scholarly journals Global Mapping of H3K4me1 and H3K4me3 Reveals the Chromatin State-Based Cell Type-Specific Gene Regulation in Human Treg Cells

PLoS ONE ◽  
2011 ◽  
Vol 6 (11) ◽  
pp. e27770 ◽  
Author(s):  
Yi Tian ◽  
Zhengcai Jia ◽  
Jun Wang ◽  
Zemin Huang ◽  
Jun Tang ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Treg Cells ◽  
Chromatin State ◽  
Specific Gene ◽  
Cell Type ◽  
Global Mapping ◽  
Cell Type Specific

scholarly journals FIREcaller: Detecting Frequently Interacting Regions from Hi-C Data

2019 ◽  
Author(s):  
Cheynna Crowley ◽  
Yuchen Yang ◽  
Yunjiang Qiu ◽  
Benxia Hu ◽  
Armen Abnousi ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Spatial Organization ◽  
R Package ◽  
Specific Gene ◽  
List Type ◽  
Cell Type ◽  
R Software ◽  
Computational Tools ◽  
Cell Type Specific ◽  
User Friendly

AbstractHi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We have recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from Hi-C data are still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package for detecting FIREs from Hi-C data. FIREcaller takes raw Hi-C contact matrices as input, performs within-sample and cross-sample normalization, and outputs continuous FIRE scores, dichotomous FIREs, and super-FIREs. Applying FIREcaller to Hi-C data from various human tissues, we demonstrate that FIREs and super-FIREs identified, in a tissue-specific manner, are closely related to gene regulation, are enriched for enhancer-promoter (E-P) interactions, tend to overlap with regions exhibiting epigenomic signatures of cis-regulatory roles, and aid the interpretation or GWAS variants. The FIREcaller package is implemented in R and freely available at https://yunliweb.its.unc.edu/FIREcaller.Highlights– Frequently Interacting Regions (FIREs) can be used to identify tissue and cell-type-specific cis-regulatory regions.– An R software, FIREcaller, has been developed to identify FIREs and clustered FIREs into super-FIREs.

Identification of the mouse neurochondrin promoter region and the responsible region for cell type specific gene regulation

2004 ◽  
Vol 356 (2) ◽  
pp. 107-110 ◽  
Author(s):  
Minori Dateki ◽  
Reiko Mochizuki ◽  
Kazuyuki Yanai ◽  
Akiyoshi Fukamizu
Keyword(s):  
Gene Regulation ◽  
Promoter Region ◽  
Specific Gene ◽  
Cell Type ◽  
Cell Type Specific

scholarly journals A new class of constitutively active super-enhancers is associated with fast recovery of 3D chromatin loops

2018 ◽  
Author(s):  
Jayoung Ryu ◽  
Hyunwoong Kim ◽  
Dongchan Yang ◽  
Andrew J. Lee ◽  
Inkyung Jung
Keyword(s):  
Gene Regulation ◽  
Comprehensive Analysis ◽  
Specific Gene ◽  
Cell Type ◽  
Chromatin Loops ◽  
New Class ◽  
Genome Regulation ◽  
Super Enhancer ◽  
Cell Tissue ◽  
Cell Type Specific

AbstractSuper-enhancers or stretch enhancers are clusters of active enhancers that often coordinate cell-type specific gene regulation. However, little is known about the function of super-enhancers beyond gene regulation. In this study, through a comprehensive analysis of super-enhancers in 30 human cell/tissue types, we identified a new class of super-enhancers which are constitutively active across most cell/tissue types. These ‘common’ super-enhancers are associated with universally highly expressed genes in contrast to the canonical definition of super-enhancers that assert cell-type specific gene regulation. In addition, the genome sequence of these super-enhancers is highly conserved by evolution and among humans, advocating their universal function in genome regulation. Integrative analysis of 3D chromatin loops demonstrates that, in comparison to the cell-type specific super-enhancers, the cell-type common super-enhancers present a striking association with rapidly recovering loops. We propose that a new class of super-enhancers may play an important role in the early establishment of 3D chromatin structure.BackgroundSuper-enhancers or stretch enhancers are defined by a strong enrichment of mediators and transcription-regulating proteins, appearing to play a deterministic role in cellular identity by controlling the expression of cell-type specific genes[1, 2]. Previous studies have revealed the critical function of super-enhancers during development and differentiation[3]. The enrichment of disease-associated single nucleotide polymorphism (SNP) in super-enhancers compared to that of typical enhancers proposed a substantial link between super-enhancers and many complex human diseases[2]. In addition, a set of recent studies have proposed potential functions of super-enhancers in the extremely long-range chromatin communications and the establishment of 3D chromatin loops[4]. These results suggest a more universal role of super-enhancers in genome regulation apart from cell-type specific gene regulation, but little is known about the mechanisms underlying these various functions. To extend the current knowledge of super-enhancers and their biological roles, we conducted a comprehensive analysis of super-enhancer activities across 30 human cell/tissue types. Our analysis suggests that a substantial number of super-enhancers exhibits prevalent activities across cell-types in terms of H3K27ac signals, and that these non-canonical super-enhancers are involved in the formation of fast recovering chromatin loops.NoteA genome browser session has been set up for visualization of the super-enhancer domains described in the current study– https://genome.ucsc.edu/cgi-bin/hgTracks?hgS-doOtherUser=submit&hgS-otherUserName=abundantiavosliberabit&hgS-otherUserSessionName=SuperEnhancerDomain

scholarly journals Unique ERα Cistromes Control Cell Type-Specific Gene Regulation

2008 ◽  
Vol 22 (11) ◽  
pp. 2393-2406 ◽  
Author(s):  
Susan A. Krum ◽  
Gustavo A. Miranda-Carboni ◽  
Mathieu Lupien ◽  
Jerome Eeckhoute ◽  
Jason S. Carroll ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Control Cell ◽  
Specific Gene ◽  
Cell Type ◽  
Cell Type Specific

scholarly journals Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm

2021 ◽  
Vol 119 (1) ◽  
pp. e2115601119
Author(s):  
Shining Ma ◽  
Xi Chen ◽  
Xiang Zhu ◽  
Philip S. Tsao ◽  
Wing Hung Wong
Keyword(s):  
Gene Regulation ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Regulatory Networks ◽  
Cell Types ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Cell Type ◽  
Abdominal Aortic ◽  
Cell Type Specific

Abdominal aortic aneurysm (AAA) is a common degenerative cardiovascular disease whose pathobiology is not clearly understood. The cellular heterogeneity and cell-type-specific gene regulation of vascular cells in human AAA have not been well-characterized. Here, we performed analysis of whole-genome sequencing data in AAA patients versus controls with the aim of detecting disease-associated variants that may affect gene regulation in human aortic smooth muscle cells (AoSMC) and human aortic endothelial cells (HAEC), two cell types of high relevance to AAA disease. To support this analysis, we generated H3K27ac HiChIP data for these cell types and inferred cell-type-specific gene regulatory networks. We observed that AAA-associated variants were most enriched in regulatory regions in AoSMC, compared with HAEC and CD4+ cells. The cell-type-specific regulation defined by this HiChIP data supported the importance of ERG and the KLF family of transcription factors in AAA disease. The analysis of regulatory elements that contain noncoding variants and also are differentially open between AAA patients and controls revealed the significance of the interleukin-6-mediated signaling pathway. This finding was further validated by including information from the deleteriousness effect of nonsynonymous single-nucleotide variants in AAA patients and additional control data from the Medical Genome Reference Bank dataset. These results shed important insights into AAA pathogenesis and provide a model for cell-type-specific analysis of disease-associated variants.

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