Abstract
Epigenetic editing is a promising strategy for modifying gene expression while avoiding the permanent alterations and potential genotoxicity of genome-editing technologies. Here we designed optimized epigenetic regulators (EpiRegs) by testing combinations of transcription activator-like effector (TALE)-based and catalytically deactivated Cas9 (dCas9)-based epigenetic modification effectors and fusion protein structures. TALE-based EpiReg (EpiReg-T) achieved a final efficiency of 98% in mice, surpassing the initial dCas9-based efficiency of 64%. We demonstrated the approach in macaques by introducing DNA methylation and histone modifications to inhibit proprotein convertase subtilisin/kexin type 9 (PCSK9) expression, thereby lowering low-density lipoprotein cholesterol levels. A single dose of EpiReg-T delivered with lipid nanoparticles achieved efficient (>90%) and long-lasting (343 days) silencing of PCSK9 in the liver. Integrative multiomic analyses revealed minimal off-target effects in EpiReg-T-treated monkeys, mice and human-derived cells. EpiReg can be redirected to other genes by reengineering the DNA-binding domain. Our findings represent a step toward the clinical application of epigenetic editing for the treatment of human diseases.
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Data availability
The raw sequencing data generated in this study were deposited to the National Center for Biotechnology Information Sequence Read Archive under BioProject PRJNA1303397. Data are available without restrictions as of the date of publication. All other data are available in the main text or Supplementary Information. Source data are provided with this paper.
References
Leibowitz, M. L. et al. Chromothripsis as an on-target consequence of CRISPR–Cas9 genome editing. Nat. Genet. 53, 895–905 (2021).
Turchiano, G. et al. Quantitative evaluation of chromosomal rearrangements in gene-edited human stem cells by CAST-Seq. Cell Stem Cell 28, 1136–1147 (2021).
Nahmad, A. D. et al. Frequent aneuploidy in primary human T cells after CRISPR–Cas9 cleavage. Nat. Biotechnol. 40, 1807–1813 (2022).
Cappelluti, M. A. et al. Durable and efficient gene silencing in vivo by hit-and-run epigenome editing. Nature 627, 416–423 (2024).
Urnov, F. D., Rebar, E. J., Holmes, M. C., Zhang, H. S. & Gregory, P. D. Genome editing with engineered zinc finger nucleases. Nat. Rev. Genet. 11, 636–646 (2010).
Carroll, D. Genome engineering with zinc-finger nucleases. Genetics 188, 773–782 (2011).
Boch, J. et al. Breaking the code of DNA binding specificity of TAL-type III effectors. Science 326, 1509–1512 (2009).
Moscou, M. J. & Bogdanove, A. J. A simple cipher governs DNA recognition by TAL effectors. Science 326, 1501 (2009).
Jinek, M. et al. A programmable dual-RNA–guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).
Tremblay, F. A potent epigenetic editor targeting human PCSK9 for durable reduction of low-density lipoprotein cholesterol levels. Nat. Med. 31, 1329–1338 (2025).
Nuñez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell 184, 2503–2519 (2021).
Cohen, J. C., Boerwinkle, E., Mosley, T. H. Jr & Hobbs, H. H. Sequence variations in PCSK9, low LDL, and protection against coronary heart disease. N. Engl. J. Med. 354, 1264–1272 (2006).
Rao, A. S. et al. Large-scale phenome-wide association study of PCSK9 variants demonstrates protection against ischemic stroke. Circ. Genom. Precis. Med. 11, e002162 (2018).
Ecco, G., Imbeault, M. & Trono, D. KRAB zinc finger proteins. Development 144, 2719–2729 (2017).
Alerasool, N., Segal, D., Lee, H. & Taipale, M. An efficient KRAB domain for CRISPRi applications in human cells. Nat. Methods 17, 1093–1096 (2020).
Haberland, M., Montgomery, R. L. & Olson, E. N. The many roles of histone deacetylases in development and physiology: implications for disease and therapy. Nat. Rev. Genet. 10, 32–42 (2009).
O'Geen, H. et al. Ezh2-dCas9 and KRAB-dCas9 enable engineering of epigenetic memory in a context-dependent manner. Epigenetics Chromatin 12, 26 (2019).
O’Geen, H., Tomkova, M., Combs, J. A., Tilley, E. K. & Segal, D. J. Determinants of heritable gene silencing for KRAB-dCas9+ DNMT3 and Ezh2-dCas9+ DNMT3 hit-and-run epigenome editing. Nucleic Acids Res. 50, 3239–3253 (2022).
Tanenbaum, M. E., Gilbert, L. A., Qi, L. S., Weissman, J. S. & Vale, R. D. A protein-tagging system for signal amplification in gene expression and fluorescence imaging. Cell 159, 635–646 (2014).
