A time-resolved transcriptome landscape of the developing mouse ovary

Abstract

The ovarian structure is complex and diverse, including egg cells, granulosa cells and other cell types. Its organ function depends heavily on normal development. Numerous studies have focused on certain gene function changes during ovarian development, but systematic analyses of its molecular changes are extremely rare. Here, we present a comprehensive transcriptional profile of the mouse ovary from 11 time points across multiple developmental stages, which enables us to explore the dynamics of ovarian development. By performing coexpression analysis, we identified gene modules with similar expression trends and determined 159 functional gene interaction networks based on machine learning. Most of these gene interaction networks are related to biological processes involved in the development of the ovary, which provides functional predictions for some genes with unknown functions and a reference for subsequent functional research. In general, our study provides a resource for understanding ovarian development.