Casein SNP in Norwegian goats: additive and dominance effects on milk composition and quality

Polymorphisms of ITGA9 Gene and Their Correlation with Milk Quality Traits in Yak (Bos grunniens)

A single-nucleotide polymorphism (SNP) is a genome-level trait that arises from a variation in a single nucleotide, leading to diversity in DNA sequences. SNP screening is commonly used to provide candidate genes for yak breeding efforts. Integrin Subunit Alpha 9 (ITGA9) is an integrin protein. It plays an important role in cell adhesion, signalling, and other processes. The aim of this study was to discuss the association between genetic polymorphisms in the ITGA9 gene and milk quality traits and to identify potential molecular marker loci for yak breeding quality. We genotyped 162 yaks using an Illumina Yak cGPS 7K liquid chip and identified the presence of polymorphisms at nine SNP loci in the ITGA9 gene of yaks. The results showed that the mutant genotypes in the loci g.285,808T>A, g.306,600T>C, and g.315,413C>T were positively correlated with the contents of casein, protein, total solids (TS), and solid nonfat (SNF) in yak milk. In other loci, heterozygous genotypes had a positive correlation with nutrient content in yak milk. Then, two ITGA9 haplotype blocks were constructed based on linkage disequilibrium, which facilitated a more accurate screening of ITGA9 as a candidate gene for yak milk quality improvement. In conclusion, we identified SNPs and haplotype blocks related to yak milk quality traits and provided genetic resources for marker-assisted selection in yak breeding.

Discriminant canonical tool for inferring the effect of αS1, αS2, β, and κ casein haplotypes and haplogroups on zoometric/linear appraisal breeding values in Murciano-Granadina goats

Genomic tools have shown promising results in maximizing breeding outcomes, but their impact has not yet been explored. This study aimed to outline the effect of the individual haplotypes of each component of the casein complex (αS1, β, αS2, and κ-casein) on zoometric/linear appraisal breeding values. A discriminant canonical analysis was performed to study the relationship between the predicted breeding value for 17 zoometric/linear appraisal traits and the aforementioned casein gene haplotypic sequences. The analysis considered a total of 41,323 zoometric/linear appraisal records from 22,727 primiparous does, 17,111 multiparous does, and 1,485 bucks registered in the Murciano-Grandina goat breed herdbook. Results suggest that, although a lack of significant differences (p > 0.05) was reported across the predictive breeding values of zoometric/linear appraisal traits for αS1, αS2, and κ casein, significant differences were found for β casein (p < 0.05). The presence of β casein haplotypic sequences GAGACCCC, GGAACCCC, GGAACCTC, GGAATCTC, GGGACCCC, GGGATCTC, and GGGGCCCC, linked to differential combinations of increased quantities of higher quality milk in terms of its composition, may also be connected to increased zoometric/linear appraisal predicted breeding values. Selection must be performed carefully, given the fact that the consideration of apparently desirable animals that present the haplotypic sequence GGGATCCC in the β casein gene, due to their positive predicted breeding values for certain zoometric/linear appraisal traits such as rear insertion height, bone quality, anterior insertion, udder depth, rear legs side view, and rear legs rear view, may lead to an indirect selection against the other zoometric/linear appraisal traits and in turn lead to an inefficient selection toward an optimal dairy morphological type in Murciano-Granadina goats. Contrastingly, the consideration of animals presenting the GGAACCCC haplotypic sequence involves also considering animals that increase the genetic potential for all zoometric/linear appraisal traits, thus making them recommendable as breeding animals. The relevance of this study relies on the fact that the information derived from these analyses will enhance the selection of breeding individuals, in which a desirable dairy type is indirectly sought, through the haplotypic sequences in the β casein locus, which is not currently routinely considered in the Murciano-Granadina goat breeding program.

