"Upstream Analysis": An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data

Area of Science:

• Bioinformatics
• Systems Biology
• Genomics

Background:

• Co-expressed genes often share common regulatory influences, complicating causal analysis.
• Identifying upstream regulators of gene expression is crucial for understanding biological processes.
• Existing methods may not fully capture complex regulatory networks.

Purpose of the Study:

• To develop and validate a computational strategy for causal analysis of co-expressed genes.
• To identify hypothetical master regulators by integrating promoter analysis with upstream pathway knowledge.
• To apply this strategy to gene expression data from naphthalene-induced murine liver and lung tissues.

Main Methods:

• A workflow combining state-of-the-art promoter analysis for transcription factor (TF) binding sites.
• Knowledge-based analysis of upstream pathways controlling TF activity.
• Application of a novel triclustering algorithm to gene expression signatures.
• Implementation within a comprehensive bioinformatic software platform.

Main Results:

• Identification of hypothetical master regulators controlling co-expressed genes.
• Successful application to gene sets from naphthalene-induced murine liver and lung tissues.
• Discovery of tissue-specific master regulators associated with tumorigenic and apoptotic processes.

Conclusions:

• The presented strategy enables causal analysis of co-expressed genes by identifying master regulators.
• This is the first reported use of gene expression triclusters to identify upstream regulators.
• The workflow provides a powerful tool for dissecting regulatory networks in various biological contexts.