Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Potent and uniform fetal hemoglobin induction via base editing

Nature Genetics volume 55, pages 1210–1220 (2023)Cite this article

Subjects

Abstract

Inducing fetal hemoglobin (HbF) in red blood cells can alleviate β-thalassemia and sickle cell disease. We compared five strategies in CD34+ hematopoietic stem and progenitor cells, using either Cas9 nuclease or adenine base editors. The most potent modification was adenine base editor generation of γ-globin –175A>G. Homozygous –175A>G edited erythroid colonies expressed 81 ± 7% HbF versus 17 ± 11% in unedited controls, whereas HbF levels were lower and more variable for two Cas9 strategies targeting a BCL11A binding motif in the γ-globin promoter or a BCL11A erythroid enhancer. The –175A>G base edit also induced HbF more potently than a Cas9 approach in red blood cells generated after transplantation of CD34+ hematopoietic stem and progenitor cells into mice. Our data suggest a strategy for potent, uniform induction of HbF and provide insights into γ-globin gene regulation. More generally, we demonstrate that diverse indels generated by Cas9 can cause unexpected phenotypic variation that can be circumvented by base editing.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Potent induction of HbF with ABE7.10.
Fig. 2: γ-Globin –175A>G generates a TAL1-GATA1 binding motif that stimulates promoter–enhancer interactions.
Fig. 3: Base editing induces HbF more potently and with less clonal variability when compared with Cas9.
Fig. 4: Improved –175A>G editing frequency and HbF induction with ABE8e.
Fig. 5: Durable base editing of γ-globin –175A>G in BM-repopulating HSCs with induction of HbF in erythroid progeny.
Fig. 6: Off-target editing by ABE7.10 or ABE8e.

Similar content being viewed by others

Data availability

The plasmid used for spCas9-NG, ABE8e-NG and ABE7.10-NG protein purification from bacteria has been deposited at AddGene (ID 194705, 170663, 201190). DNA sequencing files can be accessed using the NCBI SRA. The CUT&RUN, RNA-seq and Micro Capture-C data are deposited in the Gene Expression Omnibus database (accession number GSE228822). All the sequencing data are mapped to the hg19 human genome. Source data are provided with this paper.

Code availability

The codes and pipeline used to perform RNA-seq, CUT-RUN and MicroC are available at https://github.com/YichaoOU/HbF_BE_NG_2023, https://doi.org/10.5281/zenodo.7922488.

References

  1. Piel, F. B., Steinberg, M. H. & Rees, D. C. Sickle cell disease. N. Engl. J. Med. 376, 1561–1573 (2017).

    Article  CAS  PubMed  Google Scholar 

  2. Taher, A. T., Musallam, K. M. & Cappellini, M. D. Beta-thalassemias. N. Engl. J. Med. 384, 727–743 (2021).

    Article  PubMed  Google Scholar 

  3. Doerfler, P. A. et al. Genetic therapies for the first molecular disease. J. Clin. Invest. 131, e146394 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Esrick, E. B. et al. Post-transcriptional genetic silencing of BCL11A to treat sickle cell disease. N. Engl. J. Med. 384, 205–215 (2021).

    Article  CAS  PubMed  Google Scholar 

  5. Frangoul, H. et al. CRISPR-Cas9 gene editing for sickle cell disease and β-thalassemia. N. Engl. J. Med. 384, 252–260 (2021).

    Article  CAS  PubMed  Google Scholar 

  6. Forget, B. G. Molecular basis of hereditary persistence of fetal hemoglobin. Ann. N. Y. Acad. Sci. 850, 38–44 (1998).

    Article  CAS  PubMed  Google Scholar 

  7. Wienert, B., Martyn, G. E., Funnell, A. P. W., Quinlan, K. G. R. & Crossley, M. Wake-up sleepy gene: reactivating fetal globin for beta-hemoglobinopathies. Trends Genet. 34, 927–940 (2018).

