Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms

ABSTRACT: Eukaryotic genes often generate a variety of RNA isoforms that can lead to functionally distinct protein variants. The synthesis and stability of RNA isoforms is however poorly characterized. The reason for this is that current methods to quantify RNA metabolism use short-read sequencing that cannot detect RNA isoforms. Here we present nanopore sequencing-based Isoform Dynamics (nano-ID), a method that detects newly synthesized RNA isoforms and monitors isoform metabolism. nano-ID combines metabolic RNA labeling, long-read nanopore sequencing of native RNA molecules and machine learning. nano-ID derived RNA stability estimates enable a distinctive evaluation of stability determining factors such as sequence, poly(A)-tail length, RNA secondary structure, translation efficiency and RNA binding proteins. Application of nano-ID to the heat shock response in human cells reveals that many RNA isoforms change their stability. nano-ID also shows that the metabolism of individual RNA isoforms differs strongly from that estimated for the combined RNA signal at a specific gene locus. nano-ID enables studies of RNA metabolism on the level of single RNA molecules and isoforms in different cell states and conditions.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE127890 | GEO | 2020/05/06

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Revealing nascent RNA processing dynamics with nano-COP

Project description:During maturation, eukaryotic precursor RNAs undergo processing events including intron splicing, 3’-end cleavage, and polyadenylation. Here, we describe nanopore analysis of CO-transcriptional Processing (nano-COP), a method for probing the timing and patterns of RNA processing. An extension of native elongating transcript sequencing (NET-seq), which quantifies transcription genome-wide through short-read sequencing of nascent RNA 3’ ends, nano-COP uses long-read nascent RNA sequencing to observe global patterns of RNA processing. First, nascent RNA is stringently purified through a combination of 4-thiouridine metabolic labeling and cellular fractionation. In contrast to cDNA or short-read–based approaches relying on reverse transcription or amplification, the sample is sequenced directly through nanopores to reveal the native context of nascent RNA. nano-COP identifies both active transcription sites and splice isoforms of single RNA molecules during synthesis, providing insight into patterns of intron removal and the physical coupling between transcription and splicing. The nano-COP protocol yields data within 3 days.

2021-01-06 | GSE154079 | GEO

Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms

Project description:Native molecule sequencing by nano-ID reveals synthesis and stability of RNA isoforms

| PRJNA525707 | ENA

ESPRESSO: Robust discovery and quantification of transcript isoforms from error-prone long-read RNA-seq data

Project description:Long-read RNA sequencing (RNA-seq) holds great potential for characterizing transcriptome variation and full-length transcript isoforms, but the relatively high error rate of current long-read sequencing platforms poses a major challenge. We present ESPRESSO, a computational tool for robust discovery and quantification of transcript isoforms from error-prone long reads. ESPRESSO jointly considers alignments of all long reads aligned to a gene and uses error profiles of individual reads to improve the identification of splice junctions and the discovery of their corresponding transcript isoforms. On both a synthetic spike-in RNA sample and human RNA samples, ESPRESSO outperforms multiple contemporary tools in not only transcript isoform discovery but also transcript isoform quantification. In total, we generated and analyzed ~1.1 billion nanopore RNA-seq reads covering 30 human tissue samples and three human cell lines. ESPRESSO and its companion dataset provide a useful resource for studying the RNA repertoire of eukaryotic transcriptomes.

2022-10-14 | GSE192955 | GEO

Determination of isoform-specific RNA structure with nanopore long reads

Project description:Current methods for determening RNA structure with short-read sequencing cannot capture most differences between distinct transcript isoforms. Here, we present RNA structure analysis using nanopore sequencing (PORE-cupine),which combines structure probing using chemical modifications with direct long-read RNA sequencing and machine learning to detect secondary structures in cellular RNAs. PORE-cupine also captures global structural features, such as RNA binding protein (RBP) binding sites and reactivity differences at single nucleotide variants (SNVs). We show that shared sequences in different transcript isoforms of the same gene can fold into different structures, highlighting the importance of long-read sequencing for obtaining phase information. We also demonstrate that structural differences between transcript isoforms of the same gene lead to differences in translation efficiency. By revealing isoform-specific RNA structure, PORE-cupine will deepen our understanding of the role of structures in controlling gene regulation.

2020-09-09 | GSE133361 | GEO

Long-read Proteogenomics Internal Standard triggered PRM (LRP-IS-PRM)

Project description:Long-read proteogenomic data was used to create sample-matched protein database for WTC11 sample. This includes many potential alternative protein isoforms (major and minor isoforms) per gene. The IS-PRM method called Tomahto was tested versus DDA to demonstrate improved coverage of isoform-specific peptides. We called this overall method of long-read RNA informed Tomahto targeting LRP-IS-PRM and used it for protein-level evidence of multiple isoforms derived from alternative splicing.

2024-07-17 | PXD050909 | Pride

Long-read Proteogenomics Internal Standard triggered PRM (LRP-IS-PRM)

2024-07-17 | PXD050904 | Pride

Aberrant splicing isoforms detected by full-length transcriptome sequencing as transcripts of potential neoantigens in non-small cell lung cancer

Project description:To identify aberrant splicing isoforms and potential neoantigens, we performed full-length cDNA sequencing of lung adenocarcinoma cell lines using a long-read sequencer MinION. We constructed a comprehensive catalog of aberrant splicing isoforms and detected isoform-specific peptides using proteome analysis.

2020-12-09 | PXD019915 | JPOST Repository

High-throughput error corrected Nanopore single cell transcriptome sequencing

Project description:E18 mouse brain single cell profiling using the 10x Genomics Chromium instrument workflow with either Illumina short read sequencing for the standard gene profiling and Nanopore PromethION long read sequencing for isoform profiling.

2020-07-10 | GSE130708 | GEO

Long-read RNA sequencing of cattle, pig, and chicken tissues

Project description:Long-read Nanopore cDNA sequencing of polyA-enriched RNA was implemented in a range of adult tissues isolated from cattle, pig, and chicken. These data were used to identify and characterize the expression patterns of full-length transcript isoforms.

2021-01-01 | GSE160028 | GEO

Direct long-read RNA sequencing of Raji cells

Project description:To identify full-length cap-to-poly(A) mRNA isoforms of CD20 and rule out reverse transcription artifacts which are common in cDNA-seq approaches, long-read Oxford Nanopore direct RNA sequencing was performed on the Raji cell line.

2023-12-08 | GSE243920 | 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