Relation between αS1-casein, genotype, and quality traits of milk from Swedish dairy goats

Locally produced food is becoming popular among Swedish consumers. One product that has increased in popularity is artisan-manufactured goat cheese, and although the dairy goat industry in Sweden is small-scale, production is gradually increasing. In goats, the CSN1S1 gene regulates expression of the protein α_S1-casein (α_S1-CN), which has been found to be important for cheese yield. Over the years, breeding animals have been imported to Sweden from Norway. Historically, a high frequency of the Norwegian goat population carried a polymorphism at the CSN1S1 gene. This polymorphism, called the Norwegian null allele (D), leads to zero or significantly reduced expression of α_S1-CN. Using milk samples from 75 goats, this study investigated associations between expression of α_S1-CN and genotype at the CSN1S1 gene on milk quality traits from Swedish Landrace goats. Milk samples were grouped according to relative level of α_S1-CN (low: 0-6.9% of total protein; medium-high: 7-25% of total protein) and genotype (DD, DG, DA/AG/AA). While the D allele leads to extremely low expression of α_S1-CN, the G allele is low expressing and the A allele is highly expressing for this protein. Principal component analysis was used to explore the total variation in milk quality traits. To evaluate the effect of different allele groups on milk quality attributes, 1-way ANOVA and Tukey pairwise comparison tests were used. The majority (72%) of all goat milk samples investigated showed relative α_S1-CN content of 0% to 6.82% of total protein. The frequency of individuals homozygous for the Norwegian null allele (DD) was 59% in the population of sampled goats, and only 15% carried at least one A allele. A low relative concentration of α_S1-CN was associated with lower total protein, higher pH, and higher relative concentration of β-casein and levels of free fatty acids. Milk from goats homozygous for the null allele (DD) showed a similar pattern as milk with low relative concentration of α_S1-CN, but total protein was only numerically lower, and somatic cell count and α_S2-CN were higher than for the other genotypes. The associations between levels of α_S1-CN and the investigated genotype at the CSN1S1 gene indicate a need for a national breeding program for Swedish dairy goats.

Candidate Genes and Their Expressions Involved in the Regulation of Milk and Meat Production and Quality in Goats (Capra hircus)

Simple Summary

During the present decade, highly selected caprine farming has increased in popularity due to the hardiness and adaptability inherent to goats. Recent advances in genetics have enabled the improvement in goat selection efficiency. The present review explores how genetic technologies have been applied to the goat-farming sector in the last century. The main candidate genes related to economically relevant traits are reported. The major source of income in goat farming derives from the sale of milk and meat. Consequently, yield and quality must be specially considered. Meat-related traits were evaluated considering three functional groups (weight gain, carcass quality and fat profile). Milk traits were assessed in three additional functional groups (milk production, protein and fat content).

Abstract

Despite their pivotal position as relevant sources for high-quality proteins in particularly hard environmental contexts, the domestic goat has not benefited from the advances made in genomics compared to other livestock species. Genetic analysis based on the study of candidate genes is considered an appropriate approach to elucidate the physiological mechanisms involved in the regulation of the expression of functional traits. This is especially relevant when such functional traits are linked to economic interest. The knowledge of candidate genes, their location on the goat genetic map and the specific phenotypic outcomes that may arise due to the regulation of their expression act as a catalyzer for the efficiency and accuracy of goat-breeding policies, which in turn translates into a greater competitiveness and sustainable profit for goats worldwide. To this aim, this review presents a chronological comprehensive analysis of caprine genetics and genomics through the evaluation of the available literature regarding the main candidate genes involved in meat and milk production and quality in the domestic goat. Additionally, this review aims to serve as a guide for future research, given that the assessment, determination and characterization of the genes associated with desirable phenotypes may provide information that may, in turn, enhance the implementation of goat-breeding programs in future and ensure their sustainability.

Polymorphism of CSN1S1 (g.12164G>A) and CSN2 (g.8913C>A) genes in pure and cross dairy goats

Casein genes directly control milk protein of animals. CSN1S1 (αS1-Casein) and CSN2 (β-Casein) genes influence on milk protein fractions. Genetic polymorphisms of CSN1S1 gene at g.12164G>A locus and CSN2 gene at g.8913C>A locus were identified by PCR-RFLP technique. Animal samples were pure dairy goats providing PE (5 hds.), Saanen (8 hds.) and their crosses providing Sapera (50% Saanen, 50% PE) (51 hds.) and SaanPE (75% Saanen, 25% PE) (3 hds.) from IRIAP dairy goat station. Allele frequency, genotype frequency, heterozygosity value, and Hardy-Weinberg (H-W) equilibrium value were analyzed by Popgen32 program. CSN1S1_g.12164G>A locus resulted in two alleles, i.e. G allele (192 bp, 145 bp, and 101 bp) and A allele (337 bp and 101 bp). The G allele from the highest frequenciest was successively Saanen (0.625), Sapera (0.578), PE (0.400), and SaanPE (0.333). Most dairy goats were heterozygote (Ho>He) and in H-W equilibrium (q2 count < q2P0.05). Whereas CSN2_g.8913C>A locus was monomorphic for possesing only C allele (233 bp and 162 bp), without A allele (416 bp). The existent g.12164G>A SNP of the CSN1S1 gene of could be a potencial molecular selection marker of milk protein content in dairy goat.

