Sequence-specific recognition of RNA hairpins by the SAM domain of Vts1p

Identification of whole-cell dsRNA-binding proteins by phase separation

Interactions between double-stranded RNA (dsRNA) and proteins play an important role in cellular homeostasis by regulating the editing, stability, and splicing of intracellular RNA. The identification of dsRNA-binding proteins (dsRBPs) is key; however, it has long been challenging to purify dsRBPs from cells. In this study, we developed a novel method, dsRBPC (dsRNA-binding protein capture), to purify cellular dsRBPs based on classic phase separation purification procedures. A global dsRNA-binding proteome of LLC-PK1 cells was obtained, and we identified 1326 dsRBPs, including 1303 putative novel dsRBPs. Functional analyses suggested that these enriched dsRBPs are mainly associated with rRNA processing, RNA splicing, transcriptional regulation, and nucleocytoplasmic transport. We also found that the ARM (armadillo/beta-catenin-like repeats) motif is a previously unknown dsRNA-binding domain, as demonstrated by biochemical experiments. Collectively, this study provides a useful approach for dsRBP identification and the discovery of a global dsRNA-binding proteome to comprehensively map the dsRNA - protein interaction network.

RNA-binding proteins that lack canonical RNA-binding domains are rarely sequence-specific

Thousands of RNA-binding proteins (RBPs) crosslink to cellular mRNA. Among these are numerous unconventional RBPs (ucRBPs)-proteins that associate with RNA but lack known RNA-binding domains (RBDs). The vast majority of ucRBPs have uncharacterized RNA-binding specificities. We analyzed 492 human ucRBPs for intrinsic RNA-binding in vitro and identified 23 that bind specific RNA sequences. Most (17/23), including 8 ribosomal proteins, were previously associated with RNA-related function. We identified the RBDs responsible for sequence-specific RNA-binding for several of these 23 ucRBPs and surveyed whether corresponding domains from homologous proteins also display RNA sequence specificity. CCHC-zf domains from seven human proteins recognized specific RNA motifs, indicating that this is a major class of RBD. For Nudix, HABP4, TPR, RanBP2-zf, and L7Ae domains, however, only isolated members or closely related homologs yielded motifs, consistent with RNA-binding as a derived function. The lack of sequence specificity for most ucRBPs is striking, and we suggest that many may function analogously to chromatin factors, which often crosslink efficiently to cellular DNA, presumably via indirect recruitment. Finally, we show that ucRBPs tend to be highly abundant proteins and suggest their identification in RNA interactome capture studies could also result from weak nonspecific interactions with RNA.

RNA binding protein SAMD4: current knowledge and future perspectives

SAMD4 protein family is a class of novel RNA-binding proteins that can mediate post-transcriptional regulation and translation repression in eukaryotes, which are highly conserved from yeast to humans during evolution. In mammalian cells, SAMD4 protein family consists of two members including SAMD4A/Smaug1 and SAMD4B/Smaug2, both of which contain common SAM domain that can specifically bind to different target mRNAs through stem-loop structures, also known as Smaug recognition elements (SREs), and regulate the mRNA stability, degradation and translation. In addition, SAMD4 can form the cytoplasmic mRNA silencing foci and regulate the translation of SRE-containing mRNAs in neurons. SAMD4 also can form the cytosolic membrane-less organelles (MLOs), termed as Smaug1 bodies, and regulate mitochondrial function. Importantly, many studies have identified that SAMD4 family members are involved in various pathological processes including myopathy, bone development, neural development, and cancer occurrence and progression. In this review, we mainly summarize the structural characteristics, biological functions and molecular regulatory mechanisms of SAMD4 protein family members, which will provide a basis for further research and clinical application of SAMD4 protein family.

ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural Networks

Deep neural networks have demonstrated improved performance at predicting sequence specificities of DNA- and RNA-binding proteins. However, it remains unclear why they perform better than previous methods that rely on k-mers and position weight matrices. Here, we highlight a recent deep learning-based software package, called ResidualBind, that analyzes RNA-protein interactions using only RNA sequence as an input feature and performs global importance analysis for model interpretability. We discuss practical considerations for model interpretability to uncover learned sequence motifs and their secondary structure preferences.

The Adaptor Protein UvSte50 Governs Fungal Pathogenicity of Ustilaginoidea virens via the MAPK Signaling Pathway

The mitogen-activated protein kinase (MAPK) signaling pathways regulate diverse cellular processes and have been partially characterized in the rice false smut fungus Ustilaginoidea virens. UvSte50 has been identified as a homolog to Saccharomyces cerevisiae Ste50, which is known to be an adaptor protein for MAPK cascades. ΔUvste50 was found to be defective in conidiation, sensitive to hyperosmotic and oxidative stresses, and non-pathogenic. The mycelial expansion of ΔUvste50 inside spikelets of rice terminated at stamen filaments, eventually resulting in a lack of formation of false smut balls on spikelets. We determined that UvSte50 directly interacts with both UvSte7 (MAPK kinase; MEK) and UvSte11 (MAPK kinase kinase; MEKK), where the Ras-association (RA) domain of UvSte50 is indispensable for its interaction with UvSte7. UvSte50 also interacts with UvHog1, a MAP kinase of the Hog1-MAPK pathway, which is known to have important roles in hyphal growth and stress responses in U. virens. In addition, affinity capture-mass spectrometry analysis and yeast two-hybrid assay were conducted, through which we identified the interactions of UvSte50 with UvRas2, UvAc1 (adenylate cyclase), and UvCap1 (cyclase-associated protein), key components of the Ras/cAMP signaling pathway in U. virens. Together, UvSte50 functions as an adaptor protein interacting with multiple components of the MAPK and Ras/cAMP signaling pathways, thus playing critical role in plant infection by U. virens.

Smaug1 membrane-less organelles respond to AMPK/mTOR and affect mitochondrial function‡

Smaug is a conserved translational regulator that binds numerous mRNAs, including nuclear transcripts that encode mitochondrial enzymes. Smaug orthologs form cytosolic membrane-less organelles (MLOs) in several organisms and cell types. We have performed single-molecule FISH assays that revealed that SDHB and UQCRC1 mRNAs associate with Smaug1 bodies in U2OS cells. Loss of function of Smaug1 and Smaug2 affected both mitochondrial respiration and morphology of the mitochondrial network. Phenotype rescue by Smaug1 transfection depends on the presence of its RNA binding domain. Moreover, we identified specific Smaug1 domains involved in MLO formation, and found that impaired Smaug1 MLO condensation correlates with mitochondrial defects. Mitochondrial Complex I inhibition by rotenone -but not strong mitochondrial uncoupling by CCCP- rapidly induced Smaug1 MLOs dissolution. Metformin and rapamycin elicited similar effects, which were blocked by pharmacological inhibition of AMPK. Finally, we found that Smaug1 MLO dissolution weakens the interaction with target mRNAs, thus enabling their release. We propose that mitochondrial respiration and the AMPK/mTOR balance controls the condensation and dissolution of Smaug1 MLOs, thus regulating nuclear mRNAs that encode key mitochondrial proteins.

