variance in these data indicate this may be an important tool in detecting infection. This pilot study demonstrates that colony air filtration has strong potential for the rapid screening of honey bee health and for the study of bee behavior.

Honey bees (Apis mellifera) are vital pollinators in fruit-producing agroecosystems like highbush blueberry (HBB) and cranberry (CRA). However, their health is threatened by multiple interacting stressors, including pesticides, pathogens, and nutritional changes. We tested the hypothesis that distinct agricultural ecosystems-with different combinations of agrochemical exposure, pathogen loads, and floral resources-elicit ecosystem-specific, tissue-level molecular responses in honey bees. We conducted an integrated multi-omics analysis using RNA-sequencing (RNA-seq), proteomics, and gut microbiome profiling across three key tissue types (head, abdomen, and gut) of honey bees collected from two agroecosystems over two field seasons. Quantification was performed for pesticide residues, pathogen loads (Nosema spp., Varroa destructor, and multiple viruses), and gut microbiota. Weighted gene co-expression network analysis (WGCNA) revealed tissue-specific protein modules with ecosystem-associated patterns, which differed from RNA co-expression networks. Microbiome composition also varied, with key genera like Gilliamella, Snodgrassella, and Bartonella correlating with metabolic modules. These findings underscore the complex, environment-dependent impacts of agroecosystem conditions on bee health. Our study provides a system-level understanding of how combined pesticide, pathogen, and parasitic stressors, mediated by diet and microbiome, shape molecular phenotypes in honey bees-informing strategies for pollinator protection in managed landscapes.Summary This study provides a comprehensive multi-omics analysis of honey bees foraging in blueberry and cranberry agroecosystems, offering novel insights into the molecular mechanisms underlying pollinator health in managed crop environments. By integrating transcriptomic, proteomic, and microbiome profiling across key tissues-head, abdomen, and gut-we reveal how environmental stressors, including pesticide exposure, pathogen infections, and parasitic infestations (e.g., Varroa destructor), differentially impact bee physiology and microbiome composition. Our findings highlight tissue-specific responses to these stressors, with distinct metabolic pathway alterations observed in each tissue. Proteomic and transcriptomic analyses uncovered dysregulated pathways linked to oxidative phosphorylation and protein synthesis, while microbiome analysis revealed crop-dependent shifts in gut bacterial communities, suggesting potential roles in pesticide detoxification and immune modulation. Notably, we identified key molecular biomarkers associated with stress adaptation, which may serve as early indicators of colony health deterioration. This research underscores the need for a system-level approach to understanding pollinator stress in agricultural landscapes. By elucidating the interactions between diet, pesticide residues, pathogen loads, and molecular stress responses, our study provides a foundation for targeted conservation strategies aimed at mitigating environmental risks and improving pollination sustainability in agroecosystems.

The Western honey bee (Apis mellifera) plays an essential role in agriculture around the world. In Canada, honey bees contribute up to 7 billion in economic value annually by pollinating crops and producing honey. However, since 2006–2007 North American beekeepers have lost more than a quarter of their colonies each winter. In recent years, the losses have been up to 50

Honey bee viruses are serious pathogens that can cause poor colony health and productivity. We analyzed a multi-year longitudinal dataset of abundances of nine honey bee viruses (deformed wing virus A, deformed wing virus B, black queen cell virus, sacbrood virus, Lake Sinai virus, Kashmir bee virus, acute bee paralysis virus, chronic bee paralysis virus, and Israeli acute paralysis virus) in colonies located across Canada to describe broad trends in virus intensity and occurrence among regions and years. We also tested climatic variables (temperature, wind speed, and precipitation) as predictors in an effort to understand possible drivers underlying seasonal patterns in viral prevalence. Temperature was a significant positive predictor of the total number of viruses per sample, which was highest in British Columbia (mean = 5.0). Lake Sinai virus (LSV) was the most prevalent overall (at 89%) and had the highest infection intensity, at an average of 3.9 x 108 copies per bee. Acute bee paralysis virus was the least prevalent virus (at 4.7%) and had the lowest infection intensity (1.9 x 105 copies per bee). Surprisingly, including Varroa abundance as a covariate did not significantly improve model fit for any virus. All viruses, except Kashmir bee virus, varied by region, and one or more climatic variables were significant predictors for six of the nine viruses. Although climatic effects were often inconsistent among individual viruses, we show that climatic variables can be better predictors of virus intensity and occurrence than Varroa mite abundance, at least when infestation rates are low.

