Effect of transgenerational environmental condition on genetics parameters of Italian Brown Swiss.

The aim of this study was to infer the effects of heat stress (HS) of dams during late gestation on direct and maternal genetic parameters for traits related to milk production and milk quality parameters (90,558 records) in Italian Brown Swiss cattle (12,072 cows in 617 herds). Daily average temperature-humidity indices (THI) during the last 56 d of pregnancy were calculated, using the climate data from the nearest public weather station for each herd. Heat load effects were considered as the average across the entire periods considering a thermoneutrality condition for data below the THI 60. For parameter estimation a random regression model using the second-order Legendre polynomial regression coefficient for THI considering both animal and maternal effect for heat load. Direct heritability increased sharply from THI 60 to 65, then decreased gradually up to THI ∼72, and sharply thereafter. Maternal heritability showed a different trend, with values close to 0 up until to THI 65 and slightly increasing toward extreme THI values. The study suggests a lower threshold of THI 60 for the onset of HS. Higher heritability values indicate greater selective efficiency in the THI range of 65 to 70, even if a higher standard deviation value have been detected. The effects of high THI during intrauterine life varied among traits with different heritability levels. Genetic correlations for milk, fat, and protein content at 60 THI with increasing value of environmental variable, remained constant (∼0.90) until THI >75, where they slightly decreased (∼0.85). Fat and protein yields, as well as milk and energy-corrected milk, showed correlations dropping to 0.80 around THI 67 to 68 and stabilizing between 0.75 and 0.85 at extreme THI values. Maternal component correlations dropped close to zero, with negative values for protein content at THI 65 to 70. Antagonism between direct and maternal components was stronger for intermediate THI values but less divergent for extremes. Genotype by environment interaction was observed, indicating the selection of resilient animals would be theoretically possible. In the future, the application of climate variables in selection schemes first should take into account the dimensions of the genetic correlations to be able to decide between the simple inclusion of the environmental effect in the statistical models, rather than a real parallel genetic evaluation.

Kidney function, but not nitrogen excretion, differs between Brown Swiss and Holstein dairy cows.

Brown Swiss (BS) cows have greater urea concentrations in milk and blood compared with Holstein (HO) cows. We tested the hypothesis that BS and HO cows differ in kidney function and nitrogen excretion. Blood, saliva, urine, and feces were sampled in 31 multiparous BS and 46 HO cows kept under identical feeding and management conditions. Samples were collected at different lactational stages after the monthly DHIA control test-day. To test the glomerular filtration rate (GFR) and urea excretion, concentrations of creatinine and urea were measured in serum, urine, and saliva. As an additional marker to estimate GFR, we determined symmetric dimethylarginine (SDMA) in serum. Feces were analyzed for DM content and nitrogen concentration. Data on milk urea and protein concentrations and daily milk yield were obtained from the monthly DHIA test-day records. The effects of breed, time, and parity number on blood, saliva, urine, feces, and milk parameters were evaluated with the GLM procedure of SAS, with breed, time, and parity number as fixed effects. Differences between BS and HO were assessed by the Tukey-corrected t-test. Concentrations of urea, creatinine, and SDMA in serum, were greater in BS than in HO cows: 5.46 ± 0.19 versus 4.72 ± 0.13 mmol/L (urea), 105.96 ± 2.23 versus 93.07 ± 1.50 mmol/L (creatinine), and 16.78 ± 0.69 versus 13.39 ± 0.44 µg/dL (SDMA). We observed a greater urea concentration in BS cows (25.8 ± 0.7 vs. 21.8 ± 0.7 mg/dL) and protein content in milk (3.70% ± 0.08% vs. 3.45% ± 0.07%) than in HO cows. Urea and creatinine concentrations in urine and saliva did not differ between breeds. No differences between BS and HO were observed for milk yield, fecal DM, and fecal nitrogen content. Dry matter intake and BW were similar in BS and HO cows. Despite greater urea, creatinine, and SDMA concentrations in blood, as well as a higher milk urea content in BS compared with HO, respective concentrations in urine did not differ between breeds. In conclusion, our results demonstrate a lower renal GFR in BS compared with HO cows, thereby contributing to the greater plasma urea concentration in BS cows. However, estimation of nitrogen excretion via milk, urine, and feces does not entirely reflect nitrogen turnover within the animal.

