Long-Range Chromatin Interaction Regulates hTERT Expression Through Epigenetic Modifications

2018 ◽  
Vol 4 ◽  
Genes ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 985 ◽  
Author(s):  
Thomas Vanhaeren ◽  
Federico Divina ◽  
Miguel García-Torres ◽  
Francisco Gómez-Vela ◽  
Wim Vanhoof ◽  
...  

The role of three-dimensional genome organization as a critical regulator of gene expression has become increasingly clear over the last decade. Most of our understanding of this association comes from the study of long range chromatin interaction maps provided by Chromatin Conformation Capture-based techniques, which have greatly improved in recent years. Since these procedures are experimentally laborious and expensive, in silico prediction has emerged as an alternative strategy to generate virtual maps in cell types and conditions for which experimental data of chromatin interactions is not available. Several methods have been based on predictive models trained on one-dimensional (1D) sequencing features, yielding promising results. However, different approaches vary both in the way they model chromatin interactions and in the machine learning-based strategy they rely on, making it challenging to carry out performance comparison of existing methods. In this study, we use publicly available 1D sequencing signals to model cohesin-mediated chromatin interactions in two human cell lines and evaluate the prediction performance of six popular machine learning algorithms: decision trees, random forests, gradient boosting, support vector machines, multi-layer perceptron and deep learning. Our approach accurately predicts long-range interactions and reveals that gradient boosting significantly outperforms the other five methods, yielding accuracies of about 95%. We show that chromatin features in close genomic proximity to the anchors cover most of the predictive information, as has been previously reported. Moreover, we demonstrate that gradient boosting models trained with different subsets of chromatin features, unlike the other methods tested, are able to produce accurate predictions. In this regard, and besides architectural proteins, transcription factors are shown to be highly informative. Our study provides a framework for the systematic prediction of long-range chromatin interactions, identifies gradient boosting as the best suited algorithm for this task and highlights cell-type specific binding of transcription factors at the anchors as important determinants of chromatin wiring mediated by cohesin.


2020 ◽  
Vol 77 (6) ◽  
pp. 1307-1321.e10 ◽  
Author(s):  
Helen Zhu ◽  
Liis Uusküla-Reimand ◽  
Keren Isaev ◽  
Lina Wadi ◽  
Azad Alizada ◽  
...  

2013 ◽  
Vol 111 (11) ◽  
Author(s):  
R. E. Boulos ◽  
A. Arneodo ◽  
P. Jensen ◽  
B. Audit

2020 ◽  
Author(s):  
Wei Yu ◽  
V. Praveen Chakravarthi ◽  
Shaon Borosha ◽  
Anamika Ratri ◽  
Khyati Dalal ◽  
...  

ABSTRACTSATB homeobox proteins are important regulators of developmental gene expression. Among the stem cell lineages determined during early embryonic development, trophoblast stem (TS) cells exhibit robust SATB expression. Both SATB1 and SATB2 act to maintain trophoblast stem-state. However, the molecular mechanisms that regulate TS-specific Satb expression are not yet known. We identified Satb1 variant 2 as the predominant transcript in trophoblasts. Histone marks, and RNA polymerase II occupancy in TS cells indicated active state of the promoter. A novel cis-regulatory region with active histone marks was identified ∼21kbp upstream of variant 2 promoter. CRISPR/Cas9 mediated disruption of this sequence decreased Satb1 expression in TS cells and chromatin conformation capture confirmed looping of this regulatory region into the promoter. Scanning position weight matrices across the enhancer predicted two ELF5 binding sites in close vicinity of SATB1 sites, which were confirmed by chromatin immunoprecipitation. Knockdown of ELF5 downregulated Satb1 expression in TS cells and overexpression of ELF5 increased the enhancer-reporter activity. Interestingly, ELF5 interacts with SATB1 in TS cells, and the enhancer activity was upregulated following SATB overexpression. Our findings indicate that trophoblast-specific Satb1 expression is regulated by long-range chromatin looping of an enhancer that interacts with ELF5 and SATB proteins.


2017 ◽  
Author(s):  
Lina Wadi ◽  
Liis Uusküla-Reimand ◽  
Keren Isaev ◽  
Shimin Shuai ◽  
Vincent Huang ◽  
...  

