Supplementary Materials for the Article:

Weighted Gene Coexpression Network Analysis

Identifies Biomarkers in Glycerol Kinase Deficient Mice

 

Nicole K. MacLennan1, Jun Dong2,3, Jason E. Aten2,4, Steve Horvath2,3, Lola Rahib5, Loren Ornelas1, Katrina M. Dipple1,2,5, Edward R.B. McCabe1,2,5,6*.
1Departments of Pediatrics, 2Human Genetics, and 4Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA; 3Departments of Biostatistics, School of Public Health at UCLA, Los Angeles, California 90095, USA; 5Biomedical Engineering Interdepartmental Program, and 6Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, UCLA, Los Angeles, California 90095, USA.
*Corresponding Author: Edward R.B. McCabe, Department of Pediatrics, David Geffen School of Medicine at UCLA, 10833 Le Conte Ave, 22-412 MDCC, Los Angeles CA 90095-1752. Phone: (310) 825-5095; Fax: (310) 206-4584; Email: emccabe@mednet.ucla.edu

Citation

TBD

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Presentation

Link to talks:    PowerPoint Version    PDF version

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Abstract

Symptomatic glycerol kinase deficiency (GKD) is associated with episodic metabolic and central nervous system deterioration.  We report here the first application of Weighted Gene Co-Expression Network Analysis (WGCNA) to investigate a knockout (KO) murine model of a human genetic disease.  WGCNA identified networks and key hub transcripts from liver mRNA of glycerol kinase (Gyk) KO and wild type (WT) mice. Day of life 1 (dol1) samples from KO mice contained a network module enriched for organic acid metabolism before Gyk KO mice develop organic acidemia and die on dol3-4 and the module containing Gyk was enriched with apoptotic genes.  Roles for the highly connected Acot, Psat and Plk3 transcripts were confirmed in cell cultures and subsequently validated by causality testing.  We provide evidence that GK may have an apoptotic moonlighting role that is lost in GKD. This systems biology strategy has improved our understanding of GKD pathogenesis and suggests possible treatments.

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Additional Files

  1. Functional Enrichment Analysis (Gene Ontology) of the Mouse Gene Co-expression Modules (Download)

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R Tutorials

For this  application, please save all files to the same folder.

R Tutorials:

  1. Network Generation: Microsoft word version (recommended)    PDF version

  2. Network Overlap:       Microsoft word version (recommended)    PDF version

  3. Network Breakdown: Microsoft word version (recommended)    PDF version

Data Files:

Mouse Microarray Data

Custom made network R functions

file 1

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Acknowledgement

We would like to acknowledge the help from everyone ... ...

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Other Materials Regarding Weighted Gene Co-expression Network Analysis

Weighted Gene Co-Expression Network Page

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2008-10-04

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