Selection of reliable reference genes in eutopic and ectopic endometrium for quantitative expression studies.

PURPOSE: Physiological changes during menstrual cycle cause the endometrium and endometriosis to develop specific kind of tissues, especially in regard to the gene expression profiles, which may include also housekeeping genes, commonly used as reference genes (RGs) in quantitative studies. Reverse transcription, followed by quantitative polymerase chain reaction (RT-qPCR) is the most precise and commonly used method in gene expression studies. In order to reduce effects of technical approaches and biological variability of gene's expression level, the studies often employ RGs in experimental data normalization. However, the expression of RGs is not always stable and depends on several variables. Thus, the selection of appropriate RG is one of the most significant steps to obtain reliable results in RT-qPCR-based methods. MATERIAL AND METHODS: With the usage of RT-qPCR, we researched the expression of seven genes (ACTB, B2M, G6PD, GAPD, GUSB, HPRT and PPIA) as reliable reference genes in eutopic and ectopic endometrial tissue specimens obtained during standard surgery of women of reproductive age. Stability of expression level was analyzed by the most universal MS Excel plug-ins including: geNorm, NormFinder and BestKeeper. The descriptive statistics were evaluated using Statistica software. RESULTS: The distribution of threshold (Ct) values was not equal. We identified genes with higher expression level (referring to Ct values) such as ACTB and B2M, medium e.g., GAPD and low expression level, e.g., G6PD and HPRT. We demonstrated that the stability of the analyzed reference genes was not homogenous, and different algorithms pointed to PPIA, GAPD and B2M as the most stable ones in eutopic and ectopic endometrium. On the contrary to these, GUSB and G6PD were the most unstable ones. CONCLUSIONS: In RT-qPCR-based analyses of gene expression level in eutopic and ectopic endometrium, we strongly recommend that a minimum of two reference genes are to be used and we determined that the most suitable seem to be PPIA and GAPD.