ATtRACT-a database of RNA-binding proteins and associated motifs

Subcellular Localization of uc.8+ as a Prognostic Biomarker in Bladder Cancer Tissue

Simple Summary

DNA regions having high sequence similarity among human, rat and mouse genomes are defined as Ultraconserved Regions. Non-coding RNA transcripts originating by these regions may play relevant roles in the onset and progression of multiple cancer types. We recently found that ultra-conserved-transcript-8+ (uc.8+) levels correlate with the grading and staging of bladder cancer. The aim of this study is to systematically evaluate the expression of ultra-conserved-transcript-8+ (uc.8+) in biopsies and assess its intracellular localization. Furthermore, we aimed to correlate uc.8+ levels with clinical parameters and patient survival. Our analysis indicates that uc.8+ can localize both in the cytoplasm and nucleus of bladder cells at early stages of tumorigenesis, while in tumors at advanced stages, uc.8+ has a prevalent cytoplasmic localization. These data provide relevant information about uc.8+ localization as a hallmark of tumor stage. Finally, using advanced computer-based techniques, we predicted the binding of uc.8+ to RNA-binding proteins. Our study overall suggests that uc.8+ localization can be used as a prognostic biomarker for bladder cancer.

Abstract

Non-coding RNA transcripts originating from Ultraconserved Regions (UCRs) have tissue-specific expression and play relevant roles in the pathophysiology of multiple cancer types. Among them, we recently identified and characterized the ultra-conserved-transcript-8+ (uc.8+), whose levels correlate with grading and staging of bladder cancer. Here, to validate uc.8+ as a potential biomarker in bladder cancer, we assessed its expression and subcellular localization by using tissue microarray on 73 human bladder cancer specimens. We quantified uc.8+ by in-situ hybridization and correlated its expression levels with clinical characteristics and patient survival. The analysis of subcellular localization indicated the simultaneous presence of uc.8+ in the cytoplasm and nucleus of cells from the Low-Grade group, whereas a prevalent cytoplasmic localization was observed in samples from the High-Grade group, supporting the hypothesis of uc.8+ nuclear-to-cytoplasmic translocation in most malignant tumor forms. Moreover, analysis of uc.8+ expression and subcellular localization in tumor-surrounding stroma revealed a marked down-regulation of uc.8+ levels compared to the paired (adjacent) tumor region. Finally, deep machine-learning approaches identified nucleotide sequences associated with uc.8+ localization in nucleus and/or cytoplasm, allowing to predict possible RNA binding proteins associated with uc.8+, recognizing also sequences involved in mRNA cytoplasm-translocation. Our model suggests uc.8+ subcellular localization as a potential prognostic biomarker for bladder cancer.

The GAUGAA Motif Is Responsible for the Binding between circSMARCA5 and SRSF1 and Related Downstream Effects on Glioblastoma Multiforme Cell Migration and Angiogenic Potential

Circular RNAs (circRNAs) are a large class of RNAs with regulatory functions within cells. We recently showed that circSMARCA5 is a tumor suppressor in glioblastoma multiforme (GBM) and acts as a decoy for Serine and Arginine Rich Splicing Factor 1 (SRSF1) through six predicted binding sites (BSs). Here we characterized RNA motifs functionally involved in the interaction between circSMARCA5 and SRSF1. Three different circSMARCA5 molecules (Mut1, Mut2, Mut3), each mutated in two predicted SRSF1 BSs at once, were obtained through PCR-based replacement of wild-type (WT) BS sequences and cloned in three independent pcDNA3 vectors. Mut1 significantly decreased its capability to interact with SRSF1 as compared to WT, based on the RNA immunoprecipitation assay. In silico analysis through the “Find Individual Motif Occurrences” (FIMO) algorithm showed GAUGAA as an experimentally validated SRSF1 binding motif significantly overrepresented within both predicted SRSF1 BSs mutated in Mut1 (q-value = 0.0011). U87MG and CAS-1, transfected with Mut1, significantly increased their migration with respect to controls transfected with WT, as revealed by the cell exclusion zone assay. Immortalized human brain microvascular endothelial cells (IM-HBMEC) exposed to conditioned medium (CM) harvested from U87MG and CAS-1 transfected with Mut1 significantly sprouted more than those treated with CM harvested from U87MG and CAS-1 transfected with WT, as shown by the tube formation assay. qRT-PCR showed that the intracellular pro- to anti-angiogenic Vascular Endothelial Growth Factor A (VEGFA) mRNA isoform ratio and the amount of total VEGFA mRNA secreted in CM significantly increased in Mut1-transfected CAS-1 as compared to controls transfected with WT. Our data suggest that GAUGAA is the RNA motif responsible for the interaction between circSMARCA5 and SRSF1 as well as for the circSMARCA5-mediated control of GBM cell migration and angiogenic potential.

Improving CLIP-seq data analysis by incorporating transcript information

BACKGROUND

Current peak callers for identifying RNA-binding protein (RBP) binding sites from CLIP-seq data take into account genomic read profiles, but they ignore the underlying transcript information, that is information regarding splicing events. So far, there are no studies available that closer observe this issue.

RESULTS

Here we show that current peak callers are susceptible to false peak calling near exon borders. We quantify its extent in publicly available datasets, which turns out to be substantial. By providing a tool called CLIPcontext for automatic transcript and genomic context sequence extraction, we further demonstrate that context choice affects the performances of RBP binding site prediction tools. Moreover, we show that known motifs of exon-binding RBPs are often enriched in transcript context sites, which should enable the recovery of more authentic binding sites. Finally, we discuss possible strategies on how to integrate transcript information into future workflows.

CONCLUSIONS

Our results demonstrate the importance of incorporating transcript information in CLIP-seq data analysis. Taking advantage of the underlying transcript information should therefore become an integral part of future peak calling and downstream analysis tools.

Intronic tRNAs of mitochondrial origin regulate constitutive and alternative splicing

BACKGROUND

The presence of nuclear mitochondrial DNA (numtDNA) has been reported within several nuclear genomes. Next to mitochondrial protein-coding genes, numtDNA sequences also encode for mitochondrial tRNA genes. However, the biological roles of numtDNA remain elusive.

RESULTS

Employing in silico analysis, we identify 281 mitochondrial tRNA homologs in the human genome, which we term nimtRNAs (nuclear intronic mitochondrial-derived tRNAs), being contained within introns of 76 nuclear host genes. Despite base changes in nimtRNAs when compared to their mtRNA homologs, a canonical tRNA cloverleaf structure is maintained. To address potential functions of intronic nimtRNAs, we insert them into introns of constitutive and alternative splicing reporters and demonstrate that nimtRNAs promote pre-mRNA splicing, dependent on the number and positioning of nimtRNA genes and splice site recognition efficiency. A mutational analysis reveals that the nimtRNA cloverleaf structure is required for the observed splicing increase. Utilizing a CRISPR/Cas9 approach, we show that a partial deletion of a single endogenous nimtRNALys within intron 28 of the PPFIBP1 gene decreases inclusion of the downstream-located exon 29 of the PPFIBP1 mRNA. By employing a pull-down approach followed by mass spectrometry, a 3'-splice site-associated protein network is identified, including KHDRBS1, which we show directly interacts with nimtRNATyr by an electrophoretic mobility shift assay.

CONCLUSIONS

We propose that nimtRNAs, along with associated protein factors, can act as a novel class of intronic splicing regulatory elements in the human genome by participating in the regulation of splicing.

