IVT-seq reveals extreme bias in RNA-sequencing
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ABSTRACT:
PROVIDER: PRJNA217498 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR959430_1.fastq.gz | Fastqsanger.gz | |||
| SRR959430_2.fastq.gz | Fastqsanger.gz | |||
| SRR959431_1.fastq.gz | Fastqsanger.gz | |||
| SRR959431_2.fastq.gz | Fastqsanger.gz | |||
| SRR959432_1.fastq.gz | Fastqsanger.gz |
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Project description:Background RNA sequencing (RNA-seq) is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. Results Here we present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of > 1000 in vitro transcribed (IVT) RNAs from a full-length human cDNA library and sequenced them with poly-A and total RNA-seq, the most common protocols. Because each cDNA is full length and we show IVT is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find ~50% of transcripts have > 2-fold and ~10% have > 10-fold differences in within-transcript sequence coverage. Strikingly, we also find > 6% of transcripts have regions of high, unpredictable sequencing coverage, where the same transcript varies dramatically in coverage between samples, confounding accurate determination of their expression. To get at causal factors, we used a combination of experimental and computational approaches to show that rRNA depletion is responsible for the most significant variability in coverage and that several sequence determinants also strongly influence representation. Conclusions In sum, these results show the utility of IVT-seq in promoting better understanding of bias introduced by RNA-seq and suggest caution in its interpretation. Furthermore, we find that rRNA-depletion is responsible for substantial, unappreciated biases in coverage. Perhaps most importantly, these coverage biases introduced during library preparation suggest exon level expression analysis may be inadvisable. 5 rRNA-depleted samples with duplicates, 1 polyA selected, 1 total RNA, and 1 plasmid library all without replicates.
2014-05-21 | E-GEOD-50445 | biostudies-arrayexpress
Project description:Background: RNA-seq is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value. Results: We present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of over 1,000 in vitro transcribed RNAs from a full-length human cDNA library and sequenced them with polyA and total RNA-seq, the most common protocols. Because each cDNA is full length, and we show in vitro transcription is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find 50% of transcripts have more than two-fold and 10% have more than 10-fold differences in within-transcript sequence coverage. We also find greater than 6% of transcripts have regions of dramatically unpredictable sequencing coverage between samples, confounding accurate determination of their expression. We use a combination of experimental and computational approaches to show rRNA depletion is responsible for the most significant variability in coverage, and several sequence determinants also strongly influence representation. Conclusions: These results show the utility of IVT-seq for promoting better understanding of bias introduced by RNA-seq. We find rRNA depletion is responsible for substantial, unappreciated biases in coverage introduced during library preparation. These biases suggest exon-level expression analysis may be inadvisable, and we recommend caution when interpreting RNA-seq results.
2014-05-21 | GSE50445 | GEO
Project description:RNA-seq is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value.We present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of over 1,000 in vitro transcribed RNAs from a full-length human cDNA library and sequenced them with polyA and total RNA-seq, the most common protocols. Because each cDNA is full length, and we show in vitro transcription is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find 50% of transcripts have more than two-fold and 10% have more than 10-fold differences in within-transcript sequence coverage. We also find greater than 6% of transcripts have regions of dramatically unpredictable sequencing coverage between samples, confounding accurate determination of their expression. We use a combination of experimental and computational approaches to show rRNA depletion is responsible for the most significant variability in coverage, and several sequence determinants also strongly influence representation.These results show the utility of IVT-seq for promoting better understanding of bias introduced by RNA-seq. We find rRNA depletion is responsible for substantial, unappreciated biases in coverage introduced during library preparation. These biases suggest exon-level expression analysis may be inadvisable, and we recommend caution when interpreting RNA-seq results.
| S-EPMC4197826 | biostudies-literature
Project description:Mutational analysis of IVT mRNAs
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Project description:The ligation step in RNA sequencing library generation is a known source of bias. We present the first comparison of the standard duplex adaptor protocol supplied by Life Technologies for use on the Ion Torrent PGM with an alternate single adaptor approach involving CircLigase (CircLig). We also investigate whether using the thermostable ligase Methanobacterium thermoautotrophicum RNA ligase K97A (Mth K97A) for the initial ligation step in the CircLigase protocol reduces bias. A pool of small RNA fragments of known composition was converted into a sequencing library using one of three protocols and sequenced on an Ion Torrent PGM. The single adaptor CircLigase-based approach significantly reduces, but does not eliminate, bias in Ion Torrent data. Using Mth K97A as part of the CircLig method does not further reduce bias.
2014-06-24 | E-MTAB-2566 | biostudies-arrayexpress
Project description:Single cell sequencing reveals sex bias in autism associated cells and genes
| PRJNA694426 | ENA
Project description:To investigate the epigenetic landscape at the interface between mother and fetus, we provide a comprehensive analysis of parent of origin bias in the placenta. Using F1 interspecies hybrids, we sequenced RNA from 23 individual midgestation placentas, five late stage placentas, and two yolk sac samples and then used SNPs to determine whether transcripts were preferentially generated from the maternal or paternal allele. In the placenta, we find 103 genes that show significant and reproducible parent-of-origin bias, of which 78 are novel candidates. Most (96%) show a strong maternal bias which, using multiple models, we demonstrate is not due to maternal decidual contamination. Analysis of the X chromosome also reveals paternal expression of Xist and several genes that escape inactivation, most significantly Rps4x, Fhl1, and Slc38a5. Finally, sequencing individual placentas allowed us to reveal notable expression similarity between littermates. In all, we observe a striking preference for maternal transcription in the midgestation mouse placenta and a dynamic imprinting landscape in extraembryonic tissues, reflecting the complex nature of epigenetic pathways in the placenta. 3'-end Sequencing for Expression Quantification (3SEQ) and SNP Analysis to observe parent-of-origin bias in 28 placental samples at two time points and 2 yolk sac samples
2014-02-28 | E-GEOD-42671 | biostudies-arrayexpress
Project description:The use of RNA-seq as the preferred method for the discovery and validation of small RNA biomarkers is hindered by high variability and biased sequence counts. In this paper we develop a statistical model for sequence counts that accounts for ligase bias and stochastic variation in library amplification steps and sequencing depth variation. Our analytical contributions are the description of the Linear Quadratic (LQ) relation between the mean and variance of the sequence counts in an RNA-seq experiment and the derivation of the Poisson truncated mixture as the underlying probability distribution for RNA-seq data. Using a large number of sequencing datasets, we demonstrate here how one can use this modeling framework to calculate empirical correction factors for ligase bias, while accounting for random variation in sequence counts. Bias correction may remove the majority of bias in the absence of differential expression and more than 40% of the bias in the presence of variable expression of miRNAs. Empirical bias correction factors appear to be nearly constant over at least one and up to four orders of magnitude of total RNA input and independent of sample composition.
2017-03-15 | GSE93399 | GEO