The genetics of antibody response to paratuberculosis in dairy cattle

Genetic parameters were estimated for antibody response to paratuberculosis (Mycobacterium avium ssp. paratuberculosis) using milk ELISA test results, collected and analyzed by National Milk Records, from Holstein Friesian cows on UK dairy farms in their first 3 lactations. Milk ELISA test results were obtained from 2007 to 2012 and combined with milk recording data and pedigree information. The reduced data set edited for the purposes of genetic parameter estimation consisted of 148,054 milk ELISA records from 64,645 lactations in 40,142 cows of 908 sires, recorded in 641 herds. Milk ELISA test results were log_e-transformed and univariate analysis of 3 alternative animal models and equivalent sire models were considered. The most appropriate model included additive genetic and permanent environmental random effects, whereas maternal effects were significant according to likelihood ratio test and Akaike's information criterion but not for Bayesian information criterion. Heritability and repeatability estimates were 0.06 and 0.37, respectively, for the chosen animal model and its equivalent sire model. A subset of the data including herds with greater than 10% positive tests gave a slightly higher heritability of 0.08. Favorable but generally low significant genetic correlations were obtained between antibody response with 305-d milk yield (−0.16), 305-d protein yield (−0.16), log_e-transformed lactation-average somatic cell count (0.15), and the number of mastitis episodes (0.22). Thus, selection on the antibody response to paratuberculosis, should not be detrimental to production or udder health traits. Testing cattle for paratuberculosis is important for its use in control programs and although the heritability of antibody response was low, breeding against the disease might be a good prospect as a preventative measure to assist together with other approaches in an overall control strategy.     

Associations between paratuberculosis ELISA results and test-day records of cows enrolled in the Irish Johne's Disease Control Program

The effect of the Mycobacterium avium ssp. paratuberculosis (MAP) ELISA status on test-day milk performance of cows from Irish herds enrolled in the pilot national voluntary Johne's disease control program during 2013 to 2015 was estimated. A data set comprising 92,854 cows and 592,623 complete test-day records distributed across 1,700 herds was used in this study. The resulting ELISA outcome (negative, inconclusive, and positive) of each cow within each year of the program was used to allocate the cow into different scenarios representing the MAP status. At MAPscenario₁, all cows testing ELISA nonnegative (i.e., inconclusive and positive) were assigned a MAP-positive status; at MAPscenario₂ only cows testing ELISA-positive were assigned a MAP-positive status; at MAPscenario₃ only cows testing ELISA nonnegative (inconclusive or positive) and gathered exclusively from herds where at least 2 further ELISA nonnegative (inconclusive or positive) cows were found were assigned a MAP-positive status; at MAPscenario₄ only cows testing ELISA-positive that were gathered exclusively from herds where at least 2 further ELISA-positive cows were found were assigned a MAP-positive status. Milk outputs based on test-day records were standardized for fat and protein contents (SMY) and the effect of MAP ELISA status on the SMY was estimated by a linear mixed effects model structure. The SMY mean difference recorded at test day between cows with a MAP-positive status and those with a MAP-negative status within MAPscenario₁ was estimated at ?0.182 kg/test day; the mean difference was ?0.297 kg/test day for MAPscenario₂; for MAPscenario₃ mean difference between MAP-positive status and MAP test-negative cows was ?0.209 kg/test day, and for MAPscenario₄, the difference was ?0.326 kg/test day.     

Cows with paratuberculosis (Johne's disease) alter their lying behavior around peak lactation

