Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle

Decoding epigenetic markers: implications of traits and genes through DNA methylation in resilience and susceptibility to mastitis in dairy cows

Cattle farming faces challenges linked to intensive exploitation and climate change, requiring the reinforcement of animal resilience in response to these dynamic environments. Currently, genetic selection is used to enhance resilience by identifying animals resistant to specific diseases; however, certain diseases, such as mastitis, pose difficulties in genetic prediction. This study introduced the utilization of enzymatic methyl sequencing (EM-seq) of the blood genomic DNA from twelve dairy cows to identify DNA methylation biomarkers, with the aim of predicting resilience and susceptibility to mastitis. The analysis uncovered significant differences between cows resilient and susceptible to mastitis, with 196,275 differentially methylated cytosines (DMCs) and 1,227 Differentially Methylated Regions (DMRs). Key genes associated with the immune response and morphological traits, including ENOPH1, MYL10 and KIR2DL5A, were identified by our analysis. Quantitative trait loci (QTL) were also highlighted and the body weight trait was the most targeted by DMCs and DMRs. Based on our results, the risk of developing mastitis can potentially be estimated with as few as fifty methylation biomarkers, paving the way for early animal selection. This research sets the stage for improved animal health management and economic yields within the framework of agricultural sustainability through early selection based on the epigenetic status of animals.

Omonijo F, A Ganai N, M. Ibeagha-Awemu E, Mudasir Ahmad S. Immunotherapy in mastitis: state of knowledge, research gaps and way forward

Mastitis is an inflammatory condition that affects dairy cow's mammary glands. Traditional treatment approaches with antibiotics are increasingly leading to challenging scenarios such as antimicrobial resistance. In order to mitigate the unwanted side effects of antibiotics, alternative strategies such as those that harness the host immune system response, also known as immunotherapy, have been implemented. Immunotherapy approaches to treat bovine mastitis aims to enhance the cow's immune response against pathogens by promoting pathogen clearance, and facilitating tissue repair. Various studies have demonstrated the potential of immunotherapy for reducing the incidence, duration and severity of mastitis. Nevertheless, majority of reported therapies are lacking in specificity hampering their broad application to treat mastitis. Meanwhile, advancements in mastitis immunotherapy hold great promise for the dairy industry, with potential to provide effective and sustainable alternatives to traditional antibiotic-based approaches. This review synthesizes immunotherapy strategies, their current understanding and potential future perspectives. The future perspectives should focus on the development of precision immunotherapies tailored to address individual pathogens/group of pathogens, development of combination therapies to address antimicrobial resistance, and the integration of nano- and omics technologies. By addressing research gaps, the field of mastitis immunotherapy can make significant strides in the control, treatment and prevention of mastitis, ultimately benefiting both animal and human health/welfare, and environment health.

Genetic parameters for udder conformation traits derived from Cartesian coordinates generated by robotic milking systems in North American Holstein cattle

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms.

Genetic parameters for novel mastitis traits defined by combining test-day somatic cell score and differential somatic cell count in the first lactation of Japanese Holsteins

In this study, we aimed to improve current udder health genetic evaluations by addressing the limitations of monthly sampled somatic cell score (SCS) for distinguishing cows with robust innate immunity from those susceptible to chronic infections. The objectives were to (1) establish novel somatic cell traits by integrating SCS and the differential somatic cell count (DSCC), which represents the combined proportion of polymorphonuclear leukocytes and lymphocytes in somatic cells and (2) estimate genetic parameters for the new traits, including their daily heritability and genetic correlations with milk production traits and SCS, using a random regression test-day model (RRTDM). We derived 3 traits, termed ML_SCS_DSCC, SCS_4_DSCC_65_binary, and ML_SCS_DSCC_binary, by using milk loss (ML) estimates at corresponding SCS and DSCC levels, thresholds established in previous studies, and a threshold established from milk loss estimates, respectively. Data consisted of test-day records collected during January 2021 through March 2022 from 265 herds in Hokkaido, Japan. From these records, we extracted records between 7 to 305 d in milk (DIM) in the first lactation to fit the RRTDM. The model included the random effect of herd-test-day, the fixed effect of year-month, fixed lactation curves nested with calving age groups, and random regressions with Legendre polynomials of order 3 for additive genetic and permanent environmental effects. The analysis was performed using Gibbs sampling with Gibbsf90+ software. The averages (ranges) of the daily heritability estimates over lactation were 0.086 (0.075-0.095) for SCS, 0.104 (0.073-0.127) for ML_SCS_DSCC, 0.137 (0.014-0.297) for SCS_4_DSCC_65_binary, and 0.138 (0.115-0.185) for ML_SCS_DSCC_binary; the heritability curve for SCS_4_DSCC_65_binary was erratic. Genetic correlations within the trait decreased as the DIM interval widened, especially for those integrating DSCC, indicating that these traits should be analyzed using RRTDM rather than repeatability models. The averages (ranges) of genetic correlations with milk yield over lactation were 0.01 (-0.22 to 0.28) for SCS, -0.05 (-0.40 to 0.13) for ML_SCS_DSCC, -0.08 (-0.17 to 0.09) for SCS_4_DSCC_65_binary, and -0.08 (-0.22 to 0.27) for ML_SCS_DSCC_binary. Compared with SCS, the newly defined traits exhibited slightly stronger negative genetic correlations with milk yield. Especially in late lactation stages, the genetic correlation between ML_SCS_DSCC and milk yield was significantly below zero, with a posterior median of -0.40. Furthermore, the new traits showed positive correlations with SCS, having estimates varying from 0.68 to 0.85 for ML_SCS_DSCC, 0.14 to 0.47 for SCS_4_DSCC_65_binary, and 0.61 to 0.66 for ML_SCS_DSCC_binary, depending on DIM. Considering that ML_SCS_DSCC and ML_SCS_DSCC_binary have relatively high heritability (compared with SCS) and favorable genetic correlations with milk production traits and SCS, their incorporation into breeding programs appears promising. Nevertheless, their genetic relationships with (sub)clinical mastitis require further investigation.

A comprehensive meta-analysis of genetic parameters for resilience and productivity indicator traits in Holstein cattle

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices.

Mendelian randomization analysis of 34,497 German Holstein cows to infer causal associations between milk production and health traits

BACKGROUND

Claw diseases and mastitis represent the most important health issues in dairy cattle with a frequently mentioned connection to milk production. Although many studies have aimed at investigating this connection in more detail by estimating genetic correlations, they do not provide information about causality. An alternative is to carry out Mendelian randomization (MR) studies using genetic variants to investigate the effect of an exposure on an outcome trait mediated by genetic variants. No study has yet investigated the causal association of milk yield (MY) with health traits in dairy cattle. Hence, we performed a MR analysis of MY and seven health traits using imputed whole-genome sequence data from 34,497 German Holstein cows. We applied a method that uses summary statistics and removes horizontal pleiotropic variants (having an effect on both traits), which improves the power and unbiasedness of MR studies. In addition, genetic correlations between MY and each health trait were estimated to compare them with the estimates of causal effects that we expected.

RESULTS

All genetic correlations between MY and each health trait were negative, ranging from - 0.303 (mastitis) to - 0.019 (digital dermatitis), which indicates a reduced health status as MY increases. The only non-significant correlation was between MY and digital dermatitis. In addition, each causal association was negative, ranging from - 0.131 (mastitis) to - 0.034 (laminitis), but the number of significant associations was reduced to five nominal and two experiment-wide significant results. The latter were between MY and mastitis and between MY and digital phlegmon. Horizontal pleiotropic variants were identified for mastitis, digital dermatitis and digital phlegmon. They were located within or nearby variants that were previously reported to have a horizontal pleiotropic effect, e.g., on milk production and somatic cell count.

CONCLUSIONS

Our results confirm the known negative genetic connection between health traits and MY in dairy cattle. In addition, they provide new information about causality, which for example points to the negative energy balance mediating the connection between these traits. This knowledge helps to better understand whether the negative genetic correlation is based on pleiotropy, linkage between causal variants for both trait complexes, or indeed on a causal association.

Transcriptomic Changes and Regulatory Networks Associated with Resistance to Mastitis in Xinjiang Brown Cattle

Xinjiang brown cattle are highly resistant to disease and tolerant of roughage feeding. The identification of genes regulating mastitis resistance in Xinjiang brown cattle is a novel means of genetic improvement. In this study, the blood levels of IL-1β, IL-6, IL-10, TNF-α, and TGF-β in Xinjiang brown cattle with high and low somatic cell counts (SCCs) were investigated, showing that cytokine levels were higher in cattle with high SCCs. The peripheral blood transcriptomic profiles of healthy and mastitis-affected cattle were constructed by RNA-seq. Differential expression analysis identified 1632 differentially expressed mRNAs (DE-mRNAs), 1757 differentially expressed lncRNAs (DE-lncRNAs), and 23 differentially expressed circRNAs (DE-circRNAs), which were found to be enriched in key pathways such as PI3K/Akt, focal adhesion, and ECM-receptor interactions. Finally, ceRNA interaction networks were constructed using the differentially expressed genes and ceRNAs. It was found that keynote genes or mRNAs were also enriched in pathways such as PI3K-Akt, cholinergic synapses, cell adhesion molecules, ion binding, cytokine receptor activity, and peptide receptor activity, suggesting that the key genes and ncRNAs in the network may play an important role in the regulation of bovine mastitis.

DNA methylation haplotype block signatures responding to Staphylococcus aureus subclinical mastitis and association with production and health traits

BACKGROUND

DNA methylation has been documented to play vital roles in diseases and biological processes. In bovine, little is known about the regulatory roles of DNA methylation alterations on production and health traits, including mastitis.

RESULTS

Here, we employed whole-genome DNA methylation sequencing to profile the DNA methylation patterns of milk somatic cells from sixteen cows with naturally occurring Staphylococcus aureus (S. aureus) subclinical mastitis and ten healthy control cows. We observed abundant DNA methylation alterations, including 3,356,456 differentially methylated cytosines and 153,783 differential methylation haplotype blocks (dMHBs). The DNA methylation in regulatory regions, including promoters, first exons and first introns, showed global significant negative correlations with gene expression status. We identified 6435 dMHBs located in the regulatory regions of differentially expressed genes and significantly correlated with their corresponding genes, revealing their potential effects on transcriptional activities. Genes harboring DNA methylation alterations were significantly enriched in multiple immune- and disease-related pathways, suggesting the involvement of DNA methylation in regulating host responses to S. aureus subclinical mastitis. In addition, we found nine discriminant signatures (differentiates cows with S. aureus subclinical mastitis from healthy cows) representing the majority of the DNA methylation variations related to S. aureus subclinical mastitis. Validation of seven dMHBs in 200 cows indicated significant associations with mammary gland health (SCC and SCS) and milk production performance (milk yield).

CONCLUSIONS

In conclusion, our findings revealed abundant DNA methylation alterations in milk somatic cells that may be involved in regulating mammary gland defense against S. aureus infection. Particularly noteworthy is the identification of seven dMHBs showing significant associations with mammary gland health, underscoring their potential as promising epigenetic biomarkers. Overall, our findings on DNA methylation alterations offer novel insights into the regulatory mechanisms of bovine subclinical mastitis, providing further avenues for the development of effective control measures.

Genetic aspects of immunoglobulins and cyclophilin A in milk as potential indicators of mastitis resistance in Holstein cows

Mastitis is one of the most frequent and costly diseases affecting dairy cattle. Natural antibodies (immunoglobulins) and cyclophilin A (CyPA), the most abundant member of the family of peptidyl prolyl cis/trans isomerases, in milk may serve as indicators of mastitis resistance in dairy cattle. However, genetic information for CyPA is not available, and knowledge on the genetic and nongenetic relationships between these immune-related traits and somatic cell score (SCS) and milk yield in dairy cattle is sparse. Therefore, we aimed to comprehensively evaluate whether immune-related traits consisting of 5 Ig classes (IgG, IgG1, IgG2, IgA, and IgM) and CyPA in the test-day milk of Holstein cows can be used as genetic indicators of mastitis resistance by evaluating the genetic and nongenetic relationships with SCS in milk. The nongenetic factors affecting immune-related traits and the effects of these traits on SCS were evaluated. Furthermore, the genetic parameters of immune-related traits according to health status and genetic relationships under different SCS environments were estimated. All immune-related traits were significantly associated with SCS and directly proportional. Additionally, evaluation using a classification tree revealed that IgA, IgG2, and IgG were associated with SCS levels. Genetic factor analyses indicated that heritability estimates were low for CyPA (0.08) but moderate for IgG (0.37), IgA (0.44), and IgM (0.44), with positive genetic correlations among Ig (0.25-0.96). We also evaluated the differences in milk yield and SCS of cows between the low and high groups according to their sires' estimated breeding value for immune-related traits. In the high group, IgA had a significantly lower SCS in milk at 7 to 30 d compared with that in the low group. Furthermore, the Ig in milk had high positive genetic correlations between healthy and infected conditions (0.82-0.99), suggesting that Ig in milk under healthy conditions could interact with those under infected conditions, owing to the genetic ability based on the level of Ig in milk. Thus, Ig in milk are potential indicators for the genetic selection of mastitis resistance. However, because only the relationship between immune-related traits and SCS was investigated in this study, further study on the relationship between clinical mastitis and Ig in milk is needed before Ig can be used as an indicator of mastitis resistance.

Investigating the relationship between fluctuations in daily milk yield as resilience indicators and health traits in Holstein cattle

Disease-related milk losses directly affect dairy herds' profitability and the production efficiency of the dairy industry. Therefore, this study aimed to quantify phenotypic variability in milk fluctuation periods related to diseases and to explore milk fluctuation traits as indicators of disease resilience. By combining high-frequency daily milk yield data with disease records of cows that were treated and recovered from the disease, we estimated milk variability trends within a fixed period around the treatment day of each record for 5 diseases: udder health, reproductive disorders, metabolic disorders, digestive disorders, and hoof health. The average milk yield decreased rapidly from 6 to 8 d before the treatment day for all diseases, with the largest milk reduction observed on the treatment day. Additionally, we assessed the significance of milk fluctuation periods highly related to diseases by defining milk fluctuations as a period of at least 10 consecutive days in which milk yield fell below 90% of the expected milk production values at least once. We defined the development and recovery phases of milk fluctuations using 3,847 milk fluctuation periods related to disease incidences, and estimated genetic parameters of milk fluctuation traits, including milk losses, duration of the fluctuation, variation rate in daily milk yield, and standard deviation of milk deviations for each phase and their genetic correlation with several important traits. In general, the disease-related milk fluctuation periods lasted 21.19 ± 10.36 d with a milk loss of 115.54 ± 92.49 kg per lactation. Compared with the development phase, the recovery phase lasted an average of 3.3 d longer, in which cows produced 11.04 kg less milk and exhibited a slower variation rate in daily milk yield of 0.35 kg/d. There were notable differences in milk fluctuation traits depending on the disease, and greater milk losses were observed when multiple diseases occurred simultaneously. All milk fluctuation traits evaluated were heritable with heritability estimates ranging from 0.01 to 0.10, and moderate to high genetic correlations with milk yield (0.34 to 0.64), milk loss throughout the lactation (0.22 to 0.97), and resilience indicator (0.39 to 0.95). These results indicate that cows with lower milk losses and higher resilience tend to have more stable milk fluctuations, which supports the potential for breeding for more disease-resilient cows based on milk fluctuation traits. Overall, this study confirms the high effect of diseases on milk yield variability and provides insightful information about their relationship with relevant traits in Holstein cattle. Furthermore, this study shows the potential of using high-frequency automatic monitoring of milk yield to assist on breeding practices and health management in dairy cows.

Genetic parameters and genome-wide association studies for mozzarella and milk production traits, lactation length, and lactation persistency in Murrah buffaloes

Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to (1) compare single-trait random regression models under a single-step genomic BLUP setting based on alternative covariance functions (i.e., Wood, Wilmink, and Ali and Schaeffer) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); (2) combine the best functions for each trait under a multiple-trait framework; (3) estimate time-dependent SNP effects for all the studied longitudinal traits; and (4) identify the most likely candidate genes associated with the traits. A total of 323,140 test-day records from the first lactation of 4,588 Murrah buffaloes were made available for the study. The model included the average curve of the population nested within herd-year-season of calving, systematic effects of number of milkings per day, and age at first calving as linear and quadratic covariates, and additive genetic, permanent environment, and residual as random effects. The Wood model had the best goodness of fit based on the deviance information criterion and posterior model probabilities for all traits. Moderate heritabilities were estimated over time for most traits (0.30 ± 0.02 for MY; 0.26 ± 0.03 for FY; 0.45 ± 0.04 for PY; 0.28 ± 0.05 for MZY; 0.13 ± 0.02 for FPR; and 0.15 ± 0.03 for SCS). The heritability estimates for LP ranged from 0.38 ± 0.02 to 0.65 ± 0.03 depending on the trait definition used. Similarly, heritabilities estimated for LL ranged from 0.10 ± 0.01 to 0.14 ± 0.03. The genetic correlation estimates across days in milk (DIM) for all traits ranged from -0.06 (186-215 DIM for MY-SCS) to 0.78 (66-95 DIM for PY-MZY). The SNP effects calculated for the random regression model coefficients were used to estimate the SNP effects throughout the lactation curve (from 5 to 305 d). Numerous relevant genomic regions and candidate genes were identified for all traits, confirming their polygenic nature. The candidate genes identified contribute to a better understanding of the genetic background of milk-related traits in Murrah buffaloes and reinforce the value of incorporating genomic information in their breeding programs.

