Genetic parameters and genome-wide association studies for mozzarella and milk production traits, lactation length, and lactation persistency in Murrah buffaloes.

Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to (1) compare single-trait random regression models under a single-step genomic BLUP setting based on alternative covariance functions (i.e., Wood, Wilmink, and Ali and Schaeffer) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); (2) combine the best functions for each trait under a multiple-trait framework; (3) estimate time-dependent SNP effects for all the studied longitudinal traits; and (4) identify the most likely candidate genes associated with the traits. A total of 323,140 test-day records from the first lactation of 4,588 Murrah buffaloes were made available for the study. The model included the average curve of the population nested within herd-year-season of calving, systematic effects of number of milkings per day, and age at first calving as linear and quadratic covariates, and additive genetic, permanent environment, and residual as random effects. The Wood model had the best goodness of fit based on the deviance information criterion and posterior model probabilities for all traits. Moderate heritabilities were estimated over time for most traits (0.30 ± 0.02 for MY; 0.26 ± 0.03 for FY; 0.45 ± 0.04 for PY; 0.28 ± 0.05 for MZY; 0.13 ± 0.02 for FPR; and 0.15 ± 0.03 for SCS). The heritability estimates for LP ranged from 0.38 ± 0.02 to 0.65 ± 0.03 depending on the trait definition used. Similarly, heritabilities estimated for LL ranged from 0.10 ± 0.01 to 0.14 ± 0.03. The genetic correlation estimates across days in milk (DIM) for all traits ranged from -0.06 (186-215 DIM for MY-SCS) to 0.78 (66-95 DIM for PY-MZY). The SNP effects calculated for the random regression model coefficients were used to estimate the SNP effects throughout the lactation curve (from 5 to 305 d). Numerous relevant genomic regions and candidate genes were identified for all traits, confirming their polygenic nature. The candidate genes identified contribute to a better understanding of the genetic background of milk-related traits in Murrah buffaloes and reinforce the value of incorporating genomic information in their breeding programs.

Genomic analysis of genotype-environment interaction in age at first calving of Murrah buffaloes.

Age at first calving (AFC) is a measure of sexual maturity associated with the start of productive life of dairy animals. Additionally, a lower AFC reduces the generation interval and early culling of females. However, AFC has low heritability, making it a trait highly influenced by environmental factors. In this scenario, one way to improve the reproductive performance of buffalo cows is to select robust animals according to estimated breeding value (EBV) using models that include genotype-environment interaction (GEI) with the application of reaction norm models (RNMs). This can be achieved by understanding the genomic basis related to GEI of AFC. Thus, in this study, we aimed to predict EBV considering GEI via the RNM and identify candidate genes related to this component in dairy buffaloes through genome-wide association studies (GWAS). We used 1795 AFC records from three Murrah buffalo herds and formed environmental gradients (EGs) from contemporary group solutions obtained from genetic analysis of 270-day cumulative milk yield. Heritability estimates ranged from 0.15 to 0.39 along the EG. GWAS of the RNM slope parameter identified important genomic regions. The genomic window that explained the highest percentage of genetic variance of the slope (0.67%) was located on BBU1. After functional analysis, five candidate genes were detected, involved in two biological processes. The results suggested the existence of a GEI for AFC in Murrah buffaloes, with reclassification of animals when different environmental conditions were considered. The inclusion of genomic information increased the accuracy of breeding values for the intercept and slope of the reaction norm. GWAS analysis suggested that important genes associated with the AFC reaction norm slope were possibly also involved in biological processes related to lipid metabolism and immunity.

Random regression models using B-splines functions provide more accurate genomic breeding values for milk yield and lactation persistence in Murrah buffaloes.

There is a great worldwide demand for cheese made with buffalo milk, due to its flavour and nutritional properties. In this context, there is a need for increasing the efficiency of buffalo milk production (including lactation persistence), which can be achieved through genomic selection. The most used methods for the genetic evaluation of longitudinal data, such as milk-related traits, are based on random regression models (RRM). The choice of the best covariance functions and polynomial order for modelling the random effects is an important step to properly fit RRM. To our best knowledge, there are no studies evaluating the impact of the order and covariance function (Legendre polynomials-LEG and B-splines-BSP) used to fit RRM for genomic prediction of breeding values in dairy buffaloes. Therefore, the main objectives of this study were to estimate variance components and evaluate the performance of LEG and BSP functions of different orders on the predictive ability of genomic breeding values for the first three lactations of milk yield (MY1, MY2, and MY3) and lactation persistence (LP1, LP2, and LP3) of Brazilian Murrah. Twenty-two models for each lactation were contrasted based on goodness of fit, genetic parameter estimates, and predictive ability. Overall, the models of higher orders of LEG or BSP had a better performance based on the deviance information criterion (DIC). The daily heritability estimates ranged from 0.01 to 0.30 for MY1, 0.08 to 0.42 for MY2, and from 0.05 to 0.47 for MY3. For lactation persistence (LP), the heritability estimates ranged from 0.09 to 0.32 for LP1, from 0.15 to 0.33 for LP2, and from 0.06 to 0.32 for LP3. In general, the curves plotted for variance components and heritability estimates based on BSP models presented lower oscillation along the lactation trajectory. Similar predictive ability was observed among the models. Considering a balance between the complexity of the model, goodness of fit, and credibility of the results, RRM using quadratic B-splines functions based on four or five segments to model the systematic, additive genetic, and permanent environment curves provide better fit with no significant differences between genetic variances estimates, heritabilities, and predictive ability for the genomic evaluation of dairy buffaloes.

Genetics of tolerance to heat stress in milk yield of dairy buffaloes assessed by a reaction norm model.

The objectives of this study were to assess the effects of heat stress on the milk yield and investigate the presence of genotype × environment interaction (G × E) in Brazilian Murrah buffaloes reared under tropical conditions. With this, 58,070 test-day (TD) records for milk yield from 3,459 first lactations of buffaloes collected between 1987 and 2018 were evaluated. A mixed model considering days in milk (DIM) and temperature-humidity index (THI) was applied to quantify milk yield losses due to heat stress. The most detrimental effect of THI on TD milk yield was observed in the mid-stages of lactation, after lactation peak, in DIM 105-154 and 155-204 days (-0.020 and -0.015 kg/day per THI, respectively). The least-squares means of TD milk yield were used to identify a heat stress threshold using a piecewise linear regression model. A substantial reduction in TD milk yield due to heat stress was observed for THI values above 77.8 (-0.251 kg/day per increase of 1 THI unit). An analysis using a single-trait random regression animal model was carried out to estimate variance components and genetic parameters for TD milk yield over THI and DIM values. Increased additive genetic variance and heritability estimates were observed for extreme THI values (THI = 60 and 80) combined with mid-lactation stages. The lowest genetic correlation (0.50) was observed between TD records at opposite extremes of the THI scale (THI = 60 vs. THI = 80). The genetic trends observed for the regression coefficients related to the general level of production (0.02) and specific ability to respond to heat stress (-0.002) indicated that selection to increase milk yield did not affect the specific ability to respond to heat stress until the present moment. These trends reflect the low genetic correlation between these components (0.05 ± 0.14). In this sense, monitoring trends of genetic components related to response to heat stress is recommended.

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models.

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from -0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.

Water buffaloes (Bubalus bubalis) only have A2A2 genotype for beta-casein.

