Abstract
Ovarian follicle is the basic functional unit of female reproduction, and is composed of oocyte and surrounding granulosa cells. In mammals, folliculogenesis strictly rely on gonadotropin regulations to determine the ovulation and the quality of eggs. However, the dynamic changes of protein-expressing profiles in follicles at different developmental stages remain largely unknown. By performing mass-spectrometry-based quantitative proteomic analysis of mouse follicles, we provide a proteomic database (~3000 proteins) that covers three key stages of gonadotropin-dependent folliculogenesis. By combining bioinformatics analysis with in situ expression validation, we showed that our proteomic data well reflected physiological changes during folliculogenesis, which provided potential to predict unknown regulators of folliculogenesis. Additionally, by using the oocyte structural protein zona pellucida protein 2 as the internal control, we showed the possibility of our database to predict the expression dynamics of oocyte-expressing proteins during folliculogenesis. Taken together, we provide a high-coverage proteomic database to study protein-expression dynamics during gonadotropin-dependent folliculogenesis in mammals.
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