Genetic analysis on infrared-predicted milk minerals for Danish dairy cattle.

A group of milk components that has shown potential to be predicted with milk spectra is milk minerals. Milk minerals are important for human health and cow health. Having an inexpensive and fast way to measure milk mineral concentrations would open doors for research, herd management, and selective breeding. The first aim of this study was to predict milk minerals with infrared milk spectra. Additionally, milk minerals were predicted with infrared-predicted fat, protein, and lactose content. The second aim was to perform a genetic analysis on infrared-predicted milk minerals, to identify QTL, and estimate variance components. For training and validating a multibreed prediction model for individual milk minerals, 264 Danish Jersey cows and 254 Danish Holstein cows were used. Partial least square regression prediction models were built for Ca, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on 80% of the cows, selected randomly. Prediction models were externally validated with 8 herds based on the remaining 20% of the cows. The prediction models were applied on a population of approximately 1,400 Danish Holstein cows with 5,600 infrared spectral records and 1,700 Danish Jersey cows with 7,200 infrared spectral records. Cows from this population had 50k imputed genotypes. Prediction accuracy was good for P and Ca, with external R2 ≥ 0.80 and a relative prediction error of 5.4% for P and 6.3% for Ca. Prediction was moderately good for Na with an external R2 of 0.63, and a relative error of 18.8%. Prediction accuracies of milk minerals based on infrared-predicted fat, protein, and lactose content were considerably lower than those based on the infrared milk spectra. This shows that the milk infrared spectrum contains valuable information on milk minerals, which is currently not used. Heritability for infrared-predicted Ca, Na, and P varied from low (0.13) to moderate (0.36). Several QTL for infrared-predicted milk minerals were observed that have been associated with gold standard milk minerals previously. In conclusion, this study has shown infrared milk spectra were good at predicting Ca, Na, and P in milk. Infrared-predicted Ca, Na, and P had low to moderate heritability estimates.

Changes in milk lactose content as indicators for longevity and udder health in Holstein cows.

Changes in milk production traits over time might be informative of the health status of cows and may contain useful information for selective breeding purposes. In particular, early indicators are useful for traits such as longevity, which become available late in the cow's life. Lactose percentage (LP) tends to decrease in the presence of udder infection and with parity. Therefore, it can be hypothesized that cows exhibiting limited changes in LP across lactations have experienced fewer udder infections in their productive life and have a higher chance to stay longer in the herd than cows with more pronounced reduction of LP across lactations. In this study, 9 descriptors of change in LP during a cow's lifetime were defined and evaluated as potential indicators for selective breeding. For the purpose of this study, test-day records of the first 44 days in milk (DIM) of each lactation were discarded, and cows were required to have at least 5 test-days/cow per lactation (≥45 DIM) over the first 3 lactations. In this study, descriptors of LP were available for 69,586 Italian Holstein cows. Changes in LP in each lactation were quantified by regressing LP on DIM; thus, ß1, ß2, and ß3 represented the changes in LP within lactations 1, 2, and 3, respectively. Changes in LP across multiple lactations were also quantified by regressing LP on DIM (with exclusion of the first 44 DIM of each lactation); briefly, ß12 was the change of LP over lactation 1 and 2, ß23 was the change of LP over lactation 2 and 3, and ß123 was the change of LP over lactation 1, 2, and 3. Alternatively, changes in the LP lactation means (Δ) were quantified between lactations 1 and 2 (Δ12), 2 and 3 (Δ23), and 1 and 3 (Δ13). For comparison, ß and Δ were also derived for milk yield (kg/d), somatic cell score, and log-transformed total somatic cells excreted daily in milk (units). Variance components and estimated breeding values (EBV) for all ß's and Δ's were estimated. In addition, EBV for bulls with at least 25 daughters were used to assess Calo's genetic correlations between descriptors of change in LP with official published EBV for functional traits. Heritabilities for ß and Δ of LP ranged from 0.06 (Δ23) to 0.20 (Δ13), and differed significantly from 0. Furthermore, LP EBV for ß and Δ were correlated with official EBV for functional longevity index, udder health index, udder score (mammary gland morphology) index, and milk persistency; Calo's genetic correlations of LP ß123 with functional longevity and udder health index were 0.52 and 0.33, respectively. Cows with a stronger reduction of LP across lactations (i.e., stronger and negative ß, and greater and positive Δ) were characterized by lower milk persistency, impaired longevity, and worse udder health and morphology than cows with smaller reduction in LP across lactations. Results highlighted that changes in milk LP have the potential to be exploited as indicators for functional traits in Italian Holstein cattle. Further research on the biological relationship between changes in LP and mastitis is recommended.

Genetic analysis of orotic acid predicted with Fourier transform infrared milk spectra.

Fourier transform infrared spectral analysis is a cheap and fast method to predict milk composition. A not very well studied milk component is orotic acid. Orotic acid is an intermediate in the biosynthesis pathway of pyrimidine nucleotides and is an indicator for the metabolic cattle disorder deficiency of uridine monophosphate synthase. The function of orotic acid in milk and its effect on calf health, health of humans consuming milk or milk products, manufacturing properties of milk, and its potential as an indicator trait are largely unknown. The aims of this study were to determine if milk orotic acid can be predicted from infrared milk spectra and to perform a large-scale phenotypic and genetic analysis of infrared-predicted milk orotic acid. An infrared prediction model for orotic acid was built using a training population of 292 Danish Holstein and 299 Danish Jersey cows, and a validation population of 381 Danish Holstein cows. Milk orotic acid concentration was determined with nuclear magnetic resonance spectroscopy. For genetic analysis of infrared orotic acid, 3 study populations were used: 3,210 Danish Holstein cows, 3,360 Danish Jersey cows, and 1,349 Dutch Holstein Friesian cows. Using partial least square regression, a prediction model for orotic acid was built with 18 latent variables. The error of the prediction for the infrared model varied from 1.0 to 3.2 mg/L, and the accuracy varied from 0.68 to 0.86. Heritability of infrared orotic acid predicted with the standardized prediction model was 0.18 for Danish Holstein, 0.09 for Danish Jersey, and 0.37 for Dutch Holstein Friesian. We conclude that milk orotic acid can be predicted with moderate to good accuracy based on infrared milk spectra and that infrared-predicted orotic acid is heritable. The availability of a cheap and fast method to predict milk orotic acid opens up possibilities to study the largely unknown functions of milk orotic acid.

Can greenhouse gases in breath be used to genetically improve feed efficiency of dairy cows?

There is considerable interest in improving feed utilization of dairy cattle while limiting losses to the environment (i.e., greenhouse gases, GHG). To breed for feed-efficient or climate-friendly cattle, it is first necessary to obtain accurate estimates of genetic parameters and correlations of feed intake, greenhouse gases, and production traits. Reducing dry matter take (DMI) requirements while maintaining production has high economic value to farmers, but DMI is costly to record and thus limited to small research or nucleus herds. Conversely, enteric methane (CH4) currently has no economic value, is also costly to record, and is limited to small experimental trials. However, breath gas concentrations of methane (CH4c) and carbon dioxide (CO2c) are relatively cheap to measure at high throughput under commercial conditions by installing sniffers in automated milking stations. The objective of this study was to assess the genetic correlations between DMI, body weight (BW), fat- and protein-corrected milk yield (FPCM), and GHG-related traits: CH4c and CO2c from Denmark (DNK) and the Netherlands (NLD). A second objective was to assess the genetic potential for improving feed efficiency and the added benefits of using CH4c and CO2c as indicators. Feed intake data were available on 703 primiparous cows in DNK and 524 in NLD; CH4c and CO2c records were available on 434 primiparous cows in DNK and 656 in NLD. The GHG-related traits were heritable (e.g., CH4c h2: DNK = 0.26, NLD = 0.15) but were differentially genetically correlated with DMI and feed efficiency in both magnitude and sign, depending on the population and the definition of feed efficiency. Across feed efficiency traits and DMI, having bulls with 100 daughters with FPCM, BW, and GHG traits resulted in sufficiently high accuracy to almost negate the need for DMI records. Despite differences in genetic correlation structure, the relatively cheap GHG-related traits showed considerable potential for improving the accuracy of breeding values of highly valuable feed intake and feed efficiency traits.

Combining multi-population datasets for joint genome-wide association and meta-analyses: The case of bovine milk fat composition traits.