Heat stress has divergent effects on the milk microbiota of Holstein and Brown Swiss cows.

Heat stress (HS) is one of the pivotal causes of economic losses in dairy industries and affects welfare and performance, but its effect on milk microbiota remains elusive. It is also unclear if and how different breeds may cope with HS in sustaining productive performance. The objectives of this study were to compare a) the performance of 2 dairy breeds, namely Holstein and Brown Swiss, subjected to HS and b) the different effects of HS on the milk microbiota of the 2 breeds in thermal comfort conditions and HS. The study was carried out on 36 dairy cows, 18 per breed. The HS was induced by switching off the cooling system during a natural heat wave for 4 d. Besides the Temperature Humidity Index (THI), the animal stress was confirmed by measuring respiratory frequency and rectal temperature twice daily at 4 a.m. and 3 p.m. The HS differently impacted the 2 breeds. Rectal temperatures were higher in Holstein cows, while no changes in rectal temperature were found in Brown Swiss. Milk yield recording and sampling were performed during the morning milking of d 1 (at 4.00 a.m.) and afternoon milking of d 4 (at 5.00 p.m.). Productive parameters were also different: milk yield, fat-corrected milk, energy-corrected milk, protein and casein content, and renneting parameters were decreased in Holstein but remained unaffected in Brown Swiss. The HS also modified the milk microbiota of the 2 breeds differently. During HS, the Brown Swiss milk microbiota was richer (α diversity) than the Holstein one. Comparing the time points before and during HS within breeds showed that Brown Swiss milk microbiota was less affected by HS than Holstein's. Under the same thermal comfort condition, milk microbiota did not discriminate between Brown Swiss and Holstein. Consistently with α and ß diversity, the number of operational taxonomic units (OTUs) at the genus level that changed their abundance during HS was higher in Holstein (74 OTUs) than in Brown Swiss (only 20 OTUs). The most significant changes in abundance affected Acinetobacter, Chryseobacterium, Cutibacterium, Enterococcus, Lactococcus, Prevotella-9, Serratia, and Streptococcus. In conclusion, the present report confirms and extends previous studies by demonstrating that Brown Swiss cows regulate their body temperature better than the Holstein breed. The relative thermal tolerance to HS compared with Holstein is also confirmed by changes in milk uncultured microbiota, which were more evident in Holstein than in Brown Swiss.

Genotype by environment interaction due to heat stress in Brown Swiss cattle.

Due to its geographical position and a highly variable orography, Italy is characterized by several climatic areas and thus, by many different dairy cow farming systems. Brown Swiss cattle, in this context, are a very appreciated genetic resource for their adaptability and low metabolic requirement. The significant heterogeneity in farming systems may consist of genotype by environment (G × E) interactions with neglected changes in animals' rank position. The objective of this study was to investigate G × E for heat tolerance in Brown Swiss cattle for several production traits (milk, fat, and protein yield in kilograms; fat, protein, and cheese yield in percentage) and 2 derivate traits (fat-corrected milk and energy-corrected milk). We used the daily maximum temperature-humidity index (THI) range, calculated according to weather stations' data from 2008 to 2018 in Italy, and 202,776 test-day records from 23,396 Brown Swiss cows from 639 herds. Two different methodologies were applied to estimate the effect of the environmental variable (THI) on genetic parameters: (1) the reaction norm model, which uses a continuous random covariate to estimate the animal additive effect, and (2) the multitrait model, which splits each production pattern as a distinct and correlated trait according to the first (a thermal comfort condition), third (a moderate heat stress condition), and fifth (a severe heat stress condition) mean THI value quintile. The results from the reaction norm model showed a descending trend of the additive genetic effect until THI reached the value of 80. Then we recorded an increase with high extreme THI values (THI 90). Permanent environmental variance at increasing THI values revealed an opposite trend: The plot of heritability and the ratio of animal permanent environmental variance to phenotypic variance showed that when the environmental condition worsens, the additive genetic and permanent environmental component for production traits play a growing role. The negative additive genetic correlation between slope and linear random coefficient indicates no linear relationship between the production traits or under heat stress conditions, except for milk yield and protein yield. In tridimensional wireframe plots, the extreme margin decreases until a minimum of ∼0.90 of genetic correlation in the ECM trait, showing that the magnitude of G × E interaction is greater than the other traits. Genetic correlation values in Brown Swiss suggest the possibility of moderate changes in animals' estimated breeding value in heat stress conditions. Results indicated a moderate G × E interaction but significant variability in sire response related to their production level.

