RNA secondary structure ensemble mapping in a living cell identifies conserved RNA regulatory switches and thermometers
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1036687 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26712051.fastq.gz | Fastqsanger.gz | |||
| SRR26712052.fastq.gz | Fastqsanger.gz | |||
| SRR26712053.fastq.gz | Fastqsanger.gz | |||
| SRR26712054.fastq.gz | Fastqsanger.gz | |||
| SRR26712055_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 28 |
Similar Datasets
Project description:RNA molecules can populate ensembles of alternative structural conformations, but comprehensively mapping RNA conformational landscapes within living cells presents significant challenges and has, as such, so far remained elusive. Here, we generated the first transcriptome-scale maps of RNA secondary structure ensembles in a living cell, using Escherichia coli as a model. Our analysis uncovered features of structurally-dynamic regions, as well as the existence of hundreds of highly-conserved bacterial RNA structural elements. Conditional structure mapping revealed extensive restructuring of RNA ensembles during cold shock, leading to the discovery of several novel RNA thermometers in the 5′ UTRs of the cspG, cspI, cpxP and lpxP mRNAs. We mechanistically characterized how these thermometers switch structure in response to cold shock and revealed the cspE chaperone-mediated regulation of lpxP. Collectively, this work reveals a previously unappreciated complexity of RNA structural dynamics in living cells, and it provides a key resource to significantly accelerate the discovery of regulatory RNA switches.
2024-09-24 | GSE247244 | GEO
Project description:Dynamical Modeling of Secondary Metabolism and Metabolic Switches in Streptomyces xiamenensis 318
| PRJEB29252 | ENA
Project description:Secondary transporters undergo structural rearrangements to catalyze substrate translocation across the cell membrane – yet how such conformational changes happen within a lipid environment remains poorly understood. Here, we combine hydrogen-deuterium exchange mass spectrometry (HDX-MS) with molecular dynamics (MD) simulations to understand how lipids regulate the conformational dynamics of secondary transporters at the molecular level. Using the homologous transporters XylE, LacY and GlpT from Escherichia coli as model systems, we discover that conserved networks of charged residues act as molecular switches that drive the conformational transition between different states. We reveal that these molecular switches are regulated by interactions with surrounding phospholipids and show that phosphatidylethanolamine interferes with the formation of the conserved networks and favors an inward-facing state. Overall, this work provides insights into the importance of lipids in shaping the conformational landscape of an important class of transporters.
2018-10-16 | PXD011060 | Pride
Project description:we resolved the RNA secondary structure of human (HEK293, HeLa, K562, HepG2, H9) and mouse (mES) cells based on optimized in vivo click selective 2'-hydroxyl acylation and profiling experiment (icSHAPE). we describe a deep discriminative neural network (PrismNet) that integrates big data of RBP binding and RNA secondary structure from matched living cells and accurately models the RNA sequence and structural preferences of protein-RNA interactions in vivo, enabling precise prediction of the perturbation effects of genetic variants.
2021-02-05 | GSE145805 | GEO
Project description:We show that N6-methyladenosine (m6A), the most abundant internal modification in mRNA/lncRNA with still poorly characterized function, alters RNA structure to facilitate the access of RBM for heterogeneous nuclear ribonucleoprotein C (hnRNP C). We term this mechanism m6A-switch. Through combining PAR-CLIP with Me-RIP, we identify 39,060 m6A-switches among hnRNP C binding sites transcriptome-wide. We show that m6A-methyltransferases METTL3 or METTL14 knockdown decreases hnRNP C binding at 16,582 m6A-switches. Taken together, 2,798 m6A-switches of high confidence are identified to mediate RNA-hnRNP C interactions and affect diverse biological processes including cell cycle regulation. These findings reveal the biological importance of m6A and provide insights into the sophisticated regulation of RNA-RBP interactions through m6A-induced RNA structural remodeling. Measure the m6A methylated hnRNP C binding sites transcriptome-wide by PARCLIP-MeRIP; measure the differential hnRNP C occupancies upon METTL3/METTL14 knockdown by PAR-CLIP; measure RNA abundance and splicing level changes upon HNRNPC, METTL3 and METTL14 knockdown
2015-02-27 | E-GEOD-56010 | biostudies-arrayexpress
Project description:RNA structural switches are key regulators of gene expression in bacteria, yet their characterization in Metazoa remains limited. Here we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3’UTR of the RORC transcript. In vivo DMS-MaPseq, coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated mRNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally-driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.
2024-07-05 | GSE266058 | GEO
Project description:BackgroundAccurate 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.ResultsIn 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.ConclusionsOur 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 false negative and false positive base pair predictions. Finally, AveRNA can make use of arbitrary sets of secondary structure prediction procedures and can therefore be used to leverage improvements in prediction accuracy offered by algorithms and energy models developed in the future. Our data, MATLAB software and a web-based version of AveRNA are publicly available at http://www.cs.ubc.ca/labs/beta/Software/AveRNA.
| S-EPMC3750279 | biostudies-literature
Project description:We show that N6-methyladenosine (m6A), the most abundant internal modification in mRNA/lncRNA with still poorly characterized function, alters RNA structure to facilitate the access of RBM for heterogeneous nuclear ribonucleoprotein C (hnRNP C). We term this mechanism m6A-switch. Through combining PAR-CLIP with Me-RIP, we identify 39,060 m6A-switches among hnRNP C binding sites transcriptome-wide. We show that m6A-methyltransferases METTL3 or METTL14 knockdown decreases hnRNP C binding at 16,582 m6A-switches. Taken together, 2,798 m6A-switches of high confidence are identified to mediate RNA-hnRNP C interactions and affect diverse biological processes including cell cycle regulation. These findings reveal the biological importance of m6A and provide insights into the sophisticated regulation of RNA-RBP interactions through m6A-induced RNA structural remodeling.
2015-02-27 | GSE56010 | GEO
Project description:Mangrove-derived Streptomyces xiamenensis 318, with a relatively compact genome and simpler secondary metabolism, is used as model organism in our investigation. We performed integrated studies of metabolic dynamical modeling, transcriptome level measurements, and metabolic profiling experiments on this strain. To explore the relationship between primary and secondary metabolism, the global gene expression levels of strain 318 from early stationary phase to late stationary phase were compared by RNAseq analysis at 16 hour, 24 hour, 36 hour and 72 hour after batch culture started.
2019-02-10 | E-MTAB-7314 | biostudies-arrayexpress
Project description:Designing Molecular RNA Switches with Restricted Boltzmann Machines
| PRJNA1106466 | ENA