In genome-wide association studies (GWAS), sample size is the most important factor affecting statistical power that is under control of the investigator, posing a major challenge in understanding the genetics underlying difficult-to-measure traits. Combining data sets available from different populations for joint or meta-analysis is a promising alternative to increasing sample sizes available for GWAS. Simulation studies indicate statistical advantages from combining raw data or GWAS summaries in enhancing quantitative trait loci (QTL) detection power. However, the complexity of genetics underlying most quantitative traits, which itself is not fully understood, is difficult to fully capture in simulated data sets. In this study, population-specific and combined-population GWAS as well as a meta-analysis of the population-specific GWAS summaries were carried out with the objective of assessing the advantages and challenges of different data-combining strategies in enhancing detection power of GWAS using milk fatty acid (FA) traits as examples. Gas chromatography (GC) quantified milk FA samples and high-density (HD) genotypes were available from 1,566 Dutch, 614 Danish, and 700 Chinese Holstein Friesian cows. Using the joint GWAS, 28 additional genomic regions were detected, with significant associations to at least 1 FA, compared with the population-specific analyses. Some of these additional regions were also detected using the implemented meta-analysis. Furthermore, using the frequently reported variants of the diacylglycerol acyltransferase 1 (DGAT1) and stearoyl-CoA desaturase (SCD1) genes, we show that significant associations were established with more FA traits in the joint GWAS than the remaining scenarios. However, there were few regions detected in the population-specific analyses that were not detected using the joint GWAS or the meta-analyses. Our results show that combining multi-population data set can be a powerful tool to enhance detection power in GWAS for seldom-recorded traits. Detection of a higher number of regions using the meta-analysis, compared with any of the population-specific analyses also emphasizes the utility of these methods in the absence of raw multi-population data sets to undertake joint GWAS.

Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition.

BACKGROUND: The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes. RESULTS: Multi-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes. CONCLUSION: Integration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.

Genome-wide association study for αS1- and αS2-casein phosphorylation in Dutch Holstein Friesian.

Phosphorylation of caseins (CN) is a crucial post-translational modification that allows caseins to form colloid particles known as casein micelles. Both αS1- and αS2-CN show varying degrees of phosphorylation (isoforms) in cow milk and were suggested to be more relevant for stabilizing internal micellar structure than ß- and κ-CN. However, little is known about the genetic background of individual αS2-CN phosphorylation isoforms and the phosphorylation degrees of αS1- and αS2-CN (αS1-CN PD and αS2-CN PD), defined as the proportion of isoforms with higher degrees of phosphorylation in total αS1- and αS2-CN, respectively. We aimed to identify genomic regions associated with these traits using 50K single nucleotide polymorphisms for 1,857 Dutch Holstein Friesian cows. A total of 10 quantitative trait loci (QTL) regions were identified for all studied traits on 10 Bos taurus autosomes (BTA1, 2, 6, 9, 11, 14, 15, 18, 24, and 28). Regions associated with multiple traits were found on BTA1, 6, 11, and 14. We showed 2 QTL regions on BTA1, one affecting αS2-CN production and the other harboring the SLC37A1 gene, which encodes a phosphorus antiporter and affects αS1- and αS2-CN PD. The QTL on BTA6 harbors the casein gene cluster and affects individual αS2-CN phosphorylation isoforms. The QTL on BTA11 harbors the PAEP gene that encodes for ß-lactoglobulin and affects relative concentrations of αS2-CN-10P and αS2-CN-11P as well as αS1-CN PD and αS2-CN PD. The QTL on BTA14 harbors the DGAT1 gene and affects relative concentrations of αS2-CN-10P and αS2-CN-11P as well as αS1-CN PD and αS2-CN PD. Our results suggest that effects of identified genomic regions on phosphorylation of αS1- and αS2-CN are related to changes in milk synthesis and phosphorus secretion in milk. The actual roles of SLC37A1, PAEP, and DGAT1 in αS1- and αS2-CN phosphorylation in Dutch Holstein Friesian require further investigation.

Selective breeding for high natural antibody level increases resistance to avian pathogenic Escherichia coli (APEC) in chickens.

Keyhole limpet hemocyanin (KLH)-binding natural antibody (NAb) titers in chickens are heritable, and higher levels have previously been associated with a higher survival. This suggests that selective breeding for higher NAb levels might increase survival by means of improved general disease resistance. Chickens were divergently selected and bred for total NAb levels binding KLH at 16 weeks of age for six generations, resulting in a High NAb selection line and a Low NAb selection line. To for test differences in disease resistance, chickens were challenged with avian pathogenic Escherichia coli (APEC) in two separate experiments. Chickens at 8 days of age received one of four intratracheal inoculations of 0.2 mL phosphate buffered saline (PBS): 1) mock inoculate, 2) with 0.2 mL PBS containing 108.20 colony-forming units (CFU)/mL APEC, 3) with 0.2 mL PBS containing 106.64 CFU/mL APEC, and 4) with 0.2 mL PBS containing 107.55 CFU/mL APEC. Mortality was recorded during 7 days post inoculation. Overall, 50-60% reduced mortality was observed in the High line compared to the Low line for all APEC doses. In addition, morbidity was determined of the surviving chickens at 15 days of age. The High line had lower morbidity scores compared to the Low line. We conclude that selective breeding for high KLH-binding NAb levels at 16 weeks of age increase APEC resistance in early life. This study and previous studies support the hypothesis that KLH-binding NAb might be used as an indicator trait for to selective breed for general disease resistance in an antigen non-specific fashion.

