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We thank the Guigo laboratory for their valuable input and help with sample handling. Special thanks are extended to the members of Uszczynska's lab, in particular Monika Kwiatkowska, Marta Blangiewicz, and Tomasz Madry for their valuable input and assistance in data analysis and figure preparation. We also thank the GENCODE experimental group for their valuable input and discussion, in particular A. Frankish, J.Mudge (EBI, UK) and Rory Johnson (UCD, Ireland), and also thanks to the entire GENCODE group, in particular, M.Diekhans (UCSC, US). We would like to acknowledge the CRG Genomics Unit for assistance with short-read Illumina sequencing and the NGS Sequencing Core facility headed by S. Goodwin for their assistance in generating PacBio Sequel I and Sequel II data. This work and its publication were supported by the National Human Genome Research Institute of the US National Institutes of Health grant (2U24HG007234-09 to R.G.) and the National Science Center PL grant (2018/31/B/NZ2/01940 to B.U.-R.). We acknowledge the support of the Spanish Ministry of Science and Innovation to the EMBL partnership, Centro de Excelencia Severo Ochoa and CERCA Program/Generalitat de Catalunya. We thank R. Garrido Enamorado and R. Carbonell Garcia (CRG), as well as K. Solka and A. Chmielewska (IBCH PAS) for administrative support. Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing

Publicated to:Nature Communications. 15 (1): 5278- - 2024-06-27 15(1), DOI: 10.1038/s41467-024-49523-3

Authors: Carbonell-Sala, S; Perteghella, T; Lagarde, J; Nishiyori, H; Palumbo, E; Arnan, C; Takahashi, H; Carninci, P; Uszczynska-Ratajczak, B; Guigó, R

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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. Long-read RNA sequencing has the potential to support exhaustive annotation of eukaryotic genomes, but reliable end-to-end sequencing is still challenging. Here the authors report a method called CapTrap-seq which combines the cap-trapping strategy with oligo(dT) priming for precise full-length transcript detection.

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