Evidence map›Paper›PMID 27064082›Full record

ArticleMethods (San Diego, Calif.)2016

Characterizing RNA structures in vitro and in vivo with selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq).

Kyle E Watters, Angela M Yu, Eric J Strobel, Alex H Settle, Julius B Lucks

Abstract read
In one paragraph

Article in Methods (San Diego, Calif.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

47 citing papers in PubMed.

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  9. A Guide to Computational Cotranscriptional Folding Featuring the SRP RNA.Methods in molecular biology (Clifton, N.J.) · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kyle E WattersSchool of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States.
Angela M YuSchool of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States; Tri-Institutional Program in Computational Biology and Medicine, Cornell University, Ithaca, New York, Weill Cornell Medical College, New York, New York, Memorial Sloan-Kettering Cancer Center, New York, New York, United States; Computational Biology Program, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, United States.
Eric J StrobelSchool of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States.
Alex H SettleSchool of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States.
Julius B LucksSchool of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY 14853, United States. Electronic address: jblucks@cornell.edu.

Funding

Tri-Institutional Training Program in Computational Biology & MedicineT32GM083937 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI CHRISTINI, DAVID J. · 2009 to 2018
$3.1M
A New High-Throughput Technology To Reveal The Dynamic Functional States of RNAsDP2GM110838 · NIGMS · NORTHWESTERN UNIVERSITY · PI LUCKS, JULIUS BEAU · 2013 to 2013
$2.1M
NIGMS NIH HHS DP2 GM110838NIGMS NIH HHS T32 GM083937
6 · The paper itself

Abstract

RNA molecules adopt a wide variety of structures that perform many cellular functions, including, among others, catalysis, small molecule sensing, and cellular defense. Our ability to characterize, predict, and design RNA structures are key factors for understanding and controlling the biological roles of RNAs. Fortunately, there has been rapid progress in this area, especially with respect to experimental methods that can characterize RNA structures in a high throughput fashion using chemical probing and next-generation sequencing. Here, we describe one such method, selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq), which measures nucleotide resolution flexibility information for RNAs in vitro and in vivo. We outline the process of designing and performing a SHAPE-Seq experiment and describe methods for using experimental SHAPE-Seq data to restrain computational folding algorithms to generate more accurate predictions of RNA secondary structure. We also provide a number of examples of SHAPE-Seq reactivity spectra obtained in vitro and in vivo and discuss important considerations for performing SHAPE-Seq experiments, both in terms of collecting and analyzing data. Finally, we discuss improvements and extensions of these experimental and computational techniques that promise to deepen our knowledge of RNA folding and function.

Indexed as

AcylationBase SequenceCells, CulturedComputer SimulationDNA PrimersHydroxyl RadicalInverted Repeat SequencesModels, MolecularRNARNA FoldingSequence Analysis, RNADNA PrimersHydroxyl RadicalRNAIn vivo RNA structureRNARNA-ligand interactionsRNA structure predictionRNA structure probingSHAPESHAPE-Seq

Identifiers

PMID27064082
PMCPMC4921265

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.