Discovering structural cis-regulatory elements by modeling the behaviors of mRNAs

RNA-binding protein SAMD4A inhibits breast tumor angiogenesis by modulating the balance of angiogenesis program

Tumor-induced angiogenesis is important for further progression of solid tumors. The initiation of tumor angiogenesis is dictated by a shift in the balance between proangiogenic and antiangiogenic gene expression programs. However, the potential mechanism controlling the expression of angiogenesis-related genes in the tumor cells, especially the process mediated by RNA-binding protein (RBP) remains unclear. SAMD4A is a conserved RBP across fly to mammals, and is believed to play an important role in controlling gene translation and stability. In this study, we identified the potential role of SAMD4A in modulating angiogenesis-related gene expression and tumor progression in breast cancer. SAMD4A expression was repressed in breast cancer tissues and cells and low SAMD4A expression in human breast tumor samples was strongly associated with poor survival of patients. Overexpression of SAMD4A inhibited breast tumor angiogenesis and caner progression, whereas knockdown of SAMD4A demonstrated a reversed effect. Mechanistically, SAMD4A was found to specifically destabilize the proangiogenic gene transcripts, including C-X-C motif chemokine ligand 5 (CXCL5), endoglin (ENG), interleukin 1β (IL1β), and angiopoietin 1 (ANGPT1), by directly interacting with the stem-loop structure in the 3' untranslated region (3'UTR) of these mRNAs through its sterile alpha motif (SAM) domain, resulting in the imbalance of angiogenic genes expression. Collectively, our results suggest that SAMD4A is a novel breast tumor suppressor that inhibits tumor angiogenesis by specifically downregulating the expression of proangiogenic genes, which might be a potential antiangiogenic target for breast cancer therapy.

SSMART: sequence-structure motif identification for RNA-binding proteins

Motivation

RNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized.

Results

We developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3'UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP.

Availability and implementation

SSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Regulatory principles governing the maternal-to-zygotic transition: insights from Drosophila melanogaster

The onset of metazoan development requires that two terminally differentiated germ cells, a sperm and an oocyte, become reprogrammed to the totipotent embryo, which can subsequently give rise to all the cell types of the adult organism. In nearly all animals, maternal gene products regulate the initial events of embryogenesis while the zygotic genome remains transcriptionally silent. Developmental control is then passed from mother to zygote through a process known as the maternal-to-zygotic transition (MZT). The MZT comprises an intimately connected set of molecular events that mediate degradation of maternally deposited mRNAs and transcriptional activation of the zygotic genome. This essential developmental transition is conserved among metazoans but is perhaps best understood in the fruit fly, Drosophila melanogaster. In this article, we will review our understanding of the events that drive the MZT in Drosophila embryos and highlight parallel mechanisms driving this transition in other animals.

Clearance of Maternal RNAs: Not a Mummy's Embryo Anymore

Until the zygotic genome is activated, early development relies on the products deposited by the mother. Once the zygotic genome starts to be transcribed, most maternal products are not needed anymore by the developing embryo. This emancipation from the maternal genome occurs during the Zygotic Genome Activation (ZGA). Although the process by which the maternal content is replaced with zygotic products differs from species to species, there is a common theme to all of them: maternal transcripts are actively degraded. Here, a review of how the degradation of maternal RNAs is regulated during early development and discussions on some computational tools that may be of use in this research area are outlined.

Affinity regression predicts the recognition code of nucleic acid-binding proteins

Predicting the affinity profiles of nucleic acid-binding proteins directly from the protein sequence is a major unsolved problem. We present a statistical approach for learning the recognition code of a family of transcription factors (TFs) or RNA-binding proteins (RBPs) from high-throughput binding assays. Our method, called affinity regression, trains on protein binding microarray (PBM) or RNA compete experiments to learn an interaction model between proteins and nucleic acids, using only protein domain and probe sequences as inputs. By training on mouse homeodomain PBM profiles, our model correctly identifies residues that confer DNA-binding specificity and accurately predicts binding motifs for an independent set of divergent homeodomains. Similarly, learning from RNA compete profiles for diverse RBPs, our model can predict the binding affinities of held-out proteins and identify key RNA-binding residues. More broadly, we envision applying our method to model and predict biological interactions in any setting where there is a high-throughput ‘affinity’ readout.

