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The mitotic STAG3–cohesin complex shapes male germline nucleome

Nature Structural & Molecular Biology volume 32, pages 2203–2218 (2025)Cite this article

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Abstract

Germ cells are unique in that they tailor chromatin toward generating totipotency. Accordingly, mammalian spermatogonia, including spermatogonial stem cells that constitute the source for male gametes, acquire distinctive chromatin organization with weak insulation, but the underlying mechanism remains unknown. Here we show that STAG3, so far known to exclusively form meiotic cohesins, generates a mitotic cohesin for male germline nucleome programming in mice. Owing to its shorter chromatin residence, STAG3–cohesin attenuates topologically associating domains, rewires enhancer–promoter and Polycomb-mediated repressive interactions, and facilitates finer and more strengthened compartments, establishing a distinctive spermatogonial nucleome. Moreover, in the absence of STAG3–cohesin, spermatogonial stem cells show an impaired differentiation priming for spermatogenesis. Mitotic STAG3–cohesin is also expressed in human B cells and their malignant variations, promoting their propagation. Our findings on mitotic STAG3–cohesin elucidate a principle of male germline nucleome programming, demonstrate an unexpected mitotic role for STAG3 and might potentially improve understanding of human malignancies.

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Fig. 1: Identification of STAG3–cohesin in GSCs and spermatogonia.
Fig. 2: The functions of STAG3–cohesin during male germ-cell development.
Fig. 3: STAG3–cohesin attenuates insulation for relevant gene expression.
Fig. 4: STAG3 is sufficient for mitosis and meiosis.
Fig. 5: STAG3–cohesin exhibits shorter chromatin residence with potentially slower loop extrusion.
Fig. 6: Mitotic STAG3–cohesin in a heterologous context.
Fig. 7: STAG3–cohesin in human cells and their malignancies.

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Data availability

Sequencing data generated in this study have been deposited in the Gene Expression Omnibus (GEO) under accession number GSE243962. The raw MS data and analysis files have been deposited in the ProteomeXchange Consortium at http://proteomecentral.proteomexchange.org via the jPOST partner repository at https://jpostdb.org, and can be accessed using the dataset identifier PXD045854 (ref. 144). Source data are provided with this paper.

Code availability

Computational codes and scripts used in this study are available via GitHub at https://github.com/masahiro-nagano/Nagano_2025_NSMB and via Zenodo at https://doi.org/10.5281/zenodo.15813858 (ref. 145).

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Acknowledgements

We thank the members of our laboratory for their helpful input on this study. We are grateful to S. Goulas and J. A. Drayton for the critical review of the paper; T. Nakamura, K. Fujiwara, M. Kawasaki, Y. Kojima, I. Okamoto, Y. Nagai, N. Konishi, E. Tsutsumi, M. Kawasaki and the Single-Cell Genome Information Analysis Core (SignAC) in ASHBi for technical assistance and help with all sequencing experiments; R. Maeda for helpful discussion regarding the genetic manipulation; Y. Mori for discussion on the testis dissociation; Y. Guo, K. Nakao, M. Nishikori and A. Takaori-Kondo for help with the lymphoma experiments; M. Imakeav, N. Chowdhury and L. A. Mirny for help with polymer simulation; and G. Wutz and I. F. Davidson for discussions. The mouse strain used for this research project, C57BL/6N-/A/^/tm1Brd//Stag3/^/tm1e.1(KOMP)Wtsi//JMmucd, RRID MMRRC_049884-UCD, was obtained from the Mutant Mouse Resource and Research Center (MMRRC) at University of California at Davis, an NIH-funded strain repository, and was donated to the MMRRC by The KOMP Repository, University of California, Davis; originating from S. Murray at The Jackson Laboratory. This work was supported in part by a Grant-in-Aid for Specially Promoted Research from JSPS (22H04920), a grant from HFSP (RGP0057/2018), a grant from the Open Philanthropy Project (2018-193685, GV673604305) to M.S., a JSPS KAKENHI grant (JP 21K20635) to M.N., a Grant-in-Aid for Transformative Research Areas (A) (23H04952) to S.Y., a JSPS KAKENHI grant (JP23H04777), a JST FOREST grant (JPMJFR2317) to M.Y., and NIH grants (CA196539 and NS111997) to B.A.G. Research in the laboratory of J.-M.P. was supported by Boehringer Ingelheim and the European Research Council Horizon 2020 Research and Innovation Programme (101020558). A.S.H. acknowledges funding from the NIH (DP2GM140938, R33CA257878, R01EB035127 and UM1HG011536) and the Mathers Foundation, and M.G. acknowledges funding from the NIH (K99GM149815). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.

Author information

Author notes

  1. These authors contributed equally: Masahiro Nagano, Bo Hu.

Authors and Affiliations

  1. Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan

    Masahiro Nagano, Bo Hu, Fumiya Umemura, Yukiko Ishikura, Yoshiaki Nosaka, Hiromichi Sasada, Hanbo Wang, Daichi Kondo, Yoshitaka Katou, Ken Mizuta, Yukihiro Yabuta, Hiroshi Ohta, Takafumi Ichikawa & Mitinori Saitou

  2. Department of Anatomy and Cell Biology, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Masahiro Nagano, Bo Hu, Fumiya Umemura, Yukiko Ishikura, Yoshiaki Nosaka, Hiromichi Sasada, Hanbo Wang, Daichi Kondo, Yoshitaka Katou, Ken Mizuta, Yukihiro Yabuta, Hiroshi Ohta & Mitinori Saitou

  3. Department of Human Genetics, McGill University, Montreal, Quebec, Canada

    Bo Hu & Jacek Majewski

  4. Department of Molecular Systems BioAnalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan

    Kosuke Ogata & Yasushi Ishihama

  5. Division of Germ Cell Biology, National Institute for Basic Biology, National Institutes of Natural Sciences, Myodaiji, Japan

    Shinnosuke Suzuki & Shosei Yoshida

  6. Graduate Institute for Advanced Studies, SOKENDAI, Myodaiji, Japan

    Shinnosuke Suzuki & Shosei Yoshida

  7. Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Christos C. Katsifis, Michele Gabriele & Anders S. Hansen

  8. The Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Christos C. Katsifis, Michele Gabriele & Anders S. Hansen

  9. Koch Institute for Integrative Cancer Research, Cambridge, MA, USA

    Christos C. Katsifis, Michele Gabriele & Anders S. Hansen

  10. The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Christos C. Katsifis, Michele Gabriele & Anders S. Hansen

  11. Department of Medical Chemistry, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Masanori Yoshinaga & Osamu Takeuchi

  12. Research Institute of Molecular Pathology (IMP), Vienna BioCenter (VBC), Vienna, Austria

    Gabriele Litos, Kota Nagasaka, Wen Tang & Jan-Michael Peters

  13. Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA

    Francisca Nathalia de Luna Vitorino & Benjamin A. Garcia

  14. Department of Hematology, Kyoto University Hospital, Kyoto, Japan

    Hiroshi Arima

  15. Department of Developmental Biology, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Takafumi Ichikawa

  16. Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan

    Mitinori Saitou

Authors
  1. Masahiro Nagano
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  2. Bo Hu
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  3. Kosuke Ogata
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  31. Mitinori Saitou
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Contributions

M.N. and B.H. are equally contributing first author; K.O. and F.U. are equally contributing second authors. Conceptualization: M.N., B.H. and M.S. Investigation: M.N., B.H., K.O., F.U., Y. Ishikura, S.S., C.C.K., G.L., Y.N., H.S., H.W., D.K. and F.N.L.V. Methodology: M.N., B.H., K.O., F.U., Y. Ishikura, M.Y., K.N., W.T., T.I., Y.N., H.S., H.W., D.K., F.N.L.V., Y.K., K.M., Y.Y., H.O., H.A., T.I. and M.G. Formal analysis: M.N., B.H., K.O. and F.U. Writing: M.N., B.H. and M.S. Supervision: J.M., B.A.G., O.T., S.Y., A.S.H., J.-M.P., Y. Ishihama and M.S.

Corresponding authors

Correspondence to Masahiro Nagano or Mitinori Saitou.

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Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Structural & Molecular Biology thanks Ana Losada and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: Dimitris Typas, in collaboration with the Nature Structural & Molecular Biology team.

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

Extended data

Extended Data Fig. 1 The in vitro system recapitulates key features of germ-cell development.

a, Correlation heatmap of transcriptomic profiles of the top 5,000 most variable genes among the indicated cell types [ESCs; EpiLCs; d2PGCLCs; d4c7PGCLCs; GSCs31,41,146; E11.5/12.5 germ cells38; and P7 Kit− spermatogonia]. b, Correlation heatmap of 5mC profiles in the genome-wide 2 kb bins among the indicated cell types: E13.5 germ cells (ESCs; EpiLCs; d2PGCLCs; d4c7PGCLCs; GSCs31,41,147; E13.5 germ cells148; and P7 Kit− spermatogonia24). c, Unsupervised hierarchical clustering (UHC) based on Euclidean distance among 100 kb compartment score tracks of the indicated cell types [in vitro (ESCs/EpiLCs/d4c7PGCLCs/GSCs)19, in vivo [E3.5 ICM/E6.5 epiblast cells149/E11.5 PGCs20], and spermatogonia in several publications81,150,151. Note that spermatogonia reported by Zuo et al.81 and Vara et al.150 were purified by FACS based on DNA content and include undifferentiated and differentiating spermatogonia, while those by Luo et al.151 were collected with unit gravity sedimentation followed by purity confirmation with immunofluorescence (IF) analysis. Primitive type A spermatogonia (priSG-A) expressed GFRA1 and were enriched for spermatogonial stem cells, while type A spermatogonia expressed KIT and were enriched for differentiating spermatogonia151.

Source data

Extended Data Fig. 2 STAG3–cohesin in GSCs and during male germ-cell development.

a, The numbers of RAD21 peaks co-localizing (red, CTCF) or not co-localizing (blue, non-CTCF) with CTCF peaks in the indicated cell types. b, Proportion of non-CTCF RAD21 sites annotated to open sites bearing different chromatin states in GSCs. Open sites are annotated in Nagano et al.19, with promoter and promoterCTCF designated as active promoter (Act. Prom) and CTCF, respectively. c, ChIP-seq read density for CTCF, STAG1/2, and RAD21 (2 kb window) around the RAD21 peak centers in the indicated cell types. The RAD21 peaks with CTCF and STAG1/2, with STAG1 only, with STAG2 only, and with no STAGs are shown. Note that GSCs show a substantial proportion ( ~ 30%) of no STAG peaks. d, Proportion of RAD21 peaks overlapping with those of STAGs in the indicated cell types. e, Representative ChIP-seq tracks of STAG 1/2 and RAD21 in EpiLCs and GSCs. Blue highlight represent RAD21 peaks lacking CTCF, STAG1, and STAG2 f, RNA [log2 (RPM + 1)] and protein expression (normalized with RAD21) of Stag1/2/3/STAG1/2/3 in the indicated cell types measured by 3′ RNA-seq and Western blot analysis, respectively. g, Stag1/2/3 mRNA expression during male and female germ-cell development in vivo at the indicated embryonic days (E) and postnatal days (P)33,38,99. h, STAG3 mRNA expression during human male germ cell developtment128,129,130 at the indicated embryonic weeks (wk) and postnatal months (M). i, Protein quantification with RAD21 (left)- and STAG3 (right)-IP-MS from GSCs using iBAQ. “N.D.” indicates not detected. Note that this RAD21-IP-MS was an independent experiment from that in Fig. 1d.

Source data

Extended Data Fig. 3 Generation of Stag3 knockout in GSCs and characterization of their phenotype.

a, (top) Scheme of PAM and guide RNA in the Stag3 exon 2. (bottom) Sequences of the targeted loci in two Stag3 KO lines. b, Western blot for STAG3 and α-tubulin in WT and Stag3 KO GSCs. c, STAG3 enrichment at STAG3-peaks defined in WT GSCs in WT and Stag3 KO GSCs (one experiment). d, DEGs between WT and Stag3 KO GSCs by MA plot. e, Two-sided Fisher’s exact test of the overlap of DEGs between E12.5 male germ cells38 and P7 KIT− spermatogonia24 with DEGs between WT and Stag3 KO GSCs. p-values and the proportion of overlapped genes are indicated, and colors represent the odds ratio. f, A model of spermatogonia subpopulations44,45,46. Undifferentiated spermatogonia contain spermatogonial stem cells (SSCs) (“stem-cell” spermatogonia: Gfrα1+/Plvap+), which either self-renew or form “intermediate” (Gfrα1+/Plvap−) and “differentiation-primed” (Gfrα1−/Ngn3+/Rarg+) spermatogonia. The “differentiation-primed” spermatogonia are immediate precursors for “differentiating” spermatogonia (Kit+) for spermatogenesis. Both “intermediate” and “differentiation-primed” spermatogonia retain a capacity to revert to “stem-cell” spermatogonia. The expression of key markers is described at the bottom of the panel. g, Uniform manifold approximation and projection (UMAP) for dimensionality reduction and Louvain clustering of the mouse “spermatogonia” scRNA-seq dataset43. “Spermatogonia” are classified into: “stem-cell” spermatogonia (2), “differentiation-primed” spermatogonia (3), “differentiating” spermatogonia 1 (1), “differentiating” spermatogonia 2 (0), and “early meiotic” spermatocytes (4). h, UMAP embedding as in (g) for marker expression (normalized expression levels). i, Marker gene expression in the five cell populations in (g). j, Mean expression of the Stag1/2/3 in the “stem-cell” spermatogonia (StemCellSg), “differentiation-primed” spermatogonia (Diff. Primed), and “differentiating” spermatogonia 1 (DiffSg1). k, UMAP embedding and Louvain clustering of a human “spermatogonia” scRNA-seq dataset131. Cells were classified into 12 populations. DiffSg: differentiating spermatogonia; StemCellSg: “stem-cell” spermatogonia; Diff.Primed: “differentiation-primed” spermatogonia; NonSg: non-spermatogonia. l, Marker gene expression in the 12 cell populations in (k).

