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.

Advertisement

Nature Communications
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. nature communications
  3. articles
  4. article
DIS3 mutations enhance AID-driven translocations during B-cell activation, promoting transformation to multiple myeloma
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 14 March 2026

DIS3 mutations enhance AID-driven translocations during B-cell activation, promoting transformation to multiple myeloma

  • Tomasz M. Kuliński1,2,
  • Olga Gewartowska  ORCID: orcid.org/0000-0003-2623-03093,4,
  • Mélanie Mahé5,6,
  • Karolina Kasztelan1,2,
  • Nina Durys2,
  • Anna Stroynowska-Czerwińska  ORCID: orcid.org/0000-0002-1080-303X7,
  • Marta Jedynak-Slyvka8,9 nAff10,
  • Ewelina P. Owczarek1,
  • Debadeep Chaudhury  ORCID: orcid.org/0000-0002-9089-732X7,
  • Marcin Nowotny8,
  • Aleksandra Pękowska  ORCID: orcid.org/0000-0002-0425-43887,
  • Bertrand Séraphin  ORCID: orcid.org/0000-0002-5168-19215,6 &
  • …
  • Andrzej Dziembowski  ORCID: orcid.org/0000-0001-8492-75721,2,3 

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

  • 2464 Accesses

  • 1 Altmetric

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • B cells
  • Gene targeting
  • Myeloma
  • RNA decay

Abstract

DIS3, a key nuclear RNA-degrading enzyme, is essential for immunoglobulin class switch recombination (CSR), promoting activation-induced cytidine deaminase (AID) activity on both DNA strands to induce double-strand DNA breaks. During somatic hypermutation, AID-dependent lesions predominantly occur on the non-template DNA strand. Dominant mutations impairing DIS3 exoribonucleolytic activity are common in multiple myeloma (MM), but their role in carcinogenesis remains unclear. Here we show, using a knock-in mouse model, that the clinically relevant DIS3 G766R variant causes chromosomal translocations in B-cells, characterized by aberrant AID activity signatures. The mice develop pristane-induced plasmacytomas, modeling early-stage MM. In clinical MM samples, DIS3 mutations correlate with IGH translocations and AID-driven lesions in driver genes. Mechanistically, mutated DIS3 accumulates on chromatin-bound RNA, particularly at aberrant AID target sites, promoting mutations on both DNA strands. This results in increased AID-dependent double-strand DNA breaks, fostering microhomology-mediated oncogenic rearrangements. Translocations occur specifically during CSR, which remains functionally intact. The DIS3 G766R mutation does not disrupt chromatin architecture in activated B cells but exploits spatial proximity to permanently juxtapose enhancers and proto-oncogenes, facilitating transformation. Thus, gain-of-function DIS3 mutations enhance AID promiscuity, driving IGH translocations and MM development without broadly affecting B-cell physiology.

Similar content being viewed by others

DIS3 licenses B cells for plasma cell differentiation in humans

Article Open access 25 November 2025

Increased AID results in mutations at the CRLF2 locus implicated in Latin American ALL health disparities

Article Open access 27 July 2024

p53-NEIL1 co-abnormalities induce genomic instability and promote synthetic lethality with Chk1 inhibition in multiple myeloma having concomitant 17p13(del) and 1q21(gain)

Article 21 February 2022

Data availability

The sequencing data have been deposited in NCBI’s Gene Expression Omnibus (GEO) under the accession code GSE155631. The raw sequencing data have been deposited in the Sequence Read Archive (SRA) under the accession code SRP275679, associated with BioProject PRJNA650522. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE repository under the accession code PXD050438. Source data are provided with this paper.

Code availability

All custom scripts used for analyses have been deposited in Mendeley Data and are publicly available at: 10.17632/7tdgwkzmnr.1.

References

  1. Walker, B. A. et al. Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma. Blood 132, 587–597 (2018).

    Google Scholar 

  2. Lohr, J. G. et al. Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell 25, 91–101 (2014).

    Google Scholar 

  3. Chapman, M. A. et al. Initial genome sequencing and analysis of multiple myeloma. Nature 471, 467–472 (2011).

    Google Scholar 

  4. Dziembowski, A., Lorentzen, E., Conti, E. & Séraphin, B. A single subunit, Dis3, is essentially responsible for yeast exosome core activity. Nat. Struct. Mol. Biol. 14, 15–22 (2007).

    Google Scholar 

  5. Tomecki, R. et al. Multiple myeloma-associated hDIS3 mutations cause perturbations in cellular RNA metabolism and suggest hDIS3 PIN domain as a potential drug target. Nucleic Acids Res. 42, 1270–1290 (2014).

    Google Scholar 

  6. Szczepińska, T. et al. DIS3 shapes the RNA polymerase II transcriptome in humans by degrading a variety of unwanted transcripts. Genome Res. 25, 1622–1633 (2015).

    Google Scholar 

  7. Pefanis, E. et al. Noncoding RNA transcription targets AID to divergently transcribed loci in B cells. Nature 514, 389–393 (2014).

    Google Scholar 

  8. Laffleur, B. et al. Noncoding RNA processing by DIS3 regulates chromosomal architecture and somatic hypermutation in B cells. Nat. Genet. 53, 230–242 (2021).

    Google Scholar 

  9. Basu, U. et al. The RNA exosome targets the AID cytidine deaminase to both strands of transcribed duplex DNA substrates. Cell 144, 353–363 (2011).

    Google Scholar 

  10. Laffleur, B. et al. RNA exosome drives early B cell development via noncoding RNA processing mechanisms. Sci. Immunol. 7, 2738 (2022).

  11. Methot, S. P. & Di Noia, J. M. Molecular Mechanisms of Somatic Hypermutation and Class Switch Recombination. Adv. Immunol. 133, 37–87 (2017).

  12. Feng, Y., Seija, N., Di Noia, J. M. & Martin, A. AID in antibody diversification: there and back again. Trends Immunol. 41, 586–600 (2020).

    Google Scholar 

  13. Revy, P. et al. Activation-induced cytidine deaminase (AID) deficiency causes the autosomal recessive form of the hyper-IgM syndrome (HIGM2). Cell 102, 565–575 (2000).

    Google Scholar 

  14. Muramatsu, M. et al. Class switch recombination and hypermutation require activation-induced cytidine deaminase (AID), a potential RNA editing enzyme. Cell 102, 553–563 (2000).

    Google Scholar 

  15. Hwang, J. K., Alt, F. W. & Yeap, L.-S. Related mechanisms of antibody somatic hypermutation and class switch recombination. Microbiol. Spectr. 3, 1128 (2015).

  16. Carpenter, M. A., Rajagurubandara, E., Wijesinghe, P. & Bhagwat, A. S. Determinants of sequence-specificity within human AID and APOBEC3G. DNA Repair 9, 579–587 (2010).

    Google Scholar 

  17. Pefanis, E. et al. RNA exosome-regulated long non-coding RNA transcription controls super-enhancer activity. Cell 161, 774–789 (2015).

    Google Scholar 

  18. Yu, K., Chedin, F., Hsieh, C.-L. L., Wilson, T. E. & Lieber, M. R. R-loops at immunoglobulin class switch regions in the chromosomes of stimulated B cells. Nat. Immunol. 4, 442–451 (2003).

    Google Scholar 

  19. Shinkura, R. et al. The influence of transcriptional orientation on endogenous switch region function. Nat. Immunol. 4, 435–441 (2003).

    Google Scholar 

  20. Chaudhuri, J. et al. Transcription-targeted DNA deamination by the AID antibody diversification enzyme. Nature 422, 726–730 (2003).

    Google Scholar 

  21. Qiao, Q. et al. AID recognizes structured DNA for class switch recombination. Mol. Cell 67, 361–373.e4 (2017).

    Google Scholar 

  22. Zarrin, A. A. et al. An evolutionarily conserved target motif for immunoglobulin class-switch recombination. Nat. Immunol. 5, 1275–1281 (2004).

    Google Scholar 

  23. Pavri, R. et al. Activation-induced cytidine deaminase targets DNA at sites of RNA polymerase II stalling by interaction with Spt5. Cell 143, 122–133 (2010).

    Google Scholar 

  24. Ramiro, A. R. et al. AID is required for c-myc/IgH chromosome translocations in vivo. Cell 118, 431–438 (2004).

    Google Scholar 

  25. Okazaki, I. M. et al. Constitutive expression of AID leads to tumorigenesis. J. Exp. Med. 197, 1173–1181 (2003).

    Google Scholar 

  26. Robbiani, D. F. et al. AID produces DNA double-strand breaks in non-Ig genes and mature B cell lymphomas with reciprocal chromosome translocations. Mol. Cell 36, 631–641 (2009).

    Google Scholar 

  27. Takizawa, M. et al. AID expression levels determine the extent of cMyc oncogenic translocations and the incidence of B cell tumor development. J. Exp. Med. 205, 1949–1957 (2008).

    Google Scholar 

  28. Miglierina, E., Ordanoska, D., Le Noir, S. & Laffleur, B. RNA processing mechanisms contribute to genome organization and stability in B cells. Oncogene 43, 615–623 (2024).

    Google Scholar 

  29. Qian, J. et al. B cell super-enhancers and regulatory clusters recruit AID tumorigenic activity. Cell 159, 1524–1537 (2014).

    Google Scholar 

  30. Zhang, X. et al. Fundamental roles of chromatin loop extrusion in antibody class switching. Nature https://doi.org/10.1038/s41586-019-1723-0 (2019).

  31. Vian, L. et al. The energetics and physiological impact of cohesin extrusion. Cell 173, 1165–1178.e20 (2018).

    Google Scholar 

  32. Manier, S. et al. Genomic complexity of multiple myeloma and its clinical implications. Nat. Rev. Clin. Oncol. 14, 100–113 (2017).

    Google Scholar 

  33. Kumar, S. K. et al. Multiple myeloma. Nat. Rev. Dis. Prim. 3, 1–20 (2017).

    Google Scholar 

  34. Chen, Z. & Wang, J. H. Signaling control of antibody isotype switching. in Advances in Immunology vol. 141, 105–164 (Academic Press Inc., 2019).

  35. Castaneda, O. & Baz, R. Multiple myeloma genomics-a concise review. Narrat. Rev. Acta Med. Acad. 48, 57–67 (2019).

    Google Scholar 

  36. Affer, M. et al. Promiscuous MYC locus rearrangements hijack enhancers but mostly super-enhancers to dysregulate MYC expression in multiple myeloma. Leukemia 28, 1725–1735 (2014).

    Google Scholar 

  37. Potter, M. & Wiener, F. Plasmacytomagenesis in mice: model of neoplastic development dependent upon chromosomal translocations. Carcinogenesis 13, 1681–1697 (1992).

    Google Scholar 

  38. Shen-Ong, G. L. C., Keath, E. J., Piccoli, S. P. & Cole, M. D. Novel myc oncogene RNA from abortive immunoglobulin-gene recombination in mouse plasmacytomas. Cell 31, 443–452 (1982).

    Google Scholar 

  39. Gostissa, M. et al. Long-range oncogenic activation of Igh-c-myc translocations by the Igh 3′ regulatory region. Nature 462, 803–807 (2009).

    Google Scholar 

  40. Harris, L. J., Lang, R. B. & Marcu, K. B. Non-immunoglobulin-associated DNA rearrangements in mouse plasmacytomas. Proc. Natl. Acad. Sci. USA 79, 4175–4179 (1982).

    Google Scholar 

  41. Maura, F. et al. Role of AID in the temporal pattern of acquisition of driver mutations in multiple myeloma. Leukemia 34, 1476–1480 (2020).

