Friday, March 13, 2026

New study clarifies how temperature shapes sex development in leopard gecko

Researchers pinpoint when temperature determines sex and uncover early genetic changes guiding male or female development in leopard gecko

Tokyo University of Science

Transcriptome analysis of temperature-dependent sex determination in leopard geckos — image:
Researchers discover leopard gecko produces females at cooler incubation temperatures and mostly males at warmer ones. This clear sex-determination pattern of leopard gecko has established it as a key model for studying environmental effects on development.
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Credit: Professor Shinichi Miyagawa from Tokyo University of Science, Japan

In reptiles, a simple temperature change can determine whether an egg develops into a male or female. This process is formally known as temperature-dependent sex determination (TSD), in which the sex of an embryo is determined by the temperature it experiences during a specific window of development known as the temperature-sensitive period. For example, in American alligators, incubation at around 30 °C typically produces females, while temperatures near 33 °C produce males, although extremely high temperatures can again result in females. Although TSD has been studied for decades, its mechanisms in squamates—the large and diverse group of reptiles that includes lizards and snakes—have been largely overlooked.

To address this gap, a team of researchers led by Professor Shinichi Miyagawa from the Department of Biological Science and Technology, Tokyo University of Science, Japan, investigated TSD in the leopard gecko (Eublepharis macularius), a lizard species where lower temperatures of about 26 °C produce females, while higher temperatures around 32 °C produce mostly males. Their study was made available online on February 18, 2026, and will be published in Volume 533 of the journal Developmental Biology on May 01, 2026.

“Our study is the first to provide a comprehensive histological and transcriptomic analysis of gonadal development in the leopard gecko with a TSD system,” says Prof.
Miyagawa.

In this study, the team incubated eggs at either 26.5 °C, a female-producing temperature, or 31.5 °C, a male-producing temperature. To determine the exact window when temperature influences sex, they performed shift experiments, moving eggs between the two temperatures on different days after they were laid.

When the eggs were close to hatching, the researchers examined their gonads, the organs that develop into ovaries or testes, to determine their sex. Notably, incubation at the cooler temperature produced 100% females, while the warmer temperature produced 91% males.

Early in development, embryos from both temperature groups appeared similar, with no obvious external differences. The first clear structural differences appeared later, when ovaries became more spherical and testes elongated and formed seminiferous tubules. However, gene expression analysis showed that male and female developmental pathways had already begun to diverge before these visible changes appeared. Important testis-related genes such as AMH, DMRT1, and SOX9 were activated earlier at male-producing temperatures, while ovarian genes such as FOXL2 and CYP19A1 became more active at female-producing temperatures.

The team determined that the temperature-sensitive period ends at embryonic stage 36. Before this stage, changing the incubation temperature could still alter the sex. However, after this point, the sex was set and could no longer be changed by temperature.

The study also uncovered features unique to the leopard gecko. For example, the gene KDM6B, which plays a key role in male determination in turtles, showed a different pattern of regulation in this species. In addition, it identified early temperature-responsive genes involved in RNA splicing and cell adhesion, suggesting that changes at the molecular level begin before any physical differences between males and females become apparent.

The researchers add that factors such as the mother’s body temperature before laying egg may influence early development and could vary between laboratories. However, their findings show that the genes responsible for forming gonads are largely shared across reptiles, but the way temperature controls these genes has evolved differently in different reptile groups.

“Our study addresses a critical phylogenetic gap in TSD studies and contributes significantly to the broader understanding of the evolutionary plasticity and molecular complexity by which environmental cues direct biological fate,” concludes Prof. Miyagawa.

***

Reference
DOI: 10.1016/j.ydbio.2026.02.011

About The Tokyo University of Science
Tokyo University of Science (TUS) is a well-known and respected university, and the largest science-specialized private research university in Japan, with four campuses in central Tokyo and its suburbs and in Hokkaido. Established in 1881, the university has continually contributed to Japan's development in science through inculcating the love for science in researchers, technicians, and educators.

