In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.
RNA-binding proteins (RBPs) have roles in the regulation of many post-transcriptional steps in gene expression, but relatively few RBPs have been systematically studied. We searched for the RNA targets of 40 proteins in the yeast Saccharomyces cerevisiae: a selective sample of the approximately 600 annotated and predicted RBPs, as well as several proteins not annotated as RBPs. At least 33 of these 40 proteins, including three of the four proteins that were not previously known or predicted to be RBPs, were reproducibly associated with specific sets of a few to several hundred RNAs. Remarkably, many of the RBPs we studied bound mRNAs whose protein products share identifiable functional or cytotopic features. We identified specific sequences or predicted structures significantly enriched in target mRNAs of 16 RBPs. These potential RNA-recognition elements were diverse in sequence, structure, and location: some were found predominantly in 3′-untranslated regions, others in 5′-untranslated regions, some in coding sequences, and many in two or more of these features. Although this study only examined a small fraction of the universe of yeast RBPs, 70% of the mRNA transcriptome had significant associations with at least one of these RBPs, and on average, each distinct yeast mRNA interacted with three of the RBPs, suggesting the potential for a rich, multidimensional network of regulation. These results strongly suggest that combinatorial binding of RBPs to specific recognition elements in mRNAs is a pervasive mechanism for multi-dimensional regulation of their post-transcriptional fate.
Regulation of gene transcription has been extensively studied, but much less is known about how the fates of the resulting mRNA transcripts are regulated. We were intrigued by the fact that while most eukaryotic genomes encode hundreds of RNA-binding proteins (RBPs), the targets and regulatory roles of only a small fraction of these proteins have been characterized. In this study, we systematically identified the RNAs associated with a select sample of 40 of the approximately 600 predicted RBPs in the budding yeast, Saccharomyces cerevisiae. We found that most of these RBPs bound specific sets of mRNAs whose protein products share physiological themes or similar locations within the cell. For 16 of the 40 RBPs, we identified sequence motifs significantly enriched in their RNA targets that presumably mediate recognition of the target by the RBP. The intricate, overlapping patterns of mRNAs associated with RBPs suggest an extensive combinatorial system for post-transcriptional regulation, involving dozens or even hundreds of RBPs. The organization and molecular mechanisms involved in this regulatory system, including how RBP–mRNA interactions are integrated with signal transduction systems and how they affect the fates of their RNA targets, provide abundant opportunities for investigation and discovery.
A systematic study of the RNA targets of 40 known or predicted RNA-binding proteins in yeast suggests that an extensive system of dozens or hundreds of specific RNA-binding proteins may act to regulate the post-transcriptional fate of most or all RNAs in the yeast cell.
Posttranscriptional gene regulation is a rapid and efficient process to adjust the proteome of a cell to a changing environment. RNA-binding proteins (RBPs) are the master regulators of mRNA processing and translation and are often aberrantly expressed in cancer. In addition to well-studied transcription factors, RBPs are emerging as fundamental players in tumor development. RBPs and their mRNA targets form a complex network that plays a crucial role in tumorigenesis. This paper describes mechanisms by which RBPs influence the expression of well-known oncogenes, focusing on precise examples that illustrate the versatility of RBPs in posttranscriptional control of cancer development. RBPs appeared very early in evolution, and new RNA-binding domains and combinations of them were generated in more complex organisms. The identification of RBPs, their mRNA targets, and their mechanism of action have provided novel potential targets for cancer therapy.
RNAs in cells are associated with RNA-binding proteins (RBPs) to form ribonucleoprotein (RNP) complexes. The RBPs influence the structure and interactions of the RNAs and play critical roles in their biogenesis, stability, function, transport and cellular localization. Eukaryotic cells encode a large number of RBPs (thousands in vertebrates), each of which has unique RNA-binding activity and protein-protein interaction characteristics. The remarkable diversity of RBPs, which appears to have increased during evolution in parallel to the increase in the number of introns, allows eukaryotic cells to utilize them in an enormous array of combinations giving rise to a unique RNP for each RNA. In this short review, we focus on the RBPs that interact with pre-mRNAs and mRNAs and discuss their roles in the regulation of post-transcriptional gene expression.
