Chromatin Looping and Long Distance Regulation by Androgen Receptor

Author(s):  
Benjamin Sunkel ◽  
Qianben Wang
RNA Biology ◽  
2013 ◽  
Vol 10 (4) ◽  
pp. 516-527 ◽  
Author(s):  
Mirjana Nedeljkovic ◽  
Luisa Costessi ◽  
Alessandra Iaconcig ◽  
Fabiola Porro ◽  
Andrés F. Muro

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Neel Patel ◽  
William S. Bush

Abstract Background Transcriptional regulation is complex, requiring multiple cis (local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. In this study, we create a general model of transcription factor influence on gene expression by incorporating both cis and trans gene regulatory features. Results We describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and measures of the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for sequence kernel association test analyses of gene expression. Conclusions Our models generate refined effect estimates for the influence of individual transcription factors on gene expression, allowing characterization of their roles across the genome. This work also provides a framework for integrating multiple data types into a single model of transcriptional regulation.


2011 ◽  
Vol 22 (12) ◽  
pp. 474-480 ◽  
Author(s):  
Dayong Wu ◽  
Chunpeng Zhang ◽  
Yanping Shen ◽  
Kenneth P. Nephew ◽  
Qianben Wang

Planta ◽  
2020 ◽  
Vol 252 (4) ◽  
Author(s):  
Ziv Spiegelman ◽  
Or Broshi ◽  
Amit Shahar ◽  
Sumita Omer ◽  
Hagit Hak ◽  
...  

2013 ◽  
Vol 54 (4) ◽  
pp. 433-447 ◽  
Author(s):  
Masahiro Takahara ◽  
Shimpei Magori ◽  
Takashi Soyano ◽  
Satoru Okamoto ◽  
Chie Yoshida ◽  
...  

2005 ◽  
Vol 202 (4) ◽  
pp. 467-472 ◽  
Author(s):  
Abbas Hawwari ◽  
Michael S. Krangel

Murine Tcrd and Tcra gene segments reside in a single genetic locus and undergo recombination in CD4−CD8− (double negative [DN]) and CD4+CD8+ (double positive [DP]) thymocytes, respectively. TcraTcrd locus variable gene segments are subject to complex regulation. Only a small subset of ∼100 variable gene segments contributes substantially to the adult TCRδ repertoire. Moreover, although most contribute to the TCRα repertoire, variable gene segments that are Jα proximal are preferentially used during primary Tcra recombination. We investigate the role of local chromatin accessibility in determining the developmental pattern of TcraTcrd locus variable gene segment recombination. We find variable gene segments to be heterogeneous with respect to acetylation of histones H3 and H4. Those that dominate the adult TCRδ repertoire are hyperacetylated in DN thymocytes, independent of their position in the locus. Moreover, proximal variable gene segments show dramatic increases in histone acetylation and germline transcription in DP thymocytes, a result of super long-distance regulation by the Tcra enhancer. Our results imply that differences in chromatin accessibility contribute to biases in TcraTcrd locus variable gene segment recombination in DN and DP thymocytes and extend the distance over which the Tcra enhancer can regulate chromatin structure to a remarkable 525 kb.


2019 ◽  
Author(s):  
Pavel P. Kuksa ◽  
Alexandre Amlie-Wolf ◽  
Yih-Chii Hwang ◽  
Otto Valladares ◽  
Brian D. Gregory ◽  
...  

AbstractMost regulatory chromatin interactions are mediated by various transcription factors (TFs) and involve physically-interacting elements such as enhancers, insulators, or promoters. To map these elements and interactions, we developed HIPPIE2 which analyzes raw reads from high-throughput chromosome conformation (Hi-C) experiments to identify fine-scale physically-interacting regions (PIRs). Unlike standard genome binning approaches (e.g., 10K-1Mbp bins), HIPPIE2 dynamically calls physical locations of PIRs with better precision and higher resolution based on the pattern of restriction events and relative locations of interacting sites inferred from the sequencing readout.We applied HIPPIE2 to in situ Hi-C datasets across 6 human cell lines (GM12878, IMR90, K562, HMEC, HUVEC, NHEK) with matched ENCODE and Roadmap functional genomic data. HIPPIE2 detected 1,042,738 distinct PIRs across cell lines, with high resolution (average PIR length of 1,006bps) and high reproducibility (92.3% in GM12878 replicates). 32.8% of PIRs were shared among cell lines. PIRs are enriched for epigenetic marks (H3K27ac, H3K4me1) and open chromatin, suggesting active regulatory roles. HIPPIE2 identified 2.8M significant intrachromosomal PIR–PIR interactions, 27.2% of which were enriched for TF binding sites. 50,608 interactions were enhancer–promoter interactions and were enriched for 33 TFs (31 in enhancers/29 in promoters), several of which are known to mediate DNA looping/long-distance regulation. 29 TFs were enriched in >1 cell line and 4 were cell line-specific. These findings demonstrate that the dynamic approach used in HIPPIE2 (https://bitbucket.com/wanglab-upenn/HIPPIE2) characterizes PIR–PIR interactions with high resolution and reproducibility.


Immunity ◽  
2001 ◽  
Vol 15 (2) ◽  
pp. 187-199 ◽  
Author(s):  
Eric Pinaud ◽  
Ahmed Amine Khamlichi ◽  
Caroline Le Morvan ◽  
Mireille Drouet ◽  
Valérie Nalesso ◽  
...  

2020 ◽  
Author(s):  
Neel Patel ◽  
William Bush

Abstract BackgroundTranscriptional regulation is complex, requiring multiple cis(local) and trans acting mechanisms working in concert to drive gene expression, with disruption of these processes linked to multiple diseases. Previous computational attempts to understand the influence of regulatory mechanisms on gene expression have used prediction models containing input features derived from cis regulatory factors. However, local chromatin looping and trans-acting mechanisms are known to also influence transcriptional regulation, and their inclusion may improve model accuracy and interpretation. ResultsWe describe a computational framework to model gene expression for GM12878 and K562 cell lines. This framework weights the impact of transcription factor-based regulatory data using multi-omics gene regulatory networks to account for both cis and trans acting mechanisms, and the local chromatin context. These prediction models perform significantly better compared to models containing cis-regulatory features alone. Models that additionally integrate long distance chromatin interactions (or chromatin looping) between distal transcription factor binding regions and gene promoters also show improved accuracy. As a demonstration of their utility, effect estimates from these models were used to weight cis-regulatory rare variants for SKAT(sequence kernel association test) analyses of gene expression. ConclusionsOur models generate refined effect estimates for individual transcription factors, allow characterization of their roles across the genome, and provide a framework for integrating multiple data types into a single model of transcriptional regulation.


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