RNA-binding Proteins Binding Research Articles

RBP-Tar – a searchable database for experimental RBP binding sites

Background: RNA-binding proteins (RBPs) play a critical role in regulating gene expression by binding to specific sites on RNA molecules. Identifying these binding sites is crucial for understanding the many functions of RBPs in cellular function, development and disease. Current experimental methods for identifying RBP binding sites, such as ultra-violet (UV) crosslinking and immunoprecipitation (CLIP), and especially the enhanced CLIP (eCLIP) protocol, were developed to identify authentic RBP binding sites experimentally. Methods: To make this data more accessible to the scientific community, we have developed RBP-Tar (https://ncbr.muni.cz/RBP-Tar), a web server and database that utilises eCLIP data for 167 RBPs mapped on the human genome. The web server allows researchers to easily search and retrieve binding site information by genomic location and RBP name. Use case: Researchers can produce lists of all known RBP binding sites on a gene of interest, or produce lists of binding sites for one RBP on different genomic loci. Conclusions: Our future goal is to continue to populate the web server with additional experimental datasets from CLIP experiments as they become available and processed, making it an increasingly valuable resource for the scientific community.

On the limits of inferring biophysical parameters of RBP-RNA interactions from in vitro RNA Bind’n Seq data

We develop a thermodynamic model describing the binding of RNA binding proteins (RBP) to oligomers in vitro. We apply expectation-maximization to infer the specificity of RBPs, represented as position-specific weight matrices (PWMs), by maximizing the likelihood of RNA Bind’n Seq data from the ENCODE project. Analyzing these public data we find sequence motifs that can partly explain the data for more than half of the studied 111 RBPs, and for 48 of the proteins these motifs are consistent with the known specificity. Our code is publicly available, facilitating analysis of RBP binding data.

Multi-resolution sequence and structure feature extraction for binding site prediction

Circular ribonucleic acids (circRNAs) are single-stranded RNA molecules that form loops and are widely expressed in various cells and tissues. They interact with RNA-binding proteins (RBPs) and play a vital regulatory role in the onset and development of several diseases. Researchers have proposed various hybrid architecture prediction methods based on convolutional neural networks and recurrent neural networks to recognize the interactions and sites between circRNAs and RBPs and thus reveal the biological functions of circRNAs. However, existing methods usually ignore the structural information of circRNA, which may affect the modeling of circRNA and RBP binding modes. To address these problems, we propose a prediction model based on multi-resolution feature extraction. First, it generates sequence features using unsupervised word embedding and nucleotide density. Then, it uses implicit and explicit pseudo-secondary structure hybrid encoding to fuse sequence and structural information and better simulate circRNA-RBP binding patterns. Second, it uses an enhanced bidirectional sample convolution and interaction network encoder to capture and integrate high-order features of distinct resolutions from the multi-scale convolution module. This provides rich semantic input to the downstream bidirectional long short-term memory network to improve prediction accuracy. Experimental results on 37 circRNA and 31 linear RNA datasets show that our method has significant advantages in identifying RNA-RBP interactions. Furthermore, the four motifs learned by our method are verified against existing motif databases, indicating that it can discover biologically meaningful circRNA-RBP binding patterns.

Integrative annotation scores of variants for impact on RNA binding protein activities.

The ENCODE project generated a large collection of eCLIP-seq RNA binding protein (RBP) profiling data with accompanying RNA-seq transcriptomes of shRNA knockdown of RBPs. These data could have utility in understanding the functional impact of genetic variants, however their potential has not been fully exploited. We implement INCA (Integrative annotation scores of variants for impact on RBP activities) as a multi-step genetic variant scoring approach that leverages the ENCODE RBP data together with ClinVar and integrates multiple computational approaches to aggregate evidence. INCA evaluates variant impacts on RBP activities by leveraging genotypic differences in cell lines used for eCLIP-seq. We show that INCA provides critical specificity, beyond generic scoring for RBP binding disruption, for candidate variants and their linkage-disequilibrium partners. As a result, it can, on average, augment scoring of 46.2% of the candidate variants beyond generic scoring for RBP binding disruption and aid in variant prioritization for follow-up analysis. INCA is implemented in R and is available at https://github.com/keleslab/INCA.