With a mission of “Creating science and technology for the harmonious development of nature, human beings, and society," TUS has undertaken a wide range of research from basic to applied science. TUS has embraced a multidisciplinary approach to research and undertaken intensive study in some of today's most vital fields. TUS is a meritocracy where the best in science is recognized and nurtured. It is the only private university in Japan that has produced a Nobel Prize winner and the only private university in Asia to produce Nobel Prize winners within the natural sciences field.

Website: https://www.tus.ac.jp/en/mediarelations/

About Professor Shinichi Miyagawa from Tokyo University of Science
Dr. Shinichi Miyagawa is a Professor at the Department of Biological Science and Technology, Tokyo University of Science, Japan. His research area includes tumor biology, developmental biology, and morphology/structure. He serves on the editorial board of the Journal of Applied Toxicology and is an active member of several international scientific committees focused on endocrinology and environmental science. He has been felicitated with several awards including the NIBB Young Scientist Award in 2015 and the National Institutes of Natural Sciences Young Scientist Award in 2012.

Funding information
This work was supported by Grant-in-Aid for Scientific Research B [Grant Number JP21H02522 (Shinichi Miyagawa)], Early-Career Scientists [20K15835 (Genki Yamagishi)], JSPS Fellows [22KJ2802 (Genki Yamagishi)] and Scientific Research on Innovative Areas [JP17H06432 (Shinichi Miyagawa)] from Japan Society for the Promotion of Science (JSPS).

Journal

Developmental Biology

DOI

10.1016/j.ydbio.2026.02.011

Method of Research

Experimental study

Subject of Research

Animals

Article Title

Gonadal development and gene expression in the leopard gecko during temperature-dependent sex determination

Article Publication Date

1-May-2026

Watching a lifetime in motion reveals the architecture of aging

Stanford University

Nath Bedbrook Killifish Brodhead — image:
Claire Bedbrook (right) and Ravi Nath studied the behavior of the short-lived African killifish, like the one in the foreground. They showed that aging proceeded in discrete steps and that behavior relatively early in life could predict killifish lifespans.
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Credit: Andrew Brodhead/Stanford University

By midlife, an animal’s everyday behaviors can signal how long it is likely to live.

That is the striking conclusion of a new study supported by the Knight Initiative for Brain Resilience at Stanford’s Wu Tsai Neurosciences Institute, in which researchers put scores of short-lived fish under continuous, lifelong surveillance to explore how behavior and aging are linked.

Individual fish aged in markedly different ways, despite having similar genetics and living in a carefully controlled environment. By early adulthood, those differences were already visible in how the animals swam and rested—and were strong enough to predict whether a fish would ultimately live a long or short life.

While the research was conducted in fish, the findings raise the possibility that tracking subtle, daily behaviors like movement and sleep, now routinely captured by wearable devices, may offer clues about how aging unfolds in people.

The findings were published in Science on March 12, 2016, in a study led by Wu Tsai Neuro postdoctoral scholars Claire Bedb rook and Ravi Nath. The research grew out of a Knight Initiative–supported collaboration between the Stanford labs of geneticist Anne Brunet and bioengineer Karl Deisseroth, the study’s senior authors.

How to watch aging unfold in real time

Most aging studies contrast groups of young animals with groups of old ones. While informative, those snapshots blur how aging unfolds within individuals over time, and how differences between individuals emerge.

Bedbrook and Nath wanted to know what might be revealed by watching aging continuously across an entire adult lifespan. Even animals of the same species, raised under similar conditions, can follow very different aging paths and live dramatically different lengths of time. The researchers asked whether natural behavior could reveal when and how those individual trajectories begin to diverge.

The African turquoise killifish made that question experimentally possible. With a typical lifespan of just four to eight months, it is one of the shortest-lived vertebrates studied in the lab, yet it shares key biological features with longer-lived species like humans, including a complex brain.

The Brunet lab has been at the forefront of developing the killifish as a model for studying aging, laying the foundation for this study, the first to follow individual vertebrates continuously, day and night, across their entire adult lives.

