Search

Establishing fresh cow monitoring procedures is considered beneficial for cow health, welfare, and productivity. However, they are time consuming and require the cows to be locked up, which restricts their natural behavior. In this study, different fresh cow monitoring procedures were evaluated. Two experiments were conducted to determine: (1) the duration of various examinations and treatments; (2) the time cows remain locked up in headlocks; and (3) the proportion of examination and treatment times relative to the total headlock time. In advance, standard operating procedures were established. Three veterinarians conducted the examinations and treatments based on changes in milk yield, clinical symptoms, and alarms by an accelerometer system. The headlock time was evaluated for three workflow strategies, which differed in the order of examinations and treatments. To determine the duration, cameras were installed, and the video footage was analyzed. The examinations lasted between 1 and 227 s, and the cows were locked up in headlocks between 0.01 and 1.76 h. The lock-up times differed significantly among the three strategies, as well as the proportion. This study provides information that can be used as a basis for the development of time-efficient strategies, and to minimize the impact on cows’ time budgets.

In the last decade, several countries have included feed efficiency (as residual feed intake; RFI) in their breeding goal. Recent studies showed that RFI is favorably correlated with methane emissions. Thus, selecting for lower emitting animals indirectly through RFI could be a short-term strategy in order to achieve the intended reduction set by the EU Commission (-55% for 2030). The objectives were to 1) estimate genetic parameters for six methane traits, including genetic correlations between methane traits, production, and feed efficiency traits, 2) evaluate the expected correlated response of methane traits when selecting for feed efficiency with or without including methane, 3) quantify the impact of reducing methane emissions in dairy cattle using the Danish Holstein population as an example. A total of 26,664 CH4 breath records from 647 Danish Holstein cows measured over 7 years in a research farm were analyzed. Records on dry matter intake (DMI), body weight (BW), and energy corrected milk (ECM) were also available. Methane traits were methane concentration (MeC, ppm), methane production (MeP; g/d), methane yield (MeY; g CH4/kg DMI), methane intensity (MeI; g CH4/kg ECM), residual methane concentration (RMeC), residual methane production (RMeP, g/d), and two definitions of residual feed intake with or without including body weight change (RFI1, RFI2). The estimated heritability of MeC was 0.20 ± 0.05 and for MeP, it was 0.21 ± 0.05, whereas heritability estimates for MeY and MeI were 0.22 ± 0.05 and 0.18 ± 0.04, and for the RMeC and RMeP, they were 0.23 ± 0.06 and 0.16 ± 0.02, respectively. Genetic correlations between methane traits ranged from moderate to highly correlated (0.48 ± 0.16–0.98 ± 0.01). Genetic correlations between methane traits and feed efficiency were all positive, ranging from 0.05 ± 0.20 (MeI-RFI2) to 0.76 ± 0.09 (MeP-RFI2). Selection index calculations showed that selecting for feed efficiency has a positive impact on reducing methane emissions’ expected response, independently of the trait used (MeP, RMeP, or MeI). Nevertheless, adding a negative economic value for methane would accelerate the response and help to reach the reduction goal in fewer generations. Therefore, including methane in the breeding goal seems to be a faster way to achieve the desired methane emission reductions in dairy cattle.

Animal products may play a role in developing and spreading antimicrobial resistance in several ways. On the one hand, residues of antibiotics not adequately used in animal farming can enter the human body via food. However, resistant bacteria may also be present in animal products, which can transfer the antimicrobial resistance genes (ARG) to the bacteria in the consumer's body by horizontal gene transfer. As previous studies have shown that fermented foods have a meaningful ARG content, it is indicated that such genes may also be present in silage used as mass feed in the cattle sector. In our study, we aspired to answer what ARGs occur in silage and what mobility characteristics they have? For this purpose, we have analyzed bioinformatically 52 freely available deep sequenced silage samples from shotgun metagenome next-generation sequencing. A total of 16 perfect matched ARGs occurred 54 times in the samples. More than half of these ARGs are mobile because they can be linked to integrative mobile genetic elements, prophages or plasmids. Our results point to a neglected but substantial ARG source in the food chain. University of Veterinary Medicine Open access funding provided by University of Veterinary Medicine.

Bovine respiratory syncytial virus (BRSV) is one of the causative viral agents of the bovine respiratory disease complex. This study was conducted to determine the seropositivity and risk factors associated with BRSV infection and to evaluate the phylogenetic relatedness of the BRSVs in the inner Aegean region of Turkey. In this cross-sectional study, serum samples (n = 557) and nasal swabs (n = 21) were collected from cattle herds (n = 43) between February 2018 and March 2019. A commercial indirect-ELISA kit was used for the detection of antibodies in the sera samples. Reverse-transcriptase PCR was used to detect viral RNA in nasal swabs. Nasal samples were also examined for the detection of bovine parainfluenza-3, bovine viral diarrhoea virus, and bovine herpesvirus 1 by molecular detection methods. Genetic characterization of the local BRSV field isolates was conducted by sequencing attachment glycoprotein (G) gene segment. Epidemiological data on potential risk factors were collected from each sampled herd during blood collection. All herds had at least one seropositive animal. After adjustment for assay sensitivity and specificity, the overall true seropositivity was 58.48% (95% CI: 53.32–63.47). BRSV RNA was detected in 2 of the 21 nasal swabs, whereas other infectious agents were not detected in the investigated samples. Phylogenetic analysis showed that the field isolates of BRSV obtained in this study belonged to subgroup III, but they were located on separate branch from previously characterised Turkish subgroup III isolates. BRSV field strains from this study displayed 3 new amino acid substitutions (P89S, D115G, and S165L) in the G protein chains compared to other main reference BRSV isolates, demonstrating that BRSV is still evolving. Generalised estimating equation model showed that there were positive associations between BRSV infection, age (OR = 2.36, p = 0.001), herd size (OR = 10.32, p

The genus Macavirus, subfamily Gammaherpesvirinae, comprises ungulate viruses that infect domestic and wild ruminants and swine. They cause asymptomatic latent infections in reservoir hosts and malignant catarrhal fever in susceptible species. Lung, spleen, bronchial lymph node, and tongue were collected from 448 cattle (348 necropsied, 100 slaughtered) in Switzerland, United Kingdom, Finland, Belgium, and Germany to determine their infection with bovine herpesvirus-6 (BoHV-6) and gammaherpesviruses of other ruminants, i.e., ovine herpesvirus-1 and -2, caprine herpesvirus-2, and bison lymphotropic herpesvirus, using quantitative PCR. Only BoHV-6 was detected, with an overall frequency of 32%, ranging between 22% and 42% in the different countries. Infection was detected across all ages, from one day after birth, and was positively correlated with age. There was no evidence of an association with specific disease processes. In positive animals, BoHV-6 was detected in all organs with high frequency, consistently in the lungs or spleen. Viral loads varied substantially. In BoHV-6-positive gravid cows, organs of fetuses tested negative for infection, indicating that the virus is not vertically transmitted. Our results confirm previous data indicating that BoHV-6 is a commensal of domestic cattle not associated with disease processes and confirm that infections with other macaviruses are rare and sporadic.

