RAID: a comprehensive resource for human RNA-associated (RNA–RNA/RNA–protein) interaction

Science.gov (United States)

Zhang, Xiaomeng; Wu, Deng; Chen, Liqun; Li, Xiang; Yang, Jinxurong; Fan, Dandan; Dong, Tingting; Liu, Mingyue; Tan, Puwen; Xu, Jintian; Yi, Ying; Wang, Yuting; Zou, Hua; Hu, Yongfei; Fan, Kaili; Kang, Juanjuan; Huang, Yan; Miao, Zhengqiang; Bi, Miaoman; Jin, Nana; Li, Kongning; Li, Xia; Xu, Jianzhen; Wang, Dong

2014-01-01

Transcriptomic analyses have revealed an unexpected complexity in the eukaryote transcriptome, which includes not only protein-coding transcripts but also an expanding catalog of noncoding RNAs (ncRNAs). Diverse coding and noncoding RNAs (ncRNAs) perform functions through interaction with each other in various cellular processes. In this project, we have developed RAID (http://www.rna-society.org/raid), an RNA-associated (RNA–RNA/RNA–protein) interaction database. RAID intends to provide the scientific community with all-in-one resources for efficient browsing and extraction of the RNA-associated interactions in human. This version of RAID contains more than 6100 RNA-associated interactions obtained by manually reviewing more than 2100 published papers, including 4493 RNA–RNA interactions and 1619 RNA–protein interactions. Each entry contains detailed information on an RNA-associated interaction, including RAID ID, RNA/protein symbol, RNA/protein categories, validated method, expressing tissue, literature references (Pubmed IDs), and detailed functional description. Users can query, browse, analyze, and manipulate RNA-associated (RNA–RNA/RNA–protein) interaction. RAID provides a comprehensive resource of human RNA-associated (RNA–RNA/RNA–protein) interaction network. Furthermore, this resource will help in uncovering the generic organizing principles of cellular function network. PMID:24803509

On RNA-RNA interaction structures of fixed topological genus.

Science.gov (United States)

Fu, Benjamin M M; Han, Hillary S W; Reidys, Christian M

2015-04-01

Interacting RNA complexes are studied via bicellular maps using a filtration via their topological genus. Our main result is a new bijection for RNA-RNA interaction structures and a linear time uniform sampling algorithm for RNA complexes of fixed topological genus. The bijection allows to either reduce the topological genus of a bicellular map directly, or to lose connectivity by decomposing the complex into a pair of single stranded RNA structures. Our main result is proved bijectively. It provides an explicit algorithm of how to rewire the corresponding complexes and an unambiguous decomposition grammar. Using the concept of genus induction, we construct bicellular maps of fixed topological genus g uniformly in linear time. We present various statistics on these topological RNA complexes and compare our findings with biological complexes. Furthermore we show how to construct loop-energy based complexes using our decomposition grammar. Copyright © 2015 Elsevier Inc. All rights reserved.

Accurate microRNA target prediction correlates with protein repression levels

Directory of Open Access Journals (Sweden)

Simossis Victor A

2009-09-01

Full Text Available Abstract Background MicroRNAs are small endogenously expressed non-coding RNA molecules that regulate target gene expression through translation repression or messenger RNA degradation. MicroRNA regulation is performed through pairing of the microRNA to sites in the messenger RNA of protein coding genes. Since experimental identification of miRNA target genes poses difficulties, computational microRNA target prediction is one of the key means in deciphering the role of microRNAs in development and disease. Results DIANA-microT 3.0 is an algorithm for microRNA target prediction which is based on several parameters calculated individually for each microRNA and combines conserved and non-conserved microRNA recognition elements into a final prediction score, which correlates with protein production fold change. Specifically, for each predicted interaction the program reports a signal to noise ratio and a precision score which can be used as an indication of the false positive rate of the prediction. Conclusion Recently, several computational target prediction programs were benchmarked based on a set of microRNA target genes identified by the pSILAC method. In this assessment DIANA-microT 3.0 was found to achieve the highest precision among the most widely used microRNA target prediction programs reaching approximately 66%. The DIANA-microT 3.0 prediction results are available online in a user friendly web server at http://www.microrna.gr/microT

On topological RNA interaction structures.

Science.gov (United States)

Qin, Jing; Reidys, Christian M

2013-07-01

Recently a folding algorithm of topological RNA pseudoknot structures was presented in Reidys et al. (2011). This algorithm folds single-stranded γ-structures, that is, RNA structures composed by distinct motifs of bounded topological genus. In this article, we set the theoretical foundations for the folding of the two backbone analogues of γ structures: the RNA γ-interaction structures. These are RNA-RNA interaction structures that are constructed by a finite number of building blocks over two backbones having genus at most γ. Combinatorial properties of γ-interaction structures are of practical interest since they have direct implications for the folding of topological interaction structures. We compute the generating function of γ-interaction structures and show that it is algebraic, which implies that the numbers of interaction structures can be computed recursively. We obtain simple asymptotic formulas for 0- and 1-interaction structures. The simplest class of interaction structures are the 0-interaction structures, which represent the two backbone analogues of secondary structures.

Prediction of RNA-Binding Proteins by Voting Systems

Directory of Open Access Journals (Sweden)

C. R. Peng

2011-01-01

Full Text Available It is important to identify which proteins can interact with RNA for the purpose of protein annotation, since interactions between RNA and proteins influence the structure of the ribosome and play important roles in gene expression. This paper tries to identify proteins that can interact with RNA using voting systems. Firstly through Weka, 34 learning algorithms are chosen for investigation. Then simple majority voting system (SMVS is used for the prediction of RNA-binding proteins, achieving average ACC (overall prediction accuracy value of 79.72% and MCC (Matthew’s correlation coefficient value of 59.77% for the independent testing dataset. Then mRMR (minimum redundancy maximum relevance strategy is used, which is transferred into algorithm selection. In addition, the MCC value of each classifier is assigned to be the weight of the classifier’s vote. As a result, best average MCC values are attained when 22 algorithms are selected and integrated through weighted votes, which are 64.70% for the independent testing dataset, and ACC value is 82.04% at this moment.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

Science.gov (United States)

Boniecki, Michal J; Lach, Grzegorz; Dawson, Wayne K; Tomala, Konrad; Lukasz, Pawel; Soltysinski, Tomasz; Rother, Kristian M; Bujnicki, Janusz M

2016-04-20

RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Free energy minimization to predict RNA secondary structures and computational RNA design.

Science.gov (United States)

Churkin, Alexander; Weinbrand, Lina; Barash, Danny

2015-01-01

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Topology of RNA-RNA interaction structures

DEFF Research Database (Denmark)

Andersen, Jørgen Ellegaard; Huang, Fenix Wenda; Penner, Robert

2012-01-01

Abstract The topological filtration of interacting RNA complexes is studied, and the role is analyzed of certain diagrams called irreducible shadows, which form suitable building blocks for more general structures. We prove that, for two interacting RNAs, called interaction structures, there exist...

Heart structure-specific transcriptomic atlas reveals conserved microRNA-mRNA interactions.

Science.gov (United States)

Vacchi-Suzzi, Caterina; Hahne, Florian; Scheubel, Philippe; Marcellin, Magali; Dubost, Valerie; Westphal, Magdalena; Boeglen, Catherine; Büchmann-Møller, Stine; Cheung, Ming Sin; Cordier, André; De Benedetto, Christopher; Deurinck, Mark; Frei, Moritz; Moulin, Pierre; Oakeley, Edward; Grenet, Olivier; Grevot, Armelle; Stull, Robert; Theil, Diethilde; Moggs, Jonathan G; Marrer, Estelle; Couttet, Philippe

2013-01-01

MicroRNAs are short non-coding RNAs that regulate gene expression at the post-transcriptional level and play key roles in heart development and cardiovascular diseases. Here, we have characterized the expression and distribution of microRNAs across eight cardiac structures (left and right ventricles, apex, papillary muscle, septum, left and right atrium and valves) in rat, Beagle dog and cynomolgus monkey using microRNA sequencing. Conserved microRNA signatures enriched in specific heart structures across these species were identified for cardiac valve (miR-let-7c, miR-125b, miR-127, miR-199a-3p, miR-204, miR-320, miR-99b, miR-328 and miR-744) and myocardium (miR-1, miR-133b, miR-133a, miR-208b, miR-30e, miR-499-5p, miR-30e*). The relative abundance of myocardium-enriched (miR-1) and valve-enriched (miR-125b-5p and miR-204) microRNAs was confirmed using in situ hybridization. MicroRNA-mRNA interactions potentially relevant for cardiac functions were explored using anti-correlation expression analysis and microRNA target prediction algorithms. Interactions between miR-1/Timp3, miR-125b/Rbm24, miR-204/Tgfbr2 and miR-208b/Csnk2a2 were identified and experimentally investigated in human pulmonary smooth muscle cells and luciferase reporter assays. In conclusion, we have generated a high-resolution heart structure-specific mRNA/microRNA expression atlas for three mammalian species that provides a novel resource for investigating novel microRNA regulatory circuits involved in cardiac molecular physiopathology.

Heart structure-specific transcriptomic atlas reveals conserved microRNA-mRNA interactions.

Directory of Open Access Journals (Sweden)

Caterina Vacchi-Suzzi

Full Text Available MicroRNAs are short non-coding RNAs that regulate gene expression at the post-transcriptional level and play key roles in heart development and cardiovascular diseases. Here, we have characterized the expression and distribution of microRNAs across eight cardiac structures (left and right ventricles, apex, papillary muscle, septum, left and right atrium and valves in rat, Beagle dog and cynomolgus monkey using microRNA sequencing. Conserved microRNA signatures enriched in specific heart structures across these species were identified for cardiac valve (miR-let-7c, miR-125b, miR-127, miR-199a-3p, miR-204, miR-320, miR-99b, miR-328 and miR-744 and myocardium (miR-1, miR-133b, miR-133a, miR-208b, miR-30e, miR-499-5p, miR-30e*. The relative abundance of myocardium-enriched (miR-1 and valve-enriched (miR-125b-5p and miR-204 microRNAs was confirmed using in situ hybridization. MicroRNA-mRNA interactions potentially relevant for cardiac functions were explored using anti-correlation expression analysis and microRNA target prediction algorithms. Interactions between miR-1/Timp3, miR-125b/Rbm24, miR-204/Tgfbr2 and miR-208b/Csnk2a2 were identified and experimentally investigated in human pulmonary smooth muscle cells and luciferase reporter assays. In conclusion, we have generated a high-resolution heart structure-specific mRNA/microRNA expression atlas for three mammalian species that provides a novel resource for investigating novel microRNA regulatory circuits involved in cardiac molecular physiopathology.

Exploring complex miRNA-mRNA interactions with Bayesian networks by splitting-averaging strategy

Directory of Open Access Journals (Sweden)

Liu Lin

2009-12-01

Full Text Available Abstract Background microRNAs (miRNAs regulate target gene expression by controlling their mRNAs post-transcriptionally. Increasing evidence demonstrates that miRNAs play important roles in various biological processes. However, the functions and precise regulatory mechanisms of most miRNAs remain elusive. Current research suggests that miRNA regulatory modules are complicated, including up-, down-, and mix-regulation for different physiological conditions. Previous computational approaches for discovering miRNA-mRNA interactions focus only on down-regulatory modules. In this work, we present a method to capture complex miRNA-mRNA interactions including all regulatory types between miRNAs and mRNAs. Results We present a method to capture complex miRNA-mRNA interactions using Bayesian network structure learning with splitting-averaging strategy. It is designed to explore all possible miRNA-mRNA interactions by integrating miRNA-targeting information, expression profiles of miRNAs and mRNAs, and sample categories. We also present an analysis of data sets for epithelial and mesenchymal transition (EMT. Our results show that the proposed method identified all possible types of miRNA-mRNA interactions from the data. Many interactions are of tremendous biological significance. Some discoveries have been validated by previous research, for example, the miR-200 family negatively regulates ZEB1 and ZEB2 for EMT. Some are consistent with the literature, such as LOX has wide interactions with the miR-200 family members for EMT. Furthermore, many novel interactions are statistically significant and worthy of validation in the near future. Conclusions This paper presents a new method to explore the complex miRNA-mRNA interactions for different physiological conditions using Bayesian network structure learning with splitting-averaging strategy. The method makes use of heterogeneous data including miRNA-targeting information, expression profiles of miRNAs and

Characteristics and Prediction of RNA Structure

Directory of Open Access Journals (Sweden)

Hengwu Li

2014-01-01

Full Text Available RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is NP-hard. Most RNAs fold during transcription from DNA into RNA through a hierarchical pathway wherein secondary structures form prior to tertiary structures. Real RNA secondary structures often have local instead of global optimization because of kinetic reasons. The performance of RNA structure prediction may be improved by considering dynamic and hierarchical folding mechanisms. This study is a novel report on RNA folding that accords with the golden mean characteristic based on the statistical analysis of the real RNA secondary structures of all 480 sequences from RNA STRAND, which are validated by NMR or X-ray. The length ratios of domains in these sequences are approximately 0.382L, 0.5L, 0.618L, and L, where L is the sequence length. These points are just the important golden sections of sequence. With this characteristic, an algorithm is designed to predict RNA hierarchical structures and simulate RNA folding by dynamically folding RNA structures according to the above golden section points. The sensitivity and number of predicted pseudoknots of our algorithm are better than those of the Mfold, HotKnots, McQfold, ProbKnot, and Lhw-Zhu algorithms. Experimental results reflect the folding rules of RNA from a new angle that is close to natural folding.

Predicting RNA Structure Using Mutual Information

DEFF Research Database (Denmark)

Freyhult, E.; Moulton, V.; Gardner, P. P.

2005-01-01

, to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...... package. Conclusion: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam. Availability: MIfold is freely available from http......Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure...

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

Science.gov (United States)

Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Literature-based condition-specific miRNA-mRNA target prediction.

Directory of Open Access Journals (Sweden)

Minsik Oh

Full Text Available miRNAs are small non-coding RNAs that regulate gene expression by binding to the 3'-UTR of genes. Many recent studies have reported that miRNAs play important biological roles by regulating specific mRNAs or genes. Many sequence-based target prediction algorithms have been developed to predict miRNA targets. However, these methods are not designed for condition-specific target predictions and produce many false positives; thus, expression-based target prediction algorithms have been developed for condition-specific target predictions. A typical strategy to utilize expression data is to leverage the negative control roles of miRNAs on genes. To control false positives, a stringent cutoff value is typically set, but in this case, these methods tend to reject many true target relationships, i.e., false negatives. To overcome these limitations, additional information should be utilized. The literature is probably the best resource that we can utilize. Recent literature mining systems compile millions of articles with experiments designed for specific biological questions, and the systems provide a function to search for specific information. To utilize the literature information, we used a literature mining system, BEST, that automatically extracts information from the literature in PubMed and that allows the user to perform searches of the literature with any English words. By integrating omics data analysis methods and BEST, we developed Context-MMIA, a miRNA-mRNA target prediction method that combines expression data analysis results and the literature information extracted based on the user-specified context. In the pathway enrichment analysis using genes included in the top 200 miRNA-targets, Context-MMIA outperformed the four existing target prediction methods that we tested. In another test on whether prediction methods can re-produce experimentally validated target relationships, Context-MMIA outperformed the four existing target prediction

Shapes of interacting RNA complexes

DEFF Research Database (Denmark)

Fu, Benjamin Mingming; Reidys, Christian

2014-01-01

Shapes of interacting RNA complexes are studied using a filtration via their topological genus. A shape of an RNA complex is obtained by (iteratively) collapsing stacks and eliminating hairpin loops.This shape-projection preserves the topological core of the RNA complex and for fixed topological...... genus there are only finitely many such shapes. Our main result is a new bijection that relates the shapes of RNA complexes with shapes of RNA structures. This allows to compute the shape polynomial of RNA complexes via the shape polynomial of RNA structures. We furthermore present a linear time uniform...... sampling algorithm for shapes of RNA complexes of fixed topological genus....

Using a Specific RNA-Protein Interaction To Quench the Fluorescent RNA Spinach.

Science.gov (United States)

Roszyk, Laura; Kollenda, Sebastian; Hennig, Sven

2017-12-15

RNAs are involved in interaction networks with other biomolecules and are crucial for proper cell function. Yet their biochemical analysis remains challenging. For Förster Resonance Energy Transfer (FRET), a common tool to study such interaction networks, two interacting molecules have to be fluorescently labeled. "Spinach" is a genetically encodable RNA aptamer that starts to fluoresce upon binding of an organic molecule. Therefore, it is a biological fluorophore tag for RNAs. However, spinach has never been used in a FRET assembly before. Here, we describe how spinach is quenched when close to acceptors. We used RNA-DNA hybridization to bring quenchers or red organic dyes in close proximity to spinach. Furthermore, we investigate RNA-protein interactions quantitatively on the example of Pseudomonas aeruginosa phage coat protein 7 (PP7) and its interacting pp7-RNA. We utilize spinach quenching as a fully genetically encodable system even under lysate conditions. Therefore, this work represents a direct method to analyze RNA-protein interactions by quenching the spinach aptamer.

TargetRNA: a tool for predicting targets of small RNA action in bacteria

OpenAIRE

Tjaden, Brian

2008-01-01

Many small RNA (sRNA) genes in bacteria act as posttranscriptional regulators of target messenger RNAs. Here, we present TargetRNA, a web tool for predicting mRNA targets of sRNA action in bacteria. TargetRNA takes as input a genomic sequence that may correspond to an sRNA gene. TargetRNA then uses a dynamic programming algorithm to search each annotated message in a specified genome for mRNAs that evince basepair-binding potential to the input sRNA sequence. Based on the calculated basepair-...

Ensemble-based prediction of RNA secondary structures.

Science.gov (United States)

Aghaeepour, Nima; Hoos, Holger H

2013-04-24

Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

Science.gov (United States)

Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-01

For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

Computational prediction of miRNA genes from small RNA sequencing data

Directory of Open Access Journals (Sweden)

Wenjing eKang

2015-01-01

Full Text Available Next-generation sequencing now for the first time allows researchers to gauge the depth and variation of entire transcriptomes. However, now as rare transcripts can be detected that are present in cells at single copies, more advanced computational tools are needed to accurately annotate and profile them. miRNAs are 22 nucleotide small RNAs (sRNAs that post-transcriptionally reduce the output of protein coding genes. They have established roles in numerous biological processes, including cancers and other diseases. During miRNA biogenesis, the sRNAs are sequentially cleaved from precursor molecules that have a characteristic hairpin RNA structure. The vast majority of new miRNA genes that are discovered are mined from small RNA sequencing (sRNA-seq, which can detect more than a billion RNAs in a single run. However, given that many of the detected RNAs are degradation products from all types of transcripts, the accurate identification of miRNAs remain a non-trivial computational problem. Here we review the tools available to predict animal miRNAs from sRNA sequencing data. We present tools for generalist and specialist use cases, including prediction from massively pooled data or in species without reference genome. We also present wet-lab methods used to validate predicted miRNAs, and approaches to computationally benchmark prediction accuracy. For each tool, we reference validation experiments and benchmarking efforts. Last, we discuss the future of the field.

Measuring RNA-Ligand Interactions with Microscale Thermophoresis.

Science.gov (United States)

Moon, Michelle H; Hilimire, Thomas A; Sanders, Allix M; Schneekloth, John S

2018-01-31

In recent years, there has been dramatic growth in the study of RNA. RNA has gone from being known as an intermediate in the central dogma of molecular biology to a molecule with a large diversity of structure and function that is involved in all aspects of biology. As new functions are rapidly discovered, it has become clear that there is a need for RNA-targeting small molecule probes to investigate RNA biology and clarify the potential for therapeutics based on RNA-small molecule interactions. While a host of techniques exist to measure RNA-small molecule interactions, many of these have drawbacks that make them intractable for routine use and are often not broadly applicable. A newer technology called microscale thermophoresis (MST), which measures the directed migration of a molecule and/or molecule-ligand complex along a temperature gradient, can be used to measure binding affinities using very small amounts of sample. The high sensitivity of this technique enables measurement of affinity constants in the nanomolar and micromolar range. Here, we demonstrate how MST can be used to study a range of biologically relevant RNA interactions, including peptide-RNA interactions, RNA-small molecule interactions, and displacement of an RNA-bound peptide by a small molecule.

RAIN: RNA-protein Association and Interaction Networks

DEFF Research Database (Denmark)

Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

2017-01-01

is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data...

DIANA-microT web server: elucidating microRNA functions through target prediction.

Science.gov (United States)

Maragkakis, M; Reczko, M; Simossis, V A; Alexiou, P; Papadopoulos, G L; Dalamagas, T; Giannopoulos, G; Goumas, G; Koukis, E; Kourtis, K; Vergoulis, T; Koziris, N; Sellis, T; Tsanakas, P; Hatzigeorgiou, A G

2009-07-01

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT.

Predicting protein-binding RNA nucleotides with consideration of binding partners.

Science.gov (United States)

Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

2015-06-01

In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

Science.gov (United States)

Will, Sebastian; Jabbari, Hosna

2016-01-01

RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

Science.gov (United States)

Endoh, Tamaki; Sugimoto, Naoki

2015-08-04

Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

Mapping protein-RNA interactions by RCAP, RNA-cross-linking and peptide fingerprinting.

Science.gov (United States)

Vaughan, Robert C; Kao, C Cheng

2015-01-01

RNA nanotechnology often feature protein RNA complexes. The interaction between proteins and large RNAs are difficult to study using traditional structure-based methods like NMR or X-ray crystallography. RCAP, an approach that uses reversible-cross-linking affinity purification method coupled with mass spectrometry, has been developed to map regions within proteins that contact RNA. This chapter details how RCAP is applied to map protein-RNA contacts within virions.

Disruption of Specific RNA-RNA Interactions in a Double-Stranded RNA Virus Inhibits Genome Packaging and Virus Infectivity.

Science.gov (United States)

Fajardo, Teodoro; Sung, Po-Yu; Roy, Polly

2015-12-01

Bluetongue virus (BTV) causes hemorrhagic disease in economically important livestock. The BTV genome is organized into ten discrete double-stranded RNA molecules (S1-S10) which have been suggested to follow a sequential packaging pathway from smallest to largest segment during virus capsid assembly. To substantiate and extend these studies, we have investigated the RNA sorting and packaging mechanisms with a new experimental approach using inhibitory oligonucleotides. Putative packaging signals present in the 3'untranslated regions of BTV segments were targeted by a number of nuclease resistant oligoribonucleotides (ORNs) and their effects on virus replication in cell culture were assessed. ORNs complementary to the 3' UTR of BTV RNAs significantly inhibited virus replication without affecting protein synthesis. Same ORNs were found to inhibit complex formation when added to a novel RNA-RNA interaction assay which measured the formation of supramolecular complexes between and among different RNA segments. ORNs targeting the 3'UTR of BTV segment 10, the smallest RNA segment, were shown to be the most potent and deletions or substitution mutations of the targeted sequences diminished the RNA complexes and abolished the recovery of viable viruses using reverse genetics. Cell-free capsid assembly/RNA packaging assay also confirmed that the inhibitory ORNs could interfere with RNA packaging and further substitution mutations within the putative RNA packaging sequence have identified the recognition sequence concerned. Exchange of 3'UTR between segments have further demonstrated that RNA recognition was segment specific, most likely acting as part of the secondary structure of the entire genomic segment. Our data confirm that genome packaging in this segmented dsRNA virus occurs via the formation of supramolecular complexes formed by the interaction of specific sequences located in the 3' UTRs. Additionally, the inhibition of packaging in-trans with inhibitory ORNs

Comprehensive characterization of lncRNA-mRNA related ceRNA network across 12 major cancers

Science.gov (United States)

Feng, Li; Li, Feng; Sun, Zeguo; Wu, Tan; Shi, Xinrui; Li, Jing; Li, Xia

2016-01-01

Recent studies indicate that long noncoding RNAs (lncRNAs) can act as competing endogenous RNAs (ceRNAs) to indirectly regulate mRNAs through shared microRNAs, which represents a novel layer of RNA crosstalk and plays critical roles in the development of tumor. However, the global regulation landscape and characterization of these lncRNA related ceRNA crosstalk in cancers is still largely unknown. Here, we systematically characterized the lncRNA related ceRNA interactions across 12 major cancers and the normal physiological states by integrating multidimensional molecule profiles of more than 5000 samples. Our study suggest the large difference of ceRNA regulation between normal and tumor states and the higher similarity across similar tissue origin of tumors. The ceRNA related molecules have more conserved features in tumor networks and they play critical roles in both the normal and tumorigenesis processes. Besides, lncRNAs in the pan-cancer ceRNA network may be potential biomarkers of tumor. By exploring hub lncRNAs, we found that these conserved key lncRNAs dominate variable tumor hallmark processes across pan-cancers. Network dynamic analysis highlights the critical roles of ceRNA regulation in tumorigenesis. By analyzing conserved ceRNA interactions, we found that miRNA mediate ceRNA regulation showed different patterns across pan-cancer; while analyzing the cancer specific ceRNA interactions reveal that lncRNAs synergistically regulated tumor driver genes of cancer hallmarks. Finally, we found that ceRNA modules have the potential to predict patient survival. Overall, our study systematically dissected the lncRNA related ceRNA networks in pan-cancer that shed new light on understanding the molecular mechanism of tumorigenesis. PMID:27580177

Retroviral Gag protein-RNA interactions: Implications for specific genomic RNA packaging and virion assembly.

Science.gov (United States)

Olson, Erik D; Musier-Forsyth, Karin

2018-03-31

Retroviral Gag proteins are responsible for coordinating many aspects of virion assembly. Gag possesses two distinct nucleic acid binding domains, matrix (MA) and nucleocapsid (NC). One of the critical functions of Gag is to specifically recognize, bind, and package the retroviral genomic RNA (gRNA) into assembling virions. Gag interactions with cellular RNAs have also been shown to regulate aspects of assembly. Recent results have shed light on the role of MA and NC domain interactions with nucleic acids, and how they jointly function to ensure packaging of the retroviral gRNA. Here, we will review the literature regarding RNA interactions with NC, MA, as well as overall mechanisms employed by Gag to interact with RNA. The discussion focuses on human immunodeficiency virus type-1, but other retroviruses will also be discussed. A model is presented combining all of the available data summarizing the various factors and layers of selection Gag employs to ensure specific gRNA packaging and correct virion assembly. Copyright © 2018 Elsevier Ltd. All rights reserved.

RNA 3D modules in genome-wide predictions of RNA 2D structure

DEFF Research Database (Denmark)

Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner

2015-01-01

. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D......Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational...... approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution...

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

Science.gov (United States)

Puton, Tomasz; Kozlowski, Lukasz P.; Rother, Kristian M.; Bujnicki, Janusz M.

2013-01-01

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks. PMID:23435231

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction.

Science.gov (United States)

Puton, Tomasz; Kozlowski, Lukasz P; Rother, Kristian M; Bujnicki, Janusz M

2013-04-01

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.

Predicting and Modeling RNA Architecture

Science.gov (United States)

Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

2011-01-01

SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

Facilitating RNA structure prediction with microarrays.

Science.gov (United States)

Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

2006-01-17

Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

RNA secondary structure prediction using soft computing.

Science.gov (United States)

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

Interactions between the HIV-1 Unspliced mRNA and Host mRNA Decay Machineries

Directory of Open Access Journals (Sweden)

Daniela Toro-Ascuy

2016-11-01

Full Text Available The human immunodeficiency virus type-1 (HIV-1 unspliced transcript is used both as mRNA for the synthesis of structural proteins and as the packaged genome. Given the presence of retained introns and instability AU-rich sequences, this viral transcript is normally retained and degraded in the nucleus of host cells unless the viral protein REV is present. As such, the stability of the HIV-1 unspliced mRNA must be particularly controlled in the nucleus and the cytoplasm in order to ensure proper levels of this viral mRNA for translation and viral particle formation. During its journey, the HIV-1 unspliced mRNA assembles into highly specific messenger ribonucleoproteins (mRNPs containing many different host proteins, amongst which are well-known regulators of cytoplasmic mRNA decay pathways such as up-frameshift suppressor 1 homolog (UPF1, Staufen double-stranded RNA binding protein 1/2 (STAU1/2, or components of miRNA-induced silencing complex (miRISC and processing bodies (PBs. More recently, the HIV-1 unspliced mRNA was shown to contain N6-methyladenosine (m6A, allowing the recruitment of YTH N6-methyladenosine RNA binding protein 2 (YTHDF2, an m6A reader host protein involved in mRNA decay. Interestingly, these host proteins involved in mRNA decay were shown to play positive roles in viral gene expression and viral particle assembly, suggesting that HIV-1 interacts with mRNA decay components to successfully accomplish viral replication. This review summarizes the state of the art in terms of the interactions between HIV-1 unspliced mRNA and components of different host mRNA decay machineries.

RNA-Pareto: interactive analysis of Pareto-optimal RNA sequence-structure alignments.

Science.gov (United States)

Schnattinger, Thomas; Schöning, Uwe; Marchfelder, Anita; Kestler, Hans A

2013-12-01

Incorporating secondary structure information into the alignment process improves the quality of RNA sequence alignments. Instead of using fixed weighting parameters, sequence and structure components can be treated as different objectives and optimized simultaneously. The result is not a single, but a Pareto-set of equally optimal solutions, which all represent different possible weighting parameters. We now provide the interactive graphical software tool RNA-Pareto, which allows a direct inspection of all feasible results to the pairwise RNA sequence-structure alignment problem and greatly facilitates the exploration of the optimal solution set.

3dRPC: a web server for 3D RNA-protein structure prediction.

Science.gov (United States)

Huang, Yangyu; Li, Haotian; Xiao, Yi

2018-04-01

RNA-protein interactions occur in many biological processes. To understand the mechanism of these interactions one needs to know three-dimensional (3D) structures of RNA-protein complexes. 3dRPC is an algorithm for prediction of 3D RNA-protein complex structures and consists of a docking algorithm RPDOCK and a scoring function 3dRPC-Score. RPDOCK is used to sample possible complex conformations of an RNA and a protein by calculating the geometric and electrostatic complementarities and stacking interactions at the RNA-protein interface according to the features of atom packing of the interface. 3dRPC-Score is a knowledge-based potential that uses the conformations of nucleotide-amino-acid pairs as statistical variables and that is used to choose the near-native complex-conformations obtained from the docking method above. Recently, we built a web server for 3dRPC. The users can easily use 3dRPC without installing it locally. RNA and protein structures in PDB (Protein Data Bank) format are the only needed input files. It can also incorporate the information of interface residues or residue-pairs obtained from experiments or theoretical predictions to improve the prediction. The address of 3dRPC web server is http://biophy.hust.edu.cn/3dRPC. yxiao@hust.edu.cn.

Topology and prediction of RNA pseudoknots

DEFF Research Database (Denmark)

Reidys, Christian; Huang, Fenix; Andersen, Jørgen Ellegaard

2011-01-01

Motivation: Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ dramatically from one another in the classes of structures considered. Results: Here, we use the natural topological classification of RNA structures in terms...

Evolutionary rate variation and RNA secondary structure prediction

DEFF Research Database (Denmark)

Knudsen, B.; Andersen, E.S.; Damgaard, C.

2004-01-01

Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type...... by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions...

RNAstructure: software for RNA secondary structure prediction and analysis.

Science.gov (United States)

Reuter, Jessica S; Mathews, David H

2010-03-15

To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

Concepts and introduction to RNA bioinformatics

DEFF Research Database (Denmark)

Gorodkin, Jan; Hofacker, Ivo L.; Ruzzo, Walter L.

2014-01-01

RNA bioinformatics and computational RNA biology have emerged from implementing methods for predicting the secondary structure of single sequences. The field has evolved to exploit multiple sequences to take evolutionary information into account, such as compensating (and structure preserving) base...... for interactions between RNA and proteins.Here, we introduce the basic concepts of predicting RNA secondary structure relevant to the further analyses of RNA sequences. We also provide pointers to methods addressing various aspects of RNA bioinformatics and computational RNA biology....

Current insights into the molecular systems pharmacology of lncRNA-miRNA regulatory interactions and implications in cancer translational medicine

Directory of Open Access Journals (Sweden)

Sujit Nair

2016-04-01

Full Text Available In recent times, the role(s of microRNAs (miRNAs and long noncoding RNAs (lncRNAs in the pathogenesis of various cancers has received great attention. Indeed, there is also a growing recognition of regulatory RNA cross-talk, i.e., lncRNA-miRNA interactions, that may modulate various events in carcinogenesis and progression to metastasis. This review summarizes current evidence in the literature of lncRNA-miRNA interactions in various cancers such as breast, liver, stomach, lung, prostate, bladder, colorectal, blood, brain, skin, kidney, cervical, laryngeal, gall bladder, and bone. Further, the potential prognostic and theragnostic clinical applications of lncRNA-miRNA interactions in cancer are discussed along with an overview of noncoding RNA (ncRNA-based studies that were presented at the American Society of Clinical Oncology (ASCO 2015. Interestingly, the last decade has seen tremendous innovation, as well as increase in complexity, of the cancer biological network(s from mRNA- to miRNA- and lncRNA-based networks. Thus, biological networks devoted to understanding regulatory interactions between these ncRNAs would be the next frontier in better elucidating the contributions of lncRNA-miRNA interactions in cancer. Herein, a cancer biological network of lncRNA-miRNA interactions is presented wherein “edges” connect interacting lncRNA-miRNA pairs, with each ncRNA serving as a discrete “node” of the network. In conclusion, the untapped potential of lncRNA-miRNA interactions in terms of its diagnostic, prognostic and therapeutic potential as targets for clinically actionable intervention as well as biomarker validation in discovery pipelines remains to be explored. Future research will likely harness this potential so as to take us closer to the goal of “precision” and “personalized medicine” which is tailor-made to the unique needs of each cancer patient, and is clearly the way forward going into the future.

Improved nucleic acid descriptors for siRNA efficacy prediction.

Science.gov (United States)

Sciabola, Simone; Cao, Qing; Orozco, Modesto; Faustino, Ignacio; Stanton, Robert V

2013-02-01

Although considerable progress has been made recently in understanding how gene silencing is mediated by the RNAi pathway, the rational design of effective sequences is still a challenging task. In this article, we demonstrate that including three-dimensional descriptors improved the discrimination between active and inactive small interfering RNAs (siRNAs) in a statistical model. Five descriptor types were used: (i) nucleotide position along the siRNA sequence, (ii) nucleotide composition in terms of presence/absence of specific combinations of di- and trinucleotides, (iii) nucleotide interactions by means of a modified auto- and cross-covariance function, (iv) nucleotide thermodynamic stability derived by the nearest neighbor model representation and (v) nucleic acid structure flexibility. The duplex flexibility descriptors are derived from extended molecular dynamics simulations, which are able to describe the sequence-dependent elastic properties of RNA duplexes, even for non-standard oligonucleotides. The matrix of descriptors was analysed using three statistical packages in R (partial least squares, random forest, and support vector machine), and the most predictive model was implemented in a modeling tool we have made publicly available through SourceForge. Our implementation of new RNA descriptors coupled with appropriate statistical algorithms resulted in improved model performance for the selection of siRNA candidates when compared with publicly available siRNA prediction tools and previously published test sets. Additional validation studies based on in-house RNA interference projects confirmed the robustness of the scoring procedure in prospective studies.

Dissecting the interactions of SERRATE with RNA and DICER-LIKE 1 in Arabidopsis microRNA precursor processing

KAUST Repository

Iwata, Yuji

2013-08-05

Efficient and precise microRNA (miRNA) biogenesis in Arabidopsis is mediated by the RNaseIII-family enzyme DICER-LIKE 1 (DCL1), double-stranded RNA-binding protein HYPONASTIC LEAVES 1 and the zinc-finger (ZnF) domain-containing protein SERRATE (SE). In the present study, we examined primary miRNA precursor (pri-miRNA) processing by highly purified recombinant DCL1 and SE proteins and found that SE is integral to pri-miRNA processing by DCL1. SE stimulates DCL1 cleavage of the pri-miRNA in an ionic strength-dependent manner. SE uses its N-terminal domain to bind to RNA and requires both N-terminal and ZnF domains to bind to DCL1. However, when DCL1 is bound to RNA, the interaction with the ZnF domain of SE becomes indispensible and stimulates the activity of DCL1 without requiring SE binding to RNA. Our results suggest that the interactions among SE, DCL1 and RNA are a potential point for regulating pri-miRNA processing. 2013 The Author(s) 2013.

Detailed analysis of RNA-protein interactions within the bacterial ribosomal protein L5/5S rRNA complex.

Science.gov (United States)

Perederina, Anna; Nevskaya, Natalia; Nikonov, Oleg; Nikulin, Alexei; Dumas, Philippe; Yao, Min; Tanaka, Isao; Garber, Maria; Gongadze, George; Nikonov, Stanislav

2002-12-01

The crystal structure of ribosomal protein L5 from Thermus thermophilus complexed with a 34-nt fragment comprising helix III and loop C of Escherichia coli 5S rRNA has been determined at 2.5 A resolution. The protein specifically interacts with the bulged nucleotides at the top of loop C of 5S rRNA. The rRNA and protein contact surfaces are strongly stabilized by intramolecular interactions. Charged and polar atoms forming the network of conserved intermolecular hydrogen bonds are located in two narrow planar parallel layers belonging to the protein and rRNA, respectively. The regions, including these atoms conserved in Bacteria and Archaea, can be considered an RNA-protein recognition module. Comparison of the T. thermophilus L5 structure in the RNA-bound form with the isolated Bacillus stearothermophilus L5 structure shows that the RNA-recognition module on the protein surface does not undergo significant changes upon RNA binding. In the crystal of the complex, the protein interacts with another RNA molecule in the asymmetric unit through the beta-sheet concave surface. This protein/RNA interface simulates the interaction of L5 with 23S rRNA observed in the Haloarcula marismortui 50S ribosomal subunit.

Identifying and characterizing Hfq-RNA interactions.

Science.gov (United States)

Faner, M A; Feig, A L

2013-09-15

To regulate stress responses and virulence, bacteria use small regulatory RNAs (sRNAs). These RNAs can up or down regulate target mRNAs through base pairing by influencing ribosomal access and RNA decay. A large class of these sRNAs, called trans-encoded sRNAs, requires the RNA binding protein Hfq to facilitate base pairing between the regulatory RNA and its target mRNA. The resulting network of regulation is best characterized in Escherichia coli and Salmonella typhimurium, but the importance of Hfq dependent sRNA regulation is recognized in a diverse population of bacteria. In this review we present the approaches and methods used to discover Hfq binding RNAs, characterize their interactions and elucidate their functions. Copyright © 2013 Elsevier Inc. All rights reserved.

Structural basis of genomic RNA (gRNA) dimerization and packaging determinants of mouse mammary tumor virus (MMTV).

Science.gov (United States)

Aktar, Suriya J; Vivet-Boudou, Valérie; Ali, Lizna M; Jabeen, Ayesha; Kalloush, Rawan M; Richer, Delphine; Mustafa, Farah; Marquet, Roland; Rizvi, Tahir A

2014-11-14

One of the hallmarks of retroviral life cycle is the efficient and specific packaging of two copies of retroviral gRNA in the form of a non-covalent RNA dimer by the assembling virions. It is becoming increasingly clear that the process of dimerization is closely linked with gRNA packaging, and in some retroviruses, the latter depends on the former. Earlier mutational analysis of the 5' end of the MMTV genome indicated that MMTV gRNA packaging determinants comprise sequences both within the 5' untranslated region (5' UTR) and the beginning of gag. The RNA secondary structure of MMTV gRNA packaging sequences was elucidated employing selective 2'hydroxyl acylation analyzed by primer extension (SHAPE). SHAPE analyses revealed the presence of a U5/Gag long-range interaction (U5/Gag LRI), not predicted by minimum free-energy structure predictions that potentially stabilizes the global structure of this region. Structure conservation along with base-pair covariations between different strains of MMTV further supported the SHAPE-validated model. The 5' region of the MMTV gRNA contains multiple palindromic (pal) sequences that could initiate intermolecular interaction during RNA dimerization. In vitro RNA dimerization, SHAPE analysis, and structure prediction approaches on a series of pal mutants revealed that MMTV RNA utilizes a palindromic point of contact to initiate intermolecular interactions between two gRNAs, leading to dimerization. This contact point resides within pal II (5' CGGCCG 3') at the 5' UTR and contains a canonical "GC" dyad and therefore likely constitutes the MMTV RNA dimerization initiation site (DIS). Further analyses of these pal mutants employing in vivo genetic approaches indicate that pal II, as well as pal sequences located in the primer binding site (PBS) are both required for efficient MMTV gRNA packaging. Employing structural prediction, biochemical, and genetic approaches, we show that pal II functions as a primary point of contact between

LDAP: a web server for lncRNA-disease association prediction.

