Dynamical modeling of the H3K27 epigenetic landscape in mouse embryonic stem cells

Abstract

The Polycomb system via the methylation of the lysine 27 of histone H3 (H3K27) plays central roles in the silencing of many lineage-specific genes during development. Recent experimental evidence suggested that the recruitment of histone modifying enzymes like the Polycomb repressive complex 2 (PRC2) at specific sites and their spreading capacities from these sites are key to the establishment and maintenance of a proper epigenomic landscape around Polycomb-target genes. Here, based on previous biochemical knowledge, we turned this hypothesis into a mathematical model that can predict the locus-specific distributions of H3K27 modifications. Within the biological context of mouse embryonic stem cells, our model showed quantitative agreement with experimental profiles of H3K27 acetylation and methylation around Polycomb-target genes in wild-type and mutants. In particular, we demonstrated the key role of the reader-writer module of PRC2 and of the competition between the binding of activating and repressing enzymes in shaping the H3K27 landscape around transcriptional start sites. The predicted dynamics of establishment and maintenance of the repressive trimethylated H3K27 state suggest a slow accumulation, in perfect agreement with experiments. Our approach represents a first step towards a quantitative description of PcG regulation in various cellular contexts and provides a generic framework to better characterize epigenetic regulation in normal or disease situations.

Painters in chromatin: a unified quantitative framework to systematically characterize epigenome regulation and memory

“…To conclude the formalism developed here is generic and modular, as it provides a simple description of epigenomic regulation in terms of HMEs recruitment and enzymatic activity. It can be easily upgraded to include more chromatin modifications and cross-talks and feedback loops and can thus be contextualized to a variety of specific chromatin regulatory systems [29]. A very promising application of our painter model might be to explore how epigenomic (and corresponding transcriptional) dynamics might influence genome evolutionary processes.…”

“…Our work consists of three main methodological parts: (i) modeling chromatin state dynamics; (ii) modeling its impact on transcription; (iii) comparing model predictions with experimental data. As in our previous studies [21,22,29], chromatin is modeled by a unidimensional array of n nucleosomes. As a proxy for the local chromatin state, we assume that each nucleosome can fluctuate stochastically between a finite number of epigenetic states, each state corresponding to a specific combination of histone marks.…”

“…Such 3D activity k 3 D ( i → j ) depends on the the probability P c ( i, j ) that i and j are in contact and is assumed to be proportional to k w ( i ): k 3 D ( i → j ) = ϵk w ( i ) P c ( i, j ) with 0 ≤ ϵ ≤ 1, ϵ accounting for a putative modulation (reduction) of writing efficiency to neighboring nucleosomes. For short genomic distances between i and j ( < 100kbp), the looping rates are ∼ sec −1 [56, 57] while the chromatin modification rates are often ∼ h −1 [29, 58]. Thus, in these conditions of fast polymer dynamics, P c ( i, j ) can be approximated by the average contact probability [59] as observed in Hi-C experiments [60].…”

“…In each condition, 1000 different trajectories were simulated. Times are given in 1 /k 0 unit that characterizes the typical turnover time of histone marks and is ∼ h [29, 53].…”

“…Such "reader-writer" principle of chromatin enzymes and its impact on epigenetic memory has been already investigated using simple mathematical models of chromatin state regulation with a focus on the dynamics of histone marks mediated by HMEs [11,[18][19][20][21][22][23][24][25][26][27][28][29]. In particular, in their seminal work, Dodd et al [18] suggested that the maintenance of stable, extended active or repressed chromatin domains over generations, even in absence of nucleation signals, is made possible by the reader-writer property of HMEs coupled to their capacity to spread (or write) a mark at long-range along the genome.…”