AbstractA comprehensive catalogue of the mutations that drive tumorigenesis and progression is essential to understanding tumor biology and developing therapies. Protein-coding driver mutations have been well-characterized by large exome-sequencing studies, however many tumors have no mutations in protein-coding driver genes. Non-coding mutations are thought to explain many of these cases, however few non-coding drivers besides TERT promoter are known. To fill this gap, we analyzed 150,000 cis-regulatory regions in 1,844 whole cancer genomes from the ICGC-TCGA PCAWG project. Using our new method, ActiveDriverWGS, we found 41 frequently mutated regulatory elements (FMREs) enriched in non-coding SNVs and indels (FDR<0.05) characterized by aging-associated mutation signatures and frequent structural variants. Most FMREs are distal from genes, reported here for the first time and also recovered by additional driver discovery methods. FMREs were enriched in super-enhancers, H3K27ac enhancer marks of primary tumors and long-range chromatin interactions, suggesting that the mutations drive cancer by distally controlling gene expression through threedimensional genome organization. In support of this hypothesis, the chromatin interaction network of FMREs and target genes revealed associations of mutations and differential gene expression of known and novel cancer genes (e.g., CNNB1IP1, RCC1), activation of immune response pathways and altered enhancer marks. Thus distal genomic regions may include additional, infrequently mutated drivers that act on target genes via chromatin loops. Our study is an important step towards finding such regulatory regions and deciphering the somatic mutation landscape of the non-coding genome.


2020 ◽  
Author(s):  
Weifang Liu ◽  
Armen Abnousi ◽  
Qian Zhang ◽  
Yun Li ◽  
Ming Hu ◽  
...  

AbstractChromatin spatial organization (interactome) plays a critical role in genome function. Deep understanding of chromatin interactome can shed insights into transcriptional regulation mechanisms and human disease pathology. One essential task in the analysis of chromatin interactomic data is to identify long-range chromatin interactions. Existing approaches, such as HiCCUPS, FitHiC/FitHiC2 and FastHiC, are all designed for analyzing individual cell types. None of them accounts for unbalanced sequencing depths and heterogeneity among multiple cell types in a unified statistical framework. To fill in the gap, we have developed a novel statistical framework MUNIn (Multiple cell-type UNifying long-range chromatin Interaction detector) for identifying long-range chromatin interactions from multiple cell types. MUNIn adopts a hierarchical hidden Markov random field (H-HMRF) model, in which the status (peak or background) of each interacting chromatin loci pair depends not only on the status of loci pairs in its neighborhood region, but also on the status of the same loci pair in other cell types. To benchmark the performance of MUNIn, we performed comprehensive simulation studies and real data analysis, and showed that MUNIn can achieve much lower false positive rates for detecting cell-type-specific interactions (33.1 - 36.2%), and much enhanced statistical power for detecting shared peaks (up to 74.3%), compared to uni-cell-type analysis. Our data demonstrated that MUNIn is a useful tool for the integrative analysis of interactomic data from multiple cell types.


Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 280-280
Author(s):  
Wulan Deng ◽  
Jeremy W Rupon ◽  
Hongxin Wang ◽  
Andreas Reik ◽  
Philip D. Gregory ◽  
...  

Abstract Abstract 280 Distal enhancers physically contact target promoters to confer high level transcription. At the mammalian β-globin loci long-range chromosomal interactions between a distal enhancer, called the locus control region (LCR), and the globin genes are developmentally dynamic such that the LCR contacts the embryonic, fetal and adult globin genes in a stage-appropriate fashion. LCR-globin gene interactions require the nuclear factor Ldb1. Recently, we employed artificial zinc finger (ZF) proteins to target Ldb1 to the endogenous β-globin locus to force an LCR-promoter interaction. This led to substantial activation of β-globin transcription and suggested that forced chromatin looping could be employed as a powerful tool to manipulate gene expression in vivo (Deng et al., Cell 2012). Reactivation of the fetal globin genes in adult erythroid cells has been a long-standing goal in the treatment of patients with sickle cell anemia. Therefore, building on our findings, we investigated whether the developmentally silenced embryonic globin gene βh1 can be re-activated in adult murine erythroblasts by re-directing the LCR away from the adult type globin gene and towards its embryonic counterpart. To this end, Ldb1 was fused to artificial ZF proteins (ZF-Ldb1) designed to bind to the βh1 promoter. ZF-Ldb1 was introduced into definitive erythroid cells in which only the adult but not the embryonic β-like globin gene is expressed. In vivo binding of the ZF-Ldb1 to its intended target was verified by chromatin immunoprecipitation assay. Strikingly, expression of ZF-Ldb1 re-activated βh1 transcription up to approximately ∼15% of total cellular β-globin production. This suggests that forced tethering of a looping factor to a select promoter can be employed to override a pre-existing developmental long-range chromatin interaction to reprogram a developmentally controlled gene locus. We are now in the process of testing whether our approach might be suitable to reactivate the silent fetal globin genes in adult human erythroid cells. These studies are underway and the results will be discussed at the meeting. Disclosures: Reik: Sangamo BioSciences, Inc.: Employment. Gregory:Sangamo BioSciences, Inc.: Employment.


2011 ◽  
Vol 30 (13) ◽  
pp. 2569-2581 ◽  
Author(s):  
Si Kee Tan ◽  
Zhen Hua Lin ◽  
Cheng Wei Chang ◽  
Vipin Varang ◽  
Kern Rei Chng ◽  
...  

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