Quantification of bull sperm characteristics by computer-assisted sperm analysis (CASA) and the relationship to fertility
Department of Animal Science, Cornell University, Ithaca, NY, USA.Theriogenology (Impact Factor: 1.8). 04/1998; 49(4):871-9. DOI: 10.1016/S0093-691X(98)00036-3
Two experiments were conducted to evaluate semen quality of bulls housed under controlled conditions at a large AI facility and relate results to fertility. In Experiment 1 semen was collected from six 6-yr-old bulls twice daily at 3- to 4-d intervals for 3 d. In Experiment 2 eleven 6- to 11-yr-old bulls were used. Extensive breeding information was available and semen was collected as in Experiment 1 but replicated 4 times. Standard semen analysis and computer-assisted sperm analysis (CASA) with the Hamilton Thorne IVOS, model 10 unit, were performed on 36 first and second ejaculates in Experiment 1 and on 44 first ejaculates in Experiment 2. Sixteen fields (2 chambers with 8 fields per chamber) were examined per sample. In Experiment 1 the correlation between estimated sperm concentration by spectrophotometry and CASA was 0.91 (P < 0.01). Among bulls the range in the percentage of motile spermatozoa was 52 to 82 for CASA versus 62 to 69 for subjective measurements made by highly experienced technicians. Thus, CASA, with high repeatability, provided a more discriminating estimate of the percentage of motile sperm cells than did the subjective procedure. Bull effect was much greater than any other variable in the experiments. Chamber differences were small and so the results for the 2 chambers with 8 fields each were combined. One to five CASA values were correlated with bull fertility, defined as 59-day nonreturn rates corrected for cow and herd effects. The percentage of motile spermatozoa accounted for a small fraction of the total variation in fertility (r2 = 0.34). However higher r2 values (0.68 to 0.98) were obtained for 2 to 5 variables used in the multiple regression equations. The results are promising, and further testing will determine more precisely which of these CASA variables are most useful in estimating bull fertility potential.
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- "Sperm motility was also considered as a crucial parameter, but only a few studies have investigated its predictive value. Low but significant relations between motility and fertility have been described   . While manual analysis is markedly slow and prone to within and between technician errors due to subjectivity, computer-assisted semen analysis (CASA) is currently becoming the most popular method to evaluate sperm motility   . "
ABSTRACT: Predicting in vivo fertility of bull ejaculates using in vitro-assessed semen quality criteria remains challenging for the breeding industry. New technologies such as computer-assisted semen analysis (CASA) and flow cytometry may provide accurate and objective methods to improve semen quality control. The aim of this study was to evaluate the relationship between semen quality parameters and field fertility of bull ejaculates. A total of 153 ejaculates from 19 Holstein bulls have been analyzed using CASA (postthawing semen motility and morphology) and several flow cytometric tests, including sperm DNA integrity, viability (estimated by membrane integrity), acrosomal integrity, mitochondria aerobic functionality and oxidation. Samples were analyzed both immediately after thawing and after 4 hours at 37 °C. A fertility value (FV), based on nonreturn rate at 56 days after insemination and adjusted for environment factors, was calculated for each ejaculate. Simple and multiple regressions have been used to correlate FV with CASA and flow cytometric parameters. Significant simple correlations have been observed between some parameters and FV (e.g., straight line velocity [μm/s], r(2) = -0.12; polarized mitochondria sperm (%), r(2) = 0.07), but the relation between simple parameter and FV was too week to predict the fertility. Partial least square procedure identified several mathematical models combining flow cytometer and CASA variables and had better correlations with FV (adjusted r(2) ranging between 0.24 and 0.40 [P < 0.0001], depending on the number of included variables). In conclusion, this study suggests that quality assessment of thawed bull sperm using CASA and flow cytometry may provide a reasonable prediction of bovine semen fertility. Additional work will be required to increase the prediction reliability and promote this technology in routine artificial insemination laboratory practice. Copyright © 2015 Elsevier Inc. All rights reserved.
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- "Yet these semen parameters have limited value for predicting a bull's fertility (Rodriguez-Martinez , 2006; Gillan et al., 2008; Dogan et al., 2013). The advent of sophisticated equipment, powerful computers and software, and fluorescent stains have established semen assays whose metrics show a positive relationship with bull fertility, including computer-assisted sperm motility parameters (Farrell et al., 1998); sperm membrane integrity (Januskauskas et al., 2003); normal acrosome; mitochondrial function and DNA damage (Waterhouse et al., 2006); fertility-associated proteins (Bellin et al., 1998; Klinefelter 2008; Byrne et al., 2012; Park et al., 2012a); specific microRNAs (Govindaraju et al., 2012); apoptotic changes (Anzar et al., 2002); penetration through artificial mucus (Al Naib et al., 2011); ability to undergo an acrosome reaction (Januskauskas et al., 2000); binding with oviductal epithelium (Lefebvre and Suarez, 1996) and zona pellucida (Zhang et al., 1998; Saacke et al., 2000); and in vitro fertilization using bovine (Marquant-Le Guienne et al., 1990; Zhang et al., 1997) and zona-free hamster (Park et al., 2012b) oocytes. However, these assays remain controversial in regards to their reliability and accuracy in predicting a bull's fertility. "
ABSTRACT: Early estimation of bull fertility is highly desirable for the conservation of male genetics of endangered species and for the exploitation of genetically superior sires in artificial insemination programs. The present work was conducted as a proof-of-principle study to identify fertility-associated metabolites in dairy bull seminal plasma and blood serum using proton nuclear magnetic resonance (1H NMR). Semen and blood samples were collected from high- and low-fertility breeding bulls (n = 5 each), stationed at Semex, Guelph, Canada. NMR spectra of serum and seminal plasma were recorded at a resonance frequency of 500.13 MHz on a Bruker Avance-500 spectrometer equipped with an inverse triple resonance probe (TXI, 5 mm). Spectra were phased manually, baseline corrected, and calibrated against 3-(trimethylsilyl) propionic-2,2,3,3-d4 acid at 0.0 parts per million (ppm). Spectra were converted to an appropriate format for analysis using Prometab software running within MATLAB. Principal component analysis was used to examine intrinsic variation in the NMR data set, and to identify trends and to exclude outliers. Partial least square-discriminant analysis was performed to identify the significant features between fertility groups. The fertility-associated metabolites with variable importance in projections (VIP) scores >2 were citrate (2.50 ppm), tryptamine/taurine (3.34–3.38 ppm), isoleucine (0.74 ppm), and leucine (0.78 ppm) in the seminal plasma; and isoleucine (1.14 ppm), asparagine (2.90–2.94 ppm), glycogen (3.98 ppm), and citrulline (1.54 ppm) in the serum. These metabolites showed identifiable peaks, and thus can be used as biomarkers of fertility in breeding bulls. Mol. Reprod. Dev. 2015. © 2015 Wiley Periodicals, Inc.
- "Computer-assisted semen analysis provides objective and reproducible data on a number of sperm motion parameters and it should enhance the value of motility assessment to fertility prognosis. In recent years, there has been an increase in the use of these systems to evaluate semen quality  , resulting in high correlations among several CASA motility parameters and the in vivo fertility of sperm from different species in horses , in boar , and in bulls . Marco-Jimenez et al.  documented that different physiological responses for attempted recovery were observed only when EE was used (80% efficiency versus 100% for AV). "
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