Abstract 1845: Development of a quantitative targeted RNA-Seq methodology for use in differential gene expression analysis

Abstract RNA Sequencing (RNA-Seq) uses the capabilities of Next Generation high-throughput sequencing (NGS) methods to provide insight into the transcriptome of a cell as it generates millions of reads. Whole transcriptome sequencing can be used to quantify gene expression on a transcriptome-wide scale, identify splice variants, quantify allele specific expression, and characterize fusion transcripts. Development of a highly reproducible and sensitive targeted quantitative sequencing method would aid in facilitating a deeper understanding and characterization of the roles of a specific set of genes, while enabling much higher sample throughput and significant cost savings relative to whole-transcriptome sequencing. In this study, we report a targeted RNA-Seq technology, QIAseq RNA, which makes use of several methodologies to deliver an extremely flexible, highly precise tool for characterizing gene expression. QIASeq RNA incorporates 12-base random molecular barcodes into each unique target strand which benefits quantifying gene expression in a given multiplexed sample. Counting the number of molecular tags allows one to determine the sequence coverage per target and adjust experimental conditions to use the read budget of any sequencing platform most efficiently. Using either the Illumina or Ion Torrent platforms, users can choose to multiplex up to 96 RNA samples from 12 to 1000-plex expression panels. No mRNA selection or rRNA removal or blocking is required. The entire protocol, from cDNA synthesis to finished library, which is ready for sequencing, can be accomplished in under one day. Custom assays for a specific target site can add the ability to distinguish between isoforms or identify allele specific expression. We explore the capabilities of this system by profiling large numbers of genes in a cell model system's response to small molecule treatment. Changes in gene expression by these treatments were measured by targeted RNA NGS, and fold-changes in gene expression due to chemical perturbation were characterized. Complex gene relationships in perturbed pathways were mapped using QIAGEN's Ingenuity Pathway Analysis (IPA) tool. The IPA tool also facilitated the elucidation of the impact of gene expression changes in the context of biological processes, molecular interactions, cellular phenotypes and disease. This article will provide application data for GRRC including a discussion of technical challenges faced when profiling large numbers of genes in a large cohort. Citation Format: Eric Lader, Melanie Hussong, Matthew Fosbrink. Development of a quantitative targeted RNA-Seq methodology for use in differential gene expression analysis. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1845.