An ovary is only a few centimeters wide, but its precious cargo is even smaller. Oocytes are a few dozen micrometers in diameter and are individually wrapped in layers of specialized cells that form a follicle that supports the developing egg. “[The ovary] dictates the future of our species,” said Jun Li, a bioinformatician at the University of Michigan.
An ovary may have as few as ten follicles at a time, which poses an obstacle for studying these cells. Even with high-resolution technologies like single-cell RNA-sequencing (scRNA-seq), key follicular cells can be hard to isolate.1,2
To get a deeper look at these elusive cells, Li teamed up with Ariella Shikanov, a bioengineer at the University of Michigan, to study healthy ovaries by combining spatial and single-cell profiling technologies.3 In a paper published in Science Advances, they presented a detailed atlas of the ovary, and like city maps, they zoomed in on the follicles to get a closer look at the rare cells. Capturing follicular gene expression patterns can help scientists identify the factors that promote healthy eggs.
“The morphology of the ovary is so beautiful,” Shikanov said. “By combining [spatial and scRNA-seq], we were able to build a more nuanced atlas.”
The team studied two ovaries from young, healthy women—a rarity for reproductive biologists, since most ovaries available for research are from people with reproductive diseases or who are postmenopausal, said Britt Goods, a bioengineer at Dartmouth College who was not involved in this study.
From slices of the ovaries, the researchers selected more than 200 features of interest, including old and young follicles, specific layers of cells within follicles, and the surface of the ovary. Then by using a spatial biology platform called GeoMx they measured the RNA levels for more than 18,000 genes. While this technology didn’t have single-cell resolution, it scanned across the selected region and captured RNA expression from small groups of around a dozen adjacent cells. The researchers used this information to map out spatial patterns of gene expression in cells that hadn’t been well described before.
Inside follicles, they found not only oocytes, but also theca and granulosa cells, two types of hormone-secreting cells that surround the immature eggs. By digging into these cells’ gene expression profiles, the researchers compiled lists of genes that other researchers can now use to identify these cells in their own datasets. The study also offered insights into ovarian biology. For example, when the authors measured gradients of gene expression that occurred in concentric rings around follicles, they found that genes that encode signals promoting oocyte development were highly expressed in the follicles' cores, while genes encoding signals promoting hormone production and ovulation were concentrated in the periphery.
With three different ovaries, the researchers used scRNA-seq to measure gene expression in an unbiased way. “Marrying the two technologies together can be really valuable because you can see exactly where a particular group of cells is important in tissue,” Goods said, although she noted that with a small sample size and relatively coarse spatial technology, she would like to see validation of the cell types and their gene expression profiles in future studies. “This paper really lays the groundwork for a lot of future studies in this space, which is really exciting,” she said.
Li and Shikanov believe that other researchers can use this atlas as a reference to identify cell types and key regions in other ovarian studies, or as a point of comparison for finding molecular pathways that are dysregulated in disease. Shikanov also sees potential for this atlas to promote the development of fertility treatments. She is interested in developing artificial ovaries, and now she can use the atlas to figure out what genes are critical to cells that support developing eggs.
The ovarian cell atlas isn’t the end of Shikanov and Li’s collaboration. This project is part of a three-part endeavor that they are undertaking on behalf of the Human Cell Atlas, an international consortium that aims to map all the organs in the human body at single-cell resolution. The duo previously published a study of the fallopian tubes, and have now set their sights on the uterus.4,5 They also hope to isolate individual oocytes and track them across development to find the genes that orchestrate ovulation.
“There are different types of infertility, so knowing the biology gives us a better footing to predict and to intervene,” Li said.
References
1. Fan X, et al. Single-cell reconstruction of follicular remodeling in the human adult ovary. Nat Commun. 2019;10(1):3164.
2. Wagner M, et al. Single-cell analysis of human ovarian cortex identifies distinct cell populations but no oogonial stem cells. Nat Commun. 2020;11(1):1147.
3. Jones ASK, et al. Cellular atlas of the human ovary using morphologically guided spatial transcriptomics and single-cell sequencing. Sci Adv. 2024;10(14):eadm7506.
4. Ulrich ND, et al. Cellular heterogeneity of human fallopian tubes in normal and hydrosalpinx disease states identified using scRNA-seq. Dev Cell. 2022;57(7):914-929.e7.
5. Ulrich ND, et al. Cellular heterogeneity and dynamics of the human uterus in healthy premenopausal women. bioRxiv. 2024.
