E-MTAB-2287
Ontology highlight
ABSTRACT:
PROVIDER: E-MTAB-2287 | ExpressionAtlas | 2015-06-10
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-MTAB-2287-analysis-methods.tsv | Tabular | |||
| E-MTAB-2287-atlasExperimentSummary.Rdata | Rdata | |||
| E-MTAB-2287-configuration.xml | Xml | |||
| E-MTAB-2287-percentile-ranks.tsv | Tabular | |||
| E-MTAB-2287.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 51 |
Similar Datasets
Project description:<p>Rust fungi are plant pathogens that cause epidemics which threatens the production of many important plant species, such as wheat, soy, coffee and poplar. Melampsora larici-populina (Mlp) causes the poplar rust and encodes at least 1184 candidate effectors (CEs), however their functions are poorly known. In this study, we analysed the transcriptome and metabolome of Arabidopsis constitutively expressing CEs of Mlp to discover processes targeted by these fungal proteins. For this purpose, we sequenced the transcriptome and used mass spectrometry to analyse the metabolome of Arabidopsis plants expressing one of 14 selected CEs and of a control line. We found 2299 deregulated genes in at least one of the 14 transgenic lines. Among the down-regulated genes, the KEGG pathways “MAPK signaling pathway” and “Plant-pathogen interaction” were over-represented in six and five of the 14 transgenic lines, respectively. Moreover, the genes down-regulated across the fourteen transgenic lines are related to hormone response and defense. </p><p>Regarding the metabolome, there were 680 metabolites deregulated across the 14 transgenic lines, with highly unsaturated and phenolic compounds and peptides enriched among down-regulated and up-regulated metabolites, respectively, in almost all transgenic lines. Interestingly, we found that some transgenic lines expressing CEs with no similarity in amino acid sequence had similar patterns of gene and metabolite deregulation, while plants expressing CEs from the same family deregulated different genes and metabolites. Taken together, our results indicate that the sequence of effectors may not be a good predictor of its impact in the plant.</p>
2020-12-03 | MTBLS2096 | MetaboLights
Project description:WARNING: This library was yield low amount of material and it was over-amplified by PCR. This libraries are used study the robustness of several statitical methods against PCR artifacts. ChIP experiments were performed on Arabidopsis wildtype inflorescences using an antibody raised against a C-terminal peptide of SEP3. ArrayExpress Release Date: 2011-04-27 Publication Title: ChIP-seq Analysis in R (CSAR): An R package for the statistical detection of protein-bound genomic regions Publication Author List: Jose M. Muino, Kerstin Kaufmann, Roeland C. H. J. van Ham, Gerco C. Angenent, and Pawel Krajewski Person Roles: submitter Person Last Name: Muino Person First Name: Jose Person Mid Initials: M. Person Email: jose.muino@wur.nl Person Phone: 0317-481122 Person Address: Droevendaalsesteeg 1, P.O. Box 16, 6700 AA Wageningen, The Netherlands Person Affiliation: Plant Research International B.V.
2011-07-14 | GSE30616 | GEO
Project description:Despite the broad use of single-cell and single-nucleus RNA sequencing in plant research, accurate cluster annotation in less studied plant species remains a major challenge due to the lack of validated marker genes. Here, using soil-grown wheat roots as a model, we generated a single-cell RNA-sequencing (scRNA-seq) atlas and annotated cluster identities in an unbiased way by transferring existing annotations from publicly available datasets in wheat, rice, maize and Arabidopsis. These cross-species orthology-based predictions were next validated using untargeted spatial transcriptomics. This information refined existing cluster annotations for different datasets across key plant model species. We then used the validated clusters to generate cell type-specific gene regulatory networks for root tissues of wheat and two other monocot crop species. By integrating all available data, including homeolog expression in wheat, we predicted reliable tissue-specific markers which are conserved across different species. In summary, we provided an annotated and validated single cell transcriptomic resource for soil-grown wheat root apical meristems and revealed conserved cell type-specific regulators and markers across species. These data expand upon previous root single cell atlas resources in crops, and will facilitate cell type annotation in non-model plant species in the future.
2025-01-06 | GSE271725 | GEO
Project description:Despite the broad use of single-cell and single-nucleus RNA sequencing in plant research, accurate cluster annotation in less studied plant species remains a major challenge due to the lack of validated marker genes. Here, using soil-grown wheat roots as a model, we generated a single-cell RNA-sequencing (scRNA-seq) atlas and annotated cluster identities in an unbiased way by transferring existing annotations from publicly available datasets in wheat, rice, maize and Arabidopsis. These cross-species orthology-based predictions were next validated using untargeted spatial transcriptomics. This information refined existing cluster annotations for different datasets across key plant model species. We then used the validated clusters to generate cell type-specific gene regulatory networks for root tissues of wheat and two other monocot crop species. By integrating all available data, including homeolog expression in wheat, we predicted reliable tissue-specific markers which are conserved across different species. In summary, we provided an annotated and validated single cell transcriptomic resource for soil-grown wheat root apical meristems and revealed conserved cell type-specific regulators and markers across species. These data expand upon previous root single cell atlas resources in crops, and will facilitate cell type annotation in non-model plant species in the future.
2025-01-06 | GSE270342 | GEO
Project description:Canola plants inoculated with plant growth-promoting bacteria either expressing ACC deaminase or not to determine the effect on plant gene expression using an Arabidopsis microarray.
2011-11-01 | GSE31396 | GEO
Project description:deOliveiraDalMolin2010 - Genome-scale
metabolic network of Arabidopsis thaliana (AraGEM)
This model is described in the article:
AraGEM, a genome-scale
reconstruction of the primary metabolic network in
Arabidopsis.
de Oliveira Dal'Molin CG, Quek LE,
Palfreyman RW, Brumbley SM, Nielsen LK.
Plant Physiol. 2010 Feb; 152(2):
579-589
Abstract:
Genome-scale metabolic network models have been successfully
used to describe metabolism in a variety of microbial organisms
as well as specific mammalian cell types and organelles. This
systems-based framework enables the exploration of global
phenotypic effects of gene knockouts, gene insertion, and
up-regulation of gene expression. We have developed a
genome-scale metabolic network model (AraGEM) covering primary
metabolism for a compartmentalized plant cell based on the
Arabidopsis (Arabidopsis thaliana) genome. AraGEM is a
comprehensive literature-based, genome-scale metabolic
reconstruction that accounts for the functions of 1,419 unique
open reading frames, 1,748 metabolites, 5,253 gene-enzyme
reaction-association entries, and 1,567 unique reactions
compartmentalized into the cytoplasm, mitochondrion, plastid,
peroxisome, and vacuole. The curation process identified 75
essential reactions with respective enzyme associations not
assigned to any particular gene in the Kyoto Encyclopedia of
Genes and Genomes or AraCyc. With the addition of these
reactions, AraGEM describes a functional primary metabolism of
Arabidopsis. The reconstructed network was transformed into an
in silico metabolic flux model of plant metabolism and
validated through the simulation of plant metabolic functions
inferred from the literature. Using efficient resource
utilization as the optimality criterion, AraGEM predicted the
classical photorespiratory cycle as well as known key
differences between redox metabolism in photosynthetic and
nonphotosynthetic plant cells. AraGEM is a viable framework for
in silico functional analysis and can be used to derive new,
nontrivial hypotheses for exploring plant metabolism.
This model is hosted on
BioModels Database
and identified by:
MODEL1507180028.
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 | MODEL1507180028 | BioModels
Project description:Rust fungi are plant pathogens that cause epidemics which threatens the production of many important plant species, such as wheat, soy, coffee and poplar. Melampsora larici-populina (Mlp) causes the poplar rust and encodes at least 1 184 candidate effectors (CEs), however their functions are poorly known. In this study, we analysed the transcriptome and metabolome of Arabidopsis constitutively expressing CEs of Mlp to discover processes targeted by these fungal proteins. For this purpose, we sequenced the transcriptome and used mass spectrometry to analyse the metabolome of Arabidopsis plants expressing one of 14 selected CEs and of a control line. We found 2 299 deregulated genes in at least one of the 14 transgenic lines. Among the down-regulated genes, the KEGG pathways MAPK signaling pathway and Plant-pathogen interaction were over-represented in six and five of the 14 transgenic lines, respectively. Moreover, the genes down-regulated across the fourteen transgenic lines are related to hormone response and defense. Regarding the metabolome, there were 680 metabolites deregulated across the 14 transgenic lines, with highly unsaturated and phenolic compounds and peptides enriched among down-regulated and up-regulated metabolites, respectively, in almost all transgenic lines. Interestingly, we found that some transgenic lines expressing CEs with no similarity in amino acid sequence had similar patterns of gene and metabolite deregulation, while plants expressing CEs from the same family deregulated different genes and metabolites. Taken together, our results indicate that the sequence of effectors may not be a good predictor of its impact in the plant.
2020-09-24 | GSE158410 | GEO
Project description:TabZIP6 is a Subgroup C bZIP protein from wheat. Some evidences have shown that TabZIP6 is involved in cold stress response. To elucidate the regulatory mechanism of TabZIP6 in plant cold response, cold treated/untreated TabZIP6-overexpressing Arabidopsis seedlings were used to perform microarray analysis.
2018-01-01 | GSE106635 | GEO
Project description:Cytokinins are plant hormones with biological functions ranging from coordination of plant growth and development to the regulation of senescence. A series of 2-chloro-N6-(halogenobenzylamino)purine ribosides was prepared and tested for cytokinin activity in selected bioassays. Several compounds showed significant activity, especially in delaying senescence in detached wheat leaves. We used microarrays to gather information about the reprogramming of gene transcription when senescent Arabidopsis leaves were treated with selected C2-substituted aromatic cytokinin ribosides that showed high activity in the senescence bioassay.
2015-12-11 | GSE75875 | GEO
Project description:Phytohormones are key regulators of plant growth, development, and signalling networks involved in responses to diverse biotic and abiotic stresses. Transcriptional reference maps of hormone responses have been reported for several model plant species such as Arabidopsis thaliana, Oryza sativa, and Brachypodium distachyon. However, because of species differences and the complexity of the wheat genome, these transcriptome data are not appropriate reference material for wheat studies. We comprehensively analysed the transcriptomic responses in wheat spikes to seven phytohormones, including indole acetic acid (IAA), gibberellic acid (GA), abscisic acid (ABA), ethylene (ET), cytokinin (CK), salicylic acid (SA), and methyl jasmonic acid (MeJA). A total of 3386 genes were differentially expressed at 24 h after the hormone treatments. Furthermore, 22.7% of these genes exhibited overlapping transcriptional responses for at least two hormones, implying there is crosstalk among phytohormones. We subsequently identified genes with expression levels that were significantly and differentially induced by a specific phytohormone (i.e., hormone-specific responses). The data for these hormone-responsive genes were then compared with the transcriptome data for wheat spikes exposed to biotic (Fusarium head blight) and abiotic (water deficit) stresses. Our data were used to develop a transcriptional reference map of hormone responses in wheat spikes.
2017-09-05 | GSE103430 | GEO