Inferring Condition-Specific Modulation of Transcription Factor Activity in Yeast
Author Information
Author(s): Boorsma André, Lu Xiang-Jun, Zakrzewska Anna, Klis Frans M., Bussemaker Harmen J.
Primary Institution: Swammerdam Institute for Life Sciences, University of Amsterdam
Hypothesis
Can prior information about regulatory network connectivity be used to infer condition-specific transcription factor activity from genomewide mRNA expression patterns?
Conclusion
Regulon-based monitoring of transcription factor activity modulation is a powerful tool for analyzing regulatory network function.
Supporting Evidence
- The study created a database of inferred transcription factor activities across various experimental conditions.
- Experimental validation showed that the method accurately predicts transcription factor activity modulation.
- Results indicated that mRNA expression levels are not always reliable indicators of transcription factor activity.
Takeaway
The study shows how scientists can figure out how certain proteins that control gene activity change their behavior in different situations by looking at gene expression data.
Methodology
The study used T-profiler to analyze differential expression of gene sets (regulons) to infer transcription factor activity.
Limitations
The results are limited to the yeast Saccharomyces cerevisiae and may not be directly applicable to other organisms without further validation.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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