Functional Profiling of Human MeCP2 by Automated Data Comparison Analysis and Computerized Expression Pathway Modeling

Abstract

ObjectivesMethyl-CpG binding protein 2 (MeCP2) is a ubiquitous epigenetic factor that represses gene expression by modifying chromatin. Mutations in the MeCP2 gene cause Rett syndrome, a progressive neurodevelopmental disorder. Recent studies also have shown that MeCP2 plays a role in carcinogenesis. Specifically, functional ablation of MeCP2 suppresses cell growth and leads to the proliferation of cancer cells. However, MeCP2's function in adult tissues remains poorly understood. We utilized a weight matrix-based comparison software to identify transcription factor binding site (TFBS) of MeCP2-regulated genes, which were recognized by cDNA microarray analysis.MethodsMeCP2 expression was silenced using annealed siRNA in HEK293 cells, and then a cDNA microarray analysis was performed. Functional analysis was carried out, and transcriptional levels in target genes regulated by MeCP2 were investigated. TFBS analysis was done within genes selected by the cDNA microarray analysis, using a weight matrix-based program and the TRANSFAC 6.0 database.ResultsAmong the differentially expressed genes with a change in expression greater than two-fold, 189 genes were up-regulated and 91 genes were down-regulated. Genes related to apoptosis and cell proliferation (JUN, FOSL2, CYR61, SKIL, ATF3, BMABI, BMPR2, RERE, and FALZ) were highly up-regulated. Genes with anti-apoptotic and anti-proliferative functions (HNRPA0, HIS1, and FOXC1) were down-regulated. Using TFBS analysis within putative promoters of novel candidate target genes of MeCP2, disease-related transcription factors were identified.ConclusionsThe present results provide insights into the new target genes regulated by MeCP2 under epigenetic control. This information will be valuable for further studies aimed at clarifying the pathogenesis of Rett syndrome and neoplastic diseases.

Keywords

• rett syndrome
• methyl-cpg-binding protein 2
• carcinogenesis
• microarray analysis
• transcription factors