Gilbert, L. A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).
Musunuru, K. et al. In vivo CRISPR base editing of PCSK9 durably lowers cholesterol in primates. Nature 593, 429–434 (2021).
Lee, R. G. et al. Efficacy and safety of an investigational single-course CRISPR base-editing therapy targeting PCSK9 in nonhuman primate and mouse models. Circulation 147, 242–253 (2023).
Bannister, A. J. & Kouzarides, T. Regulation of chromatin by histone modifications. Cell Res. 21, 381–395 (2011).
Thakore, P. I. et al. Highly specific epigenome editing by CRISPR–Cas9 repressors for silencing of distal regulatory elements. Nat. Methods 12, 1143–1149 (2015).
Quenneville, S. et al. In embryonic stem cells, ZFP57/KAP1 recognize a methylated hexanucleotide to affect chromatin and DNA methylation of imprinting control regions. Mol. cell 44, 361–372 (2011).
Mitchell, C. & Willenbring, H. A reproducible and well-tolerated method for 2/3 partial hepatectomy in mice. Nat. Protoc. 3, 1167–1170 (2008).
Doyle, E. L. et al. TAL effector-nucleotide targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction. Nucleic Acids Res. 40, W117–W122 (2012).
Mussolino, C. et al. A novel TALE nuclease scaffold enables high genome editing activity in combination with low toxicity. Nucleic Acids Res. 39, 9283–9293 (2011).
Verdera, H. C., Kuranda, K. & Mingozzi, F. AAV vector immunogenicity in humans: a long journey to successful gene transfer. Mol. Ther. 28, 723–746 (2020).
Gallego-Colon, E., Daum, A. & Yosefy, C. Statins and PCSK9 inhibitors: a new lipid-lowering therapy. Eur. J. Pharmacol. 878, 173114 (2020).
Ray, K. K. et al. Inclisiran in patients at high cardiovascular risk with elevated LDL cholesterol. N. Engl. J. Med. 376, 1430–1440 (2017).
Finn, J. et al. A single administration of CRISPR/Cas9 lipid nanoparticles achieves robust and persistent in vivo genome editing. Cell Rep. 22, 2227–2235 (2018).
Conway, A. et al. Non-viral delivery of zinc finger nuclease mRNA enables highly efficient in vivo genome editing of multiple therapeutic gene targets. Mol. Ther. 27, 866–877 (2019).
Villiger, L. et al. In vivo cytidine base editing of hepatocytes without detectable off-target mutations in RNA and DNA. Nat. Biomed. Eng. 5, 179–189 (2021).
Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21 (2014).
Hovestadt, V. et al. Decoding the regulatory landscape of medulloblastoma using DNA methylation sequencing. Nature 510, 537–541 (2014).
Tarasov, A., Vilella, A. J., Cuppen, E., Nijman, I. J. & Prins, P. Sambamba: fast processing of NGS alignment formats. Bioinformatics 31, 2032–2034 (2015).
Hansen, K. D., Langmead, B. & Irizarry, R. A. BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biol. 13, R83 (2012).
Wu, H., Wang, C. & Wu, Z. A new shrinkage estimator for dispersion improves differential expression detection in RNA-seq data. Biostatistics 14, 232–243 (2013).
Krueger, F. TrimGalore: a wrapper tool around Cutadapt and FastQC to consistently apply quality and adapter trimming to FastQ files. Babraham Bioinformatics https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ (2015).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Yu, G., Wang, L.-G. & He, Q.-Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383 (2015).
Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).
Acknowledgements
We thank M. Poo for helpful discussions and insightful comments on this paper. The study was supported by the National Key Research and Development Program of China (2022YFC3400100 and 2024YFC3408000), the National Science and Technology Innovation 2030 Major Program (2021ZD0200900, 2021ZD0200101 and 2021ZD0200103), the National Natural Science Foundation of China Outstanding Youth Foundation (T2422026), the National Natural Science Foundation of China (U23A6010), the Science and Technology Projects of the Science and Technology Commission of Shanghai Municipality (23HC1401000) and the Shanghai Science and Technology Development Funds (21QA1409900 and 23QA1410400).
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C.Z., Y.S., S.M. and W.P. designed the study and interpreted the results. Z.F., P.W., Y.Z., C.Y. and H.W. constructed and screened plasmids. J.Z., H.L., X.Q., M.C., H.C. and D.S. conducted cell experiments, animal studies and ELISA assays. H.L. and Y.W. performed the CUT&Tag experiments. Y.C., L.W. and P.H. analyzed the data. J.S., J.L. and Z.L. contributed to the formulation and manufacturing of LNPs. Y.S. and S.M. wrote the paper. C.Z., Y.S. and J.X. supervised the project. All authors reviewed and approved the final manuscript.
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S.M., W.P., Z.F., Y.C., J.S., P.W., P.H., J.Z., L.W., Y.W., J.L., H.L., Y.Z., C.Y., X.Q., Z.L., H.W., M.C. and D.S. are employees of Epigenic Therapeutics. C.Z. and Y.S. are scientific co-founders of Epigenic Therapeutics. The study was supported by grants from Epigenic Therapeutics and the Institute of Neuroscience. The authors also declare patent applications related to various aspects of epigenetic editors and delivery methods.
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Extended data
Extended Data Fig. 1 In vivo target screening and optimization of EpiRegs.
a, Schematic of the workflow used to test different EpiReg versions in vivo. LNPs were administered to mice via tail vein injection. Blood samples were collected via retro-orbital bleeding at least 7 days post-injection for ELISA analysis. b, Bar graph showing the effect of different gRNAs on PCSK9 repression using the V1 version of EpiReg mRNA in AML12 cells. PCSK9 expression was measured by qPCR 7 days post-transfection. Data are presented as mean ± SEM, n = 3 independent experiments per group. Mm.gRNA8 was selected for use in subsequent experiments. c, schematic of dCas9-based EpiReg V10 and V11. d, Bar graph showing the efficiency of PCSK9 repression in wild-type mice using V10, V11 and V10 OP with Mm.gRNA8. The dose was 1 mg/kg and samples were collected 7 days post-injection. Data are presented as mean ± SEM, n = 5 animals per group. e, Schematic of different TALEs targeting various positions on human PCSK9. Red arrows indicate targets on the sense (top) or antisense (bottom) strands, with the selected TALE marked in blue. UTR and CDS regions are labeled, and CpG island is highlighted in blue. f-h, Bar graphs showing the efficiency of PCSK9 repression in three rounds of TALE screening in humanized PCSK9 mice, samples collected 7 days post-injection. Data are presented as mean ± SEM, n = 5 animals per group for all screenings. First round (f) using a V10-based structure at 1 mg/kg. Second round (g) using a V1-based structure at 3 mg/kg. Third round (h) using a V1-based structure at 3 mg/kg. i, Conservation analysis of TALE9 and TALE11 target sequences across mouse, monkey, and human. The TALE targeting sequences are highlighted in red, with asterisks marking conserved nucleotides across all three species. The -1 T nucleotide required for TALE binding is marked in blue. j, Schematic showing different EpiReg versions tested based on TALE11, displaying only the CDS regions. The full mRNA sequence includes UTRs and polyA sequences, which are identical for all versions. k, Bar graph showing the efficiency of PCSK9 repression in humanized PCSK9 mice using TALE11-based versions of EpiReg. The dose was 1 mg/kg, and samples were collected 14 days post-injection. Data are presented as mean ± SEM, n = 5 animals per group. l, Violin plot showing the distribution of methylation levels of every CpG site of Fig. 1d. Statistical analysis by two-tailed paired t-test, with a 95% confidence interval. Schematic in a created with BioRender.com.
Extended Data Fig. 2 gRNA screening and comparison of EpiReg-C and EpiReg-T.
a, b, Bar graph showing the effect of different gRNAs on PCSK9 repression using the V1 version of EpiReg mRNA in Huh7 cells (a) and primary monkey hepatocytes (b). A combination of Hs.gRNA1 + 2 (a) or Mfa.gRNA 5 + 12 (b) was selected for use in subsequent experiments. PCSK9 expression was measured by qPCR 7 days post-transfection. Data are presented as mean ± SEM, n = 3 independent experiments per group. c, The comparison between EpiReg-C and EpiReg-T at high doses in the second batch of humanized PCSK9 mice. Bar graph comparing the efficiency of PCSK9 repression. EpiRegs were administered via tail vein injection, and samples were collected 21 days post-injection. PCSK9 levels in the serum were measured by ELISA. Data are presented as mean ± SEM, n = 5 animals per group. To compare the differences, a two-tailed, unpaired Mann-Whitney test was performed. ns, not significant. d-f, Dose-response curves comparing the efficiency of EpiReg-C and EpiReg-T in Huh7 cells (d), PHH (e), and humanized PCSK9 mice (f). The half-maximum effective concentration (EC50) and the coefficient of determination (R2) for each group are indicated, calculated by fitting a four-parameter logistic model (R2 > 0.8 for all treatments). Dashed lines represent 50% inhibition. Data are presented as mean ± SEM, n = 3 for Huh7 and PHH, n = 5 for humanized PCSK9 mice. g, Bar graph comparing the EC50 values of EpiReg-C and EpiReg-T Huh7 cells, PHH, and humanized PCSK9 mice.
