Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Protocol for detecting RBM33-binding sites in HEK293T cells using PAR-CLIP-seq.

ABSTRACT: RNA-binding proteins (RBPs) regulate gene expression both co-transcriptionally and post-transcriptionally. Here, we provide a protocol for photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation followed by next-generation sequencing (PAR-CLIP-seq). PAR-CLIP-seq is a transcriptome-scale technique for identifying in vivo binding sites of RBPs at the single-nucleotide level. We detail procedures for the establishment of FLAG-RBM33 stable cell line, the sequencing library preparation, and the data analysis.

SUBMITTER: Yu F

PROVIDER: S-EPMC10846379 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Protocol for detecting RBM33-binding sites in HEK293T cells using PAR-CLIP-seq.

Yu Fang F Liu Shun S Zhu Allen C AC He Chuan C Qian Zhijian Z

STAR protocols 20240131 1

RNA-binding proteins (RBPs) regulate gene expression both co-transcriptionally and post-transcriptionally. Here, we provide a protocol for photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation followed by next-generation sequencing (PAR-CLIP-seq). PAR-CLIP-seq is a transcriptome-scale technique for identifying in vivo binding sites of RBPs at the single-nucleotide level. We detail procedures for the establishment of FLAG-RBM33 stable cell line, the sequencing library prep ...[more]

PMID: 38300798

Similar Datasets

Optimization of PAR-CLIP for transcriptome-wide identification of binding sites of RNA-binding proteins.

Project description:Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) in combination with next-generation sequencing is a powerful method for identifying endogenous targets of RNA-binding proteins (RBPs). Depending on the characteristics of each RBP, key steps in the PAR-CLIP procedure must be optimized. Here we present a comprehensive step-by-step PAR-CLIP protocol with detailed explanations of the critical steps. Furthermore, we report the application of a new PAR-CLIP data analysis pipeline to three distinct RBPs targeting different annotation categories of cellular RNAs.

| S-EPMC5393971 | biostudies-literature

PARalyzer: definition of RNA binding sites from PAR-CLIP short-read sequence data.

Project description:Crosslinking and immunoprecipitation (CLIP) protocols have made it possible to identify transcriptome-wide RNA-protein interaction sites. In particular, PAR-CLIP utilizes a photoactivatable nucleoside for more efficient crosslinking. We present an approach, centered on the novel PARalyzer tool, for mapping high-confidence sites from PAR-CLIP deep-sequencing data. We show that PARalyzer delineates sites with a high signal-to-noise ratio. Motif finding identifies the sequence preferences of RNA-binding proteins, as well as seed-matches for highly expressed microRNAs when profiling Argonaute proteins. Our study describes tailored analytical methods and provides guidelines for future efforts to utilize high-throughput sequencing in RNA biology. PARalyzer is available at http://www.genome.duke.edu/labs/ohler/research/PARalyzer/.

| S-EPMC3302668 | biostudies-literature

Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP.

Project description:RNA transcripts are subject to posttranscriptional gene regulation involving hundreds of RNA-binding proteins (RBPs) and microRNA-containing ribonucleoprotein complexes (miRNPs) expressed in a cell-type dependent fashion. We developed a cell-based crosslinking approach to determine at high resolution and transcriptome-wide the binding sites of cellular RBPs and miRNPs. The crosslinked sites are revealed by thymidine to cytidine transitions in the cDNAs prepared from immunopurified RNPs of 4-thiouridine-treated cells. We determined the binding sites and regulatory consequences for several intensely studied RBPs and miRNPs, including PUM2, QKI, IGF2BP1-3, AGO/EIF2C1-4 and TNRC6A-C. Our study revealed that these factors bind thousands of sites containing defined sequence motifs and have distinct preferences for exonic versus intronic or coding versus untranslated transcript regions. The precise mapping of binding sites across the transcriptome will be critical to the interpretation of the rapidly emerging data on genetic variation between individuals and how these variations contribute to complex genetic diseases.

| S-EPMC2861495 | biostudies-literature

PAR-CLIP analysis of YB-1 RNA binding in HEK293T cells

Project description:In this study, we performed PAR-CLIP experiment in HEK293T to explore RNAs directly bound by YB-1.

2024-01-18 | GSE249896 | GEO

PolyaPeak: detecting transcription factor binding sites from ChIP-seq using peak shape information.