    Article  CAS  PubMed  Google Scholar 

  8. Métais, J.-Y. et al. Genome editing of HBG1 and HBG2 to induce fetal hemoglobin. Blood Adv. 3, 3379–3392 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Weber, L. et al. Editing a gamma-globin repressor binding site restores fetal hemoglobin synthesis and corrects the sickle cell disease phenotype. Sci. Adv. 6, eaay9392 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Humbert, O. et al. Therapeutically relevant engraftment of a CRISPR–Cas9-edited HSC-enriched population with HbF reactivation in nonhuman primates. Sci. Transl. Med. 11, eaaw3768 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Traxler, E. A. et al. A genome-editing strategy to treat β-hemoglobinopathies that recapitulates a mutation associated with a benign genetic condition. Nat. Med. 22, 987–990 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420–424 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Gaudelli, N. M. et al. Programmable base editing of A• T to G• C in genomic DNA without DNA cleavage. Nature 551, 464–471 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Wang, L. et al. Reactivation of gamma-globin expression through Cas9 or base editor to treat beta-hemoglobinopathies. Cell Res. 30, 276–278 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Zeng, J. et al. Therapeutic base editing of human hematopoietic stem cells. Nat. Med. 26, 535–541 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Ravi, N. S. et al. Identification of novel HPFH-like mutations by CRISPR base editing that elevate the expression of fetal hemoglobin. eLife 11, e65421 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Cheng, L. et al. Single-nucleotide-level mapping of DNA regulatory elements that control fetal hemoglobin expression. Nat. Genet. 53, 869–880 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Li, C. et al. In vivo HSPC gene therapy with base editors allows for efficient reactivation of fetal γ-globin in β-YAC mice. Blood Adv. 5, 1122–1135 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Gaudelli, N. M. et al. Directed evolution of adenine base editors with increased activity and therapeutic application. Nat. Biotechnol. 38, 892–900 (2020).

    Article  CAS  PubMed  Google Scholar 

  20. Fu, J. et al. Human cell based directed evolution of adenine base editors with improved efficiency. Nat. Commun. 12, 5897 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Antoniou, P. et al. Base-editing-mediated dissection of a γ-globin cis-regulatory element for the therapeutic reactivation of fetal hemoglobin expression. Nat. Commun. 13, 6618 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Leibowitz, M. L. et al. Chromothripsis as an on-target consequence of CRISPR-Cas9 genome editing. Nat. Genet. 53, 895–905 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Haapaniemi, E., Botla, S., Persson, J., Schmierer, B. & Taipale, J. CRISPR–Cas9 genome editing induces a p53-mediated DNA damage response. Nat. Med. 24, 927–930 (2018).

    Article  CAS  PubMed  Google Scholar 

  24. Ihry, R. J. et al. p53 inhibits CRISPR–Cas9 engineering in human pluripotent stem cells. Nat. Med. 24, 939–946 (2018).

    Article  CAS  PubMed  Google Scholar 

  25. Kosicki, M. et al. Cas9-induced large deletions and small indels are controlled in a convergent fashion. Nat. Commun. 13, 3422 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Weber, L. et al. Editing a γ-globin repressor binding site restores fetal hemoglobin synthesis and corrects the sickle cell disease phenotype. Sci. Adv. 6, eaay9392 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Park, S. H. et al. Comprehensive analysis and accurate quantification of unintended large gene modifications induced by CRISPR-Cas9 gene editing. Sci. Adv. 8, eabo7676 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Wienert, B. et al. KLF1 drives the expression of fetal hemoglobin in British HPFH. Blood 130, 803–807 (2017).

    Article  CAS  PubMed  Google Scholar 

  29. Wienert, B. et al. Editing the genome to introduce a beneficial naturally occurring mutation associated with increased fetal globin. Nat. Commun. 6, 1–8 (2015).

    Article  Google Scholar 

  30. Martyn, G. E. et al. A natural regulatory mutation in the proximal promoter elevates fetal globin expression by creating a de novo GATA1 site. Blood 133, 852–856 (2019).

    Article  CAS  PubMed  Google Scholar 

  31. Wu, Y. et al. Highly efficient therapeutic gene editing of human hematopoietic stem cells. Nat. Med. 25, 776–783 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Canver, M. C. et al. BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis. Nature 527, 192–197 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kurita, R. et al. Establishment of immortalized human erythroid progenitor cell lines able to produce enucleated red blood cells. PLoS ONE 8, e59890 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Doerfler, P. A. et al. Activation of γ-globin gene expression by GATA1 and NF-Y in hereditary persistence of fetal hemoglobin. Nat. Genet. 53, 1177–1186 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Manca, L. & Masala, B. Disorders of the synthesis of human fetal hemoglobin. IUBMB Life 60, 94–111 (2008).

    Article  CAS  PubMed  Google Scholar 

  36. Di Leonardo, A., Linke, S. P., Clarkin, K. & Wahl, G. M. DNA damage triggers a prolonged p53-dependent G1 arrest and long-term induction of Cip1 in normal human fibroblasts. Genes Dev. 8, 2540–2551 (1994).

