Genetic parameters for milk urea and its relationship with milk yield and compositions in Holstein dairy cows

The aim was to estimate genetic parameters for milk urea (MU) concentration and its relationship with milk yield and compositions in Holstein dairy Cows. Edited data were 90,594 test-day records of milk yield and composition collected during 2015 to 2018 on 13,737 lactations obtained from 7,850 Holstein cows in 50 herds. Random regression test-day model was used to estimate genetic parameters. (Co)variance components were estimated with the Bayesian Gibbs sampling method using a single chain of 400,000 iterates. The first 50,000 iterates of each chain were regarded as a burn-in period. Mean (SD) of MU was 23.03 (5.99) and 22.41 (5.74) mg/dl in primiparous and multiparous cows, respectively. Average heritability estimates for daily MU was 0.33 (SD = 0.02) ranged 0.29 to 0.36 and 0.32 (SD = 0.03) ranged 0.27 to 0.34, respectively, for primiparous and multiparous cows. The mean (SD) genetic correlation between MU and milk yield, fat yield, protein yield, lactose yield, fat percentage, protein percentage, lactose percentage, and somatic cell score was, respectively, -0.02 (0.03), -0.02 (0.01), 0.01 (0.04), 0.01 (0.03), 0.00 (0.07), -0.03 (0.04), 0.00 (0.01), -0.11 (0.06) in primiparous cows. The corresponding values in multiparous cows were -0.01 (0.02), -0.01 (0.03), -0.04 (0.04), -0.04 (0.04), 0.04 (0.04), 0.04 (0.07), -0.03 (0.09), 0.06 (0.11), respectively. The results indicate that selection on MU is possible with no effect on milk yield or compositions, however, relationships between MU and other important traits such as longevity, metabolic diseases, and fertility are needed

Comparison of the transcriptome in circulating leukocytes in early lactation between primiparous and multiparous cows provides evidence for age-related changes.

BACKGROUND: Previous studies have identified many immune pathways which are consistently altered in humans and model organisms as they age. Dairy cows are often culled at quite young ages due to an inability to cope adequately with metabolic and infectious diseases, resulting in reduced milk production and infertility. Improved longevity is therefore a desirable trait which would benefit both farmers and their cows. This study analysed the transcriptome derived from RNA-seq data of leukocytes obtained from Holstein cows in early lactation with respect to lactation number. RESULTS: Samples were divided into three lactation groups for analysis: i) primiparous (PP, n = 53), ii) multiparous in lactations 2–3 (MP 2–3, n = 121), and iii) MP in lactations 4–7 (MP > 3, n = 55). Leukocyte expression was compared between PP vs MP > 3 cows with MP 2–3 as background using DESeq2 followed by weighted gene co-expression network analysis (WGCNA). Seven modules were significantly correlated (r ≥ 0.25) to the trait lactation number. Genes from the modules which were more highly expressed in either the PP or MP > 3 cows were pooled, and the gene lists subjected to David functional annotation cluster analysis. The top three clusters from modules more highly expressed in the PP cows all involved regulation of gene transcription, particularly zinc fingers. Another cluster included genes encoding enzymes in the mitochondrial beta-oxidation pathway. Top clusters up-regulated in MP > 3 cows included the terms Glycolysis/Gluconeogenesis, C-type lectin, and Immunity. Differentially expressed candidate genes for ageing previously identified in the human blood transcriptome up-regulated in PP cows were mainly associated with T-cell function (CCR7, CD27, IL7R, CAMK4, CD28), mitochondrial ribosomal proteins (MRPS27, MRPS9, MRPS31), and DNA replication and repair (WRN). Those up-regulated in MP > 3 cows encoded immune defence proteins (LYZ, CTSZ, SREBF1, GRN, ANXA5, ADARB1). CONCLUSIONS: Genes and pathways associated with lactation number in cows were identified for the first time to date, and we found that many were comparable to those known to be associated with ageing in humans and model organisms. We also detected changes in energy utilization and immune responses in leukocytes from older cows. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07977-5