Beta-casein is a milk protein that has two variants: A1 and A2. Some individuals have difficulties digesting beta-casein A1, which can cause gastrointestinal disorders. A2 milk has emerged as an alternative. This milk only contains beta-casein A2 and is obtained from females carrying the A2A2 genotype of the gene. In cattle, allele and genotype frequencies vary according to breed and marker-assisted selection is performed to obtain A2A2 animals and the consequent production of A2 milk that is easier to digest. This study aimed to evaluate the alleles of beta-casein in buffaloes. A total of 657 buffaloes of four different breeds were genotyped and all animals carried the A2A2 genotype, i.e., allele A1 does not exist in the buffalo species. Thus, all milk products of buffaloes are naturally A2. This result adds value to products derived from buffalo milk.

Short communication: Characterization of the milk protein expression profiles in dairy buffaloes with and without subclinical mastitis.

The aim of this study was to characterize the proteins present in milk whey from buffaloes with and without subclinical mastitis using a proteomic approach to identify differentially expressed proteins as potential biomarkers for this disease. Whey from Murrah buffaloes with subclinical mastitis was compared with whey from healthy animals using liquid chromatography-tandem mass spectrometry. The annotated protein databases for Bubalus bubalis and Bos taurus were used in the analysis, and the gene annotations from the buffalo and bovine reference assemblies were also used. After integrating gene annotations from both buffaloes and bovines, a total of 1,033 proteins were identified, of which 156 were differentially expressed. Eighteen biological processes were annotated with Gene Ontology. Cathelicidin-3 was identified as a potential biomarker for subclinical mastitis. These results are important to the characterization of mastitis in the buffalo mammary gland and may aid in the development of tools for early diagnosis.

Genome-wide association study applied to type traits related to milk yield in water buffaloes (Bubalus bubalis).

This research aimed to estimate genetic parameters for milk yield and type traits [withers height (WH), croup height (CH), body length (BL), croup length (CL), iliac width (ILW), ischial width (ISW), and thoracic circumference] in Murrah buffaloes and to identify genomic regions related to type traits by applying a single-step genome-wide association study. Data used to estimate the genetic parameters consisted of 601 records of milk yield in the first lactation and the aforementioned type traits. For the single-step genome-wide association study, 322 samples genotyped with a 90K Axiom Buffalo Genotyping array (Thermo Fisher Scientific, Santa Clara, CA) were used. Bivariate analysis revealed that heritability for milk yield (kg) at 305 d was 0.31 ± 0.11, whereas it ranged from 0.22 ± 0.07 to 0.34 ± 0.09 for the studied conformation traits. Based on the percentages of genetic variance explained by windows of 10 markers, there were 16 genomic regions explaining more than 0.5% of the variance for WH, CH, BL, CL, ILW, ISW, and thoracic circumference. Between those regions, 4 were associated with more than 1 trait, suggesting pleiotropic roles for some genes of Bos taurus autosome (BTA) 12 on CL and WH, BTA13 on ISW and ILW, BTA23 on CH and BL, and BTA28 on ISW and BL. Most of these regions coincide with known quantitative trait loci for milk traits. Thus, further studies based on sequence data will help to validate the association of this region with type traits and likely identify the causal mutations.

Identification of genomic regions related to age at first calving and first calving interval in water buffalo using single-step GBLUP.

In Brazil, water buffaloes have been used to produce milk for mozzarella cheese production. Consequently, the main selection criterion applied for the buffalo genetic improvement is the estimated mozzarella yield as a function of milk, fat and protein production. However, given the importance of reproductive traits in production systems, this study aimed to use techniques for identifying genomic regions that affect the age at first calving (AFC) and first calving interval (FCI) in buffalo cows and to select candidate genes for the identification of QTL and gene expression studies. The single-step GBLUP method was used for the identification of genomic regions. Windows of 1 Mb containing single-nucleotide polymorphisms were constructed and the 10 windows that explained the greatest proportion of genetic variance were considered candidate regions for each trait. Genes present into the selected windows were identified using the UOA_WB_1 assembly as the reference, and their ontology was defined with the Panther tool. Candidate regions for both traits were identified on BBU 3, 12, 21 and 22; for AFC, candidates were detected on BBU 6, 7, 8, 9 and 15 and for first calving interval on BBU 4, 14 and 19. This study identified regions with great contribution to the additive genetic variance of age at first calving and first calving interval in the population of buffalo cows studied. The ROCK2, PMVK, ADCY2, MAP2K6, BMP10 and GFPT1 genes are main candidates for reproductive traits in water dairy buffaloes, and these results may have future applications in animal breeding programs or in gene expression studies of the species.