Bedbrook, Nath, and their colleagues built an automated system in which individual fish lived in separate, camera-monitored tanks. Like a scientific version of The Truman Show, the 1998 film in which a man’s entire life is recorded continuously, the setup captured every moment of the animals’ lives. In total, they tracked 81 fish and generated billions of video frames.

From those recordings, the researchers extracted detailed information about the animals’ posture, speed, rest, and movement, identifying 100 distinct “behavioral syllables”—short, recurrent actions that represent the basic building blocks of how a fish moves and rests.

“Behavior is a wonderfully integrated readout, reflecting what’s happening across the brain and body,” said Brunet, the Michele and Timothy Barakett Professor of Genetics at Stanford Medicine. “Molecular markers are essential, but they capture only slices of biology. With behavior, you see the whole organism, continuously and non-invasively.”

With this life-long behavioral record in hand, the researchers could begin asking a new set of questions: When do animals start to age differently? What distinguishes those paths early on? And, can behavior alone predict whether an individual will live to a ripe old age?

Early signals of an animal’s lifespan

One of the team’s most surprising findings was how early individual aging paths begin to diverge. After following each fish through its entire lifespan, the researchers grouped animals based on how long they ultimately lived and then looked back to see when behavioral differences first emerged. They found by early midlife (70 to 100 days of age), fish that would go on to live shorter or longer lives were already behaving differently.

Some of the clearest differences involved sleep. As young adults, fish that went on to have shorter lives tended to sleep not only at night but increasingly during the day. In contrast, fish that went on to longer lives mainly slumbered at night.

But sleep was not the only signal. Fish on paths to a longer life also swam with greater vigor and reached higher speeds when darting around the tank—a measure of spontaneous movement that has been linked to longevity in other species as well. They also tended to be far more active during daylight hours.

Crucially, those behavioral differences were not just descriptive but predictive. Using machine-learning models, the researchers showed that just a few days of behavioral data from middle-aged fish were enough to forecast lifespan. “Behavioral changes pretty early on in life are telling us about future health and future lifespan,” said Bedbrook.

Aging unfolds in steps

The team’s observations also revealed that aging—in killifish, at least—does not progress as a smooth, gradual drift. Most of the fish underwent two to six rapid behavioral transitions, each lasting just a few days, followed by longer, stable stages that lasted weeks. Importantly, fish tended to progress through these stages in sequence, rather than switching back and forth between them.

“We expected aging to be a slow, gradual process,” said Bedbrook. “Instead, animals stay stable for long periods and then transition very quickly into a new stage. Seeing this staged architecture appear from continuous behavior alone was one of the most exciting discoveries.”

This stepwise pattern echoes emerging evidence from human studies, including research showing that molecular features of aging change in waves, especially during midlife and older adulthood. The killifish results offer a behavioral view of the same phenomenon.

The researchers suggest that aging may involve long stretches of relative stability punctuated by brief periods of rapid change. This process is more like a Jenga tower, in which many blocks can be removed with little effect, until one change forces a sudden restructuring, than a smooth downhill slide.

The researchers also examined gene activity across eight organs in adult fish at a stage when behavior could reliably predict future lifespan. Rather than focusing on individual genes, they looked for coordinated changes across groups of genes that work together in shared biological processes.

The clearest differences appeared in the liver, where genes involved in protein production and cellular maintenance were more active in fish on shorter aging paths. These findings offered a molecular hint that the animals’ internal biology is changing alongside the behavioral patterns as they age.

Behavior as a new window into aging

“Behavior turns out to be an incredibly sensitive readout of aging,” said Nath. “You can look at two animals of the same chronological age and see from their behavior alone that they’re aging very differently.”

That sensitivity shows up across many aspects of daily life, including sleep, which emerged as an important signal of how aging was unfolding. In humans, sleep quality and sleep-wake cycles often deteriorate with age, and these changes have been linked to cognitive decline and neurodegenerative disease. Nath aims to explore whether sleep itself can be manipulated to promote healthier aging, and whether intervening early, before decline sets in, can alter an individual’s aging path.

