In Silico Analysis of Sperm From Ejaculates with Different Semen Characteristics

Male infertility is associated with altered characteristics of the sperm within the ejaculate. It is possible to find molecular explanations for the observed phenotypes and their consequences. This study aimed to analyze, using a specialized software, a gene set of transcriptomic data from different types of ejaculates.

Data from ejaculate samples categorized as normal, oligospermia, and teratozoospermia were obtained from Gene Expression Omnibus (GEO). After normalization, the data average for each sample category was calculated and analyzed independently using Ingenuity Pathway Analysis (IPA).

Five important canonical pathways are involved in normal and altered semen samples (Oligospermia and teratozoospermia) except sirtuin signaling and mitochondrial dysfunction pathways. The five most important biological processes are identified in all semen phenotypes, but the only difference is the genes connected with initiation of RNA transcription in oligospermic and asthenospermic samples.

Surprisingly, different types of ejaculates share many pathways and biological processes; sperm proteomics as a new global approach gives clues for the development of strategies to explain the reason for observed phenotypes of ejaculated spermatozoa, their possible effect on fertility, and for implementing research strategies in the context of infertility diagnosis and treatment.