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PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process

The Plant Resistance Genes database (PRGdb; http://prgdb.org/prgdb4/) has been greatly expanded, keeping pace with the increasing amount of available knowledge and data (sequenced proteomes, cloned genes, public analysis data, etc.). The easy-to-use style of the database website has been maintained,...

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Autores principales: Calle García, Joan, Guadagno, Anna, Paytuvi-Gallart, Andreu, Saera-Vila, Alfonso, Amoroso, Ciro Gianmaria, D’Esposito, Daniela, Andolfo, Giuseppe, Aiese Cigliano, Riccardo, Sanseverino, Walter, Ercolano, Maria Raffaella
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8729912/
https://www.ncbi.nlm.nih.gov/pubmed/34850118
http://dx.doi.org/10.1093/nar/gkab1087
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author Calle García, Joan
Guadagno, Anna
Paytuvi-Gallart, Andreu
Saera-Vila, Alfonso
Amoroso, Ciro Gianmaria
D’Esposito, Daniela
Andolfo, Giuseppe
Aiese Cigliano, Riccardo
Sanseverino, Walter
Ercolano, Maria Raffaella
author_facet Calle García, Joan
Guadagno, Anna
Paytuvi-Gallart, Andreu
Saera-Vila, Alfonso
Amoroso, Ciro Gianmaria
D’Esposito, Daniela
Andolfo, Giuseppe
Aiese Cigliano, Riccardo
Sanseverino, Walter
Ercolano, Maria Raffaella
author_sort Calle García, Joan
collection PubMed
description The Plant Resistance Genes database (PRGdb; http://prgdb.org/prgdb4/) has been greatly expanded, keeping pace with the increasing amount of available knowledge and data (sequenced proteomes, cloned genes, public analysis data, etc.). The easy-to-use style of the database website has been maintained, while an updated prediction tool, more data and a new section have been added. This new section will contain plant resistance transcriptomic experiments, providing additional easy-to-access experimental information. DRAGO3, the tool for automatic annotation and prediction of plant resistance genes behind PRGdb, has been improved in both accuracy and sensitivity, leading to more reliable predictions. PRGdb offers 199 reference resistance genes and 586.652 putative resistance genes from 182 sequenced proteomes. Compared to the previous release, PRGdb 4.0 has increased the number of reference resistance genes from 153 to 199, the number of putative resistance genes from 177K from 76 proteomes to 586K from 182 sequenced proteomes. A new section has been created that collects plant-pathogen transcriptomic data for five species of agricultural interest. Thereby, with these improvements and data expansions, PRGdb 4.0 aims to serve as a reference to the plant scientific community and breeders worldwide, helping to further study plant resistance mechanisms that contribute to fighting pathogens.
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spelling pubmed-87299122022-01-06 PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process Calle García, Joan Guadagno, Anna Paytuvi-Gallart, Andreu Saera-Vila, Alfonso Amoroso, Ciro Gianmaria D’Esposito, Daniela Andolfo, Giuseppe Aiese Cigliano, Riccardo Sanseverino, Walter Ercolano, Maria Raffaella Nucleic Acids Res Database Issue The Plant Resistance Genes database (PRGdb; http://prgdb.org/prgdb4/) has been greatly expanded, keeping pace with the increasing amount of available knowledge and data (sequenced proteomes, cloned genes, public analysis data, etc.). The easy-to-use style of the database website has been maintained, while an updated prediction tool, more data and a new section have been added. This new section will contain plant resistance transcriptomic experiments, providing additional easy-to-access experimental information. DRAGO3, the tool for automatic annotation and prediction of plant resistance genes behind PRGdb, has been improved in both accuracy and sensitivity, leading to more reliable predictions. PRGdb offers 199 reference resistance genes and 586.652 putative resistance genes from 182 sequenced proteomes. Compared to the previous release, PRGdb 4.0 has increased the number of reference resistance genes from 153 to 199, the number of putative resistance genes from 177K from 76 proteomes to 586K from 182 sequenced proteomes. A new section has been created that collects plant-pathogen transcriptomic data for five species of agricultural interest. Thereby, with these improvements and data expansions, PRGdb 4.0 aims to serve as a reference to the plant scientific community and breeders worldwide, helping to further study plant resistance mechanisms that contribute to fighting pathogens. Oxford University Press 2021-11-24 /pmc/articles/PMC8729912/ /pubmed/34850118 http://dx.doi.org/10.1093/nar/gkab1087 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database Issue
Calle García, Joan
Guadagno, Anna
Paytuvi-Gallart, Andreu
Saera-Vila, Alfonso
Amoroso, Ciro Gianmaria
D’Esposito, Daniela
Andolfo, Giuseppe
Aiese Cigliano, Riccardo
Sanseverino, Walter
Ercolano, Maria Raffaella
PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
title PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
title_full PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
title_fullStr PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
title_full_unstemmed PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
title_short PRGdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
title_sort prgdb 4.0: an updated database dedicated to genes involved in plant disease resistance process
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8729912/
https://www.ncbi.nlm.nih.gov/pubmed/34850118
http://dx.doi.org/10.1093/nar/gkab1087
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