scholarly journals Post-transcriptionally impaired de novo mutations contribute to the genetic etiology of four neuropsychiatric disorders

2017 ◽  
Author(s):  
Fengbiao Mao ◽  
Lu Wang ◽  
Xiaolu Zhao ◽  
Zhongshan Li ◽  
Luoyuan Xiao ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Rna Binding ◽  
De Novo ◽  
Rna Binding Proteins ◽  
Genetic Disorders ◽  
Interaction Network ◽  
Neuropsychiatric Disorders ◽  
Protein Protein Interactions ◽  
De Novo Mutations ◽  
Coding Region

AbstractWhile deleterious de novo mutations (DNMs) in coding region conferring risk in neuropsychiatric disorders have been revealed by next-generation sequencing, the role of DNMs involved in post-transcriptional regulation in pathogenesis of these disorders remains to be elucidated. Here, we identified 1,736 post-transcriptionally impaired DNMs (piDNMs), and prioritized 1,482 candidate genes in four neuropsychiatric disorders from 7,748 families. Our results revealed higher prevalence of piDNMs in the probands than in controls (P = 8.19×10−17), and piDNM-harboring genes were enriched for epigenetic modifications and neuronal or synaptic functions. Moreover, we identified 86 piDNM-containing genes forming convergent co-expression modules and intensive protein-protein interactions in at least two neuropsychiatric disorders. These cross-disorder genes carrying piDNMs could form interaction network centered on RNA binding proteins, suggesting a shared post-transcriptional etiology underlying these disorders. Our findings illustrate the significant contribution of piDNMs to four neuropsychiatric disorders, and lay emphasis on combining functional and network-based evidences to identify regulatory causes of genetic disorders.

scholarly journals RNA regulons and the RNA-protein interaction network

2012 ◽  
Vol 3 (5) ◽  
pp. 403-414 ◽  
Author(s):  
Jochen Imig ◽  
Alexander Kanitz ◽  
André P. Gerber
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Network ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Interaction Network ◽  
Coordinated Control ◽  
Non Coding Rnas ◽  
Rna Interaction

AbstractThe development of genome-wide analysis tools has prompted global investigation of the gene expression program, revealing highly coordinated control mechanisms that ensure proper spatiotemporal activity of a cell’s macromolecular components. With respect to the regulation of RNA transcripts, the concept of RNA regulons, which – by analogy with DNA regulons in bacteria – refers to the coordinated control of functionally related RNA molecules, has emerged as a unifying theory that describes the logic of regulatory RNA-protein interactions in eukaryotes. Hundreds of RNA-binding proteins and small non-coding RNAs, such as microRNAs, bind to distinct elements in target RNAs, thereby exerting specific and concerted control over posttranscriptional events. In this review, we discuss recent reports committed to systematically explore the RNA-protein interaction network and outline some of the principles and recurring features of RNA regulons: the coordination of functionally related mRNAs through RNA-binding proteins or non-coding RNAs, the modular structure of its components, and the dynamic rewiring of RNA-protein interactions upon exposure to internal or external stimuli. We also summarize evidence for robust combinatorial control of mRNAs, which could determine the ultimate fate of each mRNA molecule in a cell. Finally, the compilation and integration of global protein-RNA interaction data has yielded first insights into network structures and provided the hypothesis that RNA regulons may, in part, constitute noise ‘buffers’ to handle stochasticity in cellular transcription.

scholarly journals miR-503 represses CUG-binding protein 1 translation by recruiting CUGBP1 mRNA to processing bodies

