Abstract
In recurrent spontaneous abortion (RSA), impaired decidualization due to decidual stromal cell (DS) apoptosis or pyroptosis disrupts pregnancy maintenance. RNA-binding proteins (RBPs) are crucial regulators of gene expression in reproductive disorders. However, the comprehensive profile and dynamic role of RBPs in DS cells during RSA are not fully understood. In this study, single-cell transcriptome sequencing (scRNA-seq) data originated from six decidua tissues of RSA group and five health controls were downloaded and analyzed by differentially expressed genes (DEGs) analysis, pseudotime analysis, functional enrichment analysis, RBPs regulatory program analysis, transcription factor regulatory network analysis, correlation analysis and etc. We employed bulk RNA-seq data (including three RSA decidua tissues and three decidua in normal early pregnancy) to confirm the results from scRNA-seq data. DS cells were the most abundant population in decidua and the primary dysregulated type in RSA, showing a reduced proportion. DS harbored the most DEGs, enriched in post-transcriptional regulation. RBPs served as effective markers for cell annotation and reflected pathological states. Decorin (DCN) and lectin galactoside-binding soluble 3 (LGALS3) were upregulated, while ribosomal protein S17 (RPS17) was downregulated across various cells. The DS subclusters RBP-DS_0, 2, and 4 were diminished in RSA, with RBP-DS_2 nearly absent. Pseudotime analysis revealed an aberrant DS differentiation trajectory from State1 (pseudotime starting point) to State2 linked to abnormal progression in RSA. The expression of DCN, LGALS3, and solute carrier family 3 member 2 (SLC3A2) in DS subpopulations was significantly elevated in RSA and peaked in State2 along the pseudotime. This study explores RBPs for cell annotation and clustering in decidual tissue. Our findings implicated the regulatory role of RBPs in RSA pathogenesis and highlighted three key RBPs (DCN, LGALS3, and SLC3A2) whose upregulation in DS subclusters during the progression of RSA may be associated with aberrant differentiation, suggesting their potential as biomarkers and therapeutic targets.
Data availability
The data that support the findings of this study are available in the supplementary file of this article. Further inquiries can be directed to the corresponding author.
References
RPL, E. G. G. et al. ESHRE guideline: recurrent pregnancy loss: an update in 2022. Hum Reprod Open hoad002, (2023). https://doi.org/10.1093/hropen/hoad002 (2023).
Dimitriadis, E., Menkhorst, E., Saito, S., Kutteh, W. H. & Brosens, J. J. Recurrent pregnancy loss. Nat. Rev. Dis. Primers. 6, 98. https://doi.org/10.1038/s41572-020-00228-z (2020).
PrabhuDas, M. et al. Immune mechanisms at the maternal-fetal interface: perspectives and challenges. Nat. Immunol. 16, 328–334. https://doi.org/10.1038/ni.3131 (2015).
Papas, R. S. & Kutteh, W. H. A new algorithm for the evaluation of recurrent pregnancy loss redefining unexplained miscarriage: review of current guidelines. Curr. Opin. Obstet. Gynecol. 32, 371–379. https://doi.org/10.1097/GCO.0000000000000647 (2020).
Cha, J., Sun, X. & Dey, S. K. Mechanisms of implantation: strategies for successful pregnancy. Nat. Med. 18, 1754–1767. https://doi.org/10.1038/nm.3012 (2012).
Liang, Y. et al. JAZF1 safeguards human endometrial stromal cells survival and decidualization by repressing the transcription of G0S2. Commun. Biol. 6, 568. https://doi.org/10.1038/s42003-023-04931-x (2023).
Ander, S. E., Diamond, M. S. & Coyne, C. B. Immune responses at the maternal-fetal interface. Sci. Immunol. 4 https://doi.org/10.1126/sciimmunol.aat6114 (2019).
Li, D., Zheng, L., Zhao, D., Xu, Y. & Wang, Y. The Role of Immune Cells in Recurrent Spontaneous Abortion. Reprod. Sci. 28, 3303–3315. https://doi.org/10.1007/s43032-021-00599-y (2021).
Glisovic, T., Bachorik, J. L., Yong, J. & Dreyfuss, G. RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 582, 1977–1986. https://doi.org/10.1016/j.febslet.2008.03.004 (2008).
Gebauer, F., Schwarzl, T., Valcarcel, J. & Hentze, M. W. RNA-binding proteins in human genetic disease. Nat. Rev. Genet. 22, 185–198. https://doi.org/10.1038/s41576-020-00302-y (2021).
