Single-Cell RNA-Seq Analysis Maps Development of Human Germline Cells and Gonadal Niche Interactions

Abstract

Human fetal germ cells (FGCs) are precursors to sperm and eggs and are crucial for maintenance of the species. However, the developmental trajectories and heterogeneity of human FGCs remain largely unknown. Here we performed single-cell RNA-seq analysis of over 2,000 FGCs and their gonadal niche cells in female and male human embryos spanning several developmental stages. We found that female FGCs undergo four distinct sequential phases characterized by mitosis, retinoic acid signaling, meiotic prophase, and oogenesis. Male FGCs develop through stages of migration, mitosis, and cell-cycle arrest. Individual embryos of both sexes simultaneously contain several subpopulations, highlighting the asynchronous and heterogeneous nature of FGC development. Moreover, we observed reciprocal signaling interactions between FGCs and their gonadal niche cells, including activation of the bone morphogenic protein (BMP) and Notch signaling pathways. Our work provides key insights into the crucial features of human FGCs during their highly ordered mitotic, meiotic, and gametogenetic processes in vivo.

Mettl3-mediated m6A regulates spermatogonial differentiation and meiosis initiation

“…These included 699 down-regulated genes that were mainly enriched in genes required for spermatogenesis and regulation of meiosis ( Figure 3A and Supplementary information, Table S4). We next examined expression patterns of 50 genes specifically expressed in germ cells according to a previous study [30]. Unsupervised Table S4).…”

Bayesian inference of transcriptional branching identifies regulators of early germ cell development in humans

“…Finally, in the past, scRNA-seq datasets tended to be of low temporal resolution, albeit with observations in many cells, which reflect a continuum of developmental states Petropoulos et al 2016;Borensztein et al 2017;Huang et al 2017). However, due to decreased costs, scRNA-seq datasets are now routinely generated over finely resolved time series, including the early stages of embryogenesis Petropoulos et al 2016;Borensztein et al 2017;Huang et al 2017;Ibarra-Soria et al 2018;Han et al 2018) and during PGC development Li et al 2017). While individual populations of cells associated with the different stages still reflect a continuum of states, with some degree of overlap between stages, the existence of a well-defined capture time provides highly informative prior information about the ordering of cells, which most approaches are incapable of utilising.…”

Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

“…To explore the cell composition of each organ, we processed the single-cell data and obtained 228 cell clusters (Table S2), each of which was annotated according to wellknown marker genes from the literature (Gao et al, 2018;Li et al, 2017;MacParland et al, 2018;Pellin et al, 2019;Young et al, 2018). Then all the cells were clustered to make up the global transcriptome landscape ( Figures 1B and 2A), which consisted of 6 primary cell groups common in most organs (epithelial cells, endothelial cells, fibroblasts, glial cells, immune cells and erythrocytes) ( Figure 2B) as well as several cell clusters specific to sexual organs such as Granulosa cells in the ovary and Sertoli cells in the testis.…”