Single-cell-scale spatial transcriptome of the developing and adult mouse ovary

Area of Science:

• Developmental Biology
• Genomics
• Reproductive Biology

Background:

• Mammalian ovary development is critical for female fertility, involving intricate spatial organization of cell types to form ovarian follicles.
• Previous single-cell transcriptome analyses offered insights into cell specification but lacked spatial context.

Purpose of the Study:

• To overcome the limitations of spatial context loss in previous studies.
• To generate a high-resolution spatial gene expression map of the developing mouse ovary.
• To investigate the spatial patterning mechanisms underlying ovarian development and follicle assembly.

Main Methods:

• Utilized 10X Genomics Visium HD spatial transcriptomics.
• Analyzed the developing mouse ovary across eight key fetal and postnatal timepoints.
• Maintained native cellular architecture to preserve spatial information.

Main Results:

• Captured all ovarian cell types at near single-cell resolution.
• Generated a comprehensive spatial gene expression dataset across ovarian development.
• Identified dynamic transcriptional signatures linked to spatial patterning, including cortex/medulla formation and follicle assembly.

Conclusions:

• The generated dataset is a fundamental resource for studying ovarian spatial patterning.
• This work opens new avenues for exploring spatial determinants of female fertility and reproductive longevity.
• Provides a foundation for understanding regulatory mechanisms driving ovary development.