CSBPI_Site：Multi-Information Sources of Features to RNA Binding Sites Prediction

2021 ◽  
Vol 15 ◽  
Author(s):  
Lichao Zhang ◽  
Zihong Huang ◽  
Liang Kong
Keyword(s):  
Computational Model ◽  
Binding Sites ◽  
Noncoding Rna ◽  
Computational Models ◽  
Information Sources ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Gradient Boosting ◽  
Position Information ◽  
Rna Binding Sites

Background: RNA-binding proteins establish posttranscriptional gene regulation by coordinating the maturation, editing, transport, stability, and translation of cellular RNAs. The immunoprecipitation experiments could identify interaction between RNA and proteins, but they are limited due to the experimental environment and material. Therefore, it is essential to construct computational models to identify the function sites. Objective: Although some computational methods have been proposed to predict RNA binding sites, the accuracy could be further improved. Moreover, it is necessary to construct a dataset with more samples to design a reliable model. Here we present a computational model based on multi-information sources to identify RNA binding sites. Method: We construct an accurate computational model named CSBPI_Site, based on xtreme gradient boosting. The specifically designed 15-dimensional feature vector captures four types of information (chemical shift, chemical bond, chemical properties and position information). Results: The satisfied accuracy of 0.86 and AUC of 0.89 were obtained by leave-one-out cross validation. Meanwhile, the accuracies were slightly different (range from 0.83 to 0.85) among three classifiers algorithm, which showed the novel features are stable and fit to multiple classifiers. These results showed that the proposed method is effective and robust for noncoding RNA binding sites identification. Conclusion: Our method based on multi-information sources is effective to represent the binding sites information among ncRNAs. The satisfied prediction results of Diels-Alder riboz-yme based on CSBPI_Site indicates that our model is valuable to identify the function site.

scholarly journals A conserved abundant cytoplasmic long noncoding RNA modulates repression by Pumilio proteins in human cells

2015 ◽  
Author(s):  
Ailone Tichon ◽  
Noa Gil ◽  
Yoav Lubelsky ◽  
Tal Havkin Solomon ◽  
Doron Lemze ◽  
...  
Keyword(s):  
Cell Division ◽  
Human Genome ◽  
Chromosome Segregation ◽  
Binding Sites ◽  
Long Noncoding Rna ◽  
Noncoding Rna ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Mrna Levels ◽  
Pumilio Proteins

AbstractThousands of long noncoding RNA (lncRNA) genes are encoded in the human genome, and hundreds of them are evolutionary conserved, but their functions and modes of action remain largely obscure. Particularly enigmatic lncRNAs are those that are exported to the cytoplasm, including NORAD – an abundant and highly conserved cytoplasmic lncRNA. Most of the sequence of NORAD is comprised of repetitive units that together contain at least 17 functional binding sites for the two Pumilio homologs in mammals. Through binding to PUM1 and PUM2, NORAD modulates the mRNA levels of their targets, which are enriched for genes involved in chromosome segregation during cell division. Our results suggest that some cytoplasmic lncRNAs function by modulating the activities of RNA binding proteins, an activity which positions them at key junctions of cellular signaling pathways.

Dissection and prediction of RNA-binding sites on proteins

2010 ◽  
Vol 1 (5-6) ◽  
pp. 345-355 ◽  
Author(s):  
Laura Pérez-Cano ◽  
Juan Fernández-Recio
Keyword(s):  
Binding Sites ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Large Variability ◽  
Regulatory Processes ◽  
Points Of View ◽  
Living Organisms ◽  
Positively Charged ◽  
Rna Binding Sites

AbstractRNA-binding proteins are involved in many important regulatory processes in cells and their study is essential for a complete understanding of living organisms. They show a large variability from both structural and functional points of view. However, several recent studies performed on protein-RNA crystal structures have revealed interesting common properties. RNA-binding sites usually constitute patches of positively charged or polar residues that make most of the specific and non-specific contacts with RNA. Negatively charged or aliphatic residues are less frequent at protein-RNA interfaces, although they can also be found either forming aliphatic and positive-negative pairs in protein RNA-binding sites or contacting RNA through their main chains. Aromatic residues found within these interfaces are usually involved in specific base recognition at RNA single-strand regions. This specific recognition, in combination with structural complementarity, represents the key source for specificity in protein-RNA association. From all this knowledge, a variety of computational methods for prediction of RNA-binding sites have been developed based either on protein sequence or on protein structure. Some reported methods are really successful in the identification of RNA-binding proteins or the prediction of RNA-binding sites. Given the growing interest in the field, all these studies and prediction methods will undoubtedly contribute to the identification and comprehension of protein-RNA interactions.