Lukong, K. E., Chang, K. W., Khandjian, E. W. & Richard, S. RNA-binding proteins in human genetic disease. Trends Genet. 24, 416–425. https://doi.org/10.1016/j.tig.2008.05.004 (2008).
Khalaj, K. et al. RNA-Binding Proteins in Female Reproductive Pathologies. Am. J. Pathol. 187, 1200–1210. https://doi.org/10.1016/j.ajpath.2017.01.017 (2017).
Van Nostrand, E. L. et al. A large-scale binding and functional map of human RNA-binding proteins. Nature 583, 711–719. https://doi.org/10.1038/s41586-020-2077-3 (2020).
Zhu, R. H. et al. The Mechanism of Insulin-Like Growth Factor II mRNA-Binging Protein 3 Induce Decidualization and Maternal-Fetal Interface Cross Talk by TGF-beta1 in Recurrent Spontaneous Abortion. Front. Cell. Dev. Biol. 10, 862180. https://doi.org/10.3389/fcell.2022.862180 (2022).
Du, L. et al. Single-cell transcriptome analysis reveals defective decidua stromal niche attributes to recurrent spontaneous abortion. Cell. Prolif. 54, e13125. https://doi.org/10.1111/cpr.13125 (2021).
Liu, X. et al. Comprehensive Analysis of circRNAs, miRNAs, and mRNAs Expression Profiles and ceRNA Networks in Decidua of Unexplained Recurrent Spontaneous Abortion. Front. Genet. 13, 858641. https://doi.org/10.3389/fgene.2022.858641 (2022).
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411–420. https://doi.org/10.1038/nbt.4096 (2018).
Kim, D., Langmead, B. & Salzberg, S. L. HISAT: a fast spliced aligner with low memory requirements. Nat. Methods. 12, 357–360. https://doi.org/10.1038/nmeth.3317 (2015).
Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515. https://doi.org/10.1038/nbt.1621 (2010).
Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods. 16, 1289–1296. https://doi.org/10.1038/s41592-019-0619-0 (2019).
Ianevski, A., Giri, A. K. & Aittokallio, T. Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic data. Nat. Commun. 13, 1246. https://doi.org/10.1038/s41467-022-28803-w (2022).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550. https://doi.org/10.1186/s13059-014-0550-8 (2014).
Qiu, X. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat. Methods. 14, 979–982. https://doi.org/10.1038/nmeth.4402 (2017).
Xie, C. et al. KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 39, W316–322. https://doi.org/10.1093/nar/gkr483 (2011).
Castello, A. et al. Insights into RNA biology from an atlas of mammalian mRNA-binding proteins. Cell 149, 1393–1406. https://doi.org/10.1016/j.cell.2012.04.031 (2012).
Aibar, S. et al. SCENIC: single-cell regulatory network inference and clustering. Nat. Methods. 14, 1083–1086. https://doi.org/10.1038/nmeth.4463 (2017).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47. https://doi.org/10.1093/nar/gkv007 (2015).
Suo, S. et al. Revealing the Critical Regulators of Cell Identity in the Mouse Cell Atlas. Cell Rep 25, 1436–1445 e1433, (2018). https://doi.org/10.1016/j.celrep.2018.10.045
Baltz, A. G. et al. The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts. Mol. Cell. 46, 674–690. https://doi.org/10.1016/j.molcel.2012.05.021 (2012).
Sun, Q. & Zhang, X. L. Research on apoptotic signaling pathways of recurrent spontaneous abortion caused by dysfunction of trophoblast infiltration. Eur. Rev. Med. Pharmacol. Sci. 21, 12–19 (2017).
Gupta, S., Agarwal, A., Banerjee, J. & Alvarez, J. G. The role of oxidative stress in spontaneous abortion and recurrent pregnancy loss: a systematic review. Obstet. Gynecol. Surv. 62, 335–347. https://doi.org/10.1097/01.ogx.0000261644.89300.df (2007). quiz 353 – 334.
RPL, E. G. G. et al. ESHRE guideline: recurrent pregnancy loss. Hum Reprod Open hoy004, (2018). https://doi.org/10.1093/hropen/hoy004 (2018).
Practice Committee of the American Society for Reproductive. Evaluation and treatment of recurrent pregnancy loss: a committee opinion. Fertil. Steril. 98, 1103–1111. https://doi.org/10.1016/j.fertnstert.2012.06.048 (2012).
Salker, M. S. et al. Deregulation of the serum- and glucocorticoid-inducible kinase SGK1 in the endometrium causes reproductive failure. Nat. Med. 17, 1509–1513. https://doi.org/10.1038/nm.2498 (2011).