Rapid structure-function insights via hairpin-centric analysis of big RNA structure probing datasets

The functions of RNA are often tied to its structure, hence analyzing structure is of significant interest when studying cellular processes. Recently, large-scale structure probing (SP) studies have enabled assessment of global structure-function relationships via standard data summarizations or local folding. Here, we approach structure quantification from a hairpin-centric perspective where putative hairpins are identified in SP datasets and used as a means to capture local structural effects. This has the advantage of rapid processing of big (e.g. transcriptome-wide) data as RNA folding is circumvented, yet it captures more information than simple data summarizations. We reformulate a statistical learning algorithm we previously developed to significantly improve precision of hairpin detection, then introduce a novel nucleotide-wise measure, termed the hairpin-derived structure level (HDSL), which captures local structuredness by accounting for the presence of likely hairpin elements. Applying HDSL to data from recent studies recapitulates, strengthens and expands on their findings which were obtained by more comprehensive folding algorithms, yet our analyses are orders of magnitude faster. These results demonstrate that hairpin detection is a promising avenue for global and rapid structure-function analysis, furthering our understanding of RNA biology and the principal features which drive biological insights from SP data.

Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networks

Deep neural networks have demonstrated improved performance at predicting the sequence specificities of DNA- and RNA-binding proteins compared to previous methods that rely on k-mers and position weight matrices. To gain insights into why a DNN makes a given prediction, model interpretability methods, such as attribution methods, can be employed to identify motif-like representations along a given sequence. Because explanations are given on an individual sequence basis and can vary substantially across sequences, deducing generalizable trends across the dataset and quantifying their effect size remains a challenge. Here we introduce global importance analysis (GIA), a model interpretability method that quantifies the population-level effect size that putative patterns have on model predictions. GIA provides an avenue to quantitatively test hypotheses of putative patterns and their interactions with other patterns, as well as map out specific functions the network has learned. As a case study, we demonstrate the utility of GIA on the computational task of predicting RNA-protein interactions from sequence. We first introduce a convolutional network, we call ResidualBind, and benchmark its performance against previous methods on RNAcompete data. Using GIA, we then demonstrate that in addition to sequence motifs, ResidualBind learns a model that considers the number of motifs, their spacing, and sequence context, such as RNA secondary structure and GC-bias.

Precise Temporal Regulation of Post-transcriptional Repressors Is Required for an Orderly Drosophila Maternal-to-Zygotic Transition

In animal embryos, the maternal-to-zygotic transition (MZT) hands developmental control from maternal to zygotic gene products. We show that the maternal proteome represents more than half of the protein-coding capacity of Drosophila melanogaster’s genome, and that 2% of this proteome is rapidly degraded during the MZT. Cleared proteins include the post-transcriptional repressors Cup, Trailer hitch (TRAL), Maternal expression at 31B (ME31B), and Smaug (SMG). Although the ubiquitin-proteasome system is necessary for clearance of these repressors, distinct E3 ligase complexes target them: the C-terminal to Lis1 Homology (CTLH) complex targets Cup, TRAL, and ME31B for degradation early in the MZT and the Skp/Cullin/F-box-containing (SCF) complex targets SMG at the end of the MZT. Deleting the C-terminal 233 amino acids of SMG abrogates F-box protein interaction and confers immunity to degradation. Persistent SMG downregulates zygotic re-expression of mRNAs whose maternal contribution is degraded by SMG. Thus, clearance of SMG permits an orderly MZT.

Cao et al. show that 2% of the proteome is degraded in early Drosophila embryos, including a repressive ribonucleoprotein complex. Two E3 ubiquitin ligases separately act on distinct components of this complex to phase their clearance. Failure to degrade a key component, the Smaug RNA-binding protein, disrupts an orderly maternal-to-zygotic transition.

Bicaudal C is required for the function of the follicular epithelium during oogenesis in Rhodnius prolixus

The morphology and physiology of the oogenesis have been well studied in the vector of Chagas disease Rhodnius prolixus. However, the molecular interactions that regulate the process of egg formation, key for the reproductive cycle of the vector, is still largely unknown. In order to understand the molecular and cellular basis of the oogenesis, we examined the function of the gene Bicaudal C (BicC) during oogenesis and early development of R. prolixus. We show that R. prolixus BicC (Rp-BicC) gene is expressed in the germarium, with cytoplasmic distribution, as well as in the follicular epithelium of the developing oocytes. RNAi silencing of Rp-BicC resulted in sterile females that lay few, small, non-viable eggs. The ovaries are reduced in size and show a disarray of the follicular epithelium. This indicates that Rp-BicC has a central role in the regulation of oogenesis. Although the follicular cells are able to form the chorion, the uptake of vitelline by the oocytes is compromised. We show evidence that the polarity of the follicular epithelium and the endocytic pathway, which are crucial for the proper yolk deposition, are affected. This study provides insights into the molecular mechanisms underlying oocyte development and show that Rp-BicC is important for de developmental of the egg and, therefore, a key player in the reproduction of this insect.

Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions

Motivation

RNA-protein interactions are key effectors of post-transcriptional regulation. Significant experimental and bioinformatics efforts have been expended on characterizing protein binding mechanisms on the molecular level, and on highlighting the sequence and structural traits of RNA that impact the binding specificity for different proteins. Yet our ability to predict these interactions in silico remains relatively poor.

Results

In this study, we introduce RPI-Net, a graph neural network approach for RNA-protein interaction prediction. RPI-Net learns and exploits a graph representation of RNA molecules, yielding significant performance gains over existing state-of-the-art approaches. We also introduce an approach to rectify an important type of sequence bias caused by the RNase T1 enzyme used in many CLIP-Seq experiments, and we show that correcting this bias is essential in order to learn meaningful predictors and properly evaluate their accuracy. Finally, we provide new approaches to interpret the trained models and extract simple, biologically interpretable representations of the learned sequence and structural motifs.

Availability and implementation

Source code can be accessed at https://www.github.com/HarveyYan/RNAonGraph.

Supplementary information

Supplementary data are available at Bioinformatics online.

On the Nature of Nucleobase Stacking in RNA: A Comprehensive Survey of Its Structural Variability and a Systematic Classification of Associated Interactions

The astonishing diversity in folding patterns of RNA three-dimensional (3D) structures is crafted by myriads of noncovalent contacts, of which base pairing and stacking are the most prominent. A systematic and comprehensive classification and annotation of these interactions is necessary for a molecular-level understanding of their roles. However, unlike in the case of base pairing, where a widely accepted nomenclature and classification scheme exists in the public domain, currently available classification schemes for base-base stacking need major enhancements to comprehensively capture the necessary features underlying the rich stacking diversity in RNA. Here, we extend the previous stacking classification based on nucleobase interacting faces by introducing a structurally intuitive geometry-cum topology-based scheme. Specifically, a stack is first classified in terms of the geometry described by the relative orientation of the glycosidic bonds, which generates eight basic stacking geometric families for heterodimeric stacks and six of those for homodimeric stacks. Further annotation in terms of the identity of the bases and the region of involvement of purines (five-membered, six-membered, or both rings) leads to the enumeration of 384 distinct RNA base stacks. Based on our classification scheme, we present an algorithm for automated identification of stacks in RNA crystal structures and analyze the stacking context in selected RNA structures. Overall, the work described here is expected to greatly facilitate the structure-based RNA research.

