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.

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.

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.

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.

Estimates of genetic parameters for growth traits in Brahman cattle using random regression and multitrait models.

Random regression models (RRM) and multitrait models (MTM) were used to estimate genetic parameters for growth traits in Brazilian Brahman cattle and to compare the estimated breeding values obtained by these 2 methodologies. For RRM, 78,641 weight records taken between 60 and 550 d of age from 16,204 cattle were analyzed, and for MTM, the analysis consisted of 17,385 weight records taken at the same ages from 12,925 cattle. All models included the fixed effects of contemporary group and the additive genetic, maternal genetic, and animal permanent environmental effects and the quadratic effect of age at calving (AAC) as covariate. For RRM, the AAC was nested in the animal's age class. The best RRM considered cubic polynomials and the residual variance heterogeneity (5 levels). For MTM, the weights were adjusted for standard ages. For RRM, additive heritability estimates ranged from 0.42 to 0.75, and for MTM, the estimates ranged from 0.44 to 0.72 for both models at 60, 120, 205, 365, and 550 d of age. The maximum maternal heritability estimate (0.08) was at 140 d for RRM, but for MTM, it was highest at weaning (0.09). The magnitude of the genetic correlations was generally from moderate to high. The RRM adequately modeled changes in variance or covariance with age, and provided there was sufficient number of samples, increased accuracy in the estimation of the genetic parameters can be expected. Correlation of bull classifications were different in both methods and at all the ages evaluated, especially at high selection intensities, which could affect the response to selection.

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.

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.

Polymorphisms in the ghrelin gene and their associations with milk yield and quality in water buffaloes.

Ghrelin is a gastrointestinal hormone that acts in releasing growth hormone and influences the body general metabolism. It has been proposed as a candidate gene for traits such as growth, carcass quality, and milk production of livestock because it influences feed intake. In this context, the aim of this study was to verify the existence of polymorphisms in the ghrelin gene and their associations with milk, fat and protein yield, and percentage in water buffaloes (Bubalus bubalis). A group of 240 animals was studied. Five primer pairs were used and 11 single nucleotide polymorphisms (SNP) were found in the ghrelin gene by sequencing. The animals were genotyped for 8 SNP by PCR-RFLP. The SNP g.960G>A and g.778C>T were associated with fat yield and the SNP g.905T>C was associated with fat yield and percentage and protein percentage. These SNP are located in intronic regions of DNA and may be in noncoding RNA sites or affect transcriptional efciency. The ghrelin gene in buffaloes influences milk fat and protein synthesis. The polymorphisms observed can be used as molecular markers to assist selection.

Identification of polymorphisms in the osteopontin gene and their associations with certain semen production traits of water buffaloes in the Brazilian Amazon.

The osteopontin gene may influence the fertility of water buffaloes because it is a protein present in sperm. The aim of this work was to identify polymorphisms in this gene and associate them with fertility parameters of animals kept under extensive grazing. A total of 306 male buffaloes older than 18 months, from two farms, one in the state of Amapá and the other in the state of Pará, Brazil were used in the study. Seven SNPs were identified in the regions studied. The polymorphisms were in gene positions 1478, 1513 and 1611 in the region 5'upstrem and positions 6690, 6737, 6925 and 6952 in the region amplified in intron 5. The SNPs were associated with the traits, namely scrotal circumference, scrotal volume, sperm motility, sperm concentration and sperm pathology. There were significant SNPs (p < 0.05) for all the traits. The SNP 6690 was significant for scrotal circumference, sperm concentration, sperm motility and sperm pathology and the SNP 6737 for scrotal volume. The genotype AA of SNP 6690 presented the highest averages for scrotal circumference, sperm concentration and motility and the lowest total number of sperm pathologies. For the scrotal volume trait, the animals with the largest volume were correlated with the presence of the genotype GG of SNP 6737. These results indicate a significance of the osteopontin gene as it seems to exert a substantial influence on the semen production traits of male buffaloes.

Population structure and effects of inbreeding on milk yield and quality of Murrah buffaloes.

