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A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

BACKGROUND: Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional a...

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Autores principales: Dharmawardhana, Palitha, Ren, Liya, Amarasinghe, Vindhya, Monaco, Marcela, Thomason, Jim, Ravenscroft, Dean, McCouch, Susan, Ware, Doreen, Jaiswal, Pankaj
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer New York 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883713/
https://www.ncbi.nlm.nih.gov/pubmed/24280345
http://dx.doi.org/10.1186/1939-8433-6-15
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author Dharmawardhana, Palitha
Ren, Liya
Amarasinghe, Vindhya
Monaco, Marcela
Thomason, Jim
Ravenscroft, Dean
McCouch, Susan
Ware, Doreen
Jaiswal, Pankaj
author_facet Dharmawardhana, Palitha
Ren, Liya
Amarasinghe, Vindhya
Monaco, Marcela
Thomason, Jim
Ravenscroft, Dean
McCouch, Susan
Ware, Doreen
Jaiswal, Pankaj
author_sort Dharmawardhana, Palitha
collection PubMed
description BACKGROUND: Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. RESULTS: RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. CONCLUSIONS: Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1939-8433-6-15) contains supplementary material, which is available to authorized users.
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spelling pubmed-48837132016-06-21 A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress Dharmawardhana, Palitha Ren, Liya Amarasinghe, Vindhya Monaco, Marcela Thomason, Jim Ravenscroft, Dean McCouch, Susan Ware, Doreen Jaiswal, Pankaj Rice (N Y) Research BACKGROUND: Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment. RESULTS: RiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis. CONCLUSIONS: Here we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway/. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1939-8433-6-15) contains supplementary material, which is available to authorized users. Springer New York 2013-05-29 /pmc/articles/PMC4883713/ /pubmed/24280345 http://dx.doi.org/10.1186/1939-8433-6-15 Text en © Dharmawardhana et al.; licensee Springer. 2013 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Dharmawardhana, Palitha
Ren, Liya
Amarasinghe, Vindhya
Monaco, Marcela
Thomason, Jim
Ravenscroft, Dean
McCouch, Susan
Ware, Doreen
Jaiswal, Pankaj
A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
title A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
title_full A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
title_fullStr A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
title_full_unstemmed A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
title_short A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
title_sort genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883713/
https://www.ncbi.nlm.nih.gov/pubmed/24280345
http://dx.doi.org/10.1186/1939-8433-6-15
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