Viral hijacking of the TENT4-ZCCHC14 complex protects viral RNAs via mixed tailing

TENT4 enzymes generate 'mixed tails' of diverse nucleotides at 3' ends of RNAs via nontemplated nucleotide addition to protect messenger RNAs from deadenylation. Here we discover extensive mixed tailing in transcripts of hepatitis B virus (HBV) and human cytomegalovirus (HCMV), generated via a similar mechanism exploiting the TENT4-ZCCHC14 complex. TAIL-seq on HBV and HCMV RNAs revealed that TENT4A and TENT4B are responsible for mixed tailing and protection of viral poly(A) tails. We find that the HBV post-transcriptional regulatory element (PRE), specifically the CNGGN-type pentaloop, is critical for TENT4-dependent regulation. HCMV uses a similar pentaloop, an interesting example of convergent evolution. This pentaloop is recognized by the sterile alpha motif domain-containing ZCCHC14 protein, which in turn recruits TENT4. Overall, our study reveals the mechanism of action of PRE, which has been widely used to enhance gene expression, and identifies the TENT4-ZCCHC14 complex as a potential target for antiviral therapeutics.

SAMD4 family members suppress human hepatitis B virus by directly binding to the Smaug recognition region of viral RNA

HBV infection initiates hepatitis B and promotes liver cirrhosis and hepatocellular carcinoma. IFN-α is commonly used in hepatitis B therapy, but how it inhibits HBV is not fully understood. We screened 285 human interferon-stimulated genes (ISGs) for anti-HBV activity using a cell-based assay, which revealed several anti-HBV ISGs. Among these ISGs, SAMD4A was the strongest suppressor of HBV replication. We found the binding site of SAMD4A in HBV RNA, which was a previously unidentified Smaug recognition region (SRE) sequence conserved in HBV variants. SAMD4A binds to the SRE site in viral RNA to trigger its degradation. The SAM domain in SAMD4A is critical for RNA binding and the C-terminal domain of SAMD4A is required for SAMD4A anti-HBV function. Human SAMD4B is a homolog of human SAMD4A but is not an ISG, and the murine genome encodes SAMD4. All these SAMD4 proteins suppressed HBV replication when overexpressed in vitro and in vivo. We also showed that knocking out the Samd4 gene in hepatocytes led to a higher level of HBV replication in mice and AAV-delivered SAMD4A expression reduced the virus titer in HBV-producing transgenic mice. In addition, a database analysis revealed a negative correlation between the levels of SAMD4A/B and HBV in patients. Our data suggest that SAMD4A is an important anti-HBV ISG for use in IFN therapy of hepatitis B and that the levels of SAMD4A/B expression are related to HBV sensitivity in humans.

How RNA-Binding Proteins Interact with RNA: Molecules and Mechanisms

RNA-binding proteins (RBPs) comprise a large class of over 2,000 proteins that interact with transcripts in all manner of RNA-driven processes. The structures and mechanisms that RBPs use to bind and regulate RNA are incredibly diverse. In this review, we take a look at the components of protein-RNA interaction, from the molecular level to multi-component interaction. We first summarize what is known about protein-RNA molecular interactions based on analyses of solved structures. We additionally describe software currently available for predicting protein-RNA interaction and other resources useful for the study of RBPs. We then review the structure and function of seventeen known RNA-binding domains and analyze the hydrogen bonds adopted by protein-RNA structures on a domain-by-domain basis. We conclude with a summary of the higher-level mechanisms that regulate protein-RNA interactions.

The RNA-Binding Protein Rasputin/G3BP Enhances the Stability and Translation of Its Target mRNAs

G3BP RNA-binding proteins are important components of stress granules (SGs). Here, we analyze the role of the Drosophila G3BP Rasputin (RIN) in unstressed cells, where RIN is not SG associated. Immunoprecipitation followed by microarray analysis identifies over 550 mRNAs that copurify with RIN. The mRNAs found in SGs are long and translationally silent. In contrast, we find that RIN-bound mRNAs, which encode core components of the transcription, splicing, and translation machinery, are short, stable, and highly translated. We show that RIN is associated with polysomes and provide evidence for a direct role for RIN and its human homologs in stabilizing and upregulating the translation of their target mRNAs. We propose that when cells are stressed, the resulting incorporation of RIN/G3BPs into SGs sequesters them away from their short target mRNAs. This would downregulate the expression of these transcripts, even though they are not incorporated into stress granules.

A Non-amyloid Prion Particle that Activates a Heritable Gene Expression Program

Spatiotemporal gene regulation is often driven by RNA-binding proteins that harbor long intrinsically disordered regions in addition to folded RNA-binding domains. We report that the disordered region of the evolutionarily ancient developmental regulator Vts1/Smaug drives self-assembly into gel-like condensates. These proteinaceous particles are not composed of amyloid, yet they are infectious, allowing them to act as a protein-based epigenetic element: a prion [SMAUG⁺]. In contrast to many amyloid prions, condensation of Vts1 enhances its function in mRNA decay, and its self-assembly properties are conserved over large evolutionary distances. Yeast cells harboring [SMAUG⁺] downregulate a coherent network of mRNAs and exhibit improved growth under nutrient limitation. Vts1 condensates formed from purified protein can transform naive cells to acquire [SMAUG⁺]. Our data establish that non-amyloid self-assembly of RNA-binding proteins can drive a form of epigenetics beyond the chromosome, instilling adaptive gene expression programs that are heritable over long biological timescales.

Widespread Prion-Based Control of Growth and Differentiation Strategies in Saccharomyces cerevisiae

Theory and experiments suggest that organisms would benefit from pre-adaptation to future stressors based on reproducible environmental fluctuations experienced by their ancestors, but the mechanisms driving pre-adaptation remain enigmatic. We report that the [SMAUG⁺] prion allows yeast to anticipate nutrient repletion after periods of starvation, providing a strong selective advantage. By transforming the landscape of post-transcriptional gene expression, [SMAUG⁺] regulates the decision between two broad growth and survival strategies: mitotic proliferation or meiotic differentiation into a stress-resistant state. [SMAUG⁺] is common in laboratory yeast strains, where standard propagation practice produces regular cycles of nutrient scarcity followed by repletion. Distinct [SMAUG⁺] variants are also widespread in wild yeast isolates from multiple niches, establishing that prion polymorphs can be utilized in natural populations. Our data provide a striking example of how protein-based epigenetic switches, hidden in plain sight, can establish a transgenerational memory that integrates adaptive prediction into developmental decisions.

Linking RNA Sequence, Structure, and Function on Massively Parallel High-Throughput Sequencers

High-throughput sequencing methods have revolutionized our ability to catalog the diversity of RNAs and RNA-protein interactions that can exist in our cells. However, the relationship between RNA sequence, structure, and function is enormously complex, demonstrating the need for methods that can provide quantitative thermodynamic and kinetic measurements of macromolecular interaction with RNA, at a scale commensurate with the sequence diversity of RNA. Here, we discuss a class of methods that extend the core functionality of DNA sequencers to enable high-throughput measurements of RNA folding and RNA-protein interactions. Topics discussed include a description of the method and multiple applications to RNA-binding proteins, riboswitch design and engineering, and RNA tertiary structure energetics.

