Dataset Information

The ovulatory signal precipitates LRH-1 transcriptional switching mediated by differential chromatin accessibility.

ABSTRACT: In the ovary, follicular growth and maturation are complicated processes that involve a series of morphological and physiological changes in oocytes and somatic cells leading to ovulation and luteinization, essential processes for fertility in females. Given the complexity of ovulation, characterization of genome-wide regulatory elements is essential to understand the mechanisms governing the expression of specific genes in the rapidly differentiating follicle. We therefore employed a systems biology approach to determine global transcriptional mechanisms during the early stages of the ovulatory process. We demonstrate that, following the hormonal signal that initiates ovulation, granulosa cells undergo major modification of distal regulatory elements which coincides with cistrome reprogramming of the indispensable orphan nuclear receptor, liver receptor homolog-1 (LRH-1). This cistromic reorganization correlates with the extensive changes in gene expression in ovarian granulosa cells, leading to ovulation. Together, our study yields a transcriptional map of unprecedented detail, delineating ovarian cell differentiation during the initiation of ovulation. It further demonstrates the power of complementary global approaches to accurately characterize molecular events that direct the multiple and rapid changes that characterize reproductive processes.

ORGANISM(S): Mus musculus

PROVIDER: GSE119508 | GEO | 2019/05/14

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Ovulation refers to the process when the ovarian surface-facing wall of a preovulatory follicle ruptures and releases the cumulus oocyte complex (COC) into the oviduct or fallopian tube in response to hormonal cues. In parallel, the unruptured wall of the follicle within the ovary transitions to becoming a progesterone-producing corpus luteum. Ovulation is essential for fertilization and eventual pregnancy. Disruption of ovulation, whether purposefully through contraceptive intervention or idiopathically in cases of anovulatory infertility, has translational implications for human health. Importantly, key processes of ovulation, including follicle rupture and luteinization, are recapitulated in models of ex vivo ovulation despite the absence of an intact hypothalamic-pituitary-gonadal axis and intra-ovarian cues. In our study, we used an ex vivo ovulation model to identify functional and molecular differences between distinct regions of the follicle wall, which we refer to as the ruptured and unruptured sides. We observed that the unruptured side of the follicle wall exhibits hallmarks of luteinization after ovulation while the ruptured side exhibits signs of cell death. RNA-sequencing of these specific follicle regions revealed 2,099 differentially expressed genes between follicle sides without hCG exposure and 1,673 between follicle sides 12 hours post-hCG, which were further validated in vivo. We found enriched pathways that recapitulate known ovulation biology, including oxidative stress on the ruptured side and angiogenesis on the unruptured side. We also identified previously unappreciated pathways that may play an important role in ovulation, such as amino acid transport and Jag-Notch signaling on the ruptured side, as well as metal ion processing and IL-11 signaling on the unruptured side. Ultimately our studies demonstrate that our ex vivo model recapitulates known in vivo ovarian biology, identifies pathways that may be novel regulators of ovulation and luteinization, and may have future translational applications for the study of ovulatory disorders and the development of novel non-hormonal contraceptives.

Dataset Information

The ovulatory signal precipitates LRH-1 transcriptional switching mediated by differential chromatin accessibility.

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets