Transcriptional condensates encode a “golden mean” to optimize enhancer–promoter communication across genomic distances
Year: 2025
Type: article
Abstract: Enhancers regulate gene expression by physically contacting their target promoters, yet these contacts often span large genomic distances. Phase-separated condensates (droplet-like clusters) of transcription factors (TFs) are thought to facilitate such long-range enhancer-promoter (E-P) communication, but the quantitative principles underlying this mechanism remain unclear. Here, we use polymer-based chromatin simulations to systematically vary the strength of TF clustering and the E-P genomic distance, examining their combined effects on E-P contact formation. We find that E-P contact frequency shows a nonmonotonic dependence on the degree of TF clustering: Contact frequency peaks at an intermediate TF abundance and TF-TF affinity, leading to a "golden mean" optimum. Two distinct regimes emerge: Under weak TF-TF attraction, contact probability increases with condensate size, whereas strong TF attraction produces a peaked response that declines at high condensation levels. These results indicate that TF condensate acts as a tunable "rheostat," buffering E-P interactions against increasing genomic distances. However, excessive TF clustering leads to molecular crowding and competition that ultimately impair E-P communication. Our study, consistent with recent experiments, establishes a mechanistic framework at the molecular level, where balanced TF condensation enables robust long-range E-P communication, reconciling the stochastic nature of chromatin dynamics with the fidelity of gene regulation.
Authors: Tao Zhu, Chunhe Li, Xiakun Chu
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Funders: Human Resources and Social Security Department of Guangdong Province, National Natural Science Foundation of China, Guangdong Science and Technology Department, Department of Education of Guangdong Province, Guangdong Provincial Pearl River Talents Program, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
OpenAlex ID: W4415523497