An emerging role of chromatin-interacting RNA-binding proteins in transcription regulation

Transcription factors (TFs) are well-established key factors orchestrating gene transcription, and RNA-binding proteins (RBPs) are mainly thought to participate in post-transcriptional control of gene. In fact, these two steps are functionally coupled, offering a possibility for reciprocal communications between transcription and regulatory RNAs and RBPs. Recently, a series of exploratory studies, utilizing functional genomic strategies, have revealed that RBPs are prevalently involved in transcription control genome-wide through their interactions with chromatin. Here, we present a refined census of RBPs to grope for such an emerging role and discuss the global view of RBP-chromatin interactions and their functional diversities in transcription regulation.

SMDB: pivotal somatic sequence alterations reprogramming regulatory cascades

Binding motifs for transcription factors, RNA-binding proteins, microRNAs (miRNAs), etc. are vital for proper gene transcription and translation regulation. Sequence alteration mechanisms including single nucleotide mutations, insertion, deletion, RNA editing and single nucleotide polymorphism can lead to gains and losses of binding motifs; such consequentially emerged or vanished binding motifs are termed 'somatic motifs' by us. Somatic motifs have been studied sporadically but have never been curated into a comprehensive resource. By analyzing various types of sequence altering data from large consortiums, we successfully identified millions of somatic motifs, including those for important transcription factors, RNA-binding proteins, miRNA seeds and miRNA-mRNA 3'-UTR target motifs. While a few of these somatic motifs have been well studied, our results contain many novel somatic motifs that occur at high frequency and are thus likely to cause important biological repercussions. Genes targeted by these altered motifs are excellent candidates for further mechanism studies. Here, we present the first database that hosts millions of somatic motifs ascribed to a variety of sequence alteration mechanisms.

Galaxy CLIP-Explorer: a web server for CLIP-Seq data analysis

BACKGROUND

Post-transcriptional regulation via RNA-binding proteins plays a fundamental role in every organism, but the regulatory mechanisms lack important understanding. Nevertheless, they can be elucidated by cross-linking immunoprecipitation in combination with high-throughput sequencing (CLIP-Seq). CLIP-Seq answers questions about the functional role of an RNA-binding protein and its targets by determining binding sites on a nucleotide level and associated sequence and structural binding patterns. In recent years the amount of CLIP-Seq data skyrocketed, urging the need for an automatic data analysis that can deal with different experimental set-ups. However, noncanonical data, new protocols, and a huge variety of tools, especially for peak calling, made it difficult to define a standard.

FINDINGS

CLIP-Explorer is a flexible and reproducible data analysis pipeline for iCLIP data that supports for the first time eCLIP, FLASH, and uvCLAP data. Individual steps like peak calling can be changed to adapt to different experimental settings. We validate CLIP-Explorer on eCLIP data, finding similar or nearly identical motifs for various proteins in comparison with other databases. In addition, we detect new sequence motifs for PTBP1 and U2AF2. Finally, we optimize the peak calling with 3 different peak callers on RBFOX2 data, discuss the difficulty of the peak-calling step, and give advice for different experimental set-ups.

CONCLUSION

CLIP-Explorer finally fills the demand for a flexible CLIP-Seq data analysis pipeline that is applicable to the up-to-date CLIP protocols. The article further shows the limitations of current peak-calling algorithms and the importance of a robust peak detection.

A circular RNA generated from an intron of the insulin gene controls insulin secretion

Fine-tuning of insulin release from pancreatic β-cells is essential to maintain blood glucose homeostasis. Here, we report that insulin secretion is regulated by a circular RNA containing the lariat sequence of the second intron of the insulin gene. Silencing of this intronic circular RNA in pancreatic islets leads to a decrease in the expression of key components of the secretory machinery of β-cells, resulting in impaired glucose- or KCl-induced insulin release and calcium signaling. The effect of the circular RNA is exerted at the transcriptional level and involves an interaction with the RNA-binding protein TAR DNA-binding protein 43 kDa (TDP-43). The level of this circularized intron is reduced in the islets of rodent diabetes models and of type 2 diabetic patients, possibly explaining their impaired secretory capacity. The study of this and other circular RNAs helps understanding β-cell dysfunction under diabetes conditions, and the etiology of this common metabolic disorder.

A lead candidate functional single nucleotide polymorphism within the WARS2 gene associated with waist-hip-ratio does not alter RNA stability

We have prioritised a single nucleotide polymorphism (SNP) rs2645294 as one candidate functional SNP in the TBX15-WARS2 waist-hip-ratio locus using posterior probability analysis. This SNP is located in the 3' untranslated region of the WARS2 (tryptophanyl tRNA synthetase 2, mitochondrial) gene with which it has an expression quantitative trait in subcutaneous white adipose tissue. We show that transcripts of the WARS2 gene in a human white adipose cell line, heterozygous for the rs2645294 SNP, showed allelic imbalance. We tested whether the rs2645294 SNP altered WARS2 RNA stability using three different methods: actinomycin-D inhibition and RNA decay, mature and nascent RNA analysis and luciferase reporter assays. We found no evidence of a difference in RNA stability between the rs2645294 alleles indicating that the allelic expression imbalance was likely due to transcriptional regulation.

New RNA Structural Elements Identified in the Coding Region of the Coxsackie B3 Virus Genome

Here we present a set of new structural elements formed within the open reading frame of the virus, which are highly probable, evolutionarily conserved and may interact with host proteins. This work focused on the coding regions of the CVB3 genome (particularly the V4-, V1-, 2C-, and 3D-coding regions), which, with the exception of the cis-acting replication element (CRE), have not yet been subjected to experimental analysis of their structures. The SHAPE technique, chemical modification with DMS and RNA cleavage with Pb²⁺, were performed in order to characterize the RNA structure. The experimental results were used to improve the computer prediction of the structural models, whereas a phylogenetic analysis was performed to check universality of the newly identified structural elements for twenty CVB3 genomes and 11 other enteroviruses. Some of the RNA motifs turned out to be conserved among different enteroviruses. We also observed that the 3'-terminal region of the genome tends to dimerize in a magnesium concentration-dependent manner. RNA affinity chromatography was used to confirm RNA-protein interactions hypothesized by database searches, leading to the discovery of several interactions, which may be important for virus propagation.

A Survey of Regulatory Interactions Among RNA Binding Proteins and MicroRNAs in Cancer

Recent advances in genomics and proteomics generated a large amount of trans regulatory data such as those mediated by RNA binding proteins (RBPs) and microRNAs. Since many trans regulators target 3′ UTR of mRNA transcripts, it is likely that there would be interactions, i.e., competitive or cooperative effect, among these trans factors. We compiled the available RBP and microRNA binding sites, mapped them to the mRNA transcripts, and correlated the binding data with mRNA expression data generated by The Cancer Genome Atlas (TCGA). We separated pairs of RBPs and microRNAs into three scenarios: those that have overlapping target sites on the same mRNA transcript (overlapping), those that have target sites on the same mRNA transcript but non-overlapping (neighboring), and those that do not target the same mRNA transcript (independent). Through a regression analysis on expression profiles, we indeed observed interaction effect between RBPs and microRNAs in the majority of the cancer expression data sets. We further discussed implication of such widespread interactions in the context of cancer and diseases.

