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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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Analysis of gene modules using Genevestigator. Expression of four clusters (see Tables 6 and 7, Figure 4) was analyzed using Genevestigator. (A) Graph showing the genes in the clusters and the edges that exist between them in the 0.3 and 0.4 networks (each cluster shows edges from the network it was detected in). 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. Figures in B and C were generated using Genevestigator.
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Figure 5: Analysis of gene modules using Genevestigator. Expression of four clusters (see Tables 6 and 7, Figure 4) was analyzed using Genevestigator. (A) Graph showing the genes in the clusters and the edges that exist between them in the 0.3 and 0.4 networks (each cluster shows edges from the network it was detected in). 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. Figures in B and C were generated using Genevestigator.

Mentions: The globally co-expressed gene modules detected in the networks may serve as a basis for more extensive studies of genes and modules of interest. A simple, straightforward analysis can be done using Genevestigator [22], a gene expression analysis tool for Arabidopsis and other organisms. Here we show selected examples of some of the analysis we were able to perform using this tool. For the analysis, we have chosen 2788 samples available in the Genevestigator database that encompass all high quality experiments performed using the 22k Arabidopsis Affymetrix chip. Experiments already used in our co-expression analysis were excluded from the comparison, to limit bias. Using the Genevestigator Analysis tool, we compared the expression levels of the genes in four of our clusters, two from each of the two networks (Figure 5A). These four clusters are all classified as node-score-independent clusters, and were identified as enriched for specific GO terms (Table 6). As seen in Figure 5, the modules we identified contain genes which also appear co-expressed in Genevestigator. For example, the genes in these four modules behave as four unique clusters in both the plant anatomy (Figure 5B) and plant development (Figure 5C) analyses. This provides a verification of our results with regard to these clusters, as well as an initial insight into the anatomical and developmental conditions under which the modules are likely to be biologically relevant. For example, the cluster marked as #2 is functional in cell wall structure (see Table 6), and according to the Genevestigator data is preferentially expressed in seedling roots.


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

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

Analysis of gene modules using Genevestigator. Expression of four clusters (see Tables 6 and 7, Figure 4) was analyzed using Genevestigator. (A) Graph showing the genes in the clusters and the edges that exist between them in the 0.3 and 0.4 networks (each cluster shows edges from the network it was detected in). 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. Figures in B and C were generated using Genevestigator.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 5: Analysis of gene modules using Genevestigator. Expression of four clusters (see Tables 6 and 7, Figure 4) was analyzed using Genevestigator. (A) Graph showing the genes in the clusters and the edges that exist between them in the 0.3 and 0.4 networks (each cluster shows edges from the network it was detected in). 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. Figures in B and C were generated using Genevestigator.
Mentions: The globally co-expressed gene modules detected in the networks may serve as a basis for more extensive studies of genes and modules of interest. A simple, straightforward analysis can be done using Genevestigator [22], a gene expression analysis tool for Arabidopsis and other organisms. Here we show selected examples of some of the analysis we were able to perform using this tool. For the analysis, we have chosen 2788 samples available in the Genevestigator database that encompass all high quality experiments performed using the 22k Arabidopsis Affymetrix chip. Experiments already used in our co-expression analysis were excluded from the comparison, to limit bias. Using the Genevestigator Analysis tool, we compared the expression levels of the genes in four of our clusters, two from each of the two networks (Figure 5A). These four clusters are all classified as node-score-independent clusters, and were identified as enriched for specific GO terms (Table 6). As seen in Figure 5, the modules we identified contain genes which also appear co-expressed in Genevestigator. For example, the genes in these four modules behave as four unique clusters in both the plant anatomy (Figure 5B) and plant development (Figure 5C) analyses. This provides a verification of our results with regard to these clusters, as well as an initial insight into the anatomical and developmental conditions under which the modules are likely to be biologically relevant. For example, the cluster marked as #2 is functional in cell wall structure (see Table 6), and according to the Genevestigator data is preferentially expressed in seedling roots.

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