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Analysis of institutional authors

Cruciani, SoniaFirst authorDelgado-Tejedor, AnnaFirst authorPryszcz, Leszek PCorresponding AuthorMedina, RebecaAuthorLlovera, LaiaAuthorNovoa, Eva MariaCorresponding Author

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March 11, 2025
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De novo basecalling of RNA modifications at single molecule and nucleotide resolution

Publicated to: Genome Biology. 26 (1): 38- - 2025-02-25 26(1), DOI: 10.1186/s13059-025-03498-6

Authors:

Cruciani, S; Delgado-Tejedor, A; Pryszcz, LP; Medina, R; Llovera, L; Novoa, EM
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Affiliations

Barcelona Inst Sci & Technol, Ctr Genom Regulat CRG, Dr Aiguader 88, Barcelona 08003, Spain - Author
ICREA, Pg Lluis Co 23, Barcelona, Spain - Author
Univ Pompeu Fabra UPF, Barcelona, Spain - Author
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Abstract

RNA modifications influence RNA function and fate, but detecting them in individual molecules remains challenging for most modifications. Here we present a novel methodology to generate training sets and build modification-aware basecalling models. Using this approach, we develop the m6ABasecaller, a basecalling model that predicts m6A modifications from raw nanopore signals. We validate its accuracy in vitro and in vivo, revealing stable m6A modification stoichiometry across isoforms, m6A co-occurrence within RNA molecules, and m6A-dependent effects on poly(A) tails. Finally, we demonstrate that our method generalizes to other RNA and DNA modifications, paving the path towards future efforts detecting other modifications.
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Keywords

BasecallingCell fateM6Machine learningMessenger-rnaN6-methyladenosineNanopore sequencingNative rnaNuclear-rnaProteinsRevealsRna modificationsSingle molecule resolutioTraining dataTranslation

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal GENOME BIOLOGY due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2025, it was in position 7/192, thus managing to position itself as a Q1 (Primer Cuartil), in the category Genetics & Heredity. Notably, the journal is positioned above the 90th percentile.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-07:

  • WoS: 9
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-07:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 26.
  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 26 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 15.
  • The number of mentions on the social network X (formerly Twitter): 16 (Altmetric).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
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Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Cruciani, Sonia) and Last Author (NOVOA PARDO, EVA MARIA).

the authors responsible for correspondence tasks have been Pryszcz, LESZEK PIOTR and NOVOA PARDO, EVA MARIA.

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Awards linked to the item

We thank all the members of the Novoa lab for their insightful discussions. We acknowledge support of the Spanish Ministry of Science and Innovation through the Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/501100011033), and the Generalitat de Catalunya through the CERCA programme and to the EMBL partnership. We are grateful to the CRG Core Technologies Programme for their support and assistance in this work. In particular, we would like to thank the CRG Scientific Information Technologies (SIT) facility for setting up the GPU cluster and continuously upgrading the corresponding software that was needed to benchmark the software using diverse Guppy and CUDA versions. We also thank the CRG Tissue Engineering Facility for their help in establishing the tamoxifen-inducible METTL3 knockout cell lines. We thank STORM Therapeutics for sharing the STM2457 METTL3 inhibitor.
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