Estimates of non-genetic effects and genetic parameters for semen traits in Piemontese bulls.

Male reproductive performances are often ignored in cattle breeding programmes, although semen traits might be used to improve bull breeding soundness. Effects of genetic and environmental factors on semen production and quality traits were estimated in 693 Piemontese bulls with the aim of providing the first estimates of genetic parameters for semen traits for this breed. Volume and concentrations of individual ejaculates (up to three per each test-day), and volume, concentration, total number of spermatozoa and post-thawing progressive motility of within test-day pooled semen were available for 19 060 ejaculates. Bulls reached the maximum amount of daily semen production after their third year of age, with concentration rapidly increasing until 23 months of age, and then slowly decreasing. Semen volume was at its highest when collection days were at least 15 days apart, whereas the maximum concentration was reached when the interval was 6 days. Heritability estimates were generally moderate (0.14-0.26), and low for progressive motility (0.08). Estimates of genetic correlation among the volumes of the individual ejaculates were high and positive (≥0.79), as were the genetic correlations among their concentrations (≥0.46). Genetic correlations among volume and concentration traits varied from -0.47 (with a 95% high posterior density interval ranging from -0.65 to -0.23) to -0.32 (with a 95% high posterior density interval ranging from -0.55 to -0.09). Progressive motility was unrelated with the other traits, but moderately positively correlated with volumes of the second and third ejaculates. The magnitude of heritabilities showed that selection for semen traits is possible. However, the unfavourable relationship between volume and concentration must be taken into account if a future selection programme is to be established.

On-site visible-near IR prediction of iodine number and fatty acid composition of subcutaneous fat of raw hams as phenotypes for a heavy pig breeding program.

The quality of subcutaneous fat of raw hams is a trait of interest in selective breeding programs for pig lines used in dry-cured ham production, and rapid, non-invasive methods for its assessment are available. However, the efficacy of such methods to provide indicator traits for breeding programs needs to be proven. The study investigated the accuracy of on-site visible-near IR spectroscopy predictions of iodine number and fatty acid (FA) composition of raw ham subcutaneous fat, and it evaluated their effectiveness as indicator traits of ham fat quality in a pig breeding program. Prediction equations were developed using visible-near IR spectra acquired at the slaughterhouse from five sites in subcutaneous fat of raw hams of 1025 crossbred pigs. Pigs were raised, under standardized rearing and feeding conditions, in the sib-testing program of the Goland C21 boar line and slaughtered at nine months of age and average body weight of 166 ±â€¯15 kg. Accuracy was generally relatively poor, but R2 in external validation was >0.7 for iodine number and concentration of C18:2n-6, polyunsaturated FAs and omega-6 FAs. To assess the effectiveness of the on-site predictions as indicator traits in a breeding program, (co)variance components of the measured traits (OBS) and of their predictions using in-lab (in-lab-PR) or on-site (on-site-PR) spectrometers were estimated. Available records for OBS were 6814 and 2048, for iodine number and FA composition, respectively. Predictions using in-lab were available for pigs slaughtered between 2006 and 2014, for a total of 10 153 records. Predictions using on-site were obtained from spectra collected since 2011, for a total of 10 296 records. The estimated heritabilities for the investigated traits ranged from 0.34 to 0.50 and were greater for on-site-PR than for OBS. Genetic correlations between OBS and in-lab-PR were very close to 1.00 for all the investigated traits, whereas those between OBS and on-site-PRED ranged from 0.86 to 0.94. On-site visible-IR predictions are accurate enough to support the use of this technique for large-scale phenotyping of raw ham fat quality, even when dealing with animals of a single genetic line raised in standardized conditions, and may be implemented as indicator traits in breeding programs.

Prediction of dry-cured ham weight loss and prospects of use in a pig breeding program.

