Comparison of poly(A) and capture RNA-seq: controlled degradation in vitro
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE64113 | GEO | 2015/08/03
SECONDARY ACCESSION(S): PRJNA270181
REPOSITORIES: GEO
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Project description:We compare the performance of two library preparation protocols (poly(A) and exome capture) in in vitro degraded RNA samples VcaP cell were grown, and treated with MDV3100 (enzalutamide) or DHT (dihydrotestosterone), intact RNA was isolated and samples were prepared in technical triplicates using two library preparation protocol. Also cells were subject to in vitro degradation through incubation of the whole cell lysate in 37C for increasing amounts of time. Following incbation paired capture and poly(A) libraries were prepared.
2015-08-03 | E-GEOD-64113 | biostudies-arrayexpress
Project description:Purpose: Popular methods for library preparation in RNA-seq such as Illumina TruSeq® RNA v2 kit use a poly-A pulldown strategy. Such methods can cause loss of coverage at the 5’ end of genes, impacting the ability to detect fusions when used on degraded samples. The goal of this study was to quantify the effects RNA degradation has on fusion detection when using poly-A selected mRNA and to identify the variables involved in this process Methods: Total RNA was extracted from solid tumor tissue and whole blood using the Qiagen® miRNeasy Micro and Mini kits, respectively. The KU812 cell line was purchased from Sigma-Aldrich (St. Louis, MO) and UHR (Universal Human Reference RNA) was purchased from Agilent (Santa Clara, CA). UHR is a mixture of cell lines derived from breast adenocarcinoma, hepatoblastoma, cervix adenocarcinoma, testis embryonal carcinoma, gliobastoma, melanoma, liposarcoma, histiocytic lymphoma, lymphoblastic leukemia and plasmocytoma. For Degradation experiments, two micrograms of human universal reference RNA (UHR) (Agilent Technologies, Santa Clara, CA) and 1ug of RNA extracted from KU812 cell line (purchased from ATCC) were degraded at 74oC from 1 to 11 minutes in 1 minute intervals, using the NEBNext® Magnesium RNA Fragmentation Module Kit (NEB, Ipswich, MA). RNA was then purified and concentrated with RNeasy MinElute Cleanup Kit (Qiagen, Valencia, CA). Results: In this study, we designed experiments using artificially degraded RNA from cell lines as well as naturally degraded RNA from tissue samples to quantify the effect RNA degradation has on fusion detection when using poly-A selected RNA libraries We found that both the RNA degradation level and the distance from the 3’ end of a gene, negatively impact the read coverage profile in RNA-seq. Furthermore, the median transcript coverage decreases exponentially as a function of the distance from the 3’ end and there is a linear relationship between the coverage decay rate and the RNA integrity number (RIN). Conclusions: we found that when using poly-A pulldown techniques for library preparation in RNA-seq, the fusion sensitivity is negatively impacted by both sample degradation and distance of the fusion breakpoint from the 3’ end and developed graphs that show such effect. Such graphs can be useful in assessing the fusion sensitivity of RNA-seq in both research and clinical settings
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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.
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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
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Project description:Immediate early genes (IEGs) represent a unique class of genes with rapid induction kinetics and transient expression patterns, which requires IEG mRNAs to be short-lived. Here, we establish cytoplasmic polyadenylation element-binding protein 4 (CPEB4) as a major determinant of IEG mRNA instability. We identified human CPEB4 as an RNA-binding protein (RBP) with enhanced association to poly(A) RNA upon inhibition of class I histone deacetylases (HDACs), which is known to cause widespread degradation of poly(A)-containing mRNA. Photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP) analysis using endogenously tagged CBEP4 in HeLa cells revealed that CPEB4 preferentially binds to the 3' untranslated region (UTR) of IEG mRNAs, at U-rich sequence motifs located in close proximity to the poly(A) site. By transcriptome-wide mRNA decay measurements, we found that the strength of CPEB4 binding correlates with short mRNA half-lives, and that loss of CPEB4 expression leads to the stabilization of IEG mRNAs. Further, we demonstrate that CPEB4 mediates mRNA degradation by recruitment of the evolutionarily conserved CCR4-NOT complex, the major eukaryotic deadenylase. While CPEB4 is primarily known for its ability to stimulate cytoplasmic polyadenylation, our findings establish an additional function for CPEB4 as an RBP that enhances the degradation of short-lived IEG mRNAs.
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2017-10-30 | GSE104213 | GEO
Project description:Polyadenylation at the 3’ end of eukaryotic messenger RNAs enhances mRNA stability and translational efficiency. Global analysis for poly(A) tail lengths may shed lights on various aspects of gene regulation studies. Two NGS-based methods have been introduced for genome-wide poly(A) profiling, and they have shown human poly(A) profiles with shorter than previously conceived tail lengths. However, both methods are technically challenging and difficult to be repeated or widely adapted. Here we present a more straightforward method for poly(A) profiling. Poly(A)-seq performed on Illumina NextSeq 500 produces single-end 300 nt reads that covers the entirety of poly(A) tails, and poly(A) lengths can be directly calculated from base call data. With Poly(A)-seq we report that the global poly(A) lengths of several human cell lines may be longer than previously reported. We also show that the size selection step during Poly(A)-seq library preparation may greatly affect the sequencing profile, and thus cautions should be taken for comparisons between samples. As a convenient tool, we hope wide applications of Poly(A)-seq helps to bring better understanding of poly(A) tail properties and functions.
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