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DOI 10.1038/s41598-023-45620-3

Медицинская библиотека · Scientific reports · 2023

Identification of hub genes associated with spermatogenesis by bioinformatics analysis.

Liu Shuang, Bian Yan-Chao, Wang Wan-Lun, Liu Tong-Jia, Zhang Ting, Chang Yue, Xiao Rui, Zhang Chuan-Ling

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Spermatogenesis is a complex process related to male infertility. Till now, the critical genes and specific mechanisms have not been elucidated clearly. Our objective was to determine the hub genes that play a crucial role in spermatogenesis by analyzing the differentially expressed genes (DEGs) present in non-obstructive azoospermia (NOA) compared to OA and normal samples using bioinformatics analysis. Four datasets, namely GSE45885, GSE45887, GSE9210 and GSE145467 were used. Functional enrichment analyses were performed on the DEGs. Hub genes were identified based on protein-protein interactions between DEGs. The expression of the hub genes was further examined in the testicular germ cell tumors from the TCGA by the GEPIA and validated by qRT-PCR in the testes of lipopolysaccharide-induced acute orchitis mice with impaired spermatogenesis. A total of 203 DEGs including 34 up-regulated and 169 down-regulated were identified. Functional enrichment analysis showed DEGs were mainly involved in microtubule motility, the process of cell growth and protein transport. PRM2, TEKT2, FSCN3, UBQLN3, SPATS1 and GTSF1L were identified and validated as hub genes for spermatogenesis. Three of them (PRM2, FSCN3 and TEKT2) were significantly down-regulated in the testicular germ cell tumors and their methylation levels were associated with the pathogenesis. In summary, the hub genes identified may be related to spermatogenesis and may act as potential therapeutic targets for NOA and testicular germ cell tumors.

Для цитирования: Liu Shuang, Bian Yan-Chao, Wang Wan-Lun, Liu Tong-Jia, Zhang Ting, Chang Yue, Xiao Rui, Zhang Chuan-Ling. Identification of hub genes associated with spermatogenesis by bioinformatics analysis.. Scientific reports. 2023. DOI: 10.1038/s41598-023-45620-3.

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