    Google Scholar 

  42. Lionetti, M. et al. A compendium of DIS3 mutations and associated transcriptional signatures in plasma cell dyscrasias. Oncotarget 6, 26129–26141 (2015).

    Google Scholar 

  43. Todoerti, K. et al. DIS3 mutations in multiple myeloma impact the transcriptional signature and clinical outcome. Haematologica 106, 921–932 (2022).

    Google Scholar 

  44. Ohkura, H. et al. Cold-sensitive and caffeine-supersensitive mutants of the Schizosaccharomyces pombe dis genes implicated in sister chromatid separation during mitosis. EMBO J. 7, 1465–1473 (1988).

    Google Scholar 

  45. Snee, M. J. et al. Collaborative control of cell cycle progression by the RNA exonuclease Dis3 and ras is conserved across species. Genetics 203, 749–762 (2016).

    Google Scholar 

  46. Mukarami, H. et al. Ribonuclease Activity of Dis3 Is Required for Mitotic Progression and Provides a Possible Link between Heterochromatin and Kinetochore Function. PLoS One 2, e317 (2007).

    Google Scholar 

  47. Segalla, S. et al. The ribonuclease DIS3 promotes let-7 miRNA maturation by degrading the pluripotency factor LIN28B mRNA. Nucleic Acids Res. 43, 5182–5193 (2015).

    Google Scholar 

  48. Domingo-Prim, J. et al. EXOSC10 is required for RPA assembly and controlled DNA end resection at DNA double-strand breaks. Nat. Commun. 10, 2135 (2019).

    Google Scholar 

  49. Marin-Vicente, C., Domingo-Prim, J., Eberle, A. B. & Visa, N. RRP6/EXOSC10 is required for the repair of DNA double-strand breaks by homologous recombination. J. Cell Sci. 128, 1097–1107 (2015).

    Google Scholar 

  50. Laffleur, B. et al. RNA exosome drives early B cell development via noncoding RNA processing mechanisms. Sci. Immunol. 7, 1–14 (2022).

    Google Scholar 

  51. Milbury, K. L. et al. Exonuclease domain mutants of yeast DIS3 display genome instability. Nucleus 10, 21–32 (2019).

    Google Scholar 

  52. Favasuli, V. K. et al. DIS3 depletion in multiple myeloma causes extensive perturbation in cell cycle progression and centrosome amplification. Haematologica 109, 231–244 (2024).

    Google Scholar 

  53. Skaar, J. R. et al. The Integrator complex controls the termination of transcription at diverse classes of gene targets. Cell Res 25, 288–305 (2015).

    Google Scholar 

  54. Cevher, M. A. et al. Nuclear deadenylation/polyadenylation factors regulate 3′ processing in response to DNA damage. EMBO J. 29, 1674–1687 (2010).

    Google Scholar 

  55. Kamp, J. A. et al. THO complex deficiency impairs DNA double-strand break repair via the RNA surveillance kinase SMG-1. Nucleic Acids Res. 50, 6235–6250 (2022).

    Google Scholar 

  56. Murphy, M. R. & Kleiman, F. E. Connections between 3′ end processing and DNA damage response: ten years later. Wiley Interdiscip. Rev. RNA 11, 1–24 (2020).

    Google Scholar 

  57. Insco, M. L. et al. Oncogenic CDK13 mutations impede nuclear RNA surveillance. Science 380, 7625 (2023).

    Google Scholar 

  58. Kuliński, T. M. et al. Recurrent multiple myeloma DIS3 alleles arise early but are later counter-selected due to toxicity. bioRxiv 2023.07.27.550471 https://doi.org/10.1101/2023.07.27.550471 (2023).

  59. Manzoni, M. et al. Application of next-generation sequencing for the genomic characterization of patients with smoldering myeloma. Cancers 12, 1332 (2020).

    Google Scholar 

  60. Hu, Y., Chen, W. & Wang, J. Progress in the identification of gene mutations involved in multiple myeloma. Onco. Targets Ther. 12, 4075–4080 (2019).