RNA; ribonucleoproteins; RNPs; RNA-binding proteins; RNA processing; gene expression 1 Equal contributions
Gene expression is regulated at multiple levels, including transcription and translation, as well as mRNA and protein stability. Although systems-level functions of transcription factors and microRNAs are rapidly being characterized, few studies have focused on the posttranscriptional gene regulation by RNA binding proteins (RBPs). RBPs are important to many aspects of gene regulation. Thus, it is essential to know which genes encode RBPs, which RBPs regulate which gene(s), and how RBP genes are themselves regulated. Here we provide a comprehensive compendium of RBPs from the nematode Caenorhabditis elegans (wRBP1.0). We predict that as many as 887 (4.4%) of C. elegans genes may encode RBPs ~250 of which likely function in a gene-specific manner. In addition, we find that RBPs, and most notably gene-specific RBPs, are themselves enriched for binding and modification by regulatory proteins, indicating the potential for extensive regulation of RBPs at many different levels. wRBP1.0 will provide a significant contribution toward the comprehensive delineation of posttranscriptional regulatory networks and will provide a resource for further studies regulation by RBPs.
RNA binding protein; gene expression; regulation; systems biology; C. elegans; RBP
RBP-Jkappa is a sequence-specific DNA binding protein which plays a central role in signalling downstream of the Notch receptor by physically interacting with its intracellular region. Although at least four Notch genes exist in mammals, it is unknown whether each Notch requires a specific downstream signalling molecule. Here we report isolation and characterization of a mouse RBP-Jkappa-related gene named RBP-L that is expressed almost exclusively in lung, in contrast to the ubiquitous expression of RBP-Jkappa. For simplicity, we propose to call RBP-Jkappa RBP-J. The RBP-L protein bound to a DNA sequence almost identical to that of RBP-J. Surprisingly, RBP-L did not interact with any of the known four mouse Notch proteins. Although we found that RBP-L and EBNA-2 cooperated in transcriptional activation, they did not show significantly strong protein-protein interaction that can be detected by several in vivo and in vitro assays. This is again in contrast to physical association of RBP-J with EBNA-2. Several models to explain functional interaction between RBP-L and EBNA-2 are discussed.
Metazoan genomes encode hundreds of RNA-binding proteins (RBPs). These proteins regulate post-transcriptional gene expression and have critical roles in numerous cellular processes including mRNA splicing, export, stability and translation. Despite their ubiquity and importance, the binding preferences for most RBPs are not well characterized. In vitro and in vivo studies, using affinity selection-based approaches, have successfully identified RNA sequence associated with specific RBPs; however, it is difficult to infer RBP sequence and structural preferences without specifically designed motif finding methods. In this study, we introduce a new motif-finding method, RNAcontext, designed to elucidate RBP-specific sequence and structural preferences with greater accuracy than existing approaches. We evaluated RNAcontext on recently published in vitro and in vivo RNA affinity selected data and demonstrate that RNAcontext identifies known binding preferences for several control proteins including HuR, PTB, and Vts1p and predicts new RNA structure preferences for SF2/ASF, RBM4, FUSIP1 and SLM2. The predicted preferences for SF2/ASF are consistent with its recently reported in vivo binding sites. RNAcontext is an accurate and efficient motif finding method ideally suited for using large-scale RNA-binding affinity datasets to determine the relative binding preferences of RBPs for a wide range of RNA sequences and structures.
Many disease-associated mutations do not change the protein sequence of genes; instead they change the instructions on how a gene's mRNA transcript should be processed. Translating these instructions allows us to better understand the connection between these mutations and disease. RNA-binding proteins (RBP) perform this translation by recognizing particular “phrases” that occupy short regions of the transcript. Recognition occurs by the binding of the RBP to the phrase. The set of phrases bound by a particular RBP is defined by the RNA base content of the binding site as well as the 3D configuration of these bases. Because it is impossible to assess RBP binding to every possible phrase, we have developed a mathematical model called RNAcontext that can be trained by measuring RBP binding strength on one set of phrases. Once trained, this model can then be used to accurately predict binding strength to any possible phrase. Compared to previously described methods, RNAcontext learns a more precise description of the 3D shapes of binding sites. This precision translates into more accurate generalization of RBP binding preferences to new phrases and allows us to make new discoveries about the binding preferences of well-studied RBPs.
