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

Published: 15 August 2024| Version 1 | DOI: 10.17632/fgn9myv746.1
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Description

Interpretation of disease-causing genetic variants remains a challenge in human genetics. Current costs and complexity of deep mutational scanning methods are obstacles for achieving genome-wide resolution of variants in disease-related genes. Our framework, Saturation Mutagenesis-Reinforced Functional assays (SMuRF), offers simple and cost-effective saturation mutagenesis paired with streamlined functional assays to enhance the interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we generated functional scores for all possible coding single nucleotide variants, which aid in resolving clinically reported variants of uncertain significance. SMuRF also demonstrates utility in predicting disease severity, resolving critical structural regions, and providing training datasets for the development of computational predictors. Overall, our approach enables variant-to-function insights for disease genes in a cost-effective manner that can be broadly implemented by standard research laboratories. This dataset contains the designs, plasmid maps, raw results, raw data, raw pictures generated during the development of SMuRF. For application of SMuRF, please refer to the manuscript associated with this dataset.

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Funders

  • ML Bio Solutions
  • Muscular Dystrophy Association
    United States
    Grant ID: 629095
  • Chan Zuckerberg Initiative (United States)
    United States
    Grant ID: 2022-309740
  • Paul D. Wellstone Muscular Dystrophy Specialized Research Center
    Grant ID: 1U54NS053672
  • National Institute of Allergy And Infectious Diseases of the National Institutes of Health
    Grant ID: R01AI139238
  • Muscular Dystrophy Association
    United States
    Grant ID: MDA 963708
  • The Chris Carrino Foundation for FSHD
  • NIH
    Grant ID: 5F32AR079892-02
  • NCI Cancer Center Support
    Grant ID: # NIH P30 CA016359

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