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, to test whether such mechanisms, as a minimal set of qualitative rules, are quantitatively compatible with data, we developed a mathematical model that can predict the locus-specific distributions of H3K27 modifications based on previous biochemical knowledge. 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.

4D epigenomics: deciphering the coupling between genome folding and epigenomic regulation with biophysical modeling

“…In this case, the more compact the region, the more efficient the long-range-spreading and the easier the maintenance of stable epigenetic memory [2]. Interestingly, as suggested by several quantitative studies, the long-range recruited conversions might be only a feature of repressive states, active marks rather contributing only locally with weak or no reader-writer processes [26,29,33,34,37]. More generally, any processes that favor the "communication" between distant loci may contribute to epigenomic stability [2].…”

Fundamental insights into the correlation between chromosome configuration and transcription

“…For example, Newar et al developed a stochastic model that can predict the locus-specific distributions of H3K27 modifications based on previous biochemical knowledge and also provides a quantitative description of epigenetic regulation in normal and disease situations (2022). This model accounts for the recruitment of HMEs (histone modifying enzymes) at a genomic region of interest and then determines the histone modification landscapes as a consequence of competition between the spreading and erasing capacities of these HMEs (Newar et al 2022) (Liu et al 2019, Hu andMa 2021) have been used to predict highresolution interaction maps. For example, Al Bkhetan et al used a comprehensive workflow for predicting chromatin interactions using a combination of genomic analyses and ML techniques such as random forest, GBM, and deep learning models within TADs in the GM12878 cell line (2019) (figure 4(f)).…”

“…polymer-based models(Fudenberg et al 2016, Bianco et al 2017, Shukron and Holcman 2017, Nuebler et al 2018, geometric models(Wang et al 2017), stochastic models(Xiao et al 2021, Newar et al 2022, machine learning (ML) approaches(Vanhaeren et al 2020, Xie et al 2020, Di Stefano and Cavalli 2022, and other optimization-based approaches(Rousseau et al 2011) that can overcome the aforementioned limitations of experimental approaches.A polymer model-based molecular simulation approach is often used to understand the threedimensional configuration of a small chromatin fiber or whole genome based on the inputs from experiments such as HiC. Such a model describes chromatin as a single continuous chain of beads, with each bead representing a nucleosome or portion of chromatin.…”

Interplay between epigenome and 3D chromatin structure

“…Empirical validations of these models have yielded encouraging results, exemplified by phenomena like the formation of γH2AX domains near double-stranded breaks, the evolution of heterochromatin domain around the insertion sites of Transposable Elements (TE) in mammals, and the memory retention of heterochromatin in fission yeast ( 101 , 102 ). Furthermore, mathematical modeling of the Polycomb system’s repressive mark domain, which includes site-specific HME (PRC2) recruitment and mark propagation, has demonstrated its capability to accurately predict the experimental condition of chromatin mark domains in both wild-type and mutant cells ( 103 ).…”