DOI: 10.5061/dryad.prr4xgxws
title: How population structure and nest membership shape pathogen patterns in bumble bees?

description: Host density, genetic diversity, and social groups are key factors
 influencing pathogen transmission in wildlife populations, but their
 interactions remain poorly understood in insects. Islands can provide
 natural laboratories with distinct populations that vary in density and
 genetic diversity, whereby dense, genetically homogenous populations are
 expected to facilitate pathogen transmission. We used bumble bees to test
 these predictions, assessing the population structure of the two common
 species Bombus pascuorum and B. terrestris across island and mainland
 sites in the British Isles and France, and testing bees for five
 micro-parasitic and four viral pathogens. B. pascuorum formed distinct
 genetic clusters on islands, with varying levels of heterozygosity, and
 only the Isle of Arran clustered with mainland populations. B. terrestris
 populations were less structured, but populations on the Isle of Man and
 the Scilly Isles were genetically separated from other island and mainland
 populations while showing low heterozygosity. Colony density was similar
 between species and not linked to genetic diversity, but had a positive
 effect on the prevalence of some pathogens. Contrary to expectations,
 there was no protective effect of high genetic diversity, suggesting that
 generalist bumble bee pathogens could be more affected by host species
 diversity and density. Yet, within B. terrestris populations, we found
 that nestmates showed more similar pathogen profiles than unrelated
 individuals, suggesting that genetic similarity and high contact rates
 within nests affect pathogen prevalence in wild bees.
description: 216 <em>Bombus pascuorum</em> and 573 <em>B.
 terrestris</em> were collected from flowers from mid June to late
 August in 2021 across seven islands in the Irish Sea, the English Channel,
 and off the coast of Brittany in France, and four coastal sites in England
 and France in 2021. From late June to early August 2022, islands (except
 for the Scilly Isles) were sampled again using five sampling sites on
 large islands (Arran, Isle of Man, Guernsey, Belle-Ile) or collecting
 across the whole island on smaller islands (&lt; 15
 km<sup>2</sup>, Alderney and Ouessant). A total of 988
 <em>B. pascuorum</em> and 1,163 <em>B.
 terrestris</em> were obtained in 2022. DNA was
 extracted from bees using a single hind leg. Bees were genotyped at 12
 loci, and fragments were run on a Thermo Fisher Scientific Genetic
 Analyzer 3130 Series. Alleles were scored in Geneious Prime® v2023.0.1.
 Sibship reconstruction was performed in COLONY v2.0.6,7, and population
 structure was assessed using DAPC (discriminant analysis of principal
 components) and the Bayesian clustering algorithm in Structure
 v2.3.4. To study how population structure affects
 pathogen prevalence, we used island samples from 2022. We screened bumble
 bees for nine pathogens. Tissue from half bees (laterally bisected) was
 homogenized, and RNA was extracted and reverse transcribed to cDNA to test
 for RNA viruses and mRNA from parasite infections. PCR was used to screen
 for black queen cell virus (BQCV), deformed wing virus type A and B (DWV-A
 and DWV-B), slow bee paralysis virus (SBPV), <em>Apicistis
 bombi</em>, <em>Crithidia bombi</em>, <em>Nosema
 apis, N. bombi,</em> and <em>N. ceranae.</em>
description: # How population structure and nest membership shape pathogen patterns in
 bumble bees?