Translatome and Transcriptome Profiling of Hypoxic-Induced Rat Cardiomyocytes

Adult cardiac hypoxia as a crucial pathogenesis factor can induce detrimental effects on cardiac injury and dysfunction. The global transcriptome and translatome reflecting the cellular response to hypoxia have not yet been extensively studied in myocardium. In this study, we conducted RNA sequencing (RNA-seq) and ribosome profiling technique (polyribo-seq) in rat heart tissues and H9C2 cells exposed to different periods of hypoxia stress in vivo and in vitro. The temporal gene-expression profiling displayed the distinction of transcriptome and translatome, which were mainly concentrated in cell apoptosis, autophagy, DNA repair, angiogenesis, vascular process, and cardiac cell proliferation and differentiation. A large number of genes such as GNAI3, SEPT4, FANCL, BNIP3, TBX3, ESR2, PTGS2, KLF4, and ADRB2, whose transcript and translation levels are closely correlated, were identified to own a common RNA motif “5′-GAAGCUGCC-3′” in 5′ UTR. NCBP3 was further determined to recognize this RNA motif and facilitate translational process in myocardium under hypoxia stress. Taken together, our data show the close connection between alterations of transcriptome and translatome after hypoxia exposure, emphasizing the significance of translational regulation in related studies. The profiled molecular responses in current study may be valuable resources for advanced understanding of the mechanisms underlying hypoxia-induced effect on heart diseases.

Role of SARS-CoV-2 in Altering the RNA-Binding Protein and miRNA-Directed Post-Transcriptional Regulatory Networks in Humans

The outbreak of a novel coronavirus SARS-CoV-2 responsible for the COVID-19 pandemic has caused a worldwide public health emergency. Due to the constantly evolving nature of the coronaviruses, SARS-CoV-2-mediated alterations on post-transcriptional gene regulations across human tissues remain elusive. In this study, we analyzed publicly available genomic datasets to systematically dissect the crosstalk and dysregulation of the human post-transcriptional regulatory networks governed by RNA-binding proteins (RBPs) and micro-RNAs (miRs) due to SARS-CoV-2 infection. We uncovered that 13 out of 29 SARS-CoV-2-encoded proteins directly interacted with 51 human RBPs, of which the majority of them were abundantly expressed in gonadal tissues and immune cells. We further performed a functional analysis of differentially expressed genes in mock-treated versus SARS-CoV-2-infected lung cells that revealed enrichment for the immune response, cytokine-mediated signaling, and metabolism-associated genes. This study also characterized the alternative splicing events in SARS-CoV-2-infected cells compared to the control, demonstrating that skipped exons and mutually exclusive exons were the most abundant events that potentially contributed to differential outcomes in response to the viral infection. A motif enrichment analysis on the RNA genomic sequence of SARS-CoV-2 clearly revealed the enrichment for RBPs such as SRSFs, PCBPs, ELAVs, and HNRNPs, suggesting the sponging of RBPs by the SARS-CoV-2 genome. A similar analysis to study the interactions of miRs with SARS-CoV-2 revealed functionally important miRs that were highly expressed in immune cells, suggesting that these interactions may contribute to the progression of the viral infection and modulate the host immune response across other human tissues. Given the need to understand the interactions of SARS-CoV-2 with key post-transcriptional regulators in the human genome, this study provided a systematic computational analysis to dissect the role of dysregulated post-transcriptional regulatory networks controlled by RBPs and miRs across tissue types during a SARS-CoV-2 infection.

Robust partitioning of microRNA targets from downstream regulatory changes

The biological impact of microRNAs (miRNAs) is determined by their targets, and robustly identifying direct miRNA targets remains challenging. Existing methods suffer from high false-positive rates and are unable to effectively differentiate direct miRNA targets from downstream regulatory changes. Here, we present an experimental and computational framework to deconvolute post-transcriptional and transcriptional changes using a combination of RNA-seq and PRO-seq. This novel approach allows us to systematically profile the regulatory impact of a miRNA. We refer to this approach as CARP: Combined Analysis of RNA-seq and PRO-seq. We apply CARP to multiple miRNAs and show that it robustly distinguishes direct targets from downstream changes, while greatly reducing false positives. We validate our approach using Argonaute eCLIP-seq and ribosome profiling, demonstrating that CARP defines a comprehensive repertoire of targets. Using this approach, we identify miRNA-specific activity of target sites within the open reading frame. Additionally, we show that CARP facilitates the dissection of complex changes in gene regulatory networks triggered by miRNAs and identification of transcription factors that mediate downstream regulatory changes. Given the robustness of the approach, CARP would be particularly suitable for dissecting miRNA regulatory networks in vivo.

Role of SARS-CoV-2 in altering the RNA binding protein and miRNA directed post-transcriptional regulatory networks in humans

The outbreak of a novel coronavirus SARS-CoV-2 responsible for COVID-19 pandemic has caused worldwide public health emergency. Due to the constantly evolving nature of the coronaviruses, SARS-CoV-2 mediated alteration on post-transcriptional gene regulation across human tissues remains elusive. In this study, we analyze publicly available genomic datasets to systematically dissect the crosstalk and dysregulation of human post-transcriptional regulatory networks governed by RNA binding proteins (RBPs) and micro-RNAs (miRs), due to SARS-CoV-2 infection. We uncovered that 13 out of 29 SARS-CoV-2 encoded proteins directly interact with 51 human RBPs of which majority of them were abundantly expressed in gonadal tissues and immune cells. We further performed a functional analysis of differentially expressed genes in mock-treated versus SARS-CoV-2 infected lung cells that revealed enrichment for immune response, cytokine-mediated signaling, and metabolism associated genes. This study also characterized the alternative splicing events in SARS-CoV-2 infected cells compared to control demonstrating that skipped exons and mutually exclusive exons were the most abundant events that potentially contributed to differential outcomes in response to viral infection. Motif enrichment analysis on the RNA genomic sequence of SARS-CoV-2 clearly revealed the enrichment for RBPs such as SRSFs, PCBPs, ELAVs, and HNRNPs suggesting the sponging of RBPs by SARS-CoV-2 genome. A similar analysis to study the interactions of miRs with SARS-CoV-2 revealed functionally important miRs that were highly expressed in immune cells, suggesting that these interactions may contribute to the progression of the viral infection and modulate host immune response across other human tissues. Given the need to understand the interactions of SARS-CoV-2 with key post-transcriptional regulators in the human genome, this study provides a systematic computational analysis to dissect the role of dysregulated post-transcriptional regulatory networks controlled by RBPs and miRs, across tissues types during SARS-CoV-2 infection.

Long non-coding RNAs and transposable elements: A functional relationship

Long non-coding RNAs (lncRNAs) have become increasingly important in the past decade. They are known to regulate gene expression and to interact with chromatin, proteins and other coding and non-coding RNAs. The study of lncRNAs has been challenging due to their low expression and the lack of tools developed to adapt to their particular features. Studies on lncRNAs performed to date have largely focused on cellular functions, whereas details on the mechanism of action has only been thoroughly investigated for a small number of lncRNAs. Nevertheless, some studies have highlighted the potential of these transcripts to contain functional domains, following the same accepted trend as proteins. Interestingly, many of these identified "domains" are attributed to functional units derived from transposable elements. Here, we review several types of functions of lncRNAs and relate these functions to lncRNA-embedded transposable elements.

