scholarly journals CoBold: a method for identifying different functional classes of transient RNA structure features that can impact RNA structure formation in vivo

2020 ◽  
Author(s):  
Adrián López Martín ◽  
Mohamed Mounir ◽  
Irmtraud M Meyer
Keyword(s):  
Structure Formation ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
Computational Method ◽  
Data Visualisation ◽  
Multiple Sequence ◽  
Functional Roles ◽  
Functional Classes ◽  
The Given

Abstract RNA structure formation in vivo happens co-transcriptionally while the transcript is being made. The corresponding co-transcriptional folding pathway typically involves transient RNA structure features that are not part of the final, functional RNA structure. These transient features can play important functional roles of their own and also influence the formation of the final RNA structure in vivo. We here present CoBold, a computational method for identifying different functional classes of transient RNA structure features that can either aid or hinder the formation of a known reference RNA structure. Our method takes as input either a single RNA or a corresponding multiple-sequence alignment as well as a known reference RNA secondary structure and identifies different classes of transient RNA structure features that could aid or prevent the formation of the given RNA structure. We make CoBold available via a web-server which includes dedicated data visualisation.

scholarly journals R-chie: a web server and R package for visualizing cis and trans RNA–RNA, RNA–DNA and DNA–DNA interactions

2020 ◽  
Vol 48 (18) ◽  
pp. e105-e105 ◽  
Author(s):  
Volodymyr Tsybulskyi ◽  
Mohamed Mounir ◽  
Irmtraud M Meyer
Keyword(s):  
Web Server ◽  
R Package ◽  
Quantitative Information ◽  
Evolutionary Information ◽  
Dna Interactions ◽  
Sequence Alignments ◽  
Multiple Sequence ◽  
Functional Roles ◽  
Genome Interactions

Abstract Interactions between biological entities are key to understanding their potential functional roles. Three fields of research have recently made particular progress: the investigation of transRNA–RNA and RNA–DNA transcriptome interactions and of trans DNA–DNA genome interactions. We now have both experimental and computational methods for examining these interactions in vivo and on a transcriptome- and genome-wide scale, respectively. Often, key insights can be gained by visually inspecting figures that manage to combine different sources of evidence and quantitative information. We here present R-chie, a web server and R package for visualizing cis and transRNA–RNA, RNA–DNA and DNA–DNA interactions. For this, we have completely revised and significantly extended an earlier version of R-chie (1) which was initially introduced for visualizing RNA secondary structure features. The new R-chie offers a range of unique features for visualizing cis and transRNA–RNA, RNA–DNA and DNA–DNA interactions. Particularly note-worthy features include the ability to incorporate evolutionary information, e.g. multiple-sequence alignments, to compare two alternative sets of information and to incorporate detailed, quantitative information. R-chie is readily available via a web server as well as a corresponding R package called R4RNA which can be used to run the software locally.

scholarly journals Predicting dynamic cellular protein-RNA interactions using deep learning and in vivo RNA structure

2020 ◽  
Author(s):  
Lei Sun ◽  
Kui Xu ◽  
Wenze Huang ◽  
Yucheng T. Yang ◽  
Lei Tang ◽  
...  
Keyword(s):  
Neural Network ◽  
Binding Sites ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
Deep Neural Network ◽  
Cell Types ◽  
Cellular Protein ◽  
Rna Regulation ◽  
Multiple Cell

