journal article·2025-04Open access

X‐Linked Gene Dosage and SOX2 Act as Key Roadblocks for Human Germ Cell Specification in Klinefelter Syndrome

Wenteng He, Qing Luo, Jian Zhao, Mengting Wang, Allan Zhao, Luohua Feng, Ahmed Reda, Eva Lindgren, Jan‐Bernd Stukenborg, Jiayu Chen, Qiaolin Deng

Advanced Science· Volume 12· Issue 15

Abstract

Abstract Klinefelter syndrome (KS), characterized by the presence of at least one extra X‐chromosome, is a common cause of male infertility. However, the mechanism underlying the failure of germline specification is not well studied. Intriguingly, the differentiation efficiency of female human pluripotent stem cells (hPSCs) is often lower than that of male. This study investigates how X‐linked gene dosage affects human primordial germ cell‐like cells (hPGCLCs) specification in both healthy and diseased conditions. This work reveals that X‐linked genes play a multifaceted role against the fate competency to hPGCLCs, with escape genes IGSF1 and CHRDL1 inhibiting the TGF‐beta/Activin A and BMP pathways, respectively. Notably, this work identifies a previously unrecognized role of SOX2, upregulated by the escape gene USP9X, elucidating a species‐specific function in the mammalian germline. The USP9X‐SOX2 regulatory axis profoundly influenced cellular metabolism, mitochondrial morphology, and progenitor competence in hPGCLCs specification. Furthermore, the inability to downregulate SOX2 and upregulate SOX17 in response to BMP signaling impedes downstream gene activation due to motif binding competition. These findings shed novel insights into the human germline specification by elucidating the divergent roles of SOX2 versus SOX17 in mammals, influenced by X‐linked gene dosage effects. These results offer potential applications for improving the induction efficiency of hPGCLCs, facilitating disease mechanistic studies.
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Research context

OpenAlex topics: Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities · CRISPR and Genetic Engineering · Animal Genetics and Reproduction

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

Affiliations

Department of Physiology and Pharmacology Karolinska Institutet Stockholm 171 77 Sweden

Department of Oncology‐Pathology Karolinska Institutet Stockholm 171 77 Sweden

Clinical and Translational Research Center of Shanghai First Maternity and Infant Hospital Shanghai Key Laboratory of Signaling and Disease Research School of Life Sciences and Technology Tongji University Shanghai 200092 China

NORDFERTIL Research Lab Stockholm Childhood Cancer Research Unit Department of Women's and Children's Health Karolinska Institutet Karolinska University Hospital Stockholm 17 165 Sweden

Frontier Science Center for Stem Cell Research Tongji University Shanghai 200092 China

Department of Molecular Biosciences, The Wenner‐Gren Institute Stockholm Unviersity Stockholm 11418 Sweden

Funding

Vetenskapsrådet · National Key Research and Development Program of China

References (89)

