SHAPE analysis of RNA structure in living cells with unprecedented accuracy
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA646706 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12235517.fastq.gz | Fastqsanger.gz | |||
| SRR12235518.fastq.gz | Fastqsanger.gz | |||
| SRR12235519.fastq.gz | Fastqsanger.gz | |||
| SRR12235520.fastq.gz | Fastqsanger.gz | |||
| SRR12235521.fastq.gz | Fastqsanger.gz |
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Project description:Due to the mounting evidence that RNA structure plays a critical role in regulating almost any essential physiological as well as pathological process, being able to accurately define the folding of RNA molecules within living cells has become a crucial need. We introduce here 2-aminopyridine-3-carboxylic acid (2A3), as a general probe for the interrogation of RNA structures in vivo. 2A3 performs comparably well to NAI on naked RNA under in vitro conditions and it significantly outperforms NAI when probing RNA structure in vivo, particularly in bacteria, underlining its increased ability to permeate biological membranes. When used as a restraint to drive RNA structure prediction, data derived by SHAPE-MaP with 2A3 yields more accurate predictions than NAI-derived data. Due to its extreme efficiency and accuracy, we can anticipate that 2A3 will rapidly take over conventional SHAPE reagents for probing RNA structures both in vitro and in vivo.
2020-12-16 | GSE154563 | GEO
Project description:Due to the mounting evidence that RNA structure plays a critical role in regulating almost any physiological as well as pathological process, being able to accurately define the folding of RNA molecules within living cells has become a crucial need. We introduce here 2-aminopyridine-3-carboxylic acid imidazolide (2A3), as a general probe for the interrogation of RNA structures in vivo. 2A3 shows moderate improvements with respect to the state-of-the-art selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) reagent NAI on naked RNA under in vitro conditions, but it significantly outperforms NAI when probing RNA structure in vivo, particularly in bacteria, underlining its increased ability to permeate biological membranes. When used as a restraint to drive RNA structure prediction, data derived by SHAPE-MaP with 2A3 yields more accurate predictions than NAI-derived data. Due to its extreme efficiency and accuracy, we can anticipate that 2A3 will rapidly take over conventional SHAPE reagents for probing RNA structures both in vitro and in vivo.
| S-EPMC8034653 | biostudies-literature
Project description:Binding of transcription factors to DNA is mediated by the recognition of the chemical signatures of the DNA bases and the three-dimensional shape of the DNA molecule. The direct contribution of DNA shape to DNA-binding specificity has been difficult to assess, as DNA shape is a consequence of its sequence. Here, we teased apart these two modes of recognition in the context of Hox-DNA binding. We made a series of mutations in Hox residues that, in a co-crystal structure, only recognize DNA shape, and tested the effect on DNA binding preferences using SELEX-seq. Analysis of shape features of selected sequences revealed that these residues are both necessary and sufficient for selection of sequences with distinct shape features. We used statistical machine learning to show that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence. We conclude that shape readout is a direct and critical component of binding site selection by Hox proteins. Three rounds of SELEX were performed on a series of Hox mutants as described in Slattery et al, Cell, 2011 (PMID 22153072) and Riley et al, Methods in molecular Biology, 2014 (PMID 25151169). Briefly, His-tagged Scr and Antp mutant proteins were incubated with a randomized 16mer oligonucleotide library, and bound DNA was amplified and sequenced as described (PMID 22153072, PMID 25151169).
