Evidence map›Paper›PMID 28851837›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2017

RNA structure inference through chemical mapping after accidental or intentional mutations.

Clarence Y Cheng, Wipapat Kladwang, Joseph D Yesselman, Rhiju Das

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
3.0field-weighted citation impact, top 8% of its field
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

51 citing papers in PubMed, 79 citations in OpenAlex.

  1. Article
  2. Review
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  4. Quantifying MgbioRxiv : the preprint server for biology · 2026
    Article
  5. Article
  6. Article
  7. Article
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  13. Review
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  15. RNA tertiary structure and conformational dynamics revealed by BASH MaP.bioRxiv : the preprint server for biology · 2024
    Article
  16. Article
  17. Article
  18. Tertiary folds of the SL5 RNA from the 5' proximal region of SARS-CoV-2 and related coronaviruses.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  19. Article
  20. Article
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

4 authors at 1 institution in 1 country.

Clarence Y ChengDepartment of Biochemistry, Stanford University, Stanford, CA 94305.ORCID 0000-0003-3741-1906
Wipapat KladwangDepartment of Biochemistry, Stanford University, Stanford, CA 94305.
Joseph D YesselmanDepartment of Biochemistry, Stanford University, Stanford, CA 94305.
Rhiju DasDepartment of Biochemistry, Stanford University, Stanford, CA 94305; rhiju@stanford.edu.ORCID 0000-0001-7497-0972
Stanford University · US

Funding

Supplement to Enhance Wellness and Resiliency in the Graduate EnvironmentT32GM007276 · NIGMS · STANFORD UNIVERSITY · PI MORRISON, ASHBY J. · 1985 to 2023
$32.9M
Non-coding RNA Structure through a Mutate-and-Map StrategyR01GM102519 · NIGMS · STANFORD UNIVERSITY · PI DAS, RHIJU · 2012 to 2016
$1.5M
NIGMS NIH HHS R01 GM102519NIGMS NIH HHS T32 GM007276
6 · The paper itself

Abstract

Despite the critical roles RNA structures play in regulating gene expression, sequencing-based methods for experimentally determining RNA base pairs have remained inaccurate. Here, we describe a multidimensional chemical-mapping method called "mutate-and-map read out through next-generation sequencing" (M2-seq) that takes advantage of sparsely mutated nucleotides to induce structural perturbations at partner nucleotides and then detects these events through dimethyl sulfate (DMS) probing and mutational profiling. In special cases, fortuitous errors introduced during DNA template preparation and RNA transcription are sufficient to give M2-seq helix signatures; these signals were previously overlooked or mistaken for correlated double-DMS events. When mutations are enhanced through error-prone PCR, in vitro M2-seq experimentally resolves 33 of 68 helices in diverse structured RNAs including ribozyme domains, riboswitch aptamers, and viral RNA domains with a single false positive. These inferences do not require energy minimization algorithms and can be made by either direct visual inspection or by a neural-network-inspired algorithm called M2-net. Measurements on the P4-P6 domain of the

Indexed as

Nucleic Acid ConformationAnimalsBase PairingBase SequenceGeobacillus stearothermophilusPlasmidsRiboswitchRNARNA, CatalyticSequence Analysis, RNATetrahymenaXenopus laevisGIR1 ribozymeRiboswitchRNARNA, Catalyticchemical mappingmutational profilingneural networkRNA structure modelingXenopus egg extract

Identifiers

PMID28851837
PMCPMC5603990
OpenAlexW2952169301

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.