Paratuberculosis or Johne's disease (JD) is a fatal chronic enteritis that causes detrimental effects on production and health and significantly reduces the welfare of cattle. Control of JD is highly desirable, but single milk ELISA testing may not be sensitive enough to identify all affected animals, particularly in the early stages of the disease. The objective of this study was to compare the activity of JD-positive (JD5) to JD-negative (JD0) cows from calving until wk 20 of lactation. The study was conducted at Harper Adams University, United Kingdom, using 42 multiparous [3.1 ± 0.22 (mean ± standard error of the mean); range: 2–7 lactations] Holstein Friesian cows, fitted with an IceQube accelerometer (IceRobotics Ltd., Edinburgh, UK) on the back left leg. The sensors recorded data on lying and standing time, steps, and motion index with a granularity of 15 min. In addition, start and stop times for lying bouts, and exact lying bout durations were recorded, which permits calculation of the number of lying bouts. Every 3 mo the cows were milk sampled and subsequently tested for JD using an ELISA. Cows in the infection group JD0 were classed as JD negative and cows in the infection group JD5 were classed as JD positive. Johne's-positive cows [JD5; n = 21 (repeat ELISA positive)] were matched to negative cows [JD0; n = 21 (repeat ELISA negative)] based on lactation number and age. Around peak lactation we found differences in lying behavior. The JD5 cows spend less time lying/d during wk 7 to 11 of lactation. The largest difference observed was around wk 8 of lactation, with JD5 cows spending, on average, 2 h/d less time lying down than JD0 cows (9.3 ± 0.33 vs. 11.3 ± 0.61 h/d, respectively). The JD5 cows also had fewer lying bouts per day from wk 7 to 15 of lactation (excluding wk 13), and during wk 11 and 12 average lying bout duration was longer for JD5 cows compared with JD0 cows. No differences were observed in steps per day, milk yield, BCS, and mobility score between JD5 and JD0 cows from calving to wk 20 of lactation. As far as we are aware, this is the first study to show changes in activity of JD-positive cows. The results show that activity data from leg-mounted accelerometers has the potential to help identify JD-positive cows, although more research is required.     

Structural equation modeling for unraveling the multivariate genomic architecture of milk proteins in dairy cattle

The aims of this study were to investigate potential functional relationships among milk protein fractions in dairy cattle and to carry out a structural equation model (SEM) GWAS to provide a decomposition of total SNP effects into direct effects and effects mediated by traits that are upstream in a phenotypic network. To achieve these aims, we first fitted a mixed Bayesian multitrait genomic model to infer the genomic correlations among 6 milk nitrogen fractions [4 caseins (CN), namely κ-, β-, α_S1-, and α_S2-CN, and 2 whey proteins, namely β-lactoglobulin (β-LG) and α-lactalbumin (α-LA)], in a population of 989 Italian Brown Swiss cows. Animals were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc.). A Bayesian network approach using the max-min hill-climbing (MMHC) algorithm was implemented to model the dependencies or independence among traits. Strong and negative genomic correlations were found between β-CN and α_S1-CN (?0.706) and between β-CN and κ-CN (?0.735). The application of the MMHC algorithm revealed that κ-CN and β-CN seemed to directly or indirectly influence all other milk protein fractions. By integrating multitrait model GWAS and SEM-GWAS, we identified a total of 127 significant SNP for κ-CN, 89 SNP for β-CN, 30 SNP for α_S1-CN, and 14 SNP for α_S2-CN (mostly shared among CN and located on Bos taurus autosome 6) and 15 SNP for β-LG (mostly located on Bos taurus autosome 11), whereas no SNP passed the significance threshold for α-LA. For the significant SNP, we assessed and quantified the contribution of direct and indirect paths to total marker effect. Pathway analyses confirmed that common regulatory mechanisms (e.g., energy metabolism and hormonal and neural signals) are involved in the control of milk protein synthesis and metabolism. The information acquired might be leveraged for setting up optimal management and selection strategies aimed at improving milk quality and technological characteristics in dairy cattle.     

Phenotypic and genetic effects of season on milk production traits in dairy cattle in the Netherlands

Milk production systems in several countries show considerable differences between seasons. For example, in the Netherlands, cows are kept inside and fed silage in winter, whereas they are on pasture in summer. The differences between seasons affect milk yield and composition and might influence the genetic background of milk production traits. The objective of this study was to estimate phenotypic and genetic effects of season on milk production traits. For this purpose, 19,286 test-day milk production records of 1,800 first-parity Dutch Holstein-Frisian cows were available, and these cows were genotyped using a 50K SNP panel. Phenotypic effects of season were significant for all milk production traits. Effects of season were large for milk fat yield, fat content, and protein content. Genetic correlations between milk production traits in different seasons showed that genotype by season interaction effects were relatively small for most milk production traits. The genetic background of protein content and lactose content seems to be sensitive to seasonal effects. Furthermore, the genetic correlations between spring and autumn differed significantly from unity for almost all milk production traits. A genome-wide association study for genotype by season interaction identified chromosomal regions on BTA3, BTA14, BTA20, and BTA25 that showed genotype by season interaction effects, including a region containing DGAT1, which showed interaction effects for fat content and protein content.     

