Every cell in the human body contains the same DNA, yet cells become fundamentally different types — brain cells, muscle cells, immune cells, or liver cells — each with unique functions. This remarkable diversity arises not from changes to the DNA sequence itself, but from mechanisms that control genome ‘activity’ and in particular, the epigenome. The epigenome consists of chemical and structural marks that determine which genes are active, silent, or poised, effectively shaping how genetic information is interpreted. In this way, the epigenome acts as the operating system of the genome: it does not change the code, but it determines how the code runs. Understanding the epigenome is one of the most exciting frontiers in modern biology and medicine because it sits at the interface of nature, environment, and development. Epigenetic regulation helps explain how cells establish and maintain their identity, how early-life events may influence later health, and why genetically identical cells or individuals can behave differently. Crucially, many diseases including cancers, autoimmune conditions, and developmental syndromes, involve disrupted epigenetic states.
Despite its importance, our understanding of the epigenome remains incomplete. The field urgently needs causal, quantitative, and scalable tools to understand how specific epigenetic marks influence gene activity and cellular behaviour. Without this knowledge, we cannot fully interpret genome-wide data, accurately model cell states, or design targeted epigenetic therapies. The ModLogic project directly tackles this gap. We are developing a new experimental platform known as high-throughput ‘epigenetic editing’, which allows us to place specific epigenetic marks on chosen genomic sites and measure their consequences at single-cell resolution at large scale. This enables us to move from describing correlations to discovering cause-and-effect rules of epigenetic regulation. We combine this technology with advanced stem-cell-based models, including 3-dimensional structures that mimic early human development, and sophisticated computational and machine-learning approaches to decode patterns emerging from thousands of controlled perturbations. The research outcome will unravel three foundational scientific questions related to how epigenetics works: (i) Causality — which epigenetic marks directly change gene expression, and by how much? (ii) Context dependence — how do genetic differences, DNA sequence features, or cell identity alter the effect of an epigenetic change? (iii) Mechanism — through which molecular pathways and protein networks do epigenetic marks exert their influence?
The project will also have impact beyond its scientific achievements:
• Fundamental insight: It will generate the first large-scale, experimentally validated rules or ‘regulatory logic’ describing how the epigenome control gene expression.
• Improved disease understanding: The unraveling of epigenetic rules will help interpret human genetic risk factors located in regulatory regions, improving links between genomics and clinical biology.
• New therapeutic opportunities: The epigenetic editing technology developed is anticipated to inspire next-generation treatments that tune gene activity without altering DNA sequence, with potential relevance to cancer, metabolic disease, ageing, and regenerative medicine.
