RNA-Seq mapping and detection of gene fusions with a suffix array algorithm.

• Main Authors: Onur Sakarya, Heinz Breu, Milan Radovich, Yongzhi Chen, Yulei N Wang, Catalin Barbacioru, Sowmi Utiramerur, Penn P Whitley, Joel P Brockman, Paolo Vatta, Zheng Zhang, Liviu Popescu, Matthew W Muller, Vidya Kudlingar, Nriti Garg, Chieh-Yuan Li, Benjamin S Kong, John P Bodeau, Robert C Nutter, Jian Gu, Kelli S Bramlett, Jeffrey K Ichikawa, Fiona C Hyland, Asim S Siddiqui
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2012-01-01
• Series: PLoS Computational Biology
• Online Access: http://europepmc.org/articles/PMC3320572?pdf=render

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions-particularly those expressed with low abundance- is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software. We introduced new features including filter and junction mapping, annotation-aided pairing rescue and accurate mapping quality values. We combined this pipeline with a Suffix Array Spliced Read (SASR) aligner to detect chimeric transcripts. Performing paired-end RNA-Seq of the breast cancer cell line MCF-7 using the SOLiD system, we called 40 gene fusions among over 120,000 splicing junctions. We validated 36 of these 40 fusions with TaqMan assays, of which 25 were expressed in MCF-7 but not the Human Brain Reference. An intra-chromosomal gene fusion involving the estrogen receptor alpha gene ESR1, and another involving the RPS6KB1 (Ribosomal protein S6 kinase beta-1) were recurrently expressed in a number of breast tumor cell lines and a clinical tumor sample.