Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Mapping RNA-RNA interactome and RNA structures in vivo

ABSTRACT: This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

ORGANISM(S): Mus musculus

SUBMITTER: Sheng Zhong

PROVIDER: E-GEOD-81388 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Mapping RNA-RNA interactome and RNA structures in vivo with MARIO

Project description:Many biological processes are regulated by RNA-RNA interactions 1, nonetheless it remains formidable to analyze the entire RNA interactome. We developed a method, MARIO (MApping Rna-rna Interactions in vivO), to map protein-assisted RNA-RNA interactions in vivo. By circumventing the selection for a specific RNA-binding protein 2-5, our approach vastly expands the identifiable portion of the RNA interactome. Using this technology, we mapped the RNA interactome in mouse embryonic stem cells, which was composed of 46,780 RNA-RNA interactions. The RNA interactome was a scale-free network, with several lincRNAs and mRNAs emerging as hubs. We validated an interaction between two hubs, Malat1 and Slc2a3 using single molecule RNA fluorescence in situ hybridization. Base pairing was observed at the interaction sites of long RNAs, and was particularly strong in transposonRNA-mRNA and lincRNA-mRNA interactions. This reveals a new type of regulatory sequences acting in trans. Consistent with their hypothesized roles, the RNA interaction sites were more evolutionarily conserved than other regions of the transcripts. MARIO also provided new information on RNA structures, by simultaneously revealing the footprint of single stranded regions and the spatially proximal sites of each RNA. The unbiased mapping of the protein-assisted RNA interactome with minimum perturbation of cell physiology will greatly expand our capacity to investigate RNA functions. Three (3) ESC samples with different treatment (different digestion size and/or crosslinking method) and one (1) MEF sample were included to test our new approach for RNA-interactome mapping and the different samples were analyzed to show RNA interactome differences between them.

2016-06-23 | E-GEOD-61489 | biostudies-arrayexpress

A lncRNA from the FTO locus acts as an inhibitor of the m6A writer complex and p53 tumor suppression signaling

Project description:control RNA and FTO-IT1 RNA and their interacting proteins were pulled down by biotin-streptavidin beads to see the interacting protein of FTO-IT1 RNA.

2024-08-09 | PXD041053 | Pride

HARD-AP-drived RBPome in HEK293 cells, mouse brain and kidney without UV-crosslinking

Project description:Identification of RBPs proteome in HEK293 cells and adult mouse brain and kidney which were not treated with UV light before isolation with HARD beads.

2024-08-26 | PXD053382 | Pride

RBPs proteome in HEK293 cells, mESCs and mouse organs

Project description:Identification of RBPs proteome in HEK293 cells, mouse embryonic stem cells (mESCs) and adult mouse primary organs (brain, heart, lung, kidney, liver)

2024-08-26 | PXD037105 | Pride

RBS-ID: Comprehensive identification of RNA-binding sites at single amino acid-resolution

Project description:We developed RBS-ID, which greatly simplifies the RNA moiety by chemical cleavage, reducing the complexity of MS/MS search space to accurately identify and localize RBS in peptides. RBS-ID comprehensively and robustly identifies RNA-binding sites at both proteome and single protein level.

2020-06-02 | PXD016254 | Pride

A simple method for generating high-resolution maps of genome wide protein binding

Project description:Chromatin immunoprecipitation (ChIP) and its derivatives are the main techniques used to determine transcription factor binding sites. However, conventional ChIP with sequencing (ChIP-seq) has problems with poor resolution and newer techniques require significant experimental alterations and complex bioinformatics. Here we build upon our high-resolution crosslinking ChIP-seq (X-ChIP-seq) method and compare it to existing methodologies. By using micrococcal nuclease, which has both endo- and exo-nuclease activity to fragment the chromatin and thereby generate precise protein-DNA footprints, high-resolution X-ChIP-seq achieves single base pair resolution of transcription factor binding. A significant advantage of this protocol is the minimal alteration to the conventional ChIP-seq workflow and simple bioinformatic processing. Using High-resolution X-ChIP-seq we determined the genome-wide binding profile of various DNA binding proteins.

2015-06-12 | E-GEOD-67454 | biostudies-arrayexpress

A transcriptome-wide atlas of RNP compositions reveals diverse classes of mRNAs and lncRNAs

Project description:Aim: To determine how different classes of transcript (e.g. lncRNAs and mRNAs) are defined in the cell. Approach: We determined the transcriptome-wide targets of key RNA packaging, maturation, export and turnover factors. We used the CRAC technique, whereby RNA:protein interactions are fixed by UV irradiation of yeast cultures, and RNA:protein complexes obtained via a stringent multi-step purification. A mild RNase treatment fragments the bound RNAs, which are then used as templates for RT-PCR, prior to sequencing. This approach enabled us to compare the maturation and turnover pathways of mRNAs and lncRNAs. Results: Our data reveal that mRNA and lncRNA maturation pathways diverge prior to nuclear export, and 3' end processing emerges as a key step in determining transcript fate. Our analyses also reveal when and where the tested proteins bind to mRNAs, and thus offer much insight into the dynamic assembly of mRNPs. Analyses of reads with non-genome-encoded A-tails enabled us to distinguish proteins bound to stable poly(A) tails on full-length mRNAs, and to short oligo(A)4-5 tails on nuclear surveillance intermediates. This lead to the identification of a novel class of promoter-proximal ncRNAs, that we suggest arise from early termination within protein-coding genes. Identification of targets of RNA packaging, processing, export and turnover factors in wild-type cells; replicates included for some but not all samples; “BY” samples are negative controls, which use untagged strains

2013-08-29 | E-GEOD-46742 | biostudies-arrayexpress

CLIP-seq of S. cerevisiae Drn1-TAP and Dbr1-TAP

Project description:Data for replicate Drn1-TAP and Dbr1-TAP CLIP-seq experiments to identify RNA-protein interactions Drn1-TAP and Dbr1-TAP CLIP-seq

2013-06-28 | E-GEOD-44959 | biostudies-arrayexpress

Early cleavage of preimplantation embryos is regulated by tRNAGln-TTG-derived small RNAs present in mature spermatozoa

Project description:Sperm-derived tsRNAs could act as acquired epigenetic factors and contribute to offspring phenotypes. However, the roles of specific tsRNAs in early embryo development remain to be elucidated. Here, by using pigs as a research model, we probed the tsRNA dynamics during spermatogenesis and sperm maturation, and demonstrated the delivery of tsRNAs from semen-derived exosomes to spermatozoa. By microinjection of the antisense sequence into in vitro fertilized oocytes and subsequent single-cell RNA-sequencing of embryos, we identified a specific functional tsRNA group (Gln-TTGs) that participate in the early cleavage of porcine preimplantation embryos, probably by regulating cell cycle-associated genes. Thus, specific tsRNAs present in mature spermatozoa play significant roles during preimplantation embryo development.

2020-07-13 | PXD019054 | Pride

Sex comb on midleg (Scm) is a functional link between PcG repressive complexes in Drosophila

Project description:We profiled Sex comb on midleg (Scm), Pc and E(z) in fly embryos and S2 based on BioTAP-XL ChIP-seq. ChIP-seq revealed that Scm is co-localized with PRC1, PRC2, and H3K27me3 in both S2 cells and embryos. Genomic binding/occupancy profiling of Scm, Pc and E(z) by high throughput sequencing

2015-07-09 | E-GEOD-66183 | 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