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The aim of this study was to quantify, identify, evaluate antimicrobial resistance, and characterize the virulence factors of enteropathogenic (EPEC), Shiga-toxigenic (STEC), and enterohemorrhagic (EHEC) Escherichia coli in raw milk (RM) and legal (LMFC) and illegal (IMFC) Minas Frescal cheeses in southern and northeast Brazil. Illegal cheeses are those made without official inspection service or sanitary surveillance. We evaluated samples of RM produced in Paraná (southern) and Maranhão (northeast) States, LMFC produced using pasteurized milk in inspected industries, and IMFC potentially produced with raw milk. Mean total coliform counts were 8.4 × 104 cfu/mL for RM, 1.4 × 107 cfu/mL for LMFC, and 2.9 × 107 cfu/mL for IMFC. Mean E. coli counts were 2.4 × 103 cfu/mL for RM, 1.9 × 102 cfu/mL for LMFC, and 1.1 × 105 cfu/mL for IMFC. Among the 205 E. coli isolates from RM, 9.75% were identified as EPEC, mainly (90%) in samples from Paraná. Of the total isolates from the cheese samples, 97.4% (n = 111) came from IMFC, of which 1.8 and 2.7% were identified as EPEC and STEC, respectively; no EHEC was detected. The phylogenetic group A (60%) and typical EPEC (68%) predominated, which confirms the possible human origin of pathogenic isolates in RM and IMFC. Of these, 50% were resistant to at least one antibiotic, and streptomycin was the antimicrobial with the highest number (8) of EPEC and STEC resistant isolates. This study reports the first isolation of serogroup O28ac in Brazilian milk. We found no predominance of a specific serogroup of EPEC or STEC in milk or cheese or clonal isolates in the same sample, indicating different origins of the contamination in these products, presumably mostly related to poor hygienic handling. [ABSTRACT FROM AUTHOR]

An alternative control for gastrointestinal nematode (GIN) infection in goats can be achieved by genetic improvement of the host resistance through identification of genes controlling the resistance mechanisms and their use in breeding programs under a marker-assisted selection or gene introgression frameworks. In this context, we aimed to develop genome wide association studies (GWAS) for resistance to H. contortus in Creole goats from Guadeloupe to identify possible candidate genes associated with GIN resistance in this population. Resistance was characterized by the fecal egg counting (FEC). A total of 182 Creole goats were phenotyped for FEC and genotyped through Illumina Goat SNP50 BeadChip. After SNP quality control analysis, 46,643 SNP markers were used for GWAS. The significant associations were identified by fitting a linear mixed model. A total of seven QTL (on the chromosomes 4, 6, 11, and 17) associated to FEC were reported and candidate genes recording was performed at these positions. The identified genes were related to the intestine damage ( PROM1 ), inflammation process ( FGFBP1 ), immune response ( LIMCH1 ), hemorrhage control ( ADAMTS3 ), and muscle weakness ( SUCLG1 ). Network analysis provided annotation results linking all identified candidate genes, which are biologically related to resistance mechanisms approaching H. contortus infections. [ABSTRACT FROM AUTHOR]

We studied the effect of including GWAS results on the accuracy of single- and multipopulation genomic predictions. Phenotypes (backfat thickness) and genotypes of animals from two sire lines ( SL1, n = 1146 and SL3, n = 1264) were used in the analyses. First, GWAS were conducted for each line and for a combined data set (both lines together) to estimate the genetic variance explained by each SNP. These estimates were used to build matrices of weights (D), which was incorporated into a GBLUP method. Single population evaluated with traditional GBLUP had accuracies of 0.30 for SL1 and 0.31 for SL3. When weights were employed in GBLUP, the accuracies for both lines increased (0.32 for SL1 and 0.34 for SL3). When a multipopulation reference set was used in GBLUP, the accuracies were higher (0.36 for SL1 and 0.32 for SL3) than in single-population prediction. In addition, putting together the multipopulation reference set and the weights from the combined GWAS provided even higher accuracies (0.37 for SL1, and 0.34 for SL3). The use of multipopulation predictions and weights estimated from a combined GWAS increased the accuracy of genomic predictions. [ABSTRACT FROM AUTHOR]

The objective of this work was to evaluate the efficiency of the supervised independent component regression ( SICR) method for the estimation of genomic values and the SNP marker effects for boar taint and carcass traits in pigs. The methods were evaluated via the agreement between the predicted genetic values and the corrected phenotypes observed by cross-validation. These values were also compared with other methods generally used for the same purposes, such as RR- BLUP, SPCR, SPLS, ICR, PCR and PLS. The SICR method was found to have the most accurate prediction values. [ABSTRACT FROM AUTHOR]

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations ( MLOG); a linear model without transformation of the observations ( MLIN); and a generalized linear Poisson model with residual term ( MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion ( DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. [ABSTRACT FROM AUTHOR]

Pig is an important animal for meat production; this is generally associated with characteristics determined prenatally during myogenesis. Expressed sequence tags ( EST) can provide direct information on the transcriptome and indirect information on the relation between the genome and phenotype, giving information about differentially expressed genes ( DEG). In this work, the identification and annotation of DEG from EST libraries of three pig breeds ( Duroc, Large White and Local Breed Piau) were performed followed by real-time PCR analyses during pre- and postnatal stages (21, 40, 70 and 90 days of pregnancy and 107, 121 and 171 days postnatal) from commercial breed animals for analysis of genes expression levels. Therefore, 34 genes differentially expressed were identified, of which 21 grouped in a network related with muscle development. From this, the expression profile of 13 genes was measured, to confirm their relationship with myogenesis like ANKRD2, MYBPC1, NEB and MYL2. These genes showed a prenatal high expression in this study. Besides, novels candidates for muscle development ( TP53 and DCTN1) were listed. These findings can contribute to better explaining gene function mechanism and are helpful in uncovering the pathways that mediate pre- and postnatal skeletal muscle development in vertebrates. [ABSTRACT FROM AUTHOR]

The progenies of international bulls in diverse climatic conditions and management levels may lead to different expressions of their genetic potential resulting in a re-ranking of these bulls. Therefore, evaluate the presence of genotype by environment interaction (G × E) within and across countries is important to guide the decision-making on alternative selection strategies. Thus, a two-step reaction norm (RN) approach was used to investigate the presence of G × E in Portuguese and Brazilian Holstein cattle. In step 1, we performed a within-country genetic evaluation using an autoregressive model to obtain precorrected phenotypes and environmental gradients (herd test-day solutions, HTD levels). In step 2, the precorrected phenotypes were considered as two distinct traits in a bi-trait RN model to estimate variance components across HTD levels, genetic correlation between HTD levels in Portugal and Brazil, and RN of the estimated breeding values. Additionally, the genetic correlation between countries using a bi-trait random regression (RR) sire model was obtained. In step 1, genetic additive variance for milk yield (MY) in Portugal was 14.1% higher than in Brazil. For somatic cell score (SCS), the genetic additive variance in Portugal was 12.7% lower than in Brazil. Although similar heritability estimates for SCS were observed in both countries, MY heritabilities were 0.31 for Portugal and 0.23 for Brazil. Genetic correlations (SD) between both countries obtained using RR sire model were 0.78 (0.051) for MY and 0.75 (0.062) for SCS. In step 2, MY genetic correlations among HTD levels within countries were higher than 0.94 for Portugal and 0.98 for Brazil. Somatic cell score genetic correlations among HTD levels ranged from 0.70 to 0.99 for Portugal and from 0.84 to 0.99 for Brazil. The average (SD) of genetic correlation estimates between Portuguese and Brazilian HTD levels were 0.74 (0.009) for MY and 0.57 (0.060) for SCS. These results suggest the presence of G × E for MY and SCS of Holstein cattle between both countries. Although there was no indication of G × E between Brazilian herd environments, the low genetic correlation for SCS indicates potential re-ranking of bulls between extreme environmental gradient in Portugal. Overall, the results of this study evidence the importance of national and international genetic evaluation systems to assist dairy farmers in the selection of the best genotypes to obtain the expected returns from investments in imported semen and to realize genetic progress in dairy populations under local environmental conditions. [ABSTRACT FROM AUTHOR]

Milk fat composition has important implications in the nutritional and processing properties of milk. Additionally, milk fat composition is associated with cow physiological and health status. The main objectives of this study were (1) to estimate genetic parameters for 5 milk fatty acid (FA) groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted from milk infrared spectra using a large data set; (2) to predict genomic breeding values using a longitudinal single-step genomic BLUP approach; and (3) to conduct a single-step GWAS aiming to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA, and consequently, to understand the underlying biology of these traits. We used 629,769 test-day records of 201,465 first-parity Holstein cows from 6,105 herds. A total of 8,865 genotyped (Illumina BovineSNP50K BeadChip, Illumina, San Diego, CA) animals were considered for the genomic analyses. The average daily heritability ranged from 0.24 (unsaturated FA) to 0.47 (medium-chain and saturated FA). The reliability of the genomic breeding values ranged from 0.56 (long-chain fatty acid) to 0.74 (medium-chain fatty acid) when using the default τ and ω scaling parameters, whereas it ranged from 0.58 (long-chain fatty acid) to 0.73 (short-chain fatty acid) when using the optimal τ and ω values (i.e., τ = 1.5 and ω = 0.6), as defined in a previous study in the same population. Relevant chromosomal regions were identified in Bos taurus autosomes 5 and 14. The proportion of the variance explained by 20 adjacent single nucleotide polymorphisms ranged from 0.71% (saturated FA) to 15.12% (long-chain FA). Important candidate genes and pathways were also identified. In summary, our results contribute to a better understanding of the genetic architecture of predicted milk FA in dairy cattle and reinforce the relevance of using genomic information for genetic analyses of these traits. [ABSTRACT FROM AUTHOR]

Caprine arthritis encephalitis (CAE) is a chronic disease caused by a retrovirus from the Lentivirus genus. No effective vaccines or treatments exist, and therefore genetic selection for CAE resistance might be a feasible alternative. To our best knowledge, no other studies have investigated the genetic architecture of CAE resistance in dairy goats. In this context, this study was designed to estimate genetic parameters for CAE infection in Alpine and Saanen goats using a Bayesian threshold model. A total of 542 adult goats (and >3-generation pedigree), which were group-housed in a population with high CAE prevalence, were tested based on a serological infection assessment test (negative = 1 or positive = 2) and used for this study. Genetic parameters were estimated using the BLUPF90 family programs. There was considerable genetic variability for CAE resistance, and pedigree-based heritability was significantly different from zero (0.026 < heritability < 0.128). Our findings indicate that the prevalence of CAE in goat herds can be reduced or eliminated through direct genetic selection for CAE resistance in addition to proper management strategies. [ABSTRACT FROM AUTHOR]

Milk fat content and fatty acid (FA) composition have great economic value to the dairy industry as they are directly associated with taste and chemical-physical characteristics of milk and dairy products. In addition, consumers' choices are not only based on the nutritional aspects of food, but also on products known to promote better health. Milk FA composition is also related to the metabolic status and physiological stages of cows and thus can also be used as indicator for other novel traits of interest (e.g., metabolic diseases and methane yield). Genetic selection is a promising alternative to manipulate milk FA composition. In this study, we aimed to (1) estimate time-dependent genetic parameters for 5 milk FA groups (i.e., short-chain, medium-chain, long-chain, saturated, and unsaturated) predicted based on milk mid-infrared spectroscopy, for Canadian Ayrshire and Jersey breeds, and (2) conduct a time-dependent, single-step genome-wide association study to identify genomic regions, candidate genes, and metabolic pathways associated with milk FA. We analyzed 31,709 test-day records of 9,648 Ayrshire cows from 268 herds, and 34,341 records of 11,479 Jersey cows from 883 herds. The genomic database contained a total of 2,330 Ayrshire and 1,019 Jersey animals. The average daily heritability ranged from 0.18 (long-chain FA) to 0.34 (medium-chain FA) in Ayrshire, and from 0.25 (long-chain and unsaturated FA) to 0.52 (medium-chain and saturated FA) in Jersey. Important genomic regions were identified in Bos taurus autosomes BTA3, BTA5, BTA12, BTA13, BTA14, BTA16, BTA18, BTA20, and BTA21. The proportion of the variance explained by 20 adjacent SNP ranged from 0.71% (saturated FA) to 1.11% (long-chain FA) in Ayrshire, and from 0.70% (unsaturated FA) to 3.09% (medium-chain FA) in Jersey cattle. Important candidate genes and pathways were also identified, such as the PTK2 and TRAPPC9 genes, associated with milk fat percentage, and HMGCS , FGF10 , and C6 genes, associated with fertility traits and immune response. Our findings on the genetic parameters and candidate genes contribute to a better understanding of the genetic architecture of milk FA composition in Ayrshire and Jersey dairy cattle. [ABSTRACT FROM AUTHOR]