Beyond reader proteins: RNA binding proteins and RNA modifications in conversation to regulate gene expression.

Post-transcriptional mRNA modifications play diverse roles in gene expression and RNA function. In many cases, RNA modifications function by altering how cellular machinery such as RNA binding proteins (RBPs) interact with RNA substrates. For instance, N6-methyladenosine (m6A) is recognized by the well-characterized YTH domain-containing family of "reader" proteins. For other mRNA modifications, similar global readers of modification status have not been clearly defined. Rather, most interactions between RBPs and RNA modifications have a more complicated dependence on sequence context and binding modality. The current handful of studies that demonstrate modifications impacting protein binding likely represent only a fraction of the full landscape. In this review, we dissect the known instances of RNA modifications altering RBP binding, specifically m6A, N1-methyladenosine (m1A), 5-methylcytosine (m5C), pseudouridine (Ψ), and internal N7-methylguanosine. We then review the biochemical properties of these and other identified mRNA modifications including dihydrouridine (D), N4-acetylcytosine (ac4C), and 2'-O-Methylation (Nme). We focus on how these properties would be likely to impact RNA:RBP interactions, including by changes to hydrogen bond potential, base-stacking efficiency, and RNA conformational preferences. The effects of RNA modifications on secondary structure have been well-studied, and we briefly discuss how structural effects imparted by modifications can lead to protein binding changes. Finally, we discuss strategies for uncovering as-yet-to-be identified modification-sensitive RBP:RNA Interactions. Coordinating future efforts to intersect the epitranscriptome and the RNA-protein interactome will illuminate the rules governing RNA modification recognition and the mechanisms responsible for the biological consequences of mRNA modification. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Processing > RNA Editing and Modification.

Decoding protein binding landscape on circular RNAs with base-resolution transformer models

Circular RNAs (circRNAs), a class of endogenous RNA with a covalent loop structure, can regulate gene expression by serving as sponges for microRNAs and RNA-binding proteins (RBPs). To date, most computational methods for predicting RBP binding sites on circRNAs focus on circRNA fragments instead of circRNAs. These methods detect whether a circRNA fragment contains binding sites, but cannot determine where are the binding sites and how many binding sites are on the circRNA transcript. We report a hybrid deep learning-based tool, CircSite, to predict RBP binding sites at single-nucleotide resolution and detect key contributed nucleotides on circRNA transcripts. CircSite takes advantage of convolutional neural networks (CNNs) and Transformer for learning local and global representations of circRNAs binding to RBPs, respectively. We construct 37 datasets of circRNAs interacting with proteins for benchmarking and the experimental results show that CircSite offers accurate predictions of RBP binding nucleotides and detects key subsequences aligning well with known binding motifs. CircSite is an easy-to-use online webserver for predicting RBP binding sites on circRNA transcripts and freely available at http://www.csbio.sjtu.edu.cn/bioinf/CircSite/.

Improved modeling of RNA-binding protein motifs in an interpretable neural model of RNA splicing

Sequence-specific RNA-binding proteins (RBPs) play central roles in splicing decisions. Here, we describe a modular splicing architecture that leverages in vitro-derived RNA affinity models for 79 human RBPs and the annotated human genome to produce improved models of RBP binding and activity. Binding and activity are modeled by separate Motif and Aggregator components that can be mixed and matched, enforcing sparsity to improve interpretability. Training a new Adjusted Motif (AM) architecture on the splicing task not only yields better splicing predictions but also improves prediction of RBP-binding sites in vivo and of splicing activity, assessed using independent data.

Profiling of RNA-binding protein binding sites by in situ reverse transcription-based sequencing.