Source data

Extended Data Fig. 4 Characterization of spermatogenesis/spermatogonia in Stag3 KO mice.

a, UMAP and Louvain clustering of scRNA-seq data of WT and Stag3 KO mouse testes at P15. Cells were classified into 12 distinct populations, as indicated. UndiffSg: undifferentiated spermatogonia; DiffSg: differentiating spermatogonia. b, Expression of spermatogonia markers and a Sertoli marker (Sox9) in the UMAP in (a). c, Distribution of WT and Stag3 KO cells in the UMAP in (a). d, UMAP and Louvain clustering of the spermatogonia population (cluster1) in (a). The spermatogonia were classified into “stem-cell” (cluster 1), “intermediate” (cluster 2), “differentiation-primed” (cluster 0), and “differentiating” (cluster 3) spermatogonia. e, Marker gene expression in the four populations described in (d). f, Violin and box plots of the normalized expression of the indicated genes in WT and Stag3 KO spermatogonia at P15. Box plots are as in Fig. 2d. p-values are measured by two-sided Welch’s t-test. Each box plot includes 2,616 WT and 2,418 KO cells. p-values shown in the panels are as follows: Id4 (6.3 × 10−5), Dusp6 (3.2 × 10−3), Neurog3 (1.6 × 10−3), Gfra1 (1.3 × 10−2), Sox3 (6.9 × 10−3), Rarg (2.9 × 10−3). g, UMAP and Louvain clustering of scRNA-seq data of WT and Stag3 KO undifferentiated spermatogonia at 8 weeks. Cells were classified into 11 distinct populations, as indicated. StemCellSg: “stem-cell” spermatogonia; Diff.Primed: “differentiation-primed” spermatogonia; EarlyMs: early meiotic cells; LateGerm: late-stage germ cells, including spermatocytes and spermatids. h, Spermatogonia marker expression in the UMAP in (g). i, Violin and dot plots of the normalized expression of the indicated genes in the clusters for undifferentiated spermatogonia [clusters 0 − 6 in the UMAP in (g)]. j, Correlation of Stag1, Stag2, and Stag3 with genes in undifferentiated spermatogonia [cluster 0 − 6 in (g)] in 8-week testes. The genes on the X-axis are ordered by correlation. k, Immunofluorescence (IF) analysis for GFRA1 (magenta), SOX9 (cyan), and PLZF (yellow) expression in P15 WT and Stag3 KO testes. Bar, 50 μm. For each genotype, a total of four slides were analyzed, prepared from two testes obtained from two different mice (two slides per testis).

Source data

Extended Data Fig. 5 A mechanistic basis of the Stag3 KO phenotypes in GSCs.

