Comparison of Poly(A) capture versus Ribosomal RNA depletion methods for RNA-seq
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: S-ECPF-GEOD-51783 | BioStudies |
REPOSITORIES: biostudies
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Project description:Methods: RNA-sequencing was performed on matched samples obtained across several different gene expression measurement methods including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN. We also assayed the matched samples with Agilent microarray. RNA-seq data was compared on the rRNA-removal efficiency, genome profile, library complexity, coverage uniformity and quantitative cosinstency across protocols and with microarray data. Results: Compared to mRNA-seq, Ribo-zero provides equivalent percentage of rRNA component, genome-based mapped reads, and consistent quantification of transcripts. Moreover, Ribo-zero and DSN protocols achieve concordant transcript profiling in FFPE samples, and provide substantially more information on non-poly(A) RNA, which cannot be captured by mRNA-seq. Therefore, our study provides evidence that RNA-sequencing can generate accurate and reproducible transcript quantification using FFPE tissues. mRNA profile of 11 breast tumors were assayed by Agilent microarray, and by RNA-sequencing on libraries including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN, using Illunia HiSeq2000 2x50bp. RNA-Seq raw data is to be made available through dbGaP (controlled access) due to patient privacy concerns: http://www.ncbi.nlm.nih.gov/gap/?term=phs000676
| E-GEOD-51783 | BioStudies
Project description:RNA 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.To 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.Our 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.
| S-EPMC4070569 | BioStudies
Project description:Methods: RNA-sequencing was performed on matched samples obtained across several different gene expression measurement methods including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN. We also assayed the matched samples with Agilent microarray. RNA-seq data was compared on the rRNA-removal efficiency, genome profile, library complexity, coverage uniformity and quantitative cosinstency across protocols and with microarray data. Results: Compared to mRNA-seq, Ribo-zero provides equivalent percentage of rRNA component, genome-based mapped reads, and consistent quantification of transcripts. Moreover, Ribo-zero and DSN protocols achieve concordant transcript profiling in FFPE samples, and provide substantially more information on non-poly(A) RNA, which cannot be captured by mRNA-seq. Therefore, our study provides evidence that RNA-sequencing can generate accurate and reproducible transcript quantification using FFPE tissues. mRNA profile of 11 breast tumors were assayed by Agilent microarray, and by RNA-sequencing on libraries including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN, using Illunia HiSeq2000 2x50bp. RNA-Seq raw data is to be made available through dbGaP (controlled access) due to patient privacy concerns: http://www.ncbi.nlm.nih.gov/gap/?term=phs000676
2014-08-20 | E-GEOD-51783 | ArrayExpress
Project description:Methods: RNA-sequencing was performed on matched samples obtained across several different gene expression measurement methods including: (a) fresh-frozen (FF) RNA samples by mRNA-seq, Ribo-zero and DSN and (b) FFPE samples by Ribo-zero and DSN. We also assayed the matched samples with Agilent microarray. RNA-seq data was compared on the rRNA-removal efficiency, genome profile, library complexity, coverage uniformity and quantitative cosinstency across protocols and with microarray data. Results: Compared to mRNA-seq, Ribo-zero provides equivalent percentage of rRNA component, genome-based mapped reads, and consistent quantification of transcripts. Moreover, Ribo-zero and DSN protocols achieve concordant transcript profiling in FFPE samples, and provide substantially more information on non-poly(A) RNA, which cannot be captured by mRNA-seq. Therefore, our study provides evidence that RNA-sequencing can generate accurate and reproducible transcript quantification using FFPE tissues.
2014-08-20 | GSE51783 | GEO
Project description:Formalin-fixed paraffin-embedded (FFPE) tissue samples are routinely archived in the course of patient care and can be linked to clinical outcomes with long-term follow-up. However, FFPE tissues have degraded RNA which poses challenges for analyzing gene expression. Next-generation sequencing (NGS) is rapidly becoming accepted as an effective tool for measuring gene expressions for research and clinical use. However, the feasibility of NGS has not been firmly established when using FFPE tissue.We optimized strategies for whole transcriptome sequencing (RNA-seq) using FFPE tissue. Ribosomal RNA (rRNA) was successfully depleted by competitive hybridization using the Ribo-zero™ Kit (Epicentre Biotechnologies), and rRNA sequence content was less than one percent for each library. Gene expression measured by FFPE RNA-seq was compared to two different standards: RNA-seq from fresh frozen (FF) tissue and quantitative PCR (qPCR). Both FF and FFPE tumors were sequenced on an Illumina Genome Analyzer IIX with an average of 10 million reads. The distribution of FPKMs (fragments per kilobase of exon per million fragments mapped) and number of detected genes were similar between FFPE and FF. RNA-seq expressions from FF and FFPE samples from the same renal cell carcinoma (RCC) correlated highly (r = 0.919 for tumor 1 and r = 0.954 for tumor 2). On hierarchical cluster analysis, samples clustered by patient identity rather than method of preservation. TaqMan qPCR of 424 RCC-related genes correlated highly with FFPE RNA-seq expressions (r = 0.775 for FFPE tumor 1, r = 0.803 for FFPE tumor 2). Expression fold changes were considered, to assess biologic relevance of gene expressions. Expression fold changes between FFPE tumors (tumor 1/tumor 2) correlated well when comparing qPCR and RNA-seq (r = 0.890). Expression fold changes between tumors from different risk groups (our high risk RCC/The Cancer Genome Atlas, TCGA, low risk RCC) also correlated well when comparing RNA-seq from FF and FFPE tumors (r = 0.887).FFPE RNA-seq provides reliable genes expression data, comparable to that obtained from fresh frozen tissue. It represents a useful tool for discovery and validation of biomarkers.
