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R-loop editing by DNA cytosine deaminase APOBEC3B modulates the activity of oestrogen receptor enhancers
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  • Published: 18 February 2026

R-loop editing by DNA cytosine deaminase APOBEC3B modulates the activity of oestrogen receptor enhancers

  • Chi Zhang  ORCID: orcid.org/0000-0002-9188-63071,2,3,
  • Yu-jing Lu  ORCID: orcid.org/0000-0003-2494-843X4 na1,
  • Bingjie Chen  ORCID: orcid.org/0000-0001-7689-21465 na1,
  • Zhiyan Bai6,
  • Qiaoxi Zeng2,3,
  • Alexia Hervieu  ORCID: orcid.org/0000-0002-8061-66781,
  • Marco P. Licciardello1,
  • Konstantinos Mitsopoulos1,
  • Bissan Al-Lazikani1,
  • Marcello Tortorici1,
  • Olivia W. Rossanese  ORCID: orcid.org/0000-0002-1262-95221,
  • Paul Workman  ORCID: orcid.org/0000-0003-1659-30341 &
  • …
  • Paul A. Clarke  ORCID: orcid.org/0000-0001-9342-12901 

Nature Communications , Article number:  (2026) Cite this article

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Subjects

  • Breast cancer
  • DNA mismatch repair
  • Double-strand DNA breaks
  • Hormone receptors

Abstract

Oestrogen receptor (ER) activation leads to the formation of DNA double strand breaks (DSB), promoting genomic instability and tumour heterogeneity. The single-stranded DNA cytosine deaminase APOBEC3B (A3B) serves as a co-activator of ER and is implicated in inducing DSBs at transcriptional enhancers regulated by ER. Using whole-genome sequencing in an engineered cell model lacking base excision repair (BER) function, we demonstrate that A3B preferentially targets transcriptionally active regulatory regions in an R-loop-dependent manner. Strand-specific DNA:RNA immunoprecipitation sequencing (ssDRIP-seq) and ssDNA-associated protein immunoprecipitation sequencing (SPI-seq) confirm that A3B binds to and deaminates ssDNA within R-loops, a process facilitated by ER transactivation. Furthermore, BER-mediated processing of A3B-induced uracil bases contributes to the formation of R-loop-associated DSBs, which are essential for ER-regulated gene activation. These findings establish a role for A3B in R-loop homeostasis and transcriptional regulation, with implications for understanding ER-driven genomic instability and potential therapeutic targeting of A3B.

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Data availability

The WGS, ChIP-seq, SPI-seq, ssDRIP-seq, DSBCapture-seq, and RNA-seq data generated in this study have been deposited in NCBI’s Gene Expression Omnibus (GEO) database under the GEO series accession code GSE193234. The processed RNA-seq data generated in this study are provided in Supplementary Data 1 Source data are provided in this paper.

References

  1. Orzolek, I., Sobieraj, J. & Domagala-Kulawik, J. Estrogens, cancer and immunity. Cancers 14, https://doi.org/10.3390/cancers14092265 (2022).

  2. Yang, J. A., Stires, H., Belden, W. J. & Roepke, T. A. The arcuate estrogen-regulated transcriptome: estrogen response element-dependent and -independent signaling of ERalpha in female mice. Endocrinology 158, 612–626 (2017).

    Google Scholar 

  3. Hewitt, S. C. & Korach, K. S. Estrogen receptors: new directions in the new millennium. Endocr. Rev. 39, 664–675 (2018).

    Google Scholar 

  4. Rajan, A. et al. Deregulated estrogen receptor signaling and DNA damage response in breast tumorigenesis. Biochim. Biophys. Acta Rev. Cancer 1875, 188482 (2021).

    Google Scholar 

  5. Periyasamy, M. et al. APOBEC3B-Mediated cytidine deamination is required for estrogen receptor action in breast cancer. Cell Rep. 13, 108–121 (2015).

    Google Scholar 

  6. Stork, C. T. et al. Co-transcriptional R-loops are the main cause of estrogen-induced DNA damage. Elife 5, https://doi.org/10.7554/eLife.17548 (2016).

  7. Li, J. J. et al. Estrogen mediates Aurora-A overexpression, centrosome amplification, chromosomal instability, and breast cancer in female ACI rats. Proc. Natl. Acad. Sci. USA 101, 18123–18128 (2004).

    Google Scholar 

  8. Nik-Zainal, S. et al. Mutational processes molding the genomes of 21 breast cancers. Cell 149, 979–993 (2012).

    Google Scholar 

  9. Nik-Zainal, S. et al. Landscape of somatic mutations in 560 breast cancer whole-genome sequences. Nature 534, 47–54 (2016).

