DOI: 10.5061/dryad.jsxksn0ns
title: Bumble bees and honey bees on islands harbour reduced viral species richness, yet honey bee populations are dominated by a deformed wing virus recombinant

description: Pollinators harbour diverse RNA viromes that play a vital role in their
 health. Yet, factors that shape viral communities are often unclear. The
 European honey bee (Apis mellifera) is experiencing a viral epidemic since
 the emergence of the parasitic mite Varroa destructor (varroa) introduced
 vector-borne transmission, which has also been linked to increased viral
 spillover into wild pollinator communities. Varroa-free island populations
 provide natural laboratories to study the effect of varroa, while also
 allowing us to ask how islands affect viral communities. Barriers that
 restrict the dispersal of wild pollinators and their pathogens to islands
 may be overcome by human-mediated transport in managed honey bees. Here we
 used islands with and without varroa and matched mainland populations of
 honey bees (A. mellifera) and bumble bees (Bombus terrestris) from 2015
 and 2021 to explore how varroa presence and island location affect the
 virome of managed and wild bees. We find lower viral richness on islands
 in both species. Bumble bees harbour a distinct viral community that was
 not affected by varroa but geographically structured. In honey bees,
 however, varroa-present populations contained more viral reads driven by a
 high abundance of deformed wing virus (DWV). Within the six years between
 the sampling events, DWV underwent a shift from mostly DWV-B towards a mix
 of DWV-B and recombinant strains. Surprisingly, these shifts appeared
 independent of varroa. Viewing pollinator virome composition within an
 ecological framework provides valuable insights into the barriers to virus
 spread and could help to predict drivers of disease emergence.
description: # Bumble bees and honey bees on islands harbour reduced viral species
 richness, yet honey bee populations are dominated by a deformed wing virus
 recombinant Dataset DOI:
 [10.5061/dryad.jsxksn0ns](10.5061/dryad.jsxksn0ns) ## Description of the
 data and file structure This dataset contains the raw and processed data,
 BLASTx results, R scripts, and supporting files used in the analyses
 described in "Bumble bees and honey bees on islands harbour reduced
 viral species richness, yet honey bee populations are dominated by a
 deformed wing virus recombinant" by Jana Dobelmann and Lena Wilfert.
 All files are provided to facilitate reproducibility. ### Files and
 variables #### File: 02\_diversity\_heatmap.R **Description:** This R
 script is used to analyse the virome diversity and create plots for viral
 richness, simpson's diversity and a heatmap. It requires
 "read_coverage.csv.csv" as input. #### File:
 01\_CoverM\_analysis.R **Description:** This R script is used to apply
 detection threshold for read coverage files and gives basic statisical
 analyses of viral read coverage and abundance. It is also used to plot a
 map with sampling locations and pie charts with viral abundance. the
 virome diversity and create plots for viral richness, simpson's
 diversity and a heatmap. It requires "read_coverage.csv" as
 input. #### File: 03\_NMDS\_permanova.R **Description:** This R script is
 used to analyse beta diversity in virome data, including a permanova and
 creates NMDS plots. It requires "virus*_*wide*_*summary.csv" as
 input. #### File: read\_coverage.csv **Description:** Reads mapping viral
 references using CoverM. ##### Variables * X: Running number * reference:
 Name of reference in FASTA files used during mapping * sample: RNA-seq
 library (numbered) * Site: sampling site * Virus: Virus name * Island: yes
 - islands, no - mainland * Year: collection year, 2015 or 2021 * Species:
 host species, *Apis mellifera* or *Bombus terrestris* * Varroa: varroa
 presence at site, yes or no * Latitude: Latitude sampling site *
 Longitude: Longitude sampling site * sum_depth: Sum of mapped reads *
 length: Reference length or genome size in bases * average_depth: average
 read depth * coverage: bases covered by reads * perc_coverage: percent
 genome covered by reads * perc_RdRp_coverage: percent RdRp covered by
 reads * N: number of individuals in sample pool * n_reads: total reads in
 library #### File: virus\_wide\_summary.csv **Description:**  #####
 Variables * sample: RNA-seq library (numbered) * Site: sampling site *
 Island: yes - islands, no - mainland * Year: collection year, 2015 or 2021
 * Species: host species, *Apis mellifera* or *Bombus terrestris* * Varroa:
 varroa-presence at sampling site * Latitude: Latitude * Longitude:
 Longitude * N:number of individuals in sample pool * n_reads: total reads
 in library * BQCV Cherb.: normalised average read coverage over genome *
 BQCV B-I: normalised average read coverage over genome * Bt Iflavirus 2:
 normalised average read coverage over genome * Bt Iflavirus 1: normalised
 average read coverage over genome * SBPV roth: normalised average read
 coverage over genome * SBPV harp: normalised average read coverage over
 genome * LSV: normalised average read coverage over genome * LSV1:
 normalised average read coverage over genome * LSV TO: normalised average
 read coverage over genome * LSV Lpool: normalised average read coverage
 over genome * LSV France: normalised average read coverage over genome *
 LSV3 Scilly: normalised average read coverage over genome * AGV:
 normalised average read coverage over genome * AMV1: normalised average
 read coverage over genome * AMV3: normalised average read coverage over
 genome * MfV1: normalised average read coverage over genome * MLV:
 normalised average read coverage over genome * ARV1: normalised average
 read coverage over genome * LSV4: normalised average read coverage over
 genome * LSV3 Liaoning: normalised average read coverage over genome *
 MfV2: normalised average read coverage over genome * BMlV: normalised
 average read coverage over genome * BCD: normalised average read coverage
 over genome * DWV-A: normalised average read coverage over genome * DWV-B:
 normalised average read coverage over genome * SBV: normalised average
 read coverage over genome * SBV-like: normalised average read coverage
 over genome * Bt Iflavirus 3: normalised average read coverage over genome
 #### File: sample\_info.csv **Description:**  ##### Variables * sample:
 RNA-seq library (numbered) * Site: collection site * Year: sampling year,
 2015 or 2021 * Species: host species * Varroa: varroa presence at site,
 yes or no * Island: yes - islands, no - mainland * Latitude: Longitude *
 Longitude: Latitude #### File: CoverM\_read\_depth.zip
 **Description:** Archive containing 44 files with the read depth. Each
 file has three columns which show the reference name, genome position, and
 number of reads that mapped at the genome position. #### File:
 04\_DWV\_cov\_plots.R **Description:** R script uder to generate plots
 that show the coverage of deformed wing virus reads over the genome.
 Requires "CoverM_read_depth.zip", "sample_info.csv"
 and "reference_names_final.csv". #### File:
 reference\_names\_final.csv **Description:**  ##### Variables * Name:
 Reference name * Description: Virus name * Virus: Virus acronym * Family:
 Virus family (if known) * Genome: Virus genome organization * Detected: if
 virus was detected with &gt;33% genome coverage and &gt;75% RdRp coverage
 in at least one library * Length: Reference length in bases * RdRp_start:
 start of the RdRp in bases * RdRp_end: end of the RdRp in bases #### File:
 blastx\_results\_unfiltered.zip **Description:** Archive containing
 results from blastx searched of de novo assembled contigs against a large
 protein reference database for all 44 samples. ## Code/software R