Project description:The reproductive and endocrine functions of the human ovary involve spatially defined interactions among highly specialized cell populations. Despite the importance of the ovary in female fertility and overall endocrine health, the functional attributes of ovarian cells and the complex structures in which they reside are largely uncharacterized, limiting our understanding of the key mechanisms of follicle development such as steroid hormone production and somatic-germ cells interactions. In this study we profiled the expression of >18,000 protein genes in 257 spatially defined human ovary samples to examine major types of functional units in the ovary, including areas enriched for oocytes, theca cells, and granulosa cells. To complement the spatial data, we generated single-cell RNA sequencing data for 21,198 past-QC cells from three additional donors and identified four major cell types and four immune cell subtypes. Custom selection of sampling areas and antibody-guided targeting of known cell types led to transcriptional profiles that are spatially highly specific, revealing distinct gene activities for early-stage oocytes and for theca and granulosa cells, respectively, all collected from their native tissue sites. These data significantly expanded the knowledge of molecular programs driving follicle development, contributing to a panel of 76 oocyte-specific genes including novel markers PADI6, UCHL1, ZFAND2A, and REC114, and similarly a 96- and 45-gene panel for granulosa and theca cells, respectively. Serial samples in follicle rings and across consecutive layers of the cortex and medulla uncovered spatial gradients in antral follicles and in the cortex surface, as well as previously unappreciated diversity of local gene expression patterns, reflecting regional variations of hormone signaling (NR4A1, CEBPD, STAR, and ADAMTS4) and extracellular matrix remodeling (VIM, COL1/8/12/14/16/18, and TIMP1/2). The combined spatial and single-cell human ovary atlas reported here serves as a resource for developing next-generation reagents for cell enrichment, high-resolution imaging, lineage analysis, and perturbation.

Dataset Information

Cellular atlas of the human ovary using morphologically guided spatial transcriptomics and single-cell sequencing.

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Cellular atlas of the human ovary using morphologically guided spatial transcriptomics and single-cell sequencing.

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