    Google Scholar 

  10. Compe, E. & Egly, J. M. TFIIH: when transcription met DNA repair. Nat. Rev. Mol. Cell Biol. 13, 343–354 (2012).

    Google Scholar 

  11. Kamileri, I., Karakasilioti, I. & Garinis, G. A. Nucleotide excision repair: new tricks with old bricks. Trends Genet. 28, 566–573 (2012).

    Google Scholar 

  12. Fong, Y. W., Cattoglio, C. & Tjian, R. The intertwined roles of transcription and repair proteins. Mol. Cell 52, 291–302 (2013).

    Google Scholar 

  13. Schuermann, D., Weber, A. R. & Schar, P. Active DNA demethylation by DNA repair: Facts and uncertainties. DNA Repair 44, 92–102 (2016).

    Google Scholar 

  14. Perillo, B., Castoria, G. & Migliaccio, A. Exploiting the mechanism of estrogen-induced transcription to fight breast cancer. Exp. Mol. Med. 53, 1205–1206 (2021).

    Google Scholar 

  15. Puc, J. et al. Ligand-dependent enhancer activation regulated by topoisomerase-I activity. Cell 160, 367–380 (2015).

    Google Scholar 

  16. Ju, B. G. et al. A topoisomerase IIbeta-mediated dsDNA break required for regulated transcription. Science 312, 1798–1802 (2006).

    Google Scholar 

  17. Green, A. M. & Weitzman, M. D. The spectrum of APOBEC3 activity: From anti-viral agents to anti-cancer opportunities. DNA Repair 83, 102700 (2019).

    Google Scholar 

  18. Harris, R. S. & Dudley, J. P. APOBECs and virus restriction. Virology 479-480, 131–145 (2015).

    Google Scholar 

  19. Henderson, S. & Fenton, T. APOBEC3 genes: retroviral restriction factors to cancer drivers. Trends Mol. Med. 21, 274–284 (2015).

    Google Scholar 

  20. Burns, M. B. et al. APOBEC3B is an enzymatic source of mutation in breast cancer. Nature 494, 366–370 (2013).

    Google Scholar 

  21. Salamango, D. J. et al. APOBEC3B Nuclear localization requires two distinct N-terminal domain surfaces. J. Mol. Biol. 430, 2695–2708 (2018).

    Google Scholar 

  22. Mas-Ponte, D. & Supek, F. DNA mismatch repair promotes APOBEC3-mediated diffuse hypermutation in human cancers. Nat. Genet. 52, 958–968 (2020).

    Google Scholar 

  23. Taylor, B. J. et al. DNA deaminases induce break-associated mutation showers with implication of APOBEC3B and 3A in breast cancer kataegis. Elife 2, e00534 (2013).

    Google Scholar 

  24. Law, E. K. et al. The DNA cytosine deaminase APOBEC3B promotes tamoxifen resistance in ER-positive breast cancer. Sci. Adv. 2, e1601737 (2016).

    Google Scholar 

  25. Garcia-Muse, T. & Aguilera, A. R Loops: from physiological to pathological roles. Cell 179, 604–618 (2019).

    Google Scholar 

  26. Gu, S., Bodai, Z., Cowan, Q. T. & Komor, A. C. Base editors: expanding the types of DNA damage products harnessed for genome editing. Gene Genome Ed. 1, https://doi.org/10.1016/j.ggedit.2021.100005 (2021).

  27. McCann, J. L. et al. APOBEC3B regulates R-loops and promotes transcription-associated mutagenesis in cancer. Nat. Genet. 55, 1721–1734 (2023).

    Google Scholar 

  28. Alexandrov, L. B. et al. The repertoire of mutational signatures in human cancer. Nature 578, 94–101 (2020).

    Google Scholar 

  29. Krokan, H. E. et al. Error-free versus mutagenic processing of genomic uracil-relevance to cancer. DNA Repair 19, 38–47 (2014).

    Google Scholar 

  30. Petljak, M. et al. Mechanisms of APOBEC3 mutagenesis in human cancer cells. Nature 607, 799–807 (2022).

    Google Scholar 

  31. Akre, M. K. et al. Mutation processes in 293-based clones overexpressing the DNA cytosine deaminase APOBEC3B. PLoS ONE 11, e0155391 (2016).

    Google Scholar 

  32. Hoopes, J. I. et al. APOBEC3A and APOBEC3B Preferentially deaminate the lagging strand template during DNA replication. Cell Rep. 14, 1273–1282 (2016).

