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Published on: December 22, 2015
Disentangling information flow in the Ras-cAMP signaling network
Gregory W Carter1, Steffen Rupp, Gerald R Fink
1Institute for Systems Biology, Seattle, Washington 98103, USA. gcarter@systemsbiology.org
Signal transduction involves complex, interconnected pathways influencing broad genomic expression changes, not isolated gene sets. This study maps these intricate signaling networks using a yeast model, revealing multiple information flow paths.
Area of Science:
- Molecular Biology
- Systems Biology
- Genomics
Background:
- Signal transduction pathways regulate gene expression.
- Genomic responses to signaling perturbations are complex and widespread.
- Existing models often simplify signal flow into isolated pathways.
Purpose of the Study:
- To investigate the complex, interconnected nature of signal transduction pathways.
- To model multiple, entangled information flow paths influencing gene expression.
- To develop testable hypotheses for genome-wide transcriptional responses.
Main Methods:
- Utilized the Ras-cAMP pathway in Saccharomyces cerevisiae as a model system.
- Perturbed key signaling elements and collected genome-wide expression data.
- Applied singular value decomposition to analyze transcriptional responses.
- Integrated molecular interaction data to link gene groups with signaling elements.
Main Results:
- Identified broad, varied, and complex changes in gene expression across the genome.
- Separated genome-wide transcriptional response into weighted expression components.
- Mapped multiple putative pathways of information flow through a dense signaling network.
- Connected specific gene groups to perturbed signaling elements.
Conclusions:
- Signal transduction is mediated by multiple, entangled pathways influencing overlapping gene sets.
- The developed network model provides insights into complex gene-expression regulation.
- This approach generates testable hypotheses for understanding signaling networks.
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