    Article  PubMed  Google Scholar 

  37. el-Deiry, W. S. et al. WAF1/CIP1 is induced in p53-mediated G1 arrest and apoptosis. Cancer Res. 54, 1169–1174 (1994).

    CAS  PubMed  Google Scholar 

  38. Love, P. E., Warzecha, C. & Li, L. Ldb1 complexes: the new master regulators of erythroid gene transcription. Trends Genet. 30, 1–9 (2014).

    Article  CAS  PubMed  Google Scholar 

  39. Rochette, J., Craig, J. E., Thein, S. L. & Rochette, J. Fetal hemoglobin levels in adults. Blood Rev. 8, 213–224 (1994).

    Article  CAS  PubMed  Google Scholar 

  40. Richter, M. F. et al. Phage-assisted evolution of an adenine base editor with improved Cas domain compatibility and activity. Nat. Biotechnol. 38, 883–891 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Wang, J. et al. Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors. Genome Res. 22, 1798–1812 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Han, G. C. et al. Genome-wide organization of GATA1 and TAL1 determined at high resolution. Mol. Cell. Biol. 36, 157–172 (2016).

    Article  CAS  PubMed  Google Scholar 

  43. Doman, J. L., Raguram, A., Newby, G. A. & Liu, D. R. Evaluation and minimization of Cas9-independent off-target DNA editing by cytosine base editors. Nat. Biotechnol. 38, 620–628 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Masuda, T. et al. Transcription factors LRF and BCL11A independently repress expression of fetal hemoglobin. Science 351, 285–289 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Liu, N. et al. Direct promoter repression by BCL11A controls the fetal to adult hemoglobin switch. Cell 173, 430–442.e17 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sankaran, V. G. et al. Human fetal hemoglobin expression is regulated by the developmental stage-specific repressor BCL11A. Science 322, 1839–1842 (2008).

    Article  CAS  PubMed  Google Scholar 

  47. Martyn, G. E., Quinlan, K. G. R. & Crossley, M. The regulation of human globin promoters by CCAAT box elements and the recruitment of NF-Y. Biochim. Biophys. Acta Gene Regul. Mech. 1860, 525–536 (2017).

    Article  CAS  PubMed  Google Scholar 

  48. Amato, A. et al. Interpreting elevated fetal hemoglobin in pathology and health at the basic laboratory level: new and known γ- gene mutations associated with hereditary persistence of fetal hemoglobin. Int. J. Lab. Hematol. 36, 13–19 (2014).

    Article  CAS  PubMed  Google Scholar 

  49. Song, S. H. et al. Multiple functions of Ldb1 required for beta-globin activation during erythroid differentiation. Blood 116, 2356–2364 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Deng, W. et al. Reactivation of developmentally silenced globin genes by forced chromatin looping. Cell 158, 849–860 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Newby, G. A. et al. Base editing of haematopoietic stem cells rescues sickle cell disease in mice. Nature 595, 295–302 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Knipping, F. et al. Disruption of HIV-1 co-receptors CCR5 and CXCR4 in primary human T cells and hematopoietic stem and progenitor cells using base editing. Mol. Ther. 30, 130–144 (2022).

    Article  CAS  PubMed  Google Scholar 

  53. Rees, H. A., Wilson, C., Doman, J. L. & Liu, D. R. Analysis and minimization of cellular RNA editing by DNA adenine base editors. Sci. Adv. 5, eaax5717 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  54. Chu, S. H. et al. Rationally designed base editors for precise editing of the sickle cell disease mutation. CRISPR J. 4, 169–177 (2021).

    Article  CAS  PubMed  Google Scholar 

  55. Jiang, L. et al. Internally inlaid SaCas9 base editors enable window specific base editing. Theranostics 12, 4767–4778 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Steinberg, M. H. Fetal hemoglobin in sickle cell anemia. Blood 136, 2392–2400 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Huang, T. P. et al. Circularly permuted and PAM-modified Cas9 variants broaden the targeting scope of base editors. Nat. Biotechnol. 37, 626–631 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Huang, T. P., Newby, G. A. & Liu, D. R. Precision genome editing using cytosine and adenine base editors in mammalian cells. Nat. Protoc. 16, 1089–1128 (2021).

    Article  CAS  PubMed  Google Scholar 

  59. Sentmanat, M. F., Peters, S. T., Florian, C. P., Connelly, J. P. & Pruett-Miller, S. M. A survey of validation strategies for CRISPR-Cas9 editing. Sci. Rep. 8, 888 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Connelly, J. P. & Pruett-Miller, S. M. CRIS.Py: a versatile and high-throughput analysis program for CRISPR-based genome editing. Sci. Rep. 9, 4194 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Hu, J. et al. Isolation and functional characterization of human erythroblasts at distinct stages: implications for understanding of normal and disordered erythropoiesis in vivo. Blood 121, 3246–3253 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Martyn, G. E. et al. Natural regulatory mutations elevate the fetal globin gene via disruption of BCL11A or ZBTB7A binding. Nat. Genet. 50, 498–503 (2018).

    Article  CAS  PubMed  Google Scholar 

  63. Hua, P. et al. Defining genome architecture at base-pair resolution. Nature 595, 125–129 (2021).

    Article  CAS  PubMed  Google Scholar 

  64. Kent, W. J. BLAT—the BLAST-like alignment tool. Genome Res. 12, 656–664 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Tsai, S. Q. et al. CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR–Cas9 nuclease off-targets. Nat. Methods 14, 607–614 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Bae, S., Park, J. & Kim, J.-S. Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics 30, 1473–1475 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Hollander, M., Wolfe, D. A. & Chicken, E. Nonparametric Statistical Methods (John Wiley & Sons, 2013).

Download references

Acknowledgements

We are grateful to the patients with SCD who contributed samples for this study. HUDEP1 and HUDEP2 cells were a gift from R. Kurita and Y. Nakamura (RIKEN BioResource Center). APC-conjugated anti-Band3 was a gift from X. An (New York Blood Center). We thank the following core facilities and individuals at St. Jude Children’s Research Hospital: Flow Cytometry (David Cullins, Richard Ashmun and Stacie Woolard), the Animal Resource Center (Chandra Savage), and the Protein Production Core (Richard Heath). We thank Keith A. Laycock for editing the manuscript. This work was supported by National Institutes of Health (NIH) award nos. U01 AI142756, RM1 HG009490, R01 EB022376, R35 GM118062 (D.R.L.), R01 HL156647, R01 HL136135 (M.J.W. and D.R.L.), P01 HL053749 (M.J.W. and S.Q.T.), U01 AI157189 (S.Q.T.) and R35 GM133614 (Y.C.); the Bill and Melinda Gates Foundation (J.S.Y., D.R.L. and M.J.W.); the Howard Hughes Medical Institute (D.R.L.); the St. Jude Collaborative Research Consortium for SCD (J.S.Y., D.R.L., S.M.P.-M., S.Q.T. and M.J.W.); the Doris Duke Foundation (for aspects of this study that did not use mice) (M.J.W., S.Q.T. and A.S.); the American Lebanese Syrian Associated Charities (J.S.Y., A.S. and M.J.W.) and the Assisi Foundation of Memphis (M.J.W.). G.A.N. was supported by a Helen Hay Whitney Postdoctoral Fellowship of the HHMI and by K99 award HL163805. P.A.D. was supported by a Cooley’s Anemia Foundation Postdoctoral Research Fellowship Award and by NIH award K01 DK132453. S.B. is supported by the American Society of Hematology (RTAF). The St. Jude Children’s Research Hospital core facilities are supported by NIH grant P30 CA21765 and by St. Jude/ALSAC. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The funders had no role in the study design, the data collection and analysis, the decision to publish the work or the preparation of the manuscript.

Author information

Author notes

  1. These authors contributed equally: Thiyagaraj Mayuranathan, Gregory A. Newby.

Authors and Affiliations

  1. Department of Hematology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Thiyagaraj Mayuranathan, Ruopeng Feng, Yu Yao, Kalin D. Mayberry, Cicera R. Lazzarotto, Yichao Li, Rachel M. Levine, Nikitha Nimmagadda, Erin Dempsey, Phillip A. Doerfler, Jingjing Zhang, Yoonjeong Jang, Jingjing Chen, Senthil Velan Bhoopalan, Yong Cheng, Shengdar Q. Tsai, Mitchell J. Weiss & Jonathan S. Yen

  2. Merkin Institute of Transformative Technologies in Healthcare, Broad Institute of Harvard and MIT, Cambridge, MA, USA

    Gregory A. Newby & David R. Liu

  3. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA

    Gregory A. Newby & David R. Liu

  4. Howard Hughes Medical Institute, Harvard University, Cambridge, MA, USA

    Gregory A. Newby & David R. Liu

  5. Department of Biostatistics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Guolian Kang

  6. Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Shaina N. Porter & Shondra M. Pruett-Miller

  7. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia

    Henry W. Bell & Merlin Crossley

  8. Department of Bone Marrow Transplantation and Cellular Therapy, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Akshay Sharma

