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Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach

Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships d...

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Autores principales: Sircar, Sanchari, Parekh, Nita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519691/
https://www.ncbi.nlm.nih.gov/pubmed/26284112
http://dx.doi.org/10.3389/fgene.2015.00256
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author Sircar, Sanchari
Parekh, Nita
author_facet Sircar, Sanchari
Parekh, Nita
author_sort Sircar, Sanchari
collection PubMed
description Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships derived from condition-dependent gene expression data is an effective way to identify the functional associations between genes that are part of the same biological process and may be under similar transcriptional control. For this purpose, vast amount of freely available transcriptomic data may be used. In this study, we consider gene expression data for different tissues and developmental stages in response to drought stress. We analyze the network of co-expressed genes to identify drought-responsive genes modules in a tissue and stage-specific manner based on differential expression and gene enrichment analysis. Taking cues from the systems-level behavior of these modules, we propose two approaches to identify clusters of tightly co-expressed/co-regulated genes. Using graph-centrality measures and differential gene expression, we identify biologically informative genes that lack any functional annotation. We show that using orthologous information from other plant species, the conserved co-expression patterns of the uncharacterized genes can be identified. Presence of a conserved neighborhood enables us to extrapolate functional annotation. Alternatively, we show that single ‘guide-gene’ approach can help in understanding tissue-specific transcriptional regulation of uncharacterized genes. Finally, we confirm the predicted roles of uncharacterized genes by the analysis of conserved cis-elements and explain the possible roles of these genes toward drought tolerance.
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spelling pubmed-45196912015-08-17 Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach Sircar, Sanchari Parekh, Nita Front Genet Genetics Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships derived from condition-dependent gene expression data is an effective way to identify the functional associations between genes that are part of the same biological process and may be under similar transcriptional control. For this purpose, vast amount of freely available transcriptomic data may be used. In this study, we consider gene expression data for different tissues and developmental stages in response to drought stress. We analyze the network of co-expressed genes to identify drought-responsive genes modules in a tissue and stage-specific manner based on differential expression and gene enrichment analysis. Taking cues from the systems-level behavior of these modules, we propose two approaches to identify clusters of tightly co-expressed/co-regulated genes. Using graph-centrality measures and differential gene expression, we identify biologically informative genes that lack any functional annotation. We show that using orthologous information from other plant species, the conserved co-expression patterns of the uncharacterized genes can be identified. Presence of a conserved neighborhood enables us to extrapolate functional annotation. Alternatively, we show that single ‘guide-gene’ approach can help in understanding tissue-specific transcriptional regulation of uncharacterized genes. Finally, we confirm the predicted roles of uncharacterized genes by the analysis of conserved cis-elements and explain the possible roles of these genes toward drought tolerance. Frontiers Media S.A. 2015-07-30 /pmc/articles/PMC4519691/ /pubmed/26284112 http://dx.doi.org/10.3389/fgene.2015.00256 Text en Copyright © 2015 Sircar and Parekh. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Sircar, Sanchari
Parekh, Nita
Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach
title Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach
title_full Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach
title_fullStr Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach
title_full_unstemmed Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach
title_short Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach
title_sort functional characterization of drought-responsive modules and genes in oryza sativa: a network-based approach
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519691/
https://www.ncbi.nlm.nih.gov/pubmed/26284112
http://dx.doi.org/10.3389/fgene.2015.00256
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