Single-cell RNA sequencing analysis of mouse follicular somatic cells

Abstract

Abstract Within the development of ovarian follicle, in addition to cell proliferation and differentiation, sophisticated cell–cell cross talks are established among follicular somatic cells such as granulosa cells (GCs) and theca cells. To systematically reveal the cell differentiation and signal transductions in follicular somatic cells, we collected the mouse follicular somatic cells from secondary to ovulatory stage, and analyzed the single cell transcriptomes. Having data filtered and screened, we found 6883 high variable genes in 4888 single cells. Then follicular somatic cells were clustered into 26 cell clusters, including 18 GC clusters, 4 theca endocrine cell (TEC) clusters, and 4 other somatic cell clusters, which include immune cells and Acta2 positive theca externa cells. From our data, we found there was metabolic reprogramming happened during GC differentiation. We also found both Cyp19a1 and Cyp11a1 could be expressed in TECs. We analyzed the expression patterns of genes associated with cell–cell interactions such as steroid hormone receptor genes, insulin signaling genes, and cytokine/transformation growth factor beta associated genes in all cell clusters. Lastly, we clustered the highly variable genes into 300 gene clusters, which could be used to search new genes involved in follicle development. These transcriptomes of follicular somatic cells provide us potential clues to reveal how mammals regulating follicle development and could help us find targets to improve oocyte quality for women with low fertility.