The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models
Joel S. RozowskyiD, Jiahao GaoiD, Beatrice BorsariiD, Yucheng YangiD, Timur R. GaleeviD, Gamze GürsoyiD, Charles B. EpsteiniD, Kun XiongiD, Jinrui XuiD, Tianxiao LiiD, Jason J. LiuiD, Keyang YuiD, Ana BertheliD, Zhanlin CheniD, Fábio C. P. NavarroiD, Maxwell S. Sun, James C. WrightiD, Justin ChangiD, Christopher J. F. CameroniD, Noam Shoresh FiD, Elizabeth GaskelliD, Jörg Drenkow, Jessika AdrianiD, Sergey S. AganezoviD, François AguetiD, , B BernsteiniD
Abstract
Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for [~]25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.
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