Detection of microRNA in cattle serum and their potential use to diagnose severity of Johne's disease

Mycobacterium avium subspecies paratuberculosis (MAP) causes Johne's disease in ruminants, which is characterized by chronic progressive granulomatous enteritis. The infection leads to wasting and weight loss in the animals and eventually death, causing considerable production losses to the agricultural industry worldwide. Currently available ELISA- and PCR-based diagnostic tests have limited sensitivity and specificity during early MAP infection in cattle, suggesting that there is an urgent demand for alternative diagnostic tests. Circulating microRNA (miRNA) have recently gained attention as potential biomarkers for several diseases in humans. However, knowledge and use of miRNA as biomarkers in diseases of ruminants, including Johne's disease, are very limited. Here we used NanoString nCounter technology (NanoString, Seattle, WA), a digital platform for amplification-free and hybridization-based quantitative measurement of miRNA in the sera of noninfected and naturally MAP-infected cattle with different severity of infection. Using probes developed against human miRNA, 26 miRNA were detected in cattle serum; 13 of these miRNA were previously uncharacterized for cattle. Canonical discrimination analysis using 20 miRNA grouped animals into 4 distinct clusters based on their disease status, suggesting that the levels of these miRNA can reflect disease severity. A model was developed using a combination of 4 miRNA (miR-1976, miR-873-3p, miR-520f-3p, and miR-126-3p), which distinguished moderate and severely infected animals from noninfected animals. Our study demonstrated the ability of the NanoString nCounter technology to detect differential expression of circulating miRNA in cattle and contributes to widely growing evidence that miRNA can be used as biomarkers in infectious diseases in cattle.     

Economic losses due to Johne's disease (paratuberculosis) in dairy cattle

Johne's disease (JD), or paratuberculosis, is an infectious inflammatory disorder of the intestines primarily associated with domestic and wild ruminants including dairy cattle. The disease, caused by an infection with Mycobacterium avium subspecies paratuberculosis (MAP) bacteria, burdens both animals and producers through reduced milk production, premature culling, and reduced salvage values among MAP-infected animals. The economic losses associated with these burdens have been measured before, but not across a comprehensive selection of major dairy-producing regions within a single methodological framework. This study uses a Markov chain Monte Carlo approach to estimate the annual losses per cow within MAP-infected herds and the total regional losses due to JD by simulating the spread and economic impact of the disease with region-specific economic variables. It was estimated that approximately 1% of gross milk revenue, equivalent to US$33 per cow, is lost annually in MAP-infected dairy herds, with those losses primarily driven by reduced production and being higher in regions characterized by above-average farm-gate milk prices and production per cow. An estimated US$198 million is lost due to JD in dairy cattle in the United States annually, US$75 million in Germany, US$56 million in France, US$54 million in New Zealand, and between US$17 million and US$28 million in Canada, one of the smallest dairy-producing regions modeled.     

A validated genome-wide association study in 2 dairy cattle breeds for milk production and fertility traits using variable length haplotypes

Genome-wide association studies (GWAS) were used to discover genomic regions explaining variation in dairy production and fertility traits. Associations were detected with either single nucleotide polymorphism (SNP) markers or haplotypes of SNP alleles. An across-breed validation strategy was used to narrow the genomic interval containing causative mutations. There were 39,048 SNP tested in a discovery population of 780 Holstein sires and validated in 386 Holsteins and 364 Jersey sires. Previously identified mutations affecting milk production traits were confirmed. In addition, several novel regions were identified, including a putative quantitative trait loci for fertility on chromosome 18 that was detected only using haplotypes greater than 3 SNP long. It was found that the precision of quantitative trait loci mapping increased with haplotype length as did the number of validated haplotypes discovered, especially across breed. Promising candidate genes have been identified in several of the validated regions.     

Estimation of genetic parameters and single-step genome-wide association studies for milk urea nitrogen in Holstein cattle

The main objectives of this study were to estimate genetic parameters for milk urea nitrogen (MUN) in Holstein cattle and to conduct a single-step (ss)GWAS to identify candidate genes associated with MUN. Phenotypic measurements from 24,435 Holstein cows were collected from March 2013 to July 2019 in 9 dairy farms located in the Beijing area, China. A total of 2,029 cows were genotyped using the Illumina 150K Bovine Bead Chip, containing 121,188 SNP. A single-trait repeatability model was used to evaluate the genetic background of MUN. We found that MUN is a trait with low heritability (0.06 ± 0.004) and repeatability (0.12). Considering similar milk production levels, a lower MUN concentration indicates higher nitrogen digestibility. The genetic correlations between MUN and milk yield, net energy concentration, fat percentage, protein percentage, and lactose percentage were positive and ranged from 0.02 to 0.26. The genetic correlation between MUN and somatic cell score (SCS) was negative (?0.18), indicating that animals with higher MUN levels tend to have lower SCS. Both ssGWAS and pathway enrichment analyses were used to explore the genetic mechanisms underlying MUN. A total of 18 SNP (located on BTA11, BTA12, BTA14, BTA17, and BTA18) were found to be significantly associated with MUN. The genes CFAP77, CAMSAP1, CACNA1B, ADGRB1, FARP1, and INTU are considered to be candidate genes for MUN. These candidate genes are associated with important biological processes such as protein and lipid metabolism and binding to specific proteins. This set of candidate genes, metabolic pathways, and their functions provide a better understanding of the genomic architecture and physiological mechanisms underlying MUN in Holstein cattle.     