RNA-binding proteins (RBPs) regulate diverse cellular processes by dynamically interacting with RNA targets. However, effective methods to capture both stable and transient interactions between RBPs and their RNA targets are still lacking, especially when the interaction is dynamic or samples are limited. Here we present an assay of reverse transcription-based RBP binding site sequencing (ARTR-seq), which relies on in situ reverse transcription of RBP-bound RNAs guided by antibodies to identify RBP binding sites. ARTR-seq avoids ultraviolet crosslinking and immunoprecipitation, allowing for efficient and specific identification of RBP binding sites from as few as 20 cells or a tissue section. Taking advantage of rapid formaldehyde fixation, ARTR-seq enables capturing the dynamic RNA binding by RBPs over a short period of time, as demonstrated by the profiling of dynamic RNA binding of G3BP1 during stress granule assembly on a timescale as short as 10 minutes.

Quantifying negative selection in human 3ʹ UTRs uncovers constrained targets of RNA-binding proteins

Many non-coding variants associated with phenotypes occur in 3ʹ untranslated regions (3ʹ UTRs), and may affect interactions with RNA-binding proteins (RBPs) to regulate gene expression post-transcriptionally. However, identifying functional 3ʹ UTR variants has proven difficult. We use allele frequencies from the Genome Aggregation Database (gnomAD) to identify classes of 3ʹ UTR variants under strong negative selection in humans. We develop intergenic mutability-adjusted proportion singleton (iMAPS), a generalized measure related to MAPS, to quantify negative selection in non-coding regions. This approach, in conjunction with in vitro and in vivo binding data, identifies precise RBP binding sites, miRNA target sites, and polyadenylation signals (PASs) under strong selection. For each class of sites, we identify thousands of gnomAD variants under selection comparable to missense coding variants, and find that sites in core 3ʹ UTR regions upstream of the most-used PAS are under strongest selection. Together, this work improves our understanding of selection on human genes and validates approaches for interpreting genetic variants in human 3ʹ UTRs.

GCLiPP: global crosslinking and protein purification method for constructing high-resolution occupancy maps for RNA binding proteins

GCLiPP is a global RNA interactome capture method that detects RNA-binding protein (RBP) occupancy transcriptome-wide. GCLiPP maps RBP-occupied sites at a higher resolution than phase separation-based techniques. GCLiPP sequence tags correspond with known RBP binding sites and are enriched for sites detected by RBP-specific crosslinking immunoprecipitation (CLIP) for abundant cytosolic RBPs. Comparison of human Jurkat T cells and mouse primary T cells uncovers shared peaks of GCLiPP signal across homologous regions of human and mouse 3′ UTRs, including a conserved mRNA-destabilizing cis-regulatory element. GCLiPP signal overlapping with immune-related SNPs uncovers stabilizing cis-regulatory regions in CD5, STAT6, and IKZF1.

Improved discovery of RNA-binding protein binding sites in eCLIP data using DEWSeq.

Enhanced crosslinking and immunoprecipitation (eCLIP) sequencing is a method for transcriptome-wide detection of binding sites of RNA-binding proteins (RBPs). However, identified crosslink sites can deviate from experimentally established functional elements of even well-studied RBPs. Current peak-calling strategies result in low replication and high false positive rates. Here, we present the R/Bioconductor package DEWSeq that makes use of replicate information and size-matched input controls. We benchmarked DEWSeq on 107 RBPs for which both eCLIP data and RNA sequence motifs are available and were able to more than double the number of motif-containing binding regions relative to standard eCLIP processing. The improvement not only relates to the number of binding sites (3.1-fold with known motifs for RBFOX2), but also their subcellular localization (1.9-fold of mitochondrial genes for FASTKD2) and structural targets (2.2-fold increase of stem-loop regions for SLBP. On several orthogonal CLIP-seq datasets, DEWSeq recovers a larger number of motif-containing binding sites (3.3-fold). DEWSeq is a well-documented R/Bioconductor package, scalable to adequate numbers of replicates, and tends to substantially increase the proportion and total number of RBP binding sites containing biologically relevant features.