  9. Cellular and Molecular Therapeutics Branch, National Heart, Lung, and Blood Institute and National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA

    John F. Tisdale

Authors
  1. Thiyagaraj Mayuranathan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gregory A. Newby
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ruopeng Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yu Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kalin D. Mayberry
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Cicera R. Lazzarotto
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yichao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Rachel M. Levine
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nikitha Nimmagadda
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Erin Dempsey
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Guolian Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Shaina N. Porter
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Phillip A. Doerfler
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Jingjing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Yoonjeong Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Jingjing Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Henry W. Bell
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Merlin Crossley
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Senthil Velan Bhoopalan
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Akshay Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. John F. Tisdale
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Shondra M. Pruett-Miller
    View author publications

    You can also search for this author in PubMed Google Scholar

  23. Yong Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  24. Shengdar Q. Tsai
    View author publications

    You can also search for this author in PubMed Google Scholar

  25. David R. Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  26. Mitchell J. Weiss
    View author publications

    You can also search for this author in PubMed Google Scholar

  27. Jonathan S. Yen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

T.M., G.A.N., R.F., Y.Y., K.D.M., C.R.L., Y.L., R.M.L., N.N., E.A.D.D., G.K., S.N.P., P.A.D., J.Z., Y.J., J.C., H.W.B. and S.V.B. conducted experiments and analyzed data. M.C., A.S., J.F.T., S.M.P.-M., Y.C. and S.Q.T. prepared materials and provided advice. T.M., G.A.N., J.S.Y., M.J.W. and D.R.L. wrote the manuscript with input from all authors. J.S.Y., M.J.W. and D.R.L. supervised this study.

Corresponding authors

Correspondence to David R. Liu, Mitchell J. Weiss or Jonathan S. Yen.

Ethics declarations

Competing interests

The authors have filed patent applications on genome-editing agents. D.R.L. is a consultant and equity owner of Beam Therapeutics, Prime Medicine, Pairwise Plants, Chroma Medicine and Nvelop Therapeutics, companies that use or deliver genome editing or genome engineering agents. M.J.W. is a consultant for GSK, Cellarity, Novartis and Dyne Therapeutics. A.S. is a consultant for Spotlight Therapeutics, Medexus., and Vertex Pharmaceuticals. A.S. has also received research funding from CRISPR Therapeutics and honoraria from Vindico Medical Education. A.S. is the St. Jude Children’s Research Hospital site principal investigator of clinical trials for genome editing of sickle cell disease sponsored by Vertex Pharmaceuticals/CRISPR Therapeutics (NCT03745287), Novartis Pharmaceuticals (NCT04443907) and Beam Therapeutics (NCT05456880). The industry sponsors provide funding for the clinical trial, which includes salary support. A.S. has no direct financial interest in these therapies. J.S.Y. is an equity owner of Beam Therapeutics. S.Q.T. is a co-inventor on patents covering the CIRCLE-seq and CHANGE-seq methods. S.Q.T. is a member of the scientific advisory boards of Kromatid and Twelve Bio. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Genetics thanks James Davies, Luigi Naldini and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Insertion/deletion (indel) mutations generated in healthy donor CD34+ hematopoietic stem and progenitor cells (HSPCs) by Cas9 nuclease.

a, BCL11A gene showing the target GATA1 binding motif (TGATAA) in the +58 BCL11A erythroid enhancer highlighted in green. The single-guide RNA (sgRNA) protospacer and protospacer-adjacent motifs (PAM) are shown in black and red, respectively. The vertical dotted line indicates the Cas9 cleavage site. b, The γ-globin (HBG1/2) gene showing the target BCL11A binding motif (TGACCA) in the promoter highlighted in yellow. c,d, Sequence alignments of the BCL11A and γ-globin genes showing the most common Cas9 indels determined by next-generation sequencing (NGS) 3 days after editing. The sgRNA sequences are underlined with PAM in red text. Targeted transcription factor binding motifs are indicated by the orange columns and shown in the wild type (WT) sequences as underlined blue text. Deletions are represented by dashes and insertions by green text. The % of each indel relative to total NGS reads is shown at right. e, Percentage of indels after base editing (n = 8 for UT, −198, −175 and −113, n = 6 for NT). Bar graphs show mean ± standard deviation (SD). Each symbol represents an independent experiment with different shapes representing unique HSPC donors. UT, untreated. NT, non-targeting gRNA.

Source data

Extended Data Fig. 2 Erythroid differentiation of CD34+ HSPCs after editing with ABE7.10 or Cas9 nuclease.

