An updated Axiom buffalo genotyping array map and mapping of cattle quantitative trait loci to the new water buffalo reference genome assembly.

The objectives of this study were to provide the buffalo research community with an updated SNP map for the Axiom Buffalo Genotyping (ABG) array with genomic positions for SNP currently unmapped and to map all cattle QTL from the CattleQTLdb onto the buffalo reference assembly. To update the ABG array map, all SNP probe sequences from the ABG array were re-aligned against the UOA_WB_1 assembly. With the new map, the number of mapped markers increased by approximately 10% and went from 106 778 to 116 708, which reduced the average marker spacing by approximately 2 kb. A comparison of results between signatures of autozygosity study using the ABG and the new map showed that, when the additional markers were used there was an increase in the autozygosity peaks and additional peaks in BBU5 and BBU11 could be identified. After sequence alignment and quality control, 64 650 (UMD3.1) and 76 530 (ARS_UCD1.2) cattle QTL were mapped onto the buffalo genome. The mapping of the bovine QTL database onto the buffalo genome should be useful for genome-wide association studies in buffalo and, given the high homology between the two species, the positions of cattle QTL on the buffalo genome can serve as a stepping stone towards a water buffalo QTL database.

Inbreeding coefficients and runs of homozygosity islands in Brazilian water buffalo.

Characterization of autozygosity is relevant to monitor genetic diversity and manage inbreeding levels in breeding programs. Identification of autozygosity hotspots can unravel genomic regions targeted by selection for economically important traits and can help identify candidate genes for selection. In this study, we estimated the inbreeding levels of a Brazilian population of Murrah buffalo undergoing selection for milk production traits, particularly milk yield. We also studied the distribution of runs of homozygosity (ROH) islands and identified putative genes and quantitative trait loci (QTL) under selection. We genotyped 422 Murrah buffalo for 51,611 SNP; 350 of these had ROH longer than 10 Mb, indicating the occurrence of inbreeding in the last 5 generations. The mean length of the ROH per animal was 4.28 ± 1.85 Mb. Inbreeding coefficients were calculated from the genomic relationship matrix, the pedigree, and the ROH, with estimates varying between 0.242 and 0.035. Inbreeding estimates from the pedigree had a low correlation with the genomic estimates, and estimates from the genomic relationship matrix were much higher than those from the pedigree or the ROH. Signatures of selection were identified in 6 genomic regions, located on chromosomes 1, 2, 3, 5, 16, and 18, encompassing a total of 190 genes and 174 QTL. Many of the genes (e.g., APRT and ACSF3) and QTL identified are related to milk production traits, such as milk yield, milk fat yield and percentage, and milk protein yield and percentage. Other genes are associated with reproduction and immune response traits as well as morphological aspects of the buffalo species. Inbreeding levels in this population are still low but are increasing due to selection and should be managed to avoid future losses due to inbreeding depression. The proximity of genes linked to milk production traits with genes associated with reproduction and immune system traits suggests the need to include these latter genes in the breeding program to avoid negatively affecting them due to selection for production traits.

Variance of gametic diversity and its application in selection programs.

The variance of gametic diversity ( σgamete2) can be used to find individuals that more likely produce progeny with extreme breeding values. The aim of this study was to obtain this variance for individuals from routine genomic evaluations, and to apply gametic variance in a selection criterion in conjunction with breeding values to improve genetic progress. An analytical approach was developed to estimate σgamete2 by the sum of binomial variances of all individual quantitative trait loci across the genome. Simulation was used to verify the predictability of this variance in a range of scenarios. The accuracy of prediction ranged from 0.49 to 0.85, depending on the scenario and model used. Compared with sequence data, SNP data are sufficient for estimating σgamete2 Results also suggested that markers with low minor allele frequency and the covariance between markers should be included in the estimation. To incorporate σgamete2 into selective breeding programs, we proposed a new index, relative predicted transmitting ability, which better utilizes the genetic potential of individuals than traditional predicted transmitting ability. Simulation with a small genome showed an additional genetic gain of up to 16% in 10 generations, depending on the number of quantitative trait loci and selection intensity. Finally, we applied σgamete2 to the US genomic evaluations for Holstein and Jersey cattle. As expected, the DGAT1 gene had a strong effect on the estimation of σgamete2 for several production traits. However, inbreeding had a small impact on gametic variability, with greater effect for more polygenic traits. In conclusion, gametic variance, a potentially important parameter for selection programs, can be easily computed and is useful for improving genetic progress and controlling genetic diversity.

Differential expression of immune response genes associated with subclinical mastitis in dairy buffaloes.

Buffalo milk production has become of significant importance on the world scale, however, there are few studies involving biotechnological tools specifically for buffalo. To verify the effects caused by subclinical mastitis on the components of milk and to study the innate immune system in the udder of dairy buffaloes with subclinical mastitis, we evaluated the levels of expression of the lactoferrin (LTF), tumor necrosis factor alpha (TNF-α), interleukin-1 beta (IL-1ß), interleukin-8 (IL-8), and toll-like receptors 2 (TLR-2) and 4 (TLR-4) genes in buffaloes with and without subclinical mastitis. Milk samples were collected for the determination of milk components: somatic cell score (SCS), fat, protein, lactose, total solids and solids-not-fat (SNF), as well as for RNA extraction of milk cells, complementary DNA synthesis, and expression profile quantification by quantitative real-time PCR. For gene expression, the ΔΔCt was estimated using contrasts of the target genes expression adjusted for the expression of the housekeeping genes between both groups. Linear regression analysis was performed to determine the relationship between the genes studied and the milk components. Subclinical mastitis induced changes in the fat, lactose and SNF in milk of buffaloes, and the messenger RNA abundance was upregulated for TLR-2, TLR-4, TNF-α, IL-1ß and IL-8 genes in milk cells of buffaloes with subclinical mastitis, whereas the LTF gene was not differentially expressed. Results of linear regression analysis showed that TLR-2 gene expression most explains the variation in SCS, and the change in a unit of ΔCt of the TNF-α gene would result in a higher increase in SCS. The study of these immune function genes that are active in the mammary gland is important to characterize the action mechanism of the innate immunity that occurs in subclinical mastitis in dairy buffaloes and may aid the development of strategies to preserve the health of the udder.

Reaction norm for yearling weight in beef cattle using single-step genomic evaluation.

When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G × E). The main objective of this study was to evaluate the existence of G × E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments.

Genetic parameter estimates for carcass traits and visual scores including or not genomic information.

The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores.

Polymorphism in the A2M gene associated with high-quality milk in Murrah buffaloes (Bubalus bubalis).

The study of genes associated with host defense mechanisms, such as the A2M gene, plays a critical role in preventing diseases that reduce milk yield and its constituents. The aim of this study was to identify polymorphisms in the A2M gene in Murrah buffaloes (Bubalus bubalis), and investigate their associations with milk yield, fat and protein production, fat and protein percentages, and somatic cell count. Hair follicle samples of 136 animals were collected for DNA extraction, and polymorphisms were identified by polymerase chain reactions and sequencing. Statistical analyses were performed to ascertain the allelic and genotypic frequencies, the Hardy-Weinberg equilibrium, and association analysis was conducted between the polymorphisms and the traits studied. Comparative analysis between buffalo and bovine sequences revealed seven nucleotide substitutions. Alignments among the buffalo sequences identified three single nucleotide polymorphisms (SNPs), including one in exon 29, g.241A>G, which was used in subsequent statistical analyses. A Hardy-Weinberg test indicated that this SNP was in equilibrium in this population, and was significantly associated (P < 0.05) with fat production and fat and protein percentages. Therefore, this SNP can be used as a molecular marker for these traits.