Underlying genetic architecture of resistance to mastitis in dairy cattle: A systematic review and gene prioritization analysis of genome-wide association studies

Mastitis, the most frequent disease in dairy cattle. Resistance to mastitis is a complex, polygenic trait controlled by several genes, each with small effects. Genome-wide association studies have been widely used to identify genomic variants associated with complex traits, including resistance to mastitis, to elucidate the underlying genetic architecture of the trait. However, no systematic review and gene prioritization analysis have been conducted to date on GWAS results for resistance to mastitis in dairy cattle. Hence, the objective was to perform a systematic review and gene prioritization analysis of GWAS studies to identify potential functional candidate genes associated with resistance to mastitis-related traits in dairy cattle. Four electronic databases were searched from inception to December 2020, supplemented with multiple sources of gray literature, to identify eligible articles. Annotation for genes and quantitative trait loci (QTL), and QTL enrichment analysis were conducted using GALLO. Gene prioritization analysis was performed by a guilty-by-association approach using GUILDify and ToppGene. From 52 articles included within this systematic review, 30 articles were used for further functional analyses. Gene and QTL annotation resulted in 9,125 and 43,646 unique genes and QTL, respectively, from 39 studies. In general, overlapping of genes across studies was very low (mean ± SD = 0.02% ± 0.07%). Most annotated genes were associated with somatic cell count-related traits and the Holstein breed. Within all annotated genes, 74 genes were shared among Holstein, Jersey, and Ayrshire breeds. Approximately 7.5% of annotated QTL were related to QTL class “health.” Within the health QTL class, 2.6 and 2.2% of QTL were associated with clinical mastitis and somatic cell count-related traits. Enrichment analysis of QTL demonstrated that many enriched QTL were associated with somatic cell score located in Bos taurus autosomes 5, 6, 16, and 20. The prioritization analysis resulted in 427 significant genes after multiple test correction (false discovery rate of 5%) from 26 studies. Most prioritized genes were located in Bos taurus autosomes 19 and 7, and most top-ranked genes were from the cytokine superfamily (e.g., chemokines, interleukins, transforming growth factors, and tumor necrosis factor genes). Although most prioritized genes (397) were associated with somatic cell count-related traits, only 54 genes were associated with clinical mastitis-related traits. Twenty-four genes (ABCC9, ACHE, ADCYAP1, ARC, BCL2L1, CDKN1A, EPO, GABBR2, GDNF, GNRHR, IKBKE, JAG1, KCNJ8, KCNQ1, LIFR, MC3R, MYOZ3, NFKB1, OSMR, PPP3CA, PRLR, SHARPIN, SLC1A3, and TNFRSF25) were reported for both somatic cell count and clinical mastitis-related traits. Prioritized genes were mainly associated with immune response, regulation of secretion, locomotion, cell proliferation, and development. In conclusion, this study provided a fine-mapping of previously identified genomic regions associated with resistance to mastitis and identified key functional candidate genes for resistance to mastitis, which can be used to develop enhanced genomic strategies to combat mastitis by increasing mastitis resistance through genetic selection.     

Genomic analyses and biological validation of candidate genes for rectal temperature as an indicator of heat stress in Holstein cattle

