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£3.6 million in funding awarded by the Wellcome Trust to combine cutting-edge 3D genome technologies with machine learning approaches to decipher the role of the non-coding genome in disease.

This week it was announced that Professors Jim Hughes and James Davies from the MRC Molecular Haematology Unit, in collaboration with Professor Cecelia Lindgren, Director of the Big Data Institute, have secured a Wellcome Discovery Award to expand their work on the genetics of common disease.

The prestigious 5-year grant aims to support ‘established researchers and teams from any discipline who want to pursue bold and creative research ideas to deliver significant shifts in understanding that could improve human life, health and wellbeing’.

“This Wellcome discovery award funds a multidisciplinary team from the WIMM and BDI to use cutting edge molecular, computational and machine learning approaches to map and model the regulatory wiring of the human genome at unprecedented detail.  Our aim is to make the 98% of the human genome that is non-coding as interpretable as the well-characterised 2% that encodes for protein.

This will ultimately allow us to decode the genetics, genes and pathways associated with the common diseases that affect us all and facilitate the development of genetically guided therapies in the future” says Professor Jim Hughes.

Their approach will train Artificial Intelligence algorithms on super-resolution maps of functional interactions between coding genes and their regulatory “switches” buried in the non-coding genome. These algorithms will then be able to determine the effect of sequence differences found in all our genomes on the activity of these genes and their links to human disease.

The researchers aim to use Micro Capture-C and Deep Neural Network Machine Learning to analyse vast quantities of genetic data. Micro Capture-C offer base-pair resolution maps showing the networks of genes and gene regulators in different types of cells. The power of this approach was demonstrated last year when the researchers uncovered gene regulatory regions associated with increased risk of death from COVID-19.

This project will make large steps towards mapping and deciphering the cell type-specific grammar and language of the non-coding genome, to understand the biology of common diseases and also for rare diseases for which there is no known molecular basis.

 

 

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