Standardizing Cell Ontology terms for cross-study integration in the female reproductive tract

The female reproductive tract is essential for fertility, pregnancy, and overall health, yet many of its cellular components remain poorly defined. Recent advances in single-cell and spatial transcriptomics have begun to reveal this complexity, but inconsistent naming of cell types and states has limited the ability to compare findings across studies. To address this challenge, an international group of reproductive biologists and ontology experts collaborated to harmonize annotations within Cell Ontology, focusing on the ovary, fallopian tube, and uterus. Standardized terms are proposed for major epithelial, stromal, and germ cell populations, supported by marker gene sets and anatomical linkages. This framework provides a shared reference that can be used to harmonize existing datasets and guide annotation of future studies, enabling consistent classification of oocytes, granulosa, theca, luteal, epithelial, stromal, and immune cells across tissues. By establishing a unified taxonomy, this work lays the foundation for integrating datasets, supporting cross-tissue comparisons, and advancing the understanding of reproductive biology, health, and disease.

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Publication Details

Journal
Science Advances
Published
2026-10-09
DOI
https://doi.org/10.1126/sciadv.aef2358
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
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article

Standardizing Cell Ontology terms for cross-study integration in the female reproductive tract

Benjamin K. Johnson, Caroline E. Kratka, José V.V. Isola, Michael R. Angelo et al.
Science Advances
Biomedical Text Mining and Ontologies
article

Standardizing Cell Ontology terms for cross-study integration in the female reproductive tract

Benjamin K. Johnson, Caroline E. Kratka, José V.V. Isola, Michael R. Angelo, Sophia H.L. George, Jennifer L. Young, Michael B. Stout, Roser Vento‐Tormo, Hui Shen, Patricia P. Jeudin, Jordan H. Machlin, Anna M. Galligos, Valentina Lorenzi, Wipawee Winuthayanon, Chen Jin, Gabriela Rapozo Guimarães, Mariana Boroni, Ariella Shikanov, Jennifer L. Garrison, Francesca Elizabeth Duncan, Bérénice Anath Benayoun, Brian D. Aevermann, Aleix Puig-Barbe, Mariko H. Foecke, Subhasri Biswas, Diane C. Saunders, Ronny Drapkin, Eliza A. Gaylord, Bailey Marshall, Matteo A. Molè, Norbert K. Tavares, Monica M. Laronda, Jun Z. Li, Diana J. Laird, Huan Ting Ong, Bikem Soygur, Ryan M. Samuel, Will Liao, Hattie Chung, Alison Kochersberger, Svetlana Djirackor, Xifan Wang, Xingyu Shen, Katelyn M. Adam, Sophia Szady, Taylor Schissel, Srinivasan Mahalingam, Daniela Betancur, Caroline Eastwood, Yousin Suh, Osmaray Morales-Casanova
article en

Abstract

The female reproductive tract is essential for fertility, pregnancy, and overall health, yet many of its cellular components remain poorly defined. Recent advances in single-cell and spatial transcriptomics have begun to reveal this complexity, but inconsistent naming of cell types and states has limited the ability to compare findings across studies. To address this challenge, an international group of reproductive biologists and ontology experts collaborated to harmonize annotations within Cell Ontology, focusing on the ovary, fallopian tube, and uterus. Standardized terms are proposed for major epithelial, stromal, and germ cell populations, supported by marker gene sets and anatomical linkages. This framework provides a shared reference that can be used to harmonize existing datasets and guide annotation of future studies, enabling consistent classification of oocytes, granulosa, theca, luteal, epithelial, stromal, and immune cells across tissues. By establishing a unified taxonomy, this work lays the foundation for integrating datasets, supporting cross-tissue comparisons, and advancing the understanding of reproductive biology, health, and disease.

Science AdvancesVol. 12(41)
Northwestern University (US), Stowers Institute for Medical Research (US), University of Southern California (US), Lurie Children's Hospital (US), European Bioinformatics Institute (GB), Van Andel Institute (US), Buck Institute for Research on Aging (US), University of Miami (US), National University of Singapore (SG), Universidade Federal de Pelotas (BR), University of California, San Francisco (US), Universidade Estadual de Campinas (UNICAMP) (BR), Wellcome/MRC Cambridge Stem Cell Institute (GB), University of Cambridge (GB), University of Michigan (US), Columbia University Irving Medical Center (US), University of Missouri Health System (US), Wellcome Sanger Institute (GB), Oklahoma Medical Research Foundation (US), Yale University (US), Oklahoma City VA Medical Center (US), Parker Institute for Cancer Immunotherapy (US), Michigan Medicine (US), USC Norris Comprehensive Cancer Center (US), Chan Zuckerberg Initiative (United States) (US), Stanford Medicine (US), Instituto Nacional de Câncer - INCA (BR), New York Genome Center (US), Sylvester Comprehensive Cancer Center (US), UCSF Helen Diller Family Comprehensive Cancer Center (US), Abramson Cancer Center (US), Institute for Stem Cell Biology and Regenerative Medicine, Mechanobiology Institute (SG), University of Oklahoma Health Sciences Center (US), University of Missouri (US), University of Pennsylvania (US), Stanford University (US)
Openalex Percentile: Top 23%
Biomedical Text Mining and Ontologies
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