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Endogenous ADAR-mediated RNA editing in non-human primates using stereopure chemically modified oligonucleotides


Technologies that recruit and direct the activity of endogenous RNA-editing enzymes to specific cellular RNAs have therapeutic potential, but translating them from cell culture into animal models has been challenging. Here we describe short, chemically modified oligonucleotides called AIMers that direct efficient and specific A-to-I editing of endogenous transcripts by endogenous adenosine deaminases acting on RNA (ADAR) enzymes, including the ubiquitously and constitutively expressed ADAR1 p110 isoform. We show that fully chemically modified AIMers with chimeric backbones containing stereopure phosphorothioate and nitrogen-containing linkages based on phosphoryl guanidine enhanced potency and editing efficiency 100-fold compared with those with uniformly phosphorothioate-modified backbones in vitro. In vivo, AIMers targeted to hepatocytes with N-acetylgalactosamine achieve up to 50% editing with no bystander editing of the endogenous ACTB transcript in non-human primate liver, with editing persisting for at least one month. These results support further investigation of the therapeutic potential of stereopure AIMers.

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Fig. 1: AIMer optimization through structure–activity relationship analysis.
Fig. 2: Optimization for GalNAc–AIMers.
Fig. 3: Multiplex editing with AIMers and ADAR1 enzymes in primary human hepatocytes.
Fig. 4: AIMers support up to 50% ACTB editing in NHP liver.
Fig. 5: AIMers direct specific editing in vitro and in vivo.
Fig. 6: AIMers correct SERPINA1 Z transcript and increase AAT protein secretion from hepatocytes.

Data availability

RNA-seq data that support the findings of this study have been deposited in BioProject with the accession code PRJNA791338 ( Crystallographic data for PN-Rp-fGmA have been deposited in the Cambridge Structural Database with reference code 2113502. Genome assembly for off-target analysis in human cells relied on GRch38 ( Alu repeat regions were taken from UCSC Table Browser ( Source data are provided with this paper.


  1. Krokan, H. E., Drabløs, F. & Slupphaug, G. Uracil in DNA—occurrence, consequences and repair. Oncogene 21, 8935–8948 (2002).

    CAS  PubMed  Google Scholar 

  2. Cooper, D. N. & Krawczak, M. The mutational spectrum of single base-pair substitutions causing human genetic disease: patterns and predictions. Human Genet. 85, 55–74 (1990).

    CAS  Google Scholar 

  3. Sommer, B., Kohler, M., Sprengel, R. & Seeburg, P. H. RNA editing in brain controls a determinant of ion flow in glutamate-gated channels. Cell 67, 11–19 (1991).

    CAS  PubMed  Google Scholar 

  4. Lomeli, H. et al. Control of kinetic properties of AMPA receptor channels by nuclear RNA editing. Science 266, 1709–1713 (1994).

    CAS  PubMed  Google Scholar 

  5. Burns, C. M. et al. Regulation of serotonin-2C receptor G-protein coupling by RNA editing. Nature 387, 303–308 (1997).

    CAS  PubMed  Google Scholar 

  6. Patton, D. E., Silva, T. & Bezanilla, F. RNA editing generates a diverse array of transcripts encoding squid Kv2 K+ channels with altered functional properties. Neuron 19, 711–722 (1997).

    CAS  PubMed  Google Scholar 

  7. Chen, G., Katrekar, D. & Mali, P. RNA-guided adenosine deaminases: advances and challenges for therapeutic RNA editing. Biochemistry 58, 1947–1957 (2019).

    CAS  PubMed  Google Scholar 

  8. Bass, B. L. & Weintraub, H. An unwinding activity that covalently modifies its double-stranded RNA substrate. Cell 55, 1089–1098 (1988).

    CAS  PubMed  Google Scholar 

  9. Wong, S. K., Sato, S. & Lazinski, D. W. Substrate recognition by ADAR1 and ADAR2. RNA 7, 846–858 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Wettengel, J., Reautschnig, P., Geisler, S., Kahle, P. J. & Stafforst, T. Harnessing human ADAR2 for RNA repair—recoding a PINK1 mutation rescues mitophagy. Nucleic Acids Res. 45, 2797–2808 (2017).

