Long-read Transcripts CLS long-read RNAs Track Settings
 
Capture long-seq long-read lncRNAs

Track collection: Transcripts and other data generated using long-read sequencing technology (PacBio and Oxford Nanopore)

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Description

These tracks represent the results of targeted long-read RNA sequencing aimed at identifying lowly expressed lncRNAs in adult and embryonic tissues. The track consists of capture target regions, mappings of pre- and post-capture reads, and transcript models built from the data.

Portions of this dataset were used to develop the lncRNA annotations introduced in GENCODE v47. The data are a superset of the data incorporated into GENCODE. The transcript models for a given RNA do not necessarily match those in GENCODE and are provided as a guide to exploring the sequencing data.

Detailed descriptions of the data are available at the GENCODE CLS Project site.

Display Conventions and Configuration

This is a multi-view composite track containing multiple data types (views). Each view includes subtracks that are displayed individually in the browser. Instructions for configuring multi-view tracks are here.

Views:

  • Targets: Capture target regions
  • Models: Transcript models generated from reads and merging
  • Sample models: Transcript models by sample in which they were observed
  • Per-experiment reads: Read mappings per experiment
  • Per-experiment Models: Transcript models generated from the experiments

Methods

This project, led by the GENCODE consortium, employed the Capture Long-read Sequencing (CLS) protocol to enrich transcripts from targeted genomic regions. It used a large capture array with orthologous probes in human and mouse genomes, targeting non-GENCODE lncRNA annotations and regions suspected of unannotated transcription. CapTrap-Seq, a cDNA library preparation protocol, was used to enrich for full-length RNA molecules (5′ to 3′).

Matched adult and embryonic tissues from human and mouse were selected to maximize transcriptome complexity. Libraries were sequenced pre- and post-capture using PacBio and Oxford Nanopore Technologies (ONT) long-read platforms, as well as short-read technologies.

Transcript isoform models were built from reads using the LyRic analysis software. These were merged using intron chains, with transcription start and end sites anchored using CAGE and poly(A) data.

Credits

This dataset was developed by the Guigó Lab, Centre for Genomic Regulation (CRG) and the GENCODE consortium.
The track set was constructed by Sílvia Carbonell-Sala, Andrea Tanzer, and Mark Diekhans.

References

Kaur G, Perteghella T, Carbonell-Sala S, Gonzalez-Martinez J, Hunt T, MÄ…dry T, Jungreis I, Arnan C, Lagarde J, Borsari B et al. GENCODE: massively expanding the lncRNA catalog through capture long-read RNA sequencing. bioRxiv. 2024 Oct 31;. PMID: 39554180; PMC: PMC11565817

Mudge JM, Carbonell-Sala S, Diekhans M, Martinez JG, Hunt T, Jungreis I, Loveland JE, Arnan C, Barnes I, Bennett R et al. GENCODE 2025: reference gene annotation for human and mouse. Nucleic Acids Res. 2025 Jan 6;53(D1):D966-D975. PMID: 39565199; PMC: PMC11701607

Pardo-Palacios FJ, Wang D, Reese F, Diekhans M, Carbonell-Sala S, Williams B, Loveland JE, De María M, Adams MS, Balderrama-Gutierrez G et al. Systematic assessment of long-read RNA-seq methods for transcript identification and quantification. Nat Methods. 2024 Jul;21(7):1349-1363. PMID: 38849569; PMC: PMC11543605

Carbonell-Sala S, Perteghella T, Lagarde J, Nishiyori H, Palumbo E, Arnan C, Takahashi H, Carninci P, Uszczynska-Ratajczak B, Guigó R. CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing. Nat Commun. 2024 Jun 27;15(1):5278. PMID: 38937428; PMC: PMC11211341

LyRic: Long RNA-seq analysis workflow https://github.com/guigolab/LyRic