By Charlene N. Rivera-Bonet | Waisman Science Writer
Our brain is big on team work makes the dream work. Not only brain cells, but even smaller units that make up a cell work in cooperation to make the brain work properly. A new study done by Waisman Center investigators, published in Communications Biology, developed a computational framework to identify genes that work together to regulate the function and development of brain cells important for neuron-to-neuron communication called oligodendrocytes.
Oligodendrocytes are glial cells – or neuron-supporting cells – in charge of creating myelin, a fatty substance that wraps around neurons to allow faster and more efficient communication. When oligodendrocytes or myelin do not work properly, it can lead to disorders of the nervous system. With this study, the Waisman investigators wanted to understand how gene regulatory proteins known as transcription factors pair up and work together to regulate gene expression in oligodendrocytes.
In order to develop from progenitor cells, oligodendrocytes’ gene expression is controlled by transcription factors. These are in charge of turning genes on or off at specific times and locations. Previous research by the lab of Daifeng Wang, PhD, associate professor of biostatistics and medical informatics and computer sciences, looked at how individual transcription factors bind DNA to control individual target genes involved in various brain cell types including oligodendrocytes.
This new study by Wang’s lab takes it one step further by looking into how transcription factors work together to regulate genes in oligodendrocytes. The ultimate goal of this research is creating a regulatory map that gives a more complete picture of how oligodendrocytes make myelin and how the process can be affected by disease-causing mutations in the DNA.
The challenge: it would take a large amount of data to create this map. “To figure out how that’s wired is a major problem,” says John Svaren, PhD, Vilas Distinguished Achievement Professor of Comparative Biosciences and co-author of the study. Part of the solution is coTF-reg, an analytical framework that identifies pairs of transcription factors that work together to regulate target genes developed by Jerome Choi, doctoral student in population health sciences in the Wang lab. In 2024, Jerome was awarded the Wisconsin Distinguished Graduate Student Fellowship by Friends of the Waisman Center.
Using coTF-reg to integrate two different types of single-cell sequencing data (scRNA-seq and scATAC-seq), the group identified cooperative pairs of transcription factors that bound to the same region of the DNA involved in oligodendrocyte gene regulation. CoTF-reg includes a deep learning model – a form of artificial intelligence that can extract characteristics, features, and relationships from large amounts of data to make accurate predictions.
Once they identified the cooperative transcription factors, they used their expression levels to predict the expression of each target gene they regulate together using the deep learning model. “Once we learn such a predictive function, we can zoom in the deep learning prediction and prioritize which transcription factors are important for prediction for each gene,” Wang says.
The computational pipeline coTF-reg is publicly available and can be used with other types of cells in addition to oligodendrocytes. “It’s pretty flexible. [Other scientists] can bring their own data for different cell types,” Choi says.
“One of the issues in the brain is that there’s a lot of heterogeneity. Even within a cell type like oligodendrocytes, they’re not all the same,” Svaren says. The framework of coTF-reg allows researchers to look at each single cell to figure out what parts of the genome are regulatory elements and how they influence target gene expression. “This approach was only made possible by the coTF-reg framework and the databases that are available. But it’s a lot of data, and you have to be very creative to come up with methods like Jerome did to try to assemble that into a regulatory network,” Svaren explains.
The collaboration between the Wang and Svaren labs brings in perspectives and expertise from different fields to answer one scientific question. The Wang lab focuses on the computational aspect and the development of these programs that are able to integrate large amounts of biological data that would otherwise be near impossible to analyze. Svaren, whose research focus is the regulation of myelination, brings in the biological context. “We have to work with John to see if our prediction makes sense or not,” Wang says. “I think this is a great example in terms of Waisman collaboration.”
The team plans to continue optimizing coTF-reg to make better and more accurate predictions. They also hope to be able to use this type of data to help interpret whole genome data that comes from patients with white matter disorders affecting oligodendrocytes.
| Your support makes a difference. Donate now to advance knowledge about human development, developmental disabilities, and neurodegenerative diseases through research, services, training, and community outreach. | DONATE NOW |