Detection of fusion transcripts and their genomic breakpoints from RNA sequencing data
Hoogstrate, Y.; Komor, M. A.; Böttcher, R.; van Riet, J.; van de Werken, H. J. G.; van Lieshout, S.; Hoffmann, R.; van den Broek, E.; Bolijn, A. S.; Dits, N.; Sie, D.; van der Meer, D.; Pepers, F.; Bangma, C. H.; van Leenders, A. J. H. L.; Smid, M.; French, P. J.; Martens, J. W. M.; van Workum, W.; van der Spek, P. J.; Janssen, B.; Caldenhoven, E.; Rausch, C.; de Jong, M.; Stubbs, A. P.; Meijer, G. A.; Fijneman, R. J. A.; Jenster, G.
Show abstract
Spliced fusion-transcripts are typically identified by RNA-seq without elucidating the causal genomic breakpoints. However, non poly(A)-enriched RNA-seq contains large proportions of intronic reads spanning also genomic breakpoints. Using 1.274 RNA-seq samples, we investigated what additional information is embedded in non poly(A)-enriched RNA-seq data. Here, we present our novel, graph-based, Dr. Disco algorithm that makes use of both intronic and exonic RNA-seq reads to identify not only fusion transcripts but also genomic breakpoints in gene but also in intergenic regions. Dr. Disco identified TMPRSS2-ERG fusions with genomic breakpoints and other transcribed rearrangements from multiple RNA-sequencing cohorts. In breast cancer and glioma samples Dr. Disco identified rearrangement hotspots near CCND1 and MDM2 and could directly associate this with increased expression. A comparison with matched DNA-sequencing revealed that most genomic breakpoints are not, or minimally, transcribed while also revealing highly expressed translocations missed by DNA-seq. By using the full potential of non poly(A)-enriched RNA-seq data, Dr. Disco can reliably identify expressed genomic breakpoints and their transcriptional effects.
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