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Boolean modeling of transcriptome data reveals novel modes of heterotrimeric G-protein action.

Pandey S, Wang RS, Wilson L, Li S, Zhao Z, Gookin TE, Assmann SM, Albert R - Mol. Syst. Biol. (2010)

Bottom Line: Although G-protein control of the transcriptome has received little attention to date in any system, transcriptome analysis allows us to search for potentially uncommon yet significant signaling mechanisms.We find that (1) classical mechanisms of G-protein signaling are well represented.Our method holds significant promise for analyzing analogous 'switch-like' signal transduction events in any organism.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.

ABSTRACT
Heterotrimeric G-proteins mediate crucial and diverse signaling pathways in eukaryotes. Here, we generate and analyze microarray data from guard cells and leaves of G-protein subunit mutants of the model plant Arabidopsis thaliana, with or without treatment with the stress hormone, abscisic acid. Although G-protein control of the transcriptome has received little attention to date in any system, transcriptome analysis allows us to search for potentially uncommon yet significant signaling mechanisms. We describe the theoretical Boolean mechanisms of G-protein x hormone regulation, and then apply a pattern matching approach to associate gene expression profiles with Boolean models. We find that (1) classical mechanisms of G-protein signaling are well represented. Conversely, some theoretical regulatory modes of the G-protein are not supported; (2) a new mechanism of G-protein signaling is revealed, in which Gbeta regulates gene expression identically in the presence or absence of Galpha; (3) guard cells and leaves favor different G-protein modes in transcriptome regulation, supporting system specificity of G-protein signaling. Our method holds significant promise for analyzing analogous 'switch-like' signal transduction events in any organism.

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Examples of idealized differential expression patterns determined by the regulatory modes of the G-protein and/or ABA. The lines on the left panel represent idealized gene expression patterns such as those in Table I. In the corresponding differential expression patterns in the right panel, the first six elements correspond to genotype comparisons in the absence of ABA, the second six elements correspond to genotype comparisons in the presence of ABA, and the last four elements correspond to comparison of ±ABA treatment within the same genotype. The dashed horizontal line corresponds to no differential expression. Segments below the dashed line indicate downregulation in the first condition versus the second condition and segments above it indicate upregulation.
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f2: Examples of idealized differential expression patterns determined by the regulatory modes of the G-protein and/or ABA. The lines on the left panel represent idealized gene expression patterns such as those in Table I. In the corresponding differential expression patterns in the right panel, the first six elements correspond to genotype comparisons in the absence of ABA, the second six elements correspond to genotype comparisons in the presence of ABA, and the last four elements correspond to comparison of ±ABA treatment within the same genotype. The dashed horizontal line corresponds to no differential expression. Segments below the dashed line indicate downregulation in the first condition versus the second condition and segments above it indicate upregulation.

Mentions: Each regulatory mode represented by A(GPA1, AGB1) or B(ABA, A(GPA1, AGB1)) corresponds to an idealized Boolean expression pattern. To avoid potential biases in binarizing expression levels, instead of correlating absolute expression profiles, our method is based on the differential expression patterns of genes. Figure 2 illustrates four examples of idealized expression patterns and idealized differential expression patterns of genes governed by Boolean functions. To associate genes with regulatory modes of the G-protein and/or ABA, we construct the real differential expression pattern of each gene and adopt a correlation-based pattern matching approach to examine whether the real differential expression pattern of the gene is consistent with one of the idealized differential expression patterns given by the Boolean regulatory modes of the G-protein and/or ABA (see Materials and methods). By looking at the number of genes belonging to each regulatory mode, we are able to gauge the plausibility of each mode.


Boolean modeling of transcriptome data reveals novel modes of heterotrimeric G-protein action.

Pandey S, Wang RS, Wilson L, Li S, Zhao Z, Gookin TE, Assmann SM, Albert R - Mol. Syst. Biol. (2010)

Examples of idealized differential expression patterns determined by the regulatory modes of the G-protein and/or ABA. The lines on the left panel represent idealized gene expression patterns such as those in Table I. In the corresponding differential expression patterns in the right panel, the first six elements correspond to genotype comparisons in the absence of ABA, the second six elements correspond to genotype comparisons in the presence of ABA, and the last four elements correspond to comparison of ±ABA treatment within the same genotype. The dashed horizontal line corresponds to no differential expression. Segments below the dashed line indicate downregulation in the first condition versus the second condition and segments above it indicate upregulation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2913393&req=5

f2: Examples of idealized differential expression patterns determined by the regulatory modes of the G-protein and/or ABA. The lines on the left panel represent idealized gene expression patterns such as those in Table I. In the corresponding differential expression patterns in the right panel, the first six elements correspond to genotype comparisons in the absence of ABA, the second six elements correspond to genotype comparisons in the presence of ABA, and the last four elements correspond to comparison of ±ABA treatment within the same genotype. The dashed horizontal line corresponds to no differential expression. Segments below the dashed line indicate downregulation in the first condition versus the second condition and segments above it indicate upregulation.
Mentions: Each regulatory mode represented by A(GPA1, AGB1) or B(ABA, A(GPA1, AGB1)) corresponds to an idealized Boolean expression pattern. To avoid potential biases in binarizing expression levels, instead of correlating absolute expression profiles, our method is based on the differential expression patterns of genes. Figure 2 illustrates four examples of idealized expression patterns and idealized differential expression patterns of genes governed by Boolean functions. To associate genes with regulatory modes of the G-protein and/or ABA, we construct the real differential expression pattern of each gene and adopt a correlation-based pattern matching approach to examine whether the real differential expression pattern of the gene is consistent with one of the idealized differential expression patterns given by the Boolean regulatory modes of the G-protein and/or ABA (see Materials and methods). By looking at the number of genes belonging to each regulatory mode, we are able to gauge the plausibility of each mode.

Bottom Line: Although G-protein control of the transcriptome has received little attention to date in any system, transcriptome analysis allows us to search for potentially uncommon yet significant signaling mechanisms.We find that (1) classical mechanisms of G-protein signaling are well represented.Our method holds significant promise for analyzing analogous 'switch-like' signal transduction events in any organism.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.

ABSTRACT
Heterotrimeric G-proteins mediate crucial and diverse signaling pathways in eukaryotes. Here, we generate and analyze microarray data from guard cells and leaves of G-protein subunit mutants of the model plant Arabidopsis thaliana, with or without treatment with the stress hormone, abscisic acid. Although G-protein control of the transcriptome has received little attention to date in any system, transcriptome analysis allows us to search for potentially uncommon yet significant signaling mechanisms. We describe the theoretical Boolean mechanisms of G-protein x hormone regulation, and then apply a pattern matching approach to associate gene expression profiles with Boolean models. We find that (1) classical mechanisms of G-protein signaling are well represented. Conversely, some theoretical regulatory modes of the G-protein are not supported; (2) a new mechanism of G-protein signaling is revealed, in which Gbeta regulates gene expression identically in the presence or absence of Galpha; (3) guard cells and leaves favor different G-protein modes in transcriptome regulation, supporting system specificity of G-protein signaling. Our method holds significant promise for analyzing analogous 'switch-like' signal transduction events in any organism.

Show MeSH
Related in: MedlinePlus