ArticleCell2024
Saturation mutagenesis-reinforced functional assays for disease-related genes.
Article in Cell, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Knowledge-guided contextual gene set analysis with large language models.Bioinformatics (Oxford, England) · 2026Article
- Determining the intra-residue correlation of missense variant impact using MAVE scores: implications for the ACMG/AMP PM5 criterion for DNA variant classification.Genome medicine · 2026Article
- MaveMD: A functional data resource for genomic medicine.medRxiv : the preprint server for health sciences · 2025Article
- LARGE1 processively polymerizes length-controlled matriglycan on prodystroglycan.Nature communications · 2025Article
- Article
- Article
- Saturation mapping of MUTYH variant effects using DNA repair reporters.American journal of human genetics · 2025Article
- Article
- Development of patient-specific iPSC-based epilepsy models and identification of differentially expressed genes for disease mechanisms.Frontiers in neuroscience · 2025Article
- Genetics of inherited peripheral neuropathies and the next frontier: looking backwards to progress forwards.Journal of neurology, neurosurgery, and psychiatry · 2024Review
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16 authors.
Funding
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.