Novel lncRNA regulatory elements in milk somatic cells of Holstein dairy cows associated with mastitis

Despite regulatory elements such as long non - coding RNAs representing most of the transcriptome, the functional understanding of long non - coding RNAs in relation to major health conditions including bovine mastitis is limited. This study examined the milk somatic cell transcriptome from udder quarters of 6 Holstein dairy cows to identify differentially expressed long non - coding RNAs using RNA - Sequencing. Ninety - four differentially expressed long non - coding RNAs are identified, 5 of which are previously annotated for gene name and length, 11 are annotated for gene name and 78 are novel, having no gene name or length previously annotated. Significant inflammatory response and regulation of immune response pathways (false discovery rate < 0.05) are associated with the differentially expressed long non - coding RNAs. QTL annotation analysis revealed 31 QTL previously annotated in the genomic regions of the 94 differentially expressed long non - coding RNAs, and the majority are associated with milk traits. This research provides a better understanding of long non - coding RNAs regulatory elements in milk somatic cells, which may enhance current breeding strategies for more adaptable or high mastitis resistant cattle.

Antibacterial activity of medicinal plants on the management of mastitis in dairy cows: A systematic review

BACKGROUND

Mastitis is a disease of economic importance in dairy production systems. The common management regime for mastitis is the use of synthetic antibiotics, giving a new problem of antibiotic resistance. There is, therefore, a need to prospect for alternatives to conventional antibiotics from herbal plants.

OBJECTIVES

This systematic review evaluates the use of plants as alternatives for the control of mastitis in dairy cattle, focussing on the effectiveness of studied plants and plant-based products and possible implications on the use of these products in livestock health.

METHODOLOGY

The PRISMA model was implemented with searches done in five electronic databases: Scopus, ScienceDirect, PubMed, Ovid and Research4Life. Data were extracted from 45 studies with 112 plant species from plant species belonging to 42 different families. The specific keywords were 'mastitis', 'dairy cows' and 'medicinal plants'.

RESULTS

The most cited plant species included Allium sativum L., Azadirachta indica and Eucalyptus globulus Labill with the latter further exploring its components. Microbial species causing mastitis mainly were Staphylococcus aureus and Escherichia coli. The extraction methods used included maceration approach using ethanol, methanol and water as solvents for phytochemicals and chromatographic techniques for essential oils. A few studies explored the mode of action, and toxicities of the herbal extracts as well as evaluating their efficacy in clinical trials using animal models.

CONCLUSION

Plants with defined levels of phytochemicals were essential sources of antibacterials. Standardisation of analytical methods is required.

A comprehensive characterization of longevity and culling reasons in Canadian Holstein cattle based on various systematic factors

The decision of premature culling cows directly impacts the profitability of dairy farms. A comprehensive characterization of the primary causes of culling reasons would greatly improve both management and selection objectives in dairy cattle breeding programs. Therefore, this study aimed to analyze the temporal frequencies of 34 culling reasons in Canadian Holstein cows. After data editing and quality control, records from 3,096,872 cows culled from 9,683 herds spread across Canada were used for the analyses covering the periods from 1996 to 2020. Reproductive issues were the main culling reason accounting for 23.02%, followed by milk production (20.82%), health (20.39%), conformation problems (13.69%), economic factors (13.10%), accidents (5.67%), age-related causes (1.67%), and workability (1.63%). Nearly fifty-eight percent of cows were culled after 47 months of age. The observed frequencies of culling due to economic factors were lower than expected from 1996 to 2014 and higher than expected between 2015 and 2020. Reproduction issues had the highest culling frequencies during fall (24.54%), winter (24.02%), and spring (22.51%), while health issues were the most frequent (22.51%) culling reason in the summer season. Health issues (25.50%) and milk production (27.71%) were the most frequent culling reasons in the provinces of Quebec and Ontario, respectively. Reproductive issues showed the highest frequency across climates based on the Köppen climate classification, except for Csb (Dry-summer subtropical or Mediterranean climate) and Bsk (Middle latitude steppe climate), which correspond to small regions in Canada, where production was the most frequent culling reason (29.42% and 21.56%, respectively). Reproductive and milk performance issues were the two main culling reasons in most ecozones, except in Boreal Shield and Atlantic Marine, where health issues had the highest frequencies (25.12 and 23.75%, respectively). These results will contribute to improving management practices and selective decisions to reduce involuntary culling of Holstein cows.

Gene co-expression in response to Staphylococcus aureus infection reveals networks of genes with specific functions during bovine subclinical mastitis

Staphylococcus aureus is one of the most prevalent contagious bacterial pathogen of bovine mastitis. The subclinical mastitis it causes has long-term economic implications and it is difficult to control. To further understanding of the genetic basis of mammary gland defense against S. aureus infection, the transcriptomes of milk somatic cells from 15 cows with persistent natural S. aureus infection (S. aureus-positive, SAP) and 10 healthy control cows (HC) were studied by deep RNA-sequencing technology. Comparing the transcriptomes of SAP to HC group revealed 4,077 differentially expressed genes (DEG; 1,616 up- and 2,461 downregulated). Functional annotation indicated enrichment of DEG in 94 Gene Ontology (GO) and 47 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Terms related to the immune response and disease processes were mostly enriched for by upregulated DEG, whereas biological process terms related to cell adhesion, cell movement and localization, and tissue development were mostly enriched for by downregulated DEG. Weighted gene co-expression network analysis grouped DEG into 7 modules, the most important module (colored turquoise by software and here referred to as Turquoise module) was positively significantly correlated with S. aureus subclinical mastitis. The 1,546 genes in the Turquoise module were significantly enriched in 48 GO terms and 72 KEGG pathways, with 80% of them being disease- and immune-related terms [e.g., immune system process (GO:0002376), cytokine-cytokine receptor interaction (bta04060) and S. aureus infection (bta05150)]. Some DEG such as IFNG, IL18, IL1B, NFKB1, CXCL8, and IL12B were enriched in immune and disease pathways suggesting their possible involvement in the regulation of the host response to S. aureus infection. Four modules (Yellow, Brown, Blue, and Red) were negatively correlated (significantly) with S. aureus subclinical mastitis, and were enriched in functional annotations involved in the regulation of cell migration, cell communication, metabolic process, and blood circulatory system development, respectively. Application of sparse partial least squares discriminant analysis to genes of the Turquoise module identified 5 genes (NR2F6, PDLIM5, RAB11FIP5, ACOT4, and TMEM53) capable of explaining the majority of the differences in the expression patterns between SAP and HC cows. In conclusion, this study has furthered understanding of the genetic changes in the mammary gland and the molecular mechanisms underlying S. aureus mastitis, as well as revealed a list of candidate discriminant genes with potential regulatory roles in response to S. aureus infection.

Transcriptome-wide mapping of milk somatic cells upon subclinical mastitis infection in dairy cattle

BACKGROUND

Subclinical intramammary infection (IMI) represents a significant problem in maintaining dairy cows' health. Disease severity and extent depend on the interaction between the causative agent, environment, and host. To investigate the molecular mechanisms behind the host immune response, we used RNA-Seq for the milk somatic cells (SC) transcriptome profiling in healthy cows (n = 9), and cows naturally affected by subclinical IMI from Prototheca spp. (n = 11) and Streptococcus agalactiae (S. agalactiae; n = 11). Data Integration Analysis for Biomarker discovery using Latent Components (DIABLO) was used to integrate transcriptomic data and host phenotypic traits related to milk composition, SC composition, and udder health to identify hub variables for subclinical IMI detection.

RESULTS

A total of 1,682 and 2,427 differentially expressed genes (DEGs) were identified when comparing Prototheca spp. and S. agalactiae to healthy animals, respectively. Pathogen-specific pathway analyses evidenced that Prototheca's infection upregulated antigen processing and lymphocyte proliferation pathways while S. agalactiae induced a reduction of energy-related pathways like the tricarboxylic acid cycle, and carbohydrate and lipid metabolism. The integrative analysis of commonly shared DEGs between the two pathogens (n = 681) referred to the core-mastitis response genes, and phenotypic data evidenced a strong covariation between those genes and the flow cytometry immune cells (r² = 0.72), followed by the udder health (r² = 0.64) and milk quality parameters (r² = 0.64). Variables with r ≥ 0.90 were used to build a network in which the top 20 hub variables were identified with the Cytoscape cytohubba plug-in. The genes in common between DIABLO and cytohubba (n = 10) were submitted to a ROC analysis which showed they had excellent predictive performances in terms of discriminating healthy and mastitis-affected animals (sensitivity > 0.89, specificity > 0.81, accuracy > 0.87, and precision > 0.69). Among these genes, CIITA could play a key role in regulating the animals' response to subclinical IMI.

