Interpretation of disease-causing genetic variants remains a challenge in the field of human genetics and rare disease. Current costs and complexity of performing deep mutational scanning for charting variant effects hampers crowd-sourcing approaches toward genome-wide resolution of variants in all disease-related genes. Our framework, Saturation Mutagenesis-Reinforced Functional assays (SMuRF), addresses these issues by modularizing DMS components, offering simple and cost-effective saturation mutagenesis, as well as streamlining functional assays to enhance interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we have generated functional scores for over 99.8% of all possible coding single nucleotide variants (SNVs), providing an additional line of evidence for clinical variant interpretation in dystroglycanopathies. Data generated from SMuRF enables severity prediction, resolve critical protein structural regions susceptible to missense disruptions, and provide training datasets for development of computational predictors. In summary, our approach provides a framework for enabling variant-to-function insights for disease genes in a manner that is accessible for crowd-sourcing implementation across standard research laboratories.

Deep Mutational Scanning in Rare Disease-related Genes with Saturation Mutagenesis-Reinforced Functional Assays (SMuRF)