    Google Scholar 

  33. Nikkila, J. et al. Elevated APOBEC3B expression drives a kataegic-like mutation signature and replication stress-related therapeutic vulnerabilities in p53-defective cells. Br. J. Cancer 117, 113–123 (2017).

    Google Scholar 

  34. Sui, Y. et al. Analysis of APOBEC-induced mutations in yeast strains with low levels of replicative DNA polymerases. Proc. Natl. Acad. Sci. USA 117, 9440–9450 (2020).

    Google Scholar 

  35. Serebrenik, A. A. et al. The deaminase APOBEC3B triggers the death of cells lacking uracil DNA glycosylase. Proc. Natl. Acad. Sci. USA 116, 22158–22163 (2019).

    Google Scholar 

  36. McLaren, W. et al. The ensembl variant effect predictor. Genome Biol. 17, 122 (2016).

    Google Scholar 

  37. Ernst, J. & Kellis, M. Chromatin-state discovery and genome annotation with ChromHMM. Nat. Protoc. 12, 2478–2492 (2017).

    Google Scholar 

  38. Lee, C. Y. et al. R-loop induced G-quadruplex in non-template promotes transcription by successive R-loop formation. Nat. Commun. 11, 3392 (2020).

    Google Scholar 

  39. Xu, W. et al. The R-loop is a common chromatin feature of the Arabidopsis genome. Nat. Plants 3, 704–714 (2017).

    Google Scholar 

  40. Cristini, A., Groh, M., Kristiansen, M. S. & Gromak, N. RNA/DNA Hybrid interactome identifies DXH9 as a molecular player in transcriptional termination and R-loop-associated DNA damage. Cell Rep. 23, 1891–1905 (2018).

    Google Scholar 

  41. Zhou, Z. X. et al. Mapping genomic hotspots of DNA damage by a single-strand-DNA-compatible and strand-specific ChIP-seq method. Genome Res. 23, 705–715 (2013).

    Google Scholar 

  42. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Google Scholar 

  43. Lensing, S. V. et al. DSBCapture: in situ capture and sequencing of DNA breaks. Nat. Methods 13, 855–857 (2016).

    Google Scholar 

  44. Differential Binding Analysis of ChIP-Seq peak data (https://github.com/aeron15/DiffBind (2015).

  45. Williamson, L. M. & Lees-Miller, S. P. Estrogen receptor alpha-mediated transcription induces cell cycle-dependent DNA double-strand breaks. Carcinogenesis 32, 279–285 (2011).

    Google Scholar 

  46. Aguilera, A. & Garcia-Muse, T. R loops: from transcription byproducts to threats to genome stability. Mol. Cell 46, 115–124 (2012).

    Google Scholar 

  47. Sollier, J. et al. Transcription-coupled nucleotide excision repair factors promote R-loop-induced genome instability. Mol. Cell 56, 777–785 (2014).

    Google Scholar 

  48. McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).

    Google Scholar 

  49. Liberzon, A. et al. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 1, 417–425 (2015).

    Google Scholar 

  50. Cancer Genome Atlas Research, N. et al. The cancer genome atlas pan-cancer analysis project. Nat. Genet. 45, 1113–1120 (2013).

    Google Scholar 

  51. Hutter, C. & Zenklusen, J. C. The cancer genome atlas: creating lasting value beyond its data. Cell 173, 283–285 (2018).

    Google Scholar 

  52. Sollier, J. & Cimprich, K. A. Breaking bad: R-loops and genome integrity. Trends Cell Biol. 25, 514–522 (2015).

    Google Scholar 

  53. Cristini, A. et al. Dual processing of R-Loops and topoisomerase I induces transcription-dependent DNA double-strand breaks. Cell Rep. 28, 3167–3181 (2019).

    Google Scholar 

  54. Chatzinikolaou, G. et al. XPF interacts with TOP2B for R-loop processing and DNA looping on actively transcribed genes. Sci. Adv. 9, eadi2095 (2023).

    Google Scholar 

  55. Sartorelli, V. & Lauberth, S. M. Enhancer RNAs are an important regulatory layer of the epigenome. Nat. Struct. Mol. Biol. 27, 521–528 (2020).

    Google Scholar 

  56. Liu, J. et al. Endogenous DNA damage at sites of terminated transcripts. Nature 640, 240–248 (2025).

    Google Scholar 

  57. Long, J. et al. A common deletion in the APOBEC3 genes and breast cancer risk. J. Natl. Cancer Inst. 105, 573–579 (2013).

