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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Long-read transcriptomics of a diverse human cohort reveals widespread ancestry bias in gene annotation

ABSTRACT: Understanding gene expression diversity across human populations is essential for accurate genome annotation and disease interpretation. However, existing annotations are primarily based on European-derived transcriptomic data, potentially limiting their applicability to other populations. This study aims to assess population-specific transcript diversity and its impact on gene annotation. To achieve this, we performed long-read RNA sequencing on lymphoblastoid cell lines from 43 individuals across eight globally diverse populations. Our workflow included RNA extraction, cDNA synthesis, and sequencing using Oxford Nanopore long-read technology, followed by transcript assembly and comparison with existing gene annotations. We also integrated novel transcripts into reference annotations to evaluate their effect on allele-specific transcript usage detection. This work provides a critical step toward improving transcriptome annotation across diverse populations, ensuring a more comprehensive representation of human genetic variation. We provide here unprocessed, unaligned BAMs (just basecalled; uploaded file names end with *.bam) along with (ONT duplex read resolution, chimeric read splitting, UMI-based deduplication, adapter trimming, and basecalling quality >= 10; uploaded file names end with *preprocessed_Q10.fastq.gz) for each sample.

INSTRUMENT(S): GridION

ORGANISM(S): Homo sapiens

SUBMITTER: Pau Clavell-Revelles

PROVIDER: E-MTAB-14935 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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