Antigen-dependent effects of divergent selective breeding based on natural antibodies on specific humoral immune responses in chickens.

NAb are defined as antigen binding antibodies present without a known previous exposure to this antigen. NAb are suggested to enhance specific antibody (SpAb) responses, but consequences of different NAb levels on immunization are largely unknown. Layer chickens were divergently selected and bred for keyhole limpet hemocyanin (KLH)-binding NAb titers, resulting in a High line and a Low line. In this study, we investigated: (1) the relation of NAb levels with SpAb titers; and (2) the effect of immunization on NAb titers. The 50 highest females of the High line and the 50 lowest females of the Low line of generation 2 were intramuscularly immunized at 33 weeks of age with 1 mL phosphate buffered saline (PBS) containing one of four treatments: (1) negative control (no antigen), (2) 500 µg KLH, (3) 100 µg avian tuberculin purified protein derivative of Mycobacterium avium (PPD), or (4) 250 µg human serum albumin (HuSA). IgM and IgG titers of NAb and SpAb in plasma were determined prior to immunization and weekly for 5 weeks post immunization by indirect ELISA. In addition, antibody affinity was investigated. No differences in SpAb and NAb response against KLH and PPD were observed as a consequence of different NAb titers, but increased and prolonged SpAb and NAb titer responses against HuSA were observed for the High line compared to the Low line. Different natural antibody titers did not impair SpAb dynamics and SpAb affinity. NAb titers were not, or for only short-term, affected by immunization. We show here that NAb may enhance SpAb responses, but that this effect is antigen-dependent. We hypothesize that NAb play a role in general disease resistance through enhancement of the humoral adaptive immune response.

Genetic background of methane emission by Dutch Holstein Friesian cows measured with infrared sensors in automatic milking systems.

International environmental agreements have led to the need to reduce methane emission by dairy cows. Reduction could be achieved through selective breeding. The aim of this study was to quantify the genetic variation of methane emission by Dutch Holstein Friesian cows measured using infrared sensors installed in automatic milking systems (AMS). Measurements of CH4 and CO2 on 1,508 Dutch Holstein Friesian cows located on 11 commercial dairy farms were available. Phenotypes per AMS visit were the mean of CH4, mean of CO2, mean of CH4 divided by mean of CO2, and their log10-transformations. The repeatabilities of the log10-transformated methane phenotypes were 0.27 for CH4, 0.31 for CO2, and 0.14 for the ratio. The log10-transformated heritabilities of these phenotypes were 0.11 for CH4, 0.12 for CO2, and 0.03 for the ratio. These results indicate that measurements taken using infrared sensors in AMS are repeatable and heritable and, thus, could be used for selection for lower CH4 emission. Furthermore, it is important to account for farm, AMS, day of measurement, time of day, and lactation stage when estimating genetic parameters for methane phenotypes. Selection based on log10-transformated CH4 instead of the ratio would be expected to give a greater reduction of CH4 emission by dairy cows.

Genetic parameters for αS1-casein and αS2-casein phosphorylation isoforms in Dutch Holstein Friesian.

Relative concentrations of αS1-casein and αS2-casein (αS1-CN and αS2-CN) phosphorylation isoforms vary considerably among milk of individual cows. We estimated heritabilities for αS2-CN phosphorylation isoforms, determined by capillary zone electrophoresis from 1,857 morning milk samples, and genetic correlations among αS2-CN phosphorylation isoforms in Dutch Holstein Friesian. To investigate if phosphorylation of αS1-CN and αS2-CN are due to the same genetic mechanism, we also estimated genetic correlations between αS1-CN and αS2-CN phosphorylation isoforms as well as the genetic correlations between the phosphorylation degrees (PD) of αS1-CN and αS2-CN defined as the proportion of isoforms with higher degrees of phosphorylation in total αS1-CN and αS2-CN, respectively. The intra-herd heritabilities for the relative concentrations of αS2-CN phosphorylation isoforms were high and ranged from 0.54 for αS2-CN-10P to 0.89 for αS2-CN-12P. Furthermore, the high intra-herd heritabilities of αS1-CN PD and αS2-CN PD imply a strong genetic control of the phosphorylation process, which is independent of casein production. The genetic correlations between αS2-CN phosphorylation isoforms are positive and moderate to high (0.33-0.90). Furthermore, the strong positive genetic correlation (0.94) between αS1-CN PD and αS2-CN PD suggests that the phosphorylation processes of αS1-CN and αS2-CN are related. This study shows the possibility of breeding for specific αS1-CN and αS2-CN phosphorylation isoforms, and relations between the phosphorylation degrees of αS1-CN and αS2-CN and technological properties of milk need to be further investigated to identify potential benefits for the dairy industry.

