Researchers at the Massachusetts Institute of Technology (MIT) have introduced a groundbreaking framework called KATMAP, designed to enhance the understanding of gene splicing and predict regulatory activities of splicing factors. Published in the journal Nature Biotechnology on November 4, 2025, this innovative approach enables scientists to interpret how different gene segments can be combined to produce a diverse array of proteins, essential for the functioning of various cell types.
Gene splicing is a critical biological process that allows cells to utilize the same DNA instructions in varied ways, depending on the cell’s needs. The process hinges on splicing factors, which influence how genes are expressed. KATMAP, short for Knockdown Activity and Target Models from Additive regression Predictions, utilizes experimental data to identify which sequences interact with specific splicing factors and predict their targets. This capability is particularly valuable for understanding how splicing mutations can lead to diseases, including cancer.
KATMAP’s development stems from a collaboration within the MIT Department of Biology. According to first author Michael P. McGurk, a postdoctoral researcher in the lab of Professor Christopher Burge, previous models often provided only an average picture of splicing regulation. In contrast, KATMAP focuses on specific exons in particular genes, offering a more granular analysis of splicing factor regulation.
By leveraging RNA sequencing data from perturbation experiments, where the expression of splicing factors is manipulated, KATMAP can reveal how these changes affect splicing outcomes. This method distinguishes between direct targets of splicing factors and indirect effects by considering the presence of binding sites—specific regions where splicing factors are likely to exert their influence.
McGurk emphasizes the importance of making KATMAP an interpretable model, stating, “I don’t just want to predict things, I want to explain and understand.” This transparency allows researchers to generate hypotheses and analyze splicing patterns in relation to regulatory factors, while also clarifying how predictions are derived.
The model does have limitations; it currently examines one splicing factor at a time, even though splicing factors often work together. Nonetheless, KATMAP serves as a foundational tool for future research. McGurk and his team plan to expand the model to account for cooperative interactions among splicing factors, enhancing its predictive capabilities.
Looking ahead, the Burge lab is collaborating with the Dana-Farber Cancer Institute to explore how splicing factors may be altered in disease contexts. Furthermore, McGurk aims to adapt KATMAP to address splicing regulation in response to stress, broadening its applicability in both health and disease research.
As noted by Burge, who holds the title of Uncas (1923) and Helen Whitaker Professor, KATMAP represents a significant advancement in the study of gene regulation. “We now have a tool that can learn the pattern of activity of a splicing factor from types of data that can be readily generated for any factor of interest,” he states. This capability will facilitate the identification of splicing factors that exhibit altered activity in various disease states, offering promising avenues for therapeutic intervention.
The full study can be accessed in Nature Biotechnology, providing essential insights for researchers and clinicians alike in the quest to understand the complexities of gene splicing and its implications for human health.