Polymorphisms in major histocompatibility complex genes and its associations with milk quality in Murrah buffaloes.

Animal breeding programs have used molecular genetic tools as an auxiliary method to identify and select animals with superior genetic merit for milk production and milk quality traits as well as disease resistance. Genes of the major histocompatibility complex (MHC) are important molecular markers for disease resistance that could be applied for genetic selection. The aim of this study was to identify single nucleotide polymorphisms (SNPs) and haplotypes in DRB2, DRB3, DMA, and DMB genes in Murrah breed and to analyze the association between molecular markers and milk, fat, protein and mozzarella production, fat and protein percentage, and somatic cell count. Two hundred DNA samples from Murrah buffaloes were used. The target regions of candidate genes were amplified by polymerase chain reaction (PCR) followed by sequencing and identification of polymorphisms. Allele and genotype frequencies, as well as linkage disequilibrium between SNPs, were calculated. Genotypes were used in association analyses with milk production and quality traits. Except for the DMA gene, identified as monomorphic, the other genes presented several polymorphisms. The DMB, DRB2, and DRB3 genes presented two, six, and seven SNPs, respectively. Fifty-seven haplotype blocks were constructed from 15 SNPs identified, which was used in association analyses. All the studied traits had at least one associated haplotype. In conclusion, it is suggested that the haplotypes found herein can be associated with important traits related to milk production and quality.

Analysis of the population structure of buffaloes in Brazil.

The aim of this study was to evaluate the population structure of Brazilian buffaloes using of pedigree information. The pedigree used in the analyses included records of 16,915 animals. The population parameters were obtained through the ENDOG software. The estimates of mean of inbreeding (F) and average relatedness (AR) coefficients were 3.22% and 5.99%, respectively. The average generation interval was 6.39 years. The effective number of founders and ancestors was 28 and 22, respectively. In this study, we concluded that the selection of individuals with lower AR is necessary to avoid an increase in matings between inbreeding individuals in this population, in order to obtain greater genetic gain by selection.

Genetic parameters for tonic immobility, body weight, and morphological traits of the red-winged tinamou (Rhynchotus rufescens).

This study was carried out to estimate genetic parameters for morphology, body weight, and tonic immobility traits in the red-winged tinamou (Rhynchotus rufescens). Information on 690 birds was used and genetic parameters were estimated using Bayesian methods under a multi-trait animal model. The following traits were considered in this study: tarsal length (TL), bill length (BL), wing length (WL), head width (HW), bill width (BW), mature weight (MW), weight at 90 days (W90), and tonic immobility (TI). The heritability showed estimates between 0.15 for wing length and 0.56 for bill length. Positive and negative genetic correlations were estimated, ranging from - 0.33 to 0.81. All the morphological, production, and behavioral traits studied will have moderate to high response to selection. The body weight at 90 days is a better alternative for use in breeding programs and its selection would not lead to an increase in the time of tonic immobility. Both the selection for weight gain and for reduction of tonic immobility time would lead to an increase in the size of the legs of the red-winged tinamou, which could be advantageous for thermal control of these birds in tropical systems.

Twinning rate in buffaloes: A case report.

The information of twin pregnancy frequencies in buffaloes is scarce in the literature. Evidence even indicates that twin pregnancies are not carried to term, but it does not seem to be the case. In this case report, the event of twin pregnancy in buffaloes is reported as well as its frequency. Twin birth is the presence of two or more embryos in a single gestation. Multiple births are uncommon in buffaloes since the species is uniparous. We studied a population of Murrah buffaloes in which slightly more than 13,000 births were observed. In this study, the frequency of occurrence of twin births in Murrah buffaloes was 0.14%. This low incidence impaired the estimation of genetic parameters. Twins can have advantages and disadvantages depending on the production system, which are discussed in this case report.