Effects of breed, farm intensiveness, and cow productivity on infrared predicted milk urea.

Milk urea content is receiving growing interest from science and industry as a tool to infer the protein adequacy of dairy cows' diets, nitrogen excretion and its environmental impact, and efficiency of animals' protein metabolism. Fourier-transform infrared (FTIR) prediction is a high-throughput method for rapidly and cheaply evaluating milk urea content at the population level. Existing knowledge of the major sources of variation (e.g., year, season, farming system, individual herd, and the cow's breed, parity, stage of lactation, and productive potential) is fragmentary. The objective of this work was to study at the population level the simultaneous effects of all the major sources of variation and their most important interactions. Milk urea content in 1,759,706 test day milk samples collected from 291,129 lactations of 115,819 cows from 6,430 herds over 8 yr was predicted by FTIR. The milk urea content data (and also milk protein percentage, for comparison) were analyzed using a linear model that included the effects of parity, days in milk (DIM) class, year, month, herd intensiveness level, cow productivity level, breed, and herd intensiveness and cow productivity levels within breed. All sources of variation of milk urea content proved highly significant, the most important in terms of F-value being breed > year > herd intensiveness level > parity. The ranking for milk protein was very different (DIM class > herd intensiveness level > parity > breed). The patterns of the least squares means for urea and protein contents of milk were also very different and sometimes contrasting. The seasonal variation in urea was sinusoidal. Urea content increased during the first 4 mo of lactation and then remained almost stable before decreasing after 11 mo. Specialized dairy breeds had lower average milk urea content than dual-purpose breeds; in the former case it was lower in Holsteins than in Brown Swiss, and in the latter it was lower in Simmentals than in Alpine Greys. The effect of herd intensiveness level was much stronger than the effect of cow productivity level; the increase in milk urea with increasing herd average daily milk yield was almost linear in the case of dairy breeds but curvilinear in dual-purpose breeds. The large differences in breed and the modest relationships with the cow's productive potential require further analysis at the genetic level to obtain information of potential use in genetic improvement of the dairy cow populations.

Across-countries genomic prediction using national breeding values or multitrait across-countries evaluation breeding values.

In across-country genomic predictions for dairy cattle, 2 kinds of bull information can be used as dependent variables. The first is estimated breeding value (EBV) from the national genetic evaluations, assuming genetic correlations between countries are less than 1. The second is EBV from multitrait across-countries evaluation (MACE), assuming genetic correlations between countries equal 1. In the present study, the level of bias and reliability of a cross-countries genomic prediction using national EBV or MACE EBV as the dependent variable were investigated. Data from Brown Swiss Organizations joining the InterGenomics Service by Interbull Centre (Uppsala, Sweden) were used. National and MACE EBV of 3 traits (protein yield, cow conception rate, and calving interval) from 7, 5, and 4 countries, respectively, were used, resulting in 16 trait-country combinations. Genotypes for 45,473 SNP markers and deregressed (national or MACE) EBV of 7,490; 5,833; and 5,177 bulls were used in analysis of protein yield, cow conception rate, and calving interval, respectively. For most of trait-country combinations, the use of MACE EBV via single-trait approach resulted in less biased and more reliable across-countries genomic predictions. In case some of the MACE EBV might have been inflated, the resulting single-trait genomic predictions were inflated as well. For these specific cases, the use of national EBV via multitrait approach provided less bias and more reliable across-countries genomic predictions.

Comparison of models for lactation curves of Holstein, Brown Swiss, and F1 crossbred cows under subtropical conditions.

Tropical and subtropical milk production herds in Mexico generally generate different types of milk-yield records as milk yield per month and mean production per month. Lactation curves generated by these types of records may contribute to understand milk production in the tropical regions of Mexico. The aim of this study was to compare five lactation-curve models fitted to two types of milk-yield records of Holstein, Brown Swiss, and F1 crossbred cows under subtropical conditions. The two types of records (n = 3756) used were: (1) milk yield per month (TR) and 2) mean production per months (MR). Goodness-of-fit statistics, including Akaike's information criterion (AIC) and root mean square error (RMSE), were applied to compare the models for each type of records. The Brody model provided the best goodness-of-fit when using monthly milk-yield records, while the Wilmink model provided the best goodness-of-fit for lactation milk-yield records. The RMSE and AIC values were similar between datasets. The final third of the lactation curve showed a little difference between model predictions in both datasets. The comparison of several models was useful to better describe the actual lactation curves of the herd. The Wood model may be adequate to compare information as a reference with other models for decision making process at milk production.

Association between days open and milk spectral data in dairy cows.

Data on 19,489 Brown Swiss cows reared in northeastern Italy were used to associate absorbances of individual wavenumbers within the mid-infrared range with days open (DO). Different postcalving days in milk (DIM) intervals were studied to determine the most informative milk sampling periods for predicting DO. Milk samples were analyzed using a MilkoScan (Foss Electric, Hillerød, Denmark) Fourier-transform infrared (FTIR) spectrometer for 1,060 wavenumbers (wn) ranging from 5,011 to 925 cm-1. To determine DO, we considered an insemination to lead to conception when there was no return of heat (i.e., no successive insemination) and the cow had a subsequent calving date whereby gestation length was required to be within ±30 d of 290 d. Only milk records within the first 90 DIM were considered. Associations were inferred by (1) fitting linear regression models between the DO and each individual wavenumber or milk component, and (2) fitting a Bayesian regression model that included the complete FTIR spectral data. The effects of including systematic effects (parity number, year-season, herd) in the model on these associations were also studied. These analyses were performed for the complete data (5-90 DIM) and for data stratified by DIM period (5 to 30, 31 to 60, and 61 to 90 DIM). Overall, regions of wavenumbers of the milk FTIR spectra that were associated with DO included wn 2,973 to 2,830 cm-1 [related to fat-B (C-H stretch)], wn 2,217 to 1,769 cm-1 [related to fat-A (C = O stretch)], wn 1,546 cm-1 (related to protein), wn 1,465 cm-1 (related to urea and fat), wn 1,399 to 1,245 cm-1 (related to acetone), and wn 1,110 cm-1 (related to lactose). Estimated effects depended on the DIM period, with milk samples drawn during DIM intervals 31 to 60 d and 61 to 90 d being most strongly associated with DO. These DIM intervals are also typically most associated with negative energy balance and peak lactation.

Realized genetic selection differentials in Canadian Ayrshire, Jersey, and Brown Swiss dairy cattle populations.

