Evidence map›Paper›PMID 21239468›Full record

ArticleRNA (New York, N.Y.)2011

A mutate-and-map strategy accurately infers the base pairs of a 35-nucleotide model RNA.

Wipapat Kladwang, Pablo Cordero, Rhiju Das

Abstract read
In one paragraph

Article in RNA (New York, N.Y.), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

32 citing papers in PubMed.

  1. De novo design of RNA pseudoknots with deep learning.bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. An RNA pseudoknot stimulates HTLV-1RNA (New York, N.Y.) · 2020
    Article
  7. Article
  8. High-throughput determination of RNA structures.Nature reviews. Genetics · 2018
    Review
  9. Article
  10. Article
  11. RNA structure inference through chemical mapping after accidental or intentional mutations.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  12. Article
  13. Article
  14. Modeling Small Noncanonical RNA Motifs with the Rosetta FARFAR Server.Methods in molecular biology (Clifton, N.J.) · 2016
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. The mutate-and-map protocol for inferring base pairs in structured RNA.Methods in molecular biology (Clifton, N.J.) · 2014
    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

3 authors.

Wipapat KladwangDepartment of Biochemistry, Stanford University, Stanford, California 94305, USA.
Pablo Cordero
Rhiju Das

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present a rapid experimental strategy for inferring base pairs in structured RNAs via an information-rich extension of classic chemical mapping approaches. The mutate-and-map method, previously applied to a DNA/RNA helix, systematically searches for single mutations that enhance the chemical accessibility of base-pairing partners distant in sequence. To test this strategy for structured RNAs, we have carried out mutate-and-map measurements for a 35-nt hairpin, called the MedLoop RNA, embedded within an 80-nt sequence. We demonstrate the synthesis of all 105 single mutants of the MedLoop RNA sequence and present high-throughput DMS, CMCT, and SHAPE modification measurements for this library at single-nucleotide resolution. The resulting two-dimensional data reveal visually clear, punctate features corresponding to RNA base pair interactions as well as more complex features; these signals can be qualitatively rationalized by comparison to secondary structure predictions. Finally, we present an automated, sequence-blind analysis that permits the confident identification of nine of the 10 MedLoop RNA base pairs at single-nucleotide resolution, while discriminating against all 1460 false-positive base pairs. These results establish the accuracy and information content of the mutate-and-map strategy and support its feasibility for rapidly characterizing the base-pairing patterns of larger and more complex RNA systems.

Indexed as

Base PairingNucleic Acid ConformationBase SequenceDNAMolecular Sequence DataMutagenesisMutationRNADNARNA

Identifiers

PMID21239468
PMCPMC3039151

What OpenQuestion holds

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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.