The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models

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  • dc.contributor.author Rozowsky, Joel
  • dc.contributor.author Borsari, Beatrice, 1992-
  • dc.contributor.author Guigó Serra, Roderic
  • dc.contributor.author Gerstein, Mark B.
  • dc.date.accessioned 2023-05-23T10:33:04Z
  • dc.date.available 2023-05-23T10:33:04Z
  • dc.date.issued 2023
  • dc.description.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 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 variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Rozowsky J, Gao J, Borsari B, Yang YT, Galeev T, Gürsoy G, et al. The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models. Cell. 2023 Mar 30;186(7):1493-1511.e40. DOI: 10.1016/j.cell.2023.02.018
  • dc.identifier.doi http://dx.doi.org/10.1016/j.cell.2023.02.018
  • dc.identifier.issn 0092-8674
  • dc.identifier.uri http://hdl.handle.net/10230/56942
  • dc.language.iso eng
  • dc.publisher Elsevier
  • dc.relation.ispartof Cell. 2023 Mar 30;186(7):1493-1511.e40
  • dc.rights © 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword Personal genome
  • dc.subject.keyword Allele-specific activity
  • dc.subject.keyword Functional epigenomes
  • dc.subject.keyword Predictive models
  • dc.subject.keyword eQTLs
  • dc.subject.keyword Genome annotations
  • dc.subject.keyword Transformer model
  • dc.subject.keyword Functional genomics
  • dc.subject.keyword ENCODE
  • dc.subject.keyword GTEx
  • dc.subject.keyword Structural variants
  • dc.subject.keyword Tissue specificity
  • dc.title The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion