Ovulation is the process by which an ovulatory follicle releases a mature egg and is essential for fertility and maintaining female reproductive cycle. Understanding the mechanisms of ovulation have implications for the development of non-hormonal contraceptives and treatments of anovulatory diseases. We developed a 3D alginate encapsulated in vitro follicle growth (eIVFG) system that recapitulates key events of folliculogenesis. Mature follicles grown from the eIVFG system can undergo ovulation in response to hormonal cues in an autonomous manner, providing a unique and controlled model system to study ovulation. Herein, we further determined whether this ex vivo ovulation model preserves molecular signatures of ovulation and evaluated the use of this model as a tool for discovering novel ovulatory signaling and non-hormonal contraceptives. Mature mouse follicles derived from eIVFG were induced to ovulate using human chorionic gonadotropin (hCG) and collected at 0-, 1-, 4-, and 8-hours post-induction. Phenotypic analyses confirmed that ex vivo ovulation encompassed cumulus cell expansion, oocyte maturation, follicle rupture, and luteinization. Single-follicle RNA-sequencing (RNA-seq) revealed dynamic genome-wide temporal transcriptome profiles and also the preservation of the temporal expression of many established ovulatory genes. Soft clustering of single-follicle RNA-seq data identified distinct gene expression patterns and novel pathways that may critically contribute to ovulation. We further demonstrated that eIVFG is a robust model for ovulation screening and identification of molecular targets for developing non-hormonal contraceptives, such as pathways associated with proprotein convertase and adrenergic receptor. Taken together, our studies demonstrate that follicles grown from the eIVFG system preserve molecular signatures of mammalian ovulation, presenting a new powerful tool for studying ovulation biology and anovulatory diseases, as well as for performing a high-throughput ovulation screening for discovering novel non-hormonal contraceptives.

Creator

• Zhang, Jiyang

DOI

• https://doi.org/10.21985/n2-rkz5-7c56

Subject

• Biology

Language

• en

Alternate Identifier

• http://dissertations.umi.com/northwestern:15863
• etdadmin_upload_863229

Keyword

• soft clustering analysis
• single-follicle RNA-seq
• follicle culture
• ovulation
• non-hormonal contraceptives

Date created

• 2021-01-01

Resource type

• Dissertation

Rights statement

• In Copyright