Deciphering RNA Regulatory Elements Involved in the Developmental and Environmental Gene Regulation of Trypanosoma brucei

Trypanosoma brucei is a vector-borne parasite with intricate life cycle that can cause serious diseases in humans and animals. This pathogen relies on fine regulation of gene expression to respond and adapt to variable environments, with implications in transmission and infectivity. However, the involved regulatory elements and their mechanisms of actions are largely unknown. Here, benefiting from a new graph-based approach for finding functional regulatory elements in RNA (GRAFFER), we have predicted 88 new RNA regulatory elements that are potentially involved in the gene regulatory network of T. brucei. We show that many of these newly predicted elements are responsive to both transcriptomic and proteomic changes during the life cycle of the parasite. Moreover, we found that 11 of predicted elements strikingly resemble previously identified regulatory elements for the parasite. Additionally, comparison with previously predicted motifs on T. brucei suggested the superior performance of our approach based on the current limited knowledge of regulatory elements in T. brucei.

Different motif requirements for the localization zipcode element of β-actin mRNA binding by HuD and ZBP1

Interactions of RNA-binding proteins (RBPs) with their target transcripts are essential for regulating gene expression at the posttranscriptional level including mRNA export/localization, stability, and translation. ZBP1 and HuD are RBPs that play pivotal roles in mRNA transport and local translational control in neuronal processes. While HuD possesses three RNA recognition motifs (RRMs), ZBP1 contains two RRMs and four K homology (KH) domains that either increase target specificity or provide a multi-target binding capability. Here we used isolated cis-element sequences of the target mRNA to examine directly protein-RNA interactions in cell-free systems. We found that both ZBP1 and HuD bind the zipcode element in rat β-actin mRNA's 3' UTR. Differences between HuD and ZBP1 were observed in their binding preference to the element. HuD showed a binding preference for U-rich sequence. In contrast, ZBP1 binding to the zipcode RNA depended more on the structural level, as it required the proper spatial organization of a stem-loop that is mainly determined by the U-rich element juxtaposed to the 3' end of a 5'-ACACCC-3' motif. On the basis of this work, we propose that ZBP1 and HuD bind to overlapping sites in the β-actin zipcode, but they recognize different features of this target sequence.

Revealing protein-lncRNA interaction

Long non-coding RNAs (lncRNAs) are associated to a plethora of cellular functions, most of which require the interaction with one or more RNA-binding proteins (RBPs); similarly, RBPs are often able to bind a large number of different RNAs. The currently available knowledge is already drawing an intricate network of interactions, whose deregulation is frequently associated to pathological states. Several different techniques were developed in the past years to obtain protein–RNA binding data in a high-throughput fashion. In parallel, in silico inference methods were developed for the accurate computational prediction of the interaction of RBP–lncRNA pairs. The field is growing rapidly, and it is foreseeable that in the near future, the protein–lncRNA interaction network will rise, offering essential clues for a better understanding of lncRNA cellular mechanisms and their disease-associated perturbations.

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.

Metastasis-suppressor transcript destabilization through TARBP2 binding of mRNA hairpins

Aberrant regulation of RNA stability has an important role in many disease states. Deregulated post-transcriptional modulation, such as that governed by microRNAs targeting linear sequence elements in messenger RNAs, has been implicated in the progression of many cancer types. A defining feature of RNA is its ability to fold into structures. However, the roles of structural mRNA elements in cancer progression remain unexplored. Here we performed an unbiased search for post-transcriptional modulators of mRNA stability in breast cancer by conducting whole-genome transcript stability measurements in poorly and highly metastatic isogenic human breast cancer lines. Using a computational framework that searches RNA sequence and structure space, we discovered a family of GC-rich structural cis-regulatory RNA elements, termed sRSEs for structural RNA stability elements, which are significantly overrepresented in transcripts displaying reduced stability in highly metastatic cells. By integrating computational and biochemical approaches, we identified TARBP2, a double-stranded RNA-binding protein implicated in microRNA processing, as the trans factor that binds the sRSE family and similar structural elements--collectively termed TARBP2-binding structural elements (TBSEs)--in transcripts. TARBP2 is overexpressed in metastatic cells and metastatic human breast tumours and destabilizes transcripts containing TBSEs. Endogenous TARBP2 promotes metastatic cell invasion and colonization by destabilizing amyloid precursor protein (APP) and ZNF395 transcripts, two genes previously associated with Alzheimer's and Huntington's disease, respectively. We reveal these genes to be novel metastasis suppressor genes in breast cancer. The cleavage product of APP, extracellular amyloid-α peptide, directly suppresses invasion while ZNF395 transcriptionally represses a pro-metastatic gene expression program. The expression levels of TARBP2, APP and ZNF395 in human breast carcinomas support their experimentally uncovered roles in metastasis. Our findings establish a non-canonical and direct role for TARBP2 in mammalian gene expression regulation and reveal that regulated RNA destabilization through protein-mediated binding of mRNA structural elements can govern cancer progression.