Extended Data Fig. 3 Transient H3K9me3 enrichment at the Pcsk9 locus after EpiReg-T administration.
a, b, CUT&Tag analysis of H3K9me3 enrichment at the Pcsk9 locus in liver tissue from wild-type mice following a single 1.5 mg/kg injection of EpiReg-T or PBS. At Day 28 post-injection, H3K9me3 levels are comparable between EpiReg-T and PBS groups (a). In contrast, at Day 3 post-injection, an increase in H3K9me3 is detected in the EpiReg-T group, supporting its role as an initiating signal for epigenetic silencing (b).
Extended Data Fig. 4 Long-term and redose pharmacodynamic effects of EpiReg-T in primates.
a-j, Absolute values of ALT (a), AST (b), total cholesterol (c), high-density lipoprotein (HDL) cholesterol (d), triglycerides (e), alkaline phosphatase (f), Gamma-glutamyltransferase (g), total bilirubin (h), albumin (i) and globulin (j) in monkeys portrayed in Fig. 4c (n = 4 animals for 0.75, 1.5, and 2.25 mg/kg groups, n = 2 animals for saline control group). The averages of blood samples collected 10 and 3 days before injection were calculated as baseline levels. Data are shown as mean for control and mean ± SEM for EpiReg-T groups.
Extended Data Fig. 5 On-target and off-target analysis in monkeys from 0.75 mg/kg and 2.25 mg/kg dose groups.
a, Volcano plots from an integrative analysis displaying expression changes for genes associated with DMRs in monkeys from 0.75 mg/kg and 2.25 mg/kg dose groups. b, Genome browser tracks displaying DNA methylation status at CASTOR2 and KEG98_p02. c, Line graph showing the long-term suppression of PCSK9 protein in individual monkeys from the saline control group (n = 2) and the 0.75 mg/kg EpiReg-T group (n = 4). EpiReg-T or saline was administered via intravenous injection, with a second injection on day 30. Results are presented as the percentage reduction from baseline for each individual monkey (labeled by ID). Dashed lines represent 100% of baseline levels. d, Bar graph showing PCSK9 expression levels in individual monkeys from the saline control group and the 0.75 mg/kg EpiReg-T group, as determined by RNA-seq analysis of liver biopsy samples collected on day 253 post-first injection.
Extended Data Fig. 6 Off-target evaluation of EpiReg-T in mice.
a-b, Off-target evaluation of EpiReg-T in wild-type mice 28 days after a single 1.5 mg/kg LNP injection. Volcano plots from an integrative analysis displaying expression changes for genes associated with DMRs (a) or computationally predicted near-cognate sites (b). Genes down-regulated and up-regulated in EpiReg-T-treated groups were marked as blue and red, respectively. Data shown are the mean values from each group, n = 3 animals per group.
Extended Data Fig. 7 Multi-omic off-target evaluation of EpiReg-T in human-derived cells.
a-f, Off-target assessment in PHH 14 days after transfection with 2.5 µg/ml EpiReg-T. Scatter plot of transcriptome-wide gene expression comparing EpiReg-T and control groups, with the on-target PCSK9 transcript highlighted (a). On-target DNA methylation analysis, showing specific methylation increase near the target site (b) and a Manhattan plot of differentially methylated CpGs across the genome (c). Volcano plot showing no significant expression changes in genes associated with computationally predicted near-cognate sites (d). Analysis of local spillover, showing no changes in the DNA methylation within the surrounding 10 kb window (e) or the expression of 10 flanking genes (f). g-h, Histone-level off-target assessment in Huh7 cells 3 days after transfection with 0.25 µg/ml EpiReg-T, including H3K4me3, H3K9ac, H3K27ac, and H3K27me3. Scatter plots display alterations, with significantly changed peaks highlighted in blue (g). Histone modification changes near the PCSK9 gene (h). Genes significantly down-regulated in EpiReg-T-treated groups were marked in blue. All data represent the mean of independent biological replicates (n = 2 for the control group; n = 3 for the experimental group).
Supplementary information
Supplementary Tables
Supplementary Table 1: List of DMRs and differentially expressed genes. Supplementary Table 2: gRNAs, TALE targets and primers used in this study. Supplementary Table 3: Plasmids and mRNA sequences used in this study. Supplementary Table 4: Near-cognate sequences of EpiReg-T.
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Mao, S., Peng, W., Feng, Z. et al. Design of optimized epigenetic regulators for durable gene silencing with application to PCSK9 in nonhuman primates. Nat Biotechnol (2025). https://doi.org/10.1038/s41587-025-02838-y
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DOI: https://doi.org/10.1038/s41587-025-02838-y
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