As mice age, their total egg reserve collapses around tenfold. Yet, according to a new study in Nature Ageing, the proportion of eggs in the brief window where a follicle is shifting from dormant to growing stays constant throughout life, at approximately 14%.
"The same percentage of oocytes are being activated regardless of old the mouse is. That means the ovary has a sensing mechanism which knows how many oocytes are in there and only awakens a fixed proportion. No one has ever known that before. It is completely new biology," says Dr. Elvan Böke, group leader at the Centre for Genomic Regulation (CRG) in Barcelona and senior author of the study.
The finding challenges the perception that ovaries are a passive reservoir of eggs. The authors of the study reframe the female reproductive organ as an actively monitored system and suggest the ovary could be counting its own egg supply because of a yet-to-be-identified hormone or neuronal signalling.
The discovery was possible thanks to the first complete three-dimensional map of how a mammalian ovary changes across its reproductive lifespan. The CRG researchers combined high-resolution microscopy with artificial intelligence to count and classify every single egg cell, or oocyte, in more than 100 intact ovaries spanning the full reproductive lifespan of a mouse.
Earlier studies have imaged both human and mouse ovaries in three dimensions but couldn't track oocyte growth with as much precision as the CRG researchers, who are the first to follow a mouse throughout its reproductive life, oocyte by oocyte, in three-dimensional space. In total, they tracked over 85,000 cells, producing a dataset of unprecedented scale and resolution.
The study also made a second surprising finding. By the time they reach puberty, a mouse can end up with three times as many egg cells compared to another mouse, despite both animals being genetically identical and raised in the exact same conditions.
"These mice are essentially identical twins of the same age with the same living conditions yet have completely different ovaries. We found huge variability and it's not genetic. It means there's something else going on that we don't understand yet," says Dr. Böke.
The variability was already present in mice before they reached puberty, suggesting it originates very early in life, possibly during embryonic development. Mice with smaller ovarian reserves also had smaller ovaries and fewer growing eggs, suggesting that these early events shape ovarian function for life.
A third important finding overturns an old assumption about egg activation. At any given moment, only a handful of oocytes activate, despite the ovary having hundreds of thousands of dormant eggs stored. One long-standing hypothesis suggested that densely packed dormant eggs suppress one another.
The CRG's research found the opposite to be true. Regions of the ovary with the highest density of dormant eggs were also where the most eggs emerged from dormancy. "This idea has always floated around, but this is the first time there's actual data," says Arturo D'Angelo, first author of the study.
In another finding, the researchers also found a previously unrecognised developmental bottleneck at a particular stage of egg growth, around 60 micrometres in diameter, where many follicles appear to pause before becoming hormonally responsive.
The discovery is important because female mammals, including humans, are born with all the eggs they will have in their lifetime. Understanding what controls this checkpoint could matter for any future intervention aimed at extending reproductive lifespan or delaying menopause.
"We have thousands and thousands of oocytes in our bodies that we don't need," said Dr. Böke. "If we figure out why they're being lost without ever being ovulated, then we could tune the system. It could help keep the hormonal cycle going and help delay menopause, which half the world's population must go through. The health and economic implications are enormous."
The study is also careful about linking mouse biology to humans. Humans are born with roughly a million oocytes which decrease to 400,000 by puberty, and 1,000 by menopause. Only about 400 oocytes last for a lifetime. Mice have similar depletion rates but start with around 5,000.
However, mice ovulate from both ovaries every four to five days, while women typically release a single egg roughly every 28 days. Those differences in scale and tempo likely shape how the reserve is spent. Even so, the authors argue that the discovery that the ovary keeps a fixed fraction of eggs primed for activation regardless of age may be a universal feature of mammalian reproduction.
The authors of the study also believe the variation in ovarian reserve in women, with all their genetic and environmental diversity, is likely to be far larger compared to mice. They warn human studies will need larger cohorts to draw firm conclusions.
"In my mind, this data should have been out there 20 years ago, so we could have started building on it. It really changes how experiments should be planned," she says.
As a proof-of-concept, Böke and D'Angelo also show the method works on human ovarian cortex tissue, opening the door to similar studies in humans, although Dr. Böke cautions that the practical challenges are substantial. "The method is ready, but a lifespan study in humans is much harder," she says.
The new insights into mammalian reproductive biology were possible thanks to technical achievements. Mapping the entire ovarian reserve in three dimensions across an animal's lifespan required tissue clearing, whole-organ imaging on a microscope at EMBL Barcelona's Mesoscopic Imaging Facility and AI-driven image segmentation developed with collaborators at the Donostia International Physics Center (DIPC), the University of the Basque Country (UPV/EHU) and the Biofisika Institute.
"We wanted this tool to be useful to other scientists, not just for our own study. The complete workflow is freely available through BiaPy, our open-source platform for AI-based image analysis, and we've also released the microscopy images and the trained AI model itself. That means other labs can check our work, or point the same method at their own images without having to build it from scratch," says Ignacio Arganda-Carreras, leader of the CVPD group at the University of the Basque Country (UPV/EHU) and co-developer of BiaPy.
