Expresso

Expresso aggregates and analyzes Arabidopsis ChIP-Seq peak datasets using motif analysis to identify transcription factor target genes and relate binding events to gene expression.

Key Features:

• Integration of ChIP-Seq Data: Aggregates publicly available Arabidopsis ChIP-Seq peak data and links these datasets with user-provided gene expression profiles.
• Target Gene Identification: Performs motif analysis on GEO ChIP-Seq datasets to identify known target genes of specific transcription factors.
• Regulatory Factor Analysis: Determines which transcription factors regulate a gene of interest by querying curated ChIP-Seq peak datasets.
• Correlation Computation: Computes correlations between transcription factor gene expression levels and expression of their target genes.

Scientific Applications:

• Gene Regulation Studies: Identify transcription factor binding sites and associate them with gene expression to study mechanisms of gene regulation in Arabidopsis.
• Transcription Factor Network Analysis: Map networks of transcription factors and their target genes to investigate regulatory interactions relevant to development and stress responses.
• Comparative Genomics: Integrate multiple ChIP-Seq and expression datasets to compare regulatory patterns across conditions or species.

Methodology:

Uses motif analysis of ChIP-Seq peak data (including GEO datasets), curates and links these peaks with gene expression profiles, stores data in a relational database for querying, and computes correlations between transcription factor and target gene expression.