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

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.

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

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.

Non-parametric association analysis of additive and dominance effects of casein complex SNPs on milk content and quality in Murciano-Granadina goats

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.

Genome-wide association study of conformation and milk yield in mixed-breed dairy goats

Identification of genetic markers that affect economically important traits is of high value from a biological point of view, enabling the targeting of candidate genes and providing practical benefits for the industry such as wide-scale genomic selection. This study is one of the first to investigate the genetic background of economically important traits in dairy goats using the caprine 50K single nucleotide polymorphism (SNP) chip. The aim of the project was to perform a genome-wide association study for milk yield and conformation of udder, teat, and feet and legs. A total of 137,235 milk yield records on 4,563 goats each scored for 10 conformation traits were available. Out of these, 2,381 goats were genotyped with the Illumina Caprine 50K BeadChip (Illumina Inc., San Diego, CA). A range of pseudo-phenotypes were used including deregressed breeding values and pseudo-estimated breeding values. Genome-wide association studies were performed using the multi-locus mixed model (MLMM) algorithm implemented in SNP & Variation Suite v7.7.8 (Golden Helix Inc., Bozeman, MT). A genome-wise significant [-log₁₀(P-value) > 5.95] SNP for milk yield was identified on chromosome 19, with additional chromosome-wise significant (-log₁₀(P-value) > 4.46] SNP on chromosomes 4, 8, 14, and 29. Three genome-wise significant SNP for conformation of udder attachment, udder depth, and front legs were identified on chromosome 19, and chromosome-wise SNP were found on chromosomes 4, 5, 6, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 23, and 27. The proportion of variance explained by the significant SNP was between 0.4 and 7.0% for milk yield and between 0.1 and 13.8% for conformation traits. This study is the first attempt to identify SNP associated with milk yield and conformation in dairy goats. Two genome-wise significant SNP for milk yield and 3 SNP for conformation of udder attachment, udder depth, and front legs were found. Our results suggest that conformation traits have a polygenic background because, for most of them, we did not identify any quantitative trait loci with major effect.

Differential Expression of the Alpha S1 Casein and Beta-Lactoglobulin Genes in Different Physiological Stages of the Adani Goats Mammary Glands

Background

Milk proteins genes have been the focus of the researches as the candidate target genes that play a decisive role when animal breeding is desired.

Objectives

In the present study, the transcriptional levels of Beta-lactoglobulin (BLG) and Alpha S1 casein (CSN1S1) genes were investigated during prenatal, milking and drying times in mammary glands of the Adani goats which showed high and low breeding values.

Materials and Methods

The breeding values of the animals were estimated first by applying multi-trait random regression model. Using the biopsy gun, the mammary gland samples were taken and real-time PCR was applied to search the expression of the genes. Fixed factors of the model were the breeding value groups, sampling times and their interactions.

Results

The interactions were significant for both genes. At milking time, the high breeding value group exhibited more transcriptional levels for BLG and less transcriptional levels for CSN1S1 gene compared with the low breeding value group. The expression patterns of these genes were also different between the two breeding value groups. The maximum level of BLG and CSN1S1 transcriptions were found to occur at drying time.

Conclusions

A difference in the gene expression was observed between the two groups which indicate the change in the nucleotide sequence for transcription factor binding sites, or miRNA binding sites, otherwise in the coding regions. Therefore, the variations in the coding and promoter regions of this gene should be investigated in the further studies.

Longitudinal data analysis of polymorphisms in the κ-casein and β-lactoglobulin genes shows differential effects along the trajectory of the lactation curve in tropical dairy goats

