Identification of LC3B's binding mRNAs through a n-RIP-seq
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE243991 | GEO | 2024/05/29
REPOSITORIES: GEO
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Project description:To identify the target mRNAs of the m6A reader protein YTHDF2 in mouse hippocampus, we carired out anti YTHDF2 RNA Immunoprecipitation (RIP) followed by RNA-sequencencing. Using EZ-Magna RIP™ RNA-Binding Protein Immunoprecipitation Kit (Millipore), RNA from P40 wild type mouse hippocampus was pulled down by rabbit polyclonal anti-YTHDF2 (proteintech) and then sequenced on Illumina Novaseq 6000. The filtered reads were aligned to the mouse reference genome (GRCm38) using BWA mem (v 0.7.12).Then the MACS2 (version 2.1.0) peak calling software was used to identify regions of IP enrichment over background, followed by the motif detected by Homer (Heinz et al., 2010). Peak related genes are then confirmed by PeakAnnotator. Different peak analysis was based on the fold enrichment of peaks of different experiments. A peak was determined as different peak when the odds ratio between two groups was more than 2. Using the same method, genes associated with different peaks were identified. Finally, Biological replicates of anti-YTHDF2 RIP-Seq identified 408 mRNAs transcripts. This study provides gene lists which shows mRNA binding with YTHDF2 in mouse hippocampus.
2023-01-19 | GSE171791 | GEO
Project description:ac4C-RIP-seq to identify mRNA ac4C peaks
| PRJNA941324 | ENA
Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Scott Tenenbaum mailto:STenenbaum@uamail.albany.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). The RNA binding protein (RBP) associated mRNA sequencing track (RIP-Seq) is produced as part of the Encyclopedia of DNA Elements (ENCODE) Project (http://hgwdev.cse.ucsc.edu/ENCODE/index.html). This track displays transcriptional fragments associated with RBP in cell lines (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?type=cellType) K562 and GM12878, using Ribonomic profiling via Illumina SBS. In eukaryotic organisms gene regulatory networks require an additional level of coordination that links transcriptional and post-transcriptional processes. Messenger RNAs have traditionally been viewed as passive molecules in the pathway from transcription to translation. However, it is now clear that RNA-binding proteins play a major role in regulating multiple mRNAs in order to facilitate gene expression patterns. These tracks show the associated mRNAs that co-precipitate with the targeted RNA-binding proteins using RIP-Seq profiling. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf RBP-mRNA complexes were purified from cells grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell). RNA samples were amplified and converted to cDNA with the Nugen (http://www.nugeninc.com/) Ovation© RNA-Seq System and prepped for sequencing with the Illumina (http://www.illumina.com/) mRNA-Seq protocol. Approximately 30 million single end sequencing reads were obtained for each K562 and GM12878. RIP samples were analyzed for signal that was at or above the 60th percentile and statistically enriched compared to the negative control. Sequences were analyzed using TopHat (http://tophat.cbcb.umd.edu/) (Trapnell et al., 2009) with Bowtie (http://bowtie-bio.sourceforge.net/index.shtml) (Langmead et al., 2009). Peaks were called from the top 40% of TopHat normalized reads, with a max gap, min run of (24:48). Unions of overlapping peak regions from total RNA replicates (RIP-Input) are presented with p-value from a one tailed t-test for average signal from replicates versus 0 (no cut-off was used for totals). Replicate overlap for positive RIP treatment peaks (ELAVL1 and PABPC1) are presented with a p-value from one tailed t-test versus signal for same the region in negative control replicates (T7-tag). RIP peaks were from sequences longer than 120 bp and p-value < .05. For both totals (RIP-input) and RIPs, the peak scores are scaled relative p-values between treatment and control.
2012-06-06 | E-GEOD-35585 | biostudies-arrayexpress
Project description:We performed m6A-RIPs in Ascl1-induced neurons (iNeurons) to investigate the neuronal m6A epitranscriptome. Immunoprecipitation was done twice using two different antibodies, acquired from Abcam and Synaptic Systems (SySy), allowing for a more robust detection of m6A modification marks. Additionally, RIP-seq was performed separately with intact and fragmented RNA. The former approach allowed to identify proportions of m6A-modified transcripts among the total number, while the latter approach provided the information to identify genomic coordinates of m6A peaks.
2023-07-12 | E-MTAB-9542 | biostudies-arrayexpress
Project description:RNA-binding proteins (RBPs) and non-coding RNAs orchestrate post-transcriptional processes through the recognition of specific sites on targeted transcripts. Thus, understanding the connection between binding to specific sites and active regulation of the whole transcript is essential. Many immunoprecipitation techniques have been developed that identify either whole transcripts or binding sites of RBPs on each transcript using cell lysates. However, none of these methods simultaneously measures the strength of each binding site, and quantifies binding to whole transcripts. In this study, we compare current procedures and present Digestion Optimized (DO)-RIP-seq, a simple method that locates and quantifies RBP binding sites using a continuous metric. We have used the RBP HuR/ELAVL1 to demonstrate that DO-RIP-seq can quantify HuR binding sites with high coverage across the entire human transcriptome, thereby generating metrics of relative RNA binding strength. We demonstrate that this quantitative enrichment of binding sites is proportional to the relative in vitro binding strength for these sites. Also, we used DO-RIP-seq to quantify and compare HuR's binding to whole transcripts, thus allowing for seamless integration of binding site data with whole transcript measurements. Finally, we demonstrate that DO-RIP-seq is useful for identifying functional mRNA target sets, and binding sites where combinatorial interactions between HuR and AGO-microRNAs regulate the fate of the transcripts. Our data indicate that DO-RIP-seq will be useful for quantifying RBP binding events that regulate dynamic biological processes.
2016-10-13 | GSE87887 | GEO
Project description:To demonstrate RIPSeeker program that is developed for RIP-seq analyses, we generated RIP-seq data corresponding to the protein CCNT1 in HEK293 cell line using standard RIP-seq protocols described in Zhao et al., (2010).
2012-12-28 | GSE43170 | GEO
Project description:We performed gene expression profiling analysis using data obtained from RNA-seq and m6A peaks profiling analysis using data obtained from RIP-Seq of spared nerve injury model at 3rd, 7th, 14th postoperative day and sham group. To investigate the differential m6A expression profiling, we established spared nerve injury model at 3rd, 7th, 14th postoperative day and sham group.
2022-05-06 | GSE202166 | GEO
Project description:To demonstrate RIPSeeker program that is developed for RIP-seq analyses, we generated RIP-seq data corresponding to the protein CCNT1 in HEK293 cell line using standard RIP-seq protocols described in Zhao et al., (2010). We performed two in-house RIP-seq experiments both for CCNT1 in human HEK293 cells. Briefly, we generated tagged CCNT1 using a triple tag system that supports lentiviral stable expression and mammalian affinity purification (MAPLE) Mak et al (2010). The HEK293 cells stably expressing tagged CCNT1 was purified by M2 agarose beads, followed by RNA extraction by Trizol. The library synthesis was carried out according to the RIP-seq protocol described in Zhao et al., (2010) except that one of the two experiments was done with non-strand-specific sequencing.
2012-12-28 | E-GEOD-43170 | biostudies-arrayexpress