Bovine paratuberculosis (PTB) is a chronic inflammatory disease caused by Mycobacterium avium susbp. paratuberculosis (MAP). Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with susceptibility to bovine PTB. The main objective of this study was to identify quantitative trait loci (QTLs) associated with MAP infection in Spanish Holstein cows (N = 983) using combinations of diagnostic tests and imputed whole-genome sequence (WGS) data. The infection status of these animals was defined by three diagnostic methods including ELISA for MAP-antibodies detection, and tissue culture and PCR for MAP detection. The 983 cows included in this study were genotyped with the Bovine MD SNP50 Bead Chip, and the corresponding genotypes were imputed to WGS using the 1,000 Bull genomes reference population. In total, 33.77 million SNP variants per animal were identified across the genome. Linear mixed models were used to calculate the heritability (h2) estimates for each diagnostic test and test combinations. Next, we performed a case-control GWAS using the imputed WGS datasets and the phenotypes and combinations of phenotypes with h2 estimates > 0.080. After performing the GWAS, the test combinations that showed SNPs with a significant association (PFDR ≤ 0.05), were the ELISA-tissue PCR-tissue culture, ELISA-tissue culture, and ELISA-tissue PCR. A total of twelve quantitative trait loci (QTLs) highly associated with MAP infection status were identified on the Bos taurus autosomes (BTA) 4, BTA5, BTA11, BTA12, BTA14, BTA23, BTA24, and BTA28, and some of these QTLs were linked to immune-modulating genes. The identified QTLs on BTA23 spanning from 18.81 to 22.95 Mb of the Bos taurus genome overlapped with several QTLs previously found to be associated with PTB susceptibility, bovine tuberculosis susceptibility, and clinical mastitis. The results from this study provide more clues regarding the molecular mechanisms underlying susceptibility to PTB infection in cattle and might be used to develop national genetic evaluations for PTB in Spain. Financial support for this study was provided by a grant from the Spanish Ministry of Science, Innovation, and Universities (MICINN, project code: RTI2018-094192-R-C21) and by European Regional Development Funds (FEDER) to MAH. MC and GBB have been awarded fellowships from the National Institute for Agricultural Research (INIA) and MICINN, respectively

Sickness behaviour has been suggested as an applicable indicator for monitoring disease. Deviating feeding behaviour and activity can provide information about animals' health and welfare status. Recent advances in sensor technology enable monitoring of such behaviours and could potentially be utilized as an indicator of gastrointestinal nematode (GIN) infections. This study investigated activity and rumination patterns in first-season grazing steers exposed to subclinical infection levels of the GIN Ostertagia ostertagi and Cooperia oncophora. At turnout, animals were allocated to one of four experimental groups and were faced with "high" (H1, n = 15; H2, n = 17) or "low" (L1, n = 17; L2, n = 11) levels of parasite exposure by grazing in similar enclosures contaminated with overwintering third stage (13) GIN larvae. Animals in H1 and H2 (HP) received a 1:1 mix of approximately 10,000 0. ostertagi and C. oncophora L3 at turnout; whereas the animals in Ll and L2 (LP) were treated monthly with ivermectin. Activity and rumination patterns were monitored by fitting animals with leg- (IceQube) and neck-mounted (Heatime) sensors. BW was recorded every fortnight, whereas faecal and blood samples were examined every four weeks for nematode faecal egg count and serum pepsinogen concentrations (SPCs). There was an interaction effect of exposure level and period (P < 0.0001) on average lying daily time across the entire grazing time. A higher mean daily lying time (P = 0.0037) was found in HP compared with LP during the first 40 days on pasture. There was also interaction effects of treatment and day since turnout on rumination time (P < 0.0001) and rumination change (P = 0.0008). Also mean daily steps (P < 0.0001) and mean daily motion index (P < 0.0001) were markedly higher in HP during days 62-69, coinciding with peaking SPC in HP. Strongyle eggs were observed both in HP and LP from 31 days after turnout. Eggs per gram (EPG) differed between parasite exposure levels (P < 0.0001), with mean EPG remaining low in LP throughout the experiment. Similarly, an increase in SPC was observed (P < 0.0001), but only in HP where it peaked at day 56. In contrast, no difference in BW gain (BWG) (P = 0.78) between HP and LP was observed. In conclusion, this study shows that behavioural measurements monitored with sensors were affected even at low infection levels not affecting BWG. These combined results demonstrate the potential of automated behavioural recordings as a tool for detection of subclinical parasitism.

Background: Little is known on significance, diversity and characteristics of gut E. coli in goats despite their importance as food animals globally. We characterized the temporal dynamics in diversity of E. coli in fecal samples from a cohort of goat kids and adult meat goats on pasture over a one-year period. Isolates were characterized based on phylogenetic grouping, virulence genes; shiga toxins 1 and 2 (Stx1&Stx2) (STEC), intimin (eaeA), hemolysin (hly) and select important sero-groups (026, 045, 0103, 0126 and 0146) using molecular methods. Results: A total of 516 E. coli isolates were screened. Prevalence of virulence genes and STEC was 65 and 56% respectively. Prevalence of virulence genes and STEC was significantly higher in goat kids less than six months (76% /66%) than adults (48% /28%). Isolates with virulence profiles of two or more genes were also higher in young goat kids (50%) than adults (20%). Entero-pathogenic E. coli (EPEC-eaeA gene only) were mostly from pre-weaned goat kids while hly gene only isolates were significantly higher in adults. The stx1, stx2 and hly genes peaked around weaning (60, 63 and 52%) respectively. Goats kids were mostly hosts to group D (59%) while adults older than one year had B1 (75%) isolates. Group D isolates were most abundant at weaning (64%) and diarrhea samples (74%). Group B2 isolates overall (6%) were mostly detected around weaning (63%) while A isolates were 4% overall. Twenty-four isolates belonged to sero-groups 026, 0103 and 0146 with 70% of the isolates detected around weaning. Nineteen of these isolates were STEC with most harboring the stx1/stx2/hly/eae (25%) profile. Most belonged to O26 sero-group (75%) and phylogroup D (75%). Conclusion: To our knowledge this is the first study to highlight longitudinal age related differences in E. coli phylogenetic diversity, abundance of virulence genes and select important sero-groups in goats. Differences detected suggest a possible role of age and weaning stress in influencing E. coli diversity in the gut of goats. The findings are relevant to both animal and public health to advise on further studies on caprine E. coli isolates as animal and human pathogens. Published version

peer-reviewed Current bovine pregnancy detection methods are not reliable until at least day 28 post artificial insemination (AI). The bovine estrous cycle is approximately 21 days; consequently, producers miss an opportunity to rebreed at the next estrous event. Therefore, commercial interest exists for the discovery of novel biomarkers of pregnancy which could reliably detect pregnancy status at or before day 21 of pregnancy. The objective of the present study was to use liquid chromatography tandem mass spectrometry (LC-MS/MS) to perform a global, label-free, proteomics study on (i) milk whey and (ii) extracellular vesicle (EV) enriched milk whey samples, from day 21 of pregnancy, compared with day 21 of the estrous cycle, in order to identify potential protein biomarkers of early pregnancy. The estrous cycles of 10 dairy cows were synchronized, they went through one (control) estrous cycle and these cows were artificially inseminated during the following estrus. These cows were confirmed pregnant by ultrasound scanning. Milk whey samples were collected on day 21 of the estrous cycle and on day 21 post AI. Milk whey samples and EV enriched milk whey samples were analyzed by LC-MS/MS and subsequent analyzes of the label-free quantitative data was performed in MaxQuant and Perseus. Four proteins (APOB, SPADH1, PLIN2 and LPO) were differentially expressed between the proteomes of milk whey from day 21 of pregnancy and day 21 of the estrous cycle (P

Obesity is a worldwide epidemic, with major health and economic costs. Here we estimate heritability for body mass index (BMI) in 172,000 sibling pairs and 150,832 unrelated individuals and explore the contribution of genotype-covariate interaction effects at common SNP loci. We find evidence for genotype-age interaction (likelihood ratio test (LRT) = 73.58, degrees of freedom (df) = 1, P = 4.83 × 10-18), which contributed 8.1% (1.4% s.e.) to BMI variation. Across eight self-reported lifestyle factors, including diet and exercise, we find genotype-environment interaction only for smoking behavior (LRT = 19.70, P = 5.03 × 10-5 and LRT = 30.80, P = 1.42 × 10-8), which contributed 4.0% (0.8% s.e.) to BMI variation. Bayesian association analysis suggests that BMI is highly polygenic, with 75% of the SNP heritability attributable to loci that each explain

The aim of this study was to investigate the sources of variation of milk fatty acids (FA) routinely predicted by mid-infrared spectroscopy in Holstein-Friesian (HF), Brown Swiss (BS), Simmental (SI) and Alpine Grey (AG) cattle breeds. A linear mixed model was used to analyse the data which included 153,801 individual milk samples from 14,301 cows. Fixed effects included in the model were breed, month of sampling, year of sampling, stage of lactation, parity and first order interactions between them, and random effects were herd nested within breed, cow nested within breed and the residual error. Milk of AG cows exhibited the lowest content of saturated FA and the greatest content of unsaturated FA, whereas milk of BS had an opposite pattern. Holstein-Friesian and SI were intermediate between AG and BS breeds for all the FA except for total C18:1, which was the greatest in HF. Saturated FA, C14:0 and C16:0 increased from calving until 120 days in milk, whereas unsaturated FA and C18:1 decreased. First parity cows produced milk with lower concentration of de novo FA than multiparous animals. The greatest content of unsaturated FA and C18:1 was observed in summer, whereas saturated FA, C14:0, C16:0 and C18:0 decreased in summer and increased in winter. The differences in milk FA profile among breeds are useful for genetic selection and for feeding strategies.

Ruminants are generally considered to be less susceptible to the effects of mycotoxins than monogastric animals as the rumen microbiota are capable of detoxifying some of these toxins. Despite this potential degradation, mycotoxin-associated subclinical health problems are seen in dairy cows. In this research, the disappearance of several mycotoxins was determined in an in vitro rumen model and the effect of realistic concentrations of those mycotoxins on fermentation was assessed by volatile fatty acid production. In addition, two hypotheses were tested: (1) a lower rumen pH leads to a decreased degradation of mycotoxins and (2) rumen fluid of lactating cows degrade mycotoxins better than rumen fluid of non-lactating cows. Maize silage was spiked with a mixture of deoxynivalenol (DON), nivalenol (NIV), enniatin B (ENN B), mycophenolic acid (MPA), roquefortine C (ROQ-C) and zearalenone (ZEN). Fresh rumen fluid of two lactating cows (L) and two non-lactating cows (N) was added to a buffer of normal pH (6.8) and low pH (5.8), leading to four combinations (L6.8, L5.8, N6.8, N5.8), which were added to the spiked maize substrate. In this study, mycotoxins had no effect on volatile fatty acid production. However, not all mycotoxins fully disappeared during incubation. ENN B and ROQ-C disappeared only partially, whereas MPA showed almost no disappearance. The disappearance of DON, NIV, and ENN B was hampered when pH was low, especially when the inoculum of non-lactating cows was used. For ZEN, a limited transformation of ZEN to &alpha, ZEL and &beta, ZEL was observed, but only at pH 6.8. In conclusion, based on the type of mycotoxin and the ruminal conditions, mycotoxins can stay intact in the rumen.

The killing of cattle for human consumption (slaughtering) can take place in a slaughterhouse or on farm. The processes of slaughtering that were assessed for welfare, from the arrival of cattle until their death (including slaughtering without stunning), were grouped into three main phases: pre-stunning (including arrival, unloading from the truck, lairage, handling and moving of cattle); stunning (including restraint); and bleeding. Stunning methods were grouped into two categories: mechanical and electrical. Twelve welfare consequences that cattle may be exposed to during slaughter were identified: heat stress, cold stress, fatigue, prolonged thirst, prolonged hunger, impeded movement, restriction of movements, resting problems (inability to rest or discomfort during resting), social stress, pain, fear and distress. Welfare consequences and their relevant animal-based measures are described. In total, 40 welfare hazards that could occur during slaughter were identified and characterised, most of them related to stunning and bleeding. Staff were identified as the origin of 39 hazards, which were attributed to the lack of appropriate skill sets needed to perform tasks or to fatigue. Measures to prevent and correct hazards were identified, and structural and managerial measures were identified as those with a crucial role in prevention. Outcome tables linking hazards, welfare consequences, animal-based measures, origin of hazards, and preventive and corrective measures were developed for each process. Mitigation measures to minimise welfare consequences are proposed. (C) 2020 European Food Safety Authority. EFSA Journal published by John Wiley and Sons Ltd on behalf of European Food Safety Authority. Non

The competent authorities of the Member States of the European Union are required to perform animal welfare inspections on livestock farms. The data obtained from these official inspections performed in Finnish cattle and pig farms in 2010&ndash, 2015 were used with the aim of estimating the prevalence of the most common non-compliances and identifying underlying risk factors. The prevalence of non-compliant cattle and pig farms was 24.2% and 27.9%, respectively. In cattle, the most common problem was an inadequate lying area followed by deficient housing conditions for calves, in pigs, it was a lack of enrichment material. The non-compliances concerning cattle were most frequently detected in autumn and in farms with small herd size, with tie-stall housing and outdoor rearing year-round. The pig farms with a farrow-to-finish unit had a higher prevalence of non-compliances than other production types. The prevalence of the non-compliant farms differed notably between the regions. It can be concluded that the cattle welfare inspections should be performed with a focus on the cold and rainy seasons and at small farms, whereas the pig welfare inspections should mainly focus on farrow-to-finish units. The data received from official inspections should be efficiently utilized in the development of animal welfare inspection system, with the aim of risk-based, consistent and uniform inspections. In addition, the data should be utilized in targeting information for farmers.

Published version

17 páginas, 5 tablas, 5 figuras., Paratuberculosis is chronic granulomatous enteritis of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP). Whole RNA-sequencing (RNA-Seq) is a promising source of novel biomarkers for early MAP infection and disease progression in cattle. Since the blood transcriptome is widely used as a source of biomarkers, we analyzed whether it recapitulates, at least in part, the transcriptome of the ileocecal valve (ICV), the primary site of MAP colonization. Total RNA was prepared from peripheral blood (PB) and ICV samples, and RNA-Seq was used to compare gene expression between animals with focal or diffuse histopathological lesions in gut tissues versus control animals with no detectable signs of infection. Our results demonstrated both shared, and PB and ICV-specific gene expression in response to a natural MAP infection. As expected, the number of differentially expressed (DE) genes was larger in the ICV than in the PB samples. Among the DE genes in the PB and ICV samples, there were some common genes irrespective of the type of lesion including the C-X-C motif chemokine ligand 8 (CXCL8/IL8), apolipoprotein L (APOLD1), and the interferon inducible protein 27 (IF127). The biological processes (BP) enriched in the PB gene expression profiles from the cows with diffuse lesions included the killing of cells of other organism, defense response, immune response and the regulation of neutrophil chemotaxis. Two of these BP, the defense and immune response, were also enriched in the ICV from the cows with diffuse lesions. Metabolic analysis of the DE genes revealed that the N-glycan biosynthesis, bile secretion, one-carbon pool by folate and purine metabolism were significantly enriched in the ICV from the cows with focal lesions. In the ICV from cows with diffuse lesions; the valine, leucine and isoleucine degradation route, purine metabolism, vitamin digestion and absorption and the cholesterol routes were enriched. Some of the identified DE genes, BP and metabolic pathways will be studied further to develop novel diagnostic tools, vaccines and immunotherapeutics., This work was supported by grants from the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (INIA) and by European Funds for Regional Development (FEDER) (INIA RTA2014-00009-C02 and RTA2018-094192). The study is partially funded by the Principado de Asturias (PCTI 2018-2020, GRUPIN: IDI2018-000237). Maria Canive and Cristina Blanco-Vazquez are recipients of INIA fellowships. The authors thank ASTEGA Veterinary services for their assistance on sample collection. We are also grateful to Kyle Hearn for the careful editing of the manuscript.

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.

Document Type:Correction : GENETICS SELECTION EVOLUTION Volume: 51/Issue: 1 /Article Number: 69/DOI: 10.1186/s12711-019-0511-5/Published: NOV 22 2019 WOS:000504108800001 / PubMed ID: 31757207; International audience; AbstractBackgroundCross-validation tools are used increasingly to validate and compare genetic evaluation methods but analytical properties of cross-validation methods are rarely described. There is also a lack of cross-validation tools for complex problems such as prediction of indirect effects (e.g. maternal effects) or for breeding schemes with small progeny group sizes.ResultsWe derive the expected value of several quadratic forms by comparing genetic evaluations including “partial” and “whole” data. We propose statistics that compare genetic evaluations including “partial” and “whole” data based on differences in means, covariance, and correlation, and term the use of these statistics “method LR” (from linear regression). Contrary to common belief, the regression of true on estimated breeding values is (on expectation) lower than 1 for small or related validation sets, due to family structures. For validation sets that are sufficiently large, we show that these statistics yield estimators of bias, slope or dispersion, and population accuracy for estimated breeding values. Similar results hold for prediction of future phenotypes although we show that estimates of bias, slope or dispersion using prediction of future phenotypes are sensitive to incorrect heritabilities or precorrection for fixed effects. We present an example for a set of 2111 Brahman beef cattle for which, in repeated partitioning of the data into training and validation sets, there is very good agreement of statistics of method LR with prediction of future phenotypes.ConclusionsAnalytical properties of cross-validation measures are presented. We present a new method named LR for cross-validation that is automatic, easy to use, and which yields the quantities of interest. The method compares predictions based on partial and whole data, which results in estimates of accuracy and biases. Prediction of observed records may yield biased results due to precorrection or use of incorrect heritabilities.

Unbalanced metabolic status in the weeks after calving predisposes dairy cows to metabolic and infectious diseases. Blood glucose, IGF-I, non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) are used as indicators of the metabolic status of cows. This work aims to (1) evaluate the potential of milk mid-IR spectra to predict these blood components individually and (2) to evaluate the possibility of predicting the metabolic status of cows based on the clustering of these blood components. Blood samples were collected from 241 Holstein cows on six experimental farms, at days 14 and 35 after calving. Blood samples were analyzed by reference analysis and metabolic status was defined by k-means clustering (k=3) based on the four blood components. Milk mid-IR analyses were undertaken on different instruments and the spectra were harmonized into a common standardized format. Quantitative models predicting blood components were developed using partial least squares regression and discriminant models aiming to differentiate the metabolic status were developed with partial least squares discriminant analysis. Cross-validations were performed for both quantitative and discriminant models using four subsets randomly constituted. Blood glucose, IGF-I, NEFA and BHB were predicted with respective R2 of calibration of 0.55, 0.69, 0.49 and 0.77, and R2 of cross-validation of 0.44, 0.61, 0.39 and 0.70. Although these models were not able to provide precise quantitative values, they allow for screening of individual milk samples for high or low values. The clustering methodology led to the sharing out of the data set into three groups of cows representing healthy, moderately impacted and imbalanced metabolic status. The discriminant models allow to fairly classify the three groups, with a global percentage of correct classification up to 74%. When discriminating the cows with imbalanced metabolic status from cows with healthy and moderately impacted metabolic status, the models were able to distinguish imbalanced group with a global percentage of correct classification up to 92%. The performances were satisfactory considering the variables are not present in milk, and consequently predicted indirectly. This work showed the potential of milk mid-IR analysis to provide new metabolic status indicators based on individual blood components or a combination of these variables into a global status. Models have been developed within a standardized spectral format, and although robustness should preferably be improved with additional data integrating different geographic regions, diets and breeds, they constitute rapid, cost-effective and large-scale tools for management and breeding of dairy cows.

Background: Equine gastric ulcer syndrome is an important cause of morbidity in weanling foals. Many foals are asymptomatic, and the development of an inexpensive screening test to ensure an early diagnosis is desirable. The objective of this study was to determine the diagnostic accuracy of blood sucrose for diagnosis of EGUS in weanling foals. Results: 45 foals were studied 7 days before and 14 days after weaning. The diagnostic accuracy of blood sucrose for diagnosis of gastric lesions (GL); glandular lesions (GDL); squamous lesions (SQL) and clinically significant gastric lesions (CSL) at 45 and 90 min after administration of 1 g/kg of sucrose via nasogastric intubation was assessed using ROC curves and calculating the AUC. For each lesion type, sucrose concentration in blood was compared to gastroscopy; and sensitivities (Se) and specificities (Sp) were calculated across a range of sucrose concentrations. Cut- off values were selected manually to optimize Se. Because of concerns over the validity of the gold standard, additional Se, Sp, and lesion prevalence data were subsequently estimated and compared using Bayesian latent class analysis. Using the frequentist approach, the prevalence of GL; GDL; SQL and CSL before weaning was 21; 9; 7 and 8% respectively; and increased to 98; 59; 97 and 82% respectively after weaning. At the selected cut- off, Se ranged from 84 to 95% and Sp ranged from 47 to 71%, depending upon the lesion type and time of sampling. In comparison, estimates of Se and Sp were consistently higher when using a Bayesian approach, with Se ranging from 81 to 97%; and Sp ranging from 77 to 97%, depending upon the lesion type and time of sampling. Conclusions: Blood sucrose is a sensitive test for detecting EGUS in weanling foals. Due to its poor specificity, it is not expected that the sucrose blood test will replace gastroscopy, however it may represent a clinically useful screening test to identify foals that may benefit from gastroscopy. Bayesian latent class analysis represents an alternative method to evaluate the diagnostic accuracy of the blood sucrose test in an attempt to avoid bias associated with the assumption that gastroscopy is a perfect test.

De intensivering van de moderne landbouw wordt geassocieerd met een toename van Clostridium perfringens-gerelateerde, gastro-intestinale problemen bij intensief gevoede runderen, zoals “hemorrhagic bowel disease” bij hoogproductief melkvee en enterotoxemie bij kalveren. Waar de pathogenese van hemorrhagic bowel disease nog grotendeels ongekend is, werden er de laatste jaren nieuwe inzichten in de pathogenese van enterotoxemie bekomen die een belangrijke repercussie op de aanpak van deze ziekte onder praktijkomstandigheden hebben. Ook andere clostridiumgeassocieerde maagdarminfecties, zoals “overeating disease” en neonatale clostridiose, worden regelmatig gediagnosticeerd. Overvoedering met structuurarme, eiwitrijke voeders is een overkoepelende risicofactor bij zowel HBD, enterotoxemie als overeating disease. Een goed uitgebalanceerd dieet dat zo stabiel mogelijk gehouden wordt, is dan ook het belangrijkste aandachtspunt op bedrijven die problemen hebben met clostridiose. Daarnaast dient bij jonge kalveren voldoende aandacht gegeven te worden aan een correcte en hygiënische biestverstrekking om problemen met neonatale clostridiose te vermijden.

Hungate1000 project collaborators: Nikola Palevich, Peter H. Janssen, Ron S. Ronimus, Samantha Noel, Priya Soni, Kerri Reilly, Todd Atherly, Cherie Ziemer, Andre-Denis Wright, Suzanne Ishaq, Michael Cotta, Stephanie Thompson, Katie Crosley, Nest McKain, R. John Wallace, Harry J. Flint, Jennifer C. Martin, Robert J. Forster, Robert J. Gruninger, Tim McAllister, Rosalind Gilbert, Diane Ouwerkerk, Athol Klieve, Rafat Al Jassim, Stuart Denman, Chris McSweeney, Carly Rosewarne, Satoshi Koike, Yasuo Kobayashi, Makoto Mitsumori, Takumi Shinkai, Silvio Cravero & María Cerón Cucchi; International audience; Productivity of ruminant livestock depends on the rumen microbiota, which ferment indigestible plant polysaccharides into nutrients used for growth. Understanding the functions carried out by the rumen microbiota is important for reducing greenhouse gas production by ruminants and for developing biofuels from lignocellulose. We present 410 cultured bacteria and archaea, together with their reference genomes, representing every cultivated rumen-associated archaeal and bacterial family. We evaluate polysaccharide degradation, short-chain fatty acid production and methanogenesis pathways, and assign specific taxa to functions. A total of 336 organisms were present in available rumen metagenomic data sets, and 134 were present in human gut microbiome data sets. Comparison with the human microbiome revealed rumen-specific enrichment for genes encoding de novo synthesis of vitamin B12, ongoing evolution by gene loss and potential vertical inheritance of the rumen microbiome based on underrepresentation of markers of environmental stress. We estimate that our Hungate genome resource represents ∼75% of the genus-level bacterial and archaeal taxa present in the rumen.

The current study evaluated the effects of protein provision to calves fed a combination of solid feed (SF) and milk replacer (MR) at equal total N intake on urea recycling and N retention. Nitrogen balance traits and [ 15 N 2 ]urea kinetics were measured in 30 calves (23 wk of age, 180±3.7kg of body weight), after being exposed to the following experimental treatments for 11 wk: a low level of SF with a low N content (SF providing 12% of total N intake), a high level of SF with a low N content (SF providing 22% of total N intake), or a high level of SF with a high N content (SF providing 36% of total N intake). The SF mixture consisted of 50% concentrates, 25% corn silage, and 25% straw on a dry matter basis. Total N intake was equalized to 1.8g of N·kg of BW −0.75 ·d −1 by adjusting N intake via MR. All calves were housed individually on metabolic cages to allow for quantification of a N balance of calves for 5 d, and for the assessment of urea recycling from [ 15 N 2 ]urea kinetics. Increasing low-N SF intake at equal total N intake resulted in a shift from urinary to fecal N excretion but did not affect protein retention (0.71g of N·kg of BW −0.75 ·d −1 ). Increasing low-N SF intake increased urea recycling but urea reused for anabolism remained unaffected. Total-tract neutral detergent fiber digestibility decreased (−9%) with increasing low-N SF intake, indicating reduced rumen fermentation. Increasing the N content of SF at equal total N intake resulted in decreased urea production, excretion, and return to ornithine cycle, and increased protein retention by 17%. This increase was likely related to an effect of energy availability on protein retention due to an increase in total-tract neutral detergent fiber digestion (>10%) and due to an increased energy supply via the MR. In conclusion, increasing low-N SF intake at the expense of N intake from MR, did not affect protein retention efficiency in calves. Increasing the N content of SF at equal total N intake decreased urea production, increased protein retention, and coincided with improved fiber degradation. Therefore, results suggest that low N availability in the rumen limits microbial growth and rumen fermentation in calves fed low-N SF (93g of CP/kg of DM), and this effect cannot be compensated for by recycling of urea originating from MR.

Our long-term objective is to develop breeding strategies for improving feed efficiency in dairy cattle. In this study, phenotypic data were pooled across multiple research stations to facilitate investigation of the genetic and nongenetic components of feed efficiency in Holstein cattle. Specifically, the heritability of residual feed intake (RFI) was estimated and heterogeneous relationships between RFI and traits relating to energy utilization were characterized across research stations. Milk, fat, protein, and lactose production converted to megacalories (milk energy; MilkE), dry matter intakes (DMI), and body weights (BW) were collected on 6,824 lactations from 4,893 Holstein cows from research stations in Scotland, the Netherlands, and the United States. Weekly DMI, recorded between 50 to 200 d in milk, was fitted as a linear function of MilkE, BW0.75, and change in BW (¿BW), along with parity, a fifth-order polynomial on days in milk (DIM), and the interaction between this polynomial and parity in a first-stage model. The residuals from this analysis were considered to be a phenotypic measure of RFI. Estimated partial regression coefficients of DMI on MilkE and on BW0.75 ranged from 0.29 to 0.47 kg/Mcal for MilkE across research stations, whereas estimated partial regression coefficients on BW0.75 ranged from 0.06 to 0.16 kg/kg0.75. Estimated partial regression coefficients on ¿BW ranged from 0.06 to 0.39 across stations. Heritabilities for country-specific RFI were based on fitting second-stage random regression models and ranged from 0.06 to 0.24 depending on DIM. The overall heritability estimate across all research stations and all DIM was 0.15±0.02, whereas an alternative analysis based on combining the first- and second-stage model as 1 model led to an overall heritability estimate of 0.18±0.02. Hence future genomic selection programs on feed efficiency appear to be promising; nevertheless, care should be taken to allow for potentially heterogeneous variance components and partial relationships between DMI and other energy sink traits across environments when determining RFI.

Single nucleotide polymorphism (SNP) data enable the estimation of inbreeding at the genome level. In this study, we estimated inbreeding levels for 19,075 Finnish Ayrshire cows genotyped with a low-density SNP panel (8K). The genotypes were imputed to 50K density, and after quality control, 39,144 SNPs remained for the analysis. Inbreeding coefficients were estimated for each animal based on the percentage of homozygous SNPs (F-PH), runs of homozygosity (F-ROH) and pedigree (F-PED). Phenotypic records were available for 13,712 animals including non-return rate (NRR), number of inseminations (AIS) and interval from first to last insemination (IFL) for heifers and up to three parities for cows, as well as interval from calving to first insemination (ICF) for cows. Average F-PED was 0.02, F-ROH 0.06 and F-PH 0.63. A correlation of 0.71 was found between F-PED and F-ROH, 0.66 between F-PED and F-PH and 0.94 between F-ROH and F-PH. Pedigree-based inbreeding coefficients did not show inbreeding depression in any of the traits. However, when F-ROH or F-PH was used as a covariate, significant inbreeding depression was observed; a 10% increase in F-ROH was associated with 5days longer IFL0 and IFL1, 2weeks longer IFL3 and 3days longer ICF2 compared to non-inbred cows.

The objective of this study was to determine the association of single nucleotide polymorphisms ( SNPs) with carcass characteristics and meat quality traits in selected candidate genes in Holstein bulls. Five SNPs in four genes, i.e. calpain 1 (CAPN1), calpastatin (CAST), leptin (LEP) and growth hormone receptor (GHR), were genotyped in 400 purebred bulls using PCR-RFLP. Statistically significant associations were as follows: CAPN1 G316A with live weight, carcass weight, back fat thickness, m. longissimus thoracis et lumborum area and carcass measurements; CAPN1 V530I with pH and L *; CAST S20T with live weight, inner chest depth and b * value; and GHR with ph, a * and h *. In addition, significant genotypic interactions were observed for dressing percentage (LEP A80V x CAST S20T), pH (CAPN1 V530I x GHR S555G and LEP A80V x GHR S555G) and rump width (CAPN1 V530I * CAST S20T). There was no association between the LEP A80V marker and any of the traits evaluated, nor was there any association of the tested SNPs with chest width, C* and marbling score. The present results could therefore be indicative for future studies on meat yield and quality.

Improving feed efficiency in dairy cattle could result in more profitable and environmentally sustainable dairy production through lowering feed costs and emissions from dairy farming. In addition, beef production based on dairy herds generates fewer greenhouse gas emissions per unit of meat output than beef production from suckler cow systems. Different scenarios were used to assess the profitability of adding traits, excluded from the current selection index for Finnish Ayrshire, to the breeding goal for combined dairy and beef production systems. The additional breeding goal traits were growth traits (average daily gain of animals in the fattening and rearing periods), carcass traits (fat covering, fleshiness and dressing percentage), mature live weight (LW) of cows and residual feed intake (RFI) traits. A breeding scheme was modeled for Finnish Ayrshire under the current market situation in Finland using the deterministic simulation software ZPLAN+. With the economic values derived for the current production system, the inclusion of growth and carcass traits, while preventing LW increase generated the highest improvement in the discounted profit of the breeding program (3.7%), followed by the scenario where all additional traits were included simultaneously (5.1%). The use of a selection index that included growth and carcass traits excluding LW, increased the profit (0.8%), but reduced the benefits resulted from breeding for beef traits together with LW. A moderate decrease in the profit of the breeding program was obtained when adding only LW to the breeding goal (-3.1%), whereas, adding only RFI traits to the breeding goal resulted in a minor increase in the profit (1.4%). Including beef traits with LW in the breeding goal showed to be the most potential option to improve the profitability of the combined dairy and beef production systems and would also enable a higher rate of self-sufficiency in beef. When considering feed efficiency related traits, the inclusion of LW traits in the breeding goal that includes growth and carcass traits could be more profitable than the inclusion of RFI, because the marginal costs of measuring LW can be expected to be lower than for RFI and it is readily available for selection. In addition, before RFI can be implemented as a breeding objective, the genetic correlations between RFI and other breeding goal traits estimated for the studied population as well as information on the most suitable indicator traits for RFI are needed to assess more carefully the consequences of selecting for RFI.

Breeding values for dry matter intake (DMI) are important to optimize dairy cattle breeding goals for feed efficiency. However, generally, only small data sets are available for feed intake, due to the cost and difficulty of measuring DMI, which makes understanding the genetic associations between traits across lactation difficult, let alone the possibility for selection of breeding animals. However, estimating national breeding values through cheaper and more easily measured correlated traits, such as milk yield and liveweight (LW), could be a first step to predict DMI. Combining DMI data across historical nutritional experiments might help to expand the data sets. Therefore, the objective was to estimate genetic parameters for DMI, fat- and protein-corrected milk (FPCM) yield, and LW across the entire first lactation using a relatively large data set combining experimental data across the Netherlands. A total of 30,483 weekly records for DMI, 49,977 for FPCM yield, and 31,956 for LW were available from 2,283 Dutch Holstein-Friesian first-parity cows between 1990 and 2011. Heritabilities, covariance components, and genetic correlations were estimated using a multivariate random regression model. The model included an effect for year-season of calving, and polynomials for age of cow at calving and days in milk (DIM). The random effects were experimental treatment, year-month of measurement, and the additive genetic, permanent environmental, and residual term. Additive genetic and permanent environmental effects were modeled using a third-order orthogonal polynomial. Estimated heritabilities ranged from 0.21 to 0.40 for DMI, from 0.20 to 0.43 for FPCM yield, and from 0.25 to 0.48 for LW across DIM. Genetic correlations between DMI at different DIM were relatively low during early and late lactation, compared with mid lactation. The genetic correlations between DMI and FPCM yield varied across DIM. This correlation was negative (up to -0.5) between FPCM yield in early lactation and DMI across the entire lactation, but highly positive (above 0.8) when both traits were in mid lactation. The correlation between DMI and LW was 0.6 during early lactation, but decreased to 0.4 during mid lactation. The highest correlations between FPCM yield and LW (0.3-0.5) were estimated during mid lactation. However, the genetic correlations between DMI and either FPCM yield or LW were not symmetric across DIM, and differed depending on which trait was measured first. The results of our study are useful to understand the genetic relationship of DMI, FPCM yield, and LW on specific days across lactation.