Systematic identification of regulatory elements in conserved 3' UTRs of human transcripts

Posttranscriptional regulatory programs governing diverse aspects of RNA biology remain largely uncharacterized. Understanding the functional roles of RNA cis-regulatory elements is essential for decoding complex programs that underlie the dynamic regulation of transcript stability, splicing, localization, and translation. Here, we describe a combined experimental/computational technology to reveal a catalog of functional regulatory elements embedded in 3' UTRs of human transcripts. We used a bidirectional reporter system coupled with flow cytometry and high-throughput sequencing to measure the effect of short, noncoding, vertebrate-conserved RNA sequences on transcript stability and translation. Information-theoretic motif analysis of the resulting sequence-to-gene-expression mapping revealed linear and structural RNA cis-regulatory elements that positively and negatively modulate the posttranscriptional fates of human transcripts. This combined experimental/computational strategy can be used to systematically characterize the vast landscape of posttranscriptional regulatory elements controlling physiological and pathological cellular state transitions.

Deciphering RNA regulatory elements in trypanosomatids: one piece at a time or genome-wide?

Morphological and metabolic changes in the life cycle of Trypanosoma brucei are accomplished by precise regulation of hundreds of genes. In the absence of transcriptional control, RNA-binding proteins (RBPs) shape the structure of gene regulatory maps in this organism, but our knowledge about their target RNAs, binding sites, and mechanisms of action is far from complete. Although recent technological advances have revolutionized the RBP-based approaches, the main framework for the RNA regulatory element (RRE)-based approaches has not changed over the last two decades in T. brucei. In this Opinion, after highlighting the current challenges in RRE inference, we explain some genome-wide solutions that can significantly boost our current understanding about gene regulatory networks in T. brucei.

Impact of human pathogenic micro-insertions and micro-deletions on post-transcriptional regulation

Small insertions/deletions (INDELs) of ≤21 bp comprise 18% of all recorded mutations causing human inherited disease and are evident in 24% of documented Mendelian diseases. INDELs affect gene function in multiple ways: for example, by introducing premature stop codons that either lead to the production of truncated proteins or affect transcriptional efficiency. However, the means by which they impact post-transcriptional regulation, including alternative splicing, have not been fully evaluated. In this study, we collate disease-causing INDELs from the Human Gene Mutation Database (HGMD) and neutral INDELs from the 1000 Genomes Project. The potential of these two types of INDELs to affect binding-site affinity of RNA-binding proteins (RBPs) was then evaluated. We identified several sequence features that can distinguish disease-causing INDELs from neutral INDELs. Moreover, we built a machine-learning predictor called PinPor (predicting pathogenic small insertions and deletions affecting post-transcriptional regulation, http://watson.compbio.iupui.edu/pinpor/) to ascertain which newly observed INDELs are likely to be pathogenic. Our results show that disease-causing INDELs are more likely to ablate RBP-binding sites and tend to affect more RBP-binding sites than neutral INDELs. Additionally, disease-causing INDELs give rise to greater deviations in binding affinity than neutral INDELs. We also demonstrated that disease-causing INDELs may be distinguished from neutral INDELs by several sequence features, such as their proximity to splice sites and their potential effects on RNA secondary structure. This predictor showed satisfactory performance in identifying numerous pathogenic INDELs, with a Matthews correlation coefficient (MCC) value of 0.51 and an accuracy of 0.75.

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.

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

Global identification of conserved post-transcriptional regulatory programs in trypanosomatids

While regulatory programs are extensively studied at the level of transcription, elements that are involved in regulation of post-transcriptional processes are largely unknown, and methods for systematic identification of these elements are in early stages. Here, using a novel computational framework, we have integrated sequence information with several functional genomics data sets to characterize conserved regulatory programs of trypanosomatids, a group of eukaryotes that almost entirely rely on post-transcriptional processes for regulation of mRNA abundance. This analysis revealed a complex network of linear and structural RNA elements that potentially govern mRNA abundance across different life stages and environmental conditions. Furthermore, we show that the conserved regulatory network that we have identified is responsive to chemical perturbation of several biological functions in trypanosomatids. We have further characterized one of the most abundant regulatory RNA elements that we discovered, an AU-rich element (ARE) that can be found in 3' untranslated region of many trypanosomatid genes. Using bioinformatics approaches as well as in vitro and in vivo experiments, we have identified three ELAV-like homologs, including the developmentally critical protein TbRBP6, which regulate abundance of a large number of trypanosomatid ARE-containing transcripts. Together, these studies lay out a roadmap for characterization of mechanisms that modulate development and metabolic pathways in trypanosomatids.

