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Network statistics of genetically-driven gene co-expression modules in mouse crosses
Marie-Pier Scott-Boyer1, Benjamin Haibe-Kains2, Christian F Deschepper1
1Cardiovascular Biology Research Unit, Institut de Recherches Cliniques de Montréal Montreál, QC, Canada.
Frontiers in Genetics
|January 15, 2014
Summary
Genetic factors significantly organize gene co-expression modules in mouse models. These "genetically-driven" modules exhibit distinct network properties, aiding in biological interpretation and prediction.
Area of Science:
- Systems biology
- Genetics
- Bioinformatics
Background:
- Biological networks represent complex relationships between genes, proteins, and metabolites.
- Understanding the organization and biological validity of gene co-expression networks is crucial for deciphering complex traits.
Purpose of the Study:
- To investigate the biological validity and organizational principles of gene co-expression modules.
- To determine the extent to which genetic factors influence the structure of these networks.
Main Methods:
- Utilized Weighted Gene Co-expression Network Analysis (WGCNA) on seven gene expression datasets from mouse recombinant inbred strains (RIS).
- Analyzed linkage between gene co-expression modules and module quantitative trait loci (mQTLs).
Main Results:
- Established linkage to mQTLs for 29.3% of detected gene co-expression modules across mouse RIS.
- Found that for 74.6% of linked modules, the mQTL resided on the same chromosome as the majority of module genes.
- Identified "genetically-driven" modules, characterized by higher gene connectivity from the mQTL chromosome and distinct network statistics (density, centralization).
Conclusions:
- A significant portion of gene co-expression modules in mouse RIS panels are primarily organized by genetic determinants.
- These genetic underpinnings validate the biological relevance of modules and impart unique network properties, allowing for prediction based on network statistics.