AbstractInteractions with RNA-binding proteins (RBPs) are crucial for RNA regulation and function. While both RNA sequence and structure are critical determinants, RNA structure is dependent on cellular environment and especially important in regulating dynamic RBP bindings across various conditions. However, how distinct it contributes to RBP binding in vivo remains poorly understood. To address this issue, we obtained transcriptome-wide RNA secondary structure profiles in multiple cell-types, and established a deep neural network, PrismNet, that uses in vivo RNA structures to accurately predict cellular protein-RNA interactions. With a deep learning “attention” strategy, PrismNet discovers the exact binding nucleotides and their mutational effect. The predicted binding sites are highly conserved and enriched for rare, deleterious genetic variants. Remarkably, dynamic RBP binding sites are enriched for structure-changing variants (riboSNitches), which are often associated with disease, reflecting dysregulated RBP bindings. Our resource enables the analysis of cell-type-specific RNA regulation, with applications in human disease.Highlights1, A big data resource of transcriptome-wide RNA secondary structure profiles in multiple cell types2, PrismNet, a deep neural network, accurately models the sequence and structural combined patterns of protein-RNA interactions in vivo3, RNA structural information in vivo is critical for the accurate prediction of dynamic RBP binding in various cellular conditions4, PrismNet can dissect and predict how mutations affect RBP binding via RNA sequence or structure changes5, RNA structure-changing RiboSNitches are enriched in dynamic RBP binding sites and often associated with disease, likely disrupting RBP-based regulation

Dawn of the in vivo RNA structurome and interactome

2016 ◽  
Vol 44 (5) ◽  
pp. 1395-1410 ◽  
Author(s):  
Chun Kit Kwok
Keyword(s):  
Gene Regulation ◽  
Rna Structure ◽  
Information Storage ◽  
The Novel ◽  
Rna Structures ◽  
Functional Roles ◽  
Structure Probing ◽  
Function Relationship ◽  
Next Generation Sequencing Ngs

RNA is one of the most fascinating biomolecules in living systems given its structural versatility to fold into elaborate architectures for important biological functions such as gene regulation, catalysis, and information storage. Knowledge of RNA structures and interactions can provide deep insights into their functional roles in vivo. For decades, RNA structural studies have been conducted on a transcript-by-transcript basis. The advent of next-generation sequencing (NGS) has enabled the development of transcriptome-wide structural probing methods to profile the global landscape of RNA structures and interactions, also known as the RNA structurome and interactome, which transformed our understanding of the RNA structure–function relationship on a transcriptomic scale. In this review, molecular tools and NGS methods used for RNA structure probing are presented, novel insights uncovered by RNA structurome and interactome studies are highlighted, and perspectives on current challenges and potential future directions are discussed. A more complete understanding of the RNA structures and interactions in vivo will help illuminate the novel roles of RNA in gene regulation, development, and diseases.

scholarly journals In Vivo and In Vitro Genome-Wide Profiling of RNA Secondary Structures Reveals Key Regulatory Features in Plasmodium falciparum

2021 ◽  
Vol 11 ◽  
Author(s):  
Yanwei Qi ◽  
Yuhong Zhang ◽  
Guixing Zheng ◽  
Bingxia Chen ◽  
Mengxin Zhang ◽  
...  
Keyword(s):  
Secondary Structure ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
Secondary Structures ◽  
Rna Structures ◽  
Trophozoite Stage ◽  
Rna Secondary Structures ◽  
Biological Programme

It is widely accepted that the structure of RNA plays important roles in a number of biological processes, such as polyadenylation, splicing, and catalytic functions. Dynamic changes in RNA structure are able to regulate the gene expression programme and can be used as a highly specific and subtle mechanism for governing cellular processes. However, the nature of most RNA secondary structures in Plasmodium falciparum has not been determined. To investigate the genome-wide RNA secondary structural features at single-nucleotide resolution in P. falciparum, we applied a novel high-throughput method utilizing the chemical modification of RNA structures to characterize these structures. Structural data from parasites are in close agreement with the known 18S ribosomal RNA secondary structures of P. falciparum and can help to predict the in vivo RNA secondary structure of a total of 3,396 transcripts in the ring-stage and trophozoite-stage developmental cycles. By parallel analysis of RNA structures in vivo and in vitro during the Plasmodium parasite ring-stage and trophozoite-stage intraerythrocytic developmental cycles, we identified some key regulatory features. Recent studies have established that the RNA structure is a ubiquitous and fundamental regulator of gene expression. Our study indicate that there is a critical connection between RNA secondary structure and mRNA abundance during the complex biological programme of P. falciparum. This work presents a useful framework and important results, which may facilitate further research investigating the interactions between RNA secondary structure and the complex biological programme in P. falciparum. The RNA secondary structure characterized in this study has potential applications and important implications regarding the identification of RNA structural elements, which are important for parasite infection and elucidating host-parasite interactions and parasites in the environment.