Large ham weight losses (WL) in dry-curing are undesired as they lead to a loss of marketable product and penalise the quality of the dry-cured ham. The availability of early predictions of WL may ease the adaptation of the dry-curing process to the characteristics of the thighs and increase the effectiveness of selective breeding in enhancing WL. Aims of this study were (i) to develop Bayesian and Random Forests (RFs) regression models for the prediction of ham WL during dry-curing using on-site infrared spectra of raw ham subcutaneous fat, carcass and raw ham traits as predictors and (ii) to estimate genetic parameters for WL and their predictions (P-WL). Visible-near infrared spectra were collected on the transversal section of the subcutaneous fat of raw hams. Carcass traits were carcass weight, carcass backfat depth, lean meat content and weight of raw hams. Raw ham traits included measures of ham subcutaneous fat depth and linear scores for round shape, subcutaneous fat thickness and marbling of the visible muscles of the thigh. Measures of WL were available for 1672 hams. The best prediction accuracies were those of a Bayesian regression model including the average spectrum, carcass and raw ham traits, with R2 values in validation of 0.46, 0.55 and 0.62, for WL at end of salting (23 days), resting (90 days) and curing (12 months), respectively. When WL at salting was used as an additional predictor of total WL, the R2 in validation was 0.67. Bayesian regressions were more accurate than RFs models in predicting all the investigated traits. Restricted maximum likelihood (REML) estimates of genetic parameters for WL and P-WL at the end of curing were estimated through a bivariate animal model including 1672 measures of WL and 8819 P-WL records. Results evidenced that the traits are heritable (h2 ± SE was 0.27 ± 0.04 for WL and 0.39 ± 0.04 for P-WL), and the additive genetic correlation is positive and high (ra = 0.88 ± 0.03). Prediction accuracy of ham WL is high enough to envisage a future use of prediction models in identifying batches of hams requiring an adaptation of the processing conditions to optimise results of the manufacturing process. The positive and high genetic correlation detected between WL and P-WL at the end of dry-curing, as well as the estimated heritability for P-WL, suggests that P-WL can be successfully used as an indicator trait of the measured WL in pig breeding programs.

Effects of the detailed protein composition of milk on curd yield and composition measured by model micro-cheese curd making of individual milk samples.

The effect of the contents of casein (CN) and whey protein fractions on curd yield (CY) and composition was estimated using 964 individual milk samples. Contents of αS1-CN, αS2-CN, ß-CN, γ-CN, glycosylated κ-CN (Gκ-CN), unglycosylated κ-CN, ß-LG, and α-LA of individual milk samples were measured using reversed-phase HPLC. Curd yield and curd composition were measured by model micro-cheese curd making using 25 mL of milk. Dry matter CY (DMCY) was positively associated with all casein fractions but especially with αS1-CN and ß-CN. Curd moisture decreased at increasing ß-CN content and increased at increasing γ-CN and Gκ-CN content. Due to their associations with moisture, Gκ-CN and ß-CN were the fractions with the greatest effect on raw CY, which decreased by 0.66% per 1-standard deviation (SD) increase in the content of ß-CN and increased by 0.62% per 1-SD increase in the content of Gκ-CN. The effects due to variation in percentages of the casein fractions in total casein were less marked than those exerted by contents. A 1-SD increase in ß-CN percentage in casein (+3.8% in casein) exerted a slightly negative effect on DMCY (ß = -0.05%). Conversely, increasing amounts of αS1-CN percentage were associated with a small increase in DMCY. Hence, results suggest that, at constant casein and whey protein contents in milk, the DMCY depends to a limited extent on the variation in the αS1-CN:ß-CN ratio. κ-Casein percentage did not affect DMCY, indicating that the positive relationship detected between the content of κ-CN and DMCY can be attributed to the increase in total casein resulting from the increased amount of κ-CN and not to variation in κ-CN relative content. However, milk with increased Gκ-CN percentage in κ-CN also shows increased raw CY and produces curds with increased moisture content. Curd yield increased at increasing content and relative proportion of ß-LG in whey protein, but this is attributable to an improved capacity of the curd to retain water. Results obtained in this study support the hypothesis that, besides variation in total casein and whey protein contents, variation in protein composition might affect the cheese-making ability of milk, but this requires further studies.

Comparison of Bayesian regression models and partial least squares regression for the development of infrared prediction equations.

The objective of this study was to compare the prediction accuracy of 92 infrared prediction equations obtained by different statistical approaches. The predicted traits included fatty acid composition (n = 1,040); detailed protein composition (n = 1,137); lactoferrin (n = 558); pH and coagulation properties (n = 1,296); curd yield and composition obtained by a micro-cheese making procedure (n = 1,177); and Ca, P, Mg, and K contents (n = 689). The statistical methods used to develop the prediction equations were partial least squares regression (PLSR), Bayesian ridge regression, Bayes A, Bayes B, Bayes C, and Bayesian least absolute shrinkage and selection operator. Model performances were assessed, for each trait and model, in training and validation sets over 10 replicates. In validation sets, Bayesian regression models performed significantly better than PLSR for the prediction of 33 out of 92 traits, especially fatty acids, whereas they yielded a significantly lower prediction accuracy than PLSR in the prediction of 8 traits: the percentage of C18:1n-7 trans-9 in fat; the content of unglycosylated κ-casein and its percentage in protein; the content of α-lactalbumin; the percentage of αS2-casein in protein; and the contents of Ca, P, and Mg. Even though Bayesian methods produced a significant enhancement of model accuracy in many traits compared with PLSR, most variations in the coefficient of determination in validation sets were smaller than 1 percentage point. Over traits, the highest predictive ability was obtained by Bayes C even though most of the significant differences in accuracy between Bayesian regression models were negligible.

Genetic parameters of measures and population-wide infrared predictions of 92 traits describing the fine composition and technological properties of milk in Italian Simmental cattle.

The objectives of this study were to estimate, for the Italian Simmental cattle population, genetic parameters for 92 traits and their infrared predictions (IP) and to investigate the genetic relationship between measured traits (MT) and IP. Data for milk fat fatty acid composition (n = 1,040), detailed protein composition (n = 3,337), lactoferrin (n = 558), pH (n = 3,438), coagulation properties (n = 3,266), curd yield and composition obtained by a micro-cheese making procedure (n = 1,177), and content of Ca, P, Mg, and K (n = 689) were obtained using reference laboratory analysis. Infrared prediction for all the investigated traits was performed using 143,198 spectra records belonging to 17,619 Italian Simmental cows. (Co)variance components for MT and their IP were estimated in a set of bivariate animal model REML analyses and genetic correlations between MT and IP were estimated using all IP obtained at the population level. A significant positive relationship was observed between the coefficient of determination of the infrared prediction models and the phenotypic and genetic variation of the IP. The decrease in the estimated genetic variance of IP compared with MT was on average 64%. For traits exhibiting calibration models with coefficients of determination in cross-validation (R2CV) greater than 0.9, the decrease in the genetic variance ranged from approximately 20 to 50%. Most traits (88 out of 92) exhibited lower heritability estimates for IP than for the corresponding MT. The estimated genetic correlations between IP and MT (ra) were in general very high. A positive relationship (r = 0.57) between R2CV of calibration models and the estimated ra has been detected. For calibration models exhibiting R2CV higher than 0.75, ra were greater than 0.9. The variability in the estimated correlations increased when R2CV decreased, and for calibration models of moderate predictive ability, estimates of ra ranged from 0.2 to 1. Genetic parameter estimates suggested that IP can be used as indicator traits in breeding programs for the enhancement of fine composition and technological properties of milk. The genetic gain achievable selecting for IP is expected to be high for fatty acid composition, minerals, and for technological properties of milk, whereas it will be low for casein and whey protein composition and for the content of lactoferrin.

Comparison between direct and indirect methods for exploiting Fourier transform spectral information in estimation of breeding values for fine composition and technological properties of milk.

The aim of this study was to compare the common method of exploiting infrared spectral data in animal breeding; that is, estimating the breeding values for the traits predicted by infrared spectroscopy, and an alternative approach based on the direct use of spectral information (direct prediction, DP) to predict the estimated breeding values (EBV). Traits were pH, milk coagulation properties, contents of the main casein and whey protein fractions, cheese yield measured by micro-cheese making, lactoferrin, Ca, and fat composition. For the DP method, the number of spectral variables was reduced by principal components analysis to 8 latent traits that explained 99% of the original spectral variation. Restricted maximum likelihood was used to estimate variance components of the latent traits. (Co)variance components of the original spectral traits were obtained by back-transformation and EBV of all derived milk traits were then predicted as traits correlated with the genetic information of the spectra. The rank correlation between the EBV obtained for the infrared-predicted traits and those obtained from the DP method was variable across traits. Rank correlations ranged from 0.07 (for the content of saturated fatty acids expressed as g/100 g of fat) to 0.96 (for dry matter cheese yield, %) and, for most traits, was <0.5. This result can be explained by the nature of the principal components analysis: it does not take into account the covariance between the spectral variables and the reference traits but produces latent traits that maximize the spectral variance explained. Thus, the direct approach is more likely to be effective for traits more related to the main sources of spectral variation (i.e., protein and fat). More research is required to study spectral genetic variation and to determine the best way to choose spectral regions and the type and number of considered latent traits for potential applications.

Short communication: Mid-infrared spectroscopy prediction of fine milk composition and technological properties in Italian Simmental.

The objective of this study was to evaluate the ability of mid-infrared predictions of fine milk composition and technological traits to serve as a tool for large-scale phenotyping of the Italian Simmental population. Calibration equations accurately predicted the fatty acid profile of the milk, but we obtained moderate or poor accuracy for detailed protein composition, coagulation properties, curd yield and composition, lactoferrin, and concentration of major minerals. To evaluate the role of infrared predictions as indicator traits of fine milk composition in indirect selective breeding programs, the genetic parameters of the traits predicted using mid-infrared spectra need to be estimated.