Erythroid differentiation of CD34+ HSPCs after editing with ABE7.10 complexed with sgRNA −175 or Cas9 nuclease complexed with sgRNA targeting the BCL11A binding site in the γ-globin promoter, the +58 BCL11A erythroid enhancer or the control locus AAVS1. Cells were edited by electroporation with RNPs, incubated in CD34+ expansion medium for two days, then transferred to erythroid differentiation medium. a, Cell expansion after base editing (n = 2 from two donors). b, Cell expansion after Cas9 editing (n = 3 from one donor). c, Representative flow cytometry scatter plot showing maturation markers in CD235a+ erythroblasts after 7 and 14 days of in vitro erythroid differentiation. d, Summary of multiple experiments to assess cell maturation using gating strategy depicted in panel c. n = 2 replicates each from two donors for ABE7.10 and n = 3 from one donor for Cas9. e, Representative flow cytometry scatter plot showing enucleated reticulocytes distinguished by loss of staining with the DNA-binding dye Hoechst 33342 (gated). f, Percentage of enucleated CD235a+ erythroid cells (reticulocytes) at differentiation day 21 (n = 4 from two donors for ABE7.10 and n = 3 from one donor for Cas9). Graphs show mean ± SD. UT, untreated. NT, non-targeting gRNA.

Source data

Extended Data Fig. 3 Analysis of γ-globin −175A > G edited HUDEP2 cells.

a, HUDEP2Degdb cells harboring a heterozygous 91-kb deletion encompassing the extended β-like globin locus were edited with ABE7.10 protein complexed with sgRNA −175. b, Editing outcomes in γ-globin promoters of HBG2 and HBG1 and nomenclature for clones. c, Representative reverse-phase high performance liquid chromatography (RP-HPLC) chromatograms of lysates from HUDEP2Degdb clones with the indicated genotypes after 10 days of culture in erythroid differentiation medium. Gγ and Aγ refer to the protein products of HBG2 and HBG1, respectively. d, Percentage of β-like globins in HUDEP2Degdb clones with the indicated genotypes. WT, n = 5; HBG2−175G, n = 4; HBG1−175G, n = 2; HBG1/2−175G, n = 6. Bar graphs show mean ± SD with each dot representing a separate clone. LCR, locus control region. WT, wild type.

Source data

Extended Data Fig. 4 DNA damage response and 4.9-kb deletion analysis of ABE7.10-edited or Cas9 nuclease–edited HSPCs.

Healthy donor CD34+ cells were edited by electroporation with Cas9 nuclease protein complexed with sgRNA targeting the γ-globin promoter BCL11A binding motif or ABE7.10 protein complexed with sgRNA −175. a, Frequencies of on-target ABE7.10 edits or Cas9 nuclease indels measured by NGS. b, Relative expression of CDKN1 (P21) mRNA vs. hours after electroporation, measured by droplet digital PCR (ddPCR) and normalized to RPP30 mRNA. c, Quantitative PCR detection method used to assess the frequency of the 4.9-kb HBG2–HBG1 intergenic deletion resulting from simultaneous on-target indels. d, Percentage of the 4.9-kb deletion after editing by ABE7.10 or Cas9 nuclease. Graphs show mean ± SD (n = 3 independent replicates from one CD34+ cell donor). P values were determined using a two-sample t-test to assess differences between the Cas9 nuclease-treated samples and the electroporated control. UT, untreated.

Source data

Extended Data Fig. 5 Dose-titration of Cas9 nuclease RNP targeting the BCL11A binding site in the γ-globin promoters.

Healthy donor CD34+ HSPCs were electroporated with the indicated doses of Cas9 complexed to the sgRNA shown in Extended Data Fig. 1b, followed by induced erythroid differentiation. a, Indel frequencies at day 3. b, Distributions of specific indels at day 3. c, Relative expression of CDKN1 (P21) mRNA vs. hours after electroporation d, Percentage of alleles with the 4.9-kb deletion at day 6. e, Percentage of HbF on day 21 of erythroid differentiation. Graphs show mean ± SD (n = 3 independent replicates from one CD34+ cell donor).

Source data

Extended Data Fig. 6 Effect of the −175A > G edit on HbF and transcription factor binding in WT HUDEP2 cells.

