Abstract

The number of genetic studies of human traits and diseases has grown over the past years with hundreds of thousands of gene-to-phenotype mappings done through genome-wide association, clinical studies or studies of model organisms. However, connecting trait associated genetic variation to mechanisms through individual proteins and cellular processes remains a challenge. Our group is interested in building computational and experimental approaches that aim to address this challenge. In this talk I will briefly introduce some of our work on using AlphaFold models to study the impact of protein missense mutations and on predicting tissue type differences in protein-protein interactions. I will then focus primarily on describing our ongoing efforts to study the differences and similarities between genes linked to traits by different genetic approaches: GWAS, rare disorder studies and mouse KO phenotypes. We find that rare disorder studies and GWAS are biased in the identification of different types of genes that often do not overlap even for the same or related traits. Despite the low gene-level overlap, we observe convergence at the level of cellular processes linked to the same types of traits regardless of the technologies used to study gene-to-trait associations. Finally, we show how this convergence allows us to improve the prediction of novel candidate disease genes.