journal article·2026-06-11Open access

Synergistic HMGN1 and VP64 Fusions Potentiate High‐Precision and PAM‐Flexible Base Editing

Xi Luo, Yuyao Qu, Zhengyan Ye, Zheng Li, Yuanyan Zhang, Longjiong Luo, Shaokang Li, Wei Zhao, Ming Wang, Ralph Bock, Jianmin Wan, Junjie Tan

Abstract

ABSTRACT RNA‐guided CRISPR‐derived base editors (BEs) have revolutionized genome editing by enabling targeted base substitutions. However, their application is frequently constrained by the stringent requirement for PAM sequences and low editing precision (bystander editing). Here, we present a robust strategy to overcome these limitations by coupling SpRY, a near‐PAM‐less Cas9 variant, with truncated CDA1 cytidine deaminases. While this combination enables precise editing of virtually any cytosine in the genome, it initially exhibited suboptimal efficiency. To address this, we systematically screened a diverse panel of candidate DNA‐binding proteins and identified that the synergistic fusion of HMGN1 and VP64 substantially enhances editing activity without compromising precision. Importantly, this enhanced editing efficiency was achieved without markedly increasing off‐target effects. Our new BEs demonstrated robust performance not only in yeast but also in rice, suggesting broad applicability in gene therapy, precision breeding, and fundamental research.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: CRISPR and Genetic Engineering · RNA regulation and disease · RNA and protein synthesis mechanisms

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Crop Genetics & Germplasm Enhancement and Utilization Collaborative Innovation Center for Modern Crop Production co‐sponsored by Province and Ministry Nanjing Agricultural University Nanjing China

Zhongshan Biological Breeding Laboratory Nanjing Jiangsu China

Department of Plant Pathology Nanjing Agricultural University Nanjing China

Department of Organelle Biology, Biotechnology and Molecular Ecophysiology Max‐Planck‐Institut für Molekulare Pflanzenphysiologie Potsdam‐Golm Germany

References (62)