2015-01-21 | E-GEOD-65073 | biostudies-arrayexpress
Project description:New regulatory roles continue to emerge for both natural and engineered noncoding RNAs, many of which have specific secondary and tertiary structures essential to their function. Thus there is a growing need to develop technologies that enable rapid characterization of structural features within complex RNA populations. We have developed a high-throughput technique, SHAPE-Seq, that can simultaneously measure quantitative, single nucleotide-resolution secondary and tertiary structural information for hundreds of RNA molecules of arbitrary sequence. SHAPE-Seq combines selective 2â²-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry with multiplexed paired-end deep sequencing of primer extension products. This generates millions of sequencing reads, which are then analyzed using a fully automated data analysis pipeline, based on a rigorous maximum likelihood model of the SHAPE-Seq experiment. We demonstrate the ability of SHAPE-Seq to accurately infer secondary and tertiary structural information, detect subtle conformational changes due to single nucleotide point mutations, and simultaneously measure the structures of a complex pool of different RNA molecules. SHAPE-Seq thus represents a powerful step toward making the study of RNA secondary and tertiary structures high throughput and accessible to a wide array of scientific pursuits, from fundamental biological investigations to engineering RNA for synthetic biological systems. We sequenced in-vitro transcribed RNaseP in wild type and barcoded variants and probed them with SHAPE-Seq. Comparison to existing crystalography data and previous SHAPE experiments verified the accuracy of the technique and the absence of bias due to our multiplexiing strategy.
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Project description:Binding of transcription factors to DNA is mediated by the recognition of the chemical signatures of the DNA bases and the three-dimensional shape of the DNA molecule. The direct contribution of DNA shape to DNA-binding specificity has been difficult to assess, as DNA shape is a consequence of its sequence. Here, we teased apart these two modes of recognition in the context of Hox-DNA binding. We made a series of mutations in Hox residues that, in a co-crystal structure, only recognize DNA shape, and tested the effect on DNA binding preferences using SELEX-seq. Analysis of shape features of selected sequences revealed that these residues are both necessary and sufficient for selection of sequences with distinct shape features. We used statistical machine learning to show that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence. We conclude that shape readout is a direct and critical component of binding site selection by Hox proteins.
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Project description:SHAPE-MaP structure probing experiment was performed on SARS-CoV-2 infected Vero cells at 4 days post infection with two biological replicates. For each replciate, SHAPE-MaP includes a sample treated with 2-methylnicotinic acid imidazolide acid (modified) or a minue reagent (unmodified). NAI preferentially reacts with unpaired bases in RNA, forming acylated bases. These modifications are encoded as mutation during reverse transcripatse and library preparation. After sequencing and alignment, the reactivity profiles of 'modified' and 'unmodified' samples are used to calculate SHAPE reactivity of each base
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Project description:SHAPE-guided RNA structure homology search and motif discovery
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Project description:The rapidly growing popularity of RNA structure probing methods is leading to increasingly large amounts of available RNA structure information. This demands the development of efficient tools for the identification of RNAs sharing regions of structural similarity by direct comparison of their reactivity profiles, hence enabling the discovery of conserved structural features. We here introduce SHAPEwarp, a largely sequence-agnostic SHAPE-guided algorithm for the identification of structurally-similar regions in RNA molecules. Analysis of Dengue, Zika and coronavirus genomes recapitulates known regulatory RNA structures and identifies novel highly-conserved structural elements. This work represents a preliminary step towards the model-free search and identification of shared RNA structural features within transcriptomes.
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Project description:RNA duplex map in living cells reveals higher order transcriptome structure
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Project description:RNA molecules can populate ensembles of alternative structural conformations; however, comprehensively mapping RNA conformational landscapes within living cells presents notable challenges and has, as such, so far remained elusive. Here, we generate transcriptome-scale maps of RNA secondary structure ensembles in both Escherichia coli and human cells, uncovering features of structurally heterogeneous regions. By combining ensemble deconvolution and covariation analyses, we report the discovery of several bacterial RNA thermometers in the 5′ untranslated regions (UTRs) of the cspG, cspI, cpxP and lpxP mRNAs of Escherichia coli. We mechanistically characterize how these thermometers switch structure in response to cold shock and reveal the CspE chaperone-mediated regulation of lpxP. Furthermore, we introduce a method for the transcriptome-scale mapping of 5′ UTR structures in eukaryotes and leverage it to uncover RNA structural switches regulating the differential usage of open reading frames in the 5′ UTRs of the CKS2 and TXNL4A mRNAs in HEK293 cells. Collectively, this work reveals the complexity of RNA structural dynamics in living cells and provides a resource to accelerate the discovery of regulatory RNA switches.
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