CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Carbonell Sala, Silvia
- dc.contributor.author Perteghella, Tamara
- dc.contributor.author Lagarde, Julien
- dc.contributor.author Nishiyori, Hiromi
- dc.contributor.author Palumbo, Emilio
- dc.contributor.author Arnan Ros, Carme
- dc.contributor.author Takahashi, Hazuki
- dc.contributor.author Carninci, Piero
- dc.contributor.author Uszczynska-Ratajczak, Barbara
- dc.contributor.author Guigó Serra, Roderic
- dc.date.accessioned 2024-09-17T06:24:32Z
- dc.date.available 2024-09-17T06:24:32Z
- dc.date.issued 2024
- dc.description.abstract Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we develop CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5' capped, full-length transcripts. In our study, we evaluate the performance of CapTrap-seq alongside other widely used RNA-seq library preparation protocols in human and mouse tissues, employing both ONT and PacBio sequencing technologies. To explore the quantitative capabilities of CapTrap-seq and its accuracy in reconstructing full-length RNA molecules, we implement a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5'cap formation. Our benchmarks, incorporating the Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) data, demonstrate that CapTrap-seq is a competitive, platform-agnostic RNA library preparation method for generating full-length transcript sequences.
- dc.format.mimetype application/pdf
- dc.identifier.citation Carbonell-Sala S, Perteghella T, Lagarde J, Nishiyori H, Palumbo E, Arnan C, et al. CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing. Nat Commun. 2024 Jun 27;15(1):5278. DOI: 10.1038/s41467-024-49523-3
- dc.identifier.doi http://dx.doi.org/10.1038/s41467-024-49523-3
- dc.identifier.issn 2041-1723
- dc.identifier.uri http://hdl.handle.net/10230/61112
- dc.language.iso eng
- dc.publisher Nature Research
- dc.relation.ispartof Nat Commun. 2024 Jun 27;15(1):5278
- dc.rights © The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.keyword Data processing
- dc.subject.keyword Genomics
- dc.subject.keyword RNA sequencing
- dc.subject.keyword Transcriptomics
- dc.title CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion