NatureMolecular BiologyPeer-reviewed journal article
Nonlinear control of transcription through enhancer-promoter interactions
Jessica ZuiniD, Grégory RothiD, Yinxiu ZhaniD, Julie CramardiD, Josef Redolfi, Ewa PiskadloiD, Pia MachiD, Mariya Kryzhanovska, Gergely TihanyiiD, Hubertus KohleriD, M EderiD, Christ LeemansiD, Bas van SteenseliD, Peter MeisteriD, Sébastien A. SmallwoodiD, Luca GiorgettiiD
Abstract
Chromosome structure in mammals is thought to regulate transcription by modulating the three-dimensional interactions between enhancers and promoters, notably through CTCF-mediated interactions and topologically associating domains (TADs)1-4. However, how chromosome interactions are actually translated into transcriptional outputs remains unclear. To address this question we use a novel assay to position an enhancer at a large number of densely spaced chromosomal locations relative to a fixed promoter, and measure promoter output and interactions within a genomic region with minimal regulatory and structural complexity. Quantitative analysis of hundreds of cell lines reveal that the transcriptional effect of an enhancer depends on its contact probabilities with the promoter through a non-linear relationship. Mathematical modeling and validation against experimental data further provide evidence that nonlinearity arises from transient enhancer-promoter interactions being memorized into longer-lived promoter states in individual cells, thus uncoupling the temporal dynamics of interactions from those of transcription. This uncovers a potential mechanism for how enhancers control transcription across large genomic distances despite rarely meeting their target promoters, and for how TAD boundaries can block distal enhancers. We finally show that enhancer strength additionally determines not only absolute transcription levels, but also the sensitivity of a promoter to CTCF-mediated functional insulation. Our unbiased, systematic and quantitative measurements establish general principles for the context-dependent role of chromosome structure in long-range transcriptional regulation.
- organism: human
- assay: ChIP-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 415
- FWCI
- 29.71
- Field percentile
- top 1%
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