Single-cell roadmap of human gonadal development

Abstract

Gonadal development is a complex process that involves sex determination followed by divergent maturation into either testes or ovaries1. Historically, limited tissue accessibility, a lack of reliable in vitro models and critical differences between humans and mice have hampered our knowledge of human gonadogenesis, despite its importance in gonadal conditions and infertility. Here, we generated a comprehensive map of first- and second-trimester human gonads using a combination of single-cell and spatial transcriptomics, chromatin accessibility assays and fluorescent microscopy. We extracted human-specific regulatory programmes that control the development of germline and somatic cell lineages by profiling equivalent developmental stages in mice. In both species, we define the somatic cell states present at the time of sex specification, including the bipotent early supporting population that, in males, upregulates the testis-determining factor SRY and sPAX8s, a gonadal lineage located at the gonadal–mesonephric interface. In females, we resolve the cellular and molecular events that give rise to the first and second waves of granulosa cells that compartmentalize the developing ovary to modulate germ cell differentiation. In males, we identify human SIGLEC15+ and TREM2+ fetal testicular macrophages, which signal to somatic cells outside and inside the developing testis cords, respectively. This study provides a comprehensive spatiotemporal map of human and mouse gonadal differentiation, which can guide in vitro gonadogenesis.

Germline stem cells in human

“…Nevertheless, it is perhaps different from the origin of hPGCs, that PGCs in cynomolgus monkey might emerge in amnion. 87,95 In general, hPGCs/hPGCLCs express a range of types of key genes, including (1) pluripotency markers: NANOG, POU5F1, ALPL, KLF4, LIN28, KIT, NANOS3, SSEA-1, SSEA-4, DPPA3 (also called as STELLA), and ZFP42 (also known as REX1), 17,20,21,[161][162][163][164][165][166][167] (2) cell-surface makers: CD38, EPCAM, ITGA6 (INTEGRIN alpha 6), ITGB3, FGFR3, KIT, and ALPL, 20,21,167,168 (3) germline markers: SOX17, BLIMP1 (also known as PRDM1), TFAP2C, PRDM14, DDX4 (also known as VASA), DAZL, and TCL1A, 20,21,167,[169][170][171][172] (4) amnion-related genes: CDX2 and GATA3, 24 (5) mesoderm markers: EOMES, NODAL, SP5, and T, 20,21 (6) transcription factors: SOX17, BLIMP1, SOX15, GATA4, PRDM14, SALL4, and UTF1, 20,21,[172][173][174][175] and ( 7) epigenetic regulation factors: DNA demethylation dioxygenases (TET1, TET2, and TET3), protein arginine methyltransferase 5(PRMT5), and DND microRNAmediated repression inhibitor 1(DND1). 20,167,176,177 The types and expression patterns of these marker genes reflect corresponding states of hPGC development and cell identity.…”

MEBOCOST: Metabolite-mediated Cell Communication Modeling by Single Cell Transcriptome

“…Two recently released algorithms, including the CellPhoneDBv4 54 and scConnect 55 , could perform analysis of cell-cell communications mediated by some small molecules. Likely because these two algorithms were designed mainly for analysis of protein ligand-receptor analysis, only 199 small molecule-receptor partners and 8 neurotransmitter-receptor partners were included respectively.…”

“…Finally, MEBOCOST infers potential metabolite-sensor communications using single cell transcriptomics data without considering the spatial proximity of the cells. Recently, spatial transcriptomics has been successfully utilized to improve the prediction of protein-based cell-cell interaction by many other computational tools 5, 7, 8, 54 , demonstrating the informative role of spatial information in the cell-cell communication prediction. Although a robust performance has been observed in the current MEBOCOST, we believe that it will have the potential to provide a more comprehensive view of metabolite-sensor communications by combining spatial distribution of the cells into consideration.…”

Becoming female: Ovarian differentiation from an evolutionary perspective

“…In addition, the use of related techniques such as spatial transcriptomics and single-cell ATAC-seq will allow the building of a comprehensive developmental cell atlas of gonad differentiation and further improve the comparative analyses of granulosa cell origins and differentiation kinetics within vertebrate clades. For instance, the Human Gonad Development Atlas, a part of the Human Developmental Cell Atlas (HDCA), is aimed to create a comprehensive map of cells during human fetal development using 2D/3D imaging as well as single cell multiomics ( Haniffa et al, 2021 ; Garcia-Alonso et al, 2022 ). Beyond gene expression, identifying non-coding regulatory elements, enhancers with potential granulosa cell signatures and cell-specific chromatin dynamics associated with different stages of ovarian differentiation will further improve our knowledge of ovarian differentiation and maintenance of its identity.…”