Mammalian and primate constraint to decipher human genetic disease and cancer

Evolutionary constraint is a unique identifier of functional sequences in the human genome. The level of constraint can define causative mutations for both inherited diseases and cancer.

The major aim of this project is to identify evolutionary constraint across mammals and specifically on the primate and canine lineages.

The generated constraint scores will be used to further characterize genome evolution as well as to identify variants that cause complex inherited diseases or cancers to develop.

Dogs are excellent spontaneous models for human disease and we utilize this to map genes in diseases where the disease phenotypes show the strongest homology e.g., amyotrophic lateral sclerosis (ALS) and obsessive compulsive disorder (OCD).

Genome-wide association mapping has identified thousands of associated regions, but it is still challenging to go beyond association and identify the disease-causing functional variants.

By defining the level of evolutionary constraint, we can understand which mutations are more likely to cause altered gene expression.

The same principle applies to somatic tumor mutations where non-coding mutations with high evolutionary constraint can point out novel cancer driver genes.

We will use machine learning to better detect functional variants and perform large scale experimental analysis to validate functionality and to find the genes affected by the mutations. These datasets will provide a unique opportunity to decipher the biology of human disease.