Science.gov (United States)

Lan, Wei; Li, Min; Zhao, Kaijie; Liu, Jin; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2017-02-01

Increasing evidences have demonstrated that long noncoding RNAs (lncRNAs) play important roles in many human diseases. Therefore, predicting novel lncRNA-disease associations would contribute to dissect the complex mechanisms of disease pathogenesis. Some computational methods have been developed to infer lncRNA-disease associations. However, most of these methods infer lncRNA-disease associations only based on single data resource. In this paper, we propose a new computational method to predict lncRNA-disease associations by integrating multiple biological data resources. Then, we implement this method as a web server for lncRNA-disease association prediction (LDAP). The input of the LDAP server is the lncRNA sequence. The LDAP predicts potential lncRNA-disease associations by using a bagging SVM classifier based on lncRNA similarity and disease similarity. The web server is available at http://bioinformatics.csu.edu.cn/ldap jxwang@mail.csu.edu.cn. Supplementary data are available at Bioinformatics online.

Ranking of microRNA target prediction scores by Pareto front analysis.

Science.gov (United States)

Sahoo, Sudhakar; Albrecht, Andreas A

2010-12-01

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Meta-Path-Based Prediction Method for Human miRNA-Target Association

Directory of Open Access Journals (Sweden)

Jiawei Luo

2016-01-01

Full Text Available MicroRNAs (miRNAs are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

The interaction between the iron-responsive element binding protein and its cognate RNA is highly dependent upon both RNA sequence and structure.

Science.gov (United States)

Jaffrey, S R; Haile, D J; Klausner, R D; Harford, J B

1993-09-25

To assess the influence of RNA sequence/structure on the interaction RNAs with the iron-responsive element binding protein (IRE-BP), twenty eight altered RNAs were tested as competitors for an RNA corresponding to the ferritin H chain IRE. All changes in the loop of the predicted IRE hairpin and in the unpaired cytosine residue characteristically found in IRE stems significantly decreased the apparent affinity of the RNA for the IRE-BP. Similarly, alteration in the spacing and/or orientation of the loop and the unpaired cytosine of the stem by either increasing or decreasing the number of base pairs separating them significantly reduced efficacy as a competitor. It is inferred that the IRE-BP forms multiple contacts with its cognate RNA, and that these contacts, acting in concert, provide the basis for the high affinity of this interaction.

The DEAD-Box RNA Helicase DDX3 Interacts with m6A RNA Demethylase ALKBH5

Directory of Open Access Journals (Sweden)

Abdullah Shah

2017-01-01

Full Text Available DDX3 is a member of the family of DEAD-box RNA helicases. DDX3 is a multifaceted helicase and plays essential roles in key biological processes such as cell cycle, stress response, apoptosis, and RNA metabolism. In this study, we found that DDX3 interacted with ALKBH5, an m6A RNA demethylase. The ATP domain of DDX3 and DSBH domain of ALKBH5 were indispensable to their interaction with each other. Furthermore, DDX3 could modulate the demethylation of mRNAs. We also showed that DDX3 regulated the methylation status of microRNAs and there was an interaction between DDX3 and AGO2. The dynamics of m6A RNA modification is still a field demanding further investigation, and here, we add a link by showing that RNA demethylation can be regulated by proteins such as DDX3.

A quick reality check for microRNA target prediction.

Science.gov (United States)

Kast, Juergen

2011-04-01

The regulation of protein abundance by microRNA (miRNA)-mediated repression of mRNA translation is a rapidly growing area of interest in biochemical research. In animal cells, the miRNA seed sequence does not perfectly match that of the mRNA it targets, resulting in a large number of possible miRNA targets and varied extents of repression. Several software tools are available for the prediction of miRNA targets, yet the overlap between them is limited. Jovanovic et al. have developed and applied a targeted, quantitative approach to validate predicted miRNA target proteins. Using a proteome database, they have set up and tested selected reaction monitoring assays for approximately 20% of more than 800 predicted let-7 targets, as well as control genes in Caenorhabditis elegans. Their results demonstrate that such assays can be developed quickly and with relative ease, and applied in a high-throughput setup to verify known and identify novel miRNA targets. They also show, however, that the choice of the biological system and material has a noticeable influence on the frequency, extent and direction of the observed changes. Nonetheless, selected reaction monitoring assays, such as those developed by Jovanovic et al., represent an attractive new tool in the study of miRNA function at the organism level.

A semi-supervised learning approach for RNA secondary structure prediction.

Science.gov (United States)

Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

2015-08-01

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comprehensive comparison of comparative RNA structure prediction approaches

DEFF Research Database (Denmark)

Gardner, P. P.; Giegerich, R.

2004-01-01

-finding and multiple-sequence-alignment algorithms. Results Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance. Conclusions We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms......Background An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene...

Integration and visualization of non-coding RNA and protein interaction networks

OpenAIRE

Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian; Pan, Xiaoyong; Santos Delgado, Alberto; Anthon, Christian; Alkan, Ferhat; von Mering, Christian; Workman, Christopher; Jensen, Lars Juhl; Gorodkin, Jan

2015-01-01

Non-coding RNAs (ncRNAs) fulfill a diverse set of biological functions relying on interactions with other molecular entities. The advent of new experimental and computational approaches makes it possible to study ncRNAs and their associations on an unprecedented scale. We present RAIN (RNA Association and Interaction Networks) - a database that combines ncRNA-ncRNA, ncRNA-mRNA and ncRNA-protein interactions with large-scale protein association networks available in the STRING database. By int...

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

Science.gov (United States)

Singh, Garima; Roy, Jyoti; Rout, Pratiti; Mallick, Bibekanand

2018-01-01

PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).

RNA folding: structure prediction, folding kinetics and ion electrostatics.

Science.gov (United States)

Tan, Zhijie; Zhang, Wenbing; Shi, Yazhou; Wang, Fenghua

2015-01-01

Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

Genome wide predictions of miRNA regulation by transcription factors.

Science.gov (United States)

Ruffalo, Matthew; Bar-Joseph, Ziv

2016-09-01

Reconstructing regulatory networks from expression and interaction data is a major goal of systems biology. While much work has focused on trying to experimentally and computationally determine the set of transcription-factors (TFs) and microRNAs (miRNAs) that regulate genes in these networks, relatively little work has focused on inferring the regulation of miRNAs by TFs. Such regulation can play an important role in several biological processes including development and disease. The main challenge for predicting such interactions is the very small positive training set currently available. Another challenge is the fact that a large fraction of miRNAs are encoded within genes making it hard to determine the specific way in which they are regulated. To enable genome wide predictions of TF-miRNA interactions, we extended semi-supervised machine-learning approaches to integrate a large set of different types of data including sequence, expression, ChIP-seq and epigenetic data. As we show, the methods we develop achieve good performance on both a labeled test set, and when analyzing general co-expression networks. We next analyze mRNA and miRNA cancer expression data, demonstrating the advantage of using the predicted set of interactions for identifying more coherent and relevant modules, genes, and miRNAs. The complete set of predictions is available on the supporting website and can be used by any method that combines miRNAs, genes, and TFs. Code and full set of predictions are available from the supporting website: http://cs.cmu.edu/~mruffalo/tf-mirna/ zivbj@cs.cmu.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

Science.gov (United States)

Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

2018-05-12

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

Directory of Open Access Journals (Sweden)

Arthur C. Oliveira

2017-05-01

Full Text Available Target prediction is generally the first step toward recognition of bona fide microRNA (miRNA-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single miRNA or a subset of miRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan (TS, miRanda-mirSVR (MR, Pita, and RNA22 (R22, and we determined the most effective approach for analyzing target prediction data (individual, union, or intersection. For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 miRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p and 1,400 genes (700 validated and 700 non-validated as targets of these miRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TS/MR and TS/MR/R22 enhanced the quality of in silico prediction analysis of miRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of miRNA-target interactions.

Genome-scale characterization of RNA tertiary structures and their functional impact by RNA solvent accessibility prediction.

Science.gov (United States)

Yang, Yuedong; Li, Xiaomei; Zhao, Huiying; Zhan, Jian; Wang, Jihua; Zhou, Yaoqi

2017-01-01

As most RNA structures are elusive to structure determination, obtaining solvent accessible surface areas (ASAs) of nucleotides in an RNA structure is an important first step to characterize potential functional sites and core structural regions. Here, we developed RNAsnap, the first machine-learning method trained on protein-bound RNA structures for solvent accessibility prediction. Built on sequence profiles from multiple sequence alignment (RNAsnap-prof), the method provided robust prediction in fivefold cross-validation and an independent test (Pearson correlation coefficients, r, between predicted and actual ASA values are 0.66 and 0.63, respectively). Application of the method to 6178 mRNAs revealed its positive correlation to mRNA accessibility by dimethyl sulphate (DMS) experimentally measured in vivo (r = 0.37) but not in vitro (r = 0.07), despite the lack of training on mRNAs and the fact that DMS accessibility is only an approximation to solvent accessibility. We further found strong association across coding and noncoding regions between predicted solvent accessibility of the mutation site of a single nucleotide variant (SNV) and the frequency of that variant in the population for 2.2 million SNVs obtained in the 1000 Genomes Project. Moreover, mapping solvent accessibility of RNAs to the human genome indicated that introns, 5' cap of 5' and 3' cap of 3' untranslated regions, are more solvent accessible, consistent with their respective functional roles. These results support conformational selections as the mechanism for the formation of RNA-protein complexes and highlight the utility of genome-scale characterization of RNA tertiary structures by RNAsnap. The server and its stand-alone downloadable version are available at http://sparks-lab.org. © 2016 Yang et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

Science.gov (United States)

Li, Tao; Li, Qian-Zhong

2012-11-07

RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

microRNA-independent recruitment of Argonaute 1 to nanos mRNA through the Smaug RNA-binding protein.

Science.gov (United States)

Pinder, Benjamin D; Smibert, Craig A

2013-01-01

Argonaute (Ago) proteins are typically recruited to target messenger RNAs via an associated small RNA such as a microRNA (miRNA). Here, we describe a new mechanism of Ago recruitment through the Drosophila Smaug RNA-binding protein. We show that Smaug interacts with the Ago1 protein, and that Ago1 interacts with and is required for the translational repression of the Smaug target, nanos mRNA. The Ago1/nanos mRNA interaction does not require a miRNA, but it does require Smaug. Taken together, our data suggest a model whereby Smaug directly recruits Ago1 to nanos mRNA in a miRNA-independent manner, thereby repressing translation.

Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

Energy Technology Data Exchange (ETDEWEB)

Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling; Wu, Jie; Sun, Wen-Ju; Wang, Ze-Lin; Zhou, Hui; Qu, Liang-Hu, E-mail: lssqlh@mail.sysu.edu.cn; Yang, Jian-Hua, E-mail: lssqlh@mail.sysu.edu.cn [RNA Information Center, Key Laboratory of Gene Engineering of the Ministry of Education, State Key Laboratory for Biocontrol, Sun Yat-sen University, Guangzhou (China)

2015-01-14

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

Discovery of Protein–lncRNA Interactions by Integrating Large-Scale CLIP-Seq and RNA-Seq Datasets

International Nuclear Information System (INIS)

Li, Jun-Hao; Liu, Shun; Zheng, Ling-Ling; Wu, Jie; Sun, Wen-Ju; Wang, Ze-Lin; Zhou, Hui; Qu, Liang-Hu; Yang, Jian-Hua

2015-01-01

Long non-coding RNAs (lncRNAs) are emerging as important regulatory molecules in developmental, physiological, and pathological processes. However, the precise mechanism and functions of most of lncRNAs remain largely unknown. Recent advances in high-throughput sequencing of immunoprecipitated RNAs after cross-linking (CLIP-Seq) provide powerful ways to identify biologically relevant protein–lncRNA interactions. In this study, by analyzing millions of RNA-binding protein (RBP) binding sites from 117 CLIP-Seq datasets generated by 50 independent studies, we identified 22,735 RBP–lncRNA regulatory relationships. We found that one single lncRNA will generally be bound and regulated by one or multiple RBPs, the combination of which may coordinately regulate gene expression. We also revealed the expression correlation of these interaction networks by mining expression profiles of over 6000 normal and tumor samples from 14 cancer types. Our combined analysis of CLIP-Seq data and genome-wide association studies data discovered hundreds of disease-related single nucleotide polymorphisms resided in the RBP binding sites of lncRNAs. Finally, we developed interactive web implementations to provide visualization, analysis, and downloading of the aforementioned large-scale datasets. Our study represented an important step in identification and analysis of RBP–lncRNA interactions and showed that these interactions may play crucial roles in cancer and genetic diseases.

Inferring microRNA regulation of mRNA with partially ordered samples of paired expression data and exogenous prediction algorithms.

Directory of Open Access Journals (Sweden)

Brian Godsey

Full Text Available MicroRNAs (miRs are known to play an important role in mRNA regulation, often by binding to complementary sequences in "target" mRNAs. Recently, several methods have been developed by which existing sequence-based target predictions can be combined with miR and mRNA expression data to infer true miR-mRNA targeting relationships. It has been shown that the combination of these two approaches gives more reliable results than either by itself. While a few such algorithms give excellent results, none fully addresses expression data sets with a natural ordering of the samples. If the samples in an experiment can be ordered or partially ordered by their expected similarity to one another, such as for time-series or studies of development processes, stages, or types, (e.g. cell type, disease, growth, aging, there are unique opportunities to infer miR-mRNA interactions that may be specific to the underlying processes, and existing methods do not exploit this. We propose an algorithm which specifically addresses [partially] ordered expression data and takes advantage of sample similarities based on the ordering structure. This is done within a Bayesian framework which specifies posterior distributions and therefore statistical significance for each model parameter and latent variable. We apply our model to a previously published expression data set of paired miR and mRNA arrays in five partially ordered conditions, with biological replicates, related to multiple myeloma, and we show how considering potential orderings can improve the inference of miR-mRNA interactions, as measured by existing knowledge about the involved transcripts.

RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

International Nuclear Information System (INIS)

Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E.; Eghbalnia, Hamid R.

2012-01-01

The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ( 1 H– 15 N 2D HMQC) and proton–proton nuclear Overhauser enhancement spectroscopy ( 1 H– 1 H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino resonances for a

RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

Energy Technology Data Exchange (ETDEWEB)

Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E. [National Magnetic Resonance Facility at Madison (United States); Eghbalnia, Hamid R., E-mail: eghbalhd@uc.edu [University of Cincinnati, Department of Molecular and Cellular Physiology (United States)

2012-04-15

The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ({sup 1}H-{sup 15}N 2D HMQC) and proton-proton nuclear Overhauser enhancement spectroscopy ({sup 1}H-{sup 1}H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino

Characterization of MRP RNA-protein interactions within the perinucleolar compartment.

Science.gov (United States)

Pollock, Callie; Daily, Kelly; Nguyen, Van Trung; Wang, Chen; Lewandowska, Marzena Anna; Bensaude, Olivier; Huang, Sui

2011-03-15

The perinucleolar compartment (PNC) forms in cancer cells and is highly enriched with a subset of polymerase III RNAs and RNA-binding proteins. Here we report that PNC components mitochondrial RNA-processing (MRP) RNA, pyrimidine tract-binding protein (PTB), and CUG-binding protein (CUGBP) interact in vivo, as demonstrated by coimmunoprecipitation and RNA pull-down experiments. Glycerol gradient analyses show that this complex is large and sediments at a different fraction from known MRP RNA-containing complexes, the MRP ribonucleoprotein ribozyme and human telomerase reverse transcriptase. Tethering PNC components to a LacO locus recruits other PNC components, further confirming the in vivo interactions. These interactions are present both in PNC-containing and -lacking cells. High-resolution localization analyses demonstrate that MRP RNA, CUGBP, and PTB colocalize at the PNC as a reticulated network, intertwining with newly synthesized RNA. Furthermore, green fluorescent protein (GFP)-PTB and GFP-CUGBP show a slower rate of fluorescence recovery after photobleaching at the PNC than in the nucleoplasm, illustrating the different molecular interaction of the complexes associated with the PNC. These findings support a working model in which the MRP RNA-protein complex becomes nucleated at the PNC in cancer cells and may play a role in gene expression regulation at the DNA locus that associates with the PNC.

A discontinuous RNA platform mediates RNA virus replication: building an integrated model for RNA-based regulation of viral processes.

Directory of Open Access Journals (Sweden)

Baodong Wu

2009-03-01

Full Text Available Plus-strand RNA viruses contain RNA elements within their genomes that mediate a variety of fundamental viral processes. The traditional view of these elements is that of local RNA structures. This perspective, however, is changing due to increasing discoveries of functional viral RNA elements that are formed by long-range RNA-RNA interactions, often spanning thousands of nucleotides. The plus-strand RNA genomes of tombusviruses exemplify this concept by possessing different long-range RNA-RNA interactions that regulate both viral translation and transcription. Here we report that a third fundamental tombusvirus process, viral genome replication, requires a long-range RNA-based interaction spanning approximately 3000 nts. In vivo and in vitro analyses suggest that the discontinuous RNA platform formed by the interaction facilitates efficient assembly of the viral RNA replicase. This finding has allowed us to build an integrated model for the role of global RNA structure in regulating the reproduction of a eukaryotic RNA virus, and the insights gained have extended our understanding of the multifunctional nature of viral RNA genomes.

Boundary Associated Long Noncoding RNA Mediates Long-Range Chromosomal Interactions.

Directory of Open Access Journals (Sweden)

Ifeoma Jane Nwigwe

Full Text Available CCCTC binding factor (CTCF is involved in organizing chromosomes into mega base-sized, topologically associated domains (TADs along with other factors that define sub-TAD organization. CTCF-Cohesin interactions have been shown to be critical for transcription insulation activity as it stabilizes long-range interactions to promote proper gene expression. Previous studies suggest that heterochromatin boundary activity of CTCF may be independent of Cohesin, and there may be additional mechanisms for defining topological domains. Here, we show that a boundary site we previously identified known as CTCF binding site 5 (CBS5 from the homeotic gene cluster A (HOXA locus exhibits robust promoter activity. This promoter activity from the CBS5 boundary element generates a long noncoding RNA that we designate as boundary associated long noncoding RNA-1 (blncRNA1. Functional characterization of this RNA suggests that the transcript stabilizes long-range interactions at the HOXA locus and promotes proper expression of HOXA genes. Additionally, our functional analysis also shows that this RNA is not needed in the stabilization of CTCF-Cohesin interactions however CTCF-Cohesin interactions are critical in the transcription of blncRNA1. Thus, the CTCF-associated boundary element, CBS5, employs both Cohesin and noncoding RNA to establish and maintain topologically associated domains at the HOXA locus.

Hsp90 interacts specifically with viral RNA and differentially regulates replication initiation of Bamboo mosaic virus and associated satellite RNA.

Directory of Open Access Journals (Sweden)

Ying Wen Huang

Full Text Available Host factors play crucial roles in the replication of plus-strand RNA viruses. In this report, a heat shock protein 90 homologue of Nicotiana benthamiana, NbHsp90, was identified in association with partially purified replicase complexes from BaMV-infected tissue, and shown to specifically interact with the 3' untranslated region (3' UTR of BaMV genomic RNA, but not with the 3' UTR of BaMV-associated satellite RNA (satBaMV RNA or that of genomic RNA of other viruses, such as Potato virus X (PVX or Cucumber mosaic virus (CMV. Mutational analyses revealed that the interaction occurs between the middle domain of NbHsp90 and domain E of the BaMV 3' UTR. The knockdown or inhibition of NbHsp90 suppressed BaMV infectivity, but not that of satBaMV RNA, PVX, or CMV in N. benthamiana. Time-course analysis further revealed that the inhibitory effect of 17-AAG is significant only during the immediate early stages of BaMV replication. Moreover, yeast two-hybrid and GST pull-down assays demonstrated the existence of an interaction between NbHsp90 and the BaMV RNA-dependent RNA polymerase. These results reveal a novel role for NbHsp90 in the selective enhancement of BaMV replication, most likely through direct interaction with the 3' UTR of BaMV RNA during the initiation of BaMV RNA replication.

Evolving stochastic context-free grammars for RNA secondary structure prediction

DEFF Research Database (Denmark)

Anderson, James WJ; Tataru, Paula Cristina; Stains, Joe

2012-01-01

Background Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s. The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few...... to structure prediction as has been previously suggested. Results These search techniques were applied to predict RNA secondary structure on a maximal data set and revealed new and interesting grammars, though none are dramatically better than classic grammars. In general, results showed that many grammars...... with quite different structure could have very similar predictive ability. Many ambiguous grammars were found which were at least as effective as the best current unambiguous grammars. Conclusions Overall the method of evolving SCFGs for RNA secondary structure prediction proved effective in finding many...

Solving RNA's structural secrets: interaction with antibodies and crystal structure of a nuclease resistant RNA

International Nuclear Information System (INIS)

Wallace, S.T.

1998-10-01

This Ph.D. thesis concerns the structural characterization of RNA. The work is split into two sections: 1) in vitro selection and characterization of RNAs which bind antibiotics and 2) crystal structure of a nuclease resistant RNA molecule used in antisense applications. Understanding antibiotic-RNA interactions is crucial in aiding rational drug design. We were interested in studying antibiotic interactions with RNAs small enough to characterize at the molecular and possibly at the atomic level. In order to do so, we previously performed in vitro selection to find small RNAs which bind to the peptide antibiotic viomycin and the aminoglycoside antibiotic streptomycin. The characterization of the viomycin-binding RNAs revealed the necessity of a pseudoknot-structure in order to interact with the antibiotic. The RNAs which were selected to interact with streptomycin require the presence of magnesium to bind the antibiotic. One of the RNAs, upon interacting with streptomycin undergoes a significant conformational change spanning the entire RNA sequence needed to bind the antibiotic. In a quest to design oligodeoxynucleotides (ODNs) which are able to specifically bid and inactivate the mRNA of a gene, it is necessary to fulfill two criteria: 1) increase binding affinity between the ODN and the target RNA and 2) increase the ODN's resistance to nuclease degradation. An ODN with an aminopropyl modification at the 2' position of its ribose has emerged as the most successful candidate at fulfilling both criteria. It is the most nuclease resistant modification known to date. We were interested in explaining how this modification is able to circumvent degradation by nucleases. A dodecamer containing a single 2'-O-aminopropyl modified nucleotide was crystallized and the structure was solved to a resolution of 1.6 A. In an attempt to explain the nuclease resistance, the crystal coordinates were modeled into the active exonuclease site of DNA polymerase I. We propose the

5'-3' RNA-RNA interaction facilitates cap- and poly(A) tail-independent translation of tomato bushy stunt virus mrna: a potential common mechanism for tombusviridae.

Science.gov (United States)

Fabian, Marc R; White, K Andrew

2004-07-09

Tomato bushy stunt virus (TBSV) is the prototypical member of the genus Tombusvirus in the family Tombusviridae. The (+)-strand RNA genome of TBSV lacks both a 5' cap and a 3' poly(A) tail and instead contains a 3'-terminal RNA sequence that acts as a cap-independent translational enhancer (3' CITE). In this study, we have determined the RNA secondary structure of the translation-specific central segment of the 3' CITE, termed region 3.5 (R3.5). MFOLD structural modeling combined with solution structure mapping and comparative sequence analysis indicate that R3.5 adopts a branched structure that contains three major helices. Deletion and substitution studies revealed that two of these extended stem-loop (SL) structures are essential for 3' CITE activity in vivo. In particular, the terminal loop of one of these SLs, SL-B, was found to be critical for translation. Compensatory mutational analysis showed that SL-B functions by base pairing with another SL, SL3, in the 5' untranslated region of the TBSV genome. Thus, efficient translation of TBSV mRNA in vivo requires a 5'-3' RNA-RNA interaction that effectively circularizes the message. Similar types of interactions are also predicted to occur in TBSV subgenomic mRNAs between their 5' untranslated regions and the 3' CITE, and both genomic and subgenomic 5'-3' interactions are well conserved in all members of the genus Tombusvirus. In addition, a survey of other genera in Tombusviridae revealed the potential for similar 5'-3' RNA-RNA-based interactions in their viral mRNAs, suggesting that this mechanism extends throughout this large virus family.

RNA secondary structure prediction with pseudoknots: Contribution of algorithm versus energy model.

Science.gov (United States)

Jabbari, Hosna; Wark, Ian; Montemagno, Carlo

2018-01-01

RNA is a biopolymer with various applications inside the cell and in biotechnology. Structure of an RNA molecule mainly determines its function and is essential to guide nanostructure design. Since experimental structure determination is time-consuming and expensive, accurate computational prediction of RNA structure is of great importance. Prediction of RNA secondary structure is relatively simpler than its tertiary structure and provides information about its tertiary structure, therefore, RNA secondary structure prediction has received attention in the past decades. Numerous methods with different folding approaches have been developed for RNA secondary structure prediction. While methods for prediction of RNA pseudoknot-free structure (structures with no crossing base pairs) have greatly improved in terms of their accuracy, methods for prediction of RNA pseudoknotted secondary structure (structures with crossing base pairs) still have room for improvement. A long-standing question for improving the prediction accuracy of RNA pseudoknotted secondary structure is whether to focus on the prediction algorithm or the underlying energy model, as there is a trade-off on computational cost of the prediction algorithm versus the generality of the method. The aim of this work is to argue when comparing different methods for RNA pseudoknotted structure prediction, the combination of algorithm and energy model should be considered and a method should not be considered superior or inferior to others if they do not use the same scoring model. We demonstrate that while the folding approach is important in structure prediction, it is not the only important factor in prediction accuracy of a given method as the underlying energy model is also as of great value. Therefore we encourage researchers to pay particular attention in comparing methods with different energy models.

The Role of RNA Interference (RNAi in Arbovirus-Vector Interactions

Directory of Open Access Journals (Sweden)

Carol D. Blair

2015-02-01

Full Text Available RNA interference (RNAi was shown over 18 years ago to be a mechanism by which arbovirus replication and transmission could be controlled in arthropod vectors. During the intervening period, research on RNAi has defined many of the components and mechanisms of this antiviral pathway in arthropods, yet a number of unexplored questions remain. RNAi refers to RNA-mediated regulation of gene expression. Originally, the term described silencing of endogenous genes by introduction of exogenous double-stranded (dsRNA with the same sequence as the gene to be silenced. Further research has shown that RNAi comprises three gene regulation pathways that are mediated by small RNAs: the small interfering (siRNA, micro (miRNA, and Piwi-interacting (piRNA pathways. The exogenous (exo-siRNA pathway is now recognized as a major antiviral innate immune response of arthropods. More recent studies suggest that the piRNA and miRNA pathways might also have important roles in arbovirus-vector interactions. This review will focus on current knowledge of the role of the exo-siRNA pathway as an arthropod vector antiviral response and on emerging research into vector piRNA and miRNA pathway modulation of arbovirus-vector interactions. Although it is assumed that arboviruses must evade the vector’s antiviral RNAi response in order to maintain their natural transmission cycles, the strategies by which this is accomplished are not well defined. RNAi is also an important tool for arthropod gene knock-down in functional genomics studies and in development of arbovirus-resistant mosquito populations. Possible arbovirus strategies for evasion of RNAi and applications of RNAi in functional genomics analysis and arbovirus transmission control will also be reviewed.

Interaction of sulforaphane with DNA and RNA.

Directory of Open Access Journals (Sweden)

Farzaneh Abassi Joozdani

Full Text Available Sulforaphane (SFN is an isothiocyanate found in cruciferous vegetables with anti-inflammatory, anti-oxidant and anti-cancer activities. However, the antioxidant and anticancer mechanism of sulforaphane is not well understood. In the present research, we reported binding modes, binding constants and stability of SFN-DNA and -RNA complexes by Fourier transform infrared (FTIR and UV-Visible spectroscopic methods. Spectroscopic evidence showed DNA intercalation with some degree of groove binding. SFN binds minor and major grooves of DNA and backbone phosphate (PO2, while RNA binding is through G, U, A bases with some degree of SFN-phosphate (PO2 interaction. Overall binding constants were estimated to be K(SFN-DNA=3.01 (± 0.035×10(4 M(-1 and K(SFN-RNA= 6.63 (±0.042×10(3 M(-1. At high SFN concentration (SFN/RNA = 1/1, DNA conformation changed from B to A occurred, while RNA remained in A-family structure.

Vfold: a web server for RNA structure and folding thermodynamics prediction.

Science.gov (United States)

Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2014-01-01

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

CentroidFold: a web server for RNA secondary structure prediction

OpenAIRE

Sato, Kengo; Hamada, Michiaki; Asai, Kiyoshi; Mituyama, Toutai

2009-01-01

The CentroidFold web server (http://www.ncrna.org/centroidfold/) is a web application for RNA secondary structure prediction powered by one of the most accurate prediction engine. The server accepts two kinds of sequence data: a single RNA sequence and a multiple alignment of RNA sequences. It responses with a prediction result shown as a popular base-pair notation and a graph representation. PDF version of the graph representation is also available. For a multiple alignment sequence, the ser...

MetaRNA-Seq: An Interactive Tool to Browse and Annotate Metadata from RNA-Seq Studies

Directory of Open Access Journals (Sweden)

Pankaj Kumar

2015-01-01

Full Text Available The number of RNA-Seq studies has grown in recent years. The design of RNA-Seq studies varies from very simple (e.g., two-condition case-control to very complicated (e.g., time series involving multiple samples at each time point with separate drug treatments. Most of these publically available RNA-Seq studies are deposited in NCBI databases, but their metadata are scattered throughout four different databases: Sequence Read Archive (SRA, Biosample, Bioprojects, and Gene Expression Omnibus (GEO. Although the NCBI web interface is able to provide all of the metadata information, it often requires significant effort to retrieve study- or project-level information by traversing through multiple hyperlinks and going to another page. Moreover, project- and study-level metadata lack manual or automatic curation by categories, such as disease type, time series, case-control, or replicate type, which are vital to comprehending any RNA-Seq study. Here we describe “MetaRNA-Seq,” a new tool for interactively browsing, searching, and annotating RNA-Seq metadata with the capability of semiautomatic curation at the study level.

DeepMirTar: a deep-learning approach for predicting human miRNA targets.

Science.gov (United States)

Wen, Ming; Cong, Peisheng; Zhang, Zhimin; Lu, Hongmei; Li, Tonghua

2018-06-01

MicroRNAs (miRNAs) are small noncoding RNAs that function in RNA silencing and post-transcriptional regulation of gene expression by targeting messenger RNAs (mRNAs). Because the underlying mechanisms associated with miRNA binding to mRNA are not fully understood, a major challenge of miRNA studies involves the identification of miRNA-target sites on mRNA. In silico prediction of miRNA-target sites can expedite costly and time-consuming experimental work by providing the most promising miRNA-target-site candidates. In this study, we reported the design and implementation of DeepMirTar, a deep-learning-based approach for accurately predicting human miRNA targets at the site level. The predicted miRNA-target sites are those having canonical or non-canonical seed, and features, including high-level expert-designed, low-level expert-designed, and raw-data-level, were used to represent the miRNA-target site. Comparison with other state-of-the-art machine-learning methods and existing miRNA-target-prediction tools indicated that DeepMirTar improved overall predictive performance. DeepMirTar is freely available at https://github.com/Bjoux2/DeepMirTar_SdA. lith@tongji.edu.cn, hongmeilu@csu.edu.cn. Supplementary data are available at Bioinformatics online.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

Science.gov (United States)

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Evf2 lncRNA/BRG1/DLX1 interactions reveal RNA-dependent inhibition of chromatin remodeling.

Science.gov (United States)

Cajigas, Ivelisse; Leib, David E; Cochrane, Jesse; Luo, Hao; Swyter, Kelsey R; Chen, Sean; Clark, Brian S; Thompson, James; Yates, John R; Kingston, Robert E; Kohtz, Jhumku D

2015-08-01

Transcription-regulating long non-coding RNAs (lncRNAs) have the potential to control the site-specific expression of thousands of target genes. Previously, we showed that Evf2, the first described ultraconserved lncRNA, increases the association of transcriptional activators (DLX homeodomain proteins) with key DNA enhancers but represses gene expression. In this report, mass spectrometry shows that the Evf2-DLX1 ribonucleoprotein (RNP) contains the SWI/SNF-related chromatin remodelers Brahma-related gene 1 (BRG1, SMARCA4) and Brahma-associated factor (BAF170, SMARCC2) in the developing mouse forebrain. Evf2 RNA colocalizes with BRG1 in nuclear clouds and increases BRG1 association with key DNA regulatory enhancers in the developing forebrain. While BRG1 directly interacts with DLX1 and Evf2 through distinct binding sites, Evf2 directly inhibits BRG1 ATPase and chromatin remodeling activities. In vitro studies show that both RNA-BRG1 binding and RNA inhibition of BRG1 ATPase/remodeling activity are promiscuous, suggesting that context is a crucial factor in RNA-dependent chromatin remodeling inhibition. Together, these experiments support a model in which RNAs convert an active enhancer to a repressed enhancer by directly inhibiting chromatin remodeling activity, and address the apparent paradox of RNA-mediated stabilization of transcriptional activators at enhancers with a repressive outcome. The importance of BRG1/RNA and BRG1/homeodomain interactions in neurodevelopmental disorders is underscored by the finding that mutations in Coffin-Siris syndrome, a human intellectual disability disorder, localize to the BRG1 RNA-binding and DLX1-binding domains. © 2015. Published by The Company of Biologists Ltd.

Detailed analysis of RNA-protein interactions within the bacterial ribosomal protein L5/5S rRNA complex.

OpenAIRE

Perederina, Anna; Nevskaya, Natalia; Nikonov, Oleg; Nikulin, Alexei; Dumas, Philippe; Yao, Min; Tanaka, Isao; Garber, Maria; Gongadze, George; Nikonov, Stanislav

2002-01-01

The crystal structure of ribosomal protein L5 from Thermus thermophilus complexed with a 34-nt fragment comprising helix III and loop C of Escherichia coli 5S rRNA has been determined at 2.5 A resolution. The protein specifically interacts with the bulged nucleotides at the top of loop C of 5S rRNA. The rRNA and protein contact surfaces are strongly stabilized by intramolecular interactions. Charged and polar atoms forming the network of conserved intermolecular hydrogen bonds are located in ...

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

Science.gov (United States)

Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

2010-04-10

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

Directory of Open Access Journals (Sweden)

Xue Hong

2010-04-01

Full Text Available Abstract Background Gene silencing using exogenous small interfering RNAs (siRNAs is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to

CID-miRNA: A web server for prediction of novel miRNA precursors in human genome

International Nuclear Information System (INIS)

Tyagi, Sonika; Vaz, Candida; Gupta, Vipin; Bhatia, Rohit; Maheshwari, Sachin; Srinivasan, Ashwin; Bhattacharya, Alok

2008-01-01

microRNAs (miRNA) are a class of non-protein coding functional RNAs that are thought to regulate expression of target genes by direct interaction with mRNAs. miRNAs have been identified through both experimental and computational methods in a variety of eukaryotic organisms. Though these approaches have been partially successful, there is a need to develop more tools for detection of these RNAs as they are also thought to be present in abundance in many genomes. In this report we describe a tool and a web server, named CID-miRNA, for identification of miRNA precursors in a given DNA sequence, utilising secondary structure-based filtering systems and an algorithm based on stochastic context free grammar trained on human miRNAs. CID-miRNA analyses a given sequence using a web interface, for presence of putative miRNA precursors and the generated output lists all the potential regions that can form miRNA-like structures. It can also scan large genomic sequences for the presence of potential miRNA precursors in its stand-alone form. The web server can be accessed at (http://mirna.jnu.ac.in/cidmirna/)

Avian reovirus L2 genome segment sequences and predicted structure/function of the encoded RNA-dependent RNA polymerase protein

Directory of Open Access Journals (Sweden)

Xu Wanhong

2008-12-01

Full Text Available Abstract Background The orthoreoviruses are infectious agents that possess a genome comprised of 10 double-stranded RNA segments encased in two concentric protein capsids. Like virtually all RNA viruses, an RNA-dependent RNA polymerase (RdRp enzyme is required for viral propagation. RdRp sequences have been determined for the prototype mammalian orthoreoviruses and for several other closely-related reoviruses, including aquareoviruses, but have not yet been reported for any avian orthoreoviruses. Results We determined the L2 genome segment nucleotide sequences, which encode the RdRp proteins, of two different avian reoviruses, strains ARV138 and ARV176 in order to define conserved and variable regions within reovirus RdRp proteins and to better delineate structure/function of this important enzyme. The ARV138 L2 genome segment was 3829 base pairs long, whereas the ARV176 L2 segment was 3830 nucleotides long. Both segments were predicted to encode λB RdRp proteins 1259 amino acids in length. Alignments of these newly-determined ARV genome segments, and their corresponding proteins, were performed with all currently available homologous mammalian reovirus (MRV and aquareovirus (AqRV genome segment and protein sequences. There was ~55% amino acid identity between ARV λB and MRV λ3 proteins, making the RdRp protein the most highly conserved of currently known orthoreovirus proteins, and there was ~28% identity between ARV λB and homologous MRV and AqRV RdRp proteins. Predictive structure/function mapping of identical and conserved residues within the known MRV λ3 atomic structure indicated most identical amino acids and conservative substitutions were located near and within predicted catalytic domains and lining RdRp channels, whereas non-identical amino acids were generally located on the molecule's surfaces. Conclusion The ARV λB and MRV λ3 proteins showed the highest ARV:MRV identity values (~55% amongst all currently known ARV and MRV

Prediction of RNA secondary structures: from theory to models and real molecules

International Nuclear Information System (INIS)

Schuster, Peter

2006-01-01

empirical parameters can be determined and by principal deficiencies, for example by the lack of energy contributions resulting from tertiary interactions. In addition, native structures may be determined by folding kinetics rather than by thermodynamics. We address the first problem by considering base pair probabilities or base pairing entropies, which are derived from the partition function of conformations. A high base pair probability corresponding to a low pairing entropy is taken as an indicator of a high reliability of prediction. Pseudoknots are discussed as an example of a tertiary interaction that is highly important for RNA function. Moreover, pseudoknot formation is readily incorporated into structure prediction algorithms. Some examples of experimental data on RNA secondary structures that are readily explained using the landscape concept are presented. They deal with (i) properties of RNA molecules with random sequences, (ii) RNA molecules from restricted alphabets, (iii) existence of neutral networks, (iv) shape space covering, (v) riboswitches and (vi) evolution of non-coding RNAs as an example of evolution restricted to neutral networks

Protein solubility and folding enhancement by interaction with RNA.

Directory of Open Access Journals (Sweden)

Seong Il Choi

Full Text Available While basic mechanisms of several major molecular chaperones are well understood, this machinery has been known to be involved in folding of only limited number of proteins inside the cells. Here, we report a chaperone type of protein folding facilitated by interaction with RNA. When an RNA-binding module is placed at the N-terminus of aggregation-prone target proteins, this module, upon binding with RNA, further promotes the solubility of passenger proteins, potentially leading to enhancement of proper protein folding. Studies on in vitro refolding in the presence of RNA, coexpression of RNA molecules in vivo and the mutants with impaired RNA binding ability suggests that RNA can exert chaperoning effect on their bound proteins. The results suggest that RNA binding could affect the overall kinetic network of protein folding pathway in favor of productive folding over off-pathway aggregation. In addition, the RNA binding-mediated solubility enhancement is extremely robust for increasing soluble yield of passenger proteins and could be usefully implemented for high-throughput protein expression for functional and structural genomic research initiatives. The RNA-mediated chaperone type presented here would give new insights into de novo folding in vivo.

MCTBI: a web server for predicting metal ion effects in RNA structures.

Science.gov (United States)

Sun, Li-Zhen; Zhang, Jing-Xiang; Chen, Shi-Jie

2017-08-01

Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg 2+ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures. © 2017 Sun et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

A new method to study the change of miRNA-mRNA interactions due to environmental exposures.

Science.gov (United States)

Petralia, Francesca; Aushev, Vasily N; Gopalakrishnan, Kalpana; Kappil, Maya; W Khin, Nyan; Chen, Jia; Teitelbaum, Susan L; Wang, Pei

2017-07-15

Integrative approaches characterizing the interactions among different types of biological molecules have been demonstrated to be useful for revealing informative biological mechanisms. One such example is the interaction between microRNA (miRNA) and messenger RNA (mRNA), whose deregulation may be sensitive to environmental insult leading to altered phenotypes. The goal of this work is to develop an effective data integration method to characterize deregulation between miRNA and mRNA due to environmental toxicant exposures. We will use data from an animal experiment designed to investigate the effect of low-dose environmental chemical exposure on normal mammary gland development in rats to motivate and evaluate the proposed method. We propose a new network approach-integrative Joint Random Forest (iJRF), which characterizes the regulatory system between miRNAs and mRNAs using a network model. iJRF is designed to work under the high-dimension low-sample-size regime, and can borrow information across different treatment conditions to achieve more accurate network inference. It also effectively takes into account prior information of miRNA-mRNA regulatory relationships from existing databases. When iJRF is applied to the data from the environmental chemical exposure study, we detected a few important miRNAs that regulated a large number of mRNAs in the control group but not in the exposed groups, suggesting the disruption of miRNA activity due to chemical exposure. Effects of chemical exposure on two affected miRNAs were further validated using breast cancer human cell lines. R package iJRF is available at CRAN. pei.wang@mssm.edu or susan.teitelbaum@mssm.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Combining miRNA and mRNA Expression Profiles in Wilms Tumor Subtypes

Directory of Open Access Journals (Sweden)

Nicole Ludwig

2016-03-01

Full Text Available Wilms tumor (WT is the most common childhood renal cancer. Recent findings of mutations in microRNA (miRNA processing proteins suggest a pivotal role of miRNAs in WT genesis. We performed miRNA expression profiling of 36 WTs of different subtypes and four normal kidney tissues using microarrays. Additionally, we determined the gene expression profile of 28 of these tumors to identify potentially correlated target genes and affected pathways. We identified 85 miRNAs and 2107 messenger RNAs (mRNA differentially expressed in blastemal WT, and 266 miRNAs and 1267 mRNAs differentially expressed in regressive subtype. The hierarchical clustering of the samples, using either the miRNA or mRNA profile, showed the clear separation of WT from normal kidney samples, but the miRNA pattern yielded better separation of WT subtypes. A correlation analysis of the deregulated miRNA and mRNAs identified 13,026 miRNA/mRNA pairs with inversely correlated expression, of which 2844 are potential interactions of miRNA and their predicted mRNA targets. We found significant upregulation of miRNAs-183, -301a/b and -335 for the blastemal subtype, and miRNAs-181b, -223 and -630 for the regressive subtype. We found marked deregulation of miRNAs regulating epithelial to mesenchymal transition, especially in the blastemal subtype, and miRNAs influencing chemosensitivity, especially in regressive subtypes. Further research is needed to assess the influence of preoperative chemotherapy and tumor infiltrating lymphocytes on the miRNA and mRNA patterns in WT.

Global mapping of miRNA-target interactions in cattle (Bos taurus)

DEFF Research Database (Denmark)

Scheel, Troels K H; Moore, Michael J; Luna, Joseph M

2017-01-01

With roles in development, cell proliferation and disease, micro-RNA (miRNA) biology is of great importance and a potential therapeutic target. Here we used cross-linking immunoprecipitation (CLIP) and ligation of miRNA-target chimeras on the Argonaute (AGO) protein to globally map miRNA interact...

Effect of mutations in the A site of 16 S rRNA on aminoglycoside antibiotic-ribosome interaction

DEFF Research Database (Denmark)

Recht, M I; Douthwaite, S; Dahlquist, K D

1999-01-01

antibiotics, which also interact with this region of rRNA. Mutations of certain nucleotides in rRNA reduce aminoglycoside binding affinity, as previously demonstrated using a model RNA oligonucleotide system. Here, predictions from the oligonucleotide system were tested in the ribosome by mutation...... for the aminoglycoside paromomycin, whereas no discernible reduction in affinity was observed with 1406 mutant ribosomes. These data are consistent with prior NMR structural determination of aminoglycoside interaction with the decoding region, and further our understanding of how aminoglycoside resistance can...

An Intrinsically Disordered Peptide from Ebola Virus VP35 Controls Viral RNA Synthesis by Modulating Nucleoprotein-RNA Interactions

Directory of Open Access Journals (Sweden)

Daisy W. Leung

2015-04-01

Full Text Available During viral RNA synthesis, Ebola virus (EBOV nucleoprotein (NP alternates between an RNA-template-bound form and a template-free form to provide the viral polymerase access to the RNA template. In addition, newly synthesized NP must be prevented from indiscriminately binding to noncognate RNAs. Here, we investigate the molecular bases for these critical processes. We identify an intrinsically disordered peptide derived from EBOV VP35 (NPBP, residues 20–48 that binds NP with high affinity and specificity, inhibits NP oligomerization, and releases RNA from NP-RNA complexes in vitro. The structure of the NPBP/ΔNPNTD complex, solved to 3.7 Å resolution, reveals how NPBP peptide occludes a large surface area that is important for NP-NP and NP-RNA interactions and for viral RNA synthesis. Together, our results identify a highly conserved viral interface that is important for EBOV replication and can be targeted for therapeutic development.

An Intrinsically Disordered Peptide from Ebola Virus VP35 Controls Viral RNA Synthesis by Modulating Nucleoprotein-RNA Interactions.

Science.gov (United States)

Leung, Daisy W; Borek, Dominika; Luthra, Priya; Binning, Jennifer M; Anantpadma, Manu; Liu, Gai; Harvey, Ian B; Su, Zhaoming; Endlich-Frazier, Ariel; Pan, Juanli; Shabman, Reed S; Chiu, Wah; Davey, Robert A; Otwinowski, Zbyszek; Basler, Christopher F; Amarasinghe, Gaya K

2015-04-21

During viral RNA synthesis, Ebola virus (EBOV) nucleoprotein (NP) alternates between an RNA-template-bound form and a template-free form to provide the viral polymerase access to the RNA template. In addition, newly synthesized NP must be prevented from indiscriminately binding to noncognate RNAs. Here, we investigate the molecular bases for these critical processes. We identify an intrinsically disordered peptide derived from EBOV VP35 (NPBP, residues 20-48) that binds NP with high affinity and specificity, inhibits NP oligomerization, and releases RNA from NP-RNA complexes in vitro. The structure of the NPBP/ΔNPNTD complex, solved to 3.7 Å resolution, reveals how NPBP peptide occludes a large surface area that is important for NP-NP and NP-RNA interactions and for viral RNA synthesis. Together, our results identify a highly conserved viral interface that is important for EBOV replication and can be targeted for therapeutic development. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

The MicroRNA Interaction Network of Lipid Diseases

Science.gov (United States)

Kandhro, Abdul H.; Shoombuatong, Watshara; Nantasenamat, Chanin; Prachayasittikul, Virapong; Nuchnoi, Pornlada

2017-01-01

Background: Dyslipidemia is one of the major forms of lipid disorder, characterized by increased triglycerides (TGs), increased low-density lipoprotein-cholesterol (LDL-C), and decreased high-density lipoprotein-cholesterol (HDL-C) levels in blood. Recently, MicroRNAs (miRNAs) have been reported to involve in various biological processes; their potential usage being a biomarkers and in diagnosis of various diseases. Computational approaches including text mining have been used recently to analyze abstracts from the public databases to observe the relationships/associations between the biological molecules, miRNAs, and disease phenotypes. Materials and Methods: In the present study, significance of text mined extracted pair associations (miRNA-lipid disease) were estimated by one-sided Fisher's exact test. The top 20 significant miRNA-disease associations were visualized on Cytoscape. The CyTargetLinker plug-in tool on Cytoscape was used to extend the network and predicts new miRNA target genes. The Biological Networks Gene Ontology (BiNGO) plug-in tool on Cytoscape was used to retrieve gene ontology (GO) annotations for the targeted genes. Results: We retrieved 227 miRNA-lipid disease associations including 148 miRNAs. The top 20 significant miRNAs analysis on CyTargetLinker provides defined, predicted and validated gene targets, further targeted genes analyzed by BiNGO showed targeted genes were significantly associated with lipid, cholesterol, apolipoprotein, and fatty acids GO terms. Conclusion: We are the first to provide a reliable miRNA-lipid disease association network based on text mining. This could help future experimental studies that aim to validate predicted gene targets. PMID:29018475

Structural Analysis of ‘key’ Interactions in Functional RNA Molecules

KAUST Repository

Chawla, Mohit

2018-04-01

The main objective of the thesis is to carry out structural bioinformatics study along with usage of advanced quantum chemical methods to look at the structural stability and energetics of RNA building blocks. The main focus of the work described here lies on understanding the reasons behind the intrinsic stability of key interactions in nucleic acids. Crystal structures of RNA molecules exhibit fascinating variety of non-covalent interactions, which play an important role in maintaining the three dimensional structures. An accurate atomic level description of these interactions in the structural building blocks of RNA is a key to understand the structure-function relationship in these molecules. An effort has been made to link the conclusions drawn from quantum chemical computations on RNA base pairs in wide biochemical context of their occurrence in RNA structures. The initial attention was on the impact of natural and non-natural modifications of the nucleic acid bases on the structure and stability of base pairs that they are involved in. In the remaining sections we cover other molecular interactions shaping nucleic acids, as the interaction between ribose and the bases, and the fluoride sensing riboswitch system in order to investigate structure and dynamics of nucleic acids at the atomic level and to gain insight into the physical chemistry behind.

Structural Analysis of ‘key’ Interactions in Functional RNA Molecules

KAUST Repository

Chawla, Mohit

2018-01-01

The main objective of the thesis is to carry out structural bioinformatics study along with usage of advanced quantum chemical methods to look at the structural stability and energetics of RNA building blocks. The main focus of the work described here lies on understanding the reasons behind the intrinsic stability of key interactions in nucleic acids. Crystal structures of RNA molecules exhibit fascinating variety of non-covalent interactions, which play an important role in maintaining the three dimensional structures. An accurate atomic level description of these interactions in the structural building blocks of RNA is a key to understand the structure-function relationship in these molecules. An effort has been made to link the conclusions drawn from quantum chemical computations on RNA base pairs in wide biochemical context of their occurrence in RNA structures. The initial attention was on the impact of natural and non-natural modifications of the nucleic acid bases on the structure and stability of base pairs that they are involved in. In the remaining sections we cover other molecular interactions shaping nucleic acids, as the interaction between ribose and the bases, and the fluoride sensing riboswitch system in order to investigate structure and dynamics of nucleic acids at the atomic level and to gain insight into the physical chemistry behind.

MicroRNA-target binding structures mimic microRNA duplex structures in humans.

Directory of Open Access Journals (Sweden)

Xi Chen

Full Text Available Traditionally, researchers match a microRNA guide strand to mRNA sequences using sequence comparisons to predict its potential target genes. However, many of the predictions can be false positives due to limitations in sequence comparison alone. In this work, we consider the association of two related RNA structures that share a common guide strand: the microRNA duplex and the microRNA-target binding structure. We have analyzed thousands of such structure pairs and found many of them share high structural similarity. Therefore, we conclude that when predicting microRNA target genes, considering just the microRNA guide strand matches to gene sequences may not be sufficient--the microRNA duplex structure formed by the guide strand and its companion passenger strand must also be considered. We have developed software to translate RNA binding structure into encoded representations, and we have also created novel automatic comparison methods utilizing such encoded representations to determine RNA structure similarity. Our software and methods can be utilized in the other RNA secondary structure comparisons as well.

miREE: miRNA recognition elements ensemble

Science.gov (United States)

2011-01-01

Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between

TBI server: a web server for predicting ion effects in RNA folding.

Science.gov (United States)

Zhu, Yuhong; He, Zhaojian; Chen, Shi-Jie

2015-01-01

Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects. The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects. By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

TBI server: a web server for predicting ion effects in RNA folding.

Directory of Open Access Journals (Sweden)

Yuhong Zhu

Full Text Available Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects.The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects.By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

Bifurcations in the interplay of messenger RNA, protein and nonprotein coding RNA

International Nuclear Information System (INIS)

Zhdanov, Vladimir P

2008-01-01

The interplay of messenger RNA (mRNA), protein, produced via translation of this RNA, and nonprotein coding RNA (ncRNA) may include regulation of the ncRNA production by protein and (i) ncRNA-protein association resulting in suppression of the protein regulatory activity or (ii) ncRNA-mRNA association resulting in degradation of the miRNA-mRNA complex. The kinetic models describing these two scenarios are found to predict bistability provided that protein suppresses the ncRNA formation

A tale of two sequences: microRNA-target chimeric reads.

Science.gov (United States)

Broughton, James P; Pasquinelli, Amy E

2016-04-04

In animals, a functional interaction between a microRNA (miRNA) and its target RNA requires only partial base pairing. The limited number of base pair interactions required for miRNA targeting provides miRNAs with broad regulatory potential and also makes target prediction challenging. Computational approaches to target prediction have focused on identifying miRNA target sites based on known sequence features that are important for canonical targeting and may miss non-canonical targets. Current state-of-the-art experimental approaches, such as CLIP-seq (cross-linking immunoprecipitation with sequencing), PAR-CLIP (photoactivatable-ribonucleoside-enhanced CLIP), and iCLIP (individual-nucleotide resolution CLIP), require inference of which miRNA is bound at each site. Recently, the development of methods to ligate miRNAs to their target RNAs during the preparation of sequencing libraries has provided a new tool for the identification of miRNA target sites. The chimeric, or hybrid, miRNA-target reads that are produced by these methods unambiguously identify the miRNA bound at a specific target site. The information provided by these chimeric reads has revealed extensive non-canonical interactions between miRNAs and their target mRNAs, and identified many novel interactions between miRNAs and noncoding RNAs.

MysiRNA-designer: a workflow for efficient siRNA design.

Directory of Open Access Journals (Sweden)

Mohamed Mysara

Full Text Available The design of small interfering RNA (siRNA is a multi factorial problem that has gained the attention of many researchers in the area of therapeutic and functional genomics. MysiRNA score was previously introduced that improves the correlation of siRNA activity prediction considering state of the art algorithms. In this paper, a new program, MysiRNA-Designer, is described which integrates several factors in an automated work-flow considering mRNA transcripts variations, siRNA and mRNA target accessibility, and both near-perfect and partial off-target matches. It also features the MysiRNA score, a highly ranked correlated siRNA efficacy prediction score for ranking the designed siRNAs, in addition to top scoring models Biopredsi, DISR, Thermocomposition21 and i-Score, and integrates them in a unique siRNA score-filtration technique. This multi-score filtration layer filters siRNA that passes the 90% thresholds calculated from experimental dataset features. MysiRNA-Designer takes an accession, finds conserved regions among its transcript space, finds accessible regions within the mRNA, designs all possible siRNAs for these regions, filters them based on multi-scores thresholds, and then performs SNP and off-target filtration. These strict selection criteria were tested against human genes in which at least one active siRNA was designed from 95.7% of total genes. In addition, when tested against an experimental dataset, MysiRNA-Designer was found capable of rejecting 98% of the false positive siRNAs, showing superiority over three state of the art siRNA design programs. MysiRNA is a freely accessible (Microsoft Windows based desktop application that can be used to design siRNA with a high accuracy and specificity. We believe that MysiRNA-Designer has the potential to play an important role in this area.

The ViennaRNA web services.

Science.gov (United States)

Gruber, Andreas R; Bernhart, Stephan H; Lorenz, Ronny

2015-01-01

The ViennaRNA package is a widely used collection of programs for thermodynamic RNA secondary structure prediction. Over the years, many additional tools have been developed building on the core programs of the package to also address issues related to noncoding RNA detection, RNA folding kinetics, or efficient sequence design considering RNA-RNA hybridizations. The ViennaRNA web services provide easy and user-friendly web access to these tools. This chapter describes how to use this online platform to perform tasks such as prediction of minimum free energy structures, prediction of RNA-RNA hybrids, or noncoding RNA detection. The ViennaRNA web services can be used free of charge and can be accessed via http://rna.tbi.univie.ac.at.

RNA STRAND: The RNA Secondary Structure and Statistical Analysis Database

Directory of Open Access Journals (Sweden)

Andronescu Mirela

2008-08-01

Full Text Available Abstract Background The ability to access, search and analyse secondary structures of a large set of known RNA molecules is very important for deriving improved RNA energy models, for evaluating computational predictions of RNA secondary structures and for a better understanding of RNA folding. Currently there is no database that can easily provide these capabilities for almost all RNA molecules with known secondary structures. Results In this paper we describe RNA STRAND – the RNA secondary STRucture and statistical ANalysis Database, a curated database containing known secondary structures of any type and organism. Our new database provides a wide collection of known RNA secondary structures drawn from public databases, searchable and downloadable in a common format. Comprehensive statistical information on the secondary structures in our database is provided using the RNA Secondary Structure Analyser, a new tool we have developed to analyse RNA secondary structures. The information thus obtained is valuable for understanding to which extent and with which probability certain structural motifs can appear. We outline several ways in which the data provided in RNA STRAND can facilitate research on RNA structure, including the improvement of RNA energy models and evaluation of secondary structure prediction programs. In order to keep up-to-date with new RNA secondary structure experiments, we offer the necessary tools to add solved RNA secondary structures to our database and invite researchers to contribute to RNA STRAND. Conclusion RNA STRAND is a carefully assembled database of trusted RNA secondary structures, with easy on-line tools for searching, analyzing and downloading user selected entries, and is publicly available at http://www.rnasoft.ca/strand.

Characterization of mRNA-Cytoskeleton Interactions In Situ Using FMTRIP and Proximity Ligation

Science.gov (United States)

Jung, Jeenah; Lifland, Aaron W.; Alonas, Eric J.; Zurla, Chiara; Santangelo, Philip J.

2013-01-01

Many studies have demonstrated an association between the cytoskeleton and mRNA, as well as the asymmetric distribution of mRNA granules within the cell in response to various signaling events. It is likely that the extensive cytoskeletal network directs mRNA transport and localization, with different cytoskeletal elements having their own specific roles. In order to understand the spatiotemporal changes in the interactions between the mRNA and the cytoskeleton as a response to a stimulus, a technique that can visualize and quantify these changes across a population of cells while capturing cell-to-cell variations is required. Here, we demonstrate a method for imaging and quantifying mRNA-cytoskeleton interactions on a per cell basis with single-interaction sensitivity. Using a proximity ligation assay with flag-tagged multiply-labeled tetravalent RNA imaging probes (FMTRIP), we quantified interactions between mRNAs and β-tubulin, vimentin, or filamentous actin (F-actin) for two different mRNAs, poly(A) + and β-actin mRNA, in two different cell types, A549 cells and human dermal fibroblasts (HDF). We found that the mRNAs interacted predominantly with F-actin (>50% in HDF, >20% in A549 cells), compared to β-tubulin (cytoskeleton itself and mRNA localization. Both perturbations led to a decrease in poly(A) + mRNA interactions with F-actin and an increase in the interactions with microtubules, in a time dependent manner. PMID:24040294

T box riboswitches in Actinobacteria: Translational regulation via novel tRNA interactions

Science.gov (United States)

Sherwood, Anna V.; Grundy, Frank J.; Henkin, Tina M.

2015-01-01

The T box riboswitch regulates many amino acid-related genes in Gram-positive bacteria. T box riboswitch-mediated gene regulation was shown previously to occur at the level of transcription attenuation via structural rearrangements in the 5′ untranslated (leader) region of the mRNA in response to binding of a specific uncharged tRNA. In this study, a novel group of isoleucyl-tRNA synthetase gene (ileS) T box leader sequences found in organisms of the phylum Actinobacteria was investigated. The Stem I domains of these RNAs lack several highly conserved elements that are essential for interaction with the tRNA ligand in other T box RNAs. Many of these RNAs were predicted to regulate gene expression at the level of translation initiation through tRNA-dependent stabilization of a helix that sequesters a sequence complementary to the Shine–Dalgarno (SD) sequence, thus freeing the SD sequence for ribosome binding and translation initiation. We demonstrated specific binding to the cognate tRNAIle and tRNAIle-dependent structural rearrangements consistent with regulation at the level of translation initiation, providing the first biochemical demonstration, to our knowledge, of translational regulation in a T box riboswitch. PMID:25583497

Freiburg RNA Tools: a web server integrating INTARNA, EXPARNA and LOCARNA.

Science.gov (United States)

Smith, Cameron; Heyne, Steffen; Richter, Andreas S; Will, Sebastian; Backofen, Rolf

2010-07-01

The Freiburg RNA tools web server integrates three tools for the advanced analysis of RNA in a common web-based user interface. The tools IntaRNA, ExpaRNA and LocARNA support the prediction of RNA-RNA interaction, exact RNA matching and alignment of RNA, respectively. The Freiburg RNA tools web server and the software packages of the stand-alone tools are freely accessible at http://rna.informatik.uni-freiburg.de.

Impact of target mRNA structure on siRNA silencing efficiency: A large-scale study.

Science.gov (United States)

Gredell, Joseph A; Berger, Angela K; Walton, S Patrick

2008-07-01

The selection of active siRNAs is generally based on identifying siRNAs with certain sequence and structural properties. However, the efficiency of RNA interference has also been shown to depend on the structure of the target mRNA, primarily through studies using exogenous transcripts with well-defined secondary structures in the vicinity of the target sequence. While these studies provide a means for examining the impact of target sequence and structure independently, the predicted secondary structures for these transcripts are often not reflective of structures that form in full-length, native mRNAs where interactions can occur between relatively remote segments of the mRNAs. Here, using a combination of experimental results and analysis of a large dataset, we demonstrate that the accessibility of certain local target structures on the mRNA is an important determinant in the gene silencing ability of siRNAs. siRNAs targeting the enhanced green fluorescent protein were chosen using a minimal siRNA selection algorithm followed by classification based on the predicted minimum free energy structures of the target transcripts. Transfection into HeLa and HepG2 cells revealed that siRNAs targeting regions of the mRNA predicted to have unpaired 5'- and 3'-ends resulted in greater gene silencing than regions predicted to have other types of secondary structure. These results were confirmed by analysis of gene silencing data from previously published siRNAs, which showed that mRNA target regions unpaired at either the 5'-end or 3'-end were silenced, on average, approximately 10% more strongly than target regions unpaired in the center or primarily paired throughout. We found this effect to be independent of the structure of the siRNA guide strand. Taken together, these results suggest minimal requirements for nucleation of hybridization between the siRNA guide strand and mRNA and that both mRNA and guide strand structure should be considered when choosing candidate si

Interaction of tRNA with Eukaryotic Ribosome

Directory of Open Access Journals (Sweden)

Dmitri Graifer

2015-03-01

Full Text Available This paper is a review of currently available data concerning interactions of tRNAs with the eukaryotic ribosome at various stages of translation. These data include the results obtained by means of cryo-electron microscopy and X-ray crystallography applied to various model ribosomal complexes, site-directed cross-linking with the use of tRNA derivatives bearing chemically or photochemically reactive groups in the CCA-terminal fragment and chemical probing of 28S rRNA in the region of the peptidyl transferase center. Similarities and differences in the interactions of tRNAs with prokaryotic and eukaryotic ribosomes are discussed with concomitant consideration of the extent of resemblance between molecular mechanisms of translation in eukaryotes and bacteria.

Characterization of mRNA-cytoskeleton interactions in situ using FMTRIP and proximity ligation.

Directory of Open Access Journals (Sweden)

Jeenah Jung

Full Text Available Many studies have demonstrated an association between the cytoskeleton and mRNA, as well as the asymmetric distribution of mRNA granules within the cell in response to various signaling events. It is likely that the extensive cytoskeletal network directs mRNA transport and localization, with different cytoskeletal elements having their own specific roles. In order to understand the spatiotemporal changes in the interactions between the mRNA and the cytoskeleton as a response to a stimulus, a technique that can visualize and quantify these changes across a population of cells while capturing cell-to-cell variations is required. Here, we demonstrate a method for imaging and quantifying mRNA-cytoskeleton interactions on a per cell basis with single-interaction sensitivity. Using a proximity ligation assay with flag-tagged multiply-labeled tetravalent RNA imaging probes (FMTRIP, we quantified interactions between mRNAs and β-tubulin, vimentin, or filamentous actin (F-actin for two different mRNAs, poly(A + and β-actin mRNA, in two different cell types, A549 cells and human dermal fibroblasts (HDF. We found that the mRNAs interacted predominantly with F-actin (>50% in HDF, >20% in A549 cells, compared to β-tubulin (<5% and vimentin (11-13%. This likely reflects differences in mRNA management by the two cell types. We then quantified changes in these interactions in response to two perturbations, F-actin depolymerization and arsenite-induced oxidative stress, both of which alter either the cytoskeleton itself and mRNA localization. Both perturbations led to a decrease in poly(A + mRNA interactions with F-actin and an increase in the interactions with microtubules, in a time dependent manner.

Conformational Selection and Induced Fit for RNA Polymerase and RNA/DNA Hybrid Backtracked Recognition

Directory of Open Access Journals (Sweden)

Haifeng eChen

2015-11-01

Full Text Available RNA polymerase catalyzes transcription with a high fidelity. If DNA/RNA mismatch or DNA damage occurs downstream, a backtracked RNA polymerase can proofread this situation. However, the backtracked mechanism is still poorly understood. Here we have performed multiple explicit-solvent molecular dynamics (MD simulations on bound and apo DNA/RNA hybrid to study backtracked recognition. MD simulations at room temperature suggest that specific electrostatic interactions play key roles in the backtracked recognition between the polymerase and DNA/RNA hybrid. Kinetics analysis at high temperature shows that bound and apo DNA/RNA hybrid unfold via a two-state process. Both kinetics and free energy landscape analyses indicate that bound DNA/RNA hybrid folds in the order of DNA/RNA contracting, the tertiary folding and polymerase binding. The predicted Φ-values suggest that C7, G9, dC12, dC15 and dT16 are key bases for the backtracked recognition of DNA/RNA hybrid. The average RMSD values between the bound structures and the corresponding apo ones and Kolmogorov-Smirnov (KS P test analyses indicate that the recognition between DNA/RNA hybrid and polymerase might follow an induced fit mechanism for DNA/RNA hybrid and conformation selection for polymerase. Furthermore, this method could be used to relative studies of specific recognition between nucleic acid and protein.

microRNA-independent recruitment of Argonaute 1 to nanos mRNA through the Smaug RNA-binding protein

OpenAIRE

Pinder, Benjamin D; Smibert, Craig A

2012-01-01

Argonaute 1 directly interacts with the RNA binding protein Smaug in Drosophila, is thereby recruited to the Smaug target nanos mRNA and is required for Smaug-mediated translational repression of the nanos mRNA.

Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

Science.gov (United States)

Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo; Schroeder, Susan J

2017-05-01

Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. © 2017 Phan et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Analysis of electric moments of RNA-binding proteins: implications for mechanism and prediction

Directory of Open Access Journals (Sweden)

Sarai Akinori

2011-02-01

Full Text Available Abstract Background Protein-RNA interactions play important role in many biological processes such as gene regulation, replication, protein synthesis and virus assembly. Although many structures of various types of protein-RNA complexes have been determined, the mechanism of protein-RNA recognition remains elusive. We have earlier shown that the simplest electrostatic properties viz. charge, dipole and quadrupole moments, calculated from backbone atomic coordinates of proteins are biased relative to other proteins, and these quantities can be used to identify DNA-binding proteins. Closely related, RNA-binding proteins are investigated in this study. In particular, discrimination between various types of RNA-binding proteins, evolutionary conservation of these bulk electrostatic features and effect of conformational changes by complex formation are investigated. Basic binding mechanism of a putative RNA-binding protein (HI1333 from Haemophilus influenza is suggested as a potential application of this study. Results We found that similar to DNA-binding proteins (DBPs, RNA-binding proteins (RBPs also show significantly higher values of electric moments. However, higher moments in RBPs are found to strongly depend on their functional class: proteins binding to ribosomal RNA (rRNA constitute the only class with all three of the properties (charge, dipole and quadrupole moments being higher than control proteins. Neural networks were trained using leave-one-out cross-validation to predict RBPs from control data as well as pair-wise classification capacity between proteins binding to various RNA types. RBPs and control proteins reached up to 78% accuracy measured by the area under the ROC curve. Proteins binding to rRNA are found to be best distinguished (AUC = 79%. Changes in dipole and quadrupole moments between unbound and bound structures were small and these properties are found to be robust under complex formation. Conclusions Bulk electric

The expanding universe of ribonucleoproteins: of novel RNA-binding proteins and unconventional interactions.

Science.gov (United States)

Beckmann, Benedikt M; Castello, Alfredo; Medenbach, Jan

2016-06-01

Post-transcriptional regulation of gene expression plays a critical role in almost all cellular processes. Regulation occurs mostly by RNA-binding proteins (RBPs) that recognise RNA elements and form ribonucleoproteins (RNPs) to control RNA metabolism from synthesis to decay. Recently, the repertoire of RBPs was significantly expanded owing to methodological advances such as RNA interactome capture. The newly identified RNA binders are involved in diverse biological processes and belong to a broad spectrum of protein families, many of them exhibiting enzymatic activities. This suggests the existence of an extensive crosstalk between RNA biology and other, in principle unrelated, cell functions such as intermediary metabolism. Unexpectedly, hundreds of new RBPs do not contain identifiable RNA-binding domains (RBDs), raising the question of how they interact with RNA. Despite the many functions that have been attributed to RNA, our understanding of RNPs is still mostly governed by a rather protein-centric view, leading to the idea that proteins have evolved to bind to and regulate RNA and not vice versa. However, RNPs formed by an RNA-driven interaction mechanism (RNA-determined RNPs) are abundant and offer an alternative explanation for the surprising lack of classical RBDs in many RNA-interacting proteins. Moreover, RNAs can act as scaffolds to orchestrate and organise protein networks and directly control their activity, suggesting that nucleic acids might play an important regulatory role in many cellular processes, including metabolism.

Analysis of hepatitis C virus RNA dimerization and core–RNA interactions

Science.gov (United States)

Ivanyi-Nagy, Roland; Kanevsky, Igor; Gabus, Caroline; Lavergne, Jean-Pierre; Ficheux, Damien; Penin, François; Fossé, Philippe; Darlix, Jean-Luc

2006-01-01

The core protein of hepatitis C virus (HCV) has been shown previously to act as a potent nucleic acid chaperone in vitro, promoting the dimerization of the 3′-untranslated region (3′-UTR) of the HCV genomic RNA, a process probably mediated by a small, highly conserved palindromic RNA motif, named DLS (dimer linkage sequence) [G. Cristofari, R. Ivanyi-Nagy, C. Gabus, S. Boulant, J. P. Lavergne, F. Penin and J. L. Darlix (2004) Nucleic Acids Res., 32, 2623–2631]. To investigate in depth HCV RNA dimerization, we generated a series of point mutations in the DLS region. We find that both the plus-strand 3′-UTR and the complementary minus-strand RNA can dimerize in the presence of core protein, while mutations in the DLS (among them a single point mutation that abolished RNA replication in a HCV subgenomic replicon system) completely abrogate dimerization. Structural probing of plus- and minus-strand RNAs, in their monomeric and dimeric forms, indicate that the DLS is the major if not the sole determinant of UTR RNA dimerization. Furthermore, the N-terminal basic amino acid clusters of core protein were found to be sufficient to induce dimerization, suggesting that they retain full RNA chaperone activity. These findings may have important consequences for understanding the HCV replicative cycle and the genetic variability of the virus. PMID:16707664

Analysis of hepatitis C virus RNA dimerization and core-RNA interactions.

Science.gov (United States)

Ivanyi-Nagy, Roland; Kanevsky, Igor; Gabus, Caroline; Lavergne, Jean-Pierre; Ficheux, Damien; Penin, François; Fossé, Philippe; Darlix, Jean-Luc

2006-01-01

The core protein of hepatitis C virus (HCV) has been shown previously to act as a potent nucleic acid chaperone in vitro, promoting the dimerization of the 3'-untranslated region (3'-UTR) of the HCV genomic RNA, a process probably mediated by a small, highly conserved palindromic RNA motif, named DLS (dimer linkage sequence) [G. Cristofari, R. Ivanyi-Nagy, C. Gabus, S. Boulant, J. P. Lavergne, F. Penin and J. L. Darlix (2004) Nucleic Acids Res., 32, 2623-2631]. To investigate in depth HCV RNA dimerization, we generated a series of point mutations in the DLS region. We find that both the plus-strand 3'-UTR and the complementary minus-strand RNA can dimerize in the presence of core protein, while mutations in the DLS (among them a single point mutation that abolished RNA replication in a HCV subgenomic replicon system) completely abrogate dimerization. Structural probing of plus- and minus-strand RNAs, in their monomeric and dimeric forms, indicate that the DLS is the major if not the sole determinant of UTR RNA dimerization. Furthermore, the N-terminal basic amino acid clusters of core protein were found to be sufficient to induce dimerization, suggesting that they retain full RNA chaperone activity. These findings may have important consequences for understanding the HCV replicative cycle and the genetic variability of the virus.

Distinct Mechanism Evolved for Mycobacterial RNA Polymerase and Topoisomerase I Protein-Protein Interaction.

Science.gov (United States)

Banda, Srikanth; Cao, Nan; Tse-Dinh, Yuk-Ching

2017-09-15

We report here a distinct mechanism of interaction between topoisomerase I and RNA polymerase in Mycobacterium tuberculosis and Mycobacterium smegmatis that has evolved independently from the previously characterized interaction between bacterial topoisomerase I and RNA polymerase. Bacterial DNA topoisomerase I is responsible for preventing the hyper-negative supercoiling of genomic DNA. The association of topoisomerase I with RNA polymerase during transcription elongation could efficiently relieve transcription-driven negative supercoiling. Our results demonstrate a direct physical interaction between the C-terminal domains of topoisomerase I (TopoI-CTDs) and the β' subunit of RNA polymerase of M. smegmatis in the absence of DNA. The TopoI-CTDs in mycobacteria are evolutionarily unrelated in amino acid sequence and three-dimensional structure to the TopoI-CTD found in the majority of bacterial species outside Actinobacteria, including Escherichia coli. The functional interaction between topoisomerase I and RNA polymerase has evolved independently in mycobacteria and E. coli, with distinctively different structural elements of TopoI-CTD utilized for this protein-protein interaction. Zinc ribbon motifs in E. coli TopoI-CTD are involved in the interaction with RNA polymerase. For M. smegmatis TopoI-CTD, a 27-amino-acid tail that is rich in basic residues at the C-terminal end is responsible for the interaction with RNA polymerase. Overexpression of recombinant TopoI-CTD in M. smegmatis competed with the endogenous topoisomerase I for protein-protein interactions with RNA polymerase. The TopoI-CTD overexpression resulted in decreased survival following treatment with antibiotics and hydrogen peroxide, supporting the importance of the protein-protein interaction between topoisomerase I and RNA polymerase during stress response of mycobacteria. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Comparative Taxonomy of Parallel Algorithms for RNA Secondary Structure Prediction

Science.gov (United States)

Al-Khatib, Ra’ed M.; Abdullah, Rosni; Rashid, Nur’Aini Abdul

2010-01-01

RNA molecules have been discovered playing crucial roles in numerous biological and medical procedures and processes. RNA structures determination have become a major problem in the biology context. Recently, computer scientists have empowered the biologists with RNA secondary structures that ease an understanding of the RNA functions and roles. Detecting RNA secondary structure is an NP-hard problem, especially in pseudoknotted RNA structures. The detection process is also time-consuming; as a result, an alternative approach such as using parallel architectures is a desirable option. The main goal in this paper is to do an intensive investigation of parallel methods used in the literature to solve the demanding issues, related to the RNA secondary structure prediction methods. Then, we introduce a new taxonomy for the parallel RNA folding methods. Based on this proposed taxonomy, a systematic and scientific comparison is performed among these existing methods. PMID:20458364

Computational prediction and experimental validation of Ciona intestinalis microRNA genes

Directory of Open Access Journals (Sweden)

Pasquinelli Amy E

2007-11-01

Full Text Available Abstract Background This study reports the first collection of validated microRNA genes in the sea squirt, Ciona intestinalis. MicroRNAs are processed from hairpin precursors to ~22 nucleotide RNAs that base pair to target mRNAs and inhibit expression. As a member of the subphylum Urochordata (Tunicata whose larval form has a notochord, the sea squirt is situated at the emergence of vertebrates, and therefore may provide information about the evolution of molecular regulators of early development. Results In this study, computational methods were used to predict 14 microRNA gene families in Ciona intestinalis. The microRNA prediction algorithm utilizes configurable microRNA sequence conservation and stem-loop specificity parameters, grouping by miRNA family, and phylogenetic conservation to the related species, Ciona savignyi. The expression for 8, out of 9 attempted, of the putative microRNAs in the adult tissue of Ciona intestinalis was validated by Northern blot analyses. Additionally, a target prediction algorithm was implemented, which identified a high confidence list of 240 potential target genes. Over half of the predicted targets can be grouped into the gene ontology categories of metabolism, transport, regulation of transcription, and cell signaling. Conclusion The computational techniques implemented in this study can be applied to other organisms and serve to increase the understanding of the origins of non-coding RNAs, embryological and cellular developmental pathways, and the mechanisms for microRNA-controlled gene regulatory networks.

Identification of Subtype Specific miRNA-mRNA Functional Regulatory Modules in Matched miRNA-mRNA Expression Data: Multiple Myeloma as a Case

Directory of Open Access Journals (Sweden)

Yunpeng Zhang

2015-01-01

Full Text Available Identification of miRNA-mRNA modules is an important step to elucidate their combinatorial effect on the pathogenesis and mechanisms underlying complex diseases. Current identification methods primarily are based upon miRNA-target information and matched miRNA and mRNA expression profiles. However, for heterogeneous diseases, the miRNA-mRNA regulatory mechanisms may differ between subtypes, leading to differences in clinical behavior. In order to explore the pathogenesis of each subtype, it is important to identify subtype specific miRNA-mRNA modules. In this study, we integrated the Ping-Pong algorithm and multiobjective genetic algorithm to identify subtype specific miRNA-mRNA functional regulatory modules (MFRMs through integrative analysis of three biological data sets: GO biological processes, miRNA target information, and matched miRNA and mRNA expression data. We applied our method on a heterogeneous disease, multiple myeloma (MM, to identify MM subtype specific MFRMs. The constructed miRNA-mRNA regulatory networks provide modular outlook at subtype specific miRNA-mRNA interactions. Furthermore, clustering analysis demonstrated that heterogeneous MFRMs were able to separate corresponding MM subtypes. These subtype specific MFRMs may aid in the further elucidation of the pathogenesis of each subtype and may serve to guide MM subtype diagnosis and treatment.

CircRNA-0004904, CircRNA-0001855, and PAPP-A: Potential Novel Biomarkers for the Prediction of Preeclampsia

Directory of Open Access Journals (Sweden)

Min Jiang

2018-05-01

Full Text Available Background/Aims: Circular RNAs (circRNAs are transcribed prevalently in the genome; however, their potential roles in multiple cardiovascular diseases, particularly preeclampsia (PE, are not yet well understood. This study investigated the expression profiles of circRNAs and explored circRNA-mediated pregnancy-associated plasma protein A (PAPP-A expression as a potential biomarker for PE before 20 weeks of pregnancy. Methods: A nested case-control two-phase screening/validation study was performed in pregnant women before 20 weeks of gestation (before clinical diagnosis at Guangzhou Women and Children’s Medical Center from 2012 to 2015. In the screening phase, circRNA expression profiles of blood cells were assessed using a human circRNA microarray, which was designed to detect simultaneously 5396 circRNAs, in 5 patients with PE and 5 age- and gestational week-matched controls. In the validation phase, 18 circRNAs in blood cells predicted by bioinformatics tools were validated by quantitative reverse transcription PCR in a cohort of 60 patients (PE and age-, gestational week-, and sample storage time-matched controls. Then, we examined the involvement of circRNAs in PE-related pathways via interactions with miRNAs by multiple bioinformatics approaches. Bioinformatics analysis predicted that hsa_circ_0004904 and hsa_circ_0001855 miRNA sponges directly target PAPP-A. PAPP-A was verified in the serum of the same cohort of patients using an enzyme-linked immunosorbent assay. Finally, we combined PAPP-A with circRNAs to create a novel preclinical diagnostic model for PE with logistic regression and evaluated the efficiency of this model with receiver operating curve analysis. Results: Volcano plot analysis using various parameters showed that circRNAs were differentially expressed among both groups (P < 0.01, fold change > 2. In the screening phase, we found that 2178 circRNAs were differentially expressed between the control and PE groups, in

Mechanism of microRNA-target interaction: molecular dynamics simulations and thermodynamics analysis.

Directory of Open Access Journals (Sweden)

Yonghua Wang

Full Text Available MicroRNAs (miRNAs are endogenously produced approximately 21-nt riboregulators that associate with Argonaute (Ago proteins to direct mRNA cleavage or repress the translation of complementary RNAs. Capturing the molecular mechanisms of miRNA interacting with its target will not only reinforce the understanding of underlying RNA interference but also fuel the design of more effective small-interfering RNA strands. To address this, in the present work the RNA-bound (Ago-miRNA, Ago-miRNA-target and RNA-free Ago forms were analyzed by performing both molecular dynamics simulations and thermodynamic analysis. Based on the principal component analysis results of the simulation trajectories as well as the correlation analysis in fluctuations of residues, we discover that: 1 three important (PAZ, Mid and PIWI domains exist in Argonaute which define the global dynamics of the protein; 2 the interdomain correlated movements are so crucial for the interaction of Ago-RNAs that they not only facilitate the relaxation of the interactions between residues surrounding the RNA binding channel but also induce certain conformational changes; and 3 it is just these conformational changes that expand the cavity of the active site and open putative pathways for both the substrate uptake and product release. In addition, by thermodynamic analysis we also discover that for both the guide RNA 5'-end recognition and the facilitated site-specific cleavage of the target, the presence of two metal ions (of Mg(2+ plays a predominant role, and this conclusion is consistent with the observed enzyme catalytic cleavage activity in the ternary complex (Ago-miRNA-mRNA. Our results find that it is the set of arginine amino acids concentrated in the nucleotide-binding channel in Ago, instead of the conventionally-deemed seed base-paring, that makes greater contributions in stabilizing the binding of the nucleic acids to Ago.

