Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Abstract

Assessing dominance and additive effects of casein complex single-nucleotide polymorphisms (SNPs) (αS1, αS2, β, and κ casein), and their epistatic relationships may maximize our knowledge on the genetic regulation of profitable traits. Contextually, new genomic selection perspectives may translate this higher efficiency into higher accuracies for milk yield and components’ genetic parameters and breeding values. A total of 2594 lactation records were collected from 159 Murciano-Granadina goats (2005–2018), genotyped for 48 casein loci-located SNPs. Bonferroni-corrected nonparametric tests, categorical principal component analysis (CATPCA), and nonlinear canonical correlations were performed to quantify additive, dominance, and interSNP epistatic effects and evaluate the outcomes of their inclusion in quantitative and qualitative milk production traits’ genetic models (yield, protein, fat, solids, and lactose contents and somatic cells count). Milk yield, lactose, and somatic cell count heritabilities increased considerably when the model including genetic effects was considered (0.46, 0.30, 0.43, respectively). Components standard prediction errors decreased, and accuracies and reliabilities increased when genetic effects were considered. Conclusively, including genetic effects and relationships among these heritable biomarkers may improve model efficiency, genetic parameters, and breeding values for milk yield and composition, optimizing selection practices profitability for components whose technological application may be especially relevant for the cheese-making dairy sector.

Bayesian Analysis of the Association between Casein Complex Haplotype Variants and Milk Yield, Composition, and Curve Shape Parameters in Murciano-Granadina Goats

“…In line with the aforementioned results, Pizarro Inostroza et al [ 86 ] reported the lack of significant differences in the ability to predict breeding values depending on whether genetic effects derived from the study of SNP effects (either additive, dominant, or epistatic effects) were included or not. However, despite being significant, the drastic reduction in the values of reliability and accuracy of predicted breeding values when genetic factors were included suggested the fact that the inclusion of genetic effects as fixed effects may increase the estimative power and accuracy of the model used to perform genetic evaluations for economically important traits linked to milk yield and its components.…”

Nonparametric analysis of casein complex genes' epistasis and their effects on phenotypic expression of milk yield and composition in Murciano-Granadina goats

“…We conclude that milk performance and quality may depend not only on the specific casein gene background of individuals, nor on the relationships of additivity and dominance that may exist, but may also be strongly conditioned by the relationships established across and within the genes that regulate the expression of caseins. In this context, NLCCA may maximize the outcomes derived from the study of epistasis, which may play a pivotal part when our aim is to optimize selective practices for economically important dairy traits (Pizarro et al, 2020).…”

Exploring Breed-Specific Milk Coagulation in Spanish Dairy Sheep: A Canonical Correlation Approach

“…In recent years, canonical correlation analysis has been used in some studies involving dairy ruminants for the analysis of aspects such as milk immunoglobulin profiles, genomic characterisation, or the impact of housing on animal health [ 59 , 60 , 61 , 62 ]. Moreover, a recent study from our research group has used CCA to explore species-specific differences in milk processing [ 43 ].…”