Computational assessment of the cooperativity between RNA binding proteins and MicroRNAs in Transcript Decay

Systematic analysis of the target recognition and repression by the Pumilio proteins

RNA binding proteins orchestrate the post-transcriptional fate of RNA molecules, but the principles of their action remain poorly understood. Pumilio (PUM) proteins bind 3' UTRs of mRNAs and lead to mRNA decay. To comprehensively map the determinants of recognition of sequences by PUM proteins in cells and to study the binding outcomes, we developed a massively parallel RNA assay that profiled thousands of PUM-binding sites in cells undergoing various perturbations or RNA immunoprecipitation. By studying fragments from the NORAD long non-coding RNA, we find two features that antagonize repression by PUM proteins - G/C rich sequences, particularly those upstream of the PUM recognition element, and binding of FAM120A, which limits the repression elicited by PUM-binding sites. We also find that arrays of PUM sites separated by 8-12 bases offer particularly strong repression and use them to develop a particularly sensitive reporter for PUM repression. In contrast, PUM sites separated by shorter linkers, such as some of those found in NORAD, exhibit strong activity interdependence, likely mediated by competition between PUM binding and formation of strong secondary structures. Overall, our findings expand our understanding of the determinants of PUM protein activity in human cells.

A spatiotemporally resolved atlas of mRNA decay in the C. elegans embryo reveals differential regulation of mRNA stability across stages and cell types

During embryonic development, cells undergo dynamic changes in gene expression that are required for appropriate cell fate specification. Although both transcription and mRNA degradation contribute to gene expression dynamics, patterns of mRNA decay are less well understood. Here, we directly measure spatiotemporally resolved mRNA decay rates transcriptome-wide throughout C. elegans embryogenesis by transcription inhibition followed by bulk and single-cell RNA sequencing. This allows us to calculate mRNA half-lives within specific cell types and developmental stages, and identify differentially regulated mRNA decay throughout embryonic development. We identify transcript features that are correlated with mRNA stability and find that mRNA decay rates are associated with distinct peaks in gene expression over time. Moreover, we provide evidence that, on average, mRNA is more stable in the germline than in the soma and in later embryonic stages than in earlier stages. This work suggests that differential mRNA decay across cell states and time helps to shape developmental gene expression, and it provides a valuable resource for studies of mRNA turnover regulatory mechanisms.

A spatiotemporally resolved atlas of mRNA decay in the C. elegans embryo reveals differential regulation of mRNA stability across stages and cell types

During embryonic development, cells undergo dynamic changes in gene expression that are required for appropriate cell fate specification. Although both transcription and mRNA degradation contribute to gene expression dynamics, patterns of mRNA decay are less well-understood. Here we directly measured spatiotemporally resolved mRNA decay rates transcriptome-wide throughout C. elegans embryogenesis by transcription inhibition followed by bulk and single-cell RNA-sequencing. This allowed us to calculate mRNA half-lives within specific cell types and developmental stages and identify differentially regulated mRNA decay throughout embryonic development. We identified transcript features that are correlated with mRNA stability and found that mRNA decay rates are associated with distinct peaks in gene expression over time. Moreover, we provide evidence that, on average, mRNA is more stable in the germline compared to in the soma and in later embryonic stages compared to in earlier stages. This work suggests that differential mRNA decay across cell states and time helps to shape developmental gene expression, and it provides a valuable resource for studies of mRNA turnover regulatory mechanisms.

LION: an integrated R package for effective prediction of ncRNA-protein interaction

Understanding ncRNA-protein interaction is of critical importance to unveil ncRNAs' functions. Here, we propose an integrated package LION which comprises a new method for predicting ncRNA/lncRNA-protein interaction as well as a comprehensive strategy to meet the requirement of customisable prediction. Experimental results demonstrate that our method outperforms its competitors on multiple benchmark datasets. LION can also improve the performance of some widely used tools and build adaptable models for species- and tissue-specific prediction. We expect that LION will be a powerful and efficient tool for the prediction and analysis of ncRNA/lncRNA-protein interaction. The R Package LION is available on GitHub at https://github.com/HAN-Siyu/LION/.

