Identification of Key Genes and Construction of Po-tential miRNA–mRNA Regulatory Network in Teratozoo-spermia

Background: Teratozoospermia is characterized by the pres-ence of spermatozoa with abnormal morphology over 85 % in sperm. mRNAs that aid in the detection of sperm abnormalities are potential biomarkers to evaluate the quality of sperm in the of male infertility. The current study was aimed at identifying key genes and molecular mechanism in teratozoospermia.Materials and Methods: We downloaded two gene expression profiles (GSE6872 and GSE6967) from the Gene Expression Omnibus (GEO). We conducted differential screens of the ex-pression of genes (DEGs) between two groups using the online tool GEO2R based on the R software limma package. Target miRNAs of DEGs were predicted using miRNet. Gene Ontol-ogy (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed for the DEGs to investigate the biological processes involved in the development of teratozoospermia, subsequently, pathways in-terrelation analysis of hub genes was carried out using plug-in ClueGO v2.3.3. Finally, miRNA–mRNA regulatory networks were visualized using Cytoscape.Results: With the criteria of adjusted P value (adj.p) <0.01 and absolute log value of fold-change (log|FC|) > 2, 970 and 4799 DEGs from GSE6872 and GSE6967 were obtained re-spectively. A total of 509 intersection DEGs were shared by two datasets. 2256 target miRNAs were predicted for DEGs. The mRNA-miRNA networks were composed of 2256 miRNA nodes and 454 mRNA nodes. The DEGs were mainly enriched in the cytosol and cytoplasm and were involved in the regula-tion of translational initiation, related to protein binding, and participated in the regulation of the Ribosome pathway.Conclusion: The current study revealed the potential key genes, pathways, and miRNA–mRNA regulatory networks in teratozoospermia, which may contribute to a more comprehen-sive understanding and treatment of male infertility

Keywords:

Teratozoospermia , Bioinformatics Analysis , Disease Makers , miRNA-mRNA pairs , Functional Enrichment Analysis