2012 ◽  
Vol 23 (1) ◽  
pp. 151-162 ◽  
Author(s):  
Yu-Hong Cui ◽  
Lan Xiao ◽  
Jaladanki N. Rao ◽  
Tongtong Zou ◽  
Lan Liu ◽  
...  
Keyword(s):  
Rna Binding ◽  
De Novo ◽  
Rna Binding Proteins ◽  
Binding Protein ◽  
Mrna Levels ◽  
Intestinal Epithelial ◽  
Coding Region ◽  
Processing Bodies ◽  
Target Mrnas ◽  
Repressive Effect

microRNAs (miRNAs) and RNA-binding proteins (RBPs) jointly regulate gene expression at the posttranscriptional level and are involved in many aspects of cellular functions. The RBP CUG-binding protein 1 (CUGBP1) destabilizes and represses the translation of several target mRNAs, but the exact mechanism that regulates CUGBP1 abundance remains elusive. In this paper, we show that miR-503, computationally predicted to associate with three sites of the CUGBP1 mRNA, represses CUGBP1 expression. Overexpression of an miR-503 precursor (pre-miR-503) reduced the de novo synthesis of CUGBP1 protein, whereas inhibiting miR-503 by using an antisense RNA (antagomir) enhanced CUGBP1 biosynthesis and elevated its abundance; neither intervention changed total CUGBP1 mRNA levels. Studies using heterologous reporter constructs revealed a greater repressive effect of miR-503 through the CUGBP1 coding region sites than through the single CUGBP1 3′-untranslated region target site. CUGBP1 mRNA levels in processing bodies (P-bodies) increased in cells transfected with pre-miR-503, while silencing P-body resident proteins Ago2, RCK, or LSm4 decreased miR-503–mediated repression of CUGBP1 expression. Decreasing the levels of cellular polyamines reduced endogenous miR-503 levels and promoted CUGBP1 expression, an effect that was prevented by ectopic miR-503 overexpression. Repression of CUGBP1 by miR-503 in turn altered the expression of CUGBP1 target mRNAs and thus increased the sensitivity of intestinal epithelial cells to apoptosis. These findings identify miR-503 as both a novel regulator of CUGBP1 expression and a modulator of intestinal epithelial homoeostasis.

scholarly journals Targeting RNA Binding Proteins Involved in Neurodegeneration

2013 ◽  
Vol 18 (9) ◽  
pp. 967-983 ◽  
Author(s):  
Maurizio Romano ◽  
Emanuele Buratti
Keyword(s):  
Protein Interactions ◽  
Rna Processing ◽  
Noncoding Rna ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Correct Identification ◽  
Protein Protein Interactions ◽  
Aggregation Processes ◽  
Cellular Pathways ◽  
Screening Approaches

Dysfunctions at the level of RNA processing have recently been shown to play a fundamental role in the pathogenesis of many neurodegenerative diseases. Several proteins responsible for these dysfunctions (TDP-43, FUS/TLS, and hnRNP A/Bs) belong to the nuclear class of heterogeneous ribonucleoproteins (hnRNPs) that predominantly function as general regulators of both coding and noncoding RNA metabolism. The discovery of the importance of these factors in mediating neuronal death has represented a major paradigmatic shift in our understanding of neurodegenerative processes. As a result, these discoveries have also opened the way toward novel biomolecular screening approaches in our search for therapeutic options. One of the major hurdles in this search is represented by the correct identification of the most promising targets to be prioritized. These may include aberrant aggregation processes, protein-protein interactions, RNA-protein interactions, or specific cellular pathways altered by disease. In this review, we discuss these four major options together with their various advantages and drawbacks.

scholarly journals iSUMO - integrative prediction of functionally relevant SUMOylation events

2016 ◽  
Author(s):  
Xiaotong Yao ◽  
Shuvadeep Maity ◽  
Shashank Gandhi ◽  
Marcin Imielenski ◽  
Christine Vogel
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
False Positive Rate ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Positive Rate ◽  
Protein Nucleic Acid ◽  
Scale Experiment

AbstractPost-translational modifications by the Small Ubiquitin-like Modifier (SUMO) are essential for diverse cellular functions. Large-scale experiment and sequence-based predictions have identified thousands of SUMOylated proteins. However, the overlap between the datasets is small, suggesting many false positives with low functional relevance. Therefore, we integrated ~800 sequence features and protein characteristics such as cellular function and protein-protein interactions in a machine learning approach to score likely functional SUMOylation events (iSUMO). iSUMO is trained on a total of 24 large-scale datasets, and it predicts 2,291 and 706 SUMO targets in human and yeast, respectively. These estimates are five times higher than what existing sequence-based tools predict at the same 5% false positive rate. Protein-protein and protein-nucleic acid interactions are highly predictive of protein SUMOylation, supporting a role of the modification in protein complex formation. We note the marked prevalence of SUMOylation amongst RNA-binding proteins. We validate iSUMO predictions by experimental or other evidence. iSUMO therefore represents a comprehensive tool to identify high-confidence, functional SUMOylation events for human and yeast.

