Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA-seq data is shaped in characteristic ways by polymerase processivities

ABSTRACT: We present here an integrated framework that allows inference of enzyme reactions during library preparation and which predicts characteristic coverage shapes for different protocols. Analysis of several existing (sc)RNA-seq datasets confirms our model and reveals polymerase processivities as mechanistic origins of the resulting coverage shapes. We show how correction factors are necessary for proper RNA-seq-based mRNA quantification. Finally, we demonstrate the sensitivity of our methodology in inferring increased processivities at lowered reaction temperatures, suggesting possible improvements to existing protocols. Our findings have broad implications for existing and future RNA-seq experiments.

ORGANISM(S): Mus musculus

PROVIDER: GSE84785 | GEO | 2016/11/09

SECONDARY ACCESSION(S): PRJNA331155

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Characteristic bimodal profiles of RNA polymerase II at thousands of active mammalian promoters

Project description:Here, we present PolII binding profiles from high-coverage ChIP-seq on promoters of actively transcribed genes in mouse and humans. We show that the enrichment of PolII near transcription start sites exhibits a stereotypical bimodal structure, with one peak near active transcription start sites and a second peak 110 base pairs downstream from the first. High-resolution characterization of PolII at promoters in mouse liver

2014-06-13 | E-GEOD-58443 | biostudies-arrayexpress

Characteristic bimodal profiles of RNA polymerase II at thousands of active mammalian promoters

2014-06-13 | GSE58443 | GEO

Modeling Enzyme Processivity Reveals that RNA-Seq Libraries Are Biased in Characteristic and Correctable Ways.

Project description:Experimental procedures for preparing RNA-seq and single-cell (sc) RNA-seq libraries are based on assumptions regarding their underlying enzymatic reactions. Here, we show that the fairness of these assumptions varies within libraries: coverage by sequencing reads along and between transcripts exhibits characteristic, protocol-dependent biases. To understand the mechanistic basis of this bias, we present an integrated modeling framework that infers the relationship between enzyme reactions during library preparation and the characteristic coverage patterns observed for different protocols. Analysis of new and existing (sc)RNA-seq data from six different library preparation protocols reveals that polymerase processivity is the mechanistic origin of coverage biases. We apply our framework to demonstrate that lowering incubation temperature increases processivity, yield, and (sc)RNA-seq sensitivity in all protocols. We also provide correction factors based on our model for increasing accuracy of transcript quantification in existing samples prepared at standard temperatures. In total, our findings improve our ability to accurately reflect in vivo transcript abundances in (sc)RNA-seq libraries.

| S-EPMC5167349 | biostudies-literature

Multiplexed Illumina sequencing libraries from picogram quantities of DNA

Project description:High throughput sequencing is frequently used to discover the location of regulatory interactions on chromatin. However, techniques that enrich DNA where regulatory activity takes place, such as chromatin immunoprecipitation (ChIP), often yield less DNA than optimal for sequencing library preparation. Existing protocols for picogram-scale libraries require concomitant fragmentation of DNA, pre-amplification, or long overnight steps. We report a simple and fast library construction method that produces libraries from sub-nanogram quantities of DNA. This protocol yields conventional libraries with barcodes suitable for multiplexed sample analysis on the Illumina platform. We demonstrate the utility of this method by constructing a ChIP-seq library from 100 pg of ChIP DNA that demonstrates equivalent genomic coverage of target regions to a library produced from a larger scale experiment. Application of this method allows whole genome studies from samples where material or yields are limiting. Comparison of ChIP-seq libraries constructed from 100 pg DNA (this study) and nanograms of DNA (modENCODE). ChIP antibody: H3K27me3, Active Motif 31955.

2013-07-01 | E-GEOD-48431 | biostudies-arrayexpress

EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics - I

Project description:Background Next Generation Sequencing technologies have facilitated differential gene expression analysis through RNA-seq and Tag-seq methods. RNA-seq has biases associated with transcript lengths, lacks uniform coverage of regions in mRNA and requires 10–20 times more reads than a typical Tag-seq. Most existing Tag-seq methods either have biases or not high throughput due to use of restriction enzymes or enzymatic manipulation of 5’ ends of mRNA or use of RNA ligations. Results We have developed EXpression Profiling through Randomly Sheared cDNA tag Sequencing (EXPRSS) that employs acoustic waves to randomly shear cDNA and generate sequence tags at a relatively defined position (~150-200 bp) from the 3′ end of each mRNA. Implementation of the method was verified through comparative analysis of expression data generated from EXPRSS, NlaIII-DGE and Affymetrix microarray and through qPCR quantification of selected genes. EXPRSS is a strand specific and restriction enzyme independent tag sequencing method that does not require cDNA length-based data transformations. EXPRSS is highly reproducible, is high-throughput and it also reveals alternative polyadenylation and polyadenylated antisense transcripts. It is cost-effective using barcoded multiplexing, avoids the biases of existing SAGE and derivative methods and can reveal polyadenylation position from paired-end sequencing. Conclusions EXPRSS Tag-seq provides sensitive and reliable gene expression data and enables high-throughput expression profiling with relatively simple downstream analysis. Five weeks old Arabidopsis (Col-0) leaf discs treated with water or flg22 for 60min; mRNA profiles were generated by deep sequencing on Illumina GAIIx using EXPRSS and NlaIII-DGE protocols, in quadruplicate.

2014-06-20 | E-GEOD-45989 | biostudies-arrayexpress

Multiplexed Illumina sequencing libraries from picogram quantities of DNA

2013-07-01 | GSE48431 | GEO

EXPRSS: an Illumina based high-throughput expression-profiling method to reveal transcriptional dynamics - II

Project description:Background Next Generation Sequencing technologies have facilitated differential gene expression analysis through RNA-seq and Tag-seq methods. RNA-seq has biases associated with transcript lengths, lacks uniform coverage of regions in mRNA and requires 10–20 times more reads than a typical Tag-seq. Most existing Tag-seq methods either have biases or not high throughput due to use of restriction enzymes or enzymatic manipulation of 5’ ends of mRNA or use of RNA ligations. Results We have developed EXpression Profiling through Randomly Sheared cDNA tag Sequencing (EXPRSS) that employs acoustic waves to randomly shear cDNA and generate sequence tags at a relatively defined position (~150-200 bp) from the 3? end of each mRNA. Implementation of the method was verified through comparative analysis of expression data generated from EXPRSS, NlaIII-DGE and Affymetrix microarray and through qPCR quantification of selected genes. EXPRSS is a strand specific and restriction enzyme independent tag sequencing method that does not require cDNA length-based data transformations. EXPRSS is highly reproducible, is high-throughput and it also reveals alternative polyadenylation and polyadenylated antisense transcripts. It is cost-effective using barcoded multiplexing, avoids the biases of existing SAGE and derivative methods and can reveal polyadenylation position from paired-end sequencing. Conclusions EXPRSS Tag-seq provides sensitive and reliable gene expression data and enables high-throughput expression profiling with relatively simple downstream analysis. Five weeks old Arabidopsis (Col-0, ein2-5, jar1-1 and npr1-1) leaf discs treated with water or flg22 and a time course of samples were collected; mRNA profiles were generated by deep sequencing on Illumina GAIIx using EXPRSS protocols.

2014-06-20 | E-GEOD-51720 | biostudies-arrayexpress

Single-cell profiling of histone modifications and transcription in developmental systems with EpiDamID [RPE1]

Project description:We developed EpiDamID, an adaptation of existing DamID protocols that extends their applicability to histone PTMs.

2022-04-01 | GSE196959 | GEO

Single-cell profiling of histone modifications and transcription in developmental systems with EpiDamID [mouse EB]

Project description:We developed EpiDamID, an adaptation of existing DamID protocols that extends their applicability to histone PTMs.

2022-04-01 | GSE184033 | GEO

Single-cell profiling of histone modifications and transcription in developmental systems with EpiDamID [bulk ChIP-seq]

Project description:We developed EpiDamID, an adaptation of existing DamID protocols that extends their applicability to histone PTMs.

2022-04-01 | GSE184030 | GEO