Single-cell and spatiotemporal profile of ovulation in the mouse ovary

Ovulation is a spatiotemporally coordinated process that involves several tightly controlled events, including oocyte meiotic maturation, cumulus expansion, follicle wall rupture and repair, and ovarian stroma remodeling. To date, no studies have detailed the precise window of ovulation at single-cell resolution. Here, we performed parallel single-cell RNA-seq and spatial transcriptomics on paired mouse ovaries across an ovulation time course to map the spatiotemporal profile of ovarian cell types. We show that major ovarian cell types exhibit time-dependent transcriptional states enriched for distinct functions and have specific localization profiles within the ovary. We also identified gene markers for ovulation-dependent cell states and validated these using orthogonal methods. Finally, we performed cell-cell interaction analyses to identify ligand-receptor pairs that may drive ovulation, revealing previously unappreciated interactions. Taken together, our data provides a rich and comprehensive resource of murine ovulation that can be mined for discovery by the scientific community.

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Publication Details

Journal
PLoS Biology
Published
2025-06-24
DOI
https://doi.org/10.1371/journal.pbio.3003193
Citations
5
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
4.03

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article

Single-cell and spatiotemporal profile of ovulation in the mouse ovary

Caroline E. Kratka, Ruixu Huang, Jeffrey Pea, John Bryan et al.
5 citations
PLoS Biology
Single-cell and spatial transcriptomics
4.03
article

Single-cell and spatiotemporal profile of ovulation in the mouse ovary

Caroline E. Kratka, Ruixu Huang, Jeffrey Pea, John Bryan, Jack Nelson, Francesca Elizabeth Duncan, Luhan T. Zhou, Cai McCann, Brittany A. Goods, Samouil L. Farhi, Brian Cleary, Alex K. Shalek, Daniela D. Russo, Achla H. Gandhi, Emily J. Zaniker-Gomez
article en
5 citations

Abstract

Ovulation is a spatiotemporally coordinated process that involves several tightly controlled events, including oocyte meiotic maturation, cumulus expansion, follicle wall rupture and repair, and ovarian stroma remodeling. To date, no studies have detailed the precise window of ovulation at single-cell resolution. Here, we performed parallel single-cell RNA-seq and spatial transcriptomics on paired mouse ovaries across an ovulation time course to map the spatiotemporal profile of ovarian cell types. We show that major ovarian cell types exhibit time-dependent transcriptional states enriched for distinct functions and have specific localization profiles within the ovary. We also identified gene markers for ovulation-dependent cell states and validated these using orthogonal methods. Finally, we performed cell-cell interaction analyses to identify ligand-receptor pairs that may drive ovulation, revealing previously unappreciated interactions. Taken together, our data provides a rich and comprehensive resource of murine ovulation that can be mined for discovery by the scientific community.

PLoS BiologyVol. 23(6)
Broad Institute (US), Dartmouth College (US), Boston University (US), Northwestern University (US), Ragon Institute of MGH, MIT and Harvard (US), University of Massachusetts Boston (US), Massachusetts Institute of Technology (US)
Bill and Melinda Gates Foundation, National Institutes of Health, National Institute of General Medical Sciences, National Institute of Child Health and Human Development
Openalex Percentile: Top 6%
Single-cell and spatial transcriptomics
4.03
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