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Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Non-Obstructive Azoospermia Testis.


ABSTRACT: Non-obstructive azoospermia (NOA) is one of the most important causes of male infertility. Although many congenital factors have been identified, the aetiology in the majority of idiopathic NOA (iNOA) cases remains unknown. Herein, using single-cell RNA-Seq data sets (GSE149512) from the Gene Expression Omnibus (GEO) database, we constructed transcriptional regulatory networks (TRNs) to explain the mutual regulatory relationship and the causal relationship between transcription factors (TFs). We defined 10 testicular cell types by their marker genes and found that the proportion of Leydig cells (LCs) and macrophages (tMΦ) was significantly increased in iNOA testis. We identified specific TFs including LHX9, KLF8, KLF4, ARID5B and RXRG in iNOA LCs. In addition, we found specific TFs in iNOA tMΦ such as POU2F2, SPIB IRF5, CEBPA, ELK4 and KLF6. All these identified TFs are strongly engaged in cellular fate, function and homeostasis of the microenvironment. Changes in the activity of the above-mentioned TFs might affect the function of LCs and tMΦ and ultimately cause spermatogenesis failure. This study illustrate that these TFs play important regulatory roles in the occurrence and development of NOA.

SUBMITTER: Tang XJ 

PROVIDER: S-EPMC9163961 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Non-Obstructive Azoospermia Testis.

Tang Xiao-Juan XJ   Xiao Qiao-Hong QH   Wang Xue-Lin XL   He Yan Y   Tian Ya-Nan YN   Xia Bin-Tong BT   Guo Yang Y   Huang Jiao-Long JL   Duan Peng P   Tan Yan Y  

Frontiers in genetics 20220520


Non-obstructive azoospermia (NOA) is one of the most important causes of male infertility. Although many congenital factors have been identified, the aetiology in the majority of idiopathic NOA (iNOA) cases remains unknown. Herein, using single-cell RNA-Seq data sets (GSE149512) from the Gene Expression Omnibus (GEO) database, we constructed transcriptional regulatory networks (TRNs) to explain the mutual regulatory relationship and the causal relationship between transcription factors (TFs). We  ...[more]

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