Uncovering the ovary’s secrets with radical collaboration

Collaborating with Iwijin De Vlaminck, associate professor in the Meinig School of Biomechanical Engineering, Ren and her colleagues conducted high-resolution, spatial, gene-expression profiling on mouse ovaries. The researchers collected the imaged tissue samples over various time points in the ovulation process, resulting in a huge dataset of ovarian gene expression. Then they created the first atlas of spatial transcriptomic maps showing the location of cells and cellular gene expression in normal ovaries and in those under hormone-controlled ovulation. The information the maps revealed can potentially be used to inform reproductive medicine. 

The researchers published a paper on this work in January 2024 in Proceedings of the Academy of Science. It was cited over 30 times within the first year after its publication. “That paper got a lot of attention because we were the first to report using spatial transcriptomics in the ovary,” Ren said. “I’m very happy about bringing that to the field.” 

Ren and Vlaminck are continuing to work on imaging the ovary, but this time at higher resolution, using Spatial Total RNA Sequencing (STRS). This technique, developed by Vlaminck, expands the scope of sequencing-based spatial transcriptomics to the total transcriptome. The researchers will look at individual cells and sub-cellular RNAs, including noncoding RNA, which very often regulates gene expression. 

“We can recompose the ovary digitally because we can map out each single cell: where it is in the ovary and what gene it expresses, including the non-coding RNA.”

“No one has comprehensively studied that in the ovary,” Ren said, pointing out that usually, researchers will focus on one or few non-coding RNAs, test it and then report on their findings. “But we are looking at the single-cell level for the whole ovary spanning the entire genome,” she explained. “That’s a lot of cells; you have 20 different cell types right there. And we can recompose the ovary digitally because we can map out each single cell: where it is in the ovary and what gene it expresses, including the non-coding RNA.”

The Ren lab has also been collaborating for some years with Paul Soloway, professor emeritus of molecular genetics in the College of Veterinary Medicine. Together with Soloway and his lab, they published a recent paper in Advanced Science about the Semaphorin 3E-Plexin-D1 cell-signaling pathway, which they discovered has a role in ovulation. 

Now, looking forward, Ren and her colleagues will be using the unique database of large single-cell-level datasets with high spatial and temporal resolution that they have been building with Solloway. “We’ll be analyzing these datasets to probe new mechanisms of gene regulation at the single-cell level during ovulation,” Ren said. “My students and I are going to be creative about the questions we ask.”

One question that intrigues Ren centers on that rupture to the follicle that releases the egg. What controls this process? A possible way to answer this is to use the datasets to look at gene expression over time and compare the top of the follicle where the rupture takes place to the bottom of the follicle, which does not rupture, Ren explained. 

“By comparing the two regions temporally at the single cell level, it should be possible to figure out what is required for the rupture to happen,” she said.

“I like to ask questions that are conceptually new,” she added. “I really like this style of science where I can bring ideas and technology that are more novel to the field and change the way people approach things.”

Jackie Swift is the communications specialist for the Cornell CALS Department of Animal Science.