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pmid:34221106

Altered Gene Expression in the Testis of Infertile Patients with Nonobstructive Azoospermia.

Zhiqiang Wang · Zhongjun Ding · Yan Guan · Chunhui Liu · Linjun Wang · Wensheng Shan · Jie Yang

Computational and mathematical methods in medicine · 2021 doi:10.1155/2021/5533483

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:34221106
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science-record
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2026-11-01T15:41:41Z
updated_at
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generator object · 2 fields
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paper object · 10 fields
state
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title
Altered Gene Expression in the Testis of Infertile Patients with Nonobstructive Azoospermia.
doi
10.1155/2021/5533483
pmid
34221106
authors array · 7 items
[0]
Zhiqiang Wang
[1]
Zhongjun Ding
[2]
Yan Guan
[3]
Chunhui Liu
[4]
Linjun Wang
[5]
Wensheng Shan
[6]
Jie Yang
journal
Computational and mathematical methods in medicine
year
2021
abstract
BACKGROUND: The molecular mechanism of nonobstructive azoospermia (NOA) remains unclear. The aim of this study was to identify gene expression changes in NOA patients and to explore potential biomarkers and therapeutic targets. METHODS: The gene expression profiles of GSE45885 and GSE145467 were collected from the Gene Expression Omnibus (GEO) database, and the differences between NOA and normal spermatogenesis were analyzed. Enrichment analysis was performed to explore biological functions for common differentially expressed genes (DEGs) in GSE45885 and GSE145467. Coexpression analysis of DEGs in GSE45885 was performed, and two modules with the highest correlation with NOA were screened. Key genes were then screened from the intersection genes of the two modules and common DEGs and PPI network. The expression of key genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. Finally, through miRTarBase, miRDB, and RAID, the miRNAs were predicted to regulate key genes, respectively. RESULTS: A total of 345 common DEGs were identified and they were mainly related to spermatogenesis, insulin signaling pathway. Coexpression analysis of DEGs in GSE45885 yielded eight modules; MEblack and MEturquoise had the highest correlation with NOA. Six genes in MEturquoise and RNF141 in MEblack were identified as key genes. qRT-PCR experiments validated the differential expression of key genes between NOA and control. Furthermore, RNF141 was regulated by the largest number of miRNAs. CONCLUSION: Our findings suggest that the significant change expression of key genes may be potential markers and therapeutic targets of NOA and may have some impact on the development of NOA.
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Differential expression analysis was performed using the limma R package [21, 22] to identify differentially expressed genes (DEGs) between NOA and normal spermatogenesis.
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sections[4] "2.2. Difference Analysis" paragraph 2
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Differential expression analysis was performed using the limma R package [21, 22] to identify differentially expressed genes (DEGs) between NOA and normal spermatogenesis.
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sections[19] "Data Availability" paragraph 2
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The corresponding data can be found in GSE45885 and GSE145467.
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Transcriptome changes in patients with severely impaired spermatogenesis
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Potential biomarkers of non-obstructive azoospermia identified in microarray gene expression analysis
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Differential expression analysis was performed using the limma R package [21, 22] to identify differentially expressed genes (DEGs) between NOA and normal spermatogenesis.
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Differential expression analysis was performed using the limma R package [21, 22] to identify differentially expressed genes (DEGs) between NOA and normal spermatogenesis.
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Complete file
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The aim of this study was to identify gene expression changes in NOA patients and to explore potential biomarkers and therapeutic targets.\nMETHODS: The gene expression profiles of GSE45885 and GSE145467 were collected from the Gene Expression Omnibus (GEO) database, and the differences between NOA and normal spermatogenesis were analyzed. Enrichment analysis was performed to explore biological functions for common differentially expressed genes (DEGs) in GSE45885 and GSE145467. Coexpression analysis of DEGs in GSE45885 was performed, and two modules with the highest correlation with NOA were screened. Key genes were then screened from the intersection genes of the two modules and common DEGs and PPI network. The expression of key genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. 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