Abstract
Ataxia represents a heterogeneous group of neurodegenerative disorders characterized by a loss of balance and coordination, often resulting from mutations in genes vital for cerebellar function and maintenance. Recent advances in genomics have identified gene fusion events as critical contributors to various cancers and neurodegenerative diseases. However, their role in ataxia pathogenesis remains largely unexplored. Our study Hdelved into this possibility by analyzing RNA sequencing data from 1443 diverse samples, including cell and mouse models, patient samples, and healthy controls. We identified 7067 novel gene fusions, potentially pivotal in disease onset. These fusions, notably in-frame, could produce chimeric proteins, disrupt gene regulation, or introduce new functions. We observed conservation of specific amino acids at fusion breakpoints and identified potential aggregate formations in fusion proteins, known to contribute to ataxia. Through AI-based protein structure prediction, we identified topological changes in three high-confidence fusion proteins—TEN1-ACOX1, PEX14-NMNAT1, and ITPR1-GRID2—which could potentially alter their functions. Subsequent virtual drug screening identified several molecules and peptides with high-affinity binding to fusion sites. Molecular dynamics simulations confirmed the stability of these protein-ligand complexes at fusion breakpoints. Additionally, we explored the role of non-coding RNA fusions as miRNA sponges. One such fusion, RP11-547P4-FLJ33910, showed strong interaction with hsa-miR-504-5p, potentially acting as its sponge. This interaction correlated with the upregulation of hsa-miR-504-5p target genes, some previously linked to ataxia. In conclusion, our study unveils new aspects of gene fusions in ataxia, suggesting their significant role in pathogenesis and opening avenues for targeted therapeutic interventions.
Communicated by Ramaswamy H. Sarma
Acknowledgments
The authors are thankful for the technical assistance of Gamze Kırtoklu, Kasım Kaan Koca, and Necati Atalay. Graphical representations were generated using Microsoft Excel and GraphPad Prism version 9 to facilitate data visualization and analysis.
Author contributions
Conceptualization: O.G. conceived and designed the study. Data curation: O.G., E.O., M.T.O., and M.S.K. were responsible for collecting, managing and organizing the data. Investigation and formal analysis: O.G., E.O., M.T.O., and M.S.K. carried out the analyses. Methodology: O.G. developed the methodology, with input from U.H.T. Project administration: O.G. and U.H.T. coordinated the research project and ensured that everything ran smoothly. Resources: O.G. and U.H.T. provided key resources and research materials. Software: O.G., E.O., M.T.O., and M.S.K. contributed to the software used for data analyses. Supervision: O.G. provided oversight and leadership to the research activity planning and execution with input from U.H.T. Validation: All authors (O.G., E.O., M.T.O., and M.S.K., and U.H.T.) validated the data collection and analysis methods. Visualization: O.G., E.O., M.T.O., and M.S.K. created the visual representations of the data. Writing – original draft: All authors (O.G., E.O., M.T.O., and M.S.K., and U.H.T.) contributed on writing the first draft of the manuscript. Writing – review & editing: All authors (O.G., E.O., M.T.O., and M.S.K., and U.H.T.) reviewed, edited, and approved the final manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Data availability statement
All relevant data supporting the findings of this study are included within the article and its supplementary information files. The raw reads of the RNA-Seq datasets analyzed in this study, which are publicly available, can be accessed through the NCBI GEO accession codes listed in .