scholarly journals CROSSalive: a web server for predicting the in vivo structure of RNA molecules

2019 ◽  
Author(s):  
Riccardo Delli Ponti ◽  
Alexandros Armaos ◽  
Gian Gaetano Tartaglia
Keyword(s):  
Protein Interactions ◽  
Rna Structure ◽  
Rna Secondary Structure ◽  
Sequence Length ◽  
Test Set ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Map Data ◽  
Long Non Coding Rna

ABSTRACTHere we introduce CROSSalive, an algorithm to predict the RNA secondary structure profile (double and single stranded regions) in vivo and without sequence length limitations. Using predictions of protein interactions CROSSalive predicts the effect of N6 adenosine methylation (m6a) on RNA structure. Trained on icSHAPE data in presence (m6a+) and absence (m6a-) of methylation CROSSalive achieves an accuracy of 0.88 on the test set. The algorithm was also applied to the murine long non-coding RNA Xist (17900 nt, not present in the training) and shows a Pearson’s correlation of 0.45 with SHAPE-map data. CROSSalive webserver is freely accessible at the following page: http://service.tartaglialab.com/new_submission/crossalive

scholarly journals Exosomal S100A4 derived from highly metastatic hepatocellular carcinoma cells promotes metastasis by activating STAT3

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Haoting Sun ◽  
Chaoqun Wang ◽  
Beiyuan Hu ◽  
Xiaomei Gao ◽  
Tiantian Zou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cancer Progression ◽  
Calcium Binding ◽  
Tumor Metastasis ◽  
Metastatic Potential ◽  
Functional Roles ◽  
Stat3 Phosphorylation ◽  
Hcc Cells

AbstractIntercellular cross-talk plays important roles in cancer progression and metastasis. Yet how these cancer cells interact with each other is still largely unknown. Exosomes released by tumor cells have been proved to be effective cell-to-cell signal mediators. We explored the functional roles of exosomes in metastasis and the potential prognostic values for hepatocellular carcinoma (HCC). Exosomes were extracted from HCC cells of different metastatic potentials. The metastatic effects of exosomes derived from highly metastatic HCC cells (HMH) were evaluated both in vitro and in vivo. Exosomal proteins were identified with iTRAQ mass spectrum and verified in cell lines, xenograft tumor samples, and functional analyses. Exosomes released by HMH significantly enhanced the in vitro invasion and in vivo metastasis of low metastatic HCC cells (LMH). S100 calcium-binding protein A4 (S100A4) was identified as a functional factor in exosomes derived from HMH. S100A4rich exosomes significantly promoted tumor metastasis both in vitro and in vivo compared with S100A4low exosomes or controls. Moreover, exosomal S100A4 could induce expression of osteopontin (OPN), along with other tumor metastasis/stemness-related genes. Exosomal S100A4 activated OPN transcription via STAT3 phosphorylation. HCC patients with high exosomal S100A4 in plasma also had a poorer prognosis. In conclusion, exosomes from HMH could promote the metastatic potential of LMH, and exosomal S100A4 is a key enhancer for HCC metastasis, activating STAT3 phosphorylation and up-regulating OPN expression. This suggested exosomal S100A4 to be a novel prognostic marker and therapeutic target for HCC metastasis.

scholarly journals HIV-1 Matrix Protein p17 Promotes Lymphangiogenesis and Activates the Endothelin-1/Endothelin B Receptor Axis

