Gene fusion detection and characterization in long-read cancer transcriptome sequencing data with FusionSeeker

Abstract Gene fusions are prevalent in a wide array of cancer types with different frequencies. Long-read transcriptome sequencing technologies, 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 characterize gene fusions in long-read cancer transcriptome data and reconstruct accurate fused transcripts from raw reads. FusionSeeker identified gene fusions in both exonic and intronic regions, allowing comprehensive characterization of gene fusions in cancer transcriptomes. Fused transcript sequences were reconstructed 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 basepair 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 diagnosis and treatment.