Genetic blueprint behind early brain development uncovered by team of Waisman investigators

By Emily Leclerc | Waisman Science Writer

At a glance

  • Early neuronal maturation is not well understood. A new study at Waisman was able to map the gene and regulatory networks driving early neuronal maturation for the first time.
  • The electrophysiological properties of neurons are key to their function. The study found that different properties mature and develop on distinct and dynamic timelines which was not known before.
  • The paper was able to strengthen the correlation between the known autism risk gene CHD8 and the development of autism.
  • This work would not have been possible without the close interdisciplinary collaboration between the four Waisman labs.
André Sousa, Xinyu Zhao, Qiang Chang, and Daifeng Wang
From left to right: André Sousa, Xinyu Zhao, Qiang Chang, and Daifeng Wang

In a new study published in the journal Neuron, a team of researchers from four Waisman Center labs has, for the first time, mapped the genetic and regulatory networks that guide the early maturation of neurons in the primate prefrontal cortex (PFC) – a brain region essential for cognition, decision-making, and social behavior. This pioneering work offers new insights into how the brain’s communication cells develop and how disruptions in this process may contribute to neurodevelopmental conditions such as autism.

The study, led by the labs of Waisman investigators André Sousa, PhD, assistant professor of neuroscience, Xinyu Zhao, PhD, Jenni and Kyle Professor in Novel Neurodevelopmental Diseases, Qiang Chang, PhD, director of the Waisman Center and professor of medical genetics and neurology, and Daifeng Wang, PhD, associate professor of biostatistics and medical informatics, combined two powerful data collection techniques to match individual neurons’ gene expression profiles with their developing electrophysiological properties – the electrical traits that allow neurons to send and receive signals.

The four graphs showcase the different maturation trajectories of four different electrophysiological traits over time.
The four graphs showcase the different maturation trajectories of four different electrophysiological traits over time.

“We don’t know much about early neuronal maturation even though it’s a very important period. We know quite a lot about the mechanisms that are important for how neurons gain their identity, how they find their final place, and where they project to and connect to other neurons,” says Sousa. “But how neurons’ intrinsic features like electrophysiology mature? We know almost nothing.” The four Waisman labs decided they wanted to change that.

Neurons are the communication cells of the brain. The brain’s numerous functions rest primarily on the shoulders of neurons and their ability to electrically convey messages. Parts of neuronal development have been heavily studied with synapse – the connections between neurons that allow messages to pass back and forth – development being the core focus of much of the scientific literature. That leaves a large gap in the knowledge base. One that ripples far past the laboratory.

In general, researchers have been rather unsuccessful in building treatments and therapeutics for conditions involving the brain. It is a deeply complex organ that is still not well understood. “This makes anything related to the brain very hard to treat,” Sousa says. Unearthing the processes guiding early neuronal development lays crucially important scientific groundwork as disruptions in early development are often correlated with neurodevelopmental conditions like autism. It also could open doors for potentially developing more effective treatments.

A depiction of how some of the genes found in the study interact with and influence one another.
A depiction of how some of the genes found in the study interact with and influence one another.

“If you don’t know how a machine is built and how it works typically, it is very hard to know how to treat a disorder. It is like asking someone who has never seen an engine before to fix your car,” Sousa says. “It is really important to understand how the brain is assembled and how the circuits are put together.”

This study is the first to lay out the network of genes directing the prenatal maturation of neurons’ electrophysiological traits in the PFC of non-human primates. The team was not only able to put together how hundreds of different genes are involved in the maturation process but also how interruptions to the process could factor into conditions like autism. “There is no study previously done that uses the approach we used to look at the details we looked at,” Chang says.

The PFC is a section of the brain that is highly associated with social behaviors, working memory, and various executive functions and is heavily implicated in neurodevelopmental and psychiatric conditions. In order for the neurons in the PFC to work properly, their electrical abilities must be intact as neurons’ core function of communication is a product of their ability to conduct an electrical current.

Changes in gene expression over time
The colors of the charts represent changes in the expression of the genes listed on the left side of the charts. Blue is less expression and the shifts into yellows and reds is increased expression. The charts showcase the changes in gene expression over time as the studied neurons matured.

Using brain tissue from non-human primates at various stages of prenatal development, the team collected thousands of neurons from the PFC and gathered information on each individual cell’s electrical activity, physical structure, and gene expression. This resulted in massive sets of complex data. Daifeng Wang and his lab worked to build algorithms that would be capable of not only analyzing the data but illuminating the larger picture of the overall maturation process.

“We had multiple data types, such as gene expression and electrophysiology, along with more information about the cells. Integrating all of this data was not trivial and required sophisticated computational analysis such as using machine learning and AI approaches,” Wang says. “My lab developed a pipeline to integrate these data types and deliver biologically meaningful cell clusters, dynamic patterns of developmental gene expression, and regulatory networks.”

The wealth of accumulated data combined with Wang and his lab’s computational analysis skills, created a unique perspective into the neurons’ maturation journey. “One of the key points of this study is that because we had all of this single cell data, we could match gene expression profiles exactly to different developmental stages,” says Yu Gao, PhD, scientist in Zhao’s lab and first author of the study. This allowed the team to identify hundreds of genes involved in the maturation process – many of them previously unknown – and to map how these genes interact over time in relation to developing electrophysiological traits.

One of the study’s most surprising and striking findings was that different electrophysiological traits mature at different rates inside of a single cell. Some develop steadily, while others follow more complex, non-linear patterns. “This dynamic change seen in each feature has never been shown before,” says Xinyu Zhao. “And because we can correlate individual cells with gene expression, we can determine which genes are involved with each maturation state.”

After testing the validity of their data collection and analysis system and finding it to be strong, the team decided to try it out on a gene that is known to be associated with autism – CHD8. Neurons with knocked down CHD8 showed distinct physical immaturities when compared with other neurons. “Even some of their electrophysiological properties looked more immature,” Sousa says. This reinforced not only the team’s methods but the association between CHD8 and autism.

While this study revealed much it also starkly showed how much researchers do not know. The potential evolution of this work is vast. “We found so many genes. CHD8 is just one of them and most of them are not well studied,” Chang says. The team of labs is already working on a way to systematically study the novel genes that were revealed. “And we need to study what happens mechanistically,” Sousa says. “We don’t know molecularly what is happening beyond which genes are involved.” This platform also has the potential to study any gene of interest, creating opportunities for research beyond the Waisman Center and Madison.

Alongside the novel results of the study, this work illuminates the importance of interdisciplinary collaboration between scientists and labs. This paper and its findings would not have been possible without the knowledge of each of the four labs.

Color coded neurons.
Color coded neurons. The red and yellow neurons are neurons with CHD8 knocked down. The green are control neurons with normal CHD8 expression.

Zhao’s lab brings expertise in disease modeling. “And Yu Gao in my lab is an incredible scientist. He is just a tour de force,” Zhao says. Sousa’s lab brings a deep knowledge of functional genomics and brain development. Chang’s lab are experts in electrophysiology. “Qiping Dong (PhD, scientist, co-first author) in Chang’s lab is an extremely talented electrophysiologist,” Sousa says. And Daifeng Wang’s lab, particularly Kalpana Hanthanan Arachchilage, PhD, postdoctoral fellow in Wang’s lab and co-first author, brings the skill and ability to analyze such massive sets of data.

Sousa and Wang are also part of a cluster of faculty members brought in to Waisman specifically to study functional genetics and genomics of neurodevelopmental and neurodegenerative diseases. The sample distribution program of the Wisconsin Nonhuman Primate Research Center (WNPRC) at UW-Madison, directed by Jon Levine, PhD, director of WNPRC and professor of neuroscience, was also essential for the success of this project.

The Waisman Center is intentionally designed to facilitate close relationships between researchers to create opportunities for larger scale and broader reaching work like this. “When you combine all of it together,” Sousa say, “it works out pretty well.”

 


This work was supported by the National Institutes of Health (R01MH118827, R01MH116582, R01MH136152, R01NS138268, and R01NS105200 to X.Z.; R01HD064743 to Q.C; R01NS064025, R01AG067025, and RF1MH128695 to D.W; 1R01HD106197 to A.M.M.S; UM1MH130991 to A.M.M.S. and J.E.L.; P51 OD011106 to WNPRC; P50HD105353 to Waisman Center; and R24HD000836 to BDRL). Further support was provided by the National Science Foundation Career Award (2144475 to D.W.), DOD IIRA grant (X.Z.), SFARI pilot grant (X.Z., A.M.M.S., Q.C., and D.W.), Jenni and Kyle Professorship, Kellet Mid-Career Award, and Vilas Distinguished Achievement Professorship (X.Z.), Brain and Behavior Research Foundation (29721 to A.M.M.S.), Brain Research Foundation (BRFSG-2023-11 to A.M.M.S.), the Medical Scientist Training Program T32 (GM140935) and the Morse Society Fellowship to R.D.R., R36MH136790 (to S.O.S), and the Warren Alpert Distinguished Scholarship (to Y.Guo).