Efficiency of Utilizing Bulls with High Immune Response (HIR) in Terms of Reproductive Traits of PHF Cows

Reproductive traits in dairy cattle are crucial for herd productivity and profitability. This study investigates the influence of relatedness to high immune response (HIR) Immunity+ sires on reproductive performance indicators in Polish Holstein-Friesian cows. A total of 5094 cows were analyzed, categorized based on their relatedness to HIR Immunity+ sires, and assessed for various reproductive parameters, including age at first insemination, gestation length, days open, calving interval, and calving ease. The results showed that the level of relatedness to HIR Immunity+ sires influenced certain reproductive traits, such as service period, gestation length, and age at first and second calving. Additionally, cows related to HIR Immunity+ sires exhibited a higher frequency of twin pregnancies and more complicated births. While some benefits were observed in certain reproductive traits among cows related to HIR Immunity+ sires, such as reduced age at first insemination and shortened gestation length, the overall impact on reproductive efficiency remains inconclusive. Further studies are needed to fully elucidate the effects of using semen from HIR Immunity+ sires on reproductive performance in dairy cattle.

The genetic architecture of complete blood counts in lactating Holstein dairy cows

Complete blood counts (CBCs) measure the abundance of individual immune cells, red blood cells, and related measures such as platelets in circulating blood. These measures can indicate the health status of an animal; thus, baseline circulating levels in a healthy animal may be related to the productive life, resilience, and production efficiency of cattle. The objective of this study is to determine the heritability of CBC traits and identify genomic regions that are associated with CBC measurements in lactating Holstein dairy cattle. The heritability of CBCs was estimated using a Bayes C0 model. The study population consisted of 388 cows with genotypes at roughly 75,000 markers and 16 different CBC phenotypes taken at one to three time points (n = 33, 131, and 224 for 1, 2, and 3 time points, respectively). Heritabilities ranged from 0.00 ± 0.00 (red cell distribution width) to 0.68 ± 0.06 (lymphocytes). A total of 96 different 1-Mb windows were identified that explained more than 1% of the genetic variance for at least one CBC trait, with 10 windows explaining more than 1% of the genetic variance for two or more traits. Multiple genes in the identified regions have functions related to immune response, cell differentiation, anemia, and disease. Positional candidate genes include RAD52 motif-containing protein 1 (RDM1), which is correlated with the degree of immune infiltration of immune cells, and C-X-C motif chemokine ligand 12 (CXCL12), which is critically involved in neutrophil bone marrow storage and release regulation and enhances neutrophil migration. Since animal health directly impacts feed intake, understanding the genetics of CBCs may be useful in identifying more disease-resilient and feed-efficient dairy cattle. Identification of genes responsible for variation in CBCs will also help identify the variability in how dairy cattle defend against illness and injury.

Genetic profile of adaptive immune traits and relationships with parasite resistance and productivity in Scottish Blackface sheep

Gastrointestinal (GI) parasites cause significant production losses in grazing ruminants which can be mitigated by breeding animals resistant to disease. Lymphocyte cytokine production and parasite-specific Immunoglobulin A (IgA) are adaptive immune traits associated with immunity to GI parasites. To explore the utility of these traits for selective breeding purposes, this study estimated the genetic parameters of the immune traits in sheep and assessed their relationship with disease and productivity traits. Whole blood stimulation assays were performed on 1 040 Scottish Blackface lambs at two months of age in 2016-2017. Blood was stimulated with either pokeweed mitogen (PWM), a non-specific activator of lymphocytes, and Teladorsagia circumcincta (T-ci) larval antigen to activate parasite-specific T lymphocytes. The type of adaptive immune response was determined by quantifying production of cytokines interferon-gamma (IFN-γ), interleukin (IL)-4, and IL-10, which relate to T-helper type (Th) 1, Th2 and regulatory T cell responses, respectively. Serum T-ci specific IgA was also quantified. Heritabilities were estimated for each immune trait by univariate analyses. Genetic and phenotypic correlations were estimated between different immune traits, and between immune traits vs. disease and productivity traits that were recorded at three months of age. Disease phenotypes were expressed as faecal egg counts (FEC) of nematode parasites (Strongyles and Nematodirus), faecal oocyst counts (FOC) of coccidian parasites, and faecal soiling score; production was measured as lamb live weight. Significant genetic variation was observed in all immune response traits. Heritabilities of cytokine production varied from low (0.14 ± 0.06) to very high (0.77 ± 0.09) and were always significantly greater than zero (P < 0.05). IgA heritability was found to be moderate (0.41 ± 0.09). Negative associations previously identified between IFN-γ production and FOC, and IL-4 production and strongyle FEC, were not evident in this study, potentially due to the time-lag between immune and parasitology measures. Instead, a positive genetic correlation was found between FOC and PWM-induced IFN-γ production, while a negative genetic correlation was found between FOC and T-ci induced IL-10. Live weight was negatively genetically correlated with IFN-γ responses. Overall, IFN-γ and IL-4 responses were positively correlated, providing little evidence of cross-regulation of Th1 and Th2 immunity within individual sheep. Furthermore, T-ci specific IgA was highly positively correlated with PWM-induced IL-10, indicating a possible role for this cytokine in IgA production. Our results suggest that while genetic selection for adaptive immune response traits is possible and may be beneficial for parasite control, selection of high IFN-γ responsiveness may negatively affect productivity.

Genetic correlations of direct and indirect genetic components of social dominance with fitness and morphology traits in cattle

BACKGROUND

Within the same species, individuals show marked variation in their social dominance. Studies on a handful of populations have indicated heritable genetic variation for this trait, which is determined by both the genetic background of the individual (direct genetic effect) and of its opponent (indirect genetic effect). However, the evolutionary consequences of selection for this trait are largely speculative, as it is not a usual target of selection in livestock populations. Moreover, studying social dominance presents the challenge of working with a phenotype with a mean value that cannot change in the population, as for every winner of an agonistic interaction there will necessarily be a loser. Thus, to investigate what could be the evolutionary response to selection for social dominance, it is necessary to focus on traits that might be correlated with it. This study investigated the genetic correlations of social dominance, both direct and indirect, with several morphology and fitness traits. We used a dataset of agonistic contests involving cattle (Bos taurus): during these contests, pairs of cows compete in ritualized interactions to assess social dominance. The outcomes of 37,996 dominance interactions performed by 8789 cows over 20 years were combined with individual data for fertility, mammary health, milk yield and morphology and analysed using bivariate animal models including indirect genetic effects.

RESULTS

We found that winning agonistic interactions has a positive genetic correlation with more developed frontal muscle mass, lower fertility, and poorer udder health. We also discovered that the trends of changes in the estimated breeding values of social dominance, udder health and more developed muscle mass were consistent with selection for social dominance in the population.

CONCLUSIONS

We present evidence that social dominance is genetically correlated with fitness traits, as well as empirical evidence of the possible evolutionary trade-offs between these traits. We show that it is feasible to estimate genetic correlations involving dyadic social traits.

Correlations of milk and serum element concentrations with production and management traits in dairy cows

The present study investigated the potential consequences, positive or negative, that selection for favorable production-related traits may have on concentrations of vitamin B12 and key chemical elements in dairy cow milk and serum and the possible impact on milk healthiness, and associated benefits, for the dairy product consumer. Milk and serum samples (950 and 755, respectively) were collected from Holstein-Friesian dairy cows (n = 479) on 19 occasions over a 59-mo period, generating 34,258 individual records, and analyzed for concentrations of key trace and quantity elements, heavy metals, and milk vitamin B12. These data were then matched to economically important production data (milk, fat, and protein yield) and management data (dry matter intake, liveweight, and body condition score). Multivariate animal models, including full pedigree information, were used to analyze data and investigate relationships between traits of interest. Results highlighted negative genetic correlations between many quantity and trace elements in both milk and serum with production and management traits. Milk yield was strongly negatively correlated with the milk quantity elements Mg and Ca (genetic correlation between traits, ra = -0.58 and -0.63, respectively) as well as the trace elements Mn, Fe, Ni, Cu, Zn, and Mo (ra = -0.32, -0.58, -0.52, -0.40, -0.34, and -0.96, respectively); and in serum, Mg, Ca, Co, Fe, and Zn (ra = -0.50, -0.36, -0.68, -0.54, and -0.90, respectively). Strong genetic correlations were noted between dry matter intake with V (ra = 0.97), Fe (ra = -0.69), Ni (ra = -0.81), and Zn (ra = -0.75), and in serum, strong negative genetic correlations were observed between dry matter intake with Ca and Se (ra = -0.95 and -0.88, respectively). Body condition score was negatively correlated with serum P, Cu, Se, and Pb (ra = -0.45, -0.35, -0.51, and -0.64, respectively) and positively correlated with Mn, Fe, and Zn (ra = 0.40, 0.71, and 0.55, respectively). Our results suggest that breeding strategies aimed at improving economically important production-related traits would most likely result in a negative impact on levels of beneficial nutrients within milk for human consumption (such as Mg, Ca, Fe, Zn, and Se).

Genetic parameters of differential somatic cell count, milk composition, and cheese-making traits measured and predicted using spectral data in Holstein cows

Mastitis is one of the most prevalent diseases in dairy cattle and is the cause of considerable economic losses. Alongside somatic cell count (SCC), differential somatic cell count (DSCC) has been recently introduced as a new indicator of intramammary infection. The DSCC is expressed as a count or a proportion (%) of polymorphonuclear neutrophils plus lymphocytes (PMN-LYM) in milk somatic cells. These numbers are complemented to total somatic cell count or to 100 by macrophages (MAC). The aim of this study was to investigate the genetic variation and heritability of DSCC, and its correlation with milk composition, udder health indicators, milk composition, and technological traits in Holstein cattle. Data used in the analysis consisted in single test-day records from 2,488 Holstein cows reared in 36 herds located in northern Italy. Fourier-transform infrared (FTIR) spectroscopy was used to predict missing information for some milk coagulation and cheese-making traits, to increase sample size and improve estimation of the genetic parameters. Bayesian animal models were implemented via Gibbs sampling. Marginal posterior means of the heritability estimates were 0.13 for somatic cell score (SCS); 0.11 for DSCC, MAC proportion, and MAC count; and 0.10 for PMN-LYM count. Posterior means of additive genetic correlations between SCS and milk composition and udder health were low to moderate and unfavorable. All the relevant genetic correlations between the SCC traits considered and the milk traits (composition, coagulation, cheese yield and nutrients recovery) were unfavorable. The SCS showed genetic correlations of -0.30 with the milk protein proportion, -0.56 with the lactose proportion and -0.52 with the casein index. In the case of milk technological traits, SCS showed genetic correlations of 0.38 with curd firming rate (k₂₀), 0.45 with rennet coagulation time estimated using the curd firming over time equation (RCT_eq), -0.39 with asymptotic potential curd firmness, -0.26 with maximum curd firmness (CF_max), and of -0.31 with protein recovery in the curd. Differential somatic cell count expressed as proportion was correlated with SCS (0.60) but had only 2 moderate genetic correlations with milk traits: with lactose (-0.32) and CF_max (-0.33). The SCS was highly correlated with the log PMN-LYM count (0.79) and with the log MAC count (0.69). The 2 latter traits were correlated with several milk traits: fat (-0.38 and -0.43 with PMN-LYM and MAC counts, respectively), lactose percentage (-0.40 and -0.46), RCT_eq (0.53 and 0.41), t_max (0.38 and 0.48). Log MAC count was correlated with k₂₀ (+0.34), and log PMN-LYM count was correlated with CF_max (-0.26) and weight of water curd as percentage of weight of milk processed (-0.26). The results obtained offer new insights into the relationships between the indicators of udder health and the milk technological traits in Holstein cows.

Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows

Bovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms to predict the udder health status of cows. In this study, we compared eight different machine learning methods (Linear Discriminant Analysis, Generalized Linear Model with logit link function, Naïve Bayes, Classification and Regression Trees, k-Nearest Neighbors, Support Vector Machines, Random Forest and Neural Network) to predict udder health status of cows based on somatic cell counts. Prediction accuracies of all methods were above 75%. According to different metrics, Neural Network, Random Forest and linear methods had the best performance in predicting udder health classes at a given test-day (healthy or mastitic according to somatic cell count below or above a predefined threshold of 200,000 cells/mL) based on the cow’s milk traits recorded at previous test-day. Our findings suggest machine learning algorithms as a promising tool to improve decision making for farmers. Machine learning analysis would improve the surveillance methods and help farmers to identify in advance those cows that would possibly have high somatic cell count in the subsequent test-day.

Genetic parameters for rectal temperature, respiration rate, and drooling score in Holstein cattle and their relationships with various fertility, production, body conformation, and health traits

Genetic selection for improved climatic resilience is paramount to increase the long-term sustainability of high-producing dairy cattle, especially in face of climate change. Various physiological indicators, such as rectal temperature (RT), respiration rate score (RR), and drooling score (DS), can be used to genetically identify animals with more effective coping mechanisms in response to heat stress events. In this study, we investigated genetic parameters for RT, RR (score from 1-3), and DS (score from 1-3). Furthermore, we assessed the genetic relationship among these indicators and other economically important traits for the dairy cattle industry. After data editing, 59,265 (RT), 30,290 (RR), and 30,421 (DS) records from 13,592 lactating Holstein cows were used for the analyses. Variance components were estimated based on a multiple-trait repeatability animal model. The heritability ± standard error estimate for RT, RR, and DS was 0.06 ± 0.01, 0.04 ± 0.01, and 0.02 ± 0.01, respectively, whereas their repeatability was 0.19, 0.14, and 0.14, respectively. Moderate genetic correlations of RR with RT and DS (0.26 ± 0.11 and 0.25 ± 0.16) and nonsignificant correlation between RT and DS (-0.11 ± 0.14) were observed. Furthermore, the approximate genetic correlations between RT, RR, and DS with 12 production, 29 conformation, 5 fertility and reproduction, 5 health, and 9 longevity-indicator traits were assessed. In general, the approximate genetic correlations calculated were low to moderate. In summary, 3 physiological indicators of heat stress response were measured in a large number of animals and shown to be lowly heritable. There is a value in developing a selection index including all the 3 indicators to improve heat tolerance in dairy cattle. All the unfavorable genetic relationships observed between heat tolerance and other economically important traits can be accounted for in a selection index to enable improved climatic resilience while also maintaining or increasing productivity in Holstein cattle.

Inverted CD4+/CD8+ T cell ratio in Boran (Bos indicus) cattle

The CD4⁺/CD8⁺ ratio is used as a marker of the immune regulation of T cell balance. When the ratio in peripheral blood is less than 1, this is considered an indication of immune suppression in an individual. Previous work on bovine Peripheral Blood Mononuclear Cells (PBMC) has consistently reported a ratio ≥1 as seen in other mammalian hosts, i.e. higher circulating CD4⁺ cell numbers than CD8⁺ cell numbers. However, a consistent inverted CD4⁺/CD8⁺ ratio (<1) was observed in Boran cattle, an African Bos indicus breed. The T cell populations were characterized in Boran cattle (n = 52), revealing higher percentages of circulating CD8⁺ cells (31.9 % average) than CD4⁺ cells (19.1 % average), thus resulting in the inversion of the expected T cell homeostasis in these animals. The results show that this inversion is not an effect of age or relatedness of the cattle, rather, it was shared by almost all Boran cattle used in this study. Despite this inversion being a feature shared by both males and females, the female cattle had significantly higher CD4⁺/CD8⁺ ratios than the male Boran. This paper describes the characteristics of the T cell fractions in the study animals and compares the findings to those of other Boran cattle in Kenya, and four other cattle breeds representing African indicine, African taurine, Brazilian indicine and European taurine cattle. We demonstrate that the consistent observation of inverted CD4⁺/CD8⁺ cell ratio was restricted to the Boran.