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi- and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological process terms including alanine transport, L-alanine transport, proline transport, and glycine transport were identified as the most important terms enriched by the genes inside the identified windows

Transcriptomic analysis of circulating leukocytes obtained during the recovery from clinical mastitis caused by Escherichia coli in Holstein dairy cows

SIMPLE SUMMARY: Escherichia coli is a bacterium which infects cow udders causing clinical mastitis, a potentially severe disease with welfare and economic consequences. During an infection, white blood cells (leukocytes) enter the udder to provide immune defence and assist tissue repair. We sequenced RNA derived from circulating leukocytes to investigate which genes are up- or down-regulated in dairy cows with naturally occurring cases of clinical mastitis in comparison with healthy control cows from the same farm. We also looked for genetic variations between infected and healthy cows. Blood samples were taken either EARLY (around 10 days) or LATE (after 4 weeks) during the recovery phase after diagnosis. Many genes (1090) with immune and inflammatory functions were up-regulated during the EARLY phase. By the LATE phase only 29 genes were up-regulated including six haemoglobin subunits, possibly important for the production of new red blood corpuscles. Twelve genetic variations which were associated with an increased or decreased expression of some important immune genes were identified between the infected and control cows. These results show that the initial inflammatory response to E. coli continued for at least 10 days despite the cows having received prompt veterinary treatment, but they had largely recovered within 4 weeks. Genetic differences between cows may predispose some animals to infection. ABSTRACT: The risk and severity of clinical infection with Escherichia coli as a causative pathogen for bovine mastitis is influenced by the hosts’ phenotypic and genotypic variables. We used RNA-Seq analysis of circulating leukocytes to investigate global transcriptomic profiles and genetic variants from Holstein cows with naturally occurring cases of clinical mastitis, diagnosed using clinical symptoms and milk microbiology. Healthy lactation-matched cows served as controls (CONT, n = 6). Blood samples were collected at two time periods during the recovery phase post diagnosis: EARLY (10.3 ± 1.8 days, n = 6) and LATE (46.7 ± 11 days, n = 3). Differentially expressed genes (DEGs) between the groups were identified using CLC Genomics Workbench V21 and subjected to enrichment analysis. Variant calling was performed following GATKv3.8 best practice. The comparison of E. coli(+) EARLY and CONT cows found the up-regulation of 1090 DEGs, mainly with immune and inflammatory functions. The key signalling pathways involved NOD-like and interleukin-1 receptors and chemokines. Many up-regulated DEGs encoded antimicrobial peptides including cathelicidins, beta-defensins, S100 calcium binding proteins, haptoglobin and lactoferrin. Inflammation had largely resolved in the E. coli(+) LATE group, with only 29 up-regulated DEGs. Both EARLY and LATE cows had up-regulated DEGs encoding ATP binding cassette (ABC) transporters and haemoglobin subunits were also up-regulated in LATE cows. Twelve candidate genetic variants were identified in DEGs between the infected and CONT cows. Three were in contiguous genes WIPI1, ARSG and SLC16A6 on BTA19. Two others (RAC2 and ARHGAP26) encode a Rho-family GTPase and Rho GTPase-activating protein 26. These results show that the initial inflammatory response to E. coli continued for at least 10 days despite prompt treatment and provide preliminary evidence for genetic differences between cows that may predispose them to infection

Relationships between metabolic profiles and gene expression in liver and leukocytes of dairy cows in early lactation