FLARE: a fast and flexible workflow for identifying RNA editing foci

BackgroundFusion of RNA-binding proteins (RBPs) to RNA base-editing enzymes (such as APOBEC1 or ADAR) has emerged as a powerful tool for the discovery of RBP binding sites. However, current methods that analyze sequencing data from RNA-base editing experiments are vulnerable to false positives due to off-target editing, genetic variation and sequencing errors.ResultsWe present FLagging Areas of RNA-editing Enrichment (FLARE), a Snakemake-based pipeline that builds on the outputs of the SAILOR edit site discovery tool to identify regions statistically enriched for RNA editing. FLARE can be configured to analyze any type of RNA editing, including C to U and A to I. We applied FLARE to C-to-U editing data from a RBFOX2-APOBEC1 STAMP experiment, to show that our approach attains high specificity for detecting RBFOX2 binding sites. We also applied FLARE to detect regions of exogenously introduced as well as endogenous A-to-I editing.ConclusionsFLARE is a fast and flexible workflow that identifies significantly edited regions from RNA-seq data. The FLARE codebase is available at https://github.com/YeoLab/FLARE.

RBP-Tar – a searchable database for experimental RBP binding sites

Background: RNA-binding proteins (RBPs) play a critical role in regulating gene expression by binding to specific sites on RNA molecules. Identifying these binding sites is crucial for understanding the many functions of RBPs in cellular function, development and disease. Current experimental methods for identifying RBP binding sites, such as ultra-violet (UV) crosslinking and immunoprecipitation (CLIP), and especially the enhanced CLIP (eCLIP) protocol, were developed to identify authentic RBP binding sites experimentally. Methods: To make this data more accessible to the scientific community, we have developed RBP-Tar (https://ncbr.muni.cz/RBP-Tar), a web server and database that utilises eCLIP data for 167 RBPs mapped on the human genome. The web server allows researchers to easily search and retrieve binding site information by genomic location and RBP name. Use case: Researchers can produce lists of all known RBP binding sites on a gene of interest, or produce lists of binding sites for one RBP on different genomic loci. Conclusions: Our future goal is to continue to populate the web server with additional experimental datasets from CLIP experiments as they become available and processed, making it an increasingly valuable resource for the scientific community.

Alternative Splicing Outcomes Across an RNA-Binding Protein Concentration Gradient

Alternative splicing (AS) is a dynamic RNA processing step that produces multiple RNA isoforms from a single pre-mRNA transcript and contributes to the complexity of the cellular transcriptome and proteome. This process is regulated through a network of cis-regulatory sequence elements and trans-acting factors, most-notably RNA binding proteins (RBPs). The muscleblind-like (MBNL) and RNA binding fox-1 homolog (RBFOX) are two well characterized families of RBPs that regulate fetal to adult AS transitions critical for proper muscle, heart, and central nervous system development. To better understand how the concentration of these RBPs influences AS transcriptome wide, we engineered a MBNL1 and RBFOX1 inducible HEK-293 cell line. Modest induction of exogenous RBFOX1 in this cell line modulated MBNL1-dependent AS outcomes in 3 skipped exon events, despite significant levels of endogenous RBFOX1 and RBFOX2. Due to background RBFOX levels, we conducted a focused analysis of dose-dependent MBNL1 skipped exon AS outcomes and generated transcriptome wide dose–response curves. Analysis of this data demonstrates that MBNL1-regulated exclusion events may require higher concentrations of MBNL1 protein to properly regulate AS outcomes compared to inclusion events and that multiple arrangements of YGCY motifs can produce similar splicing outcomes. These results suggest that rather than a simple relationship between the organization of RBP binding sites and a specific splicing outcome, that complex interaction networks govern both AS inclusion and exclusion events across a RBP gradient.