Mechanism of microRNA-target interaction: molecular dynamics simulations and thermodynamics analysis.

Science.gov (United States)

Wang, Yonghua; Li, Yan; Ma, Zhi; Yang, Wei; Ai, Chunzhi

2010-07-29

MicroRNAs (miRNAs) are endogenously produced approximately 21-nt riboregulators that associate with Argonaute (Ago) proteins to direct mRNA cleavage or repress the translation of complementary RNAs. Capturing the molecular mechanisms of miRNA interacting with its target will not only reinforce the understanding of underlying RNA interference but also fuel the design of more effective small-interfering RNA strands. To address this, in the present work the RNA-bound (Ago-miRNA, Ago-miRNA-target) and RNA-free Ago forms were analyzed by performing both molecular dynamics simulations and thermodynamic analysis. Based on the principal component analysis results of the simulation trajectories as well as the correlation analysis in fluctuations of residues, we discover that: 1) three important (PAZ, Mid and PIWI) domains exist in Argonaute which define the global dynamics of the protein; 2) the interdomain correlated movements are so crucial for the interaction of Ago-RNAs that they not only facilitate the relaxation of the interactions between residues surrounding the RNA binding channel but also induce certain conformational changes; and 3) it is just these conformational changes that expand the cavity of the active site and open putative pathways for both the substrate uptake and product release. In addition, by thermodynamic analysis we also discover that for both the guide RNA 5'-end recognition and the facilitated site-specific cleavage of the target, the presence of two metal ions (of Mg(2+)) plays a predominant role, and this conclusion is consistent with the observed enzyme catalytic cleavage activity in the ternary complex (Ago-miRNA-mRNA). Our results find that it is the set of arginine amino acids concentrated in the nucleotide-binding channel in Ago, instead of the conventionally-deemed seed base-paring, that makes greater contributions in stabilizing the binding of the nucleic acids to Ago.

Computational analysis of RNA-protein interaction interfaces via the Voronoi diagram.

Science.gov (United States)

Mahdavi, Sedigheh; Mohades, Ali; Salehzadeh Yazdi, Ali; Jahandideh, Samad; Masoudi-Nejad, Ali

2012-01-21

Cellular functions are mediated by various biological processes including biomolecular interactions, such as protein-protein, DNA-protein and RNA-protein interactions in which RNA-Protein interactions are indispensable for many biological processes like cell development and viral replication. Unlike the protein-protein and protein-DNA interactions, accurate mechanisms and structures of the RNA-Protein complexes are not fully understood. A large amount of theoretical evidence have shown during the past several years that computational geometry is the first pace in understanding the binding profiles and plays a key role in the study of intricate biological structures, interactions and complexes. In this paper, RNA-Protein interaction interface surface is computed via the weighted Voronoi diagram of atoms. Using two filter operations provides a natural definition for interface atoms as classic methods. Unbounded parts of Voronoi facets that are far from the complex are trimmed using modified convex hull of atom centers. This algorithm is implemented to a database with different RNA-Protein complexes extracted from Protein Data Bank (PDB). Afterward, the features of interfaces have been computed and compared with classic method. The results show high correlation coefficients between interface size in the Voronoi model and the classical model based on solvent accessibility, as well as high accuracy and precision in comparison to classical model. Copyright © 2011 Elsevier Ltd. All rights reserved.

Statistical properties of thermodynamically predicted RNA secondary structures in viral genomes

Science.gov (United States)

Spanò, M.; Lillo, F.; Miccichè, S.; Mantegna, R. N.

2008-10-01

By performing a comprehensive study on 1832 segments of 1212 complete genomes of viruses, we show that in viral genomes the hairpin structures of thermodynamically predicted RNA secondary structures are more abundant than expected under a simple random null hypothesis. The detected hairpin structures of RNA secondary structures are present both in coding and in noncoding regions for the four groups of viruses categorized as dsDNA, dsRNA, ssDNA and ssRNA. For all groups, hairpin structures of RNA secondary structures are detected more frequently than expected for a random null hypothesis in noncoding rather than in coding regions. However, potential RNA secondary structures are also present in coding regions of dsDNA group. In fact, we detect evolutionary conserved RNA secondary structures in conserved coding and noncoding regions of a large set of complete genomes of dsDNA herpesviruses.

Optimizing prognosis-related key miRNA-target interactions responsible for cancer metastasis.

Science.gov (United States)

Zhao, Hongying; Yuan, Huating; Hu, Jing; Xu, Chaohan; Liao, Gaoming; Yin, Wenkang; Xu, Liwen; Wang, Li; Zhang, Xinxin; Shi, Aiai; Li, Jing; Xiao, Yun

2017-12-12

Increasing evidence suggests that the abnormality of microRNAs (miRNAs) and their downstream targets is frequently implicated in the pathogenesis of human cancers, however, the clinical benefit of causal miRNA-target interactions has been seldom studied. Here, we proposed a computational method to optimize prognosis-related key miRNA-target interactions by combining transcriptome and clinical data from thousands of TCGA tumors across 16 cancer types. We obtained a total of 1,956 prognosis-related key miRNA-target interactions between 112 miRNAs and 1,443 their targets. Interestingly, these key target genes are specifically involved in tumor progression-related functions, such as 'cell adhesion' and 'cell migration'. Furthermore, they are most significantly correlated with 'tissue invasion and metastasis', a hallmark of metastasis, in ten distinct types of cancer through the hallmark analysis. These results implicated that the prognosis-related key miRNA-target interactions were highly associated with cancer metastasis. Finally, we observed that the combination of these key miRNA-target interactions allowed to distinguish patients with good prognosis from those with poor prognosis both in most TCGA cancer types and independent validation sets, highlighting their roles in cancer metastasis. We provided a user-friendly database named miRNATarget (freely available at http://biocc.hrbmu.edu.cn/miRNATar/), which provides an overview of the prognosis-related key miRNA-target interactions across 16 cancer types.

An Interaction between KSHV ORF57 and UIF Provides mRNA-Adaptor Redundancy in Herpesvirus Intronless mRNA Export

Science.gov (United States)

Jackson, Brian R.; Boyne, James R.; Noerenberg, Marko; Taylor, Adam; Hautbergue, Guillaume M.; Walsh, Matthew J.; Wheat, Rachel; Blackbourn, David J.; Wilson, Stuart A.; Whitehouse, Adrian

2011-01-01

The hTREX complex mediates cellular bulk mRNA nuclear export by recruiting the nuclear export factor, TAP, via a direct interaction with the export adaptor, Aly. Intriguingly however, depletion of Aly only leads to a modest reduction in cellular mRNA nuclear export, suggesting the existence of additional mRNA nuclear export adaptor proteins. In order to efficiently export Kaposi's sarcoma-associated herpesvirus (KSHV) intronless mRNAs from the nucleus, the KSHV ORF57 protein recruits hTREX onto viral intronless mRNAs allowing access to the TAP-mediated export pathway. Similarly however, depletion of Aly only leads to a modest reduction in the nuclear export of KSHV intronless mRNAs. Herein, we identify a novel interaction between ORF57 and the cellular protein, UIF. We provide the first evidence that the ORF57-UIF interaction enables the recruitment of hTREX and TAP to KSHV intronless mRNAs in Aly-depleted cells. Strikingly, depletion of both Aly and UIF inhibits the formation of an ORF57-mediated nuclear export competent ribonucleoprotein particle and consequently prevents ORF57-mediated mRNA nuclear export and KSHV protein production. Importantly, these findings highlight that redundancy exists in the eukaryotic system for certain hTREX components involved in the mRNA nuclear export of intronless KSHV mRNAs. PMID:21814512

Nucleolin Mediates MicroRNA-directed CSF-1 mRNA Deadenylation but Increases Translation of CSF-1 mRNA*

Science.gov (United States)

Woo, Ho-Hyung; Baker, Terri; Laszlo, Csaba; Chambers, Setsuko K.

2013-01-01

CSF-1 mRNA 3′UTR contains multiple unique motifs, including a common microRNA (miRNA) target in close proximity to a noncanonical G-quadruplex and AU-rich elements (AREs). Using a luciferase reporter system fused to CSF-1 mRNA 3′UTR, disruption of the miRNA target region, G-quadruplex, and AREs together dramatically increased reporter RNA levels, suggesting important roles for these cis-acting regulatory elements in the down-regulation of CSF-1 mRNA. We find that nucleolin, which binds both G-quadruplex and AREs, enhances deadenylation of CSF-1 mRNA, promoting CSF-1 mRNA decay, while having the capacity to increase translation of CSF-1 mRNA. Through interaction with the CSF-1 3′UTR miRNA common target, we find that miR-130a and miR-301a inhibit CSF-1 expression by enhancing mRNA decay. Silencing of nucleolin prevents the miRNA-directed mRNA decay, indicating a requirement for nucleolin in miRNA activity on CSF-1 mRNA. Downstream effects followed by miR-130a and miR-301a inhibition of directed cellular motility of ovarian cancer cells were found to be dependent on nucleolin. The paradoxical effects of nucleolin on miRNA-directed CSF-1 mRNA deadenylation and on translational activation were explored further. The nucleolin protein contains four acidic stretches, four RNA recognition motifs (RRMs), and nine RGG repeats. All three domains in nucleolin regulate CSF-1 mRNA and protein levels. RRMs increase CSF-1 mRNA, whereas the acidic and RGG domains decrease CSF-1 protein levels. This suggests that nucleolin has the capacity to differentially regulate both CSF-1 RNA and protein levels. Our finding that nucleolin interacts with Ago2 indirectly via RNA and with poly(A)-binding protein C (PABPC) directly suggests a nucleolin-Ago2-PABPC complex formation on mRNA. This complex is in keeping with our suggestion that nucleolin may work with PABPC as a double-edged sword on both mRNA deadenylation and translational activation. Our findings underscore the complexity of

MirZ: an integrated microRNA expression atlas and target prediction resource.

Science.gov (United States)

Hausser, Jean; Berninger, Philipp; Rodak, Christoph; Jantscher, Yvonne; Wirth, Stefan; Zavolan, Mihaela

2009-07-01

MicroRNAs (miRNAs) are short RNAs that act as guides for the degradation and translational repression of protein-coding mRNAs. A large body of work showed that miRNAs are involved in the regulation of a broad range of biological functions, from development to cardiac and immune system function, to metabolism, to cancer. For most of the over 500 miRNAs that are encoded in the human genome the functions still remain to be uncovered. Identifying miRNAs whose expression changes between cell types or between normal and pathological conditions is an important step towards characterizing their function as is the prediction of mRNAs that could be targeted by these miRNAs. To provide the community the possibility of exploring interactively miRNA expression patterns and the candidate targets of miRNAs in an integrated environment, we developed the MirZ web server, which is accessible at www.mirz.unibas.ch. The server provides experimental and computational biologists with statistical analysis and data mining tools operating on up-to-date databases of sequencing-based miRNA expression profiles and of predicted miRNA target sites in species ranging from Caenorhabditis elegans to Homo sapiens.

Plant RNA binding proteins for control of RNA virus infection

Directory of Open Access Journals (Sweden)

Sung Un eHuh

2013-12-01

Full Text Available Plant RNA viruses have effective strategies to infect host plants through either direct or indirect interactions with various host proteins, thus suppressing the host immune system. When plant RNA viruses enter host cells exposed RNAs of viruses are recognized by the host immune system through processes such as siRNA-dependent silencing. Interestingly, some host RNA binding proteins have been involved in the inhibition of RNA virus replication, movement, and translation through RNA-specific binding. Host plants intensively use RNA binding proteins for defense against viral infections in nature. In this mini review, we will summarize the function of some host RNA binding proteins which act in a sequence-specific binding manner to the infecting virus RNA. It is important to understand how plants effectively suppresses RNA virus infections via RNA binding proteins, and this defense system can be potentially developed as a synthetic virus defense strategy for use in crop engineering.

A path-based measurement for human miRNA functional similarities using miRNA-disease associations

Science.gov (United States)

Ding, Pingjian; Luo, Jiawei; Xiao, Qiu; Chen, Xiangtao

2016-09-01

Compared with the sequence and expression similarity, miRNA functional similarity is so important for biology researches and many applications such as miRNA clustering, miRNA function prediction, miRNA synergism identification and disease miRNA prioritization. However, the existing methods always utilized the predicted miRNA target which has high false positive and false negative to calculate the miRNA functional similarity. Meanwhile, it is difficult to achieve high reliability of miRNA functional similarity with miRNA-disease associations. Therefore, it is increasingly needed to improve the measurement of miRNA functional similarity. In this study, we develop a novel path-based calculation method of miRNA functional similarity based on miRNA-disease associations, called MFSP. Compared with other methods, our method obtains higher average functional similarity of intra-family and intra-cluster selected groups. Meanwhile, the lower average functional similarity of inter-family and inter-cluster miRNA pair is obtained. In addition, the smaller p-value is achieved, while applying Wilcoxon rank-sum test and Kruskal-Wallis test to different miRNA groups. The relationship between miRNA functional similarity and other information sources is exhibited. Furthermore, the constructed miRNA functional network based on MFSP is a scale-free and small-world network. Moreover, the higher AUC for miRNA-disease prediction indicates the ability of MFSP uncovering miRNA functional similarity.

Cancer-Related Triplets of mRNA-lncRNA-miRNA Revealed by Integrative Network in Uterine Corpus Endometrial Carcinoma

Directory of Open Access Journals (Sweden)

Chenglin Liu

2017-01-01

Full Text Available The regulation of transcriptome expression level is a complex process involving multiple-level interactions among molecules such as protein coding RNA (mRNA, long noncoding RNA (lncRNA, and microRNA (miRNA, which are essential for the transcriptome stability and maintenance and regulation of body homeostasis. The availability of multilevel expression data enables a comprehensive view of the regulatory network. In this study, we analyzed the coding and noncoding gene expression profiles of 301 patients with uterine corpus endometrial carcinoma (UCEC. A new method was proposed to construct a genome-wide integrative network based on variance inflation factor (VIF regression method. The cross-regulation relations of mRNA, lncRNA, and miRNA were then selected based on clique-searching algorithm from the network, when any two molecules of the three were shown as interacting according to the integrative network. Such relation, which we call the mRNA-lncRNA-miRNA triplet, demonstrated the complexity in transcriptome regulation process. Finally, six UCEC-related triplets were selected in which the mRNA participates in endometrial carcinoma pathway, such as CDH1 and TP53. The multi-type RNAs are proved to be cross-regulated as to each of the six triplets according to literature. All the triplets demonstrated the association with the initiation and progression of UCEC. Our method provides a comprehensive strategy for the investigation of transcriptome regulation mechanism.

Methylated nucleosides in tRNA and tRNA methyltransferases

Directory of Open Access Journals (Sweden)

Hiroyuki eHori

2014-05-01

Full Text Available To date, more than 90 modified nucleosides have been found in tRNA and the biosynthetic pathways of the majority of tRNA modifications include a methylation step(s. Recent studies of the biosynthetic pathways have demonstrated that the availability of methyl group donors for the methylation in tRNA is important for correct and efficient protein synthesis. In this review, I focus on the methylated nucleosides and tRNA methyltransferases. The primary functions of tRNA methylations are linked to the different steps of protein synthesis, such as the stabilization of tRNA structure, reinforcement of the codon–anticodon interaction, regulation of wobble base pairing, and prevention of frameshift errors. However, beyond these basic functions, recent studies have demonstrated that tRNA methylations are also involved in the RNA quality control system and regulation of tRNA localization in the cell. In a thermophilic eubacterium, tRNA modifications and the modification enzymes form a network that responses to temperature changes. Furthermore, several modifications are involved in genetic diseases, infections, and the immune response. Moreover, structural, biochemical, and bioinformatics studies of tRNA methyltransferases have been clarifying the details of tRNA methyltransferases and have enabled these enzymes to be classified. In the final section, the evolution of modification enzymes is discussed.

Terminal structures of West Nile virus genomic RNA and their interactions with viral NS5 protein

International Nuclear Information System (INIS)

Dong Hongping; Zhang Bo; Shi Peiyong

2008-01-01

Genome cyclization is essential for flavivirus replication. We used RNases to probe the structures formed by the 5'-terminal 190 nucleotides and the 3'-terminal 111 nucleotides of the West Nile virus (WNV) genomic RNA. When analyzed individually, the two RNAs adopt stem-loop structures as predicted by the thermodynamic-folding program. However, when mixed together, the two RNAs form a duplex that is mediated through base-pairings of two sets of RNA elements (5'CS/3'CSI and 5'UAR/3'UAR). Formation of the RNA duplex facilitates a conformational change that leaves the 3'-terminal nucleotides of the genome (position - 8 to - 16) to be single-stranded. Viral NS5 binds specifically to the 5'-terminal stem-loop (SL1) of the genomic RNA. The 5'SL1 RNA structure is essential for WNV replication. The study has provided further evidence to suggest that flavivirus genome cyclization and NS5/5'SL1 RNA interaction facilitate NS5 binding to the 3' end of the genome for the initiation of viral minus-strand RNA synthesis

MicroRNA transfection and AGO-bound CLIP-seq data sets reveal distinct determinants of miRNA action

DEFF Research Database (Denmark)

Wen, Jiayu; Parker, Brian J; Jacobsen, Anders

2011-01-01

the predictive effect of target flanking features. We observe distinct target determinants between expression-based and CLIP-based data. Target flanking features such as flanking region conservation are an important AGO-binding determinant-we hypothesize that CLIP experiments have a preference for strongly bound......Microarray expression analyses following miRNA transfection/inhibition and, more recently, Argonaute cross-linked immunoprecipitation (CLIP)-seq assays have been used to detect miRNA target sites. CLIP and expression approaches measure differing stages of miRNA functioning-initial binding of the mi...... miRNP-target interactions involving adjacent RNA-binding proteins that increase the strength of cross-linking. In contrast, seed-related features are major determinants in expression-based studies, but less so for CLIP-seq studies, and increased miRNA concentrations typical of transfection studies...

RNA-Binding Proteins Revisited – The Emerging Arabidopsis mRNA Interactome

KAUST Repository

Köster, Tino

2017-04-13

RNA–protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture – where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes.

RNA-Binding Proteins Revisited – The Emerging Arabidopsis mRNA Interactome

KAUST Repository

Kö ster, Tino; Marondedze, Claudius; Meyer, Katja; Staiger, Dorothee

2017-01-01

RNA–protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture – where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes.

Probing binding hot spots at protein-RNA recognition sites.

Science.gov (United States)

Barik, Amita; Nithin, Chandran; Karampudi, Naga Bhushana Rao; Mukherjee, Sunandan; Bahadur, Ranjit Prasad

2016-01-29

We use evolutionary conservation derived from structure alignment of polypeptide sequences along with structural and physicochemical attributes of protein-RNA interfaces to probe the binding hot spots at protein-RNA recognition sites. We find that the degree of conservation varies across the RNA binding proteins; some evolve rapidly compared to others. Additionally, irrespective of the structural class of the complexes, residues at the RNA binding sites are evolutionary better conserved than those at the solvent exposed surfaces. For recognitions involving duplex RNA, residues interacting with the major groove are better conserved than those interacting with the minor groove. We identify multi-interface residues participating simultaneously in protein-protein and protein-RNA interfaces in complexes where more than one polypeptide is involved in RNA recognition, and show that they are better conserved compared to any other RNA binding residues. We find that the residues at water preservation site are better conserved than those at hydrated or at dehydrated sites. Finally, we develop a Random Forests model using structural and physicochemical attributes for predicting binding hot spots. The model accurately predicts 80% of the instances of experimental ΔΔG values in a particular class, and provides a stepping-stone towards the engineering of protein-RNA recognition sites with desired affinity. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Dinucleotide controlled null models for comparative RNA gene prediction.

Science.gov (United States)

Gesell, Tanja; Washietl, Stefan

2008-05-27

Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple alignments can be considered. SISSIz

Dinucleotide controlled null models for comparative RNA gene prediction

Directory of Open Access Journals (Sweden)

Gesell Tanja

2008-05-01

Full Text Available Abstract Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require

A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.

Science.gov (United States)

Zhang, Xiaotian; Yin, Jian; Zhang, Xu

2018-03-02

Increasing evidence suggests that dysregulation of microRNAs (miRNAs) may lead to a variety of diseases. Therefore, identifying disease-related miRNAs is a crucial problem. Currently, many computational approaches have been proposed to predict binary miRNA-disease associations. In this study, in order to predict underlying miRNA-disease association types, a semi-supervised model called the network-based label propagation algorithm is proposed to infer multiple types of miRNA-disease associations (NLPMMDA) by mutual information derived from the heterogeneous network. The NLPMMDA method integrates disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity information of miRNAs and diseases to construct a heterogeneous network. NLPMMDA is a semi-supervised model which does not require verified negative samples. Leave-one-out cross validation (LOOCV) was implemented for four known types of miRNA-disease associations and demonstrated the reliable performance of our method. Moreover, case studies of lung cancer and breast cancer confirmed effective performance of NLPMMDA to predict novel miRNA-disease associations and their association types.

Functional characterization of the Drosophila MRP (mitochondrial RNA processing) RNA gene.

Science.gov (United States)

Schneider, Mary D; Bains, Anupinder K; Rajendra, T K; Dominski, Zbigniew; Matera, A Gregory; Simmonds, Andrew J

2010-11-01

MRP RNA is a noncoding RNA component of RNase mitochondrial RNA processing (MRP), a multi-protein eukaryotic endoribonuclease reported to function in multiple cellular processes, including ribosomal RNA processing, mitochondrial DNA replication, and cell cycle regulation. A recent study predicted a potential Drosophila ortholog of MRP RNA (CR33682) by computer-based genome analysis. We have confirmed the expression of this gene and characterized the phenotype associated with this locus. Flies with mutations that specifically affect MRP RNA show defects in growth and development that begin in the early larval period and end in larval death during the second instar stage. We present several lines of evidence demonstrating a role for Drosophila MRP RNA in rRNA processing. The nuclear fraction of Drosophila MRP RNA localizes to the nucleolus. Further, a mutant strain shows defects in rRNA processing that include a defect in 5.8S rRNA processing, typical of MRP RNA mutants in other species, as well as defects in early stages of rRNA processing.

Cooperation of an RNA Packaging Signal and a Viral Envelope Protein in Coronavirus RNA Packaging

OpenAIRE

Narayanan, Krishna; Makino, Shinji

2001-01-01

Murine coronavirus mouse hepatitis virus (MHV) produces a genome-length mRNA, mRNA 1, and six or seven species of subgenomic mRNAs in infected cells. Among these mRNAs, only mRNA 1 is efficiently packaged into MHV particles. MHV N protein binds to all MHV mRNAs, whereas envelope M protein interacts only with mRNA 1. This M protein-mRNA 1 interaction most probably determines the selective packaging of mRNA 1 into MHV particles. A short cis-acting MHV RNA packaging signal is necessary and suffi...

Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas

Science.gov (United States)

Petrov, Anton I.; Zirbel, Craig L.; Leontis, Neocles B.

2013-01-01

The analysis of atomic-resolution RNA three-dimensional (3D) structures reveals that many internal and hairpin loops are modular, recurrent, and structured by conserved non-Watson–Crick base pairs. Structurally similar loops define RNA 3D motifs that are conserved in homologous RNA molecules, but can also occur at nonhomologous sites in diverse RNAs, and which often vary in sequence. To further our understanding of RNA motif structure and sequence variability and to provide a useful resource for structure modeling and prediction, we present a new method for automated classification of internal and hairpin loop RNA 3D motifs and a new online database called the RNA 3D Motif Atlas. To classify the motif instances, a representative set of internal and hairpin loops is automatically extracted from a nonredundant list of RNA-containing PDB files. Their structures are compared geometrically, all-against-all, using the FR3D program suite. The loops are clustered into motif groups, taking into account geometric similarity and structural annotations and making allowance for a variable number of bulged bases. The automated procedure that we have implemented identifies all hairpin and internal loop motifs previously described in the literature. All motif instances and motif groups are assigned unique and stable identifiers and are made available in the RNA 3D Motif Atlas (http://rna.bgsu.edu/motifs), which is automatically updated every four weeks. The RNA 3D Motif Atlas provides an interactive user interface for exploring motif diversity and tools for programmatic data access. PMID:23970545

A Broad RNA Virus Survey Reveals Both miRNA Dependence and Functional Sequestration

DEFF Research Database (Denmark)

Scheel, Troels K H; Luna, Joseph M; Liniger, Matthias

2016-01-01

, critically depended on the interaction of cellular miR-17 and let-7 with the viral 3' UTR. Unlike canonical miRNA interactions, miR-17 and let-7 binding enhanced pestivirus translation and RNA stability. miR-17 sequestration by pestiviruses conferred reduced AGO binding and functional de...... immunoprecipitation (CLIP) of the Argonaute (AGO) proteins to characterize strengths and specificities of miRNA interactions in the context of 15 different RNA virus infections, including several clinically relevant pathogens. Notably, replication of pestiviruses, a major threat to milk and meat industries...

TargetSpy: a supervised machine learning approach for microRNA target prediction.

Science.gov (United States)

Sturm, Martin; Hackenberg, Michael; Langenberger, David; Frishman, Dmitrij

2010-05-28

Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences.In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila

TargetSpy: a supervised machine learning approach for microRNA target prediction

Directory of Open Access Journals (Sweden)

Langenberger David

2010-05-01

Full Text Available Abstract Background Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. Results We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences. In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I no seed match requirement, II seed match requirement, and III conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Conclusion Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on

Detecting microRNA activity from gene expression data

LENUS (Irish Health Repository)

Madden, Stephen F

2010-05-18

Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Detecting microRNA activity from gene expression data.

LENUS (Irish Health Repository)

Madden, Stephen F

2010-01-01

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art.

Science.gov (United States)

Walia, Rasna R; Caragea, Cornelia; Lewis, Benjamin A; Towfic, Fadi; Terribilini, Michael; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2012-05-10

RNA molecules play diverse functional and structural roles in cells. They function as messengers for transferring genetic information from DNA to proteins, as the primary genetic material in many viruses, as catalysts (ribozymes) important for protein synthesis and RNA processing, and as essential and ubiquitous regulators of gene expression in living organisms. Many of these functions depend on precisely orchestrated interactions between RNA molecules and specific proteins in cells. Understanding the molecular mechanisms by which proteins recognize and bind RNA is essential for comprehending the functional implications of these interactions, but the recognition 'code' that mediates interactions between proteins and RNA is not yet understood. Success in deciphering this code would dramatically impact the development of new therapeutic strategies for intervening in devastating diseases such as AIDS and cancer. Because of the high cost of experimental determination of protein-RNA interfaces, there is an increasing reliance on statistical machine learning methods for training predictors of RNA-binding residues in proteins. However, because of differences in the choice of datasets, performance measures, and data representations used, it has been difficult to obtain an accurate assessment of the current state of the art in protein-RNA interface prediction. We provide a review of published approaches for predicting RNA-binding residues in proteins and a systematic comparison and critical assessment of protein-RNA interface residue predictors trained using these approaches on three carefully curated non-redundant datasets. We directly compare two widely used machine learning algorithms (Naïve Bayes (NB) and Support Vector Machine (SVM)) using three different data representations in which features are encoded using either sequence- or structure-based windows. Our results show that (i) Sequence-based classifiers that use a position-specific scoring matrix (PSSM

Interactions Between HIV-1 Gag and Viral RNA Genome Enhance Virion Assembly

DEFF Research Database (Denmark)

Dilley, Kari A; Nikolaitchik, Olga A; Galli, Andrea

2017-01-01

between Gag and viral RNA are required for the enhancement of particle production. Taken together, these studies are consistent with our previous hypothesis that specific dimeric viral RNA:Gag interactions are the nucleation event of infectious virion assembly, ensuring that one RNA dimer is packaged......Most HIV-1 virions contain two copies of full-length viral RNA, indicating that genome packaging is efficient and tightly regulated. However, the structural protein Gag is the only component required for the assembly of noninfectious virus-like particles and the viral RNA is dispensable...... in this process. The mechanism that allows HIV-1 to achieve such high efficiency of genome packaging when a packageable viral RNA is not required for virus assembly is currently unknown. In this report, we examined the role of HIV-1 RNA in virus assembly and found that packageable HIV-1 RNA enhances particle...

Simple genomes, complex interactions: Epistasis in RNA virus

Science.gov (United States)

Elena, Santiago F.; Solé, Ricard V.; Sardanyés, Josep

2010-06-01

Owed to their reduced size and low number of proteins encoded, RNA viruses and other subviral pathogens are often considered as being genetically too simple. However, this structural simplicity also creates the necessity for viral RNA sequences to encode for more than one protein and for proteins to carry out multiple functions, all together resulting in complex patterns of genetic interactions. In this work we will first review the experimental studies revealing that the architecture of viral genomes is dominated by antagonistic interactions among loci. Second, we will also review mathematical models and provide a description of computational tools for the study of RNA virus dynamics and evolution. As an application of these tools, we will finish this review article by analyzing a stochastic bit-string model of in silico virus replication. This model analyzes the interplay between epistasis and the mode of replication on determining the population load of deleterious mutations. The model suggests that, for a given mutation rate, the deleterious mutational load is always larger when epistasis is predominantly antagonistic than when synergism is the rule. However, the magnitude of this effect is larger if replication occurs geometrically than if it proceeds linearly.

Assembling RNA Nanoparticles.

Science.gov (United States)

Xiao, Shou-Jun

2017-01-01

RNA nanoparticles are designed and self-assembled according to noncanonical interactions of naturally conserved RNA motifs and/or canonical Watson-Crick base-pairing interactions, which have potential applications in gene therapy and nanomedicine. These artificially engineered nanoparticles are mainly synthesized from in vitro transcribed RNAs, purified by denaturing and native polyacrylamide gel electrophoresis (PAGE), and characterized with native PAGE, AFM, and TEM technologies. The protocols of in vitro transcription, denaturing and native PAGE, and RNA nanoparticle self-assembly are described in detail.

Affinity labeling of Escherichia coli phenylalanyl-tRNA synthetase at the binding site for tRNA

International Nuclear Information System (INIS)

Hountondji, C.; Schmitter, J.M.; Beauvallet, C.; Blanquet, S.

1987-01-01

Periodate-oxidized tRNA/sup Phe/ (tRNA/sub ox//sup Phe/) behaves as a specific affinity label of tetrameric Escherichia coli phenylalanyl-tRNA synthetase (PheRS). Reaction of the α 2 β 2 enzyme with tRNA/sub ox//sup Phe/ results in the loss of tRNA/sup Phe/ aminoacylation activity with covalent attachment of 2 mol of tRNA dialdehyde/mol of enzyme, in agreement with the stoichiometry of tRNA binding. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of the PheRS-[ 14 C]tRNA/sub ox//sup Phe/ covalent complex indicates that the large (α, M/sub r/ 87K) subunit of the enzyme interacts with the 3'-adenosine of tRNA/sub ox//sup Phe/. The [ 14 C]tRNA-labeled chymotryptic peptides of PheRS were purified by both gel filtration and reverse-phase high-performance liquid chromatography. The radioactivity was almost equally distributed among three peptides: Met-Lys[Ado]-Phe, Ala-Asp-Lys[Ado]-Leu, and Lys-Ile-Lys[Ado]-Ala. These sequences correspond to residues 1-3, 59-62, and 104-107, respectively, in the N-terminal region of the 795 amino acid sequence of the α subunit. It is noticeable that the labeled peptide Ala-Asp-Lys-Leu is adjacent to residues 63-66 (Arg-Val-Thr-Lys). The latter sequence was just predicted to resemble the proposed consensus tRNA CCA binding region Lys-Met-Ser-Lys-Ser, as deduced from previous affinity labeling studies on E. coli methionyl- and tyrosyl-tRNA synthetases

Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

Science.gov (United States)

Legendre, Audrey; Angel, Eric; Tahi, Fariza

2018-01-15

RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

Role of Electrostatics in Protein-RNA Binding: The Global vs the Local Energy Landscape.

Science.gov (United States)

Ghaemi, Zhaleh; Guzman, Irisbel; Gnutt, David; Luthey-Schulten, Zaida; Gruebele, Martin

2017-09-14

U1A protein-stem loop 2 RNA association is a basic step in the assembly of the spliceosomal U1 small nuclear ribonucleoprotein. Long-range electrostatic interactions due to the positive charge of U1A are thought to provide high binding affinity for the negatively charged RNA. Short range interactions, such as hydrogen bonds and contacts between RNA bases and protein side chains, favor a specific binding site. Here, we propose that electrostatic interactions are as important as local contacts in biasing the protein-RNA energy landscape toward a specific binding site. We show by using molecular dynamics simulations that deletion of two long-range electrostatic interactions (K22Q and K50Q) leads to mutant-specific alternative RNA bound states. One of these states preserves short-range interactions with aromatic residues in the original binding site, while the other one does not. We test the computational prediction with experimental temperature-jump kinetics using a tryptophan probe in the U1A-RNA binding site. The two mutants show the distinct predicted kinetic behaviors. Thus, the stem loop 2 RNA has multiple binding sites on a rough RNA-protein binding landscape. We speculate that the rough protein-RNA binding landscape, when biased to different local minima by electrostatics, could be one way that protein-RNA interactions evolve toward new binding sites and novel function.

Correlation of microRNA levels during hypoxia with predicted target mRNAs through genome-wide microarray analysis

Directory of Open Access Journals (Sweden)

Page Grier P

2009-03-01

Full Text Available Abstract Background Low levels of oxygen in tissues, seen in situations such as chronic lung disease, necrotic tumors, and high altitude exposures, initiate a signaling pathway that results in active transcription of genes possessing a hypoxia response element (HRE. The aim of this study was to investigate whether a change in miRNA expression following hypoxia could account for changes in the cellular transcriptome based on currently available miRNA target prediction tools. Methods To identify changes induced by hypoxia, we conducted mRNA- and miRNA-array-based experiments in HT29 cells, and performed comparative analysis of the resulting data sets based on multiple target prediction algorithms. To date, few studies have investigated an environmental perturbation for effects on genome-wide miRNA levels, or their consequent influence on mRNA output. Results Comparison of miRNAs with predicted mRNA targets indicated a lower level of concordance than expected. We did, however, find preliminary evidence of combinatorial regulation of mRNA expression by miRNA. Conclusion Target prediction programs and expression profiling techniques do not yet adequately represent the complexity of miRNA-mediated gene repression, and new methods may be required to better elucidate these pathways. Our data suggest the physiologic impact of miRNAs on cellular transcription results from a multifaceted network of miRNA and mRNA relationships, working together in an interconnected system and in context of hundreds of RNA species. The methods described here for comparative analysis of cellular miRNA and mRNA will be useful for understanding genome wide regulatory responsiveness and refining miRNA predictive algorithms.

The identification and functional annotation of RNA structures conserved in vertebrates

DEFF Research Database (Denmark)

Seemann, Ernst Stefan; Mirza, Aashiq Hussain; Hansen, Claus

2017-01-01

Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for Conserved RNA Structures (CRSs), leveraging structure-b......-structured counterparts. Our findings of transcribed uncharacterized regulatory regions that contain CRSs support their RNA-mediated functionality.......Structured elements of RNA molecules are essential in, e.g., RNA stabilization, localization and protein interaction, and their conservation across species suggests a common functional role. We computationally screened vertebrate genomes for Conserved RNA Structures (CRSs), leveraging structure......-based, rather than sequence-based, alignments. After careful correction for sequence identity and GC content, we predict ~516k human genomic regions containing CRSs. We find that a substantial fraction of human-mouse CRS regions (i) co-localize consistently with binding sites of the same RNA binding proteins...

Supervised learning classification models for prediction of plant virus encoded RNA silencing suppressors.

Directory of Open Access Journals (Sweden)

Zeenia Jagga

Full Text Available Viral encoded RNA silencing suppressor proteins interfere with the host RNA silencing machinery, facilitating viral infection by evading host immunity. In plant hosts, the viral proteins have several basic science implications and biotechnology applications. However in silico identification of these proteins is limited by their high sequence diversity. In this study we developed supervised learning based classification models for plant viral RNA silencing suppressor proteins in plant viruses. We developed four classifiers based on supervised learning algorithms: J48, Random Forest, LibSVM and Naïve Bayes algorithms, with enriched model learning by correlation based feature selection. Structural and physicochemical features calculated for experimentally verified primary protein sequences were used to train the classifiers. The training features include amino acid composition; auto correlation coefficients; composition, transition, and distribution of various physicochemical properties; and pseudo amino acid composition. Performance analysis of predictive models based on 10 fold cross-validation and independent data testing revealed that the Random Forest based model was the best and achieved 86.11% overall accuracy and 86.22% balanced accuracy with a remarkably high area under the Receivers Operating Characteristic curve of 0.95 to predict viral RNA silencing suppressor proteins. The prediction models for plant viral RNA silencing suppressors can potentially aid identification of novel viral RNA silencing suppressors, which will provide valuable insights into the mechanism of RNA silencing and could be further explored as potential targets for designing novel antiviral therapeutics. Also, the key subset of identified optimal features may help in determining compositional patterns in the viral proteins which are important determinants for RNA silencing suppressor activities. The best prediction model developed in the study is available as a

The RNA synthesis machinery of negative-stranded RNA viruses

International Nuclear Information System (INIS)

Ortín, Juan; Martín-Benito, Jaime

2015-01-01

The group of Negative-Stranded RNA Viruses (NSVs) includes many human pathogens, like the influenza, measles, mumps, respiratory syncytial or Ebola viruses, which produce frequent epidemics of disease and occasional, high mortality outbreaks by transmission from animal reservoirs. The genome of NSVs consists of one to several single-stranded, negative-polarity RNA molecules that are always assembled into mega Dalton-sized complexes by association to many nucleoprotein monomers. These RNA-protein complexes or ribonucleoproteins function as templates for transcription and replication by action of the viral RNA polymerase and accessory proteins. Here we review our knowledge on these large RNA-synthesis machines, including the structure of their components, the interactions among them and their enzymatic activities, and we discuss models showing how they perform the virus transcription and replication programmes. - Highlights: • Overall organisation of NSV RNA synthesis machines. • Structure and function of the ribonucleoprotein components: Atomic structure of the RNA polymerase complex. • Commonalities and differences between segmented- and non-segmented NSVs. • Transcription versus replication programmes

The RNA synthesis machinery of negative-stranded RNA viruses

Energy Technology Data Exchange (ETDEWEB)

Ortín, Juan, E-mail: jortin@cnb.csic.es [Department of Molecular and Cellular Biology, Centro Nacional de Biotecnología (CSIC) and CIBER de Enfermedades Respiratorias (ISCIII), Madrid (Spain); Martín-Benito, Jaime, E-mail: jmartinb@cnb.csic.es [Department of Macromolecular Structures, Centro Nacional de Biotecnología (CSIC), Madrid (Spain)

2015-05-15

The group of Negative-Stranded RNA Viruses (NSVs) includes many human pathogens, like the influenza, measles, mumps, respiratory syncytial or Ebola viruses, which produce frequent epidemics of disease and occasional, high mortality outbreaks by transmission from animal reservoirs. The genome of NSVs consists of one to several single-stranded, negative-polarity RNA molecules that are always assembled into mega Dalton-sized complexes by association to many nucleoprotein monomers. These RNA-protein complexes or ribonucleoproteins function as templates for transcription and replication by action of the viral RNA polymerase and accessory proteins. Here we review our knowledge on these large RNA-synthesis machines, including the structure of their components, the interactions among them and their enzymatic activities, and we discuss models showing how they perform the virus transcription and replication programmes. - Highlights: • Overall organisation of NSV RNA synthesis machines. • Structure and function of the ribonucleoprotein components: Atomic structure of the RNA polymerase complex. • Commonalities and differences between segmented- and non-segmented NSVs. • Transcription versus replication programmes.

