Since most dominant human mutations are single nucleotide substitutions1,2, we explored gene editing strategies to disrupt dominant mutations efficiently and selectively without affecting wild-type alleles. However, single nucleotide discrimination can be difficult to achieve3 because commonly used endonucleases, such as Streptococcus pyogenes Cas9 (SpCas9), can tolerate up to seven mismatches between guide RNA (gRNA) and target DNA. Furthermore, the protospacer-adjacent motif (PAM) in some Cas9 enzymes can tolerate mismatches with the target DNA3,4. To circumvent these limitations, we screened 14 Cas9/gRNA combinations for specific and efficient disruption of a nucleotide substitution that causes the dominant progressive hearing loss, DFNA36. As a model for DFNA36, we used Beethoven mice5, which harbor a point mutation in Tmc1, a gene required for hearing that encodes a pore-forming subunit of mechanosensory transduction channels in inner-ear hair cells6. We identified a PAM variant of Staphylococcus aureus Cas9 (SaCas9-KKH) that selectively and efficiently disrupted the mutant allele, but not the wild-type Tmc1/TMC1 allele, in Beethoven mice and in a DFNA36 human cell line. Adeno-associated virus (AAV)-mediated SaCas9-KKH delivery prevented deafness in Beethoven mice up to one year post injection. Analysis of current ClinVar entries revealed that ~21% of dominant human mutations could be targeted using a similar approach.
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Raw sequencing files have been be uploaded to NCBI’s Sequence Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra/PRJNA541170). A list of uploaded files including SRA IDs are listed in Supplementary Table 6. Detailed data analysis is available in the supplementary tables and supplementary data sets published with this manuscript. The pBG201 empty vector (pAAV-CMV-NLS(SV40)-SaCas9(E782K/N968K/R1015H)-NLS(nucleoplasmin)-3xHA-bGHpA0-U6-BsaI-sgRNA) is available upon completion of a standard Material Transfer Agreement with Harvard Medical School. The HAP1DFNA36 cell line is available upon request and completion of standard Material Transfer Agreement with Ecole Polytechnique Fédérale de Lausanne. Any other raw data including ABR traces and electrophysiological recordings that support the findings of this study are available from the corresponding author.
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We thank members of Holt/Géléoc and Corey laboratories for many helpful discussions and critical review of the manuscript. We thank the MGH DNA Core for sequencing services and the BCH Viral Core (BCH IDDRC, grant no. 1U54HD090255) for vector production. We also thank L. Pinello for assistance with CRISPResso analysis, V. Dillard for the help with TIDE analysis and A. A. Sousa for technical assistance with the GUIDE-Seq analysis. This work was supported by the Jeff and Kimberly Barber Fund and NIH grant nos. R01-DC013521 and R01-DC05439 (to J.R.H.), R01-DC000304 and R01-DC016932 (to D.P.C.), DC008853 (to G.S.G) and no. K99-CA218870, the Charles A. King Trust, a Banting Postdoctoral Fellowship (to B.P.K.), the Richard Floor Biorepository Fund, the Kosciuszko Foundation (to M.P.Z.) and by the Bertarelli Foundation. J.K.J. is supported by a Desmond and Ann Heathwood MGH Research Scholar award and B.G. was an Edward R. and Anne G. Lefler Center Postdoctoral Fellow.
J.R.H. holds patents on TMC1 gene therapy and is an advisor to several biotech firms focused on inner-ear therapies. J.K.J. has financial interests in Beam Therapeutics, Editas Medicine, Pairwise Plants, Poseida Therapeutics, Transposagen Biopharmaceuticals and Verve Therapeutics. J.K.J.’s interests were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict of interest policies. J.K.J. holds equity in Excelsior Genomics, and is a member of the Board of Directors of the American Society of Gene and Cell Therapy. J.K.J. and B.P.K. are co-inventors on various patents and patent applications that describe gene editing and epigenetic editing technologies. The authors declare no other competing interests.