    CAS  PubMed  Google Scholar 

  11. Schneider, M. F., Wettengel, J., Hoffmann, P. C. & Stafforst, T. Optimal guideRNAs for re-directing deaminase activity of hADAR1 and hADAR2 in trans. Nucleic Acids Res. 42, e87 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Montiel-Gonzalez, M. F., Vallecillo-Viejo, I., Yudowski, G. A. & Rosenthal, J. J. Correction of mutations within the cystic fibrosis transmembrane conductance regulator by site-directed RNA editing. Proc. Natl Acad. Sci. USA 110, 18285–18290 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Fukuda, M. et al. Construction of a guide-RNA for site-directed RNA mutagenesis utilising intracellular A-to-I RNA editing. Sci. Rep. 7, 41478 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Vallecillo-Viejo, I. C., Liscovitch-Brauer, N., Montiel-Gonzalez, M. F., Eisenberg, E. & Rosenthal, J. J. C. Abundant off-target edits from site-directed RNA editing can be reduced by nuclear localization of the editing enzyme. RNA Biol. 15, 104–114 (2018).

    PubMed  Google Scholar 

  15. Sinnamon, J. R. et al. Site-directed RNA repair of endogenous Mecp2 RNA in neurons. Proc. Natl Acad. Sci. USA 114, E9395–E9402 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Cox, D. B. T. et al. RNA editing with CRISPR–Cas13. Science 358, 1019–1027 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Montiel-González, M. F., Vallecillo-Viejo, I. C. & Rosenthal, J. J. An efficient system for selectively altering genetic information within mRNAs. Nucleic Acids Res. 44, e157 (2016).

    PubMed  PubMed Central  Google Scholar 

  18. Katrekar, D. et al. In vivo RNA editing of point mutations via RNA-guided adenosine deaminases. Nat. Methods 16, 239–242 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Merkle, T. et al. Precise RNA editing by recruiting endogenous ADARs with antisense oligonucleotides. Nat. Biotechnol. 37, 133–138 (2019).

    CAS  PubMed  Google Scholar 

  20. Qu, L. et al. Programmable RNA editing by recruiting endogenous ADAR using engineered RNAs. Nat. Biotechnol. 37, 1059–1069 (2019).

    CAS  PubMed  Google Scholar 

  21. Kupryushkin, M. S., Pyshnyi, D. V. & Stetsenko, D. A. Phosphoryl guanidines: a new type of nucleic acid analogues. Acta Naturae 6, 116–118 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Jarver, P., O’Donovan, L. & Gait, M. J. A chemical view of oligonucleotides for exon skipping and related drug applications. Nucleic Acid Ther. 24, 37–47 (2014).

    PubMed  PubMed Central  Google Scholar 

  23. Aartsma-Rus, A. & Arechavala-Gomeza, V. Why dystrophin quantification is key in the eteplirsen saga. Nat. Rev. Neurol. 14, 454–456 (2018).

    CAS  PubMed  Google Scholar 

  24. Cirak, S. et al. Exon skipping and dystrophin restoration in patients with Duchenne muscular dystrophy after systemic phosphorodiamidate morpholino oligomer treatment: an open-label, phase 2, dose-escalation study. Lancet 378, 595–605 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Kawecka, K. et al. Adeno-associated virus (AAV) mediated dystrophin gene transfer studies and exon skipping strategies for Duchenne muscular dystrophy (DMD). Curr. Gene Ther. 15, 395–415 (2015).

    CAS  PubMed  Google Scholar 

  26. Moulton, H. M. & Moulton, J. D. Morpholinos and their peptide conjugates: therapeutic promise and challenge for Duchenne muscular dystrophy. Biochim. Biophys. Acta 1798, 2296–2303 (2010).

    CAS  PubMed  Google Scholar 

  27. Viney, N. J. et al. Antisense oligonucleotides targeting apolipoprotein(a) in people with raised lipoprotein(a): two randomised, double-blind, placebo-controlled, dose-ranging trials. Lancet 388, 2239–2253 (2016).

    CAS  PubMed  Google Scholar 

  28. Nair, J. K. et al. Impact of enhanced metabolic stability on pharmacokinetics and pharmacodynamics of GalNAc-siRNA conjugates. Nucleic Acids Res. 45, 10969–10977 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Janas, M. M. et al. The nonclinical safety profile of GalNAc-conjugated RNAi therapeutics in subacute studies. Toxicol. Pathol. 46, 735–745 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Benjamin, D. et al. Calling somatic SNVs and indels with Mutect2. Preprint at bioRxiv (2019).

  31. Chen, Z. et al. Systematic comparison of somatic variant calling performance among different sequencing depth and mutation frequency. Sci. Rep. 10, 3501 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Bian, X. et al. Comparing the performance of selected variant callers using synthetic data and genome segmentation. BMC Bioinformatics 19, 429 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Strnad, P., McElvaney, N. G. & Lomas, D. A. Alpha1-antitrypsin deficiency. N. Engl. J. Med. 382, 1443–1455 (2020).

