Ovarian follicular growth and development are regulated by extraovarian and intraovarian factors, which influence granulosa cell proliferation and differentiation. However, the molecular mechanisms that drive follicular growth are not completely understood. Ovarian follicular cysts are one of the most common causes of reproductive failure in dairy cattle. Nevertheless, the primary cause of cyst formation has not been clearly established. A gene expression comparison may aid in elucidating the causes of ovarian cyst disease. Our objective was to identify differentially expressed genes in ovarian granulosa cells between normal dominant and cystic follicles of cattle. Granulosa cells and follicular fluid were isolated from dominant and cystic follicles collected via either ultrasound-guided aspiration from dairy cows (n = 24) or slaughterhouse ovaries from beef cows (n = 23). Hormonal analysis for progesterone, estradiol, and androstenedione in follicular fluid was performed by RIA. Total RNA was extracted and hybridized to 6 Affymetrix GeneChip Bovine Genome Arrays (Affymetrix, Santa Clara, CA). Abundance of mRNA for differentially expressed selected genes was determined through quantitative real-time reverse-transcription PCR. Follicular cysts showed greater (P < 0.05) progesterone, lesser (P < 0.05) estradiol, and no differences (P > 0.10) in androstenedione concentrations compared with noncystic follicles. A total of 163 gene sequences were differentially expressed (P < 0.01), with 19 upregulated and 144 downregulated. From selected target genes, quantitative real-time reverse-transcription PCR confirmed angiogenin, PGE(2) receptor 4, and G-protein coupled receptor 34 genes as upregulated in cystic follicles, and Indian hedgehog protein precursor and secreted frizzled-related protein 4 genes as downregulated in cystic follicles. Further research is required to elucidate the role of these factors in follicular development and cyst formation.
Insulin-like growth factor-I in conjunction with gonadotropins are important stimulators of mitosis and ovarian steroid production by granulosa and thecal cells, which are required for normal oocyte development and hormonal feedback signaling to the hypothalamus and pituitary. However, a comprehensive evaluation of the changes in gene expression induced by IGF-I has not been conducted. Our objective was to characterize granulosa cell gene expression in response to IGF-I treatment. Porcine granulosa cells were pooled in 4 biological replicates and treated with FSH (baseline) or FSH+IGF-I for 24 h in vitro. The RNA was collected and hybridized to 8 Affymetrix Porcine GeneChips (Affymetrix, Santa Clara, CA) in a paired design. Differentially regulated gene sequence element sets (P < 0.01) were used as queries in the UniGene database searching for annotated genes. Abundance of messenger RNA (mRNA) for genes differentially expressed in the microarray analysis was determined through multiplex assays of one-step real-time reverse transcription-PCR and further analyzed under a statistical model including the fixed effect of treatment. A total of 388 gene sequence element sets were differentially expressed, and 42 matched annotated genes in the UniGene database. Of the 3 upregulated target genes selected for further quantitative reverse transcription-PCR analysis, only FGF receptor 2 III c (FGFR2IIIc) mRNA abundance was significantly increased by IGF-I. Of the 3 downregulated target genes selected for further analysis, only thrombospondin-1 (THBS1) mRNA abundance was significantly decreased by IGF-I. Further study revealed that neither FSH nor estradiol affected the IGF-I-induced suppression of THBS1 mRNA abundance. These results provide the first comprehensive assessment of IGF-I-induced gene expression in granulosa cells and will contribute to a better understanding of the molecular mechanisms of IGF-I regulation of follicular development. Involvement of FGFR2IIIc and THBS1 in mediating IGF-I-induced granulosa cell steroidogenesis and proliferation during follicular development is novel, but their specific roles will require further elucidation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.