a, ChIP-seq read density for RAD21 in WT and Stag3 KO GSCs (2 kb window) around the CTCF-colocalized and CTCF-non-colocalized RAD21 peak centers. b, Differential Hi-C contact map between WT and Stag3 KO GSCs (top) and CTCF-binding profile in WT GSCs (bottom). Red circles, more frequent interactions between CTCF-binding sites (pink) in Stag3 KO GSCs. c, Genome-wide contact probability (P(s)) curves (top) and their slopes (P’(s)) (bottom) for E11.5 mitotic pro-spermatogonia20 and WT and Stag3 KO GSCs. d, Overlap of CTCF-binding sites between WT and Stag3 KO GSCs. e, Comparison of the normalized CTCF-binding intensity in CTCF/cohesin co-occupied regions between WT and Stag3 KO GSCs. f, Differential interaction strength, as measured by chromosight84, for enhancer–promoter (left two panels) and Polycomb-associated loops (right two panels) between WT and Stag3 KO GSCs. p-values are measured by two-sided Welch’s t-test. Control genes, expression-matched genes with the genes of interest as defined in Fig. 3i, j. Box plots are as in Fig. 2d. Gene numbers analyzed are as follows: E–P interaction (left panel) — DEG-Control: Upregulated genes (left): 218-95, 174-91, 135-86, 125-73, 297-224; Downregulated genes (right): 297-134, 354-251, 271-180, 213-141, 397-378. Polycomb interaction (right panel) — Upregulated genes (left): 22-13, 14-8, 16-14, 8-8, 345-158; Downregulated genes (right): 42-15, 16-8, 26-15, 35-33, 934-456. p-values (ordered left to right) for each panel are as follows: E–P interaction (left panel) — Upregulated genes (left): 0.44, 0.0035, 0.15, 0.022, 0.55; Downregulated genes (right): 0.00012, 0.015, 0.00036, 0.94, 0.0068. Polycomb interaction (right panel) — Upregulated genes (left): 0.14, 0.13, 0.14, 0.71, 0.00039; Downregulated genes (right): 0.26, 0.010, 0.059, 0.62, 0.70. g, Violin and box plots of the expression of down-regulated genes in Stag3 KO GSCs defined in E12.5 male germ cells38 and P7 Kit− spermatogonia24. The p-value (<2.22e−16) was measured by two-sided Welch’s t-test. Box plots (471 genes each) are as in Fig. 2d. h, Virtual 4 C plot from the transcription start site (TSS: yellow shade) of Ddx4 in E13.5 male germ cells20 and undifferentiated spermatogonia151. Red shading, Ddx4 enhancer19.

Source data

Extended Data Fig. 6 Generation and phenotypes of single-Stag GSCs.

a, (Top) Scheme for PAM and guide RNA sequences in the Stag1 exon4 (left) or in the Stag2 exon8 (right). (Bottom) Sequences of the targeted loci in the Stag1/2 double-knockout (dKO) (Stag3-only) and Stag1/3 dKO (Stag2-only) lines (left) or in the Stag1/2 dKO (Stag3-only) and Stag2/3 dKO (Stag1-only) lines (right). b, The protein abundance of STAG1/2/3 was measured by in-gel digestion followed by mass spectrometry (MS) in the indicated cell lines. The protein abundance was calculated from the peak area intensities of the top 3 unique peptides that only map to the protein and do not map to other identified proteins. The protein abundance was represented using iBAQ. Two technical replicates (dots) were analyzed and the averages are shown as bars. c, Doubling time (hour, averages as bars) of WT (n = 4) and single-Stag GSCs (each n = 2). While all single-Stag GSCs appeared to show slower propagation compared to WT GSCs, we did not perform statistical analysis, since independent each single-Stag GSC clone numbers we analyzed were two. d, Representative IF images of GFP (green), SYCP3 (red) and DAPI (grey) in a testis transplanted with Stag3 KO GSCs. Bar, 50 μm. Two slides obtained from two independent mice, were analyzed. e, Representative IF images of GFP (green), SYCP3 (red) and DAPI (grey) in a testis transplanted with Stag3-only GSCs. Bar, 50 μm. Five slides obtained from two independent mice, were analyzed.

Source data

Extended Data Fig. 7 CTCF and cohesin-associated factors in single-Stag GSCs.

a, Upset plot for overlap of CTCF-binding sites among WT and single-Stag GSCs. b, Comparison of normalized CTCF intensity in CTCF/cohesin co-occupied sites between WT and single-Stag GSCs as indicated. c, Spike-in-normalized RAD21 enrichment at CTCF-binding sites in WT and single-Stag GSCs. d, The numbers of TAD boundaries defined by the TAD boundary strength measured by cooltools152 in the indicated single-Stag GSCs. e, Violin and box plots of the loop strength quantified by Chromosight84. Box plots (45,701 loops each) are as in Fig. 2d. f, Representative image of Western blot analysis for the enrichment/expression of PDS5A/B and RAD21 in WT and single-Stag GSCs in the chromatin fraction. Two technical replicates were analyzed. g, Abundance of acetylated SMC3 (SMC3ac), PDS5A/B and RAD21 in the chromatin fraction as quantified by Western blot analysis as in (f) normalized by histone H3. Two technical replicates were analyzed. Histone H3, used as a loading control, was obtained from three different lanes. All proteins were derived from the same protein lysate.

