Two waves of transcriptomic changes in periovulatory human granulosa cells. Issue 5 (7th May 2020)

• Record Type: Journal Article
• Authors: Poulsen, L C; Bøtkjær, J A; Østrup, O; Petersen, K B; Andersen, C Yding; Grøndahl, M L; Englund, A L M
• Is Part Of: Human reproduction. Volume 35:Issue 5(2020)
• Page Start: 1230
• Page End: 1245
• Publication Date: 2020-05-07
• Subjects: ovulation -- LH -- human -- granulosa cells -- transcriptomics -- oocyte maturation -- follicle rupture; Human reproduction -- Periodicals; 618
• DOI: 10.1093/humrep/deaa043
• Languages: English
• ISSNs: 0268-1161

Abstract

Abstract: STUDY QUESTION: How does the human granulosa cell (GC) transcriptome change during ovulation? SUMMARY ANSWER: Two transcriptional peaks were observed at 12 h and at 36 h after induction of ovulation, both dominated by genes and pathways known from the inflammatory system. WHAT IS KNOWN ALREADY: The crosstalk between GCs and the oocyte, which is essential for ovulation and oocyte maturation, can be assessed through transcriptomic profiling of GCs. Detailed transcriptional changes during ovulation have not previously been assessed in humans. STUDY DESIGN, SIZE, DURATION: This prospective cohort study comprised 50 women undergoing fertility treatment in a standard antagonist protocol at a university hospital-affiliated fertility clinic in 2016–2018. PARTICIPANTS/MATERIALS, SETTING, METHODS: From each woman, one sample of GCs was collected by transvaginal ultrasound-guided follicle aspiration either before or 12 h, 17 h or 32 h after ovulation induction (OI). A second sample was collected at oocyte retrieval, 36 h after OI. Total RNA was isolated from GCs and analyzed by microarray. Gene expression differences between the five time points were assessed by ANOVA with a random factor accounting for the pairing of samples, and seven clusters of protein-coding genes representing distinct expression profiles were identified. These were used as input for subsequent bioinformatic analyses to identify enriched pathways and suggest upstream regulators. Subsets of genes were assessed to explore specific ovulatory functions. MAIN RESULTS AND THE ROLE OF CHANCE: We identified 13 345 differentially expressed transcripts across the five time points (false discovery rate, <0.01) of which 58% were protein-coding genes. Two clusters of mainly downregulated genes represented cell cycle pathways and DNA repair. Upregulated genes showed one peak at 12 h that resembled the initiation of an inflammatory response, and one peak at 36 h that resembled the effector functions of inflammation such as vasodilation, angiogenesis, coagulation, chemotaxis and tissue remodelling. Genes involved in cell–matrix interactions as a part of cytoskeletal rearrangement and cell motility were also upregulated at 36 h. Predicted activated upstream regulators of ovulation included FSH, LH, transforming growth factor B1, tumour necrosis factor, nuclear factor kappa-light-chain-enhancer of activated B cells, coagulation factor 2, fibroblast growth factor 2, interleukin 1 and cortisol, among others. The results confirmed early regulation of several previously described factors in a cascade inducing meiotic resumption and suggested new factors involved in cumulus expansion and follicle rupture through co-regulation with previously described factors. LARGE SCALE DATA: The microarray data were deposited to the Gene Expression Omnibus (www.ncbi.nlm.nih.gov/gds/, accession number: GSE133868). LIMITATIONS, REASONS FOR CAUTION: The study included women undergoing ovarian stimulation and the findings may therefore differ from a natural cycle. However, the results confirm significant regulation of many well-established ovulatory genes from a series of previous studies such as amphiregulin, epiregulin, tumour necrosis factor alfa induced protein 6, tissue inhibitor of metallopeptidases 1 and plasminogen activator inhibitor 1, which support the relevance of the results. WIDER IMPLICATIONS OF THE FINDINGS: The study increases our understanding of human ovarian function during ovulation, and the publicly available dataset is a valuable resource for future investigations. Suggested upstream regulators and highly differentially expressed genes may be potential pharmaceutical targets in fertility treatment and gynaecology. STUDY FUNDING/COMPETING INTEREST(S): The study was funded by EU Interreg ÔKS V through ReproUnion (www.reprounion.eu ) and by a grant from the Region Zealand Research Foundation. None of the authors have any conflicts of interest to declare.