Effect of the −175A > G edit on HbF and transcription factor binding in WT HUDEP2 cells (β-globin-like globin loci intact). HUDEP2 cells were electroporated with ABE7.10 protein complexed with sgRNA −175. Negative controls included untreated cells (UT) that received no electroporation and cells electroporated with ABE7.10 protein complexed with AAVS1 sgRNA. a, Frequencies of on-target (A5) and bystander (A3, A11) γ-globin edits 3 days after electroporation. b, Frequencies of AAVS1 edits at 3 days after electroporation. c, % F-cells in the bulk-edited population on day 4 after electroporation. d, %HbF in the bulk-edited population after 10 days of erythroid maturation. Graphs show mean ± SD (n = 3). e, CUT&RUN analysis to assess chromatin occupancy of TAL1, GATA1, LDB1, and LMO2 in a wild type (WT) HUDEP2 clone or a clone with −175A > G base edits at all four γ-globin promoters. f, Model for HbF induction by −175A > G. The −175A > G variant creates a new TAL1 binding motif near a GATA motif that binds GATA1. Binding of TAL1 stimulates recruitment of the indicated proteins. Homodimerization of LDB1 within the γ-globin promoter protein complex and a similar complex at the locus control region (LCR) mediates DNA looping and transcriptional activation. WT, wild type; UT, untreated.

Source data

Extended Data Fig. 7 Induction of HbF according to the frequency of common indels alleles in erythroid colonies generated from Cas9 nuclease-edited or base edited CD34+ cells.

a–f, Percentage of HbF according to the frequency of the specified indel in the γ-globin promoter BCL11A motif. Most colonies analyzed have indels at all γ-globin promoters (see main Fig. 3a,b). Colonies have 0% of a given indel allele if the indicated indel was not detected by sequencing that colony (n = 353). g–j, Percentage of HbF according to the frequency of the specified indel in the +58 BCL11A erythroid gene enhancer (n = 228). k, Percentage of HbF according to the frequency of the ABE7.10-generated −175A > G (n = 221). EST, coefficient estimate, corresponding to the slope of the linear regression line, adjusting for batch effects; P, statistical significance calculated by a linear regression model adjusting for batch effects. Each dot represents a separate clone and each color represents a different CD34+ cell donor.

Source data

Extended Data Fig. 8 Comparison of ABE7.10 and ABE8e editing at γ-globin −175A>G in healthy donor CD34+ HSPCs.

Controls included UT and AAVS1 sgRNA. Cells were edited by electroporation with RNPs, incubated in expansion medium for two days, then transferred to erythroid differentiation medium. a, Results of a Design of Experiment (DoE) study to optimize ABE8e concentration and sgRNA molar ratio (see Methods). Red color indicates most efficient editing. An ABE concentration of 8 µM with a 3.5-fold excess of sgRNA was determined to be optimal and used in subsequent experiments. b, AAVS1 editing frequencies six days after electroporation (n = 3). c, Indel frequencies six days after electroporation (n = 9 for UT, ABE7.10 and ABE8e −175; n = 3 for AAVS1, ABE7.10, and ABE8e). d, Cell viability and e, cell recovery two days after electroporation (n = 3). f, %HbF in control edited cells (n = 3). g, Cell number versus days erythroid differentiation (n = 3). h, Representative flow cytometry scatter plots of maturation markers in CD235a+ erythroblasts after 7 and 14 days of in vitro erythroid differentiation. i, Summary of multiple experiments to assess cell maturation using gating strategy depicted in panel h. n = 3 replicates from one CD34+ cell donor. j, Representative flow cytometry scatter plot showing enucleated reticulocytes distinguished by loss of staining with the DNA-binding dye Hoechst 33342 (gated). k, Percentage of enucleated CD235a+ erythroid cells (reticulocytes) at differentiation day 21 (n = 9 for UT, ABE7.10 and ABE8e −175; n = 3 for AAVS1, ABE7.10 and ABE8e). l, Percentage of HbF versus editing frequencies. A linear regression model was used to correlate %HbF with %−175A > G in panel l (n = 9). Each symbol represents a different donor. Graphs show mean ± SD. The slope (coefficient estimate), coefficient of multiple determination (R2), and P values were calculated based on two-sample t-test (panel k) and a linear regression model (panel l). UT, untreated; ns, not significant.