Regulation of Parkinson's disease-associated genes by Pumilio proteins and microRNAs in SH-SY5Y neuronal cells

Parkinson's disease is the second most common age-related, neurodegenerative disease. A small collection of genes has been linked to Parkinson's disease including LRRK2, SAT1, and SNCA, the latter of which encodes the protein alpha-synuclein that aggregates in Lewy bodies as a hallmark of the disease. Overexpression of even wild-type versions of these genes can lead to pathogenesis, yet the regulatory mechanisms that control protein production of the genes are not fully understood. Pumilio proteins belong to the highly conserved PUF family of eukaryotic RNA-binding proteins that post-transcriptionally regulate gene expression through binding conserved motifs in the 3' untranslated region (UTR) of mRNA targets known as PUF Recognition Elements (PREs). The 3'UTRs of LRRK2, SNCA and SAT1 each contain multiple putative PREs. Knockdown (KD) of the two human Pumilio homologs (Pumilio 1 and Pumilio 2) in a neurodegenerative model cell line, SH-SY5Y, resulted in increased SNCA and LRRK2 mRNA, as well as alpha-synuclein levels, suggesting these genes are normally repressed by the Pumilio proteins. Some studies have indicated a relationship between Pumilio and microRNA activities on the same target, especially when their binding sites are close together. LRRK2, SNCA, and SAT1 each contain several putative microRNA-binding sites within the 3'UTR, some of which reside near PREs. Small RNA-seq and microRNA qPCR assays were performed in both wild type and Pumilio KD SH-SY5Y cells to analyze global and differential microRNA expression. One thousand four hundred and four microRNAs were detected across wild type and Pumilio KD cells. Twenty-one microRNAs were differentially expressed between treatments, six of which were previously established to be altered in Parkinson's disease patient samples or research models. Expression of ten miRs predicted to target LRRK2 and SNCA was verified by RT-qPCR. Collectively, our results demonstrate that Pumilios and microRNAs play a multi-faceted role in regulating Parkinson's disease-associated genes.

Modulation of miRISC-Mediated Gene Silencing in Eukaryotes

Gene expression is regulated at multiple levels in eukaryotic cells. Regulation at the post-transcriptional level is modulated by various trans-acting factors that bind to specific sequences in the messenger RNA (mRNA). The binding of different trans factors influences various aspects of the mRNA such as degradation rate, translation efficiency, splicing, localization, etc. MicroRNAs (miRNAs) are short endogenous ncRNAs that combine with the Argonaute to form the microRNA-induced silencing complex (miRISC), which uses base-pair complementation to silence the target transcript. RNA-binding proteins (RBPs) contribute to post-transcriptional control by influencing the mRNA stability and translation upon binding to cis-elements within the mRNA transcript. RBPs have been shown to impact gene expression through influencing the miRISC biogenesis, composition, or miRISC-mRNA target interaction. While there is clear evidence that those interactions between RBPs, miRNAs, miRISC and target mRNAs influence the efficiency of miRISC-mediated gene silencing, the exact mechanism for most of them remains unclear. This review summarizes our current knowledge on gene expression regulation through interactions of miRNAs and RBPs.

Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network

BACKGROUND

Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA-protein interactions (LPIs) is key to understanding lncRNA functions. Although some LPIs computational methods have been developed, the LPIs prediction problem remains challenging. How to integrate multimodal features from more perspectives and build deep learning architectures with better recognition performance have always been the focus of research on LPIs.

RESULTS

We present a novel multichannel capsule network framework to integrate multimodal features for LPI prediction, Capsule-LPI. Capsule-LPI integrates four groups of multimodal features, including sequence features, motif information, physicochemical properties and secondary structure features. Capsule-LPI is composed of four feature-learning subnetworks and one capsule subnetwork. Through comprehensive experimental comparisons and evaluations, we demonstrate that both multimodal features and the architecture of the multichannel capsule network can significantly improve the performance of LPI prediction. The experimental results show that Capsule-LPI performs better than the existing state-of-the-art tools. The precision of Capsule-LPI is 87.3%, which represents a 1.7% improvement. The F-value of Capsule-LPI is 92.2%, which represents a 1.4% improvement.