LncAS2Cancer: a comprehensive database for alternative splicing of lncRNAs across human cancers

Accumulating studies demonstrated that the roles of lncRNAs for tumorigenesis were isoform-dependent and their aberrant splicing patterns in cancers contributed to function specificity. However, there is no existing database focusing on cancer-related alternative splicing of lncRNAs. Here, we developed a comprehensive database called LncAS2Cancer, which collected 5335 bulk RNA sequencing and 1826 single-cell RNA sequencing samples, covering over 30 cancer types. By applying six state-of-the-art splicing algorithms, 50 859 alternative splicing events for 8 splicing types were identified and deposited in the database. In addition, the database contained the following information: (i) splicing patterns of lncRNAs under seven different conditions, such as gene interference, which facilitated to infer potential regulators; (ii) annotation information derived from eight sources and manual curation, to understand the functional impact of affected sequences; (iii) survival analysis to explore potential biomarkers; as well as (iv) a suite of tools to browse, search, visualize and download interesting information. LncAS2Cancer could not only confirm the known cancer-associated lncRNA isoforms but also indicate novel ones. Using the data deposited in LncAS2Cancer, we compared gene model and transcript overlap between lncRNAs and protein-coding genes and discusses how these factors, along with sequencing depth, affected the interpretation of splicing signals. Based on recurrent signals and potential confounders, we proposed a reliable score to prioritize splicing events for further elucidation. Together, with the broad collection of lncRNA splicing patterns and annotation, LncAS2Cancer will provide important new insights into the diverse functional roles of lncRNA isoforms in human cancers. LncAS2Cancer is freely available at https://lncrna2as.cd120.com/.

Noncoding RNAs in Cardiovascular Disease: Current Knowledge, Tools and Technologies for Investigation, and Future Directions: A Scientific Statement From the American Heart Association

BACKGROUND

The discovery that much of the non-protein-coding genome is transcribed and plays a diverse functional role in fundamental cellular processes has led to an explosion in the development of tools and technologies to investigate the role of these noncoding RNAs in cardiovascular health. Furthermore, identifying noncoding RNAs for targeted therapeutics to treat cardiovascular disease is an emerging area of research. The purpose of this statement is to review existing literature, offer guidance on tools and technologies currently available to study noncoding RNAs, and identify areas of unmet need.

METHODS

The writing group used systematic literature reviews (including MEDLINE, Web of Science through 2018), expert opinion/statements, analyses of databases and computational tools/algorithms, and review of current clinical trials to provide a broad consensus on the current state of the art in noncoding RNA in cardiovascular disease.

RESULTS

Significant progress has been made since the initial studies focusing on the role of miRNAs (microRNAs) in cardiovascular development and disease. Notably, recent progress on understanding the role of novel types of noncoding small RNAs such as snoRNAs (small nucleolar RNAs), tRNA (transfer RNA) fragments, and Y-RNAs in cellular processes has revealed a noncanonical function for many of these molecules. Similarly, the identification of long noncoding RNAs that appear to play an important role in cardiovascular disease processes, coupled with the development of tools to characterize their interacting partners, has led to significant mechanistic insight. Finally, recent work has characterized the unique role of extracellular RNAs in mediating intercellular communication and their potential role as biomarkers.

CONCLUSIONS

The rapid expansion of tools and pipelines for isolating, measuring, and annotating these entities suggests that caution in interpreting results is warranted until these methodologies are rigorously validated. Most investigators have focused on investigating the functional role of single RNA entities, but studies suggest complex interaction between different RNA molecules. The use of network approaches and advanced computational tools to understand the interaction of different noncoding RNA species to mediate a particular phenotype may be required to fully comprehend the function of noncoding RNAs in mediating disease phenotypes.

Exploring the functional impact of alternative splicing on human protein isoforms using available annotation sources

In recent years, the emphasis of scientific inquiry has shifted from whole-genome analyses to an understanding of cellular responses specific to tissue, developmental stage or environmental conditions. One of the central mechanisms underlying the diversity and adaptability of the contextual responses is alternative splicing (AS). It enables a single gene to encode multiple isoforms with distinct biological functions. However, to date, the functions of the vast majority of differentially spliced protein isoforms are not known. Integration of genomic, proteomic, functional, phenotypic and contextual information is essential for supporting isoform-based modeling and analysis. Such integrative proteogenomics approaches promise to provide insights into the functions of the alternatively spliced protein isoforms and provide high-confidence hypotheses to be validated experimentally. This manuscript provides a survey of the public databases supporting isoform-based biology. It also presents an overview of the potential global impact of AS on the human canonical gene functions, molecular interactions and cellular pathways.

Y Chromosome LncRNA Are Involved in Radiation Response of Male Non-Small Cell Lung Cancer Cells

Numerous studies have implicated changes in the Y chromosome in male cancers, yet few have investigated the biological importance of Y chromosome noncoding RNA. Here we identify a group of Y chromosome-expressed long noncoding RNA (lncRNA) that are involved in male non-small cell lung cancer (NSCLC) radiation sensitivity. Radiosensitive male NSCLC cell lines demonstrated a dose-dependent induction of linc-SPRY3-2/3/4 following irradiation, which was not observed in radioresistant male NSCLC cell lines. Cytogenetics revealed the loss of chromosome Y (LOY) in the radioresistant male NSCLC cell lines. Gain- and loss-of-function experiments indicated that linc-SPRY3-2/3/4 transcripts affect cell viability and apoptosis. Computational prediction of RNA binding proteins (RBP) motifs and UV-cross-linking and immunoprecipitation (CLIP) assays identified IGF2BP3, an RBP involved in mRNA stability, as a binding partner for linc-SPRY3-2/3/4 RNA. The presence of linc-SPRY3-2/3/4 reduced the half-life of known IGF2BP3 binding mRNA, such as the antiapoptotic HMGA2 mRNA, as well as the oncogenic c-MYC mRNA. Assessment of Y chromosome in NSCLC tissue microarrays and expression of linc-SPRY3-2/3/4 in NSCLC RNA-seq and microarray data revealed a negative correlation between the loss of the Y chromosome or linc-SPRY3-2/3/4 and overall survival. Thus, linc-SPRY3-2/3/4 expression and LOY could represent an important marker of radiotherapy in NSCLC. SIGNIFICANCE: This study describes previously unknown Y chromosome-expressed lncRNA regulators of radiation response in male NSCLC and show a correlation between loss of chromosome Y and radioresistance. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/80/19/4046/F1.large.jpg.

SURF: integrative analysis of a compendium of RNA-seq and CLIP-seq datasets highlights complex governing of alternative transcriptional regulation by RNA-binding proteins

Advances in high-throughput profiling of RNA-binding proteins (RBPs) have resulted inCLIP-seq datasets coupled with transcriptome profiling by RNA-seq. However, analysis methods that integrate both types of data are lacking. We describe SURF, Statistical Utility for RBP Functions, for integrative analysis of large collections of CLIP-seq and RNA-seq data. We demonstrate SURF's ability to accurately detect differential alternative transcriptional regulation events and associate them to local protein-RNA interactions. We apply SURF to ENCODE RBP compendium and carry out downstream analysis with additional reference datasets. The results of this application are browsable at http://www.statlab.wisc.edu/shiny/surf/.

oRNAment: a database of putative RNA binding protein target sites in the transcriptomes of model species

Protein-RNA interactions are essential for controlling most aspects of RNA metabolism, including synthesis, processing, trafficking, stability and degradation. In vitro selection methods, such as RNAcompete and RNA Bind-n-Seq, have defined the consensus target motifs of hundreds of RNA-binding proteins (RBPs). However, readily available information about the distribution features of these motifs across full transcriptomes was hitherto lacking. Here, we introduce oRNAment (o RNA motifs enrichment in transcriptomes), a database that catalogues the putative motif instances of 223 RBPs, encompassing 453 motifs, in a transcriptome-wide fashion. The database covers 525 718 complete coding and non-coding RNA species across the transcriptomes of human and four prominent model organisms: Caenorhabditis elegans, Danio rerio, Drosophila melanogaster and Mus musculus. The unique features of oRNAment include: (i) hosting of the most comprehensive mapping of RBP motif instances to date, with 421 133 612 putative binding sites described across five species; (ii) options for the user to filter the data according to a specific threshold; (iii) a user-friendly interface and efficient back-end allowing the rapid querying of the data through multiple angles (i.e. transcript, RBP, or sequence attributes) and (iv) generation of several interactive data visualization charts describing the results of user queries. oRNAment is freely available at http://rnabiology.ircm.qc.ca/oRNAment/.

