Taxonomic resolution of different 16S rRNA variable regions varies strongly across plant-associated bacteria.

Autor:	Hrovat K; Bioinformatics Group, Wageningen University and Research, 6708 PB Wageningen, The Netherlands., Dutilh BE; Theoretical Biology and Bioinformatics, Department of Biology, Faculty of Science, Utrecht University, 3584 CH Utrecht, The Netherlands.; Institute of Biodiversity, Faculty of Biological Sciences, Friedrich Schiller University Jena, 07743 Jena, Germany.; Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07745 Jena, Germany., Medema MH; Bioinformatics Group, Wageningen University and Research, 6708 PB Wageningen, The Netherlands., Melkonian C; Bioinformatics Group, Wageningen University and Research, 6708 PB Wageningen, The Netherlands.; Theoretical Biology and Bioinformatics, Department of Biology, Faculty of Science, Utrecht University, 3584 CH Utrecht, The Netherlands.
Jazyk:	angličtina
Zdroj:	ISME communications [ISME Commun] 2024 Mar 08; Vol. 4 (1), pp. ycae034. Date of Electronic Publication: 2024 Mar 08 (Print Publication: 2024).
DOI:	10.1093/ismeco/ycae034
Abstrakt:	Plant-microbiome research plays a pivotal role in understanding the relationships between plants and their associated microbial communities, with implications for agriculture and ecosystem dynamics. Metabarcoding analysis on variable regions of the 16S ribosomal RNA (rRNA) gene remains the dominant technology to study microbiome diversity in this field. However, the choice of the targeted variable region might affect the outcome of the microbiome studies. In our in silico analysis, we have evaluated whether the targeted variable region has an impact on taxonomic resolution in 16 plant-related microbial genera. Through a comparison of 16S rRNA gene variable regions with whole-genome data, our findings suggest that the V1-V3 region is generally a more suitable option than the widely used V3-V4 region for targeting microbiome analysis in plant-related genera. However, sole reliance on one region could introduce detection biases for specific genera. Thus, we are suggesting that while transitioning to full-length 16S rRNA gene and whole-genome sequencing for plant-microbiome analysis, the usage of genus-specific variable regions can achieve more precise taxonomic assignments. More broadly, our approach provides a blueprint to identify the most discriminating variable regions of the 16S rRNA gene for genera of interest. Competing Interests: None declared. (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.)
Databáze:	MEDLINE
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