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Data from: Whole-genome duplication and host genotype affect rhizosphere microbial communities

Citation

Bennett Ponsford, Julian; Hubbard, Charley; Harrison, Joshua (2021), Data from: Whole-genome duplication and host genotype affect rhizosphere microbial communities, Dryad, Dataset, https://doi.org/10.5061/dryad.hqbzkh1ff

Abstract

The composition of microbial communities found in association with plants is influenced by host phenotype and genotype. Yet, the ways in which specific genetic architectures of host plants shape microbiomes is unknown. Genome duplication events are common in the evolutionary history of plants, influence many important plant traits, and, thus, they may affect associated microbial communities. Using experimentally induced whole genome duplication (WGD), we tested the effect of WGD on rhizosphere bacterial communities in Arabidopsis thaliana. We performed 16S rRNA amplicon sequencing to characterize differences between microbiomes associated with specific host genetic backgrounds (Columbia vs. Landsberg) and ploidy levels (diploid vs. tetraploid). We modeled relative abundances of bacterial taxa using the Dirichlet and multinomial distributions via a hierarchical Bayesian approach. We found that host genetic background and ploidy level affected rhizosphere community composition. We then tested to what extent microbiomes derived from a specific genetic background or ploidy level affected plant performance by inoculating sterile seedlings with microbial communities harvested from a prior generation. We found a negative effect of the tetraploid Columbia microbiome on growth of all four plant genetic backgrounds. These findings suggest an interplay between host genetic architecture and bacterial community assembly with potential ramifications for host fitness. Moreover, we uncovered an intriguing role of ploidy-level for shaping plant microbiomes. Given the prevalence of ploidy-level variation in both wild and managed plant populations, the effects on microbiomes of this aspect of host genetic architecture could be a widespread driver of differences in plant microbiomes.

Usage Notes

Raw phenotypic and amplicon data are not provided here. Raw amplicon data can be found using the short read archive identifier in the preprint text.

Analysis was performed primarily using R version 3.5. Packages and functions may have been deprecated since.

Funding

National Science Foundation, Award: IOS-1444571