The κ-casein (CSN-3) and β-lactoglobulin (BLG) genes are extensively polymorphic in ruminants. Several association studies have estimated the effects of polymorphisms in these genes on milk yield, milk composition, and cheese-manufacturing properties. Usually, these results are based on production integrated over the lactation curve or on cross-sectional studies at specific days in milk (DIM). However, as differential expression of milk protein genes occurs over lactation, the effect of the polymorphisms may change over time. In this study, we fitted a mixed-effects regression model to test-day records of milk yield and milk quality traits (fat, protein, and total solids yields) from Colombian tropical dairy goats. We used the well-characterized A/B polymorphisms in the CSN-3 and BLG genes. We argued that this approach provided more efficient estimators than cross-sectional designs, given the same number and pattern of observations, and allowed exclusion of between-subject variation from model error. The BLG genotype AA showed a greater performance than the BB genotype for all traits along the whole lactation curve, whereas the heterozygote showed an intermediate performance. We observed no such constant pattern for the CSN-3 gene between the AA homozygote and the heterozygote (the BB genotype was absent from the sample). The differences among the genotypic effects of the BLG and the CSN-3 polymorphisms were statistically significant during peak and mid lactation (around 40-160 DIM) for the BLG gene and only for mid lactation (80-145 DIM) for the CSN-3 gene. We also estimated the additive and dominant effects of the BLG locus. The locus showed a statistically significant additive behavior along the whole lactation trajectory for all quality traits, whereas for milk yield the effect was not significant at later stages. In turn, we detected a statistically significant dominance effect only for fat yield in the early and peak stages of lactation (at about 1-45 DIM). The longitudinal analysis of test-day records allowed us to estimate the differential effects of polymorphisms along the lactation curve, pointing toward stages that could be affected by the gene.

Effect of body mass index at parturition on goat milk quality and yield

A hypothesis that goats in high body condition (BC) at kidding produce milk with lower free fatty acid (FFA) concentrations than do goats in poor condition was tested. Dry goats were measured for neck height and bodyweight 103 days prepartum, and body mass index (BMI) was calculated as bodyweight/height2, and used as a measure of BC. One-third of the goats with the highest BMI were allocated to the ‘high-BMI’ group, and the remaining two-thirds were allocated to ‘increased-BMI’ and ‘low-BMI’ groups. Until kidding, the high and low BMI groups were offered a low-energy diet, whereas the increased-BMI group was offered a high-energy diet. After parturition, all animals were offered the same diet. The goats that attained high BMI through feeding, but not those with inherent high BMI, mobilised body fat during early lactation, and increased milk yield. Milk FFA concentrations were reduced in multiparous goats, but not in yearling goats that had another genetic status and therefore were less susceptible to high milk-FFA concentrations.

Newly identified mutations at the CSN1S1 gene in Ethiopian goats affect casein content and coagulation properties of their milk

Very high casein content and good coagulation properties previously observed in some Ethiopian goat breeds led to investigating the αs1-casein (CSN1S1) gene in these breeds. Selected regions of the CSN1S1 gene were sequenced in 115 goats from 5 breeds (2 indigenous: Arsi-Bale and Somali, 1 exotic: Boer, and 2 crossbreeds: Boer × Arsi-Bale and Boer × Somali). The DNA analysis resulted in 35 new mutations: 3 in exons, 3 in the 5' untranslated region (UTR), and 29 in the introns. The mutations in exons that resulted in an amino acid shift were then picked to evaluate their influence on individual casein content (αs1-, αs2-, β-, and κ-CN), micellar size, and coagulation properties in the milk from the 5 goat breeds. A mutation at nucleotide 10657 (exon 10) involved a transversion: CAG→CCG, resulting in an amino acid exchange Gln77→Pro77. This mutation was associated with the indigenous breeds only. Two new mutations, at nucleotide 6072 (exon 4) and 12165 (exon 12), revealed synonymous transitions: GTC→GTT in Val15 and AGA→AGG in Arg100 of the mature protein. Transitions G→A and C→T at nucleotides 1374 and 1866, respectively, occurred in the 5' UTR, whereas the third mutation involved a transversion T→G at nucleotide location 1592. The goats were grouped into homozygote new (CC), homozygote reference (AA), and heterozygote (CA) based on the nucleotide that involved the transversion. The content of αs1-CN (15.32g/kg) in milk samples of goats homozygous (CC) for this newly identified mutation, Gln77→Pro77 was significantly higher than in milks of heterozygous (CA; 9.05g/kg) and reference (AA; 7.61g/kg) genotype animals. The αs2-, β-, and κ-CN contents showed a similar pattern. Milk from goats with a homozygous new mutation had significantly lower micellar size. Milk from both homozygote and heterozygote new-mutation goats had significantly shorter coagulation rate and stronger gel than the reference genotype. Except the transversion, the sequence corresponded to allele A and presumably derived from it. Therefore, this allele is denoted by A3. All goats from the reference genotype (AA) were homozygous for the allele at nucleotide position 1374 and 1866, whereas all mutations in the 5' UTR existed in a heterozygous form in both heterozygous (CA) and the new mutation (CC) genotype. The newly identified mutation (CC) detected in some of the goat breeds is, therefore, important in selection for genetic improvement and high-quality milk for the emerging goat cheese-producing industries. The finding will also benefit farmers raising these goat breeds due to the increased selling price of goats. Further studies should investigate the effect of this amino acid exchange on the secondary and tertiary structure of the αs1-CN molecule and on the susceptibility of peptide hydrolysis by digestive enzymes.

