Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Inherent Specificity and Mutational Sensitivity as Quantitative Metrics for RBP Binding

ABSTRACT: Interactions between RNAs and RNA binding proteins (RBPs) regulate gene expression in eukaryotic cells. RNA-RBP affinities measured in vitro reveal diverse binding specificities, yet approaches to directly compare specificities across RBPs are lacking. Here, we introduce two quantitative metrics: inherent specificity, which measures how selectively an RBP distinguishes its strongest binding motif from all possible motifs, and mutational sensitivity, which assesses tolerance to single nucleotide variations within preferred motifs. Analyzing high-throughput sequencing datasets, we compared these metrics across 100 RBPs in vitro and 27 RBPs in cells, finding strong correlation between in vitro and cellular measurements for RBPs that bind RNA independently of a local structural context. Through CLIP experiments with swapped RNA recognition motifs between a low-specificity RBP (RBM25) and a high-specificity RBP (HNRNPC), we demonstrated that sequence specificity can be transferred between protein contexts. Using these insights, we developed mathematical models showing how RBPs with different specificity profiles compete for binding sites, revealing how variations in inherent specificity and mutational sensitivity influence target selection. Together, our results provide a quantitative framework for modeling RNA-RBP interactions and designing RBPs with targeted specificity.

ORGANISM(S): Homo sapiens

PROVIDER: GSE291358 | GEO | 2025/03/28

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Inherent Specificity and Mutational Sensitivity as Quantitative Metrics for RBP Binding

Project description:Inherent Specificity and Mutational Sensitivity as Quantitative Metrics for RBP Binding

| PRJNA1233231 | ENA

rec-Y2H matrix in S. cerevisiae screening reveals a vast potential for direct protein-protein interactions among RNA binding proteins

Project description:RNA-binding proteins (RBPs) are crucial factors of post-transcriptional gene regulation and their modes of action are intensely investigated. At the center of attention are RNA motifs that guide where RBPs bind. However, sequence motifs recognized by RBPs are typically a poor predictor of RBP-RNA interactions in vivo. It is hence believed that many RBPs recognize RNAs as complexes, to increase specificity and regulatory potential. To probe the potential for RBP–RBP complex formation, we assembled a library of 978 mammalian RBPs and used rec-Y2H screening to detect direct interactions between RBPs, sampling >1M possible interactions. We discovered 1994 new interactions and demonstrate that our interaction screening discovers RBP pairs that bind RNAs adjacently. We further find that the mRNA binding region preferences of an RBP can deviate, depending on its adjacently binding interaction partner. Finally, we reveal novel RBP–RBP interaction networks among major RNA processing steps and show that RBP mutations observed in cancer rewire spliceosomal interaction networks.

2021-09-01 | E-MTAB-9612 | biostudies-arrayexpress

A comprehensive resource of RNA-binding motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function

Project description:Although RNA-binding proteins (RBPs) are key regulators of gene expression, their RNA-binding specificities, i.e., motifs, have not been comprehensively determined. Here, we introduce EuPRI (Eukaryotic Protein-RNA Interactions), a freely available resource of RNA motifs for 34,746 RBPs from 690 eukaryotes. EuPRI includes in vitro binding data for 504 RBPs, including newly collected RNAcompete data for 174 RBPs, along with thousands of predicted motifs. We predict these motifs with a new algorithm, Joint Protein-Ligand Embedding (JPLE), which can detect distant homology relationships and map specificity-determining peptides. EuPRI quadruples the number of available RBP motifs, expanding the motif repertoire across all major eukaryotic clades, and assigning motifs to the majority of human RBPs. We demonstrate the utility of EuPRI for inferring post-transcriptional function and evolutionary relationships by identifying rapid, recent evolution of post-transcriptional regulatory networks in worms and plants, in contrast to the vertebrate RNA motif set, which has remained relatively stable after a large expansion between metazoan and vertebrate ancestors.

2025-06-04 | GSE192895 | GEO

Signal-noise metrics for RNA binding protein identification reveal broad spectrum protein-RNA interaction frequencies and dynamics

Project description:Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven to be analytically challenging and prone to error. Here we report a novel method termed LEAP-RBP for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce new strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. The utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.

2023-08-01 | GSE235647 | GEO

RNase-mediated protein footprint sequencing reveals protein-binding sites throughout the human transcriptome

Project description:RNAs are continuously associated with RNA-binding proteins (RBPs), and these interactions are necessary for many key cellular processes ranging from splicing to chromatin regulation. Although numerous approaches have been developed to map RNA-binding sites of individual RBPs, few methods exist that allow assessment of global RBP-RNA interactions. Here, we describe a universal, high-throughput, ribonuclease-mediated protein footprint sequencing approach that reveals RNA-protein interaction sites throughout a transcriptome of interest. We apply this method to the HeLa transcriptome and compare RBP binding sites found using different cross-linkers and ribonucleases. From this analysis, we identify numerous putative RBP binding motifs, reveal novel insights into co-binding by RBPs, and uncover a significant enrichment for disease-associated polymorphisms within RBP interaction sites. Protein interaction profile sequencing (PIP-seq) in HeLa cells. Two crosslinkers (formaldehyde and UV) with two RNases (dsRNase and ssRNase) each, as well as a no-crosslink sample. Performed with and without proteins. Three replicates for formaldehyde, two replicates for UV, single replicate for no crosslinker.

