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 VM36. 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. Note that GENCODE VM36 is released on GRCm39/mm39 while these tracks are on GRCm38/mm10.
Detailed descriptions of the data are available at the GENCODE CLS Project site.
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:
Model Color Coding
Model annotations are color-coded based on their incorporation into GENCODE VM36 and the assigned GENCODE VM36 BioType. Note that VM36 is not on the mm10 assembly.
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.
Data and metadata is discoverable via Array Express entry E-MTAB-14562
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.
Kaur G, Perteghella T, Carbonell-Sala S, Gonzalez-Martinez J, Hunt T, Mądry 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