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Open AccessArticle

Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota

Department of Life Sciences and Systems Biology, University of Torino, Viale P.A. Mattioli 25, I-10125 Torino, Italy
Institute for Sustainable Plant Protection, National Research Council of Italy (CNR), Viale P.A. Mattioli 25, I-10125 Torino, Italy
Bioproducts Research Chair, Zoology Department, College of Science, King Saud University, 11451 Riyadh, Saudi Arabia
Botany and Microbiology Department, Faculty of Science, Beni-Suef University, Beni-Suef 62511, Egypt
Author to whom correspondence should be addressed.
Microorganisms 2020, 8(1), 38;
Received: 2 December 2019 / Revised: 19 December 2019 / Accepted: 21 December 2019 / Published: 24 December 2019
(This article belongs to the Special Issue Plant Microbial Interactions)
Next-generation approaches have enabled researchers to deeply study the plant microbiota and to reveal how microbiota associated with plant roots has key effects on plant nutrition, disease resistance, and plant development. Although early “omics” experiments focused mainly on the species composition of microbial communities, new “meta-omics” approaches such as meta-transcriptomics provide hints about the functions of the microbes when interacting with their plant host. Here, we used an RNA-seq dataset previously generated for tomato (Solanum lycopersicum) plants growing on different native soils to test the hypothesis that host-targeted transcriptomics can detect the taxonomic and functional diversity of root microbiota. Even though the sequencing throughput for the microbial populations was limited, we were able to reconstruct the microbial communities and obtain an overview of their functional diversity. Comparisons of the host transcriptome and the meta-transcriptome suggested that the composition and the metabolic activities of the microbiota shape plant responses at the molecular level. Despite the limitations, mining available next-generation sequencing datasets can provide unexpected results and potential benefits for microbiota research. View Full-Text
Keywords: fungi; holobiont; meta-transcriptome; microbiota; RNA-seq; tomato fungi; holobiont; meta-transcriptome; microbiota; RNA-seq; tomato
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Chialva, M.; Ghignone, S.; Novero, M.; Hozzein, W.N.; Lanfranco, L.; Bonfante, P. Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota. Microorganisms 2020, 8, 38.

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