CONCLUSIONS

Despite some differences in the enriched pathways, the two mastitis-causing pathogens seemed to induce a shared host immune-transcriptomic response. The hub variables identified with the integrative approach might be included in screening and diagnostic tools for subclinical IMI detection.

How Does Nutrition Affect the Epigenetic Changes in Dairy Cows?

Dairy cows require a balanced diet that provides enough nutrients to support milk production, growth, and reproduction. Inadequate nutrition can lead to metabolic disorders, impaired fertility, and reduced milk yield. Recent studies have shown that nutrition can affect epigenetic modifications in dairy cows, which can impact gene expression and affect the cows' health and productivity. One of the most important epigenetic modifications in dairy cows is DNA methylation, which involves the addition of a methyl group to the DNA molecule. Studies have shown that the methylation status of certain genes in dairy cows can be influenced by dietary factors such as the level of methionine, lysine, choline, and folate in the diet. Other important epigenetic modifications in dairy cows are histone modification and microRNAs as regulators of gene expression. Overall, these findings suggest that nutrition can have a significant impact on the epigenetic regulation of gene expression in dairy cows. By optimizing the diet of dairy cows, it may be possible to improve their health and productivity by promoting beneficial epigenetic modifications. This paper reviews the main nutrients that can cause epigenetic changes in dairy cattle by analyzing the effect of diet on milk production and its composition.

Genomic and Phenotypic Udder Evaluation for Dairy Cattle Selection: A Review

The traditional point of view regarding dairy cattle selection has been challenged by recent genomic studies indicating that livestock productivity prediction can be redefined based on the evaluation of genomic and phenotypic data. Several studies that included different genomic-derived traits only indicated that interactions among them or even with conventional phenotypic evaluation criteria require further elucidation. Unfortunately, certain genomic and phenotypic-derived traits have been shown to be secondary factors influencing dairy production. Thus, these factors, as well as evaluation criteria, need to be defined. Owing to the variety of genomic and phenotypic udder-derived traits which may affect the modern dairy cow functionality and conformation, a definition of currently important traits in the broad sense is indicated. This is essential for cattle productivity and dairy sustainability. The main objective of the present review is to elucidate the possible relationships among genomic and phenotypic udder evaluation characteristics to define the most relevant traits related to selection for function and conformation in dairy cattle. This review aims to examine the potential impact of various udder-related evaluation criteria on dairy cattle productivity and explore how to mitigate the adverse effects of compromised udder conformation and functionality. Specifically, we will consider the implications for udder health, welfare, longevity, and production-derived traits. Subsequently, we will address several concerns covering the application of genomic and phenotypic evaluation criteria with emphasis on udder-related traits in dairy cattle selection as well as its evolution from origins to the present and future prospects.

Analysis of the effect of polymorphisms within the CATHL7 gene on dairy performance parameters

Introduction

Antimicrobial peptides, including cathelicidins, play a significant role in farm animals, influencing animal welfare, immunity, and thus the quality of animal products.

Material and Methods

The study used amplification-created restriction site and PCR-restriction fragment length polymorphism to analyse single nucleotide polymorphisms of the CATHL7 gene encoding the BMAP-34 protein in cattle, at positions 2,383 G > C and 2,468 G > C. The material was collected from 279 Polish Black-and-White Holstein-Friesian dairy cows.

Results

There were statistically significant differences between milk performance parameters in cows with the CATHL7/HhaI and CATHL7/HinfI genotypes. In the case of the CATHL7/HhaI polymorphism, the highest milk yield and protein and lactose content and the lowest somatic cell count in milk were observed for the CC genotype, while the fat content was the highest in milk from cows with the GG genotype. In the case of the CATHL7/HinfI polymorphism, the highest protein and lactose content in milk was observed for the CC genotype.

Conclusion

The results were statistically significant, which suggests that the search for relationships can be continued, and that the results can be used to improve selection programmes supporting dairy farming.

Genetic polymorphisms in immune- and inflammation-associated genes and their association with bovine mastitis resistance/susceptibility

Bovine mastitis, the inflammation of the mammary gland, is a contagious disease characterized by chemical and physical changes in milk and pathological changes in udder tissues. Depressed immunity and higher expression of inflammatory cytokines with an elevated milk somatic cell count can be observed during mastitis in dairy cattle. The use of somatic cell count (SCC) and somatic cell score (SCS) as correlated traits in the indirect selection of animals against mastitis resistance is in progress globally. Traditional breeding for mastitis resistance seems difficult because of the low heritability (0.10-0.16) of SCC/SCS and clinical mastitis. Thus, genetic-marker-selective breeding to improve host genetics has attracted considerable attention worldwide. Moreover, genomic selection has been found to be an effective and fast method of screening for dairy cattle that are genetically resistant and susceptible to mastitis at a very early age. The current review discusses and summarizes the candidate gene approach using polymorphisms in immune- and inflammation-linked genes (CD4, CD14, CD46, TRAPPC9, JAK2, Tf, Lf, TLRs, CXCL8, CXCR1, CXCR2, C4A, C5, MASP2, MBL1, MBL2, LBP, NCF1, NCF4, MASP2, A2M, and CLU, etc.) and their related signaling pathways (Staphylococcus aureus infection signaling, Toll-like receptor signaling, NF-kappa B signaling pathway, Cytokine-cytokine receptor, and Complement and coagulation cascades, etc.) associated with mastitis resistance and susceptibility phenotypic traits (IL-6, interferon-gamma (IFN-γ), IL17, IL8, SCS, and SCC) in dairy cattle.

Genomic-based genetic parameters for milkability traits derived from automatic milking systems in North American Holstein cattle

The number of dairy farms adopting automatic milking systems (AMS) has considerably increased around the world aiming to reduce labor costs, improve cow welfare, increase overall performance, and generate a large amount of daily data, including production, behavior, health, and milk quality records. In this context, this study aimed to (1) estimate genomic-based variance components for milkability traits derived from AMS in North American Holstein cattle based on random regression models; and (2) derive and estimate genetic parameters for novel behavioral indicators based on AMS-derived data. A total of 1,752,713 daily records collected using 36 milking robot stations and 70,958 test-day records from 4,118 genotyped Holstein cows were used in this study. A total of 57,600 SNP remained after quality control. The daily-measured traits evaluated were milk yield (MY, kg), somatic cell score (SCS, score unit), milk electrical conductivity (EC, mS), milking efficiency (ME, kg/min), average milk flow rate (FR, kg/min), maximum milk flow rate (FRM, kg/min), milking time (MT, min), milking failures (MFAIL), and milking refusals (MREF). Variance components and genetic parameters for MY, SCS, ME, FR, FRM, MT, and EC were estimated using the AIREMLF90 software under a random regression model fitting a third-order Legendre orthogonal polynomial. A threshold Bayesian model using the THRGIBBS1F90 software was used for genetically evaluating MFAIL and MREF. The daily heritability estimates across days in milk (DIM) ranged from 0.07 to 0.28 for MY, 0.02 to 0.08 for SCS, 0.38 to 0.49 for EC, 0.45 to 0.56 for ME, 0.43 to 0.52 for FR, 0.47 to 0.58 for FRM, and 0.22 to 0.28 for MT. The estimates of heritability (± SD) for MFAIL and MREF were 0.02 ± 0.01 and 0.09 ± 0.01, respectively. Slight differences in the genetic correlations were observed across DIM for each trait. Strong and positive genetic correlations were observed among ME, FR, and FRM, with estimates ranging from 0.94 to 0.99. Also, moderate to high and negative genetic correlations (ranging from -0.48 to -0.86) were observed between MT and other traits such as SCS, ME, FR, and FRM. The genetic correlation (± SD) between MFAIL and MREF was 0.25 ± 0.02, indicating that both traits are influenced by different sets of genes. High and negative genetic correlations were observed between MFAIL and FR (-0.58 ± 0.02) and MFAIL and FRM (-0.56 ± 0.02), indicating that cows with more MFAIL are those with lower FR. The use of random regression models is a useful alternative for genetically evaluating AMS-derived traits measured throughout the lactation. All the milkability traits evaluated in this study are heritable and have demonstrated selective potential, suggesting that their use in dairy cattle breeding programs can improve dairy production efficiency in AMS.