Genetic parameters for somatic cell count (SCC) and milk production traits of Guzerá cows using data normalized by different procedures

This study aimed to estimate the genetic parameters for somatic cell count (SCC) and the genetic association between SCC and milk production traits using two different methods of SCC normalization. The dataset contained information on 8870 lactation records of 6172 Guzerá dairy cows selected for dual-purpose from 95 herds. The lactation means of SCC were normalized in two ways: (a) SCC₁ = log₁₀ (SCC) and (b) SCC₂ = log₂ (SCC/100) + 3. Multivariate analyses were performed considering milk production traits over the course of 305 days of lactation. Estimates of the variance components and genetic parameters were carried out by the Bayesian inference method, applying Gibbs sampling. Single chains of 2,000,000 iterations were used, with sampling discards of the first 5000 chains and a sampling period of every 50 iterations. The deviation of information criteria (DIC) was used to evaluate the best transformation for standardization of the SCC data, comparing analysis 1 (milk production traits over 305 days and SCC₁) with analysis 2 (milk production traits over 305 days and SCC₂). According to the data structure of this study, SCC₁ normalization was the most efficient method and produced better estimates than normalization by the SCC₂ method. The heritability estimates for SCC were low regardless of the transformation method used, indicating a small possibility of expressive genetic gains from the direct selection of these traits. However, the repeatability indicated the potential for increasing heritability estimates if the effects of the permanent environment were reduced. The genetic correlations between the milk yield and SCC traits do not indicate the possibility of a correlated genetic gain from the direct selection of one trait. However, concomitant selection for milk production traits and SCC will likely not affect the individual response either.

The genetic architecture of helminth-specific immune responses in a wild population of Soay sheep (Ovis aries)

Much of our knowledge of the drivers of immune variation, and how these responses vary over time, comes from humans, domesticated livestock or laboratory organisms. While the genetic basis of variation in immune responses have been investigated in these systems, there is a poor understanding of how genetic variation influences immunity in natural, untreated populations living in complex environments. Here, we examine the genetic architecture of variation in immune traits in the Soay sheep of St Kilda, an unmanaged population of sheep infected with strongyle gastrointestinal nematodes. We assayed IgA, IgE and IgG antibodies against the prevalent nematode Teladorsagia circumcincta in the blood plasma of > 3,000 sheep collected over 26 years. Antibody levels were significantly heritable (h² = 0.21 to 0.57) and highly stable over an individual’s lifespan. IgA levels were strongly associated with a region on chromosome 24 explaining 21.1% and 24.5% of heritable variation in lambs and adults, respectively. This region was adjacent to two candidate loci, Class II Major Histocompatibility Complex Transactivator (CIITA) and C-Type Lectin Domain Containing 16A (CLEC16A). Lamb IgA levels were also associated with the immunoglobulin heavy constant loci (IGH) complex, and adult IgE levels and lamb IgA and IgG levels were associated with the major histocompatibility complex (MHC). This study provides evidence of high heritability of a complex immunological trait under natural conditions and provides the first evidence from a genome-wide study that large effect genes located outside the MHC region exist for immune traits in the wild.

Understanding how immune responses vary in natural populations can give an insight into how infection affects the ability of hosts and parasites to survive and reproduce, and how this drives evolutionary and ecological dynamics. Yet, very little is known about how immune responses vary over an individual’s lifetime and how genes contribute to this variation under natural conditions. Our study investigates the genetic architecture of variation in three antibody types, IgA, IgE and IgG in a wild population of Soay sheep on the St Kilda archipelago in North-West Scotland. Using data collected over 26 years, we show that antibody levels have a heritable basis in lambs and adults and are stable over an individual’s lifetime. We also identify several genomic regions with large effects on immune responses. Our study offers the first insights into the genetic control of immunity in a wild population, which is essential to understand how immune profiles vary in challenging natural conditions and how natural selection maintains genetic variation in complex immune traits.

Genetic and Epigenetic Regulation of Immune Response and Resistance to Infectious Diseases in Domestic Ruminants

Infectious diseases are the outcome of complex interactions between the host, pathogen, and environment. After exposure to a pathogen, the host immune system uses various mechanisms to remove the pathogen. However, environmental factors and characteristics of pathogens can compromise the host immune responses and subsequently alter the outcome of infection. In this article, genetic and epigenetic factors that shape the individual variation in mounting protective responses are reviewed. Different approaches that have been used by researchers to investigate the genetic regulation of immunity in ruminants and various sources of genetic information are discussed.