    Google Scholar 

  61. Gritti, I. et al. Loss of ribonuclease DIS3 hampers genome integrity in myeloma by disrupting DNA:RNA hybrid metabolism. EMBO J. 41, 1–22 (2022).

    Google Scholar 

  62. Tomecki, R. et al. The human core exosome interacts with differentially localized processive RNases: HDIS3 and hDIS3L. EMBO J. 29, 2342–2357 (2010).

    Google Scholar 

  63. Hsieh, T. H. S. et al. Mapping nucleosome resolution chromosome folding in yeast by Micro-C. Cell 162, 108–119 (2015).

    Google Scholar 

  64. Kieffer-Kwon, K. R. et al. Myc regulates chromatin decompaction and nuclear architecture during B cell activation. Mol. Cell 67, 566–578 (2017).

    Google Scholar 

  65. Sun, H. & Taneja, R. Analysis of transformation and tumorigenicity using mouse embryonic fibroblast cells. Methods Mol. Biol. 383, 303–310 (2007).

    Google Scholar 

  66. Gadó, K., Silva, S., Pálóczi, K., Domján, G. & Falus, A. Mouse plasmacytoma: an experimental model of human multiple myeloma. Haematologica 86, 227–236 (2001).

    Google Scholar 

  67. Potter, M. Experimental plasmacytomagenesis in mice. Hematol. Oncol. Clin. North Am. 11, 323–347 (1997).

    Google Scholar 

  68. Libouban, H. The use of animal models in multiple myeloma. Morphologie 99, 63–72 (2015).

    Google Scholar 

  69. Álvarez-Prado, ÁF. et al. A broad atlas of somatic hypermutation allows prediction of activation-induced deaminase targets. J. Exp. Med. 215, 761–771 (2018).

    Google Scholar 

  70. Casellas, R. et al. Mutations, kataegis and translocations in B cells: understanding AID promiscuous activity. Nat. Rev. Immunol. 16, 164–176 (2016).

    Google Scholar 

  71. Rustad, E. H. et al. MMSIG: a fitting approach to accurately identify somatic mutational signatures in hematological malignancies. Commun. Biol. 4, 1–12 (2021).

    Google Scholar 

  72. Hoang, P. H. et al. An enhanced genetic model of relapsed IGH-translocated multiple myeloma evolutionary dynamics. Blood Cancer J. 10, 101 (2020).

    Google Scholar 

  73. Alexandrov, L. B. et al. Clock-like mutational processes in human somatic cells. Nat. Genet. 47, 1402–1407 (2015).

    Google Scholar 

  74. Kasar, S. et al. Whole-genome sequencing reveals activation-induced cytidine deaminase signatures during indolent chronic lymphocytic leukaemia evolution. Nat. Commun. 6, 8866 (2015).

    Google Scholar 

  75. Vogel, M. J., Peric-Hupkes, D. & van Steensel, B. Detection of in vivo protein - DNA interactions using DamID in mammalian cells. Nat. Protoc. 2, 1467–1478 (2007).

    Google Scholar 

  76. Mah, L. J., El-Osta, A. & Karagiannis, T. C. γh2AX: a sensitive molecular marker of DNA damage and repair. Leukemia 24, 679–686 (2010).

    Google Scholar 

  77. Ramiro, A. R., Stavropoulos, P., Jankovic, M. & Nussenzweig, M. C. Transcription enhances AID-mediated cytidine deamination by exposing single-stranded DNA on the nontemplate strand. Nat. Immunol. 4, 452–456 (2003).

    Google Scholar 

  78. Han, L., Masani, S. & Yu, K. Overlapping activation-induced cytidine deaminase hotspot motifs in Ig class-switch recombination. Proc. Natl. Acad. Sci. USA 108, 11584–11589 (2011).

    Google Scholar 

  79. Chiarle, R. et al. Genome-wide translocation sequencing reveals mechanisms of chromosome breaks and rearrangements in B cells. Cell 147, 107–119 (2011).