Salker, M. S. et al. Disordered IL-33/ST2 activation in decidualizing stromal cells prolongs uterine receptivity in women with recurrent pregnancy loss. PLoS One. 7, e52252. https://doi.org/10.1371/journal.pone.0052252 (2012).
Haig, D. Cooperation and conflict in human pregnancy. Curr. Biol. 29, R455–R458. https://doi.org/10.1016/j.cub.2019.04.040 (2019).
Jin, B. et al. Deciphering decidual deficiencies in recurrent spontaneous abortion and the therapeutic potential of mesenchymal stem cells at single-cell resolution. Stem Cell. Res. Ther. 15, 228. https://doi.org/10.1186/s13287-024-03854-6 (2024).
Zhang, H. et al. The roles of RNA-binding proteins in ovarian aging. J. Assist. Reprod. Genet. https://doi.org/10.1007/s10815-025-03765-2 (2025).
Wang, L. et al. Decorin promotes decidual M1-like macrophage polarization via mitochondrial dysfunction resulting in recurrent pregnancy loss. Theranostics 12, 7216–7236. https://doi.org/10.7150/thno.78467 (2022).
Halari, C. D., Zheng, M. & Lala, P. K. Roles of Two Small Leucine-Rich Proteoglycans Decorin and Biglycan in Pregnancy and Pregnancy-Associated Diseases. Int. J. Mol. Sci. 22 https://doi.org/10.3390/ijms221910584 (2021).
Dumic, J., Dabelic, S. & Flogel, M. Galectin-3: an open-ended story. Biochim. Biophys. Acta. 1760, 616–635. https://doi.org/10.1016/j.bbagen.2005.12.020 (2006).
Abramovic, I. et al. LGALS3 cfDNA methylation in seminal fluid as a novel prostate cancer biomarker outperforming PSA. Prostate 84, 1128–1137. https://doi.org/10.1002/pros.24749 (2024).
Dong, R. et al. Galectin-3 as a novel biomarker for disease diagnosis and a target for therapy (Review). Int. J. Mol. Med. 41, 599–614. https://doi.org/10.3892/ijmm.2017.3311 (2018).
Jovanovic Krivokuca, M. et al. Galectins in Early Pregnancy and Pregnancy-Associated Pathologies. Int. J. Mol. Sci. 23 https://doi.org/10.3390/ijms23010069 (2021).
Xiao, Q. et al. Expression of galectin-3 and apoptosis in placental villi from patients with missed abortion during early pregnancy. Exp. Ther. Med. 17, 2623–2631. https://doi.org/10.3892/etm.2019.7227 (2019).
Fort, J. et al. The structure of human 4F2hc ectodomain provides a model for homodimerization and electrostatic interaction with plasma membrane. J. Biol. Chem. 282, 31444–31452. https://doi.org/10.1074/jbc.M704524200 (2007).
Fotiadis, D., Kanai, Y. & Palacin, M. The SLC3 and SLC7 families of amino acid transporters. Mol. Aspects Med. 34, 139–158. https://doi.org/10.1016/j.mam.2012.10.007 (2013).
Shi, J. W. et al. TNFSF14(+) natural killer cells prevent spontaneous abortion by restricting leucine-mediated decidual stromal cell senescence. EMBO J. 43, 5018–5036. https://doi.org/10.1038/s44318-024-00220-3 (2024).
Khalaj, K. et al. RNA binding protein, tristetraprolin in a murine model of recurrent pregnancy loss. Oncotarget 7, 72486–72502. https://doi.org/10.18632/oncotarget.12539 (2016).
Dai, F. et al. IGF2BP3 participates in the pathogenesis of recurrent spontaneous abortion by regulating ferroptosis. J. Reprod. Immunol. 165, 104271. https://doi.org/10.1016/j.jri.2024.104271 (2024).
Zhang, W. et al. Deciphering the IGF2BP3-mediated control of ferroptosis: mechanistic insights and therapeutic prospects. Discov Oncol. 15, 547. https://doi.org/10.1007/s12672-024-01432-z (2024).
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Q.Y. were responsible for study concept and design. Y.Z. was in charge of drafting the manuscript. Y.Z., X.W and A.L. performed data analysis. Q.Y. B.X. and D.C. contributed to critical revision of the manuscript for important intellectual contents. All authors have read and agreed to the published version of the manuscript.
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Zhu, Y., Chen, D., Xu, B. et al. Dysregulated landscape of RNA-binding proteins in unexplained recurrent spontaneous abortion revealed by bulk and single-cell transcriptome. Sci Rep (2026). https://doi.org/10.1038/s41598-026-45052-9
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DOI: https://doi.org/10.1038/s41598-026-45052-9