Linseed oil and DGAT1 K232A polymorphism: Effects on methane emission, energy and nitrogen metabolism, lactation performance, ruminal fermentation, and rumen microbial composition of Holstein-Friesian cows.

Complex interactions between rumen microbiota, cow genetics, and diet composition may exist. Therefore, the effect of linseed oil, DGAT1 K232A polymorphism (DGAT1), and the interaction between linseed oil and DGAT1 on CH4 and H2 emission, energy and N metabolism, lactation performance, ruminal fermentation, and rumen bacterial and archaeal composition was investigated. Twenty-four lactating Holstein-Friesian cows (i.e., 12 with DGAT1 KK genotype and 12 with DGAT1 AA genotype) were fed 2 diets in a crossover design: a control diet and a linseed oil diet (LSO) with a difference of 22 g/kg of dry matter (DM) in fat content between the 2 diets. Both diets consisted of 40% corn silage, 30% grass silage, and 30% concentrates (DM basis). Apparent digestibility, lactation performance, N and energy balance, and CH4 emission were measured in climate respiration chambers, and rumen fluid samples were collected using the oral stomach tube technique. No linseed oil by DGAT1 interactions were observed for digestibility, milk production and composition, energy and N balance, CH4 and H2 emissions, and rumen volatile fatty acid concentrations. The DGAT1 KK genotype was associated with a lower proportion of polyunsaturated fatty acids in milk fat, and with a higher milk fat and protein content, and proportion of saturated fatty acids in milk fat compared with the DGAT1 AA genotype, whereas the fat- and protein-corrected milk yield was unaffected by DGAT1. Also, DGAT1 did not affect nutrient digestibility, CH4 or H2 emission, ruminal fermentation or ruminal archaeal and bacterial concentrations. Rumen bacterial and archaeal composition was also unaffected in terms of the whole community, whereas at the genus level the relative abundances of some bacterial genera were found to be affected by DGAT1. The DGAT1 KK genotype was associated with a lower metabolizability (i.e., ratio of metabolizable to gross energy intake), and with a tendency for a lower milk N efficiency compared with the DGAT1 AA genotype. The LSO diet tended to decrease CH4 production (g/d) by 8%, and significantly decreased CH4 yield (g/kg of DM intake) by 6% and CH4 intensity (g/kg of fat- and protein-corrected milk) by 11%, but did not affect H2 emission. The LSO diet also decreased ruminal acetate molar proportion, the acetate to propionate ratio, and the archaea to bacteria ratio, whereas ruminal propionate molar proportion and milk N efficiency increased. Ruminal bacterial and archaeal composition tended to be affected by diet in terms of the whole community, with several bacterial genera found to be significantly affected by diet. These results indicate that DGAT1 does not affect enteric CH4 emission and production pathways, but that it does affect traits other than lactation characteristics, including metabolizability, N efficiency, and the relative abundance of Bifidobacterium. Additionally, linseed oil reduces CH4 emission independent of DGAT1 and affects the rumen microbiota and its fermentative activity.

Fine-mapping of BTA17 using imputed sequences for associations with de novo synthesized fatty acids in bovine milk.