| S-EPMC4298956 | BioStudies
Project description:BACKGROUND:The main bottleneck for genomic studies of tumors is the limited availability of fresh frozen (FF) samples collected from patients, coupled with comprehensive long-term clinical follow-up. This shortage could be alleviated by using existing large archives of routinely obtained and stored Formalin-Fixed Paraffin-Embedded (FFPE) tissues. However, since these samples are partially degraded, their RNA sequencing is technically challenging. RESULTS:In an effort to establish a reliable and practical procedure, we compared three protocols for RNA sequencing using pairs of FF and FFPE samples, both taken from the same breast tumor. In contrast to previous studies, we compared the expression profiles obtained from the two matched sample types, using the same protocol for both. Three protocols were tested on low initial amounts of RNA, as little as 100 ng, to represent the possibly limited availability of clinical samples. For two of the three protocols tested, poly(A) selection (mRNA-seq) and ribosomal-depletion, the total gene expression profiles of matched FF and FFPE pairs were highly correlated. For both protocols, differential gene expression between two FFPE samples was in agreement with their matched FF samples. Notably, although expression levels of FFPE samples by mRNA-seq were mainly represented by the 3'-end of the transcript, they yielded very similar results to those obtained by ribosomal-depletion protocol, which produces uniform coverage across the transcript. Further, focusing on clinically relevant genes, we showed that the high correlation between expression levels persists at higher resolutions. CONCLUSIONS:Using the poly(A) protocol for FFPE exhibited, unexpectedly, similar efficiency to the ribosomal-depletion protocol, with the latter requiring much higher (2-3 fold) sequencing depth to compensate for the relative low fraction of reads mapped to the transcriptome. The results indicate that standard poly(A)-based RNA sequencing of archived FFPE samples is a reliable and cost-effective alternative for measuring mRNA-seq on FF samples. Expression profiling of FFPE samples by mRNA-seq can facilitate much needed extensive retrospective clinical genomic studies.
| S-EPMC5977534 | BioStudies
Project description:Transcriptome profiling can provide information of great value in clinical decision-making, yet RNA from readily available formalin-fixed paraffin-embedded (FFPE) tissue is often too degraded for quality sequencing. To assess the clinical utility of FFPE-derived RNA, we performed ribo-deplete RNA extractions on?>?3200 FFPE slide samples; 25 of these had direct FFPE vs. fresh frozen (FF) replicates, 57 were sequenced in 2 different labs, 87 underwent multiple library analyses, and 16 had direct microdissected vs. macrodissected replicates. Poly-A versus ribo-depletion RNA extraction methods were compared using transcriptomes of TCGA cohort and 3116 FFPE samples. Compared to FF, FFPE transcripts coding for nuclear/cytoplasmic proteins involved in DNA packaging, replication, and protein synthesis were detected at lower rates and zinc finger family transcripts were of poorer quality. The greatest difference in extraction methods was in histone transcripts which typically lack poly-A tails. Encouragingly, the overall sequencing success rate was 81%. Exome coverage was highly concordant in direct FFPE and FF replicates, with 98% agreement in coding exon coverage and a median correlation of whole transcriptome profiles of 0.95. We provide strong rationale for clinical use of FFPE-derived RNA based on the robustness, reproducibility, and consistency of whole transcriptome profiling.
