Single-Cell Transcriptomic Analysis in Ovarian Development

Single-cell transcriptomics has revolutionised our understanding of ovarian development by resolving the molecular states of individual cells within follicles. This approach dissects the transcriptome of oocytes, granulosa and theca cells, stromal populations and immune components across developmental stages. High-throughput droplet-based and plate-based platforms enable profiling of thousands of single cells from ovarian cortex, antral and primordial follicles, revealing dynamic gene expression programmes underlying follicle activation, growth, atresia and differentiation. Integrative analyses with spatial mapping and multi-omics further elucidate cell–cell communication networks, lineage trajectories and epigenetic regulation during oogenesis. This granular view informs the classification of follicle subtypes, identifies novel marker genes for early activation or atretic states, and refines models of stromal and vascular interactions. Collectively, single-cell studies shed light on evolutionary conservation of developmental pathways, highlight species-specific adaptations and pave the way for targeted interventions in reproductive health and fertility preservation.

Research from Nature Portfolio

Recent studies have harnessed single-cell transcriptomics to characterise human ovarian cortical follicles, dissecting both paediatric and adult samples. Detailed profiling of 120 cortical follicles uncovered two principal follicle classes distinguished by oocyte-granulosa axis transcripts and intercellular signalling signatures, and identified extracellular matrix and microRNA alterations upon chemotherapy exposure, refining markers for early follicle activation. High-resolution multi-omics of antral-stage follicles has resolved the differentiation hierarchy of ovarian stroma into structural, androgenic and perifollicular theca subtypes, and traced a lineage-negative progenitor population, thereby elucidating the origins and functional specialisation of theca cells. These insights illuminate cell-specific roles in steroidogenesis, follicular support and pathological remodelling, offering a framework for diagnostic markers and therapeutic targets in ovarian dysfunction.

Single-Cell Transcriptomic Analysis in Ovarian Development publication trend

The graph below shows the total number of articles in single-cell transcriptomic analysis in ovarian development across all publications each year (not limited to Nature Index journals).

Technical terms

Single-cell RNA sequencing (scRNA-seq): A technique that profiles gene expression in individual cells to reveal cellular heterogeneity.

Transcriptome: The complete set of RNA transcripts produced by the genome in a cell at a given time.

Granulosa cells: Somatic follicular cells that surround the oocyte and support its growth and hormone production.

Theca cells: Follicular cells that form an outer layer around granulosa cells and contribute to steroidogenesis.

Folliculogenesis: The process of follicle development and maturation in the ovary.

Ligand–receptor interaction: Molecular communication whereby secreted or membrane-bound ligands bind to specific receptors on target cells.

References

1. In-depth analysis of transcriptomes in ovarian cortical follicles from children and adults reveals interfollicular heterogeneity. Nature Communications (2024).
2. Human theca arises from ovarian stroma and is comprised of three discrete subtypes. Communications Biology (2023).
3. A Single‐Cell Atlas of Crab Ovary Provides New Insights Into Oogenesis in Crustaceans. Advanced Science (2024).
4. Single-cell sequencing reveals the reproductive variations between primiparous and multiparous Hu ewes. Journal of Animal Science and Biotechnology (2023).
5. A spatiotemporal gene expression and cell atlases of the developing rat ovary. Cell Proliferation (2023).