Genotype-environment interaction for age at first calving in buffaloes, using the reaction norm model.

The objective of this study was to evaluate the genotype-environment interaction effect on age at first calving in buffaloes. The records were analysed using two approaches: (a) standard animal model and (b) reaction norm model. For the reaction norm analysis, two environmental gradients were formed, using age of first calving or milk yield group contemporary average. The results showed differences in the heritability estimates when using the two approaches. The reaction norm model indicated high heritability in more favourable environments and low magnitude genetic correlations between extreme environments. Based on our findings, we verified the significance of the genotype-environment interaction effect on age at first calving in buffaloes.

Expression profile of the CSF3 and LPO genes in milk from buffalo (Bubalus bubalis) with and without mastitis.

This study compared the expression profile of the candidate genes, CSF3 and LPO, by investigating the immune response mechanisms involved in the phenotype of resistance and susceptibility to mastitis of healthy and infected buffaloes. The Granulocyte Colony Stimulating Factor 3 (CSF3) and Lactoperoxidase (LPO) genes expression profiles were determined in 24 milk samples from buffaloes with (N = 12) and without (N = 12) mastitis, using the quantitative real-time PCR (qRT-PCR) technique. CSF3 and LPO expressions were 5.14 (P = 0.001) and 2.41 (P = 0.097) times higher in animals with mastitis compared to healthy animals, respectively, evidencing a trend toward different expressions of this gene in the studied groups. Our finding suggests that LPO and CSF3 genes are an important defense mechanism against mastitis in dairy buffaloes, and may be putative genes for selecting healthier animals in buffalo breeding programs.

Genome-wide scan reveals population stratification and footprints of recent selection in Nelore cattle.

BACKGROUND: This study aimed at (1) assessing the genomic stratification of experimental lines of Nelore cattle that have experienced different selection regimes for growth traits, and (2) identifying genomic regions that have undergone recent selection. We used a sample of 763 animals genotyped with the Illumina BovineHD BeadChip, among which 674 animals originated from two lines that are maintained under directional selection for increased yearling body weight and 89 animals from a control line that is maintained under stabilizing selection. RESULTS: Multidimensional analysis of the genomic dissimilarity matrix and admixture analysis revealed a substantial level of population stratification between the directional selection lines and the stabilizing selection control line. Two of the three tests used to detect selection signatures (FST, XP-EHH and iHS) revealed six candidate regions with indications of selection, which strongly indicates truly positive signals. The set of identified candidate genes included several genes with roles that are functionally related to growth metabolism, such as COL14A1, CPT1C, CRH, TBC1D1, and XKR4. CONCLUSIONS: The current study identified genetic stratification that resulted from almost four decades of divergent selection in an experimental Nelore population, and highlighted autosomal genomic regions that present patterns of recent selection. Our findings provide a basis for a better understanding of the metabolic mechanism that underlies the growth traits, which are modified by selection for yearling body weight.

Use of single-step genome-wide association studies for prospecting genomic regions related to milk production and milk quality of buffalo.

The aim of this research communication was to identify chromosome regions and genes that could be related to milk yield (MY), milk fat (%F) and protein percentage (%P) in Brazilian buffalo cows using information from genotyped and non-genotyped animals. We used the 90 K Axiom® Buffalo Genotyping array. A repeatability model was used. An iterative process was performed to calculate the weights of markers as a function of the squared effects of Single Nucleotide Polymorphism (SNP) and allele frequencies. The 10 SNPs with the largest effects for MY, %F and %P were studied and they explained 7·48, 9·94 and 6·56% of the genetic variance, respectively. These regions harbor genes with biological functions that could be related to the traits analyzed. The identification of such regions and genes will contribute to a better understanding of their influence on milk production and milk quality traits of buffaloes.