The multiple-lactation autoregressive test-day (AR) model is the adopted model for the national genetic evaluation of dairy cattle in Portugal. Under this model, animals' permanent environment effects are assumed to follow a first-order autoregressive process over the long (auto-correlations between parities) and short (auto-correlations between test-days within lactation) terms. Given the relevance of genomic prediction in dairy cattle, it is essential to include marker information in national genetic evaluations. In this context, we aimed to evaluate the feasibility of applying the single-step genomic (G)BLUP to analyze milk yield using the AR model in Portuguese Holstein cattle. In total, 11,434,294 test-day records from the first 3 lactations collected between 1994 and 2017 and 1,071 genotyped bulls were used in this study. Rank correlations and differences in reliability among bulls were used to compare the performance of the traditional (A-AR) and single-step (H-AR) models. These 2 modeling approaches were also applied to reduced data sets with records truncated after 2012 (deleting daughters of tested bulls) to evaluate the predictive ability of the H-AR. Validation scenarios were proposed, taking into account young and proven bulls. Average EBV reliabilities, empirical reliabilities, and genetic trends predicted from the complete and reduced data sets were used to validate the genomic evaluation. Average EBV reliabilities for H-AR (A-AR) using the complete data set were 0.52 (0.16) and 0.72 (0.62) for genotyped bulls with no daughters and bulls with 1 to 9 daughters, respectively. These results showed an increase in EBV reliabilities of 0.10 to 0.36 when genomic information was included, corresponding to a reduction of up to 43% in prediction error variance. Considering the 3 validation scenarios, the inclusion of genomic information improved the average EBV reliability in the reduced data set, which ranged, on average, from 0.16 to 0.26, indicating an increase in the predictive ability. Similarly, empirical reliability increased by up to 0.08 between validation tests. The H-AR outperformed A-AR in terms of genetic trends when unproven genotyped bulls were included. The results suggest that the single-step GBLUP AR model is feasible and may be applied to national Portuguese genetic evaluations for milk yield. [ABSTRACT FROM AUTHOR]

Application of random regression models (RRM) in a 2-step genomic prediction might be a feasible way to select young animals based on the complete pattern of the lactation curve. In this context, the prediction reliability and bias of genomic estimated breeding value (GEBV) for milk, fat, and protein yields and somatic cell score over days in milk (DIM) using a 2-step genomic approach were investigated. In addition, the effect of including cows in the training and validation populations was investigated. Estimated breeding values for each DIM (from 5 to 305 d) from the first 3 lactations of Holstein animals were deregressed and used as pseudophenotypes in the second step. Individual additive genomic random regression coefficients for each trait were predicted using RRM and genomic best linear unbiased prediction and further used to derive GEBV for each DIM. Theoretical reliabilities of GEBV obtained by the RRM were slightly higher than theoretical reliabilities obtained by the accumulated yield up to 305 d (P305). However, validation reliabilities estimated for GEBV using P305 were higher than for GEBV using RRM. For all traits, higher theoretical and validation reliabilities were estimated when incorporating genomic information. Less biased GEBV estimates were found when using RRM compared with P305, and different validation reliability and bias patterns for GEBV over time were observed across traits and lactations. Including cows in the training population increased the theoretical reliabilities and bias of GEBV; nonetheless, the inclusion of cows in the validation population does not seem to affect the regression coefficients and the theoretical reliabilities. In summary, the use of RRM in 2-step genomic prediction produced fairly accurate GEBV over the entire lactation curve for all analyzed traits. Thus, selecting young animals based on the pattern of lactation curves seems to be a feasible alternative in genomic selection of Holstein cattle for milk production traits. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the inclusion of physically effective fiber (peNDF) from sugarcane in feedlot diets containing whole corn grain on ingestive, digestive, and ruminal parameters. Five rumen-cannulated Nellore bulls (BW = 393 ± 9 kg) distributed in an incomplete 5 × 5 Latin square received diets containing 5% (D5), 15% (D15), 25% (D25), or 35% (D35) sugarcane. All diets included a mineral-protein supplement. Omasal digesta collection and fecal spot collection were carried out to estimate ruminal and total digestibility. The ruminal contents were emptied to calculate ingestion (ki), passage (kp), and digestion (kd) rates. The linear, quadratic, and cubic effects of including sugarcane (i.e., different peNDF contents) were evaluated using orthogonal contrasts. The intake of total digestible nutrients (TDN , P = 0.06), dry matter (DM , P = 0.03), and organic matter (OM , P = 0.03) showed a quadratic pattern, with the highest estimated values occurring between 6.14 and 10.2% of peNDF. Ruminal digestibility [%, (P = 0.01) and kg/d, (P = < 0.01)] and total digestibility (kg/d, P = 0.03) of OM, ki (P = < 0.01), kp (P = 0.01) and kd (P = < 0.01) rates of OM, ki (P = 0.07), kp (P = 0.01), and kd (P = 0.05) rates of neutral detergent fiber (NDF) and microbial crude protein synthesis (MPS) (P = < 0.01) were also maximized, with inclusion levels between 6.14 and 10.2% of peNDF, although the efficiency of MPS tended to increase linearly (P = 0.08). The total concentration of volatile fatty acids (VFA) decreased linearly (P = 0.03), while the rumen ammonia pool [concentration (mmol/L) x volume of rumen liquid (L)] increased linearly (P = < 0.01). Ruminal pH responded linearly with the addition of sugarcane to the diet. We conclude that feedlot animals might benefit from diets containing between 6.14 and 10.2% of peNDF when whole corn grain diets are used. • Levels of 6.14 to 10.2% peNDF in finishing diets improve TDN intake. • Inclusion of peNDF in whole corn diets improves ruminal pH and fibre digestion. • Improvement in intake and ruminal pH allow greater microbial synthesis. • Fibre content in the diet is directly related to microbial efficiency. [ABSTRACT FROM AUTHOR]

Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression. [ABSTRACT FROM AUTHOR]

We performed genome-wide association analyses for milk, fat, and protein yields and somatic cell score based on lactation stages in the first 3 parities of Canadian Ayrshire, Holstein, and Jersey cattle. The genome-wide association analyses were performed considering 3 different lactation stages for each trait and parity: from 5 to 95, from 96 to 215, and from 216 to 305 d in milk. Effects of single nucleotide polymorphisms (SNP) for each lactation stage, trait, parity, and breed were estimated by back-solving the direct breeding values estimated using the genomic best linear unbiased predictor and single-trait random regression test-day models containing only the fixed population average curve and the random genomic curves. To identify important genomic regions related to the analyzed lactation stages, traits, parities and breeds, moving windows (SNP-by-SNP) of 20 adjacent SNP explaining more than 0.30% of total genetic variance were selected for further analyses of candidate genes. A lower number of genomic windows with a relatively higher proportion of the explained genetic variance was found in the Holstein breed compared with the Ayrshire and Jersey breeds. Genomic regions associated with the analyzed traits were located on 12, 8, and 15 chromosomes for the Ayrshire, Holstein, and Jersey breeds, respectively. Especially for the Holstein breed, many of the identified candidate genes supported previous reports in the literature. However, well-known genes with major effects on milk production traits (e.g., diacylglycerol O-acyltransferase 1) showed contrasting results among lactation stages, traits, and parities of different breeds. Therefore, our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the analyzed traits across breeds, parities, and lactation stages. Further functional studies are needed to validate our findings in independent populations. [ABSTRACT FROM AUTHOR]

An important goal in animal breeding is to improve longitudinal traits; that is, traits recorded multiple times during an individual's lifetime or physiological cycle. Longitudinal traits were first genetically evaluated based on accumulated phenotypic expression, phenotypic expression at specific time points, or repeatability models. Until now, the genetic evaluation of longitudinal traits has mainly focused on using random regression models (RRM). Random regression models enable fitting random genetic and environmental effects over time, which results in higher accuracy of estimated breeding values compared with other statistical approaches. In addition, RRM provide insights about temporal variation of biological processes and the physiological implications underlying the studied traits. Despite the fact that genomic information has substantially contributed to increase the rates of genetic progress for a variety of economically important traits in several livestock species, less attention has been given to longitudinal traits in recent years. However, including genomic information to evaluate longitudinal traits using RRM is a feasible alternative to yield more accurate selection and culling decisions, because selection of young animals may be based on the complete pattern of the production curve with higher accuracy compared with the use of traditional parent average (i.e., without genomic information). Moreover, RRM can be used to estimate SNP effects over time in genome-wide association studies. Thus, by analyzing marker associations over time, regions with higher effects at specific points in time are more likely to be identified. Despite the advances in applications of RRM in genetic evaluations, more research is needed to successfully combine RRM and genomic information. Future research should provide a better understanding of the temporal variation of biological processes and their physiological implications underlying the longitudinal traits. [ABSTRACT FROM AUTHOR]

