Edinburgh Molecular Mechanisms Cluster (EMMC) to launch

£5 million UKRI-funding has been awarded to Professor Kenneth Baillie and team to establish the EMMC, which will aim to identify the molecular mechanisms linking genetic associations and disease.

This funding is part of a new UK-wide initiative led by the Medical Research Council (MRC) and forms part of the Government’s Life Sciences Vision which commits to position the UK as a leader to deliver a world-class offer on functional genomics.

There is a critical gap in translation of genetic associations into therapeutic insights: molecular mechanisms. Finding molecular quantitative trait loci (molQTL) can fill this gap. molQTL are genetic regions that affect a molecular event such as how much of a given RNA or protein is expressed.

Finding disease-relevant molQTL requires us to look in the right cells and states. EMMC is a targeted molQTL discovery programme with the vision generate quantitative, disease-relevant, functional genomic data to take genetic associations past the evidentiary threshold for therapeutic testing in patients.

EMMC Logo
Edinburgh Molecular Mechanisms Cluster.

EMMC will do this by examining single cells of several disease-relevant human tissues (brain, lung, blood and skin) in a number of states or perturbations to identify the molecular consequences of variation at genetic loci associated with human diseases.  

EMMC is led by scientists from across the University of Edinburgh including the Roslin Institute, Centre for Clinical Brain Sciences, Centre for Genomic and Experimental Medicine, Centre for Inflammation Research, MRC Human Genetics Unit, and the Baillie Gifford Pandemic Science Hub.

Diagram showing that different human tissues will be investigated in several different states
Various tissues will be investigated in a number of different perturbations.

Genetics has found thousands of disease associations, but very few of these can be linked to the cell-type specific molecular events that often drive disease. The EMMC funding will enable help provide molecular explanations for genetic associations, providing a foundation for mechanistic biology and therapeutic research across the University and beyond.