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

Antibacterial activity and metabolomic analysis of linalool against bovine mastitis pathogen Streptococcus agalactiae

Streptococcus agalactiae is among the major causative pathogens of bovine mastitis, as well as crucial pathogen leading to human morbidity and mortality. Being a promising natural antibacterial agent, linalool has been broadly applied in medicine and food processing. However, its antibacterial effect against S. agalactiae has barely been elucidated. This study is the first to investigate the antibacterial activity and action mechanism of linalool against S. agalactiae causing bovine mastitis. Linalool exhibited significant antibacterial activity against S. agalactiae, with an inhibition zone diameter of 23 mm and a minimum inhibitory concentration of 1.875 μL/mL. In addition, linalool damaged cell structural integrity of S. agalactiae, leading to the leakage of intracellular components (alkaline phosphatase, nucleic acids and protein). Linalool also exhibited a scavenging effect on biofilm. Moreover, untargeted metabolomics analysis revealed that linalool stress substantially disrupted intracellular metabolism of S. agalactiae. Linalool caused energy metabolism disorder, and obstructed nucleic acid synthesis in S. agalactiae. Furthermore, downregulation of amino acids (e.g., proline, alanine) and upregulation of saturated fatty acids provide strong evidence for linalool induced cell wall and membrane damage. Overall, linalool exhibited strong antibacterial activity against S. agalactiae by destroying the cell structure and disrupting intracellular metabolism. This study provides a new insight and theoretical foundation for linalool application in preventing S. agalactiae infection.

Herd and animal factors affect the variability of total and differential somatic cell count in bovine milk

The aim of this study was to quantify some environmental (individual herds, herd productivity, milking system, and season) and animal factors [individual animals, breed, days in milk (DIM) and parity] on the variability of the log-10 transformation of somatic cell count (LSCC) and differential somatic cell count (DSCC) on individual bovine milk. A total of 159,360 test-day records related to milk production and composition were extracted from 12,849 Holstein-Friesian and 9,275 Simmental cows distributed across 223 herds. Herds were classified into high and low productivity, defined according to the average daily milk net energy output (DMEO) yielded by the cows. Data included daily milk yield (DYM; kg/d), milk fat, protein, lactose, SCC, and DSCC, and information on herds (i.e., productivity, milking system). The daily production of total and differential somatic cells in milk was calculated and then log-10 transformed, obtaining DLSCC and DLDSCC, respectively. Data were analyzed using a mixed model including the effects of individual herd, animal, repeated measurements intra animal as random, and herd productivity, milking system, season, breed, DIM, parity, DIM × parity, breed × season, DIM × milking system and parity × milking system as fixed factors. Herds with a high DMEO were characterized by a lower content of LSCC and DSCC, and higher DLSCC and DLDSCC, compared to the low DMEO herds. The association between milking system and somatic cell traits suggested that the use of the automatic milking systems would not allow for a rapid intervention on the cow, as evidenced by the higher content of all somatic cell traits compared to the other milking systems. Season was an important source of variation, as evidenced by high LSCC and DSCC content in milk during summer. Breed of cow had a large influence, with Holstein-Friesian having greater LSCC, DSCC, DLSCC, and DLDSCC compared to Simmental. With regard to DIM, the variability of LSCC was mostly related to that of DSCC, showing an increase from calving to the end of lactation, and suggesting the higher occurrence of chronic mastitis in cows toward the end of lactation. All the somatic cell traits increased across number of parities, possibly because older cows may have increased susceptibility to intramammary infections.

Progress and opportunities through use of genomics in animal production

The rearing of farmed animals is a vital component of global food production systems, but its impact on the environment, human health, animal welfare, and biodiversity is being increasingly challenged. Developments in genetic and genomic technologies have had a key role in improving the productivity of farmed animals for decades. Advances in genome sequencing, annotation, and editing offer a means not only to continue that trend, but also, when combined with advanced data collection, analytics, cloud computing, appropriate infrastructure, and regulation, to take precision livestock farming (PLF) and conservation to an advanced level. Such an approach could generate substantial additional benefits in terms of reducing use of resources, health treatments, and environmental impact, while also improving animal health and welfare.

Immunomodulatory Effects of Probiotics: A Novel Preventive Approach for the Control of Bovine Mastitis

Bovine mastitis (BM) is one of the most common diseases of dairy cattle, causing economic and welfare problems in dairy farming worldwide. Because of the predominant bacterial etiology, the treatment of BM is mostly based on antibiotics. However, the antimicrobial resistance (AMR), treatment effectiveness, and the cost of mastitis at farm level are linked to limitations in the antibiotic therapy. These scenarios have prompted the quest for new preventive options, probiotics being one interesting alternative. This review article sought to provide an overview of the recent advances in the use of probiotics for the prevention and treatment of BM. The cellular and molecular interactions of beneficial microbes with mammary gland (MG) cells and the impact of these interactions in the immune responses to infections are revised. While most research has demonstrated that some probiotics strains can suppress mammary pathogens by competitive exclusion or the production of antimicrobial compounds, recent evidence suggest that other probiotic strains have a remarkable ability to modulate the response of MG to Toll-like receptor (TLR)-mediated inflammation. Immunomodulatory probiotics or immunobiotics can modulate the expression of negative regulators of TLR signaling in the MG epithelium, regulating the expression of pro-inflammatory cytokines and chemokines induced upon pathogen challenge. The scientific evidence revised here indicates that immunobiotics can have a beneficial role in MG immunobiology and therefore they can be used as a preventive strategy for the management of BM and AMR, the enhancement of animal and human health, and the improvement of dairy cow milk production.

Effects of lipoteichoic and arachidonic acids on the immune-regulatory mechanism of bovine mammary epithelial cells using multi-omics analysis

Staphylococcus aureus is one of the most important pathogens causing mastitis in dairy cows. It mainly utilizes the properties of its pathogenic factor, lipoteichoic acid (LTA), to elicit a host-cell inflammatory response and evade the host-cell immune response. Arachidonic acid (AA) has a regulatory role in the inflammatory response, cell metabolism, and apoptosis. The study aimed to establish a cell model by determining the optimal concentration of LTA and AA for cell induction using the Cell Counting Kit−8 assay and the quantitative polymerase chain reaction of interleukin (IL)-1β, IL-2, and IL-6. MAC-T cells were planted in 36 10-cm² culture dishes at a density of 1 × 10⁷ cells per dish. They were treated with LTA for 24 h to constitute the LTA group and with AA for 12 h to constitute the AA group. The cells were pretreated with LTA for 24 h followed by treatment with AA for 12 h to constitute the LTA + AA group. Using proteomic, transcriptomic, and metabolomic analyses, this study determined that LTA can regulate the expression of Actin Related protein 2/3 complex (ARPC)3, ARPC4, Charged Multivesicular Body Protein 3, protein kinase cGMP-dependent, NF-κB Inhibitor Alpha,and other genes to affect cellular metabolism, immune regulation and promote apoptosis. In contrast, AA was observed to regulate the expression of genes such as ARPC3, ARPC4, Charged Multivesicular Body Protein 3, Laminin Gamma 1, Insulin Receptor, Filamin B, and Casein Kinase 1 Epsilon to inhibit cellular apoptosis and promote immune regulation, which provides a theoretical basis for future studies.

Improving Genomic Selection for Heat Tolerance in Dairy Cattle: Current Opportunities and Future Directions

Heat tolerance is the ability of an animal to maintain production and reproduction levels under hot and humid conditions and is now a trait of economic relevance in dairy systems worldwide because of an escalating warming climate. The Australian dairy population is one of the excellent study models for enhancing our understanding of the biology of heat tolerance because they are predominantly kept outdoors on pastures where they experience direct effects of weather elements (e.g., solar radiation). In this article, we focus on evidence from recent studies in Australia that leveraged large a dataset [∼40,000 animals with phenotypes and 15 million whole-genome sequence variants] to elucidate the genetic basis of thermal stress as a critical part of the strategy to breed cattle adapted to warmer environments. Genotype-by-environment interaction (i.e., G × E) due to temperature and humidity variation is increasing, meaning animals are becoming less adapted (i.e., more sensitive) to changing environments. There are opportunities to reverse this trend and accelerate adaptation to warming climate by 1) selecting robust or heat-resilient animals and 2) including resilience indicators in breeding goals. Candidate causal variants related to the nervous system and metabolic functions are relevant for heat tolerance and, therefore, key for improving this trait. This could include adding these variants in the custom SNP panels used for routine genomic evaluations or as the basis to design specific agonist or antagonist compounds for lowering core body temperature under heat stress conditions. Indeed, it was encouraging to see that adding prioritized functionally relevant variants into the 50k SNP panel (i.e., the industry panel used for genomic evaluation in Australia) increased the prediction accuracy of heat tolerance by up to 10% units. This gain in accuracy is critical because genetic improvement has a linear relationship with prediction accuracy. Overall, while this article used data mainly from Australia, this could benefit other countries that aim to develop breeding values for heat tolerance, considering that the warming climate is becoming a topical issue worldwide.

