Data for: An invasive ant increases deformed wing virus loads in honey bees
Data files
Dec 09, 2022 version files 10.23 MB
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ant_qPCR.csv
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bee_gene_count_matrix.csv
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bee_pheno_data.csv
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bee_qPCR.csv
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bee_RNA-seq_results.csv
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bee_survival.csv
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bee_trinity_genes.isoform.counts.matrix
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bee_virus_blast.csv
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README.md
Abstract
The majority of invasive species are best known for their effects as predators. However, many introduced predators may also be substantial reservoirs for pathogens. Honey bee-associated viruses are found in various arthropod species including invasive ants. We examined how the globally invasive Argentine ant (Linepithema humile), which can reach high densities and infest beehives, is associated with pathogen dynamics in honey bees. Viral loads of Deformed wing virus (DWV), which has been linked to millions of beehive deaths around the globe, and black queen cell virus significantly increased in bees when invasive ants were present. Microsporidian and trypanosomatid infections, which are more bee-specific, were not affected by ant invasion. The bee virome in autumn revealed that DWV was the predominant virus with the highest infection levels and that no ant-associated viruses were infecting bees. Viral spillback from ants could increase infections in bees. In addition, ant attacks could pose a significant stressor to bee colonies that may affect virus susceptibility. These viral dynamics are a hidden effects of ant pests, which could have a significant impact on disease emergence in an economically important pollinator. Our study contributes to unravel a perhaps overlooked effect of species invasions: changes in pathogen dynamics.
Methods
In the austral summer of January 2019, 18 beehives from an Argentine ant-free apiary were moved into six sites in the Northland region, New Zealand, half with known Argentine ant incursions, placing three hives in each site. Monthly collections of adult worker bees from brood frames took place from January until August, except July.
Quantitative PCR (qPCR) data was generated from reverse transcribed total RNA extracted from honey bees or Argentine ants on a StepOne™ Real-Time PCR cycler or a QuantStudio 7 Real-Time PCR System, respectively. Survival data was generated from field observations.
RNA-seq data originates from Illumina 1.9 Hi-seq 100 base pair (bp) paired-end sequencing of total RNA from honey bees. Reads were aligned to the honey bee reference genome (Amel_HAv3.1) in HISAT2 2.1.0 to exclude host-derived reads. Unaligned reads were de novo assembled in Trinity 2.9.1 and transcript counts generated using a pipeline integrated with the Trinity package (www.github.com/trinityrnaseq/trinityrnaseq/blob/master/util/abundance_estimates_to_matrix.pl).
Further details of the experimental setup and method used can be found in the accompanying manuscript.
Usage notes
Files ending in .matrix can be opened in R (r-project.org) using DESEQ2 and files ending in .csv can, for instance, be opened in Microsoft Excel or Cal in the LibreOffice suite.