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Nested epistasis enhancer networks for robust genome regulation.
Lin, Xueqiu; Liu, Yanxia; Liu, Shuai; Zhu, Xiang; Wu, Lingling; Zhu, Yanyu; Zhao, Dehua; Xu, Xiaoshu; Chemparathy, Augustine; Wang, Haifeng; Cao, Yaqiang; Nakamura, Muneaki; Noordermeer, Jasprina N; La Russa, Marie; Wong, Wing Hung; Zhao, Keji; Qi, Lei S.
  • Lin X; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Liu Y; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Liu S; Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute NIH, Bethesda, MD 20892, USA.
  • Zhu X; Department of Statistics, Stanford University, Stanford, CA 94305, USA.
  • Wu L; Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA.
  • Zhu Y; Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA.
  • Zhao D; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Xu X; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Chemparathy A; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Wang H; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Cao Y; School of Medicine, Stanford University, Stanford, CA 94305, USA.
  • Nakamura M; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Noordermeer JN; Laboratory of Epigenome Biology, Systems Biology Center, National Heart, Lung and Blood Institute NIH, Bethesda, MD 20892, USA.
  • La Russa M; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Wong WH; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Zhao K; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA.
  • Qi LS; Department of Statistics, Stanford University, Stanford, CA 94305, USA.
Science ; 377(6610): 1077-1085, 2022 09 02.
Article en En | MEDLINE | ID: mdl-35951677
ABSTRACT
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning to define quantitative enhancer-enhancer interactions. We find that the ultralong distance enhancer network has a nested multilayer architecture that confers functional robustness of gene expression. Experimental characterization reveals that enhancer epistasis is maintained by three-dimensional chromosomal interactions and BRD4 condensation. Machine learning prediction of synergistic enhancers provides an effective strategy to identify noncoding variant pairs associated with pathogenic genes in diseases beyond genome-wide association studies analysis. Our work unveils nested epistasis enhancer networks, which can better explain enhancer functions within cells and in diseases.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Enfermedad / Elementos de Facilitación Genéticos / Epistasis Genética / Aprendizaje Automático Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Enfermedad / Elementos de Facilitación Genéticos / Epistasis Genética / Aprendizaje Automático Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article