CONCLUSIONS

This study provides a novel and feasible LPI prediction tool based on the integration of multimodal features and a capsule network. A webserver ( http://csbg-jlu.site/lpc/predict ) is developed to be convenient for users.

Role of PUM RNA-Binding Proteins in Cancer

Simple Summary

PUM1 and PUM2 are RNA-binding Pumilio proteins controlling the accessibility of hundreds of mRNAs for translation in a variety of human tissues. As a result, PUMs exemplify one of the mechanisms safeguarding the cellular proteome. PUM expression is disturbed in cancer, resulting in dysregulation of their target mRNAs. These targets encode factors responsible for processes usually affected in cancer, such as proliferation, apoptosis, and the cell cycle. This review describes PUM1 and PUM2 ribonucleoprotein networks and highlights the mechanisms underlying the regulatory role of PUM proteins and, most importantly, the emerging impact of PUM dysregulation in cancer. It also emphasizes the importance of upcoming studies on PUM proteins in the context of cancer, as they may provide new therapeutic targets in the future.

Abstract

Until recently, post-transcriptional gene regulation (PTGR), in contrast to transcriptional regulation, was not extensively explored in cancer, even though it seems to be highly important. PUM proteins are well described in the PTGR of several organisms and contain the PUF RNA-binding domain that recognizes the UGUANAUA motif, located mostly in the 3′ untranslated region (3′UTR) of target mRNAs. Depending on the protein cofactors recruited by PUM proteins, target mRNAs are directed towards translation, repression, activation, degradation, or specific localization. Abnormal profiles of PUM expression have been shown in several types of cancer, in some of them being different for PUM1 and PUM2. This review summarizes the dysregulation of PUM1 and PUM2 expression in several cancer tissues. It also describes the regulatory mechanisms behind the activity of PUMs, including cooperation with microRNA and non-coding RNA machineries, as well as the alternative polyadenylation pathway. It also emphasizes the importance of future studies to gain a more complete picture of the role of PUM proteins in different types of cancer. Such studies may result in identification of novel targets for future cancer therapies.

Rox8 promotes microRNA-dependent yki messenger RNA decay

The Hippo pathway is an evolutionarily conserved regulator of organ growth and tumorigenesis. In Drosophila, oncogenic Ras^V12 cooperates with loss-of-cell polarity to promote Hippo pathway-dependent tumor growth. To identify additional factors that modulate this signaling, we performed a genetic screen utilizing the Drosophila Ras ^V12 /lgl ^-/- in vivo tumor model and identified Rox8, a RNA-binding protein (RBP), as a positive regulator of the Hippo pathway. We found that Rox8 overexpression suppresses whereas Rox8 depletion potentiates Hippo-dependent tissue overgrowth, accompanied by altered Yki protein level and target gene expression. Mechanistically, Rox8 directly binds to a target site located in the yki 3' UTR, recruits and stabilizes the targeting of miR-8-loaded RISC, which accelerates the decay of yki messenger RNA (mRNA). Moreover, TIAR, the human ortholog of Rox8, is able to promote the degradation of yki mRNA when introduced into Drosophila and destabilizes YAP mRNA in human cells. Thus, our study provides in vivo evidence that the Hippo pathway is posttranscriptionally regulated by the collaborative action of RBP and microRNA (miRNA), which may provide an approach for modulating Hippo pathway-mediated tumorigenesis.

Principles of mRNA control by human PUM proteins elucidated from multimodal experiments and integrative data analysis

The human PUF-family proteins, PUM1 and PUM2, posttranscriptionally regulate gene expression by binding to a PUM recognition element (PRE) in the 3'-UTR of target mRNAs. Hundreds of PUM1/2 targets have been identified from changes in steady-state RNA levels; however, prior studies could not differentiate between the contributions of changes in transcription and RNA decay rates. We applied metabolic labeling to measure changes in RNA turnover in response to depletion of PUM1/2, showing that human PUM proteins regulate expression almost exclusively by changing RNA stability. We also applied an in vitro selection workflow to precisely identify the binding preferences of PUM1 and PUM2. By integrating our results with prior knowledge, we developed a "rulebook" of key contextual features that differentiate functional versus nonfunctional PREs, allowing us to train machine learning models that accurately predict the functional regulation of RNA targets by the human PUM proteins.

