Literature DB >> 35961952

Enhancer-promoter communication: unraveling enhancer strength and positioning within a given topologically associating domain (TAD).

Benedetto Daniele Giaimo1, Tilman Borggrefe2.   

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Year:  2022        PMID: 35961952      PMCID: PMC9374741          DOI: 10.1038/s41392-022-01114-8

Source DB:  PubMed          Journal:  Signal Transduct Target Ther        ISSN: 2059-3635


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In a recent study published in Nature, Zuin et al. elucidate the molecular mechanisms of how enhancer positioning and strength affect gene expression levels.[1] Cell-type-specific transcription factors (TFs) and ubiquitously expressed cofactors regulate the complex network of eukaryotic gene transcription in an exquisitely specific and sensitive manner. The DNA elements bound by TFs are called enhancers and can be located close to the transcription start site (TSS) or far away, even hundreds of kilobases (kb) away. Historically, enhancers were identified in the early 1980s by injecting DNA into nuclei or cells.[2] Subsequently, several assays such as EMSAs (electrophoretic mobility shift assays) and DNAse footprinting analyses were used to identify enhancers which were further functionally characterized by luciferase assays. These techniques have been key in discovering and characterizing many different enhancers and their cognate TFs. In the last two decades genome-wide techniques like ATAC-Seq (assay for transposase-accessible chromatin using sequencing), ChIP-Seq (chromatin immunoprecipitation followed by sequencing) combined with RNA-Seq widened our understanding of enhancer biology. Still the long-standing questions remained: What are the principles governing the enhancer-promoter communication and what are the key regulatory steps resulting in adequate transcriptional output? Does genomic context and possible insulation matter? In this regard, Chromatin Conformation Capture (3C) and related techniques[3] significantly enlarged our understanding of enhancer biology. Topological associating domains (TADs) were defined as the building blocks of genome organization, in which enhancers operate.[4] The relationship between enhancers and TADs was and is still intensely studied and whole novel toolbox of techniques is available to study enhancer functions.[5] In this context, Zuin et al. developed an unbiased experimental strategy in mouse embryonic stem cells (ESCs) to investigate how genomic distance between a given enhancer element and its cognate TSS affects transcriptional output within a specific TAD.[1] For this purpose, a transgene was inserted on chromosome 15 within a TAD that does not contain any gene or active enhancer. In particular, this region of ~500 kb in size was chosen because it is “neutral” and its structural complexity is minimal. The transgene carries the mouse Sry (sex determining region Y)-box 2 (Sox2) promoter that drives the expression of the enhanced green fluorescent protein (eGFP). The eGFP is divided into two parts by a piggyBac transposon that contains the cognate enhancer of the Sox2 promoter known as Sox2 control region (SCR). Enhancer hopping only of the SCR is mediated via expression of the piggyBac transposase (PBase), that leads to excision and reintegration of the enhancer randomly in cis in the vicinity of the original site This system allowed Zuin et al. to generate hundreds of individual clones or cell lines, each having the very same enhancer element positioned in different locations within a given TAD. By using this system, Zuin et al. could observe that gene expression levels rapidly decrease with increasing distance between the enhancer and the promoter, as measured on protein level by eGFP intensity or mRNA number per cell using RNA-FISH (RNA-fluorescence in situ hybridization) (Fig. 1a). In addition, there is a nonlinear correlation between gene expression and contact probability; this is also supported by a mathematical two-state model, in which the promoter on rate follows a sigmoidal function of enhancer-promoter contact probability (Fig. 1b). Importantly, there is an interplay between enhancer and insulators: Strong enhancers are less susceptible to insulation by CTCF compared to weak enhancers (Fig. 1c). The chosen approach by Zuin et al. is elegant and unbiased and allows the comparison of enhancer positioning in the genomic context with minimal variables.
Fig. 1

Schematic summary of the main findings of Zuin et al. a Gene expression depends on the enhancer-promoter distance. b Gene expression depends on contact probability by following a nonlinear relationship. c Enhancer strength determines its sensitivity to CTCF-mediated insulation

Schematic summary of the main findings of Zuin et al. a Gene expression depends on the enhancer-promoter distance. b Gene expression depends on contact probability by following a nonlinear relationship. c Enhancer strength determines its sensitivity to CTCF-mediated insulation In future, using such an extremely well-defined system, it will be interesting to investigate how a particular chromatin configuration influences enhancer strength within a given TAD. Would it be possible to predict the outcome of transcriptional output with a mathematical model? And again, what are the critical variables in such an equation? Would it be also possible to define the differences between a locus with multiple enhancer elements, such as super-enhancers? In this case, are the rules different? Taken together, the study from Zuin et al. reveals that changes in frequency of promoter bursting dynamics is nonlinear and depends on contact probability, enhancer strength, and positioning in relation to boundary elements. These findings broaden our fundamental understanding of enhancers in a genome-wide context. Checklist
  5 in total

Review 1.  Methods for mapping 3D chromosome architecture.

Authors:  Rieke Kempfer; Ana Pombo
Journal:  Nat Rev Genet       Date:  2019-12-17       Impact factor: 53.242

2.  Nonlinear control of transcription through enhancer-promoter interactions.

Authors:  Jessica Zuin; Gregory Roth; Yinxiu Zhan; Julie Cramard; Josef Redolfi; Ewa Piskadlo; Pia Mach; Mariya Kryzhanovska; Gergely Tihanyi; Hubertus Kohler; Mathias Eder; Christ Leemans; Bas van Steensel; Peter Meister; Sebastien Smallwood; Luca Giorgetti
Journal:  Nature       Date:  2022-04-13       Impact factor: 69.504

Review 3.  A Comprehensive Toolbox to Analyze Enhancer-Promoter Functions.

Authors:  Benedetto Daniele Giaimo; Tobias Friedrich; Tilman Borggrefe
Journal:  Methods Mol Biol       Date:  2021

Review 4.  Transcriptional Regulation by (Super)Enhancers: From Discovery to Mechanisms.

Authors:  Frank Grosveld; Jente van Staalduinen; Ralph Stadhouders
Journal:  Annu Rev Genomics Hum Genet       Date:  2021-05-05       Impact factor: 8.929

Review 5.  Chromatin-driven behavior of topologically associating domains.

Authors:  Filippo Ciabrelli; Giacomo Cavalli
Journal:  J Mol Biol       Date:  2014-10-02       Impact factor: 5.469

  5 in total

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