    Google Scholar 

  80. Mikulasova, A. et al. Microhomology-mediated end joining drives complex rearrangements and overexpression of MYC and PVT1 in multiple myeloma. Haematologica 105, 1055–1060 (2020).

    Google Scholar 

  81. Preker, P. et al. PROMoter uPstream Transcripts share characteristics with mRNAs and are produced upstream of all three major types of mammalian promoters. Nucleic Acids Res. 39, 7179–7193 (2011).

    Google Scholar 

  82. Mroczek, S. et al. The non-canonical poly(A) polymerase FAM46C acts as an onco-suppressor in multiple myeloma. Nat. Commun. 8, 619 (2017).

  83. Manfrini, N. et al. FAM46C and FNDC3A are multiple myeloma tumor suppressors that act in concert to impair clearing of protein aggregates and autophagy. Cancer Res. 80, 4693–4706 (2020).

    Google Scholar 

  84. Yu, K. & Lieber, M. R. Current insights into the mechanism of mammalian immunoglobulin class switch recombination. Crit. Rev. Biochem. Mol. Biol. 54, 333–351 (2019).

    Google Scholar 

  85. Basu, U. et al. Regulation of activation-induced cytidine deaminase DNA deamination activity in B-cells by Ser38 phosphorylation. Biochem. Soc. Trans. 37, 561–568 (2009).

    Google Scholar 

  86. Mielczarek, O. et al. Intra- and interchromosomal contact mapping reveals the Igh locus has extensive conformational heterogeneity and interacts with B-lineage genes. Cell Rep. 42, 113074 (2023).

    Google Scholar 

  87. Kind, J. et al. Genome-wide maps of nuclear lamina interactions in single human cells. Cell 163, 134–147 (2015).

    Google Scholar 

  88. Pettitt, S. J. et al. Agouti C57BL/6N embryonic stem cells for mouse genetic resources. Nat. Methods 6, 493–495 (2009).

    Google Scholar 

  89. Goel, V. Y., Huseyin, M. K. & Hansen, A. S. Region capture Micro-C reveals coalescence of enhancers and promoters into nested microcompartments. Nat. Genet. 55, 1048–1056 (2023).

    Google Scholar 

  90. Doellinger, J., Schneider, A., Hoeller, M. & Lasch, P. Sample preparation by easy extraction and digestion (SPEED) - a universal, rapid, and detergent-free protocol for proteomics based on acid extraction. Mol. Cell. Proteom. 19, 209–222 (2020).

    Google Scholar 

  91. Tyanova, S., Temu, T. & Cox, J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc. 11, 2301–2319 (2016).

    Google Scholar 

  92. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    Google Scholar 

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

    Google Scholar 

  94. Li, H. & Barrett, J. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).

    Google Scholar 

  95. Zeitouni, B. et al. SVDetect: A tool to identify genomic structural variations from paired-end and mate-pair sequencing data. Bioinformatics 26, 1895–1896 (2010).

    Google Scholar 

  96. Liao, Y., Smyth, G. K. & Shi, W. Sequence analysis featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    Google Scholar 

  97. Lovén, J. et al. Revisiting global gene expression analysis. Cell 151, 476–482 (2012).

    Google Scholar 

  98. Bergstrom, E. N. et al. SigProfilerMatrixGenerator: a tool for visualizing and exploring patterns of small mutational events. BMC Genomics 20, 1–12 (2019).

    Google Scholar 

  99. O’Connell, J. et al. NxTrim: optimized trimming of Illumina mate pair reads. Bioinformatics 31, 2035–2037 (2015).

    Google Scholar 

  100. Chen, X. et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220–1222 (2016).

    Google Scholar 

  101. Niroula, A., Urolagin, S. & Vihinen, M. PON-P2: prediction method for fast and reliable identification of harmful variants. PLoS One 10, 1–17 (2015).

    Google Scholar 

  102. Krueger, F. TrimGalore! https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/. https://doi.org/10.5281/zenodo.7598955.