Genetic Parameters of Somatic Cell Score in Florida Goats Using Single and Multiple Traits Models

A total of 1,031,143 records of daily dairy control test of Spanish Florida goats were used for this study. The database was edited, and only the records of the first three lactations were kept. The final database contained 340,654 daily-test somatic cell counts from 27,749 daughters of 941 males and 16,243 goats. The evolution of this count in the last 14 years was analyzed following French and American international associations’ criteria for the risk of mastitis in goats, and confirmed the slight increase in SCS in the last years and the importance of this problem (50% of dairy control tests show a risk of suffering mastitis). For the genetic analysis, the SCS records were log-transformed to normalize this variable. Two strategies were used for the genetic analysis: a univariate animal model for the SCS assuming that SCS does not vary throughout the parities, and a multi-character animal model, where SCS is not considered as the same character in the different parities. The heritabilities (h2) were higher in the multiple traits models, showings an upward trend from the first to the third parity (h2 between 0.245 to 0.365). The genetic correlations of the same trait, as well as between breeding values (GVs) between different parities, were different from unity. The breeding values (EBVs) obtained for both models were subjected to a PCA: the first eigenvector (λ1) explained most of the variations (between 74% to 90%), while the second λ2 accounted for between 9% to 20% of the variance, which shows that the selection will be proportionally favorable but not equivalent in all parities and that there are some variations in the type of response.

C4BPA: A Novel Co-Regulator of Immunity and Fat Metabolism in the Bovine Mammary Epithelial Cells

The C4b binding protein alpha (C4BPA) chain primarily engages in critical inflammatory and coagulation processes. The previous transcriptomic analysis showed that C4BPA is a differentially expressed gene in lower and higher fat content mammary gland cell lines from Chinese Holstein. This study aimed to investigate the effects of C4BPA on the inflammation and milk fat synthesis in bMECs by C4BPA knockdown and overexpression. The results highlighted that knockdown of C4BPA in bMECs could suppress the mRNA and protein expression of IL-6, IL-8, IL-12, and the TLR-4/NF-κB pathway-related genes and promote the expression of complement and coagulation cascade pathways related genes as well as TNF-α. Moreover, knockdown of C4BPA expression in bMECs reduced the content of triglyceride (TG) and cholesterol (CHOL) in bMECs, increased NEFA content, reduced mRNA and protein expression of ACSL1 and PPARA, and increased the mRNA and protein expression of ELOVL6, FADS1, and LPL. The bMECs, with the overexpression of C4BPA, showed the enhanced expression of TLR-4/NF-κB linked genes, IL-6, IL-8, IL-12, and mRNA and protein level while reduced mRNA expression of TNF-α, compliment, and coagulation cascade related genes was observed. In bMECs, overexpression of C4BPA enhanced the content of TG and CHOL while reducing NEFA and stimulated the mRNA and protein expression of ACSL1, PPARA, and PPARG genes while inhibiting the mRNA and protein expression of FADS1 and LPL genes. Our results show that C4BPA not only regulates the lipid metabolism through the PPAR signaling pathway in bMECs but also contributes to the inflammatory response through TLR-4/NF-κB and the complement and coagulation cascade pathways. This study, for the first time, provides the primary basis for understanding the role of C4BPA in immunity and fat metabolism, which enables the researchers for innovative direction to investigate genes associated with fat metabolism and immunity. This study also advocates that the breeders must pay attention to such type of genes with multiple functions during animal breeding.

The quantitative genetics of the prevalence of infectious diseases: hidden genetic variation due to indirect genetic effects dominates heritable variation and response to selection

Infectious diseases have profound effects on life, both in nature and agriculture. However, a quantitative genetic theory of the host population for the endemic prevalence of infectious diseases is almost entirely lacking. While several studies have demonstrated the relevance of transmission of infections for heritable variation and response to selection, current quantitative genetics ignores transmission. Thus, we lack concepts of breeding value and heritable variation for endemic prevalence, and poorly understand response of endemic prevalence to selection. Here, we integrate quantitative genetics and epidemiology, and propose a quantitative genetic theory for the basic reproduction number R0 and for the endemic prevalence of an infection. We first identify the genetic factors that determine the prevalence. Subsequently, we investigate the population-level consequences of individual genetic variation, for both R0 and the endemic prevalence. Next, we present expressions for the breeding value and heritable variation, for endemic prevalence and individual binary disease status, and show that these depend strongly on the prevalence. Results show that heritable variation for endemic prevalence is substantially greater than currently believed, and increases strongly when prevalence decreases, while heritability of disease status approaches zero. As a consequence, response of the endemic prevalence to selection for lower disease status accelerates considerably when prevalence decreases, in contrast to classical predictions. Finally, we show that most heritable variation for the endemic prevalence is hidden in indirect genetic effects, suggesting a key role for kin-group selection in the evolutionary history of current populations and for genetic improvement in animals and plants.

Mini Review: Lactoferrin-binding protein of Streptococcus in Bovine Mastitis

Bovine mastitis is an udder inflammation mostly found in dairy cattle that causes enormous economic losses. Streptococcus is a bacterium that is often found in mastitis, including Streptococcus agalactiae, Streptococcus dysgalactiae, and Streptococcus uberis. These three species have lactoferrinbinding protein (LBP) as one of their virulence factors. Lactoferrin is a host innate immune protein that acts as antibacterial, immunomodulator, anti-adhesion, and has iron-binding properties. The LBP on the surface of Streptococcus could bind to lactoferrin produced by host cells. Uniquely, the three Streptococcus bacteria showed different responses to lactoferrin. The lactoferrin-LBP bound on S. agalactiae and S. dysgalactiae was known to inhibit their penetration ability into the host epithelial cells, on the contrary, in S. uberis it could enhance their ability to invade the cells. This paper aims to review the role of the lactoferrin-binding protein of Streptococcus in bovine mastitis.

Milk Somatic Cell Count and Polymorphonuclear Cells in Healthy Quarters of Cows That Underwent Blanket and Selective Dry Therapy: An Italian Case Study

The incidence of mastitis increases with parity in dairy cattle and multiparous cows are often treated at drying off to limit the risk of udder health issues and support mammary gland tissues recovery. Milk somatic cells count (SCC, cells/mL) comprises different white blood cells fractions and is worldwide used to monitor and genetically improve udder health. Nevertheless, only certain SCC fractions increase when an udder inflammation occurs. Considering that antibiotic use for preventive purposes will be forbidden in 2022, we compared two different dry therapy protocols, blanket (BDCT) and selective (SDCT), on different SCC fractions in healthy quarters milk. Multiparous Holstein cows were enrolled in a randomized controlled trial and SCC, neutrophils, macrophages, lymphocytes, polymorphonuclear cells (PMN) and differential somatic cell count (DSCC) recorded after the experimental drying off were available. Significant differences were observed between the two protocols, with more favorable parameters in BDCT than SDCT cows. Results showed that moving from BDCT to SDCT is expected to significantly increase some SCC fractions, such as PMN, in healthy quarters. The baseline SCC level at the onset of lactation was greater in cows under SDCT than BDCT. Although not significant, clinical mastitis prevalence was numerically lower in BDCT (7.32%) than SDCT (8.62%). In this study we referred to a limited number of cows, but still findings will be useful to improve the knowledge on the impact of SDCT on milk SCC fractions in healthy quarters.