Connections between 3' end processing and DNA damage response: Ten years later

Ten years ago we reviewed how the cellular DNA damage response (DDR) is controlled by changes in the functional and structural properties of nuclear proteins, resulting in a timely coordinated control of gene expression that allows DNA repair. Expression of genes that play a role in DDR is regulated not only at transcriptional level during mRNA biosynthesis but also by changing steady-state levels due to turnover of the transcripts. The 3' end processing machinery, which is important in the regulation of mRNA stability, is involved in these gene-specific responses to DNA damage. Here, we review the latest mechanistic connections described between 3' end processing and DDR, with a special emphasis on alternative polyadenylation, microRNA and RNA binding proteins-mediated deadenylation, and discuss the implications of deregulation of these steps in DDR and human disease. This article is categorized under: RNA Processing > 3' End Processing RNA-Based Catalysis > Miscellaneous RNA-Catalyzed Reactions RNA in Disease and Development > RNA in Disease.

Demonstration of protein cooperativity mediated by RNA structure using the human protein PUM2

Posttranslational gene regulation requires a complex network of RNA-protein interactions. Cooperativity, which tunes response sensitivities, originates from protein-protein interactions in many systems. For RNA-binding proteins, cooperativity can also be mediated through RNA structure. RNA structural cooperativity (RSC) arises when binding of one protein induces a redistribution of RNA conformational states that enhance access (positive cooperativity) or block access (negative cooperativity) to additional binding sites. As RSC does not require direct protein-protein interactions, it allows cooperativity to be tuned for individual RNAs, via alterations in sequence that alter structural stability. Given the potential importance of this mechanism of control and our desire to quantitatively dissect features that underlie physiological regulation, we developed a statistical mechanical framework for RSC and tested this model by performing equilibrium binding measurements of the human PUF family protein PUM2. Using 68 RNAs that contain two to five PUM2-binding sites and RNA structures of varying stabilities, we observed a range of structure-dependent cooperative behaviors. To test our ability to account for this cooperativity with known physical constants, we used PUM2 affinity and nearest-neighbor RNA secondary structure predictions. Our model gave qualitative agreement for our disparate set of 68 RNAs across two temperatures, but quantitative deviations arise from overestimation of RNA structural stability. Our results demonstrate cooperativity mediated by RNA structure and underscore the power of quantitative stepwise experimental evaluation of mechanisms and computational tools.

Ciphers and Executioners: How 3'-Untranslated Regions Determine the Fate of Messenger RNAs

The sequences and structures of 3'-untranslated regions (3'UTRs) of messenger RNAs govern their stability, localization, and expression. 3'UTR regulatory elements are recognized by a wide variety of trans-acting factors that include microRNAs (miRNAs), their associated machinery, and RNA-binding proteins (RBPs). In turn, these factors instigate common mechanistic strategies to execute the regulatory programs encoded by 3'UTRs. Here, we review classes of factors that recognize 3'UTR regulatory elements and the effector machineries they guide toward mRNAs to dictate their expression and fate. We outline illustrative examples of competitive, cooperative, and coordinated interplay such as mRNA localization and localized translation. We further review the recent advances in the study of mRNP granules and phase transition, and their possible significance for the functions of 3'UTRs. Finally, we highlight some of the most recent strategies aimed at deciphering the complexity of the regulatory codes of 3'UTRs, and identify some of the important remaining challenges.

