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Seasonal Effect on Developmental Competence, Oxidative Status and Tubulin Assessment of Prepubertal Ovine Oocyte.

Elisa SerraSergio Domenico GadauGiovanni Giuseppe LeoniSalvatore NaitanaSara Succu
Published in: Animals : an open access journal from MDPI (2021)
The reproductive seasonality of domestic animals is often manipulated in order to have more reproductive periods for commercial purposes related to the production of milk and meat. It is scientifically proven that such an alteration of the reproductive activity in sheep entails a deterioration in oocyte quality, leading to an inability to generate embryos. Since oocytes obtained from prepubertal ewes can be incorporated into an in vitro embryo production system and considering that their quality is crucial to the success of in vitro procedures, the aim of this work was to investigate the effect of seasons on the quality of prepubertal ovine oocytes collected in autumn and spring. Ovaries were collected from a local slaughterhouse from 30-40-day-old suckling lambs during both seasons. Following 24 h of in vitro maturation, oocytes developmental competence, reactive oxygen species (ROS) intracellular levels, and mitochondrial activity were evaluated, and a tubulin assessment was performed. The results on embryo production, as a percentage of first divisions and number of blastocysts obtained, were significantly higher in oocytes collected in the spring. Mitochondrial activity in oocytes was higher, and ROS production significantly lower, in spring than in autumn. Tubulin PTMs (tyrosinated and acetylated α-tubulin) showed a higher immunoreactivity in oocytes collected in spring compared with autumn sampling. Our data showed that seasons may affect the developmental competence, energetic status, and tubulin assessment of oocytes recovered from prepubertal ewes. Therefore, special care should be taken when choosing the period of the year for prepuberal ovine oocytes collection aimed at in vitro embryo reproduction programs.
Keyphrases
  • reactive oxygen species
  • quality improvement
  • oxidative stress
  • cell death
  • healthcare
  • palliative care
  • dna damage
  • big data
  • artificial intelligence
  • data analysis