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Enhancer RNA transcriptomics-wide association study reveals an atlas of pan-cancer susceptibility eRNAs

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE242322
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Increasing evidence has demonstrated that enhancer RNAs (eRNAs) play essential roles in human diseases. However, the complete identification of disease-related subsets of eRNAs remains a major challenge. Here, we construct an atlas of common and rare genetic variants influencing the expression of enhancer RNAs across 49 human tissues. We identify 11,757 eRNA quantitative trait loci (eRNA-QTLs) associated with the expression of 89.75% annotated eRNAs. Mechanically, eRNA-QTLs frequently altered the binding motifs of transcription factors and were further experimentally validated by CRISPR-based base editing. We also observed that 28.48% of cancer signals were co-localized with eRNA-QTLs. Utilizing our newly developed eRNA transcriptome-wide association study (eRNA-TWAS) model, we have effectively identified 259 cancer susceptibility eRNAs spanning 23 distinct cancer types. Notably, among the identified eRNAs, these eRNA-linked cancer susceptibility genes exhibit significant dependence across various cancer cell lines. Interestingly, cancer risk can be significantly influenced by rare functional variants that are linked to eRNAs with transcriptomic outliers. Additionally, we develop a comprehensive and flexible data portal for exploring the genetic underpinnings of eRNAs. Overall, this study reveals a systematic landscape of genetic dependencies on eRNAs across pan-cancers and significantly expands the pool of disease-associated eRNAs. Total RNA extracted from HEK293T cells was subjected to strand-specific RNA sequencing using the Illumina nova seq 6000 platform at Berry Genomics Co, Ltd (Beijing, China). Briefly, strand-specific RNA-Seq libraries were prepared by combining the Ribo-Zero rRNA Removal Kit (Epicentre, Madison, WI, USA) and the dUTP method to ensure strand specificity.
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2025-04-11
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