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Saturation variant interpretation using CRISPR prime editing

Nature Biotechnology volume 40, pages 885–895 (2022)Cite this article

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Abstract

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.

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Fig. 1: Allele-specific genome editing permits haploidization of the NPC1 locus.
Fig. 2: Establishment of a functional assay for variants in NPC1.
Fig. 3: SPE enables multiplexed interpretation of NPC1 variants.
Fig. 4: SPE function scores accurately reflect NPC1 variant pathogenicity.
Fig. 5: The functional classification of 426 variants in BRCA2 using SPE.

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Data availability

Next-generation sequencing data have been deposited to the NCBI Sequence Read Archive database under accession PRJNA728726. All function scores and corresponding classifications can be found in Supplementary Tables 1–3. The protein subgrouping underlying Fig. 4d is found in Supplementary Table 7. CADD scores underlying the plots in Figs. 4b,c and 5g are found in Supplementary Tables 1 and 3. Source data are provided with this paper.

Code availability

The custom Python scripts used in determining the function score and classification of each variant are available upon request.

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Acknowledgements

This study was supported by Niemann–Pick Canada and the SickKids Foundation. Additional support was provided by a research grant from the University of Pennsylvania Orphan Disease Center in partnership with The Andrew Coppola Foundation (grant no. MDBR-21-113-NPC to E.A.I.) and by the Canadian Institute for Health Research (project grant no. 462511 to E.A.I.). We also thank the Hospital for Sick Children (Restracomp to S.E). We thank D. Durocher for sharing the TP53-null RPE1 cells. We thank B. Thiruvahindrapuram and T. Nalpathamkalam of the Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Canada for assistance with applying their variant annotation pipeline. We are grateful to T. Durbic and the rest of the Donnelly Sequencing Centre staff for their assistance with sequencing experiments. This study was conducted with the support of the Ontario Institute for Cancer Research’s Genomics and Bioinformatics platform (genomics.oicr.on.ca) through funding provided by the Government of Ontario.

Author information

Author notes

  1. These authors contributed equally: Teija M.I. Bily, Jason Lequyer.

Authors and Affiliations

  1. Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada

    Steven Erwood, Jason Lequyer, Laurence Pelletier & Ronald D. Cohn

  2. Program in Genetics and Genome Biology, The Hospital for Sick Children Research Institute, Toronto, ON, Canada

    Steven Erwood, Teija M. I. Bily, Joyce Yan, Nitya Gulati, Reid A. Brewer, Liangchi Zhou, Evgueni A. Ivakine & Ronald D. Cohn

  3. Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada

    Jason Lequyer & Laurence Pelletier

  4. Department of Physiology, University of Toronto, Toronto, ON, Canada

    Reid A. Brewer & Evgueni A. Ivakine

  5. Department of Pediatrics, University of Toronto and The Hospital for Sick Children, Toronto, ON, Canada

    Ronald D. Cohn

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Contributions

S.E., T.M.I.B. and J.L. designed experiments. S.E., T.M.I.B., J.L., J.Y., N.G., R.A.B. and L.Z. performed experiments and analyzed data. J.L. designed and implemented the statistical framework for variant classification. S.E. and T.M.I.B. wrote the manuscript. All authors edited and revised the manuscript. E.A.I., L.P. and R.D.C. supervised the research.

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Correspondence to Evgueni A. Ivakine.

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Extended data

Extended Data Fig. 1 Characterization of the NPC1 haploidized HEK293T cell line.

(a) Schematic illustrating the position of digital droplet PCR probes (blue arrowheads) used to confirm haploidization. (b) Plot showing the droplet count values from assays used to measure NPC1 copy number relative to RNase P. The assay using probe 1, located in the unedited region, shows comparable counts between NPC1 and RNase P, while the assay from probe 2, located within the haploidized region, shows approximately one third the NPC1 droplets compared to RNase P. (c) Immunoblot for NPC1 demonstrating the relative NPC1 protein expression in wild type HEK293T cells versus NPC1 haploidized HEK293T cells. Values indicate quantity of protein lysate loaded in each lane. Representative image from one of two biological replicates. (d) Filipin staining was performed to visualize cholesterol distribution throughout wild type HEK293T cells, NPC1 haploidized HEK293T cells, and NPC1 haploidized NPC1 p.C909X cells. Distinct foci of cholesterol accumulation are apparent in NPC1 haploidized NPC1 p.C909X cells, which is absent from both wild type HEK293T cells and NPC1 haploidized HEK293T cells. Representative images from one of two biological replicates. Scale bars = 10 µm.

Extended Data Fig. 2 Functional scores for both NPC1 and BRCA2 were highly reproducible.