Antagonistic and cooperative AGO2-PUM interactions in regulating mRNAs

Approximately 1500 RNA-binding proteins (RBPs) profoundly impact mammalian cellular function by controlling distinct sets of transcripts, often using sequence-specific binding to 3′ untranslated regions (UTRs) to regulate mRNA stability and translation. Aside from their individual effects, higher-order combinatorial interactions between RBPs on specific mRNAs have been proposed to underpin the regulatory network. To assess the extent of such co-regulatory control, we took a global experimental approach followed by targeted validation to examine interactions between two well-characterized and highly conserved RBPs, Argonaute2 (AGO2) and Pumilio (PUM1 and PUM2). Transcriptome-wide changes in AGO2-mRNA binding upon PUM knockdown were quantified by CLIP-seq, and the presence of PUM binding on the same 3′UTR corresponded with cooperative and antagonistic effects on AGO2 occupancy. In addition, PUM binding sites that overlap with AGO2 showed differential, weakened binding profiles upon abrogation of AGO2 association, indicative of cooperative interactions. In luciferase reporter validation of candidate 3′UTR sites where AGO2 and PUM colocalized, three sites were identified to host antagonistic interactions, where PUM counteracts miRNA-guided repression. Interestingly, the binding sites for the two proteins are too far for potential antagonism due to steric hindrance, suggesting an alternate mechanism. Our data experimentally confirms the combinatorial regulatory model and indicates that the mostly repressive PUM proteins can change their behavior in a context-dependent manner. Overall, the approach underscores the importance of further elucidation of complex interactions between RBPs and their transcriptome-wide extent.

PTRE-seq reveals mechanism and interactions of RNA binding proteins and miRNAs

RNA binding proteins (RBP) and microRNAs (miRNAs) often bind sequences in 3' untranslated regions (UTRs) of mRNAs, and regulate stability and translation efficiency. With the identification of numerous RBPs and miRNAs, there is an urgent need for new technologies to dissect the function of the cis-acting elements of RBPs and miRNAs. We describe post-transcriptional regulatory element sequencing (PTRE-seq), a massively parallel method for assaying the target sequences of miRNAs and RBPs. We use PTRE-seq to dissect sequence preferences and interactions between miRNAs and RBPs. The binding sites for these effector molecules influenced different aspects of the RNA lifecycle: RNA stability, translation efficiency, and translation initiation. In some cases, post-transcriptional control is modular, with different factors acting independently of each other, while in other cases factors show specific epistatic interactions. The throughput, flexibility, and reproducibility of PTRE-seq make it a valuable tool to study post-transcriptional regulation by 3'UTR elements.

Transcriptome-wide Identification and Validation of Interactions between the miRNA Machinery and HuR on mRNA Targets

The 3' untranslated region (UTR) of mRNAs is the primary regulatory region that mediates post-transcriptional control by microRNAs and RNA-binding proteins in the cytoplasm. Aside from individual sequence-specific binding and regulation, examples of interaction between these factors at particular 3' UTR sites have emerged. However, the whole picture of such higher-order regulatory modules across the transcriptome is lacking. Here, we investigate the interactions between HuR, a ubiquitous RNA-binding protein, and Ago2, a core effector of the miRNA pathway, at the transcriptome-wide level. Using HITS-CLIP, we map HuR and miRNA binding sites on human 3' UTRs and assess their co-occurrence. In addition, we demonstrate global effects of HuR knockdown on Ago2 occupancy, suggesting a co-regulatory relationship. Focusing on sites of Ago2-HuR overlap, 13 candidates were screened in luciferase reporter assays. Eleven sites showed miRNA-dependent repression, as confirmed in Dicer-null cells. To test for HuR's role in co-regulation, we measured the reporters in HuR KO cells. Three of the miRNA sites demonstrated altered activities, indicating that HuR has an effect on miRNA repression at those sites. Our study presents an efficient search and validation system for studying miRNA-HuR interactions, which expands our understanding of the combinatorial post-transcriptional control of gene expression at the 3' UTR.