Studies investigating social evolution often focus on species that are obligately eusocial, where presumably all of the adaptive genetic changes associated with sociality have already been completed. To fully understand eusociality, we must study species with facultative social behaviour. The small carpenter bee Ceratina calcarata is an ideal model for studying the genetics and molecular biology of eusocial evolution as it can exhibit both subsocial behaviour with parental care and social behaviour facilitated by the altruistic dwarf eldest daughter. Here, we sequenced the genomes of subsocial and social C. calcarata to identify mutations and genes associated with social behaviour and used these data to test several hypotheses related to the evolution of eusociality. Many single nucleotide polymorphisms that had high levels of genetic differentiation (Fst) between social and subsocial C. calcarata were in or near genes or regions important for regulating gene expression. These results are consistent with the Genetic Toolkit Hypothesis of eusocial evolution. Our findings suggest that the low behavioural complexity observed in C. calcarata may involve modulation of existing regulatory genes and gene networks to generate phenotypes associated with social behaviour.

Behavior is a complex trait that is often controlled by the interaction of many genes and the environment. Studying the genetics of behavior is an important endeavor for both understanding how genes produce behavioral phenotypes, and how genes underlying behavior evolve. Genomics has provided several new avenues to study the genetic architecture and evolution of behavior in animals. Primarily, analysis of individual genomes from populations that vary with respect to phenotype has provided a powerful way to identify mutations and genes influencing behavior. Additionally, analysis of neuro-transcriptomes of individuals performing different behaviors helps illuminate the genetic and molecular networks regulating behavior and behavioral plasticity. Here we provide a brief review of how genomic methods can be applied to study the genetics and evolution of animal behavior. We start with an introduction of the 'forward genetic' paradigm and cross-based approaches to mapping the genetics of complex traits. We then delve into the application of genome scans and association mapping of complex traits in natural populations. We also illustrate how population genomics can be used to understand the evolution of the genes underlying behavior. We then discuss current limits and knowledge gaps in behavioral genomics research. Genomics provides a very powerful framework to identify putative genes and gene networks underlying behavior in animals.

ABSTRACT Global climate change is producing novel biospheric conditions, presenting a threat to the stability of ecological systems and the health of the organisms that reside within them. Variation in climatic conditions is expected to facilitate phenological reshuffling within plant communities, impacting the plant‐pollinator interface and the release of allergenic pollen into the atmosphere. Impacts on plant, invertebrate, and human health remain unclear largely due to the variable nature of phenological reshuffling and insufficient monitoring of these trends. Large‐scale temporal surveillance of plant community flowering has been difficult in the past due to logistical constraints. To address this, we set out to test if metabarcoding ( ITS2 and rbcL1 ) of pollen collected by honey bees could be used to infer the phenology of plant communities via comparison to in situ field monitoring at our urban apiary in Toronto, Canada. We found that pooled pollen samples from the five honey bee colonies used in our pilot project could accurately indicate the onset of anthesis, but not its duration, in the wide variety of plant genera they forage on. Increasing the number of colonies used to monitor and employing a multi‐locus approach for metabarcoding of pollen substantially increased the genus detection power of our approach. Here, we demonstrate that metabarcoding of bee‐collected pollen could streamline the establishment of long‐term phenological monitoring programs to document the consequences of global climate change and its impact on the temporal aspects of plant‐pollinator relationships.

Honey bees play a major role in crop pollination but have experienced declining health throughout most of the globe. Despite decades of research on key honey bee stressors (e.g., parasitic Varroa destructor mites and viruses), researchers cannot fully explain or predict colony mortality, potentially because it is caused by exposure to multiple interacting stressors in the field. Understanding which honey bee stressors co-occur and have the potential to interact is therefore of profound importance. Here, we used the emerging field of systems theory to characterize the stressor networks found in honey bee colonies after they were placed in fields containing economically valuable crops across Canada. Honey bee stressor networks were often highly complex, with hundreds of potential interactions between stressors. Their placement in crops for the pollination season generally exposed colonies to more complex stressor networks, with an average of 23 stressors and 307 interactions. We discovered that the most influential stressors in a network—those that substantively impacted network architecture—are not currently addressed by beekeepers. Finally, the stressor networks showed substantial divergence among crop systems from different regions, which is consistent with the knowledge that some crops (e.g., highbush blueberry) are traditionally riskier to honey bees than others. Our approach sheds light on the stressor networks that honey bees encounter in the field and underscores the importance of considering interactions among stressors. Clearly, addressing and managing these issues will require solutions that are tailored to specific crops and regions and their associated stressor networks.