To provide data for conservation, selection, and expansion programs of buffalo herds, this study evaluated the history of a population of Murrah buffaloes based on population structure and the effect of inbreeding on accumulated 305-d milk yield (MY), fat yield (FY), protein yield (PY), mozzarella production (MProd), and somatic cell score (SCS). The usefulness of including the individual inbreeding coefficient (F) or individual increase in inbreeding coefficient (ΔF) in the model to describe inbreeding depression was evaluated. Pedigree information from 8,054 animals born between 1976 and 2008 and 4,497 lactation records obtained from 12 herds were used. The realized effective population size was 40.10 ± 1.27, and the mean F of the entire population was 2.14%. The ratio between the number of founders and ancestors demonstrated the existence of a bottleneck in the pedigree of this population, which may contribute to a reduction of genetic diversity. The effect of F on MY, FY, PY, MProd, and SCS was -1.005 kg, -0.299 kg, -0.246 kg, -1.201 kg, and -0.002 units, and the effect of ΔF transformed to equivalent F (%) for a mean of 2.57 equivalent generations was -4.287 kg, -0.581 kg, -0.383 kg, -2.001 kg, and -0.007 units, respectively. The inbreeding depression observed may have important economic repercussions for production systems. The ΔF can be considered the better of the two indicators of inbreeding depression due to its properties that prevent underestimation of this effect. A designed mating system to avoid inbreeding may be applied to this population to maintain genetic diversity.

Genetic parameter estimates for buffalo milk yield, milk quality and mozzarella production and Bayesian inference analysis of their relationships.

Buffalo milk has excellent physical and chemical qualities as a consequence of the high percentage of constituents. This milk property is desirable for the dairy industry because it facilitates manufacture of mozzarella cheese. We estimated genetic parameters for milk yield, milk fat and protein and their effects on mozzarella cheese production using Bayesian inference. Using information from 4907 lactation records of buffaloes, genetic and non-genetic parameters were estimated for accumulated 305-day milk yield (MY), milk fat (%F) and protein (%P) percentages and mozzarella production per lactation (MP). The (co)variance components were obtained by Bayesian inference using a multiple trait model, which included as fixed effects contemporary group, milking number and buffalo age at calving as covariables (linear and quadratic), along with the additive genetic, permanent environmental and residual random effects. Mean a posteriori heritability distributions for MY, %F, %P, and MP were 0.25, 0.30, 0.38, and 0.23, respectively. The genetic correlation estimates between MY with %P and %F were negative and moderate. Positive genetic correlation estimates varying from 0.19 (%P/MP) to 0.95 (MY/MP) were obtained among the traits. Milk yield, milk components, and mozzarella production in Murrah buffaloes have enough genetic variation for selection purposes. We conclude that selection to increase milk yield would be effective in improving mozzarella production.

Genetic parameters for buffalo milk yield and milk quality traits using Bayesian inference.

The availability of accurate genetic parameters for important economic traits in milking buffaloes is critical for implementation of a genetic evaluation program. In the present study, heritabilities and genetic correlations for fat (FY305), protein (PY305), and milk (MY305) yields, milk fat (%F) and protein (%P) percentages, and SCS were estimated using Bayesian methodology. A total of 4,907 lactations from 1,985 cows were used. The (co)variance components were estimated using multiple-trait analysis by Bayesian inference method, applying an animal model, through Gibbs sampling. The model included the fixed effects of contemporary groups (herd-year and calving season), number of milking (2 levels), and age of cow at calving as (co)variable (quadratic and linear effect). The additive genetic, permanent environmental, and residual effects were included as random effects in the model. The posterior means of heritability distributions for MY305, FY305, PY305, %F, P%, and SCS were 0.22, 0.21, 0.23, 0.33, 0.39, and 0.26, respectively. The genetic correlation estimates ranged from -0.13 (between %P and SCS) to 0.94 (between MY305 and PY305). The permanent environmental correlation estimates ranged from -0.38 (between MY305 and %P) to 0.97 (between MY305 and PY305). Residual and phenotypic correlation estimates ranged from -0.26 (between PY305 and SCS) to 0.97 (between MY305 and PY305) and from -0.26 (between MY305 and SCS) to 0.97 (between MY305 and PY305), respectively. Milk yield, milk components, and milk somatic cells counts have enough genetic variation for selection purposes. The genetic correlation estimates suggest that milk components and milk somatic cell counts would be only slightly affected if increasing milk yield were the selection goal. Selecting to increase FY305 or PY305 will also increase MY305, %P, and %F.