Multiple Puf proteins regulate the stability of ribosome biogenesis transcripts

Cells must make careful use of the resources available to them. A key area of cellular regulation involves the biogenesis of ribosomes. Transcriptional regulation of ribosome biogenesis factor genes through alterations in histone acetylation has been well studied. This work identifies a post-transcriptional mechanism of ribosome biogenesis regulation by Puf protein control of mRNA stability. Puf proteins are eukaryotic mRNA binding proteins that play regulatory roles in mRNA degradation and translation via association with specific conserved elements in the 3' untranslated region (UTR) of target mRNAs and with degradation and translation factors. We demonstrate that several ribosome biogenesis factor mRNAs in Saccharomyces cerevisiae containing a canonical Puf4p element in their 3' UTRs are destabilized by Puf2p, Puf4, and Puf5p, yet stabilized by Puf1p and Puf3p. In the absence of all Puf proteins, these ribosome biogenesis mRNAs are destabilized by a secondary mechanism involving the same 3' UTR element. Unlike other targets of Puf4p regulation, the decay of these transcripts is not altered by carbon source. Overexpression of Puf4p results in delayed ribosomal RNA processing and altered ribosomal subunit trafficking. These results represent a novel role for Puf proteins in yeast as regulators of ribosome biogenesis transcript stability.

Both Maintenance and Avoidance of RNA-Binding Protein Interactions Constrain Coding Sequence Evolution

While the principal force directing coding sequence (CDS) evolution is selection on protein function, to ensure correct gene expression CDSs must also maintain interactions with RNA-binding proteins (RBPs). Understanding how our genes are shaped by these RNA-level pressures is necessary for diagnostics and for improving transgenes. However, the evolutionary impact of the need to maintain RBP interactions remains unresolved. Are coding sequences constrained by the need to specify RBP binding motifs? If so, what proportion of mutations are affected? Might sequence evolution also be constrained by the need not to specify motifs that might attract unwanted binding, for instance because it would interfere with exon definition? Here, we have scanned human CDSs for motifs that have been experimentally determined to be recognized by RBPs. We observe two sets of motifs-those that are enriched over nucleotide-controlled null and those that are depleted. Importantly, the depleted set is enriched for motifs recognized by non-CDS binding RBPs. Supporting the functional relevance of our observations, we find that motifs that are more enriched are also slower-evolving. The net effect of this selection to preserve is a reduction in the over-all rate of synonymous evolution of 2-3% in both primates and rodents. Stronger motif depletion, on the other hand, is associated with stronger selection against motif gain in evolution. The challenge faced by our CDSs is therefore not only one of attracting the right RBPs but also of avoiding the wrong ones, all while also evolving under selection pressures related to protein structure.

mRNA localization in metazoans: A structural perspective

Asymmetric localization of mRNAs is a widespread gene regulatory mechanism that is crucial for many cellular processes. The localization of a transcript involves multiple steps and requires several protein factors to mediate transport, anchoring and translational repression of the mRNA. Specific recognition of the localizing transcript is a key step that depends on linear or structured localization signals, which are bound by RNA-binding proteins. Genetic studies have identified many components involved in mRNA localization. However, mechanistic aspects of the pathway are still poorly understood. Here we provide an overview of structural studies that contributed to our understanding of the mechanisms underlying mRNA localization, highlighting open questions and future challenges.

RNAcompete-S: Combined RNA sequence/structure preferences for RNA binding proteins derived from a single-step in vitro selection

RNA-binding proteins recognize RNA sequences and structures, but there is currently no systematic and accurate method to derive large (>12base) motifs de novo that reflect a combination of intrinsic preference to both sequence and structure. To address this absence, we introduce RNAcompete-S, which couples a single-step competitive binding reaction with an excess of random RNA 40-mers to a custom computational pipeline for interrogation of the bound RNA sequences and derivation of SSMs (Sequence and Structure Models). RNAcompete-S confirms that HuR, QKI, and SRSF1 prefer binding sites that are single stranded, and recapitulates known 8-10bp sequence and structure preferences for Vts1p and RBMY. We also derive an 18-base long SSM for Drosophila SLBP, which to our knowledge has not been previously determined by selections from pure random sequence, and accurately discriminates human replication-dependent histone mRNAs. Thus, RNAcompete-S enables accurate identification of large, intrinsic sequence-structure specificities with a uniform assay.

Estimating the prevalence of functional exonic splice regulatory information

In addition to coding information, human exons contain sequences necessary for correct splicing. These elements are known to be under purifying selection and their disruption can cause disease. However, the density of functional exonic splicing information remains profoundly uncertain. Several groups have experimentally investigated how mutations at different exonic positions affect splicing. They have found splice information to be distributed widely in exons, with one estimate putting the proportion of splicing-relevant nucleotides at >90%. These results suggest that splicing could place a major pressure on exon evolution. However, analyses of sequence conservation have concluded that the need to preserve splice regulatory signals only slightly constrains exon evolution, with a resulting decrease in the average human rate of synonymous evolution of only 1–4%. Why do these two lines of research come to such different conclusions? Among other reasons, we suggest that the methods are measuring different things: one assays the density of sites that affect splicing, the other the density of sites whose effects on splicing are visible to selection. In addition, the experimental methods typically consider short exons, thereby enriching for nucleotides close to the splice junction, such sites being enriched for splice-control elements. By contrast, in part owing to correction for nucleotide composition biases and to the assumption that constraint only operates on exon ends, the conservation-based methods can be overly conservative.

Comprehensive and quantitative mapping of RNA-protein interactions across a transcribed eukaryotic genome

RNA-binding proteins (RBPs) control the fate of nearly every transcript in a cell. However, no existing approach for studying these posttranscriptional gene regulators combines transcriptome-wide throughput and biophysical precision. Here, we describe an assay that accomplishes this. Using commonly available hardware, we built a customizable, open-source platform that leverages the inherent throughput of Illumina technology for direct biophysical measurements. We used the platform to quantitatively measure the binding affinity of the prototypical RBP Vts1 for every transcript in the Saccharomyces cerevisiae genome. The scale and precision of these measurements revealed many previously unknown features of this well-studied RBP. Our transcribed genome array (TGA) assayed both rare and abundant transcripts with equivalent proficiency, revealing hundreds of low-abundance targets missed by previous approaches. These targets regulated diverse biological processes including nutrient sensing and the DNA damage response, and implicated Vts1 in de novo gene "birth." TGA provided single-nucleotide resolution for each binding site and delineated a highly specific sequence and structure motif for Vts1 binding. Changes in transcript levels in vts1Δ cells established the regulatory function of these binding sites. The impact of Vts1 on transcript abundance was largely independent of where it bound within an mRNA, challenging prevailing assumptions about how this RBP drives RNA degradation. TGA thus enables a quantitative description of the relationship between variant RNA structures, affinity, and in vivo phenotype on a transcriptome-wide scale. We anticipate that TGA will provide similarly comprehensive and quantitative insights into the function of virtually any RBP.

A combined sequence and structure based method for discovering enriched motifs in RNA from in vivo binding data

RNA binding proteins (RBPs) play an important role in regulating many processes in the cell. RBPs often recognize their RNA targets in a specific manner. In addition to the RNA primary sequence, the structure of the RNA has been shown to play a central role in RNA recognition by RBPs. In recent years, many experimental approaches, both in vitro and in vivo, were developed and employed to identify and characterize RBP targets and extract their binding specificities. In vivo binding techniques, such as CrossLinking and ImmunoPrecipitation (CLIP)-based methods, enable the characterization of protein binding sites on RNA targets. However, these methods do not provide information regarding the structural preferences of the protein. While methods to obtain the structure of RNA are available, inferring both the sequence and the structure preferences of RBPs remains a challenge. Here we present SMARTIV, a novel computational tool for discovering combined sequence and structure binding motifs from in vivo RNA binding data relying on the sequences of the target sites, the ranking of their binding scores and their predicted secondary structure. The combined motifs are provided in a unified representation that is informative and easy for visual perception. We tested the method on CLIP-seq data from different platforms for a variety of RBPs. Overall, we show that our results are highly consistent with known binding motifs of RBPs, offering additional information on their structural preferences.