The aim of this study was to fine-map a genomic region associated with milk fatty acids (FA) on Bos taurus autosome (BTA) 17. This genomic region has been discovered with 50,000 (50k) single nucleotide polymorphisms (SNP) imputed to 777,000 (777k) SNP. In this study, high-density genotypes were imputed to whole-genome sequences level to identify candidate gene(s) associated with milk FA composition on BTA17. Phenotypes and genotypes were available for 1,640 cows sampled in winter, and for 1,581 cows sampled in summer. Phenotypes consisted of gas chromatography measurements in winter and in summer milk samples of 6 individual FA and the indicator of de novo synthesis, C6:0-C14:0. Genotypes consisted of imputed 777k SNP, and 89 sequenced ancestors of the population of genotyped cows. In addition, 450 whole-genome sequences from the 1,000 Bull Genome Consortium were available. Using 495 Holstein-Friesian sequences as a reference population, the 777k SNP genotypes of the cows were imputed to sequence level. We then applied single-variant analyses with an animal model, and identified thousands of significant associations with C6:0, C8:0, C10:0, C12:0, C14:0, and C6:0-C14:0. For C8:0 in summer milk samples, the genomic region located between 29 and 34 Mbp on BTA17 revealed a total of 646 significant associations. The most significant associations [-log10(P-value) = 7.82] were 8 SNP in perfect linkage disequilibrium. After fitting one of these 8 SNP as a fixed effect in the model, and re-running the single-variant analyses, no further significant associations were found for any of the 6 FA or C6:0-C14:0. These findings suggest that one polymorphism underlying this QTL on BTA17 influences multiple de novo synthesized milk FA. Thirteen genes in the QTL region were identified and analyzed carefully. Six out of the 8 SNP that showed the strongest associations were located in the La ribonucleoprotein domain family, member 1B (LARP1B) gene, and we suggest LARP1B as a primary candidate gene. Another gene of interest for this QTL region might be PKL4. None of these suggested candidate genes have previously been associated with milk fat synthesis or milk FA composition.

Genetic and nongenetic factors contributing to differences in αS-casein phosphorylation isoforms and other major milk proteins.

Relative concentrations of αS-casein (αS-CN) phosphorylation isoforms vary considerably among milk of individual cows. We aimed to explore to what extent genetic and other factors contribute to the variation in relative concentrations of αS-CN phosphorylation isoforms and the phosphorylation degree of αS-CN defined as the proportion of isoforms with higher degrees of phosphorylation. We also investigated the associations of genetic variants of milk proteins and casein haplotypes with relative concentrations of αS-CN phosphorylation isoforms and with the phosphorylation degree of αS-CN in French Montbéliarde cattle from the cheese production area of Franche-Comté. Detailed milk protein composition was determined by liquid chromatography coupled with electrospray ionization mass spectrometry from 531 test-day morning milk samples. Parity, lactation stage, and genetic variation of cows contributed to the phenotypic variation in relative concentrations of individual αS-CN phosphorylation isoforms and in the phosphorylation degree of αS-CN. As lactation progressed, we observed a significant increase for relative concentrations of αS-CN isoforms with higher degrees of phosphorylation (αS1-CN-9P, αS2-CN-13P, and αS2-CN-14P) as well as for the phosphorylation degree of both αS1-CN and αS2-CN. Furthermore, the ß-CN I variant was associated with a greater proportion of isoforms with lower degrees of phosphorylation (αS1-CN-8P, αS2-CN-10P, and αS2-CN-11P); the ß-CN B variant was associated with a greater proportion of isoforms with higher degrees of phosphorylation (αS1-CN-9P, αS2-CN-12P to αS2-CN-14P). The heritability estimates were low to moderate for relative concentrations of αS2-CN phosphorylation isoforms (0.07 to 0.32), high for relative concentrations of αS1-CN-8P (0.84) and αS1-CN-9P (0.56), and moderate for phosphorylation degrees of αS1-CN (0.37) and αS2-CN (0.23). Future studies investigating relations between the phosphorylation degree of αS-CN and technological properties of milk will be beneficial for the dairy industry.

Using markers with large effect in genetic and genomic predictions.

The first attempts of applying marker-assisted selection (MAS) in animal breeding were not very successful because the identification of markers closely linked to QTL using low-density microsatellite panels was difficult. More recently, the use of high-density SNP panels in genome-wide association studies (GWAS) have increased the power and precision of identifying markers linked to QTL, which offer new possibilities for MAS. However, when GWAS started to be performed, the focus of many breeders had already shifted from the use of MAS to the application of genomic selection (using all available markers without any preselection of markers linked to QTL). In this study, we aimed to evaluate the prediction accuracy of a MAS approach that accounts for GWAS findings in the prediction models by including the most significant SNP from GWAS as a fixed effect in the marker-assisted BLUP (MA-BLUP) and marker-assisted genomic BLUP (MA-GBLUP) prediction models. A second aim was to compare the prediction accuracies from the marker-assisted models with those obtained from a Bayesian variable selection (BVS) model. To compare the prediction accuracies of traditional BLUP, MA-BLUP, genomic BLUP (GBLUP), MA-GBLUP, and BVS, we applied these models to the trait "number of teats" in 4 distinct pig populations, for validation of the results. The most significant SNP in each population was located at approximately 103.50 Mb on chromosome 7. Applying MAS by accounting for the most significant SNP in the prediction models resulted in improved prediction accuracy for number of teats in all evaluated populations compared with BLUP and GBLUP. Using MA-BLUP instead of BLUP, the increase in prediction accuracy ranged from 0.021 to 0.124, whereas using MA-GBLUP instead of GBLUP, the increase in prediction accuracy ranged from 0.003 to 0.043. The BVS model resulted in similar or higher prediction accuracies than MA-GBLUP. For the trait number of teats, BLUP resulted in the lowest prediction accuracies whereas the highest were observed when applying MA-GBLUP or BVS. In the same data set, MA-BLUP can yield similar or superior accuracies compared with GBLUP. The superiority of MA-GBLUP over traditional GBLUP is more pronounced when training populations are smaller and when relationships between training and validation populations are smaller. Marker-assisted GBLUP did not outperform BVS but does have implementation advantages in large-scale evaluations.