Highly accessible AU-rich regions in 3' untranslated regions are hotspots for binding of regulatory factors

Post-transcriptional regulation is regarded as one of the major processes involved in the regulation of gene expression. It is mainly performed by RNA binding proteins and microRNAs, which target RNAs and typically affect their stability. Recent efforts from the scientific community have aimed at understanding post-transcriptional regulation at a global scale by using high-throughput sequencing techniques such as cross-linking and immunoprecipitation (CLIP), which facilitates identification of binding sites of these regulatory factors. However, the diversity in the experimental procedures and bioinformatics analyses has hindered the integration of multiple datasets and thus limited the development of an integrated view of post-transcriptional regulation. In this work, we have performed a comprehensive analysis of 107 CLIP datasets from 49 different RBPs in HEK293 cells to shed light on the complex interactions that govern post-transcriptional regulation. By developing a more stringent CLIP analysis pipeline we have discovered the existence of conserved regulatory AU-rich regions in the 3’UTRs where miRNAs and RBPs that regulate several processes such as polyadenylation or mRNA stability bind. Analogous to promoters, many factors have binding sites overlapping or in close proximity in these hotspots and hence the regulation of the mRNA may depend on their relative concentrations. This hypothesis is supported by RBP knockdown experiments that alter the relative concentration of RBPs in the cell. Upon AGO2 knockdown (KD), transcripts containing “free” target sites show increased expression levels compared to those containing target sites in hotspots, which suggests that target sites within hotspots are less available for miRNAs to bind. Interestingly, these hotspots appear enriched in genes with regulatory functions such as DNA binding and RNA binding. Taken together, our results suggest that hotspots are functional regulatory elements that define an extra layer of regulation of post-transcriptional regulatory networks.

All the cells in a given organism contain the same genome, yet their phenotype can be very diverse. The vast majority of this diversity arises from the differences in the expression of genes and proteins in them. One of the main mechanisms involved in controlling the protein and mRNA repertoire in cells is post-transcriptional regulation. The recent development of high-throughput sequencing techniques gives us now an unprecedented opportunity to investigate how post-transcriptional regulation works and which are the elements involved in defining the final set of mRNAs and proteins inside cells. In this work, we have performed a comprehensive computational analysis of several post-transcriptional regulators in a commonly used human cell line in order to understand which factors are involved in post-transcriptional regulation and how they coordinate their function. The results of our analysis show that this process is orchestrated around small regions in the mRNAs where many regulators bind and may compete with each other to regulate the mRNAs. The investigation and characterization of these regions gives us insight into the underlying combinatorial control that causes gene expression to differ across cell types and in diseases.

SimiRa: A tool to identify coregulation between microRNAs and RNA-binding proteins

microRNAs and microRNA-independent RNA-binding proteins are 2 classes of post-transcriptional regulators that have been shown to cooperate in gene-expression regulation. We compared the genome-wide target sets of microRNAs and RBPs identified by recent CLIP-Seq technologies, finding that RBPs have distinct target sets and favor gene interaction network hubs. To identify microRNAs and RBPs with a similar functional context, we developed simiRa, a tool that compares enriched functional categories such as pathways and GO terms. We applied simiRa to the known functional cooperation between Pumilio family proteins and miR-221/222 in the regulation of tumor supressor gene p27 and show that the cooperation is reflected by similar enriched categories but not by target genes. SimiRa also predicts possible cooperation of microRNAs and RBPs beyond direct interaction on the target mRNA for the nuclear RBP TAF15. To further facilitate research into cooperation of microRNAs and RBPs, we made simiRa available as a web tool that displays the functional neighborhood and similarity of microRNAs and RBPs: http://vsicb-simira.helmholtz-muenchen.de.