    CAS  PubMed  Google Scholar 

  34. Werder, R. B. et al. Adenine base editing reduces misfolded protein accumulation and toxicity in alpha-1 antitrypsin deficient patient iPSC-hepatocytes. Mol. Ther. 29, 3219–3229 (2021).

  35. Iwamoto, N. et al. Control of phosphorothioate stereochemistry substantially increases the efficacy of antisense oligonucleotides. Nat. Biotechnol. 35, 845–851 (2017).

    CAS  PubMed  Google Scholar 

  36. Vogel, P., Schneider, M. F., Wettengel, J. & Stafforst, T. Improving site-directed RNA editing in vitro and in cell culture by chemical modification of the guideRNA. Angew. Chem. 53, 6267–6271 (2014).

    CAS  Google Scholar 

  37. Butler, D. C. D. et al. Compounds, compositions and methods for synthesis. International patent WO 2018/237194-A1, edn. C07D 209/10 (2006.01), C07F 7/18 (2006.01) (2018).

  38. Butler, D., et al. Chiral design. International patent WO 2015107425-A3 (2014).

  39. Skvortsova, Y. V. et al. A new antisense phosphoryl guanidine oligo-2′-O-methylribonucleotide penetrates into intracellular Mycobacteria and suppresses target gene expression. Front. Pharmacol. 10, 1049 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Vargeese, C. et al. Oligonucleotide compositions and methods of use thereof. International patent WO/2018/223056 (2018).

  41. Kandasamy, P. et al. Technologies useful for oligonucleotide preparation. International patent WO/2020/191252 (2020).

  42. Kluesner, M. G. et al. EditR: a method to quantify base editing from Sanger sequencing. CRISPR J. 1, 239–250 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Kluesner, M. et al. MultiEditR: an easy validation method for detecting and quantifying RNA editing from Sanger sequencing. Mol. Ther. Nucleic Acids 25, 515–523 (2021).

  44. Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164 (2010).

    PubMed  PubMed Central  Google Scholar 

  45. R Development Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).

  46. Berthold, M. R. et al. in Data Analysis, Machine Learning and Applications. Studies in Classification, Data Analysis, and Knowledge Organization. (eds Preisach, C. et al.) 319–326 (Springer, 2008).

  47. Fox, J. & Weisberg, S. An R Companion to Applied Regression 3rd edn (Sage Publications, 2019).

  48. Hothorn, T., Bretz, F. & Westfall, P. Simultaneous inference in general parametric models. Biom. J. 50, 346–363 (2008).

    PubMed  Google Scholar 

  49. Genz, A. et al. mvtnorm: multivariate normal and t distributions (R package version 1.1-3) (2020).

  50. Genz, A. & Bretz, F. Computation of Multivariate Normal and t Probabilities Vol. 195 (Springer-Verlag, 2009).

  51. Zeileis, A. Object-oriented computation of sandwich estimators. J. Stat. Softw. 16, 1–16 (2006).

    Google Scholar 

  52. Zeileis, A. Econometric computing with HC and HAC covariance matrix estimators. J. Stat. Softw. 11, 1–17 (2004).

    Google Scholar 

  53. Ritz, C., Baty, F., Streibig, J. C. & Gerhard, D. Dose–response analysis using R. PLoS ONE 10, e0146021 (2015).

    PubMed  PubMed Central  Google Scholar 

  54. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).

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We are grateful to P. Shum and K. Bowman for analytical and process development support, A. Donner for assistance with graphics and writing, S. Towers and K. Mezic (Chameleon Communications International with funding from Wave Life Sciences) for the imagery shown in Extended Data Fig. 1b, S. Lamore for historical data for ALT/AST levels in cynomolgus monkeys and M. Cannon for support with in vivo studies. We are also grateful to Wave Life Sciences for funding.

