More than half of the human genome is made up of transposable elements, often called “jumping genes.” These sequences are usually inactive, but in cancer they can become active again and interfere with normal gene regulation. Understanding how they affect RNA processing is important for uncovering how cancers like glioblastoma develop and evolve.

Researchers at Brown University explored how transposable elements influence RNA behavior in glioblastoma stem cells. These cells are thought to drive tumor growth and resistance to therapy.

The team used long-read RNA sequencing to capture full-length RNA molecules, allowing them to see how genes are spliced and combined with transposable elements. They also used a technique called polysome profiling to determine which RNA molecules are actively being translated into proteins.

Schematic and Benchmarking of Fusion TE Reporter (FuTER)

(A) A schematic depicting the approach used by FuTER. (B) Benchmarking of FuTER using a simulated long read library containing normal transcripts, gene-gene fusions and gene-TE fusion transcripts demonstrates strong performance. Performance was tuned to maximize precision and minimize the risks of false positives.

Their findings showed that transposable elements are often located near splice sites, regions where RNA is cut and reassembled. When these elements are present, they increase the likelihood of alternative splicing, meaning a single gene can produce multiple RNA variants. This leads to a higher level of RNA diversity in cancer cells.

Importantly, these RNA changes are not just structural. The researchers found that transcripts influenced by transposable elements are more likely to associate with ribosomes, the cellular machinery that makes proteins. Different RNA variants showed distinct patterns, with shorter forms more often linked to single ribosomes and longer forms associated with multiple ribosomes, suggesting differences in how efficiently they are translated.

To better identify these complex RNA molecules, the team developed a new computational framework called FuTER. This tool detects fusion transcripts that combine gene sequences with transposable elements. Using this approach, they identified dozens of glioblastoma-specific RNA fusions, some of which appear to be actively translated into proteins.

Overall, the work highlights how transposable elements contribute to abnormal RNA processing and protein production in cancer. By combining RNA sequencing with advanced analytical tools, the researchers provide a clearer picture of how these genomic elements reshape gene expression and potentially drive tumor behavior.

Availability – FuTER wil be publicly available on a GitHub repository (https://github.com/mpizzagalli777/FuTER),