Periodic Reporting for period 1 - PEP-NET (Predictive Epigenetics: Fusing Theory and Experiment) Reporting period: 2018-11-01 to 2020-10-31 Summary of the context and overall objectives of the project Epigenetics research aims to understand how a single genomic DNA sequence can generate and maintain the extraordinary diversity of cell identities and functions that comprise the adult organism. Modifications of DNA and chromatin and the binding of other molecules provide a gene-regulatory layer that modulates gene activity states, so that one genome gives rise to several “epigenomes”. Epigenetic regulation can be defined as “the structural adaptation of chromosomal regions so as to register, signal or perpetuate altered activity states”. Many of the proteins that mediate epigenetic regulation are enzymes that covalently modify DNA or chromatin. These modifications can have profound and specific effects on gene activity, and include methylation, acetylation and ubiquitylation of histones and methylation of DNA. Epigenetic regulatory proteins are highly conserved from yeast to mammals, and they work on thousands of genes including those encoding developmental regulators, tumour suppressors and signaling molecules.Given the identities of these target genes, it is not surprising that epigenetic mechanisms are profoundly implicated in human health and disease. There is virtually no area of human health that is not affected by epigenetics, and pharmaceutical companies are responding rapidly to these discoveries. Despite the importance of epigenetic processes for human health, we are still far from a complete mechanistic understanding of many epigenetic phenomena. A quantitative mechanistic understanding of epigenetic regulation is essential to understand its function in healthy cells and in disease states. Ultimately this knowledge will enable prediction of the effects and side effects of existing therapeutic interventions and the development of new targeted therapies.One barrier to understanding epigenetic mechanisms is information itself. The field of epigenetics is currently dominated by information, due to an explosion of technologies and the generation and availability of big data. These data include detailed studies on hundreds of different single loci, a vast number of genome-wide data sets from different labs documenting the distribution of regulators and histone modifications in different cell types, and a rapidly growing repository of ‘Hi-C” data, documenting three-dimensional chromatin conformation for entire genomes. Making sense of these data to achieve mechanistic understanding and to identify deep unifying concepts requires a paradigm shift in the way that epigenetics research is performed. This can be achieved by applying a rigorous theoretical framework to quantitative experimental data.In short, epigenetics needs mathematics. Epigenetic regulatory systems share several key features: first, they are complex, comprising multiple molecular components that regulate many genomic targets. Second, they are dynamic, allowing flexibility in reaction to environmental, developmental or disease signals. Finally, they involve stochastic processes, meaning that the effects can vary from cell to cell, over time, and from individual to individual. These features can only be captured by “moving models”, comprising comprehensive mathematical descriptions. Mathematical descriptions allow predictions. Testing predictions by experimental perturbations proves whether or not we have understood our system. To achieve the fusion of epigenetics and mathematics, the PEP-NET ITN unites 14 outstanding European academic laboratories and companies who have pioneered the successful combination of experimental and theoretical epigenetics. We comprise an equal mix of experimentalists and theorists, with long experience of successful cross-disciplinary collaborations, through which our members have made ground-breaking discoveries that would not have been possible by experiment or theory alone. PEP-NET participants have been instrumental in pioneering reductionist mechanistic models, aiming to construct the simplest model that explains observed phenomena. Simple mechanistic models are immensely powerful, because they unify and clarify deep principles, and make experimentally testable predictions. PEP-NET research combines mathematical modeling with quantitative experiments to address fundamental and applied questions in epigenetics. In addition, the PEP-NET ITN unites highly successful teachers in a new endeavor, namely to train a new cohort of researchers with a full range of interdisciplinary research and transferable skills in academic and industrial settings. Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far In this reporting period, we have addressed the following research objectives:1) Single-locus regulation: Using defined reporter genes in combination with stochastic and ODE modelling, we have developed mechanistic models to describe the influence of epigenetic regulators on gene expression states. 2) Genome-wide targeting: Using live imaging and genome-wide analysis in combination with machine learning and stochastic modelling, we have developed mechanistic models to describe the targeting of epigenetic regulators to their sites of action. 3) 3D genome organisation: Using technologies for measuring chromatin conformation in combination with polymer modelling, we have developed mechanistic models to describe the effects of genome architecture on epigenetic regulation. In addition, we organized three main PEP-NET Network-wide training events, the Berlin Basics Training camp, the Network Spring Meeting and the Strasbourg Summer School, which consisted of Interdisciplinary Training modules and Transferable Skills Training modules. The Strasbourg Summer School was the first main dissemination event that in addition to the training modules included a workshop on experimental and theoretical epigenetics where PEP-NET and external PIs presented their innovative research. These research talks were open to external researchers and therefore facilitated the dissemination of the PEP-NET network actions and research. Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far) PEP-NET aims to combine quantitative experiments with theoretical models in epigenetics, with the goal of deepening mechanistic understanding beyond what can be achieved with either approach alone. The work we have completed so far combines globally applicable models with quantitative experiments, and gives unexpected insights into several aspects of epigenetic function. We are thus on the path towards a far broader formalization and a deeper understanding than has previously been possible. Models describing different systems have already begun to uncover unifying principles, and we expect that this trajectory will continue.In the broader context of the Horizon 2020 Societal Challenges, our research programme is highly relevant to Challenge no. 1 “Health, demographic change and wellbeing,” in particular under the aspects of healthy ageing and personalised medicine. We envisage at least three major socio-economic benefits of PEP-NET projects applying mathematical modelling to epigenetics: Benefits to citizens: citizens need to be educated about what epigenetics is and is not and how it impinges on our health and wellbeing. Benefits to healthcare: PEP-NET projects will enable the creation of patient-specific models. Benefits to pharmaceutical industry: PEP-NET projects will enable in-silico trials for the development and assessment of biomedical products, including epigenetic drugs. PEP-NET: A highly interconnected network Epigenetic gene regulation in health and disease Epigenetics needs mathematics