Estimated breeding values of a selection index, production, durability, health, and fertility traits from Canadian Ayrshire, Jersey, and Brown Swiss bulls and cows were used to study genetic selection differentials (GSD). The bulls and cows were born from 1950 and 1960, respectively. The GSD for the 3 Canadian dairy populations were studied along the 4-path selection model: sire-to-bull (SB), dam-to-bull (DB), sire-to-cow (SC), and dam-to-cow (DC) pathways. We also determined the variations in realized GSD due to herd and herd × year of conception in addition to the effects of some environmental factors on realized GSD of the SC and DC paths. The mean realized GSD of the DB were higher than those of other paths and were increasing for lifetime performance index, 305-d milk yield, 305-d fat yield, and 305-d protein yield in all 3 dairy cattle populations. We observed no clear trends in realized GSD for type traits in all 3 dairy cattle breeds except for the apparent increasing trends in realized GSD of mammary system, dairy strength, and feet and legs in the DB and SC paths of the Ayrshire breed. No clear patterns were observed in the realized GSD of daughter fertility in the SB, DB, and SC paths of all dairy cattle breeds. Realized GSD for somatic cell score showed increasing and favorable trends in the 3 most influential selection paths (SB, DB, and SC). Year of conception influenced realized GSD of artificial insemination bulls in Ayrshire, Jersey, and Brown Swiss dairy populations. Selection emphases for the SC path generally increased with time. There was considerable variation among herds in selection pressures applied in the SC and DC pathways but no clear association with housing system or region. This study demonstrates that variations exist among herds of minor dairy cattle breeds in their selection for economically important traits. These variations offer opportunities for further improvements in these populations.

Fatty acid profilies and some meat quality traits at different slaughter weights of Brown Swiss bulls.

This research was done to detect some meat quality traits and tissue fatty acid combination of the longissimus dorsi thoracis (LT) muscle of Brown Swiss bulls at the different slaughter weights (SW). The animal material of the study comprised 20 Brown Swiss bulls. In the study, Brown Swiss bulls were divided into two groups according to their SW as low (LSW (n = 10); 431-503 kg) and high (HSW (n = 10); 504-583 kg). In the study, the LSW group showed the lowest final pH value (pHF) (5.44) (P < 0.05). As the SW increase, the L* (lightness) value decreased in the LT muscle of Brown Swiss bulls (P > 0.05). In the research, the differences observed between the SW groups considering a* (redness) and C (chroma) values were found significant (P < 0.05). LT muscle water holding capacity (PL) decreased (P < 0.01) with increasing slaughter weight. In the study, the differences observed between SW groups in terms of drip losses (DL) after 3-day (DRP3) and 7-day (DRP7) storages and cooking losses (CL) determined were found insignificant (P > 0.05). Freeze-thaw loss (FL) and ether extract (PEE) were found 4.35% and 1.01% higher, respectively, in the HSW group than the LSW group (P < 0.05). Cholesterol content was determined as 66.15 and 70.68 mg 100 g-1 meat in LSW and HSW groups, respectively. The ratios of n-6/n-3 (P < 0.05) and PUFA/SFA (P > 0.05) in the LT muscle decreased with the increase of SW. As a result, when LSW and HSW slaughter weight groups were evaluated considering the water losses causing financial losses in meat and fatty acids having beneficial effects on human health, it was seen that the LSW group came to the fore.

Estimation of maximum thermo-hygrometric index thresholds affecting milk production in Italian Brown Swiss cattle.

It is known that heat stress affects dairy cow performance in multiple ways: physiological, behavioral, reproductive, and productive. The aim of the present study was to determine if a threshold of temperature-humidity index (THI) exists for multiple milk production traits (milk yield, fat-corrected milk, protein and fat yield and percentage, energy-corrected milk, cheese production, and cheese yield) in Italian Brown Swiss dairy cows from the period 15 d before the day of the Italian Breeders Association test-day sampling. A 10-yr data set (2009-2018) containing 202,776 test-day records of 23,296 Brown Swiss cows was matched with the maximum THI. In all parities considered, no THI thresholds were observed for milk yield in Brown Swiss. In contrast, a THI threshold of 75 was identified for fat-corrected milk. No THI threshold was found for fat percentage, but fat yield showed the highest THI thresholds in cows of first and second parity. Protein yield and cheese production were affected by heat stress with average THI threshold of 74. The THI thresholds identified indicate that the Brown Swiss breed has higher thermal tolerance versus literature values reported for Holstein cows. As THI rises, Brown Swiss cows tend to produce the same volume of milk, but with a decreasing quality with regard to components. Further study is necessary to estimate the genetic component of heat tolerance, in Brown Swiss cattle, considering that the correct estimation of THI thresholds represents the first step to identify components that could be included in selection procedures.