Mitogen-activated protein kinases (MAPKs), which are found in all eukaryotes, are signal transducing enzymes playing a central role in diverse biological processes, such as cell proliferation, sexual differentiation, and apoptosis. The MAPK signaling pathway plays a key role in the regulation of gene expression through the phosphorylation of transcription factors. Recent studies have identified several RNA-binding proteins (RBPs) as regulators of MAPK signaling because these RBPs bind to the mRNAs encoding the components of the MAPK pathway and regulate the stability of their transcripts. Moreover, RBPs also serve as targets of MAPKs because MAPK phosphorylate and regulate the ability of RBPs to bind and stabilize target mRNAs, thus controlling various cellular functions. In this review, we present evidence for the significance of the MAPK signaling in the regulation of RBPs and their target mRNAs, which provides additional information about the regulatory mechanism underlying gene expression. We further present evidence for the clinical importance of the posttranscriptional regulation of mRNA stability and its implications for drug discovery.
RNA-binding proteins (RBPs) perform many essential functions in the post-transcriptional control of gene expression. If we were able to engineer RBPs with new specificity, it would also become possible to develop new tools to control and investigate gene expression pathways. Molecular evolution methods such as phage display have been introduced to achieve this goal, but the large interface between these proteins and RNA relative to the size of library that can be constructed limits the efficacy of this method. In order to increase the diversity of libraries used for selection of RBPs, we applied the emulsion-based in vitro compartmentalization (IVC) method to select RBPs with defined specificity. A new approach was developed to link genotype and phenotype by fusing the target RBP to zinc finger proteins (ZFPs) that bind to a cognate DNA sequence inserted upstream of the promoter. The expressed fusion protein (ZFP–RBP) binds to its encoding DNA with high affinity via the ZFP target-binding site. After breaking the emulsion, the RBP can be selected based on its affinity for a biotinylated RNA bait. We demonstrate the effectiveness of this method that should enable the selection of RBPs with new specificity or improved affinity.
Post-transcriptional gene regulation is mediated through complex networks of protein–RNA interactions. The targets of only a few RNA binding proteins (RBPs) are known, even in the well-characterized budding yeast. In silico prediction of protein–RNA interactions is therefore useful to guide experiments and to provide insight into regulatory networks. Computational approaches have identified RBP targets based on sequence binding preferences. We investigate here to what extent RBP–RNA interactions can be predicted based on RBP and mRNA features other than sequence motifs. We analyze global relationships between gene and protein properties in general and between selected RBPs and known mRNA targets in particular. Highly translated RBPs tend to bind to shorter transcripts, and transcripts bound by the same RBP show high expression correlation across different biological conditions. Surprisingly, a given RBP preferentially binds to mRNAs that encode interaction partners for this RBP, suggesting coordinated post-transcriptional auto-regulation of protein complexes. We apply a machine-learning approach to predict specific RBP targets in yeast. Although this approach performs well for RBPs with known targets, predictions for uncharacterized RBPs remain challenging due to limiting experimental data. We also predict targets of fission yeast RBPs, indicating that the suggested framework could be applied to other species once more experimental data are available.
Numerous transcription factors are involved in the establishment and maintenance of the osteoblastic phenotype, such as Runx2, osterix and Dlx5. The transcription factor retinoblastoma binding protein-1 (RBP1) was recently identified as an estrogen regulated gene in an osteosarcoma cell model. Since the function of RBP1 in osteoblastic differentiation and mineralization is unknown, we investigated the role of RBP1 in these processes.
To create a cell model with suppressed RBP1 expression, primary calvarial osteoblasts were infected with a shRNA lentiviral vector specific for mouse RBP1 (CalOB-ΔRBP1) or a scrambled control shRNA lentivirus (CalOB-Control). Stable cell lines were generated and their mineralization potential was determined using osteoblastic differentiation medium, Alizarin Red staining, and quantitative PCR (QPCR) analyses. Runx2 coactivation by RBP1 was determined through the use of transient transfection assays.
