Mapping the evolving landscape of super-enhancers during cell differentiation.
Yan Kai,Bin E. Li,Ming Zhu,Grace Y Li,Fei Chen,Yingli Han,Hye Ji Cha,Stuart H. Orkin,Stuart H. Orkin,Wenqing Cai,Jialiang Huang,Guo-Cheng Yuan,Guo-Cheng Yuan +12 more
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TLDR
In this paper, an unbiased approach was developed to systematically analyze the evolving landscape of super-enhancers during cell differentiation in multiple lineages, and the authors discovered a general trend where superenhancers emerge through three distinct temporal patterns: conserved, temporally hierarchical, and de novo.Abstract:
Background Super-enhancers are clusters of enhancer elements that play critical roles in the maintenance of cell identity. Current investigations on super-enhancers are centered on the established ones in static cell types. How super-enhancers are established during cell differentiation remains obscure. Results Here, by developing an unbiased approach to systematically analyze the evolving landscape of super-enhancers during cell differentiation in multiple lineages, we discover a general trend where super-enhancers emerge through three distinct temporal patterns: conserved, temporally hierarchical, and de novo. The three types of super-enhancers differ further in association patterns in target gene expression, functional enrichment, and 3D chromatin organization, suggesting they may represent distinct structural and functional subtypes. Furthermore, we dissect the enhancer repertoire within temporally hierarchical super-enhancers, and find enhancers that emerge at early and late stages are enriched with distinct transcription factors, suggesting that the temporal order of establishment of elements within super-enhancers may be directed by underlying DNA sequence. CRISPR-mediated deletion of individual enhancers in differentiated cells shows that both the early- and late-emerged enhancers are indispensable for target gene expression, while in undifferentiated cells early enhancers are involved in the regulation of target genes. Conclusions In summary, our analysis highlights the heterogeneity of the super-enhancer population and provides new insights to enhancer functions within super-enhancers.read more
Citations
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Inner nuclear protein Matrin-3 coordinates cell differentiation by stabilizing chromatin architecture.
Hye Ji Cha,Özgün Uyan,Yan Kai,Tianxin Liu,Qian Zhu,Zuzana Tothova,Zuzana Tothova,Zuzana Tothova,Giovanni A. Botten,Jian Xu,Guo-Cheng Yuan,Job Dekker,Stuart H. Orkin,Stuart H. Orkin +13 more
TL;DR: In this paper, the role of Matrin-3 (Matr3) in erythroid cells was investigated and it was shown that loss of the nuclear scaffolding protein leads to morphological and gene expression changes characteristic of accelerated maturation.
Journal ArticleDOI
A Novel Defined Super-Enhancer Associated Gene Signature to Predict Prognosis in Patients With Diffuse Large B-Cell Lymphoma
Hong Xu,Yuhang Li,Yanan Jiang,Jinhuan Wang,Huiyong Sun,Yangyang Lv,Su Liu,Yixin Zhai,Lin-Lin Tian,Lanfang Li,Zhen Zhao +10 more
TL;DR: A novel and reliable SE-associated-gene signature that can effectively classify DLBCL patients into high-risk and low-risk groups in terms of overall survival was developed, which may assist clinicians in the treatment ofDLBCL.
Journal ArticleDOI
Single-cell chromatin accessibility identifies enhancer networks driving gene expression during spinal cord development in mouse.
Muya Shu,Danni Hong,Hongli Lin,Jixiang Zhang,Zhengnan Luo,Yi Du,Zheng Sun,Man Yin,Yan-qing Yin,Lifang Liu,Shilai Bao,Zhiyong Liu,Falong Lu,Jialiang Huang,Jianwu Dai +14 more
TL;DR: In this paper , single-cell chromatin accessibility landscapes in mouse neural tubes spanning embryonic days 9.5-13.5 were profiled and a novel computational method, eNet, was applied to build enhancer networks.
Posted ContentDOI
Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis
TL;DR: ENet is introduced, a computational method to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles and outperforms the existing models in predicting cell identity and disease genes, such as super-enhancer and enhancer cluster.
Journal ArticleDOI
OUP accepted manuscript
TL;DR: In this article , the authors proposed a method to identify differential super enhancers by weighting the combinatorial effects of constituent-enhancer activities and locations (i.e. internal dynamics).
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