Microarray gene expression profiling and bioinformatics analysis of premature ovarian failure in a rat model

Abstract

Premature ovarian failure (POF) remains one of the major gynecological problems worldwide which affected 1% of women. Even though tremendous achievements had been acquired as opposed to years past, molecular pathogenesis associated with POF is still unclear and needs to be well-defined. The aim of this study was to analyze the gene expression profiles in the POF rat model. To predict potential regulating factors, we firstly treated female Sprague Dawley (SD) rat with 4-vinylcyclohexene diepoxide (VCD). Total RNA from ovarian tissue was converted to cDNA and hybridized to mRNA Chip array. The differentially expressed genes (DEGs) were identified by two-sample t test and assessed using hierarchical clustering and Principal Component Analysis methods. Potential regulatory targets associated with these DEGs were constructed using BisoGenet in Cytoscape. Gene Ontology (GO) and functional enrichment analysis were performed using BiNGO and DAVID, respectively. As the results, 25 DEGs were found to be closely associated with POF initiation. Hierarchical clustering and Principal Component Analysis on the transcriptional profiles revealed an excellent separation of the vehicle and POF compartments. Pathway enrichment analysis based on the disease-gene interaction network analysis led to the identification of two core signaling pathways that were strongly affected during POF initiation and progression: immune response and cardiovascular disorders. In conclusion, we constructed a gene regulatory network associated with POF using the microarray gene expression profiling, and screened out some genes or transcription factors that may be used as potential molecular therapeutic targets for POF.

Keywords: Bioinformatics analysis; Expression profiling; Premature ovarian failure.