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The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.
Rozowsky, Joel; Gao, Jiahao; Borsari, Beatrice; Yang, Yucheng T; Galeev, Timur; Gürsoy, Gamze; Epstein, Charles B; Xiong, Kun; Xu, Jinrui; Li, Tianxiao; Liu, Jason; Yu, Keyang; Berthel, Ana; Chen, Zhanlin; Navarro, Fabio; Sun, Maxwell S; Wright, James; Chang, Justin; Cameron, Christopher J F; Shoresh, Noam; Gaskell, Elizabeth; Drenkow, Jorg; Adrian, Jessika; Aganezov, Sergey; Aguet, François; Balderrama-Gutierrez, Gabriela; Banskota, Samridhi; Corona, Guillermo Barreto; Chee, Sora; Chhetri, Surya B; Cortez Martins, Gabriel Conte; Danyko, Cassidy; Davis, Carrie A; Farid, Daniel; Farrell, Nina P; Gabdank, Idan; Gofin, Yoel; Gorkin, David U; Gu, Mengting; Hecht, Vivian; Hitz, Benjamin C; Issner, Robbyn; Jiang, Yunzhe; Kirsche, Melanie; Kong, Xiangmeng; Lam, Bonita R; Li, Shantao; Li, Bian; Li, Xiqi; Lin, Khine Zin.
Afiliación
  • Rozowsky J; Section on Biomedical Informatics and Data Science, Yale University, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Gao J; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Borsari B; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain.
  • Yang YT; Institute of Science and Technology for Brain-Inspired Intelligence; MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence; MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China; Program in Computational Biology and Bioinformatics, Yale Universit
  • Galeev T; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Gürsoy G; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Epstein CB; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Xiong K; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Xu J; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Li T; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Liu J; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Yu K; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
  • Berthel A; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Chen Z; Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
  • Navarro F; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Sun MS; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Wright J; Institute of Cancer Research, London, UK.
  • Chang J; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Cameron CJF; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Shoresh N; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Gaskell E; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Drenkow J; Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
  • Adrian J; Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
  • Aganezov S; Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA.
  • Aguet F; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Balderrama-Gutierrez G; Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA.
  • Banskota S; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Corona GB; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Chee S; Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA.
  • Chhetri SB; HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA.
  • Cortez Martins GC; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Danyko C; Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
  • Davis CA; Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
  • Farid D; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Farrell NP; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Gabdank I; Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
  • Gofin Y; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
  • Gorkin DU; Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA.
  • Gu M; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Hecht V; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Hitz BC; Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
  • Issner R; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Jiang Y; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Kirsche M; Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA.
  • Kong X; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Lam BR; Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
  • Li S; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Li B; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
  • Li X; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
  • Lin KZ; Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA.
Cell ; 186(7): 1493-1511.e40, 2023 03 30.
Article en En | MEDLINE | ID: mdl-37001506
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 × âˆ¼15 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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Sitios de Carácter Cuantitativo / Epigenoma Tipo de estudio: Prognostic_studies Idioma: En Revista: Cell Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Sitios de Carácter Cuantitativo / Epigenoma Tipo de estudio: Prognostic_studies Idioma: En Revista: Cell Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos