Gene association analysis of an osteopontin polymorphism and ketosis resistance in dairy cattle

The aim of this study was to identify the c.495C > T polymorphism within exon 1 of the osteopontin gene (OPN), and to analyze its association with susceptibility to ketosis in Polish Holstein-Friesian (HF) cows. The study utilized blood samples from 977 HF cows, for the determination of β-hydroxybutyric acid (BHB) and for DNA isolation. The c.495C > T polymorphism of the bovine osteopontin gene was determined by PCR-RFLP. The CT genotype (0.50) was deemed the most common, while TT (0.08) was the rarest genotype. Cows with ketosis most often had the CC genotype, while cows with the TT genotype had the lowest incidence of ketosis. To confirm the relationship between the genotype and ketosis in cows, a weight of evidence (WoE) was generated. A very strong effect of the TT genotype on resistance to ketosis was demonstrated. The distribution of the ROC curve shows that the probability of resistance to ketosis is > 75% if cows have the TT genotype of the OPN gene (cutoff value is 0.758). Results suggest that TT genotype at the c.495C > T locus of the OPN gene might be effective way to detect the cows with risk of ketosis.

Association of herd hyperketolactia prevalence with transition management practices and herd productivity on Canadian dairy farms-A retrospective cross-sectional study

The objective of this observational study was to assess the relationship between herd-level prevalence of hyperketolactia (HPH) with management practices of the transition period and herd milk production. Dairy herds (n = 71) were selected based on their inclusion in a herd management risk assessment study (August 2014-March 2018) using a Vital 90 (Elanco) Risk Assessment tool (one assessment per farm). Data from multiple milk recording test-days (Dairy Herd Improvement, DHI; Lactanet) were included in the analysis. Tests performed within ±6 mo relative to each farm's risk assessment date were included (10 ± 2 SD tests per farm). The majority of the farms were located in Ontario (83%). For each farm DHI test, the data set included herd average milk yield (kg/cow per day), average milk fat and protein (%), average somatic cell count (cells/mL), average days in milk (DIM), number of cows tested for ketosis, number of ketosis-positive tests (milk β-hydroxybutyrate ≥0.15 mmol/L), and proportion of cows by parity groups. Overall HPH (5-21 DIM) was calculated based on data available per farm (sum of all positive tests within 5-21 DIM/sum of all cows tested within 5-21 DIM). Each farm average was obtained by considering all test-days. A logit-transformation was applied to hyperketolactia prevalence. Linear regression models (PROC GLM and MIXED of SAS, Version 9.4) were used to predict herd HPH (milk β-hydroxybutyrate ≥0.15 mmol/L within 5 to 21 DIM; the outcome of interest). Four initial models (far-off, close-up, and fresh periods, and DHI) were separately built to assess associations between their variables and HPH; a final model considered variables selected in the initial models. Univariable (liberal P < 0.25) followed by multivariable models were used to build specific models for each period of the risk assessment. Herd prevalence of hyperketolactia was 27 ± 14%, with an average herd size of 141 ± 110 cows. The final HPH model (R² = 24.8%) included weighted milk yield, the proportion of primiparous cows, water access in the close-up period, and access to rest areas or stall access in the fresh period. Herd prevalence of hyperketolactia was negatively associated with milk yield [odds ratio, OR = 0.96 (95% confidence interval 0.92-0.99)] and proportion of primiparous cows [OR = 0.98 (0.96-0.99)]. The odds of hyperketolactia were greater with poor water access and quality (<5 cm of linear access per cow; dirty water; only 1 water location in pen) than with ≥10.2 cm of linear access per cow; clean water; >2 water locations in pen [1.23 (1.11-2.39)] in the close-up period. The odds of hyperketolactia were greater in farms providing limited access to rest areas in the fresh period than in farms providing constant access to rest areas, without dead-ends [1.64 (1.03-2.80)]. In Canadian dairy herds, HPH in early lactation was associated with certain transition-period management practices and was negatively associated with herd productivity.

