Relationships between Podolic cattle breeds assessed by single nucleotide polymorphisms (SNPs) genotyping

Italian Maremmana, Turkish Grey and Hungarian Grey breeds belong to the same Podolic group of cattle, have a similar conformation and recently experienced a similar demographic reduction. The aim of this study was to assess the relationship among the analysed Podolic breeds and to verify whether their genetic state reflects their history. To do so, approximately 100 single nucleotide polymorphisms (SNPs) were genotyped on individuals belonging to these breeds and compared to genotypes of individuals of two Italian beef breeds, Marchigiana and Piemontese, which underwent different selection and migration histories. Population genetic parameters such as allelic frequencies and heterozygosity values were assessed, genetic distances calculated and assignment test performed to evaluate the possibility of recent admixture between the populations. The data show that the physical similarity among the Podolic breeds examined, and particularly between Hungarian Grey and Maremmana cattle that experienced admixture in the recent past, is mainly morphological. The assignment of individuals from genotype data was achieved using Bayesian inference, confirming that the set of chosen SNPs is able to distinguish among the breeds and that the breeds are genetically distinct. Individuals of Turkish Grey breed were clearly assigned to their breed of origin for all clustering alternatives, showing that this breed can be differentiated from the others on the basis of the allelic frequencies. Remarkably, in the Turkish Grey there were differences observed between the population of Enez district, where in situ conservation studies are practised, and that of Bandirma district of Balikesir, where ex situ conservation studies are practised out of the original raising area. In conclusion, this study demonstrates that molecular data could be used to reveal an unbiased view of past events and provide the basis for a rational exploitation of livestock, suggesting appropriate cross-breeding plans based on genetic distance or breeding strategies that include the population structure.     

Genetic correlations between categorical morphological traits in Nelore cattle by applying Bayesian analysis under a threshold animal model

In this study, Bayesian analysis under a threshold animal model was used to estimate genetic correlations between morphological traits (body structure, finishing precocity and muscling) in Nelore cattle evaluated at weaning and yearling. Visual scores obtained from 7651 Nelore cattle at weaning and from 4155 animals at yearling, belonging to the Brazilian Nelore Program, were used. Genetic parameters for the morphological traits were estimated by two‐trait Bayesian analysis under a threshold animal model. The genetic correlations between the morphological traits evaluated at two ages of the animal (weaning and yearling) were positive and high for body structure (0.91), finishing precocity (0.96) and muscling (0.94). These results indicate that the traits are mainly determined by the same set of genes of additive action and that direct selection at weaning will also result in genetic progress for the same traits at yearling. Thus, selection of the best genotypes during only one phase of life of the animal is suggested. However, genetic differences between morphological traits were better detected during the growth phase to yearling. Direct selection for body structure, finishing precocity and muscling at only one age, preferentially at yearling, is recommended as genetic differences between traits can be detected at this age.     

Management interventions in dairy herds: Exploring within herd uncertainty using an integrated Bayesian model

Knowledge of the efficacy of an intervention for disease control on an individual farm is essential to make good decisions on preventive healthcare, but the uncertainty in outcome associated with undertaking a specific control strategy has rarely been considered in veterinary medicine. The purpose of this research was to explore the uncertainty in change in disease incidence and financial benefit that could occur on different farms, when two effective farm management interventions are undertaken. Bovine mastitis was used as an example disease and the research was conducted using data from an intervention study as prior information within an integrated Bayesian simulation model. Predictions were made of the reduction in clinical mastitis within 30 days of calving on 52 farms, attributable to the application of two herd interventions previously reported as effective; rotation of dry cow pasture and differential dry cow therapy. Results indicated that there were important degrees of uncertainty in the predicted reduction in clinical mastitis for individual farms when either intervention was undertaken; the magnitude of the 95% credible intervals for reduced clinical mastitis incidence were substantial and of clinical relevance. The large uncertainty associated with the predicted reduction in clinical mastitis attributable to the interventions resulted in important variability in possible financial outcomes for each farm. The uncertainty in outcome associated with farm control measures illustrates the difficulty facing a veterinary clinician when making an on-farm decision and highlights the importance of iterative herd health procedures (continual evaluation, reassessment and adjusted interventions) to optimise health in an individual herd.     

贝叶斯统计学在遗传中的应用

经典统计分析方法在遗传学中已经得到广泛应用,而在解决许多复杂的遗传学问题中,贝叶斯方法显得更为有效,因而贝叶斯统计学的应用也逐渐受到重视。本文主要讨论贝叶斯统计分析方法与经典统计分析方法的异同、贝叶斯统计学在遗传学的主要应用及其优点。     

Bayesian spatio-temporal modelling of national milk-recording data of seasonal-calving New Zealand dairy herds

A spatio-temporal analysis was undertaken with the aim of identifying the dynamics of herd mean individual cow SCCs (MICSCC) in seasonally calving New Zealand dairy herds. Two datasets were extracted from the Livestock Improvement Corporation's extensive national dairy recording database: (1) milk-recording data aggregated at the herd-level and (2) sales questionnaire data containing information on the size, location and infrastructure of each farm. A Bayesian spatio-temporal modelling approach was applied to the analysis. The data were aggregated by 10 km² grid cells and linear regression models were developed with spatially structured and unstructured random effects, a linear temporal trend random effect and spatial-temporal interactions for log-transformed median MISCC (ln(median MISCC)).

Significant associations were found between ln(median MISCC) and milk yield, milk fat, milk protein, farm area and number of cups in the dairy. This led us to suggest that SCCs should be adjusted for volume and constituents prior to determining a threshold MISCC for identification of subclinical mastitis (SCM) problem herds. Part, or all, of the temporal trend in MISCC in the spatio-temporal model was accounted for by inclusion of yield and milk constituents as independent variables. This supports the hypothesis of a dilution effect with potential consequences for misdiagnosis of SCM, particularly in late lactation. Unmeasured covariates were similarly likely to be spatially structured and unstructured.     

Estimating the probability of freedom of classical swine fever virus of the East-Belgium wild-boar population

A report of the Scientific Committee on Animal Health and Animal Welfare of the European Commission (CEC, 1999.) includes recommendations for setting up monitoring programmes for classical swine fever (CSF) infection in a wild-boar population, based on the assumption that one would detect at least 5% prevalence in a CSF-infected wild-boar population. This assumption, however, is not science based. We propose an alternative method to provide evidence for a wild-boar population being free of CSF and evaluate the efficiency of a surveillance programme that was implemented in Belgium in 1998.

In our study, the probability of freedom of CSF-virus was estimated based on 789 samples; these were collected from wild-boars within the surveillance programme (within the three provinces which include 95% of the Belgian wild-boar population) and examined by three diagnostics methods (antibody detection, virus detection and virus RNA detection). A Bayesian framework was used for the estimation, accounting for the diagnostic test characteristics without the assumption of the presence of a gold standard. The median probability of freedom of CSF-virus was estimated at 0.970, with a 95% credibility interval of 0.149–1.000. Independent on the choice of the prior information, the posterior distributions for the probability of freedom of CSF-virus were always skewed close to the upper boundary of 1. This represents a big gain of knowledge since we did not use any prior information for the probability of freedom of CSF-virus and took the uncertainty about the accuracy of the diagnostic methods into account.     

Prevalence estimates for paratuberculosis adjusted for test variability using Bayesian analysis

The ELISA tests that are available to detect an infection with Mycobacterium avium subsp. paratuberculosis (MAP) have a limited validity expressed as the sensitivity (Se) and specificity (Sp). In many studies, the Se and Sp of the tests are treated as constants and this will result in an underestimation of the variability of the true prevalence (TP). Bayesian inference provided a natural framework for using information on the test variability (i.e., the uncertainty) in the estimates of test Se and Sp when estimating the TP.