RNA structural dynamics regulate early embryogenesis through controlling transcriptome fate and function

BACKGROUND

Vertebrate early embryogenesis is initially directed by a set of maternal RNAs and proteins, yet the mechanisms controlling this program remain largely unknown. Recent transcriptome-wide studies on RNA structure have revealed its pervasive and crucial roles in RNA processing and functions, but whether and how RNA structure regulates the fate of the maternal transcriptome have yet to be determined.

RESULTS

Here we establish the global map of four nucleotide-based mRNA structures by icSHAPE during zebrafish early embryogenesis. Strikingly, we observe that RNA structurally variable regions are enriched in the 3' UTR and contain cis-regulatory elements important for maternal-to-zygotic transition (MZT). We find that the RNA-binding protein Elavl1a stabilizes maternal mRNAs by binding to the cis-elements. Conversely, RNA structure formation suppresses Elavl1a's binding leading to the decay of its maternal targets.

CONCLUSIONS

Our study finds that RNA structurally variable regions are enriched in mRNA 3' UTRs and contain cis-regulatory elements during zebrafish early embryogenesis. We reveal that Elavl1a regulates maternal RNA stability in an RNA structure-dependent fashion. Overall, our findings reveal a broad and fundamental role of RNA structure-based regulation in vertebrate early embryogenesis.

ENPD - A Database of Eukaryotic Nucleic Acid Binding Proteins: Linking Gene Regulations to Proteins

Eukaryotic nucleic acid binding protein database (ENPD, http://qinlab.sls.cuhk.edu.hk/ENPD/) is a library of nucleic acid binding proteins (NBPs) and their functional information. NBPs such as DNA binding proteins (DBPs), RNA binding proteins (RBPs), and DNA and RNA binding proteins (DRBPs) are involved in every stage of gene regulation through their interactions with DNA and RNA. Due to the importance of NBPs, the database was constructed based on manual curation and a newly developed pipeline utilizing both sequenced transcriptomes and genomes. In total the database has recorded 2.8 million of NBPs and their binding motifs from 662 NBP families and 2423 species, constituting the largest NBP database. ENPD covers evolutionarily important lineages which have never been included in the previous NBP databases, while lineage-specific NBP family expansions were also found. ENPD also focuses on the involvements of DBPs, RBPs and DRBPs in non-coding RNA (ncRNA) mediated gene regulation. The predicted and experimentally validated targets of NBPs have both been recorded and manually curated in ENPD, linking the interactions between ncRNAs, DNA regulatory elements and NBPs in gene regulation. This database provides key resources for the scientific community, laying a solid foundation for future gene regulatory studies from both functional and evolutionary perspectives.

RNAct: Protein-RNA interaction predictions for model organisms with supporting experimental data

Protein-RNA interactions are implicated in a number of physiological roles as well as diseases, with molecular mechanisms ranging from defects in RNA splicing, localization and translation to the formation of aggregates. Currently, ∼1400 human proteins have experimental evidence of RNA-binding activity. However, only ∼250 of these proteins currently have experimental data on their target RNAs from various sequencing-based methods such as eCLIP. To bridge this gap, we used an established, computationally expensive protein-RNA interaction prediction method, catRAPID, to populate a large database, RNAct. RNAct allows easy lookup of known and predicted interactions and enables global views of the human, mouse and yeast protein-RNA interactomes, expanding them in a genome-wide manner far beyond experimental data (http://rnact.crg.eu).

Upstream analysis of alternative splicing: a review of computational approaches to predict context-dependent splicing factors

Alternative splicing (AS) has shown to play a pivotal role in the development of diseases, including cancer. Specifically, all the hallmarks of cancer (angiogenesis, cell immortality, avoiding immune system response, etc.) are found to have a counterpart in aberrant splicing of key genes. Identifying the context-specific regulators of splicing provides valuable information to find new biomarkers, as well as to define alternative therapeutic strategies. The computational models to identify these regulators are not trivial and require three conceptual steps: the detection of AS events, the identification of splicing factors that potentially regulate these events and the contextualization of these pieces of information for a specific experiment. In this work, we review the different algorithmic methodologies developed for each of these tasks. Main weaknesses and strengths of the different steps of the pipeline are discussed. Finally, a case study is detailed to help the reader be aware of the potential and limitations of this computational approach.

Distinct Processing of lncRNAs Contributes to Non-conserved Functions in Stem Cells

Long noncoding RNAs (lncRNAs) evolve more rapidly than mRNAs. Whether conserved lncRNAs undergo conserved processing, localization, and function remains unexplored. We report differing subcellular localization of lncRNAs in human and mouse embryonic stem cells (ESCs). A significantly higher fraction of lncRNAs is localized in the cytoplasm of hESCs than in mESCs. This turns out to be important for hESC pluripotency. FAST is a positionally conserved lncRNA but is not conserved in its processing and localization. In hESCs, cytoplasm-localized hFAST binds to the WD40 domain of the E3 ubiquitin ligase β-TrCP and blocks its interaction with phosphorylated β-catenin to prevent degradation, leading to activated WNT signaling, required for pluripotency. In contrast, mFast is nuclear retained in mESCs, and its processing is suppressed by the splicing factor PPIE, which is highly expressed in mESCs but not hESCs. These findings reveal that lncRNA processing and localization are previously under-appreciated contributors to the rapid evolution of function.

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.

dSreg: a Bayesian model to integrate changes in splicing and RNA-binding protein activity

MOTIVATION

Alternative splicing (AS) is an important mechanism in the generation of transcript diversity across mammals. AS patterns are dynamically regulated during development and in response to environmental changes. Defects or perturbations in its regulation may lead to cancer or neurological disorders, among other pathological conditions. The regulatory mechanisms controlling AS in a given biological context are typically inferred using a two-step framework: differential AS analysis followed by enrichment methods. These strategies require setting rather arbitrary thresholds and are prone to error propagation along the analysis.

RESULTS

To overcome these limitations, we propose dSreg, a Bayesian model that integrates RNA-seq with data from regulatory features, e.g. binding sites of RNA-binding proteins. dSreg identifies the key underlying regulators controlling AS changes and quantifies their activity while simultaneously estimating the changes in exon inclusion rates. dSreg increased both the sensitivity and the specificity of the identified AS changes in simulated data, even at low read coverage. dSreg also showed improved performance when analyzing a collection of knock-down RNA-binding proteins' experiments from ENCODE, as opposed to traditional enrichment methods, such as over-representation analysis and gene set enrichment analysis. dSreg opens the possibility to integrate a large amount of readily available RNA-seq datasets at low coverage for AS analysis and allows more cost-effective RNA-seq experiments.

AVAILABILITY AND IMPLEMENTATION

dSreg was implemented in python using stan and is freely available to the community at https://bitbucket.org/cmartiga/dsreg.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Systematically Dissecting the Function of RNA-Binding Proteins During Glioma Progression

RNA-binding proteins (RBPs) play important roles in regulating gene expression and dysregulation of RBPs have been observed in various types of cancer. However, the role of RBPs during glioma progression, and particular in Chinese patients, is only starting to be unveiled. Here, we systematically analyzed the somatic mutation, gene expression patterns of 2949 RBPs during glioma progression. Our comprehensive study reveals several of highly mutated genes (such as ATRX, TTN and SETD2) and differentially expressed genes (such as KIF4A, TTK and CEP55). Integration of the expression of RBPs and genes, we constructed a regulatory network in glioma and revealed the functional links between RBPs and cancer-related genes. Moreover, we identified the prognosis spectrum of RBPs during glioma progression. The expression of a number of RBPs, such as SNRPN and IGF2BP3, are significantly associated with overall survival of patients in all grades. Taken together, our analyses provided a valuable RBP resource during glioma progression, and revealed several candidates that potentially contribute to development of therapeutic targets for glioma.