Stable expression of the RBP1 shRNA lentivirus in CalOB-ΔRBP1 cells resulted in a 65-70% suppression of RBP1 expression. Osteoblastic mineralization assays demonstrated that suppression of RBP1 results in a potent delay in osteoblastic nodule formation in the CalOB-ΔRBP1 cells with a concomitant decrease in the expression of the osteogenic transcription factors Runx2 and osterix, along with decreases in BMP2, alkaline phosphatase, osteocalcin and bone sialoprotein. Regulation of Runx2 expression by RBP1 was shown to be mediated through the proximal P2 Runx2 promoter. Furthermore, RBP1 was demonstrated to be a potent coactivator of Runx2 transcriptional activity on two known Runx2 reporter constructs. These data suggest that the expression and activity of Runx2 is critically dependent on the presence of RBP1.
This study is the first to demonstrate that RBP1 is an important mediator of the osteoblastic phenotype and clearly defines RBP1 as a novel transcription factor involved in the well known Runx2-osterix transcriptional cascade. As such, the effects of RBP1 on these processes are mediated through both regulation of Runx2 expression and transcriptional activity.
Sequence-specific interactions of RNA-binding proteins (RBPs) with their target transcripts are essential for post-transcriptional gene expression regulation in mammals. However, accurate prediction of RBP motif sites has been difficult because many RBPs recognize short and degenerate sequences. Here we describe a hidden Markov model (HMM)-based algorithm mCarts to predict clustered functional RBP-binding sites by effectively integrating the number and spacing of individual motif sites, their accessibility in local RNA secondary structures and cross-species conservation. This algorithm learns and quantifies rules of these features, taking advantage of a large number of in vivo RBP-binding sites obtained from cross-linking and immunoprecipitation data. We applied this algorithm to study two representative RBP families, Nova and Mbnl, which regulate tissue-specific alternative splicing through interacting with clustered YCAY and YGCY elements, respectively, and predicted their binding sites in the mouse transcriptome. Despite the low information content in individual motif elements, our algorithm made specific predictions for successful experimental validation. Analysis of predicted sites also revealed cases of extensive and distal RBP-binding sites important for splicing regulation. This algorithm can be readily applied to other RBPs to infer their RNA-regulatory networks. The software is freely available at http://zhanglab.c2b2.columbia.edu/index.php/MCarts.
RNA-binding proteins play a central role in post-transcriptional mechanisms that control gene expression. Identification of novel RNA-binding proteins in fungi is essential to unravel post-transcriptional networks and cellular processes that confer identity to the fungal kingdom. Here, we carried out the functional characterisation of the filamentous fungus-specific RNA-binding protein RBP35 required for full virulence and development in the rice blast fungus. RBP35 contains an N-terminal RNA recognition motif (RRM) and six Arg-Gly-Gly tripeptide repeats. Immunoblots identified two RBP35 protein isoforms that show a steady-state nuclear localisation and bind RNA in vitro. RBP35 coimmunoprecipitates in vivo with Cleavage Factor I (CFI) 25 kDa, a highly conserved protein involved in polyA site recognition and cleavage of pre-mRNAs. Several targets of RBP35 have been identified using transcriptomics including 14-3-3 pre-mRNA, an important integrator of environmental signals. In Magnaporthe oryzae, RBP35 is not essential for viability but regulates the length of 3′UTRs of transcripts with developmental and virulence-associated functions. The Δrbp35 mutant is affected in the TOR (target of rapamycin) signaling pathway showing significant changes in nitrogen metabolism and protein secretion. The lack of clear RBP35 orthologues in yeast, plants and animals indicates that RBP35 is a novel auxiliary protein of the polyadenylation machinery of filamentous fungi. Our data demonstrate that RBP35 is the fungal equivalent of metazoan CFI 68 kDa and suggest the existence of 3′end processing mechanisms exclusive to the fungal kingdom.