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

Science.gov (United States)

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

Genome-wide search for miRNA-target interactions in Arabidopsis thaliana with an integrated approach

Directory of Open Access Journals (Sweden)

Ding Jiandong

2012-06-01

Full Text Available Abstract Background MiRNA are about 22nt long small noncoding RNAs that post transcriptionally regulate gene expression in animals, plants and protozoa. Confident identification of MiRNA-Target Interactions (MTI is vital to understand their function. Currently, several integrated computational programs and databases are available for animal miRNAs, the mechanisms of which are significantly different from plant miRNAs. Methods Here we present an integrated MTI prediction and analysis toolkit (imiRTP for Arabidopsis thaliana. It features two important functions: (i combination of several effective plant miRNA target prediction methods provides a sufficiently large MTI candidate set, and (ii different filters allow for an efficient selection of potential targets. The modularity of imiRTP enables the prediction of high quality targets on genome-wide scale. Moreover, predicted MTIs can be presented in various ways, which allows for browsing through the putative target sites as well as conducting simple and advanced analyses. Results Results show that imiRTP could always find high quality candidates compared with single method by choosing appropriate filter and parameter. And we also reveal that a portion of plant miRNA could bind target genes out of coding region. Based on our results, imiRTP could facilitate the further study of Arabidopsis miRNAs in real use. All materials of imiRTP are freely available under a GNU license at (http://admis.fudan.edu.cn/projects/imiRTP.htm.

miRNA-mediated 'tug-of-war' model reveals ceRNA propensity of genes in cancers.

Science.gov (United States)

Swain, Arpit Chandan; Mallick, Bibekanand

2018-06-01

Competing endogenous RNA (ceRNA) are transcripts that cross-regulate each other at the post-transcriptional level by competing for shared microRNA response elements (MREs). These have been implicated in various biological processes impacting cell-fate decisions and diseases including cancer. There are several studies that predict possible ceRNA pairs by adopting various machine-learning and mathematical approaches; however, there is no method that enables us to gauge as well as compare the propensity of the ceRNA of a gene and precisely envisages which among a pair exerts a stronger pull on the shared miRNA pool. In this study, we developed a method that uses the 'tug of war of genes' concept to predict and quantify ceRNA potential of a gene for the shared miRNA pool in cancers based on a score represented by SoCeR (score of competing endogenous RNA). The method was executed on the RNA-Seq transcriptional profiles of genes and miRNA available at TCGA along with CLIP-supported miRNA-target sites to predict ceRNA in 32 cancer types which were validated with already reported cases. The proposed method can be used to determine the sequestering capability of the gene of interest as well as in ranking the probable ceRNA candidates of a gene. Finally, we developed standalone applications (SoCeR tool) to aid researchers in easier implementation of the method in analysing different data sets or diseases. © 2018 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.

Cyclophilin B stimulates RNA synthesis by the HCV RNA dependent RNA polymerase.

Science.gov (United States)

Heck, Julie A; Meng, Xiao; Frick, David N

2009-04-01

Cyclophilins are cellular peptidyl isomerases that have been implicated in regulating hepatitis C virus (HCV) replication. Cyclophilin B (CypB) is a target of cyclosporin A (CsA), an immunosuppressive drug recently shown to suppress HCV replication in cell culture. Watashi et al. recently demonstrated that CypB is important for efficient HCV replication, and proposed that it mediates the anti-HCV effects of CsA through an interaction with NS5B [Watashi K, Ishii N, Hijikata M, Inoue D, Murata T, Miyanari Y, et al. Cyclophilin B is a functional regulator of hepatitis C virus RNA polymerase. Mol Cell 2005;19:111-22]. We examined the effects of purified CypB proteins on the enzymatic activity of NS5B. Recombinant CypB purified from insect cells directly stimulated NS5B-catalyzed RNA synthesis. CypB increased RNA synthesis by NS5B derived from genotype 1a, 1b, and 2a HCV strains. Stimulation appears to arise from an increase in productive RNA binding. NS5B residue Pro540, a previously proposed target of CypB peptidyl-prolyl isomerase activity, is not required for stimulation of RNA synthesis.

Semiautomated improvement of RNA alignments

DEFF Research Database (Denmark)

Andersen, Ebbe Sloth; Lind-Thomsen, Allan; Knudsen, Bjarne

2007-01-01

connects to external tools to provide a flexible semiautomatic editing environment. A new method, Pcluster, is introduced for dividing the sequences of an RNA alignment into subgroups with secondary structure differences. Pcluster was used to evaluate 574 seed alignments obtained from the Rfam database...... and we identified 71 alignments with significant prediction of inconsistent base pairs and 102 alignments with significant prediction of novel base pairs. Four RNA families were used to illustrate how SARSE can be used to manually or automatically correct the inconsistent base pairs detected by Pcluster......: the mir-399 RNA, vertebrate telomase RNA (vert-TR), bacterial transfer-messenger RNA (tmRNA), and the signal recognition particle (SRP) RNA. The general use of the method is illustrated by the ability to accommodate pseudoknots and handle even large and divergent RNA families. The open architecture...

Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

Directory of Open Access Journals (Sweden)

Cobaugh Christian W

2004-08-01

Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

Science.gov (United States)

Huang, Jingshan; Gutierrez, Fernando; Strachan, Harrison J; Dou, Dejing; Huang, Weili; Smith, Barry; Blake, Judith A; Eilbeck, Karen; Natale, Darren A; Lin, Yu; Wu, Bin; Silva, Nisansa de; Wang, Xiaowei; Liu, Zixing; Borchert, Glen M; Tan, Ming; Ruttenberg, Alan

2016-01-01

As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software.

Human Enterovirus Nonstructural Protein 2CATPase Functions as Both an RNA Helicase and ATP-Independent RNA Chaperone

Science.gov (United States)

Xia, Hongjie; Wang, Peipei; Wang, Guang-Chuan; Yang, Jie; Sun, Xianlin; Wu, Wenzhe; Qiu, Yang; Shu, Ting; Zhao, Xiaolu; Yin, Lei; Qin, Cheng-Feng; Hu, Yuanyang; Zhou, Xi

2015-01-01

RNA helicases and chaperones are the two major classes of RNA remodeling proteins, which function to remodel RNA structures and/or RNA-protein interactions, and are required for all aspects of RNA metabolism. Although some virus-encoded RNA helicases/chaperones have been predicted or identified, their RNA remodeling activities in vitro and functions in the viral life cycle remain largely elusive. Enteroviruses are a large group of positive-stranded RNA viruses in the Picornaviridae family, which includes numerous important human pathogens. Herein, we report that the nonstructural protein 2CATPase of enterovirus 71 (EV71), which is the major causative pathogen of hand-foot-and-mouth disease and has been regarded as the most important neurotropic enterovirus after poliovirus eradication, functions not only as an RNA helicase that 3′-to-5′ unwinds RNA helices in an adenosine triphosphate (ATP)-dependent manner, but also as an RNA chaperone that destabilizes helices bidirectionally and facilitates strand annealing and complex RNA structure formation independently of ATP. We also determined that the helicase activity is based on the EV71 2CATPase middle domain, whereas the C-terminus is indispensable for its RNA chaperoning activity. By promoting RNA template recycling, 2CATPase facilitated EV71 RNA synthesis in vitro; when 2CATPase helicase activity was impaired, EV71 RNA replication and virion production were mostly abolished in cells, indicating that 2CATPase-mediated RNA remodeling plays a critical role in the enteroviral life cycle. Furthermore, the RNA helicase and chaperoning activities of 2CATPase are also conserved in coxsackie A virus 16 (CAV16), another important enterovirus. Altogether, our findings are the first to demonstrate the RNA helicase and chaperoning activities associated with enterovirus 2CATPase, and our study provides both in vitro and cellular evidence for their potential roles during viral RNA replication. These findings increase our

Systematic Prediction of the Impacts of Mutations in MicroRNA Seed Sequences

Directory of Open Access Journals (Sweden)

Bhattacharya Anindya

2017-05-01

Full Text Available MicroRNAs are a class of small non-coding RNAs that are involved in many important biological processes and the dysfunction of microRNA has been associated with many diseases. The seed region of a microRNA is of crucial importance to its target recognition. Mutations in microRNA seed regions may disrupt the binding of microRNAs to their original target genes and make them bind to new target genes. Here we use a knowledge-based computational method to systematically predict the functional effects of all the possible single nucleotide mutations in human microRNA seed regions. The result provides a comprehensive reference for the functional assessment of the impacts of possible natural and artificial single nucleotide mutations in microRNA seed regions.

Integrating chemical footprinting data into RNA secondary structure prediction.

Directory of Open Access Journals (Sweden)

Kourosh Zarringhalam

Full Text Available Chemical and enzymatic footprinting experiments, such as shape (selective 2'-hydroxyl acylation analyzed by primer extension, yield important information about RNA secondary structure. Indeed, since the [Formula: see text]-hydroxyl is reactive at flexible (loop regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints, which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be 'correct', in as much as the shape data is 'correct'. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

Predicting RNA hyper-editing with a novel tool when unambiguous alignment is impossible.

Science.gov (United States)

McKerrow, Wilson H; Savva, Yiannis A; Rezaei, Ali; Reenan, Robert A; Lawrence, Charles E

2017-07-10

Repetitive elements are now known to have relevant cellular functions, including self-complementary sequences that form double stranded (ds) RNA. There are numerous pathways that determine the fate of endogenous dsRNA, and misregulation of endogenous dsRNA is a driver of autoimmune disease, particularly in the brain. Unfortunately, the alignment of high-throughput, short-read sequences to repeat elements poses a dilemma: Such sequences may align equally well to multiple genomic locations. In order to differentiate repeat elements, current alignment methods depend on sequence variation in the reference genome. Reads are discarded when no such variations are present. However, RNA hyper-editing, a possible fate for dsRNA, introduces enough variation to distinguish between repeats that are otherwise identical. To take advantage of this variation, we developed a new algorithm, RepProfile, that simultaneously aligns reads and predicts novel variations. RepProfile accurately aligns hyper-edited reads that other methods discard. In particular we predict hyper-editing of Drosophila melanogaster repeat elements in vivo at levels previously described only in vitro, and provide validation by Sanger sequencing sixty-two individual cloned sequences. We find that hyper-editing is concentrated in genes involved in cell-cell communication at the synapse, including some that are associated with neurodegeneration. We also find that hyper-editing tends to occur in short runs. Previous studies of RNA hyper-editing discarded ambiguously aligned reads, ignoring hyper-editing in long, perfect dsRNA - the perfect substrate for hyper-editing. We provide a method that simulation and Sanger validation show accurately predicts such RNA editing, yielding a superior picture of hyper-editing.

DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data.

Science.gov (United States)

Tsuji, Junko; Weng, Zhiping

2016-01-01

With the rapid accumulation of publicly available small RNA sequencing datasets, third-party meta-analysis across many datasets is becoming increasingly powerful. Although removing the 3´ adapter is an essential step for small RNA sequencing analysis, the adapter sequence information is not always available in the metadata. The information can be also erroneous even when it is available. In this study, we developed DNApi, a lightweight Python software package that predicts the 3´ adapter sequence de novo and provides the user with cleansed small RNA sequences ready for down stream analysis. Tested on 539 publicly available small RNA libraries accompanied with 3´ adapter sequences in their metadata, DNApi shows near-perfect accuracy (98.5%) with fast runtime (~2.85 seconds per library) and efficient memory usage (~43 MB on average). In addition to 3´ adapter prediction, it is also important to classify whether the input small RNA libraries were already processed, i.e. the 3´ adapters were removed. DNApi perfectly judged that given another batch of datasets, 192 publicly available processed libraries were "ready-to-map" small RNA sequence. DNApi is compatible with Python 2 and 3, and is available at https://github.com/jnktsj/DNApi. The 731 small RNA libraries used for DNApi evaluation were from human tissues and were carefully and manually collected. This study also provides readers with the curated datasets that can be integrated into their studies.

Predictions of RNA-binding ability and aggregation propensity of proteins

OpenAIRE

Agostini, Federico, 1985-

2014-01-01

RNA-binding proteins (RBPs) control the fate of a multitude of coding and non-coding transcripts. Formation of ribonucleoprotein (RNP) complexes fine-tunes regulation of post-transcriptional events and influences gene expression. Recently, it has been observed that non-canonical proteins with RNA-binding ability are enriched in structurally disordered and low-complexity regions that are generally involved in functional and dysfunctional associations. Therefore, it is possible that interaction...

Antagonism pattern detection between microRNA and target expression in Ewing's sarcoma.

Directory of Open Access Journals (Sweden)

Loredana Martignetti

Full Text Available MicroRNAs (miRNAs have emerged as fundamental regulators that silence gene expression at the post-transcriptional and translational levels. The identification of their targets is a major challenge to elucidate the regulated biological processes. The overall effect of miRNA is reflected on target mRNA expression, suggesting the design of new investigative methods based on high-throughput experimental data such as miRNA and transcriptome profiles. We propose a novel statistical measure of non-linear dependence between miRNA and mRNA expression, in order to infer miRNA-target interactions. This approach, which we name antagonism pattern detection, is based on the statistical recognition of a triangular-shaped pattern in miRNA-target expression profiles. This pattern is observed in miRNA-target expression measurements since their simultaneously elevated expression is statistically under-represented in the case of miRNA silencing effect. The proposed method enables miRNA target prediction to strongly rely on cellular context and physiological conditions reflected by expression data. The procedure has been assessed on synthetic datasets and tested on a set of real positive controls. Then it has been applied to analyze expression data from Ewing's sarcoma patients. The antagonism relationship is evaluated as a good indicator of real miRNA-target biological interaction. The predicted targets are consistently enriched for miRNA binding site motifs in their 3'UTR. Moreover, we reveal sets of predicted targets for each miRNA sharing important biological function. The procedure allows us to infer crucial miRNA regulators and their potential targets in Ewing's sarcoma disease. It can be considered as a valid statistical approach to discover new insights in the miRNA regulatory mechanisms.

Nucleocapsid-Independent Specific Viral RNA Packaging via Viral Envelope Protein and Viral RNA Signal

OpenAIRE

Narayanan, Krishna; Chen, Chun-Jen; Maeda, Junko; Makino, Shinji

2003-01-01

For any of the enveloped RNA viruses studied to date, recognition of a specific RNA packaging signal by the virus's nucleocapsid (N) protein is the first step described in the process of viral RNA packaging. In the murine coronavirus a selective interaction between the viral transmembrane envelope protein M and the viral ribonucleoprotein complex, composed of N protein and viral RNA containing a short cis-acting RNA element, the packaging signal, determines the selective RNA packaging into vi...

Clinical values of AFP, GPC3 mRNA in peripheral blood for prediction of hepatocellular carcinoma recurrence following OLT: AFP, GPC3 mRNA for prediction of HCC.

Science.gov (United States)

Wang, Yuliang; Shen, Zhongyang; Zhu, Zhijun; Han, Ruifa; Huai, Mingsheng

2011-03-01

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. Annually, about 200,000 patients died of HCC in China. Liver transplantation (LT) holds great theoretical appeal in treating HCC. However, the high recurrence rate after transplantation is the most important limiting factor for long-term survival. To assess the value of alpha-fetoprotein (AFP) messenger RNA (mRNA), Glypican-3 (GPC3) mRNA-expressing cells in the peripheral blood (PB) for prediction of HCC recurrence following orthotopic liver transplantation (OLT). 29 patients with HCC who underwent OLT with a minimum clinical follow-up of 12 months were included in this retrospective study. We detected AFP mRNA, GPC3 mRNA-expressing cells in the PB by TaqMan real-time reverse transcriptase-polymerase chain reaction (RT-PCR), pre-, intra- and post-operatively. The early recurrence of patients was evaluated. 8 (28%), 15 (52%), and 9 (31%) patients had AFP mRNA detected pre-, intra-, and post-operatively, respectively. With 12 months of follow-up, HCC recurred in 7 (24%) patients. Univariate analysis revealed that positive pre- and post-operative AFP mRNA, TNM stage as well as vascular invasion were significant predictors for the HCC recurrence. Multivariate analysis revealed that being positive for AFP mRNA pre-operatively remained a significant risk factor for HCC recurrence after OLT. GPC3 mRNA was expressed in all PB samples. There was no significant difference in the expression levels of GPC3 mRNA between the HCC and control groups. There were no significant differences in GPC3 mRNA expression values between those patients with and without tumor recurrence. The pre-operative detection of circulating AFP mRNA-expressing cells could be a useful predictor for HCC recurrence following OLT. GPC3 mRNA-expressing cells in PB seem to have no diagnostic value.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

Directory of Open Access Journals (Sweden)

Diane Heiser

Full Text Available Several individual miRNAs (miRs have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell, our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC populations, as well as "myeloid" patterns associated with two branches of myeloid development.

Correlated miR-mRNA expression signatures of mouse hematopoietic stem and progenitor cell subsets predict "Stemness" and "Myeloid" interaction networks.

Science.gov (United States)

Heiser, Diane; Tan, Yee Sun; Kaplan, Ian; Godsey, Brian; Morisot, Sebastien; Cheng, Wen-Chih; Small, Donald; Civin, Curt I

2014-01-01

Several individual miRNAs (miRs) have been implicated as potent regulators of important processes during normal and malignant hematopoiesis. In addition, many miRs have been shown to fine-tune intricate molecular networks, in concert with other regulatory elements. In order to study hematopoietic networks as a whole, we first created a map of global miR expression during early murine hematopoiesis. Next, we determined the copy number per cell for each miR in each of the examined stem and progenitor cell types. As data is emerging indicating that miRs function robustly mainly when they are expressed above a certain threshold (∼100 copies per cell), our database provides a resource for determining which miRs are expressed at a potentially functional level in each cell type. Finally, we combine our miR expression map with matched mRNA expression data and external prediction algorithms, using a Bayesian modeling approach to create a global landscape of predicted miR-mRNA interactions within each of these hematopoietic stem and progenitor cell subsets. This approach implicates several interaction networks comprising a "stemness" signature in the most primitive hematopoietic stem cell (HSC) populations, as well as "myeloid" patterns associated with two branches of myeloid development.

Global organization of a positive-strand RNA virus genome.

Directory of Open Access Journals (Sweden)

Baodong Wu

Full Text Available The genomes of plus-strand RNA viruses contain many regulatory sequences and structures that direct different viral processes. The traditional view of these RNA elements are as local structures present in non-coding regions. However, this view is changing due to the discovery of regulatory elements in coding regions and functional long-range intra-genomic base pairing interactions. The ∼4.8 kb long RNA genome of the tombusvirus tomato bushy stunt virus (TBSV contains these types of structural features, including six different functional long-distance interactions. We hypothesized that to achieve these multiple interactions this viral genome must utilize a large-scale organizational strategy and, accordingly, we sought to assess the global conformation of the entire TBSV genome. Atomic force micrographs of the genome indicated a mostly condensed structure composed of interconnected protrusions extending from a central hub. This configuration was consistent with the genomic secondary structure model generated using high-throughput selective 2'-hydroxyl acylation analysed by primer extension (i.e. SHAPE, which predicted different sized RNA domains originating from a central region. Known RNA elements were identified in both domain and inter-domain regions, and novel structural features were predicted and functionally confirmed. Interestingly, only two of the six long-range interactions known to form were present in the structural model. However, for those interactions that did not form, complementary partner sequences were positioned relatively close to each other in the structure, suggesting that the secondary structure level of viral genome structure could provide a basic scaffold for the formation of different long-range interactions. The higher-order structural model for the TBSV RNA genome provides a snapshot of the complex framework that allows multiple functional components to operate in concert within a confined context.

Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data.

Science.gov (United States)

Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

2013-09-22

High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments.

Intrinsic noise of microRNA-regulated genes and the ceRNA hypothesis.

Directory of Open Access Journals (Sweden)

Javad Noorbakhsh

Full Text Available MicroRNAs are small noncoding RNAs that regulate genes post-transciptionally by binding and degrading target eukaryotic mRNAs. We use a quantitative model to study gene regulation by inhibitory microRNAs and compare it to gene regulation by prokaryotic small non-coding RNAs (sRNAs. Our model uses a combination of analytic techniques as well as computational simulations to calculate the mean-expression and noise profiles of genes regulated by both microRNAs and sRNAs. We find that despite very different molecular machinery and modes of action (catalytic vs stoichiometric, the mean expression levels and noise profiles of microRNA-regulated genes are almost identical to genes regulated by prokaryotic sRNAs. This behavior is extremely robust and persists across a wide range of biologically relevant parameters. We extend our model to study crosstalk between multiple mRNAs that are regulated by a single microRNA and show that noise is a sensitive measure of microRNA-mediated interaction between mRNAs. We conclude by discussing possible experimental strategies for uncovering the microRNA-mRNA interactions and testing the competing endogenous RNA (ceRNA hypothesis.

The integrated analysis of RNA-seq and microRNA-seq depicts miRNA-mRNA networks involved in Japanese flounder (Paralichthys olivaceus) albinism.

Science.gov (United States)

Wang, Na; Wang, Ruoqing; Wang, Renkai; Tian, Yongsheng; Shao, Changwei; Jia, Xiaodong; Chen, Songlin

2017-01-01

Albinism, a phenomenon characterized by pigmentation deficiency on the ocular side of Japanese flounder (Paralichthys olivaceus), has caused significant damage. Limited mRNA and microRNA (miRNA) information is available on fish pigmentation deficiency. In this study, a high-throughput sequencing strategy was employed to identify the mRNA and miRNAs involved in P. olivaceus albinism. Based on P. olivaceus genome, RNA-seq identified 21,787 know genes and 711 new genes by transcripts assembly. Of those, 235 genes exhibited significantly different expression pattern (fold change ≥2 or ≤0.5 and q-value≤0.05), including 194 down-regulated genes and 41 up-regulated genes in albino versus normally pigmented individuals. These genes were enriched to 81 GO terms and 9 KEGG pathways (p≤0.05). Among those, the pigmentation related pathways-Melanogenesis and tyrosine metabolism were contained. High-throughput miRNA sequencing identified a total of 475 miRNAs, including 64 novel miRNAs. Furthermore, 33 differentially expressed miRNAs containing 13 up-regulated and 20 down-regulated miRNAs were identified in albino versus normally pigmented individuals (fold change ≥1.5 or ≤0.67 and p≤0.05). The next target prediction discovered a variety of putative target genes, of which, 134 genes including Tyrosinase (TYR), Tyrosinase-related protein 1 (TYRP1), Microphthalmia-associated transcription factor (MITF) were overlapped with differentially expressed genes derived from RNA-seq. These target genes were significantly enriched to 254 GO terms and 103 KEGG pathways (p<0.001). Of those, tyrosine metabolism, lysosomes, phototransduction pathways, etc., attracted considerable attention due to their involvement in regulating skin pigmentation. Expression patterns of differentially expressed mRNA and miRNAs were validated in 10 mRNA and 10 miRNAs by qRT-PCR. With high-throughput mRNA and miRNA sequencing and analysis, a series of interested mRNA and miRNAs involved in fish

Computational tools for genome-wide miRNA prediction and study

KAUST Repository

Malas, T.B.

2012-11-02

MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

Computational tools for genome-wide miRNA prediction and study

KAUST Repository

Malas, T.B.; Ravasi, Timothy

2012-01-01

MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

Adaptation of Tri-molecular fluorescence complementation allows assaying of regulatory Csr RNA-protein interactions in bacteria.

Science.gov (United States)

Gelderman, Grant; Sivakumar, Anusha; Lipp, Sarah; Contreras, Lydia

2015-02-01

sRNAs play a significant role in controlling and regulating cellular metabolism. One of the more interesting aspects of certain sRNAs is their ability to make global changes in the cell by interacting with regulatory proteins. In this work, we demonstrate the use of an in vivo Tri-molecular Fluorescence Complementation assay to detect and visualize the central regulatory sRNA-protein interaction of the Carbon Storage Regulatory system in E. coli. The Carbon Storage Regulator consists primarily of an RNA binding protein, CsrA, that alters the activity of mRNA targets and of an sRNA, CsrB, that modulates the activity of CsrA. We describe the construction of a fluorescence complementation system that detects the interactions between CsrB and CsrA. Additionally, we demonstrate that the intensity of the fluorescence of this system is able to detect changes in the affinity of the CsrB-CsrA interaction, as caused by mutations in the protein sequence of CsrA. While previous methods have adopted this technique to study mRNA or RNA localization, this is the first attempt to use this technique to study the sRNA-protein interaction directly in bacteria. This method presents a potentially powerful tool to study complex bacterial RNA protein interactions in vivo. © 2014 Wiley Periodicals, Inc.

The thermodynamics of Pr55Gag-RNA interaction regulate the assembly of HIV.

Directory of Open Access Journals (Sweden)

Hanumant S Tanwar

2017-02-01

Full Text Available The interactions that occur during HIV Pr55Gag oligomerization and genomic RNA packaging are essential elements that facilitate HIV assembly. However, mechanistic details of these interactions are not clearly defined. Here, we overcome previous limitations in producing large quantities of full-length recombinant Pr55Gag that is required for isothermal titration calorimetry (ITC studies, and we have revealed the thermodynamic properties of HIV assembly for the first time. Thermodynamic analysis showed that the binding between RNA and HIV Pr55Gag is an energetically favourable reaction (ΔG<0 that is further enhanced by the oligomerization of Pr55Gag. The change in enthalpy (ΔH widens sequentially from: (1 Pr55Gag-Psi RNA binding during HIV genome selection; to (2 Pr55Gag-Guanosine Uridine (GU-containing RNA binding in cytoplasm/plasma membrane; and then to (3 Pr55Gag-Adenosine(A-containing RNA binding in immature HIV. These data imply the stepwise increments of heat being released during HIV biogenesis may help to facilitate the process of viral assembly. By mimicking the interactions between A-containing RNA and oligomeric Pr55Gag in immature HIV, it was noted that a p6 domain truncated Pr50Gag Δp6 is less efficient than full-length Pr55Gag in this thermodynamic process. These data suggest a potential unknown role of p6 in Pr55Gag-Pr55Gag oligomerization and/or Pr55Gag-RNA interaction during HIV assembly. Our data provide direct evidence on how nucleic acid sequences and the oligomeric state of Pr55Gag regulate HIV assembly.

Novel modeling of combinatorial miRNA targeting identifies SNP with potential role in bone density.

Directory of Open Access Journals (Sweden)

Claudia Coronnello

Full Text Available MicroRNAs (miRNAs are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting, a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential

Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees.

Science.gov (United States)

Williams, Philip H; Eyles, Rod; Weiller, Georg

2012-01-01

MicroRNAs (miRNAs) are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require "read count" to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA(∗) duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

Signatures of RNA binding proteins globally coupled to effective microRNA target sites

DEFF Research Database (Denmark)

Jacobsen, Anders; Wen, Jiayu; Marks, Debora S

2010-01-01

MicroRNAs (miRNAs) and small interfering RNAs (siRNAs), bound to Argonaute proteins (RISC), destabilize mRNAs through base-pairing with the mRNA. However, the gene expression changes after perturbations of these small RNAs are only partially explained by predicted miRNA/siRNA targeting. Targeting...

MicroRNA prediction using a fixed-order Markov model based on the secondary structure pattern.

Directory of Open Access Journals (Sweden)

Wei Shen

Full Text Available Predicting miRNAs is an arduous task, due to the diversity of the precursors and complexity of enzyme processes. Although several prediction approaches have reached impressive performances, few of them could achieve a full-function recognition of mature miRNA directly from the candidate hairpins across species. Therefore, researchers continue to seek a more powerful model close to biological recognition to miRNA structure. In this report, we describe a novel miRNA prediction algorithm, known as FOMmiR, using a fixed-order Markov model based on the secondary structural pattern. For a training dataset containing 809 human pre-miRNAs and 6441 human pseudo-miRNA hairpins, the model's parameters were defined and evaluated. The results showed that FOMmiR reached 91% accuracy on the human dataset through 5-fold cross-validation. Moreover, for the independent test datasets, the FOMmiR presented an outstanding prediction in human and other species including vertebrates, Drosophila, worms and viruses, even plants, in contrast to the well-known algorithms and models. Especially, the FOMmiR was not only able to distinguish the miRNA precursors from the hairpins, but also locate the position and strand of the mature miRNA. Therefore, this study provides a new generation of miRNA prediction algorithm, which successfully realizes a full-function recognition of the mature miRNAs directly from the hairpin sequences. And it presents a new understanding of the biological recognition based on the strongest signal's location detected by FOMmiR, which might be closely associated with the enzyme cleavage mechanism during the miRNA maturation.

Methods for RNA Analysis

DEFF Research Database (Denmark)

Olivarius, Signe

of the transcriptome, 5’ end capture of RNA is combined with next-generation sequencing for high-throughput quantitative assessment of transcription start sites by two different methods. The methods presented here allow for functional investigation of coding as well as noncoding RNA and contribute to future...... RNAs rely on interactions with proteins, the establishment of protein-binding profiles is essential for the characterization of RNAs. Aiming to facilitate RNA analysis, this thesis introduces proteomics- as well as transcriptomics-based methods for the functional characterization of RNA. First, RNA...

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

Directory of Open Access Journals (Sweden)

Michael F Sloma

2017-11-01

Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

Science.gov (United States)

Sloma, Michael F; Mathews, David H

2017-11-01

Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

Species-independent MicroRNA Gene Discovery

KAUST Repository

Kamanu, Timothy K.

2012-12-01

MicroRNA (miRNA) are a class of small endogenous non-coding RNA that are mainly negative transcriptional and post-transcriptional regulators in both plants and animals. Recent studies have shown that miRNA are involved in different types of cancer and other incurable diseases such as autism and Alzheimer’s. Functional miRNAs are excised from hairpin-like sequences that are known as miRNA genes. There are about 21,000 known miRNA genes, most of which have been determined using experimental methods. miRNA genes are classified into different groups (miRNA families). This study reports about 19,000 unknown miRNA genes in nine species whereby approximately 15,300 predictions were computationally validated to contain at least one experimentally verified functional miRNA product. The predictions are based on a novel computational strategy which relies on miRNA family groupings and exploits the physics and geometry of miRNA genes to unveil the hidden palindromic signals and symmetries in miRNA gene sequences. Unlike conventional computational miRNA gene discovery methods, the algorithm developed here is species-independent: it allows prediction at higher accuracy and resolution from arbitrary RNA/DNA sequences in any species and thus enables examination of repeat-prone genomic regions which are thought to be non-informative or ’junk’ sequences. The information non-redundancy of uni-directional RNA sequences compared to information redundancy of bi-directional DNA is demonstrated, a fact that is overlooked by most pattern discovery algorithms. A novel method for computing upstream and downstream miRNA gene boundaries based on mathematical/statistical functions is suggested, as well as cutoffs for annotation of miRNA genes in different miRNA families. Another tool is proposed to allow hypotheses generation and visualization of data matrices, intra- and inter-species chromosomal distribution of miRNA genes or miRNA families. Our results indicate that: miRNA and miRNA

NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs.

Directory of Open Access Journals (Sweden)

Elize A Shirdel

2011-02-01

Full Text Available MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP.mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05, suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001, to be more studied (p<0.0002, and to have higher degree in the KEGG cancer pathway (p<0.0001, compared to intra-pathway microRNAs.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

m6A-Driver: Identifying Context-Specific mRNA m6A Methylation-Driven Gene Interaction Networks

OpenAIRE

Zhang, Song-Yao; Zhang, Shao-Wu; Liu, Lian; Meng, Jia; Huang, Yufei

2016-01-01

As the most prevalent mammalian mRNA epigenetic modification, N6-methyladenosine (m6A) has been shown to possess important post-transcriptional regulatory functions. However, the regulatory mechanisms and functional circuits of m6A are still largely elusive. To help unveil the regulatory circuitry mediated by mRNA m6A methylation, we develop here m6A-Driver, an algorithm for predicting m6A-driven genes and associated networks, whose functional interactions are likely to be actively modulated ...

Sensitive voltammetric detection of yeast RNA based on its interaction with Victoria Blue B

Directory of Open Access Journals (Sweden)

WEI SUN

2009-12-01

Full Text Available Voltammetric studies of the interaction of yeast RNA (y-RNA with Victoria Blue B (VBB are described in this paper. Furthermore, a linear sweep voltammetric method for the detection of y-RNA was established. The reaction conditions, such as acidity and amount of buffer solution, the concentration of VBB, the reaction time and temperature, etc., were carefully investigated by second order derivative linear sweep voltammetry. Under the optimal conditions, the reduction peak current of VBB at –0.75 V decreased greatly after the addition of y-RNA to the solution without any shift of the reduction peak potential. Based on the decrease of the peak current, a new quantitative method for the determination of y-RNA was developed. The effects of co-existing substances on the determination were carefully investigated and three synthetic samples were determined with satisfactory results. The stoichiometry of the VBB–y-RNA complex was calculated by linear sweep voltammetry and the interaction mechanism is discussed.

An integrated computational validation approach for potential novel miRNA prediction

Directory of Open Access Journals (Sweden)

Pooja Viswam

2017-12-01

Full Text Available MicroRNAs (miRNAs are short, non-coding RNAs between 17bp-24bp length that regulate gene expression by targeting mRNA molecules. The regulatory functions of miRNAs are known to be majorly associated with disease phenotypes such as cancer, cell signaling, cell division, growth and other metabolisms. Novel miRNAs are defined as sequences which does not have any similarity with the existing known sequences and void of any experimental evidences. In recent decades, the advent of next-generation sequencing allows us to capture the small RNA molecules form the cells and developing methods to estimate their expression levels. Several computational algorithms are available to predict the novel miRNAs from the deep sequencing data. In this work, we integrated three novel miRNA prediction programs miRDeep, miRanalyzer and miRPRo to compare and validate their prediction efficiency. The dicer cleavage sites, alignment density, seed conservation, minimum free energy, AU-GC percentage, secondary loop scores, false discovery rates and confidence scores will be considered for comparison and evaluation. Efficiency to identify isomiRs and base pair mismatches in a strand specific manner will also be considered for the computational validation. Further, the criteria and parameters for the identification of the best possible novel miRNA with minimal false positive rates were deduced.

Pyrite footprinting of RNA

International Nuclear Information System (INIS)

Schlatterer, Jörg C.; Wieder, Matthew S.; Jones, Christopher D.; Pollack, Lois; Brenowitz, Michael

2012-01-01

Highlights: ► RNA structure is mapped by pyrite mediated · OH footprinting. ► Repetitive experiments can be done in a powdered pyrite filled cartridge. ► High · OH reactivity of nucleotides imply dynamic role in Diels–Alderase catalysis. -- Abstract: In RNA, function follows form. Mapping the surface of RNA molecules with chemical and enzymatic probes has revealed invaluable information about structure and folding. Hydroxyl radicals ( · OH) map the surface of nucleic acids by cutting the backbone where it is accessible to solvent. Recent studies showed that a microfluidic chip containing pyrite (FeS 2 ) can produce sufficient · OH to footprint DNA. The 49-nt Diels–Alder RNA enzyme catalyzes the C–C bond formation between a diene and a dienophile. A crystal structure, molecular dynamics simulation and atomic mutagenesis studies suggest that nucleotides of an asymmetric bulge participate in the dynamic architecture of the ribozyme’s active center. Of note is that residue U42 directly interacts with the product in the crystallized RNA/product complex. Here, we use powdered pyrite held in a commercially available cartridge to footprint the Diels–Alderase ribozyme with single nucleotide resolution. Residues C39 to U42 are more reactive to · OH than predicted by the solvent accessibility calculated from the crystal structure suggesting that this loop is dynamic in solution. The loop’s flexibility may contribute to substrate recruitment and product release. Our implementation of pyrite-mediated · OH footprinting is a readily accessible approach to gleaning information about the architecture of small RNA molecules.

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

Science.gov (United States)

Ellington, Roni; Wachira, James

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems. PMID:20810968

RNA secondary structure prediction by using discrete mathematics: an interdisciplinary research experience for undergraduate students.

Science.gov (United States)

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses discrete mathematical techniques and identifies specified base pairs as parameters. The goal of the REU was to introduce upper-level undergraduate students to the principles and challenges of interdisciplinary research in molecular biology and discrete mathematics. At the beginning of the project, students from the biology and mathematics departments of a mid-sized university received instruction on the role of secondary structure in the function of eukaryotic RNAs and RNA viruses, RNA related to combinatorics, and the National Center for Biotechnology Information resources. The student research projects focused on RNA secondary structure prediction on a regulatory region of the yellow fever virus RNA genome and on an untranslated region of an mRNA of a gene associated with the neurological disorder epilepsy. At the end of the project, the REU students gave poster and oral presentations, and they submitted written final project reports to the program director. The outcome of the REU was that the students gained transferable knowledge and skills in bioinformatics and an awareness of the applications of discrete mathematics to biological research problems.

Integration and visualization of non-coding RNA and protein interaction networks

DEFF Research Database (Denmark)

Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

Non-coding RNAs (ncRNAs) fulfill a diverse set of biological functions relying on interactions with other molecular entities. The advent of new experimental and computational approaches makes it possible to study ncRNAs and their associations on an unprecedented scale. We present RAIN (RNA Associ......) co-occurrences found by text mining Medline abstracts. Each resource was assigned a reliability score by assessing its agreement with a gold standard set of microRNA-target interactions. RAIN is available at: http://rth.dk/resources/rain...

ncRNA-class Web Tool: Non-coding RNA feature extraction and pre-miRNA classification web tool

KAUST Repository

Kleftogiannis, Dimitrios A.; Theofilatos, Konstantinos A.; Papadimitriou, Stergios; Tsakalidis, Athanasios K.; Likothanassis, Spiridon D.; Mavroudi, Seferina P.

2012-01-01

Until recently, it was commonly accepted that most genetic information is transacted by proteins. Recent evidence suggests that the majority of the genomes of mammals and other complex organisms are in fact transcribed into non-coding RNAs (ncRNAs), many of which are alternatively spliced and/or processed into smaller products. Non coding RNA genes analysis requires the calculation of several sequential, thermodynamical and structural features. Many independent tools have already been developed for the efficient calculation of such features but to the best of our knowledge there does not exist any integrative approach for this task. The most significant amount of existing work is related to the miRNA class of non-coding RNAs. MicroRNAs (miRNAs) are small non-coding RNAs that play a significant role in gene regulation and their prediction is a challenging bioinformatics problem. Non-coding RNA feature extraction and pre-miRNA classification Web Tool (ncRNA-class Web Tool) is a publicly available web tool ( http://150.140.142.24:82/Default.aspx ) which provides a user friendly and efficient environment for the effective calculation of a set of 58 sequential, thermodynamical and structural features of non-coding RNAs, plus a tool for the accurate prediction of miRNAs. © 2012 IFIP International Federation for Information Processing.

Porcine Reproductive and Respiratory Syndrome Virus Nucleocapsid Protein Interacts with Nsp9 and Cellular DHX9 To Regulate Viral RNA Synthesis.

Science.gov (United States)

Liu, Long; Tian, Jiao; Nan, Hao; Tian, Mengmeng; Li, Yuan; Xu, Xiaodong; Huang, Baicheng; Zhou, Enmin; Hiscox, Julian A; Chen, Hongying

2016-06-01

Porcine reproductive and respiratory syndrome virus (PRRSV) nucleocapsid (N) protein is the main component of the viral capsid to encapsulate viral RNA, and it is also a multifunctional protein involved in the regulation of host cell processes. Nonstructural protein 9 (Nsp9) is the RNA-dependent RNA polymerase that plays a critical role in viral RNA transcription and replication. In this study, we demonstrate that PRRSV N protein is bound to Nsp9 by protein-protein interaction and that the contacting surface on Nsp9 is located in the two predicted α-helixes formed by 48 residues at the C-terminal end of the protein. Mutagenesis analyses identified E646, E608, and E611 on Nsp9 and Q85 on the N protein as the pivotal residues participating in the N-Nsp9 interaction. By overexpressing the N protein binding fragment of Nsp9 in infected Marc-145 cells, the synthesis of viral RNAs, as well as the production of infectious progeny viruses, was dramatically inhibited, suggesting that Nsp9-N protein association is involved in the process of viral RNA production. In addition, we show that PRRSV N interacts with cellular RNA helicase DHX9 and redistributes the protein into the cytoplasm. Knockdown of DHX9 increased the ratio of short subgenomic mRNAs (sgmRNAs); in contrast, DHX9 overexpression benefited the synthesis of longer sgmRNAs and the viral genomic RNA (gRNA). These results imply that DHX9 is recruited by the N protein in PRRSV infection to regulate viral RNA synthesis. We postulate that N and DHX9 may act as antiattenuation factors for the continuous elongation of nascent transcript during negative-strand RNA synthesis. It is unclear whether the N protein of PRRSV is involved in regulation of the viral RNA production process. In this report, we demonstrate that the N protein of the arterivirus PRRSV participates in viral RNA replication and transcription through interacting with Nsp9 and its RdRp and recruiting cellular RNA helicase to promote the production of

Model for an RNA tertiary interaction from the structure of an intermolecular complex between a GAAA tetraloop and an RNA helix.

Science.gov (United States)

Pley, H W; Flaherty, K M; McKay, D B

1994-11-03

In large structured RNAs, RNA hairpins in which the strands of the duplex stem are connected by a tetraloop of the consensus sequence 5'-GNRA (where N is any nucleotide, and R is either G or A) are unusually frequent. In group I introns there is a covariation in sequence between nucleotides in the third and fourth positions of the loop with specific distant base pairs in putative RNA duplex stems: GNAA loops correlate with successive 5'-C-C.G-C base pairs in stems, whereas GNGA loops correlate with 5'-C-U.G-A. This has led to the suggestion that GNRA tetraloops may be involved in specific long-range tertiary interactions, with each A in position 3 or 4 of the loop interacting with a C-G base pair in the duplex, and G in position 3 interacting with a U-A base pair. This idea is supported experimentally for the GAAA loop of the P5b extension of the group I intron of Tetrahymena thermophila and the L9 GUGA terminal loop of the td intron of bacteriophage T4 (ref. 4). NMR has revealed the overall structure of the tetraloop for 12-nucleotide hairpins with GCAA and GAAA loops and models have been proposed for the interaction of GNRA tetraloops with base pairs in the minor groove of A-form RNA. Here we describe the crystal structure of an intermolecular complex between a GAAA tetraloop and an RNA helix. The interactions we observe correlate with the specificity of GNRA tetraloops inferred from phylogenetic studies, suggesting that this complex is a legitimate model for intramolecular tertiary interactions mediated by GNRA tetraloops in large structured RNAs.

The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis.

Science.gov (United States)

Mohorianu, Irina; Stocks, Matthew Benedict; Applegate, Christopher Steven; Folkes, Leighton; Moulton, Vincent

2017-01-01

RNA silencing (RNA interference, RNAi) is a complex, highly conserved mechanism mediated by short, typically 20-24 nt in length, noncoding RNAs known as small RNAs (sRNAs). They act as guides for the sequence-specific transcriptional and posttranscriptional regulation of target mRNAs and play a key role in the fine-tuning of biological processes such as growth, response to stresses, or defense mechanism.High-throughput sequencing (HTS) technologies are employed to capture the expression levels of sRNA populations. The processing of the resulting big data sets facilitated the computational analysis of the sRNA patterns of variation within biological samples such as time point experiments, tissue series or various treatments. Rapid technological advances enable larger experiments, often with biological replicates leading to a vast amount of raw data. As a result, in this fast-evolving field, the existing methods for sequence characterization and prediction of interaction (regulatory) networks periodically require adapting or in extreme cases, a complete redesign to cope with the data deluge. In addition, the presence of numerous tools focused only on particular steps of HTS analysis hinders the systematic parsing of the results and their interpretation.The UEA small RNA Workbench (v1-4), described in this chapter, provides a user-friendly, modular, interactive analysis in the form of a suite of computational tools designed to process and mine sRNA datasets for interesting characteristics that can be linked back to the observed phenotypes. First, we show how to preprocess the raw sequencing output and prepare it for downstream analysis. Then we review some quality checks that can be used as a first indication of sources of variability between samples. Next we show how the Workbench can provide a comparison of the effects of different normalization approaches on the distributions of expression, enhanced methods for the identification of differentially expressed

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

Directory of Open Access Journals (Sweden)

Mo Min

2008-05-01

Full Text Available Abstract Background The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. Results By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (~17% showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. Conclusion An

MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.

Science.gov (United States)

Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-12

Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases. Especially, constructing computational methods to predict potential miRNA-disease associations is worthy of more studies because of the feasibility and effectivity. In this work, we developed a novel computational model of multiple kernels learning-based Kronecker regularized least squares for MiRNA-disease association prediction (MKRMDA), which could reveal potential miRNA-disease associations by automatically optimizing the combination of multiple kernels for disease and miRNA. MKRMDA obtained AUCs of 0.9040 and 0.8446 in global and local leave-one-out cross validation, respectively. Meanwhile, MKRMDA achieved average AUCs of 0.8894 ± 0.0015 in fivefold cross validation. Furthermore, we conducted three different kinds of case studies on some important human cancers for further performance evaluation. In the case studies of colonic cancer, esophageal cancer and lymphoma based on known miRNA-disease associations in HMDDv2.0 database, 76, 94 and 88% of the corresponding top 50 predicted miRNAs were confirmed by experimental reports, respectively. In another two kinds of case studies for new diseases without any known associated miRNAs and diseases only with known associations in HMDDv1.0 database, the verified ratios of two different cancers were 88 and 94%, respectively. All the results mentioned above adequately showed the reliable prediction ability of MKRMDA. We anticipated that MKRMDA could serve to facilitate further developments in the field and the follow-up investigations by biomedical researchers.

Mutant allele of rna14 in fission yeast affects pre-mRNA splicing

Indian Academy of Sciences (India)

transcript. Rna14 protein in budding yeast has been implicated in cleavage and ... Subsequently, genetic interaction of Rna14 with prp1 and physical .... molecular yeast techniques as described by Moreno et al. ..... To elucidate the role of Rna14 in splicing, RT-PCR analysis ..... design principles of a dynamic RNP machine.

Roles of Non-Coding RNA in Sugarcane-Microbe Interaction.

Science.gov (United States)

Thiebaut, Flávia; Rojas, Cristian A; Grativol, Clícia; Calixto, Edmundo P da R; Motta, Mariana R; Ballesteros, Helkin G F; Peixoto, Barbara; de Lima, Berenice N S; Vieira, Lucas M; Walter, Maria Emilia; de Armas, Elvismary M; Entenza, Júlio O P; Lifschitz, Sergio; Farinelli, Laurent; Hemerly, Adriana S; Ferreira, Paulo C G

2017-12-20

Studies have highlighted the importance of non-coding RNA regulation in plant-microbe interaction. However, the roles of sugarcane microRNAs (miRNAs) in the regulation of disease responses have not been investigated. Firstly, we screened the sRNA transcriptome of sugarcane infected with Acidovorax avenae . Conserved and novel miRNAs were identified. Additionally, small interfering RNAs (siRNAs) were aligned to differentially expressed sequences from the sugarcane transcriptome. Interestingly, many siRNAs aligned to a transcript encoding a copper-transporter gene whose expression was induced in the presence of A. avenae , while the siRNAs were repressed in the presence of A. avenae . Moreover, a long intergenic non-coding RNA was identified as a potential target or decoy of miR408. To extend the bioinformatics analysis, we carried out independent inoculations and the expression patterns of six miRNAs were validated by quantitative reverse transcription-PCR (qRT-PCR). Among these miRNAs, miR408-a copper-microRNA-was downregulated. The cleavage of a putative miR408 target, a laccase, was confirmed by a modified 5'RACE (rapid amplification of cDNA ends) assay. MiR408 was also downregulated in samples infected with other pathogens, but it was upregulated in the presence of a beneficial diazotrophic bacteria. Our results suggest that regulation by miR408 is important in sugarcane sensing whether microorganisms are either pathogenic or beneficial, triggering specific miRNA-mediated regulatory mechanisms accordingly.

Over-expression of the miRNA cluster at chromosome 14q32 in the alcoholic brain correlates with suppression of predicted target mRNA required for oligodendrocyte proliferation.

Science.gov (United States)

Manzardo, A M; Gunewardena, S; Butler, M G

2013-09-10

We examined miRNA expression from RNA isolated from the frontal cortex (Broadman area 9) of 9 alcoholics (6 males, 3 females, mean age 48 years) and 9 matched controls using both the Affymetrix GeneChip miRNA 2.0 and Human Exon 1.0 ST Arrays to further characterize genetic influences in alcoholism and the effects of alcohol consumption on predicted target mRNA expression. A total of 12 human miRNAs were significantly up-regulated in alcohol dependent subjects (fold change≥1.5, false discovery rate (FDR)≤0.3; p<0.05) compared with controls including a cluster of 4 miRNAs (e.g., miR-377, miR-379) from the maternally expressed 14q32 chromosome region. The status of the up-regulated miRNAs was supported using the high-throughput method of exon microarrays showing decreased predicted mRNA gene target expression as anticipated from the same RNA aliquot. Predicted mRNA targets were involved in cellular adhesion (e.g., THBS2), tissue differentiation (e.g., CHN2), neuronal migration (e.g., NDE1), myelination (e.g., UGT8, CNP) and oligodendrocyte proliferation (e.g., ENPP2, SEMA4D1). Our data support an association of alcoholism with up-regulation of a cluster of miRNAs located in the genomic imprinted domain on chromosome 14q32 with their predicted gene targets involved with oligodendrocyte growth, differentiation and signaling. Copyright © 2013 Elsevier B.V. All rights reserved.

Combinatorial microRNA target predictions

DEFF Research Database (Denmark)

Krek, Azra; Grün, Dominic; Poy, Matthew N.

2005-01-01

MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript1, 2, 3. Different combinations of microRNAs are expressed...... in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published micro......RNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results...

Structural imprints in vivo decode RNA regulatory mechanisms.

Science.gov (United States)

Spitale, Robert C; Flynn, Ryan A; Zhang, Qiangfeng Cliff; Crisalli, Pete; Lee, Byron; Jung, Jong-Wha; Kuchelmeister, Hannes Y; Batista, Pedro J; Torre, Eduardo A; Kool, Eric T; Chang, Howard Y

2015-03-26

Visualizing the physical basis for molecular behaviour inside living cells is a great challenge for biology. RNAs are central to biological regulation, and the ability of RNA to adopt specific structures intimately controls every step of the gene expression program. However, our understanding of physiological RNA structures is limited; current in vivo RNA structure profiles include only two of the four nucleotides that make up RNA. Here we present a novel biochemical approach, in vivo click selective 2'-hydroxyl acylation and profiling experiment (icSHAPE), which enables the first global view, to our knowledge, of RNA secondary structures in living cells for all four bases. icSHAPE of the mouse embryonic stem cell transcriptome versus purified RNA folded in vitro shows that the structural dynamics of RNA in the cellular environment distinguish different classes of RNAs and regulatory elements. Structural signatures at translational start sites and ribosome pause sites are conserved from in vitro conditions, suggesting that these RNA elements are programmed by sequence. In contrast, focal structural rearrangements in vivo reveal precise interfaces of RNA with RNA-binding proteins or RNA-modification sites that are consistent with atomic-resolution structural data. Such dynamic structural footprints enable accurate prediction of RNA-protein interactions and N(6)-methyladenosine (m(6)A) modification genome wide. These results open the door for structural genomics of RNA in living cells and reveal key physiological structures controlling gene expression.

Matrix factorization-based data fusion for the prediction of lncRNA-disease associations.

Science.gov (United States)

Fu, Guangyuan; Wang, Jun; Domeniconi, Carlotta; Yu, Guoxian

2018-05-01

Long non-coding RNAs (lncRNAs) play crucial roles in complex disease diagnosis, prognosis, prevention and treatment, but only a small portion of lncRNA-disease associations have been experimentally verified. Various computational models have been proposed to identify lncRNA-disease associations by integrating heterogeneous data sources. However, existing models generally ignore the intrinsic structure of data sources or treat them as equally relevant, while they may not be. To accurately identify lncRNA-disease associations, we propose a Matrix Factorization based LncRNA-Disease Association prediction model (MFLDA in short). MFLDA decomposes data matrices of heterogeneous data sources into low-rank matrices via matrix tri-factorization to explore and exploit their intrinsic and shared structure. MFLDA can select and integrate the data sources by assigning different weights to them. An iterative solution is further introduced to simultaneously optimize the weights and low-rank matrices. Next, MFLDA uses the optimized low-rank matrices to reconstruct the lncRNA-disease association matrix and thus to identify potential associations. In 5-fold cross validation experiments to identify verified lncRNA-disease associations, MFLDA achieves an area under the receiver operating characteristic curve (AUC) of 0.7408, at least 3% higher than those given by state-of-the-art data fusion based computational models. An empirical study on identifying masked lncRNA-disease associations again shows that MFLDA can identify potential associations more accurately than competing models. A case study on identifying lncRNAs associated with breast, lung and stomach cancers show that 38 out of 45 (84%) associations predicted by MFLDA are supported by recent biomedical literature and further proves the capability of MFLDA in identifying novel lncRNA-disease associations. MFLDA is a general data fusion framework, and as such it can be adopted to predict associations between other biological

TAPIR, a web server for the prediction of plant microRNA targets, including target mimics.

Science.gov (United States)

Bonnet, Eric; He, Ying; Billiau, Kenny; Van de Peer, Yves

2010-06-15

We present a new web server called TAPIR, designed for the prediction of plant microRNA targets. The server offers the possibility to search for plant miRNA targets using a fast and a precise algorithm. The precise option is much slower but guarantees to find less perfectly paired miRNA-target duplexes. Furthermore, the precise option allows the prediction of target mimics, which are characterized by a miRNA-target duplex having a large loop, making them undetectable by traditional tools. The TAPIR web server can be accessed at: http://bioinformatics.psb.ugent.be/webtools/tapir. Supplementary data are available at Bioinformatics online.

Know Your Enemy: Successful Bioinformatic Approaches to Predict Functional RNA Structures in Viral RNAs

Science.gov (United States)

Lim, Chun Shen; Brown, Chris M.

2018-01-01

Structured RNA elements may control virus replication, transcription and translation, and their distinct features are being exploited by novel antiviral strategies. Viral RNA elements continue to be discovered using combinations of experimental and computational analyses. However, the wealth of sequence data, notably from deep viral RNA sequencing, viromes, and metagenomes, necessitates computational approaches being used as an essential discovery tool. In this review, we describe practical approaches being used to discover functional RNA elements in viral genomes. In addition to success stories in new and emerging viruses, these approaches have revealed some surprising new features of well-studied viruses e.g., human immunodeficiency virus, hepatitis C virus, influenza, and dengue viruses. Some notable discoveries were facilitated by new comparative analyses of diverse viral genome alignments. Importantly, comparative approaches for finding RNA elements embedded in coding and non-coding regions differ. With the exponential growth of computer power we have progressed from stem-loop prediction on single sequences to cutting edge 3D prediction, and from command line to user friendly web interfaces. Despite these advances, many powerful, user friendly prediction tools and resources are underutilized by the virology community. PMID:29354101

JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

Science.gov (United States)

Shi, Jieming; Li, Xi; Dong, Min; Graham, Mitchell; Yadav, Nehul; Liang, Chun

2017-01-01

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

JNSViewer—A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures

Science.gov (United States)

Dong, Min; Graham, Mitchell; Yadav, Nehul

2017-01-01

Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome) were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html. PMID:28582416

JNSViewer-A JavaScript-based Nucleotide Sequence Viewer for DNA/RNA secondary structures.

Directory of Open Access Journals (Sweden)

Jieming Shi

Full Text Available Many tools are available for visualizing RNA or DNA secondary structures, but there is scarce implementation in JavaScript that provides seamless integration with the increasingly popular web computational platforms. We have developed JNSViewer, a highly interactive web service, which is bundled with several popular tools for DNA/RNA secondary structure prediction and can provide precise and interactive correspondence among nucleotides, dot-bracket data, secondary structure graphs, and genic annotations. In JNSViewer, users can perform RNA secondary structure predictions with different programs and settings, add customized genic annotations in GFF format to structure graphs, search for specific linear motifs, and extract relevant structure graphs of sub-sequences. JNSViewer also allows users to choose a transcript or specific segment of Arabidopsis thaliana genome sequences and predict the corresponding secondary structure. Popular genome browsers (i.e., JBrowse and BrowserGenome were integrated into JNSViewer to provide powerful visualizations of chromosomal locations, genic annotations, and secondary structures. In addition, we used StructureFold with default settings to predict some RNA structures for Arabidopsis by incorporating in vivo high-throughput RNA structure profiling data and stored the results in our web server, which might be a useful resource for RNA secondary structure studies in plants. JNSViewer is available at http://bioinfolab.miamioh.edu/jnsviewer/index.html.

Automated identification of RNA 3D modules with discriminative power in RNA structural alignments

DEFF Research Database (Denmark)

Theis, Corinna; Höner zu Siederdissen, Christian; Hofacker, Ivo L.

2013-01-01

Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general...... comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22495 3D modules in all PDB files results in 977 internal loop...

dPORE-miRNA: Polymorphic regulation of microRNA genes

KAUST Repository

Schmeier, Sebastian; Schaefer, Ulf; MacPherson, Cameron R.; Bajic, Vladimir B.

2011-01-01

Background: MicroRNAs (miRNAs) are short non-coding RNA molecules that act as post-transcriptional regulators and affect the regulation of protein-coding genes. Mostly transcribed by PolII, miRNA genes are regulated at the transcriptional level similarly to protein-coding genes. In this study we focus on human miRNAs. These miRNAs are involved in a variety of pathways and can affect many diseases. Our interest is on possible deregulation of the transcription initiation of the miRNA encoding genes, which is facilitated by variations in the genomic sequence of transcriptional control regions (promoters). Methodology: Our aim is to provide an online resource to facilitate the investigation of the potential effects of single nucleotide polymorphisms (SNPs) on miRNA gene regulation. We analyzed SNPs overlapped with predicted transcription factor binding sites (TFBSs) in promoters of miRNA genes. We also accounted for the creation of novel TFBSs due to polymorphisms not present in the reference genome. The resulting changes in the original TFBSs and potential creation of new TFBSs were incorporated into the Dragon Database of Polymorphic Regulation of miRNA genes (dPORE-miRNA). Conclusions: The dPORE-miRNA database enables researchers to explore potential effects of SNPs on the regulation of miRNAs. dPORE-miRNA can be interrogated with regards to: a/miRNAs (their targets, or involvement in diseases, or biological pathways), b/SNPs, or c/transcription factors. dPORE-miRNA can be accessed at http://cbrc.kaust.edu.sa/dpore and http://apps.sanbi.ac.za/dpore/. Its use is free for academic and non-profit users. © 2011 Schmeier et al.

dPORE-miRNA: Polymorphic regulation of microRNA genes

KAUST Repository

Schmeier, Sebastian

2011-02-04

Background: MicroRNAs (miRNAs) are short non-coding RNA molecules that act as post-transcriptional regulators and affect the regulation of protein-coding genes. Mostly transcribed by PolII, miRNA genes are regulated at the transcriptional level similarly to protein-coding genes. In this study we focus on human miRNAs. These miRNAs are involved in a variety of pathways and can affect many diseases. Our interest is on possible deregulation of the transcription initiation of the miRNA encoding genes, which is facilitated by variations in the genomic sequence of transcriptional control regions (promoters). Methodology: Our aim is to provide an online resource to facilitate the investigation of the potential effects of single nucleotide polymorphisms (SNPs) on miRNA gene regulation. We analyzed SNPs overlapped with predicted transcription factor binding sites (TFBSs) in promoters of miRNA genes. We also accounted for the creation of novel TFBSs due to polymorphisms not present in the reference genome. The resulting changes in the original TFBSs and potential creation of new TFBSs were incorporated into the Dragon Database of Polymorphic Regulation of miRNA genes (dPORE-miRNA). Conclusions: The dPORE-miRNA database enables researchers to explore potential effects of SNPs on the regulation of miRNAs. dPORE-miRNA can be interrogated with regards to: a/miRNAs (their targets, or involvement in diseases, or biological pathways), b/SNPs, or c/transcription factors. dPORE-miRNA can be accessed at http://cbrc.kaust.edu.sa/dpore and http://apps.sanbi.ac.za/dpore/. Its use is free for academic and non-profit users. © 2011 Schmeier et al.

Dissecting the interactions of SERRATE with RNA and DICER-LIKE 1 in Arabidopsis microRNA precursor processing

KAUST Repository

Iwata, Yuji; Takahashi, Masateru; Fedoroff, Nina V.; Hamdan, Samir

2013-01-01

). In the present study, we examined primary miRNA precursor (pri-miRNA) processing by highly purified recombinant DCL1 and SE proteins and found that SE is integral to pri-miRNA processing by DCL1. SE stimulates DCL1 cleavage of the pri-miRNA in an ionic strength

Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees

Directory of Open Access Journals (Sweden)

Philip H. Williams

2012-01-01

Full Text Available MicroRNAs (miRNAs are nonprotein coding RNAs between 20 and 22 nucleotides long that attenuate protein production. Different types of sequence data are being investigated for novel miRNAs, including genomic and transcriptomic sequences. A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. MirTools, mirDeep2, and miRanalyzer require “read count” to be included with the input sequences, which restricts their use to deep-sequencing data. Our aim was to train a predictor using a cross-section of different species to accurately predict miRNAs outside the training set. We wanted a system that did not require read-count for prediction and could therefore be applied to short sequences extracted from genomic, EST, or RNA-seq sources. A miRNA-predictive decision-tree model has been developed by supervised machine learning. It only requires that the corresponding genome or transcriptome is available within a sequence window that includes the precursor candidate so that the required sequence features can be collected. Some of the most critical features for training the predictor are the miRNA:miRNA∗ duplex energy and the number of mismatches in the duplex. We present a cross-species plant miRNA predictor with 84.08% sensitivity and 98.53% specificity based on rigorous testing by leave-one-out validation.

A KH-Domain RNA-Binding Protein Interacts with FIERY2/CTD Phosphatase-Like 1 and Splicing Factors and Is Important for Pre-mRNA Splicing in Arabidopsis

KAUST Repository

Chen, Tao; Cui, Peng; Chen, Hao; Ali, Shahjahan; Zhang, ShouDong; Xiong, Liming

2013-01-01

Eukaryotic genomes encode hundreds of RNA-binding proteins, yet the functions of most of these proteins are unknown. In a genetic study of stress signal transduction in Arabidopsis, we identified a K homology (KH)-domain RNA-binding protein, HOS5 (High Osmotic Stress Gene Expression 5), as required for stress gene regulation and stress tolerance. HOS5 was found to interact with FIERY2/RNA polymerase II (RNAP II) carboxyl terminal domain (CTD) phosphatase-like 1 (FRY2/CPL1) both in vitro and in vivo. This interaction is mediated by the first double-stranded RNA-binding domain of FRY2/CPL1 and the KH domains of HOS5. Interestingly, both HOS5 and FRY2/CPL1 also interact with two novel serine-arginine (SR)-rich splicing factors, RS40 and RS41, in nuclear speckles. Importantly, FRY2/CPL1 is required for the recruitment of HOS5. In fry2 mutants, HOS5 failed to be localized in nuclear speckles but was found mainly in the nucleoplasm. hos5 mutants were impaired in mRNA export and accumulated a significant amount of mRNA in the nuclei, particularly under salt stress conditions. Arabidopsis mutants of all these genes exhibit similar stress-sensitive phenotypes. RNA-seq analyses of these mutants detected significant intron retention in many stress-related genes under salt stress but not under normal conditions. Our study not only identified several novel regulators of pre-mRNA processing as important for plant stress response but also suggested that, in addition to RNAP II CTD that is a well-recognized platform for the recruitment of mRNA processing factors, FRY2/CPL1 may also recruit specific factors to regulate the co-transcriptional processing of certain transcripts to deal with environmental challenges. © 2013 Chen et al.

A KH-Domain RNA-Binding Protein Interacts with FIERY2/CTD Phosphatase-Like 1 and Splicing Factors and Is Important for Pre-mRNA Splicing in Arabidopsis

KAUST Repository

Chen, Tao

2013-10-17

Eukaryotic genomes encode hundreds of RNA-binding proteins, yet the functions of most of these proteins are unknown. In a genetic study of stress signal transduction in Arabidopsis, we identified a K homology (KH)-domain RNA-binding protein, HOS5 (High Osmotic Stress Gene Expression 5), as required for stress gene regulation and stress tolerance. HOS5 was found to interact with FIERY2/RNA polymerase II (RNAP II) carboxyl terminal domain (CTD) phosphatase-like 1 (FRY2/CPL1) both in vitro and in vivo. This interaction is mediated by the first double-stranded RNA-binding domain of FRY2/CPL1 and the KH domains of HOS5. Interestingly, both HOS5 and FRY2/CPL1 also interact with two novel serine-arginine (SR)-rich splicing factors, RS40 and RS41, in nuclear speckles. Importantly, FRY2/CPL1 is required for the recruitment of HOS5. In fry2 mutants, HOS5 failed to be localized in nuclear speckles but was found mainly in the nucleoplasm. hos5 mutants were impaired in mRNA export and accumulated a significant amount of mRNA in the nuclei, particularly under salt stress conditions. Arabidopsis mutants of all these genes exhibit similar stress-sensitive phenotypes. RNA-seq analyses of these mutants detected significant intron retention in many stress-related genes under salt stress but not under normal conditions. Our study not only identified several novel regulators of pre-mRNA processing as important for plant stress response but also suggested that, in addition to RNAP II CTD that is a well-recognized platform for the recruitment of mRNA processing factors, FRY2/CPL1 may also recruit specific factors to regulate the co-transcriptional processing of certain transcripts to deal with environmental challenges. © 2013 Chen et al.

Improved Model for Predicting the Free Energy Contribution of Dinucleotide Bulges to RNA Duplex Stability.

Science.gov (United States)

Tomcho, Jeremy C; Tillman, Magdalena R; Znosko, Brent M

2015-09-01

Predicting the secondary structure of RNA is an intermediate in predicting RNA three-dimensional structure. Commonly, determining RNA secondary structure from sequence uses free energy minimization and nearest neighbor parameters. Current algorithms utilize a sequence-independent model to predict free energy contributions of dinucleotide bulges. To determine if a sequence-dependent model would be more accurate, short RNA duplexes containing dinucleotide bulges with different sequences and nearest neighbor combinations were optically melted to derive thermodynamic parameters. These data suggested energy contributions of dinucleotide bulges were sequence-dependent, and a sequence-dependent model was derived. This model assigns free energy penalties based on the identity of nucleotides in the bulge (3.06 kcal/mol for two purines, 2.93 kcal/mol for two pyrimidines, 2.71 kcal/mol for 5'-purine-pyrimidine-3', and 2.41 kcal/mol for 5'-pyrimidine-purine-3'). The predictive model also includes a 0.45 kcal/mol penalty for an A-U pair adjacent to the bulge and a -0.28 kcal/mol bonus for a G-U pair adjacent to the bulge. The new sequence-dependent model results in predicted values within, on average, 0.17 kcal/mol of experimental values, a significant improvement over the sequence-independent model. This model and new experimental values can be incorporated into algorithms that predict RNA stability and secondary structure from sequence.

Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization

Directory of Open Access Journals (Sweden)

Junilda Spirollari

2009-01-01

Full Text Available Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http:// datalab.njit.edu/biology/RSpredict.

Self-assembled RNA-triple-helix hydrogel scaffold for microRNA modulation in the tumour microenvironment

Science.gov (United States)

Conde, João; Oliva, Nuria; Atilano, Mariana; Song, Hyun Seok; Artzi, Natalie

2016-03-01

The therapeutic potential of miRNA (miR) in cancer is limited by the lack of efficient delivery vehicles. Here, we show that a self-assembled dual-colour RNA-triple-helix structure comprising two miRNAs--a miR mimic (tumour suppressor miRNA) and an antagomiR (oncomiR inhibitor)--provides outstanding capability to synergistically abrogate tumours. Conjugation of RNA triple helices to dendrimers allows the formation of stable triplex nanoparticles, which form an RNA-triple-helix adhesive scaffold upon interaction with dextran aldehyde, the latter able to chemically interact and adhere to natural tissue amines in the tumour. We also show that the self-assembled RNA-triple-helix conjugates remain functional in vitro and in vivo, and that they lead to nearly 90% levels of tumour shrinkage two weeks post-gel implantation in a triple-negative breast cancer mouse model. Our findings suggest that the RNA-triple-helix hydrogels can be used as an efficient anticancer platform to locally modulate the expression of endogenous miRs in cancer.

Differential Regulation of rRNA and tRNA Transcription from the rRNA-tRNA Composite Operon in Escherichia coli.

Directory of Open Access Journals (Sweden)

Hiraku Takada

Full Text Available Escherichia coli contains seven rRNA operons, each consisting of the genes for three rRNAs (16S, 23S and 5S rRNA in this order and one or two tRNA genes in the spacer between 16S and 23S rRNA genes and one or two tRNA genes in the 3' proximal region. All of these rRNA and tRNA genes are transcribed from two promoters, P1 and P2, into single large precursors that are afterward processed to individual rRNAs and tRNAs by a set of RNases. In the course of Genomic SELEX screening of promoters recognized by RNA polymerase (RNAP holoenzyme containing RpoD sigma, a strong binding site was identified within 16S rRNA gene in each of all seven rRNA operons. The binding in vitro of RNAP RpoD holoenzyme to an internal promoter, referred to the promoter of riRNA (an internal RNA of the rRNA operon, within each 16S rRNA gene was confirmed by gel shift assay and AFM observation. Using this riRNA promoter within the rrnD operon as a representative, transcription in vitro was detected with use of the purified RpoD holoenzyme, confirming the presence of a constitutive promoter in this region. LacZ reporter assay indicated that this riRNA promoter is functional in vivo. The location of riRNA promoter in vivo as identified using a set of reporter plasmids agrees well with that identified in vitro. Based on transcription profile in vitro and Northern blot analysis in vivo, the majority of transcript initiated from this riRNA promoter was estimated to terminate near the beginning of 23S rRNA gene, indicating that riRNA leads to produce the spacer-coded tRNA. Under starved conditions, transcription of the rRNA operon is markedly repressed to reduce the intracellular level of ribosomes, but the levels of both riRNA and its processed tRNAGlu stayed unaffected, implying that riRNA plays a role in the continued steady-state synthesis of tRNAs from the spacers of rRNA operons. We then propose that the tRNA genes organized within the spacers of rRNA-tRNA composite operons

Parallel mRNA, proteomics and miRNA expression analysis in cell line models of the intestine.

Science.gov (United States)

O'Sullivan, Finbarr; Keenan, Joanne; Aherne, Sinead; O'Neill, Fiona; Clarke, Colin; Henry, Michael; Meleady, Paula; Breen, Laura; Barron, Niall; Clynes, Martin; Horgan, Karina; Doolan, Padraig; Murphy, Richard

2017-11-07

To identify miRNA-regulated proteins differentially expressed between Caco2 and HT-29: two principal cell line models of the intestine. Exponentially growing Caco-2 and HT-29 cells were harvested and prepared for mRNA, miRNA and proteomic profiling. mRNA microarray profiling analysis was carried out using the Affymetrix GeneChip Human Gene 1.0 ST array. miRNA microarray profiling analysis was carried out using the Affymetrix Genechip miRNA 3.0 array. Quantitative Label-free LC-MS/MS proteomic analysis was performed using a Dionex Ultimate 3000 RSLCnano system coupled to a hybrid linear ion trap/Orbitrap mass spectrometer. Peptide identities were validated in Proteome Discoverer 2.1 and were subsequently imported into Progenesis QI software for further analysis. Hierarchical cluster analysis for all three parallel datasets (miRNA, proteomics, mRNA) was conducted in the R software environment using the Euclidean distance measure and Ward's clustering algorithm. The prediction of miRNA and oppositely correlated protein/mRNA interactions was performed using TargetScan 6.1. GO biological process, molecular function and cellular component enrichment analysis was carried out for the DE miRNA, protein and mRNA lists via the Pathway Studio 11.3 Web interface using their Mammalian database. Differential expression (DE) profiling comparing the intestinal cell lines HT-29 and Caco-2 identified 1795 Genes, 168 Proteins and 160 miRNAs as DE between the two cell lines. At the gene level, 1084 genes were upregulated and 711 were downregulated in the Caco-2 cell line relative to the HT-29 cell line. At the protein level, 57 proteins were found to be upregulated and 111 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Finally, at the miRNAs level, 104 were upregulated and 56 downregulated in the Caco-2 cell line relative to the HT-29 cell line. Gene ontology (GO) analysis of the DE mRNA identified cell adhesion, migration and ECM organization, cellular lipid

RNA Sequencing and Bioinformatics Analysis Implicate the Regulatory Role of a Long Noncoding RNA-mRNA Network in Hepatic Stellate Cell Activation.

Science.gov (United States)

Guo, Can-Jie; Xiao, Xiao; Sheng, Li; Chen, Lili; Zhong, Wei; Li, Hai; Hua, Jing; Ma, Xiong

2017-01-01

To analyze the long noncoding (lncRNA)-mRNA expression network and potential roles in rat hepatic stellate cells (HSCs) during activation. LncRNA expression was analyzed in quiescent and culture-activated HSCs by RNA sequencing, and differentially expressed lncRNAs verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR) were subjected to bioinformatics analysis. In vivo analyses of differential lncRNA-mRNA expression were performed on a rat model of liver fibrosis. We identified upregulation of 12 lncRNAs and 155 mRNAs and downregulation of 12 lncRNAs and 374 mRNAs in activated HSCs. Additionally, we identified the differential expression of upregulated lncRNAs (NONRATT012636.2, NONRATT016788.2, and NONRATT021402.2) and downregulated lncRNAs (NONRATT007863.2, NONRATT019720.2, and NONRATT024061.2) in activated HSCs relative to levels observed in quiescent HSCs, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that changes in lncRNAs associated with HSC activation revealed 11 significantly enriched pathways according to their predicted targets. Moreover, based on the predicted co-expression network, the relative dynamic levels of NONRATT013819.2 and lysyl oxidase (Lox) were compared during HSC activation both in vitro and in vivo. Our results confirmed the upregulation of lncRNA NONRATT013819.2 and Lox mRNA associated with the extracellular matrix (ECM)-related signaling pathway in HSCs and fibrotic livers. Our results detailing a dysregulated lncRNA-mRNA network might provide new treatment strategies for hepatic fibrosis based on findings indicating potentially critical roles for NONRATT013819.2 and Lox in ECM remodeling during HSC activation. © 2017 The Author(s). Published by S. Karger AG, Basel.

A Two-Way Street: Regulatory Interplay between RNA Polymerase and Nascent RNA Structure.

Science.gov (United States)

Zhang, Jinwei; Landick, Robert

2016-04-01

The vectorial (5'-to-3' at varying velocity) synthesis of RNA by cellular RNA polymerases (RNAPs) creates a rugged kinetic landscape, demarcated by frequent, sometimes long-lived, pauses. In addition to myriad gene-regulatory roles, these pauses temporally and spatially program the co-transcriptional, hierarchical folding of biologically active RNAs. Conversely, these RNA structures, which form inside or near the RNA exit channel, interact with the polymerase and adjacent protein factors to influence RNA synthesis by modulating pausing, termination, antitermination, and slippage. Here, we review the evolutionary origin, mechanistic underpinnings, and regulatory consequences of this interplay between RNAP and nascent RNA structure. We categorize and rationalize the extensive linkage between the transcriptional machinery and its product, and provide a framework for future studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

The RNA gene information: retroelement-microRNA entangling as the RNA quantum code.

Science.gov (United States)

Fujii, Yoichi Robertus

2013-01-01

MicroRNA (miRNA) and retroelements may be a master of regulator in our life, which are evolutionally involved in the origin of species. To support the Darwinism from the aspect of molecular evolution process, it has tremendously been interested in the molecular information of naive RNA. The RNA wave model 2000 consists of four concepts that have altered from original idea of the miRNA genes for crosstalk among embryonic stem cells, their niche cells, and retroelements as a carrier vesicle of the RNA genes. (1) the miRNA gene as a mobile genetic element induces transcriptional and posttranscriptional silencing via networking-processes (no hierarchical architecture); (2) the RNA information supplied by the miRNA genes expands to intracellular, intercellular, intraorgan, interorgan, intraspecies, and interspecies under the cycle of life into the global environment; (3) the mobile miRNAs can self-proliferate; and (4) cells contain two types information as resident and genomic miRNAs. Based on RNA wave, we have developed an interest in investigation of the transformation from RNA information to quantum bits as physicochemical characters of RNA with the measurement of RNA electron spin. When it would have been given that the fundamental bases for the acquired characters in genetics can be controlled by RNA gene information, it may be available to apply for challenging against RNA gene diseases, such as stress-induced diseases.

Structural basis for ribosome protein S1 interaction with RNA in trans-translation of Mycobacterium tuberculosis.

Science.gov (United States)

Fan, Yi; Dai, Yazhuang; Hou, Meijing; Wang, Huilin; Yao, Hongwei; Guo, Chenyun; Lin, Donghai; Liao, Xinli

2017-05-27

Ribosomal protein S1 (RpsA), the largest 30S protein in ribosome, plays a significant role in translation and trans-translation. In Mycobacterium tuberculosis, the C-terminus of RpsA is known as tuberculosis drug target of pyrazinoic acid, which inhibits the interaction between MtRpsA and tmRNA in trans-translation. However, the molecular mechanism underlying the interaction of MtRpsA with tmRNA remains unknown. We herein analyzed the interaction of the C-terminal domain of MtRpsA with three RNA fragments poly(A), sMLD and pre-sMLD. NMR titration analysis revealed that the RNA binding sites on MtRpsA CTD are mainly located in the β2, β3 and β5 strands and the adjacent L3 loop of the S1 domain. Fluorescence experiments determined the MtRpsA CTD binding to RNAs are in the micromolar affinity range. Sequence analysis also revealed conserved residues in the mapped RNA binding region. Residues L304, V305, G308, F310, H322, I323, R357 and I358 were verified to be the key residues influencing the interaction between MtRpsA CTD and pre-sMLD. Molecular docking further confirmed that the poly(A)-like sequence and sMLD of tmRNA are all involved in the protein-RNA interaction, through charged interaction and hydrogen bonds. The results will be beneficial for designing new anti-tuberculosis drugs. Copyright © 2017 Elsevier Inc. All rights reserved.

Integrated microRNA and mRNA signatures associated with survival in triple negative breast cancer.

Science.gov (United States)

Cascione, Luciano; Gasparini, Pierluigi; Lovat, Francesca; Carasi, Stefania; Pulvirenti, Alfredo; Ferro, Alfredo; Alder, Hansjuerg; He, Gang; Vecchione, Andrea; Croce, Carlo M; Shapiro, Charles L; Huebner, Kay

2013-01-01

Triple negative breast cancer (TNBC) is a heterogeneous disease at the molecular, pathologic and clinical levels. To stratify TNBCs, we determined microRNA (miRNA) expression profiles, as well as expression profiles of a cancer-focused mRNA panel, in tumor, adjacent non-tumor (normal) and lymph node metastatic lesion (mets) tissues, from 173 women with TNBCs; we linked specific miRNA signatures to patient survival and used miRNA/mRNA anti-correlations to identify clinically and genetically different TNBC subclasses. We also assessed miRNA signatures as potential regulators of TNBC subclass-specific gene expression networks defined by expression of canonical signal pathways.Tissue specific miRNAs and mRNAs were identified for normal vs tumor vs mets comparisons. miRNA signatures correlated with prognosis were identified and predicted anti-correlated targets within the mRNA profile were defined. Two miRNA signatures (miR-16, 155, 125b, 374a and miR-16, 125b, 374a, 374b, 421, 655, 497) predictive of overall survival (P = 0.05) and distant-disease free survival (P = 0.009), respectively, were identified for patients 50 yrs of age or younger. By multivariate analysis the risk signatures were independent predictors for overall survival and distant-disease free survival. mRNA expression profiling, using the cancer-focused mRNA panel, resulted in clustering of TNBCs into 4 molecular subclasses with different expression signatures anti-correlated with the prognostic miRNAs. Our findings suggest that miRNAs play a key role in triple negative breast cancer through their ability to regulate fundamental pathways such as: cellular growth and proliferation, cellular movement and migration, Extra Cellular Matrix degradation. The results define miRNA expression signatures that characterize and contribute to the phenotypic diversity of TNBC and its metastasis.

miRNAFold: a web server for fast miRNA precursor prediction in genomes.

Science.gov (United States)

Tav, Christophe; Tempel, Sébastien; Poligny, Laurent; Tahi, Fariza

2016-07-08

Computational methods are required for prediction of non-coding RNAs (ncRNAs), which are involved in many biological processes, especially at post-transcriptional level. Among these ncRNAs, miRNAs have been largely studied and biologists need efficient and fast tools for their identification. In particular, ab initio methods are usually required when predicting novel miRNAs. Here we present a web server dedicated for miRNA precursors identification at a large scale in genomes. It is based on an algorithm called miRNAFold that allows predicting miRNA hairpin structures quickly with high sensitivity. miRNAFold is implemented as a web server with an intuitive and user-friendly interface, as well as a standalone version. The web server is freely available at: http://EvryRNA.ibisc.univ-evry.fr/miRNAFold. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gender-specific hierarchy in nuage localization of PIWI-interacting RNA factors in Drosophila

Directory of Open Access Journals (Sweden)

Mikiko C Siomi

2011-08-01

Full Text Available PIWI-interacting RNAs (piRNAs are germline-specific small non-coding RNAs that form piRNA-induced silencing complexes (piRISCs by associating with PIWI proteins, a subclade of the Argonaute proteins predominantly expressed in the germline. piRISCs protect the integrity of the germline genome from invasive transposable DNA elements by silencing them. Multiple piRNA biogenesis factors have been identified in Drosophila. The majority of piRNA factors are localized in the nuage, electron-dense non-membranous cytoplasmic structures located in the perinuclear regions of germ cells. Thus, piRNA biogenesis is thought to occur in the nuage in germ cells. Immunofluorescence analyses of ovaries from piRNA factor mutants have revealed a localization hierarchy of piRNA factors in female nuage. However, whether this hierarchy is female-specific or can also be applied in male gonads remains undetermined. Here, we show by immunostaining of both ovaries and testes from piRNA factor mutants that the molecular hierarchy of piRNA factors shows gender-specificity, especially for Krimper (Krimp, a Tudor-domain containing protein of unknown function(s: Krimp is dispensable for PIWI protein Aubergine (Aub nuage localization in ovaries but Krimp and Aub require each other for their proper nuage localization in testes. This suggests that the functional requirement of Krimp in piRNA biogenesis may be different in male and female gonads.

