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.

The aim of the study was to compare the morphometric features of sperm head size and shape from the Pietrain line and the Duroc × Pietrain boar crossbred terminal lines, and to evaluate their relationship with reproductive success after artificial insemination of sows produced from crossbreeding the York, Landrace and Pietrain breeds. Semen samples were collected from 11 sexually mature boars. Only ejaculates with greater than 70% motility rate and <15% of abnormal sperm were used for artificial inseminations (AI) and included in the study. Samples were analyzed using an ISAS®v1 computer-assisted sperm analysis system for eight morphometric parameters of head shape and size (CASA-Morph). Sub-populations of morphometric ejaculates were characterized using multivariate procedures, such as principal component (PC) analysis and clustering methods (k-means model). Four different ejaculate sub-populations were identified from two PCs that involved the head shape and size of the spermatozoa. The discriminant ability of the different morphometric sperm variables to predict sow litter size was analyzed using a receiver operating characteristics (ROC) curve analysis. Sperm head length, ellipticity, elongation, and regularity showed significant predictive capacity on litter size (0.59, 0.59, 0.60, and 0.56 area under curve (AUC), respectively). The morphometric sperm sub-populations were not related to sow litter size.

The aim was to determine the relationship between kinematic parameters of boar spermatozoa and fertility rates of sow, as well as to assess the effect of sperm clusters on the fertility capacity of the ejaculate. Semen samples were collected from 11 sexually mature boars. Samples were analyzed by an ISAS®v1 CASA-Mot system for eight kinematic parameters. Ejaculate clusters were characterized using multivariate procedures, such as principal factors (PFs) analysis and clustering methods (the k-means model). Four different ejaculate clusters were identified from two kinematic PFs which involved linear trajectory and velocity. There were differences (p < 0.05) between the sperm kinematic variables by sire line. There was no statistical difference (p > 0.05) between dam lines and ejaculate clusters in fertility variables. The discriminant ability of the different kinematics of sperm variables to predict litter size fertility was analyzed using receiver operating characteristics (ROC) curve analysis. Curvilinear velocity (VCL), average path velocity (VAP), amplitude of lateral head displacement (ALH), and beat-cross frequency (BCF) showed significant, albeit limited, predictive capacity for litter size fertility variables (range: 0.55–0.58 area under curve, AUC). The kinematic analysis of the ejaculates in clusters did not have a predictive capacity for litter size variables.

No abstract

Introducción. Las condiciones óptimas de análisis seminal permiten estandarizar los protocolos de evaluación. Objetivo. Evaluar el efecto de factores externos relacionados con el seminograma sobre las subpoblaciones espermáticas de bovinos de la raza Brahman. Materiales y métodos. El estudio se realizó con animales de dos fincas ganaderas de Alajuela, Costa Rica, de septiembre a diciembre de 2019. Se utilizaron diez toros Brahman que fueron electroeyaculados y el semen se diluyó con tres diluyentes comerciales: Andromed®, Androstar® y BTS, a dos temperaturas (37 y 29 °C). Las muestras se analizaron mediante un sistema CASA-Mot ISAS®v1 y se utilizaron cámaras de recuento ISAS®D4C (10, 16 y 20 μm) y Spermtrack® en diferentes tiempos de análisis (0, 3, 6 y 12 h). Resultados. La Spermtrack® presentó mayor velocidad curvilínea pero menor linealidad respecto de las otras cámaras de recuento (p<0,05). La durabilidad de las muestras fue menor para todas las variables de cinética espermática (p<0,05), excepto para el índice de rectitud (STR). La velocidad curvilínea fue mayor cuando se utilizó Andromed®, pero hubo mayor progresividad con Androstar® (p<0,05). Se identificaron cinco subpoblaciones espermáticas a partir de tres componentes principales: velocidad, progresividad y ondulación. La distribución de espermatozoides en las subpoblaciones varió (p<0,05) según la durabilidad de la muestra y la cámara de recuento. Conclusiones. El tipo de diluyente, la temperatura de dilución, la cámara de recuento y el tiempo transcurrido tras la carga inicial del semen condicionaron las variables cinéticas del eyaculado. La movilidad y cinética del semen mejoró cuando se utilizaron alturas de cámara de 20 µm y diluyente Androstar®. La existencia de subpoblaciones espermáticas en el eyaculado se vio afectada por el tipo de diluyente utilizado, el cual condicionó la presencia de diferentes patrones de movilidad, progresividad y ondulación de las células en las diferentes subpoblaciones dentro del eyaculado.