Modeling the combined effect of RNA-binding proteins and microRNAs in post-transcriptional regulation

Recent studies show that RNA-binding proteins (RBPs) and microRNAs (miRNAs) function in coordination with each other to control post-transcriptional regulation (PTR). Despite this, the majority of research to date has focused on the regulatory effect of individual RBPs or miRNAs. Here, we mapped both RBP and miRNA binding sites on human 3'UTRs and utilized this collection to better understand PTR. We show that the transcripts that lack competition for HuR binding are destabilized more after HuR depletion. We also confirm this finding for PUM1(2) by measuring genome-wide expression changes following the knockdown of PUM1(2) in HEK293 cells. Next, to find potential cooperative interactions, we identified the pairs of factors whose sites co-localize more often than expected by random chance. Upon examining these results for PUM1(2), we found that transcripts where the sites of PUM1(2) and its interacting miRNA form a stem-loop are more stabilized upon PUM1(2) depletion. Finally, using dinucleotide frequency and counts of regulatory sites as features in a regression model, we achieved an AU-ROC of 0.86 in predicting mRNA half-life in BEAS-2B cells. Altogether, our results suggest that future studies of PTR must consider the combined effects of RBPs and miRNAs, as well as their interactions.

RNA Binding Proteins in the miRNA Pathway

microRNAs (miRNAs) are short ~22 nucleotides (nt) ribonucleic acids which post-transcriptionally regulate gene expression. miRNAs are key regulators of all cellular processes, and the correct expression of miRNAs in an organism is crucial for proper development and cellular function. As a result, the miRNA biogenesis pathway is highly regulated. In this review, we outline the basic steps of miRNA biogenesis and miRNA mediated gene regulation focusing on the role of RNA binding proteins (RBPs). We also describe multiple mechanisms that regulate the canonical miRNA pathway, which depends on a wide range of RBPs. Moreover, we hypothesise that the interaction between miRNA regulation and RBPs is potentially more widespread based on the analysis of available high-throughput datasets.

Combinatorial Control of mRNA Fates by RNA-Binding Proteins and Non-Coding RNAs

Post-transcriptional control of gene expression is mediated by RNA-binding proteins (RBPs) and small non-coding RNAs (e.g., microRNAs) that bind to distinct elements in their mRNA targets. Here, we review recent examples describing the synergistic and/or antagonistic effects mediated by RBPs and miRNAs to determine the localisation, stability and translation of mRNAs in mammalian cells. From these studies, it is becoming increasingly apparent that dynamic rearrangements of RNA-protein complexes could have profound implications in human cancer, in synaptic plasticity, and in cellular differentiation.

Transcriptional analysis of phloem-associated cells of potato

Background

Numerous signal molecules, including proteins and mRNAs, are transported through the architecture of plants via the vascular system. As the connection between leaves and other organs, the petiole and stem are especially important in their transport function, which is carried out by the phloem and xylem, especially by the sieve elements in the phloem system. The phloem is an important conduit for transporting photosynthate and signal molecules like metabolites, proteins, small RNAs, and full-length mRNAs. Phloem sap has been used as an unadulterated source to profile phloem proteins and RNAs, but unfortunately, pure phloem sap cannot be obtained in most plant species.

Results

Here we make use of laser capture microdissection (LCM) and RNA-seq for an in-depth transcriptional profile of phloem-associated cells of both petioles and stems of potato. To expedite our analysis, we have taken advantage of the potato genome that has recently been fully sequenced and annotated. Out of the 27 k transcripts assembled that we identified, approximately 15 k were present in phloem-associated cells of petiole and stem with greater than ten reads. Among these genes, roughly 10 k are affected by photoperiod. Several RNAs from this day length-regulated group are also abundant in phloem cells of petioles and encode for proteins involved in signaling or transcriptional control. Approximately 22 % of the transcripts in phloem cells contained at least one binding motif for Pumilio, Nova, or polypyrimidine tract-binding proteins in their downstream sequences. Highlighting the predominance of binding processes identified in the gene ontology analysis of active genes from phloem cells, 78 % of the 464 RNA-binding proteins present in the potato genome were detected in our phloem transcriptome.

Conclusions

As a reasonable alternative when phloem sap collection is not possible, LCM can be used to isolate RNA from specific cell types, and along with RNA-seq, provides practical access to expression profiles of phloem tissue. The combination of these techniques provides a useful approach to the study of phloem and a comprehensive picture of the mechanisms associated with long-distance signaling. The data presented here provide valuable insights into potentially novel phloem-mobile mRNAs and phloem-associated RNA-binding proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1844-2) contains supplementary material, which is available to authorized users.