Relationship between mozzarella yield and milk composition, processing factors, and recovery of whey constituents.

Our aim was to identify the relationship between mozzarella cheese yield and buffalo milk composition, processing factors, and recovery of whey constituents. A production of 30 batches of mozzarella cheese at a dairy industry in northeast Brazil (Rio Grande do Norte) was monitored between March and November 2015. Mozzarella yield and 32 other variables were observed for each batch, and divided into 3 groups: milk composition variables (12); variables involved in the cheesemaking process (14); and variables for recovery of whey constituents (6). Data were analyzed using descriptive statistics, Pearson correlation, and principal component analysis. Most of the correlations between milk composition variables and between the variables of the manufacturing processes were not significant. Significant correlations were mostly observed between variables for recovery of whey constituents. Yield only showed significant correlation with time elapsed between curd cuttings and age of the starter culture, and it showed greater association with age of the starter culture, time elapsed between curd cuttings, and during stretching, as well as with milk pH and density. Thus, processing factors and milk characteristics are closely related to dairy efficiency in mozzarella manufacturing.

Genomic prediction of breeding values for carcass traits in Nellore cattle.

BACKGROUND: The objective of this study was to evaluate the accuracy of genomic predictions for rib eye area (REA), backfat thickness (BFT), and hot carcass weight (HCW) in Nellore beef cattle from Brazilian commercial herds using different prediction models. METHODS: Phenotypic data from 1756 Nellore steers from ten commercial herds in Brazil were used. Animals were offspring of 294 sires and 1546 dams, reared on pasture, feedlot finished, and slaughtered at approximately 2 years of age. All animals were genotyped using a 777k Illumina Bovine HD SNP chip. Accuracy of genomic predictions of breeding values was evaluated by using a 5-fold cross-validation scheme and considering three models: Bayesian ridge regression (BRR), Bayes C (BC) and Bayesian Lasso (BL), and two types of response variables: traditional estimated breeding value (EBV), and phenotype adjusted for fixed effects (Y*). RESULTS: The prediction accuracies achieved with the BRR model were equal to 0.25 (BFT), 0.33 (HCW) and 0.36 (REA) when EBV was used as response variable, and 0.21 (BFT), 0.37 (HCW) and 0.46 (REA) when using Y*. Results obtained with the BC and BL models were similar. Accuracies increased for traits with a higher heritability, and using Y* instead of EBV as response variable resulted in higher accuracy when heritability was higher. CONCLUSIONS: Our results indicate that the accuracy of genomic prediction of carcass traits in Nellore cattle is moderate to high. Prediction of genomic breeding values from adjusted phenotypes Y* was more accurate than from EBV, especially for highly heritable traits. The three models considered (BRR, BC and BL) led to similar predictive abilities and, thus, either one could be used to implement genomic prediction for carcass traits in Nellore cattle.

Genetic association between SNPs in the DGAT1 gene and milk production traits in Murrah buffaloes.

This study identified polymorphisms in the DGAT1 gene in Murrah buffaloes and investigated the associations to milk production and quality traits (milk, fat and protein yields and percentages, somatic cell count). Genomic DNA was extracted from hair follicles collected from the tail of 196 females. Three SNPs were identified in DGAT1 gene by sequencing. Statistical analyses were performed to verify the linkage and the association between polymorphisms and traits. The estimated value of r (2) between two SNPs in exon 17 (g.11,783G > A and g.11,785 T > C) was 0.029. SNP g.11,785 T > C was significantly associated (P < 0.05) to fat and protein percentage. Dominance effect was significant for milk and fat yields and protein percentage (P < 0.05). The additive effect of the SNP g.11,785 T > C was significant for protein production and somatic cell count (P < 0.05). It indicates that assisted marker selection might be done with considerations to balance production and udder health.