Immunohistochemical Labelling for Cyclo-oxygenase-2: Does the Positive Control Guarantee Standardized Results?

Since the identification of cyclo-oxygenase-2 as a potentially important therapeutic target in veterinary oncology, numerous studies on its expression have been conducted. Unfortunately, results have been heterogeneous and conclusions are difficult to draw. We tested the ability of a defined positive control to guarantee reproducibility of results among different laboratories. Valid positive controls were defined by positivity of the renal macula densa without background labelling. Fifteen colorectal tumours and 15 oral squamous cell carcinomas were labelled immunohistochemically by six European laboratories. Slides were evaluated in blinded fashion for percentage of positive cells and labelling intensity by three pathologists, and results were analyzed statistically for reproducibility and inter-reader variability. Macula densa positivity was an insufficiently sensitive control to guarantee reproducible results for percentage of positive cells and labelling intensity. Inter-reader variability was proven statistically, making the case for image analysis or other automated quantitative evaluation techniques.

Estimates of genetic parameters for content of boar taint compounds in adipose tissue of intact males at 160 and 220 days of age.

The aims of this study were to investigate variation in content of androstenone (AND), skatole (SKA), and indole (IND), quantified in adipose tissue of intact male pigs at 160 d of age (105 kg BW) and 220 d of age (155 kg BW), to estimate genetic parameters and to investigate the genetic relationships for AND, SKA, IND, and growth traits. A sample of adipose tissue was collected in vivo, using a biopsy device, from the neck of 500 intact males at the 2 ages and at slaughter from the ham of 100 of the investigated animals. Backfat depth was measured at 220 d of age, whereas BW was recorded at each sampling. Quantification of AND, SKA, and IND was performed by HPLC with fluorescence detection. Estimates of genetic parameters were obtained through Bayesian analyses after logarithmic transformations of original measures. Contents of boar taint compounds (BTC) measured at 220 d were higher than those at 160 d of age. Correlations between contents of BTC in backfat and ham fat ranged from 0.7 (IND) to 0.88 (SKA). Medium-high h were estimated for BTC at both ages, but estimates at 220 d (0.58, 0.60, and 0.69 for AND, SKA, and IND, respectively) were greater than those at 160 d. The genetic correlation between contents at 160 and 220 d of each BTC was positive, but the probability that such estimates were greater than 0.8 was very low, indicating that contents at 160 and 220 d were traits controlled by different genetic backgrounds. Different rankings were observed when breeding values for the content at 160 and 220 d of age were used to rank animals. As a consequence, performance testing programs for BTC should be based preferably on phenotypes measured at 220 d of age. Weak genetic correlations were observed between content of BT compounds and growth traits (BW, backfat depth, and daily gain from 160 to 220 d of age), indicating that selective breeding to reduce the risk of tainted pork is expected to exert trivial effects on growth performance and fat deposition. Results indicate that prevalence of BTC is high in mature and heavy pigs relative to young and light pigs. High heritability; positive genetic correlations between AND, SKA, and IND; and trivial effects on growth traits suggest that reduction of BTC through selective breeding is feasible and exploitable as an alternative to surgical castration also for pigs slaughtered at heavy BW.

Short communication: predictive ability of Fourier-transform mid-infrared spectroscopy to assess CSN genotypes and detailed protein composition of buffalo milk.

The aim of this work was to test the applicability of Fourier-transform mid-infrared spectroscopy (FT-MIR) for the prediction of the contents of casein (CN) and whey protein fractions in buffalo milk. Buffalo milk samples spectra were collected using a MilkoScan FT2 (Foss, Hillerød, Denmark) over the spectral range from 5,000 to 900 wavenumber × cm(-1). Contents of protein fractions, as well as CSN1S1 and CSN3 genotypes, were assessed by reversed phase HPLC. The highest coefficients of determination in cross-validation (1 - VR) were obtained for the contents (g/L of milk) of total protein and CN (1 - VR=0.92), followed by the content of ß-CN, total whey protein, and αS2-CN (1 - VR of 0.87, 0.77, and 0.63, respectively). Conversely, contents of αS1-CN, γ-CN, glycosylated-κ-CN, total κ-CN, and whey protein fractions were predicted with poor accuracy (1 - VR <0.51). When protein fractions were expressed as percentages to total protein, 1 - VR values were never greater than 0.61 (ß-CN). Only 56 and 70% of the observations were correctly classified by discriminant analysis in each of 2 groups of CSN1S1 and CSN3 genotypes, respectively. Results showed that FT-MIR spectroscopy is not applicable when prediction of detailed milk protein composition with high accuracy is required. Predictions may play a role as indicator traits in selective breeding, if the genetic correlation between FT-MIR predictions and measures of milk protein composition are high enough and predictions of protein fraction contents are sufficiently independent from the predicted total protein content.

