Evidence map›Paper›PMID 42818313›Full record

ArticlebioRxiv : the preprint server for biology2026

FAST-MaP: Chemical Mapping of RNA Structures Using Primer-less Sequencing.

Jigyasa Verma, Hamish M Blair, Wipapat Kladwang, Rhiju Das

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jigyasa VermaDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0002-9286-0299
Hamish M BlairDepartment of Mathematics, Stanford University, Stanford, CA, USA.ORCID 0009-0000-0091-2032
Wipapat KladwangDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0009-0001-0490-9495
Rhiju DasDepartment of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.ORCID 0000-0001-7497-0972

Funding

Next-generation computational/chemical methods for complex RNA structuresR35GM122579 · NIGMS · STANFORD UNIVERSITY · PI Rhiju Das · 2017 to 2026
$7.2M
NIGMS NIH HHS R35 GM122579
6 · The paper itself

Abstract

RNA structure governs the function of non-coding RNAs and influences mRNA stability and translation, making testing of models of experimental RNA structure relevant to fields spanning structural biology, virology, and molecular therapeutics. Here we present FAST-MaP (Fast and Accessible Sequencing Technology for Mutational Profiling), a protocol that enables per-nucleotide RNA structure characterization using standard molecular biology equipment and requiring no sequencing infrastructure or bioinformatics expertise. RNA is chemically modified with orthogonal probes (2A3 and DMS), reverse-transcribed, and PCR-amplified to produce dsDNA amplicons that are submitted directly to a commercial primer-less sequencing service. Returned FASTQ files are processed through a freely accessible web server to generate normalized reactivity profiles within minutes. The complete protocol, from DNA template to structural data, can be completed in approximately one week. We illustrate the workflow on a 659-nucleotide RNA, demonstrating how to test structure preservation across buffers, and how to test specific secondary and tertiary structure predictions of the RNA from computational modeling or cryo-electron microscopy. The protocol requires only standard molecular-biology skills and does not require sequencing or bioinformatics expertise.

Identifiers

PMID42818313
PMCPMC13622246

What OpenQuestion holds

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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.