Saturation variant interpretation using CRISPR prime editing.

High-throughput functional characterization of genetic variants in their endogenous locus has so far been possible only with methods that rely on homology-directed repair, which are limited by low editing efficiencies. Here, we adapted CRISPR prime editing for high-throughput variant classification and combined it with a strategy that allows for haploidization of any locus, which simplifies variant interpretation. We demonstrate the utility of saturation prime editing (SPE) by applying it to the NPC intracellular cholesterol transporter 1 gene (NPC1), mutations in which cause the lysosomal storage disorder Niemann-Pick disease type C. Our data suggest that NPC1 is very sensitive to genetic perturbation, with 410 of 706 assayed missense mutations being classified as deleterious, and that the derived function score of variants is reflective of diverse molecular defects. We further applied our approach to the BRCA2 gene, demonstrating that SPE is translatable to other genes with an appropriate cellular assay. In sum, we show that SPE allows for efficient, accurate functional characterization of genetic variants.

Modeling Niemann-Pick disease type C in a human haploid cell line allows for patient variant characterization and clinical interpretation.

The accurate clinical interpretation of human sequence variation is foundational to personalized medicine. This remains a pressing challenge, however, as genome sequencing becomes routine and new functionally undefined variants rapidly accumulate. Here, we describe a platform for the rapid generation, characterization, and interpretation of genomic variants in haploid cells focusing on Niemann-Pick disease type C (NPC) as an example. NPC is a fatal neurodegenerative disorder characterized by a lysosomal accumulation of unesterified cholesterol and glycolipids. In 95% of cases, NPC is caused by mutations in the NPC1 gene, for which more than 200 unique disease-causing variants have been reported to date. Furthermore, the majority of patients with NPC are compound heterozygotes that often carry at least one private mutation, presenting a challenge for the characterization and classification of individual variants. Here, we have developed the first haploid cell model of NPC. This haploid cell model recapitulates the primary biochemical and molecular phenotypes typically found in patient-derived fibroblasts, illustrating its utility in modeling NPC. Additionally, we show the power of CRISPR/Cas9-mediated base editing in quickly and efficiently generating haploid cell models of individual patient variants in NPC. These models provide a platform for understanding the disease mechanisms underlying individual NPC1 variants while allowing for definitive clinical variant interpretation for NPC.