The relationships among bovine αS-casein phosphorylation isoforms suggest different phosphorylation pathways.

Casein (CN) phosphorylation is an important posttranslational modification and is one of the key factors responsible for constructing and stabilizing casein micelles. Variation in phosphorylation degree of αS-CN is of great interest because it is suggested to affect milk technological properties. This study aimed to investigate the variation in phosphorylation degree of αS-CN among milk of individual cows and to explore relationships among different phosphorylation isoforms of αS-CN. For this purpose, we analyzed morning milk samples from 529 French Montbéliarde cows using liquid chromatography coupled with electrospray ionization mass spectrometry. We detected 3 new phosphorylation isoforms: αS2-CN-9P, αS2-CN-14P, and αS2-CN-15P in bovine milk, in addition to the known isoforms αS1-CN-8P, αS1-CN-9P, αS2-CN-10P, αS2-CN-11P, αS2-CN-12P, and αS2-CN-13P. The relative concentrations of each αS-CN phosphorylation isoform varied considerably among individual cows. Furthermore, the phenotypic correlations and hierarchical clustering suggest at least 2 regulatory systems for phosphorylation of αS-CN: one responsible for isoforms with lower levels of phosphorylation (αS1-CN-8P, αS2-CN-10P, and αS2-CN-11P), and another responsible for isoforms with higher levels of phosphorylation (αS1-CN-9P, αS2-CN-12P, αS2-CN-13P, and αS2-CN-14P). Identifying all phosphorylation sites of αS2-CN and investigating the genetic background of different αS2-CN phosphorylation isoforms may provide further insight into the phosphorylation mechanism of caseins.

Genome-wide association study for behavior, type traits, and muscular development in Charolais beef cattle.

Behavior, type traits, and muscular development are of interest for beef cattle breeding. Genome-wide association studies (GWAS) enable the identification of candidate genes, which enables gene-based selection and provides insight in the genetic architecture of these traits. The objective of the current study was to perform a GWAS for 3 behavior traits, 12 type traits, and muscular development in Charolais cattle. Behavior traits, including aggressiveness at parturition, aggressiveness during gestation period, and maternal care, were scored by farmers. Type traits, including udder conformation, teat, feet and legs, and locomotion, were scored by trained classifiers. Data used in the GWAS consisted of 3,274 cows with phenotypic records and genotyping information for 44,930 SNP. When SNP had a false discovery rate (FDR) smaller than 0.05, they were referred to as significant. When SNP had a FDR between 0.05 and 0.20, they were referred to as suggestive. Four significant and 12 suggestive regions were detected for aggressiveness during gestation, maternal care, udder balance, teat thinness, teat length, foot angle, foot depth, and locomotion. These 4 significant and 12 suggestive regions were not supported by other significant SNP in close proximity. No SNP with major effects were detected for behavior and type traits, and SNP associations for these traits were spread across the genome, suggesting that behavior and type traits were influenced by many genes, each explaining a small part of genetic variance. The GWAS identified 1 region on chromosome 2 significantly associated with muscular development, which included the myostatin gene (), which is known to affect muscularity. No other regions associated with muscular development were found. Results showed that the myostatin region associated with muscular development had pleiotropic effects on udder volume, teat thinness, rear leg, and leg angle.

Milk fat triacylglycerols and their relations with milk fatty acid composition, DGAT1 K232A polymorphism, and milk production traits.

