ArticleNature communications2025
Long-read transcriptomics of a diverse human cohort reveals ancestry bias in gene annotation.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- The novel transcripts we keep rediscovering.Nature biotechnology · 2026Article
- Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms.Nature communications · 2026Article
- Mapping the path to clinical implementation of multi-omics.Nature genetics · 2026Review
- SpliSync: Genomic language model-driven splice site correction of long RNA sequencing reads.bioRxiv : the preprint server for biology · 2026Article
- Foundation models in omics research: a comprehensive survey.Briefings in bioinformatics · 2026Review
- African Pan Genome Contigs Expose Biologically Relevant Sequence Still Hidden from Human Reference Frameworks.bioRxiv : the preprint server for biology · 2026Article
- Population-scale interpretation of RNA isoform diversity enabled by Isopedia.bioRxiv : the preprint server for biology · 2026Article
- Article
- Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms.bioRxiv : the preprint server for biology · 2025Article
- Long-read transcriptomics of a diverse human cohort reveals ancestry bias in gene annotation.Nature communications · 2025Article
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10 authors.
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Abstract
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.
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