Long-read transcriptomics of a diverse human cohort reveals ancestry bias in gene annotation
Accurate gene annotations are fundamental for interpreting genetic variation, cellular function, and disease mechanisms. However, current human gene annotations are largely derived from transcriptomic data of individuals with European ancestry, leaving gaps of annotation that remain uncharacterized. Here, we generate over 800 million full-length reads with long-read RNA-seq in 43 lymphoblastoid cell line samples from eight genetically-diverse human populations and build a cross-ancestry gene annotation. We demonstrate that transcripts from non-European samples are underrepresented in reference gene annotations, leading to incomplete characterization in allele-specific transcript usage. Furthermore, we show that personal genome assemblies enhance transcript discovery compared to the generic GRCh38 reference assembly, even though genomic regions unique to each individual are heavily depleted of genes. These findings underscore the urgent need for a more inclusive gene annotation framework that accurately represents global transcriptome diversity.
Authors
- Emilio Palumbo (ORCID: https://orcid.org/0000-0003-4599-8161)
- Carme Arnan (ORCID: https://orcid.org/0000-0002-7431-2088)
- Winona Oliveros (ORCID: https://orcid.org/0000-0002-3646-8874)
- Roderic Guigó (ORCID: https://orcid.org/0000-0002-5738-4477)
- Sílvia Carbonell Sala (ORCID: https://orcid.org/0000-0001-7956-6215)
- Fairlie Reese (ORCID: https://orcid.org/0000-0002-9240-0102)
- Marta Melé (ORCID: https://orcid.org/0000-0001-8874-6453)
- Fabien Degalez (ORCID: https://orcid.org/0000-0001-8252-6425)
- Tamara Perteghella (ORCID: https://orcid.org/0000-0001-7073-6361)
- Pau Clavell-Revelles (ORCID: https://orcid.org/0009-0003-1269-293X)
Institutions
- Universitat Pompeu Fabra (ES)
- Barcelona Supercomputing Center (ES)
- Centre for Genomic Regulation (ES)
- Universitat de Barcelona (ES)
- Universitat Politècnica de Catalunya (ES)
Publication Details
- Journal
- Nature Communications
- Published
- 2025-12-03
- DOI
- https://doi.org/10.1038/s41467-025-66096-x
- Citations
- 2
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 3.63
Funders
- California Institute of Technology
- Fundació la Marató de TV3
- Wellcome Trust
- European Molecular Biology Laboratory
- Ministerio de Ciencia, Innovación y Universidades
- Centres de Recerca de Catalunya
- Centre de Regulació Genòmica
- European Commission
- Generalitat de Catalunya
- Ministerio de Ciencia e Innovación
- Universitat de Barcelona
- Barcelona Supercomputing Center
- National Institutes of Health
- Agencia Estatal de Investigación
- European Social Fund