Dataset Information

Integrated functional networks of process, tissue, and developmental stage specific interactions in Arabidopsis thaliana.

ABSTRACT:

Background

Recent years have seen an explosion in plant genomics, as the difficulties inherent in sequencing and functionally analyzing these biologically and economically significant organisms have been overcome. Arabidopsis thaliana, a versatile model organism, represents an opportunity to evaluate the predictive power of biological network inference for plant functional genomics.

Results

Here, we provide a compendium of functional relationship networks for Arabidopsis thaliana leveraging data integration based on over 60 microarray, physical and genetic interaction, and literature curation datasets. These include tissue, biological process, and development stage specific networks, each predicting relationships specific to an individual biological context. These biological networks enable the rapid investigation of uncharacterized genes in specific tissues and developmental stages of interest and summarize a very large collection of A. thaliana data for biological examination. We found validation in the literature for many of our predicted networks, including those involved in disease resistance, root hair patterning, and auxin homeostasis.

Conclusions

These context-specific networks demonstrate that highly specific biological hypotheses can be generated for a diversity of individual processes, developmental stages, and plant tissues in A. thaliana. All predicted functional networks are available online at http://function.princeton.edu/arathGraphle.

SUBMITTER: Pop A

PROVIDER: S-EPMC3023688 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated functional networks of process, tissue, and developmental stage specific interactions in Arabidopsis thaliana.

Pop Ana A Huttenhower Curtis C Iyer-Pascuzzi Anjali A Benfey Philip N PN Troyanskaya Olga G OG

BMC systems biology 20101231

<h4>Background</h4>Recent years have seen an explosion in plant genomics, as the difficulties inherent in sequencing and functionally analyzing these biologically and economically significant organisms have been overcome. Arabidopsis thaliana, a versatile model organism, represents an opportunity to evaluate the predictive power of biological network inference for plant functional genomics.<h4>Results</h4>Here, we provide a compendium of functional relationship networks for Arabidopsis thaliana ...[more]

PMID: 21194434

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Project description:BACKGROUND: Plant microRNAs (miRNAs) have been revealed to play important roles in developmental control, hormone secretion, cell differentiation and proliferation, and response to environmental stresses. However, our knowledge about the regulatory mechanisms and functions of miRNAs remains very limited. The main difficulties lie in two aspects. On one hand, the number of experimentally validated miRNA targets is very limited and the predicted targets often include many false positives, which constrains us to reveal the functions of miRNAs. On the other hand, the regulation of miRNAs is known to be spatio-temporally specific, which increases the difficulty for us to understand the regulatory mechanisms of miRNAs. DESCRIPTION: In this paper we present miRFANs, an online database for Arabidopsis thalianamiRNA function annotations. We integrated various type of datasets, including miRNA-target interactions, transcription factor (TF) and their targets, expression profiles, genomic annotations and pathways, into a comprehensive database, and developed various statistical and mining tools, together with a user-friendly web interface. For each miRNA target predicted by psRNATarget, TargetAlign and UEA target-finder, or recorded in TarBase and miRTarBase, the effect of its up-regulated or down-regulated miRNA on the expression level of the target gene is evaluated by carrying out differential expression analysis of both miRNA and targets expression profiles acquired under the same (or similar) experimental condition and in the same tissue. Moreover, each miRNA target is associated with gene ontology and pathway terms, together with the target site information and regulating miRNAs predicted by different computational methods. These associated terms may provide valuable insight for the functions of each miRNA. CONCLUSION: First, a comprehensive collection of miRNA targets for Arabidopsis thaliana provides valuable information about the functions of plant miRNAs. Second, a highly informative miRNA-mediated genetic regulatory network is extracted from our integrative database. Third, a set of statistical and mining tools is equipped for analyzing and mining the database. And fourth, a user-friendly web interface is developed to facilitate the browsing and analysis of the collected data.

Project description:Organellar gene expression (OGE) is crucial for plant development, photosynthesis, and respiration, but our understanding of the mechanisms that control it is still relatively poor. Thus, OGE requires various nucleus-encoded proteins that promote transcription, splicing, trimming, and editing of organellar RNAs, and regulate translation. In metazoans, proteins of the mitochondrial Transcription tERmination Factor (mTERF) family interact with the mitochondrial chromosome and regulate transcriptional initiation and termination. Sequencing of the Arabidopsis thaliana genome led to the identification of a diversified MTERF gene family but, in contrast to mammalian mTERFs, knowledge about the function of these proteins in photosynthetic organisms is scarce. In this hypothesis article, I show that tandem duplications and one block duplication contributed to the large number of MTERF genes in A. thaliana, and propose that the expansion of the family is related to the evolution of land plants. The MTERF genes-especially the duplicated genes-display a number of distinct mRNA accumulation patterns, suggesting functional diversification of mTERF proteins to increase adaptability to environmental changes. Indeed, hypothetical functions for the different mTERF proteins can be predicted using co-expression analysis and gene ontology (GO) annotations. On this basis, mTERF proteins can be sorted into five groups. Members of the "chloroplast" and "chloroplast-associated" clusters are principally involved in chloroplast gene expression, embryogenesis, and protein catabolism, while representatives of the "mitochondrial" cluster seem to participate in DNA and RNA metabolism in that organelle. Moreover, members of the "mitochondrion-associated" cluster and the "low expression" group may act in the nucleus and/or the cytosol. As proteins involved in OGE and presumably nuclear gene expression (NGE), mTERFs are ideal candidates for the coordination of the expression of organelle and nuclear genomes.

Dataset Information

Integrated functional networks of process, tissue, and developmental stage specific interactions in Arabidopsis thaliana.

Background

Results

Conclusions

Publications

Integrated functional networks of process, tissue, and developmental stage specific interactions in Arabidopsis thaliana.

Similar Datasets

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