Heat stress is a major cause of welfare issues and economic losses to the worldwide dairy cattle industry. Genetic selection for heat tolerance has a great potential to positively affect the dairy industry, as the gains are permanent and cumulative over generations. Rectal temperature (RT) is hypothesized to be a good indicator trait of heat tolerance. Therefore, this study investigated the genetic architecture of RT by estimating genetic parameters, performing genome-wide association studies, and biologically validating potential candidate genes identified to be related to RT in Holstein cattle. A total of 33,013 RT records from 7,598 cows were used in this study. In addition, 1,114 cows were genotyped using the Illumina 150K Bovine BeadChip (Illumina, San Diego, CA). Rectal temperature measurements taken in the morning (AMRT) and in the afternoon (PMRT) are moderately heritable traits, with estimates of 0.09 ± 0.02 and 0.04 ± 0.01, respectively. These 2 traits are also highly genetically correlated (r = 0.90 ± 0.08). A total of 10 SNPs (located on BTA3, BTA4, BTA8, BTA13, BTA14, and BTA29) were found to be significantly associated with AMRT and PMRT. Subsequently, gene expression analyses were performed to validate the key functional genes identified (SPAG17, FAM107B, TSNARE1, RALYL, and PHRF1). This was done through in vitro exposure of peripheral blood mononuclear cells (PBMC) to different temperatures (37°C, 39°C, and 42°C). The relative mRNA expression of 2 genes, FAM107B and PHRF1, significantly changed between the control and heat stressed PBMC. In summary, RT is heritable, and enough genetic variability exists to enable genetic improvement of heat tolerance in Holstein cattle. Important genomic regions were identified and biologically validated; FAM107B and PHRF1 are the main candidate genes identified to influence heat stress response in dairy cattle.     

The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows

The objective of this study was to identify genomic regions and candidate genes associated with feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 single nucleotide polymorphisms having individual feed intake, milk yield, milk composition, and body weight records were used in this study. Cows were from research herds located in the United States, Canada, the Netherlands, and the United Kingdom. Feed efficiency, defined as residual feed intake (RFI), was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed considering each trait as a separate trait within parity group to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method with a prior assumption that 1% of single nucleotide polymorphisms have a nonzero effect. One-megabase windows with greatest percentage of the total genetic variation explained by the markers (TGVM) were identified, and adjacent windows with large proportion of the TGVM were combined and reanalyzed. Heritability estimates for RFI were 0.14 (±0.03; ±SE) in primiparous cows and 0.13 (±0.03) in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW, and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, after combining windows, significance was met on Bos taurus autosome 27 in primiparous cows, and nearly reached on Bos taurus autosome 4 in multiparous cows. Among other genes, these regions contain β-3 adrenergic receptor and the physiological candidate gene, leptin, respectively. Between the 2 parity groups, 3 of the 10 windows with the largest effects on DMI neighbored windows affecting RFI, but were not in the top 10 regions for MilkE or MBW. This result suggests a genetic basis for feed intake that is unrelated to energy consumption required for milk production or expected maintenance as determined by MBW. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.     

Pathway-based genome-wide association analysis of milk coagulation properties,curd firmness,cheese yield,and curd nutrient recovery in dairy cattle

It is becoming common to complement genome-wide association studies (GWAS) with gene-set enrichment analysis to deepen the understanding of the biological pathways affecting quantitative traits. Our objective was to conduct a gene ontology and pathway-based analysis to identify possible biological mechanisms involved in the regulation of bovine milk technological traits: coagulation properties, curd firmness modeling, individual cheese yield (CY), and milk nutrient recovery into the curd (REC) or whey loss traits. Results from 2 previous GWAS studies using 1,011 cows genotyped for 50k single nucleotide polymorphisms were used. Overall, the phenotypes analyzed consisted of 3 traditional milk coagulation property measures [RCT: rennet coagulation time defined as the time (min) from addition of enzyme to the beginning of coagulation; k₂₀: the interval (min) from RCT to the time at which a curd firmness of 20 mm is attained; a₃₀: a measure of the extent of curd firmness (mm) 30 min after coagulant addition], 6 curd firmness modeling traits [RCT_eq: RCT estimated through the CF equation (min); CF_P: potential asymptotic curd firmness (mm); k_CF: curd-firming rate constant (% × min^?1); k_SR: syneresis rate constant (% × min^?1); CF_max: maximum curd firmness (mm); and t_max: time to CF_max (min)], 3 individual CY-related traits expressing the weight of fresh curd (%CY_CURD), curd solids (%CY_SOLIDS), and curd moisture (%CY_WATER) as a percentage of weight of milk processed and 4 milk nutrient and energy recoveries in the curd (REC_FAT, REC_PROTEIN, REC_SOLIDS, and REC_ENERGY calculated as the % ratio between the nutrient in curd and the corresponding nutrient in processed milk), milk pH, and protein percentage. Each trait was analyzed separately. In total, 13,269 annotated genes were used in the analysis. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases were queried for enrichment analyses. Overall, 21 Gene Ontology and 17 Kyoto Encyclopedia of Genes and Genomes categories were significantly associated (false discovery rate at 5%) with 7 traits (RCT, RCT_eq, k_CF, %CY_SOLIDS, REC_FAT, REC_SOLIDS, and REC_ENERGY), with some being in common between traits. The significantly enriched categories included calcium signaling pathway, salivary secretion, metabolic pathways, carbohydrate digestion and absorption, the tight junction and the phosphatidylinositol pathways, as well as pathways related to the bovine mammary gland health status, and contained a total of 150 genes spanning all chromosomes but 9, 20, and 27. This study provided new insights into the regulation of bovine milk coagulation and cheese ability that were not captured by the GWAS.     

