Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

ABSTRACT: Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

PROVIDER: PRJNA523366 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR12851454_1.fastq.gz	Fastqsanger.gz
	SRR12851454_2.fastq.gz	Fastqsanger.gz
	SRR8595560_1.fastq.gz	Fastqsanger.gz
	SRR8595560_2.fastq.gz	Fastqsanger.gz
	SRR8595561_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 30

Similar Datasets

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

Project description:Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

| PRJNA523366 | ENA

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA

Project description:The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 115 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new tRNA and snoRNA genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distort the perceived architecture of the human transcriptome.

2019-02-21 | GSE126797 | GEO

Reducing the structure bias of RNA-Seq reveals a large number of non-annotated non-coding RNA.

Project description:The study of RNA expression is the fastest growing area of genomic research. However, despite the dramatic increase in the number of sequenced transcriptomes, we still do not have accurate estimates of the number and expression levels of non-coding RNA genes. Non-coding transcripts are often overlooked due to incomplete genome annotation. In this study, we use annotation-independent detection of RNA reads generated using a reverse transcriptase with low structure bias to identify non-coding RNA. Transcripts between 20 and 500 nucleotides were filtered and crosschecked with non-coding RNA annotations revealing 111 non-annotated non-coding RNAs expressed in different cell lines and tissues. Inspecting the sequence and structural features of these transcripts indicated that 60% of these transcripts correspond to new snoRNA and tRNA-like genes. The identified genes exhibited features of their respective families in terms of structure, expression, conservation and response to depletion of interacting proteins. Together, our data reveal a new group of RNA that are difficult to detect using standard gene prediction and RNA sequencing techniques, suggesting that reliance on actual gene annotation and sequencing techniques distorts the perceived architecture of the human transcriptome.

| S-EPMC7049693 | biostudies-literature

Evaluating bias-reducing protocols for RNA sequencing library preparation

Project description:Evaluating bias-reducing protocols for RNA sequencing library preparation

| PRJEB6271 | ENA

Evaluating bias-reducing protocols for RNA sequencing library preparation

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

Bias musicus

Project description:Bias musicus

| PRJNA920250 | ENA

SARS-CoV-2 annotated assembly

Project description:SARS-CoV-2 annotated assembly

| PRJEB42415 | ENA

Reducing sampling bias in molecular studies of grapevine fruit ripening: transcriptomic assessment of the density sorting method

Project description:Reducing sampling bias in molecular studies of grapevine fruit ripening: transcriptomic assessment of the density sorting method

| PRJNA305927 | ENA

citrate vs nitrate Reducing cultures

Project description:The effect of nitrate reduction (anaerobic cultivation in the presence of heme, vitamin K2 and nitrate) was compared with anaerobic cultivation supplemented with citrate (Lactobacillus plantarum). The medium was chemically defined medium with mannitol as main carbon source Two-condition experiment, nitrate vs citrate reducing cells. Biological replicates: 4 nitrate reducing cultures, 4 citrate reducing cultures, independently grown and harvested. Two slides were used, each slide contained 8 Arrays. Citrate reducing cultures are called reactor 1-4, Nitrate reducing cultures are called reactor A-D

2010-05-16 | E-GEOD-18339 | biostudies-arrayexpress

Dye Bias Array Set

Project description:Spot intensity serves as a proxy for gene expression in dual-label microarray experiments. Dye bias is defined as an intensity difference between samples labeled with different dyes attributable to the dyes instead of the gene expression in the samples. Dye bias that is not removed by array normalization can introduce bias into comparisons between samples of interest. But if the bias is consistent across the samples for the same gene, it can be corrected by proper experimental design and analysis. If the dye bias is not consistent across samples for the same gene, but is different for different samples, then removing the bias becomes more problematic, perhaps indicating a technical limitation to the ability of fluorescent signals to accurately represent gene expression. Thus, it is important to characterize dye bias to determine: (1) whether it will be removed for all genes by array normalization, (2) whether it will not be removed by normalization but can be removed by proper experimental design and analysis and (3) whether dye bias correction is more problematic than either of these and is not easily removable. Keywords: dye swap design

2006-06-06 | GSE4982 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data