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Proteomic approaches for profiling negative fertility markers in inferior boar spermatozoa

The ability to predict male fertility is of paramount importance for animal breeding industries and for human reproduction. Conventional semen analysis generally provides information on the quantitative parameters of spermatozoa, but yields no information concerning its functional competence. Proteo...

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Detalles Bibliográficos
Autores principales: Kwon, Woo-Sung, Oh, Shin-Ae, Kim, Ye-Ji, Rahman, Md Saidur, Park, Yoo-Jin, Pang, Myung-Geol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562270/
https://www.ncbi.nlm.nih.gov/pubmed/26348888
http://dx.doi.org/10.1038/srep13821
Descripción
Sumario:The ability to predict male fertility is of paramount importance for animal breeding industries and for human reproduction. Conventional semen analysis generally provides information on the quantitative parameters of spermatozoa, but yields no information concerning its functional competence. Proteomics have identified candidates for male fertility biomarkers, but no studies have clearly identified the relationship between the proteome and sperm fertility. Therefore, we performed a proteomic analysis to investigate small and large litter size boar spermatozoa and identify proteins related to male fertility. In this study, 20 proteins showed differential expression levels in small and large litter size groups. Nineteen of these proteins exhibited decreased expression in large litter size samples and increased expression in the small litter group. Interestingly, only one protein was highly expressed in the large litter size spermatozoa. We then identified signaling pathways associated with the differentially expressed protein markers. Glutathione S-transferase Mu3 and glutathione peroxidase 4 were related to the glutathione metabolic pathway and arginine vasopressin receptor 2 was linked to vasopressin R2/STAT. In summary, this is the first study to consider negative fertility biomarkers, and the identified proteins could potentially be used as biomarkers for the detection of inferior male fertility.