Epigenetic factor competition reshapes the EMT landscape.

Epigenetic factor competition reshapes the EMT landscape.
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DOI:
10.1073/pnas.2210844119
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发表时间:
2022-10-18
影响因子:
11.1
通讯作者:
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中科院分区:
综合性期刊1区
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Epigenetics refers to the role of structural modifications in the genome that encode the context governing gene-expression dynamics. Although there have been attempts at creating mathematical models of these structural changes, how these changes couple to the transcriptional circuitry has remained unclear. Here, we study the role of histone modifications—namely, the adding or removing of methyl groups from histone H3 tails—in interacting with regulatory factors governing the transitions between epithelial and mesenchymal phenotypes. Our results show the critical importance of taking into account off-target global effects due to the competition between different DNA segments for the same histone-modifying enzymes. The emergence of and transitions between distinct phenotypes in isogenic cells can be attributed to the intricate interplay of epigenetic marks, external signals, and gene-regulatory elements. These elements include chromatin remodelers, histone modifiers, transcription factors, and regulatory RNAs. Mathematical models known as gene-regulatory networks (GRNs) are an increasingly important tool to unravel the workings of such complex networks. In such models, epigenetic factors are usually proposed to act on the chromatin regions directly involved in the expression of relevant genes. However, it has been well-established that these factors operate globally and compete with each other for targets genome-wide. Therefore, a perturbation of the activity of a regulator can redistribute epigenetic marks across the genome and modulate the levels of competing regulators. In this paper, we propose a conceptual and mathematical modeling framework that incorporates both local and global competition effects between antagonistic epigenetic regulators, in addition to local transcription factors, and show the counterintuitive consequences of such interactions. We apply our approach to recent experimental findings on the epithelial–mesenchymal transition (EMT). We show that it can explain the puzzling experimental data, as well as provide verifiable predictions.
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