Published June 1, 2024 | Version v2
Dataset Open

Continental-scale associations of Arabidopsis thaliana phyllosphere members with host genotype and drought

  • 1. University of Utah

Description

Plants are colonized by distinct pathogenic and commensal microbiomes across different regions of the globe, but the factors driving their geographic variation are largely unknown. Using 16S rDNA and shotgun sequencing, we characterized the associations of the Arabidopsis thaliana leaf microbiome with host genetics and climate variables from 267 populations in the species’ native range across Europe. Comparing the distribution of the 575 major bacterial amplicon variants (phylotypes), we discovered that microbiome composition in A. thaliana segregates along a latitudinal gradient. The latitudinal clines in microbiome composition are predicted by metrics of drought, but also by the spatial genetics of the host. To validate the relative effects of drought and host genotype we conducted a common garden field study, finding 10% of the core bacteria to be affected directly by drought, and 20% to be affected by host genetic associations with drought. These data provide a valuable resource for the plant microbiome field, with the identified associations suggesting that drought can directly and indirectly shape genetic variation in A. thaliana via the leaf microbiome.

Notes

all_metagenome_metadata_9_2020_reads.tsv: This is the metadata file for the collected samples.

 OTUtab_GP1000.rds: ASV phyloseq object (to be read into R) with samples subsampled to 1000 reads.

OTUtab_GP1000_at15.rds: ASV phyloseq object (to be read into R) with samples subsampled to 1000 reads then filtered for common A. thaliana ASVs

plant_clim.rds: Adapted (non-phyloseq) object used for random forest modeling and other regression methods.

metadata_carnegie_drought_experiment_2022_final_submitted: metadata file for plants in the Carnegie experiment in 2022. Corresponding 16S ASV data found in carnegie_field_exp_asvs.rds.

carnegie_field_exp_asvs.rds: ASV phyloseq object (to be read into R) with ASVs found in the Carnegie field experiment in Stanford CA in 2022. No filtering has been applied to this phyloseq object.

Supplementary_data.xls: excel file with the raw data for the Arabiodpsis infection experiments in the growth chamber in drought and control conditions in Utah when infected with p25.C2. Used to generate figure S10 in manuscript.

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Additional details

Software

Repository URL
https://github.com/tkarasov/pathodopsis
Programming language
Python, RMarkdown, Linux Kernel Module