scholarly journals TF–RBP–AS Triplet Analysis Reveals the Mechanisms of Aberrant Alternative Splicing Events in Kidney Cancer: Implications for Their Possible Clinical Use as Prognostic and Therapeutic Biomarkers

2021 ◽  
Vol 22 (16) ◽  
pp. 8789
Author(s):  
Meng He ◽  
Fuyan Hu
Keyword(s):  
Alternative Splicing ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Cancer Development ◽  
Pathway Enrichment Analysis ◽  
Sequencing Data ◽  
Computational Framework

Aberrant alternative splicing (AS) is increasingly linked to cancer; however, how AS contributes to cancer development still remains largely unknown. AS events (ASEs) are largely regulated by RNA-binding proteins (RBPs) whose ability can be modulated by a variety of genetic and epigenetic mechanisms. In this study, we used a computational framework to investigate the roles of transcription factors (TFs) on regulating RBP-AS interactions. A total of 6519 TF–RBP–AS triplets were identified, including 290 TFs, 175 RBPs, and 16 ASEs from TCGA–KIRC RNA sequencing data. TF function categories were defined according to correlation changes between RBP expression and their targeted ASEs. The results suggested that most TFs affected multiple targets, and six different classes of TF-mediated transcriptional dysregulations were identified. Then, regulatory networks were constructed for TF–RBP–AS triplets. Further pathway-enrichment analysis showed that these TFs and RBPs involved in triplets were enriched in a variety of pathways that were associated with cancer development and progression. Survival analysis showed that some triplets were highly associated with survival rates. These findings demonstrated that the integration of TFs into alternative splicing regulatory networks can help us in understanding the roles of alternative splicing in cancer.

scholarly journals Identification of Key Deregulated RNA-Binding Proteins in Pancreatic Cancer by Meta-Analysis and Prediction of Their Role as Modulators of Oncogenesis

2021 ◽  
Vol 9 ◽  
Author(s):  
Moumita Mukherjee ◽  
Srikanta Goswami
Keyword(s):  
Pancreatic Cancer ◽  
Cell Migration ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Meta Analysis ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment

RNA-binding proteins (RBPs) play a significant role in multiple cellular processes with their deregulations strongly associated with cancer. However, there are not adequate evidences regarding global alteration and functions of RBPs in pancreatic cancer, interrogated in a systematic manner. In this study, we have prepared an exhaustive list of RBPs from multiple sources, downloaded gene expression microarray data from a total of 241 pancreatic tumors and 124 normal pancreatic tissues, performed a meta-analysis, and obtained differentially expressed RBPs (DE-RBPs) using the Limma package of R Bioconductor. The results were validated in microarray datasets and the Cancer Genome Atlas (TCGA) RNA sequencing dataset for pancreatic adenocarcinoma (PAAD). Pathway enrichment analysis was performed using DE-RBPs, and we also constructed the protein–protein interaction (PPI) network to detect key modules and hub-RBPs. Coding and noncoding targets for top altered and hub RBPs were identified, and altered pathways modulated by these targets were also investigated. Our meta-analysis identified 45 upregulated and 15 downregulated RBPs as differentially expressed in pancreatic cancer, and pathway enrichment analysis demonstrated their important contribution in tumor development. As a result of PPI network analysis, 26 hub RBPs were detected and coding and noncoding targets for all these RBPs were categorized. Functional exploration characterized the pathways related to epithelial-to-mesenchymal transition (EMT), cell migration, and metastasis to emerge as major pathways interfered by the targets of these RBPs. Our study identified a unique meta-signature of 26 hub-RBPs to primarily modulate pancreatic tumor cell migration and metastasis in pancreatic cancer. IGF2BP3, ISG20, NIP7, PRDX1, RCC2, RUVBL1, SNRPD1, PAIP2B, and SIDT2 were found to play the most prominent role in the regulation of EMT in the process. The findings not only contribute to understand the biology of RBPs in pancreatic cancer but also to evaluate their candidature as possible therapeutic targets.

scholarly journals CLIPreg: Constructing translational regulatory networks from CLIP-, Ribo- and RNA-seq

2021 ◽  
Author(s):  
Baptiste Kerouanton ◽  
Sebastian Schafer ◽  
Lena Ho ◽  
Sonia Chothani ◽  
Owen JL Rackham
Keyword(s):  
Protein Interactions ◽  
Translational Regulation ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Critical Role ◽  
Sequencing Data ◽  
Data Types ◽  
Network Resources ◽  
Gene Regulatory

Motivation: The creation and analysis of gene regulatory networks have been the focus of bioinformatic research and underpins much of what is known about gene regulation. However, as a result of a bias in the availability of data-types that are collected, the vast majority of gene regulatory network resources and tools have focused on either transcriptional regulation or protein-protein interactions. This has left other areas of regulation, for instance translational regulation, vastly underrepresented despite them having been shown to play a critical role in both health and disease. Results: In order to address this we have developed CLIPreg, a package that integrates RNA, Ribo and CLIP- sequencing data in order to construct translational regulatory networks coordinated by RNA-binding proteins. This is the first tool of its type to be created, allowing for detailed investigation into a previously unseen layer of regulation.

scholarly journals The RNA-Binding Protein HuD Regulates Alternative Splicing and Alternative Polyadenylation in the Mouse Neocortex

Molecules ◽  
2021 ◽  
Vol 26 (10) ◽  
pp. 2836
Author(s):  
Rebecca M. Sena ◽  
Jeffery L. Twiss ◽  
Amy S. Gardiner ◽  
Michela Dell’Orco ◽  
David N. Linsenbardt ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Alternative Polyadenylation ◽  
Untranslated Regions ◽  
Sequencing Data ◽  
Hu Proteins ◽  
Nuclear Events ◽  
Neuronal Functions ◽  
Polyadenylation Signals

The neuronal Hu/ELAV-like proteins HuB, HuC and HuD are a class of RNA-binding proteins that are crucial for proper development and maintenance of the nervous system. These proteins bind to AU-rich elements (AREs) in the untranslated regions (3′-UTRs) of target mRNAs regulating mRNA stability, transport and translation. In addition to these cytoplasmic functions, Hu proteins have been implicated in alternative splicing and alternative polyadenylation in the nucleus. The purpose of this study was to identify transcriptome-wide effects of HuD deletion on both of these nuclear events using RNA sequencing data obtained from the neocortex of Elavl4–/– (HuD KO) mice. HuD KO affected alternative splicing of 310 genes, including 17 validated HuD targets such as Cbx3, Cspp1, Snap25 and Gria2. In addition, deletion of HuD affected polyadenylation of 53 genes, with the majority of significantly altered mRNAs shifting towards usage of proximal polyadenylation signals (PAS), resulting in shorter 3′-UTRs. None of these genes overlapped with those showing alternative splicing events. Overall, HuD KO had a greater effect on alternative splicing than polyadenylation, with many of the affected genes implicated in several neuronal functions and neuropsychiatric disorders.

scholarly journals The risk of pancreatic adenocarcinoma following SARS-CoV family infection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Amin Ebrahimi Sadrabadi ◽  
Ahmad Bereimipour ◽  
Arsalan Jalili ◽  
Mazaher Gholipurmalekabadi ◽  
Behrouz Farhadihosseinabadi ◽  
...  
Keyword(s):  
Pancreatic Adenocarcinoma ◽  
Rna Binding ◽  
Enrichment Analysis ◽  
Cancer Development ◽  
Actin Binding ◽  
Pathway Enrichment Analysis ◽  
Double Stranded Rna ◽  
In Silico Study ◽  
Global Catastrophe ◽  
Geo Database

