An ambitious EC-funded research initiative on epigenetics advancing towards systems biology

WP2 Dynamics of Epigenetic Regulators:

While epigenetic systems have a robust epigenetic memory, they can also adapt and respond to various changes, such as during the cell cycle, during development and other environmental stress. The aim of this research is to understand how the dynamic binding of epigenetic regulators to chromatin enables both stability and flexibility of chromatin states. The idea behind this work is that the quantitative study of epigenetic systems at the single molecule and single cell level, combined with computational modelling of these systems in terms of dynamic chromatin binding behaviour of several interacting components, will bring invaluable insights into the inherent stability and plasticity of these systems.

This work package connects leading experts in epigenetics and biochemistry of chromatin, structural biology, genetics, proteomics, and live cell imaging, and computational modeling. They will predict and test how loss or overexpression of any component of the system can alter the balance between epistates. Heterochromatin states involved in gene silencing, dosage compensation, and Polycomb/Trithorax regulation are used as model epigenetic systems. The researchers involved in this work package characterize, quantify and model the interactions between key epigenetic regulators and chromatin components in vitro and in vivo, upon replication, mitosis, developmental transitions, and cellular stress such as DNA-damage.

WP3 Linking Genotype to Epigenotype:

The results of recent genome-wide approaches imply that it could be possible to predict some epigenetic states from DNA sequence. This research focus aims to decipher the crosstalk between DNA sequence and epigenomic landscapes, from the chemical modification of DNA, to the positions of nucleosomes and the recruitment of epigenetic machineries. In order to elucidate this crosstalk, rigorous high-throughput systems biology approaches will be applied to several epigenetic variables in selected model organisms and populations of known sequence diversity.

The datasets and tools generated will be utilized to model genome-wide epigenetic states and regulatory networks, and to predict regulatory interactions between genotype and epigenotypes. These will be validated and characterized through experimental testing using synthetic sequences in selected model systems. Epigenomic maps will be generated, analysed and integrated into a set of well-defined model systems that allow the epigenome to be deconvoluted into sequence dependent and independent (i.e. epigenetic) determinants and to generate quantitative regulatory models.

WP4 Signalling to the Epigenome:

Cells respond continually to their environment and to their nutritional state by inducing new programmes of gene expression, which in turn modulate cell behaviour. Tight and precise, but dynamic regulation of these processes is essential both for correct embryonic development and for the health and viability of the adult organism. The goal of this research focus is to understand how the environment, nutrients and metabolism, growth factors, cytokines and developmental forces shape the epigenome through signalling pathways from the cell surface to DNA organised into chromatin.

The systems biology goal of this work package is to quantify components of signalling pathways from cell surface molecules to chromatin components, and to build mathematical models representing the signalling events, to understand their interplay with epigenetic gene regulation in normal and perturbed situations. Approaches aimed at understanding biological design from synthetic circuits in simple systems will provide examples (Mukherji S, van Oudenaarden A. Synthetic biology: understanding biological design from synthetic circuits. Nat Rev Genet. 2009 Dec;10(12): p. 859-71.).

The approach uses simple model organisms like yeast, in which predictions based on gene loop conformations have enabled us to explain rapid transcriptional responses to changing environmental conditions and convey memory over short time scales. Based on this work, and by incorporating more components, it will be possible to try and elaborate more sophisticated models that could account for longer-term memory states. In addition, the use of probabilistic and stochastic modelling for more complex systems are exploited, taking examples as those recently developed for reprogramming. This work will not only help us understand how complex multicellular organisms develop from a single cell, but how growth and developmental defects can influence postnatal phenotypes, leading to disease in the adult.

WP5 An Integrated Computational Epigenetics Framework:

A systems biology and quantitative approach to epigenetics must develop extremely diverse approaches for analysis and modelling that integrate disparate data types and techniques from diverse fields such as biochemistry, molecular and structural biology, genomics, evolutionary theory, population genetics and network analysis. The purpose of this research focus is to transform, integrate and amplify the efforts of systems biologists and epigeneticists both within the network and outside it, by creating a curated, annotated and highly usable toolbox for computational epigenetics. The toolbox aims to bridge disciplinary gaps, to promote efficient data integration and to foster productive collaborations among partners. Standards, tools, and datasets will be tested and refined during the course of EpiGeneSys, ensuring quality validation steps before release to the community.

The network seeks to actively engage the systems and computational biology communities by articulating epigenetic challenges and promoting research into possible solutions to these challenges.
In addition to bringing systems biology into epigenetics, this work package also serves as a vehicle for the rapid dissemination of current epigenetic concepts into the systems biology community, increasing the availability of epigenetics data and making epigenomics methodologies accessible for incorporation into diverse applications. The toolbox will form a critical meeting point between systems biology and epigenetic research groups, allowing them to interact and intertwine, and contributing to fulfilling EpiGeneSys’s vision.