Test-day traits are important for genetic evaluation in dairy cattle and are better modeled by multiple-trait random regression models (RRM). The reliability and bias of genomic estimated breeding values (GEBV) predicted using multiple-trait RRM via single-step genomic best linear unbiased prediction (ssGBLUP) were investigated in the 3 major dairy cattle breeds in Canada (i.e., Ayrshire, Holstein, and Jersey). Individual additive genomic random regression coefficients for the test-day traits were predicted using 2 multiple-trait RRM: (1) one for milk, fat, and protein yields in the first, second, and third lactations, and (2) one for somatic cell score in the first, second, and third lactations. The predicted coefficients were used to derive GEBV for each lactation day and, subsequently, the daily GEBV were compared with traditional daily parent averages obtained by BLUP. To ensure compatibility between pedigree and genomic information for genotyped animals, different scaling factors for combining the inverse of genomic (G-1) and pedigree A22 ( -1 ) relationship matrices were tested. In addition, the inclusion of only genotypes from animals with accurate breeding values (defined in preliminary analysis) was compared with the inclusion of all available genotypes in the analyzes. The ssGBLUP model led to considerably larger validation reliabilities than the BLUP model without genomic information. In general, scaling factors used to combine the G-1 and A22 -1 matrices had small influence on the validation reliabilities. However, a greater effect was observed in the inflation of GEBV. Less inflated GEBV were obtained by the ssGBLUP compared with the parent average from traditional BLUP when using optimal scaling factors to combine the G-1 and A22 -1 matrices. Similar results were observed when including either all available genotypes or only genotypes from animals with accurate breeding values. These findings indicate that ssGBLUP using multiple-trait RRM increases reliability and reduces bias of breeding values of young animals when compared with parent average from traditional BLUP in the Canadian Ayrshire, Holstein, and Jersey breeds. [ABSTRACT FROM AUTHOR]

The aim of this study was to elucidate the differential gene expression in the RNA sequencing transcriptome of isolated perfused udders collected from 4 slaughtered Holstein x Zebu crossbred dairy cows experimentally inoculated with Streptococcus agalactiae. We studied 3 different statistical tools (edgeR, baySeq, and Cuffdiff 2). In summary, 2 quarters of each udder were experimentally inoculated with Strep. agalactiae and the other 2 were used as a control. Mammary tissue biopsies were collected at times 0 and 3 h after infection. The total RNA was extracted and sequenced on an Illumina HiSeq 2000 (Illumina Inc., San Diego, CA). Transcripts were assembled from the reads aligned to the bovine UMD 3.1 reference genome, and the statistical analyses were performed using the previously mentioned tools (edgeR, baySeq, and Cuffdiff 2). Finally, the identified genes were submitted to pathway enrichment analysis. A total of 1,756, 1,161, and 3,389 genes with differential gene expression were identified when using edgeR, baySeq, and Cuffdiff 2, respectively. A total of 122 genes were identified by the overlapping of the 3 methods; however, only the platelet activation presented a significantly enriched pathway. From the results, we suggest the FCER1G, GNAI2, ORAI1, and VASP genes shared among the 3 methods in this pathway for posterior biological validation. [ABSTRACT FROM AUTHOR]

