Identification of Regulatory RNA-Binding Genes in Spermatogonial Stem Cell Reprogramming to ES-like Cells Using Machine Learning-Integrated Transcriptomic and Network Analysis

利用机器学习整合的转录组学和网络分析鉴定精原干细胞重编程为ES样细胞过程中的调控RNA结合基因

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Abstract

Spermatogonial stem cells (SSCs) are unipotent germline cells with emerging pluripotent potential under specific in vitro conditions. Understanding their capacity for reprogramming and the molecular mechanisms involved offers valuable insights into regenerative medicine and fertility preservation. SSCs were isolated from Oct4-GFP C57BL/6 transgenic mice using enzymatic digestion and cultured in defined media. Under these conditions, ES-like colonies emerged expressing pluripotency markers. These cells were characterized by immunocytochemistry, teratoma assays, and transcriptomic analyses using bulk and single-cell RNA sequencing datasets. Gene expression profiles were compared with ESCs and SSCs using datasets from GEO (GSE43850, GSE38776, GSE149512). Protein-protein interaction (PPI) networks and co-expression modules were explored through STRING, Cytoscape, and WGCNA. ES-like cells derived from SSCs exhibited strong expression of OCT4, DAZL, and VASA. Transcriptomic analysis revealed key differentially expressed genes and shared regulatory networks with ESCs. WGCNA identified key co-expression modules and hub regulatory RNA binding genes (Ctdsp1, Rest, and Stra8) potentially responsible for the reprogramming process. Teratoma assays confirmed pluripotency, and single-cell RNA-seq validated expression of critical markers in cultured SSCs. This study demonstrates that SSCs can acquire pluripotency features and be reprogrammed into ES-like cells. The integration of transcriptomic and network-based analyses reveals novel insights into the molecular drivers of SSC reprogramming, highlighting their potential utility in stem cell-based therapies and male fertility preservation.

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