Genomic loci and genetic parameters for uterine diseases in first-parity Holstein cows and associations with milk production and fertility

Based on the clinical stage (e.g., vaginal discharge) and bacterial species, several forms of uterine diseases (UD) exist and can be classified as different traits [i.e., different stages of endometritis (EM) and metritis (MET)], which may differ in their genetic background and causal physiological mechanisms. Consequently, the present study aimed to study (1) the effect of UD on 305-d lactation and fertility, (2) the estimation of heritabilities for UD traits using pedigree- and SNP-based relationships, and (3) genome-wide associations to detect significant SNP markers and to infer candidate genes for UD traits. The data set contained herd manager and veterinarian recorded UD traits of 14,810 first-lactating genotyped Holstein cows from 63 large-scale contract herds. Binary defined UD traits (healthy or diseased) according to the clinical stage were endometritis catarrhalis (EM I), endometritis mucopurulenta (EM II), endometritis purulenta (EM III), pyometra (EM IV), endometritis (EM_SOD; superordinate diagnosis = no specific clinical stage defined), and MET. The binary defined trait UDall included all EM and MET diagnoses. The prevalence of UDall was 26.7%. The effect of UD on 305-d lactation and fertility was estimated via linear and generalized linear mixed models. We applied linear single-trait animal models and threshold models to estimate pedigree- and SNP-based heritabilities for UD traits, and bivariate linear models for genetic correlation estimations between UDall with 305-d lactation and fertility traits. A diagnosis for UDall had significant unfavorable effects on the female fertility traits calving interval, interval from calving to first service, days open, and nonreturn rate after 90 d, but was unrelated to 305-d lactation records for production traits milk yield, protein yield, and fat yield. Heritabilities for UDall and EM stages were close to zero, displaying maximal values of 0.05 for pedigree and 0.07 for SNP-based relationship matrices. For MET, pedigree- and SNP-based heritabilities were <0.001 and 0.07, respectively. Genetic correlations ranged from 0.20 to 0.31 between UDall with 305-d milk, protein, and fat yield, and from 0.17 to 0.40 with fertility traits. The GWAS revealed 5 SNP on bovine chromosomes (BTA) 1, 8, 10, 23 for UDall, 5 SNP on BTA 26 for EM I, 1 SNP on BTA 19 for EM II, 4 SNP on BTA 2, 18, 20, 25 for EM III, and 4 SNP on BTA 4, 16, 20 for EM IV above the significance threshold. For EM_SOD, we identified 15 significantly associated SNP on 4 chromosomes, and 4 significant SNP on BTA 3, 20, 22, 28 for MET. Marker associations for UD traits were annotated to 24 potential candidate genes using the ENSEMBL database. Six of these genes were previously reported to be involved in uterine defense mechanisms or in endometritis. Further detected genes contribute to immune response mechanisms during bacterial infections. Different SNP significantly influenced different UD stages, explaining the inter-individual variations in clinical severity of uterine infections.

Review: Genetic selection of high-yielding dairy cattle toward sustainable farming systems in a rapidly changing world

The massive improvement in food production, as a result of effective genetic selection combined with advancements in farming practices, has been one of the greatest achievements of modern agriculture. For instance, the dairy cattle industry has more than doubled milk production over the past five decades, while the total number of cows has been reduced dramatically. This was achieved mainly through the intensification of production systems, direct genetic selection for milk yield and a limited number of related traits, and the use of modern technologies (e.g., artificial insemination and genomic selection). Despite the great betterment in production efficiency, strong drawbacks have occurred along the way. First, across-breed genetic diversity reduced dramatically, with the worldwide use of few common dairy breeds, as well as a substantial reduction in within-breed genetic diversity. Intensive selection for milk yield has also resulted in unfavorable genetic responses for traits related to fertility, health, longevity, and environmental sensitivity. Moving forward, the dairy industry needs to continue refining the current selection indexes and breeding goals to put greater emphasis on traits related to animal welfare, health, longevity, environmental efficiency (e.g., methane emission and feed efficiency), and overall resilience. This needs to be done through the definition of criteria (traits) that (a) represent well the biological mechanisms underlying the respective phenotypes, (b) are heritable, and (c) can be cost-effectively measured in a large number of animals and as early in life as possible. The long-term sustainability of the dairy cattle industry will also require diversification of production systems, with greater investments in the development of genetic resources that are resilient to perturbations occurring in specific farming systems with lesser control over the environment (e.g., organic, agroecological, and pasture-based, mountain-grazing farming systems). The conservation, genetic improvement, and use of local breeds should be integrated into the modern dairy cattle industry and greater care should be taken to avoid further genetic diversity losses in dairy cattle populations. In this review, we acknowledge the genetic progress achieved in high-yielding dairy cattle, closely related to dairy farm intensification, that reaches its limits. We discuss key points that need to be addressed toward the development of a robust and long-term sustainable dairy industry that maximize animal welfare (fundamental needs of individual animals and positive welfare) and productive efficiency, while also minimizing the environmental footprint, inputs required, and sensitivity to external factors.

The Role of Streptococcus spp. in Bovine Mastitis

The Streptococcus genus belongs to one of the major pathogen groups inducing bovine mastitis. In the dairy industry, mastitis is the most common and costly disease. It not only negatively impacts economic profit due to milk losses and therapy costs, but it is an important animal health and welfare issue as well. This review describes a classification, reservoirs, and frequencies of the most relevant Streptococcus species inducing bovine mastitis (S. agalactiae, S. dysgalactiae and S. uberis). Host and environmental factors influencing mastitis susceptibility and infection rates will be discussed, because it has been indicated that Streptococcus herd prevalence is much higher than mastitis rates. After infection, we report the sequence of cow immune reactions and differences in virulence factors of the main Streptococcus species. Different mastitis detection techniques together with possible conventional and alternative therapies are described. The standard approach treating streptococcal mastitis is the application of ß-lactam antibiotics. In streptococci, increased antimicrobial resistance rates were identified against enrofloxacin, tetracycline, and erythromycin. At the end, control and prevention measures will be considered, including vaccination, hygiene plan, and further interventions. It is the aim of this review to estimate the contribution and to provide detailed knowledge about the role of the Streptococcus genus in bovine mastitis.

Advances in therapeutic and managemental approaches of bovine mastitis: a comprehensive review

Mastitis (intramammary inflammation) caused by infectious pathogens is still considered a devastating condition of dairy animals affecting animal welfare as well as economically incurring huge losses to the dairy industry by means of decreased production performance and increased culling rates. Bovine mastitis is the inflammation of the mammary glands/udder of bovines, caused by bacterial pathogens, in most cases. Routine diagnosis is based on clinical and subclinical forms of the disease. This underlines the significance of early and rapid identification/detection of etiological agents at the farm level, for which several diagnostic techniques have been developed. Therapeutic regimens such as antibiotics, immunotherapy, bacteriocins, bacteriophages, antimicrobial peptides, probiotics, stem cell therapy, native secretory factors, nutritional, dry cow and lactation therapy, genetic selection, herbs, and nanoparticle technology-based therapy have been evaluated for their efficacy in the treatment of mastitis. Even though several strategies have been developed over the years for the purpose of managing both clinical and subclinical forms of mastitis, all of them lacked the efficacy to eliminate the associated etiological agent when used as a monotherapy. Further, research has to be directed towards the development of new therapeutic agents/techniques that can both replace conventional techniques and also solve the problem of emerging antibiotic resistance. The objective of the present review is to describe the etiological agents, pathogenesis, and diagnosis in brief along with an extensive discussion on the advances in the treatment and management of mastitis, which would help safeguard the health of dairy animals.

Unintended consequences of selection for increased production on the health and welfare of livestock

Modern farming technologies, including quantitative selection and breeding methods in farm animal species, resulted in increased production and efficiency. Selection for increased output in both intensive and extensive production systems has trade-offs and negative outcomes, often more pronounced in intensive systems. Animal welfare and health are often adversely affected and this influences sustainable production. The relative importance of animal welfare differs among developed and developing countries due to the level of economic development, food security and education, as well as religious and cultural practices which presents challenges for sound scientific research. Due to breeding goals in the past set on growth performance, traits such as fertility, welfare and health have been neglected. Fertility is the single most important trait in all livestock species. Reduced fertility and lameness, claw health and mastitis results in unnecessary culling and reduced longevity. Selection pressure for growth accompanied with inbreeding has resulted in a number of genetic defects in beef, sheep and pigs. This review demonstrated the importance of inclusion of animal welfare concepts into breeding objectives and selection strategies. Accurate phenotyping of welfare traits is a limiting factor in the implementation of mitigating strategies, which include diagnostic testing, control of inbreeding and genomic selection.

