Gene Coexpression Network and Module Analysis across 52 Human Tissues.

Area of Science:

• Systems Biology
• Genomics
• Bioinformatics

Background:

• Gene coexpression network analysis is crucial for understanding gene function and disease association.
• A comprehensive, cross-tissue comparison of gene coexpression networks and modules remains underexplored.

Purpose of the Study:

• To construct and compare gene coexpression networks and modules across 52 diverse human tissues and cell lines from the GTEx dataset.
• To investigate tissue correlations based on network module similarity and identify conserved and specific functional enrichments.

Main Methods:

• Construction of gene coexpression networks for 52 GTEx tissues and cell lines.
• Identification and functional enrichment analysis of network modules.
• Correlation analysis of tissue networks and clique analysis to identify highly correlated modules.

Main Results:

• Identified tissue-common and tissue-specific functional enrichments within network modules.
• Demonstrated significant correlations among network modules across most tissues, with higher similarity observed between physically proximate tissues.
• Detected prevalent immune-associated modules in various tissues, though absent in some like the brain cerebellum.
• Discovered a large clique of 40 tissues exhibiting highly correlated modules, predominantly enriched in immune-related functions.

Conclusions:

• Gene coexpression patterns exhibit substantial conservation across human tissues, particularly for immune functions.
• Network module similarity can reflect anatomical proximity, suggesting shared regulatory mechanisms.
• The findings provide a valuable resource for comparative transcriptomics and understanding tissue-specific gene regulation.