Integration of MicroRNA and mRNA by Weighted Gene Co-Expression Network Analysis

• Activity Number: 253
• Type: Contributed
• Date/Time: Monday, July 30, 2012 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Eileen Liao*+ and David Elashoff and Steve Horvath
• Companies: and University of California at Los Angeles and University of California at Los Angeles
• Keywords: Integration ; WGCNA ; enrichment analysis

Abstract

miRNA regulates mRNA levels through base-pairing, by inducing transcript degradation or by inhibiting translation. We developed a method using network analysis methods to identify mRNA targets of miRNA, in a renal carcinoma dataset from patients with matched tumor/normal samples. We focus on the step-by-step network construction and module detection of mRNAs by signed weighted gene co-expression network analysis (WGCNA), followed by identifying the strong anti-correlation between miRNA and module eigengenes. We next evaluate whether the predicted mRNA targets are differentially present between a given module and other modules by using the fisher's exact test. WGCNA is also used to find disease-related networks (modules) and disease related hub genes. We found that six expression modules are associated with disease status and miRNAs. Within these modules, enrichment analyses are implemented and compared by both DAVID and R functions from WGCNA, and LASSO regression is used to explore the relationship between eigengenes and miRNAs. We found that two miRNAs are significantly anti-related with modules and they are integrated to their mRNA targets.