Milk urea nitrogen concentration is higher in Brown Swiss than in Holstein dairy cows despite identical feeding.

Milk urea nitrogen (MUN) content is closely related to blood urea nitrogen (BUN) concentration and reflects the balance of dietary crude protein and energy supply for ruminal microbial metabolism. The present study investigated whether the higher MUN content in Brown Swiss (BSW) compared with Holstein (HOL) cows is related to milk production and feeding conditions. Therefore, we evaluated test-day records of three consecutive official milk recordings from 86 BSW and 200 HOL cows kept on the same farm under identical feeding and management conditions. In addition, the relationships between BUN and MUN assessed either by an enzymatic method or by mid-infrared spectroscopy were analysed. For the second objective, milk and blood samples (1,112 samples each) were collected in parallel from day 5 until day 150 of lactation from 141 dairy cows housed at different farms. Concentrations of MUN determined either enzymatically (MUNENZ ) or by Fourier transform infrared spectroscopy (FTIR; MUNIR ) were regressed on the BUN concentrations of the concomitantly obtained blood samples. Both MUNIR and MUNENZ were well correlated with BUN (r = .93 and .89 respectively). Concentration of MUN was higher in BSW compared with HOL independently of lactational stage or parity number (p < .0001). Protein and fat content were higher in BSW than in HOL (p < .05). Primiparous cows had lower milk yield and ECM (p < .001 for BSW, p < .0001 for HOL) than multiparous in both breeds. Multiparous BSW had a similar milk production than primiparous HOL (p = .13). In conclusion, BSW cows have higher MUN than HOL when kept under identical feeding and management conditions. The higher MUN in BSW compared with HOL cows is not related to milk production and therefore rather genetically determined.

Detailed macro- and micromineral profile of milk: Effects of herd productivity, parity, and stage of lactation of cows of 6 dairy and dual-purpose breeds.

The aim of this study was to quantify the major sources of variation in the levels of 15 minerals in individual milk samples collected from cows raised in multibreed dairy herds. The herds (n = 27) were classified into 2 categories, according to milk productivity. Milk productivity was based on the net energy of lactating cows' average daily milk yield. Milk samples were collected from 240 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, and Jersey) and 3 dual-purpose (Simmental, Rendena, and Alpine Grey). The samples were analyzed for macro-elements (Na, Mg, P, S, K, and Ca), essential micro-elements (Mn, Fe, Cu, Zn, and Se), and environmental micro-elements (B, Si, Sr, and Sn), using inductively coupled plasma-optical emission spectrometry. Data were analyzed using a linear mixed model that included fixed effects of days in milk (DIM), parity, breed, and herd productivity, and a random effect of herd-date within productivity level. Results showed that the effect of herd-date varied across minerals. It was especially large for environmental minerals (ranging from 47 to 91% of total variance) and ranged from 11 to 61% for macrominerals and essential microminerals. Milk samples collected from farms with a high level of herd productivity had a richer mineral profile than samples from low-productivity herds. Parity only influenced macrominerals, with the exception of S and Ca, while DIM influenced almost all minerals, with a few exceptions among the environmental elements. Differences in mineral profile were small between specialized and dual-purpose breeds, but they were large within the group of the specialized cows. These breed differences were reduced after adjusting for milk quality and yield, particularly in the case of milk Mg, S, Ca, Mn, and Zn levels. Milk samples from the Jersey and Brown Swiss cows had higher mineral levels (Sn excluded) than milk from the Holstein-Friesian cows; the other breeds of Alpine origin produced milk of intermediate quality. Our findings suggest that breed has a stronger effect on macrominerals and some of the essential microminerals than herd productivity, parity, and DIM. The modification of the mineral profile in milk seems possible for many minerals, but it likely depends on genetics (e.g., breed, selection) and on environmental and management factors in variable proportions according to the mineral considered.

Genomic analysis of perinatal sucking reflex in German Brown Swiss calves.

A healthy sucking reflex is essential for newborn calves to ensure sufficient colostrum intake in the first few hours postpartum. In recent decades, European Brown Swiss breeders have repeatedly reported that some calves lack the ability to consume colostrum directly after birth due to an absent sucking reflex. In this study, we collected the phenotypes of more than 5,500 German Brown Swiss calves and performed variance component estimation with sire threshold models using Markov chain Monte Carlo algorithms. The 50K (777K) genotypes of nearly 2,000 (200) calves were collected, and an imputation was performed for all 50K genotypes up to 777K. Genome-wide association studies (GWAS) for the trait sucking reflex were conducted for all 777K genotypes. Depending on the trait coding, a low heritability was estimated to range from 0.08 to 0.11. The GWAS results identified 34 trait-associated SNP on 6 different chromosomes. Post-GWAS analyses showed significant overrepresentation of Gene Ontologies for central nervous development and several regulative processes. Functional annotation clustering and pathway analysis revealed relations to lipid metabolism, immune and endocrine systems, and signal transduction. The results of this study suggest that breeding for an improved sucking reflex is possible but requires large data sets for the estimation of reliable breeding values (either large progeny testing groups or a large reference genome in a genomic selection program).

Short communication: Genomic prediction using imputed whole-genome sequence variants in Brown Swiss Cattle.

The accuracy of genomic prediction determines response to selection. It has been hypothesized that accuracy of genomic breeding values can be increased by a higher density of variants. We used imputed whole-genome sequence data and various single nucleotide polymorphism (SNP) selection criteria to estimate genomic breeding values in Brown Swiss cattle. The extreme scenarios were 50K SNP chip data and whole-genome sequence data with intermediate scenarios using linkage disequilibrium-pruned whole-genome sequence variants, only variants predicted to be missense, or the top 50K variants from genome-wide association studies. We estimated genomic breeding values for 3 traits (somatic cell score, nonreturn rate in heifers, and stature) and found differences in accuracy levels between traits. However, among different SNP sets, accuracy was very similar. In our analyses, sequence data led to a marginal increase in accuracy for 1 trait and was lower than 50K for the other traits. We concluded that the inclusion of imputed whole-genome sequence data does not lead to increased accuracy of genomic prediction with the methods.

Estimation of relative economic weights and the marginal willingness to pay for breeding traits of Brown Swiss cattle using discrete choice experiments.

Breeding traits are usually combined in a total merit index according to their economic weights to maximize genetic gain based on economic merit. However, this maximization may not always be the aim of the selection decisions by farm managers. A discrete choice experiment was used to evaluate the importance of traits in terms of the selection decisions of farm managers operating in different environments. Six trait complexes, the semen price, the interactions between these traits, and significant characteristics of the farms were included in a conditional logit model to estimate relative economic weights and the marginal willingness to pay for all traits. Milk value, conformation/udder, and fitness were the most important traits for the farmers, and significant interactions indicated that fitness is of greater importance on organically managed farms than on conventional farms. Farm managers with an advanced education placed more weight on the milk value trait than farm managers without advanced education. On conventional farms, managers weighted the traits milk value and conformation/udder highly. The conformation/udder and fitness trait complexes were important on organic farms. A new trait called perinatal sucking behavior of newborn calves should be included in the total merit index.

Impact of crossbreeding Holstein and Brown Swiss cows on milk yield, composition, and fatty acid profiles in subtropics.

Milk yield (MY), composition, and fatty acid profiles of purebred Holstein (HO) cows, Brown Swiss (BS), and their F1 crossbreds (HS) were compared under subtropical climate in Egypt. Pure HO had significantly greater 305-MY, total-MY, and daily-MY (p < 0.05) than pure BS and crossbred HS. Furthermore, HO and HS had significantly higher peak-MY (44.2 and 43.3 kg, respectively) than BS (36.1 kg). In comparison with HO, BS had significantly higher milk fat, protein, total solids, and solid-not-fat % (p < 0.05); however, no significant differences were observed between BS and HS for milk fat %. The milk fat of BS had higher concentrations of saturated (C17:0 and C18:0) fatty acids (FA) than that of the HO and HS (p = 0.001 and 0.008, respectively). Content of C4:0, C6:0, C8:0, C12:0, and C15.0 FA did not differ between genotypes. Milk from HO and BS had significantly higher concentrations of unsaturated (C20:1 and C20:5) FA than that from HS (p < 0.05). C14:1 (myristoleic), C16:1 (palmitoleic), and C18:2 (linoleic) FA contents were similar for all genotypes. In conclusion, BS surpassed HO for all milk composition traits and some FA components; however, HS had comparable milk fat percentage with BS. There appears to be an opportunity to modify the concentration of certain FA by breeding.