Direct and indirect contributions of molecular genetics to farm animal welfare: a review

Since domestication, farm animals have played a key role to increase the prosperity of humankind, while animal welfare (AW) is debated even today. This paper aims to comprehensively review the contributions of developing molecular genetics to farm animal welfare (FAW) and to raise awareness among both scientists and farmers about AW. Welfare is a complex trait affected by genetic structure and environmental factors. Therefore, the best welfare status can be achieved not only to enhance environmental factors such as management and feeding practices, but also the genetic structure of animals must be improved. In this regard, advances in molecular genetics have made great contributions to improve the genetic structure of farm animals, which has increased AW. Today, by sequencing and/or molecular markers, genetic diseases may be detected and eliminated in local herds. Additionally, genes related to diseases or adaptations are investigated by molecular techniques, and the frequencies of desired genotypes are increased in farm animals to keep welfare at an optimized level. Furthermore, stress on animals can be reduced with DNA extraction from stool and feather samples which reduces physical contact between animals and veterinarians. Together with molecular genetics, advances in genome editing tools and biotechnology are promising to improve FAW in the future.

Genome-wide association study and functional analyses for clinical and subclinical ketosis in Holstein cattle

Ketosis is one of the most frequent metabolic diseases in high-yielding dairy cows and is characterized by high concentrations of ketone bodies in blood, urine, and milk, causing high economic losses. The search for polymorphic genes, whose alleles have different effects on resistance to developing the disease, is of extreme importance to help select less susceptible animals. The aims of this study were to identify genomic regions associated with clinical and subclinical ketosis (β-hydroxybutyrate concentration) in North American Holstein dairy cattle and to investigate these regions to identify candidate genes and metabolic pathways associated with these traits. To achieve this, a GWAS was performed for 4 traits: clinical ketosis lactation 1, clinical ketosis lactation 2 to 5, subclinical ketosis lactation 1, and subclinical ketosis lactation 2 to 5. The estimated breeding values from 77,277 cows and 7,704 bulls were deregressed and used as pseudophenotypes in the GWAS. The top-20 genomic regions explaining the largest proportion of the genetic variance were investigated for putative genes associated with the traits through functional analyses. Regions of interest were identified on chromosomes 2, 5, and 6 for clinical ketosis lactation 1; 3, 6, and 7 for clinical ketosis lactation 2 to 5; 1, 2, and 12 for subclinical ketosis lactation 1; and 20, 11, and 25 for subclinical ketosis lactation 2 to 5. The highlighted genes potentially related to clinical and subclinical ketosis included ACAT2 and IGF1. Enrichment analysis of the list of candidate genes for clinical and subclinical ketosis showed molecular functions and biological processes involved in fatty acid metabolism, lipid metabolism, and inflammatory response in dairy cattle. Several genomic regions and SNPs related to susceptibility to ketosis in dairy cattle that were previously described in other studies were confirmed. The novel genomic regions identified in this study aid to characterize the most important genes and pathways that explain the susceptibility to clinical and subclinical ketosis in dairy cattle.

Genetic and nongenetic profiling of milk β-hydroxybutyrate and acetone and their associations with ketosis in Holstein cows

Ketosis is a metabolic disorder of increasing importance in high-yielding dairy cows, but accurate population-wide binary health trait recording is difficult to implement. Against this background, proper Gaussian indicator traits, which can be routinely measured in milk, are needed. Consequently, we focused on the ketone bodies acetone and β-hydroxybutyrate (BHB), measured via Fourier-transform infrared spectroscopy (FTIR) in milk. In the present study, 62,568 Holstein cows from large-scale German co-operator herds were phenotyped for clinical ketosis (KET) according to a veterinarian diagnosis key. A sub-sample of 16,861 cows additionally had first test-day observations for FTIR acetone and BHB. Associations between FTIR acetone and BHB with KET and with test-day traits were studied phenotypically and quantitative genetically. Furthermore, we estimated SNP marker effects for acetone and BHB (application of genome-wide association studies) based on 40,828 SNP markers from 4,384 genotyped cows, and studied potential candidate genes influencing body fat mobilization. Generalized linear mixed models were applied to infer the influence of binary KET on Gaussian-distributed acetone and BHB (definition of an identity link function), and vice versa, such as the influence of acetone and BHB on KET (definition of a logit link function). Additionally, linear models were applied to study associations between BHB, acetone and test-day traits (milk yield, fat percentage, protein percentage, fat-to-protein ratio and somatic cell score) from the first test-day after calving. An increasing KET incidence was statistically significant associated with increasing FTIR acetone and BHB milk concentrations. Acetone and BHB concentrations were positively associated with fat percentage, fat-to-protein ratio and somatic cell score. Bivariate linear animal models were applied to estimate genetic (co)variance components for KET, acetone, BHB and test-day traits within parities 1 to 3, and considering all parities simultaneously in repeatability models. Pedigree-based heritabilities were quite small (i.e., in the range from 0.01 in parity 3 to 0.07 in parity 1 for acetone, and from 0.03-0.04 for BHB). Heritabilites from repeatability models were 0.05 for acetone, and 0.03 for BHB. Genetic correlations between acetone and BHB were moderate to large within parities and considering all parities simultaneously (0.69-0.98). Genetic correlations between acetone and BHB with KET from different parities ranged from 0.71 to 0.99. Genetic correlations between acetone across parities, and between BHB across parities, ranged from 0.55 to 0.66. Genetic correlations between KET, acetone, and BHB with fat-to-protein ratio and with fat percentage were large and positive, but negative with milk yield. In genome-wide association studies, we identified SNP on BTA 4, 10, 11, and 29 significantly influencing acetone, and on BTA 1 and 16 significantly influencing BHB. The identified potential candidate genes NRXN3, ACOXL, BCL2L11, HIBADH, KCNJ1, and PRG4 are involved in lipid and glucose metabolism pathways.

Phenotypic relationships, genetic parameters, genome-wide associations, and identification of potential candidate genes for ketosis and fat-to-protein ratio in German Holstein cows

Energy demand for milk production in early lactation exceeds energy intake, especially in high-yielding Holstein cows. Energy deficiency causes increasing susceptibility to metabolic disorders. In addition to several blood parameters, the fat-to-protein ratio (FPR) is suggested as an indicator for ketosis, because a FPR >1.5 refers to high lipolysis. The aim of this study was to analyze phenotypic, quantitative genetic, and genomic associations between FPR and ketosis. In this regard, 8,912 first-lactation Holstein cows were phenotyped for ketosis according to a veterinarian diagnosis key. Ketosis was diagnosed if the cow showed an abnormal carbohydrate metabolism with increased content of ketone bodies in the blood or urine. At least one entry for ketosis in the first 6 wk after calving implied a score = 1 (diseased); otherwise, a score = 0 (healthy) was assigned. The FPR from the first test-day was defined as a Gaussian distributed trait (FPRgauss), and also as a binary response trait (FPRbin), considering a threshold of FPR = 1.5. After imputation and quality controls, 45,613 SNP markers from the 8,912 genotyped cows were used for genomic studies. Phenotypically, an increasing ketosis incidence was associated with significantly higher FPR, and vice versa. Hence, from a practical trait recording perspective, first test-day FPR is suggested as an indicator for ketosis. The ketosis heritability was slightly larger when modeling the pedigree-based relationship matrix (pedigree-based: 0.17; SNP-based: 0.11). For FPRbin, heritabilities were larger when modeling the genomic relationship matrix (pedigree-based: 0.09; SNP-based: 0.15). For FPRgauss, heritabilities were almost identical for both pedigree and genomic relationship matrices (pedigree-based: 0.14; SNP-based: 0.15). Genetic correlations between ketosis with FPRbin and FPRgauss using either pedigree- or genomic-based relationship matrices were in a moderate range from 0.39 to 0.71. Applying genome-wide association studies, we identified the specific SNP rs109896020 (BTA 5, position: 115,456,438 bp) significantly contributing to ketosis. The identified potential candidate gene PARVB in close chromosomal distance is associated with nonalcoholic fatty liver disease in humans. The most important SNP contributing to FPRbin was located within the DGAT1 gene. Different SNP significantly contributed to ketosis and FPRbin, indicating different mechanisms for both traits genomically.