Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

DART-seq: an antibody-free method for global m6A detection

ABSTRACT: DART-seq: an antibody-free method for global m6A detection

PROVIDER: PRJNA517490 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR9940470.fastq.gz	Fastqsanger.gz
	SRR9940471.fastq.gz	Fastqsanger.gz
	SRR9940472.fastq.gz	Fastqsanger.gz
	SRR9940473.fastq.gz	Fastqsanger.gz
	SRR9940474.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 9

Similar Datasets

DART-seq: an antibody-free method for global m6A detection

Project description:m6A is a widespread RNA modification which plays important roles in the regulation of gene expression. Methods for the global detection of m6A rely on immunoprecipitation of methylated transcripts using m6A antibodies. However, these methods are costly and require large amounts of input RNA, making them prohibitive for many experiments. Here, we describe DART-seq, an antibody-free method for m6A detection which enables transcriptome-wide mapping of m6A residues using low amounts of input material. DART-seq can be used to obtain global m6A maps using as little as 10 nanograms of total RNA and at single-molecule resolution. This method offers several improvements over current techniques and will facilitate detection of m6A in limiting cell and tissue types.

2019-09-23 | GSE125780 | GEO

Improved methods for deamination-based m6A detection

Project description:We present an improved version of DART-seq which utilizes a variant of the YTH domain engineered to achieve enhanced m6A recognition in APO1-YTH (D422N). In addition, we develop in vitro DART-seq and show that it performs similarly to cellular DART-seq and can map m6A in any sample of interest using nanogram amounts of total RNA.

2022-05-11 | GSE196416 | GEO

Single base mapping of m6A by an antibody-independent method

Project description:N6-methyladenosine (m6A) is one of the most abundant mRNA modifications in eukaryotes, related to pivotal RNA metabolism processes. The most popular high-throughput m6A identification method relies on the commercial m6A antibody but suffers from poor reproducibility and limited resolution. Exact location of m6A site is of great vital for understanding the dynamics, functions and machinery of RNA methylation. Here, we developed a precise and high-throughput antibody-independent m6A identification method based on the m6A-sensitive RNA endoribonuclease recognizing ACA motif (m6A-sensitive RNA-Endoribonuclease–Facilitated sequencing or m6A-REF-seq). Whole-transcriptomic single base m6A map generated by m6A-REF-seq displayed a typical distribution pattern with enrichment adjacent to stop codon. Ligase-based and qPCR validation methods were used to confirm the individual m6A sites and quantify the methylation level, reinforcing the high accuracy of m6A-REF-seq. We applied m6A-REF-seq on five tissues from three mammals, showing that m6A sites were conserved and tend to gather together among species. (m6A-REF-seq had been named as Aim-seq.)

2019-07-03 | GSE125240 | GEO

Single base mapping of m6A by an antibody-independent method

Project description:Single base mapping of m6A by an antibody-independent method

| PRJNA515628 | ENA

An antibody independent verification method quantifies m6A in the chicken β-actin zipcode

Project description:N6-Methyladenosine (m6A) in mRNA regulates almost every stage in the mRNA life cycle, and the development of the high throughput detection of methylated sites in mRNA using MeRIPSeq or miCLIP revolutionized the m6A research field. Both methods are based on immunoprecipitation of fragmented mRNA. However, it is well documented that antibodies often have nonspecific activities, thus verification of identified m6A sites using an antibody-independent method would be highly desirable. Currently such approaches are limited. Here we present RedBaron, an improved biochemical method for the site-specific detection and quantification of m6A in RNA. We demonstrate that the RedBaron method is able to accurately quantify m6A levels at specific transcripts in vivo. We used this assay for the site-specific detection and quantification of m6A within the chicken β-actin (ACTB) zipcode sequence in chicken embryos and in fibroblast cells. We demonstrate that methylation of this site in the β-actin zipcode enhances ZBP1 binding in vitro, whilst methylation of a nearby adenosine abolishes

2023-05-24 | GSE185078 | GEO

Antibody-free enzyme-assisted chemical approach for detection of N6-methyladenosine

Project description:We applied chemical-assisted, m6A-SEAL method to profile m6A distributions in the transcriptomes of human and plant cells and compared its results against MeRIPm6A-seq.

2020-04-22 | GSE129979 | GEO

An antibody independent verification method quantifies m6A in the chicken β-actin zipcode

Project description:An antibody independent verification method quantifies m6A in the chicken β-actin zipcode

| PRJNA767616 | ENA

DART-seq: an antibody-free method for global m<sup>6</sup>A detection.

Project description:N6-methyladenosine (m6A) is a widespread RNA modification that influences nearly every aspect of the messenger RNA lifecycle. Our understanding of m6A has been facilitated by the development of global m6A mapping methods, which use antibodies to immunoprecipitate methylated RNA. However, these methods have several limitations, including high input RNA requirements and cross-reactivity to other RNA modifications. Here, we present DART-seq (deamination adjacent to RNA modification targets), an antibody-free method for detecting m6A sites. In DART-seq, the cytidine deaminase APOBEC1 is fused to the m6A-binding YTH domain. APOBEC1-YTH expression in cells induces C-to-U deamination at sites adjacent to m6A residues, which are detected using standard RNA-seq. DART-seq identifies thousands of m6A sites in cells from as little as 10 ng of total RNA and can detect m6A accumulation in cells over time. Additionally, we use long-read DART-seq to gain insights into m6A distribution along the length of individual transcripts.

| S-EPMC6884681 | biostudies-literature

Single-cell m6A profiling reveals mRNA methylation heterogeneity and unique cellular m6A signatures

Project description:We used DART-seq to map m6A methylation of RNA in single HEK293T cells. We also used DART-seq to map m6A from bulk RNA from HEK293T cells. Using the 10X Genomics and SMART-seq2 platforms, we sequenced a total of 19,533 experimental and control cells using the 10X Genomics platform, and 1,471 experimental and control cells using SMART-seq2. We then used a Bullseye, a computational pipeline developed within the lab, to identify m6A sites from the C-to-U mutations in bulk and single-cell datasets. We find that most m6A methylation is highly heterogenous from cell-to-cell. RNAs containing m6A methylation, are infrequently methylated, and that most individual sites are rarely methylated within the population. Additionally, we are able to identify differentially methylated RNAs in different cellular states from within a single population, and use m6A methylation information to perform clustering of single cells to find a source of novel cellular heterogeneity.

2022-01-25 | GSE180954 | GEO

m6A mapping in human RNA (untreated)

Project description:We developed a novel approach, m6A-seq, for high-resolution mapping of the transcriptome-wide m6A landscape, based on antibody-mediated capture followed by massively parallel sequencing. Identification of m6A modified sequences in HepG2 cells.

2012-04-25 | E-GEOD-37003 | biostudies-arrayexpress

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