Direct and social genetic effects on body weight at 270 days and carcass and ham quality traits in heavy pigs.

The aims of this study were to estimate covariance components for BW at 270 d (BW270) and carcass and ham quality traits in heavy pigs using models accounting for social effects and to compare the ability of such models to fit the data relative to models ignoring social interactions. Phenotypic records were from 9,871 pigs sired by 293 purebred boars mated to 456 crossbred sows. Piglets were born and reared at the same farm and randomly assigned at 60 d of age to groups (6.1 pigs per group on average) housed in finishing pens, each having an area of 6 m(2). The average additive genetic relationship among group mates was 0.11. Pigs were slaughtered at 277 ± 3 d of age and 169.7 ± 13.9 kg BW in groups of nearly 70 animals each. Four univariate animal models were compared: a basic model (M1) including only direct additive genetic effects, a model (M2) with nonheritable social group (pen) effects in addition to effects in M1, a model (M3) accounting for litter effects in addition to M2, and a model (M4) accounting for social genetic effects in addition to effects in M3. Restricted maximum likelihood estimates of covariance components were obtained for BW270; carcass backfat depth; carcass lean meat content (CLM); iodine number (IOD); and linoleic acid content (LIA) of raw ham subcutaneous fat; subcutaneous fat depth in the proximity of semimembranosus muscle (SFD1) and quadriceps femoris muscle (SFD2); and linear scores for ham round shape (RS), subcutaneous fat (SF), and marbling. Likelihood ratio tests indicated that, for all traits, M2 fit the data better than M1 and that M3 was superior to M2 except for SFD1 and SFD2. Model M4 was significantly better than M3 for BW270 (P < 0.001) and CLM, IOD, RS, and SF (P < 0.05). The contribution of social genetic effects to the total heritable variance was large for CLM and BW270, ranging from 33.2 to 35%, whereas the one for ham quality traits ranged from 6.8 (RS) to 11.2% (SF). Direct and social genetic effects on BW270 were uncorrelated, whereas there was a negative genetic covariance between direct and social effects on CLM, IOD, RS, and SF, which reduced the total heritable variance. This variance, measured relative to phenotypic variance, ranged from 21 (CLM) to 54% (BW270). Results indicate that social genetic effects affect variation in traits relevant for heavy pigs used in dry-cured hams manufacturing. Such effects should be exploited and taken into account in design of breeding programs for heavy pigs.

Oestrogen and progesterone receptor expression in subtypes of canine mammary tumours in intact and ovariectomised dogs.

The objective of this study was to investigate as a potential prognostic indicator the relationship between histological subtype of canine mammary tumours (CMTs) and oestrogen-α (ORα) and progesterone (PR) receptor expression. Using immunohistochemistry, receptor expression in neoplastic epithelial cells was assessed in 12 different subtypes in 113 CMTs (34 benign, 79 malignant) and 101 surrounding normal tissues. Sixty-eight and 45 CMTs were from intact and ovariectomised bitches, respectively. Histological subtype strongly influenced ORα/PR expression: simple and complex adenomas as well as simple tubular carcinomas exhibited the greatest expression, whereas immunohistochemical labelling for these receptors was weakest in carcinoma and malignant myoepitheliomas, as well as in solid/anaplastic carcinomas and comedocarcinomas. Receptor expression was generally higher in benign relative to malignant neoplasms, and in the latter it was significantly lower in ovariectomised vs. intact bitches. Lymphatic invasion, mitotic index, nodule diameter, and tumour grade were significantly associated with ORα/PR expression. Although not found to be an independent prognostic indicator, tumours from dogs with <10% cells with ORα/PR expression had a poorer prognosis. Lymphatic invasion, the state of the margins of excision, and mitotic index were found to be independent prognostic indicators. Overall, the results suggest that differences in histological subtype and whether or not a bitch has been ovariectomised should be considered when evaluating the significance of ORα and PR expression in CMTs.

The dog as a natural animal model for study of the mammary myoepithelial basal cell lineage and its role in mammary carcinogenesis.

Basal-like tumours constitute 2-18% of all human breast cancers (HBCs). These tumours have a basal myoepithelial phenotype and it has been hypothesized that they originate from either myoepithelial cells or mammary progenitor cells. They are heterogeneous in morphology, clinical presentation, outcome and response to therapy. Canine mammary carcinomas (CMCs) have epidemiological and biological similarities to HBCs, are frequently biphasic and are composed of two distinct neoplastic populations (epithelial and myoepithelial). The present study evaluates the potential of CMCs as a natural model for basal-like HBCs. Single and double immunohistochemistry was performed on serial sections of 10 normal canine mammary glands and 65 CMCs to evaluate expression of cytokeratin (CK) 8/18, CK5, CK14, α-smooth muscle actin (SMA), calponin (CALP), p63 and vimentin (VIM). The tumours were also evaluated for Ki67 and human epidermal growth factor receptor (HER)-2 expression. A hierarchical model of cell differentiation was established, similar to that for the human breast. We hypothesized that progenitor cells (CK5(+), CK14(+), p63(+) and VIM(+)) differentiate into terminally-differentiated luminal glandular (CK8/18(+)) and myoepithelial (CALP(+), SMA(+) and VIM(+)) cells via intermediary luminal glandular cells (CK5(+), CK14(+) and CK8/CK18(+)) and intermediary myoepithelial cells (CK5(+), CK14(+), p63(+), SMA(+), CALP(+) and VIM(+)). Neoplastic myoepithelial cells in canine complex carcinomas had labelling similar to that of terminally-differentiated myoepithelial cells, while those of carcinomas-and-malignant myoepitheliomas with a more aggressive biological behaviour (i.e. higher frequency of vascular/lymph node invasion and visceral metastases and higher risk of tumour-related death) were comparable with intermediary myoepithelial cells and had significantly higher Ki67 expression. The majority of CMCs examined were negative for expression of HER-2. The biphasic appearance of CMCs with involvement of the myoepithelial component in different stages of cell differentiation may help to define the role of myoepithelial cells in the mammary carcinogenetic process and the heterogeneous nature of basal-like HBCs.

Glycosylation of κ-casein: genetic and nongenetic variation and effects on rennet coagulation properties of milk.

The aims of this study were to investigate genetic and nongenetic variation in the degree of glycosylation of κ-casein (κ-CN) and to estimate the effects of glycosylated (G-κCN) and unglycosylated (U-κCN) κ-CN contents on milk coagulation properties of Simmental cows. Measures of contents of the main casein fractions, G-κCN, and U-κCN, and assessment of genotypes at CSN2, CSN3, and BLG were obtained by reversed-phase HPLC analysis of 2,015 individual milk samples. Content of total κ-CN (κ-CNtot, g/L) was the sum of G-κCN and U-κCN, and the glycosylation degree of κ-CN (GD) was measured as the ratio of G-κCN to κ-CNtot. Rennet coagulation time (RCT) and curd firmness were measured by using a computerized renneting meter. Measures of curd firmness were adjusted for RCT before statistical analysis. Variance components of κ-CNtot, G-κCN, U-κCN, and GD were estimated by Bayesian procedures and univariate linear models that included the class effects of the herd-test-day, parity, days in milk, genotypes at milk protein genes, and animal. These class effects, those of G-κCN, U-κCN, and content of other caseins, and the linear effect of milk pH were accounted for by models investigating the influence of κ-CN glycosylation on coagulation properties. The GD ranged from 22 to 76%, indicating that variation in G-κCN depends on the variation both in κ-CNtot and in the efficiency of κ-CN glycosylation. Genotype CSN3 BB exhibited high G-κCN and U-κCN relative to that of CSN3 AA. Heritability of G-κCN, U-κCN, and GD was high and ranged from 0.46 to 0.56. A large proportion of the additive genetic variation in G-κCN and U-κCN was attributable to influence of CSN and BLG, but these genes did not affect variation in GD, and across-genotypes differences in the trait were small or trivial. Average RCT of the milk class having the highest G-κCN was, on average, 2min (standard deviation 0.5) shorter than that of the lowest class. Conversely, U-κCN and content of other caseins were not associated with any effect on RCT, except for a slight delay in coagulation when U-κCN was very high. Curd firmness increased when the contents of both κ-CN fractions and other caseins increased. This study provides evidence that the positive association between RCT and κ-CN content is exclusively attributable to the glycosylated fraction of the protein. Because exploitable additive genetic variation in G-κCN exists, improvement of κ-CN composition through selective breeding might be an effective way to enhance milk coagulation properties.

Effect of polymorphisms in candidate genes on carcass and meat quality traits in double muscled Piemontese cattle.

The aim of this study was to investigate the association between 10 candidate genes and carcass weight and conformation, carcass daily gain, and meat quality (pH, color, cooking loss, drip loss and shear force) in 990 double-muscled Piemontese young bulls. Animals were genotyped at each of the following genes: growth hormone, growth hormone receptor, pro-opiomelanocortin, pro-opiomelanocortin class 1 homeobox 1, melanocortin-4 receptor, corticotrophin-releasing hormone, diacylglycerol O-acyltransferase-1, thyroglobulin, carboxypeptidase E and gamma-3 regulatory subunit of the AMP-activated protein kinase. All the investigated SNPs had additive effects which were relevant for at least one of the traits. Relevant associations between the investigated SNPs and carcass weight, carcass daily gain and carcass conformation were detected, whereas associations of SNPs with meat quality were moderate. Results confirmed some of previously reported associations, but diverged for others. Validation in other cattle breeds is required to use these SNPs in gene-assisted selection programs for enhancement of carcass traits and meat quality.

Protein composition affects variation in coagulation properties of buffalo milk.

The aim of this study was to investigate the effects exerted by the content of casein and whey protein fractions on variation of pH, rennet-coagulation time (RCT), curd-firming time (K20), and curd firmness of Mediterranean buffalo individual milk. Measures of milk protein composition and assessment of genotypes at CSN1S1 and CSN3 were obtained by reversed-phase HPLC analysis of 621 individual milk samples. Increased content of αS1-casein (CN) was associated with delayed coagulation onset and increased K20, whereas average pH, RCT, and K20 decreased when ß-CN content increased. Milk with low κ-CN content exhibited low pH and RCT relative to milk with high content of κ-CN. Increased content of glycosylated κ-CN was associated with unfavorable effects on RCT. Effects of milk protein composition on curd firmness were less important than those on pH, RCT, and K20. Likely, this occurred as a consequence of the very short RCT of buffalo milk, which guaranteed a complete strengthening of the curd even in the restricted 31 min time of analysis of coagulation properties and for samples initially showing soft curds. Effects of CSN1S1-CSN3 genotypes on coagulation properties were not to be entirely ascribed to existing variation in milk protein composition associated with polymorphisms at CSN1S1 and CSN3 genes. Although the role of detailed milk protein composition in variation of cheese yield needs to be further investigated, findings of this study suggest that modification of the relative content of specific CN fractions can relevantly influence the behavior of buffalo milk during processing.

Genetic associations between daily BW gain and live fleshiness of station-tested young bulls and carcass and meat quality traits of commercial intact males in Piemontese cattle.

The aim of this study was to investigate genetic relationships between beef traits of station-tested young bulls and carcass and meat quality traits (MQ) of commercial intact males in Piemontese cattle. Phenotypes for daily gain (DG) and live fleshiness traits (width at withers: WW; shoulder muscularity: SM; loin width: LW; loin thickness: LT; thigh muscularity: TM; thigh profile: TP) and thinness of the shin bone (BT) were available for 3,109 and 2,183 performance-tested young bulls, respectively. Carcass daily gain (CDG), carcass conformation (SEUS), pH at 24 h (pH24h) and 8 d after slaughter (pH8d), lightness (L*), redness (a*), yellowness (b*), hue angle (HA), saturation index (SI), drip loss (DL), cooking loss (CL), and shear force (SF) were assessed for 1,208 commercial intact males. (Co) variance components were estimated in a set of twelve 9-traits analyses using REML and linear animal models including all performance-test traits and 1 carcass or MQ trait at a time. Heritabilities ± SE of beef traits ranged from 0.26 ± 0.03 (LW) to 0.47 ± 0.01 (DG), whereas those of carcass traits and MQ from 0.06 ± 0.03 (CL) to 0.63 ± 0.04 (HA). The genetic correlation (rg) between DG and CDG was 0.75 ± 0.10, indicating that DG, as measured at the test station, is a good indicator of the carcass gain achieved by commercial animals under farms conditions. Daily BW gain of station-tested bulls correlated positively with color traits (from 0.11 ± 0.12 to 0.54 ± 0.09), ph8d (rg ± SE = 0.31 ± 0.11), DL (rg ± SE = 0.29 ± 0.17), and CL (rg ± SE = 0.27 ± 0.18). Live fleshiness of station-tested bulls exhibited genetic correlations with MQ of commercial animals that were positive for L* and b* (from 0.13 ± 0.08 to 0.65 ± 0.14) and negative for pH (from -0.27 ± 0.15 to -0.57 ± 0.11), CL (from -0.16 ± 0.23 to -0.43 ± 0.22), and SF (TM: rg ± SE = -0.31 ± 0.15; TP: rg ± SE = -0.41 ± 0.17). The thinness of the shin bone correlated unfavorably with CDG (rg ± SE = -0.74 ± 0.07) and favorably with SEUS (rg ± SE = 0.65 ± 0.17), CL (rg ± SE = -0.39 ± 0.13), and SF (rg ± SE = -0.32 ± 0.17). The estimated genetic correlations indicate that selection to increase DG, as measured at the test station, exerts moderate adverse effects on MQ. Because selection emphasis is greater for live fleshiness than for DG, the correlated response in MQ and carcass traits is expected to be influenced to a greater extent by selection for muscularity, even though these traits are less heritable than DG.