Genetic and genomic analyses of latent variables related to the milk fatty acid profile,milk composition,and udder health in dairy cattle

The aim of this study was to perform genetic, genome-wide association (GWAS), and gene-set enrichment analyses with latent variables related to milk fatty acid profile (i.e., fatty acids factor scores; FAF), milk composition, and udder health in a cohort of 1,158 Italian Brown Swiss cows. The phenotypes under study were 12 FAF previously identified through factor analysis and classified as follows: de novo FA (F1), branched-chain FA-milk yield (F2), biohydrogenation (F3), long-chain fatty acids (F4), desaturation (F5), short-chain fatty acids (F6), milk protein and fat contents (F7), odd fatty acids (F8), conjugated linoleic acids (F9), linoleic acid (F10), udder health (F11) and vaccelenic acid (F12). (Co)variance components were estimated for factor scores using a Bayesian linear animal model via Gibbs sampling. The animals were genotyped with the Illumina BovineSNP50 BeadChip v.2 (Illumina Inc., San Diego, CA). A single marker regression model was fitted for GWAS analysis. The gene-set enrichment analysis was run on the GWAS results using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway databases to identify the ontologies and pathways associated with the FAF. Marginal posterior means of the heritabilities of the aforementioned FAF ranged from 0.048 for F12 to 0.310 for F5. Factors F1 and F6 had the highest number of relevant genetic correlations with the other traits. The genomic analysis detected a total of 39 significant SNP located on 17 Bos taurus autosomes. All latent variables produced signals except for F2 and F10. The traits with the highest number of significant associations were F11 (17) and F12 (7). Gene-set enrichment analyses identified significant pathways (false discovery rate 5%) for F3 and F7. In particular, systemic lupus erythematosus was enriched for F3, whereas the MAPK (mitogen-activated protein kinase) signaling pathway was overrepresented for F7. The results support the existence of important and exploitable genetic and genomic variation in these latent explanatory phenotypes. Information acquired might be exploited in selection programs and when designing further studies on the role of the putative candidate genes identified in the regulation of milk composition and udder health.     

Estimation of genetic parameters for individual udder quarter milk content traits in Brown Swiss cattle

The aim of this study was to estimate genetic parameters and accuracies of breeding values for milk content traits of individual udder quarters in Brown Swiss cattle. Data of 1,799 phenotyped cows from 40 Swiss dairy herds were analyzed, taking the complete pedigree into account. Fat, protein, lactose, and urea contents, somatic cell score (SCS), and information about hyperkeratosis were available for each udder quarter. The milk of rear udder quarters was found to have significantly higher lactose content and significantly lower fat content than milk of the front udder quarters. The same trend found for fat content was observed for protein content, whereas no differences between the udder quarters were observed for urea content, SCS, or hyperkeratosis. Heritabilities for each udder quarter were in the following ranges: fat content 0.09 ± 0.06 to 0.14 ± 0.06, protein content 0.20 ± 0.09 to 0.33 ± 0.07, lactose content 0.04 ± 0.03 to 0.16 ± 0.07, urea content 0.13 ± 0.07 to 0.22 ± 0.08, SCS 0.18 ± 0.06 to 0.32 ± 0.07, and hyperkeratosis 0.12 ± 0.04 to 0.26 ± 0.05. In our study, hyperkeratosis, protein content, and SCS showed higher heritabilities in the front udder quarters, fat content had higher heritabilities in the rear udder quarters, and no systematic pattern in heritability was observed for lactose content or urea content. Additive genetic correlations between all udder quarters were >0.90 for protein and urea contents, whereas they were remarkably low (<0.60) for SCS. For fat and lactose contents, the genetic correlations between the 2 front or between the 2 rear quarters, respectively, were notably higher than correlations between 1 front and 1 rear quarter, suggesting that the front and the rear udders could be considered as partly genetically different organs. The variability within the udder as such was found to be of low heritability (<0.10) in general, but repeatability was moderate to high for some traits (lactose content: 0.33 ± 0.05, protein content: 0.53 ± 0.05). Some of these findings can be explained by differences in the physiological background of the traits.     

Detection of cows' milk in ewes' milk and cheese by a sandwich enzyme-linked immunosorbent assay (ELISA)

A sandwich enzyme-linked immunosorbent assay (ELISA) has been successfully developed for the detection of defined amounts of cows' milk in ewes' milk and cheese. Polyclonal antibodies were raised in goats against bovine caseins (BC). The resultant antibodies were recovered from the crude antiserum by ammonium sulphate precipitation and further purified by immunoatisorption of the cross-reacting antibodies onto columns containing immobilised ovine, caprine and bovine caseins, followed by elution of the bovine caseins specific antibodies (anti-BC) from the column containing the bovine caseins. The anti-BC bound to the wells of a microtitre plate were used to capture the BC from milk and cheese mixtures. Further immunorecognition of the captured proteins was attained with the same specific antibodies conjugated to biotin. ExtrAvidin-peroxidase was used to detect biotinylated antibodies bound to their specific antigens. Subsequent enzymic conversion of substrate gave clear absorbance differences when assaying mixtures of ewes' milk and cheese containing variable amounts of cows' milk.     

The occurrence of noncoagulating milk and the association of bovine milk coagulation properties with genetic variants of the caseins in 3 Scandinavian dairy breeds

Substantial variation in milk coagulation properties has been observed among dairy cows. Consequently, raw milk from individual cows and breeds exhibits distinct coagulation capacities that potentially affect the technological properties and milk processing into cheese. This variation is largely influenced by protein composition, which is in turn affected by underlying genetic polymorphisms in the major milk proteins. In this study, we conducted a large screening on 3 major Scandinavian breeds to resolve the variation in milk coagulation traits and the frequency of milk with impaired coagulation properties (noncoagulation). In total, individual coagulation properties were measured on morning milk collected from 1,299 Danish Holstein (DH), Danish Jersey (DJ), and Swedish Red (SR) cows. The 3 breeds demonstrated notable interbreed differences in coagulation properties, with DJ cows exhibiting superior coagulation compared with the other 2 breeds. In addition, milk samples from 2% of DH and 16% of SR cows were classified as noncoagulating. Furthermore, the cows were genotyped for major genetic variants in the α_S1- (CSN1S1), β- (CSN2), and κ-casein (CSN3) genes, revealing distinct differences in variant frequencies among breeds. Allele I of CSN2, which had not formerly been screened in such a high number of cows in these Scandinavian breeds, showed a frequency around 7% in DH and DJ, but was not detected in SR. Genetic polymorphisms were significantly associated with curd firming rate and rennet coagulation time. Thus, CSN1S1 C, CSN2 B, and CSN3 B positively affected milk coagulation, whereas CSN2 A², in particular, had a negative effect. In addition to the influence of individual casein genes, the effects of CSN1S1-CSN2-CSN3 composite genotypes were also examined, and revealed strong associations in all breeds, which more or less reflected the single gene results. Overall, milk coagulation is under the influence of additive genetic variation. Optimal milk for future cheese production can be ensured by monitoring the frequency of unfavorable variants and thus preventing an increase in the number of cows producing milk with impaired coagulation. Selective breeding for variants associated with superior milk coagulation can potentially increase raw milk quality and cheese yield in all 3 Scandinavian breeds.     

Short communication: Replication of genome-wide association studies for milk production traits in Chinese Holstein by an efficient rotated linear mixed model

Milk is regarded as an important nutrient for humans, and Chinese Holstein cows provide high-quality milk for billions of Chinese people. Therefore, detecting quantitative trait nucleotides (QTN) or candidate genes for milk production traits in Chinese Holstein is important. In this study, we performed genome-wide association studies (GWAS) in a Chinese Holstein population of 6,675 cows and 71,633 SNP using deregressed proofs (DRP) as phenotypes to replicate our previous study in a population of 1,815 cows and 39,163 SNP using estimated breeding values (EBV) as phenotypes. The associations between 3 milk production traits—milk yield (MY), fat percentage (FP), and protein percentage (PP)—and the SNP were determined by using an efficient rotated linear mixed model, which benefits from linear transformations of genomic estimated values and Eigen decomposition of the genomic relationship matrix algorithm. In total, we detected 94 SNP that were significantly associated with one or more milk production traits, including 7 SNP for MY, 76 for FP, and 36 for PP; 87% of these SNP were distributed across Bos taurus autosomes 14 and 20. In total, 83 SNP were found to be located within the reported quantitative trait loci (QTL) regions, and one novel segment (between 1.41 and 1.49 Mb) on chromosome 14 was significantly associated with FP, which could be an important candidate QTL region. In addition, the detected intervals were narrowed down from the reported regions harboring causal variants. The top significant SNP for the 3 traits was ARS-BFGL-NGS-4939, which is located within the DGAT1 gene. Five detected genes (CYHR1, FOXH1, OPLAH, PLEC, VPS28) have effects on all 3 traits. Our study provides a suite of QTN, candidate genes, and a novel QTL associated with milk production traits, and thus forms a solid basis for genomic selection and molecular breeding for milk production traits in Chinese Holstein.     

Short communication: Genetic association of variations in the osteopontin gene (SPP1) with lactation persistency in dairy cattle

Improving lactation persistency (LP) in dairy cattle has a beneficial effect on animal health and fertility and herd productivity. A complex trait, LP not only reflects the cow's ability to maintain milk secretion activity after the lactation peak but is also a function of the postcalving development of the mammary gland and, later on, of tissue remodeling as lactation declines. This decline is a consequence of an imbalance between cell proliferation and cell removal. In a previous study, single nucleotide polymorphisms were identified in the osteopontin (OPN) gene, SPP1. Osteopontin is a multifaceted protein that plays an important role in immune regulation and tissue remodeling. Because OPN is involved in involution, it might also have an effect on LP. The objective of the present study was to evaluate whether LP could be influenced by genetic variations in the SPP1 gene. This association with LP was analyzed in the population of 578 bulls characterized in a previous study. The population mean of estimated breeding value (EBV) for LP was 100.95 ± 5.06 units. Allele and genotype association analyses were performed by comparing the frequencies of the different genotypes and alleles with EBV for LP for the respective lactation using logistic regression. The EBV for LP at the first lactation (LP1), second lactation (LP2), and third lactation (LP3) and for overall lactation (OLP) are reported for the genotypes SPP1c.-1301G>A, SPP1c.-1251C>T, SPP1c.-430G>A, and SPP1c.*40A>C. The first single nucleotide polymorphism, SPP1c.-1301G>A, affected LP1, LP2, LP3, and OLP. Analysis of the estimated average allele substitution effects also confirmed that G is a favorable allele for LP, given the gain observed over LP1, LP2, LP3, and OLP. Differences in EBV for LP were observed between animals with different haplotypes at LP1, LP2, LP3, and OLP. Contrast analysis for OLP revealed that mean EBV is greater for block H1 (101.34 ± 0.30) than for animals that do not have H1 (98.20 ± 0.77). The gain with block H1 (GCGA) suggests the presence of the favorable allele G (first position in the block: SPP1c.-1301G). The pleiotropic roles of OPN position it at the crossroads of immune regulation, tissue remodeling, and involution. From a genetic perspective, data from the present study suggest OPN as a candidate gene associated with LP for dairy cows.     

The effect of genetic selection for Johne’s disease resistance in dairy cattle: Results of a genetic-epidemiological model

The objective of this study was to model genetic selection for Johne’s disease resistance and to study the effect of different selection strategies on the prevalence in the dairy cattle population. In the Netherlands, a certification-and-surveillance program is in use to reduce prevalence and presence of sources of infection in milk by culling ELISA-positive dairy cows in infected herds. To investigate the additional genetic effect of this program, a genetic-epidemiological model was developed to assess the effect of selection of cows that test negative for Johne’s disease (dam selection). The genetic effect of selection at the sire level was also considered (sire selection), assuming selection of 80% of sires producing the most resistant offspring based on their breeding values, as well as the combined effect. Parameters assumed to be affected by genetic selection were the length of the latent period, susceptibility (i.e., the number of infectious doses needed to become infected), or the length of susceptible period as a calf. The effect of selection was measured by the time in years required to eliminate infection. Sensitivity analysis was performed for heritability, accuracy of selection, and intensity of selection. For dam selection, responses to selection were small, requiring 379 to 702 yr for elimination. For sire selection, responses were much larger, although elimination still required 147 to 223 yr. The response to selection was largest if genetic selection affected the length of the susceptible period, followed by the susceptibility, and finally the length of the latent period. Genetic selection for Johne’s disease resistance by certification and surveillance is too slow for practical purpose, but that selection on the sire level is able to contribute to the control of Johne’s disease in the long run.