Crossing of lines or strains within and between breeds has been demonstrated to be beneficial for dairy cattle performance. However, even within breed, differences between strains may also give rise to heterosis. A key question is whether an interaction exists between heterosis and environment (H x E) that is independent of genotype by environment (G x E) interactions. In this study, H x E and G x E interactions were estimated in a population of approximately 300,000 Danish Jersey cows. The cows were a mixture of pure Danish Jerseys and crosses of US and Danish Jerseys. The phenotype studied was protein yield. A reaction norm model where the unknown environmental covariates are inferred simultaneously with the other parameters in the model was used to analyze the data. When H x E, but not G x E, was included in the model, heterosis was estimated to be 3.8% for the intermediate environmental level. However, when both H x E and G x E were included in the model, heterosis was estimated to be 4.1% for the intermediate environmental level. Furthermore, when only H x E was included in the model, the regression on the unknown environmental covariate was estimated to be 0.15, interpreted as meaning that an increase of average herd-year protein yield by 1 kg of protein led to an increase in heterosis of 0.15 kg above the average heterosis for a first-cross cow. When both H x E and G x E were included in the model, the regression on the unknown environmental covariate was not significantly different from zero, meaning that heterosis was similar in all environments investigated. The genetic correlation of protein yields for different environmental levels ranged from 0.72 to 0.93, which was significantly different from unity, indicating that G x E exist for protein yield.

The ability to monitor dairy cow feeding behavior and activity could improve dairy herd management. A 3-dimensional accelerometer (SensOor; Agis Automatisering BV, Harmelen, the Netherlands) has been developed that can be attached to ear identification tags. Based on the principle that behavior can be identified by ear movements, a proprietary model classifies sensor data as “ruminating,” “eating,” “resting,” or “active.” The objective of the study was to evaluate this sensor on accuracy and precision. First, a pilot evaluation of agreement between 2 independent observers, recording behavior from 3 cows for a period of approximately 9 h each, was performed. Second, to evaluate the sensor, the behavior of 15 cows was monitored both visually (VIS) and with the sensor (SENS), with approximately 20 h of registration per cow, evenly distributed over a 24-h period, excluding milking. Cows were chosen from groups of animals in different lactation stages and parities. Each minute of SENS and VIS data was classified into 1 of 9 categories (8 behaviors and 1 transition behavior) and summarized into 4 behavioral groups, namely ruminating, eating, resting, or active, which were analyzed by calculating kappa (¿) values. For the pilot evaluation, a high level of agreement between observers was obtained, with ¿ values of =0.96 for all behavioral categories, indicating that visual observation provides a good standard. For the second trial, relationships between SENS and VIS were studied by ¿ values on a minute basis and Pearson correlation and concordance correlation coefficient analysis on behavior expressed as percentage of total registration time. Times spent ruminating, eating, resting, and active were 42.6, 15.9, 31.6, and 9.9% (SENS) respectively, and 42.1, 13.0, 30.0, and 14.9% (VIS), respectively. Overall ¿ for the comparison of SENS and VIS was substantial (0.78), with ¿ values of 0.85, 0.77, 0.86, and 0.47 for “ruminating,” “eating,” “resting,” and “active,” respectively. Pearson correlation and concordance correlation coefficients between SENS and VIS for “ruminating,” “eating,” “resting,” and “active” were 0.93, 0.88, 0.98, and 0.73, and 0.93, 0.75, 0.97, and 0.35, respectively. In conclusion, the results provide strong evidence that the present ear sensor technology can be used to monitor ruminating and resting behavior of freestall-housed dairy cattle. Our results also suggest that this technology shows promise for monitoring eating behavior, whereas more work is needed to determine its suitability to monitor activity of dairy cattle.

A major quantitative trait locus (QTL) for milk fat content and fatty acids in both milk and adipose tissue has been detected on Bos taurus autosome 19 (BTA19) in several cattle breeds. The objective of this study was to refine the location of the QTL on BTA19 for bovine milk fat composition using a denser set of markers. Opportunities for fine mapping were provided by imputation from 50,000 genotyped single nucleotide polymorphisms (SNP) toward a high-density SNP panel with up to 777,000 SNP. The QTL region was narrowed down to a linkage disequilibrium block formed by 22 SNP covering 85,007 bp, from 51,303,322 to 51,388,329 bp on BTA19. This linkage disequilibrium block contained 2 genes: coiled-coil domain containing 57 (CCDC57) and fatty acid synthase (FASN). The gene CCDC57 is minimally characterized and has not been associated with bovine milk fat previously, but is expressed in the mammary gland. The gene FASN has been associated with bovine milk fat and fat in adipose tissue before. This gene is a likely candidate for the QTL on BTA19 because of its involvement in de novo fat synthesis. Future studies using sequence data of both CCDC57 and FASN, and eventually functional studies, will have to be pursued to assign the causal variant(s).

In the era of genome-wide selection (GWS), genotype-by-environment (G×E) interactions can be studied using genomic information, thus enabling the estimation of SNP marker effects and the prediction of genomic estimated breeding values (GEBVs) for young candidates for selection in different environments. Although G×E studies in pigs are scarce, the use of artificial insemination has enabled the distribution of genetic material from sires across multiple environments. Given the relevance of reproductive traits such as the total number born (TNB) and the variation in environmental conditions encountered by commercial dams, understanding G×E interactions can be essential to choose the best sires for different environments. The present work proposes a two-step reaction norm approach for G×E analysis using genomic information. The first step provided estimates of environmental effects (herd-year-season - HYS), and the second step provided estimates of the intercept and slope for the TNB across different HYS levels, obtained from the first step, using a random regression model. In both steps, pedigree (A) and genomic (G) relationship matrices were considered. The genetic parameters (variance components, h2 and genetic correlations) were very similar when estimated using the A and G relationship matrices. The reaction norm graphs showed considerable differences in environmental sensitivity between sires, indicating a reranking of sires in terms of genetic merit across the HYS levels. Based on the G matrix analysis, SNP by environment interactions were observed. For some SNPs, the effects increased at increasing HYS levels, while for others, the effects decreased at increasing HYS levels or showed no changes between HYS levels. Cross-validation analysis demonstrated better performance of the genomic approach with respect to traditional pedigrees for both the G×E and standard models. The genomic reaction norm model resulted in an accuracy of GEBVs for “juvenile” boars varying from 0.14 to 0.44 across different HYS levels, while the accuracy of the standard genomic prediction model, without reaction norms, varied from 0.09 to 0.28. These results show that it is important and feasible to consider G×E interactions in evaluations of sires using genomic prediction models and that genomic information can increase the accuracy of selection across environments.

In livestock, many studies have reported the results of imputation to 50k single nucleotide polymorphism (SNP) genotypes for animals that are genotyped with low-density SNP panels. The objective of this paper is to review different measures of correctness of imputation, and to evaluate their utility depending on the purpose of the imputed genotypes. Across studies, imputation accuracy, computed as the correlation between true and imputed genotypes, and imputation error rates, that counts the number of incorrectly imputed alleles, are commonly used measures of imputation correctness. Based on the nature of both measures and results reported in the literature, imputation accuracy appears to be a more useful measure of the correctness of imputation than imputation error rates, because imputation accuracy does not depend on minor allele frequency (MAF), whereas imputation error rate depends on MAF. Therefore imputation accuracy can be better compared across loci with different MAF. Imputation accuracy depends on the ability of identifying the correct haplotype of a SNP, but many other factors have been identified as well, including the number of genotyped immediate ancestors, the number of animals with genotypes at the high-density panel, the SNP density on the low- and high-density panel, the MAF of the imputed SNP and whether imputed SNP are located at the end of a chromosome or not. Some of these factors directly contribute to the linkage disequilibrium between imputed SNP and SNP on the low-density panel. When imputation accuracy is assessed as a predictor for the accuracy of subsequent genomic prediction, we recommend that: (1) individual-specific imputation accuracies should be used that are computed after centring and scaling both true and imputed genotypes; and (2) imputation of gene dosage is preferred over imputation of the most likely genotype, as this increases accuracy and reduces bias of the imputed genotypes and the subsequent genomic predictions.