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.

Modeling the specificity of protein-DNA interactions

The specificity of protein-DNA interactions is most commonly modeled using position weight matrices (PWMs). First introduced in 1982, they have been adapted to many new types of data and many different approaches have been developed to determine the parameters of the PWM. New high-throughput technologies provide a large amount of data rapidly and offer an unprecedented opportunity to determine accurately the specificities of many transcription factors (TFs). But taking full advantage of the new data requires advanced algorithms that take into account the biophysical processes involved in generating the data. The new large datasets can also aid in determining when the PWM model is inadequate and must be extended to provide accurate predictions of binding sites. This article provides a general mathematical description of a PWM and how it is used to score potential binding sites, a brief history of the approaches that have been developed and the types of data that are used with an emphasis on algorithms that we have developed for analyzing high-throughput datasets from several new technologies. It also describes extensions that can be added when the simple PWM model is inadequate and further enhancements that may be necessary. It briefly describes some applications of PWMs in the discovery and modeling of in vivo regulatory networks.

Toward a genome-wide landscape of translational control

Genome-wide analysis of translational control has taken strides in recent years owing to the advent of high-throughput technologies, including DNA microarrays and deep sequencing. Global studies have unraveled a principal role, among posttranscriptional mechanisms, for mRNA translation in determining protein levels in the cell. The impact of translational control in dynamic regulation of the proteome under different conditions is increasingly appreciated. Here we review genome-wide studies that use high-throughput techniques and bioinformatics to assess the role of mRNA translation in the regulation of protein levels; we also discuss how genome-wide data on mRNA translation can be obtained, analyzed, and used to identify mechanisms of translational control.

From specific to global analysis of posttranscriptional regulation in eukaryotes: posttranscriptional regulatory networks

Regulation of gene expression occurs at several levels in eukaryotic organisms and is a highly controlled process. Although RNAs have been traditionally viewed as passive molecules in the pathway from transcription to translation, there is mounting evidence that their metabolism is controlled by a class of proteins called RNA-binding proteins (RBPs), as well as a number of small RNAs. In this review, I provide an overview of the recent developments in our understanding of the repertoire of RBPs across diverse model systems, and discuss the computational and experimental approaches currently available for the construction of posttranscriptional networks governed by them. I also present an overview of the different roles played by RBPs in the cellular context, based on their cis-regulatory modules identified in the literature and discuss how their interplay can result in the dynamic, spatial and tissue-specific expression maps of RNAs. I finally present the concept of posttranscriptional network of RBPs and their cognate RNA targets and discuss their cross-talk with other important posttranscriptional regulatory molecules such as microRNAs s, resulting in diverse functional network motifs. I argue that with rapid developments in the genome-wide elucidation of posttranscriptional networks it would not only be possible to gain a deeper understanding of regulation at a level that has been under-appreciated in the past, but would also allow us to use the newly developed high-throughput approaches to interrogate the prevalence of these phenomena in different states, and thereby study their relevance to physiology and disease across organisms.

Smaug1 mRNA-silencing foci respond to NMDA and modulate synapse formation

S-foci, the first reported mRNA-silencing foci specific to neurons, may control local mRNA translation in response to NMDA receptor stimulation and synaptic plasticity.

Mammalian Smaug1/Samd4A is a translational repressor. Here we show that Smaug1 forms mRNA-silencing foci located at postsynapses of hippocampal neurons. These structures, which we have named S-foci, are distinct from P-bodies, stress granules, or other neuronal RNA granules hitherto described, and are the first described mRNA-silencing foci specific to neurons. RNA binding was not required for aggregation, which indicates that S-foci formation is not a consequence of mRNA silencing. N-methyl-d-aspartic acid (NMDA) receptor stimulation provoked a rapid and reversible disassembly of S-foci, transiently releasing transcripts (the CaMKIIα mRNA among others) to allow their translation. Simultaneously, NMDA triggered global translational silencing, which suggests the specific activation of Smaug1-repressed transcripts. Smaug1 is expressed during synaptogenesis, and Smaug1 knockdown affected the number and size of synapses, and also provoked an impaired response to repetitive depolarizing stimuli, as indicated by a reduced induction of Arc/Arg3.1. Our results suggest that S-foci control local translation, specifically responding to NMDA receptor stimulation and affecting synaptic plasticity.

