Database of RNA binding protein expression and disease dynamics (READ DB)

Non-Coding RNAs in Glioma Microenvironment and Angiogenesis

Glioma, especially glioblastoma, is the most common and lethal brain tumor. In line with the complicated vascularization processes and the strong intratumoral heterogeneity, tumor-associated blood vessels in glioma are regulated by multiple types of cells through a variety of molecular mechanisms. Components of the tumor microenvironment, including tumor cells and tumor-associated stromata, produce various types of molecular mediators to regulate glioma angiogenesis. As critical regulatory molecules, non-coding RNAs (ncRNAs) inside cells or secreted to the tumor microenvironment play essential roles in glioma angiogenesis. In this review, we briefly summarize recent studies about the production, delivery, and functions of ncRNAs in the tumor microenvironment, as well as the molecular mechanisms underlying the regulation of angiogenesis by ncRNAs. We also discuss the ncRNA-based therapeutic strategies in the anti-angiogenic therapy for glioma treatment.

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.

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.

High throughput approaches to study RNA-protein interactions in vitro

To understand the regulation of gene expression it is critical to determine how proteins interact with and discriminate between different RNAs. In this review, we discuss experimental techniques that utilize high throughput approaches to characterize the interactions of proteins with large numbers of RNAs in vitro. We describe the underlying principles for the main methods, briefly discuss their scope and limitations, and outline how insight from the techniques contributes to our understanding of specificity for RNA-protein interactions.

Mutational landscape of RNA-binding proteins in human cancers

RNA Binding Proteins (RBPs) are a class of post-transcriptional regulatory molecules which are increasingly documented to be dysfunctional in cancer genomes. However, our current understanding of these alterations is limited. Here, we delineate the mutational landscape of ∼1300 RBPs in ∼6000 cancer genomes. Our analysis revealed that RBPs have an average of ∼3 mutations per Mb across 26 cancer types. We identified 281 RBPs to be enriched for mutations (GEMs) in at least one cancer type. GEM RBPs were found to undergo frequent frameshift and inframe deletions as well as missense, nonsense and silent mutations when compared to those that are not enriched for mutations. Functional analysis of these RBPs revealed the enrichment of pathways associated with apoptosis, splicing and translation. Using the OncodriveFM framework, we also identified more than 200 candidate driver RBPs that were found to accumulate functionally impactful mutations in at least one cancer. Expression levels of 15% of these driver RBPs exhibited significant difference, when transcriptome groups with and without deleterious mutations were compared. Functional interaction network of the driver RBPs revealed the enrichment of spliceosomal machinery, suggesting a plausible mechanism for tumorogenesis while network analysis of the protein interactions between RBPs unambiguously revealed the higher degree, betweenness and closeness centrality for driver RBPs compared to non-drivers. Analysis to reveal cancer-specific Ribonucleoprotein (RNP) mutational hotspots showed extensive rewiring even among common drivers between cancer types. Knockdown experiments on pan-cancer drivers such as SF3B1 and PRPF8 in breast cancer cell lines, revealed cancer subtype specific functions like selective stem cell features, indicating a plausible means for RBPs to mediate cancer-specific phenotypes. Hence, this study would form a foundation to uncover the contribution of the mutational spectrum of RBPs in dysregulating the post-transcriptional regulatory networks in different cancer types.

Sequence-Based Prediction of RNA-Binding Residues in Proteins

Identifying individual residues in the interfaces of protein-RNA complexes is important for understanding the molecular determinants of protein-RNA recognition and has many potential applications. Recent technical advances have led to several high-throughput experimental methods for identifying partners in protein-RNA complexes, but determining RNA-binding residues in proteins is still expensive and time-consuming. This chapter focuses on available computational methods for identifying which amino acids in an RNA-binding protein participate directly in contacting RNA. Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. In addition, currently available web servers and software tools for predicting RNA-binding sites, as well as databases that contain valuable information about known protein-RNA complexes, RNA-binding motifs in proteins, and protein-binding recognition sites in RNA are provided. We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner.

MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

The MalaCards human disease database (http://www.malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards’ affiliation with the GeneCards Suite of databases. MalaCards’ capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ‘flat’ disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.

RNA-binding proteins in eye development and disease: implication of conserved RNA granule components

The molecular biology of metazoan eye development is an area of intense investigation. These efforts have led to the surprising recognition that although insect and vertebrate eyes have dramatically different structures, the orthologs or family members of several conserved transcription and signaling regulators such as Pax6, Six3, Prox1, and Bmp4 are commonly required for their development. In contrast, our understanding of posttranscriptional regulation in eye development and disease, particularly regarding the function of RNA-binding proteins (RBPs), is limited. We examine the present knowledge of RBPs in eye development in the insect model Drosophila as well as several vertebrate models such as fish, frog, chicken, and mouse. Interestingly, of the 42 RBPs that have been investigated for their expression or function in vertebrate eye development, 24 (~60%) are recognized in eukaryotic cells as components of RNA granules such as processing bodies, stress granules, or other specialized ribonucleoprotein (RNP) complexes. We discuss the distinct developmental and cellular events that may necessitate potential RBP/RNA granule-associated RNA regulon models to facilitate posttranscriptional control of gene expression in eye morphogenesis. In support of these hypotheses, three RBPs and RNP/RNA granule components Tdrd7, Caprin2, and Stau2 are linked to ocular developmental defects such as congenital cataract, Peters anomaly, and microphthalmia in human patients or animal models. We conclude by discussing the utility of interdisciplinary approaches such as the bioinformatics tool iSyTE (integrated Systems Tool for Eye gene discovery) to prioritize RBPs for deriving posttranscriptional regulatory networks in eye development and disease. WIREs RNA 2016, 7:527-557. doi: 10.1002/wrna.1355 For further resources related to this article, please visit the WIREs website.

Systems biology of lens development: A paradigm for disease gene discovery in the eye

Over the past several decades, the biology of the developing lens has been investigated using molecular genetics-based approaches in various vertebrate model systems. These efforts, involving target gene knockouts or knockdowns, have led to major advances in our understanding of lens morphogenesis and the pathological basis of cataracts, as well as of other lens related eye defects. In particular, we now have a functional understanding of regulators such as Pax6, Six3, Sox2, Oct1 (Pou2f1), Meis1, Pnox1, Zeb2 (Sip1), Mab21l1, Foxe3, Tfap2a (Ap2-alpha), Pitx3, Sox11, Prox1, Sox1, c-Maf, Mafg, Mafk, Hsf4, Fgfrs, Bmp7, and Tdrd7 in this tissue. However, whether these individual regulators interact or their targets overlap, and the significance of such interactions during lens morphogenesis, is not well defined. The arrival of high-throughput approaches for gene expression profiling (microarrays, RNA-sequencing (RNA-seq), etc.), which can be coupled with chromatin immunoprecipitation (ChIP) or RNA immunoprecipitation (RIP) assays, along with improved computational resources and publically available datasets (e.g. those containing comprehensive protein-protein, protein-DNA information), presents new opportunities to advance our understanding of the lens tissue on a global systems level. Such systems-level knowledge will lead to the derivation of the underlying lens gene regulatory network (GRN), defined as a circuit map of the regulator-target interactions functional in lens development, which can be applied to expedite cataract gene discovery. In this review, we cover the various systems-level approaches such as microarrays, RNA-seq, and ChIP that are already being applied to lens studies and discuss strategies for assembling and interpreting these vast amounts of high-throughput information for effective dispersion to the scientific community. In particular, we discuss strategies for effective interpretation of this new information in the context of the rich knowledge obtained through the application of traditional single-gene focused experiments on the lens. Finally, we discuss our vision for integrating these diverse high-throughput datasets in a single web-based user-friendly tool iSyTE (integrated Systems Tool for Eye gene discovery) - a resource that is already proving effective in the identification and characterization of genes linked to lens development and cataract. We anticipate that application of a similar approach to other ocular tissues such as the retina and the cornea, and even other organ systems, will significantly impact disease gene discovery.