The identification of stallions and or ejaculates that will provide commercially acceptable quality post-thaw before cryopreservation is of great interest, avoiding wasting time and resources freezing ejaculates that will not achieve sufficient quality to be marketed. Our hypothesis was that after bioinformatic analysis, the study of the stallion sperm proteome can provide discriminant variables able to predict the post-thaw quality of the ejaculate. At least three ejaculates from 10 different stallions were frozen following a split sample design. Half of the ejaculate was analyzed as a fresh aliquot and the other half was frozen and then analyzed as a frozen-thawed aliquot. Computer-assisted sperm analysis and flow cytometry were used to analyze sperm quality. Detailed proteomic analysis was performed on fresh and frozen and thawed aliquots, and bioinformatic analysis was used to identify discriminant variables in fresh samples able to predict the outcome of cryopreservation. Those with a fold change > 3, a P = 8.2e-04, and a q = 0.074 (equivalent to False discovery rate (FDR)) were selected, and the following proteins were identified in fresh samples as discriminant variables of good motility post-thaw: F6YTG8, K9K273, A0A3Q2I7V9, F7CE45, F6YU15, and F6SKR3. Other discriminant variables were also identified as predictors of good mitochondrial membrane potential and viability post-thaw. We concluded that proteomic approaches are a powerful tool to improve current sperm biotechnologies.

Differences in the proteome of stallion spermatozoa explain stallion-to-stallion variability in sperm quality post-thaw†

Ortiz-Rodriguez J. M.;Pena F. J.
2021

Abstract

The identification of stallions and or ejaculates that will provide commercially acceptable quality post-thaw before cryopreservation is of great interest, avoiding wasting time and resources freezing ejaculates that will not achieve sufficient quality to be marketed. Our hypothesis was that after bioinformatic analysis, the study of the stallion sperm proteome can provide discriminant variables able to predict the post-thaw quality of the ejaculate. At least three ejaculates from 10 different stallions were frozen following a split sample design. Half of the ejaculate was analyzed as a fresh aliquot and the other half was frozen and then analyzed as a frozen-thawed aliquot. Computer-assisted sperm analysis and flow cytometry were used to analyze sperm quality. Detailed proteomic analysis was performed on fresh and frozen and thawed aliquots, and bioinformatic analysis was used to identify discriminant variables in fresh samples able to predict the outcome of cryopreservation. Those with a fold change > 3, a P = 8.2e-04, and a q = 0.074 (equivalent to False discovery rate (FDR)) were selected, and the following proteins were identified in fresh samples as discriminant variables of good motility post-thaw: F6YTG8, K9K273, A0A3Q2I7V9, F7CE45, F6YU15, and F6SKR3. Other discriminant variables were also identified as predictors of good mitochondrial membrane potential and viability post-thaw. We concluded that proteomic approaches are a powerful tool to improve current sperm biotechnologies.
2021
Gaitskell-Phillips G.; Martin-Cano F.E.; Ortiz-Rodriguez J.M.; Silva-Rodriguez A.; Gil M.C.; Ortega-Ferrusola C.; Pena F.J.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/927367
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