Porcine reproductive and respiratory syndrome (PRRS) is a viral disease with negative impacts on reproduction of sows. Genetic selection to improve the response of sows to PRRS could be an approach to control the disease. Determining sow response to PRRS requires knowing pathogen burden and sow performance. In practice, though, records of pathogen burden are unavailable. We develop a statistical method to distinguish healthy and disease phases and to develop a method to quantify sows’ responses to PRRS without having individual pathogen burden. We analyzed 10,910 sows with 57,135 repeated records of reproduction performance. Disease phases were recognized as strong deviation of herd-year-week estimates for reproduction traits using two methods: Method 1 used raw weekly averages of the herd; Method 2 used a linear model with fixed effects for seasonality, parity, and year, and random effects for herd-year-week and sow. The variation of sows in response to PRRS was quantified using 2 models on the traits number of piglets born alive (NBA) and number of piglets born dead (LOSS): 1) bivariate model considering the trait in healthy and disease phases as different traits, and 2) reaction norm model modeling the response of sows as a linear regression of the trait on herd-year-week estimates of NBA. The linear model for NBA had the highest sensitivity (78%) for disease phases. Residual variances of both were more than doubled in the disease phase compared with the healthy phase. Trait correlations between healthy and disease phases deviated from unity (0.57 ± 0.13 – 0.87 ± 0.18). In the bivariate model, repeatabilities were lower in disease phase compared with healthy phase (0.07 ± 0.027 and 0.16 ± 0.005 for NBA; 0.07 ± 0.027 and 0.09 ± 0.004 for LOSS). The reaction norm model fitted the data better than the bivariate model based on Akaike’s information criterion, and had also higher predictive ability in disease phase based on cross validation. Our results show that the linear model is a practical method to distinguish between healthy and disease phases in farm data. We showed that there is variation among sows in response to PRRS, implying possibilities for selection, and the reaction norm model is a good model to study the response of animals toward diseases.

Heritability of mastitis (and diseases in general) tends to be low. One possible cause is that no clear distinction can be made between resistant and nonresistant animals, because healthy animals include animals that have not been exposed to pathogens and resistant animals. To account for this, we quantified the prevalence of clinical mastitis (CM) and subclinical mastitis (SCM) in 2,069 Swedish Holstein herds as a measure of exposure. Herd prevalence averaged 26.5% for SCM and 6.4% for CM; 61% of the first lactations of 177,309 cows were classified as having at least one case of SCM and 10% as having CM. In a reaction norm approach, heritability of (S)CM was quantified as a function of herd prevalence of (S)CM. The best-fitting model was a second-order polynomial of first-lactation cow SCM as a function of herd prevalence SCM, and a first-order (linear) polynomial of first-lactation cow CM as a function of CM herd prevalence. Heritability for SCM ranged from 0.069 to 0.105 and for CM from 0.016 to 0.032. For both, we found no clear effect of herd prevalence on their heritability. Genetic correlations within traits across herd prevalences were all greater than 0.92. Whether relationships among prevalence, exposure, disease, and genetics were as expected is a matter of discussion, but reaction norm analyses may be a valuable tool for epidemiological genetics.

Background Selection for sound conformation has been widely used as a primary approach to reduce lameness and leg weakness in pigs. Identification of genomic regions that affect conformation traits would help to improve selection accuracy for these lowly to moderately heritable traits. Our objective was to identify genetic factors that underlie leg and back conformation traits in three Danish pig breeds by performing a genome-wide association study followed by meta-analyses. Methods Data on four conformation traits (front leg, back, hind leg and overall conformation) for three Danish pig breeds (23,898 Landrace, 24,130 Yorkshire and 16,524 Duroc pigs) were used for association analyses. Estimated effects of single nucleotide polymorphisms (SNPs) from single-trait association analyses were combined in two meta-analyses: (1) a within-breed meta-analysis for multiple traits to examine if there are pleiotropic genetic variants within a breed; and (2) an across-breed meta-analysis for a single trait to examine if the same quantitative trait loci (QTL) segregate across breeds. SNP annotation was implemented through Sus scrofa Build 10.2 on Ensembl to search for candidate genes. Results Among the 14, 12 and 13 QTL that were detected in the single-trait association analyses for the three breeds, the most significant SNPs explained 2, 2.3 and 11.4% of genetic variance for back quality in Landrace, overall conformation in Yorkshire and back quality in Duroc, respectively. Several candidate genes for these QTL were also identified, i.e. LRPPRC, WRAP73, VRTN and PPARD likely control conformation traits through the regulation of bone and muscle development, and IGF2BP2, GH1, CCND2 and MSH2 can have an influence through growth-related processes. Meta-analyses not only confirmed many significant SNPs from single-trait analyses with higher significance levels, but also detected several additional associated SNPs and suggested QTL with possible pleiotropic effects. Conclusions Our results imply that conformation traits are complex and may be partly controlled by genes that are involved in bone and skeleton development, muscle and fat metabolism, and growth processes. A reliable list of QTL and candidate genes was provided that can be used in fine-mapping and marker assisted selection to improve conformation traits in pigs. Electronic supplementary material The online version of this article (doi:10.1186/s12711-017-0289-2) contains supplementary material, which is available to authorized users.

Overuse of antibiotics is a major problem in the treatment of bovine mastitis, and antibiotic treatment is frequently non-curative, thus alternative treatments are necessary. The primary aim of this study was to evaluate the efficacy of a purified phage cocktail for treatment of bovine Staphylococcus aureus mastitis in a well-defined mouse model. Candidate phages were selected based on their in vitro performance and subsequently processed into an optimally composed phage cocktail. The highest scoring phages were further tested for efficacy and resistance suppression in broth and raw milk, with and without supplemental IgG. As these in vitro results displayed significant decreases in CFU, the cocktail was purified for testing in vivo. Lactating mice were intramammarily inoculated with S. aureus N305 (ATCC 29740), a clinical bovine mastitis isolate commonly used for experimental infection of dairy cows. The phage cocktail was applied via the same route 4 h post-inoculation. Treated mammary glands were graded for gross pathological appearance and excised for bacterial and phage load quantification as well as histopathology. Observation of gross macroscopic and histopathological changes and CFU quantification demonstrated that the phage cocktail treatment significantly improved mastitis pathology and decreased bacterial counts. Phage PFU quantification indicated that the tested phage cocktail treatment was able to maintain high intramammary phage titers without spreading systemically. The in vivo results complement the in vitro data and support our concept of phage therapy as an innovative alternative or supplementation therapy to antibiotics for the treatment of bovine mastitis.

