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Prediction of Bull Fertility by Capacitation Status

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  • URLhttps://db.koreascholar.com/Article/Detail/191620
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발생공학 국제심포지엄 및 학술대회 (International Symposium on Developmental Biotechnology)
한국동물번식학회 (The Korean Society of Animal Reproduction)
초록

The prediction of male fertility is of paramount importance for breeding animal herds when artificial insemination is applied. While the male fertility assays provide valuable quantitative data, they yield limited information concerning the functional competence of the spermatozoa. The objective of this study was to standardize a method for predicting in vivo fertility in bulls using the capacitation status that was assessed by chlortetracycline (CTC) staining. To optimize the capacitation process, sperm were treated with various concentrations of heparin (0, 10, 20, 50, and 100 μg/mL) and incubated for 10, 20, and 30 min each at 39℃ in 5% CO2. We found that maximum capacitation condition obtained from 10 μg /mL heparin treated sperm cells for 20 min (p<0.05). Optimized methods were used to determine the fertility of 17 batches of frozen bull semen representing a wide range of field fertility levels as indicated by non-return rates (NRR) (35.29% 93.18%). There was no significant correlation between NRR and the percentage of capacitated spermatozoa (B type) and non-capacitated spermatozoa (F type). However, acrosome reacted spermatozoa (AR type) was significantly correlated with NRR (p<0.01). To determine the normal range for the AR type, lower limits of the AR (%) were established as 23% for low fertility (NRR < 75%) using receiver operating characteristic curve. The overall accuracy of the assay was 88.24% for low fertility, sensitivity and specificity were 81.82 and 100%, respectively. These results indicate that capacitation status as measure by CTC staining is a useful predictor of male fertility. Therefore, low and high fertility bulls can be identified primarily by the functional capacitation status.

저자
  • Yoo-Jin Park(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)
  • Woo-Sung Kwon(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)
  • Sung-Jae Yoon(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)
  • Kyu-Hyun Jeong(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)
  • Kamla Kant Shukla(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)
  • El-sayed A. Mohamed(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)
  • Myung-Geol Pang(Department of Animal Science & Technology, School of Bioresource & Bioscience, Chung-Ang University)