Cumulative effects of weakly repressive regulatory regions in the 3’ UTR maintain PD-1 expression homeostasis in mammals

PD-1 has become a common target for cancer treatment. However, the molecular regulation of PD-1 expression homeostasis remains unclear. Here we report the PD-1 3’ UTR can dramatically repress gene expression via promoting mRNA decay. Deletion of the PD-1 3’ UTR inhibits T cell activity and promotes T-ALL cell proliferation. Interestingly, the robust repression is attributable to cumulative effects of many weak regulatory regions, which we show together are better able to maintain PD-1 expression homeostasis. We further identify several RNA binding proteins (RBPs) that modulate PD-1 expression via the 3’ UTR, including IGF2BP2, RBM38, SRSF7, and SRSF4. Moreover, despite rapid evolution, PD-1 3’ UTRs are functionally conserved and strongly repress gene expression through many common RBP binding sites. These findings reveal a previously unrecognized mechanism of maintaining PD-1 expression homeostasis and might represent a general model for how small regulatory effects play big roles in regulation of gene expression and biology.

PrismNet: predicting protein-RNA interaction using invivo RNA structural information.

Fundamental to post-transcriptional regulation, the in vivo binding of RNA binding proteins (RBPs) on their RNA targets heavily depends on RNA structures. To date, most methods for RBP-RNA interaction prediction are based on RNA structures predicted from sequences, which do not consider the various intracellular environments and thus cannot predict cell type-specific RBP-RNA interactions. Here, we present a web server PrismNet that uses a deep learning tool to integrate in vivo RNA secondary structures measured by icSHAPE experiments with RBP binding site information from UV cross-linking and immunoprecipitation in the same cell lines to predict cell type-specific RBP-RNA interactions. Taking an RBP and an RNA region with sequential and structural information as input ('Sequence & Structure' mode), PrismNet outputs the binding probability of the RBP and this RNA region, together with a saliency map and a sequence-structure integrative motif. The web server is freely available at http://prismnetweb.zhanglab.net.

PO-01-145 DYNAMIC UTR COMPOSITION IMPACTS RNA BINDING PROTEIN COMPLEXING TO CONTROL TRANSLATION AND LIMIT CARDIAC GAP JUNCTION FORMATION DURING STRESS

Translational control has emerged as a critical yet dynamic process, representing one of the most rapid means by which the cardiomyocyte can alter its proteome. Several key cardiac mRNAs, including connexin43 (Cx43, gene name GJA1) are understood to undergo alternative translation initiation with resulting products (ie, GJA1-20k) impacting cardiac function. We previously found alterations to GJA1 mRNA untranslated region (UTR) length occur in aged and stressed heart tissue, suppressing internal translation of GJA1-20k, and limiting Cx43 gap junction formation. Having therefore identified dynamic mRNA cis element-based regulation of Cx43/GJA1-20k translation, we next asked what trans-acting factors are at play to alter GJA1 mRNA translation during stress. The IMP family of RNA binding proteins (RBPs) regulate alternative and canonical translation initiation of several genes, which led us to investigate how they may impact GJA1 mRNA. Using GJA1 as a model RNA, we test the hypothesis that alternative transcription start site usage controls inclusion of cis-acting elements in the mRNA 5’UTR affecting RBP binding and regulation of translation. Pathological hypertrophy was induced by isoproterenol deliverey to adult mice via implanted minipumps. Mouse models are complemented with matured human IPSC-derived cardiomyocytes, primary mouse ventricular cardiomyocytes, exposed to chronic hypoxia or TGF-β in vitro. Single molecule fluorescence in situ hybridization (smFISH) coupled with super-resolution microscopy localize GJA1 mRNA and RBPs. Hypertrophic hearts show reduced GJA1-20k and IMP1 expression. Using smFISH to label GJA1 mRNA, we find IMP1 complexes with GJA1 mRNA predominantly in comparison to IMP2 and 3, and that this complexing is reduced during stress, concomitant with loss of GJA1-20k internal translation. Biochemical assays confirm GJA1 mRNA/IMP1 binding by RNA-IP and synthetic reduction of IMP1 expression by RNAi or CRISPR/Cas9 alters GJA1 mRNA localization, reduces internal translation of GJA1-20k, and limits gap junction formation. We find comparable results during hypoxia in primary mouse cardiomyocytes and human induced pluripotent stem cell derived cardiomyocytes. Dynamic GJA1-5’UTR composition therefore represents a powerful mechanism connecting alterations in transcription to gene-specific translational regulation by RBPs such as IMP1, disruption of intercellular communication during stress, and arrhythmogenesis.

