Evidence map›Paper›PMID 37377445›Full record

ArticleNucleic acids research2023

Direct m6A recognition by IMP1 underlays an alternative model of target selection for non-canonical methyl-readers.

Giuseppe Nicastro, Giancarlo Abis, Pierre Klein, Sofia Esteban-Serna, Christopher Gallagher, Belen Chaves-Arquero, Yuyang Cai, Angelo Miguel Figueiredo, Stephen R Martin, Rickie Patani and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.4field-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

16 citing papers in PubMed, 22 citations in OpenAlex.

  1. mNature reviews. Neuroscience · 2026
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  7. Marked for Success: How RNA mCellular and molecular gastroenterology and hepatology · 2026
    Review
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  11. Review
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  15. Review
  16. Interconnections between mLife science alliance · 2024
    Review
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

12 authors at 2 institutions in 1 country.

Giuseppe NicastroMacromolecular Structure Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.
Giancarlo AbisDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.
Pierre KleinDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.
Sofia Esteban-SernaDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.ORCID 0000-0002-8770-3264
Christopher GallagherDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.
Belen Chaves-ArqueroDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.
Yuyang CaiDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.
Angelo Miguel FigueiredoDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.ORCID 0000-0001-7039-5341
Stephen R MartinStructural Biology Technology Platform, The Francis Crick Institute, 1 Midland Rd, London NW1 1AT, UK.
Rickie PataniHuman Stem Cells and Neurodegeneration Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.ORCID 0000-0002-3825-7675
Ian A TaylorMacromolecular Structure Laboratory, The Francis Crick Institute, 1 Midland Road, London NW1 1AT, UK.ORCID 0000-0002-6763-3852
Andres RamosDivision of Biosciences, Institute of Structural and Molecular Biology, University College London, London, UK.ORCID 0000-0002-9295-8042
Institute of Structural and Molecular Biology · GBThe Francis Crick Institute · GB

Funding

TRD3 NMRbox: Bayesian AnalyticsP41GM111135 · NIGMS · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · PI HOCH, JEFFREY C · 2015 to 2024
$14.0M
Biotechnology and Biological Sciences Research Council S0114438/1Cancer Research UK CC1078Cancer Research UK CC2029Medical Research Council MR/S000305/1Medical Research Council MR/S006591/1Medical Research Council S000305/1NIGMS NIH HHS P41 GM111135Wellcome Trust CC1078Wellcome Trust CC2029
6 · The paper itself

Abstract

m6A methylation provides an essential layer of regulation in organismal development, and is aberrant in a range of cancers and neuro-pathologies. The information encoded by m6A methylation is integrated into existing RNA regulatory networks by RNA binding proteins that recognise methylated sites, the m6A readers. m6A readers include a well-characterised class of dedicated proteins, the YTH proteins, as well as a broader group of multi-functional regulators where recognition of m6A is only partially understood. Molecular insight in this recognition is essential to build a mechanistic understanding of global m6A regulation. In this study, we show that the reader IMP1 recognises the m6A using a dedicated hydrophobic platform that assembles on the methyl moiety, creating a stable high-affinity interaction. This recognition is conserved across evolution and independent from the underlying sequence context but is layered upon the strong sequence specificity of IMP1 for GGAC RNA. This leads us to propose a concept for m6A regulation where methylation plays a context-dependent role in the recognition of selected IMP1 targets that is dependent on the cellular concentration of available IMP1, differing from that observed for the YTH proteins.

Indexed as

Avian ProteinsRNA-Binding ProteinsAdenosineAnimalsChickensMethylationProtein Processing, Post-TranslationalProteinsRNAAdenosineAvian ProteinsProteinsRNARNA-Binding Proteins

Identifiers

PMID37377445
PMCPMC10484666
OpenAlexW4382344794

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.