Source data

Extended Data Fig. 9 Durable editing in HSCs.

a, Percentage of human CD45+ (hCD45+) donor cells in mouse bone marrow 16 weeks after transplantation. b, Percentages of B cells, myeloid cells, and T cells within the hCD45+ population from mouse bone marrow. c, Percentage of hCD235a+ erythroid cells in mouse bone marrow. d, On-target edits, bystander base edits, and indel frequencies in bone marrow and subpopulations. e, Representative flow cytometry scatter plot of maturation markers in CD235a+ erythroblasts in bone marrow. f, Summary of multiple experiments to assess erythroid cell maturation using gating strategy depicted in panel e. g, Representative flow cytometry scatter plot showing enucleated human reticulocytes in mouse bone marrow, distinguished by loss of staining with the DNA-binding dye Hoechst 33342 (gated). h, Percentage of enucleated hCD235a+ erythroid cells (reticulocytes). i, The percentage β-like globin proteins in hCD235a+ erythroid cells recovered from mouse bone marrow. For the experiments assessing ABE7.10, n = 9 mice in the untreated samples and n = 8 mice in the ABE7.10 treated samples, corresponding to three to five mice transplanted with cells from each of two healthy donors. For the experiments assessing ABE8e, n = 9 mice in the untreated samples and n = 8 mice in the ABE8e treated samples, corresponding to three to six mice transplanted with cells from each of two healthy donors. All graphs show mean ± SD. Each symbol shape represents cells from a different CD34+ cell donor. UT, untreated. ns, not significant.

Source data

Extended Data Fig. 10 Durable editing in bone marrow–repopulating HSCs from SCD donors.

a, Percentage of hCD45+ donor cells in mouse bone marrow at 16 weeks after transplantation. b, Percentages of B, myeloid, and T cells within the hCD45+ population from mouse bone marrow. c, Percentage of hCD235a+ erythroid cells in mouse bone marrow. d, Representative flow cytometry scatter plot of maturation markers in hCD235a+ erythroblasts in bone marrow. e, Summary of multiple experiments to assess erythroid cell maturation using gating strategy depicted in panel d. f, Representative flow cytometry scatter plot showing enucleated human reticulocytes in mouse bone marrow, distinguished by loss of staining with the DNA-binding dye Hoechst 33342 (gated). g, Percentage of enucleated hCD235a+ erythroid cells (reticulocytes). h, On-target edits, bystander base edits, and indel frequencies in different bone marrow populations. i, Indel allele frequencies quantified in cells before transplantation (n = 1 donor) and 16 weeks after transplantation (n = 4 transplanted mice for Cas9 and n = 3 for ABE8e). j, Percentages of β-like globin proteins in hCD235a+ erythroid cells recovered from mouse bone marrow. k, Human reticulocytes isolated from mouse bone marrow were incubated in 2% O2 for 8 h. The sickling assay was performed as two independent experiments from three donors (UT, n = 10; ABE7.10, n = 11). Representative micrographs show examples of sickled cells. Scale bar = 50 μM. For the experiments assessing ABE7.10, n = 10 mice in the untreated samples and n = 11 mice in the ABE7.10-treated samples, corresponding to three or four mice transplanted with cells from each of three different SCD donors. For the experiments assessing ABE8e and Cas9 nuclease, n = 5 mice in the untreated samples, n = 4 mice in the Cas9-treated samples, and n = 3 mice in the ABE8e treated samples (all cells from one SCD donor). In panel e, n = 2 mice in the ABE8e treated sample because one mouse did not yield sufficient CD235a+ cells for this analysis. All graphs show mean ± SD. Each symbol represents one mouse, with different symbols designating unique HSPC donors. UT, untreated; ns, not significant.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 3–5 and 12–14 and Note 1.

Reporting Summary

Supplementary Table

Table 1. Percentage of base editing or indels after ABE7.10 or Cas9 nuclease editing of healthy donor CD34+ cells. Table 2. Genotype and percentage HbF in erythroid colonies generated from ABE7.10-edited CD34+ HSPCs. Table 6. Genotype in erythroid colonies generated from ABE8e-edited CD34+ HSPCs. Table 7. Percentage of base editing or indels after ABE7.10 or ABE8e editing of healthy donor CD34+ cells pre and postxenotransplantation. Table 8. Percentage of base editing or indels after ABE7.10, ABE8e or Cas9 nuclease editing of sickle cell disease donor CD34+ cells pre and postxenotransplantation. Table 9. Off-targets identified by CIRCLE-seq. Table 10. Cas-OFFinder predicted in silico off-targets. Table 11. Off-target sites and primer sequences used for their amplification. Table 15. CRISpy parameters.

Source data

Source Data All Figures

Source Data Figs. 1–6 and Extended Data Figs. 1–10.

Source Data Fig. 3g

Unprocessed gel.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mayuranathan, T., Newby, G.A., Feng, R. et al. Potent and uniform fetal hemoglobin induction via base editing. Nat Genet 55, 1210–1220 (2023). https://doi.org/10.1038/s41588-023-01434-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41588-023-01434-7

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research