The bicoid mRNA localization factor Exuperantia is an RNA-binding pseudonuclease

Anterior patterning in Drosophila is mediated by the localization of bicoid (bcd) mRNA at the anterior pole of the oocyte. Exuperantia (Exu) is a putative exonuclease (EXO) associated with bcd and required for its localization. We present the crystal structure of Exu, which reveals a dimeric assembly with each monomer consisting of a 3'-5' EXO-like domain and a sterile alpha motif (SAM)-like domain. The catalytic site is degenerate and inactive. Instead, the EXO-like domain mediates dimerization and RNA binding. We show that Exu binds RNA directly in vitro, that the SAM-like domain is required for RNA binding activity and that Exu binds a structured element present in the bcd 3' untranslated region with high affinity. Through structure-guided mutagenesis, we show that Exu dimerization is essential for bcd localization. Our data demonstrate that Exu is a noncanonical RNA-binding protein with EXO-SAM-like domain architecture that interacts with its target RNA as a homodimer.

A Smaug2-Based Translational Repression Complex Determines the Balance between Precursor Maintenance versus Differentiation during Mammalian Neurogenesis

Here, we have asked about post-transcriptional mechanisms regulating murine developmental neurogenesis, focusing upon the RNA-binding proteins Smaug2 and Nanos1. We identify, in embryonic neural precursors of the murine cortex, a Smaug2 protein/nanos1 mRNA complex that is present in cytoplasmic granules with the translational repression proteins Dcp1 and 4E-T. We show that Smaug2 inhibits and Nanos1 promotes neurogenesis, with Smaug2 knockdown enhancing neurogenesis and depleting precursors, and Nanos1 knockdown inhibiting neurogenesis and maintaining precursors. Moreover, we show that Smaug2 likely regulates neurogenesis by silencing nanos1 mRNA. Specifically, Smaug2 knockdown inappropriately increases Nanos1 protein, and the Smaug2 knockdown-mediated neurogenesis is rescued by preventing this increase. Thus, Smaug2 and Nanos1 function as a bimodal translational repression switch to control neurogenesis, with Smaug2 acting in transcriptionally primed precursors to silence mRNAs important for neurogenesis, including nanos1 mRNA, and Nanos1 acting during the transition to neurons to repress the precursor state.

SIGNIFICANCE STATEMENT

The mechanisms instructing neural stem cells to generate the appropriate progeny are still poorly understood. Here, we show that the RNA-binding proteins Smaug2 and Nanos1 are critical regulators of this balance and provide evidence supporting the idea that neural precursors are transcriptionally primed to generate neurons but translational regulation maintains these precursors in a stem cell state until the appropriate developmental time.

RNA recognition by Roquin in posttranscriptional gene regulation

Posttranscriptional regulation of gene expression plays a central role in the initiation of innate and adaptive immune responses. This is exemplified by the protein Roquin, which has attracted great interest during the past decade owing to its ability to prevent autoimmunity. Roquin controls T-cell activation and T helper cell differentiation by limiting the induced expression of costimulatory receptors on the surface of T cells. It does so by recognizing cis regulatory RNA-hairpin elements in the 3' UTR of target transcripts via its ROQ domain-a novel RNA-binding fold-and triggering their degradation through recruitment of factors that mediate deadenylation and decapping. Recent structural studies have revealed molecular details of the recognition of RNA hairpin structures by the ROQ domain. Surprisingly, it was found that Roquin mainly relies on shape-specific recognition of the RNA. This observation implies that a much broader range of RNA motifs could interact with the protein, but it also complicates systematic searches for novel mRNA targets of Roquin. Thus, large-scale approaches, such as crosslinking and immunoprecipitation or systematic evolution of ligands by exponential enrichment experiments coupled with next-generation sequencing, will be required to identify the complete spectrum of its target RNAs. Together with structural analyses of their binding modes, this will enable us to unravel the intricate complexity of 3' UTR regulation by Roquin and other trans-acting factors. Here, we review our current understanding of Roquin-RNA interactions and their role for Roquin function. WIREs RNA 2016, 7:455-469. doi: 10.1002/wrna.1333 For further resources related to this article, please visit the WIREs website.

Isolation and analyses of axonal ribonucleoprotein complexes

Cytoskeleton-dependent RNA transport and local translation in axons are gaining increased attention as key processes in the maintenance and functioning of neurons. Specific axonal transcripts have been found to play roles in many aspects of axonal physiology including axon guidance, axon survival, axon to soma communication, injury response and regeneration. This axonal transcriptome requires long-range transport that is achieved by motor proteins carrying transcripts as messenger ribonucleoprotein (mRNP) complexes along microtubules. Other than transport, the mRNP complex plays a major role in the generation, maintenance, and regulation of the axonal transcriptome. Identification of axonal RNA-binding proteins (RBPs) and analyses of the dynamics of their mRNPs are of high interest to the field. Here, we describe methods for the study of interactions between RNA and proteins in axons. First, we describe a protocol for identifying binding proteins for an RNA of interest by using RNA affinity chromatography. Subsequently, we discuss immunoprecipitation (IP) methods allowing the dissection of protein-RNA and protein-protein interactions in mRNPs under various physiological conditions.

Bicaudal-C plays a vital role in oogenesis in Nilaparvata lugens (Hemiptera: Delphacidae)

Bicaudal-C (Bic-C) was originally identified in a Drosophila melanogaster mutagenesis screen and plays vital roles in embryogenesis. In this study, we characterized the Bic-C gene in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae), an insect pest that undergoes incomplete metamorphosis. Our result showed that N. lugens Bic-C (NlBic-C) is a female-specific gene in this species. It is specifically expressed in developing oocytes and is not expressed in laid eggs. Ribonucleic acid interference (RNAi) of NlBic-C arrested the uptake of vitelline by oocytes, and resulted in undeveloped ovaries and the complete inhibition of oocyte growth in the ovarioles, suggesting that NlBic-C is required for oogenesis and oocyte maturation. NlBic-C is extremely highly sensitive to RNAi, suggesting that it may be a potential target in RNAi-based insect pest management.

DSSR: an integrated software tool for dissecting the spatial structure of RNA

Insight into the three-dimensional architecture of RNA is essential for understanding its cellular functions. However, even the classic transfer RNA structure contains features that are overlooked by existing bioinformatics tools. Here we present DSSR (Dissecting the Spatial Structure of RNA), an integrated and automated tool for analyzing and annotating RNA tertiary structures. The software identifies canonical and noncanonical base pairs, including those with modified nucleotides, in any tautomeric or protonation state. DSSR detects higher-order coplanar base associations, termed multiplets. It finds arrays of stacked pairs, classifies them by base-pair identity and backbone connectivity, and distinguishes a stem of covalently connected canonical pairs from a helix of stacked pairs of arbitrary type/linkage. DSSR identifies coaxial stacking of multiple stems within a single helix and lists isolated canonical pairs that lie outside of a stem. The program characterizes 'closed' loops of various types (hairpin, bulge, internal, and junction loops) and pseudoknots of arbitrary complexity. Notably, DSSR employs isolated pairs and the ends of stems, whether pseudoknotted or not, to define junction loops. This new, inclusive definition provides a novel perspective on the spatial organization of RNA. Tests on all nucleic acid structures in the Protein Data Bank confirm the efficiency and robustness of the software, and applications to representative RNA molecules illustrate its unique features. DSSR and related materials are freely available at http://x3dna.org/.

Mitochondrial dysfunction reveals the role of mRNA poly(A) tail regulation in oculopharyngeal muscular dystrophy pathogenesis

Oculopharyngeal muscular dystrophy (OPMD), a late-onset disorder characterized by progressive degeneration of specific muscles, results from the extension of a polyalanine tract in poly(A) binding protein nuclear 1 (PABPN1). While the roles of PABPN1 in nuclear polyadenylation and regulation of alternative poly(A) site choice are established, the molecular mechanisms behind OPMD remain undetermined. Here, we show, using Drosophila and mouse models, that OPMD pathogenesis depends on affected poly(A) tail lengths of specific mRNAs. We identify a set of mRNAs encoding mitochondrial proteins that are down-regulated starting at the earliest stages of OPMD progression. The down-regulation of these mRNAs correlates with their shortened poly(A) tails and partial rescue of their levels when deadenylation is genetically reduced improves muscle function. Genetic analysis of candidate genes encoding RNA binding proteins using the Drosophila OPMD model uncovers a potential role of a number of them. We focus on the deadenylation regulator Smaug and show that it is expressed in adult muscles and specifically binds to the down-regulated mRNAs. In addition, the first step of the cleavage and polyadenylation reaction, mRNA cleavage, is affected in muscles expressing alanine-expanded PABPN1. We propose that impaired cleavage during nuclear cleavage/polyadenylation is an early defect in OPMD. This defect followed by active deadenylation of specific mRNAs, involving Smaug and the CCR4-NOT deadenylation complex, leads to their destabilization and mitochondrial dysfunction. These results broaden our understanding of the role of mRNA regulation in pathologies and might help to understand the molecular mechanisms underlying neurodegenerative disorders that involve mitochondrial dysfunction.

Oculopharyngeal muscular dystrophy is a genetic disease characterized by progressive degeneration of specific muscles, leading to ptosis (eyelid drooping), dysphagia (swallowing difficulties) and proximal limb weakness. The disease results from mutations in a nuclear protein called poly(A) binding protein nuclear 1 that is involved in polyadenylation of messenger RNAs (mRNAs) and poly(A) site selection. To address the molecular mechanisms involved in the disease, we have used two animal models (Drosophila and mouse) that recapitulate the features of this disorder. We show that oculopharyngeal muscular dystrophy pathogenesis depends on defects in poly(A) tail length regulation of specific mRNAs. Because poly(A) tails play an essential role in mRNA stability, these defects result in accelerated decay of these mRNAs. The affected mRNAs encode mitochondrial proteins, and mitochondrial activity is impaired in diseased muscles. These findings have important implications for the development of potential therapies for oculopharyngeal muscular dystrophy, and might be relevant to decipher the molecular mechanisms underlying other disorders that involve mitochondrial dysfunction.

Can We Execute Stable Microsecond-Scale Atomistic Simulations of Protein-RNA Complexes?

We report over 30 μs of unrestrained molecular dynamics simulations of six protein-RNA complexes in explicit solvent. We utilize the AMBER ff99bsc0χ(OL3) RNA force field combined with the ff99SB protein force field and its more recent ff12SB version with reparametrized side-chain dihedrals. The simulations show variable behavior, ranging from systems that are essentially stable to systems with progressive deviations from the experimental structure, which we could not stabilize anywhere close to the starting experimental structure. For some systems, microsecond-scale simulations are necessary to achieve stabilization after initial sizable structural perturbations. The results show that simulations of protein-RNA complexes are challenging and every system should be treated individually. The simulations are affected by numerous factors, including properties of the starting structures (the initially high force field potential energy, resolution limits, conformational averaging, crystal packing, etc.), force field imbalances, and real flexibility of the studied systems. These factors, and thus the simulation behavior, differ from system to system. The structural stability of simulated systems does not correlate with the size of buried interaction surface or experimentally determined binding affinities but reflects the type of protein-RNA recognition. Protein-RNA interfaces involving shape-specific recognition of RNA are more stable than those relying on sequence-specific RNA recognition. The differences between the protein force fields are considerably smaller than the uncertainties caused by sampling and starting structures. The ff12SB improves description of the tyrosine side-chain group, which eliminates some problems associated with tyrosine dynamics.

Activation of TLR3 promotes the degeneration of retinal ganglion cells by upregulating the protein levels of JNK3

PURPOSE

To investigate whether activation of Toll-like receptor 3 (TLR3) promotes the degeneration of retinal ganglion cells (RGCs) by upregulating the protein levels of c-jun N-terminal kinase 3 (JNK3).

METHODS

Toll-like receptor 3-specific activator, Poly(I:C) (polyinosinic-polycytidylic acid), or PBS was injected into the vitreous humor of Thy1-YFP mice. At 24, 48, and 72 hours after treatments, degeneration of RGCs was assessed by using antibodies against brain-specific homeobox/POU domain protein 3a (Brn3a). A TLR3-specific inhibitor was injected into the vitreous humor with or without Poly(I:C). Western blot assays were performed to determine relative levels of TLR3, JNK3, pJNK3, and sterile alpha and HEAT/Armadillo motif-containing 1 (SARM1) proteins in retinal protein extracts, and immunohistochemistry assays were performed to determine their cellular localization in the retina. Mouse eyes were treated with Poly(I:C) or PBS along with MitoTracker Red, and colocalization of MitoTracker Red and JNK3 in the retinas was determined by using antibodies against JNK3.

RESULTS

Poly(I:C) activated TLR3 and upregulated its downstream target protein JNK3 but not SARM1 in the retina. Poly(I:C) activated TLR3 and upregulated JNK3 specifically in RGCs and promoted a significant degeneration of RGCs over a 72-hour time period. Toll-like receptor 3 upregulated the levels of JNK3 protein in the cytoplasm of RGCs, but not in the mitochondria. Toll-like receptor 3-specific inhibitor downregulated Poly(I:C)-mediated upregulation of JNK3 protein, and, in turn, significantly attenuated TLR3-induced degeneration of RGCs.

CONCLUSIONS

Results presented in this study show that the activation of TLR3 alone promotes the degeneration of RGCs by upregulating the protein levels of JNK3.

High-throughput characterization of protein-RNA interactions

RNA-binding proteins (RBPs) are important regulators of eukaryotic gene expression. Genomes typically encode dozens to hundreds of proteins containing RNA-binding domains, which collectively recognize diverse RNA sequences and structures. Recent advances in high-throughput methods for assaying the targets of RBPs in vitro and in vivo allow large-scale derivation of RNA-binding motifs as well as determination of RNA–protein interactions in living cells. In parallel, many computational methods have been developed to analyze and interpret these data. The interplay between RNA secondary structure and RBP binding has also been a growing theme. Integrating RNA–protein interaction data with observations of post-transcriptional regulation will enhance our understanding of the roles of these important proteins.

