biostudies-literatureRozowsky JNIMH NIH HHSNHGRI NIH HHSNCI NIH HHSNLM NIH HHS1493-1511.e40https://www.ebi.ac.uk/biostudies/studies/S-EPMC10074325biostudies-literatureUnknown186(7)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 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to vCellThe EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.PMC10074325R01 MH113005U54 HG006991UM1 HG009442R01 LM012736R01 MH101814U54 HG007004UM1 HG009390U24 HG009446U24 HG006620P30 CA045508R01 HG009318U24 HG009397U01 CA253481U24 HG009649Shi MZhang JFarid DSchreiber JMShi XWilliams BHitz BCMoore JEChhetri SBWright JArdlie KNusbaum CMendenhall EMKirsche MXu MSalichos LNoble WSRozowsky JStrattan JSCameron CJFXu JDanyko CCherry JMRamakrishnan SChoudhary JSedlazeck FJGerstein MYu LMeng RMortazavi AAdrian JSchatz MCYu KBalderrama-Gutierrez GWold BIssner RBorsari BLi BChang JAguet FGursoy GSun MSDavis CAScavelli AWerner JMyers RMRen BGofin YGingeras TRYang YTFarrell NPBerthel APratt HEKong XGorkin DUXiong KGillis JGao JCorona GBWang JMilosavljevic AQiu YDrenkow JChen ZHecht VZaleski CTanaka FYGu MWeng ZSherman RMMackiewicz MGaleev TLevine MEBernstein BENelson NLi XLi SLi TDobin ATan ZVlasova APopov IMudge JLam BRLiu JGuigo RSloan CAJiang YRaymond JLin KZGabdank ISee LHNavarro FShoresh NSnyder MPBanskota SChee SCortez Martins GCEpstein CBGaskell EAganezov SYan CLuo RfalseThe EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.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 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to v2023-01-01T00:00:00Z2023 Mar2026-05-28T21:51:57.562Z2025-04-05T23:17:44.379ZS-EPMC100743253700150610.1016/j.cell.2023.02.018