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Researchers created a comprehensive multi-omic atlas by profiling gene expression and chromatin accessibility in nearly 460,000 individual cell nuclei from 21 different adult human tissues across four donors. The study identified over 1 million potential regulatory DNA elements, including more than 160,000 not previously documented, and mapped how these elements control gene expression across different cell types and tissues. Using machine learning models trained on this data, the team predicted functional effects for over 548,000 genetic variants associated with disease risk, identifying nearly 20,000 variants likely to have significant regulatory impacts.
Why it matters
This atlas provides a critical resource for understanding how non-coding genetic variants contribute to disease risk by linking regulatory DNA elements to gene expression across diverse human tissues. The computational models enable researchers to predict which genetic variants are most likely to affect gene regulation in specific cell types, potentially accelerating identification of disease mechanisms and therapeutic targets.
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⚠️ Preprint – Noch nicht peer-reviewed
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Diverse human cell types establish specialized functions through lineage- and context-specific regulatory programs. Interpreting non-coding genetic risk requires integrated multi-omic reference maps that directly connect regulatory DNA to cellular expression across human tissues. Here we present a single-nucleus multi-omic atlas comprising 459,856 transcriptomic and chromatin accessibility profiles from 21 adult human tissues and four donors, including paired measurements from 160,688 nuclei. The atlas resolves nine cell lineages, 61 broad cell types and 313 subclusters, and identifies 1,085,062 candidate cis-regulatory elements (cCREs), including 161,270 novel elements absent from ENCODE. Regulatory activity was dominated by cell identity but refined by tissue context. Joint profiling enabled 871,177 cCRE-gene associations and revealed lineage-specific regulatory architectures. Cross-tissue accessibility further identified lineage-restricted and constitutively inaccessible chromatin domains, the latter showing preferential hypomethylation across human cancers. Furthermore, we leverage this dataset to train sequence-to-function models to predict chromatin-accessibility effects for 548,656 fine-mapped variants, identifying 18,133 high-effect variants, including 1,120 broadly active variants. Models trained for eight endothelial subtypes further resolve predicted variant effects across vascular beds. Together, this atlas provides a comprehensive cellular and computational framework for interpreting regulatory sequence, context-dependent gene control, and complex trait genetics across the human body.
Source: A single-nucleus multi-omic atlas of gene regulation across 21 adult human tissues