EuRBPDB: a comprehensive resource for annotation, functional and oncological investigation of eukaryotic RNA binding proteins (RBPs)

RNA binding proteins (RBPs) are a large protein family that plays important roles at almost all levels of gene regulation through interacting with RNAs, and contributes to numerous biological processes. However, the complete list of eukaryotic RBPs including human is still unavailable. Here, we systematically identified RBPs in 162 eukaryotic species based on both computational analysis of RNA binding domains (RBDs) and large-scale RNA binding proteomic data, and established a comprehensive eukaryotic RBP database, EuRBPDB (http://EuRBPDB.syshospital.org). We identified a total of 311 571 RBPs with RBDs (corresponding to 6368 ortholog groups) and 3,651 non-canonical RBPs without known RBDs. EuRBPDB provides detailed annotations for each RBP, including basic information and functional annotation. Moreover, we systematically investigated RBPs in the context of cancer biology based on published literatures, PPI-network and large-scale omics data. To facilitate the exploration of the clinical relevance of RBPs, we additionally designed a cancer web interface to systematically and interactively display the biological features of RBPs in various types of cancers. EuRBPDB has a user-friendly web interface with browse and search functions, as well as data downloading function. We expect that EuRBPDB will be a widely-used resource and platform for both the communities of RNA biology and cancer biology.

From parts lists to functional significance-RNA-protein interactions in gene regulation

Hundreds of canonical RNA binding proteins facilitate diverse and essential RNA processing steps in cells forming a central regulatory point in gene expression. However, recent discoveries including the identification of a large number of noncanonical proteins bound to RNA have changed our view on RNA-protein interactions merely as necessary steps in RNA biogenesis. As the list of proteins interacting with RNA has expanded, so has the scope of regulation through RNA-protein interactions. In addition to facilitating RNA metabolism, RNA binding proteins help to form subcellular structures and membraneless organelles, and provide means to recruit components of macromolecular complexes to their sites of action. Moreover, RNA-protein interactions are not static in cells but the ribonucleoprotein (RNP) complexes are highly dynamic in response to cellular cues. The identification of novel proteins in complex with RNA and ways cells use these interactions to control cellular functions continues to broaden the scope of RNA regulation in cells and the current challenge is to move from cataloguing the components of RNPs into assigning them functions. This will not only facilitate our understanding of cellular homeostasis but may bring in key insights into human disease conditions where RNP components play a central role. This review brings together the classical view of regulation accomplished through RNA-protein interactions with the novel insights gained from the identification of RNA binding interactomes. We discuss the challenges in combining molecular mechanism with cellular functions on the journey towards a comprehensive understanding of the regulatory functions of RNA-protein interactions in cells. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications aRNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition.

Characterizing the interplay between gene nucleotide composition bias and splicing

BACKGROUND

Nucleotide composition bias plays an important role in the 1D and 3D organization of the human genome. Here, we investigate the potential interplay between nucleotide composition bias and the regulation of exon recognition during splicing.

RESULTS

By analyzing dozens of RNA-seq datasets, we identify two groups of splicing factors that activate either about 3200 GC-rich exons or about 4000 AT-rich exons. We show that splicing factor-dependent GC-rich exons have predicted RNA secondary structures at 5' ss and are dependent on U1 snRNP-associated proteins. In contrast, splicing factor-dependent AT-rich exons have a large number of decoy branch points, SF1- or U2AF2-binding sites and are dependent on U2 snRNP-associated proteins. Nucleotide composition bias also influences local chromatin organization, with consequences for exon recognition during splicing. Interestingly, the GC content of exons correlates with that of their hosting genes, isochores, and topologically associated domains.

CONCLUSIONS

We propose that regional nucleotide composition bias over several dozens of kilobase pairs leaves a local footprint at the exon level and induces constraints during splicing that can be alleviated by local chromatin organization at the DNA level and recruitment of specific splicing factors at the RNA level. Therefore, nucleotide composition bias establishes a direct link between genome organization and local regulatory processes, like alternative splicing.

Dissecting splicing decisions and cell-to-cell variability with designed sequence libraries

Most human genes are alternatively spliced, allowing for a large expansion of the proteome. The multitude of regulatory inputs to splicing limits the potential to infer general principles from investigating native sequences. Here, we create a rationally designed library of >32,000 splicing events to dissect the complexity of splicing regulation through systematic sequence alterations. Measuring RNA and protein splice isoforms allows us to investigate both cause and effect of splicing decisions, quantify diverse regulatory inputs and accurately predict (R² = 0.73–0.85) isoform ratios from sequence and secondary structure. By profiling individual cells, we measure the cell-to-cell variability of splicing decisions and show that it can be encoded in the DNA and influenced by regulatory inputs, opening the door for a novel, single-cell perspective on splicing regulation.

Alternative splicing is regulated by multiple mechanisms. Here the authors employed designed splice site libraries and massively parallel reporter assays to dissect the regulatory complexity and cell-to-cell variability of splicing decisions and to build accurate predictive models.

Regulatory RNA binding proteins contribute to the transcriptome-wide splicing alterations in human cellular senescence

Dysregulation of mRNA splicing has been observed in certain cellular senescence process. However, the common splicing alterations on the whole transcriptome shared by various types of senescence are poorly understood. In order to systematically identify senescence-associated transcriptomic changes in genome-wide scale, we collected RNA sequencing datasets of different human cell types with a variety of senescence-inducing methods from public databases and performed meta-analysis. First, we discovered that a group of RNA binding proteins were consistently down-regulated in diverse senescent samples and identified 406 senescence-associated common differential splicing events. Then, eight differentially expressed RNA binding proteins were predicted to regulate these senescence-associated splicing alterations through an enrichment analysis of their RNA binding information, including motif scanning and enhanced cross-linking immunoprecipitation data. In addition, we constructed the splicing regulatory modules that might contribute to senescence-associated biological processes. Finally, it was confirmed that knockdown of the predicted senescence-associated potential splicing regulators through shRNAs in HepG2 cell line could result in senescence-like splicing changes. Taken together, our work demonstrated a broad range of common changes in mRNA splicing switches and detected their central regulatory RNA binding proteins during senescence. These findings would help to better understand the coordinating splicing alterations in cellular senescence.

Family-Based Quantitative Trait Meta-Analysis Implicates Rare Noncoding Variants in DENND1A in Polycystic Ovary Syndrome

CONTEXT

Polycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5% to15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date.

OBJECTIVE

The objective of this study was to test whether rare genetic variants contribute to PCOS pathogenesis.

DESIGN, PATIENTS, AND METHODS

We performed whole-genome sequencing on DNA from 261 individuals from 62 families with one or more daughters with PCOS. We tested for associations of rare variants with PCOS and its concomitant hormonal traits using a quantitative trait meta-analysis.

RESULTS

We found rare variants in DENND1A (P = 5.31 × 10-5, adjusted P = 0.039) that were significantly associated with reproductive and metabolic traits in PCOS families.

CONCLUSIONS

Common variants in DENND1A have previously been associated with PCOS diagnosis in genome-wide association studies. Subsequent studies indicated that DENND1A is an important regulator of human ovarian androgen biosynthesis. Our findings provide additional evidence that DENND1A plays a central role in PCOS and suggest that rare noncoding variants contribute to disease pathogenesis.

