Human functional genomics of post-translationally modifying clinical coding variants
The vision of our strategic MRC Human Functional Genomics Cluster is to mechanistically define the functional impact of PTM variants within the rare disease cohort of Genomics England’s genome resource. Bridging the knowledge gap between genomic associations, the biochemical function of PTMs and disease mechanism, our work will pave the way for personalised interventions that optimise clinical outcomes and provide diagnoses and peace-of-mind for patients with the rare disease.
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We computationally interrogate rare disease-associated missense variants from within Genomics England’s 100,000 genomes data resource (led by Prof. Smedley and Dr. David, and in collaboration with Genomics England). We then apply algorithmic atomistic modelling to prioritize functional sites (led by Dr. David, Prof. Barahona and Prof. Yaliraki).
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We generate new bioinformatic tools and process automation workflows for scalable and efficient engineering of the human proteome (led by Dr. Storch, Prof. Freemont and Dr. Child).
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Combining the outputs of our analysis, modeling & prediction with our automated engineering workflows we interpret the contribution of rare disease-associated missense variants to protein function, in live cells, at scale, and in high throughput (Dr. Storch, Prof. Freemont, Dr. Child and Prof. Tate).
We then undertake rigourous disease-appropriate orthogonal validation of variant functional annotations (led by Dr. Storch, Prof. Freemont, Dr. Child and Prof. Tate). -
Maximizing user access is a key aspect of our functional genomics cluster. We work toward data harmonization enabling stable data integration for researcher, clinician, and patient benefit (led by Prof. Smedley, Dr. David, Prof. Barahona, Prof. Yaliraki, Dr. Martin and Dr. Stephenson).
Our Team
To realize the vision of our cluster we have assembled a cross-disciplinary, multi-institutional team that brings together world-leading expertize in computational rare disease genomics, atomistic graph theory, algorithmic modelling of protein structure, bioprocess automation, high-throughput proteome engineering, chemoproteomics, data visualization and platform integration.
Dr Matthew Child, Cluster Lead, Dept. Life Sciences, Imperial College London
Prof. Damian Smedley, Clinical Pharmacology and Precision Medicine, QMUL
Prof. Sophia Yaliraki, Dept. Chemistry, Imperial
Prof. Mauricio Barahona, Dept. Mathematics, Imperial
Dr Alessia David, Dept. Life Sciences, Imperial
Prof. Paul Freemont, Dept. Medicine, Imperial
Dr Marko Storch, London Biofoundry, Imperial
Prof. Ed Tate, Dept. Chemistry, Imperial
Dr Jack Houghton, Dept. Chemistry, Imperial
Dr Maria Martin, EMBL-EBI
Dr James Stephenson, EMBL-EBI