Biochemical and bioinformatic methods for elucidating the role of RNA-protein interactions in posttranscriptional regulation

Our understanding of transcriptional gene regulation has dramatically increased over the past decades, and many regulators of gene expression, such as transcription factors, have been analyzed extensively. Additionally, in recent years, deeper insights into the physiological roles of RNA have been obtained. More precisely, splicing, polyadenylation, various modifications, localization and the translation of messenger RNAs (mRNAs) are regulated by their interaction with RNA-binding proteins (RBPs). New technologies now enable the analysis of this regulation at different levels. A technique known as ultraviolet (UV) cross-linking and immunoprecipitation (CLIP) allows us to determine physical protein–RNA interactions on a genome-wide scale. UV cross-linking introduces covalent bonds between interacting RBPs and RNAs. In combination with immunoprecipitation and deep sequencing techniques, tens of millions of short reads (representing bound RNAs by an RBP of interest) are generated and are used to characterize the regulatory network mediated by an RBP. Other methods, such as mass spectrometry, can also be used for characterization of cross-linked RBPs and RNAs instead of CLIP methods. In this review, we discuss experimental and computational methods for the generation and analysis of CLIP data. The computational methods include short-read alignment, annotation and RNA-binding motif discovery. We describe the challenges of analyzing CLIP data and indicate areas where improvements are needed.

Synaptic control of local translation: the plot thickens with new characters

The production of proteins from mRNAs localized at the synapse ultimately controls the strength of synaptic transmission, thereby affecting behavior and cognitive functions. The regulated transcription, processing, and transport of mRNAs provide dynamic control of the dendritic transcriptome, which includes thousands of messengers encoding multiple cellular functions. Translation is locally modulated by synaptic activity through a complex network of RNA-binding proteins (RBPs) and various types of non-coding RNAs (ncRNAs) including BC-RNAs, microRNAs, piwi-interacting RNAs, and small interference RNAs. The RBPs FMRP and CPEB play a well-established role in synaptic translation, and additional regulatory factors are emerging. The mRNA repressors Smaug, Nanos, and Pumilio define a novel pathway for local translational control that affects dendritic branching and spines in both flies and mammals. Recent findings support a role for processing bodies and related synaptic mRNA-silencing foci (SyAS-foci) in the modulation of synaptic plasticity and memory formation. The SyAS-foci respond to different stimuli with changes in their integrity thus enabling regulated mRNA release followed by translation. CPEB, Pumilio, TDP-43, and FUS/TLS form multimers through low-complexity regions related to prion domains or polyQ expansions. The oligomerization of these repressor RBPs is mechanistically linked to the aggregation of abnormal proteins commonly associated with neurodegeneration. Here, we summarize the current knowledge on how specificity in mRNA translation is achieved through the concerted action of multiple pathways that involve regulatory ncRNAs and RBPs, the modification of translation factors, and mRNA-silencing foci dynamics.

Mutation of mouse Samd4 causes leanness, myopathy, uncoupled mitochondrial respiration, and dysregulated mTORC1 signaling

Sterile alpha motif domain containing protein 4 (Samd4) is an RNA binding protein that mediates translational repression. We identified a Samd4 missense mutation, designated supermodel, that caused leanness and kyphosis associated with myopathy and adipocyte defects in C57BL/6J mice. The supermodel mutation protected homozygous mice from high fat diet-induced obesity, likely by promoting enhanced energy expenditure through uncoupled mitochondrial respiration. Glucose tolerance was impaired due to diminished insulin release in homozygous mutant mice. The defects of metabolism in supermodel mice may be explained by dysregulated mechanistic target of rapamycin complex 1 (mTORC1) signaling, evidenced by hypophosphorylation of 4E-BP1 and S6 in muscle and adipose tissues of homozygous mice. Samd4 may interface with mTORC1 signaling through an interaction with 14-3-3 proteins and with Akt, which phosphorylates Samd4 in vitro.

CapR: revealing structural specificities of RNA-binding protein target recognition using CLIP-seq data

RNA-binding proteins (RBPs) bind to their target RNA molecules by recognizing specific RNA sequences and structural contexts. The development of CLIP-seq and related protocols has made it possible to exhaustively identify RNA fragments that bind to RBPs. However, no efficient bioinformatics method exists to reveal the structural specificities of RBP–RNA interactions using these data. We present CapR, an efficient algorithm that calculates the probability that each RNA base position is located within each secondary structural context. Using CapR, we demonstrate that several RBPs bind to their target RNA molecules under specific structural contexts. CapR is available at https://sites.google.com/site/fukunagatsu/software/capr.

Differential protein occupancy profiling of the mRNA transcriptome

Background

RNA-binding proteins (RBPs) mediate mRNA biogenesis, translation and decay. We recently developed an approach to profile transcriptome-wide RBP contacts on polyadenylated transcripts by next-generation sequencing. A comparison of such profiles from different biological conditions has the power to unravel dynamic changes in protein-contacted cis-regulatory mRNA regions without a priori knowledge of the regulatory protein component.

Results

We compared protein occupancy profiles of polyadenylated transcripts in MCF7 and HEK293 cells. Briefly, we developed a bioinformatics workflow to identify differential crosslinking sites in cDNA reads of 4-thiouridine crosslinked polyadenylated RNA samples. We identified 30,000 differential crosslinking sites between MCF7 and HEK293 cells at an estimated false discovery rate of 10%. 73% of all reported differential protein-RNA contact sites cannot be explained by local changes in exon usage as indicated by complementary RNA-seq data. The majority of differentially crosslinked positions are located in 3′ UTRs, show distinct secondary-structure characteristics and overlap with binding sites of known RBPs, such as ELAVL1. Importantly, mRNA transcripts with the most significant occupancy changes show elongated mRNA half-lives in MCF7 cells.

Conclusions

We present a global comparison of protein occupancy profiles from different cell types, and provide evidence for altered mRNA metabolism as a result of differential protein-RNA contacts. Additionally, we introduce POPPI, a bioinformatics workflow for the analysis of protein occupancy profiling experiments. Our work demonstrates the value of protein occupancy profiling for assessing cis-regulatory RNA sequence space and its dynamics in growth, development and disease.

Global regulation of mRNA translation and stability in the early Drosophila embryo by the Smaug RNA-binding protein

Background

Smaug is an RNA-binding protein that induces the degradation and represses the translation of mRNAs in the early Drosophila embryo. Smaug has two identified direct target mRNAs that it differentially regulates: nanos and Hsp83. Smaug represses the translation of nanos mRNA but has only a modest effect on its stability, whereas it destabilizes Hsp83 mRNA but has no detectable effect on Hsp83 translation. Smaug is required to destabilize more than one thousand mRNAs in the early embryo, but whether these transcripts represent direct targets of Smaug is unclear and the extent of Smaug-mediated translational repression is unknown.

Results

To gain a panoramic view of Smaug function in the early embryo, we identified mRNAs that are bound to Smaug using RNA co-immunoprecipitation followed by hybridization to DNA microarrays. We also identified mRNAs that are translationally repressed by Smaug using polysome gradients and microarrays. Comparison of the bound mRNAs to those that are translationally repressed by Smaug and those that require Smaug for their degradation suggests that a large fraction of Smaug’s target mRNAs are both translationally repressed and degraded by Smaug. Smaug directly regulates components of the TRiC/CCT chaperonin, the proteasome regulatory particle and lipid droplets, as well as many metabolic enzymes, including several glycolytic enzymes.

Conclusions

Smaug plays a direct and global role in regulating the translation and stability of a large fraction of the mRNAs in the early Drosophila embryo, and has unanticipated functions in control of protein folding and degradation, lipid droplet function and metabolism.

