3D Enhancer-promoter networks provide predictive features for gene expression and coregulation in early embryonic lineages.


Journal

Nature structural & molecular biology
ISSN: 1545-9985
Titre abrégé: Nat Struct Mol Biol
Pays: United States
ID NLM: 101186374

Informations de publication

Date de publication:
05 Dec 2023
Historique:
received: 24 10 2022
accepted: 18 09 2023
medline: 6 12 2023
pubmed: 6 12 2023
entrez: 5 12 2023
Statut: aheadofprint

Résumé

Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages: the trophectoderm, the epiblast and the primitive endoderm. Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements through which transcriptional regulators enact these fates remain understudied. Here, we characterize, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observe extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although distinct groups of genes are irresponsive to topological changes. In each lineage, a high degree of connectivity, or 'hubness', positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a predictive model for transcriptional regulation (3D-HiChAT) that outperforms models using only 1D promoter or proximal variables to predict levels and cell-type specificity of gene expression. Using 3D-HiChAT, we identify, in silico, candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments, we validate several enhancers that control gene expression in their respective lineages. Our study identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to comprehensively understand lineage-specific transcriptional behaviors.

Identifiants

pubmed: 38053013
doi: 10.1038/s41594-023-01130-4
pii: 10.1038/s41594-023-01130-4
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.

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Auteurs

Dylan Murphy (D)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Physiology, Biophysics and Systems Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA.

Eralda Salataj (E)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

Dafne Campigli Di Giammartino (DC)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
3D Chromatin Conformation and RNA Genomics Laboratory, Center for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova, Italy.

Javier Rodriguez-Hernaez (J)

Department of Pathology, New York University Langone Health, New York, NY, USA.
Department of Medicine, New York University Langone Health, New York, NY, USA.
Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY, USA.

Andreas Kloetgen (A)

Department of Pathology, New York University Langone Health, New York, NY, USA.
Department of Medicine, New York University Langone Health, New York, NY, USA.
Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY, USA.

Vidur Garg (V)

Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA.

Erin Char (E)

Tri-Institutional Training Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, NY, USA.

Christopher M Uyehara (CM)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

Ly-Sha Ee (LS)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

UkJin Lee (U)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA.

Matthias Stadtfeld (M)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

Anna-Katerina Hadjantonakis (AK)

Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

Aristotelis Tsirigos (A)

Department of Pathology, New York University Langone Health, New York, NY, USA. Aristotelis.Tsirigos@nyulangone.org.
Department of Medicine, New York University Langone Health, New York, NY, USA. Aristotelis.Tsirigos@nyulangone.org.
Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY, USA. Aristotelis.Tsirigos@nyulangone.org.

Alexander Polyzos (A)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. app2001@med.cornell.edu.

Effie Apostolou (E)

Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA. efa2001@med.cornell.edu.

Classifications MeSH