Inference of transcriptional regulation in cancers

Despite the rapid accumulation of tumor-profiling data and transcription factor (TF) ChIP-seq profiles, efforts integrating TF binding with the tumor-profiling data to understand how TFs regulate tumor gene expression are still limited. To systematically search for cancer-associated TFs, we comprehensively integrated 686 ENCODE ChIP-seq profiles representing 150 TFs with 7484 TCGA tumor data in 18 cancer types. For efficient and accurate inference on gene regulatory rules across a large number and variety of datasets, we developed an algorithm, RABIT (regression analysis with background integration). In each tumor sample, RABIT tests whether the TF target genes from ChIP-seq show strong differential regulation after controlling for background effect from copy number alteration and DNA methylation. When multiple ChIP-seq profiles are available for a TF, RABIT prioritizes the most relevant ChIP-seq profile in each tumor. In each cancer type, RABIT further tests whether the TF expression and somatic mutation variations are correlated with differential expression patterns of its target genes across tumors. Our predicted TF impact on tumor gene expression is highly consistent with the knowledge from cancer-related gene databases and reveals many previously unidentified aspects of transcriptional regulation in tumor progression. We also applied RABIT on RNA-binding protein motifs and found that some alternative splicing factors could affect tumor-specific gene expression by binding to target gene 3'UTR regions. Thus, RABIT (rabit.dfci.harvard.edu) is a general platform for predicting the oncogenic role of gene expression regulators.

MicroRNAs in inflammatory bowel diseases: paradoxes and possibilities

MicroRNAs (miRNAs) are single-stranded RNA molecules, which influence the translation of messenger RNA and hence protein synthesis. The altered expression of miRNAs in disease states in cancer and autoimmune diseases including inflammatory bowel disease is providing new insights into disease pathogenesis. This understanding is leading to consideration of the utility of miRNAs in diagnostics, prognostics, and therapeutics in inflammatory bowel disease. A literature search was conducted using the MEDLINE/PubMed databases using search terms inflammatory bowel disease, miRNA, treatment, and biomarkers.

Scan for Motifs: a webserver for the analysis of post-transcriptional regulatory elements in the 3' untranslated regions (3' UTRs) of mRNAs

Background

Gene expression in vertebrate cells may be controlled post-transcriptionally through regulatory elements in mRNAs. These are usually located in the untranslated regions (UTRs) of mRNA sequences, particularly the 3′UTRs.

Results

Scan for Motifs (SFM) simplifies the process of identifying a wide range of regulatory elements on alignments of vertebrate 3′UTRs. SFM includes identification of both RNA Binding Protein (RBP) sites and targets of miRNAs. In addition to searching pre-computed alignments, the tool provides users the flexibility to search their own sequences or alignments. The regulatory elements may be filtered by expected value cutoffs and are cross-referenced back to their respective sources and literature. The output is an interactive graphical representation, highlighting potential regulatory elements and overlaps between them. The output also provides simple statistics and links to related resources for complementary analyses. The overall process is intuitive and fast. As SFM is a free web-application, the user does not need to install any software or databases.

Conclusions

Visualisation of the binding sites of different classes of effectors that bind to 3′UTRs will facilitate the study of regulatory elements in 3′ UTRs.

PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps

Background

The progress in mapping RNA-protein and RNA-RNA interactions at the transcriptome-wide level paves the way to decipher possible combinatorial patterns embedded in post-transcriptional regulation of gene expression.

Results

Here we propose an innovative computational tool to extract clusters of mRNA trans-acting co-regulators (RNA binding proteins and non-coding RNAs) from pairwise interaction annotations. In addition the tool allows to analyze the binding site similarity of co-regulators belonging to the same cluster, given their positional binding information. The tool has been tested on experimental collections of human and yeast interactions, identifying modules that coordinate functionally related messages.

Conclusions

This tool is an original attempt to uncover combinatorial patterns using all the post-transcriptional interaction data available so far. PTRcombiner is available at http://disi.unitn.it/~passerini/software/PTRcombiner/.

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