Arabidopsis Co-expression Tool (ACT)

Arabidopsis Co-expression Tool (ACT) performs gene coexpression analysis in Arabidopsis thaliana using 3,500 Affymetrix ATH1 Genome Array microarray samples across approximately 21,273 genes to identify functionally related genes and biological pathways.

Key Features:

• WGCNA network construction: Uses Weighted Gene Correlation Network Analysis (WGCNA) to construct a weighted gene coexpression network and organize genes into modules.
• Coexpression Ranking: Ranks genes by similarity of expression patterns to a query gene across the 3,500 Affymetrix ATH1 microarray samples.
• Clique Finder (CF): Identifies groups of consistently co-expressed genes (cliques) with adjustable parameters for cluster size and inclusion criteria.
• Scatter Plot Analysis: Visualizes correlation coefficients between genes to aid identification and refinement of coexpressed gene clusters.
• Gene Set Enrichment Analysis: Performs enrichment analysis to reveal transcription factors targeting coexpressed genes and infer pathway memberships.
• Statistical significance measures: Integrates probability and expectation values to assess significance of coexpression relationships.
• Dataset coverage: Leverages high-quality transcriptomic data from ~3,500 Affymetrix ATH1 Genome Array microarray samples covering ~21,273 Arabidopsis genes.
• Tissue/condition module identification: Organizes modules that correlate with specific tissues or conditions to facilitate discovery of functional modules and metabolic pathways.

Scientific Applications:

• Functional module discovery: Identify gene modules that suggest shared biological roles or pathway membership.
• Metabolic pathway inference: Reveal candidate genes and gene groups involved in metabolic pathways.
• Transcription factor targeting: Detect transcription factors likely to target coexpressed gene sets via enrichment analysis.
• Hypothesis generation for gene function: Generate testable hypotheses about gene roles, including investigations such as cell wall biosynthesis.
• Regulatory network exploration: Explore co-regulated gene cliques and modules underlying plant development and responses to environmental stimuli.

Methodology:

Uses Affymetrix ATH1 microarray expression data (≈3,500 samples, ≈21,273 genes); constructs weighted coexpression networks with WGCNA; ranks genes by expression correlation; identifies cliques with a Clique Finder algorithm; visualizes correlations with scatter plots; conducts gene set enrichment analysis to identify transcription factor targets; assesses significance using probability and expectation values.