Tissue-specific regulation of gene expression via unproductive splicing.

Eukaryotic gene expression is regulated post-transcriptionally by a mechanism called unproductive splicing, in which mRNA is triggered to degrade by the nonsense-mediated decay (NMD) pathway as a result of regulated alternative splicing (AS). Only a few dozen unproductive splicing events (USEs) are currently documented, and many more remain to be identified. Here, we analyzed RNA-seq experiments from the Genotype-Tissue Expression (GTEx) Consortium to identify USEs, in which an increase in the NMD isoform splicing rate is accompanied by tissue-specific down-regulation of the host gene. To characterize RNA-binding proteins (RBPs) that regulate USEs, we superimposed these results with RBP footprinting data and experiments on the response of the transcriptome to the perturbation of expression of a large panel of RBPs. Concordant tissue-specific changes between the expression of RBP and USE splicing rate revealed a high-confidence regulatory network including 27 tissue-specific USEs with strong evidence of RBP binding. Among them, we found previously unknown PTBP1-controlled events in the DCLK2 and IQGAP1 genes, for which we confirmed the regulatory effect using small interfering RNA (siRNA) knockdown experiments in the A549 cell line. In sum, we present a transcriptomic pipeline that allows the identification of tissue-specific USEs, potentially many more than were reported here using stringent filters.

Analysis of RBP expression and binding sites identifies PTBP1 as a regulator of CD19 expression in B-ALL

ABSTRACT Despite massive improvements in the treatment of B-ALL through CART-19 immunotherapy, a large number of patients suffer a relapse due to loss of the targeted epitope. Mutations in the CD19 locus and aberrant splicing events are known to account for the absence of surface antigen. However, early molecular determinants suggesting therapy resistance as well as the time point when first signs of epitope loss appear to be detectable are not enlightened so far. By deep sequencing of the CD19 locus, we identified a blast-specific 2-nucleotide deletion in intron 2 that exists in 35% of B-ALL samples at initial diagnosis. This deletion overlaps with the binding site of RNA binding proteins (RBPs) including PTBP1 and might thereby affect CD19 splicing. Moreover, we could identify a number of other RBPs that are predicted to bind to the CD19 locus being deregulated in leukemic blasts, including NONO. Their expression is highly heterogeneous across B-ALL molecular subtypes as shown by analyzing 706 B-ALL samples accessed via the St. Jude Cloud. Mechanistically, we show that downregulation of PTBP1, but not of NONO, in 697 cells reduces CD19 total protein by increasing intron 2 retention. Isoform analysis in patient samples revealed that blasts, at diagnosis, express increased amounts of CD19 intron 2 retention compared to normal B cells. Our data suggest that loss of RBP functionality by mutations altering their binding motifs or by deregulated expression might harbor the potential for the disease-associated accumulation of therapy-resistant CD19 isoforms.

Single-cell RNA binding protein regulatory network analyses reveal oncogenic HNRNPK-MYC signalling pathway in cancer

RNA-binding proteins (RBPs) are key players of gene expression and perturbations of RBP-RNA regulatory network have been observed in various cancer types. Here, we propose a computational method, RBPreg, to identify the RBP regulators by integration of single cell RNA-Seq (N = 233,591) and RBP binding data. Pan-cancer analyses suggest that RBP regulators exhibit cancer and cell specificity and perturbations of RBP regulatory network are involved in cancer hallmark-related functions. We prioritize an oncogenic RBP-HNRNPK, which is highly expressed in tumors and associated with poor prognosis of patients. Functional assays performed in cancer cells reveal that HNRNPK promotes cancer cell proliferation, migration, and invasion in vitro and in vivo. Mechanistic investigations further demonstrate that HNRNPK promotes tumorigenesis and progression by directly binding to MYC and perturbed the MYC targets pathway in lung cancer. Our results provide a valuable resource for characterizing RBP regulatory networks in cancer, yielding potential biomarkers for precision medicine.