  103. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10–12 (2011).

    Google Scholar 

  104. Durand, N. C. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3, 95–98 (2016).

    Google Scholar 

  105. Pękowska, A. et al. Gain of CTCF-anchored chromatin loops marks the exit from naive pluripotency. Cell Syst. 7, 482 (2018).

    Google Scholar 

Download references

Acknowledgements

We thank Justyna Chlebowska, Jakub Gruchota, Kamila Kłosowska-Kosicka, Dorota Adamska, Michał Kamiński, Radosław Salamon, Katarzyna Prokop, and Monika Kusio-Kobiałka for help with selected experiments, Maria Anna Ciemerych-Litwinienko, Dominika Nowis, Jakub Gołąb, Joanna Kufel, Katarzyna Matylla-Kulińska for attentive readings of the manuscript and all Andrzej Dziembowski lab members for fruitful discussions. We thank the expert support of the Mouse Clinic Institute (Illkirch) in mouse construction and handling. Efforts of the MM Research Foundation (MMRF) and centers that contributed to the CoMMpass study are also acknowledged. All mice lines were genotyped by the Genome Engineering Facility (GEF), part of IIMCB IN-MOL-CELL Infrastructure (RRID: SCR_021630) funded by the European Union – NextGenerationEU under National Recovery and Resilience Plan, Horizon Europe (Project 101059801 - RACE) and RACE-PRIME project carried out within the IRAP program of the Foundation for Polish Science co-financed by the European Union under the European Funds for Smart Economy 2021-2027 (FENG) IIMCB. This work was mainly supported by grant funding from the National Science Center (NCN) to AD (UMO-2016/22/A/NZ4/00380; UMO-2013/10/M/NZ4/00299) and TK (UMO-2019/32/C/NZ2/00558). This research was co-supported by funding from the European Union’s Horizon 2020 research and innovation program (grant agreement no. 810425). Work in BS laboratory was supported by INCA PRTK 2021-025, USIAS, ANR-10-IDEX-0002, ANR 20-SFRI-0012, ANR-17-EURE-0023. Work in the AP laboratory is funded by the Dioscuri Grant [Dioscuri is a program initiated by the Max Planck Society (MPG), jointly managed with the National Science Center in Poland (NCN), and mutually funded by the Polish Ministry of Education and Science and the German Federal Ministry of Education and Research (BMBF)]; by the OPUS17 (UMO-2019/33/B/NZ2/02437), OPUS22 (UMO-2021/43/B/NZ2/02934), and Sonata Bis 11 (UMO-2021/42/E/NZ2/00392) grants from the NCN; and by the EMBO Installation Grant.

Author information

Author notes
  1. Marta Jedynak-Slyvka

    Present address: Technical University of Denmark, Centre for Diagnostics, Department of Health Technology, Henrik Dams Allé, 2800 Kgs, Lyngby, Denmark

Authors and Affiliations

  1. Laboratory of RNA Biology, International Institute of Molecular and Cell Biology, Warsaw, Poland

    Tomasz M. Kuliński, Karolina Kasztelan, Ewelina P. Owczarek & Andrzej Dziembowski

  2. Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Warsaw, Poland

    Tomasz M. Kuliński, Karolina Kasztelan, Nina Durys & Andrzej Dziembowski

  3. Faculty of Biology, University of Warsaw, Warsaw, Poland

    Olga Gewartowska & Andrzej Dziembowski

  4. Genome Engineering Facility, International Institute of Molecular and Cell Biology, Warsaw, Poland

    Olga Gewartowska

  5. Institut de Génétique et de Biologie Moléculaire et Cellulaire, UMR, 7104, and Centre National de Recherche Scientifique, Illkirch, France