In this study, it was aimed to investigate polymorphisms in seven genes (GH, PRL, STAT5A, OPN, PIT-1, LEP and FGF2) related to reproductive traits in dairy heifers. Frequency distributions of the genotypes between fertile and repeat breeder heifers groups were investigated. Allele effects on fertility were also analyzed. Blood samples were taken from a total of 160 Holstein-Friesian heifers and they were divided into two groups according to their artificial insemination numbers (AI). The heifers becoming pregnant after the first AI were used as the fertile heifers (FH, n= 80) and the heifers with 3 or more equal AIs were accepted as the repeat breeder heifers (RBH, n= 80). All the animals were genotyped by the PCR-RFLP method for seven genes and the association works were performed for 145 animals (RBH, n= 79; FH n= 66). For all loci investigated, two alleles and three genotypes were found for overall population with the exception that PRL locus had two alleles and two genotypes. The chi-square test (.2) revealed that the whole population and the two groups separately were at Hardy-Weinberg equilibrium. The genotype distributions of PIT-1 and STAT5A conspicuously differed between the FH and the RBH groups; however, these differences were not found significant. Association of GH-AB genotype was found significant on AI number for the first pregnancy. Mixed effect logistic regression model was used to investigate the allele effects on fertility. No linkage disequilibrium was detected between the investigated loci. Bu çalışmada sütçü düvelerde reprodüktif özellikler ile ilişkili yedi gendeki (GH, PRL, STAT5A, OPN, PIT-1, LEP ve FGF2) polimorfizimlerin araştırılması amaçlanmıştır. Genotip frekanslarının fertil ve repeat breeder düve gruplarındaki dağılımı araştırılmıştır. Ayrıca fertilite üzerine allel etkisi de incelenmiştir. Toplam 160 Holstein-Friesian düveden kan alınmış ve bu düveler tohumlama sayılarına (ST) göre iki gruba ayrılmıştır. İlk tohumlamada gebe kalan düveler fertil düve (FH, n=80) olarak kullanılmış ve üç veya daha fazla ST’si olan düveler repeat breeder düve (RBH, n=80) olarak kabul edilmiştir. Tüm hayvanlar yedi gen bakımından PCR-RFLP metodu ile genotiplendirilmiş ve ilişkilendirme çalışmaları toplam 145 hayvanda yapılmıştır (RBH, n=79; FH, n=66). İki allel ve iki genotipin bulunduğu PRL hariç incelenen tüm lokuslarda iki allel ve üç genotip belirlenmiştir. Ki-kare sonuçları (χ2) tüm populasyonun ve ayrı ayrı grupların Hardy-Weinberg dengesinde olduğunu ortaya koymuştur. PIT-1 ve STAT5A lokuslarının genotip frekanslarının dağılımları FH ve RBH grupları arasında belirgin biçimde farklı olmasına rağmen bu farklılık istatistiksel anlamda önemli bulunmamıştır. GH-AB genotipinin fertilite üzerine etkisi önemli bulunmuştur. Fertilite üzerindeki allel etkisini incelemek için karışık etkili lojistik regresyon analizi kullanılmıştır. İncelenen lokuslar arasında bir bağlantı dengesizliği belirlenmemiştir. American Journal Experts (AJE).

In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the mean of SCS, but genes with large effects seem to be absent for both traits.

The genomic breeding value accuracy of scarcely recorded traits is low because of the limited number of phenotypic observations. One solution to increase the breeding value accuracy is to use predictor traits. This study investigated the impact of recording additional phenotypic observations for predictor traits on reference and evaluated animals on the genomic breeding value accuracy for a scarcely recorded trait. The scarcely recorded trait was dry matter intake (DMI, n = 869) and the predictor traits were fat-protein-corrected milk (FPCM, n = 1520) and live weight (LW, n = 1309). All phenotyped animals were genotyped and originated from research farms in Ireland, the United Kingdom and the Netherlands. Multi-trait REML was used to simultaneously estimate variance components and breeding values for DMI using available predictors. In addition, analyses using only pedigree relationships were performed. Breeding value accuracy was assessed through cross-validation (CV) and prediction error variance (PEV). CV groups (n = 7) were defined by splitting animals across genetic lines and management groups within country. With no additional traits recorded for the evaluated animals, both CV- and PEV-based accuracies for DMI were substantially higher for genomic than for pedigree analyses (CV: max. 0.26 for pedigree and 0.33 for genomic analyses; PEV: max. 0.45 and 0.52, respectively). With additional traits available, the differences between pedigree and genomic accuracies diminished. With additional recording for FPCM, pedigree accuracies increased from 0.26 to 0.47 for CV and from 0.45 to 0.48 for PEV. Genomic accuracies increased from 0.33 to 0.50 for CV and from 0.52 to 0.53 for PEV. With additional recording for LW instead of FPCM, pedigree accuracies increased to 0.54 for CV and to 0.61 for PEV. Genomic accuracies increased to 0.57 for CV and to 0.60 for PEV. With both FPCM and LW available for evaluated animals, accuracy was highest (0.62 for CV and 0.61 for PEV in pedigree, and 0.63 for CV and 0.61 for PEV in genomic analyses). Recording predictor traits for only the reference population did not increase DMI breeding value accuracy. Recording predictor traits for both reference and evaluated animals significantly increased DMI breeding value accuracy and removed the bias observed when only reference animals had records. The benefit of using genomic instead of pedigree relationships was reduced when more predictor traits were used. Using predictor traits may be an inexpensive way to significantly increase the accuracy and remove the bias of (genomic) breeding values of scarcely recorded traits such as feed intake.

Computer vision techniques are a means to extract individual animal information such as weight, activity and calving time in intensive farming. Automatic detection requires adequate image pre-processing such as segmentation to precisely distinguish the animal from its background. For some analyses such as gait analysis, a side view perspective is recommended. When using a side view angle however, the background is more difficult to control – moving objects, such as other animals may negatively impact successful image segmentation. The objective of this research was to evaluate five different background segmentation algorithms on side view images when taken against a static background (a solid transportable wall) and a dynamic background (open air, without a wall). The experiments were conducted on a commercial robotic-milking dairy farm in Israel with a herd size of 70 Israeli Holstein cows. A side view image of cow’s gait was recorded after milking when the cows exited the milking area and returned to the cowshed. From the recording database, a random selection was made of 35 frames containing a static background (solid wall) and 20 frames containing a dynamic background (natural barn environment with other cows). Five segmentation algorithms were chosen and adapted from literature to extract the cow shape from the image. The output of three algorithms gave the cow’s full body shape two identified only the contour of the cow’s body. The algorithms were compared on their ability to correctly identify the cow’s back contour line. The performance of each algorithm was quantified by comparing its outputs to a golden standard of manually labelled cow pixels in the image. The introduction of a physical wall behind the cows (static background) significantly improved the foreground segmentation results (Mean Absolute Error (MAE) = 6.7 ± 5.7 pixels vs. 19.7 ± 9.1 pixels). The fourth algorithm, based on an edge detection on the background difference frame, gave the best cow back contour line segmentation results (b0 = -0.4 ± 15.5 and b1 = 1.00 ± 0.07). The fifth algorithm which is based on consecutive frame differences was less accurate than the other four methods which are based on the background frame differences (MAE = 16.0 ± 5.9 pixels vs. 4.1 ± 2.2 pixels, 4.3 ± 2.2 pixels, 5.6 ± 2.8 pixels and 3.7 ± 1.4 pixels respectively for the other four algorithms). The results show that the applied algorithms were not robust enough to work on side view images with dynamic backgrounds.

Rainbow trout is a globally important fish species for aquaculture. However, fish for most farms worldwide are produced by only a few breeding companies. Selection based solely on fish performance recorded at a nucleus may lead to lower-than-expected genetic gains in other production environments when genotype-by-environment (G × E) interaction exists. The aim was to quantify the magnitude of G × E interaction of growth traits (tagging weight; BWT, harvest weight; BWH, and growth rate; TGC) measured across 4 environments, located in 3 different continents, by estimating genetic correlations between environments. A total of 100 families, of at least 25 in size, were produced from the mating 58 sires and 100 dams. In total, 13,806 offspring were reared at the nucleus (selection environment) in Washington State (NUC) and in 3 other environments: a recirculating aquaculture system in Freshwater Institute (FI), West Virginia; a high-altitude farm in Peru (PE), and a cold-water farm in Germany (GER). To account for selection bias due to selective mortality, a multitrait multienvironment animal mixed model was applied to analyze the performance data in different environments as different traits. Genetic correlation (rg) of a trait measured in different environments and rg of different traits measured in different environments were estimated. The results show that heterogeneity of additive genetic variances was mainly found for BWH measured in FI and PE. Additive genetic coefficient of variation for BWH in NUC, FI, PE, and GER were 7.63, 8.36, 8.64, and 9.75, respectively. Genetic correlations between the same trait in different environments were low, indicating strong reranking (BWT: rg = 0.15 to 0.37, BWH: rg = 0.19 to 0.48, TGC: rg = 0.31 to 0.36) across environments. The rg between BWT in NUC and BWH in both FI (0.31) and GER (0.36) were positive, which was also found between BWT in NUC and TGC in both FI (0.10) and GER (0.20). However, rg were negative between BWT in NUC and both BWH (–0.06) and TGC (–0.20) in PE. Correction for selection bias resulted in higher additive genetic variances. In conclusion, strong G × E interaction was found for BWT, BWH, and TGC. Accounting for G × E interaction in the breeding program, either by using sib information from testing stations or environment-specific breeding programs, would increase genetic gains for environments that differ significantly from NUC.