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Extended Data Fig. 8 Compartment profiles of single-Stag GSCs.

a, P’(s) curves for WT GSCs. Features analyzed by polymer simulation were annotated. b, Simulation results of P’(s) (top), the separation at slowest decay (representing the average loop size; middle), and the slope between peak and dip (representing the strength of insulation; bottom) in various parameters for the CTCF-capture ratio (left), loop extrusion velocity (middle), and cohesin residence time (right). LEF: loop extrusion factor. c, Diagram of the ATPase assay. Each component of the cohesin complex and DNA was purified (top), and ATP hydrolysis rates were compared based on their sequential addition (bottom) using thin-layer chromatography and autoradiography. d, Coomassie-blue staining of the indicated recombinant proteins on SDS-PAGE. Two biological replicates were analyzed. e, ATPase rates in the presence of the indicated components were determined using thin-layer chromatography/autoradiography. The upper and lower ends of the error bars represent mean + and – SD, respectively. p-values are measured by two-sided Welch’s t-test. Replicates per condition: n = 3 for most groups; n = 5 for Trimer+NM + DNA, and n = 4 for Trimer+STAG3 + NM + DNA. All data were obtained from two biological replicates of protein preparations. f, Scheme for the generation of STAG1-only and STAG3-only Hela cells for iFRAP experiments. OSTIR1: Oryza sativa Transport inhibitor response 1; DHB: DNA helicase B; IAA: indole-3-acetic acid (auxin); Dox: doxycycline. Halo, SNAP, AID, and FLAG are tags for proteins. g, Western blot for STAG1, STAG3, and α-tubulin in the whole cell lysate and for STAG2 and histone H3 in the chromatin fraction in STAG1-only and STAG3-only Hela cells in the presence (+) and absence (−) of IAA and Dox as indicated (one experiment). h, Representative Hi-C contact maps depicting chr5:9–42 mb at 50-kb resolution (a compartment scale) in Stag1-only and Stag3-only GSCs. The heatmap color scale represents the normalized contact frequency. i, Enrichment of homotypic (that is, intra-compartmental) interaction strength as measured using the saddle strength function of cooltools152 in Stag1- and Stag3-only GSCs. The enrichment of interactions between the A-A and B-B compartments over the A-B compartment is represented as higher y values.

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Extended Data Fig. 9 Generation of Stag3-only ESCs.

a, FACS selection of ESCs expressing eGFP and mCherry2 10 days after transfection of plasmids expressing Cas9 and sgRNA targeting the Rosa26 locus and the knock-in cassette as shown in Fig. 6a. b, (left) Scheme for the detection of the knock-in allele by four PCR pairs. (right) PCR bands of each primer pair on agarose gel electrophoresis. c, Efficiency of the knockouts by frame-shift mutations using either Stag1- or Stag2-sgRNAs in WT ESCs. Eight clones were assessed for each KO, and the efficiencies for any-base insertion or deletion were calculated. In-frame deletions were regarded as WT. d, (left) Scheme for the generation of Stag1/2 DKO ESCs on Stag1 KO- Stag3 over-expressing ESCs with Stag2 sgRNA. (right) KO efficiency with frame-shift mutations. Thirty-two clones were assessed, and the efficiency with any-base insertion or deletion in the Stag2 allele was calculated. In-frame deletions were regarded as WT. e, Western blot for STAG1, STAG2, eGFP-STAG3, and α-tubulin in WT GSCs and Stag3-only ESCs using the whole cell lysate (one experiment). f, Enrichment of the homotypic (that is, intra-compartmental) interaction strength measured by cooltools152 in WT and Stag3-only ESCs. g, Correlation of differential insulation scores between WT and Stag3-only ESCs with those between CTCF, WAPL, or RAD21 non-degraded and degraded ESCs47,65,66,67. Treated: auxin-treated for AID-tagged RAD21, CTCF, or WAPL. AID: auxin-inducible degron. h, Representative Western blot image for RAD21 and histone H3 expression in WT and Stag3-only ESCs using the chromatin fraction. Two biological replicates in each sample were analyzed. i, Abundance of RAD21 as quantified in (h) normalized by histone H3. j, Western blot for RAD21 and histone H3 expression in Stag1-only and Stag3-only mRAD21-Halo ESCs using the chromatin fraction (one experiment). While Stag1-only ESCs retain the intact Stag3 gene, they showed negligible STAG3 expression.