    Mélanie Mahé & Bertrand Séraphin

  6. Institut National de Santé et de Recherche Médicale, U964, and Université de Strasbourg, Illkirch, France

    Mélanie Mahé & Bertrand Séraphin

  7. Dioscuri Center for Chromatin Biology and Epigenomics, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland

    Anna Stroynowska-Czerwińska, Debadeep Chaudhury & Aleksandra Pękowska

  8. Laboratory of Protein Structure, International Institute of Molecular and Cell Biology, Warsaw, Poland

    Marta Jedynak-Slyvka & Marcin Nowotny

  9. International Institute of Molecular Mechanisms and Machines, Polish Academy of Sciences, Flisa 6, Warsaw, Poland

    Marta Jedynak-Slyvka

Authors
  1. Tomasz M. Kuliński
    View author publications

    Search author on:PubMed Google Scholar

  2. Olga Gewartowska
    View author publications

    Search author on:PubMed Google Scholar

  3. Mélanie Mahé
    View author publications

    Search author on:PubMed Google Scholar

  4. Karolina Kasztelan
    View author publications

    Search author on:PubMed Google Scholar

  5. Nina Durys
    View author publications

    Search author on:PubMed Google Scholar

  6. Anna Stroynowska-Czerwińska
    View author publications

    Search author on:PubMed Google Scholar

  7. Marta Jedynak-Slyvka
    View author publications

    Search author on:PubMed Google Scholar

  8. Ewelina P. Owczarek
    View author publications

    Search author on:PubMed Google Scholar

  9. Debadeep Chaudhury
    View author publications

    Search author on:PubMed Google Scholar

  10. Marcin Nowotny
    View author publications

    Search author on:PubMed Google Scholar

  11. Aleksandra Pękowska
    View author publications

    Search author on:PubMed Google Scholar

  12. Bertrand Séraphin
    View author publications

    Search author on:PubMed Google Scholar

  13. Andrzej Dziembowski
    View author publications

    Search author on:PubMed Google Scholar

Contributions

T.K.: conceptualization, all bioinformatic analysis, and experimental work; O.G., M.M., N.D., K.K., A.S.C., M.J.S., E.P.O., and M.N.: experimental work; A.P. and D.C.: bioinformatic analysis B.S.: conceptualization and knock-in mice; AD: conceptualization, supervision, original draft preparation.

Corresponding authors

Correspondence to Tomasz M. Kuliński or Andrzej Dziembowski.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Communications thanks P. Leif Bergsagel and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Additional information

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

Ethical issues All procedures were approved by the First Local Ethical Committee in Warsaw affiliated at the University of Warsaw, Faculty of Biology (approval numbers WAW/092/2016, WAW/177/2016, WAW/642/2018). Housing in animal facilities was performed in conformity with local and European Commission regulations under the control of veterinarians and with the assistance of trained technical personnel.

Supplementary information

Supplementary Information (download PDF )

Description of Additional Supplementary Files (download PDF )

Supplementary Data S1 (download TXT )

Supplementary Data S2 (download TXT )

Supplementary Data S3 (download TXT )

Supplementary Data S4 (download TXT )

Supplementary Data S5 (download TXT )

Supplementary Data S6 (download TXT )

Supplementary Data S7 (download TXT )

Supplementary Data S8 (download TXT )

Reporting Summary (download PDF )

Transparent Peer Review file (download PDF )

Source data

Source Data (download ZIP )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kuliński, T.M., Gewartowska, O., Mahé, M. et al. DIS3 mutations enhance AID-driven translocations during B-cell activation, promoting transformation to multiple myeloma. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70386-3

Download citation

  • Received: 18 January 2025

  • Accepted: 25 February 2026

  • Published: 14 March 2026

  • DOI: https://doi.org/10.1038/s41467-026-70386-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Download PDF

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Videos
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • Aims & Scope
  • Editors
  • Journal Information
  • Open Access Fees and Funding
  • Calls for Papers
  • Editorial Values Statement
  • Journal Metrics
  • Editors' Highlights
  • Contact
  • Editorial policies
  • Top Articles

Publish with us

  • For authors
  • For Reviewers
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Nature Communications (Nat Commun)

ISSN 2041-1723 (online)

nature.com footer links

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing