Evidence map›Paper›PMID 36350614›Full record

ArticleNucleic acids research2022

rG4detector, a novel RNA G-quadruplex predictor, uncovers their impact on stress granule formation.

Maor Turner, Yehuda M Danino, Mira Barshai, Nancy S Yacovzada, Yahel Cohen, Tsviya Olender, Ron Rotkopf, David Monchaud, Eran Hornstein, Yaron Orenstein

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.0field-weighted citation impact, top 7% 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

24 citing papers in PubMed, 40 citations in OpenAlex.

  1. Review
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  3. G-Quadruplexes: Structural Diversity and Emerging Roles in Biomolecular Condensation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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  17. Coding relationship links RNA G-quadruplexes and protein RGG motifs in RNA-binding protein autoregulation.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

10 authors at 3 institutions in 2 countries.

Maor TurnerSchool of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Be'er-Sheva 8410501, Israel.
Yehuda M DaninoDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel.ORCID 0000-0001-5295-0487
Mira BarshaiSchool of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Be'er-Sheva 8410501, Israel.
Nancy S YacovzadaDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel.
Yahel CohenDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel.
Tsviya OlenderDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel.
Ron RotkopfBioinformatics Unit, Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot 7610001, Israel.ORCID 0000-0001-9503-7348
David MonchaudInstitut de Chimie Moleculaire, ICMUB CNRS UMR 6302, UBFC Dijon, France.ORCID 0000-0002-3056-9295
Eran HornsteinDepartment of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel.
Yaron OrensteinSchool of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Be'er-Sheva 8410501, Israel.ORCID 0000-0002-3583-3112
Weizmann Institute of Science · ILBen-Gurion University of the Negev · ILCentre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

RNA G-quadruplexes (rG4s) are RNA secondary structures, which are formed by guanine-rich sequences and have important cellular functions. Existing computational tools for rG4 prediction rely on specific sequence features and/or were trained on small datasets, without considering rG4 stability information, and are therefore sub-optimal. Here, we developed rG4detector, a convolutional neural network to identify potential rG4s in transcriptomics data. rG4detector outperforms existing methods in both predicting rG4 stability and in detecting rG4-forming sequences. To demonstrate the biological-relevance of rG4detector, we employed it to study RNAs that are bound by the RNA-binding protein G3BP1. G3BP1 is central to the induction of stress granules (SGs), which are cytoplasmic biomolecular condensates that form in response to a variety of cellular stresses. Unexpectedly, rG4detector revealed a dynamic enrichment of rG4s bound by G3BP1 in response to cellular stress. In addition, we experimentally characterized G3BP1 cross-talk with rG4s, demonstrating that G3BP1 is a bona fide rG4-binding protein and that endogenous rG4s are enriched within SGs. Furthermore, we found that reduced rG4 availability impairs SG formation. Hence, we conclude that rG4s play a direct role in SG biology via their interactions with RNA-binding proteins and that rG4detector is a novel useful tool for rG4 transcriptomics data analyses.

Indexed as

G-QuadruplexesRNA-Binding ProteinsStress GranulesDNA HelicasesPoly-ADP-Ribose Binding ProteinsRNARNA HelicasesRNA Recognition Motif ProteinsDNA HelicasesPoly-ADP-Ribose Binding ProteinsRNARNA-Binding ProteinsRNA HelicasesRNA Recognition Motif Proteins

Identifiers

PMID36350614
PMCPMC9723610
OpenAlexW4308616073

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.