PAR-CLIP-seq reveals RNAs directly interacting with CTCF in human transformed cell line U2OS
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE53554 | GEO | 2014/03/18
SECONDARY ACCESSION(S): PRJNA232376
REPOSITORIES: GEO
Similar Datasets
Project description:This experiment sought to determine the genome-wide interactome of CTCF in human cells. PAR-CLIP seq for CTCF was performed in U2OS cells in 2 biological replicates
2014-03-18 | E-GEOD-53554 | biostudies-arrayexpress
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Project description:Knockout of the ubiquitously expressed microRNA-17~92 cluster in mice produces a lethal developmental defect and blocked B lymphopoiesis. We validated the equally widely expressed Bcl2l11 gene as joint target of miR-17~92 cluster members. Bcl2l11 encodes the pro-apoptotic protein BIM, central to life-death decisions in most mammalian cells. To study the contribution of miR-17~92:Bim interaction to miR-17~92 overall function, we set up a system of conditional mutagenesis of the Bim 3’UTR in mice. Ago2 Photoactivatable-Ribonucleoside Cross-linking and Immunoprecipitation (AGO2 PAR-CLIP) allowed us to assess whether the seed match mutations introduced into the Bim 3’UTR in vivo indeed precluded interaction with the miRNAs of the 17~92 cluster. This analysis was done in Abelson Virus transformed B cell progenitors which we generated from wild type and Bim3’UTRmut/mut E14.5 fetal livers, knowing that these cells express both BIM and miR-17~92, can be expanded to large numbers and incorporate 4-thiouridine sufficiently well. Focusing on 21 nt windows around the 9 putative miR-17~92 seed matches in the Bim 3’UTR and excluding reads lacking T-to-C transitions, we we verified that the introduced mutationsare functional, and we discovered differential seed match coverage in the wild type, with one miR-19 seed match co-dominating with two miR-92 seed matches, while in the mutant 3’UTR miR-17~92 binding was completely abolished. These results demonstrate functionality and efficiency of our genetically engineered mouse model for in vivo conditional seed-match inactivation. These results demonstrate functionality and efficiency of our genetically engineered mouse model for in vivo conditional seed-match inactivation.
2019-11-13 | GSE124605 | GEO
Project description:Key features of gene transcription, such as transcriptional pausing, divergent transcription, and enhancer RNA production can be explored using techniques based on the incorporation of synthetic nucleoside analogs into RNA, followed by pull-down and high-throughput sequencing. Whether these approaches can be adapted to expand our knowledge of the RNA-bound proteome is, however, unexplored. Here, we have designed a methodology (isolation of the newly transcribed RNA Interactome using ClicK reaction; RICK) based on the incorporation of 5-ethynyluridine (EU) into newly transcribed RNAs to systematically capture proteins bound to RNAs of wide scope including traditionally neglected non-polyadenylated RNAs. Amongst the novel RNA-binding proteins identified by RICK, we found mitotic regulators, components of the DNA damage response pathway, and epigenetic regulators. Because the protocol can be easily modified to include variations such as labeling time or transcriptional interference, RICK will enable an in depth and global interrogation of the RNA-bound proteome.
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Project description:miRNAs are short (20-23 nt) RNAs that are loaded into proteins of the Argonaute (AGO) family and guide them to partially complementary target sites on mRNAs, resulting in mRNA destabilization and/or translational repression. It is estimated that about 60% of the mammalian genes are potentially regulated by miRNAs, and therefore methods for experimental miRNA target determination have become valuable tools for the characterization of posttranscriptional gene regulation. Here we present a step-by-step protocol and guidelines for the computational analysis for the large-scale identification of miRNA target sites in cultured cells by photoactivatable ribonucleoside enhanced crosslinking and immunoprecipitation (PAR-CLIP) of AGO proteins.
| S-EPMC3508682 | biostudies-literature
Project description:System-wide cross-linking and immunoprecipitation (CLIP) approaches have unveiled regulatory mechanisms of RNA-binding proteins (RBPs) mainly in cultured cells due to limitations in the cross-linking efficiency of tissues. Here, we describe viP-CLIP (in vivo PAR-CLIP), a method capable of identifying RBP targets in mammalian tissues, thereby facilitating the functional analysis of RBP-regulatory networks in vivo. We applied viP-CLIP to mouse livers and identified Insig2 and ApoB as prominent TIAL1 target transcripts, indicating an important role of TIAL1 in cholesterol synthesis and secretion. The functional relevance of these targets was confirmed by showing that TIAL1 influences their translation in hepatocytes. Mutant Tial1 mice exhibit altered cholesterol synthesis, APOB secretion and plasma cholesterol levels. Our results demonstrate that viP-CLIP can identify physiologically relevant RBP targets by finding a factor implicated in the negative feedback regulation of cholesterol biosynthesis.
