Application of Emerging Transcriptomics Technologies and Methods to Gain Insight into the Human Reproductive System

Abstract

Advances in the treatment of cancer have led to increases in survival rates, especially among children and young adults. Chemotherapy, a common cancer treatment, is particularly toxic to the reproductive organs, resulting in infertility for many patients. Methods for preserving fertility, such as mature oocyte retrieval and cryopreservation, are not feasible for young cancer patients due to their inability to mature oocytes. Alternative methods center around ovarian tissue cryopreservation, followed by either orthotopic transplantation or in vitro maturation. These methods are hindered by an incomplete understanding of the biological processes underlying folliculogenesis and how freezing ovarian tissue may affect these processes. We address these issues by generating transcriptomic atlases of the ovary and oocytes and studying the regulatory cues that lead to improved maturation in vitro. We developed a single-cell and spatial transcriptomic atlas highlighting the heterogeneity of the human ovary using samples from donors without a history of cancer, previous androgen therapy, or known diseases that affect ovarian function. We identified three robust marker gene sets for understudied cell types: granulosa, theca, and oocytes. Transcriptional gradients across the medulla, cortex, and cumulus granulosa provided additional insight into the heterogeneity and function of the ovary. We further analyzed the profiles of the spatially captured oocytes, along with additional single oocyte data. This analysis allowed us to identify differences between early-stage follicles (primordial to transitioning primordial), which had previously been unexplored in the literature. With the single oocyte data, we also investigated the effects of cryopreservation on the transcriptomic profiles. We concluded there were no major transcriptomic changes brought upon by the freeze/thaw process in oocytes. Finally, we studied the regulatory cues within a time series mouse model of in vitro maturation of follicles across two different conditions. We generated a detailed transcriptomic profile of supporting somatic cells, oocytes, and their interactions, validating some of our findings with proteomic data. This analysis also led to the detection of differentially expressed genes and pathways through differences and phase shifts in expression between conditions. Furthermore, we were able to validate our in vitro data by comparing it to in vivo single-cell data. Overall, this work increased our understanding of the basic biology underlying folliculogenesis on multiple fronts and provides a platform on which future studies can be conducted.