,Varroa destructor are harmful ectoparasitic mites of Apis mellifera honey bees. Deformed wing-like viruses (DWV-A and B (VDV1)) are ubiquitous honey bee viruses that are vectored by Varroa; mite vectoring can cause an increase in virus infectivity and diversity of genetic variants. Beekeepers use both chemical (e.g., amitraz) and non-chemical (e.g., ‘brood break’) means to control mite populations in honey bee colonies, and these methods may be combined into an integrated pest management strategy. Here we explore how these control methods affected the DWV/VDV1 population in honey bee colonies, the diversity of viral genetic variants, and the competence of Varroa to transmit overt DWV infections. We found that ‘brood break’ treatment significantly elevated Varroa populations in colonies with a concomitant increase in DWV-A and VDV1 levels, but not when combined with amitraz application. Our results demonstrate negative implications to honey bee colony health from chemical treatment failures on the levels of DWV-like viruses in adult bees and mites, and the ability of mites to transmit overt infections.,

,Supplemental information from a project describing the transcriptome of a beetle parasite of honey bees,The small hive beetle (SHB), Aethina tumida, is a major pest of managed honey bee (Apis mellifera) colonies in the United States and Australia, and an emergent threat in Europe. While strong honey bee colonies generally keep SHB populations in check, weak or stressed colonies can succumb to infestations. This parasite has spread from a sub-Saharan Africa to three continents, leading to immense management and regulatory costs. We performed a transcriptomic analysis involving deep sequencing of multiple life stages and both sexes of this species. The assembled transcriptome appears to be nearly complete, as judged by conserved insect orthologs and the ability to find plausible homologs for 11,952 proteins described from the genome of the red flour beetle. Expressed genes include each of the major metabolic, developmental and sensory groups, along with genes for proteins involved with immune defenses and insecticide resistance. We also present a total of 23,085 high-quality SNP's for the assembled contigs. We highlight potential differences between this beetle and its honey bee hosts, and suggest mechanisms of future research into the biology and control of this species. SNP resources will allow functional genetic analyses and analyses of dispersal for this invasive pest.,,

,The small hive beetle (Aethina tumida, ATUMI) is an invasive parasite of bee colonies. ATUMI feeds on both fruits and bee nest products, facilitating its spread and increasing its impact on honey bees and other pollinators. The ATUMI genome has been sequenced and annotated, providing the first genomic resources for this species and for the Nitidulidae, a beetle family that is closely related to the extraordinarily species-rich clade of beetles known as the Phytophaga. ATUMI thus provides a contrasting view as a neighbor for one of the most successful known animal groups. A robust genome assembly and a gene set possessing 97.5% of the core proteins known from the holometabolous insects are presented. The ATUMI genome encodes fewer enzymes for plant digestion than the genomes of wood-feeding beetles, but nonetheless shows signs of broad metabolic plasticity. Gustatory receptors are few in number compared to other beetles, especially receptors with known sensitivity (in other beetles) to bitter substances. In contrast, several gene families implicated in detoxification of insecticides and adaptation to diverse dietary resources show increased copy numbers. The presence and diversity of homologs involved in detoxification differs substantially from the bee hosts of ATUMI. Results provide new insights into the genomic basis for local adaption and invasiveness in ATUMI, and a blueprint for control strategies that target this pest without harming their honey bee hosts. A minimal set of gustatory receptors is consistent with the observation that, once a host colony is invaded, food resources are predictable. Unique detoxification pathways and pathway members can help identify which treatments might control this species even in the presence of honey bees, which are notoriously sensitive to pesticides.,,

Code repository for scripts and model output associated with sensitivity analysis of the VarroaPop honeybee hive simulation model. This dataset is associated with the following publication: Kuan, C., G. DeGrandi-Hoffman, R. Curry, K. Garber, A. Kanarek, M. Snyder, K. Wolfe, and T. Purucker. Sensitivity analyses for simulating pesticide impacts on honey bee colonies. ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 376: 15-27, (2018).

Code repository for scripts and model output associated with sensitivity analysis of the VarroaPop honeybee hive simulation model. This dataset is associated with the following publication: Kuan, C., G. DeGrandi-Hoffman, R. Curry, K. Garber, A. Kanarek, M. Snyder, K. Wolfe, and T. Purucker. Sensitivity analyses for simulating pesticide impacts on honey bee colonies. ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, USA, 376: 15-27, (2018).

This study generated genetic 'metabarcode' data using high-throughput sequencing to characterize pollen foraging behavior of pollinating bee species on managed field habitat within units of the National Park Service. Specimens were collected within parks of the National Capital Region from 2021-2023 and subsequently identified to species or genus. DNA was then extracted from specimens using leg samples if pollen was adherent to the corbiculae ("pollen baskets") of corbiculate bees, otherwise using whole-body samples. This data release consists of three tab-delimited files and a file of DNA sequences: 1) sample.metadata.txt includes sample identifiers and the accessions they have been assigned by the National Center for Biotechnology Information (NCBI), the authoritative repository for publicly funded genetic data in the United States. These accessions can be used individually to obtain raw sequencing data or sample information at www.ncbi.nlm.nih.gov. Alternatively, the BioProject accession PRJNA1236404 can be searched to retrieve the full set of data and sample accessions listed in the file. Entity and attribute metadata are provided for this file herein. 2) ITS2.raw.pollen.counts.txt includes the inferred taxon counts at the ITS2 locus, i.e. number of ITS2 sequences in a sample attributable to each identified taxon in each sample. 3. potential.contaminants.txt lists plant taxa that were over-represented in negative controls samples within a particular sequence run. Values for these plant taxa in these runs should either be zeroed-out or adjusted based on a statistical model to account for potential sample contamination. Censoring data based on results in negative controls is a standard practice in metabarcoding. Many samples in this study were very small and/or had no visible pollen, which increases the potential for contamination as the endogenous DNA concentration is expected to be very low in these cases. 3) reference.db.fas contains the plant reference DNA sequences used for taxonomic assignment of the pollen sample sequences.