The combination of kinetic and flow cytometric semen parameters as a tool to predict fertility in cryopreserved bull semen
The combination of kinetic and flow cytometric semen parameters as a tool to predict fertility in cryopreserved bull semen
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DOI：
10.1017/s1751731117000684
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发表时间：
2017-11-01
期刊：
影响因子：
3.6
通讯作者：
Pizzi, F.
中科院分区：
文献类型：
--
作者：
Gliozzi, T. M.;Turri, F.;Pizzi, F.
近年来，人们越来越关注通过体外精液质量评估来预测公牛的生育力。因此，基于精液质量参数的早期评估的育性预测模型，将具有潜在低育性的公畜从育种计划中排除，将是有用的。本研究的目的是确定最合适的参数，将提供可靠的生育预测。采用计算机辅助精液分析（CASA）（活力和动力学参数）和流式细胞术（FCM）（活力，顶体完整性，线粒体功能，脂质过氧化，质膜稳定性和DNA完整性）分析了18头意大利荷斯坦-弗里斯兰公牛的冷冻精液。根据估计的相对受胎率（ERCR）将公牛分为两组（低生育力和高生育力）。生育力组之间的总活力，活性细胞，直线度，线性，活力和DNA片段精子的百分比存在显着差异。ERCR和一些动力学参数，膜不稳定性和一些DNA完整性指标之间的相关性进行了观察。为了建立精液质量参数与ERCR高度相关的模型，应用了反向逐步多元回归分析。因此，我们得到了一个预测模型，解释了几乎一半的（R-2 = 0.47，P < 0.05），包括9个变量：CASA测定的5个动力学参数（总运动性、活跃细胞、搏动交叉频率，曲线速度和横向头部位移幅度）和与DNA完整性相关的四个参数（染色质结构异常程度α-T、染色质结构异常程度（α-T标准差）、DNA片段化精子的百分比和具有代表未成熟细胞的高绿色荧光的精子的百分比）。真实的生育力与预测生育力之间存在显著相关性（R-2 = 0.84，P < 0.05）。一旦生育力预测的准确性得到证实，在本研究中开发的模型可用于人工授精中心的公牛选择或消除生育力差的射精。
Within recent years, there has been growing interest in the prediction of bull fertility through in vitro assessment of semen quality. A model for fertility prediction based on early evaluation of semen quality parameters, to exclude sires with potentially low fertility from breeding programs, would therefore be useful. The aim of the present study was to identify the most suitable parameters that would provide reliable prediction of fertility. Frozen semen from 18 Italian Holstein-Friesian proven bulls was analyzed using computer-assisted semen analysis (CASA) (motility and kinetic parameters) and flow cytometry (FCM) (viability, acrosomal integrity, mitochondrial function, lipid peroxidation, plasma membrane stability and DNA integrity). Bulls were divided into two groups (low and high fertility) based on the estimated relative conception rate (ERCR). Significant differences were found between fertility groups for total motility, active cells, straightness, linearity, viability and percentage of DNA fragmented sperm. Correlations were observed between ERCR and some kinetic parameters, and membrane instability and some DNA integrity indicators. In order to define a model with high relation between semen quality parameters and ERCR, backward stepwise multiple regression analysis was applied. Thus, we obtained a prediction model that explained almost half (R-2 = 0.47, P < 0.05) of the variation in the conception rate and included nine variables: five kinetic parameters measured by CASA (total motility, active cells, beat cross frequency, curvilinear velocity and amplitude of lateral head displacement) and four parameters related to DNA integrity evaluated by FCM (degree of chromatin structure abnormality Alpha-T, extent of chromatin structure abnormality (Alpha-T standard deviation), percentage of DNA fragmented sperm and percentage of sperm with high green fluorescence representative of immature cells). A significant relationship (R-2 = 0.84, P < 0.05) was observed between real and predicted fertility. Once the accuracy of fertility prediction has been confirmed, the model developed in the present study could be used by artificial insemination centers for bull selection or for elimination of poor fertility ejaculates.