scholarly journals The snoGloBe interaction predictor enables a broader study of box C/D snoRNA functions and mechanisms

2021 ◽  
Author(s):  
Gabrielle Deschamps-Francoeur ◽  
Sonia Couture ◽  
Sherif Abou Elela ◽  
Michelle S Scott
Keyword(s):  
Noncoding Rna ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Regulatory Elements ◽  
Gradient Boosting ◽  
Target Sequence ◽  
Messenger Rnas ◽  
Small Nuclear Rna ◽  
Transcript Stability ◽  
Rna Interaction

Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of noncoding RNA known to serve as guides for the site-specific 2'-O-ribose methylation of ribosomal RNAs and the U6 small nuclear RNA, through direct base pairing with the target. In recent years however, several examples of box C/D snoRNAs regulating different levels of gene expression including transcript stability and splicing have been reported. These regulatory interactions typically require direct binding of the target but do not always involve the guide region. Supporting these new box C/D snoRNA functions, high-throughput RNA-RNA interaction datasets detect many interactions between box C/D snoRNAs and messenger RNAs. To facilitate the study of box C/D snoRNA functionality, we created snoGloBe, a box C/D snoRNA machine learning target predictor based on a gradient boosting classifier and considering snoRNA and target sequence and position as well as target type. SnoGloBe convincingly outperforms general RNA duplex predictors and PLEXY, the only box C/D snoRNA-specific target predictor available. The study of snoGloBe human transcriptome-wide predictions identifies enrichment in snoRNA interactions in exons and on exon-intron junctions. Some specific snoRNAs are predicted to target groups of functionally-related transcripts on common regulatory elements and the exact position of the predicted targets strongly overlaps binding sites of RNA-binding proteins involved in relevant molecular functions. SnoGloBe was also applied to predicting interactions between human box C/D snoRNAs and the SARS-CoV-2 transcriptome, identifying known and novel interactions. Overall, snoGloBe is a timely new tool that will accelerate our understanding of C/D snoRNA targets and function.

The Therapeutic Potential and Role of miRNA, lncRNA, and circRNA in Osteoarthritis

2019 ◽  
Vol 19 (4) ◽  
pp. 255-263 ◽  
Author(s):  
Yuangang Wu ◽  
Xiaoxi Lu ◽  
Bin Shen ◽  
Yi Zeng
Keyword(s):  
Gene Expression ◽  
Gene Therapy ◽  
Extracellular Matrix ◽  
Inflammatory Reaction ◽  
Noncoding Rna ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Protein Translation ◽  
Cochrane Library

Background: Osteoarthritis (OA) is a disease characterized by progressive degeneration, joint hyperplasia, narrowing of joint spaces, and extracellular matrix metabolism. Recent studies have shown that the pathogenesis of OA may be related to non-coding RNA, and its pathological mechanism may be an effective way to reduce OA. Objective: The purpose of this review was to investigate the recent progress of miRNA, long noncoding RNA (lncRNA) and circular RNA (circRNA) in gene therapy of OA, discussing the effects of this RNA on gene expression, inflammatory reaction, apoptosis and extracellular matrix in OA. Methods: The following electronic databases were searched, including PubMed, EMBASE, Web of Science, and the Cochrane Library, for published studies involving the miRNA, lncRNA, and circRNA in OA. The outcomes included the gene expression, inflammatory reaction, apoptosis, and extracellular matrix. Results and Discussion: With the development of technology, miRNA, lncRNA, and circRNA have been found in many diseases. More importantly, recent studies have found that RNA interacts with RNA-binding proteins to regulate gene transcription and protein translation, and is involved in various pathological processes of OA, thus becoming a potential therapy for OA. Conclusion: In this paper, we briefly introduced the role of miRNA, lncRNA, and circRNA in the occurrence and development of OA and as a new target for gene therapy.