| S-EPMC7572424 | BioStudies
Project description:RNA-sequencing (RNA-seq) provides a comprehensive quantification of transcriptomic activities in biological samples. Formalin-Fixed Paraffin-Embedded (FFPE) samples are collected as part of routine clinical procedure, and are the most widely available biological sample format in medical research and patient care. Normalization is an essential step in RNA-seq data analysis. A number of normalization methods, though developed for RNA-seq data from fresh frozen (FF) samples, can be used with FFPE samples as well. The only extant normalization method specifically designed for FFPE RNA-seq data, MIXnorm, which has been shown to outperform the normalization methods, but at the cost of a complex mixture model and a high computational burden. It is therefore important to adapt MIXnorm for simplicity and computational efficiency while maintaining superior performance. Furthermore, it is critical to develop an integrated tool that performs commonly used normalization methods for both FF and FFPE RNA-seq data. We developed a new normalization method for FFPE RNA-seq data, named SMIXnorm, based on a simplified two-component mixture model compared to MIXnorm to facilitate computation. The expression levels of expressed genes are modeled by normal distributions without truncation, and those of non-expressed genes are modeled by zero-inflated Poisson distributions. The maximum likelihood estimates of the model parameters are obtained by a nested Expectation-Maximization algorithm with a less complicated latent variable structure, and closed-form updates are available within each iteration. Real data applications and simulation studies show that SMIXnorm greatly reduces computing time compared to MIXnorm, without sacrificing the performance. More importantly, we developed a web-based tool, <i>RNA-seq Normalization (RSeqNorm)</i>, that offers a simple workflow to compute normalized RNA-seq data for both FFPE and FF samples. It includes SMIXnorm and MIXnorm for FFPE RNA-seq data, together with five commonly used normalization methods for FF RNA-seq data. Users can easily upload a raw RNA-seq count matrix and select one of the seven normalization methods to produce a downloadable normalized expression matrix for any downstream analysis. The R package is available at https://github.com/S-YIN/RSEQNORM. The web-based tool, <i>RSeqNorm</i> is available at http://lce.biohpc.swmed.edu/rseqnorm with no restriction to use or redistribute.
| S-EPMC8024626 | BioStudies
Project description:Triple negative breast cancer (TNBC) is a heterogeneous disease that lacks unifying molecular alterations that can guide therapy decisions. We previously identified distinct molecular subtypes of TNBC (TNBCtype) using gene expression data generated on a microarray platform using frozen tumor specimens. Tumors and cell lines representing the identified subtypes have distinct enrichment in biologically relevant transcripts with differing sensitivity to standard chemotherapies and targeted agents. Since our initial discoveries, RNA-sequencing (RNA-seq) has evolved as a sensitive and quantitative tool to measure transcript abundance.To demonstrate that TNBC subtypes were similar between platforms, we compared gene expression from matched specimens profiled by both microarray and RNA-seq from The Cancer Genome Atlas (TCGA). In the clinical care of patients with TNBC, tumor specimens collected for diagnostic purposes are processed by formalin fixation and paraffin-embedding (FFPE). Thus, for TNBCtype to eventually have broad and practical clinical utility we performed RNA-seq gene expression and molecular classification comparison between fresh-frozen (FF) and FFPE tumor specimens.Analysis of TCGA showed consistent subtype calls between 91% of evaluable samples demonstrating conservation of TNBC subtypes across microarray and RNA-seq platforms. We compared RNA-seq performed on 21-paired FF and FFPE TNBC specimens and evaluated genome alignment, transcript coverage, differential transcript enrichment and concordance of TNBC molecular subtype calls. We demonstrate that subtype accuracy between matched FF and FFPE samples increases with sequencing depth and correlation strength to an individual TNBC subtype.TNBC subtypes were reliably identified from FFPE samples, with highest accuracy if the samples were less than 4 years old and reproducible subtyping increased with sequencing depth. To reproducibly subtype tumors using gene expression, it is critical to select genes that do not vary due to platform type, tissue processing or RNA isolation method. The majority of differentially expressed transcripts between matched FF and FFPE samples could be attributed to transcripts selected for by RNA enrichment method. While differentially expressed transcripts did not impact TNBC subtyping, they will provide guidance on determining which transcripts to avoid when implementing a gene set size reduction strategy.NCT00930930 07/01/2009.
| S-EPMC5379658 | BioStudies
Project description:RNA-seq by poly(A) selection is currently the most common protocol for whole transcriptome sequencing as it provides a broad, detailed, and accurate view of the RNA landscape. Unfortunately, the utility of poly(A) libraries is greatly limited when the input RNA is degraded, which is the norm for research tissues and clinical samples, especially when specimens are formalin-fixed. To facilitate the use of RNA sequencing beyond cell lines and in the clinical setting, we developed an exome-capture transcriptome protocol with greatly improved performance on degraded RNA. Capture transcriptome libraries enable measuring absolute and differential gene expression, calling genetic variants, and detecting gene fusions. Through validation against gold-standard poly(A) and Ribo-Zero libraries from intact RNA, we show that capture RNA-seq provides accurate and unbiased estimates of RNA abundance, uniform transcript coverage, and broad dynamic range. Unlike poly(A) selection and Ribo-Zero depletion, capture libraries retain these qualities regardless of RNA quality and provide excellent data from clinical specimens including formalin-fixed paraffin-embedded (FFPE) blocks. Systematic improvements across key applications of RNA-seq are shown on a cohort of prostate cancer patients and a set of clinical FFPE samples. Further, we demonstrate the utility of capture RNA-seq libraries in a patient with a highly malignant solitary fibrous tumor (SFT) enrolled in our clinical sequencing program called MI-ONCOSEQ. Capture transcriptome profiling from FFPE revealed two oncogenic fusions: the pathognomonic NAB2-STAT6 inversion and a therapeutically actionable BRAF fusion, which may drive this specific cancer's aggressive phenotype.
| S-EPMC4561495 | BioStudies