Show source-provided references
1. 10.1073/pnas.120850710910.1073/pnas.1208507109 ↗
2. 10.1126/science.122582910.1126/science.1225829 ↗
3. 10.1146/annurev‐biophys‐062215‐01082210.1146/annurev‐biophys‐062215‐010822 ↗
4. 10.1038/nbt.250810.1038/nbt.2508 ↗
5. 10.1126/science.125809610.1126/science.1258096 ↗
6. 10.1016/j.tig.2022.06.01510.1016/j.tig.2022.06.015 ↗
7. 10.1126/science.123203310.1126/science.1232033 ↗
8. 10.1038/nbt.265510.1038/nbt.2655 ↗
9. 10.1016/j.cell.2017.04.00510.1016/j.cell.2017.04.005 ↗
10. 10.1146/annurev.biochem.052308.09313110.1146/annurev.biochem.052308.093131 ↗
11. 10.1038/nbt.383310.1038/nbt.3833 ↗
12. 10.1038/nbt.381110.1038/nbt.3811 ↗
13. 10.1093/nar/gkv122210.1093/nar/gkv1222 ↗
14. 10.1073/pnas.91.13.606410.1073/pnas.91.13.6064 ↗
15. 10.1128/Mcb.14.12.809610.1128/Mcb.14.12.8096 ↗
16. 10.1038/nm.379310.1038/nm.3793 ↗
17. 10.1038/nrm200810.1038/nrm2008 ↗
18. 10.1038/nature1794610.1038/nature17946 ↗
19. 10.1126/science.aaf872910.1126/science.aaf8729 ↗
20. 10.1038/nature2464410.1038/nature24644 ↗
21. 10.1016/j.molcel.2017.09.02910.1016/j.molcel.2017.09.029 ↗
22. 10.1038/s41587‐021‐00938‐z10.1038/s41587‐021‐00938‐z ↗
23. 10.1038/s41587‐020‐0609‐x10.1038/s41587‐020‐0609‐x ↗
24. 10.1038/s41587‐020‐0592‐210.1038/s41587‐020‐0592‐2 ↗
25. 10.1038/s41587‐022‐01595‐610.1038/s41587‐022‐01595‐6 ↗
26. 10.1016/j.molp.2016.11.01310.1016/j.molp.2016.11.013 ↗
27. 10.1007/s13238‐017‐0475‐610.1007/s13238‐017‐0475‐6 ↗
28. 10.1038/s41477‐019‐0405‐010.1038/s41477‐019‐0405‐0 ↗
29. 10.1038/s41467‐021‐23996‐y10.1038/s41467‐021‐23996‐y ↗
30. 10.1038/s41586‐021‐03609‐w10.1038/s41586‐021‐03609‐w ↗
31. 10.1038/s41586‐021‐03534‐y10.1038/s41586‐021‐03534‐y ↗
32. 10.1038/nbt.419910.1038/nbt.4199 ↗
33. 10.1038/s41467‐018‐08034‐810.1038/s41467‐018‐08034‐8 ↗
34. 10.1038/s41467‐020‐14465‐z10.1038/s41467‐020‐14465‐z ↗
35. 10.1038/s41576‐018‐0059‐110.1038/s41576‐018‐0059‐1 ↗
36. 10.1002/(SICI)1098‐100410.1002/(SICI)1098‐1004 ↗
37. 10.1038/s41586‐022‐04823‐w10.1038/s41586‐022‐04823‐w ↗
38. 10.1038/s41586‐019‐1711‐410.1038/s41586‐019‐1711‐4 ↗
39. 10.1016/j.molcel.2021.12.00210.1016/j.molcel.2021.12.002 ↗
40. 10.1038/s41587‐023‐01758‐z10.1038/s41587‐023‐01758‐z ↗
41. 10.1016/j.cell.2023.07.03910.1016/j.cell.2023.07.039 ↗
42. 10.1016/j.ymthe.2021.07.01110.1016/j.ymthe.2021.07.011 ↗
43. 10.1016/j.cell.2021.09.01810.1016/j.cell.2021.09.018 ↗
44. 10.1126/science.aba885310.1126/science.aba8853 ↗
45. 10.1016/j.cell.2021.01.00510.1016/j.cell.2021.01.005 ↗
46. 10.1038/s41586‐020‐03086‐710.1038/s41586‐020‐03086‐7 ↗
47. 10.1126/science.aaw716610.1126/science.aaw7166 ↗
48. 10.1126/science.aav997310.1126/science.aav9973 ↗
49. 10.1038/s41556‐020‐0518‐810.1038/s41556‐020‐0518‐8 ↗
50. 10.1016/j.cell.2024.03.02010.1016/j.cell.2024.03.020 ↗
51. 10.1093/bioinformatics/btu04810.1093/bioinformatics/btu048 ↗
52. 10.1038/s41587‐022‐01254‐w10.1038/s41587‐022‐01254‐w ↗
53. 10.1186/s13059‐020‐02231‐910.1186/s13059‐020‐02231‐9 ↗
54. 10.1038/s41477‐020‐00827‐410.1038/s41477‐020‐00827‐4 ↗
55. 10.1038/nbt.380310.1038/nbt.3803 ↗
56. 10.1038/s41586‐019‐1161‐z10.1038/s41586‐019‐1161‐z ↗
57. 10.1126/science.aas912910.1126/science.aas9129 ↗
58. 10.1038/nbt.417210.1038/nbt.4172 ↗
59. 10.1093/nar/gkaf71710.1093/nar/gkaf717 ↗
60. 10.1038/s41467‐023‐41829‐y10.1038/s41467‐023‐41829‐y ↗
61. 10.1038/nprot.2007.1410.1038/nprot.2007.14 ↗
62. 10.2144/00011367210.2144/000113672 ↗