Publication history: Accepted - 11 October 2020; Published online - 15 January 2021Homeorhetic mechanisms assist dairy cows in the transition from pregnancy to lactation. Less successful cows develop severe negative energy balance (NEB), placing them at risk of metabolic and infectious diseases and reduced fertility. We have previously placed multiparous Holstein Friesian cows from 4 herds into metabolic clusters, using as biomarkers measurements of plasma nonesterified fatty acids, β-hydroxybutyrate, glucose and IGF-1 collected at 14 and 35 d in milk (DIM). This study characterized the global transcriptomic profiles of liver and circulating leukocytes from the same animals to determine underlying mechanisms associated with their metabolic and immune function. Liver biopsy and whole-blood samples were collected around 14 DIM for RNA sequencing. All cows with available RNA sequencing data were placed into balanced (BAL, n = 44), intermediate (n = 44), or imbalanced (IMBAL, n = 19) metabolic cluster groups. Differential gene expression was compared between the 3 groups using ANOVA, but only the comparison between BAL and IMBAL cows is reported. Pathway analysis was undertaken using DAVID Bioinformatic Resources (https://david.ncifcrf.gov/). Milk yields did not differ between BAL and IMBAL cows but dry matter intake was less in IMBAL cows and they were in greater energy deficit at 14 DIM (−4.48 v −11.70 MJ/d for BAL and IMBAL cows). Significantly differentially expressed pathways in hepatic tissue included AMPK signaling, glucagon signaling, adipocytokine signaling, and insulin resistance. Genes involved in lipid metabolism and cholesterol transport were more highly expressed in IMBAL cows but IGF1 and IGFALS were downregulated. Leukocytes from BAL cows had greater expression of histones and genes involved in nucleosomes and cell division. Leukocyte expression of heat shock proteins increased in IMBAL cows, suggesting an unfolded protein response, and several key genes involved in immune responses to pathogens were upregulated (e.g., DEFB13, HP, OAS1Z, PTX3, and TLR4). Differentially expressed genes upregulated in IMBAL cows in both tissues included CD36, CPT1, KFL11, and PDK4, all central regulators of energy metabolism. The IMBAL cows therefore had greater difficulty maintaining glucose homeostasis and had dysregulated hepatic lipid metabolism. Their energy deficit was associated with a reduced capacity for cell division and greater evidence of stress responses in the leukocyte population, likely contributing to an increased risk of infectious disease.This project received funding from the European Union's Seventh Framework Programme (Brussels, Belgium) for research, technological development, and demonstration under grant agreement no. 61368

Predicting physiological imbalance in Holstein dairy cows by three different sets of milk biomarkers

Blood biomarkers may be used to detect physiological imbalance and potential disease. However, blood sampling is difficult and expensive, and not applicable in commercial settings. Instead, individual milk samples are readily available at low cost, can be sampled easily and analysed instantly. The present observational study sampled blood and milk from 234 Holstein dairy cows from experimental herds in six European countries. The objective was to compare the use of three different sets of milk biomarkers for identification of cows in physiological imbalance and thus at risk of developing metabolic or infectious diseases. Random forests was used to predict body energy balance (EBAL), index for physiological imbalance (PI-index) and three clusters differentiating the metabolic status of cows created on basis of concentrations of plasma glucose, β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and serum IGF-1. These three metabolic clusters were interpreted as cows in balance, physiological imbalance and “intermediate cows” with physiological status in between. The three sets of milk biomarkers used for prediction were: milk Fourier transform mid-IR (FT-MIR) spectra, 19 immunoglobulin G (IgG) N-glycans and 8 milk metabolites and enzymes (MME). Blood biomarkers were sampled twice; around 14 days after calving (days in milk (DIM)) and around 35 DIM. MME and FT-MIR were sampled twice weekly 1−50 DIM whereas IgG N-glycan were measured only four times. Performances of EBAL and PI-index predictions were measured by coefficient of determination (R2cv) and root mean squared error (RMSEcv) from leave-one-cow-out cross-validation (cv). For metabolic clusters, performance was measured by sensitivity, specificity and global accuracy from this cross-validation. Best prediction of PI-index was obtained by MME (R2cv = 0.40 (95 % CI: 0.29−0.50) at 14 DIM and 0.35 (0.23−0.44) at 35 DIM) while FT-MIR showed a better performance than MME for prediction of EBAL (R2cv = 0.28 (0.24−0.33) vs 0.21 (0.18−0.25)). Global accuracies of predicting metabolic clusters from MME and FT-MIR were at the same level ranging from 0.54 (95 % CI: 0.39−0.68) to 0.65 (0.55−0.75) for MME and 0.51 (0.37−0.65) to 0.68 (0.53−0.81) for FT-MIR. R2cv and accuracies were lower for IgG N-glycans. In conclusion, neither EBAL nor PI-index were sufficiently well predicted to be used as a management tool for identification of risk cows. MME and FT-MIR may be used to predict the physiological status of the cows, while the use of IgG N-glycans for prediction still needs development. Nevertheless, accuracies need to be improved and a larger training data set is warranted