Peer review information: Kate Gao and Brett Benedetti were the primary editors on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
a, gRNA design for SpCas9. Mutation site is highlighted in red. PAM sites are marked by green nucleotides. Mismatching nucleotides are shown in blue. The numbers or letters (for example, 1.1) next to the PAM site represent gRNAs IDs. Our gRNA 1.1 is identical to the Tmc1-mut3 gRNA in the study of Gao et al.16. Plasmids encoding SpCas9-2A–GFP, along with the different gRNAs, were transfected into fibroblasts. Four days after transfection, GFP-positive cells were sorted by FACS. b, Sanger-sequencing traces from Tmc1Bth/WT or Tmc1WT/WT mouse fibroblasts transfected with SpCas9-2A–GFP with or without gRNA 1.1. GFP expressing cells were sorted by FACS 4 d after transfection. The mutation site is marked by a red arrow. Additional peaks appearing downstream (marked by black arrowheads) of the mutation site demonstrate sequence heterogeneity and thus indel formation. Similar results were obtained by all gRNAs from two technical replicates (forward and reverse sequencing). Genome editing is apparent both in Tmc1Bth/WT or Tmc1WT/WT cells with SpCas9 + gRNA 1.1. c, Sanger-sequencing data were analyzed by TIDE. The control sample (SpCas9–2A-GFP only, black) and the genome edited sample (SpCas9-2A–GFP + gRNA 1.1, green) are overlaid. Downstream of the expected cut site (blue dashed line) the percentage of aberrant sequences was quantified in the region for decomposition. d, Indel percentages (mean ± s.d.) in Tmc1Bth/WT or Tmc1WT/WT cells based on TIDE analysis. Cells were transfected in duplicates and two independent sequencing reactions (forward and reverse) were performed. No indel formation was observed in the case of 3.1, 3.2 and 3.3 gRNAs. gRNA 1.4 showed minimal, but specific genome editing on the Tmc1Bth/WT cells. All the other gRNAs mediated efficient indel formation both in Tmc1Bth/WT or Tmc1WT/WT cells. e, Targeted deep sequencing on control (SpCas9-2A–GFP only) cells, WT gRNA and the three most specific gRNAs (1.1, 2.1 and 2.4) in Tmc1Bth/WT (top) Tmc1WT/WT (bottom) cells. Indels were quantified after segregating Tmc1Bth and Tmc1WT reads by CRISPResso (only insertions and deletions were quantified, substitutions were ignored). None of the gRNAs are specific to the Tmc1Bth allele, and mediate efficient indel formation on the Tmc1WT allele as well (light blue). Sequencing was performed one time from pooled cells, transfected in triplicates. Numbers in pie charts represent the percentage of reads. Specificity was defined as the indel percentage towards the targeted allele among total indels. The gRNA with the highest selectivity towards the Tmc1Bth allele was gRNA 2.4. f, The most abundant reads in the SpCas9 + gRNA 2.4 treated cells, shown separately for Tmc1Bth (top) and Tmc1WT (bottom) reads. The CRISPR cut site is marked by a black dashed line. Dashes represent deleted nucleotides. Insertions are shown with nucleotides in red squares. Nucleotides in bold are substitutions; however, these were not quantified as CRISPR actions. Sequences were aligned to Bth allele; thus, in the bottom panel, WT reads appear as having a substitution (a T to A change). The mutation site is marked by red arrow. Indel formation is evident in both Tmc1Bth and Tmc1WT reads. g, Indel profiles from SpCas9 + gRNA 2.4 transfected Tmc1Bth/WT fibroblasts. Tmc1Bth and Tmc1WT reads are plotted separately. Minus numbers represent deletions, plus numbers represent insertions. Sequences without indels (value = 0) are omitted from the chart. The most common indel event is a single base deletion. h, Indels causing in-frame versus frame-shift mutations (percentages are shown) in the coding sequence after SpCas9 + gRNA 2.4 transfection. i, GUIDE-Seq analysis on SpCas9 + gRNA 2.4 transfected Tmc1Bth/WT fibroblasts. Genomic DNA was isolated from three biological replicates for sequencing on one occasion. Only one off-target site was identified. Numbers next to reads are read counts in the GUIDE-Seq assay.
Extended Data Fig. 2 Number of indels based on targeted deep-sequencing data from Tmc1Bth/WT and Tmc1WT/WT cell lines treated with different Cas9 + gRNA combinations (from Fig. 1b).
Note that data points show non-normalized read counts. Cells were transfected on two different occasions (SpCas9 only and SpCas9 + gRNA 1.1 on four occasions) and genomic DNA from two independent biological samples on each transfection day were pooled for sequencing. Indels in the SaCas9-KKH treated Tmc1WT/WT lines are not different from the background (untreated samples). This method revealed high sensitivity, as the indel rates in CRISPR treated samples were 40–160-fold higher than the background indel rates observed in untreated samples.
Cells were transfected on two different occasions (SpCas9 only and SpCas9 + gRNA 1.1 on four occasions) and genomic DNA from two independent biological samples on each transfection day were pooled for sequencing. Substitutions are given as percentages (that is normalized to total read counts) or non-normalized values (that is, the number of reads with substitutions). Analysis was performed on non-segregated .fastq files in Tmc1Bth/WT cells and in Tmc1WT/WT cells (top) and segregated.fastq files in Tmc1Bth/WT cells (bottom). Experimental conditions are the same as in Fig. 1b. Substitutions were not frequent (0.1–0.5% of reads) and there was no difference between untreated and treated samples in the percentage or number of reads with single nucleotide substitutions.
