Large-scale analysis of zebrafish (Danio rerio) transcriptomes identifies functional modules associated with...

Area of Science:

• Biomedical research
• Genomics
• Bioinformatics

Background:

• Zebrafish (Danio rerio) is a valuable model organism in biomedical research due to its genetic tractability and optical transparency.
• Numerous microarray-based transcriptomic datasets exist for zebrafish across diverse conditions, but accessible exploration tools are lacking.

Purpose of the Study:

• To develop a user-friendly web tool for exploring zebrafish transcriptomic data.
• To identify and analyze co-expressed gene modules associated with specific phenotypes and experimental conditions.

Main Methods:

• Downloaded 1434 microarray datasets from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO).
• Constructed weighted gene co-expression networks to identify 50 gene modules.
• Screened hub genes using intra-modular connectivity and analyzed higher-order module networks.

Main Results:

• Identified 50 co-expression modules linked to cell types, tissues, developmental stages, and toxicological exposures.
• Associated modules with specific experiments and traits, suggesting their potential as phenotypic signatures.
• Discovered dense connections between nucleus and cell cycle modules, indicating functional relationships.

Conclusions:

• The developed web tool offers a novel resource for zebrafish gene function studies.
• Module-based analysis facilitates the discovery of novel gene functions and biological insights.
• The tool supports the exploration of complex gene expression patterns in zebrafish research.