2014 ◽  
Vol 34 (4) ◽  
pp. 846-856 ◽  
Author(s):  
Francesca Caccuri ◽  
Christine Rueckert ◽  
Cinzia Giagulli ◽  
Kai Schulze ◽  
Daniele Basta ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Lymph Node ◽  
Structure Formation ◽  
Highly Active Antiretroviral Therapy ◽  
Matrix Protein ◽  
Lymphatic Endothelial Cells ◽  
Endothelin 1 ◽  
Tumor Dissemination ◽  
Hiv 1

Objective— AIDS-related lymphomas are high grade and aggressively metastatic with poor prognosis. Lymphangiogenesis is essential in supporting proliferation and survival of lymphoma, as well as tumor dissemination. Data suggest that aberrant lymphangiogenesis relies on action of HIV-1 proteins rather than on a direct effect of the virus itself. HIV-1 matrix protein p17 was found to accumulate and persist in lymph nodes of patients even under highly active antiretroviral therapy. Because p17 was recently found to exert a potent proangiogenic activity by interacting with chemokine (C-X-C motif) receptors 1 and 2, we tested the prolymphangiogenic activity of the viral protein. Approach and Results— Human primary lymph node–derived lymphatic endothelial cells were used to perform capillary-like structure formation, wound healing, spheroids, and Western blot assays after stimulation with or without p17. Here, we show that p17 promotes lymphangiogenesis by binding to chemokine (C-X-C motif) receptor-1 and chemokine (C-X-C motif) receptor-2 expressed on lymph node–derived lymphatic endothelial cells and activating the Akt/extracellular signal–regulated kinase signaling pathway. In particular, it was found to induce capillary-like structure formation, sprout formation from spheroids, and increase lymph node–derived lymphatic endothelial cells motility. The p17 lymphangiogenic activity was, in part, sustained by activation of the endothelin-1/endothelin receptor B axis. A Matrigel plug assay showed that p17 was able to promote the outgrowth of lymphatic vessels in vivo, demonstrating that p17 directly regulates lymphatic vessel formation. Conclusions— Our results suggest that p17 may generate a prolymphangiogenic microenvironment and plays a role in predisposing the lymph node to lymphoma growth and metastasis. This finding offers new opportunities to identify treatment strategies in combating AIDS-related lymphomas.

Regulatory effects of cotranscriptional RNA structure formation and transitions

2016 ◽  
Vol 7 (5) ◽  
pp. 562-574 ◽  
Author(s):  
Sheng-Rui Liu ◽  
Chun-Gen Hu ◽  
Jin-Zhi Zhang
Keyword(s):  
Structure Formation ◽  
Rna Structure ◽  
Regulatory Effects

Tissue specificity of type I collagen gene expression is determined at both transcriptional and post-transcriptional levels

1984 ◽  
Vol 4 (9) ◽  
pp. 1843-1852
Author(s):  
R J Focht ◽  
S L Adams
Keyword(s):  
Gene Expression ◽  
Rna Structure ◽  
Type I Collagen ◽  
Translational Efficiency ◽  
Type I ◽  
Collagen Gene ◽  
Differentiated Cells ◽  
Collagen Gene Expression

We analyzed the control of type I collagen synthesis in four kinds of differentiated cells from chicken embryos which synthesize very different amounts of the protein. Tendon, skin, and smooth muscle cells were found to have identical amounts of type I collagen RNAs; however, the RNAs had inherently different translatabilities, which were observed both in vivo and in vitro. Chondrocytes also had substantial amounts of type I collagen RNAs, even though they directed no detectable synthesis of the protein either in vivo or in vitro. Type I collagen RNAs in chondrocytes display altered electrophoretic mobilities, suggesting that in these cells the reduction in translational efficiency may be mediated in part by changes in the RNA structure. These data indicate that control of type I collagen gene expression is a complex process which is exerted at both transcriptional and post-transcriptional levels.

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