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Dryad

Pollen diet mediates how pesticide exposure impacts brain gene expression in nest-founding bumble bee queens

Cite this dataset

Costa, Claudineia et al. (2022). Pollen diet mediates how pesticide exposure impacts brain gene expression in nest-founding bumble bee queens [Dataset]. Dryad. https://doi.org/10.6086/D10Q22

Abstract

A primary goal in biology is to understand the effects of multiple, interacting environmental stressors on organisms. Wild and domesticated bees are exposed to a wide variety of interacting biotic and abiotic stressors, with widespread declines in floral resources and agrochemical exposure being two of the most important. In this study, we used examinations of brain gene expression to explore the sublethal consequences of neonicotinoid pesticide exposure and pollen diet composition in nest-founding bumble bee queens. We demonstrate for the first time that pollen diet composition can influence the strength of bumble bee queen responses to pesticide exposure at the molecular level. Specifically, one pollen mixture in our study appeared to buffer bumble bee queens entirely against the effects of pesticide exposure, with respect to brain gene expression. Additionally, we detected unique effects of pollen diet and sustained (versus more temporary) pesticide exposure on queen gene expression. Our findings support the hypothesis that nutritional status can help buffer animals against the harmful effects of other stressors, including pesticides, and highlight the importance of using molecular approaches to explore sublethal consequences of stressors.

Methods

Brain gene expression - RNAseq

Read counts table was generated using featureCount v1.5.0-p3 (Liao et al. 2014), wherein it determines the number of reads uniquely mapping to exons and summed at the gene level using gene features annotated in the B. impatiens OGSv1.0.

Pollen diet - Metabolomic data

Pollen samples were examined through untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics.

Usage notes

The complete data file contains raw data for all analyses on Costa et al. in prep. Raw sequence reads are deposited in the SRA (Accession ID: PRJNA763214). All analyses and pipelines can be found on the first author’s GitHub (https://github.com/claudinpcosta/2022-PesticideQueens-Bimpatiens).

Funding

National Institute of Food and Agriculture, Award: CA-R-ENT-5122-H