Highbush blueberry pollination depends on managed honey bees (Apis mellifera) L. for adequate fruit sets; however, beekeepers have raised concerns about the poor health of colonies after pollinating this crop. Postulated causes include agrochemical exposure, nutritional deficits, and interactions with parasites and pathogens, particularly Melisococcus plutonius [(ex. White) Bailey and Collins, Lactobacillales: Enterococcaceae], the causal agent of European foulbrood disease, but other pathogens could be involved. To broadly investigate common honey bee pathogens in relation to blueberry pollination, we sampled adult honey bees from colonies at time points corresponding to before (t1), during (t2), at the end (t3), and after (t4) highbush blueberry pollination in British Columbia, Canada, across 2 years (2020 and 2021). Nine viruses, as well as M. plutonius, Vairimorpha ceranae, and V. apis [Tokarev et al., Microsporidia: Nosematidae; formerly Nosema ceranae (Fries et al.) and N. apis (Zander)], were detected by PCR and compared among colonies located near and far from blueberry fields. We found a significant interactive effect of time and blueberry proximity on the multivariate pathogen community, mainly due to differences at t4 (corresponding to ~6 wk after the beginning of the pollination period). Post hoc comparisons of pathogens in near and far groups at t4 showed that detections of sacbrood virus (SBV), which was significantly higher in the near group, not M. plutonius, was the primary driver. Further research is needed to determine if the association of SBV with highbush blueberry pollination is contributing to the health decline that beekeepers observe after pollinating this crop.

Recent declines in the health of honey bee colonies used for crop pollination pose a considerable threat to global food security. Foraging by honey bee workers represents the primary route of exposure to a plethora of toxins and pathogens known to affect bee health, but it remains unclear how foraging preferences impact colony-level patterns of stressor exposure. Resolving this knowledge gap is crucial for enhancing the health of honey bees and the agricultural systems that rely on them for pollination. To address this, we carried out a national-scale experiment encompassing 456 Canadian honey bee colonies to first characterize pollen foraging preferences in relation to major crops and then explore how foraging behavior influences patterns of stressor exposure. We used a metagenetic approach to quantify honey bee dietary breadth and found that bees display distinct foraging preferences that vary substantially relative to crop type and proximity, and the breadth of foraging interactions can be used to predict the abundance and diversity of stressors a colony is exposed to. Foraging on diverse plant communities was associated with increased exposure to pathogens, while the opposite was associated with increased exposure to xenobiotics. Our work provides the first large-scale empirical evidence that pollen foraging behavior plays an influential role in determining exposure to dichotomous stressor syndromes in honey bees.

Pollination by the European honey bee, Apis mellifera, is essential for the production of many crops, including highbush blueberries (Vaccinum corymbosum). To understand the impact of agrochemicals (specifically, neonicotinoids, a class of synthetic, neurotoxic insecticides) on these pollinators, we conducted a field study during the blueberry blooms of 2020 and 2021 in British Columbia (B.C.). Forty experimental honey bee colonies were placed in the Fraser Valley: half of the colonies were located within 1.5 km of highbush blueberry fields ("near" colonies) and half were located more than 1.5 km away ("far" colonies). We calculated risk quotients for these compounds using their chronic lethal dietary dose (LDD50) and median lethal concentration (LC50). Pesticide risk was similar between colonies located near and far from blueberry forage, suggesting that toxicity risks are regionally ubiquitous. Two systemic neonicotinoid insecticides, clothianidin and thiamethoxam, were found at quantities that exceeded chronic international levels of concern. We developed a profit model for a pollinating beekeeper in B.C. that was parameterized by: detected pesticide levels; lethal and sublethal bee health; and economic data. For colonies exposed to neonicotinoid pesticides in and out of the blueberry forage radii, there were economic consequences from colony mortality and sublethal effects such as a loss of honey production and compromised colony health. Further, replacing dead colonies with local bees was more profitable than replacing them with imported packages, illustrating that beekeeping management selection of local options can have a positive effect on overall profit.

Since the rapid spread and establishment of Africanized honey bee populations in South America, Africanized bees have persisted as the dominant strain. Remarkably, Chile has remained free of Africanized bee populations, making the country a valuable exporter of mated queens. Given Chile's pivotal role in the apiculture industry, monitoring the genetic makeup of its honey bee colonies is crucial, yet documentation has been limited to a few studies. Here, we evaluate the ancestral composition of honey bees across eleven different regions in Chile. We find that Chilean honey bees have low levels of admixture, which is markedly lower relative to commercial colonies located internationally. The genetic ancestry of Chilean honey bees is primarily of Eastern European origin, with low levels of Western European ancestry. Finally, we detect a significant relationship between geography and genetic ancestry, suggesting regional adaptations that warrant further investigation.