Project description:ChIP-seq is a powerful technology for detecting genomic regions where a protein of interest interacts with DNA. ChIP-seq data for mapping transcription factor binding sites (TFBSs) have a characteristic pattern: around each binding site, sequence reads aligned to the forward and reverse strands of the reference genome form two separate peaks shifted away from each other, and the true binding site is located in between these two peaks. While it has been shown previously that the accuracy and resolution of binding site detection can be improved by modeling the pattern, efficient methods are unavailable to fully utilize that information in TFBS detection procedure. We present PolyaPeak, a new method to improve TFBS detection by incorporating the peak shape information. PolyaPeak describes peak shapes using a flexible Pólya model. The shapes are automatically learnt from the data using Minorization-Maximization (MM) algorithm, then integrated with the read count information via a hierarchical model to distinguish true binding sites from background noises. Extensive real data analyses show that PolyaPeak is capable of robustly improving TFBS detection compared with existing methods. An R package is freely available.

| S-EPMC3946423 | biostudies-literature

A model-based approach to identify binding sites in CLIP-Seq data.

Project description:Cross-linking immunoprecipitation coupled with high-throughput sequencing (CLIP-Seq) has made it possible to identify the targeting sites of RNA-binding proteins in various cell culture systems and tissue types on a genome-wide scale. Here we present a novel model-based approach (MiClip) to identify high-confidence protein-RNA binding sites from CLIP-seq datasets. This approach assigns a probability score for each potential binding site to help prioritize subsequent validation experiments. The MiClip algorithm has been tested in both HITS-CLIP and PAR-CLIP datasets. In the HITS-CLIP dataset, the signal/noise ratios of miRNA seed motif enrichment produced by the MiClip approach are between 17% and 301% higher than those by the ad hoc method for the top 10 most enriched miRNAs. In the PAR-CLIP dataset, the MiClip approach can identify ∼50% more validated binding targets than the original ad hoc method and two recently published methods. To facilitate the application of the algorithm, we have released an R package, MiClip (http://cran.r-project.org/web/packages/MiClip/index.html), and a public web-based graphical user interface software (http://galaxy.qbrc.org/tool_runner?tool_id=mi_clip) for customized analysis.

| S-EPMC3979666 | biostudies-literature

PARma: identification of microRNA target sites in AGO-PAR-CLIP data.

Project description:PARma is a complete data analysis software for AGO-PAR-CLIP experiments to identify target sites of microRNAs as well as the microRNA binding to these sites. It integrates specific characteristics of the experiments into a generative model. The model and a novel pattern discovery tool are iteratively applied to data to estimate seed activity probabilities, cluster confidence scores and to assign the most probable microRNA. Based on differential PAR-CLIP analysis and comparison to RIP-Chip data, we show that PARma is more accurate than existing approaches. PARma is available from http://www.bio.ifi.lmu.de/PARma.

| S-EPMC4054675 | biostudies-literature

Bayesian hidden Markov models to identify RNA-protein interaction sites in PAR-CLIP.

Project description:The photoactivatable ribonucleoside enhanced cross-linking immunoprecipitation (PAR-CLIP) has been increasingly used for the global mapping of RNA-protein interaction sites. There are two key features of the PAR-CLIP experiments: The sequence read tags are likely to form an enriched peak around each RNA-protein interaction site; and the cross-linking procedure is likely to introduce a specific mutation in each sequence read tag at the interaction site. Several ad hoc methods have been developed to identify the RNA-protein interaction sites using either sequence read counts or mutation counts alone; however, rigorous statistical methods for analyzing PAR-CLIP are still lacking. In this article, we propose an integrative model to establish a joint distribution of observed read and mutation counts. To pinpoint the interaction sites at single base-pair resolution, we developed a novel modeling approach that adopts non-homogeneous hidden Markov models to incorporate the nucleotide sequence at each genomic location. Both simulation studies and data application showed that our method outperforms the ad hoc methods, and provides reliable inferences for the RNA-protein binding sites from PAR-CLIP data.

| S-EPMC4061157 | biostudies-literature

PAR-CLIP analysis of YB-1 RNA binding in HEK293T cells

Project description:PAR-CLIP analysis of YB-1 RNA binding in HEK293T cells

| PRJNA1051100 | ENA

CLIP-seq to Identify KSHV ORF57-Binding RNA in Host B Cells.

Project description:Kaposi's sarcoma-associated herpesvirus (KSHV), a human gamma-herpesvirus, is etiologically linked to the development of several malignancies, mainly Kaposi's sarcoma. Expressed as an early viral protein, KSHV ORF57 is essential for lytic replication and virion production. ORF57 selectively binds to a subset of viral RNA and affects nearly all aspects of viral RNA processing. To globally identify all viral and host RNA associated with KSHV ORF57 in the infected cells, we have utilized UV cross-linking and immunoprecipitation (CLIP) of KSHV ORF57 combined with high-throughput RNA sequencing (CLIP-seq) to identify ORF57-binding RNA in BCBL-1 cells at genome-wide level. This unit provides step-by-step details on this new method that is applicable for any pathogen or host RNA-binding proteins by slight modification. © 2016 by John Wiley & Sons, Inc.

| S-EPMC6650155 | biostudies-literature

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