scholarly journals Mapping of In Vivo RNA-Binding Sites by Ultraviolet (UV)-Cross-Linking Immunoprecipitation (CLIP)

2018 ◽  
Vol 2018 (12) ◽  
pp. pdb.top097931 ◽  
Author(s):  
Jennifer C. Darnell ◽  
Aldo Mele ◽  
Ka Ying Sharon Hung ◽  
Robert B. Darnell
Keyword(s):  
Binding Sites ◽  
Rna Binding ◽  
Cross Linking ◽  
Rna Binding Sites

scholarly journals Predicting RNA-binding sites of proteins using support vector machines and evolutionary information

2008 ◽  
Vol 9 (Suppl 12) ◽  
pp. S6 ◽  
Author(s):  
Cheng-Wei Cheng ◽  
Emily Su ◽  
Jenn-Kang Hwang ◽  
Ting-Yi Sung ◽  
Wen-Lian Hsu
Keyword(s):  
Support Vector Machines ◽  
Binding Sites ◽  
Rna Binding ◽  
Evolutionary Information ◽  
Support Vector ◽  
Vector Machines ◽  
Rna Binding Sites

scholarly journals SSMART: Sequence-structure motif identification for RNA-binding proteins

2018 ◽  
Author(s):  
Alina Munteanu ◽  
Neelanjan Mukherjee ◽  
Uwe Ohler
Keyword(s):  
Binding Sites ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Sequence Motif ◽  
Primary Sequence ◽  
Sequence Structure ◽  
Rna Targets

AbstractMotivationRNA-binding proteins (RBPs) regulate every aspect of RNA metabolism and function. There are hundreds of RBPs encoded in the eukaryotic genomes, and each recognize its RNA targets through a specific mixture of RNA sequence and structure properties. For most RBPs, however, only a primary sequence motif has been determined, while the structure of the binding sites is uncharacterized.ResultsWe developed SSMART, an RNA motif finder that simultaneously models the primary sequence and the structural properties of the RNA targets sites. The sequence-structure motifs are represented as consensus strings over a degenerate alphabet, extending the IUPAC codes for nucleotides to account for secondary structure preferences. Evaluation on synthetic data showed that SSMART is able to recover both sequence and structure motifs implanted into 3‘UTR-like sequences, for various degrees of structured/unstructured binding sites. In addition, we successfully used SSMART on high-throughput in vivo and in vitro data, showing that we not only recover the known sequence motif, but also gain insight into the structural preferences of the RBP.AvailabilitySSMART is freely available at https://ohlerlab.mdc-berlin.de/software/SSMART_137/[email protected]

scholarly journals Genomic and cDNA selection-amplification identifies transcriptome-wide binding sites for the Drosophila protein sex-lethal

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0250592
Author(s):  
Hiren Banerjee ◽  
Ravinder Singh
Keyword(s):  
Binding Sites ◽  
Binding Proteins ◽  
Rna Binding ◽  
Developmental Stages ◽  
Rna Binding Proteins ◽  
Systematic Analysis ◽  
Downstream Targets ◽  
Drosophila Protein ◽  
Sex Lethal ◽  
Female Specific

Background Downstream targets for a large number of RNA-binding proteins remain to be identified. The Drosophila master sex-switch protein Sex-lethal (SXL) is an RNA-binding protein that controls splicing, polyadenylation, or translation of certain mRNAs to mediate female-specific sexual differentiation. Whereas some targets of SXL are known, previous studies indicate that additional targets of SXL have escaped genetic screens. Methodology/Principal findings Here, we have used an alternative molecular approach of GEnomic Selective Enrichment of Ligands by Exponential enrichment (GESELEX) using both the genomic DNA and cDNA pools from several Drosophila developmental stages to identify new potential targets of SXL. Our systematic analysis provides a comprehensive view of the Drosophila transcriptome for potential SXL-binding sites. Conclusion/Significance We have successfully identified new SXL-binding sites in the Drosophila transcriptome. We discuss the significance of our analysis and that the newly identified binding sites and sequences could serve as a useful resource for the research community. This approach should also be applicable to other RNA-binding proteins for which downstream targets are unknown.

Sign in / Sign up

Export Citation Format

Share Document