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Brewer, R. A.

Publications and source records attributed to Brewer, R. A..

2 recordsLinked to original sources

Saturation variant interpretation using CRISPR prime editing

Over the last decade, next generation sequencing has become widely implemented in clinical practice. However, as genetic variants of uncertain significance (VUS) are frequently identified, the need for scaled functional interpretation of such variants has become increasingly apparent. One method to address this is saturation genome editing (SGE), which allows for scaled multiplexed functional assessment of single nucleotide variants. The current applications of SGE, however, rely on homology-directed repair (HDR) to introduce variants of interest, which is limited by low editing efficiencies and low product purity. Here, we have adapted CRISPR prime editing for SGE and demonstrated its utility in understanding the functional significance of variants in the NPC1 gene underlying the lysosomal storage disorder Niemann-Pick disease type C1 (NPC). Additionally, we have designed a genome editing strategy that allows for the haploidization of gene loci, which permits isolated variant interpretation in virtually any cell type. By combining saturation prime editing (SPE) with a clinically relevant assay, we have functionally scored and interpreted 256 variants in NPC1 haploidized HEK293T cells. To further demonstrate the applicability of this strategy, we used SPE and cell model haploidization to functionally score 465 variants in the BRCA2 gene. We anticipate that our work will be translatable to any gene with an appropriate cellular assay, allowing for more rapid and accurate diagnosis and improved genetic counselling and ultimately precise patient care.

genetics↗

Modelling 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, where over 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 modelling NPC. Additionally, we demonstrate 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. While this study has focused on modelling NPC, the outlined approach could be translated widely and applied to a variety of genetic disorders or understanding the pathogenicity of somatic mutations in cancer.

genetics↗