scholarly journals De NovoAssembly and Characterization ofSophora japonicaTranscriptome Using RNA-seq

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Liucun Zhu ◽  
Ying Zhang ◽  
Wenna Guo ◽  
Xin-Jian Xu ◽  
Qiang Wang
Keyword(s):  
Protein Interactions ◽  
De Novo ◽  
Average Length ◽  
Genomic Analysis ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Gene Expressions ◽  
Sophora Japonica ◽  
Protein Protein Interaction ◽  
Functional Genomic Analysis

Sophora japonicaLinn (Chinese Scholar Tree) is a shrub species belonging to the subfamily Faboideae of the pea family Fabaceae. In this study, RNA sequencing ofS. japonicatranscriptome was performed to produce large expression datasets for functional genomic analysis. Approximate 86.1 million high-quality clean reads were generated and assembledde novointo 143010 unique transcripts and 57614 unigenes. The average length of unigenes was 901 bps with an N50 of 545 bps. Four public databases, including the NCBI nonredundant protein (NR), Swiss-Prot, Kyoto Encyclopedia of Genes and Genomes (KEGG), and the Cluster of Orthologous Groups (COG), were used to annotate unigenes through NCBI BLAST procedure. A total of 27541 of 57614 unigenes (47.8%) were annotated for gene descriptions, conserved protein domains, or gene ontology. Moreover, an interaction network of unigenes inS. japonicawas predicted based on known protein-protein interactions of putative orthologs of well-studied plant genomes. The transcriptome data ofS. japonicareported here represents first genome-scale investigation of gene expressions in Faboideae plants. We expect that our study will provide a useful resource for further studies on gene expression, genomics, functional genomics, and protein-protein interaction inS. japonica.

scholarly journals De novo prediction of RNA-protein interactions with Graph Neural Networks

2021 ◽  
Author(s):  
Viplove Arora ◽  
Guido Sanguinetti
Keyword(s):  
Neural Networks ◽  
Protein Interactions ◽  
Large Scale ◽  
Rna Binding ◽  
De Novo ◽  
Rna Binding Proteins ◽  
Large Data ◽  
Data Sets ◽  
Graph Neural Networks ◽  
Post Transcriptional Regulation

RNA-binding proteins (RBPs) are key co- and post-transcriptional regulators of gene expression, playing a crucial role in many biological processes. Experimental methods like CLIP-seq have enabled the identification of transcriptome-wide RNA-protein interactions for select proteins, however the time and resource intensive nature of these technologies call for the development of computational methods to complement their predictions. Here we leverage recent, large-scale CLIP-seq experiments to construct a de novo predictor of RNA-protein interactions based on graph neural networks (GNN). We show that the GNN method allows not only to predict missing links in a RNA-protein network, but to predict the entire complement of targets of previously unassayed proteins, and even to reconstruct the entire network of RNA-protein interactions in different conditions based on minimal information. Our results demonstrate the potential of machine learning methods to extract useful information on post-transcriptional regulation from large data sets.

scholarly journals rec-Y2H matrix screening reveals a vast potential for direct protein-protein interactions among RNA binding proteins

2020 ◽  
Author(s):  
Benjamin Lang ◽  
Jae-Seong Yang ◽  
Mireia Garriga-Canut ◽  
Silvia Speroni ◽  
Maria Gili ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Interaction Networks ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Binding Interaction ◽  
Transcriptional Gene Regulation

