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The GENCODE CLS project: massively expanding the lncRNA catalog through capture long-read RNA sequencing
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The GENCODE CLS project: massively expanding the lncRNA catalog through capture long-read RNA sequencing

Tamara Perteghella, Gazaldeep Kaur, Sílvia Carbonell-Sala +53 more
January 2026
 ·
bioRxiv
 ·
DOI 
10.1101/2024.10.29.620654
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Why this is interesting

Achieving the largest expansion of human gene annotations since the genome was first sequenced, this work transforms the non-coding genome into a mappable regulatory landscape, linking millions of previously orphaned disease variants to defined lncRNA loci.

Author perspective

What is the most important insight, discovery, or finding from your paper that you would like other scientists to know?
“

A signifcat step towards completing the catalogue of all genes and transcripts in the human genome

”
Roderic Guigó

QED claims analysis

Summary

Capture Long-read Sequencing of orthologous regions in matched human and mouse tissues enabled the largest expansion of GENCODE gene annotations since the human genome was sequenced, adding 17,931 human and 22,784 mouse lncRNA genes that exhibit strong biological signals of functionality including genetic regulation, disease associations, and cell-type-specific expression patterns that enable identification of previously undetected cellular subtypes.

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Main Claim 1 –

Capture long-read sequencing doubles human and sextuples mouse lncRNA transcripts

Supporting evidence

  • Expanded GENCODE doubles non-GENCODE lncRNA database coverage to 29%
  • Orthologous capture raises human–mouse lncRNA orthologs to 25%
  • CLS discovers 8 human and 24 mouse protein-coding genes
  • Capture long-read sequencing improves pseudogene expression change detection sensitivity
Main Claim 2 –

Novel lncRNAs show functional genomic signals beyond transcriptional noise

Supporting evidence

  • Novel lncRNAs provide host transcripts for orphan miRNAs and snoRNAs
  • Novel lncRNAs frequently encode translated non-canonical ORFs
  • GENCODE lncRNAs project across primates, adding ~750,000 predicted genes
Main Claim 3 –

Novel lincRNAs are eQTL-regulated with distinct independent genetic control

Supporting evidence

  • Novel lncRNAs are differentially expressed in neurological disorders, including Alzheimer’s
Main Claim 4 –

Novel lncRNAs mark cell types and reveal 850 new clusters

Abstract

Accurate and complete gene annotations are indispensable for understanding how genome sequences encode biological functions. For more than twenty years, the GENCODE consortium has developed reference annotations for the human and mouse genomes, becoming a foundation for biomedical and genomics communities worldwide. Nevertheless, collections of important yet poorly-understood gene classes like long non-coding RNAs (lncRNAs) remain incomplete and scattered across multiple, uncoordinated catalogs. To address this, GENCODE has undertaken the most comprehensive lncRNA annotation effort to date. This is founded on the manually supervised computational annotation of full-length targeted long-read sequencing, on matched embryonic and adult tissues, of orthologous regions in human and mouse. Altogether 17,931 human genes (140,268 transcripts) and 22,784 mouse genes (136,169 transcripts) have been added to the GENCODE catalog representing a 2-fold and 6-fold growth in transcripts, respectively - the greatest increase in the number of annotated human genes since the sequencing of the human genome. Our targeted design assigned human-mouse orthologs at a rate beyond previous studies, tripling the number of human disease-associated lncRNAs that have mouse orthologs. Novel lncRNA genes consistently exhibit biological signals of functionality, and they greatly enhance the functional interpretability of the human genome. While poorly expressed in bulk RNA-Seq samples, many of them are highly expressed in specific cell populations, maybe even contributing to cell-type determination. The expanded GENCODE lncRNA annotations mark a critical step toward deciphering the human and mouse genomes.

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