Milk fat (MF) triacylglycerols (TAG) determine the physical and functional properties of butter and products rich in MF. To predict these properties, it is necessary to understand the variability of fatty acids, TAG, their associations, and their effect on milk productive traits, days in milk (DIM), and genes related to fat synthesis. Therefore, the aim of this research was to study the variability of TAG using MF from individual cows and to investigate the effect of fatty acid composition, DGAT1 K232A polymorphism, DIM, and milk production traits (fat content and morning milk yield) on MF TAG profile in the Dutch Holstein-Friesian dairy cattle population. Large differences in MF TAG profiles were seen among cows. We showed that the variability of TAG is highest for low and high molecular weight TAG [TAG with carbon numbers (Cn) 26-30 and Cn52-54, respectively] and lowest for TAG with Cn38, which was the most abundant TAG. Saturation index (saturated fatty acid/unsaturated fatty acid) and the ratio C16:0/C18:1 cis-9 showed significant effects on TAG Cn34, Cn36, Cn52, and Cn54: TAG Cn34 and Cn36 increased as the saturation index and ratio C16:0/C18:1 cis-9 increased, whereas the opposite was seen for TAG Cn52 and Cn54. Moreover, the DGAT1 K232A polymorphism significantly affected TAG Cn38. We showed that the relative concentration of TAG with Cn38 was higher in cows with DGAT1 KK genotype. Production traits (fat content and morning milk yield) and DIM had no significant effect on TAG profile. This is a relevant observation because considerable increases of milk yield and fat content have been seen in the Netherlands over the last 60 yr. The large differences shown between individual cows in MF TAG profile imply differences in physical properties of MF.

Effects of the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism on fatty acid, protein, and mineral composition of dairy cattle milk.

Several studies have described associations between the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism and routinely collected milk production traits but not much is known about effects of the DGAT1 polymorphism on detailed milk composition. The aim of this study was to estimate effects of the DGAT1 polymorphism on milk fatty acid, protein, and mineral composition. We looked for effects that were significant and consistent in Danish Holstein Friesian (HF), Danish Jersey, and Dutch HF as these are likely to be true effects of the DGAT1 K232A polymorphism rather than being effects of linked loci. For fatty acid composition, significant and consistent effects of the DGAT1 polymorphism were detected on C14:0, C16:0, C15:0, C16:1, C18:1 cis-9, conjugated linoleic acid (CLA) cis-9,trans-11, C18:2 cis-9,cis-12, and C18:3 cis-9,cis-12,cis-15 content (percent by weight, wt/wt %). For C16:0, C16:1, and C18:1 cis-9, the DGAT1 polymorphism explained more than 10% of the phenotypic variation. Significant effects on milk protein composition in Dutch HF could not be confirmed in Danish Jersey or Danish HF. For mineral content, significant and consistent effects of the DGAT1 polymorphism on calcium, phosphorus, and zinc were detected. In the Dutch HF population, the contribution of the DGAT1 K232A polymorphism to phenotypic variance was 12.0% for calcium, 8.3% for phosphorus, and 6.1% for zinc. Different from effects on fatty acid composition, effects of the DGAT1 polymorphism on yields of long-chain fatty acids C18:1 cis-9, CLA cis-9,trans-11, C18:2 cis-9,cis-12, and C18:3 cis-9,cis-12,cis-15 were not significant. This indicates that effects of DGAT1 on these fatty acids are indirect, not direct, effects: DGAT1 affects de novo synthesis of fatty acids and, consequently, the contribution of the long-chain fatty acids to total fat is decreased. In addition, effects of the DGAT1 polymorphism on yields of Ca, P, and Zn were not significant, which indicates that effects on these minerals are the result of indirect rather than direct effects of DGAT1: effects on calcium, phosphorus, and zinc content can be explained by effects of DGAT1 on milk volume. The reported effects of the DGAT1 polymorphism on fatty acid and mineral composition of milk are substantial and therefore relevant for milk quality.

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein.

Genetic parameters were estimated for the major milk proteins using bivariate and multi-trait models based on genomic relationships between animals. The analyses included, apart from total protein percentage, αS1-casein (CN), αS2-CN, ß-CN, κ-CN, α-lactalbumin, and ß-lactoglobulin, as well as the posttranslational sub-forms of glycosylated κ-CN and αS1-CN-8P (phosphorylated). Standard errors of the estimates were used to compare the models. In total, 650 Danish Holstein cows across 4 parities and days in milk ranging from 9 to 481d were selected from 21 herds. The multi-trait model generally resulted in lower standard errors of heritability estimates, suggesting that genetic parameters can be estimated with high accuracy using multi-trait analyses with genomic relationships for scarcely recorded traits. The heritability estimates from the multi-trait model ranged from low (0.05 for ß-CN) to high (0.78 for κ-CN). Genetic correlations between the milk proteins and the total milk protein percentage were generally low, suggesting the possibility to alter protein composition through selective breeding with little effect on total milk protein percentage.