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Background Psoroptic mange, caused by Psoroptes ovis mites, is affecting Belgian Blue cattle’s welfare and production potential. The Belgian Blue cattle—known for its high degree of muscling, low feed conversion ratio and high beef quality—is highly susceptible for this disease. Results In this study, we phenotyped 1975 Belgian Blue cattle from more than 100 different groups on commercial beef farms for their psoroptic mange susceptibility. Substantial individual differences were observed within these management groups, with lesion extent differences up to ± 15%. Animal models showed that estimated heritabilities were low for lesion extent and severe lesion extent (0.07 and 0.09, respectively) and 0.12 for the number of mites. A genome wide association study for mange susceptibility revealed signals on BTA6, BTA11, BTA15 and BTA24. In these regions, candidate genes GBA3 , RAG2 , and TRAF6 were identified. Conclusions Despite the challenges in phenotyping for psoroptic mange due to the timing of screening, the continuous evolution of lesions and different management conditions, we successfully conducted a study on the genetic susceptibility to psoroptic mange in Belgian Blue cattle. Our results clearly indicate that psoroptic mange is under polygenic control and the underlying candidate genes should be studied more thoroughly. This is the first study providing candidate genes for this complex disease. These results are already valuable for Belgian Blue breeding, however, further research is needed to unravel the architecture of this disease and to identify causal mutations.

Increasing agricultural production while reducing the reliance on synthetic inputs such as antibiotics is an important challenge. For cattle breeding, this implies better understanding the genetics underlying meat production and the immune response. Here, we use systems immunology to investigate the genetic and environmental drivers of immune variation in Belgian White Blue male cattle, a breed historically bred for meat production. While seasonality and other non-genetic factors account for much of the immune variation observed, genome-wide association studies identify loci with major effects on specific immunophenotypes. Genetics also emerges as the primary driver of cytokine production. Finally, we develop a predictive model linking genetic data to cytokine responses. Our findings support the selection of cattle with improved immunity and advance our understanding of mammalian immune variation.

Interest in the fatty acid composition of dairy products is increasing; however, the measurement of fatty acids requires using gas-liquid chromatography. Although this method is suitable, it involves a time-consuming procedure, expensive reagents, and qualified staff. By comparison, the mid-infrared (MIR) spectrometry method could be a good alternative for assessing the fatty acid profile of dairy products. The objective of this study was to explore the calibration of MIR spectrometry for estimating fatty acid concentrations in milk and milk fat. Estimated concentrations in milk fat were less reliable than those for the same fatty acids in milk. Results also showed that when the fatty acid concentrations in milk increased, the efficiency of the infrared analysis method in predicting these values simultaneously increased. Selected prediction equations must have a high cross-validation coefficient of determination, a high ratio of standard error of cross-validation to standard deviation, and good repeatability of chromatographic data. Results from this study showed that the calibration equations predicting 12:0, 14:0, 16:0, 16:1cis-9, 18:1, and saturated and monounsaturated fatty acids in milk could be used. Thus, with its potential for use in regular milk recording, this infrared analysis method offers the possibility of assessing and improving the quality of milk produced. Indeed, it enables the fatty acid composition in milk to be estimated for each cow and the estimates to be used as indicator traits to determine the genetic values of underlying fatty acid concentrations. The knowledge of these genetic values would open up opportunities for animal selection aimed at improving the nutritional quality of cow milk.

The current cattle selection program for dairy cattle in the Walloon region of Belgium does not consider the relative content of the different fatty acids (FA) in milk. However, interest by the local dairy industry in differentiated milk products is increasing. Therefore, farmers may be interested in selecting their animals based on the fat composition. The aim of this study was to evaluate the feasibility of genetic selection to improve the nutritional quality of bovine milk fat. The heritabilities and correlations among milk yield, fat, protein, and major FA contents in milk were estimated. Heritabilities for FA in milk and fat ranged from 5 to 38%. The genetic correlations estimated among FA reflected the common origin of several groups of FA. Given these results, an index including FA contents with the similar metabolic process of production in the mammary gland could be used, for example, to increase the monounsaturated and conjugated fatty acids in milk. Moreover, the genetic correlations between the percentage of fat and the content of C14:0, C12:0, C16:0, and C18:0 in fat were −0.06, 0.55, 0.60, and 0.84, respectively. This result demonstrates that an increase in fat content is not directly correlated with undesirable changes in FA profile in milk for human health. Based on the obtained genetic parameters, a future selection program to improve the FA composition of milk fat could be initiated.

The endogenous production of unsaturated fatty acids (FA), particularly some monounsaturated FA (%MONO) and nearly all conjugated linoleic acids, is regulated by the 9-desaturase activity. The aims of this study were to assess the variation of this enzymatic activity within lactation, across dairy breeds, and to estimate its genetic parameters. The ratios of C14:1 cis-9 to C14:0, C16:1 cis-9 to C16:0, and C18:1 cis to C18:0 were calculated from FA contents predicted by mid-infrared spectrometry. Variance components and standard errors were estimated using average information REML. The multitrait mixed model included as fixed effects herd × test date × class of lactation number, class of days in milk × class of lactation number, class of age × class of lactation number, and regressions on breed composition. Four random effects were also included: animal genetic effect, 2 permanent environments (within and across lactations), and residual effect. Under the assumption that the calculated ratios are an approximate measurement of 9-desaturase activity, this study showed different sources of variation for this enzymatic activity. A slight difference was observed within lactation. The ratios of C14:1 cis-9 to C14:0 and C16:1 cis-9 to C16:0 increased as a function of days in milk. Differences across 7 dairy breeds were observed. The values of 9-desaturase indices observed for Jersey and Brown-Swiss cows were lower compared with Holstein. The opposite was observed for dual-purpose Belgian Blue cows. Values of heritability for the ratios of C14:1 cis-9 to C14:0, C16:1 cis-9 to C16:0, and C18:1 cis to C18:0 were 20, 20, and 3%, respectively. Negative genetic correlations observed between fat or protein contents and the 3 indices suggested that an increased activity of 9-desaturase could inhibit the synthesis of fat and protein in bovine milk. Negative correlations were also observed between fat or protein contents and the contents of 3 studied unsaturated FA in milk fat (C14:1 cis-9, C16:1 cis-9, and C18:1 cis). The positive genetic correlations observed between %MONO and the ratios of C14:1 cis-9 to C14:0 (0.72), C16:1 cis-9 to C16:0 (0.62), and C18:1 cis to C18:0 (0.97) showed that %MONO is linked to the 9-desaturase activity.

The aim of this research was to study the potential for selection of cows with a higher nutritional quality of milk fat by studying the differences in fatty acid profiles within and across the following breeds: Dual Purpose Belgian Blue, Holstein-Friesian, Jersey, Montbeliarde, and non-Holstein Meuse-Rhine-Yssel type Red and White. Six hundred milk samples from 275 animals were taken from 7 herds. Several types of fatty acids in milk and milk fat were quantified using mid-infrared spectrometry and previously obtained calibration equations. Statistical analyses were made using a mixed linear model with a random animal effect. The variance components were estimated by using REML. Results showed breed differences for the fatty acid profile. The repeatability estimate obtained in the present study may suggest the existence of moderate additive genetic variance for the fatty acid profile within each breed. Results also indicated variation for each analyzed milk component in the whole cow population studied. Genetic improvement of the nutritional quality of milk fat based on fatty acid profiles might be possible, and further research and development are warranted.

The calving interval (CI) can potentially impact the economic results of dairy farms. This study highlighted the most profitable CI and innovated by describing this optimum as a function of the feeding system of the farm. On-farm data were used to represent real farm conditions. A total of 1832 accounts of farms recorded from 2007 to 2014 provided economic, technical and feeding information per herd and per year. A multiple correspondence analysis created four feeding groups: extensive, low intensive, intensive and very intensive herds. The gross margin and some of its components were corrected to account for the effect of factors external to the farm, such as the market, biological status, etc. Then the corrected gross margin (cGMc) and its components were modelled by CI parameters in each feeding system by use of GLM. The relationship between cGMc and the proportion of cows with CI<380 days in each feeding group showed that keeping most of the cows in the herd with CI near to 1 year was not profitable for most farms (for the very intensive farms there was no effect of the proportion). Moreover, a low proportion of cows (0% to 20%) with a near-to-1-year CI was not profitable for the extensive and low intensive farms. Extending the proportion of cows with CI beyond 459 days until 635 days (i.e. data limitation) caused no significant economic loss for the extensive and low intensive farms, but was not profitable for the intensive and very intensive farms. Variations of the milk and feeding components explained mainly these significant differences of gross margin. A link between the feeding system and persistency, perceptible in the milk production and CI shown by the herd, could explain the different relationships observed between the extent of CI and the economic results in the feeding groups. This herd-level study tended to show different economic optima of CI as a function of the feeding system. A cow-level study would specify these tendencies to give CI objectives to dairy breeders as a function of their farm characteristics.

The objective of this research was to examine the effects of inbreeding in the population of Holstein cattle in the Walloon region of Belgium. The effects of inbreeding on the global economic index and its components were studied by using data from the genetic evaluations of February 2004 for production, somatic cell score (SCS), computed from somatic cell counts and type. Inbreeding coefficients for 956,516 animals were computed using a method that allows assigning an inbreeding coefficient to individuals without known parents. These coefficients were equal to the mean inbreeding coefficient of contemporary individuals with known parents. The significance of inbreeding effects on the different evaluated traits and on the different indexes were tested using a t-test comparing estimated standard errors and effects. The inbreeding effect was significantly different from zero for the vast majority of evaluated traits and for all of the indexes. Inbreeding had the greatest deleterious effects on production traits. Inbreeding decreased yield of milk, fat, and protein during a lactation by 19.68, 0.96, and 0.69kg, respectively, per each 1% increase in inbreeding. The regression coefficient of SCS per 1% increase in inbreeding was +0.005 SCS units. The inbreeding depression was thus relatively low for SCS, but inbred animals had higher SCS than non-inbred animals, indicating that inbred animals would be slightly more sensitive to mastitis than non-inbred animals. Estimates of inbreeding effects on evaluated type traits per 1% increase were small. The most strongly affected type traits were chest width, rear leg, and overall development on a standardized scale. For several type traits, particularly traits linked to the udder, the estimates suggested a favorable effect of inbreeding. The global economic index was depressed by around 6.13 € of lifetime profit per 1% increase in inbreeding for the Holstein animals in the Walloon region of Belgium.

The nonlinear effects of inbreeding were studied by comparing linear and curvilinear regression models of phenotypic performances on inbreeding coefficients for production traits (milk, fat, and protein yields) of Holstein cows in their first lactation. Three different regression models (linear, quadratic, and cubic) were introduced separately into a single-trait, single-lactation, random regression test-day model. The significance of the different regression coefficients was studied based on a t-test after estimation of error variances and covariances associated with the different regression coefficients. All of the tested regression coefficients were significantly different from 0. The traditional regression coefficients of milk, fat, and protein yields on inbreeding were, respectively, −22.10, −1.10, and −0.72kg for Holstein cows in their first lactation. However, the estimates of 305-d production losses for various classes of animals based on inbreeding coefficients showed that the effect of inbreeding was not a linear function of the percentage of inbreeding. The 305-d milk yield loss profiles attributable to inbreeding, obtained by the various regression models, were different. However, for inbreeding coefficients between 0 and 10%, these differences were small.