Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling

Abstract

BackgroundRNA sequencing (RNA-Seq) is often used for transcriptome profiling as well as the identification of novel transcripts and alternative splicing events. Typically, RNA-Seq libraries are prepared from total RNA using poly(A) enrichment of the mRNA (mRNA-Seq) to remove ribosomal RNA (rRNA), however, this method fails to capture non-poly(A) transcripts or partially degraded mRNAs. Hence, a mRNA-Seq protocol will not be compatible for use with RNAs coming from Formalin-Fixed and Paraffin-Embedded (FFPE) samples.ResultsTo address the desire to perform RNA-Seq on FFPE materials, we evaluated two different library preparation protocols that could be compatible for use with small RNA fragments. We obtained paired Fresh Frozen (FF) and FFPE RNAs from multiple tumors and subjected these to different gene expression profiling methods. We tested 11 human breast tumor samples using: (a) FF RNAs by microarray, mRNA-Seq, Ribo-Zero-Seq and DSN-Seq (Duplex-Specific Nuclease) and (b) FFPE RNAs by Ribo-Zero-Seq and DSN-Seq. We also performed these different RNA-Seq protocols using 10 TCGA tumors as a validation set.The data from paired RNA samples showed high concordance in transcript quantification across all protocols and between FF and FFPE RNAs. In both FF and FFPE, Ribo-Zero-Seq removed rRNA with comparable efficiency as mRNA-Seq, and it provided an equivalent or less biased coverage on gene 3′ ends. Compared to mRNA-Seq where 69% of bases were mapped to the transcriptome, DSN-Seq and Ribo-Zero-Seq contained significantly fewer reads mapping to the transcriptome (20-30%); in these RNA-Seq protocols, many if not most reads mapped to intronic regions. Approximately 14 million reads in mRNA-Seq and 45–65 million reads in Ribo-Zero-Seq or DSN-Seq were required to achieve the same gene detection levels as a standard Agilent DNA microarray.ConclusionsOur results demonstrate that compared to mRNA-Seq and microarrays, Ribo-Zero-Seq provides equivalent rRNA removal efficiency, coverage uniformity, genome-based mapped reads, and consistently high quality quantification of transcripts. Moreover, Ribo-Zero-Seq and DSN-Seq have consistent transcript quantification using FFPE RNAs, suggesting that RNA-Seq can be used with FFPE-derived RNAs for gene expression profiling.Electronic supplementary materialThe online version of this article (doi: 10.1186/1471-2164-15-419) contains supplementary material, which is available to authorized users.

The use of exome capture RNA-seq for highly degraded RNA with application to clinical cancer sequencing

“…Genes with higher expression levels in the capture libraries were identified as histones and small nucleolar RNAs ( Fig. 3B; Supplemental Table S1), which was reported for Ribo-Zero and DSN libraries (Miller et al 2013;Zhao et al 2014) and is explained by their unique biology: Histone mRNAs in metazoans are not polyadenylated (Yang et al 2011), while polyadenylation of snoRNAs is a signal for their degradation (LaCava et al 2005). A small number of genes were found to be underestimated in capture libraries.…”

“…Recently, targeted RNA sequencing was suggested as a method to comprehensively sample low-abundance isoforms (Mercer et al 2012;Halvardson et al 2013;Fu et al 2014) and even measure gene expression (Cabanski et al 2014). However, the recommendation of a novel transcriptome profiling protocol for routine use in a clinical or research setting requires careful examination of its relative merits on a wide range of metrics (Mullins et al 2007;Zeng and Mortazavi 2012;Adiconis et al 2013;Zhao et al 2014). It is critical that the recommended method is largely compatible with poly(A) RNA-seq and Ribo-Zero libraries as these are most commonly used for research and by The Cancer Genome Atlas (TCGA) (The Cancer Genome Atlas Research Network 2008).…”

Integrated RNA and DNA sequencing reveals early drivers of metastatic breast cancer

“…For DawnRank analyses, copy number levels greater than 0.25 were considered gains, and levels below -0.32 were considered losses (61). Because of bias in the FFPE and total RNA-seq data as compared with the mRNA-seq data, a normalization vector was calculated: previously published matched samples of fresh and FFPE RNA (63) sequenced at the UNC using mRNA-seq and total RNA-seq, respective-…”

Gene fusion detection in formalin-fixed paraffin-embedded benign fibrous histiocytomas using fluorescence in situ hybridization and RNA sequencing

“…[22][23][24][25][26] Furthermore, RNA-Seq on FFPE tissue has only rarely been used to detect gene fusions. 6,23,27 The study of Sweeney and co-workers is of particular interest in the present context, as they also investigated sarcomas (three synovial sarcomas, three MLS, two Ewing sarcomas, and one clear cell sarcoma), used Illumina equipment and kits, and had results similar to ours; 23 all their cases showed the expected gene fusions, although some of the samples had to be re-analyzed at greater depth or after depletion of ribosomal RNA before obtaining positive results.…”