SMARTIV: combined sequence and structure de-novo motif discovery for in-vivo RNA binding data

Gene expression regulation is highly dependent on binding of RNA-binding proteins (RBPs) to their RNA targets. Growing evidence supports the notion that both RNA primary sequence and its local secondary structure play a role in specific Protein-RNA recognition and binding. Despite the great advance in high-throughput experimental methods for identifying sequence targets of RBPs, predicting the specific sequence and structure binding preferences of RBPs remains a major challenge. We present a novel webserver, SMARTIV, designed for discovering and visualizing combined RNA sequence and structure motifs from high-throughput RNA-binding data, generated from in-vivo experiments. The uniqueness of SMARTIV is that it predicts motifs from enriched k-mers that combine information from ranked RNA sequences and their predicted secondary structure, obtained using various folding methods. Consequently, SMARTIV generates Position Weight Matrices (PWMs) in a combined sequence and structure alphabet with assigned P-values. SMARTIV concisely represents the sequence and structure motif content as a single graphical logo, which is informative and easy for visual perception. SMARTIV was examined extensively on a variety of high-throughput binding experiments for RBPs from different families, generated from different technologies, showing consistent and accurate results. Finally, SMARTIV is a user-friendly webserver, highly efficient in run-time and freely accessible via http://smartiv.technion.ac.il/.

MSGP: the first database of the protein components of the mammalian stress granules

In response to different stress stimuli, cells transiently form stress granules (SGs) in order to protect themselves and re-establish homeostasis. Besides these important cellular functions, SGs are now being implicated in different human diseases, such as neurodegenerative disorders and cancer. SGs are ribonucleoprotein granules, constituted by a variety of different types of proteins, RNAs, factors involved in translation and signaling molecules, being capable of regulating mRNA translation to facilitate stress response. However, until now a complete list of the SG components has not been available. Therefore, we aimer at identifying and linting in an open access database all the proteins described so far as components of SGs. The identification was made through an exhaustive search of studies listed in PubMed and double checked. Moreover, for each identified protein several details were also gathered from public databases, such as the molecular function, the cell types in which they were detected, the type of stress stimuli used to induce SG formation and the reference of the study describing the recruitment of the component to SGs. Expression levels in the context of different neurodegenerative diseases were also obtained and are also described in the database. The Mammalian Stress Granules Proteome is available at https://msgp.pt/, being a new and unique open access online database, the first to list all the protein components of the SGs identified so far. The database constitutes an important and valuable tool for researchers in this research area of growing interest.

Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing (RIPiT-Seq)

RNA immunoprecipitation in tandem (RIPiT) is a method for enriching RNA footprints of a pair of proteins within an RNA:protein (RNP) complex. RIPiT employs two purification steps. First, immunoprecipitation of a tagged RNP subunit is followed by mild RNase digestion and subsequent non-denaturing affinity elution. A second immunoprecipitation of another RNP subunit allows for enrichment of a defined complex. Following a denaturing elution of RNAs and proteins, the RNA footprints are converted into high-throughput DNA sequencing libraries. Unlike the more popular ultraviolet (UV) crosslinking followed by immunoprecipitation (CLIP) approach to enrich RBP binding sites, RIPiT is UV-crosslinking independent. Hence RIPiT can be applied to numerous proteins present in the RNA interactome and beyond that are essential to RNA regulation but do not directly contact the RNA or UV-crosslink poorly to RNA. The two purification steps in RIPiT provide an additional advantage of identifying binding sites where a protein of interest acts in partnership with another cofactor. The double purification strategy also serves to enhance signal by limiting background. Here, we provide a step-wise procedure to perform RIPiT and to generate high-throughput sequencing libraries from isolated RNA footprints. We also outline RIPiT's advantages and applications and discuss some of its limitations.

Alternative cleavage and polyadenylation in health and disease

Most human genes have multiple sites at which RNA 3' end cleavage and polyadenylation can occur, enabling the expression of distinct transcript isoforms under different conditions. Novel methods to sequence RNA 3' ends have generated comprehensive catalogues of polyadenylation (poly(A)) sites; their analysis using innovative computational methods has revealed how poly(A) site choice is regulated by core RNA 3' end processing factors, such as cleavage factor I and cleavage and polyadenylation specificity factor, as well as by other RNA-binding proteins, particularly splicing factors. Here, we review the experimental and computational methods that have enabled the global mapping of mRNA and of long non-coding RNA 3' ends, quantification of the resulting isoforms and the discovery of regulators of alternative cleavage and polyadenylation (APA). We highlight the different types of APA-derived isoforms and their functional differences, and illustrate how APA contributes to human diseases, including cancer and haematological, immunological and neurological diseases.

Regulation of alternative splicing by p300-mediated acetylation of splicing factors

Splicing of precursor mRNA (pre-mRNA) is an important regulatory step in gene expression. Recent evidence points to a regulatory role of chromatin-related proteins in alternative splicing regulation. Using an unbiased approach, we have identified the acetyltransferase p300 as a key chromatin-related regulator of alternative splicing. p300 promotes genome-wide exon inclusion in both a transcription-dependent and -independent manner. Using CD44 as a paradigm, we found that p300 regulates alternative splicing by modulating the binding of splicing factors to pre-mRNA. Using a tethering strategy, we found that binding of p300 to the CD44 promoter region promotes CD44v exon inclusion independently of RNAPII transcriptional elongation rate. Promoter-bound p300 regulates alternative splicing by acetylating splicing factors, leading to exclusion of hnRNP M from CD44 pre-mRNA and activation of Sam68. p300-mediated CD44 alternative splicing reduces cell motility and promotes epithelial features. Our findings reveal a chromatin-related mechanism of alternative splicing regulation and demonstrate its impact on cellular function.

Integration of CLIP experiments of RNA-binding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data

BACKGROUND

Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein.

RESULTS

In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four CLIP databases: POSTAR2, CLIPdb, DoRiNA and StarBase. The analysis of these experiments shows the strong coherence between the binding sites of RBPs of similar families. Augmenting this information with expression changes, we are able to correctly predict the splicing factors that regulate splicing in two gold-standard experiments in which specific splicing factors are knocked-down.

CONCLUSIONS

The methodology presented in this study allows the prediction of active splicing factors in either cancer or any other condition by only using the information of transcript expression. This approach opens a wide range of possible studies to understand the splicing regulation of different conditions. A tutorial with the source code and databases is available at https://gitlab.com/fcarazo.m/sfprediction .

EcRBPome: a comprehensive database of all known E. coli RNA-binding proteins

The repertoire of RNA-binding proteins (RBPs) in bacteria play a crucial role in their survival, and interactions with the host machinery, but there is little information, record or characterisation in bacterial genomes. As a first step towards this, we have chosen the bacterial model system Escherichia coli, and organised all RBPs in this organism into a comprehensive database named EcRBPome. It contains RBPs recorded from 614 complete E. coli proteomes available in the RefSeq database (as of October 2018). The database provides various features related to the E. coli RBPs, like their domain architectures, PDB structures, GO and EC annotations etc. It provides the assembly, bioproject and biosample details of each strain, as well as cross-strain comparison of occurrences of various RNA-binding domains (RBDs). The percentage of RBPs, the abundance of the various RBDs harboured by each strain have been graphically represented in this database and available alongside other files for user download. To the best of our knowledge, this is the first database of its kind and we hope that it will be of great use to the biological community.