The team also plans to test whether aging paths can be modified through targeted interventions, including changes to diet as well as to genes that may help influence the pace of aging.

For Bedbrook, the killifish study opens the door to deeper questions about what drives aging transitions and whether those transitions can be delayed, prevented, or reversed. She is also interested in pushing the experimental system toward more naturalistic settings, allowing animals to interact socially and experience richer environments that more closely resemble real life.

“We now have the tools to map aging continuously in a vertebrate,” she said. “With the rise of wearables and long-term tracking in humans, I’m excited to see whether the same principles—early predictors, staged aging, divergent trajectories—hold true in people.”

Another major frontier lies in the brain itself. Deisseroth’s lab develops tools to monitor neural activity continuously over long periods of time, making it possible to follow changes in brain activity alongside the same animals’ aging paths. Those experiments could reveal whether the brain mirrors aging in the rest of the body or plays a more active role in setting its pace.

Both Bedbrook and Nath will continue pursuing these questions as they open their own laboratories at Princeton University this July, bringing the tools and ideas developed at Stanford into the next phase of their research.

Ultimately, the hope is that mapping aging at this resolution will clarify why aging varies so widely, and point toward new ways of promoting healthy aging.

Publication Details

Research Team

Study authors were Claire Bedbrook from the Department of Bioengineering at Stanford Medicine and Stanford Engineering; Ravi Nath from the Department of Genetics at Stanford Medicine; Libby Zhang from the Department of Electrical Engineering at Stanford at Stanford Engineering; Scott Linderman from the Department of Statistics in Stanford Humanities and Sciences, the Knight Initiative for Brain Resilience and the Wu Tsai Neurosciences Institute; Anne Brunet from the Department of Genetics at Stanford Medicine, Wu Tsai Neurosciences Institute, Knight Initiative for Brain Resilience, and the Glenn Center for Biology of Aging; and, Karl Deisseroth, the D.H. Chen Professor, from Departments of Bioengineering at Stanford Medicine and Stanford Engineering and of Psychiatry and Behavioral Sciences at Stanford Medicine, Knight Initiative for Brain Resilience, and the Howard Hughes Medical Institute at Stanford University.

Research Support

The research was funded by the National Institutes of Health (R01AG063418 and K99AG07687901), a Knight Initiative for Brain Resilience Catalyst Award and Brain Resilience Scholar Award, the Keck Foundation, the ARIA Foundation, the Glenn Foundation for Medical Research, the Simons Foundation, the Chan Zuckerberg Biohub – San Francisco, a NOMIS Distinguished Scientist and Scholar Award, the Helen Hay Whitney Foundation, the Wu Tsai Neurosciences Institute Interdisciplinary Scholar Award, and the Iqbal Farrukh & Asad Jamal Center for Cognitive Health in Aging.

Competing Interests

Karl Diesseroth is a cofounder and a scientific advisory board member of Stellaromics and Maplight Therapeutics, and advises RedTree and Modulight.bio. Anne Brunet is a scientific advisory board member of Calico. All other authors declare no conflicts of interest.

Claire Bedbrook (left) pulls an African killifish tank from a shelf as Ravi Nath looks on. Bedbrook and Nath showed that aging proceeded in discrete steps and that behavior relatively early in life could predict killifish lifespans.

Ravi Nath (left) and Claire Bedbrook studied the behavior of the short-lived African killifish, like the one in the foreground. They showed that aging proceeded in discrete steps and that behavior relatively early in life could predict killifish lifespans

Killifish Brodhead — African killifish like the one pictured typically live just a few months, which helps research study them across their entire lifespans. Claire Bedbrook and Ravi Nath tracked dozens of killifish across their lifespans and found that they age in steps—and that their behavior in midlife can predict how much longer they have live.

Killifish 2 Brodhead — African killifish like the one pictured typically live just a few months, which helps research study them across their entire lifespans. Claire Bedbrook and Ravi Nath tracked dozens of killifish across their lifespans and found that they age in steps—and that their behavior in midlife can predict how much longer they have live.
Credit
Andrew Brodhead/Stanford University