Gene Fusion Detection and Characterization in Long-Read Cancer Transcriptome Sequencing Data with FusionSeeker

Gene fusions are prevalent in a wide array of cancer types with different frequencies. Long-read transcriptome sequencing tech-nologies, such as PacBio, Iso-Seq, and Nanopore direct RNA sequencing, provide full-length transcript sequencing reads, which could facilitate detection of gene fusions. In this work, we developed a method, FusionSeeker, to comprehensively char-acterize gene fusions in long-read cancer transcriptome data and reconstruct accurate fused transcripts from raw reads. Fusion-Seeker identified gene fusions in both exonic and intronic regions, allowing comprehensive characterization of gene fusions in cancer transcriptomes. Fused transcript sequences were recon-structed with FusionSeeker by correcting sequencing errors in the raw reads through partial order alignment algorithm. Using these accurate transcript sequences, FusionSeeker refined gene fusion breakpoint positions and predicted breakpoints at single bp resolution. Overall, FusionSeeker will enable users to discover gene fusions accurately using long-read data, which can facilitate downstream functional analysis as well as improved cancer diag-nosis and treatment. Significance: FusionSeeker is a new method to discover gene fusions and reconstruct fused transcript sequences in long-read cancer transcriptome sequencing data to help identify novel gene fusions important for tumorigenesis and progression.

Automated summary

In this study, a method called FusionSeeker was developed to comprehensively detect gene fusions and reconstruct accurate fused transcript sequences from long-read data. FusionSeeker can precisely locate gene fusion breakpoints and predict breakpoints at single base resolution, facilitating the discovery of novel gene fusions important for tumor development and progression.