Abstract
Teratozoospermia is a common category of male infertility and with the increase in clinical patients and the increasing sophistication of assisted reproductive technology, there is an urgent need for an accurate semen diagnostic biomarker to accomplish rapid diagnosis of patients with teratozoospermia and accurately assess the success rate of assisted reproductive technologies. In this study, we performed gene differential expression analysis on two publicly available DNA microarray datasets (GSE6872 and GSE6967), followed by GSEA analysis to parse their enriched KEGG pathways, and WGCNA analysis to obtain the most highly correlated modules. Subsequent in-depth comparative analysis of the modules screened into the two datasets resulted in a gene set containing the identical expression trend, and then the differentially expressed genes in the set were screened using the corresponding criteria. Finally, three differentially expressed genes common to both datasets were selected. In addition, we validated the expression changes of this gene using another dataset (GSE6968) and in vitro experiments, and only screened one potential semen biomarker gene whose expression trend was identical to those in other datasets, which will also provide an important theoretical basis for the diagnosis and treatment of teratozoospermia.