Capturing microRNA targets using an RNA-induced silencing complex (RISC)-trap approach.

Science.gov (United States)

Cambronne, Xiaolu A; Shen, Rongkun; Auer, Paul L; Goodman, Richard H

2012-12-11

Identifying targets is critical for understanding the biological effects of microRNA (miRNA) expression. The challenge lies in characterizing the cohort of targets for a specific miRNA, especially when targets are being actively down-regulated in miRNA- RNA-induced silencing complex (RISC)-messengerRNA (mRNA) complexes. We have developed a robust and versatile strategy called RISCtrap to stabilize and purify targets from this transient interaction. Its utility was demonstrated by determining specific high-confidence target datasets for miR-124, miR-132, and miR-181 that contained known and previously unknown transcripts. Two previously unknown miR-132 targets identified with RISCtrap, adaptor protein CT10 regulator of kinase 1 (CRK1) and tight junction-associated protein 1 (TJAP1), were shown to be endogenously regulated by miR-132 in adult mouse forebrain. The datasets, moreover, differed in the number of targets and in the types and frequency of microRNA recognition element (MRE) motifs, thus revealing a previously underappreciated level of specificity in the target sets regulated by individual miRNAs.

Inference of miRNA targets using evolutionary conservation and pathway analysis

Directory of Open Access Journals (Sweden)

van Nimwegen Erik

2007-03-01

Full Text Available Abstract Background MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially. Results We developed a general Bayesian method for the inference of miRNA target sites, in which, for each miRNA, we explicitly model the evolution of orthologous target sites in a set of related species. Using this method we predict target sites for all known miRNAs in flies, worms, fish, and mammals. By comparing our predictions in fly with a reference set of experimentally tested miRNA-mRNA interactions we show that our general method performs at least as well as the most accurate methods available to date, including ones specifically tailored for target prediction in fly. An important novel feature of our model is that it explicitly infers the phylogenetic distribution of functional target sites, independently for each miRNA. This allows us to infer species-specific and clade-specific miRNA targeting. We also show that, in long human 3' UTRs, miRNA target sites occur preferentially near the start and near the end of the 3' UTR. To characterize miRNA function beyond the predicted lists of targets we further present a method to infer significant associations between the sets of targets predicted for individual miRNAs and specific biochemical pathways, in particular those of the KEGG pathway database. We show that this approach retrieves several known functional miRNA-mRNA associations, and predicts novel functions for known miRNAs in cell growth and in development. Conclusion We have presented a Bayesian target prediction algorithm without any tunable parameters, that can be applied to sequences from any clade of species. The algorithm automatically infers the phylogenetic distribution of functional sites for each miRNA, and

2'-O-methylation in mRNA disrupts tRNA decoding during translation elongation.

Science.gov (United States)

Choi, Junhong; Indrisiunaite, Gabriele; DeMirci, Hasan; Ieong, Ka-Weng; Wang, Jinfan; Petrov, Alexey; Prabhakar, Arjun; Rechavi, Gideon; Dominissini, Dan; He, Chuan; Ehrenberg, Måns; Puglisi, Joseph D

2018-03-01

Chemical modifications of mRNA may regulate many aspects of mRNA processing and protein synthesis. Recently, 2'-O-methylation of nucleotides was identified as a frequent modification in translated regions of human mRNA, showing enrichment in codons for certain amino acids. Here, using single-molecule, bulk kinetics and structural methods, we show that 2'-O-methylation within coding regions of mRNA disrupts key steps in codon reading during cognate tRNA selection. Our results suggest that 2'-O-methylation sterically perturbs interactions of ribosomal-monitoring bases (G530, A1492 and A1493) with cognate codon-anticodon helices, thereby inhibiting downstream GTP hydrolysis by elongation factor Tu (EF-Tu) and A-site tRNA accommodation, leading to excessive rejection of cognate aminoacylated tRNAs in initial selection and proofreading. Our current and prior findings highlight how chemical modifications of mRNA tune the dynamics of protein synthesis at different steps of translation elongation.

TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples.

Science.gov (United States)

Bandyopadhyay, Sanghamitra; Mitra, Ramkrishna

2009-10-15

Prediction of microRNA (miRNA) target mRNAs using machine learning approaches is an important area of research. However, most of the methods suffer from either high false positive or false negative rates. One reason for this is the marked deficiency of negative examples or miRNA non-target pairs. Systematic identification of non-target mRNAs is still not addressed properly, and therefore, current machine learning approaches are compelled to rely on artificially generated negative examples for training. In this article, we have identified approximately 300 tissue-specific negative examples using a novel approach that involves expression profiling of both miRNAs and mRNAs, miRNA-mRNA structural interactions and seed-site conservation. The newly generated negative examples are validated with pSILAC dataset, which elucidate the fact that the identified non-targets are indeed non-targets.These high-throughput tissue-specific negative examples and a set of experimentally verified positive examples are then used to build a system called TargetMiner, a support vector machine (SVM)-based classifier. In addition to assessing the prediction accuracy on cross-validation experiments, TargetMiner has been validated with a completely independent experimental test dataset. Our method outperforms 10 existing target prediction algorithms and provides a good balance between sensitivity and specificity that is not reflected in the existing methods. We achieve a significantly higher sensitivity and specificity of 69% and 67.8% based on a pool of 90 feature set and 76.5% and 66.1% using a set of 30 selected feature set on the completely independent test dataset. In order to establish the effectiveness of the systematically generated negative examples, the SVM is trained using a different set of negative data generated using the method in Yousef et al. A significantly higher false positive rate (70.6%) is observed when tested on the independent set, while all other factors are kept the

Analysis and prediction of translation rate based on sequence and functional features of the mRNA.

Directory of Open Access Journals (Sweden)

Tao Huang

Full Text Available Protein concentrations depend not only on the mRNA level, but also on the translation rate and the degradation rate. Prediction of mRNA's translation rate would provide valuable information for in-depth understanding of the translation mechanism and dynamic proteome. In this study, we developed a new computational model to predict the translation rate, featured by (1 integrating various sequence-derived and functional features, (2 applying the maximum relevance & minimum redundancy method and incremental feature selection to select features to optimize the prediction model, and (3 being able to predict the translation rate of RNA into high or low translation rate category. The prediction accuracies under rich and starvation condition were 68.8% and 70.0%, respectively, evaluated by jackknife cross-validation. It was found that the following features were correlated with translation rate: codon usage frequency, some gene ontology enrichment scores, number of RNA binding proteins known to bind its mRNA product, coding sequence length, protein abundance and 5'UTR free energy. These findings might provide useful information for understanding the mechanisms of translation and dynamic proteome. Our translation rate prediction model might become a high throughput tool for annotating the translation rate of mRNAs in large-scale.

Efficient computation of co-transcriptional RNA-ligand interaction dynamics.

Science.gov (United States)

Wolfinger, Michael T; Flamm, Christoph; Hofacker, Ivo L

2018-05-04

Riboswitches form an abundant class of cis-regulatory RNA elements that mediate gene expression by binding a small metabolite. For synthetic biology applications, they are becoming cheap and accessible systems for selectively triggering transcription or translation of downstream genes. Many riboswitches are kinetically controlled, hence knowledge of their co-transcriptional mechanisms is essential. We present here an efficient implementation for analyzing co-transcriptional RNA-ligand interaction dynamics. This approach allows for the first time to model concentration-dependent metabolite binding/unbinding kinetics. We exemplify this novel approach by means of the recently studied I-A 2 ' -deoxyguanosine (2 ' dG)-sensing riboswitch from Mesoplasma florum. Copyright © 2018 Elsevier Inc. All rights reserved.

Markovian negentropies in bioinformatics. 1. A picture of footprints after the interaction of the HIV-1 Psi-RNA packaging region with drugs.

Science.gov (United States)

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

Many experts worldwide have highlighted the potential of RNA molecules as drug targets for the chemotherapeutic treatment of a range of diseases. In particular, the molecular pockets of RNA in the HIV-1 packaging region have been postulated as promising sites for antiviral action. The discovery of simpler methods to accurately represent drug-RNA interactions could therefore become an interesting and rapid way to generate models that are complementary to docking-based systems. The entropies of a vibrational Markov chain have been introduced here as physically meaningful descriptors for the local drug-nucleic acid complexes. A study of the interaction of the antibiotic Paromomycin with the packaging region of the RNA present in type-1 HIV has been carried out as an illustrative example of this approach. A linear discriminant function gave rise to excellent discrimination among 80.13% of interacting/non-interacting sites. More specifically, the model classified 36/45 nucleotides (80.0%) that interacted with paromomycin and, in addition, 85/106 (80.2%) footprinted (non-interacting) sites from the RNA viral sequence were recognized. The model showed a high Matthews' regression coefficient (C = 0.64). The Jackknife method was also used to assess the stability and predictability of the model by leaving out adenines, C, G, or U. Matthews' coefficients and overall accuracies for these approaches were between 0.55 and 0.68 and 75.8 and 82.7, respectively. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the aforementioned antibiotic (R2 = 0.83,Q2 = 0.825). These kinds of models may play an important role either in the discovery of new anti-HIV compounds or in the elucidation of their mode of action. On request from the corresponding author (humbertogd@cbq.uclv.edu.cu or humbertogd@navegalia.com).

Structure of Drosophila Oskar reveals a novel RNA binding protein

Science.gov (United States)

Yang, Na; Yu, Zhenyu; Hu, Menglong; Wang, Mingzhu; Lehmann, Ruth; Xu, Rui-Ming

2015-01-01

Oskar (Osk) protein plays critical roles during Drosophila germ cell development, yet its functions in germ-line formation and body patterning remain poorly understood. This situation contrasts sharply with the vast knowledge about the function and mechanism of osk mRNA localization. Osk is predicted to have an N-terminal LOTUS domain (Osk-N), which has been suggested to bind RNA, and a C-terminal hydrolase-like domain (Osk-C) of unknown function. Here, we report the crystal structures of Osk-N and Osk-C. Osk-N shows a homodimer of winged-helix–fold modules, but without detectable RNA-binding activity. Osk-C has a lipase-fold structure but lacks critical catalytic residues at the putative active site. Surprisingly, we found that Osk-C binds the 3′UTRs of osk and nanos mRNA in vitro. Mutational studies identified a region of Osk-C important for mRNA binding. These results suggest possible functions of Osk in the regulation of stability, regulation of translation, and localization of relevant mRNAs through direct interaction with their 3′UTRs, and provide structural insights into a novel protein–RNA interaction motif involving a hydrolase-related domain. PMID:26324911

Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

Science.gov (United States)

Isik, Zerrin; Ercan, Muserref Ece

2017-10-01

Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

High throughput sequencing of small RNA component of leaves and inflorescence revealed conserved and novel miRNAs as well as phasiRNA loci in chickpea.

Science.gov (United States)

Srivastava, Sangeeta; Zheng, Yun; Kudapa, Himabindu; Jagadeeswaran, Guru; Hivrale, Vandana; Varshney, Rajeev K; Sunkar, Ramanjulu

2015-06-01

Among legumes, chickpea (Cicer arietinum L.) is the second most important crop after soybean. MicroRNAs (miRNAs) play important roles by regulating target gene expression important for plant development and tolerance to stress conditions. Additionally, recently discovered phased siRNAs (phasiRNAs), a new class of small RNAs, are abundantly produced in legumes. Nevertheless, little is known about these regulatory molecules in chickpea. The small RNA population was sequenced from leaves and flowers of chickpea to identify conserved and novel miRNAs as well as phasiRNAs/phasiRNA loci. Bioinformatics analysis revealed 157 miRNA loci for the 96 highly conserved and known miRNA homologs belonging to 38 miRNA families in chickpea. Furthermore, 20 novel miRNAs belonging to 17 miRNA families were identified. Sequence analysis revealed approximately 60 phasiRNA loci. Potential target genes likely to be regulated by these miRNAs were predicted and some were confirmed by modified 5' RACE assay. Predicted targets are mostly transcription factors that might be important for developmental processes, and others include superoxide dismutases, plantacyanin, laccases and F-box proteins that could participate in stress responses and protein degradation. Overall, this study provides an inventory of miRNA-target gene interactions for chickpea, useful for the comparative analysis of small RNAs among legumes. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Differential Expression Analysis by RNA-Seq Reveals Perturbations in the Platelet mRNA Transcriptome Triggered by Pathogen Reduction Systems.

Directory of Open Access Journals (Sweden)

Abdimajid Osman

Full Text Available Platelet concentrates (PCs are prepared at blood banks for transfusion to patients in certain clinical conditions associated with a low platelet count. To prevent transfusion-transmitted infections via PCs, different pathogen reduction (PR systems have been developed that inactivate the nucleic acids of contaminating pathogens by chemical cross-linking, a mechanism that may also affect platelets' nucleic acids. We previously reported that treatment of stored platelets with the PR system Intercept significantly reduced the level of half of the microRNAs that were monitored, induced platelet activation and compromised the platelet response to physiological agonists. Using genome-wide differential expression (DE RNA sequencing (RNA-Seq, we now report that Intercept markedly perturbs the mRNA transcriptome of human platelets and alters the expression level of >800 mRNAs (P<0.05 compared to other PR systems and control platelets. Of these, 400 genes were deregulated with DE corresponding to fold changes (FC ≥ 2. At the p-value < 0.001, as many as 147 genes were deregulated by ≥ 2-fold in Intercept-treated platelets, compared to none in the other groups. Finally, integrated analysis combining expression data for microRNA (miRNA and mRNA, and involving prediction of miRNA-mRNA interactions, disclosed several positive and inverse correlations between miRNAs and mRNAs in stored platelets. In conclusion, this study demonstrates that Intercept markedly deregulates the platelet mRNA transcriptome, concomitant with reduced levels of mRNA-regulatory miRNAs. These findings should enlighten authorities worldwide when considering the implementation of PR systems, that target nucleic acids and are not specific to pathogens, for the management of blood products.

StructRNAfinder: an automated pipeline and web server for RNA families prediction.

Science.gov (United States)

Arias-Carrasco, Raúl; Vásquez-Morán, Yessenia; Nakaya, Helder I; Maracaja-Coutinho, Vinicius

2018-02-17

The function of many noncoding RNAs (ncRNAs) depend upon their secondary structures. Over the last decades, several methodologies have been developed to predict such structures or to use them to functionally annotate RNAs into RNA families. However, to fully perform this analysis, researchers should utilize multiple tools, which require the constant parsing and processing of several intermediate files. This makes the large-scale prediction and annotation of RNAs a daunting task even to researchers with good computational or bioinformatics skills. We present an automated pipeline named StructRNAfinder that predicts and annotates RNA families in transcript or genome sequences. This single tool not only displays the sequence/structural consensus alignments for each RNA family, according to Rfam database but also provides a taxonomic overview for each assigned functional RNA. Moreover, we implemented a user-friendly web service that allows researchers to upload their own nucleotide sequences in order to perform the whole analysis. Finally, we provided a stand-alone version of StructRNAfinder to be used in large-scale projects. The tool was developed under GNU General Public License (GPLv3) and is freely available at http://structrnafinder.integrativebioinformatics.me . The main advantage of StructRNAfinder relies on the large-scale processing and integrating the data obtained by each tool and database employed along the workflow, of which several files are generated and displayed in user-friendly reports, useful for downstream analyses and data exploration.

mRNA and microRNA transcriptomics analyses in a murine model of dystrophin loss and therapeutic restoration

Directory of Open Access Journals (Sweden)

Thomas C. Roberts

2016-03-01

Full Text Available Duchenne muscular dystrophy (DMD is a pediatric, X-linked, progressive muscle-wasting disorder caused by loss of function mutations affecting the gene encoding the dystrophin protein. While the primary genetic insult in DMD is well described, many details of the molecular and cellular pathologies that follow dystrophin loss are incompletely understood. To investigate gene expression in dystrophic muscle we have applied mRNA and microRNA (miRNA microarray technology to the mdx mouse model of DMD. This study was designed to generate a complete description of gene expression changes associated with dystrophic pathology and the response to an experimental therapy which restores dystrophin protein function. These datasets have enabled (1 the determination of gene expression changes associated with dystrophic pathology, (2 identification of differentially expressed genes that are restored towards wild-type levels after therapeutic dystrophin rescue, (3 investigation of the correlation between mRNA and protein expression (determined by parallel mass spectrometry proteomics analysis, and (4 prediction of pathology associated miRNA-target interactions. Here we describe in detail how the data were generated including the basic analysis as contained in the manuscript published in Human Molecular Genetics with PMID 26385637. The data have been deposited in the Gene Expression Omnibus (GEO with the accession number GSE64420.

Interaction of packaging motor with the polymerase complex of dsRNA bacteriophage

International Nuclear Information System (INIS)

Lisal, Jiri; Kainov, Denis E.; Lam, TuKiet T.; Emmett, Mark R.; Wei Hui; Gottlieb, Paul; Marshall, Alan G.; Tuma, Roman

2006-01-01

Many viruses employ molecular motors to package their genomes into preformed empty capsids (procapsids). In dsRNA bacteriophages the packaging motor is a hexameric ATPase P4, which is an integral part of the multisubunit procapsid. Structural and biochemical studies revealed a plausible RNA-translocation mechanism for the isolated hexamer. However, little is known about the structure and regulation of the hexamer within the procapsid. Here we use hydrogen-deuterium exchange and mass spectrometry to delineate the interactions of the P4 hexamer with the bacteriophage phi12 procapsid. P4 associates with the procapsid via its C-terminal face. The interactions also stabilize subunit interfaces within the hexamer. The conformation of the virus-bound hexamer is more stable than the hexamer in solution, which is prone to spontaneous ring openings. We propose that the stabilization within the viral capsid increases the packaging processivity and confers selectivity during RNA loading

RDE-2 interacts with MUT-7 to mediate RNA interference in Caenorhabditis elegans.

Science.gov (United States)

Tops, Bastiaan B J; Tabara, Hiroaki; Sijen, Titia; Simmer, Femke; Mello, Craig C; Plasterk, Ronald H A; Ketting, René F

2005-01-01

In Caenorhabditis elegans, the activity of transposable elements is repressed in the germline. One of the mechanisms involved in this repression is RNA interference (RNAi), a process in which dsRNA targets cleavage of mRNAs in a sequence-specific manner. The first gene found to be involved in RNAi and transposon silencing in C.elegans is mut-7, a gene encoding a putative exoribonuclease. Here, we show that the MUT-7 protein resides in complexes of approximately 250 kDa in the nucleus and in the cytosol. In addition, we find that upon triggering of RNAi the cytosolic MUT-7 complex increases in size. This increase is independent of the presence of target RNA, but does depend on the presence of RDE-1 and RDE-4, two proteins involved in small interfering RNA (siRNA) production. Finally, using a yeast two-hybrid screen, we identified RDE-2/MUT-8 as one of the other components of this complex. This protein is encoded by the rde-2/mut-8 locus, previously implicated in RNAi and transposon silencing. Using genetic complementation analysis, we show that the interaction between these two proteins is required for efficient RNAi in vivo. Together these data support a role for the MUT-7/RDE-2 complex downstream of siRNA formation, but upstream of siRNA mediated target RNA recognition, possibly indicating a role in the siRNA amplification step.

Studies of interactions of porphyrins with transfer RNA by high-resolution NMR

International Nuclear Information System (INIS)

Birdsall, W.J.; Lehigh Univ., Bethlehem, PA; Anderson, W.R. Jr; Foster, N.

1989-01-01

The interactions of tetra-4N-methulpyridyl porphyrin and its zinc (II), copper (II) and manganese (III) complexes with brewer's yeast type V phenylalanine specific tRNA have been evaluated by high-resolution NMR. Differences in chemical shifts have been noted for thre proton resonances in response to the presence of small quantities of the fre base and the zinc and copper complexes. The protons giving rise to these signals are located on bases T54 and psi55, both of which are involved in the primary intraloop and interloop hydroen bonds that hold the D and TpsiC loops together in the tertiary structure. In addition, broadening of specific resonances due to hydrogen bonding protons in the D stem at low ratios of porphyrin to tRNA indicates that the association of porphyrins increases the rate of imino proton exchange. The titration of the tRNA with the manganese (III) complex did not eveal shifts or spcific broadening comparable to the other porpyrins at low ratios. The changes induced in the NMR spectrum of tNA by porphyrins define their site of interaction with the polynucleotide. This site, at the outside of the elbow-bend in the tRNA 'L', is different from the locus of binding in tRNA for other classical DNA intercalators. Furthermore, a new mode of binding may be involved that is neither intercalative nor simply electrostatic. (author). 36 refs.; 4 figs

Affinity maturation of a portable Fab–RNA module for chaperone-assisted RNA crystallography

Science.gov (United States)

Koirala, Deepak; Shelke, Sandip A; Dupont, Marcel; Ruiz, Stormy; DasGupta, Saurja; Bailey, Lucas J; Benner, Steven A; Piccirilli, Joseph A

2018-01-01

Abstract Antibody fragments such as Fabs possess properties that can enhance protein and RNA crystallization and therefore can facilitate macromolecular structure determination. In particular, Fab BL3–6 binds to an AAACA RNA pentaloop closed by a GC pair with ∼100 nM affinity. The Fab and hairpin have served as a portable module for RNA crystallization. The potential for general application make it desirable to adjust the properties of this crystallization module in a manner that facilitates its use for RNA structure determination, such as ease of purification, surface entropy or binding affinity. In this work, we used both in vitro RNA selection and phage display selection to alter the epitope and paratope sides of the binding interface, respectively, for improved binding affinity. We identified a 5′-GNGACCC-3′ consensus motif in the RNA and S97N mutation in complimentarity determining region L3 of the Fab that independently impart about an order of magnitude improvement in affinity, resulting from new hydrogen bonding interactions. Using a model RNA, these modifications facilitated crystallization under a wider range of conditions and improved diffraction. The improved features of the Fab–RNA module may facilitate its use as an affinity tag for RNA purification and imaging and as a chaperone for RNA crystallography. PMID:29309709

CPSS: a computational platform for the analysis of small RNA deep sequencing data.

Science.gov (United States)

Zhang, Yuanwei; Xu, Bo; Yang, Yifan; Ban, Rongjun; Zhang, Huan; Jiang, Xiaohua; Cooke, Howard J; Xue, Yu; Shi, Qinghua

2012-07-15

Next generation sequencing (NGS) techniques have been widely used to document the small ribonucleic acids (RNAs) implicated in a variety of biological, physiological and pathological processes. An integrated computational tool is needed for handling and analysing the enormous datasets from small RNA deep sequencing approach. Herein, we present a novel web server, CPSS (a computational platform for the analysis of small RNA deep sequencing data), designed to completely annotate and functionally analyse microRNAs (miRNAs) from NGS data on one platform with a single data submission. Small RNA NGS data can be submitted to this server with analysis results being returned in two parts: (i) annotation analysis, which provides the most comprehensive analysis for small RNA transcriptome, including length distribution and genome mapping of sequencing reads, small RNA quantification, prediction of novel miRNAs, identification of differentially expressed miRNAs, piwi-interacting RNAs and other non-coding small RNAs between paired samples and detection of miRNA editing and modifications and (ii) functional analysis, including prediction of miRNA targeted genes by multiple tools, enrichment of gene ontology terms, signalling pathway involvement and protein-protein interaction analysis for the predicted genes. CPSS, a ready-to-use web server that integrates most functions of currently available bioinformatics tools, provides all the information wanted by the majority of users from small RNA deep sequencing datasets. CPSS is implemented in PHP/PERL+MySQL+R and can be freely accessed at http://mcg.ustc.edu.cn/db/cpss/index.html or http://mcg.ustc.edu.cn/sdap1/cpss/index.html.

A Circulating microRNA Signature Predicts Age-Based Development of Lymphoma.

Directory of Open Access Journals (Sweden)

Afshin Beheshti

Full Text Available Extensive epidemiological data have demonstrated an exponential rise in the incidence of non-Hodgkin lymphoma (NHL that is associated with increasing age. The molecular etiology of this remains largely unknown, which impacts the effectiveness of treatment for patients. We proposed that age-dependent circulating microRNA (miRNA signatures in the host influence diffuse large B cell lymphoma (DLBCL development. Our objective was to examine tumor development in an age-based DLBCL system using an inventive systems biology approach. We harnessed a novel murine model of spontaneous DLBCL initiation (Smurf2-deficient at two age groups: 3 and 15 months old. All Smurf2-deficient mice develop visible DLBCL tumor starting at 15 months of age. Total miRNA was isolated from serum, bone marrow and spleen and were collected for all age groups for Smurf2-deficient mice and age-matched wild-type C57BL/6 mice. Using systems biology techniques, we identified a list of 10 circulating miRNAs being regulated in both the spleen and bone marrow that were present in DLBCL forming mice starting at 3 months of age that were not present in the control mice. Furthermore, this miRNA signature was found to occur circulating in the blood and it strongly impacted JUN and MYC oncogenic signaling. In addition, quantification of the miRNA signature was performed via Droplet Digital PCR technology. It was discovered that a key miRNA signature circulates throughout a host prior to the formation of a tumor starting at 3 months old, which becomes further modulated by age and yielded calculation of a 'carcinogenic risk score'. This novel age-based circulating miRNA signature may potentially be leveraged as a DLBCL risk profile at a young age to predict future lymphoma development or disease progression as well as for potential innovative miRNA-based targeted therapeutic strategies in lymphoma.

Steric restrictions of RISC in RNA interference identified with size-expanded RNA nucleobases.

Science.gov (United States)

Hernández, Armando R; Peterson, Larryn W; Kool, Eric T

2012-08-17

Understanding the interactions between small interfering RNAs (siRNAs) and the RNA-induced silencing complex (RISC), the key protein complex of RNA interference (RNAi), is of great importance to the development of siRNAs with improved biological and potentially therapeutic function. Although various chemically modified siRNAs have been reported, relatively few studies with modified nucleobases exist. Here we describe the synthesis and hybridization properties of siRNAs bearing size-expanded RNA (xRNA) nucleobases and their use as a novel and systematic set of steric probes in RNAi. xRNA nucleobases are expanded by 2.4 Å using benzo-homologation and retain canonical Watson-Crick base-pairing groups. Our data show that the modified siRNA duplexes display small changes in melting temperature (+1.4 to -5.0 °C); substitutions near the center are somewhat destabilizing to the RNA duplex, while substitutions near the ends are stabilizing. RNAi studies in a dual-reporter luciferase assay in HeLa cells revealed that xRNA nucleobases in the antisense strand reduce activity at some central positions near the seed region but are generally well tolerated near the ends. Most importantly, we observed that xRNA substitutions near the 3'-end increased activity over that of wild-type siRNAs. The data are analyzed in terms of site-dependent steric effects in RISC. Circular dichroism experiments show that single xRNA substitutions do not significantly distort the native A-form helical structure of the siRNA duplex, and serum stability studies demonstrated that xRNA substitutions protect siRNAs against nuclease degradation.

Structure-Function Model for Kissing Loop Interactions That Initiate Dimerization of Ty1 RNA

Directory of Open Access Journals (Sweden)

Eric R. Gamache

2017-04-01

Full Text Available The genomic RNA of the retrotransposon Ty1 is packaged as a dimer into virus-like particles. The 5′ terminus of Ty1 RNA harbors cis-acting sequences required for translation initiation, packaging and initiation of reverse transcription (TIPIRT. To identify RNA motifs involved in dimerization and packaging, a structural model of the TIPIRT domain in vitro was developed from single-nucleotide resolution RNA structural data. In general agreement with previous models, the first 326 nucleotides of Ty1 RNA form a pseudoknot with a 7-bp stem (S1, a 1-nucleotide interhelical loop and an 8-bp stem (S2 that delineate two long, structured loops. Nucleotide substitutions that disrupt either pseudoknot stem greatly reduced helper-Ty1-mediated retrotransposition of a mini-Ty1, but only mutations in S2 destabilized mini-Ty1 RNA in cis and helper-Ty1 RNA in trans. Nested in different loops of the pseudoknot are two hairpins with complementary 7-nucleotide motifs at their apices. Nucleotide substitutions in either motif also reduced retrotransposition and destabilized mini- and helper-Ty1 RNA. Compensatory mutations that restore base-pairing in the S2 stem or between the hairpins rescued retrotransposition and RNA stability in cis and trans. These data inform a model whereby a Ty1 RNA kissing complex with two intermolecular kissing-loop interactions initiates dimerization and packaging.

A mRNA and cognate microRNAs localize in the nucleolus.

Science.gov (United States)

Reyes-Gutierrez, Pablo; Ritland Politz, Joan C; Pederson, Thoru

2014-01-01

We previously discovered that a set of 5 microRNAs are concentrated in the nucleolus of rat myoblasts. We now report that several mRNAs are also localized in the nucleoli of these cells as determined by microarray analysis of RNA from purified nucleoli. Among the most abundant of these nucleolus-localized mRNAs is that encoding insulin-like growth factor 2 (IGF2), a regulator of myoblast proliferation and differentiation. The presence of IGF2 mRNA in nucleoli was confirmed by fluorescence in situ hybridization, and RT-PCR experiments demonstrated that these nucleolar transcripts are spliced, thus arriving from the nucleoplasm. Bioinformatics analysis predicted canonically structured, highly thermodynamically stable interactions between IGF2 mRNA and all 5 of the nucleolus-localized microRNAs. These results raise the possibility that the nucleolus is a staging site for setting up particular mRNA-microRNA interactions prior to export to the cytoplasm.

Roles of Non-Coding RNA in Sugarcane-Microbe Interaction

Science.gov (United States)

Grativol, Clícia; Motta, Mariana R.; Ballesteros, Helkin G. F.; Peixoto, Barbara; Vieira, Lucas M.; Walter, Maria Emilia; de Armas, Elvismary M.; Entenza, Júlio O. P.; Lifschitz, Sergio; Farinelli, Laurent; Hemerly, Adriana S.

2017-01-01

Studies have highlighted the importance of non-coding RNA regulation in plant-microbe interaction. However, the roles of sugarcane microRNAs (miRNAs) in the regulation of disease responses have not been investigated. Firstly, we screened the sRNA transcriptome of sugarcane infected with Acidovorax avenae. Conserved and novel miRNAs were identified. Additionally, small interfering RNAs (siRNAs) were aligned to differentially expressed sequences from the sugarcane transcriptome. Interestingly, many siRNAs aligned to a transcript encoding a copper-transporter gene whose expression was induced in the presence of A. avenae, while the siRNAs were repressed in the presence of A. avenae. Moreover, a long intergenic non-coding RNA was identified as a potential target or decoy of miR408. To extend the bioinformatics analysis, we carried out independent inoculations and the expression patterns of six miRNAs were validated by quantitative reverse transcription-PCR (qRT-PCR). Among these miRNAs, miR408—a copper-microRNA—was downregulated. The cleavage of a putative miR408 target, a laccase, was confirmed by a modified 5′RACE (rapid amplification of cDNA ends) assay. MiR408 was also downregulated in samples infected with other pathogens, but it was upregulated in the presence of a beneficial diazotrophic bacteria. Our results suggest that regulation by miR408 is important in sugarcane sensing whether microorganisms are either pathogenic or beneficial, triggering specific miRNA-mediated regulatory mechanisms accordingly. PMID:29657296

Roles of Non-Coding RNA in Sugarcane-Microbe Interaction

Directory of Open Access Journals (Sweden)

Flávia Thiebaut

2017-12-01

Full Text Available Studies have highlighted the importance of non-coding RNA regulation in plant-microbe interaction. However, the roles of sugarcane microRNAs (miRNAs in the regulation of disease responses have not been investigated. Firstly, we screened the sRNA transcriptome of sugarcane infected with Acidovorax avenae. Conserved and novel miRNAs were identified. Additionally, small interfering RNAs (siRNAs were aligned to differentially expressed sequences from the sugarcane transcriptome. Interestingly, many siRNAs aligned to a transcript encoding a copper-transporter gene whose expression was induced in the presence of A. avenae, while the siRNAs were repressed in the presence of A. avenae. Moreover, a long intergenic non-coding RNA was identified as a potential target or decoy of miR408. To extend the bioinformatics analysis, we carried out independent inoculations and the expression patterns of six miRNAs were validated by quantitative reverse transcription-PCR (qRT-PCR. Among these miRNAs, miR408—a copper-microRNA—was downregulated. The cleavage of a putative miR408 target, a laccase, was confirmed by a modified 5′RACE (rapid amplification of cDNA ends assay. MiR408 was also downregulated in samples infected with other pathogens, but it was upregulated in the presence of a beneficial diazotrophic bacteria. Our results suggest that regulation by miR408 is important in sugarcane sensing whether microorganisms are either pathogenic or beneficial, triggering specific miRNA-mediated regulatory mechanisms accordingly.

Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach.

Science.gov (United States)

Pan, Yuliang; Wang, Zixiang; Zhan, Weihua; Deng, Lei

2018-05-01

Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally recognized energy hot spots in protein-RNA crystal structures leads to the difficulties in developing empirical identification approaches. Computational prediction of RNA-binding hot spot residues is still in its infant stage. Here, we describe a computational method, PrabHot (Prediction of protein-RNA binding hot spots), that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers. Residue interaction network features and new solvent exposure characteristics are combined together and selected for classification with the Boruta algorithm. In particular, two new reference datasets (benchmark and independent) have been generated containing 107 hot spots from 47 known protein-RNA complex structures. In 10-fold cross-validation on the training dataset, PrabHot achieves promising performances with an AUC score of 0.86 and a sensitivity of 0.78, which are significantly better than that of the pioneer RNA-binding hot spot prediction method HotSPRing. We also demonstrate the capability of our proposed method on the independent test dataset and gain a competitive advantage as a result. The PrabHot webserver is freely available at http://denglab.org/PrabHot/. leideng@csu.edu.cn. Supplementary data are available at Bioinformatics online.

The TAL effector PthA4 interacts with nuclear factors involved in RNA-dependent processes including a HMG protein that selectively binds poly(U RNA.

Directory of Open Access Journals (Sweden)

Tiago Antonio de Souza

Full Text Available Plant pathogenic bacteria utilize an array of effector proteins to cause disease. Among them, transcriptional activator-like (TAL effectors are unusual in the sense that they modulate transcription in the host. Although target genes and DNA specificity of TAL effectors have been elucidated, how TAL proteins control host transcription is poorly understood. Previously, we showed that the Xanthomonas citri TAL effectors, PthAs 2 and 3, preferentially targeted a citrus protein complex associated with transcription control and DNA repair. To extend our knowledge on the mode of action of PthAs, we have identified new protein targets of the PthA4 variant, required to elicit canker on citrus. Here we show that all the PthA4-interacting proteins are DNA and/or RNA-binding factors implicated in chromatin remodeling and repair, gene regulation and mRNA stabilization/modification. The majority of these proteins, including a structural maintenance of chromosomes protein (CsSMC, a translin-associated factor X (CsTRAX, a VirE2-interacting protein (CsVIP2, a high mobility group (CsHMG and two poly(A-binding proteins (CsPABP1 and 2, interacted with each other, suggesting that they assemble into a multiprotein complex. CsHMG was shown to bind DNA and to interact with the invariable leucine-rich repeat region of PthAs. Surprisingly, both CsHMG and PthA4 interacted with PABP1 and 2 and showed selective binding to poly(U RNA, a property that is novel among HMGs and TAL effectors. Given that homologs of CsHMG, CsPABP1, CsPABP2, CsSMC and CsTRAX in other organisms assemble into protein complexes to regulate mRNA stability and translation, we suggest a novel role of TAL effectors in mRNA processing and translational control.

A novel knowledge-based potential for RNA 3D structure evaluation

Science.gov (United States)

Yang, Yi; Gu, Qi; Zhang, Ben-Gong; Shi, Ya-Zhou; Shao, Zhi-Gang

2018-03-01

Ribonucleic acids (RNAs) play a vital role in biology, and knowledge of their three-dimensional (3D) structure is required to understand their biological functions. Recently structural prediction methods have been developed to address this issue, but a series of RNA 3D structures are generally predicted by most existing methods. Therefore, the evaluation of the predicted structures is generally indispensable. Although several methods have been proposed to assess RNA 3D structures, the existing methods are not precise enough. In this work, a new all-atom knowledge-based potential is developed for more accurately evaluating RNA 3D structures. The potential not only includes local and nonlocal interactions but also fully considers the specificity of each RNA by introducing a retraining mechanism. Based on extensive test sets generated from independent methods, the proposed potential correctly distinguished the native state and ranked near-native conformations to effectively select the best. Furthermore, the proposed potential precisely captured RNA structural features such as base-stacking and base-pairing. Comparisons with existing potential methods show that the proposed potential is very reliable and accurate in RNA 3D structure evaluation. Project supported by the National Science Foundation of China (Grants Nos. 11605125, 11105054, 11274124, and 11401448).

Inverse folding of RNA pseudoknot structures

Directory of Open Access Journals (Sweden)

Li Linda YM

2010-06-01

Full Text Available Abstract Background RNA exhibits a variety of structural configurations. Here we consider a structure to be tantamount to the noncrossing Watson-Crick and G-U-base pairings (secondary structure and additional cross-serial base pairs. These interactions are called pseudoknots and are observed across the whole spectrum of RNA functionalities. In the context of studying natural RNA structures, searching for new ribozymes and designing artificial RNA, it is of interest to find RNA sequences folding into a specific structure and to analyze their induced neutral networks. Since the established inverse folding algorithms, RNAinverse, RNA-SSD as well as INFO-RNA are limited to RNA secondary structures, we present in this paper the inverse folding algorithm Inv which can deal with 3-noncrossing, canonical pseudoknot structures. Results In this paper we present the inverse folding algorithm Inv. We give a detailed analysis of Inv, including pseudocodes. We show that Inv allows to design in particular 3-noncrossing nonplanar RNA pseudoknot 3-noncrossing RNA structures-a class which is difficult to construct via dynamic programming routines. Inv is freely available at http://www.combinatorics.cn/cbpc/inv.html. Conclusions The algorithm Inv extends inverse folding capabilities to RNA pseudoknot structures. In comparison with RNAinverse it uses new ideas, for instance by considering sets of competing structures. As a result, Inv is not only able to find novel sequences even for RNA secondary structures, it does so in the context of competing structures that potentially exhibit cross-serial interactions.

Integrated Analysis of Long Noncoding RNA and mRNA Expression Profile in Advanced Laryngeal Squamous Cell Carcinoma.

Directory of Open Access Journals (Sweden)

Ling Feng

Full Text Available Long non-coding RNA (lncRNA plays an important role in tumorigenesis. However, the expression pattern and function of lncRNAs in laryngeal squamous cell carcinoma (LSCC are still unclear. To investigate the aberrantly expressed lncRNAs and mRNAs in advanced LSCC, we screened lncRNA and mRNA expression profiles in 9 pairs of primary Stage IVA LSCC tissues and adjacent non-neoplastic tissues by lncRNA and mRNA integrated microarrays. Gene Ontology and pathway analysis were performed to find out the significant function and pathway of the differentially expressed mRNAs, gene-gene functional interaction network and ceRNA network were constructed to select core mRNAs, and lncRNA-mRNA expression correlation network was built to identify the interactions between lncRNA and mRNA. qRT-PCR was performed to further validate the expressions of selected lncRNAs and mRNAs in advanced LSCC. We found 1459 differentially expressed lncRNAs and 2381 differentially expressed mRNAs, including 846 up-regulated lncRNAs and 613 down-regulated lncRNAs, 1542 up-regulated mRNAs and 839 down-regulated mRNAs. The mRNAs ITGB1, HIF1A, and DDIT4 were selected as core mRNAs, which are mainly involved in biological processes, such as matrix organization, cell cycle, adhesion, and metabolic pathway. LncRNA-mRNA expression correlation network showed LncRNA NR_027340, MIR31HG were positively correlated with ITGB1, HIF1A respectively. LncRNA SOX2-OT was negatively correlated with DDIT4. qRT-PCR further validated the expression of these lncRNAs and mRNAs. The work provides convincing evidence that the identified lncRNAs and mRNAs are potential biomarkers in advanced LSCC for further future studies.

Mechanism of mRNA-STAR domain interaction: Molecular dynamics simulations of Mammalian Quaking STAR protein.