Gain-of-Function Mutations: An Emerging Advantage for Cancer Biology

Advances in next-generation sequencing have identified thousands of genomic variants that perturb the normal functions of proteins, further contributing to diverse phenotypic consequences in cancer. Elucidating the functional pathways altered by loss-of-function (LOF) or gain-of-function (GOF) mutations will be crucial for prioritizing cancer-causing variants and their resultant therapeutic liabilities. In this review, we highlight the fundamental function of GOF mutations and discuss the potential mechanistic effects in the context of signaling networks. We also summarize advances in experimental and computational resources, which will dramatically help with studies on the functional and phenotypic consequences of mutations. Together, systematic investigations of the function of GOF mutations will provide an important missing piece for cancer biology and precision therapy.

Global donor and acceptor splicing site kinetics in human cells

RNA splicing is an essential part of eukaryotic gene expression. Although the mechanism of splicing has been extensively studied in vitro, in vivo kinetics for the two-step splicing reaction remain poorly understood. Here, we combine transient transcriptome sequencing (TT-seq) and mathematical modeling to quantify RNA metabolic rates at donor and acceptor splice sites across the human genome. Splicing occurs in the range of minutes and is limited by the speed of RNA polymerase elongation. Splicing kinetics strongly depends on the position and nature of nucleotides flanking splice sites, and on structural interactions between unspliced RNA and small nuclear RNAs in spliceosomal intermediates. Finally, we introduce the 'yield' of splicing as the efficiency of converting unspliced to spliced RNA and show that it is highest for mRNAs and independent of splicing kinetics. These results lead to quantitative models describing how splicing rates and yield are encoded in the human genome.

Interplay between coding and exonic splicing regulatory sequences

The inclusion of exons during the splicing process depends on the binding of splicing factors to short low-complexity regulatory sequences. The relationship between exonic splicing regulatory sequences and coding sequences is still poorly understood. We demonstrate that exons that are coregulated by any given splicing factor share a similar nucleotide composition bias and preferentially code for amino acids with similar physicochemical properties because of the nonrandomness of the genetic code. Indeed, amino acids sharing similar physicochemical properties correspond to codons that have the same nucleotide composition bias. In particular, we uncover that the TRA2A and TRA2B splicing factors that bind to adenine-rich motifs promote the inclusion of adenine-rich exons coding preferentially for hydrophilic amino acids that correspond to adenine-rich codons. SRSF2 that binds guanine/cytosine-rich motifs promotes the inclusion of GC-rich exons coding preferentially for small amino acids, whereas SRSF3 that binds cytosine-rich motifs promotes the inclusion of exons coding preferentially for uncharged amino acids, like serine and threonine that can be phosphorylated. Finally, coregulated exons encoding amino acids with similar physicochemical properties correspond to specific protein features. In conclusion, the regulation of an exon by a splicing factor that relies on the affinity of this factor for specific nucleotide(s) is tightly interconnected with the exon-encoded physicochemical properties. We therefore uncover an unanticipated bidirectional interplay between the splicing regulatory process and its biological functional outcome.

Detection of Differentially Expressed Cleavage Site Intervals Within 3' Untranslated Regions Using CSI-UTR Reveals Regulated Interaction Motifs

The length of untranslated regions at the 3' end of transcripts (3'UTRs) is regulated by alternate polyadenylation (APA). 3'UTRs contain regions that harbor binding motifs for regulatory molecules. However, the mechanisms that coordinate the 3'UTR length of specific groups of transcripts are not well-understood. We therefore developed a method, CSI-UTR, that models 3'UTR structure as tandem segments between functional alternative-polyadenylation sites (termed cleavage site intervals-CSIs). This approach facilitated (1) profiling of 3'UTR isoform expression changes and (2) statistical enrichment of putative regulatory motifs. CSI-UTR analysis is UTR-annotation independent and can interrogate legacy data generated from standard RNA-Seq libraries. CSI-UTR identified a set of CSIs in human and rodent transcriptomes. Analysis of RNA-Seq datasets from neural tissue identified differential expression events within 3'UTRs not detected by standard gene-based differential expression analyses. Further, in many instances 3'UTR and CDS from the same gene were regulated differently. This modulation of motifs for RNA-interacting molecules with potential condition-dependent and tissue-specific RNA binding partners near the polyA signal and CSI junction may play a mechanistic role in the specificity of alternative polyadenylation. Source code, CSI BED files and example datasets are available at: https://github.com/UofLBioinformatics/CSI-UTR.

Quantification and discovery of sequence determinants of protein-per-mRNA amount in 29 human tissues

Despite their importance in determining protein abundance, a comprehensive catalogue of sequence features controlling protein-to-mRNA (PTR) ratios and a quantification of their effects are still lacking. Here, we quantified PTR ratios for 11,575 proteins across 29 human tissues using matched transcriptomes and proteomes. We estimated by regression the contribution of known sequence determinants of protein synthesis and degradation in addition to 45 mRNA and 3 protein sequence motifs that we found by association testing. While PTR ratios span more than 2 orders of magnitude, our integrative model predicts PTR ratios at a median precision of 3.2-fold. A reporter assay provided functional support for two novel UTR motifs, and an immobilized mRNA affinity competition-binding assay identified motif-specific bound proteins for one motif. Moreover, our integrative model led to a new metric of codon optimality that captures the effects of codon frequency on protein synthesis and degradation. Altogether, this study shows that a large fraction of PTR ratio variation in human tissues can be predicted from sequence, and it identifies many new candidate post-transcriptional regulatory elements.

PLAIDOH: a novel method for functional prediction of long non-coding RNAs identifies cancer-specific LncRNA activities

BACKGROUND

Long non-coding RNAs (lncRNAs) exhibit remarkable cell-type specificity and disease association. LncRNA's functional versatility includes epigenetic modification, nuclear domain organization, transcriptional control, regulation of RNA splicing and translation, and modulation of protein activity. However, most lncRNAs remain uncharacterized due to a shortage of predictive tools available to guide functional experiments.

RESULTS

To address this gap for lymphoma-associated lncRNAs identified in our studies, we developed a new computational method, Predicting LncRNA Activity through Integrative Data-driven 'Omics and Heuristics (PLAIDOH), which has several unique features not found in other methods. PLAIDOH integrates transcriptome, subcellular localization, enhancer landscape, genome architecture, chromatin interaction, and RNA-binding (eCLIP) data and generates statistically defined output scores. PLAIDOH's approach identifies and ranks functional connections between individual lncRNA, coding gene, and protein pairs using enhancer, transcript cis-regulatory, and RNA-binding protein interactome scores that predict the relative likelihood of these different lncRNA functions. When applied to 'omics datasets that we collected from lymphoma patients, or to publicly available cancer (TCGA) or ENCODE datasets, PLAIDOH identified and prioritized well-known lncRNA-target gene regulatory pairs (e.g., HOTAIR and HOX genes, PVT1 and MYC), validated hits in multiple lncRNA-targeted CRISPR screens, and lncRNA-protein binding partners (e.g., NEAT1 and NONO). Importantly, PLAIDOH also identified novel putative functional interactions, including one lymphoma-associated lncRNA based on analysis of data from our human lymphoma study. We validated PLAIDOH's predictions for this lncRNA using knock-down and knock-out experiments in lymphoma cell models.

CONCLUSIONS

Our study demonstrates that we have developed a new method for the prediction and ranking of functional connections between individual lncRNA, coding gene, and protein pairs, which were validated by genetic experiments and comparison to published CRISPR screens. PLAIDOH expedites validation and follow-on mechanistic studies of lncRNAs in any biological system. It is available at https://github.com/sarahpyfrom/PLAIDOH .