Short communication: CSN1S1-CSN3 (α(S1)-κ-casein) composite genotypes affect detailed milk protein composition of Mediterranean water buffalo.

The aim of the study was to investigate the effect of composite CSN1S1-CSN3 [α(S1)-κ-casein (CN)] genotype on milk protein composition in Mediterranean water buffalo. Content of α(S1)-CN, α(S2)-CN, ß-CN, γ-CN, κ-CN, glycosylated and unglycosylated κ-CN, α-lactalbumin, and ß-lactoglobulin was measured by reversed-phase HPLC using 621 individual milk samples. Genotypes at CSN1S1 and CSN3 were also obtained by reversed-phase HPLC. Two alleles were detected at CSN1S1 (corresponding to the A and B variants, O62823: p.Leu193Ser,) and at CSN3 (corresponding to the X1 and X2 variants, CAP12622.1: p.Ile156Thr). Increased proportions of α(S1)-CN in total casein (TCN) were associated with genotypes carrying CSN1S1 A. Genotypes associated with a marked decrease of the proportion of α(S1)-CN in TCN (composite genotypes AB-X1X1 and BB-X1X2) were associated with marked increases in the proportion of α(S2)-CN. In addition, composite genotypes carrying the X1 allele at CSN3 were associated with a greater proportion of α(S2)-CN in TCN relative to those carrying CSN3 X2. Composite genotypes greatly affected also the variability of ratios of κ-CN to TCN, with genotypes carrying the X1 allele at CSN3 being associated with decreased ratios. The decreased content of glycosylated κ-CN associated with CSN3 X1 was responsible for the overall lower content of total κ-CN in milk of X1-carrying animals. Increasing the frequency of specific genotypes might be an effective way to alter milk protein composition, namely the proportion of α(S1)-CN, α(S2)-CN, and κ-CN in TCN, and the degree of glycosylation of κ-CN.

Effect of parity, days in milk, and milk yield on detailed milk protein composition in Mediterranean water buffalo.

The effects of some nongenetic factors on milk protein fraction contents and relative proportions were estimated in 606 individual milk samples of Mediterranean water buffalo. Content of α(S1)-casein (CN), α(S2)-CN, ß-CN, γ-CN, κκ-CN, glycosylated κ-CN (glyco-κ-CN), α-lactalbumin, and ß-lactoglobulin was measured by reversed-phase HPLC. Relative contents of α(S1)-CN%, α(S2)-CN%, ß-CN%, and κ-CN% were, respectively, 32.1, 17.1, 34.5, and 15.7%, whereas γ-CN% accounted for 0.6% of total casein content. Increasing total casein content in milk would result in a greater proportion of ß-CN% at the expense of all of the other major casein fractions, especially of κ-CN%. Values of α(S2)-CN%, ß-CN%, and γ-CN% tended to decrease with parity, although their variations were not significant, whereas α(S1)-CN% and glyco-κ-CN% showed the opposite trend. Contents of most protein fractions showed the typical trends observed for milk components as lactation progressed, with high contents in early lactation, a minimum in midlactation, followed by a gradual increase toward the latter part of lactation. Values of α(S1)-CN% increased during lactation, whereas α(S2)-CN% decreased. The proportion of ß-CN% had its maximum value between 60 and 160 d of lactation, followed by a decrease, whereas κ-CN% had its minimum value in early lactation (<60 d) and remained relatively constant in the period of mid and late lactation. Glyco-κ-CN% and ß-lactoglobulin% decreased in the first part of lactation, to reach their minimum values in midlactation, followed by an increase. Milk of top-producing buffaloes, compared with that of low-producing ones, had a significantly greater value of ß-CN% and glyco-κ-CN%, and lower proportion of α(S1)-CN%. The possible effect exerted by protein genetic variants in affecting variation of milk protein fraction contents and relative proportions should be further considered to better get insight into buffalo milk protein composition.