Analysis of DRB3 gene polymorphisms in Jafarabadi, Mediterranean, and Murrah buffaloes from Brazil.

The DRB3 gene is an MHC class II gene that has a high degree of polymorphism with more than 100 alleles described in cattle. This variation contributes to differences among individuals in immune responsiveness and disease resistance. In this study, we searched for allelic variants in exon 2 of the DRB3 gene in 80 river buffaloes of three breeds in Brazil using a PCR-RFLP technique. The PCR product showed genetic polymorphism when digested with RsaI, PstI or HaeIII restriction enzymes. In total, 16 restriction patterns were identified: nine restriction patterns and 16 genotypes were found with RsaI; four restriction patterns and nine genotypes were found with HaeIII; and, three restriction patterns and four genotypes were found with PstI. Three RFLP patterns were exclusive to Jafarabadi buffaloes (RsaI-b, RsaI-c and RsaI-f) and three others were only observed in Mediterranean buffaloes (RsaI-g, RsaI-h and PstI-y). Jafarabadi buffaloes had a larger number of RFLP patterns than Mediterranean and Murrah breeds. The analysis showed that the DRB3 exon 2 was highly polymorphic, with the highest degree of polymorphism in Mediterranean buffaloes. This study provides the first assessment of allelic variation among three different buffalo breeds from Brazil and provides a basis for further investigations into the association between the DRB3 alleles and disease resistance.

Genetic-Quantitative Study of the First-Service Pregnancy Probability of Murrah Heifers.

Because of the importance of reproduction in stock breeding systems, it is necessary to find selection criteria that increase reproductive efficiency. The aim of this study was to estimate genetic parameters for the probability of conception on first service (PROB) in Murrah heifers, and its association with other traits of economic interest [age at first calving (AFC), service period, calving interval and milk yield at 270 days], with the purpose of evaluating their use as selection criteria. Reproductive information and first lactation records of 1200 Murrah heifers were used to perform two-trait analyses between PROB and the other characteristics. Bayesian inference was used to estimate the variance components, considering PROB as threshold and the other as linear factors. The results demonstrate that this trait has heritability of 0.15, indicating the possibility of a genetic gain by using it for selection. With respect to the genetic correlation estimates, the only high-magnitude association was with AFC (-0.899), which is the current criterion indicating sexual precocity of females. In the light of the parameters estimated, the first-service pregnancy rate is an alternative for indication of sexual precocity, although presenting a smaller genetic gain than the current standard AFC. Nevertheless, additional research should be conducted regarding this trait to assess the economic importance of its use in dairy buffalo production systems.

Estimates of genetic parameters for stayability and their associations with traits of economic interest in Gir dairy cows.

The objective of the present study was to estimate genetic parameters for stayability at 60 months of age (STAY60) and its association with first lactation cumulative milk yield (P305), age at first calving (AFC), and first calving interval (FCI), in order to adopt these traits as selection criteria for longevity in Gir dairy cattle. Records for 2770 cows born between 1982 and 2008 from six herds in the Brazilian states of Minas Gerais, São Paulo, and Paraíba were analyzed. The (co)variance components were estimated by a Bayesian approach using bivariate animal models. The heritability estimates were 0.37 ± 0.09, 0.23 ± 0.04, 0.26 ± 0.06, and 0.07 ± 0.03 for STAY60, P305, AFC, and FCI, respectively. The genetic correlations of STAY60 with P305, AFC, and FCI were moderate to high, with values of 0.61 (0.17), -0.44 (0.23), and 0.88 (0.13), respectively. STAY60, P305, and AFC exhibited additive genetic variability, and these traits should be considered in selection indices. The indirect selection for longevity through the correlated responses of early-expression traits, such as milk production at first lactation, could be used to improve the ability of animals to remain in the herd.

Multivariate analysis of test-day and total milk yield in goats.

