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Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource

BACKGROUND: Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitre...

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Autores principales: Schuette, Scott, Piatkowski, Brian, Corley, Aaron, Lang, Daniel, Geisler, Matt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4384322/
https://www.ncbi.nlm.nih.gov/pubmed/25885037
http://dx.doi.org/10.1186/s12859-015-0524-1
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author Schuette, Scott
Piatkowski, Brian
Corley, Aaron
Lang, Daniel
Geisler, Matt
author_facet Schuette, Scott
Piatkowski, Brian
Corley, Aaron
Lang, Daniel
Geisler, Matt
author_sort Schuette, Scott
collection PubMed
description BACKGROUND: Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants. RESULTS: The first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here. CONCLUSION: Addition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of “guilt-by-association” models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0524-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-43843222015-04-04 Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource Schuette, Scott Piatkowski, Brian Corley, Aaron Lang, Daniel Geisler, Matt BMC Bioinformatics Research Article BACKGROUND: Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants. RESULTS: The first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here. CONCLUSION: Addition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of “guilt-by-association” models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0524-1) contains supplementary material, which is available to authorized users. BioMed Central 2015-03-16 /pmc/articles/PMC4384322/ /pubmed/25885037 http://dx.doi.org/10.1186/s12859-015-0524-1 Text en © Schuette et al.; licensee BioMed Central. 2015 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 use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Schuette, Scott
Piatkowski, Brian
Corley, Aaron
Lang, Daniel
Geisler, Matt
Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource
title Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource
title_full Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource
title_fullStr Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource
title_full_unstemmed Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource
title_short Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource
title_sort predicted protein-protein interactions in the moss physcomitrella patens: a new bioinformatic resource
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4384322/
https://www.ncbi.nlm.nih.gov/pubmed/25885037
http://dx.doi.org/10.1186/s12859-015-0524-1
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