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A comprehensive map of missense trafficking variants in rhodopsin and their response to pharmacologic correction

Vrindavan Manian, K.; Ludwig, C. H.; Zhao, Y.; Abell, N. S.; Yang, X.; Root, D. E.; Albert, M. L.; Comander, J.

2025-03-04 genomics
10.1101/2025.02.27.640335 bioRxiv
Show abstract

Rhodopsin (RHO) missense variants are a leading cause of autosomal dominant retinitis pigmentosa (adRP), a progressive retinal degeneration with no currently approved therapies. Interpreting the pathogenicity of the growing number of identified RHO variants is a major clinical challenge, and understanding their disease mechanisms is essential for developing effective therapies. Here, we present a high-resolution map of RHO missense variant trafficking using two complementary deep mutational scanning (DMS) approaches based on a surface abundance immunoassay and a membrane proximity assay. We generated a comprehensive dataset encompassing all 6,612 possible single-residue missense variants, revealing a strong correlation between the two methods. Over 700 variants were identified with pathogenic trafficking scores, significantly expanding the number of RHO variants with functional evidence supporting pathogenicity. We demonstrate a high concordance between the trafficking scores and ClinVar pathogenicity classifications, highlighting this approachs utility in resolving variants of uncertain significance (VUS). The data also identified structurally clustered trafficking-deficient variants, predominantly within the N-terminal region and second extracellular loop, in and above the extracellular/intradiscal beta-plug region. Furthermore, we evaluated the efficacy of the non-retinoid pharmacological chaperone YC-001, observing significant rescue of trafficking defects in a majority of mistrafficking variants. This comprehensive functional map of RHO missense variants provides a valuable resource for pathogenicity assessment, genotype-phenotype correlations, and the development of targeted therapeutic strategies for RHO-adRP, paving the way for improved diagnosis and treatment for patients.

Published in Science Advances (predicted rank #17) · training set

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