No abstract

Goat milk casein proteins (αS1, αS2, β and κ) are encoded by four loci (CSN1S1, CSN1S2, CSN2 and CSN3, respectively) clustered within 250 kb in chromosome 6. In this study, 159 Murciano‐Granadina goats were genotyped for 48 SNPs within the entire casein region. Phenotypes on milk yield and components were obtained from 2,594 dairy registries. Additive and dominance effects on milk composition and quality were studied using non‐parametric tests and principal component analysis to prevent SNPs multicollinearity. Two deletions in exon 4 (CSN1S1 and CSN3), one in exon 7 (CSN2) and one in exon 15 (CSN1S2) have been found at frequencies ranging from 0.12 to 0.50. Bonferroni‐corrected significant SNP additive and dominance effects were found for milk yield, fat, protein, dry matter and lactose, and somatic cells. Exons 15 and 7 were significantly associated with milk yield and components except for lactose and somatic cells, while exon 4 was significantly associated with milk yield and components except for protein and dry matter. SNPs' associations with somatic cells were less frequent and weaker than those with milk yield and components. As caseins increase, somatic cells decrease, reducing milk enzymatic activity and consumption suitability. Hence, including molecular information in breeding schemes may promote production efficiency, as selecting against undesirable alleles could prevent the compromises derived from their dominance effects.

Sex determination is key to designing endangered poultry population conservation and breeding programs when sex distribution departs from Hardy–Weinberg equilibrium. A total of 112 Utrerana chickens (28 per variety, partridge, black, white, and franciscan) were selected for hatching day sexing. Sex assignation was performed through 10 methods. Three sex assignment criteria comprised criteria found in literature, opposite criteria to that in the literature, and composite criteria combining methods reporting the highest predictive success from the previous ones. This study aims to determine which method combinations may more successfully determine sex across the four varieties of Utrerana endangered hen breed to tailor noninvasive early specific models to determine sex in local chicken populations. Although the explanatory power of the three assignation criteria is equal (75%), assignation criteria 2 resulted to be the most efficient as it correctly assigns males more frequently. Only methods 3 (English method), 5 (general down feathers coloration), 7 (wing fan), and 10 (behavior/coping styles) reported significant differences regardless of the variety, hence, are appropriate for early sexing. Sex confirmation was performed at 1.5 months old. Identifying sex proportions enhances genetic management tasks in endangered populations, complementing more standardized techniques, which may result inefficient given the implicit diversity found in local populations.

Considering casein haplotype variants rather than SNPs may maximize the understanding of heritable mechanisms and their implication on the expression of functional traits related to milk production. Effects of casein complex haplotypes on milk yield, milk composition, and curve shape parameters were used using a Bayesian inference for ANOVA. We identified 48 single nucleotide polymorphisms (SNPs) present in the casein complex of 159 unrelated individuals of diverse ancestry, which were organized into 86 haplotypes. The Ali and Schaeffer model was chosen as the best fitting model for milk yield (Kg), protein, fat, dry matter, and lactose (%), while parabolic yield-density was chosen as the best fitting model for somatic cells count (SCC × 103 sc/mL). Peak and persistence for all traits were computed respectively. Statistically significant differences (p < 0.05) were found for milk yield and components. However, no significant difference was found for any curve shape parameter except for protein percentage peak. Those haplotypes for which higher milk yields were reported were the ones that had higher percentages for protein, fat, dry matter, and lactose, while the opposite trend was described by somatic cells counts. Conclusively, casein complex haplotypes can be considered in selection strategies for economically important traits in dairy goats.

SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R2) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry.