Advancing Epigenetics Towards Systems Biology

Research activities

 

To achieve its goal of building a bridge between epigenetics and systems biology, the EpiGeneSys has combined the efforts of the consortium, whose members have expertise in multiple disciplines, (development, molecular biology, genomics, proteomics, biochemistry, structural biology, computational biology and mathematics) and attested excellence in epigenetics research in a variety of complementary model systems (yeast, Drosophila, mouse, Xenopus, plants, and human cells) including human diseases (cancer, genomic imprinting disorders).

The four scientific WPs have had the common goal of bringing a fundamental question in epigenetics towards systems level analysis. As a further integrative component, EpiGeneSys has aimed to advance our understanding of epigenetic inheritance, i.e. by assessing stability versus plasticity during the cell-cycle, throughout multiple divisions and even several generations.

So far, more than 350 publications stemming from the research efforts of the network have been published, many of them in major journals such as Nature, Science or Cell, and the results were presented and discussed at international scientific meetings.

WP2 Dynamics of Epigenetic Regulators:

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Photo: Miguel Casanova, Institut Curie

Epigenetic systems comprise multiprotein complexes, many of which interact with chromatin in a dynamic manner, in rapid exchange between bound and free pools. Epigenetic regulators can be anchored to chromatin via many interaction partners, including other proteins, modified histone tails, metabolites, DNA and non-coding RNA. The strength and nature of these interactions changes dynamically during replication, mitosis, and upon developmental transitions. Many individual interactions have been genetically and biochemically determined in exquisite detail. Although some of these observations have been quantified, a large gap in our understanding of the dynamic nature of these complex systems has been the lack of comprehensive quantitative in vivo measurements of chromatin binding in real time. Such knowledge is essential to enable mathematical models describing the interplay of these interactions, and to inform experiments in which specific interactions are perturbed. The aim of this work package was to gain a quantitative understanding of the molecular driving forces that govern robustness and sensitivity of the binding of epigenetic regulators to chromatin and which thus are the key points for regulation during normal cellular function and for deregulation upon disease.

We focused on three main questions:

  1. Single interactions. What is the molecular structure and affinity of the interaction between a given regulator and its binding partner in vitro? What is the affinity and residence time of a given regulator binding to chromatin in vivo?
  2. Interaction maps. Which interactions determine the binding of a given epigenetic regulator to chromatin in interphase cells? To what extent, in quantitative terms, are these interactions cooperative or competitive?
  3. Dynamic changes. How does the chromatin binding behaviour of a given regulator change during replication and mitosis, in terms of quantity bound, residence time and quantitative extent of interaction with other components? How do these parameters change upon developmental cell fate transitions? How do they change upon challenges to the system such as DNA damage?

WP3 Linking Genotype to Epigenotype:

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Mouse cDNA Microarray, Source: Louis M. Staudt, National Cancer Institute

Recent genome-wide approaches have shown these mechanisms to be highly specific with respect to chromosomal regions and developmental time-points and to be dependent upon inter and intra species sequence variation. The goal of WP3 was to elucidate the crosstalk between genome and epigenome by applying rigorous high-throughput systems biology approaches for several epigenetic variables in selected model organisms and populations of known sequence diversity. The generated datasets and tools were utilized to model genome-wide epigenetic states and regulatory networks, and to predict regulatory interactions between genotype and epigenotype. Predictions were validated and characterized through experimental testing using synthetic sequences in selected model systems.

The work program had three major pillars and work within WP3 and by its member labs over the course of EpiGeneSys have contributed substantially to a systems level understanding of gene regulation and the epigenome.

WP4 Signalling to the Epigenome:

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Photo: ©Heliox

The aim of this work package was to determine how the environment, stress, metabolic status and growth factors signal to the epigenome to induce new programmes of gene expression that may either be transient or lead to long-term heritable phenotypes. WP4 was divided into three scientific tasks and a general joint task. Task 1 investigated how the metabolic status of a cell and environmental stimuli influence the epigenome to dictate transcriptional programmes that can have far reaching and long term consequences for the organism. Task 2 was dedicated to determining how developmental signalling pathways influence transcriptional programmes through the epigenome to specify cell lineages. Task 3 determined how transient signalling leads to long term, heritable changes in gene expression. In a common effort we have sought to integrate our data with the aim to establish common platforms for data generation and modelling.

The work has gone extremely well over the last five years, substantial discoveries were made.

WP5 An Integrated Computational Epigenetics Framework:

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Rapid progress was achieved in computational epigenetics during 2010-2016. The overarching goal of WP5 was to facilitate better integration between systems biology tools and techniques and epigenetic research. We originally identified several domains that were challenging (at 2010) for most experimental groups, and wished to open these by making tools more accessible and usable. Over the last five years, through work by a large number of groups , and most importantly, by deeper and deeper integration of bioinformatics and computational skills into research group, the challenges identified originally are for the most part resolved. Nevertheless, the deeper theoretical question underlying the new techniques requires additional research and perhaps new interdisciplinary ideas.