2013-11-06 | E-GEOD-49309 | biostudies-arrayexpress

Global analysis of the RNA-protein interaction and RNA secondary structure landscapes of the Arabidopsis nucleus

Project description:Post-transcriptional regulation in eukaryotes requires cis- and trans-acting features and factors including RNA secondary structure, and RNA-binding proteins (RBPs). However, a comprehensive view of the structural and RBP interaction landscape of RNAs in the nucleus has yet to be compiled for any organism. Here, we use our ribonuclease-mediated structure and RBP binding site mapping approach on Arabidopsis seedling nuclei in vivo to globally profile these features within the nuclear compartment. We reveal opposing patterns of secondary structure and RBP binding levels throughout native messenger RNAs that demarcate alternative splicing and polyadenylation. We also uncover a collection of protein bound sequence motifs, and identify their structural contexts, co-occurrences in transcripts encoding functionally related proteins, and interactions with putative RBPs. Finally, we identify a nuclear role for the chloroplast RBP, CP29A. In total, we provide the first simultaneous view of the RNA secondary structure and RBP interaction landscapes in a eukaryotic nucleus. Protein interaction profile sequencing (PIP-seq) in Arabidopsis seedling nuclei. These are crosslinked with formaldehyde and treated with two RNases (ssRNase and dsRNase) with two replicates

2014-12-16 | E-GEOD-58974 | biostudies-arrayexpress

Tranposable elements modulate human mRNAs and lncRNAs via specific RNA-protein interactions.

Project description:Transposable elements (TEs) have significantly influenced the evolution of transcriptional regulatory networks in the human genome. Post-transcriptional regulation of human genes by TE-derived sequences has been observed in specific contexts, but has yet to be systematically and comprehensively investigated. Here, studied a collection of CLIP-Seq (CrossLinked ImmunoPrecipitation) experiments mapping the RNA binding sites for a diverse set of 46 human proteins across 68 experiments to explore the role of TEs in post-transcriptional regulation genome-wide via RNA-protein interactions. We detected widespread interactions between RNA binding proteins (RBPs) and various families of TE-derived sequence in the CLIP-Seq data. Alignment coverage clustered on specific positions of the TE consensus sequences, illuminating a diversity of TE-specific motifs for many RBPs. Evidence of binding and conservation of these motifs in the nonrepetitive transcriptome suggest that TEs have appropriated existing sequence preferences of the RBP. Upon depletion of the RBPs, transcripts possessing TE-derived binding sites were similarly regulated as those bound in nonrepetitive sequence. However, in a few cases the effect of RBP binding depended on the specific TE family boundM-bM-^@M-^Te.g., the ubiquitously expressed RBP HuR conferred opposite effects on stability to transcripts when bound to Alu elements versus other families. Our meta-analysis suggests a widespread role for TEs in shaping RNA-protein regulatory networks in the human genome. HuR formaldehyde RIP-Seq in K562 cells, with RIP and input sequenced in triplicate.

2014-09-10 | E-GEOD-61238 | biostudies-arrayexpress

RNase-mediated protein footprint sequencing reveals protein-binding sites throughout the human transcriptome

2013-11-06 | GSE49309 | GEO

A compendium of RNA-binding motifs for analysis of gene regulation

Project description:RNA binding proteins are key regulators of gene expression, yet only a small fraction of these proteins has been functionally characterized. Here, we report the first large-scale analysis of the RNA motifs recognised by RNA binding proteins, encompassing 205 distinct proteins from 24 diverse eukaryotes. The sequence specificities of RBPs display deep evolutionary conservation, such that the recognition preferences for a large fraction of metazoan RNA binding proteins can be inferred from the sequences of their binding domains. The motifs we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA binding proteins in both normal physiology and in human disease. These data provide an unprecedented global view of RBPs and their targets and constitute an invaluable resource for defining post-transcriptional regulatory mechanisms in eukaryotes. Here, we analyze the RNA-binding preferences of 205 distinct RNA-binding proteins from 24 different eukaryotes, using RNAcompete. In this assay, purified GST-tagged RBPs are incubated with an excess of RNA pool and bound RNA from individual pulldowns are directly labeled, hybridized to a custom Agilent 244K microarray, and analyzed computationally to identify RNA-binding motifs.

2013-05-10 | E-GEOD-41235 | biostudies-arrayexpress

HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence

Project description:RNA-binding proteins (RBPs) control RNA metabolism to orchestrate gene expression, and dysfunctional RBPs underlie many human diseases. Proteome-wide discovery efforts predict thousands of novel RBPs, many of which lack canonical RNA-binding domains. Here, we present a hybrid ensemble RBP classifier (HydRA) that leverages information from both intermolecular protein interactions and internal protein sequence patterns to predict RNA-binding capacity with unparalleled specificity and sensitivity using support vector machine, convolutional neural networks and transformer-based protein language models. HydRA enables Occlusion Mapping to robustly detect known RNA-binding domains and to predict hundreds of uncharacterized RNA-binding domains. Enhanced CLIP validation for a diverse collection of RBP candidates reveals genome-wide targets and confirms RNA-binding activity for HydRA-predicted domains. The HydRA computational framework accelerates construction of a comprehensive RBP catalogue and expands the set of known RNA-binding protein domains.

2023-07-10 | GSE221870 | GEO

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