 [https://doi.org/10.5061/dryad.prr4xgxws](https://doi.org/10.5061/dryad.prr4xgxws) ## Description of the data and file structure This file is the primary dataset utilized for the various analyses described in our article, "How population structure and sociality shape pathogen patterns in bumble bees". In this article, we investigate the population structure of two bumble bee species and link this structure to disease patterns. Microsatellite data were used to calculate genetic diversity in bee populations and in sibship reconstructions. Inferred nest membership then allowed us to estimate the bumble bee density using mark recapture models and to further look into the similarity in pathogen infections within and between nests. ### Files and variables #### File: data_table_bb_pop_patho.csv **Description:** Individual genotype data (allele sizes) and pathogen prevalence for *Bombus pascuorum* and *B. terrestris* collected in seven island and four mainland populations in the British Isles and France in 2021 and 2022. ##### The csv file contains the following columns * `Population`: Population for collection * `Site`: Collection site within population * `Lat`: Latitude collection site * `Long`: Longitude collection site * `Date`: Collection date * `Year`: Collection year * `Species`: Bumble bee species, P for *Bombus pascuorum* and T for *B. terrestris* * `ID`: Bumble bee ID * `Comment`: Comment for samples that had to be excluded from parts of the analyses - **empty field** when sample was included in all analyses * Microsatellite alleles - showing **alle size** in bp, **0** indicates no amplification and **NA** indicates that the locus was not used in the analysis * BL06 1: Locus BL06 allele 1 * BL06 2: Locus BL06 allele 2 * B118 1: Locus B118 allele 1, in *B. pascuorum* null allele and removed from analysis * B118 2: Locus B118 allele 2, in *B. pascuorum* null allele and removed from analysis * BL03 1: Locus BL03 allele 1 * BL03 2: Locus BL03 allele 2 * B96 1: Locus B96 allele 1 * B96 2: Locus B96 allele 2 * B126 1: Locus B126 allele 1 * B126 2: Locus B126 allele 2 * BL11 1: Locus BL11 allele 1 * BL11 2: Locus BL11 allele 2 * B119 1: Locus B119 allele 1, only used in *B. terrestris*, null allele in 2021 and removed from combined analysis * B119 2: Locus B119 allele 2, only used in *B. terrestris*, null allele in 2021 and removed from combined analysis * B131 1: Locus B131 allele 1, only used in *B. pascuorum* * B131 2: Locus B131 allele 2, only used in *B. pascuorum* * B10 1: Locus B10 allele 1, in *B. pascuorum* no good amplification in Ouessant samples and removed from combinedanalysis * B10 2: Locus B10 allele 2, in *B. pascuorum* no good amplification in Ouessant samples and removed from combined analysis * B100 1: Locus B100 allele 1, only used in *B. terrestris* * B100 2: Locus B100 allele 2, only used in *B. terrestris* * B121 1: Locus B121 allele 1, only used in *B. pascuorum* * B121 2: Locus B121 allele 2, only used in *B. pascuorum* * B124 1: Locus B124 allele 1, in *B. pascuorum* 2021 null allele and removed from combined analysis * B124 2: Locus B124 allele 2, in *B. pascuorum* 2021 null allele and removed from combined analysis * B11 1: Locus B11 allele 1 * B11 2: Locus B11 allele 2 * B132 1: Locus B132 allele 1 * B132 2: Locus B132 allele 2 * Nest: Nest assigned using sibship reconstruction in Colony - Nests are named by their collection size and then numbered * Pathogen prevalence - presence/absence data from pathogen screening, **NA** indicates that a sample was not screened for pathogens, **0** indicated not PCR amplification (absence) and **1** positive PCR amplification (presence) * A. bombi: *Apicystis bombi* prevalence: 0 indicates absence and 1 presence * C. bombi: *Crithidia bombi* prevalence: 0 indicates absence and 1 presence * SBPV: Slow bee paralysis virus prevalence: 0 indicates absence and 1 presence * N. apis: *Nosema apis* prevalence: 0 indicates absence and 1 presence * N. bombi: *Nosema bombi* prevalence: 0 indicates absence and 1 presence * N. ceranae: *Nosema ceranae* prevalence: 0 indicates absence and 1 presence * DWV-A: Deformed wing virus type A prevalence: 0 indicates absence and 1 presence * DWV-B: Deformed wing virus type B prevalence: 0 indicates absence and 1 presence * BQCV: Black queen cell virus prevalence: 0 indicates absence and 1 presence ## Code/software The csv file can be opened and analysed using, for instance: * R * Microsoft Excel * Open office * Mac numbers