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Extended Data Fig. 10 STAG3 profiles in human B-cells and lymphoma and a model for the loop extrusion of the STAG1– and STAG3–cohesins.

a, Average STAG3 expression in various cell types based on the Tabula Sapiens initiative70. Box plots (others: 172 cells) are as in Fig. 2d. b, STAG3 expression in primary tumor samples as analyzed by The Cancer Genome Atlas (TCGA)71. DLBC: diffuse large B-cell lymphoma; THYM: thymoma; LGG: lower grade glioma; GBM: glioblastoma multiforme; CESC: cervical squamous cell carcinoma and endocervical adenocarcinoma. Box plots are as in Fig. 2d. Each box plot includes samples from DLBC (n = 48), THYM (n = 120), LGG (n = 514), GBM (n = 157), CESC (n = 304), and Others (n = 8,818). c, Rank–rank hypergeometric overlap (RRHO) analysis133 evaluating the correlation of the expression levels of DEGs between wild-type and Stag3 KO GSCs and the correlation of gene expression with STAG3 among DepMap lymphoma cell lines. The color coding is as indicated. The x-axis ranks genes by their correlation with STAG3 expression in lymphoid cancers, while the y-axis ranks genes by the log2 fold-change of expression between wild-type and Stag3 KO GSCs. The lower-left quadrant represents genes that have low correlation with STAG3 in lymphoid cancers and are down-regulated in wild-type GSCs. The upper-left quadrant represents genes that have low correlation with STAG3 in lymphoid cancers and are up-regulated in wild-type GSCs. The lower-right quadrant shows genes that have high correlation with STAG3 in lymphoid cancers and are down-regulated in wild-type GSCs. The upper-right quadrant represents genes that have high correlations with STAG3 in lymphoid cancer and are up-regulated in wild-type GSCs. Log10-transformed hypergeometric p-values are visualized in a heatmap, with an accompanying color scale indicating the p-value for significance. d, Scheme for the generation of mCherry-expressing STAG3 KO and GFP-expressing control OCI-Ly7 cells and design of the growth comparison experiment. CMV: Human cytomegalovirus immediate early enhancer and promoter; BSD: blasticidin; puro: puromycin. e, Representative FACS plot in a growth comparison experiment with gating strategy for the assessment of the mCherry-expressing or GFP-expressing cell ratio. f, RAD21 enrichment in CTCF-non-colocalized peaks in Stag1-only GSCs and Stag3-only GSCs. g, The fraction of reads in called peak regions (FRiP score) in WT, Stag1-only, and Stag3-only GSCs. Peaks were defined as the union of RAD21 peaks detected in at least one cell type. The FRiP score is defined as the fraction of reads that fall into a peak. The diamonds represent the mean of the two replicates. h, A model for the dynamics of loop extrusion in the indicated cell types. This model proposes that STAG1–cohesin preferentially forms longer CTCF loops and STAG3–cohesin creates shorter loops, and both cohesin variants potentially pause at non-CTCF barriers such as transcription factor complexes and Polycomb-repressive complexes.

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Supplementary information

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Supplementary Tables 1–8

Supplementary Table 1. Intensity matrix of IP–MS and gel-based MS in this study. Supplementary Table 2. DEGs between WT and Stag3 KO GSCs, and their pathway enrichments. Supplementary Table 3. List of enhancer–promoter and Polycomb-mediated loops. Supplementary Table 4. Fitting parameters of the iFRAP assays performed in this study. Supplementary Table 5. Deletion profiles in Stag KO ES cells. Supplementary Table 6. Deletion profiles in STAG3 KO OCI-Ly7 cells generated in this study. Supplementary Table 7. gRNA sequences used in this study. Supplementary Table 8. DNA oligonucleotides used in this study.

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Nagano, M., Hu, B., Ogata, K. et al. The mitotic STAG3–cohesin complex shapes male germline nucleome. Nat Struct Mol Biol 32, 2203–2218 (2025). https://doi.org/10.1038/s41594-025-01647-w

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