AbstractCOVID 19 disease has become a global catastrophe over the past year that has claimed the lives of over two million people around the world. Despite the introduction of vaccines against the disease, there is still a long way to completely eradicate it. There are concerns about the complications following infection with SARS-CoV-2. This research aimed to evaluate the possible correlation between infection with SARS-CoV viruses and cancer in an in-silico study model. To do this, the relevent dataset was selected from GEO database. Identification of differentially expressed genes among defined groups including SARS-CoV, SARS-dORF6, SARS-BatSRBD, and H1N1 were screened where the |Log FC| ≥ 1and p < 0.05 were considered statistically significant. Later, the pathway enrichment analysis and gene ontology (GO) were used by Enrichr and Shiny GO databases. Evaluation with STRING online was applied to predict the functional interactions of proteins, followed by Cytoscape analysis to identify the master genes. Finally, analysis with GEPIA2 server was carried out to reveal the possible correlation between candidate genes and cancer development. The results showed that the main molecular function of up- and down-regulated genes was “double-stranded RNA binding” and actin-binding, respectively. STRING and Cytoscape analysis presented four genes, PTEN, CREB1, CASP3, and SMAD3 as the key genes involved in cancer development. According to TCGA database results, these four genes were up-regulated notably in pancreatic adenocarcinoma. Our findings suggest that pancreatic adenocarcinoma is the most probably malignancy happening after infection with SARS-CoV family.

scholarly journals CRAFT: a bioinformatics software for custom prediction of circular RNA functions

2021 ◽  
Author(s):  
Anna Dal Molin ◽  
Enrico Gaffo ◽  
Valeria Difilippo ◽  
Alessia Buratin ◽  
Caterina Tretti Parenzan ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Circular Rna ◽  
Functional Enrichment ◽  
Circular Rnas ◽  
Cellular Processes ◽  
Functional Investigation

Circular RNAs (circRNAs), transcripts generated by backsplicing, are particularly stable and pleiotropic molecules, whose dysregulation drives human diseases and cancer by modulating gene expression and signaling pathways. CircRNAs can regulate cellular processes by different mechanisms, including interaction with microRNAs (miRNAs) and RNA-binding proteins (RBP), and encoding specific peptides. The prediction of circRNA functions is instrumental to interpret their impact in diseases, and to prioritize circRNAs for functional investigation. Currently, circRNA functional predictions are provided by web databases that do not allow custom analyses, while self-standing circRNA prediction tools are mostly limited to predict only one type of function, mainly focusing on the miRNA sponge activity of circRNAs. To solve these issues, we developed CRAFT (CircRNA Function prediction Tool), a freely available computational pipeline that predicts circRNA sequence and molecular interactions with miRNAs and RBP, along with their coding potential. Analysis of a set of circRNAs with known functions has been used to appraise CRAFT predictions and to optimize its setting. CRAFT provides a comprehensive graphical visualization of the results, links to several knowledge databases, and extensive functional enrichment analysis. Moreover, it originally combines the predictions for different circRNAs. CRAFT is a useful tool to help the user explore the potential regulatory networks involving the circRNAs of interest and generate hypotheses about the cooperation of circRNAs into the modulation of biological processes.

scholarly journals Identification of m6A-Associated RNA Binding Proteins Using an Integrative Computational Framework

2021 ◽  
Vol 12 ◽  
Author(s):  
Yiqian Zhang ◽  
Michiaki Hamada
Keyword(s):  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Enrichment Analysis ◽  
Classification Model ◽  
Expression Level ◽  
Computational Framework ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Binding Data

N6-methyladenosine (m6A) is an abundant modification on mRNA that plays an important role in regulating essential RNA activities. Several wet lab studies have identified some RNA binding proteins (RBPs) that are related to m6A's regulation. The objective of this study was to identify potential m6A-associated RBPs using an integrative computational framework. The framework was composed of an enrichment analysis and a classification model. Utilizing RBPs' binding data, we analyzed reproducible m6A regions from independent studies using this framework. The enrichment analysis identified known m6A-associated RBPs including YTH domain-containing proteins; it also identified RBM3 as a potential m6A-associated RBP for mouse. Furthermore, a significant correlation for the identified m6A-associated RBPs is observed at the protein expression level rather than the gene expression level. On the other hand, a Random Forest classification model was built for the reproducible m6A regions using RBPs' binding data. The RBP-based predictor demonstrated not only competitive performance when compared with sequence-based predictions but also reflected m6A's action of repelling against RBPs, which suggested that our framework can infer interaction between m6A and m6A-associated RBPs beyond sequence level when utilizing RBPs' binding data. In conclusion, we designed an integrative computational framework for the identification of known and potential m6A-associated RBPs. We hope the analysis will provide more insights on the studies of m6A and RNA modifications.