Author information

Authors and Affiliations



P.M. and C.S. developed and performed in vitro assays, including conceiving the AIMer design and overall approach to evaluate structure–activity relationships for AIMers and ADAR enzymes. T.P. also performed in vitro assays. J.G. and J.M. supported biological experiments. P.K. and G.L. were the lead chemists for this study. M.S. contributed to synthesis and characterization of chiral amidites and dimers. S.M. purified dimers and obtained the crystal structure. B.B., A.C., K.B, D.B., D.C., F.F., J.K., A. Lindsey, R.L., G.L., J.R., S.S., S.T., H. Yu and C.Z. synthesized, formulated and ensured the quality of oligonucleotides, including GalNAc conjugates. N.I., P.K. and C.V. designed oligonucleotides, including placement of chemistry and stereochemistry. A. Lamattina performed all statistical analyses, except those related to off-target editing, and generated graphs and heat maps for data visualization. J.G. and H. Yang generated RNA-seq data. J.D. and A.H. evaluated RNA-seq data and performed off-target editing analysis. M.B. directed, T.K. performed and R.M. coordinated outsourcing for in vivo experiments. F.L. performed the ViewRNA analysis. Y.Y. and H. Yang quantified AIMers in tissues after treatment. A.B. conducted in vivo stability assays. C.V. and L.H.A. oversaw the research program. P.M., C.S. and C.V. conceived and designed experiments and interpreted results. P.M., C.S., A. Lamattina, J.D., A.H. and C.V. directed manuscript drafting, and all authors provided input on the manuscript.

Corresponding author

Correspondence to Chandra Vargeese.

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Competing interests

All authors were employed by Wave Life Sciences during completion of this work. P.M., M.S., C.S., G.L., D.B., J.D., J.G., A.H., N.I., J.K., P.K., A. Lamattina, S.S., H. Yang, H. Yu, L.H.A. and C.V. have patent applications (WO 2018/237194-A1, WO 2015107425-A3, WO 2020/191252) related to this work.

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Extended data

Extended Data Fig. 1 Short chemically modified oligonucleotides called AIMers support luciferase editing in vitro.

a, The reporter construct encodes Gaussia luciferase (Gluc, internal control) and Cypridinia luciferase (Cluc, RNA-editing reporter) only if the UAG stop codon in Cluc undergoes A-to-I editing. P2A is a self-cleaving peptide. An AIMer is depicted in the upper cartoon near the targeted editing site with 5’-end to the right. b, Inspiration for AIMer design. Schematic representation of the endogenous substrate from GluR (top), including stem-loop structure, mismatched bases in stem, and red box denoting edit region. Our predicted substrate (bottom), showing targeted RNA strand (black backbone) bound through complementary base pairing to AIMer (blue backbone). The AIMer is depicted with the 5’-end to the left. The arrangement of mismatches and base pairs is parallel between natural and predicted substrates. c, Fold-change in RNA-editing activity (compared with mock) for LUC-155 (black), a fully PS-modified 32-mer with ribose sugars throughout domains 1 and 2 except in the 5’-and 3’-ends, which have 2’-OMe modifications, and LUC-88 (green), an AIMer with the same sequence and ribose modifications but with a PO backbone. n = 2, mean ± s.e.m. Legend depicts chemical modifications used in this figure. d-f, ADAR-mediated editing activity is shown for ADAR1 and ADAR2 in the presence of fully PS-modified stereorandom AIMer with various 2’ modifications. e-f, Overall AIMer chemistry matches the cartoon at the top, except in the edit region, which is depicted in detail. Data are presented as mean ± s.e.m., n = 2. g, Fold change in relative luciferase activity with respect to AIMer length, with deletions from the 5’-end, 3’-end or both for ADAR1 p150 (left) or ADAR2 (right). AIMer length and truncations are denoted as 29,-1,-2 representing an AIMer 29 nucleotides in length with 1 nucleotide deleted from 5’-end and 2 nucleotides deleted from the 3’-end compared with LUC-374.

Source data

Extended Data Fig. 2 Control over backbone stereochemistry enhances ADAR1-mediated RNA editing of exogenous and endogenous transcripts.

a, Schematic representation of AIMers targeting ACTB. Fold change in relative luciferase expression at increasing concentrations of the indicated AIMers. Data are represented as mean ± s.e.m., n = 2. b, Traces from Sanger sequencing reactions from RPE cells treated with no AIMer (mock, left) or ACTB-33 (right). The red arrow indicates the site of A-to-I (G) editing.

Source data

Extended Data Fig. 3 GalNAc conjugate, lack of AIMer-directed antisense activity, IFNα-mediated induction of ADAR1 p150 and siRNA-mediated depletion of ADAR1 enzymes.

a, Chemical structure for tri-antennary GalNAc used in this work. b, Relative expression of ACTB in the presence of increasing concentrations of the indicated AIMers (normalized to mock-treated cells) in primary human hepatocytes, showing a lack of dose-dependent ACTB transcript depletion with (ACTB-40) or without (ACTB-9) GalNAc and with (ACTB-81) or without (ACTB-9) PN-backbone linkages. Data are presented as mean ± s.d., n = 3. Shading shows 95% confidence intervals. c, Blots showing expression of ADAR1 p150 (top green arrow), ADAR1 p110 (bottom green arrow) and vinculin loading control (red arrow) in ARPE-19 cells treated with the indicated siRNA with or without IFNα. Molecular weight marker (125 kDa) is shown (black line). Experiment was performed three times.