Transcript clearance during the maternal-to-zygotic transition

In all animals, a key event in the transition from maternal control of development to control by products of the zygotic genome is the elimination of a significant fraction of the mRNAs loaded into the egg by the mother. Clearance of these maternal mRNAs is accomplished by two activities: the first is maternally encoded while the second requires zygotic transcription. Recent advances include identification of RNA-binding proteins that function as specificity factors to direct the maternal degradation machinery to its target mRNAs; small RNAs-most notably microRNAs-that function as components of the zygotically encoded activity; signaling pathways that trigger production and/or activation of the clearance mechanism in early embryos; and mechanisms for spatial control of transcript clearance.

Identification of differential translation in genome wide studies

Regulation of gene expression through translational control is a fundamental mechanism implicated in many biological processes ranging from memory formation to innate immunity and whose dysregulation contributes to human diseases. Genome wide analyses of translational control strive to identify differential translation independent of cytosolic mRNA levels. For this reason, most studies measure genes' translation levels as log ratios (translation levels divided by corresponding cytosolic mRNA levels obtained in parallel). Counterintuitively, arising from a mathematical necessity, these log ratios tend to be highly correlated with the cytosolic mRNA levels. Accordingly, they do not effectively correct for cytosolic mRNA level and generate substantial numbers of biological false positives and false negatives. We show that analysis of partial variance, which produces estimates of translational activity that are independent of cytosolic mRNA levels, is a superior alternative. When combined with a variance shrinkage method for estimating error variance, analysis of partial variance has the additional benefit of having greater statistical power and identifying fewer genes as translationally regulated resulting merely from unrealistically low variance estimates rather than from large changes in translational activity. In contrast to log ratios, this formal analytical approach estimates translation effects in a statistically rigorous manner, eliminates the need for inefficient and error-prone heuristics, and produces results that agree with biological function. The method is applicable to datasets obtained from both the commonly used polysome microarray method and the sequencing-based ribosome profiling method.

Identification of RNA recognition elements in the Saccharomyces cerevisiae transcriptome

Post-transcriptional regulation of gene expression, including mRNA localization, translation and decay, is ubiquitous yet still largely unexplored. How is the post-transcriptional regulatory program of each mRNA encoded in its sequence? Hundreds of specific RNA-binding proteins (RBPs) appear to play roles in mediating the post-transcriptional regulatory program, akin to the roles of specific DNA-binding proteins in transcription. As a step toward decoding the regulatory programs encoded in each mRNA, we focused on specific mRNA–protein interactions. We computationally analyzed the sequences of Saccharomyces cerevisiae mRNAs bound in vivo by 29 specific RBPs, identifying eight novel candidate motifs and confirming or extending six earlier reported recognition elements. Biochemical selections for RNA sequences selectively recognized by 12 yeast RBPs yielded novel motifs bound by Pin4, Nsr1, Hrb1, Gbp2, Sgn1 and Mrn1, and recovered the known recognition elements for Puf3, She2, Vts1 and Whi3. Most of the RNA elements we uncovered were associated with coherent mRNA expression changes and were significantly conserved in related yeasts, supporting their functional importance and suggesting that the corresponding RNA–protein interactions are evolutionarily conserved.

RNAcontext: a new method for learning the sequence and structure binding preferences of RNA-binding proteins

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.

Predicting in vivo binding sites of RNA-binding proteins using mRNA secondary structure

While many RNA-binding proteins (RBPs) bind RNA in a sequence-specific manner, their sequence preferences alone do not distinguish known target RNAs from other potential targets that are coexpressed and contain the same sequence motifs. Recently, the mRNA targets of dozens of RNA-binding proteins have been identified, facilitating a systematic study of the features of target transcripts. Using these data, we demonstrate that calculating the predicted structural accessibility of a putative RBP binding site allows one to significantly improve the accuracy of predicting in vivo binding for the majority of sequence-specific RBPs. In our new in silico approach, accessibility is predicted based solely on the mRNA sequence without consideration of the locations of bound trans-factors; as such, our results suggest a greater than previously anticipated role for intrinsic mRNA secondary structure in determining RBP binding target preference. Target site accessibility aids in predicting target transcripts and the binding sites for RBPs with a range of RNA-binding domains and subcellular functions. Based on this work, we introduce a new motif-finding algorithm that identifies accessible sequence-specific RBP motifs from in vivo binding data.