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PhytoTypeDB: a database of plant protein inter-cultivar variability and function

Despite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and var...

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Autores principales: Necci, Marco, Piovesan, Damiano, Micheletti, Diego, Paladin, Lisanna, Cestaro, Alessandro, Tosatto, Silvio C E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6301341/
https://www.ncbi.nlm.nih.gov/pubmed/30576486
http://dx.doi.org/10.1093/database/bay125
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author Necci, Marco
Piovesan, Damiano
Micheletti, Diego
Paladin, Lisanna
Cestaro, Alessandro
Tosatto, Silvio C E
author_facet Necci, Marco
Piovesan, Damiano
Micheletti, Diego
Paladin, Lisanna
Cestaro, Alessandro
Tosatto, Silvio C E
author_sort Necci, Marco
collection PubMed
description Despite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and variability. In particular, despite the economic importance of many plant accessions, there are no straightforward ways to retrieve or visualize information on their differences. To fill this gap, we developed PhytoTypeDB (http://phytotypedb.bio.unipd.it/), a scalable database containing plant protein annotations and genetic variants from resequencing of different accessions. The database content is generated by an integrated pipeline, exploiting state-of-the-art methods for protein characterization requiring only the proteome reference sequence and variant calling files. Protein names for unknown proteins are inferred by homology for over 95% of the entries. Single-nucleotide variants are visualized along with protein annotation in a user-friendly web interface. The server offers an effective querying system, which allows to compare variability among different species and accessions, to generate custom data sets based on shared functional features or to perform sequence searches. A documented set of exposed RESTful endpoints make the data accessible programmatically by third-party clients.
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spelling pubmed-63013412018-12-27 PhytoTypeDB: a database of plant protein inter-cultivar variability and function Necci, Marco Piovesan, Damiano Micheletti, Diego Paladin, Lisanna Cestaro, Alessandro Tosatto, Silvio C E Database (Oxford) Original Article Despite a fast-growing number of available plant genomes, available computational resources are poorly integrated and provide only limited access to the underlying data. Most existing databases focus on DNA/RNA data or specific gene families, with less emphasis on protein structure, function and variability. In particular, despite the economic importance of many plant accessions, there are no straightforward ways to retrieve or visualize information on their differences. To fill this gap, we developed PhytoTypeDB (http://phytotypedb.bio.unipd.it/), a scalable database containing plant protein annotations and genetic variants from resequencing of different accessions. The database content is generated by an integrated pipeline, exploiting state-of-the-art methods for protein characterization requiring only the proteome reference sequence and variant calling files. Protein names for unknown proteins are inferred by homology for over 95% of the entries. Single-nucleotide variants are visualized along with protein annotation in a user-friendly web interface. The server offers an effective querying system, which allows to compare variability among different species and accessions, to generate custom data sets based on shared functional features or to perform sequence searches. A documented set of exposed RESTful endpoints make the data accessible programmatically by third-party clients. Oxford University Press 2018-12-14 /pmc/articles/PMC6301341/ /pubmed/30576486 http://dx.doi.org/10.1093/database/bay125 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Necci, Marco
Piovesan, Damiano
Micheletti, Diego
Paladin, Lisanna
Cestaro, Alessandro
Tosatto, Silvio C E
PhytoTypeDB: a database of plant protein inter-cultivar variability and function
title PhytoTypeDB: a database of plant protein inter-cultivar variability and function
title_full PhytoTypeDB: a database of plant protein inter-cultivar variability and function
title_fullStr PhytoTypeDB: a database of plant protein inter-cultivar variability and function
title_full_unstemmed PhytoTypeDB: a database of plant protein inter-cultivar variability and function
title_short PhytoTypeDB: a database of plant protein inter-cultivar variability and function
title_sort phytotypedb: a database of plant protein inter-cultivar variability and function
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6301341/
https://www.ncbi.nlm.nih.gov/pubmed/30576486
http://dx.doi.org/10.1093/database/bay125
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