Phenotypic and genetic analysis of milk and serum element concentrations in dairy cows

Enhancing micronutrient (i.e., mineral and vitamin) concentrations within milk and serum from dairy cows is important for both the health of the cow and the nutritive value of the milk for human consumption. However, a good understanding of the genetics underlying the micronutrient content in dairy cattle is needed to facilitate such enhancements through feeding or breeding practices. In this study, milk (n = 950) and serum (n = 766) samples were collected from Holstein-Friesian dairy cows (n = 479) on 19 occasions over a 59-mo period and analyzed for concentrations of important elements. Additionally, a subset of 256 milk samples was analyzed for concentrations of vitamin B₁₂. Cows belonged to 2 genetic lines (average and highest genetic merit for milk fat plus protein yield) and were assigned to 1 of 2 diets based on either a by-product or homegrown ration. Univariate models accounting for repeated records were used to analyze element and vitamin B₁₂ data and investigate the effect of genotype and feeding system as well as derive estimates of variance components and genetic parameters. Bivariate models were used to study correlations both within and between milk and serum. Only concentrations of Hg in milk were seen to be affected by genotype, with higher concentrations in cows with high genetic merit. In contrast, element concentrations were influenced by feeding system such that cows fed the homegrown diet had increased milk concentrations of Ca, Cu, I, Mn, Mo, P, and K and increased serum concentrations of Cd, Cu, Fe, Mo, and V. Cows on the by-product diet had increased milk concentrations of Mg, Se, and Na and increased serum concentrations of P and Se. Heritability (h²) estimates were obtained for 6 milk and 4 serum elements, including Mg (h²_milk = 0.30), K (h²_serum = 0.18), Ca (h²_milk = 0.20; h²_serum = 0.12), Mn (h²_milk = 0.14), Cu (h²_serum = 0.22), Zn (h²_milk = 0.24), Se (h²_milk = 0.15; h²_serum = 0.10), and Mo (h²_milk = 0.19). Significant estimates of repeatability were observed in all milk and serum quantity elements (Na, Mg, P, K, and Ca) as well as 5 milk and 7 serum trace elements. Only K in milk and serum was found to have a significant positive genetic and phenotypic correlation (0.52 and 0.22, respectively). Significant phenotypic associations were noted between milk and serum Ca (0.17), Mo (0.19), and Na (-0.79). Additional multivariate analyses between measures within sample type (i.e., milk or serum) revealed significant positive associations, both phenotypic and genetic, between some of the elements. In milk, Se was genetically correlated with Ca (0.63), Mg (0.59), Mn (0.40), P (0.53), and Zn (0.52), whereas in serum, V showed strong genetic associations with Cd (0.71), Ca (0.53), Mn (0.63), Mo (0.57), P (0.42), K (0.45), and Hg (-0.44). These results provide evidence that element concentrations in milk and blood of dairy cows are significantly influenced by both diet and genetics and demonstrate the potential for genetic selection and dietary manipulation to alter nutrient concentration to improve both cow health and the healthfulness of milk for human consumption.

Genetic correlations of fighting ability with somatic cells and longevity in cattle

The success in competitions may be stressful for animals and costly in terms of immune functions and longevity. Focusing on Aosta Chestnut and Aosta Black Pied cattle, selected for their fighting ability in traditional competitions, this study investigated the genetic relationships of fighting ability with udder health traits (somatic cell score and two threshold traits for somatic cells), longevity (length of productive life and number of calvings) and test-day milk, fat and protein yield. Herdbook information and phenotypic records that have been routinely collected for breeding programs in 16 years were used for the abovementioned traits. Data belonged to 9328 cows and 19 283 animals in pedigree. Single-trait animal model analyses were run using a Gibbs sampling algorithm to estimate the variance components of traits, and bivariate analyses were then performed to estimate the genetic correlations. Moderate positive genetic correlations (ra) were found for fighting ability with somatic cell score (ra=0.255), suggesting that greater fighting ability is genetically related to a detriment in udder health, in agreement with the theory. The high positive genetic correlation between fighting ability and longevity (average ra=0.669) suggests that the economic importance of fighting ability (the winning cows get an higher price at selling) had probably masked the true genetic covariances. The genetic correlation between milk yield traits and fighting ability showed large intervals, but the negative values (average ra=-0.121) agreed with previous research. This study is one of the few empirical studies on genetic correlations for the competitive success v. immune functions and longevity traits. The knowledge of the genetic correlations among productive and functional traits of interest, including fighting ability, is important in animal breeding for a sustainable genetic improvement.

Immune-associated traits measured in milk of Holstein-Friesian cows as proxies for blood serum measurements

Previous work has highlighted that immune-associated (IA) traits measurable in blood are associated with health, productivity, and reproduction in dairy cows. The aim of the present study was to determine relationships between IA traits measured in blood serum and those simultaneously measured in milk as well as their association with disease phenotypes. All animals were Holstein-Friesian cows from the Langhill research herd (n = 546) housed at the SRUC Dairy Research Centre in Scotland. Milk and serum samples were collected on 20 separate occasions between July 2010 and March 2015 and analyzed by ELISA for haptoglobin (Hp), tumor necrosis factor-α (TNF-α), and natural antibodies binding keyhole limpet hemocyanin (NAb_KLH) and lipopolysaccharide (NAb_LPS). Data were analyzed using mixed linear models that included pedigree information. Analyses revealed positive phenotypic correlations between milk and serum NAb (0.59 ≤ r ≤ 0.77), Hp (r = 0.37), and TNF-α (r = 0.12). Milk and serum NAb were also found to have a strong genetic correlation (0.81 ≤ r ≤ 0.94) and were genetically correlated with cow lameness (0.66 and 0.79 for milk NAb_KLH and serum NAb_LPS, respectively). Clinical mastitis was found to be phenotypically correlated with both milk and serum Hp (0.09 ≤ r ≤ 0.23). Serum Hp was also strongly genetically correlated with other cellular IA traits such as percent NKp46⁺ (a natural killer cell marker; 0.35) and percent peripheral blood mononuclear cells (PBMC; -0.90). Similarly, genetic correlations were found to exist between serum TNF-α and percent NKp46⁺ (0.22), percent PBMC (0.41), and percent lymphocytes (0.47). Excluding serum Hp, all milk and serum IA traits were repeatable, ranging from 0.11 (milk Hp) to 0.43 (serum NAb_LPS). Between-animal variation was highest in milk and serum NAb (0.34-0.43) and significant estimates of heritability were also observed in milk and serum NAb (0.17-0.37). Our findings show that certain IA traits, such as NAb_KLH and NAb_LPS, found in milk and serum are strongly correlated and highlight the potential of using routinely collected milk samples as a less invasive and cost-effective source of informative data for predictive modeling of animal IA traits.

A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle

Over the past 100 yr, the range of traits considered for genetic selection in dairy cattle populations has progressed to meet the demands of both industry and society. At the turn of the 20th century, dairy farmers were interested in increasing milk production; however, a systematic strategy for selection was not available. Organized milk performance recording took shape, followed quickly by conformation scoring. Methodological advances in both genetic theory and statistics around the middle of the century, together with technological innovations in computing, paved the way for powerful multitrait analyses. As more sophisticated analytical techniques for traits were developed and incorporated into selection programs, production began to increase rapidly, and the wheels of genetic progress began to turn. By the end of the century, the focus of selection had moved away from being purely production oriented toward a more balanced breeding goal. This shift occurred partly due to increasing health and fertility issues and partly due to societal pressure and welfare concerns. Traits encompassing longevity, fertility, calving, health, and workability have now been integrated into selection indices. Current research focuses on fitness, health, welfare, milk quality, and environmental sustainability, underlying the concentrated emphasis on a more comprehensive breeding goal. In the future, on-farm sensors, data loggers, precision measurement techniques, and other technological aids will provide even more data for use in selection, and the difficulty will lie not in measuring phenotypes but rather in choosing which traits to select for.