Proportion of Concentrate in the Diet of Early Lactation Dairy Cows has Contrasting effects on Circulating Leukocyte Global Transcriptomic Profiles, Health and Fertility according to Parity

Publication history: Accepted - 16 December 2022; Published online - 20 December 2022The functionality of circulating leukocytes in dairy cows is suppressed after calving, with negative energy balance as a risk factor. Leukocyte transcriptomic profiles were compared separately in 44 multiparous (MP) and 18 primiparous (PP) Holstein–Friesian cows receiving diets differing in concentrate proportion to test whether immune dysfunction could be mitigated by appropriate nutrition. After calving, cows were offered either (1) low concentrate (LC); (2) medium concentrate (MC) or (3) high concentrate (HC) diets with proportions of concentrate to grass silage of 30%:70%, 50%:50% and 70%:30%, respectively. Cow phenotype data collected included circulating metabolites, milk yield and health and fertility records. RNA sequencing of circulating leukocytes at 14 days in milk was performed. The HC diet improved energy balance in both age groups. There were more differentially expressed genes in PP than MP cows (460 vs. 173, HC vs. LC comparison) with few overlaps. The MP cows on the LC diet showed upregulation of the complement and coagulation cascade and innate immune defence mechanisms against pathogens and had a trend of more cases of mastitis and poorer fertility. In contrast, the PP cows on the HC diet showed greater immune responses based on both gene expression and phenotypic data and longer interval of calving to conception. The leukocytes of MP and PP cows therefore responded differentially to the diets between age, nutrient supply and immunity affecting their health and subsequent fertility.This project received funding from the European Union’s Seventh Framework Programme (EU FP7, Brussels, Belgium) for research, technological development, and demonstration under grant agreement no. 613689 (GplusE). The views expressed in this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission

Genome-wide association for milk production and lactation curve parameters in Holstein dairy cows

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Genetic parameters for milk urea and its relationship with milk yield and compositions in Holstein dairy cows

peer reviewe

Genome-wide association for metabolic clusters in early-lactation Holstein dairy cows

The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and β-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starting from the first week until 50 DIM were used to determine Fourier-transform mid-infrared (FT-MIR) spectra and subsequently to classify the animals into the same metabolic clusters (BAL vs. OTR). Twenty-eight percent of the animals were categorized in the BAL group, and the remainder were classified in the OTR category. Although daily milk yield was lower in BAL cows, we found no difference in daily fat- and protein-corrected milk yield in cows from the BAL metabolic cluster compared with those in the OTR metabolic cluster. In the next step, a single-step genomic BLUP was used to identify the genomic region(s) associated with the predicted metabolic clusters. The results revealed that prediction of metabolic clusters is a highly polygenic trait regulated by many small-sized effects. The region of 36,258 to 36,295 kb on BTA27 was the highly associated region for the predicted metabolic clusters, with the closest genes to this region (ANK1 and miR-486) being related to hematopoiesis, erythropoiesis, and mammary gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows