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

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 compositio...

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Autores principales: Chialva, Matteo, Ghignone, Stefano, Novero, Mara, Hozzein, Wael N., Lanfranco, Luisa, Bonfante, Paola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022885/
https://www.ncbi.nlm.nih.gov/pubmed/31878183
http://dx.doi.org/10.3390/microorganisms8010038
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author Chialva, Matteo
Ghignone, Stefano
Novero, Mara
Hozzein, Wael N.
Lanfranco, Luisa
Bonfante, Paola
author_facet Chialva, Matteo
Ghignone, Stefano
Novero, Mara
Hozzein, Wael N.
Lanfranco, Luisa
Bonfante, Paola
author_sort Chialva, Matteo
collection PubMed
description 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.
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spelling pubmed-70228852020-03-12 Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota Chialva, Matteo Ghignone, Stefano Novero, Mara Hozzein, Wael N. Lanfranco, Luisa Bonfante, Paola Microorganisms Article 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. MDPI 2019-12-24 /pmc/articles/PMC7022885/ /pubmed/31878183 http://dx.doi.org/10.3390/microorganisms8010038 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chialva, Matteo
Ghignone, Stefano
Novero, Mara
Hozzein, Wael N.
Lanfranco, Luisa
Bonfante, Paola
Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota
title Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota
title_full Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota
title_fullStr Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota
title_full_unstemmed Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota
title_short Tomato RNA-seq Data Mining Reveals the Taxonomic and Functional Diversity of Root-Associated Microbiota
title_sort tomato rna-seq data mining reveals the taxonomic and functional diversity of root-associated microbiota
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7022885/
https://www.ncbi.nlm.nih.gov/pubmed/31878183
http://dx.doi.org/10.3390/microorganisms8010038
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