Associations between the breeding values of Holstein-Friesian bulls and longevity and culling reasons of their daughters

Taking into account functional traits in the breeding practice should lead to a longer productive life of cows. However, despite the increased contribution of these traits in bull selection indices, their daughters are frequently culled as early as the 2nd or 3rd lactation. The problem is whether and to what extent the genetic potential of animals is realized in the production practice. Therefore, the purpose of this study was to determine the associations between the breeding value (BV) of bulls and their daughters for cow longevity and culling reasons in the Holstein-Friesian cattle population in Poland. Data for 532 062 cows culled in 2012, 2015, and 2018 were analyzed. A majority of 5 045 cow sires originated from Poland, Germany, France, the Netherlands, and the United States. The highest variation in the contribution of culling reasons was for the cows culled at the age of 2-4 years. The contribution of the culling reasons, analyzed in relation to the cow culling age, remained similar and the only exception was culling because of old age, for which a significant increase was observed only for the culling age of at least 9 years (13.8%), which was reached by only 7.3% of the cows. The sires were characterized by generally high BV for conformation and reproductive traits. However, they had, at most, the average genetic potential for functional longevity. There were a number of beneficial associations found between the BV of bulls and the distribution of culling reasons in their daughters. For example, it concerns relations between the somatic cell score in milk and culling due to udder diseases and low milk yield, between the interval from calving to first insemination and low milk yield, between the protein yield and old age, or between the BV for certain conformation traits (size, udder) and cow culling due to age. In these cases, as the BV increased for a given trait, the contribution of the corresponding cow culling reason tended to decrease. Our study showed that it seems reasonable to consider Holstein-Friesian cows aged at least 9 years at culling to be long-living animals. This is primarily evidenced by the rapid increase in the culling due to old age in relation to younger cows. Nowadays the above age limit can be suggested as a criterion of longevity for Holstein-Friesian cows but the criterion should be updated to the relation genotype-environment-economy that tends to change over time.

A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments

Simple Summary

Cows are social animals, therefore understanding the ways that they interact can help improve their management and welfare. We used social network analysis (SNA) to data on voluntary cow movement through a sort gate in an automatic milking system to identify pairs of cows that repeatedly passed through a sort gate in close succession (affinity pairs). Results from this exploratory study showed that when cows were separated from their affinity-pair cow the day-day variability in milk production increased by a factor of 3, a possible indicator of stress. The results of this exploratory study suggest that SNA could be used as a tool to better understand the social dynamics of dairy cows and inform group and regrouping process to produce positive outcomes.

Abstract

We have applied social network analysis (SNA) to data on voluntary cow movement through a sort gate in an automatic milking system to identify pairs of cows that repeatedly passed through a sort gate in close succession (affinity pairs). The SNA was applied to social groups defined by four pens on a dairy farm, each served by an automatic milking system (AMS). Each pen was equipped with an automatic sorting gate that identified when cows voluntarily moved from the resting area to either milking or feeding areas. The aim of this study was two-fold: to determine if SNA could identify affinity pairs and to determine if milk production was affected when affinity pairs where broken. Cow traffic and milking performance data from a commercial guided-flow AMS dairy farm were used. Average number of milked cows was 214 ± 34, distributed in four AMS over 1 year. The SNA was able to identify clear affinity pairs and showed when these pairings were formed and broken as cows entered and left the social group (pen). The trend in all four pens was toward higher-than-expected milk production during periods of affinity. Moreover, we found that when affinities were broken (separation of cow pairs) the day-to-day variability in milk production was three times higher than for cows in an affinity pair. The results of this exploratory study suggest that SNA could be potentially used as a tool to reduce milk yield variation and better understand the social dynamics of dairy cows supporting management and welfare decisions.

Genomic studies of milk-related traits in water buffalo (Bubalus bubalis) based on single-step genomic best linear unbiased prediction and random regression models

Genomic selection has been widely implemented in many livestock breeding programs, but it remains incipient in buffalo. Therefore, this study aimed to (1) estimate variance components incorporating genomic information in Murrah buffalo; (2) evaluate the performance of genomic prediction for milk-related traits using single- and multitrait random regression models (RRM) and the single-step genomic best linear unbiased prediction approach; and (3) estimate longitudinal SNP effects and candidate genes potentially associated with time-dependent variation in milk, fat, and protein yields, as well as somatic cell score (SCS) in multiple parities. The data used to estimate the genetic parameters consisted of a total of 323,140 test-day records. The average daily heritability estimates were moderate (0.35 ± 0.02 for milk yield, 0.22 ± 0.03 for fat yield, 0.42 ± 0.03 for protein yield, and 0.16 ± 0.03 for SCS). The highest heritability estimates, considering all traits studied, were observed between 20 and 280 d in milk (DIM). The genetic correlation estimates at different DIM among the evaluated traits ranged from -0.10 (156 to 185 DIM for SCS) to 0.61 (36 to 65 DIM for fat yield). In general, direct selection for any of the traits evaluated is expected to result in indirect genetic gains for milk yield, fat yield, and protein yield but also increase SCS at certain lactation stages, which is undesirable. The predicted RRM coefficients were used to derive the genomic estimated breeding values (GEBV) for each time point (from 5 to 305 DIM). In general, the tuning parameters evaluated when constructing the hybrid genomic relationship matrices had a small effect on the GEBV accuracy and a greater effect on the bias estimates. The SNP solutions were back-solved from the GEBV predicted from the Legendre random regression coefficients, which were then used to estimate the longitudinal SNP effects (from 5 to 305 DIM). The daily SNP effect for 3 different lactation stages were performed considering 3 different lactation stages for each trait and parity: from 5 to 70, from 71 to 150, and from 151 to 305 DIM. Important genomic regions related to the analyzed traits and parities that explain more than 0.50% of the total additive genetic variance were selected for further analyses of candidate genes. In general, similar potential candidate genes were found between traits, but our results suggest evidence of differential sets of candidate genes underlying the phenotypic expression of the traits across parities. These results contribute to a better understanding of the genetic architecture of milk production traits in dairy buffalo and reinforce the relevance of incorporating genomic information to genetically evaluate longitudinal traits in dairy buffalo. Furthermore, the candidate genes identified can be used as target genes in future functional genomics studies.

Why genetic selection to reduce the prevalence of infectious diseases is way more promising than currently believed

Genetic selection for improved disease resistance is an important part of strategies to combat infectious diseases in agriculture. Quantitative genetic analyses of binary disease status, however, indicate low heritability for most diseases, which restricts the rate of genetic reduction in disease prevalence. Moreover, the common liability threshold model suggests that eradication of an infectious disease via genetic selection is impossible because the observed-scale heritability goes to zero when the prevalence approaches zero. From infectious disease epidemiology, however, we know that eradication of infectious diseases is possible, both in theory and practice, because of positive feedback mechanisms leading to the phenomenon known as herd immunity. The common quantitative genetic models, however, ignore these feedback mechanisms. Here, we integrate quantitative genetic analysis of binary disease status with epidemiological models of transmission, aiming to identify the potential response to selection for reducing the prevalence of endemic infectious diseases. The results show that typical heritability values of binary disease status correspond to a very substantial genetic variation in disease susceptibility among individuals. Moreover, our results show that eradication of infectious diseases by genetic selection is possible in principle. These findings strongly disagree with predictions based on common quantitative genetic models, which ignore the positive feedback effects that occur when reducing the transmission of infectious diseases. Those feedback effects are a specific kind of Indirect Genetic Effects; they contribute substantially to the response to selection and the development of herd immunity (i.e., an effective reproduction ratio less than one).

Intergenerational cycle of disease: Maternal mastitis is associated with poorer daughter performance in dairy cattle

Adverse prenatal environments, such as maternal stress and infections, can influence the health and performance of offspring. Mastitis is the most common disease in dairy cattle, yet the intergenerational effects have not been specifically investigated. Therefore, we examined the associations between the dam's mammary gland health and daughter performance using somatic cell score (SCS) as a proxy for mammary health. Using data obtained from Dairy Records Management Systems (Raleigh, NC), we linked daughter records with their dam's records for the lactation in which the daughter was conceived. Linear and quadratic relationships of dam mean SCS with the daughter's age at first calving (AFC; n = 15,992 daughters, 4,366 herds), first- (n = 15,119 daughters, 4,213 herds) and second-lactation SCS (n = 3,570 daughters, 1,554 herds), first- and second-lactation mature-equivalent 305-d milk yield, and milk component yields were assessed using mixed linear regression models. We uncovered a phenomenon similar to those found in human and mouse models examining prenatal inflammation effects, whereby daughters born from dams with elevated SCS had poorer performance. Dam mean SCS was positively associated with daughter's AFC and first- and second-lactation mean SCS. Furthermore, for every 1-unit increase in dam mean SCS, daughter's first- and second-lactation mature-equivalent fat yield declined by 0.34% and 0.91% (-1.6 ± 0.49 kg, -4.0 ± 1.0 kg, respectively), although no effect was found on first- or second-lactation milk or milk protein yield. When accounting for genetics, daughter SCS, and AFC (first lactation only), dam mean SCS was associated with reduced second-lactation milk fat yield (-3.5 ± 1.8 kg/unit SCS), and a tendency was found for first-lactation milk fat yield (-1.9 ± 1.0 kg/unit SCS). Taken together, the association of greater dam mean SCS with lesser daughter milk fat yield is likely due to a few underlying mechanisms, in particular, a predisposition for mastitis and alterations in the epigenome controlling milk fat synthesis. As such, future studies should examine epigenetic mechanisms as a potential underpinning of this phenomenon.