Abstract
Human ovarian cells are phenotypically very different and are often only available in limited amounts. Despite the fact that reference gene (RG) expression stability has been validated in oocytes and other ovarian cells from several animal species, the suitability of a single universal RG in the different human ovarian cells and tissues has not been determined. The present study aimed to validate the expression stability of five of the most used RGs in human oocytes, cumulus cells, preantral follicles, ovarian medulla, and ovarian cortex tissue. The selected genes were glyceraldehyde 3-phosphate dehydrogenase (GAPDH), beta-2-microglobulin (B2M), large ribosomal protein P0 (RPLP0), beta-actin (ACTB), and peptidylprolyl isomerase A (PPIA). Overall, the stability of all RGs differed among ovarian cell types and tissues. NormFinder identified ACTB as the best RG for oocytes and cumulus cells, and B2M for medulla tissue and isolated follicles. The combination of two RGs only marginally increased the stability, indicating that using a single validated RG would be sufficient when the available testing material is limited. For the ovarian cortex, depending on culture conditions, GAPDH or ACTB were found to be the most stable genes. Our results highlight the importance of assessing RGs for each cell type or tissue when performing RT-qPCR analysis.
Highlights
Human ovarian function is still not completely understood, especially the hormonal mechanisms underlying follicle and oocyte growth and maturation
Comparisons of the cycle threshold (Ct) values demonstrated a wide variation among the reference gene (RG) within the same group of samples, especially for oocytes and preantral follicles with normalized RNA (Table 1)
ACTB and RPLP0 showed the highest levels of expression and peptidylprolyl isomerase A (PPIA) the lowest levels of expression in all types of samples, except for cortex tissue, where PPIA had the highest level of expression and B2M the lowest (Table 1)
Summary
Human ovarian function is still not completely understood, especially the hormonal mechanisms underlying follicle and oocyte growth and maturation. The technique of quantitative real-time polymerase chain reaction (RT-qPCR) is considered the benchmark for gene expression analysis and has become the mainstream method to monitor potential improvements during many experimental conditions [4,5,6,7]. This method is based on the expression of target genes in relation to endogenous reference genes (RGs), called housekeeping genes, which are considered to have constant expression. RGs should be universally expressed with a constant level in any cell type and biological or experimental condition [10]. Selecting the appropriate RGs is crucial in any experimental design to interpret data generated by RT-qPCR with the best accuracy [16]
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