The rice blast fungus Magnaporthe oryzae is one of the most damaging diseases of cultivated rice worldwide and an emerging disease on wheat, impacting on global food security. We identify a M. oryzae virulence-deficient mutant defective in the production of a RNA-binding protein (called RBP35). Clear orthologues of RBP35 are absent in yeast, plants and metazoans. We find two RBP35 protein isoforms that localise in the nucleus and bind RNA. Notably, we demonstrate that RBP35 interacts in vivo with a highly conserved protein component of the eukaryotic polyadenylation machinery. We show that RBP35 present different diffusional properties in nuclei of distinct fungal structures, and consequently different protein/nucleic acid interactions. Further, we find that RBP35 regulates the length of 3′UTRs of transcripts with developmental and virulence-associated functions. We prove that the Δrbp35 mutant is affected in the TOR (target of rapamycin) signaling pathway showing significant changes in nitrogen metabolism and protein secretion. Nothing it is known about pre-mRNA 3′ end processing in filamentous fungi and our study suggest that their polyadenylation machinery differs from yeast and higher organisms. This study can provide new insights into the evolution of the pre-mRNA maturation and the regulation of gene expression in eukaryotes.
Trypanosomes mostly control gene expression by post-transcriptional events such as modulation of mRNA stability and translational efficiency. These mechanisms involve RNA-binding proteins (RBPs), which associate with transcripts to form messenger ribonucleoprotein (mRNP) complexes.
In this study, we report the identification of mRNA targets for Trypanosoma cruzi U-rich RBP 1 (TcUBP1) and T. cruzi RBP 3 (TcRBP3), two phylogenetically conserved proteins among Kinetoplastids. Co-immunoprecipitated RBP-associated RNAs were extracted from mRNP complexes and binding of RBPs to several targets was confirmed by independent experimental assays. Analysis of target transcript sequences allowed the identification of different signature RNA motifs for each protein. Cis-elements for RBP binding have a stem-loop structure of 30–35 bases and are more frequently represented in the 3'-untranslated region (UTR) of mRNAs. Insertion of the correctly folded RNA elements to a non-specific mRNA rendered it into a target transcript, whereas substitution of the RNA elements abolished RBP interaction. In addition, RBPs competed for RNA-binding sites in accordance with the distribution of different and overlapping motifs in the 3'-UTRs of common mRNAs.
Functionally related transcripts were preferentially associated with a given RBP; TcUBP1 targets were enriched in genes encoding proteins involved in metabolism, whereas ribosomal protein-encoding transcripts were the largest group within TcRBP3 targets. Together, these results suggest coordinated control of different mRNA subsets at the post-transcriptional level by specific RBPs.
Post-transcriptional control of mRNA transcript processing by RNA binding proteins (RBPs) is an important step in the regulation of gene expression and protein production. The post-transcriptional regulatory network is similar in complexity to the transcriptional regulatory network and is thought to be organized in RNA regulons, coherent sets of functionally related mRNAs combinatorially regulated by common RBPs. We integrated genome-wide transcriptional and translational expression data in yeast with large-scale regulatory networks of transcription factor and RBP binding interactions to analyze the functional organization of post-transcriptional regulation and RNA regulons at a system level. We found that post-transcriptional feedback loops and mixed bifan motifs are overrepresented in the integrated regulatory network and control the coordinated translation of RNA regulons, manifested as clusters of functionally related mRNAs which are strongly coexpressed in the translatome data. These translatome clusters are more functionally coherent than transcriptome clusters and are expressed with higher mRNA and protein levels and less noise. Our results show how the post-transcriptional network is intertwined with the transcriptional network to regulate gene expression in a coordinated way and that the integration of heterogeneous genome-wide datasets allows to relate structure to function in regulatory networks at a system level.