Show source-provided references
1. 10.1126/science.aaz683010.1126/science.aaz6830 ↗
2. 10.1016/j.stem.2020.02.01110.1016/j.stem.2020.02.011 ↗
3. 10.1038/nature0344010.1038/nature03440 ↗
4. 10.1038/nature0347910.1038/nature03479 ↗
5. 10.1038/nature2426510.1038/nature24265 ↗
6. 10.1186/s12864-019-5507-610.1186/s12864-019-5507-6 ↗
7. 10.1371/journal.pgen.100507910.1371/journal.pgen.1005079 ↗
8. 10.1002/ajmg.c.3178710.1002/ajmg.c.31787 ↗
9. 10.1093/humrep/dey09410.1093/humrep/dey094 ↗
10. 10.1002/ajmg.c.3180010.1002/ajmg.c.31800 ↗
11. 10.1038/s41586-024-08104-610.1038/s41586-024-08104-6 ↗
12. 10.1093/biolre/iox03810.1093/biolre/iox038 ↗
13. 10.1016/j.celrep.2019.11.08310.1016/j.celrep.2019.11.083 ↗
14. 10.1016/j.stem.2013.11.02210.1016/j.stem.2013.11.022 ↗
15. 10.1101/gr.201954.11510.1101/gr.201954.115 ↗
16. 10.1016/j.stemcr.2018.12.00410.1016/j.stemcr.2018.12.004 ↗
17. 10.1016/j.celrep.2019.02.03110.1016/j.celrep.2019.02.031 ↗
18. 10.1038/s41467-022-30259-x10.1038/s41467-022-30259-x ↗
19. 10.1016/j.celrep.2016.11.05410.1016/j.celrep.2016.11.054 ↗
20. 10.1016/j.celrep.2021.10903210.1016/j.celrep.2021.109032 ↗
21. 10.1016/j.stem.2012.03.00810.1016/j.stem.2012.03.008 ↗
22. 10.1016/j.stem.2012.02.01410.1016/j.stem.2012.02.014 ↗
23. 10.1016/j.crmeth.2022.10035210.1016/j.crmeth.2022.100352 ↗
24. 10.1128/MCB.00600-1510.1128/MCB.00600-15 ↗
25. 10.1093/humrep/dez13410.1093/humrep/dez134 ↗
26. 10.1016/j.stem.2015.06.01410.1016/j.stem.2015.06.014 ↗
27. 10.1038/srep4293710.1038/srep42937 ↗
28. 10.1016/j.cell.2014.12.01310.1016/j.cell.2014.12.013 ↗
29. 10.18632/oncotarget.2786910.18632/oncotarget.27869 ↗
30. 10.1038/s41388-021-02157-x10.1038/s41388-021-02157-x ↗
31. 10.1038/s41419-023-06274-110.1038/s41419-023-06274-1 ↗
32. 10.18632/aging.20445210.18632/aging.204452 ↗
33. 10.1016/j.celrep.2017.07.07110.1016/j.celrep.2017.07.071 ↗
34. 10.1016/j.tcb.2014.07.00410.1016/j.tcb.2014.07.004 ↗
35. 10.1016/j.biocel.2022.10615810.1016/j.biocel.2022.106158 ↗
36. 10.3390/ijms1702025310.3390/ijms17020253 ↗
37. 10.15252/embj.20149044610.15252/embj.201490446 ↗
38. 10.3389/fcell.2020.0008710.3389/fcell.2020.00087 ↗
39. 10.1101/gad.293167.11610.1101/gad.293167.116 ↗
40. 10.3389/fendo.2020.0037410.3389/fendo.2020.00374 ↗
41. 10.3390/ijms1912389310.3390/ijms19123893 ↗
42. 10.1016/j.stem.2017.08.01810.1016/j.stem.2017.08.018 ↗
43. 10.1016/j.stemcr.2013.12.00910.1016/j.stemcr.2013.12.009 ↗
44. 10.1186/s13287-019-1228-710.1186/s13287-019-1228-7 ↗
45. 10.1016/j.stem.2012.02.01610.1016/j.stem.2012.02.016 ↗
46. 10.1016/j.stem.2022.03.00110.1016/j.stem.2022.03.001 ↗
47. 10.26508/lsa.20220170610.26508/lsa.202201706 ↗
48. 10.1038/s41556-022-00878-z10.1038/s41556-022-00878-z ↗
49. 10.1016/j.molcel.2010.05.00410.1016/j.molcel.2010.05.004 ↗
50. 10.1095/biolreprod.106.05368610.1095/biolreprod.106.053686 ↗
51. 10.1038/s41467-021-27172-010.1038/s41467-021-27172-0 ↗
52. 10.1007/s00018-019-03022-710.1007/s00018-019-03022-7 ↗
53. 10.1038/nrc156810.1038/nrc1568 ↗
54. 10.1038/s41467-023-44305-910.1038/s41467-023-44305-9 ↗
55. 10.1038/s41467-019-10598-y10.1038/s41467-019-10598-y ↗
56. 10.1038/s41431-018-0291-310.1038/s41431-018-0291-3 ↗
57. 10.1016/j.cell.2023.11.03310.1016/j.cell.2023.11.033 ↗
58. 10.1038/s41574-019-0224-410.1038/s41574-019-0224-4 ↗
59. 10.1016/j.stem.2015.11.01910.1016/j.stem.2015.11.019 ↗
60. 10.18632/oncotarget.990310.18632/oncotarget.9903 ↗
61. 10.1016/j.cell.2008.10.05110.1016/j.cell.2008.10.051 ↗
62. 10.1007/s00018-015-1851-010.1007/s00018-015-1851-0 ↗
63. 10.1016/j.canlet.2019.10.01510.1016/j.canlet.2019.10.015 ↗
64. 10.1242/dev.18921710.1242/dev.189217 ↗
65. 10.1016/j.cell.2015.05.01510.1016/j.cell.2015.05.015 ↗
66. 10.1016/j.stem.2017.03.00710.1016/j.stem.2017.03.007 ↗
67. 10.1016/j.devcel.2016.12.02310.1016/j.devcel.2016.12.023 ↗
68. 10.1371/journal.pgen.003011610.1371/journal.pgen.0030116 ↗
69. 10.1038/embor.2013.6710.1038/embor.2013.67 ↗
70. 10.1038/nature1241710.1038/nature12417 ↗
71. 10.1038/s41467-020-15042-010.1038/s41467-020-15042-0 ↗
72. 10.1016/j.stemcr.2016.04.00210.1016/j.stemcr.2016.04.002 ↗
73. 10.1093/bib/bbx10910.1093/bib/bbx109 ↗
74. 10.1093/gbe/evs06410.1093/gbe/evs064 ↗
75. 10.1159/00052066210.1159/000520662 ↗
76. 10.1038/s41556-017-0017-810.1038/s41556-017-0017-8 ↗
77. 10.3390/cells808085210.3390/cells8080852 ↗
78. 10.1186/s13059-022-02660-810.1186/s13059-022-02660-8 ↗
79. 10.14806/ej.17.1.20010.14806/ej.17.1.200 ↗
80. 10.1093/gigascience/giy05910.1093/gigascience/giy059 ↗
81. 10.1093/bioinformatics/bts63510.1093/bioinformatics/bts635 ↗
82. 10.1186/s12859-023-05342-910.1186/s12859-023-05342-9 ↗
83. 10.1038/s41587-020-0497-010.1038/s41587-020-0497-0 ↗
84. 10.1016/j.cell.2021.04.04810.1016/j.cell.2021.04.048 ↗
85. 10.1186/s12864-018-4772-010.1186/s12864-018-4772-0 ↗
86. 10.1186/s13059-015-0844-510.1186/s13059-015-0844-5 ↗
87. 10.1038/s41467-020-14766-310.1038/s41467-020-14766-3 ↗
88. 10.1038/s41467-022-29414-110.1038/s41467-022-29414-1 ↗
89. 10.1093/nar/gkw25710.1093/nar/gkw257 ↗