Technical note: An R package for fitting Bayesian regularized neural networks with applications in animal breeding

In recent years, several statistical models have been developed for predicting genetic values for complex traits using information on dense molecular markers, pedigrees, or both. These models include, among others, the Bayesian regularized neural networks (BRNN) that have been widely used in prediction problems in other fields of application and, more recently, for genome-enabled prediction. The R package described here (brnn) implements BRNN models and extends these to include both additive and dominance effects. The implementation takes advantage of multicore architectures via a parallel computing approach using openMP (Open Multiprocessing) for the computations. This note briefly describes the classes of models that can be fitted using the brnn package, and it also illustrates its use through several real examples.

Comparison of random regression and repeatability models to predict breeding values from test-day records of Norwegian goats

One aim of the research was to challenge a previously selected repeatability model with 2 other repeatability models. The main aim, however, was to evaluate random regression models based on the repeatability model with lowest mean-squared error of prediction, using Legendre polynomials up to third order for both animal additive genetic and permanent environmental effects. The random regression and repeatability models were compared for model fit (using likelihood-ratio testing, Akaike information criterion, and the Bayesian information criterion) and the models' mean-squared errors of prediction, and by cross-validation. Cross-validation was carried out by correlating excluded observations in one data set with the animals' breeding values as predicted from the pedigree only in the remaining data, and vice versa (splitting proportion: 0.492). The data was from primiparous goats in 2 closely tied buck circles (17 flocks) in Norway, with 11,438 records for daily milk yield and 5,686 to 5,896 records for content traits (fat, protein, and lactose percentages). A simple pattern was revealed; for daily milk yield with about 5 records per animal in first lactation, a second-order random regression model should be chosen, whereas for content traits that had only about 3 observations per goat, a first-order polynomial was preferred. The likelihood-ratio test, Akaike information criterion, and mean-squared error of prediction favored more complex models, although the results from the latter and the Bayesian information criterion were in the direction of those obtained with cross-validation. As the correlation from cross-validation was largest with random regression, genetic merit was predicted more accurate with random regression models than with the repeatability model.

Additive and dominance effects of the α(s1)-casein locus on milk yield and composition traits in dairy goats

The objective of this study was to evaluate the effects of the CSN1S1 locus polymorphism on 305-d records of milk, fat, protein, lactose and total solids yields, fat, protein, lactose and total solids contents in Mexican dairy goats. A total of 514 lactation records belonging to Alpine (n=60), Saanen (n=105) and Toggenburg (n=74) goats, born from 2003 to 2006 in three herds were used. Discrimination between alleles E, F, N, A* (CSN1S1 A, G, H, I, O1 and O2) and B* (CSN1S1 B1, B2, B3, B4, C and L) were made by amplification of fragments of the gene CSN1S1 and digestion with the restriction endonuclease XmnI. In order to estimate additive and dominance effects, data sets including (1) all genotypes, and (2) only homozygote genotypes, were analysed using linear mixed models. The allele A*, had significant additive effects for protein content (0·21±0·07%; P=0·002) and total solids content (0·66±0·23%; P=0·005) when compared with allele F. An unfavourable additive effect of allele A* on milk yield was found in the Alpine breed (-81·4±40·2; P=0·046) when compared with allele F. Favourable dominance effects were found for some genotypes (P<0·05) for milk yield (A*N and B*N), fat yield (A*N and B*E), protein yield (A*N and B*E), lactose yield (A*N) and total solids yield (A*N). Also, unfavourable dominance effects were found (P<0·05) for protein content (A*B* and A*N) and total solids content (A*B*, A*N, and A*F). Allele A* was the only one with a positive effect for protein content. Significant allele-year interaction effects were also observed. The presence of significant dominance effects, estimated between specific pairs of alleles, challenged the purely additive nature of the genetic effect at the CSN1S1 locus. Implications from use of CSN1S1 effects in goat breeding programmes are presented.