Abstract
The ejaculate is heterogenous and sperm sub-populations with different kinematic patterns can be identified in various species. Nevertheless, although these sub-populations are statistically well defined, the statistical differences are not always relevant. The aim of the present study was to characterize kinematic sub-populations in sperm from two bovine species, and diluted with different commercial extenders, and to determine the statistical relevance of sub-populations through Bayesian analysis. Semen from 10 bulls was evaluated after thawing. An ISAS®v1 computer-assisted sperm analysis (CASA)-Mot system was employed with an image acquisition rate of 50 Hz and ISAS®D4C20 counting chambers. Sub-populations of motile spermatozoa were characterized using multivariate procedures such as principal components (PCs) analysis and clustering methods (k-means model). Four different sperm sub-populations were identified from three PCs that involved progressiveness, velocity, and cell undulatory movement. The proportions of the different sperm sub-populations varied with the extender used and in the two species. Despite a statistical difference (p < 0.05) between extenders, the Bayesian analysis confirmed that only one of them (Triladyl®) presented relevant differences in kinematic patterns when compared with Tris-EY and OptiXcell®. Extenders differed in the proportion of sperm cells in each of the kinematic sub-populations. Similar patterns were identified in Bos taurus and Bos indicus. Bayesian results indicate that sub-populations SP1, SP2, and SP3 were different for PC criteria and these differences were relevant. For velocity, linearity, and progressiveness, the SP4 did not show a relevant difference regarding the other sperm sub-populations. The classical approach of clustering or sperm subpopulation thus may not have a direct biological meaning. Therefore, the biological relevance of sperm sub-populations needs to be reevaluated.
Highlights
Fertility in cattle, as in other species, is a key determinant of productivity and, understanding factors that affect fertility in beef and dairy herds is of utmost importance [1]
The intrinsic variability of semen samples, as well as individual variation or differences arising as a result of treatments, can be studied by using computer-assisted sperm analysis (CASA)-Mot systems that allow for the generation of huge datasets consisting of kinematics trajectories from thousands of spermatozoa [8]
Current CASA-Mot systems can be used to analyze individual sperm kinematics more accurately and this information can be submitted to a multivariate procedure, such as cluster analysis, for an overview of distinct sperm patterns grouped into SPs or clusters [20]
Summary
As in other species, is a key determinant of productivity and, understanding factors that affect fertility in beef and dairy herds is of utmost importance [1]. It is well known that sire fertility is related to sperm motility and kinematic patterns [2] the effects of semen quality on reproductive efficiency in cattle are not yet fully understood [3]. The intrinsic variability of semen samples, as well as individual variation or differences arising as a result of treatments, can be studied by using computer-assisted sperm analysis (CASA)-Mot systems that allow for the generation of huge datasets consisting of kinematics trajectories from thousands of spermatozoa [8]. Current CASA-Mot systems can be used to analyze individual sperm kinematics more accurately and this information can be submitted to a multivariate procedure, such as cluster analysis, for an overview of distinct sperm patterns grouped into SPs or clusters [20]
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