AbstractRNA-binding proteins (RBPs) are crucial factors of post-transcriptional gene regulation and their modes of action are intensely investigated. At the center of attention are RNA motifs that guide where RBPs bind. However, sequence motifs are often poor predictors of RBP-RNA interactions in vivo. It is hence believed that many RBPs recognize RNAs as complexes, to increase specificity and regulatory possibilities. To probe the potential for complex formation among RBPs, we assembled a library of 978 mammalian RBPs and used rec-Y2H screening to detect direct interactions between RBPs, sampling > 600 K interactions. We discovered 1994 new interactions and demonstrate that interacting RBPs bind RNAs adjacently in vivo. We further find that the mRNA binding region and motif preferences of RBPs can deviate, depending on their adjacently binding interaction partners. Finally, we reveal novel RBP interaction networks among major RNA processing steps and show that splicing impairing RBP mutations observed in cancer rewire spliceosomal interaction networks.Graphical abstract

scholarly journals Interactions between the double-stranded RNA-binding proteins TRBP and PACT define the Medipal domain that mediates protein-protein interactions

RNA Biology ◽  
2008 ◽  
Vol 5 (2) ◽  
pp. 92-103 ◽  
Author(s):  
Ghislaine Laraki ◽  
Guerline Clerzius ◽  
Aïcha Daher ◽  
Carlos Melendez-Peña ◽  
Sylvanne Daniels ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Protein Protein Interactions ◽  
Double Stranded Rna

scholarly journals Plant Ribonuclease J: An Essential Player in Maintaining Chloroplast RNA Quality Control for Gene Expression

Plants ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 334
Author(s):  
Amber M. Hotto ◽  
David B. Stern ◽  
Gadi Schuster
Keyword(s):  
Gene Expression ◽  
Quality Control ◽  
Protein Interactions ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Land Plant ◽  
Protein Protein Interactions ◽  
Rna Quality ◽  
Rna Quality Control ◽  
Chloroplast Rna

RNA quality control is an indispensable but poorly understood process that enables organisms to distinguish functional RNAs from nonfunctional or inhibitory ones. In chloroplasts, whose gene expression activities are required for photosynthesis, retrograde signaling, and plant development, RNA quality control is of paramount importance, as transcription is relatively unregulated. The functional RNA population is distilled from this initial transcriptome by a combination of RNA-binding proteins and ribonucleases. One of the key enzymes is RNase J, a 5′→3′ exoribonuclease and an endoribonuclease that has been shown to trim 5′ RNA termini and eliminate deleterious antisense RNA. In the absence of RNase J, embryo development cannot be completed. Land plant RNase J contains a highly conserved C-terminal domain that is found in GT-1 DNA-binding transcription factors and is not present in its bacterial, archaeal, and algal counterparts. The GT-1 domain may confer specificity through DNA and/or RNA binding and/or protein–protein interactions and thus be an element in the mechanisms that identify target transcripts among diverse RNA populations. Further understanding of chloroplast RNA quality control relies on discovering how RNase J is regulated and how its specificity is imparted.

scholarly journals The increasing diversity of functions attributed to the SAFB family of RNA-/DNA-binding proteins

2016 ◽  
Vol 473 (23) ◽  
pp. 4271-4288 ◽  
Author(s):  
Michael Norman ◽  
Caroline Rivers ◽  
Youn-Bok Lee ◽  
Jalilah Idris ◽  
James Uney
Keyword(s):  
Protein Interactions ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Cellular Stress Response ◽  
Regulatory Rna ◽  
Protein Protein Interactions ◽  
Attachment Region ◽  
Dna Elements ◽  
Scaffold Attachment Region

RNA-binding proteins play a central role in cellular metabolism by orchestrating the complex interactions of coding, structural and regulatory RNA species. The SAFB (scaffold attachment factor B) proteins (SAFB1, SAFB2 and SAFB-like transcriptional modulator, SLTM), which are highly conserved evolutionarily, were first identified on the basis of their ability to bind scaffold attachment region DNA elements, but attention has subsequently shifted to their RNA-binding and protein–protein interactions. Initial studies identified the involvement of these proteins in the cellular stress response and other aspects of gene regulation. More recently, the multifunctional capabilities of SAFB proteins have shown that they play crucial roles in DNA repair, processing of mRNA and regulatory RNA, as well as in interaction with chromatin-modifying complexes. With the advent of new techniques for identifying RNA-binding sites, enumeration of individual RNA targets has now begun. This review aims to summarise what is currently known about the functions of SAFB proteins.

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