Molecular Profiling of Spermatozoa Reveals Correlations between Morphology and Gene Expression: A Novel Biomarker Panel for Male Infertility.
Nino Guy CassutoDavid PiquemalFlorence BoitrelleLionel LarueNathalie LédéeGhada HatemLéa RuosoDominique BouretJean-Pierre SiffroiAlexandre RouenSaid AssouPublished in: BioMed research international (2021)
Choosing spermatozoa with an optimum fertilizing potential is one of the major challenges in assisted reproductive technologies (ART). This selection is mainly based on semen parameters, but the addition of molecular approaches could allow a more functional evaluation. To this aim, we used sixteen fresh sperm samples from patients undergoing ART for male infertility and classified them in the high- and poor-quality groups, on the basis of their morphology at high magnification. Then, using a DNA sequencing method, we analyzed the spermatozoa methylome to identify genes that were differentially methylated. By Gene Ontology and protein-protein interaction network analyses, we defined candidate genes mainly implicated in cell motility, calcium reabsorption, and signaling pathways as well as transmembrane transport. RT-qPCR of high- and poor-quality sperm samples allowed showing that the expression of some genes, such as AURKA, HDAC4, CFAP46, SPATA18, CACNA1C, CACNA1H, CARHSP1, CCDC60, DNAH2, and CDC88B, have different expression levels according to sperm morphology. In conclusion, the present study shows a strong correlation between morphology and gene expression in the spermatozoa and provides a biomarker panel for sperm analysis during ART and a new tool to explore male infertility.
Keyphrases
- gene expression
- genome wide
- protein protein
- single cell
- poor prognosis
- patients undergoing
- dna methylation
- hiv infected
- genome wide identification
- antiretroviral therapy
- small molecule
- signaling pathway
- polycystic ovary syndrome
- binding protein
- genome wide analysis
- transcription factor
- oxidative stress
- cell therapy
- type diabetes
- epithelial mesenchymal transition
- single molecule
- candida albicans
- cell proliferation
- network analysis