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1. Enhancer Pleiotropy, Gene Expression, and the Architecture of Human Enhancer–Gene Interactions

   https://doi.org/10.1093/molbev/msab085  

   Singh, Devika; Yi, Soojin V (March 2021, Molecular Biology and Evolution)

   Saitou, Naruya (Ed.)

   Abstract Enhancers are often studied as noncoding regulatory elements that modulate the precise spatiotemporal expression of genes in a highly tissue-specific manner. This paradigm has been challenged by recent evidence of individual enhancers acting in multiple tissues or developmental contexts. However, the frequency of these enhancers with high degrees of “pleiotropy” out of all putative enhancers is not well understood. Consequently, it is unclear how the variation of enhancer pleiotropy corresponds to the variation in expression breadth of target genes. Here, we use multi-tissue chromatin maps from diverse human tissues to investigate the enhancer–gene interaction architecture while accounting for 1) the distribution of enhancer pleiotropy, 2) the variations of regulatory links from enhancers to target genes, and 3) the expression breadth of target genes. We show that most enhancers are tissue-specific and that highly pleiotropy enhancers account for <1% of all putative regulatory sequences in the human genome. Notably, several genomic features are indicative of increasing enhancer pleiotropy, including longer sequence length, greater number of links to genes, increasing abundance and diversity of encoded transcription factor motifs, and stronger evolutionary conservation. Intriguingly, the number of enhancers per gene remains remarkably consistent for all genes (∼14). However, enhancer pleiotropy does not directly translate to the expression breadth of target genes. We further present a series of Gaussian Mixture Models to represent this organization architecture. Consequently, we demonstrate that a modest trend of more pleiotropic enhancers targeting more broadly expressed genes can generate the observed diversity of expression breadths in the human genome. 

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2. Affinity-optimizing enhancer variants disrupt development

   https://doi.org/10.1038/s41586-023-06922-8  

   Lim, Fabian; Solvason, Joe J.; Ryan, Genevieve E.; Le, Sophia H.; Jindal, Granton A.; Steffen, Paige; Jandu, Simran K.; Farley, Emma K. (February 2024, Nature)

   Abstract Enhancers control the location and timing of gene expression and contain the majority of variants associated with disease^1–3. The ZRS is arguably the most well-studied vertebrate enhancer and mediates the expression ofShhin the developing limb⁴. Thirty-one human single-nucleotide variants (SNVs) within the ZRS are associated with polydactyly^4–6. However, how this enhancer encodes tissue-specific activity, and the mechanisms by which SNVs alter the number of digits, are poorly understood. Here we show that the ETS sites within the ZRS are low affinity, and identify a functional ETS site, ETS-A, with extremely low affinity. Two human SNVs and a synthetic variant optimize the binding affinity of ETS-A subtly from 15% to around 25% relative to the strongest ETS binding sequence, and cause polydactyly with the same penetrance and severity. A greater increase in affinity results in phenotypes that are more penetrant and more severe. Affinity-optimizing SNVs in other ETS sites in the ZRS, as well as in ETS, interferon regulatory factor (IRF), HOX and activator protein 1 (AP-1) sites within a wide variety of enhancers, cause gain-of-function gene expression. The prevalence of binding sites with suboptimal affinity in enhancers creates a vulnerability in genomes whereby SNVs that optimize affinity, even slightly, can be pathogenic. Searching for affinity-optimizing SNVs in genomes could provide a mechanistic approach to identify causal variants that underlie enhanceropathies. 

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3. Recurrent enhancer-promoter interactions across samples

   https://doi.org/10.1101/2025.09.27.678855  

   Weston, Mathew; Gunjala, Satvik; Hu, Haiyan; Li, Xiaoman (September 2025, bioRxiv)

   Abstract Enhancer-promoter interactions (EPIs) are fundamental to gene regulation, and understanding their recurrence across diverse biological samples is key to deciphering chromatin architecture. In this study, we systematically analyzed the recurrence of EPIs across 49 Hi-C and 95 HiChIP datasets. We found that the majority of EPIs identified in a given sample were also present in other samples, regardless of the assay type (Hi-C or HiChIP) or the enhancer annotations used. Interestingly, EPIs that appeared unique to individual samples were typically surrounded by fewer neighboring EPIs, suggesting they may not represent truly sample-specific interactions. Our findings indicate that most human EPIs have already been captured and that cells primarily reuse subsets of these shared EPIs across different cell types and conditions. This study provides new insights into the pervasive and reusable nature of EPIs in the human genome, with important implications for chromatin conformation studies. 

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4. Cardiac ACTN2 enhancer regulates cardiometabolism and maturation

   https://doi.org/10.1038/s44161-024-00483-3  

   Galdos, Francisco X; Lee, Carissa; Wu, Sean M (June 2024, Nature Cardiovascular Research)
5. An intriguing characteristic of enhancer-promoter interactions

   https://doi.org/10.1186/s12864-021-07440-5  

   Talukder, Amlan; Hu, Haiyan; Li, Xiaoman (December 2021, BMC Genomics)

   null (Ed.)

   Abstract Background It is still challenging to predict interacting enhancer-promoter pairs (IEPs), partially because of our limited understanding of their characteristics. To understand IEPs better, here we studied the IEPs in nine cell lines and nine primary cell types. Results By measuring the bipartite clustering coefficient of the graphs constructed from these experimentally supported IEPs, we observed that one enhancer is likely to interact with either none or all of the target genes of another enhancer. This observation implies that enhancers form clusters, and every enhancer in the same cluster synchronously interact with almost every member of a set of genes and only this set of genes. We perceived that an enhancer can be up to two megabase pairs away from other enhancers in the same cluster. We also noticed that although a fraction of these clusters of enhancers do overlap with super-enhancers, the majority of the enhancer clusters are different from the known super-enhancers. Conclusions Our study showed a new characteristic of IEPs, which may shed new light on distal gene regulation and the identification of IEPs. 

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