Genome-wide association studies of fertility and calving traits in Brown Swiss cattle using imputed whole-genome sequences.

BACKGROUND: The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs. RESULTS: We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle. CONCLUSION: The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants.

Highly accurate sequence imputation enables precise QTL mapping in Brown Swiss cattle.

BACKGROUND: Within the last few years a large amount of genomic information has become available in cattle. Densities of genomic information vary from a few thousand variants up to whole genome sequence information. In order to combine genomic information from different sources and infer genotypes for a common set of variants, genotype imputation is required. RESULTS: In this study we evaluated the accuracy of imputation from high density chips to whole genome sequence data in Brown Swiss cattle. Using four popular imputation programs (Beagle, FImpute, Impute2, Minimac) and various compositions of reference panels, the accuracy of the imputed sequence variant genotypes was high and differences between the programs and scenarios were small. We imputed sequence variant genotypes for more than 1600 Brown Swiss bulls and performed genome-wide association studies for milk fat percentage at two stages of lactation. We found one and three quantitative trait loci for early and late lactation fat content, respectively. Known causal variants that were imputed from the sequenced reference panel were among the most significantly associated variants of the genome-wide association study. CONCLUSIONS: Our study demonstrates that whole-genome sequence information can be imputed at high accuracy in cattle populations. Using imputed sequence variant genotypes in genome-wide association studies may facilitate causal variant detection.

Multivariate factor analysis of detailed milk fatty acid profile: Effects of dairy system, feeding, herd, parity, and stage of lactation.

We investigated the potential of using multivariate factor analysis to extract metabolic information from data on the quantity and quality of milk produced under different management systems. We collected data from individual milk samples taken from 1,158 Brown Swiss cows farmed in 85 traditional or modern herds in Trento Province (Italy). Factor analysis was carried out on 47 individual fatty acids, milk yield, and 5 compositional milk traits (fat, protein, casein, and lactose contents, somatic cell score). According to a previous study on multivariate factor analysis, a variable was considered to be associated with a specific factor if the absolute value of its correlation with the factor was ≥0.60. The extracted factors were representative of the following 12 groups of fatty acids or functions: de novo fatty acids, branched fatty acid-milk yield, biohydrogenation, long-chain fatty acids, desaturation, short-chain fatty acids, milk protein and fat contents, odd fatty acids, conjugated linoleic acids, linoleic acid, udder health, and vaccelenic acid. Only 5 fatty acids showed small correlations with these groups. Factor analysis suggested the existence of differences in the metabolic pathways for de novo short- and medium-chain fatty acids and Δ9-desaturase products. An ANOVA of factor scores highlighted significant effects of the dairy farming system (traditional or modern), season, herd/date, parity, and days in milk. Factor behavior across levels of fixed factors was consistent with current knowledge. For example, compared with cows farmed in modern herds, those in traditional herds had higher scores for branched fatty acids, which were inversely associated with milk yield; primiparous cows had lower scores than older cows for de novo fatty acids, probably due to a larger contribution of lipids mobilized from body depots on milk fat yield. The statistical approach allowed us to reduce a large number of variables to a few latent factors with biological meaning and able to represent groups of fatty acids with a common origin and function. Multivariate factor analysis would therefore be a valuable tool for studying the influence of different production environments and individual animal factors on milk fatty acid composition, and for developing nutritional strategies able to manipulate the milk fatty acid profile according to consumer demand.