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Large-scale analysis of Arabidopsis transcription reveals a basal co-regulation network.

Atias O, Chor B, Chamovitz DA - BMC Syst Biol (2009)

Bottom Line: We found clusters of globally co-expressed Arabidopsis genes that are enriched for known Gene Ontology annotations.The analysis reveals that part of the Arabidopsis transcriptome is globally co-expressed, and can be further divided into known as well as novel functional gene modules.Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Plant Sciences, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel. dafniosn@post.tau.ac.il

ABSTRACT

Background: Analyses of gene expression data from microarray experiments has become a central tool for identifying co-regulated, functional gene modules. A crucial aspect of such analysis is the integration of data from different experiments and different laboratories. How to weigh the contribution of different experiments is an important point influencing the final outcomes. We have developed a novel method for this integration, and applied it to genome-wide data from multiple Arabidopsis microarray experiments performed under a variety of experimental conditions. The goal of this study is to identify functional globally co-regulated gene modules in the Arabidopsis genome.

Results: Following the analysis of 21,000 Arabidopsis genes in 43 datasets and about 2 x 10(8) gene pairs, we identified a globally co-expressed gene network. We found clusters of globally co-expressed Arabidopsis genes that are enriched for known Gene Ontology annotations. Two types of modules were identified in the regulatory network that differed in their sensitivity to the node-scoring parameter; we further showed these two pertain to general and specialized modules. Some of these modules were further investigated using the Genevestigator compendium of microarray experiments. Analyses of smaller subsets of data lead to the identification of condition-specific modules.

Conclusion: Our method for identification of gene clusters allows the integration of diverse microarray experiments from many sources. The analysis reveals that part of the Arabidopsis transcriptome is globally co-expressed, and can be further divided into known as well as novel functional gene modules. Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.

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Related in: MedlinePlus

Genevestigator analysis of a pathogen response cluster from the pathogen response network. Expression of a cluster found using pathogen stress experiments was analyzed using Genevestigator. (A) Graph showing the genes in the cluster and the edges that exist between them in the pathogen stress network. Expression according to (B) anatomical tissues or (C) developmental stages, is shown. Expression levels are shown in heat maps, where dark blue indicates maximal expression. Expression levels in B and C are shown in heat maps, where dark blue indicates maximal expression. (D) Gene expression in different cpr5 mutants. Expression levels are shown in a heat map in which intense green and red indicate down- or up-regulation in comparison to wild type, respectively. Figures in B, C and D were generated using Genevestigator.
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Figure 7: Genevestigator analysis of a pathogen response cluster from the pathogen response network. Expression of a cluster found using pathogen stress experiments was analyzed using Genevestigator. (A) Graph showing the genes in the cluster and the edges that exist between them in the pathogen stress network. Expression according to (B) anatomical tissues or (C) developmental stages, is shown. Expression levels are shown in heat maps, where dark blue indicates maximal expression. Expression levels in B and C are shown in heat maps, where dark blue indicates maximal expression. (D) Gene expression in different cpr5 mutants. Expression levels are shown in a heat map in which intense green and red indicate down- or up-regulation in comparison to wild type, respectively. Figures in B, C and D were generated using Genevestigator.

Mentions: As before, we compared our results for the first cluster detected in the pathogen response network (cluster ID 1) using the Genevestigator data. Figures 7B and 7C show that limited overall co-expression is detected within the genes of this cluster. On the other hand, we found that all genes in the cluster are up-regulated in at least one of the cpr5 mutant lines (Figure 7D). CPR5 is a known major regulator of pathogenesis-related (PR) genes [27,28], indicating that this cluster is indeed highly specific for pathogen response.


Large-scale analysis of Arabidopsis transcription reveals a basal co-regulation network.

Atias O, Chor B, Chamovitz DA - BMC Syst Biol (2009)

Genevestigator analysis of a pathogen response cluster from the pathogen response network. Expression of a cluster found using pathogen stress experiments was analyzed using Genevestigator. (A) Graph showing the genes in the cluster and the edges that exist between them in the pathogen stress network. Expression according to (B) anatomical tissues or (C) developmental stages, is shown. Expression levels are shown in heat maps, where dark blue indicates maximal expression. Expression levels in B and C are shown in heat maps, where dark blue indicates maximal expression. (D) Gene expression in different cpr5 mutants. Expression levels are shown in a heat map in which intense green and red indicate down- or up-regulation in comparison to wild type, respectively. Figures in B, C and D were generated using Genevestigator.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2944327&req=5

Figure 7: Genevestigator analysis of a pathogen response cluster from the pathogen response network. Expression of a cluster found using pathogen stress experiments was analyzed using Genevestigator. (A) Graph showing the genes in the cluster and the edges that exist between them in the pathogen stress network. Expression according to (B) anatomical tissues or (C) developmental stages, is shown. Expression levels are shown in heat maps, where dark blue indicates maximal expression. Expression levels in B and C are shown in heat maps, where dark blue indicates maximal expression. (D) Gene expression in different cpr5 mutants. Expression levels are shown in a heat map in which intense green and red indicate down- or up-regulation in comparison to wild type, respectively. Figures in B, C and D were generated using Genevestigator.
Mentions: As before, we compared our results for the first cluster detected in the pathogen response network (cluster ID 1) using the Genevestigator data. Figures 7B and 7C show that limited overall co-expression is detected within the genes of this cluster. On the other hand, we found that all genes in the cluster are up-regulated in at least one of the cpr5 mutant lines (Figure 7D). CPR5 is a known major regulator of pathogenesis-related (PR) genes [27,28], indicating that this cluster is indeed highly specific for pathogen response.

Bottom Line: We found clusters of globally co-expressed Arabidopsis genes that are enriched for known Gene Ontology annotations.The analysis reveals that part of the Arabidopsis transcriptome is globally co-expressed, and can be further divided into known as well as novel functional gene modules.Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Plant Sciences, The George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel. dafniosn@post.tau.ac.il

ABSTRACT

Background: Analyses of gene expression data from microarray experiments has become a central tool for identifying co-regulated, functional gene modules. A crucial aspect of such analysis is the integration of data from different experiments and different laboratories. How to weigh the contribution of different experiments is an important point influencing the final outcomes. We have developed a novel method for this integration, and applied it to genome-wide data from multiple Arabidopsis microarray experiments performed under a variety of experimental conditions. The goal of this study is to identify functional globally co-regulated gene modules in the Arabidopsis genome.

Results: Following the analysis of 21,000 Arabidopsis genes in 43 datasets and about 2 x 10(8) gene pairs, we identified a globally co-expressed gene network. We found clusters of globally co-expressed Arabidopsis genes that are enriched for known Gene Ontology annotations. Two types of modules were identified in the regulatory network that differed in their sensitivity to the node-scoring parameter; we further showed these two pertain to general and specialized modules. Some of these modules were further investigated using the Genevestigator compendium of microarray experiments. Analyses of smaller subsets of data lead to the identification of condition-specific modules.

Conclusion: Our method for identification of gene clusters allows the integration of diverse microarray experiments from many sources. The analysis reveals that part of the Arabidopsis transcriptome is globally co-expressed, and can be further divided into known as well as novel functional gene modules. Our methodology is general enough to apply to any set of microarray experiments, using any scoring function.

Show MeSH
Related in: MedlinePlus