Single-cell RNA-Seq reveals a highly coordinated transcriptional program in mouse germ cells during primordial follicle formation

Aging Cell. 2021 Jul;20(7):e13424. doi: 10.1111/acel.13424. Epub 2021 Jun 26.

Abstract

The assembly of primordial follicles in mammals represents one of the most critical processes in ovarian biology. It directly affects the number of oocytes available to a female throughout her reproductive life. Premature depletion of primordial follicles contributes to the ovarian pathology primary ovarian insufficiency (POI). To delineate the developmental trajectory and regulatory mechanisms of oocytes during the process, we performed RNA-seq on single germ cells from newborn (P0.5) ovaries. Three cell clusters were classified which corresponded to three cell states (germ cell cyst, cyst breakdown, and follicle) in the newborn ovary. By Monocle analysis, a uniform trajectory of oocyte development was built with a series of genes showed dynamic changes along the pseudo-timeline. Gene Ontology term enrichment revealed a significant decrease in meiosis-related genes and a dramatic increase in oocyte-specific genes which marked the transition from a germ cell to a functional oocyte. We then established a network of regulons by using single-cell regulatory network inference and clustering (SCENIC) algorithm and identified possible candidate transcription factors that may maintain transcription programs during follicle formation. Following functional studies further revealed the differential regulation of the identified regulon Id2 and its family member Id1, on the establishment of primordial follicle pool by using siRNA knockdown and genetic modified mouse models. In summary, our study systematically reconstructed molecular cascades in oocytes and identified a series of genes and molecular pathways in follicle formation and development.

Keywords: cyst breakdown; oocyte; ovary; primordial follicle; single-cell RNA-seq.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Germ Cell Ribonucleoprotein Granules / genetics*
  • Germ Cells / metabolism
  • Mice
  • Oocytes / metabolism*
  • RNA-Seq / methods*
  • Single-Cell Analysis / methods*