A histidine cluster determines YY1-compartmentalized coactivators and chromatin elements in phase-separated super-enhancers

Wang, Wenmeng; Qiao, Shiyao; Li, Guangyue; Yang, Cuicui; Chen, Zhong; Stovall, Daniel B.; Shi, Jinming; Li, Dangdang; Sui, Guangchao

doi:10.1101/2021.09.15.460559

Cited by 4 publications

(2 citation statements)

References 64 publications

(89 reference statements)

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“…The TFBSs for a total of 23 TFs were always enriched at anchors. These TFs include more universally-expressed regulators such as USF1/2 and SP1/2, as well as proteins involved in regulating 3D chromatin organization such as CTCF and YY1 [3,37,38]. However, we found that the large majority of these 165 TFs (n=130) have BSs that are enriched in a cell type-restricted fashion in non-anchor or all CM CREs.…”

Section: Resultsmentioning

confidence: 80%

Non-coding variants impactcis-regulatory coordination in a cell type-specific manner

Pushkarev,

van Mierlo,

Kribelbauer

et al. 2023

Preprint

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Interactions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify groups of covariable regulatory elements, referred to as chromatin modules (CMs). While CM mapping allows to investigate the relationship between chromatin modularity and gene expression, the computational principles used for CM identification vary in their application and outcomes. Here, we comprehensively evaluate and streamline existing CM mapping tools and present guidelines for optimal utilization of epigenome data from a diverse population of individuals to assess regulatory coordination across the human genome. We showcase the effectiveness of our recommended practices by analysing distinct cell types and demonstrate cell type-specificity of CRE interactions in CMs and their relevance for gene expression. Integration of genotype information revealed that many non-coding disease-associated variants affect the activity of CMs in a cell type-specific manner by affecting the binding of cell type-specific transcription factors. We provide example cases that illustrate in detail how CMs can be used to deconstruct GWAS loci, understand variable expression of cell surface receptors in immune cells and reveal how genetic variation can impact the expression of prognostic markers in chronic lymphocytic leukaemia. Our study presents an optimal strategy for CM mapping, and reveals how CMs capture the coordination of CREs and its impact on gene expression. Non-coding genetic variants can disrupt this coordination, and we highlight how this may lead to disease predisposition in a cell type-specific manner.

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Section: Resultsmentioning

confidence: 80%

Non-coding variants impactcis-regulatory coordination in a cell type-specific manner

Pushkarev,

van Mierlo,

Kribelbauer

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The transcription factor YY1 is overexpressed in prostate [ 146 ], colon [ 147 ], liver [ 148 ], lung [ 149 ], and breast cancers [ 150 ], and its over-expression is associated with poor prognosis in patients with osteosarcoma and Acute Lymphoblastic Leukemia [ 151 , 152 ]. The histidine cluster in the AD of YY1 compartmentalizes BRD4, MED1, and enhancer elements in phase-separated condensates to activate FOXM1 expression in breast cancer [ 153 ]. Besides AD of TF, estrogen can bind to ligand-binding domains of estrogen receptor α (ERα) to form MED1 condensates [ 139 ].…”

Section: Phase Separation Model To Explain Features Of Super-enhancersmentioning

confidence: 99%

Super-Enhancers, Phase-Separated Condensates, and 3D Genome Organization in Cancer

Tang

Vijayakumar

Zhang

et al. 2022

Cancers

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3D chromatin organization plays an important role in transcription regulation and gene expression. The 3D genome is highly maintained by several architectural proteins, such as CTCF, Yin Yang 1, and cohesin complex. This structural organization brings regulatory DNA elements in close proximity to their target promoters. In this review, we discuss the 3D chromatin organization of super-enhancers and their relationship to phase-separated condensates. Super-enhancers are large clusters of DNA elements. They can physically contact with their target promoters by chromatin looping during transcription. Multiple transcription factors can bind to enhancer and promoter sequences and recruit a complex array of transcriptional co-activators and RNA polymerase II to effect transcriptional activation. Phase-separated condensates of transcription factors and transcriptional co-activators have been implicated in assembling the transcription machinery at particular enhancers. Cancer cells can hijack super-enhancers to drive oncogenic transcription to promote cell survival and proliferation. These dysregulated transcriptional programs can cause cancer cells to become highly dependent on transcriptional regulators, such as Mediator and BRD4. Moreover, the expression of oncogenes that are driven by super-enhancers is sensitive to transcriptional perturbation and often occurs in phase-separated condensates, supporting therapeutic rationales of targeting SE components, 3D genome organization, or dysregulated condensates in cancer.

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Non-coding variants impact cis-regulatory coordination in a cell type-specific manner

Pushkarev,

van Mierlo,

Kribelbauer

et al. 2024

Genome Biol

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Background Interactions among cis-regulatory elements (CREs) play a crucial role in gene regulation. Various approaches have been developed to map these interactions genome-wide, including those relying on interindividual epigenomic variation to identify groups of covariable regulatory elements, referred to as chromatin modules (CMs). While CM mapping allows to investigate the relationship between chromatin modularity and gene expression, the computational principles used for CM identification vary in their application and outcomes. Results We comprehensively evaluate and streamline existing CM mapping tools and present guidelines for optimal utilization of epigenome data from a diverse population of individuals to assess regulatory coordination across the human genome. We showcase the effectiveness of our recommended practices by analyzing distinct cell types and demonstrate cell type specificity of CRE interactions in CMs and their relevance for gene expression. Integration of genotype information revealed that many non-coding disease-associated variants affect the activity of CMs in a cell type-specific manner by affecting the binding of cell type-specific transcription factors. We provide example cases that illustrate in detail how CMs can be used to deconstruct GWAS loci, assess variable expression of cell surface receptors in immune cells, and reveal how genetic variation can impact the expression of prognostic markers in chronic lymphocytic leukemia. Conclusions Our study presents an optimal strategy for CM mapping and reveals how CMs capture the coordination of CREs and its impact on gene expression. Non-coding genetic variants can disrupt this coordination, and we highlight how this may lead to disease predisposition in a cell type-specific manner.

show abstract

A histidine cluster determines YY1-compartmentalized coactivators and chromatin elements in phase-separated super-enhancers

Cited by 4 publications

References 64 publications

Non-coding variants impactcis-regulatory coordination in a cell type-specific manner

Non-coding variants impactcis-regulatory coordination in a cell type-specific manner

Super-Enhancers, Phase-Separated Condensates, and 3D Genome Organization in Cancer

Non-coding variants impact cis-regulatory coordination in a cell type-specific manner

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