Dataset Information

'MicroRNA Targets', a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana.

ABSTRACT: BACKGROUND:The AthaMap database generates a genome-wide map for putative transcription factor binding sites for A. thaliana. When analyzing transcriptional regulation using AthaMap it may be important to learn which genes are also post-transcriptionally regulated by inhibitory RNAs. Therefore, a unified database for transcriptional and post-transcriptional regulation will be highly useful for the analysis of gene expression regulation. METHODS:To identify putative microRNA target sites in the genome of A. thaliana, processed mature miRNAs from 243 annotated miRNA genes were used for screening with the psRNATarget web server. Positional information, target genes and the psRNATarget score for each target site were annotated to the AthaMap database. Furthermore, putative target sites for small RNAs from seven small RNA transcriptome datasets were used to determine small RNA target sites within the A. thaliana genome. RESULTS:Putative 41,965 genome wide miRNA target sites and 10,442 miRNA target genes were identified in the A. thaliana genome. Taken together with genes targeted by small RNAs from small RNA transcriptome datasets, a total of 16,600 A. thaliana genes are putatively regulated by inhibitory RNAs. A novel web-tool, 'MicroRNA Targets', was integrated into AthaMap which permits the identification of genes predicted to be regulated by selected miRNAs. The predicted target genes are displayed with positional information and the psRNATarget score of the target site. Furthermore, putative target sites of small RNAs from selected tissue datasets can be identified with the new 'Small RNA Targets' web-tool. CONCLUSIONS:The integration of predicted miRNA and small RNA target sites with transcription factor binding sites will be useful for AthaMap-assisted gene expression analysis. URL: http://www.athamap.de/

SUBMITTER: Bulow L

PROVIDER: S-EPMC3410767 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

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'MicroRNA Targets', a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana.

Bülow Lorenz L Bolívar Julio C JC Ruhe Jonas J Brill Yuri Y Hehl Reinhard R

BioData mining 20120716 1

<h4>Background</h4>The AthaMap database generates a genome-wide map for putative transcription factor binding sites for A. thaliana. When analyzing transcriptional regulation using AthaMap it may be important to learn which genes are also post-transcriptionally regulated by inhibitory RNAs. Therefore, a unified database for transcriptional and post-transcriptional regulation will be highly useful for the analysis of gene expression regulation.<h4>Methods</h4>To identify putative microRNA target ...[more]

PMID: 22800758

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Project description:BackgroundTranscription factors (TFs) regulate downstream genes in response to environmental stresses in plants. Identification of TF target genes can provide insight on molecular mechanisms of stress response systems, which can lead to practical applications such as engineering crops that thrive in challenging environments. Despite various computational techniques that have been developed for identifying TF targets, it remains a challenge to make best use of available experimental data, especially from time-series transcriptome profiling data, for improving TF target identification.ResultsIn this study, we used a novel approach that combined kinetic modelling of gene expression with a statistical meta-analysis to predict targets of 757 TFs using expression data of 14,905 genes in Arabidopsis exposed to different durations and types of abiotic stresses. Using a kinetic model for the time delay between the expression of a TF gene and its potential targets, we shifted a TF's expression profile to make an interacting pair coherent. We found that partitioning the expression data by tissue and developmental stage improved correlation between TFs and their targets. We identified consensus pairs of correlated profiles between a TF and all other genes among partitioned datasets. We applied this approach to predict novel targets of known TFs. Some of these putative targets were validated from the literature, for E2F's targets in particular, while others provide explicit genes as hypotheses for future studies.ConclusionOur method provides a general framework for TF target prediction with consideration of the time lag between initiation of a TF and activation of its targets. The framework helps make significant inferences by reducing the effects of independent noises in different experiments and by identifying recurring regulatory relationships under various biological conditions. Our TF target predictions may shed some light on common regulatory networks in abiotic stress responses.

Dataset Information

'MicroRNA Targets', a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana.

Publications

'MicroRNA Targets', a new AthaMap web-tool for genome-wide identification of miRNA targets in Arabidopsis thaliana.

Similar Datasets

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