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pmid:30544396

An in silico analysis of human sperm genes associated with asthenozoospermia and its implication in male infertility.

Xue Xia Liu · Li Cai · Fu Jun Liu

Medicine · 2018 doi:10.1097/MD.0000000000013338

Paper

complete

Experiment

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Data

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Analysis

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pmid:30544396
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title
An in silico analysis of human sperm genes associated with asthenozoospermia and its implication in male infertility.
doi
10.1097/MD.0000000000013338
pmid
30544396
authors array · 3 items
[0]
Xue Xia Liu
[1]
Li Cai
[2]
Fu Jun Liu
journal
Medicine
year
2018
abstract
Asthenozoospermia is the most common clinical symptom of male infertility. Molecular markers associated with asthenozoospermia spermatozoa are scarcely identified. The objective of this study was to screen the differentially expressed genes (DEGs) in asthenozoospermia spermatozoa and assess the underlying bioinformatics roles in regulation of sperm quality.Based on gene expression omnibus (GEO) database, the GSE22331, GSE1133, and GSE4193 expression profile data were downloaded. The DEGs of asthenozoospermia spermatozoa were identified. Germ cell specific genes in DEGs were further screened. Then, gene ontology (GO) and over-representation analysis of DEGs were performed, followed by protein-protein interaction (PPI) network analysis. Expressions of selected genes of TEX11, ADAMTS5, ASRGL1, GMCL1, PGK2, KLHL10 in normozoospermia and asthenozoospermia spermatozoa were identified using real time Reverse Transcription-Polymerase Chain Reaction (RT-PCR).A total of 1323 DEGs were identified, including 1140 down-regulated genes. Twenty one and 96 down-regulated genes were especially expressed in spermatogonia and round spermatids, suggesting their testicular origins and influences on sperm quality. Bioinformatics analysis showed enriched functions of ubiquitin-like protein transferase or protein binding activities in down-regulated genes. Expressions of selected genes were validated by RT-PCR, which was consistent with bioinformatical results.The present study provided a novel insight into the understanding of sperm quality, and a potential method and dataset for the diagnosis and assessment of sperm quality in the event of male infertility.
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sections[9] "Statistical analysis" paragraph 2
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Means of 2 groups were analyzed using the Student t test.
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To analyze differential gene expressions between spermatozoa samples from normal and asthenozoospermia patients, data from GSE22331 were downloaded and re-analyzed.
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To analyze differential gene expressions between spermatozoa samples from normal and asthenozoospermia patients, data from GSE22331 were downloaded and re-analyzed.
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Overrepresentation enrichment analysis of differential expressed genes in asthenozoospermia spermatozoa.
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Identification of differentially expressed genes in asthenozoospermia spermatozoa
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Overrepresentation enrichment analysis of differential expressed genes in asthenozoospermia spermatozoa.
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The objective of this study was to screen the differentially expressed genes (DEGs) in asthenozoospermia spermatozoa and assess the underlying bioinformatics roles in regulation of sperm quality.Based on gene expression omnibus (GEO) database, the GSE22331, GSE1133, and GSE4193 expression profile data were downloaded. The DEGs of asthenozoospermia spermatozoa were identified. Germ cell specific genes in DEGs were further screened. Then, gene ontology (GO) and over-representation analysis of DEGs were performed, followed by protein-protein interaction (PPI) network analysis. Expressions of selected genes of TEX11, ADAMTS5, ASRGL1, GMCL1, PGK2, KLHL10 in normozoospermia and asthenozoospermia spermatozoa were identified using real time Reverse Transcription-Polymerase Chain Reaction (RT-PCR).A total of 1323 DEGs were identified, including 1140 down-regulated genes. 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