Single-cell transcriptome landscape of ovarian cells during primordial follicle assembly in mice.
Primordial follicle assembly in the mouse occurs during perinatal ages and largely determines the ovarian reserve that will be available to support the reproductive life span. The development of primordial follicles is controlled by a complex network of interactions between oocytes and ovarian somat...
Main Authors: | , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-12-01
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Series: | PLoS Biology |
Online Access: | https://doi.org/10.1371/journal.pbio.3001025 |
Summary: | Primordial follicle assembly in the mouse occurs during perinatal ages and largely determines the ovarian reserve that will be available to support the reproductive life span. The development of primordial follicles is controlled by a complex network of interactions between oocytes and ovarian somatic cells that remain poorly understood. In the present research, using single-cell RNA sequencing performed over a time series on murine ovaries, coupled with several bioinformatics analyses, the complete dynamic genetic programs of germ and granulosa cells from E16.5 to postnatal day (PD) 3 were reported. Along with confirming the previously reported expression of genes by germ cells and granulosa cells, our analyses identified 5 distinct cell clusters associated with germ cells and 6 with granulosa cells. Consequently, several new genes expressed at significant levels at each investigated stage were assigned. By building single-cell pseudotemporal trajectories, 3 states and 1 branch point of fate transition for the germ cells were revealed, as well as for the granulosa cells. Moreover, Gene Ontology (GO) term enrichment enabled identification of the biological process most represented in germ cells and granulosa cells or common to both cell types at each specific stage, and the interactions of germ cells and granulosa cells basing on known and novel pathway were presented. Finally, by using single-cell regulatory network inference and clustering (SCENIC) algorithm, we were able to establish a network of regulons that can be postulated as likely candidates for sustaining germ cell-specific transcription programs throughout the period of investigation. Above all, this study provides the whole transcriptome landscape of ovarian cells and unearths new insights during primordial follicle assembly in mice. |
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ISSN: | 1544-9173 1545-7885 |