Source data

Extended Data Fig. 4 Preliminary pharmacology in mice supports evaluating AIMers in non-human primates.

a, Schematic representation of AIMers tested in vivo in mice and NHPs. Dosing regimen for 3 d study. Yellow arrow depicts subcutaneous AIMer administration to mice, and green arrow depicts sample collection. Graph depicts tissue exposure in the liver for the indicated AIMers. Data are represented as means (lines), and each point represents one animal, n = 3. b, Dosing regimen for single dose, 1-month study (arrows are as in panel a). Graph depicts tissue (liver) exposure kinetics over 30 d for representative AIMer (ACTB-386) after administration of a single dose. Data are represented as means (line), and each point represents one animal, n = 5. c, Dosing regimen for multi dose, 2-week study (arrows are as in panel a). Graphs depict ALT and AST levels for samples treated with PBS or the indicated AIMer. Data are represented as means (lines), and each point represents one animal, n = 5. d, Dose-dependent editing in vitro in NHP hepatocytes for increasing concentrations of GalNAc-AIMers. Percentage ACTB editing dose-dependently increased with increasing concentrations (0.27 nM, 1.33 nM, 6.67 nM, 33.3 nM) of the indicated AIMer. Data are represented as mean ± s.d.; n = 2. * not detected e, Percentage ACTB editing detected in kidney biopsies for the indicated AIMer 45 d post-dose. Data are represented as means (lines), and each point represents a biological replicate, n = 2, except for ACTB-387, where only one monkey was evaluated at day 45. f, Kidney concentration of the indicated AIMer in NHPs. Data are represented as in e. D day; ALT alanine aminotransferase; AST aspartate aminotransferase; PBS phosphate-buffered saline.

Source data

Extended Data Fig. 5 AIMers elicit highly specific editing in vitro and in vivo.

a, Scatter plot showing the correlation between percentage ACTB editing detected by RNA-seq and Sanger sequencing in mock- (n = 3), ACTB-69- (n = 3), and ACTB-40-treated primary human hepatocytes (n = 3). b, Number of filtered Alu-repeat sites found in ACTB-69 and ACTB-40 samples from primary human hepatocytes. c, Overlap of off-target sites edited by ACTB-40 and ACTB-69 in primary human hepatocytes. d, Scatter plot (top) of variants detected in ACTB-69 samples. On-target ACTB editing (blue) and off-target edits (red) having >3 LOD score and >5% editing. LOD score calculated by Mutect2 is the likelihood odds ratio that the variant exists in treated samples compared with mock samples. Genes with the highest percentage editing and highest LOD scores are labeled. Total RNA coverage (bottom) across replicates for all variants (potential edited sites). Confidence that variants are bona fide edit sites decreases as coverage decreases. e-f, Editing detected in samples treated with ACTB-387 (e) or ACTB-402 (f). For each panel, the top graph shows a scatter plot of variants detected in treated primary NHP hepatocytes in vitro. On-target ACTB editing (blue) and off-target edits (red) have >3 LOD score and >5% editing. Genes with the highest percentage editing and highest LOD scores are labeled. The bottom graph in each panel shows total RNA coverage across replicates for all variants (potential edited sites). Heat maps on the right depict the top 25 editing sites detected in vivo in NHP liver at off-target editing sites observed in vitro. Black boxes in the heat maps denote <10 reads of coverage in the in vivo sample.

Supplementary information

Supplementary Information

Supplementary Tables 1–9, Methods, Notes 1 and 2 and references.

Reporting Summary

Supplementary Data 1

Off-target analysis data from cultured primary human hepatocytes.

Supplementary Data 2

BLAST search for predicted off-target sites showing poor sequence similarity to targeted site in ACTB transcript.

Supplementary Data 3

Off-target analysis data from cultured primary NHP hepatocytes.

Supplementary Data 4

Off-target analysis data from in vivo in NHP liver samples.

Supplementary Data 5

Sequence, chemistry, mass and purity for all oligonucleotides in this study.

Source data

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Monian, P., Shivalila, C., Lu, G. et al. Endogenous ADAR-mediated RNA editing in non-human primates using stereopure chemically modified oligonucleotides. Nat Biotechnol (2022).

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