title: InFusion: Advancing Discovery of Fusion Genes and Chimeric Transcripts from Deep RNA-Sequencing Data.
abstract: Analysis of fusion transcripts has become increasingly important due to their link with cancer development. Since high-throughput sequencing approaches survey fusion events exhaustively, several computational methods for the detection of gene fusions from RNA-seq data have been developed. This kind of analysis, however, is complicated by native trans-splicing events, the splicing-induced complexity of the transcriptome and biases and artefacts introduced in experiments and data analysis. There are a number of tools available for the detection of fusions from RNA-seq data; however, certain differences in specificity and sensitivity between commonly used approaches have been found. The ability to detect gene fusions of different types, including isoform fusions and fusions involving non-coding regions, has not been thoroughly studied yet. Here, we propose a novel computational toolkit called InFusion for fusion gene detection from RNA-seq data. InFusion introduces several unique features, such as discovery of fusions involving intergenic regions, and detection of anti-sense transcription in chimeric RNAs based on strand-specificity. Our approach demonstrates superior detection accuracy on simulated data and several public RNA-seq datasets. This improved performance was also evident when evaluating data from RNA deep-sequencing of two well-established prostate cancer cell lines. InFusion identified 26 novel fusion events that were validated in vitro, including alternatively spliced gene fusion isoforms and chimeric transcripts that include intergenic regions. The toolkit is freely available to download from http:/bitbucket.org/kokonech/infusion.
authors.affiliation: Department of Molecular Biology, Max Planck Institute for Infection Biology, Berlin, Germany.
authors.forename: Konstantin
authors.initials: K
authors.lastname: Okonechnikov
authors.affiliation: Department of Molecular Biology, Max Planck Institute for Infection Biology, Berlin, Germany.
authors.forename: Aki
authors.initials: A
authors.lastname: Imai-Matsushima
authors.affiliation: Lexogen GmbH, Campus Vienna Biocenter 5, Vienna, Austria.
authors.forename: Lukas
authors.identifier: http://orcid.org/0000-0001-9410-4078
authors.initials: L
authors.lastname: Paul
authors.affiliation: Lexogen GmbH, Campus Vienna Biocenter 5, Vienna, Austria.
authors.forename: Alexander
authors.initials: A
authors.lastname: Seitz
authors.affiliation: Department of Molecular Biology, Max Planck Institute for Infection Biology, Berlin, Germany.
authors.forename: Thomas F
authors.initials: TF
authors.lastname: Meyer
authors.affiliation: Department of Molecular Biology, Max Planck Institute for Infection Biology, Berlin, Germany.
authors.forename: Fernando
authors.initials: F
authors.lastname: Garcia-Alcalde
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D050939:Gene Fusion / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D009369:Neoplasms / Q000235:genetics; D015514:Oncogene Proteins, Fusion / Q000235:genetics* / Q000302:isolation & purification; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software; D059467:Transcriptome / Q000235:genetics
chemical_list: D015514:Oncogene Proteins, Fusion