| S-EPMC10256721 | biostudies-literature
Project description:BACKGROUND: MicroRNAs (miRNAs) play a critical role in down-regulating gene expression. By coupling with Argonaute family proteins, miRNAs bind to target sites on mRNAs and employ translational repression. A large amount of miRNA-target interactions (MTIs) have been identified by the crosslinking and immunoprecipitation (CLIP) and the photoactivatable-ribonucleoside-enhanced CLIP (PAR-CLIP) along with the next-generation sequencing (NGS). PAR-CLIP shows high efficiency of RNA co-immunoprecipitation, but it also lead to T to C conversion in miRNA-RNA-protein crosslinking regions. This artificial error obviously reduces the mappability of reads. However, a specific tool to analyze CLIP and PAR-CLIP data that takes T to C conversion into account is still in need. RESULTS: We herein propose the first CLIP and PAR-CLIP sequencing analysis platform specifically for miRNA target analysis, namely miRTarCLIP. From scratch, it automatically removes adaptor sequences from raw reads, filters low quality reads, reverts C to T, aligns reads to 3'UTRs, scans for read clusters, identifies high confidence miRNA target sites, and provides annotations from external databases. With multi-threading techniques and our novel C to T reversion procedure, miRTarCLIP greatly reduces the running time comparing to conventional approaches. In addition, miRTarCLIP serves with a web-based interface to provide better user experiences in browsing and searching targets of interested miRNAs. To demonstrate the superior functionality of miRTarCLIP, we applied miRTarCLIP to two public available CLIP and PAR-CLIP sequencing datasets. miRTarCLIP not only shows comparable results to that of other existing tools in a much faster speed, but also reveals interesting features among these putative target sites. Specifically, we used miRTarCLIP to disclose that T to C conversion within position 1-7 and that within position 8-14 of miRNA target sites are significantly different (p value = 0.02), and even more significant when focusing on sites targeted by top 102 highly expressed miRNAs only (p value = 0.01). These results comply with previous findings and further suggest that combining miRNA expression and PAR-CLIP data can improve accuracy of the miRNA target prediction. CONCLUSION: To sum up, we devised a systematic approach for mining miRNA-target sites from CLIP-seq and PAR-CLIP sequencing data, and integrated the workflow with a graphical web-based browser, which provides a user friendly interface and detailed annotations of MTIs. We also showed through real-life examples that miRTarCLIP is a powerful tool for understanding miRNAs. Our integrated tool can be accessed online freely at http://miRTarCLIP.mbc.nctu.edu.tw.
| S-EPMC3549799 | biostudies-literature
Project description:Systematic analysis of the RNA-protein interactome requires robust and scalable methods. We here show the combination of two completely orthogonal, generic techniques to identify RNA-protein interactions: PAR-CLIP reveals a collection of RNAs bound to a protein whereas SILAC-based RNA pull-downs identify a group of proteins bound to an RNA. We investigated binding sites for five different proteins (IGF2BP1-3, QKI and PUM2) exhibiting different binding patterns. We report near perfect agreement between the two approaches. Nevertheless, they are non-redundant, and ideally complement each other to map the RNA-protein interaction network.
| S-EPMC3479200 | biostudies-literature
Project description:BackgroundNext-generation sequencing technologies have profoundly impacted biology over recent years. Experimental protocols, such as photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP), which identifies protein-RNA interactions on a genome-wide scale, commonly employ deep sequencing. With PAR-CLIP, the incorporation of photoactivatable nucleosides into nascent transcripts leads to high rates of specific nucleotide conversions during reverse transcription. So far, the specific properties of PAR-CLIP-derived sequencing reads have not been assessed in depth.MethodsWe here compared PAR-CLIP sequencing reads to regular transcriptome sequencing reads (RNA-Seq) to identify distinctive properties that are relevant for reference-based read alignment of PAR-CLIP datasets. We developed a set of freely available tools for PAR-CLIP data analysis, called the PAR-CLIP analyzer suite (PARA-suite). The PARA-suite includes error model inference, PAR-CLIP read simulation based on PAR-CLIP specific properties, a full read alignment pipeline with a modified Burrows-Wheeler Aligner algorithm and CLIP read clustering for binding site detection.ResultsWe show that differences in the error profiles of PAR-CLIP reads relative to regular transcriptome sequencing reads (RNA-Seq) make a distinct processing advantageous. We examine the alignment accuracy of commonly applied read aligners on 10 simulated PAR-CLIP datasets using different parameter settings and identified the most accurate setup among those read aligners. We demonstrate the performance of the PARA-suite in conjunction with different binding site detection algorithms on several real PAR-CLIP and HITS-CLIP datasets. Our processing pipeline allowed the improvement of both alignment and binding site detection accuracy.AvailabilityThe PARA-suite toolkit and the PARA-suite aligner are available at https://github.com/akloetgen/PARA-suite and https://github.com/akloetgen/PARA-suite_aligner, respectively, under the GNU GPLv3 license.
| S-EPMC5088580 | biostudies-literature