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Theriogenology2016; 86(4); 1111-1131; doi: 10.1016/j.theriogenology.2016.04.001

Development of a new fertility prediction model for stallion semen, including flow cytometry.

Abstract: Several laboratories routinely use flow cytometry to evaluate stallion semen quality. However, objective and practical tools for the on-field interpretation of data concerning fertilizing potential are scarce. A panel of nine tests, evaluating a large number of compartments or functions of the spermatozoa: motility, morphology, viability, mitochondrial activity, oxidation level, acrosome integrity, DNA integrity, "organization" of the plasma membrane, and hypoosmotic resistance, was applied to a population of 43 stallions, 33 of which showing widely differing fertilities (19%-84% pregnancy rate per cycle [PRC]). Analyses were performed either within 2 hours after semen collection or after 24-hour storage at 4 °C in INRA96 extender, on three to six ejaculates for each stallion. The aim was to provide data on the distribution of values among said population, showing within-stallion and between-stallion variability, and to determine whether appropriate combinations of tests could evaluate the fertilizing potential of each stallion. Within-stallion repeatability, defined as intrastallion correlation (r = between-stallion variance/total variance) ranged between 0.29 and 0.84 for "conventional" variables (viability, morphology, and motility), and between 0.15 and 0.81 for "cytometric" variables. Those data suggested that analyzing six ejaculates would be adequate to characterize a stallion. For most variables, except those related to DNA integrity and some motility variables, results differed significantly between immediately performed analyses and analyses performed after 24 hours at 4 °C. Two "best-fit" combinations of variables were determined. Factorial discriminant analysis using a first combination of seven variables, including the polarization of mitochondria, acrosome integrity, DNA integrity, and hypoosmotic resistance, permitted exact determination of the fertility group for each stallion: fertile, that is, PRC higher than 55%; intermediate, that is, 45% < PRC less than 55%; or subfertile, that is, PRC less than 45%. Linear regression using another combination of 20 variables, including motility, viability, oxidation level, acrosome integrity, DNA integrity, and hypoosmotic resistance, accounted for 94.2% of the variability regarding fertility and was used to calculate a prediction of the PRC with a mean standard deviation of 3.1. The difference between the observed fertility and the calculated value ranged from -4.2 to 5.0. In conclusion, this study enabled to determine a new protocol for the evaluation of stallion semen, combining microscopical observation, computer-assisted motility analysis and flow cytometry, and providing a high level of fertility prediction.
Publication Date: 2016-04-11 PubMed ID: 27207472DOI: 10.1016/j.theriogenology.2016.04.001Google Scholar: Lookup
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  • Journal Article

Summary

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This research focused on developing a new predictive model for assessing the fertility of stallion semen. The model included evaluating spermatozoa compartments with nine tests and flow cytometry. The results showed this method provided a high level of fertility prediction.

Research Methodology

  • This study used a systematic approach to analyze the sperm quality of 43 stallions with varying fertility levels (19% – 84% pregnancy rate per cycle).
  • A panel of nine tests was utilized, focusing on several aspects of the spermatozoa including motility, morphology, viability, mitochondrial activity, oxidation level, acrosome integrity, DNA integrity, plasma membrane organization, and hypoosmotic resistance.
  • The semen samples were analyzed within 2 hours after collection and/or stored at 4°C for 24 hours in an INRA96 extender. Each stallion provided three to six ejaculates on different occasions.

Findings

  • The study found a range of variations in the spermatozoa markers between different stallions and even within the same stallion. This suggested that six ejaculates would be sufficient to establish a robust characterization of a stallion’s fertility.
  • The results from the tests performed immediately after semen collection were significantly different from those performed after 24 hours of storage, except for variables related to DNA integrity and some motility variables.
  • Two combinations of variables were identified as the best fit for predicting stallion fertility. The first combination included seven variables, while the other combination included 20 variables.
  • The first combination accurately determined the fertility group of every stallion. The second combination accounted for over 94% of the fertility variability and was used to calculate a prediction of the pregnancy rate per cycle, with a small standard deviation of 3.1.

Conclusion

  • The findings of this study present a new protocol for assessing stallion semen, offering a highly accurate prediction of fertility.
  • It combines microscopic observation, computer-assisted motility analysis, and flow cytometry to create a comprehensive fertility assessment model.
  • This approach can help in field interpretations of fertility potential in stallions and contribute to better breeding management and outcomes.

Cite This Article

APA
Barrier Battut I, Kempfer A, Becker J, Lebailly L, Camugli S, Chevrier L. (2016). Development of a new fertility prediction model for stallion semen, including flow cytometry. Theriogenology, 86(4), 1111-1131. https://doi.org/10.1016/j.theriogenology.2016.04.001

Publication

ISSN: 1879-3231
NlmUniqueID: 0421510
Country: United States
Language: English
Volume: 86
Issue: 4
Pages: 1111-1131

Researcher Affiliations

Barrier Battut, I
  • I.F.C.E, E.S.C.E., la Jumenterie du Pin, Exmes, France. Electronic address: isabelle.barrier@ifce.fr.
Kempfer, A
  • I.F.C.E, E.S.C.E., la Jumenterie du Pin, Exmes, France.
Becker, J
  • I.F.C.E, E.S.C.E., la Jumenterie du Pin, Exmes, France.
Lebailly, L
  • I.F.C.E, E.S.C.E., la Jumenterie du Pin, Exmes, France.
Camugli, S
  • R&D Department, IMV Technologies, Saint Ouen sur Iton, France.
Chevrier, L
  • R&D Department, IMV Technologies, Saint Ouen sur Iton, France.

MeSH Terms

  • Animals
  • Cell Membrane
  • Cell Survival
  • DNA Damage
  • Female
  • Fertility / physiology
  • Flow Cytometry / veterinary
  • Horses / physiology
  • Male
  • Pregnancy
  • Semen / cytology
  • Semen Analysis / veterinary
  • Sperm Motility / physiology
  • Spermatozoa / physiology