Effects of GDF-9 and FSH on mRNA expression for FSH-R, GDF-9 and BMPs in in vitro cultured goat preantral follicles

The aim of the present study was to determine the role of GDF-9 and/or FSH on the growth and mRNA expression for FSH-R, GDF-9, and BMPs in goat secondary follicles after culture in vitro. Goat secondary follicles (~200µm) were isolated and cultured for six days in minimum essential medium (MEM) supplemented with GDF-9 (200 ng/mL), FSH (50 ng/mL) or both. At the beginning and end of culture, the follicular diameter was evaluated and compared. The levels of mRNA for GDF-9, FSH-R and BMPs -2, -4, -6, -7 and -15 in cultured follicles were quantified by real time PCR. The results showed that a significant increase of follicle diameter after six days when compared to day 0, but the presence of GDF-9 and FSH did not influence the follicular growth in comparison with those cultured in MEM. Real time PCR showed that GDF-9 down-regulated the levels of mRNA for BMPs -2 and -15, while FSH either alone or in combination with GDF-9 did not affect the expression of GDF-9, FSH-R and BMPs. In conclusion, GDF-9 reduced the expression of BMP-2 and -15 in caprine preantral follicles after their culture, but FSH either alone or in association with GDF-9 did not control the expression of GDF-9, FSH-R and BMPs.

Real time PCR and importance of housekeepings genes for normalization and quantification of mRNA expression in different tissues

The aim of this review was to evaluate the importance of the real-time PCR (qRT-PCR) as a technique for mRNA expression analysis in different tissues. Real-time PCR is widely used for quantification of mRNA levels and is a fundamental tool for basic research, molecular medicine and biotechnology.Genes of references are expressed in a wide variety of tissues and cells with minimal variations in their expression levels, and thus are used to normalize data of mRNA quantification. Software programs, such as geNorm, BestKeeper and NormFinder, have been developed to perform the normalization of data, which help to choose the most stable reference gene. Several genes, such as GAPDH, β-actin, β-tubulin, PGK, UBQ, RPL-19 and 18S rRNA have been suggested as standards in PCR studies, but these genes can have variation in their expression in different tissues, reinforcing the idea that there is no ideal reference gene.