    Google Scholar 

  58. Wen, W. X. et al. Germline APOBEC3B deletion is associated with breast cancer risk in an Asian multi-ethnic cohort and with immune cell presentation. Breast Cancer Res. 18, 56 (2016).

    Google Scholar 

  59. Caval, V., Suspene, R., Shapira, M., Vartanian, J. P. & Wain-Hobson, S. A prevalent cancer susceptibility APOBEC3A hybrid allele bearing APOBEC3B 3’UTR enhances chromosomal DNA damage. Nat. Commun. 5, 5129 (2014).

    Google Scholar 

  60. Udquim, K. I., Zettelmeyer, C., Banday, A. R., Lin, S. H. & Prokunina-Olsson, L. APOBEC3B expression in breast cancer cell lines and tumors depends on the estrogen receptor status. Carcinogenesis 41, 1030–1037 (2020).

    Google Scholar 

  61. Zhang, C. et al. Characterisation of APOBEC3B-Mediated RNA editing in breast cancer cells reveals regulatory roles of NEAT1 and MALAT1 lncRNAs. Oncogene 43, 3366–3377 (2024).

    Google Scholar 

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

    Google Scholar 

  63. DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    Google Scholar 

  64. Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).

    Google Scholar 

  65. Piskol, R., Ramaswami, G. & Li, J. B. Reliable identification of genomic variants from RNA-seq data. Am. J. Hum. Genet. 93, 641–651 (2013).

    Google Scholar 

  66. Wang, M. & Kong, L. pblat: a multithread blat algorithm speeding up aligning sequences to genomes. BMC Bioinformatics 20, 28 (2019).

    Google Scholar 

  67. Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Google Scholar 

  68. Turner, S. D. qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots. J. Open Source Softw. 3, https://doi.org/10.21105/joss.00731 (2018).

  69. Kent, W. J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002).

    Google Scholar 

  70. Blokzijl, F., Janssen, R., van Boxtel, R. & Cuppen, E. MutationalPatterns: comprehensive genome-wide analysis of mutational processes. Genome Med. 10, 33 (2018).

    Google Scholar 

  71. Gaujoux, R. & Seoighe, C. A flexible R package for nonnegative matrix factorization. BMC Bioinform. 11, 367 (2010).

    Google Scholar 

  72. Huang, H. et al. Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling. Nat. Commun. 12, 2242 (2021).

    Google Scholar 

  73. Halasz, L. et al. RNA-DNA hybrid (R-loop) immunoprecipitation mapping: an analytical workflow to evaluate inherent biases. Genome Res. 27, 1063–1073 (2017).

    Google Scholar 

  74. Jenjaroenpun, P., Wongsurawat, T., Sutheeworapong, S. & Kuznetsov, V. A. R-loopDB: a database for R-loop forming sequences (RLFS) and R-loops. Nucleic Acids Res. 45, D119–D127 (2017).

    Google Scholar 

  75. Bedrat, A., Lacroix, L. & Mergny, J. L. Re-evaluation of G-quadruplex propensity with G4Hunter. Nucleic Acids Res. 44, 1746–1759 (2016).

    Google Scholar 

  76. Stempor, P. & Ahringer, J. SeqPlots - Interactive software for exploratory data analyses, pattern discovery and visualization in genomics. Wellcome Open Res. 1, 14 (2016).

    Google Scholar 

  77. Robinson, J. T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    Google Scholar 

  78. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Google Scholar 

  79. Feng, J., Liu, T., Qin, B., Zhang, Y. & Liu, X. S. Identifying ChIP-seq enrichment using MACS. Nat. Protoc. 7, 1728–1740 (2012).

    Google Scholar 

  80. Jalili, V., Matteucci, M., Masseroli, M. & Morelli, M. J. Using combined evidence from replicates to evaluate ChIP-seq peaks. Bioinformatics 31, 2761–2769 (2015).

    Google Scholar 

  81. Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    Google Scholar 

  82. Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481, 389–393 (2012).

    Google Scholar 

  83. McLeay, R. C. & Bailey, T. L. Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data. BMC Bioinform. 11, 165 (2010).

    Google Scholar 

  84. Bailey, T. L., Johnson, J., Grant, C. E. & Noble, W. S. The MEME suite. Nucleic Acids Res. 43, W39–W49 (2015).

    Google Scholar 

  85. Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32, 2847–2849 (2016).

    Google Scholar 

  86. Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).

