A single cell atlas of the developing Drosophila ovary identifies follicle stem cell progenitors
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA545484 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Addressing the complexity of organogenesis at a system-wide level requires a complete understanding of adult cell types, their origin, and precursor relationships. The Drosophila ovary has been a model to study how coordinated stem cell units, germline, and somatic follicle stem cells maintain and renew an organ. However, lack of cell type-specific tools have limited our ability to study the origin of individual cell types and stem cell units. Here, we used a single-cell RNA sequencing approach to uncover all known cell types of the developing ovary, reveal transcriptional signatures, and identify cell type-specific markers for lineage tracing. Our study identifies a novel cell type corresponding to the elusive follicle stem cell precursors and predicts subtypes of known cell types. Altogether, we reveal a previously unanticipated complexity of the developing ovary and provide a comprehensive resource for the systematic analysis of ovary morphogenesis.
| S-EPMC7000915 | biostudies-literature
Project description:A Cell Atlas of the Drosophila ovary
| PRJNA561416 | ENA
Project description:Single-cell RNA sequencing of adult Drosophila ovary using the 10X platform. Ovaries were dissociated to single cells and Single-cell libraries were generated for 435 cells (dataset1), 8326 cells (dataset2) or 5412 cells (dataset3). Cells were sequenced at a depth of~540,000 reads per cell (dataset1), ~40,000 reads per cell (dataset2) or ~ 70,000 reads per cell (dataset3). We identified transcriptomes of 26 distinct cell populations including the stem cells of the germline and the follicle cell lineage as well as three distinct subtypes inner germarial sheath cells, polar cells, stalk cells and subpopulations of main body follicle cells.
2020-09-08 | GSE136162 | GEO
Project description:We aimed to create an ovary cell atlas using publicly available RNA-seq data. To complement the data we sequenced 2 ovary tissue samples from patients undergoing elective surgery at the JR hospital in Oxford. We applied single-nucei sequencing using the 10x Chromium technology.
2024-10-31 | GSE278300 | GEO
Project description:We use single cell RNA sequencing approach to identify and characterize all cell types in developing Drosophila ovaries at late third instar larval stage (LL3).
2020-02-04 | GSE131971 | GEO
Project description:Single cell transcriptome atlas of microenvironment in preovulation follicle
| PRJNA785257 | ENA
Project description:A single-cell atlas of the aging murine ovary
| PRJNA971592 | ENA
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.
2024-03-06 | GSE260686 | GEO
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.
2024-03-06 | GSE260685 | GEO
Project description:single-cell RNA-seq analysis of 2 ovary tissues as part of creating a ovary cell atlas
| PRJNA1166244 | ENA