(a) Correlation of normalized functional scoring between replicates in NPC1 SPE experiments. (b) Correlation of normalized functional scoring between replicates in BRCA2 SPE experiments.

Extended Data Fig. 3 The three synonymous variants classified as deleterious disrupt proper NPC1 splicing.

(a) Immunoblot for NPC1 protein expression in each of the models isolated. Representative image from one of two biological replicates. (b) PCR amplification of cDNA from each model isolated revealed a distinct lower product that was absent in wild type control cDNA. Representative image from one of two biological replicates. (c) Sequencing of the lower PCR product depicted in (b) revealed errant splice products. These products are illustrated in the exon-intron diagrams. Arrowhead indicates approximate position of the mutation.

Source data

Extended Data Fig. 4 SPE is characterized by high editing efficiencies and product purity.

Data plotted as the mean ± standard deviation, (n = 8). PBS, primer binding site; RTT, reverse transcription template.

Extended Data Fig. 5 SPE is consistent along the length of the reverse transcription template.

Editing efficiencies of each individual mutation across the RT template are illustrated from four representative NPC1 SPE experiments (n = 8). The silent PAM-destroying is indicated within the square box. RTT, reverse transcription template.

Extended Data Fig. 6 Saturation prime editing is possible in RPE1 cells.

(a) Fluorescent distributions derived from fluorescence-activated cell sorting of LysoTracker-stained RPE1 wild type versus NPC1-deficient cell lines. (b) Plot of prime editing efficiency and outcomes in NPC1 haploidized RPE1 cells. PBS, primer binding site; RTT, reverse transcription template. Data plotted as the mean ± standard deviation (c) A plot illustrating the high correlation observed between function scores derived from saturation prime editing experiments in NPC1 haploidized HEK293T versus RPE cells (Pearson’s r = 0.92, n = 88). The functional consequence of each variant is indicated by colour.

Extended Data Fig. 7 NPC1 saturation prime editing function score reflects protein expression.

Immunoblot from subset of clones isolated from saturation prime editing experiments. The function scores followed by protein subgroups are listed in brackets. Colour of function score and protein category indicates functional classification with purple being deleterious and light turquoise being functional. Representative images from one of two biological replicates.

Source data

Extended Data Fig. 8 Copy number determination in the BRCA2 haploidized HEK293T cell line.

(a) Schematic illustrating the position of digital droplet PCR probes (blue arrowheads) used to confirm haploidization. (b) Plot showing the droplet count values from assays used to measure BRCA2 copy number relative to RNase P. The assay using probe 1, located in the haploidized region, shows approximately one third the droplets for BRCA2 compared to RNase P, while the assay from probe 2, located within the unedited region, shows comparable droplet counts between BRCA2 and RNase P.

Extended Data Fig. 9 Deleterious mutations result in impaired fitness in BRCA2 haploidized HEK293T cells.

(a,b) Plots showing the frequency of varied indels over time in BRCA2 haploidized HEK293T cells across two different loci. Frameshifting indels were markedly depleted between the two time points. Data plotted as the mean of two experimental replicates. (c-e) Editing frequency of each unique allele was determined by high-throughput sequencing over two timepoints. (c) BRCA2 p.Y2624C was introduced using base editing then depleted between the assayed time points. (d) BRCA2 p.S2691F was introduced using base editing then depleted between the assayed time points. (e) BRCA2 p.Y2726C was introduced using base editing then depleted between the assayed time points. Coloured letters indicate the amino acid change resulting from base editing.

Extended Data Fig. 10 Representative gating strategy used in the assay of NPC1 variants.

(a) Representative image depicting the initial gating of the population. (b) Representative image depicting the gating to exclude cell doublets. (c-d) Representative images depicting the linear gating strategy defining the ‘low’ and ‘high’ fluorescent populations. (c) Representative image depicting the distribution of LysoTrackerTM signal derived from unedited control NPC1 haploidized HEK293T cells. (d) Representative image depicting the distribution of LysoTrackerTM signal derived from NPC1 haploidized HEK293T cells that had been subject to saturation prime editing.

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2.

Reporting Summary.

Supplementary Tables

Supplementary Tables 1–7.

Source data

Source Data Fig. 2

Unprocessed western blots.

Source Data Fig. 4

Unprocessed western blots.

Source Data Extended Data Fig. 3

Unprocessed western blot and agarose gel.

Source Data Extended Data Fig. 7

Unprocessed western blots.

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Erwood, S., Bily, T.M.I., Lequyer, J. et al. Saturation variant interpretation using CRISPR prime editing. Nat Biotechnol 40, 885–895 (2022). https://doi.org/10.1038/s41587-021-01201-1

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