Science.gov (United States)

Sharma, Monika; Anirudh, C R

2017-10-03

STAR proteins are evolutionary conserved mRNA-binding proteins that post-transcriptionally regulate gene expression at all stages of RNA metabolism. These proteins possess conserved STAR domain that recognizes identical RNA regulatory elements as YUAAY. Recently reported crystal structures show that STAR domain is composed of N-terminal QUA1, K-homology domain (KH) and C-terminal QUA2, and mRNA binding is mediated by KH-QUA2 domain. Here, we present simulation studies done to investigate binding of mRNA to STAR protein, mammalian Quaking protein (QKI). We carried out conventional MD simulations of STAR domain in presence and absence of mRNA, and studied the impact of mRNA on the stability, dynamics and underlying allosteric mechanism of STAR domain. Our unbiased simulations results show that presence of mRNA stabilizes the overall STAR domain by reducing the structural deviations, correlating the 'within-domain' motions, and maintaining the native contacts information. Absence of mRNA not only influenced the essential modes of motion of STAR domain, but also affected the connectivity of networks within STAR domain. We further explored the dissociation of mRNA from STAR domain using umbrella sampling simulations, and the results suggest that mRNA binding to STAR domain occurs in multi-step: first conformational selection of mRNA backbone conformations, followed by induced fit mechanism as nucleobases interact with STAR domain.

siRNA and innate immunity.

Science.gov (United States)

Robbins, Marjorie; Judge, Adam; MacLachlan, Ian

2009-06-01

Canonical small interfering RNA (siRNA) duplexes are potent activators of the mammalian innate immune system. The induction of innate immunity by siRNA is dependent on siRNA structure and sequence, method of delivery, and cell type. Synthetic siRNA in delivery vehicles that facilitate cellular uptake can induce high levels of inflammatory cytokines and interferons after systemic administration in mammals and in primary human blood cell cultures. This activation is predominantly mediated by immune cells, normally via a Toll-like receptor (TLR) pathway. The siRNA sequence dependency of these pathways varies with the type and location of the TLR involved. Alternatively nonimmune cell activation may also occur, typically resulting from siRNA interaction with cytoplasmic RNA sensors such as RIG1. As immune activation by siRNA-based drugs represents an undesirable side effect due to the considerable toxicities associated with excessive cytokine release in humans, understanding and abrogating this activity will be a critical component in the development of safe and effective therapeutics. This review describes the intracellular mechanisms of innate immune activation by siRNA, the design of appropriate sequences and chemical modification approaches, and suitable experimental methods for studying their effects, with a view toward reducing siRNA-mediated off-target effects.

Covariant Evolutionary Event Analysis for Base Interaction Prediction Using a Relational Database Management System for RNA.

Science.gov (United States)

Xu, Weijia; Ozer, Stuart; Gutell, Robin R

2009-01-01

With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.

RNA interactions in the 5' region of the HIV-1 genome

DEFF Research Database (Denmark)

Damgaard, Christian Kroun; Andersen, Ebbe Sloth; Knudsen, Bjarne

2004-01-01

The untranslated leader of the dimeric HIV-1 RNA genome is folded into a complex structure that plays multiple and essential roles in the viral replication cycle. Here, we have investigated secondary and tertiary structural elements within the 5' 744 nucleotides of the HIV-1 genome using...... a combination of bioinformatics, enzymatic probing, native gel electrophoresis, and UV-crosslinking experiments. We used a recently developed RNA folding algorithm (Pfold) to predict the common secondary structure of an alignment of 20 divergent HIV-1 sequences. Combining this analysis with biochemical data, we...

Hybridization-based reconstruction of small non-coding RNA transcripts from deep sequencing data.

Science.gov (United States)

Ragan, Chikako; Mowry, Bryan J; Bauer, Denis C

2012-09-01

Recent advances in RNA sequencing technology (RNA-Seq) enables comprehensive profiling of RNAs by producing millions of short sequence reads from size-fractionated RNA libraries. Although conventional tools for detecting and distinguishing non-coding RNAs (ncRNAs) from reference-genome data can be applied to sequence data, ncRNA detection can be improved by harnessing the full information content provided by this new technology. Here we present NorahDesk, the first unbiased and universally applicable method for small ncRNAs detection from RNA-Seq data. NorahDesk utilizes the coverage-distribution of small RNA sequence data as well as thermodynamic assessments of secondary structure to reliably predict and annotate ncRNA classes. Using publicly available mouse sequence data from brain, skeletal muscle, testis and ovary, we evaluated our method with an emphasis on the performance for microRNAs (miRNAs) and piwi-interacting small RNA (piRNA). We compared our method with Dario and mirDeep2 and found that NorahDesk produces longer transcripts with higher read coverage. This feature makes it the first method particularly suitable for the prediction of both known and novel piRNAs.

Identification of high-confidence RNA regulatory elements by combinatorial classification of RNA-protein binding sites.

Science.gov (United States)

Li, Yang Eric; Xiao, Mu; Shi, Binbin; Yang, Yu-Cheng T; Wang, Dong; Wang, Fei; Marcia, Marco; Lu, Zhi John

2017-09-08

Crosslinking immunoprecipitation sequencing (CLIP-seq) technologies have enabled researchers to characterize transcriptome-wide binding sites of RNA-binding protein (RBP) with high resolution. We apply a soft-clustering method, RBPgroup, to various CLIP-seq datasets to group together RBPs that specifically bind the same RNA sites. Such combinatorial clustering of RBPs helps interpret CLIP-seq data and suggests functional RNA regulatory elements. Furthermore, we validate two RBP-RBP interactions in cell lines. Our approach links proteins and RNA motifs known to possess similar biochemical and cellular properties and can, when used in conjunction with additional experimental data, identify high-confidence RBP groups and their associated RNA regulatory elements.

MicroRNA classifier and nomogram for metastasis prediction in colon cancer.

Science.gov (United States)

Goossens-Beumer, Inès J; Derr, Remco S; Buermans, Henk P J; Goeman, Jelle J; Böhringer, Stefan; Morreau, Hans; Nitsche, Ulrich; Janssen, Klaus-Peter; van de Velde, Cornelis J H; Kuppen, Peter J K

2015-01-01

Colon cancer prognosis and treatment are currently based on a classification system still showing large heterogeneity in clinical outcome, especially in TNM stages II and III. Prognostic biomarkers for metastasis risk are warranted as development of distant recurrent disease mainly accounts for the high lethality rates of colon cancer. miRNAs have been proposed as potential biomarkers for cancer. Furthermore, a verified standard for normalization of the amount of input material in PCR-based relative quantification of miRNA expression is lacking. A selection of frozen tumor specimens from two independent patient cohorts with TNM stage II-III microsatellite stable primary adenocarcinomas was used for laser capture microdissection. Next-generation sequencing was performed on small RNAs isolated from colorectal tumors from the Dutch cohort (N = 50). Differential expression analysis, comparing in metastasized and nonmetastasized tumors, identified prognostic miRNAs. Validation was performed on colon tumors from the German cohort (N = 43) using quantitative PCR (qPCR). miR25-3p and miR339-5p were identified and validated as independent prognostic markers and used to construct a multivariate nomogram for metastasis risk prediction. The nomogram showed good probability prediction in validation. In addition, we recommend combination of miR16-5p and miR26a-5p as standard for normalization in qPCR of colon cancer tissue-derived miRNA expression. In this international study, we identified and validated a miRNA classifier in primary cancers, and propose a nomogram capable of predicting metastasis risk in microsatellite stable TNM stage II-III colon cancer. In conjunction with TNM staging, by means of a nomogram, this miRNA classifier may allow for personalized treatment decisions based on individual tumor characteristics. ©2014 American Association for Cancer Research.

Assessing Specific Oligonucleotides and Small Molecule Antibiotics for the Ability to Inhibit the CRD-BP-CD44 RNA Interaction

Science.gov (United States)

Thomsen, Dana; Lee, Chow H.

2014-01-01

Studies on Coding Region Determinant-Binding Protein (CRD-BP) and its orthologs have confirmed their functional role in mRNA stability and localization. CRD-BP is present in extremely low levels in normal adult tissues, but it is over-expressed in many types of aggressive human cancers and in neonatal tissues. Although the exact role of CRD-BP in tumour progression is unclear, cumulative evidence suggests that its ability to physically associate with target mRNAs is an important criterion for its oncogenic role. CRD-BP has high affinity for the 3′UTR of the oncogenic CD44 mRNA and depletion of CRD-BP in cells led to destabilization of CD44 mRNA, decreased CD44 expression, reduced adhesion and disruption of invadopodia formation. Here, we further characterize the CRD-BP-CD44 RNA interaction and assess specific antisense oligonucleotides and small molecule antibiotics for their ability to inhibit the CRD-BP-CD44 RNA interaction. CRD-BP has a high affinity for binding to CD44 RNA nts 2862–3055 with a Kd of 645 nM. Out of ten antisense oligonucleotides spanning nts 2862–3055, only three antisense oligonucleotides (DD4, DD7 and DD10) were effective in competing with CRD-BP for binding to 32P-labeled CD44 RNA. The potency of DD4, DD7 and DD10 in inhibiting the CRD-BP-CD44 RNA interaction in vitro correlated with their ability to specifically reduce the steady-state level of CD44 mRNA in cells. The aminoglycoside antibiotics neomycin, paramomycin, kanamycin and streptomycin effectively inhibited the CRD-BP-CD44 RNA interaction in vitro. Assessing the potential inhibitory effect of aminoglycoside antibiotics including neomycin on the CRD-BP-CD44 mRNA interaction in cells proved difficult, likely due to their propensity to non-specifically bind nucleic acids. Our results have important implications for future studies in finding small molecules and nucleic acid-based inhibitors that interfere with protein-RNA interactions. PMID:24622399

HIV-1 nef suppression by virally encoded microRNA

Directory of Open Access Journals (Sweden)

Brisibe Ebiamadon

2004-12-01

Full Text Available Abstract Background MicroRNAs (miRNAs are 21~25-nucleotides (nt long and interact with mRNAs to trigger either translational repression or RNA cleavage through RNA interference (RNAi, depending on the degree of complementarity with the target mRNAs. Our recent study has shown that HIV-1 nef dsRNA from AIDS patients who are long-term non-progressors (LTNPs inhibited the transcription of HIV-1. Results Here, we show the possibility that nef-derived miRNAs are produced in HIV-1 persistently infected cells. Furthermore, nef short hairpin RNA (shRNA that corresponded to a predicted nef miRNA (~25 nt, miR-N367 can block HIV-1 Nef expression in vitro and the suppression by shRNA/miR-N367 would be related with low viremia in an LTNP (15-2-2. In the 15-2-2 model mice, the weight loss, which may be rendered by nef was also inhibited by shRNA/miR-N367 corresponding to suppression of nef expression in vivo. Conclusions These data suggest that nef/U3 miRNAs produced in HIV-1-infected cells may suppress both Nef function and HIV-1 virulence through the RNAi pathway.

RNA2DMut: a web tool for the design and analysis of RNA structure mutations.

Science.gov (United States)

Moss, Walter N

2018-03-01

With the widespread application of high-throughput sequencing, novel RNA sequences are being discovered at an astonishing rate. The analysis of function, however, lags behind. In both the cis - and trans -regulatory functions of RNA, secondary structure (2D base-pairing) plays essential regulatory roles. In order to test RNA function, it is essential to be able to design and analyze mutations that can affect structure. This was the motivation for the creation of the RNA2DMut web tool. With RNA2DMut, users can enter in RNA sequences to analyze, constrain mutations to specific residues, or limit changes to purines/pyrimidines. The sequence is analyzed at each base to determine the effect of every possible point mutation on 2D structure. The metrics used in RNA2DMut rely on the calculation of the Boltzmann structure ensemble and do not require a robust 2D model of RNA structure for designing mutations. This tool can facilitate a wide array of uses involving RNA: for example, in designing and evaluating mutants for biological assays, interrogating RNA-protein interactions, identifying key regions to alter in SELEX experiments, and improving RNA folding and crystallization properties for structural biology. Additional tools are available to help users introduce other mutations (e.g., indels and substitutions) and evaluate their effects on RNA structure. Example calculations are shown for five RNAs that require 2D structure for their function: the MALAT1 mascRNA, an influenza virus splicing regulatory motif, the EBER2 viral noncoding RNA, the Xist lncRNA repA region, and human Y RNA 5. RNA2DMut can be accessed at https://rna2dmut.bb.iastate.edu/. © 2018 Moss; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Deciphering the details of RNA aminoglycoside interactions: from atomistic models to biotechnological applications

Energy Technology Data Exchange (ETDEWEB)

Ilgu, Muslum [Iowa State Univ., Ames, IA (United States)

2012-01-01

A detailed study was done of the neomycin-B RNA aptamer for determining its selectivity and binding ability to both neomycin– and kanamycin-class aminoglycosides. A novel method to increase drug concentrations in cells for more efficiently killing is described. To test the method, a bacterial model system was adopted and several small RNA molecules interacting with aminoglycosides were cloned downstream of T7 RNA polymerase promoter in an expression vector. Then, the growth analysis of E. coli expressing aptamers was observed for 12-hour period. Our analysis indicated that aptamers helped to increase the intracellular concentration of aminoglycosides thereby increasing their efficacy.

Deciphering RNA-Recognition Patterns of Intrinsically Disordered Proteins

Directory of Open Access Journals (Sweden)

Ambuj Srivastava

2018-05-01

Full Text Available Intrinsically disordered regions (IDRs and protein (IDPs are highly flexible owing to their lack of well-defined structures. A subset of such proteins interacts with various substrates; including RNA; frequently adopting regular structures in the final complex. In this work; we have analysed a dataset of protein–RNA complexes undergoing disorder-to-order transition (DOT upon binding. We found that DOT regions are generally small in size (less than 3 residues for RNA binding proteins. Like structured proteins; positively charged residues are found to interact with RNA molecules; indicating the dominance of electrostatic and cation-π interactions. However, a comparison of binding frequency shows that interface hydrophobic and aromatic residues have more interactions in only DOT regions than in a protein. Further; DOT regions have significantly higher exposure to water than their structured counterparts. Interactions of DOT regions with RNA increase the sheet formation with minor changes in helix forming residues. We have computed the interaction energy for amino acids–nucleotide pairs; which showed the preference of His–G; Asn–U and Ser–U at for the interface of DOT regions. This study provides insights to understand protein–RNA interactions and the results could also be used for developing a tool for identifying DOT regions in RNA binding proteins.

MiRNA expression patterns predict survival in glioblastoma

International Nuclear Information System (INIS)

Niyazi, Maximilian; Belka, Claus; Zehentmayr, Franz; Niemöller, Olivier M; Eigenbrod, Sabina; Kretzschmar, Hans; Osthoff, Klaus-Schulze; Tonn, Jörg-Christian; Atkinson, Mike; Mörtl, Simone

2011-01-01

In order to define new prognostic subgroups in patients with glioblastoma a miRNA screen (> 1000 miRNAs) from paraffin tissues followed by a bio-mathematical analysis was performed. 35 glioblastoma patients treated between 7/2005 - 8/2008 at a single institution with surgery and postoperative radio(chemo)therapy were included in this retrospective analysis. For microarray analysis the febit biochip 'Geniom ® Biochip MPEA homo-sapiens' was used. Total RNA was isolated from FFPE tissue sections and 1100 different miRNAs were analyzed. It was possible to define a distinct miRNA expression pattern allowing for a separation of distinct prognostic subgroups. The defined miRNA pattern was significantly associated with early death versus long-term survival (split at 450 days) (p = 0.01). The pattern and the prognostic power were both independent of the MGMT status. At present, this is the first dataset defining a prognostic role of miRNA expression patterns in patients with glioblastoma. Having defined such a pattern, a prospective validation of this observation is required

Different modes of interaction by TIAR and HuR with target RNA and DNA.

Science.gov (United States)

Kim, Henry S; Wilce, Matthew C J; Yoga, Yano M K; Pendini, Nicole R; Gunzburg, Menachem J; Cowieson, Nathan P; Wilson, Gerald M; Williams, Bryan R G; Gorospe, Myriam; Wilce, Jacqueline A

2011-02-01

TIAR and HuR are mRNA-binding proteins that play important roles in the regulation of translation. They both possess three RNA recognition motifs (RRMs) and bind to AU-rich elements (AREs), with seemingly overlapping specificity. Here we show using SPR that TIAR and HuR bind to both U-rich and AU-rich RNA in the nanomolar range, with higher overall affinity for U-rich RNA. However, the higher affinity for U-rich sequences is mainly due to faster association with U-rich RNA, which we propose is a reflection of the higher probability of association. Differences between TIAR and HuR are observed in their modes of binding to RNA. TIAR is able to bind deoxy-oligonucleotides with nanomolar affinity, whereas HuR affinity is reduced to a micromolar level. Studies with U-rich DNA reveal that TIAR binding depends less on the 2'-hydroxyl group of RNA than HuR binding. Finally we show that SAXS data, recorded for the first two domains of TIAR in complex with RNA, are more consistent with a flexible, elongated shape and not the compact shape that the first two domains of Hu proteins adopt upon binding to RNA. We thus propose that these triple-RRM proteins, which compete for the same binding sites in cells, interact with their targets in fundamentally different ways.

Shielding the messenger (RNA): microRNA-based anticancer therapies

Science.gov (United States)

Sotillo, Elena; Thomas-Tikhonenko, Andrei

2011-01-01

It has been a decade since scientists realized that microRNAs (miRNAs) are not an oddity invented by worms to regulate gene expression at post-transcriptional levels. Rather, many of these 21–22-nucleotide-short RNAs exist in invertebrates and vertebrates alike and some of them are in fact highly conserved. miRNAs are now recognized as an important class of non-coding small RNAs that inhibit gene expression by targeting mRNA stability and translation. In the last ten years, our knowledge of the miRNAs world was expanding at vertiginous speed, propelled by the development of computational engines for miRNA identification and target prediction, biochemical tools and techniques to modulate miRNA activity, and last but not least, the emergence of miRNA-centric animal models. One important conclusion that has emerged from this effort is that many microRNAs and their cognate targets are strongly implicated in cancer, either as oncogenes or tumor and metastasis suppressors. In this review we will discuss the diverse role that miRNAs play in cancer initiation and progression and also the tools with which miRNA expression could be corrected in vivo. While the idea of targeting microRNAs towards therapeutic ends is getting considerable traction, basic, translational, and clinical research done in the next few years will tell whether this promise is well-founded. PMID:21514318

SmD1 Modulates the miRNA Pathway Independently of Its Pre-mRNA Splicing Function.

Directory of Open Access Journals (Sweden)

Xiao-Peng Xiong

2015-08-01

Full Text Available microRNAs (miRNAs are a class of endogenous regulatory RNAs that play a key role in myriad biological processes. Upon transcription, primary miRNA transcripts are sequentially processed by Drosha and Dicer ribonucleases into ~22-24 nt miRNAs. Subsequently, miRNAs are incorporated into the RNA-induced silencing complexes (RISCs that contain Argonaute (AGO family proteins and guide RISC to target RNAs via complementary base pairing, leading to post-transcriptional gene silencing by a combination of translation inhibition and mRNA destabilization. Select pre-mRNA splicing factors have been implicated in small RNA-mediated gene silencing pathways in fission yeast, worms, flies and mammals, but the underlying molecular mechanisms are not well understood. Here, we show that SmD1, a core component of the Drosophila small nuclear ribonucleoprotein particle (snRNP implicated in splicing, is required for miRNA biogenesis and function. SmD1 interacts with both the microprocessor component Pasha and pri-miRNAs, and is indispensable for optimal miRNA biogenesis. Depletion of SmD1 impairs the assembly and function of the miRISC without significantly affecting the expression of major canonical miRNA pathway components. Moreover, SmD1 physically and functionally associates with components of the miRISC, including AGO1 and GW182. Notably, miRNA defects resulting from SmD1 silencing can be uncoupled from defects in pre-mRNA splicing, and the miRNA and splicing machineries are physically and functionally distinct entities. Finally, photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation (PAR-CLIP analysis identifies numerous SmD1-binding events across the transcriptome and reveals direct SmD1-miRNA interactions. Our study suggests that SmD1 plays a direct role in miRNA-mediated gene silencing independently of its pre-mRNA splicing activity and indicates that the dual roles of splicing factors in post-transcriptional gene regulation may be

Direct, rapid RNA sequence analysis

International Nuclear Information System (INIS)

Peattie, D.A.

1987-01-01

The original methods of RNA sequence analysis were based on enzymatic production and chromatographic separation of overlapping oligonucleotide fragments from within an RNA molecule followed by identification of the mononucleotides comprising the oligomer. Over the past decade the field of nucleic acid sequencing has changed dramatically, however, and RNA molecules now can be sequenced in a variety of more streamlined fashions. Most of the more recent advances in RNA sequencing have involved one-dimensional electrophoretic separation of 32 P-end-labeled oligoribonucleotides on polyacrylamide gels. In this chapter the author discusses two of these methods for determining the nucleotide sequences of RNA molecules rapidly: the chemical method and the enzymatic method. Both methods are direct and degradative, i.e., they rely on fragmatic and chemical approaches should be utilized. The single-strand-specific ribonucleases (A, T 1 , T 2 , and S 1 ) provide an efficient means to locate double-helical regions rapidly, and the chemical reactions provide a means to determine the RNA sequence within these regions. In addition, the chemical reactions allow one to assign interactions to specific atoms and to distinguish secondary interactions from tertiary ones. If the RNA molecule is small enough to be sequenced directly by the enzymatic or chemical method, the probing reactions can be done easily at the same time as sequencing reactions

The Ebola Virus VP30-NP Interaction Is a Regulator of Viral RNA Synthesis

Energy Technology Data Exchange (ETDEWEB)

Kirchdoerfer, Robert N.; Moyer, Crystal L.; Abelson, Dafna M.; Saphire, Erica Ollmann (Scripps)

2016-10-18

Filoviruses are capable of causing deadly hemorrhagic fevers. All nonsegmented negative-sense RNA-virus nucleocapsids are composed of a nucleoprotein (NP), a phosphoprotein (VP35) and a polymerase (L). However, the VP30 RNA-synthesis co-factor is unique to the filoviruses. The assembly, structure, and function of the filovirus RNA replication complex remain unclear. Here, we have characterized the interactions of Ebola, Sudan and Marburg virus VP30 with NP using in vitro biochemistry, structural biology and cell-based mini-replicon assays. We have found that the VP30 C-terminal domain interacts with a short peptide in the C-terminal region of NP. Further, we have solved crystal structures of the VP30-NP complex for both Ebola and Marburg viruses. These structures reveal that a conserved, proline-rich NP peptide binds a shallow hydrophobic cleft on the VP30 C-terminal domain. Structure-guided Ebola virus VP30 mutants have altered affinities for the NP peptide. Correlation of these VP30-NP affinities with the activity for each of these mutants in a cell-based mini-replicon assay suggests that the VP30-NP interaction plays both essential and inhibitory roles in Ebola virus RNA synthesis.

RStrucFam: a web server to associate structure and cognate RNA for RNA-binding proteins from sequence information.

Science.gov (United States)

Ghosh, Pritha; Mathew, Oommen K; Sowdhamini, Ramanathan

2016-10-07

RNA-binding proteins (RBPs) interact with their cognate RNA(s) to form large biomolecular assemblies. They are versatile in their functionality and are involved in a myriad of processes inside the cell. RBPs with similar structural features and common biological functions are grouped together into families and superfamilies. It will be useful to obtain an early understanding and association of RNA-binding property of sequences of gene products. Here, we report a web server, RStrucFam, to predict the structure, type of cognate RNA(s) and function(s) of proteins, where possible, from mere sequence information. The web server employs Hidden Markov Model scan (hmmscan) to enable association to a back-end database of structural and sequence families. The database (HMMRBP) comprises of 437 HMMs of RBP families of known structure that have been generated using structure-based sequence alignments and 746 sequence-centric RBP family HMMs. The input protein sequence is associated with structural or sequence domain families, if structure or sequence signatures exist. In case of association of the protein with a family of known structures, output features like, multiple structure-based sequence alignment (MSSA) of the query with all others members of that family is provided. Further, cognate RNA partner(s) for that protein, Gene Ontology (GO) annotations, if any and a homology model of the protein can be obtained. The users can also browse through the database for details pertaining to each family, protein or RNA and their related information based on keyword search or RNA motif search. RStrucFam is a web server that exploits structurally conserved features of RBPs, derived from known family members and imprinted in mathematical profiles, to predict putative RBPs from sequence information. Proteins that fail to associate with such structure-centric families are further queried against the sequence-centric RBP family HMMs in the HMMRBP database. Further, all other essential

A probabilistic model of RNA conformational space

DEFF Research Database (Denmark)

Frellsen, Jes; Moltke, Ida; Thiim, Martin

2009-01-01

, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows...... conformations for 9 out of 10 test structures, solely using coarse-grained base-pairing information. In conclusion, the method provides a theoretical and practical solution for a major bottleneck on the way to routine prediction and simulation of RNA structure and dynamics in atomic detail.......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...

RNAspa: a shortest path approach for comparative prediction of the secondary structure of ncRNA molecules

Directory of Open Access Journals (Sweden)

Michaeli Shulamit

2007-10-01

Full Text Available Abstract Background In recent years, RNA molecules that are not translated into proteins (ncRNAs have drawn a great deal of attention, as they were shown to be involved in many cellular functions. One of the most important computational problems regarding ncRNA is to predict the secondary structure of a molecule from its sequence. In particular, we attempted to predict the secondary structure for a set of unaligned ncRNA molecules that are taken from the same family, and thus presumably have a similar structure. Results We developed the RNAspa program, which comparatively predicts the secondary structure for a set of ncRNA molecules in linear time in the number of molecules. We observed that in a list of several hundred suboptimal minimal free energy (MFE predictions, as provided by the RNAsubopt program of the Vienna package, it is likely that at least one suggested structure would be similar to the true, correct one. The suboptimal solutions of each molecule are represented as a layer of vertices in a graph. The shortest path in this graph is the basis for structural predictions for the molecule. We also show that RNA secondary structures can be compared very rapidly by a simple string Edit-Distance algorithm with a minimal loss of accuracy. We show that this approach allows us to more deeply explore the suboptimal structure space. Conclusion The algorithm was tested on three datasets which include several ncRNA families taken from the Rfam database. These datasets allowed for comparison of the algorithm with other methods. In these tests, RNAspa performed better than four other programs.

High Class-Imbalance in pre-miRNA Prediction: A Novel Approach Based on deepSOM.

Science.gov (United States)

Stegmayer, Georgina; Yones, Cristian; Kamenetzky, Laura; Milone, Diego H

2017-01-01

The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high class-imbalance classification problem. The classical way of approaching it has been training a binary classifier in a supervised manner, using well-known pre-miRNAs as positive class and artificially defining the negative class. However, although the selection of positive labeled examples is straightforward, it is very difficult to build a set of negative examples in order to obtain a good set of training samples for a supervised method. In this work, we propose a novel and effective way of approaching this problem using machine learning, without the definition of negative examples. The proposal is based on clustering unlabeled sequences of a genome together with well-known miRNA precursors for the organism under study, which allows for the quick identification of the best candidates to miRNA as those sequences clustered with known precursors. Furthermore, we propose a deep model to overcome the problem of having very few positive class labels. They are always maintained in the deep levels as positive class while less likely pre-miRNA sequences are filtered level after level. Our approach has been compared with other methods for pre-miRNAs prediction in several species, showing effective predictivity of novel miRNAs. Additionally, we will show that our approach has a lower training time and allows for a better graphical navegability and interpretation of the results. A web-demo interface to try deepSOM is available at http://fich.unl.edu.ar/sinc/web-demo/deepsom/.

The 25 kDa subunit of cleavage factor Im Is a RNA-binding protein that interacts with the poly(A polymerase in Entamoeba histolytica.

Directory of Open Access Journals (Sweden)

Marisol Pezet-Valdez

Full Text Available In eukaryotes, polyadenylation of pre-mRNA 3' end is essential for mRNA export, stability and translation. Taking advantage of the knowledge of genomic sequences of Entamoeba histolytica, the protozoan responsible for human amoebiasis, we previously reported the putative polyadenylation machinery of this parasite. Here, we focused on the predicted protein that has the molecular features of the 25 kDa subunit of the Cleavage Factor Im (CFIm25 from other organisms, including the Nudix (nucleoside diphosphate linked to another moiety X domain, as well as the RNA binding domain and the PAP/PAB interacting region. The recombinant EhCFIm25 protein (rEhCFIm25 was expressed in bacteria and used to generate specific antibodies in rabbit. Subcellular localization assays showed the presence of the endogenous protein in nuclear and cytoplasmic fractions. In RNA electrophoretic mobility shift assays, rEhCFIm25 was able to form specific RNA-protein complexes with the EhPgp5 mRNA 3´ UTR used as probe. In addition, Pull-Down and LC/ESI-MS/MS tandem mass spectrometry assays evidenced that the putative EhCFIm25 was able to interact with the poly(A polymerase (EhPAP that is responsible for the synthesis of the poly(A tail in other eukaryotic cells. By Far-Western experiments, we confirmed the interaction between the putative EhCFIm25 and EhPAP in E. histolytica. Taken altogether, our results showed that the putative EhCFIm25 is a conserved RNA binding protein that interacts with the poly(A polymerase, another member of the pre-mRNA 3' end processing machinery in this protozoan parasite.

C to U RNA editing mediated by APOBEC1 requires RNA-binding protein RBM47.

Science.gov (United States)

Fossat, Nicolas; Tourle, Karin; Radziewic, Tania; Barratt, Kristen; Liebhold, Doreen; Studdert, Joshua B; Power, Melinda; Jones, Vanessa; Loebel, David A F; Tam, Patrick P L

2014-08-01

Cytidine (C) to Uridine (U) RNA editing is a post-transcriptional modification that is accomplished by the deaminase APOBEC1 and its partnership with the RNA-binding protein A1CF. We identify and characterise here a novel RNA-binding protein, RBM47, that interacts with APOBEC1 and A1CF and is expressed in tissues where C to U RNA editing occurs. RBM47 can substitute for A1CF and is necessary and sufficient for APOBEC1-mediated editing in vitro. Editing is further impaired in Rbm47-deficient mutant mice. These findings suggest that RBM47 and APOBEC1 constitute the basic machinery for C to U RNA editing. © 2014 The Authors.

Comparison of protocols and RNA carriers for plasma miRNA isolation. Unraveling RNA carrier influence on miRNA isolation

Science.gov (United States)

Martos, Laura; Fernández-Pardo, Álvaro; Oto, Julia; Medina, Pilar; España, Francisco; Navarro, Silvia

2017-01-01

microRNAs are promising biomarkers in biological fluids in several diseases. Different plasma RNA isolation protocols and carriers are available, but their efficiencies have been scarcely compared. Plasma microRNAs were isolated using a phenol and column-based procedure and a column-based procedure, in the presence or absence of two RNA carriers (yeast RNA and MS2 RNA). We evaluated the presence of PCR inhibitors and the relative abundance of certain microRNAs by qRT-PCR. Furthermore, we analyzed the association between different isolation protocols, the relative abundance of the miRNAs in the sample, the GC content and the free energy of microRNAs. In all microRNAs analyzed, the addition of yeast RNA as a carrier in the different isolation protocols used gave lower raw Cq values, indicating higher microRNA recovery. Moreover, this increase in microRNAs recovery was dependent on their own relative abundance in the sample, their GC content and the free-energy of their own most stable secondary structure. Furthermore, the normalization of microRNA levels by an endogenous microRNA is more reliable than the normalization by plasma volume, as it reduced the difference in microRNA fold abundance between the different isolation protocols evaluated. Our thorough study indicates that a standardization of pre- and analytical conditions is necessary to obtain reproducible inter-laboratory results in plasma microRNA studies. PMID:29077772

Identification of miRNA-mRNA regulatory modules by exploring collective group relationships.

Science.gov (United States)

Masud Karim, S M; Liu, Lin; Le, Thuc Duy; Li, Jiuyong

2016-01-11

microRNAs (miRNAs) play an essential role in the post-transcriptional gene regulation in plants and animals. They regulate a wide range of biological processes by targeting messenger RNAs (mRNAs). Evidence suggests that miRNAs and mRNAs interact collectively in gene regulatory networks. The collective relationships between groups of miRNAs and groups of mRNAs may be more readily interpreted than those between individual miRNAs and mRNAs, and thus are useful for gaining insight into gene regulation and cell functions. Several computational approaches have been developed to discover miRNA-mRNA regulatory modules (MMRMs) with a common aim to elucidate miRNA-mRNA regulatory relationships. However, most existing methods do not consider the collective relationships between a group of miRNAs and the group of targeted mRNAs in the process of discovering MMRMs. Our aim is to develop a framework to discover MMRMs and reveal miRNA-mRNA regulatory relationships from the heterogeneous expression data based on the collective relationships. We propose DIscovering COllective group RElationships (DICORE), an effective computational framework for revealing miRNA-mRNA regulatory relationships. We utilize the notation of collective group relationships to build the computational framework. The method computes the collaboration scores of the miRNAs and mRNAs on the basis of their interactions with mRNAs and miRNAs, respectively. Then it determines the groups of miRNAs and groups of mRNAs separately based on their respective collaboration scores. Next, it calculates the strength of the collective relationship between each pair of miRNA group and mRNA group using canonical correlation analysis, and the group pairs with significant canonical correlations are considered as the MMRMs. We applied this method to three gene expression datasets, and validated the computational discoveries. Analysis of the results demonstrates that a large portion of the regulatory relationships discovered by

A probabilistic model of RNA conformational space

DEFF Research Database (Denmark)

Frellsen, Jes; Moltke, Ida; Thiim, Martin

2009-01-01

efficient sampling of RNA conformations in continuous space, and with associated probabilities. We show that the model captures several key features of RNA structure, such as its rotameric nature and the distribution of the helix lengths. Furthermore, the model readily generates native-like 3-D......, the discrete nature of the fragments necessitates the use of carefully tuned, unphysical energy functions, and their non-probabilistic nature impairs unbiased sampling. We offer a solution to the sampling problem that removes these important limitations: a probabilistic model of RNA structure that allows......The increasing importance of non-coding RNA in biology and medicine has led to a growing interest in the problem of RNA 3-D structure prediction. As is the case for proteins, RNA 3-D structure prediction methods require two key ingredients: an accurate energy function and a conformational sampling...

SRD: a Staphylococcus regulatory RNA database.

Science.gov (United States)

Sassi, Mohamed; Augagneur, Yoann; Mauro, Tony; Ivain, Lorraine; Chabelskaya, Svetlana; Hallier, Marc; Sallou, Olivier; Felden, Brice

2015-05-01

An overflow of regulatory RNAs (sRNAs) was identified in a wide range of bacteria. We designed and implemented a new resource for the hundreds of sRNAs identified in Staphylococci, with primary focus on the human pathogen Staphylococcus aureus. The "Staphylococcal Regulatory RNA Database" (SRD, http://srd.genouest.org/) compiled all published data in a single interface including genetic locations, sequences and other features. SRD proposes novel and simplified identifiers for Staphylococcal regulatory RNAs (srn) based on the sRNA's genetic location in S. aureus strain N315 which served as a reference. From a set of 894 sequences and after an in-depth cleaning, SRD provides a list of 575 srn exempt of redundant sequences. For each sRNA, their experimental support(s) is provided, allowing the user to individually assess their validity and significance. RNA-seq analysis performed on strains N315, NCTC8325, and Newman allowed us to provide further details, upgrade the initial annotation, and identified 159 RNA-seq independent transcribed sRNAs. The lists of 575 and 159 sRNAs sequences were used to predict the number and location of srns in 18 S. aureus strains and 10 other Staphylococci. A comparison of the srn contents within 32 Staphylococcal genomes revealed a poor conservation between species. In addition, sRNA structure predictions obtained with MFold are accessible. A BLAST server and the intaRNA program, which is dedicated to target prediction, were implemented. SRD is the first sRNA database centered on a genus; it is a user-friendly and scalable device with the possibility to submit new sequences that should spread in the literature. © 2015 Sassi et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

PIWI Proteins and PIWI-Interacting RNA

DEFF Research Database (Denmark)

Han, Yi Neng; Li, Yuan; Xia, Sheng Qiang

2017-01-01

tissue types as well and play important roles in transposon silencing, epigenetic regulation, gene and protein regulation, genome rearrangement, spermatogenesis and germ stem-cell maintenance. PIWI proteins were first discovered in Drosophila and they play roles in spermatogenesis, germline stem-cell......P-Element induced wimpy testis (PIWI)-interacting RNAs (piRNAs) are a type of noncoding RNAs (ncRNAs) and interact with PIWI proteins. piRNAs were primarily described in the germline, but emerging evidence revealed that piRNAs are expressed in a tissue-specific manner among multiple human somatic...... maintenance, self-renewal, retrotransposons silencing and the male germline mobility control. A growing number of studies have demonstrated that several piRNA and PIWI proteins are aberrantly expressed in various kinds of cancers and may probably serve as a novel biomarker and therapeutic target for cancer...

Tentative mapping of transcription-induced interchromosomal interaction using chimeric EST and mRNA data.

Directory of Open Access Journals (Sweden)

Per Unneberg

Full Text Available Recent studies on chromosome conformation show that chromosomes colocalize in the nucleus, bringing together active genes in transcription factories. This spatial proximity of actively transcribing genes could provide a means for RNA interaction at the transcript level. We have screened public databases for chimeric EST and mRNA sequences with the intent of mapping transcription-induced interchromosomal interactions. We suggest that chimeric transcripts may be the result of close encounters of active genes, either as functional products or "noise" in the transcription process, and that they could be used as probes for chromosome interactions. We have found a total of 5,614 chimeric ESTs and 587 chimeric mRNAs that meet our selection criteria. Due to their higher quality, the mRNA findings are of particular interest and we hope that they may serve as food for thought for specialists in diverse areas of molecular biology.

antaRNA: ant colony-based RNA sequence design.

Science.gov (United States)

Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

2015-10-01

RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Distinct binding interactions of HIV-1 Gag to Psi and non-Psi RNAs: implications for viral genomic RNA packaging.

Science.gov (United States)

Webb, Joseph A; Jones, Christopher P; Parent, Leslie J; Rouzina, Ioulia; Musier-Forsyth, Karin

2013-08-01

Despite the vast excess of cellular RNAs, precisely two copies of viral genomic RNA (gRNA) are selectively packaged into new human immunodeficiency type 1 (HIV-1) particles via specific interactions between the HIV-1 Gag and the gRNA psi (ψ) packaging signal. Gag consists of the matrix (MA), capsid, nucleocapsid (NC), and p6 domains. Binding of the Gag NC domain to ψ is necessary for gRNA packaging, but the mechanism by which Gag selectively interacts with ψ is unclear. Here, we investigate the binding of NC and Gag variants to an RNA derived from ψ (Psi RNA), as well as to a non-ψ region (TARPolyA). Binding was measured as a function of salt to obtain the effective charge (Zeff) and nonelectrostatic (i.e., specific) component of binding, Kd(1M). Gag binds to Psi RNA with a dramatically reduced Kd(1M) and lower Zeff relative to TARPolyA. NC, GagΔMA, and a dimerization mutant of Gag bind TARPolyA with reduced Zeff relative to WT Gag. Mutations involving the NC zinc finger motifs of Gag or changes to the G-rich NC-binding regions of Psi RNA significantly reduce the nonelectrostatic component of binding, leading to an increase in Zeff. These results show that Gag interacts with gRNA using different binding modes; both the NC and MA domains are bound to RNA in the case of TARPolyA, whereas binding to Psi RNA involves only the NC domain. Taken together, these results suggest a novel mechanism for selective gRNA encapsidation.

Deep sequencing of cardiac microRNA-mRNA interactomes in clinical and experimental cardiomyopathy.

Science.gov (United States)

Matkovich, Scot J; Dorn, Gerald W

2015-01-01

MicroRNAs are a family of short (~21 nucleotide) noncoding RNAs that serve key roles in cellular growth and differentiation and the response of the heart to stress stimuli. As the sequence-specific recognition element of RNA-induced silencing complexes (RISCs), microRNAs bind mRNAs and prevent their translation via mechanisms that may include transcript degradation and/or prevention of ribosome binding. Short microRNA sequences and the ability of microRNAs to bind to mRNA sites having only partial/imperfect sequence complementarity complicate purely computational analyses of microRNA-mRNA interactomes. Furthermore, computational microRNA target prediction programs typically ignore biological context, and therefore the principal determinants of microRNA-mRNA binding: the presence and quantity of each. To address these deficiencies we describe an empirical method, developed via studies of stressed and failing hearts, to determine disease-induced changes in microRNAs, mRNAs, and the mRNAs targeted to the RISC, without cross-linking mRNAs to RISC proteins. Deep sequencing methods are used to determine RNA abundances, delivering unbiased, quantitative RNA data limited only by their annotation in the genome of interest. We describe the laboratory bench steps required to perform these experiments, experimental design strategies to achieve an appropriate number of sequencing reads per biological replicate, and computer-based processing tools and procedures to convert large raw sequencing data files into gene expression measures useful for differential expression analyses.