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Functional genomics

Epigenomes get personal

Nature Reviews Genetics volume 24, page 346 (2023)Cite this article

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The EN-TEx resource comprises a uniformly processed dataset from 1,635 experiments, in which 15 functional genomic (epigenome, transcriptome and proteome) assays were applied to 30 tissues from four donors. Reads were mapped to donor-matched, phased diploid genomes assembled from long-read, linked-read and HiC sequencing to enable more precise quantification of differential gene expression and activity at regulatory elements. Mapping to a diploid genome also allowed for the direct visualization of single-nucleotide and structural variant impact on chromatin, thus creating comprehensive personal epigenomic maps across human tissues. The EN-TEx resource thus provides a detailed catalogue of allele-specific activity, which can be leveraged to develop deep learning models that analyse the biological impact of variants. For example, deep learning was able to predict allele-specific activity of single-nucleotide variants based on surrounding nucleotide sequence context (within a 250 bp window), with specific transcription-factor-binding motifs particularly sensitive to variation.

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  1. Nature Reviews Genetics http://www.nature.com/nrg/

    Linda Koch

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  1. Linda Koch
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Correspondence to Linda Koch.

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Koch, L. Epigenomes get personal. Nat Rev Genet 24, 346 (2023). https://doi.org/10.1038/s41576-023-00604-x

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  • DOI: https://doi.org/10.1038/s41576-023-00604-x

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