The objective of this study was to estimate genetic parameters for 305-day cumulative milk yield (MY305) and its association with test-day milk yield (TDMY) in Saanen and Alpine goats in order to provide information that allows the use of TDMY as selection criteria. This was done using standard multi-trait and reduced rank models. Data from 1157 lactations, including the first three kiddings, and 5435 test-day records from 683 Saanen and 449 Alpine goats were used. MY305 was analyzed together with TDMY by multi-trait analysis, from the first to tenth test-day, using records of the first three lactations as repeated measures. Three multi-trait models were used: a standard (SM) and two reduced rank models that fitted the first two (PC2) and three (PC3) genetic principal components. Akaike and Schwarz Bayesian information criteria were used to compare models. Heritability for TDMY estimated with the SM ranged from 0.20 to 0.66, whereas the range calculated from the PC2 model was 0.16 to 0.63. Genetic correlations between TDMY and MY305 were positive and moderate to high, ranging from 0.56 to 0.98 when estimated with the SM, and 0.91 to 1.00 when estimated with the PC2. The standard multi-trait model produced estimates that were more accurate than the reduced rank models. Although the SM provided the worst fit according to the two model selection criteria, it was the best in this dataset.

Prospecting major genes in dairy buffaloes.

BACKGROUND: Asian buffaloes (Bubalus bubalis) have an important socio-economic role. The majority of the population is situated in developing countries. Due to the scarce resources in these countries, very few species-specific biotechnology tools exist and a lot of cattle-derived technologies are applied to buffaloes. However, the application of cattle genomic tools to buffaloes is not straightforward and, as results suggested, despite genome sequences similarity the genetic polymorphisms are different. RESULTS: The first SNP chip genotyping platform designed specifically for buffaloes has recently become available. Herein, a genome-wide association study (GWAS) and gene network analysis carried out in buffaloes is presented. Target phenotypes were six milk production and four reproductive traits. GWAS identified SNP with significant associations and suggested candidate genes that were specific to each trait and also genes with pleiotropic effect, associated to multiple traits. CONCLUSIONS: Network predictions of interactions between these candidate genes may guide further molecular analyses in search of disruptive mutations, help select genes for functional experiments and evidence metabolism differences in comparison to cattle. The cattle SNP chip does not offer an optimal coverage of buffalo genome, thereafter the development of new buffalo-specific genetic technologies is warranted. An annotated reference genome would greatly facilitate genetic research, with potential impact to buffalo-based dairy production.

Associations between single nucleotide polymorphisms and carcass traits in Nellore cattle using high-density panels.

The objective of this study was to evaluate associations between single nucleotide polymorphism (SNP) markers and carcass traits measured postmortem in Nellore cattle. Records of loin eye area (LEA) and backfat thickness (BF) from 740 males and records of hot carcass weight (HCW) from 726 males were analyzed. All of the animals were genotyped using the BovineHD BeadChip. Association analyses were performed by the restricted maximum likelihood method that considered one SNP at a time. Significant SNPs were identified on chromosomes 2 and 6 for LEA and on chromosomes 7, 1, and 2 for BF. For HCW, associations with SNPs were found on chromosomes 13, 14, and 28, in addition to genome regions that were directly related to this trait, such as the EFCAB8 and VSTM2L genes, and to bone development (RHOU). Some SNPs were located in very close proximity to genes involved in basal metabolism (BLCAP, NNAT, CTNNBL1, TGM2, and LOC100296770) and the immune system (BPI).

Short communication: Variable number of tandem repeat polymorphisms in DGAT1 gene of buffaloes (Bubalus bubalis) is associated with milk constituents.

