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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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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. |
format | Online Article Text |
id | pubmed-6301341 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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