• Unsaturated fatty acids (UFA) supplementation with or without chitosan decreased methane. • Chitosan (CHI) associated with UFA did not influence the ruminal digestibility of nutrients. • Ruminal fermentation was altered with UFA supplementation associated with CHI. • UFA sources associated with CHI alter reticular flows of nutrients. • Chitosan associated UFA change the ruminal kinetics of beef heifers. This study evaluated the effects of supplementation of chitosan and unsaturated fatty acid (UFAs) sources on intake, digestibility, ruminal and nitrogen metabolism, blood metabolites, and feeding behavior of beef heifers. Five crossbred Simental x Zebu heifers (335 ± 53.2 kg of initial BW), ruminally cannulated, were randomly assigned according to a 5 × 5 Latin square design containing the following treatments: 1) CON, the control diet without supplementation; 2) SO, control diet supplemented with 25.3 g/kg of soybean oil; 3) WRS, control diet supplemented with 160 g/kg of whole raw soybean (WRS); 4) SOCHI, SO diet plus 14 g/kg of CHI; 5) WRSCHI, WRS diet plus 14 g/kg of CHI. No interaction effects between CHI and WRS were observed on nutrient intakes and digestibilities. Heifers fed SO, or WRS diets with or without CHI had lower enteric methane (CH 4) emissions (P < 0.01) than those fed CON. Moreover, animals fed SO and WRS had higher CH 4 emissions than those fed SOCHI and WRSCHI. No interaction between CHI and WRS was observed on nitrogen balance. However, heifers fed SO or WRS diets with or without CHI had lower nitrogen (N) intake (P = 0.001) and fecal N (P = 0.015) than those fed CON. Besides, animals fed SO and WRS diets showed lower retained N (P = 0.010) and efficiency (P = 0.005) than those fed SOCHI and WRSCHI. Heifers fed SO, or WRS diets with or without CHI showed lower rumination efficiencies of dry matter (DM; P < 0.01) and neutral detergent fiber (NDF; P = 0.013) than those fed CON. Heifers fed SO or WRS with or without CHI, showed lower reticular flows of DM (P = 0.049), NDF (P = 0.002), and potentially digestible NDF (P = 0.002) than those fed CON. In addition, animals fed SO or WRS diets with or without CHI showed a lower rumen digestion rate of DM, turnover rates of DM and NDF, and passage rates of DM and pdNDF than those fed CON. The supply of CHI to beef heifers fed diets with SO and WRS alters ruminal fermentation, methane production, nitrogen balance, feeding behavior, and ruminal dynamics. Nevertheless, the results strengthen the evidence that the provision of CHI in beef cattle diets can positively influence the effect of fatty acid sources. Besides, fatty acids sources provided alone have a negative influence on most metabolism parameters in beef heifers. [ABSTRACT FROM AUTHOR]

The aim of this study was to evaluate the effects of the inclusion of palm kernel cake (PKC) in the supplement composition for grazing lambs on intake, digestibility, growth performance, carcass characteristics and fatty acid profile of the meat. Thirty-one non-castrated Santa Inês-crossed male lambs (age = 120 ± 15 d; initial body weight = 20 ± 3.9 kg) were divided into 4 groups, following a completely randomized design. Treatments were 0%, 10%, 20%, and 30% PKC substitution for ground corn and wheat bran in the supplement. Animals were stratified to equalize body weight: 8 animals in treatment 0%; 8 in treatment 10%; 6 in treatment 20%; and 9 in treatment 30%. Lambs were fed for 84 d and grazed a predominantly braquiarão grass ( Urochloa brizantha cv. Marandu) and Tifton 85 ( Cynodon dactylon ) grass pasture. The remainder of the supplement contained soybean meal, wheat bran, ground corn, urea, and mineral salt. The level of supplementation was 1.6% BW per animal/d. There was a linear decrease ( P < 0.01) for total DM intake and pasture intake as the inclusion of PKC in the supplement was increased. Feeding increasing PKC in the supplement did not affect ( P ≥ 0.35) lamb growth performance nor did it affect most carcass characteristics ( P ≥ 0.16). However, it did lower conformation ( P = 0.02) and carcass shrink ( P = 0.03). Palmitic fatty acid decreased (linear; P = 0.04) as PKC fed to lambs increased in the supplement. No other fatty acids were affected ( P ≥ 0.10). Feeding up to 30% PKC in a supplement for grazing lambs reduced DMI without altering average daily gain or economic traits of carcass characteristic. [ABSTRACT FROM AUTHOR]