In cells responding to low oxygen levels, gene expression patterns are strongly influenced by post-transcriptional processes. RNA-binding proteins (RBPs) are pivotal regulators of gene expression in response to numerous stresses, including hypoxia. Here, we review the RBPs that modulate mRNA turnover and translation in response to hypoxic challenge. The RBPs HuR (human antigen R) and PTB (polypyrimidine tract-binding protein) associate with mRNAs encoding hypoxia-response proteins such as HIF-1α and VEGF mRNAs, enhance their expression after hypoxia, and play a major role in establishing hypoxic gene expression patterns. Additional RBPs such as iron-response element-binding proteins (IRPs), CPEBs (cytoplasmic polyadenylation-element-binding proteins), and several hnRNPs (heterogeneous nuclear ribonucleoproteins), also bind to hypoxia-regulated transcripts and modulate the levels of the encoded proteins. We discuss the efficient regulation of hypoxic gene expression by RBPs, and the mounting interest in targeting hypoxia-regulatory RBPs in diseases with aberrant hypoxic responses.
stress; oxygen tension; post-transcriptional gene regulation; RNA-binding proteins; mRNA turnover; translational control; ribonucleoprotein complex; untranslated regions
The fate of an mRNA is largely determined by its interactions with RNA binding proteins (RBPs). Post-transcriptional processing, RNA stability, localisation and translation are some of the events regulated by the plethora of RBPs present within cells. Mutations in various RBPs cause several diseases of the central nervous system, including frontotemporal lobar degeneration, amyotrophic lateral sclerosis and fragile X syndrome. Here we review the studies that integrated UV-induced cross-linked immunoprecipitation (CLIP) with other genome-wide methods to comprehensively characterise the function of diverse RBPs in the brain. We discuss the technical challenges of these studies and review the strategies that can be used to reliably identify the RNAs bound and regulated by an RBP. We conclude by highlighting how CLIP and related techniques have been instrumental in addressing the role of RBPs in neurologic diseases. This article is part of a Special Issue entitled: RNA and splicing regulation in neurodegeneration.
CLIP; Neurodegeneration; FUS; Muscleblind; RNA binding proteins
RNA-binding proteins (RBPs) that associate with specific mRNA sequences and function as mRNA turnover and translation regulatory (TTR) RBPs are emerging as pivotal posttranscriptional regulators of gene expression. However, little is known about the mechanisms that govern the expression of TTR-RBPs. Here, we employed human cervical carcinoma HeLa cells to test the hypothesis that TTR-RBP expression is influenced posttranscriptionally by TTR-RBPs themselves. Systematic testing of the TTR-RBPs AUF1, HuR, KSRP, NF90, TIA-1, and TIAR led to three key discoveries. First, each TTR-RBP was found to associate with its cognate mRNA and with several other TTR-RBP-encoding mRNAs, as determined by testing both endogenous and biotinylated transcripts. Second, silencing of individual TTR-RBPs influenced the expression of other TTR-RBPs at the mRNA and/or protein level. Third, further analysis of two specific ribonucleoprotein (RNP) complexes revealed that TIA-1 expression was controlled via HuR-enhanced mRNA stabilization and TIAR-repressed translation. Together, our findings underscore the notion that TTR-RBP expression is controlled, at least in part, at the posttranscriptional level through a complex circuitry of self- and cross-regulatory RNP interactions.
RNA transcripts are subjected to post-transcriptional gene regulation by interacting with hundreds of RNA-binding proteins (RBPs) and microRNA-containing ribonucleoprotein complexes (miRNPs) that are often expressed in a cell-type dependently. To understand how the interplay of these RNA-binding factors affects the regulation of individual transcripts, high resolution maps of in vivo protein-RNA interactions are necessary1.
A combination of genetic, biochemical and computational approaches are typically applied to identify RNA-RBP or RNA-RNP interactions. Microarray profiling of RNAs associated with immunopurified RBPs (RIP-Chip)2 defines targets at a transcriptome level, but its application is limited to the characterization of kinetically stable interactions and only in rare cases3,4 allows to identify the RBP recognition element (RRE) within the long target RNA. More direct RBP target site information is obtained by combining in vivo UV crosslinking5,6 with immunoprecipitation7-9 followed by the isolation of crosslinked RNA segments and cDNA sequencing (CLIP)10. CLIP was used to identify targets of a number of RBPs11-17. However, CLIP is limited by the low efficiency of UV 254 nm RNA-protein crosslinking, and the location of the crosslink is not readily identifiable within the sequenced crosslinked fragments, making it difficult to separate UV-crosslinked target RNA segments from background non-crosslinked RNA fragments also present in the sample.