scholarly journals RNA-Centric Approaches to Profile the RNA–Protein Interaction Landscape on Selected RNAs

2021 ◽  
Vol 7 (1) ◽  
pp. 11 ◽  
Author(s):  
André P. Gerber
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Regulatory Networks ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Protein Complexes ◽  
Cell Protein ◽  
Transcriptional Regulatory Networks ◽  
Technological Advances

RNA–protein interactions frame post-transcriptional regulatory networks and modulate transcription and epigenetics. While the technological advances in RNA sequencing have significantly expanded the repertoire of RNAs, recently developed biochemical approaches combined with sensitive mass-spectrometry have revealed hundreds of previously unrecognized and potentially novel RNA-binding proteins. Nevertheless, a major challenge remains to understand how the thousands of RNA molecules and their interacting proteins assemble and control the fate of each individual RNA in a cell. Here, I review recent methodological advances to approach this problem through systematic identification of proteins that interact with particular RNAs in living cells. Thereby, a specific focus is given to in vivo approaches that involve crosslinking of RNA–protein interactions through ultraviolet irradiation or treatment of cells with chemicals, followed by capture of the RNA under study with antisense-oligonucleotides and identification of bound proteins with mass-spectrometry. Several recent studies defining interactomes of long non-coding RNAs, viral RNAs, as well as mRNAs are highlighted, and short reference is given to recent in-cell protein labeling techniques. These recent experimental improvements could open the door for broader applications and to study the remodeling of RNA–protein complexes upon different environmental cues and in disease.

scholarly journals Targeting Poison Exons to Treat Developmental and Epileptic Encephalopathy

2021 ◽  
pp. 1-6
Author(s):  
Miriam C. Aziz ◽  
Patricia N. Schneider ◽  
Gemma L. Carvill
Keyword(s):  
Alternative Splicing ◽  
Rna Binding ◽  
De Novo ◽  
Rna Binding Proteins ◽  
Autism Spectrum ◽  
Epileptic Encephalopathy ◽  
Nonsense Mediated Decay ◽  
Subsequent Degradation ◽  
Alternative Splicing Events ◽  
Genetic Epilepsies

Developmental and epileptic encephalopathies (DEEs) describe a subset of neurodevelopmental disorders categorized by refractory epilepsy that is often associated with intellectual disability and autism spectrum disorder. The majority of DEEs are now known to have a genetic basis with de novo coding variants accounting for the majority of cases. More recently, a small number of individuals have been identified with intronic <i>SCN1A</i> variants that result in alternative splicing events that lead to ectopic inclusion of poison exons (PEs). PEs are short highly conserved exons that contain a premature truncation codon, and when spliced into the transcript, lead to premature truncation and subsequent degradation by nonsense-mediated decay. The reason for the inclusion/exclusion of these PEs is not entirely clear, but research suggests an autoregulatory role in gene expression and protein abundance. This is seen in proteins such as RNA-binding proteins and serine/arginine-rich proteins. Recent studies have focused on targeting these PEs as a method for therapeutic intervention. Targeting PEs using antisense oligonucleotides (ASOs) has shown to be effective in modulating alternative splicing events by decreasing the amount of transcripts harboring PEs, thus increasing the abundance of full-length transcripts and thereby the amount of protein in haploinsufficient genes implicated in DEE. In the age of personalized medicine, cellular and animal models of the genetic epilepsies have become essential in developing and testing novel precision therapeutics, including PE-targeting ASOs in a subset of DEEs.

scholarly journals Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mariana G. Ferrarini ◽  
Avantika Lal ◽  
Rita Rebollo ◽  
Andreas J. Gruber ◽  
Andrea Guarracino ◽  
...  
Keyword(s):  
Transposable Element ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Initiation Factor ◽  
Sequence Variant ◽  
The Novel ◽  
Sequencing Data ◽  
Genome Wide ◽  
Respiratory Cells ◽  
Nuclear Ribonucleoprotein

AbstractThe novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host–pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19.

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