E-GEOD-109644
Ontology highlight
ABSTRACT:
PROVIDER: E-GEOD-109644 | ExpressionAtlas | 2020-04-06
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-109644-analysis-methods.tsv | Tabular | |||
| E-GEOD-109644-analytics.tsv | Tabular | |||
| E-GEOD-109644-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-109644-configuration.xml | Xml | |||
| E-GEOD-109644-g1_g2-mvaPlot.png | Other |
Items per page: 5 1 - 5 of 21 |
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Project description:Phytophthora cinnamomi is a devastating soil-borne oomycete with a very broad host range however there remains a major gap in the understanding of plant resistance responses to the pathogen, furthermore, necrotrophic plant-pathogen interactions, particularly those of root pathogens, remain poorly understood. Zea mays exhibits non-host resistance to the pathogen and has been well characterised as a model species. Using the maize Affymetrix GeneChip array we conducted genome-wide gene expression profiling to elucidate the defence genes and pathways which are induced in the root tissue of a resistant plant species to the pathogen.
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Project description:Saha2011- Genome-scale metabolic network of
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This model is described in the article:
Zea mays iRS1563: a
comprehensive genome-scale metabolic reconstruction of maize
metabolism.
Saha R, Suthers PF, Maranas
CD.
PLoS ONE 2011; 6(7): e21784
Abstract:
The scope and breadth of genome-scale metabolic
reconstructions have continued to expand over the last decade.
Herein, we introduce a genome-scale model for a plant with
direct applications to food and bioenergy production (i.e.,
maize). Maize annotation is still underway, which introduces
significant challenges in the association of metabolic
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1,825 metabolites involved in 1,985 reactions from primary and
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369 metabolites are unique to the maize model compared to the
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are present in Zea mays iRS1563 that are not accounted for in
maize C4GEM. All reactions are elementally and charged balanced
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This model is hosted on
BioModels Database
and identified by:
MODEL1507180064.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
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Project description:The apoplast of host plants serves as a dynamic interface during invasion and subsequent establishment of disease by a microbial pathogen. In the recent past, host plant apoplasts have been demonstrated to harbour small membrane bound vesicles called extracellular vesicles (EVs) that contain both RNA and protein. EVs are considered to play a significant role in cell-cell communication between the host and the pathogen during infection. In this study the RNAs associated with EVs from the host plant Zea mays under infected and uninfected conditions were sequenced. Besides EV bound RNA, plant apoplasts also contain free RNA that are equally important for host pathogen interaction. We have also detected a pool of extracellular RNA (exRNA) in Z. mays located on leaf surfaces. In this experiment, we sequenced both the free apoplastic RNA and leaf surface RNA from Z. mays during U. maydis infection and under control uninfected conditions. The U. maydis genome codes for a number of secreted ribonucleases that are essential for the pathogenesis of the fungus. For three of these ribonucleases, we have also investigated their role in the regulation of cell:cell communication between Z. mays and U. maydis. Accordingly, this study includes comparative transcript profiling of all the three different forms of exRNA between Z. mays plants infected with either wild type U. maydis or U. maydis strains lacking one or more secreted ribonucleases.
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Project description:Saha2011 - Genome-scale metabolic network of
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This model is described in the article:
Zea mays iRS1563: a
comprehensive genome-scale metabolic reconstruction of maize
metabolism.
Saha R, Suthers PF, Maranas
CD.
PLoS ONE 2011; 6(7): e21784
Abstract:
The scope and breadth of genome-scale metabolic
reconstructions have continued to expand over the last decade.
Herein, we introduce a genome-scale model for a plant with
direct applications to food and bioenergy production (i.e.,
maize). Maize annotation is still underway, which introduces
significant challenges in the association of metabolic
functions to genes. The developed model is designed to meet
rigorous standards on gene-protein-reaction (GPR) associations,
elementally and charged balanced reactions and a biomass
reaction abstracting the relative contribution of all biomass
constituents. The metabolic network contains 1,563 genes and
1,825 metabolites involved in 1,985 reactions from primary and
secondary maize metabolism. For approximately 42% of the
reactions direct literature evidence for the participation of
the reaction in maize was found. As many as 445 reactions and
369 metabolites are unique to the maize model compared to the
AraGEM model for A. thaliana. 674 metabolites and 893 reactions
are present in Zea mays iRS1563 that are not accounted for in
maize C4GEM. All reactions are elementally and charged balanced
and localized into six different compartments (i.e., cytoplasm,
mitochondrion, plastid, peroxisome, vacuole and extracellular).
GPR associations are also established based on the functional
annotation information and homology prediction accounting for
monofunctional, multifunctional and multimeric proteins,
isozymes and protein complexes. We describe results from
performing flux balance analysis under different physiological
conditions, (i.e., photosynthesis, photorespiration and
respiration) of a C4 plant and also explore model predictions
against experimental observations for two naturally occurring
mutants (i.e., bm1 and bm3). The developed model corresponds to
the largest and more complete to-date effort at cataloguing
metabolism for a plant species.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180011.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2015-07-30 | MODEL1507180011 | BioModels