<p>This study examined associations between αS1- and κ-casein genotypes and baseline and dynamic regression components of semen quality in Murciano-Granadina bucks using cubic regression models applied to 6,868 ejaculates collected over 10 years, with age at sperm collection as the time axis. Regression decomposition into baseline (b<sub>0</sub>), linear (b<sub>1</sub>), curvature (b<sub>2</sub>), and cubic tren (b<sub>3</sub>) coefficients enabled quantification of static trait levels and age-dependent dynamics, revealing substantial coefficient variability. For αS1-casein, genotype was associated with baseline progressive motility and total added semen volume (<i>p</i> &lt; 0.05), with moderate to large discriminant effects for progressive motility (ηp<sup>2</sup> = 0.277, 95% CI 0.03–0.48) and curvature-related motility and Acrosome Integrity/Intact acrosomes components (ηp<sup>2</sup> = 0.212–0.245), indicating genotype-related differences in modeled semen quality rather than direct fertility effects. In contrast, κ-casein genotypes showed predominantly small to moderate effects, mainly related to ejaculate volume dynamics and baseline sperm concentration (ηp<sup>2</sup> = 0.131–0.138), while most other components were negligible. Cubic terms captured subtle non-linear trajectories, particularly for sperm concentration and endosmosis, highlighting their relevance for long-term trait stability. Discriminant analyses indicated model-based separation of αS1–κ genotype combinations, with EE–AA (<i>n</i> = 1) and BE–AA (<i>n</i> = 3) aligning with higher sperm motility, concentration, and favorable membrane-integrity responses, whereas BB–BB (<i>n</i> = 3) aligned with higher semen volume and lower quality traits. Validation procedures were method-specific. CDA using leave-one-out cross-validation showed stronger discrimination for αS1-casein (74.03%) than κ-casein (64.94%), driven by perfect classification of the dominant BE genotype and substantial misclassification of rarer genotypes, whereas CHAID using 10-fold cross-validation showed moderate predictive performance with lower risk for αS1-casein (0.325, SE = 0.074; accuracy = 67.53%) than κ-casein (0.429, SE = 0.079; accuracy = 57.14%). Press’ Q statistics confirmed that classification accuracy for both genotypes exceeded chance expectation across methods (CDA: αS1-casein Q = 182.40, κ-casein Q = 34.60; CHAID: αS1-casein Q = 143.44, κ-casein Q = 19.64; <i>p</i> &lt; 0.05), with consistently stronger discrimination for αS1-casein genotypes. Overall, baseline and dynamic regression components capture biologically relevant, exploratory associations between casein polymorphisms and semen quality dynamics, supporting their integration into genomics-informed reproductive management strategies.</p>

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Casein genotypes associate with baseline and dynamic regression components of seminal quality in Murciano-Granadina bucks

  • María Peláez Caro,
  • Ander Arando Arbulu,
  • José Manuel León Jurado,
  • Juan Vicente Delgado Bermejo,
  • Javier Fernández Álvarez,
  • Francisco Javier Navas González

摘要

This study examined associations between αS1- and κ-casein genotypes and baseline and dynamic regression components of semen quality in Murciano-Granadina bucks using cubic regression models applied to 6,868 ejaculates collected over 10 years, with age at sperm collection as the time axis. Regression decomposition into baseline (b0), linear (b1), curvature (b2), and cubic tren (b3) coefficients enabled quantification of static trait levels and age-dependent dynamics, revealing substantial coefficient variability. For αS1-casein, genotype was associated with baseline progressive motility and total added semen volume (p < 0.05), with moderate to large discriminant effects for progressive motility (ηp2 = 0.277, 95% CI 0.03–0.48) and curvature-related motility and Acrosome Integrity/Intact acrosomes components (ηp2 = 0.212–0.245), indicating genotype-related differences in modeled semen quality rather than direct fertility effects. In contrast, κ-casein genotypes showed predominantly small to moderate effects, mainly related to ejaculate volume dynamics and baseline sperm concentration (ηp2 = 0.131–0.138), while most other components were negligible. Cubic terms captured subtle non-linear trajectories, particularly for sperm concentration and endosmosis, highlighting their relevance for long-term trait stability. Discriminant analyses indicated model-based separation of αS1–κ genotype combinations, with EE–AA (n = 1) and BE–AA (n = 3) aligning with higher sperm motility, concentration, and favorable membrane-integrity responses, whereas BB–BB (n = 3) aligned with higher semen volume and lower quality traits. Validation procedures were method-specific. CDA using leave-one-out cross-validation showed stronger discrimination for αS1-casein (74.03%) than κ-casein (64.94%), driven by perfect classification of the dominant BE genotype and substantial misclassification of rarer genotypes, whereas CHAID using 10-fold cross-validation showed moderate predictive performance with lower risk for αS1-casein (0.325, SE = 0.074; accuracy = 67.53%) than κ-casein (0.429, SE = 0.079; accuracy = 57.14%). Press’ Q statistics confirmed that classification accuracy for both genotypes exceeded chance expectation across methods (CDA: αS1-casein Q = 182.40, κ-casein Q = 34.60; CHAID: αS1-casein Q = 143.44, κ-casein Q = 19.64; p < 0.05), with consistently stronger discrimination for αS1-casein genotypes. Overall, baseline and dynamic regression components capture biologically relevant, exploratory associations between casein polymorphisms and semen quality dynamics, supporting their integration into genomics-informed reproductive management strategies.