The diacylglycerol-O-transferase 1 gene is a positional and functional candidate for milk composition traits. The objective of this study was to evaluate the segregation of the variable number of tandem repeat polymorphisms in the regulatory region of diacylglycerol-O-transferase 1 gene in a water buffalo herd, and to assess the association of this mutation with milk production traits. For this purpose, 196 Murrah buffalo cows were genotyped by PCR. The association of the marker with total milk, fat, and protein yields at 305 d of lactation, milk fat and protein percentage, and somatic cell scores were evaluated by single-trait analyses using a generalized mixed model. Two segregating alleles were identified in the population. The allele with 2 repeats affected fat percentage favorably. The present results suggest that this polymorphism is an interesting marker to include in the genetic evaluation of buffaloes.

Multiple-trait genomic evaluation for milk yield and milk quality traits using genomic and phenotypic data in buffalo in Brazil.

The objective of this study was to compare the multi-trait model using pedigree information and a model using genomic information in addition to pedigree information. We used data from 5896 lactations of 2021 buffalo cows, of which 384 were genotyped using the Illumina Infinium(®) bovine HD BeadChip, considering seven traits related to milk yield (MY305), fat (FY305), protein (PY305), and lactose (LY305), percentages of fat (%F) and protein (%P), and somatic cell score (SCS). We carried out two analyses, one using phenotype and pedigree information (matrix A) and the other using the relationship matrix based on pedigree and genomics information (a single step, matrix H). The (co)variance components were estimated using multiple-trait analysis by the Bayesian inference method. The model included the fixed effects of contemporary groups (herd-year and calving season), and the age of cow at calving as (co)variables (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The estimates of heritability using matrix A were 0.25, 0.22, 0.26, 0.25, 0.37, 0.42, and 0.17, while using matrix H the heritability values were 0.25, 0.24, 0.26, 0.26, 0.38, 0.47, and 0.18 for MY305, FY305, PY305, LY305, %F, %P, and SCS, respectively. The estimates of breeding values in the two analyses were similar for the traits studied, but the accuracies were greater when using matrix H (higher than 8% in the traits studied). Therefore, the use of genomic information in the analyses improved the accuracy.

Polymorphisms in the GHRL gene and their associations with traits of economic interest in beef cattle.

The hormone ghrelin is produced in the stomach wall, has an orexigenic function, stimulates growth hormone secretion, and affects the energy balance of the animal. Therefore, the ghrelin gene (GHRL) is considered to be a good candidate marker for the identification of traits of great economic importance in cattle, such as those associated with feed intake, growth, and carcass quality. The use of molecular genetic markers associated with such traits permits the earlier and more accurate identification of superior animals, thus reducing the interval between generations, and increasing the genetic gain. Six SNPs were found in the GHRL gene, located in intron 3, intron 4, and exon 5. The positions of the SNPs on the gene and the substitutions were: g.2184A>G, g.2347T>C, g.4469T>C, g.4548A>G, g.4663T>C, and g.4729T>C (GenBank accession No. JX565585). After analysis of linkage disequilibrium, association tests were performed between four SNPs with the traits year weight for males, yearling weight for females, dry matter intake, loin eye area, and rump fat thickness (P ≤ 0.05). Therefore, GHRL is an important candidate gene that may be used to identify genetic variations that influence traits of economic importance in beef cattle.

Genetic association of growth traits with carcass and meat traits in Nellore cattle.

The aim of this study was to estimate genetic and phenotypic associations of growth traits with carcass and meat traits in Nellore cattle. Data from male and female animals were used for weaning weight (WW; N = 241,416), yearling weight (YW, N = 126,596), weight gain from weaning to yearling (GWY, N = 78,687), and yearling hip height (YHH, N = 90,720), respectively; 877 male animals were used for hot carcass weight (HCW) and 884 for longissimus muscle area (LMA), backfat thickness (BT), marbling score (MS), and shear force (SF). The variance components were estimated by the restricted maximum likelihood method using three-trait animal models that included WW. The model for WW included direct and maternal additive genetic, maternal permanent environmental, and residual effects as random effects; contemporary group as fixed effects; and age of dam at calving and age of animal as covariates (linear and quadratic effects). For the other traits, maternal effects and the effect of age of dam at calving were excluded from the model. Heritability ranged from 0.10 ± 0.12 (LMA) to 0.44 ± 0.007 (YW). Genetic correlations ranged from -0.40 ± 0.38 (WW x LMA) to 0.55 ± 0.10 (HCW x YW). Growth, carcass, and meat traits have sufficient genetic variability to be included as selection criteria in animal breeding programs.

