,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.,,

,These data represent V. destructor genomic annotations to be used for evolutionary comparison with other arthropods.,The ectoparasitic mite Varroa destructor has emerged as the primary pest of domestic honey bees (Apis mellifera). Here we present an initial survey of the V. destructor genome carried out to advance our understanding of Varroa biology and to identify new avenues for mite control. This sequence survey provides immediate resources for molecular and population-genetic analyses of Varroa-Apis interactions and defines the challenges ahead for a comprehensive Varroa genome project.,

,Here we explore the incidence and abundance of currently known honey bee pathogens in colonies suffering from Colony Collapse Disorder (CCD), otherwise weak colonies, and strong colonies from across the United States. This data set was generated in order to use deep RNA sequencing to further characterize microbial diversity in CCD and non-CCD hives. We identified novel strains of the recently described Lake Sinai viruses (LSV) and found evidence of a shift in gut bacterial composition that may be a biomarker of CCD. The results are discussed with respect to host-parasite interactions and other environmental stressors of honey bees.,RNA was pooled by combining equal aliquots from each CCD or non-CCD colony described above. Five µg of RNA from the “CCD−” pool was used to generate cDNA using a cocktail of random heptamer primers. cDNA was size-selected from agarose and end-polished with End Repair Enzyme (Illumina) following manufacturer protocols. A 3′ polyadenine tract was then added with Klenow fragment (Invitrogen) and the products purified with a Qiaquick DNA purification column (Qiagen). Illumina adapters were ligated to cDNA with T4 DNA ligase and the products were amplified under the following thermocycler conditions: an initial denaturing step at 98°C for 30 seconds, followed by 14 cycles at 98°C for 30 seconds, 65°C for 30 seconds, and 72°C for 30 seconds. Final products of 100–300 bp were size-selected from agarose and sequenced on an Illumina Genome Analyzer by the Institute for Genome Sciences, University of Maryland, Baltimore.,Equivalently prepared cDNA from the “CCD+” pool was sequenced using a paired-end strategy with a 350-bp fragment size. A paired-end approach facilitates the assembly of longer contigs, and therefore may provide more diagnostic sequences for annotation, but at a cost of reduced read length (67 bp). Both sequencing runs were quality-trimmed by retaining only the longest contiguous sequence of each read with a minimum (Phred-equivalent) quality score of 15, excepting at most one ambiguous base. Reads less than 50 bp after this trimming step were discarded. A small number of reads were removed because they matched Illumina primer sequence in the Univec database (www.ncbi.nlm.nih.gov/VecScreen/UniVec.html).,Reads were assembled into contigs using the Velvet assembly package [24]. CCD− reads were assembled into contigs using multiple iterations of Velvet with successive hash lengths of 21, 31, 41, 51, or 61. Contigs of less than 100 bp or with less than 3X coverage were discarded. This assembly strategy was chosen to accommodate the broad spectrum of RNA sources in the sample (viruses, a diverse bacterial community, and eukaryotic pathogens as well as the host genome) that are likely to have different optimal hash lengths for assembly. CCD+ reads were assembled in a similar fashion without read-pair information; in addition, a single paired-end assembly was performed with Velvet using a hash length of 21 and an expected fragment length of 350. Contigs from all intermediate assemblies were then merged using the BlastClust component of Basic Local Alignment Search Tool (BLAST) at 98% identity and 90% nonreciprocal overlap. Because there was substantial redundancy of contigs remaining after this step, we input the contigs to CAP3 [25] for more aggressive assembly, requiring a 60-bp overlap with 92% identity. Raw reads are available as accessions SRX028143 and SRX028145 of the National Center for Biotechnology Information (NCBI) Sequence Read Archive, however, the resulting contigs were not submitted because of an NCBI policy against hosting assemblies from mixed sources.,Highlight photo credit: Image D2368-2 - Honey bee landing on a watermelon flower: Copyright free, public domain photo by Stephen Ausmus,

지능형 양봉 데이터’는 꿀벌의 생애단계별(알, 애벌레, 번데기, 수일벌, 여왕벌), 종봉별(이탈리안, 카니올란, 한봉, 호박벌) 데이터와 생애이슈인 백묵병 데이터 총 12개 클래스로 이루어진 이미지 데이터

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.

,Contemporary data (2017/2018): An open area on the north side of the ESGR (GPS coordinates: 42.461808, -84.011128) was the primary site for this study as it corresponds to the location of “Evans’ Old Field”, one of the areas historically sampled for bees. The field was described by Evans as a 7.7 ha abandoned field with a mid-successional community of plants surrounded by oak-hickory woods. It is now 1.3 ha of semi-open habitat with significant encroachment of the surrounding oak-hickory woods and invasive autumn olive (Elaeagnus umbellata Thunb.). The site was visited every other week during the summers of 2017 and 2018 to sample bees. In 2017, the first sampling day was June 1 and the final sampling day was September 25. In 2018, the first sampling day was May 8 and the final day was October 3. We expanded sampling in 2018 to include a wider diversity of bees with narrower phenological periods.,During each visit we sampled bees using three methods. First, we walked to the center of the open field and randomly selected a direction to start the first 25 meter transect. Three other 25 m transects were then established based on the first one, each at a 90-degree angle from the neighboring transect for a total of 100m sampled, with each transect segment moving away from a central location. Each transect was walked for 10 minutes each, a total of 40 minutes of sampling. We used aerial insect nets to collect bees found within 1.5m of the transect, and time was stopped for specimen processing. The host plant was recorded for all specimens captured from flowers. Flowering plants were identified to the lowest taxonomic level in the field using Newcomb’s guide and the PlantNet app, usually to species. Second, we spent 20 minutes collecting bees from plants of any species in the general vicinity of the open field. Third, to most closely match the methods used by Evans (see below), we spent 30 minutes sampling bees at each of the primary blooming plant species located in the field. Total time spent conducting this final sampling method varied based on the number of primary blooming plants at each visit, with a minimum of 30-minutes if there was only one primary plant. This sampling method was always done last, and included any plants that we collected more than one bee from that day. All bees were identified to species (or lowest possible taxonomic level) using relevant keys. All specimens collected in 2017 and 2018 are currently held in the Isaacs Lab at Michigan State University (as of 2024), and will eventually be deposited at the A.J. Cook Arthropod Collection at Michigan State University for long-term inclusion in that collection.,Historical data (1921-1999): The University of Michigan Museum of Zoology Insect Collection (UMMZI), Ann Arbor, MI, holds over 4,000 bee specimens from the historical collections at the ESGR, and specimens were databased as part of this study. Historical data were checked for entry errors and outdated taxonomies. Specimens with questionable species determinations were re-examined and re-identified using relevant keys (see above) where possible. Bees that could not be confidently identified to the species level were excluded from the dataset, and entries that were missing the date of collection were also removed. Excluded entries accounted for less than 1% of the specimens. There were notable gaps in records at the ESGR, as there were no focused survey efforts since Evans’ last efforts in 1989, and only occasional specimen records from 1990-1999. There were no surveys and no records for the ESGR after 1999 and prior to this study in 2017/2018. All specimens from the ESGR were included in this dataset, not only those specifically collected at the Evans’ Old Field.,In addition to the 4,000 plus records from the ESGR since 1921, we also include Evans’ dataset from his 1972 and 1973 collection effort. Evans’ original dataset from 1972/1973 was available through UM records. The dataset is unique compared to the

농림축산식품부에서 발행한 꿀벌 질병 방역관리방안마련 자료입니다.