Abstract 5332: Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench

Abstract

Abstract The now commonplace application of whole exome and genome sequencing in cancer research and diagnostics has allowed for rapid identification of SNPs and InDels in protein coding regions, but neither method is able to reveal situations of incomplete penetrance. That is, while possible cancer causing allele variants can be detected with these methods, this does not mean these alleles are actually expressed. Reasons for this are various and include epigenetic effects and changes, transcription regulation mechanisms, mRNA degradation and epistasis. By contrast, transcriptome sequencing (RNA-seq) can be used to identify the alleles being expressed. This method has the additional benefits of providing insight into the transcript expression levels, expressed allele isoforms and offers the possibility of identifying instances of fusion transcripts. Such knowledge about variants expressed in tumor cells is crucial for the identification of effective drug targets. Here, we illustrate the benefits of combining whole exome sequencing with RNA-seq by analyzing whole exome and RNA-seq datasets from uveal melanoma samples with our newly developed CLC Cancer Research Workbench. This software suite enables the complete analysis of both approaches, including variant calling, followed by the comparison of the called variants. The analysis will be carried out using user-friendly, automated workflows distributed with the CLC Cancer Research Workbench. In this work, we discuss and compare variants identified in the exome and RNA-seq datasets using our algorithms, and focus particularly on variants identified in the exome data that appear not to be expressed in the tumor samples. Citation Format: Anne Arens, Anne-Mette K. Hein, Uwe Appelt, Anika Joecker, Søren Mønsted, Bjarne Knudsen, Naomi Thomson, Richard Lussier, Cecilie Boysen, Roald Forsberg. Comparison of variant calling from whole exome and transcriptome sequencing using CLC Cancer Research Workbench. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5332. doi:10.1158/1538-7445.AM2014-5332