Abstract 429: Optimization of an RNA sequencing method for low-quantity degraded samples

Abstract

Abstract RNA-sequencing (RNA-seq) is an effective tool for gene expression analysis, promising to be a diagnostic tool for patient stratification and individualized therapy. However, it has been challenging to apply RNA-seq to low-quantity and degraded RNA derived from formalin fixed paraffin embedded clinical samples. The Illumina TruSeq® RNA Access approach, utilizing capture probes targeting known exons to enrich for coding RNAs, has shown high performance to profile poor quality RNA samples at input amounts at or above 20 ng. Here, we have further optimized the Illumina TruSeq® RNA Access method for samples with low quality and low quantity, and have compared results to those obtained with libraries prepared with SMARTer® Stranded Total RNA-Seq- Pico Input Kit. Libraries were prepared using 1 ng and 10 ng of degraded RNA from Banked FFPE liver specimens, and were compared to libraries prepared using the standard RNA Access method with an input of 100 ng. With the optimized low-input RNA Access method, the alignment rate was consistently high (95-97%) across both input amounts, with 82-84% of aligned reads mapped to the transcriptome. This is comparable to results obtained with the standard 100 ng input. Gene detection however, changed as a function of input, with ~ 15,900 genes detected at an input of 10 ng, and ~ 13,500 detected at 1 ng of input. In contrast, the SMARTer method detected a relatively constant number of genes (~ 14,500 genes) at both input amounts, albeit with a lower % aligned reads to transcriptome (46-47%), and an increased % reads aligned to Ribosomal RNA when compared to RNA Access. Thus, while both methods are capable of comparable levels of performance, the RNA Access method is more cost-effective from a sequencing standpoint. These characteristics were maintained across a group of additional FFPE-derived samples tested by both methods. Taken together, these results demonstrate that an optimized RNA Access method has consistent mapping performance and a high gene detection rate, and is thus suitable for the analysis of low-quantity degraded RNA. Citation Format: Dan Su, Jason G. Powers, Thomas A. Halsey, Patrick Hurban. Optimization of an RNA sequencing method for low-quantity degraded samples [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 429.