Abstract: The objective of this study was to evaluate the effects of the inclusion of oregano in the diet of dairy cows on the physicochemical quality of raw milk and the sensory attributes of pasteurized milk. Twelve crossbred Holstein×Zebu cows were divided into three 4×4 Latin squares, and increasing amounts of oregano were added to their diet. Physicochemical analysis of density, cryoscopic index, protein, fat, lactose, total solids extract (TSE), and dry nonfat extracts (DNE) was performed for the raw milk samples. The microbiological quality of pasteurized milk samples was evaluated by performing total and fecal coliform tests. Adding oregano to the diet showed no influence (P>0.05) on the fat, TSE, protein, and cryoscopic index, with mean values of 3.78g/100g, 12.60g/100g, 3.24g/100g, and g −0535 °H, respectively. However, the levels of lactose, DNE, and density were influenced by the amount of oregano (OV) and ranged from 4.82g/100g to 4.64g/100g, 9.22g/100g to 8.88g/100g, and 1.033g/mL to 1.032g/mL, respectively. Based on microbiological analysis, all samples were considered suitable for consumption (<3.0×105 CFU/mL). The sensory attributes of aroma and flavor did not alter the preference (P>0.05). Only a small difference between treatments was observed in the flavor profile for the warmed-over flavor attribute. For the attributes of a sweet aroma, characteristic milk aroma, characteristic milk flavor, and sweet flavor, the intensity ranges were similar. The results showed no changes (P>0.05) in the main components of milk and, therefore, no effect on its sensory attributes. Thus, it is possible to incorporate dry oregano into cattle feed for the purpose of studying its influence on other parameters of milk composition. [Copyright &y& Elsevier]

• Supplementation with monensin and saponins was evaluated in diets for cows. • The combination of saponins with essential oils increased the energy efficiency. • Nutrients digestibility and nitrogen utilization were not affected by the diets. • Monensin decreased ruminal pH and increased rumen ammonia nitrogen concentration. • The long-chain fatty acids profile in cows' milk was not influenced by the diets. This study aimed to evaluate the effects of diet supplementation with monensin and saponins alone or combined with essential oils (EOs) on the nutrient intake and apparent digestibility, rumen fermentation parameters, microbial population, nitrogen balance, ruminal microbial protein synthesis, blood metabolites, and milk composition, yield and fatty acid profile of mid- to late-lactating Jersey cows. Eight ruminally cannulated lactating Jersey cows (average 17.6 ± 5.5 kg/day of milk yield and 100.5 ± 26.6 days of milk (mean ± SD)) were distributed in a replicated 4 × 4 Latin square design with 21-day periods (last seven days for sampling). Treatment sequences were randomly designated to cows and consisted of: (1) CON - Control, no feed additive; (2) SAP - 16 g/cow/day of a supplement based on whole-seed fenugreek powder (variety Fenucold) standardized to diosgenin, one of the major steroidal sapogenins of fenugreek (2000 mg/kg); (3) SAPEO - SAP supplement combined with a blend of natural EOs with major components of carvacrol (2500 mg/kg), cinnamaldehyde (5600 mg/kg) and limonene (3000 mg/kg); and (4) MON - Monensin, inclusion of monensin sodium in the diet at 24 mg/kg DM. Cows fed CON showed higher dry matter, organic matter, crude protein and ether extract intakes than animals fed MON, whereas higher neutral detergent fibre intake was observed in animals fed SAPEO than those fed MON (P < 0.05). Diet and time effects were observed for ruminal pH and concentration of ruminal ammonia nitrogen (P < 0.05). Cows fed SAP showed a higher relative proportion of Fibrobacter succinogenes (P = 0.04) than animals fed MON. Cows fed CON had higher net and digestible energy intakes than animals fed MON (P < 0.05). Cows fed SAPEO showed higher albumin concentrations (P = 0.04) than those fed CON, SAP, and MON. Besides, cows fed CON showed higher urea concentrations (P = 0.04) than those fed SAP and SAPEO. Higher protein and fat levels in the milk were observed in cows fed SAPEO than animals fed MON (P < 0.05). Monensin decreased the concentrations of C4:0, C6:0, C8:0, and C18:1 cis-11 milk fatty acids (P < 0.05). Monensin decreased nutrient intake to a more energetically efficient pathway but did not alter milk production, digestibility, or rumen fermentation. Saponin supplementation associated with essential oils increases milk fat and protein contents in lactating Jersey cows compared to animals fed a monensin-supplemented diet. [ABSTRACT FROM AUTHOR]