A novel analysis flow for fused transcripts discovery from paired-end RNA-SEQ data

Chimeric phenomena have been recently recognized to play a significant role in the investigation and understanding of the fundamental mechanisms behind highly diffused pathologies such as tumors. In this paper we present a new methodology for the detection of fusion transcript from Next Generation Sequencing (NGS) data. The methodology exploits short paired-end reads coming from RNA-Seq experiments to determine a list of fused genes and to exactly identify the fusion boundaries, so that the exact chimeric sequence can be analysed. Both known and unknown transcripts are considered, enabling the detection of fusions involving unannotated genes. An automated toolflow that reports a set of candidate fused genes and the associated junctions has been implemented and applied to a publicly available data set of melanoma.