Extended Data Fig. 4 Background sequencing error versus indel formation with SaCas9-KKH (mean ± s.d.).
Background sequencing error rate (GFP only) and comparison indel events in SaCas9-KKH + gRNA 4.1/gRNA 4.2 and gRNA 4.3 transfected Tmc1WT/WT fibroblasts are plotted. The difference is not significant (two-tailed t-test, P = 0.3).
a, Representative sensory transduction currents recorded at P14–P16 from IHCs and OHCs of WT mice injected with AAV–SaCas9-KKH–gRNA-4.2 at P1–P2. b, Mean ± s.e.m. maximal transduction current amplitudes for P14–P16 IHCs (left, n = 8) and OHCs (right, n = 6) from WT mice injected with AAV–SaCas9-KKH–gRNA-4.2 at P1–P2. c, Families of ABR waveforms recorded at 8 weeks from an uninjected Tmc1WT/WT mouse (left) and a Tmc1WT/WT mouse injected with AAV–SaCas9-KKH–gRNA-4.2 at P1 (right). Traces in bold indicate threshold. Scale bar applies to all traces. d, Mean ± s.d. ABR thresholds plotted as a function of stimulus frequency for six Tmc1WT/WT mice (black, n = 6) and three Tmc1WT/WT mice injected with AAV–SaCas9-KKH–gRNA-4.2 (gray) at 24 weeks of age (P = 0.9). e, Mean ± s.d. ABR thresholds plotted as a function of stimulus frequency for six Tmc1WT/WT mice (black), nine Tmc1Bth/WT and five Tmc1Bth/WT mice injected with AAV–SaCas9-KKH–gRNA-4.2 (green) at 24 weeks of age. 8 kHz thresholds for injected, 38 ± 11 dB (n = 9) and uninjected, 64 ± 19 dB (n = 8) were significantly different (P = 0.004, unpaired two-tailed t-test). ABR thresholds at higher frequencies (22 kHz) for injected (84 ± 15 dB, n = 9) and uninjected Tmc1Bth/WT mice (103 ± 5 dB, n = 8; P = 0.004, unpaired two-tailed t-test). f, Representative confocal images of 100-µm cochlear sections harvested at 24 weeks from the 8, 16 and 32 kHz regions from three uninjected Tmc1WT/WT mice (top) and three Tmc1WT/WT mice injected with AAV–SaCas9-KKH–gRNA-4.2 (bottom). The tissue was stained for MYO7A (red) and actin (green). g, Mean ± s.d., number of surviving IHCs (left) and OHCs (right) per 100-µm section (n = 3).
Extended Data Fig. 6 ABR amplitude, latencies and correlation of thresholds with surviving hair cells.
a,b, Peak 1 amplitudes (a) and peak 1 latencies (b) measured from 8 kHz ABR waveforms at the 8 week time point, from examples shown in Fig. 5a,c, for all Tmc1Bth/WT mice injected with AAV–SaCas9-KKH–gRNA-4.2 (green traces), and an example of an uninjected Tmc1Bth/WT (red trace). c, Mean ABR thresholds measured at 24 weeks, evoked by 8 and 16 kHz tone bursts (from Extended Data Fig. 5e) plotted as function of the mean percentage of surviving IHCs and OHCs from the 8 and 16 kHz regions (from Fig. 3h). The data were fit with a linear equation that had a slope of –2.1 dB per percentage point and a correlation coefficient of –0.82 (red line, Pearson’s r).
Extended Data Fig. 7 qPCR specific for ITR region in transfected plasmid (AAV–CMV–SaCas9-KKH–U6–gRNA) normalized to albumin gene in TMC1DFNA36 and TMC1WT HAP-1 cells.
Bars show mean ± s.d. Data points are from three independent biological replicates.
Extended Data Fig. 8 Number of indels based on targeted deep-sequencing data from TMC1DFNA36 and TMC1WT cells treated with different Cas9 + gRNA combinations (from Fig. 4c).
Note that data points show non-normalized read counts. Bars show mean ± s.d. Data points are from three independent biological replicates.
a, PCR and sequencing of the Tmc1 gene. b, Global indel analysis by CRISPResso. Reads were not segregated. c, Strategy to segregate Tmc1Bth reads and Tmc1WT reads. The region for splitting partly overlaps with indels and thus some reads cannot be assigned as mutant or WT. d, Allele-specific indel analysis by CRISPResso.
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György, B., Nist-Lund, C., Pan, B. et al. Allele-specific gene editing prevents deafness in a model of dominant progressive hearing loss. Nat Med 25, 1123–1130 (2019). https://doi.org/10.1038/s41591-019-0500-9
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