Mutation of FVS1, encoding a protein with a sterile alpha motif domain, affects asexual reproduction in the fungal plant pathogen Fusarium oxysporum

Fusarium oxysporum produces three kinds of asexual spores: microconidia, macroconidia and chlamydospores. We previously analysed expressed sequence tags during vegetative growth and conidiation in F. oxysporum and found 42 genes that were markedly upregulated during conidiation compared to vegetative growth. One of the genes, FVS1, encodes a protein with a sterile alpha motif (SAM) domain, which functions in protein-protein interactions that are involved in transcriptional or post-transcriptional regulation and signal transduction. Here, we made FVS1-disrupted mutants from the melon wilt pathogen F. oxysporum f. sp. melonis. Although the mutants produced all three kinds of asexual spores with normal morphology, they formed markedly fewer microconidia and macroconidia than the wild type. The mutants appeared to have a defect in the development of the conidiogenesis cells, conidiophores and phialides, required for the formation of microconidia and macroconidia. In contrast, chlamydospore formation was dramatically promoted in the mutants. The growth rates of the mutants on media were slightly reduced, indicating that FVS1 is also involved in, but not essential for, vegetative growth. We also observed that mutation of FVS1 caused defects in conidial germination and virulence, suggesting that the Fvs1 has pleiotropic functions in F. oxysporum.

RNA-protein interactions: an overview

RNA binding proteins (RBPs) are key players in the regulation of gene expression. In this chapter we discuss the main protein-RNA recognition modes used by RBPs in order to regulate multiple steps of RNA processing. We discuss traditional and state-of-the-art technologies that can be used to study RNAs bound by individual RBPs, or vice versa, for both in vitro and in vivo methodologies. To help highlight the biological significance of RBP mediated regulation, online resources on experimentally verified protein-RNA interactions are briefly presented. Finally, we present the major tools to computationally infer RNA binding sites according to the modeling features and to the unsupervised or supervised frameworks that are adopted. Since some RNA binding site search algorithms are derived from DNA binding site search algorithms, we discuss the commonalities and novelties introduced to handle both sequence and structural features uniquely characterizing protein-RNA interactions.

Finding the target sites of RNA-binding proteins

RNA–protein interactions differ from DNA–protein interactions because of the central role of RNA secondary structure. Some RNA-binding domains (RBDs) recognize their target sites mainly by their shape and geometry and others are sequence-specific but are sensitive to secondary structure context. A number of small- and large-scale experimental approaches have been developed to measure RNAs associated in vitro and in vivo with RNA-binding proteins (RBPs). Generalizing outside of the experimental conditions tested by these assays requires computational motif finding. Often RBP motif finding is done by adapting DNA motif finding methods; but modeling secondary structure context leads to better recovery of RBP-binding preferences. Genome-wide assessment of mRNA secondary structure has recently become possible, but these data must be combined with computational predictions of secondary structure before they add value in predicting in vivo binding. There are two main approaches to incorporating structural information into motif models: supplementing primary sequence motif models with preferred secondary structure contexts (e.g., MEMERIS and RNAcontext) and directly modeling secondary structure recognized by the RBP using stochastic context-free grammars (e.g., CMfinder and RNApromo). The former better reconstruct known binding preferences for sequence-specific RBPs but are not suitable for modeling RBPs that recognize shape and geometry of RNAs. Future work in RBP motif finding should incorporate interactions between multiple RBDs and multiple RBPs in binding to RNA. WIREs RNA 2014, 5:111–130. doi: 10.1002/wrna.1201

A role for synaptic zinc in ProSAP/Shank PSD scaffold malformation in autism spectrum disorders

The establishment and maintenance of synaptic contacts as well as synaptic plasticity are crucial factors for normal brain function. The functional properties of a synapse are largely dependent on the molecular setup of synaptic proteins. Multidomain proteins of the ProSAP/Shank family act as major organizing scaffolding elements of the postsynaptic density (PSD). Interestingly, ProSAP/Shank proteins at glutamatergic synapses have been linked to a variety of Autism Spectrum Disorders (ASDs) including Phelan McDermid Syndrome, and deregulation of ProSAP/Shank has been reported in Alzheimer's disease. Although the precise molecular mechanism of the dysfunction of these proteins remains unclear, an emerging model is that mutations or deletions impair neuronal circuitry by disrupting the formation, plasticity and maturation of glutamatergic synapses. Several PSD proteins associated with ASDs are part of a complex centered around ProSAP/Shank proteins and many ProSAP/Shank interaction partners play a role in signaling within dendritic spines. Interfering with any one of the members of this signaling complex might change the output and drive the system towards synaptic dysfunction. Based on recent data, it is possible that the concerted action of ProSAP/Shank and Zn²⁺ is essential for the structural integrity of the PSD. This interplay might regulate postsynaptic receptor composition, but also transsynaptic signaling. It might be possible that environmental factors like nutritional Zn²⁺ status or metal ion homeostasis in general intersect with this distinct pathway centered around ProSAP/Shank proteins and the deregulation of any of these two factors may lead to ASDs.

RBPmotif: a web server for the discovery of sequence and structure preferences of RNA-binding proteins

RBPmotif web server (http://www.rnamotif.org) implements tools to identify binding preferences of RNA-binding proteins (RBPs). Given a set of sequences that are known to be bound and unbound by the RBP of interest, RBPmotif provides two types of analysis: (i) de novo motif finding when there is no a priori knowledge on RBP’s binding preferences and (ii) analysis of structure preferences when there is a previously identified sequence motif for the RBP. De novo motif finding is performed with the previously published RNAcontext algorithm that learns discriminative motif models to identify both sequence and structure preferences. The results of this analysis include the inferred binding preferences of the RBP and the added predictive value of incorporating structure preferences. Second type of analysis investigates whether the instances of the previously identified sequence motif are enriched in a particular structure context in bound sequences, relative to its instances in unbound sequences. On completion, the results page shows the comparison of structure contexts of the motif instances between bound and unbound sequences and an assessment of statistical significance of detected preferences. In summary, RBPmotif web server enables the concurrent analysis of sequence and structure preferences of RBPs through a user-friendly interface.

Nuclear RNA surveillance: role of TRAMP in controlling exosome specificity

The advent of high-throughput sequencing technologies has revealed that pervasive transcription generates RNAs from nearly all regions of eukaryotic genomes. Normally, these transcripts undergo rapid degradation by a nuclear RNA surveillance system primarily featuring the RNA exosome. This multimeric protein complex plays a critical role in the efficient turnover and processing of a vast array of RNAs in the nucleus. Despite its initial discovery over a decade ago, important questions remain concerning the mechanisms that recruit and activate the nuclear exosome. Specificity and modulation of exosome activity requires additional protein cofactors, including the conserved TRAMP polyadenylation complex. Recent studies suggest that helicase and RNA-binding subunits of TRAMP direct RNA substrates for polyadenylation, which enhances their degradation by Dis3/Rrp44 and Rrp6, the two exosome-associated ribonucleases. These findings indicate that the exosome and TRAMP have evolved highly flexible functions that allow recognition of a wide range of RNA substrates. This flexibility provides the nuclear RNA surveillance system with the ability to regulate the levels of a broad range of coding and noncoding RNAs, which results in profound effects on gene expression, cellular development, gene silencing, and heterochromatin formation. This review summarizes recent findings on the nuclear RNA surveillance complexes, and speculates upon possible mechanisms for TRAMP-mediated substrate recognition and exosome activation.