We developed a powerful cell-based crosslinking approach to determine at high resolution and transcriptome-wide the binding sites of cellular RBPs and miRNPs that we term PAR-CliP (Photoactivatable-Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation) (see Fig. 1A for an outline of the method). The method relies on the incorporation of photoreactive ribonucleoside analogs, such as 4-thiouridine (4-SU) and 6-thioguanosine (6-SG) into nascent RNA transcripts by living cells. Irradiation of the cells by UV light of 365 nm induces efficient crosslinking of photoreactive nucleoside-labeled cellular RNAs to interacting RBPs. Immunoprecipitation of the RBP of interest is followed by isolation of the crosslinked and coimmunoprecipitated RNA. The isolated RNA is converted into a cDNA library and deep sequenced using Solexa technology. One characteristic feature of cDNA libraries prepared by PAR-CliP is that the precise position of crosslinking can be identified by mutations residing in the sequenced cDNA. When using 4-SU, crosslinked sequences thymidine to cytidine transition, whereas using 6-SG results in guanosine to adenosine mutations. The presence of the mutations in crosslinked sequences makes it possible to separate them from the background of sequences derived from abundant cellular RNAs.
Application of the method to a number of diverse RNA binding proteins was reported in Hafner et al.18
Gene expression is intricately regulated at the post-transcriptional level by RNA-binding proteins (RBPs) via their interactions with pre-messenger RNA (pre-mRNA) and mRNA during development. However, very little is known about the mechanism regulating RBP activities in RNA metabolism. During the past few years, a large body of evidence has suggested that many RBPs, such as heterogeneous nuclear ribonucleoproteins (hnRNPs), undergo post-translational modification through poly(ADP-ribosyl)ation to modulate RNA processing, including splicing, polyadenylation, translation, miRNA biogenesis and rRNA processing. Accordingly, RBP poly(ADP-ribosyl)ation has been shown to be involved in stress responses, stem cell differentiation and retinal morphogenesis. Here, we summarize recent advances in understanding the biological roles of RBP poly(ADP-ribosyl)ation, as controlled by Poly(ADP-ribose) Polymerases (PARPs) and Poly(ADP-ribose) Glycohydrolase (PARG). In addition, we discuss the potential of PARP and PARG inhibitors for the treatment of RBP-related human diseases, including cancer and neurodegenerative disorders.
Parp; Parg; poly(ADP-ribose); RNA-binding protein; RNA metabolism
Once mRNAs are transcribed, spliced and transported to the cytoplasm, their fate is determined by the complex interplay of RNA binding proteins (RBPs) and microRNAs (miRNAs) that act on regulatory elements within the transcripts. The importance of post-transcriptional regulatory mechanisms in angiogenesis is underscored by the observation that perturbations in miRNAs and/or RBPs lead to profound phenotypic alterations in vascular development, homeostasis and disease, with current data suggesting that mRNAs for key angiogenic regulators (secreted factors and intracellular signaling intermediates) are subject to stringent post-transcriptional regulation by both RBPs and miRNAs. In addition, an intricate network of miRNAs and RBPs allow robust gene regulation in vascular cells. This review focuses on the miRNAs and RBPs which often cooperate to achieve precise spatial and temporal control of angiogenic regulatory genes.
Mammalian gene expression patterns change profoundly in response to low oxygen levels. These changes in gene expression programs are strongly influenced by post-transcriptional mechanisms mediated by mRNA-binding factors: RNA-binding proteins (RBPs) and microRNAs (miRNAs). Here, we review the RBPs and miRNAs that modulate mRNA turnover and translation in response to hypoxic challenge. RBPs such as HuR (human antigen R), PTB (polypyrimidine tract-binding protein), heterogeneous nuclear ribonucleoproteins (hnRNPs), tristetraprolin, nucleolin, iron-response element-binding proteins (IRPs), and cytoplasmic polyadenylation-element-binding proteins (CPEBs), selectively bind to numerous hypoxia-regulated transcripts and play a major role in establishing hypoxic gene expression patterns. MiRNAs including miR-210, miR-373, and miR-21 associate with hypoxia-regulated transcripts and further modulate the levels of the encoded proteins to implement the hypoxic gene expression profile. We discuss the potent regulation of hypoxic gene expression by RBPs and miRNAs and their integrated actions in the cellular hypoxic response.
hypoxia; post-transcriptional gene regulation; microRNAs; RNA-binding proteins; mRNA turnover; translational control; ribonucleoprotein complex; untranslated regions
Translation initiation is a highly regulated process that exerts a strong influence on the posttranscriptional control of gene expression. Two alternative mechanisms govern translation initiation in eukaryotic mRNAs, the cap-dependent initiation mechanism operating in most mRNAs, and the internal ribosome entry site (IRES)-dependent mechanism, first discovered in picornaviruses. IRES elements are highly structured RNA sequences that, in most instances, require specific proteins for recruitment of the translation machinery. Some of these proteins are eukaryotic initiation factors. In addition, RNA-binding proteins (RBPs) play a key role in internal initiation control. RBPs are pivotal regulators of gene expression in response to numerous stresses, including virus infection. This review discusses recent advances on riboproteomic approaches to identify IRES transacting factors (ITAFs) and the relationship between RNA-protein interaction and IRES activity, highlighting the most relevant features on picornavirus and hepatitis C virus IRESs.
RNA-binding proteins (RBPs) play crucial roles in post-transcriptional control of RNA. RBPs are designed to efficiently recognize specific RNA sequences after it is derived from the DNA sequence. To satisfy diverse functional requirements, RNA binding proteins are composed of multiple blocks of RNA-binding domains (RBDs) presented in various structural arrangements to provide versatile functions. The ability to computationally predict RNA-binding residues in a RNA-binding protein can help biologists reveal important site-directed mutagenesis in wet-lab experiments.
The proposed prediction framework named “ProteRNA” combines a SVM-based classifier with conserved residue discovery by WildSpan to identify the residues that interact with RNA in a RNA-binding protein. Although these conserved residues can be either functionally conserved residues or structurally conserved residues, they provide clues on the important residues in a protein sequence. In the independent testing dataset, ProteRNA has been able to deliver overall accuracy of 89.78%, MCC of 0.2628, F-score of 0.3075, and F0.5-score of 0.3546.
This article presents the design of a sequence-based predictor aiming to identify the RNA-binding residues in a RNA-binding protein by combining machine learning and pattern mining approaches. RNA-binding proteins have diverse functions while interacting with different categories of RNAs because these proteins are composed of multiple copies of RNA-binding domains presented in various structural arrangements to expand the functional repertoire of RNA-binding proteins. Furthermore, predicting RNA-binding residues in a RNA-binding protein can help biologists reveal important site-directed mutagenesis in wet-lab experiments.
Little is known regarding the post-transcriptional networks that control gene expression in eukaryotes. Additionally, we still need to understand how these networks evolve, and the relative role played in them by their sequence-dependent regulatory factors, non-coding RNAs (ncRNAs) and RNA-binding proteins (RBPs). Here, we used an approach that relied on both phylogenetic sequence sharing and conservation in the whole mapped 3′-untranslated regions (3′-UTRs) of vertebrate species to gain knowledge on core post-transcriptional networks. The identified human hyper conserved elements (HCEs) were predicted to be preferred binding sites for RBPs and not for ncRNAs, namely microRNAs and long ncRNAs. We found that the HCE map identified a well-known network that post-transcriptionally regulates histone mRNAs. We were then able to discover and experimentally confirm a translational network composed of RNA Recognition Motif (RRM)-type RBP mRNAs that are positively controlled by HuR, another RRM-type RBP. HuR shows a preference for these RBP mRNAs bound in stem–loop motifs, confirming its role as a ‘regulator of regulators’. Analysis of the transcriptome-wide HCE distribution revealed a profile of prevalently small clusters separated by unconserved intercluster RNA stretches, which predicts the formation of discrete small ribonucleoprotein complexes in the 3′-UTRs.