Spermiogram, Kinetics, Flow Cytometric Characteristics and DNA Damage Degree in Boar Ejaculates: Summarization and Clustering

• Published in: Veterinary sciences Vol. 11; no. 9; p. 420
• Main Authors: Ausejo-Marcos, Raquel, Tejedor, María Teresa, Miguel-Jiménez, Sara, Gómez-Giménez, Belén, Soriano-Úbeda, Cristina, Mendoza, Noelia, Vicente-Carrillo, Alejandro, Hurtado, William Fernando, Ávila Holguín, Celia, Moreno, Bernardino, Falceto, María Victoria
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 09-09-2024; MDPI
• Subjects: Acrosome reaction; Animal reproduction; Apoptosis; Artificial insemination; boar ejaculate; Cathepsin B; DNA damage; Enzymes; Fertility; Flow cytometry; Hogs; Humidity; Laboratories; Mitochondrial DNA; Morphology; Motility; Phosphatase; Plasma; Principal components analysis; Quality control; Semen; semen analysis; semen classification; Sperm; Statistical analysis; United Kingdom > UK; United States > US; Spain; semen classification; boar ejaculate; semen analysis; DNA damage
• ISSN: 2306-7381; 2306-7381
• DOI: 10.3390/vetsci11090420

Boar semen analysis includes sperm motility, concentration, morphology and other more complex analyses such as membrane integrity, DNA damage and seminal plasma components. This study aims to summarize these numerous data by linear combinations of them, to classify ejaculates in several categories (clusters) and to investigate the potential differences among clusters on fertility and prolificacy. Young Pietrain boars (23 ± 3.6 months) were investigated: ten boars from the Nucléus genetic line (group 1: 90 ejaculates weekly) and five boars from the Batallé genetic line (group 2: 30 ejaculates weekly). Computer-assisted semen analysis (CASA) examined motility. Sperm viability, acrosome reaction, early apoptosis, mitochondrial activity and DNA damage were studied by flow cytometry analysis. SPSS v.26 software was used to perform principal component analysis (PCA) and clustering. Three principal components (PC1: speed; PC2: linear path; PC3: DNA damage) were detected and four clusters identified in both groups. Clusters also differed significantly in several variables not included in these PCs (group 1: beat cross frequency and poly (ADP-ribose) polymerase; group 2: cathepsin B, abnormal forms, mitochondrial activity and high DNA stainability). PCA and clustering achieved adequate description of these ejaculates, but no differences among clusters were found for fertility or prolificacy, probably because the minimum sperm requirements had been met.