RNA-Seq: opportunities, limitations and applications in cancer research

Alexander Schramm1, Marcel Martin2, Johannes H. Schulte1, Johannes Köster2, Pieter Mestdagh3, Jo Vandesompele3, Sven Rahmann2,4
1University Hospital Essen, Pediatric Oncology, Germany; 2TU Dortmund, Dept. of Computer Science, LS11, Germany; 3Center for Medical Genetics Ghent, Belgium; 4University Hospital Essen, Genome Informatics, Germany

Next generation RNA sequencing allows for the detection of aberrantly expressed transcripts associated with cancer biology and outcome, thus enabling the identification of biomarkers and therapy targets on transcriptome level. Additionally, using both high-throughput sequencing and quantitative real-time PCR, the transcriptome can be analyzed in complementary ways. In two pilot studies, we could demonstrate that deep sequencing of both mRNA and miRNA allows for pathway and pattern identification using the embryonal tumor, neuroblastoma, as a model system. We have established the necessary bioinformatics pipeline, including software tools, and key methodological steps in the process, such as adapter removal, read mapping, normalization, and multiple testing issues for biomarker identification. The computational pipeline for obtaining a ranked list of differentially expressed miRNAs from the raw sequence reads was also standardised and methods for comparison of NGS and qPCR data have been implemented. Fundamental challenges involving estimation of expression values from short RNA reads as well as mapping of short reads will be discussed.

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