    Google Scholar 

  87. Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    Google Scholar 

  88. Liao, Y., Smyth, G. K. & Shi, W. The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads. Nucleic Acids Res. 47, e47 (2019).

    Google Scholar 

  89. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).

    Google Scholar 

  90. Zhang, Y. et al. Discovery of APOBEC cytidine deaminases inhibitors using a BspH1 restriction enzyme-based biosensor. ChemistrySelect 7, e202201456 (2022).

    Google Scholar 

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Acknowledgements

This work is financially supported by Cancer Research UK (C309/A11566 and C2739/A22897) and ICR (London, United Kingdom). C.Z. was sponsored by the Science and Technology Commission of Shanghai Municipality (23S11901100). P.W. and C.Z. acknowledge additional grant support from the Wellcome Trust (212969/Z/18/Z and 094885/Z/10/Z), Cancer Research UK (C35696/A23187). P.W. is a CRUK Life Fellow and acknowledges support from CRUK Strategic Award C35696/A23187 and Infrastructure Award C309/A27413, and funding for the CRUK Children’s Brain Tumour Centre of Excellence (C9685/A26398/RG93685); Wellcome Trust (Biomedical Resource and Technology Development Grant 212969/Z/18/Z to support the Chemical Probes Portal), Chordoma Foundation, Marcus Foundation, Mark Foundation, Bone Cancer Research Trust, CRIS Cancer, and The Institute of Cancer Research. Z.B. was supported by the Science, Technology, and Innovation Commission of Shenzhen Municipality (ZDSYS20200811142605017). We thank Prof. Ping Yuan from Sun Yat-sen University, Dr. Mike Walton and Dr. Alexandra Vasile from ICR for helpful discussions.

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  1. These authors contributed equally: Yu-jing Lu, Bingjie Chen.

Authors and Affiliations

  1. Centre for Cancer Drug Discovery, Division of Cancer Therapeutics, the Institute of Cancer Research, London, United Kingdom

    Chi Zhang, Alexia Hervieu, Marco P. Licciardello, Konstantinos Mitsopoulos, Bissan Al-Lazikani, Marcello Tortorici, Olivia W. Rossanese, Paul Workman & Paul A. Clarke

  2. Shanghai Institute of Biological Products, Shanghai, China

    Chi Zhang & Qiaoxi Zeng

  3. State Key Laboratory of Novel Vaccines for Emerging Infectious Diseases, China National Biotec Group Company Limited, Beijing, China

    Chi Zhang & Qiaoxi Zeng

  4. Institute of Biomedical and Pharmaceutical Sciences, Guangdong University of Technology, Guangzhou, China

    Yu-jing Lu

  5. GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China

    Bingjie Chen

  6. Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Advanced Synthetic Biology Institute at Hohhot, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China

    Zhiyan Bai

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Contributions

C.Z., O.W.R., P.A.C. and P.W. conceived and designed this study. C.Z., Y.L., Q.Z. and M.T. conducted the experiments and analysis unless otherwise noted. B.C., Z.B., K.M. and B.A.-L. conducted analysis of sequencing data and provided guidance on data analysis using sequencing data. C.Z., A.H., M.P.L., O.W.R., P.W. and P.A.C. prepared the manuscript.

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Correspondence to Olivia W. Rossanese, Paul Workman or Paul A. Clarke.

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Competing interests

C.Z., A.H., M.P.L., O.W.R., P.A.C., K.M., M.T., and P.W. are current or past employees of The Institute of Cancer Research, which has a commercial interest in a range of drug targets and operates a Rewards to Discoverers scheme, including A3B inhibitors, through which employees may receive financial benefits following the commercial licensing of a project. P.W. is an independent director at Storm Therapeutics, is a consultant/advisory board member at Astex Pharmaceuticals, CV6 Therapeutics, Black Diamond Therapeutics, Vividion Therapeutics and Nextechinvest; reports receiving a commercial research grant from Sixth Element Capital, Astex Pharmaceuticals, and Merck; has ownership interest in Storm Therapeutics, Chroma Therapeutics, and Nextechinvest; and has an unpaid consultant/advisory board relationship with the Chemical Probes Portal. The remaining authors declare no competing interests.

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Zhang, C., Lu, Yj., Chen, B. et al. R-loop editing by DNA cytosine deaminase APOBEC3B modulates the activity of oestrogen receptor enhancers. Nat Commun (2026). https://doi.org/10.1038/s41467-026-69679-4

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  • Received: 20 March 2025

  • Accepted: 05 February 2026

  • Published: 18 February 2026

  • DOI: https://doi.org/10.1038/s41467-026-69679-4

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