Association between single-nucleotide polymorphisms and milk production traits in buffalo.

The aim of this study was to identify single-nucleotide polymorphisms (SNPs) in buffaloes associated with milk yield and content, in addition to somatic cell scores based on the cross-species transferability of SNPs from cattle to buffalo. A total of 15,745 SNPs were analyzed, of which 1562 showed 1% significance and 4742 with 5% significance, which were associated for all traits studied. After application of Bonferroni's correction for multiple tests of the traits analyzed, we found 2 significant SNPs placed on cattle chromosomes BTA15 and BTA20, which are homologous to buffalo chromosomes BBU16 and BBU19, respectively. In this genome association study, we found several significant SNPs affecting buffalo milk production and quality. Furthermore, the use of the high-density bovine BeadChip was suitable for genomic analysis in buffaloes. Although extensive chromosome arm homology was described between cattle and buffalo, the exact chromosomal position of SNP markers associated with these economically important traits in buffalo can be determined only through buffalo genome sequencing.

Random regression models using different functions to model milk flow in dairy cows.

We analyzed 75,555 test-day milk flow records from 2175 primiparous Holstein cows that calved between 1997 and 2005. Milk flow was obtained by dividing the mean milk yield (kg) of the 3 daily milking by the total milking time (min) and was expressed as kg/min. Milk flow was grouped into 43 weekly classes. The analyses were performed using a single-trait Random Regression Models that included direct additive genetic, permanent environmental, and residual random effects. In addition, the contemporary group and linear and quadratic effects of cow age at calving were included as fixed effects. Fourth-order orthogonal Legendre polynomial of days in milk was used to model the mean trend in milk flow. The additive genetic and permanent environmental covariance functions were estimated using random regression Legendre polynomials and B-spline functions of days in milk. The model using a third-order Legendre polynomial for additive genetic effects and a sixth-order polynomial for permanent environmental effects, which contained 7 residual classes, proved to be the most adequate to describe variations in milk flow, and was also the most parsimonious. The heritability in milk flow estimated by the most parsimonious model was of moderate to high magnitude.

Water buffalo genome characterization by the Illumina BovineHD BeadChip.

To define the best strategies for genomic association studies and genomic selection, it is necessary to determine the extent of linkage disequilibrium (LD) and the genetic structure of the study population. The current study evaluated the transference of genomic information contained in the Illumina BovineHD BeadChip from cattle to buffaloes, and assessed the extent of the LD in buffaloes. Of the 688,593 bovine single nucleotide polymorphism (SNP) that were successfully genotyped from the 384 buffalo samples, only 16,580 markers were polymorphic, and had minor allele frequencies greater than 0.05. A total of 16,580 polymorphic SNPs were identified, which were uniformly distributed throughout the autosomes, because the density and mean distance between markers were similar for all autosomes. The average minor allele frequency for the 16,580 SNPs was 0.23. The overall mean LD for pairs of adjacent markers was 0.29 and 0.71, when measured as for r2 and |D'|, respectively. The 16,580 polymorphic SNPs were matched to Bos taurus chromosome in the current bovine genome assembly (Btau 4.2), and could be utilized in association studies. In conclusion, the Illumina BovineHD BeadChip contains approximately 16,580 polymorphic markers for the water buffalo, which are broadly distributed across the genome. These data could be used in genomic association and genomic selection studies; however, it might be necessary to develop a panel with specific SNP markers for water buffaloes.