Data from two prevalence studies for MAP using an ELISA in several regions in two locations were available for the analyses. In location 1, all cattle of at least 3 years of age were sampled in approximately 90 randomly sampled herds in each of the four regions of the country. In location 2, in 30 randomly sampled herds in each of three regions, approximately 30 randomly selected cows were sampled. Information about the unknown test Se and Sp and MAP prevalence was incorporated into a Bayesian model by joint prior probability distributions. Posterior estimates were obtained by combining the actual likelihood with the prior distributions using Bayes’ formula.

The corrected cow-level TP (proportion of infected cows in a herd) was low, 5.8 and 3.6% in locations 1 and 2, respectively. Certain regions within a location differed significantly in herd-level TP (proportion of infected herds). The herd-level TP was 54.3% in location 1 (95% credible interval (CI) 46.1, 63.3%) and 32.9% in location 2 (95% CI: 14.4, 73.3%). The variation in the herd-level TP estimate for location 2 was more than three times as large as the variation in location 1 mainly because of the relatively small number of investigated herds in location 2. In future prevalence studies for MAP, sample size calculations should be based on a very low cow-level prevalence. Approximately 50 and 90% of the herds in the current study had an estimated cow-level TP below 4 and 10%, respectively.     

Estimation of (co)variance components for birth weight in Nellore cattle using alternative data editing criteria

The aim of this study was to estimate the (co)variance components and breeding values for birthweight (BW) in Nellore cattle by considering or not identical weights that exhibit a high frequency within the contemporary group (CG). A total of 175,258 BW records of Nellore cattle born between 2002 and 2018 were used. The CG was formed by farm, year of birth, sex and feeding regime at birth. CGs with more than 16% of identical BW values were eliminated, generating a data file called BWd. Another file was created without removing these animals (BWt). A mixed linear model was used for statistical analysis, which included fixed and random effects. In both data files analysed, single-trait analysis was performed by Bayesian inference. The mean direct and maternal heritability for BW and the correlation between direct and maternal effects were 0.27, 0.07 and −0.07 for BWt, respectively, and 0.30, 0.093 and −0.07 for BWd. This method should affect the estimation of genetic merits of animals for BW, providing greater safety in the choice of sires.     

基于分层贝叶斯方法的高山松单木生物量模型

以香格里拉市典型森林生态系统高山松林为对象,在前期进行Ⅰ区和Ⅱ区共115株高山松单木地上生物量实测基础上,以异速生长方程为单木生物量基础模型,并采用分层贝叶斯方法、非线性混合模型法、贝叶斯方法和非线性最小二乘法进行异速生长参数拟合,运用决定系数(R²)、估测精度(E)、均方根误差(RMSE)等指标对模型参数拟合效果进行评价。结果表明:1)从拟合精度看,4种方法的模型拟合效果均较好,R²均达到了0.98以上。但分层贝叶斯方法估计结果更优,其R²=0.985 6,E=84.76%和R_MSE=39.75 kg;2)通过对比不同方法的差异发现,加入了区域随机效应的分层贝叶斯方法和非线性混合模型法的拟合效果均优于未加入区域随机效应的贝叶斯方法和非线性最小二乘法。分层贝叶斯方法在拟合高山松单木生物量模型中具有更大优势,模型拟合效果最好。加入了随机效应的分层贝叶斯方法和非线性混合模型法可以提高单木生物量模型的估计精度,采用分层贝叶斯方法进行高山松单木生物量模型参数估测,为大尺度样本数据模型参数估测方法提供新思路。     

Investigation of the occurrence of Angiostrongylus vasorum in coyotes in southern Ontario,Canada

In North America, the only endemic focus for Angiostrongylus vasorum (French heartworm) was historically thought to occur in the southeastern part of the island of Newfoundland. However, reports of A. vasorum infection in wild canids in West Virginia, USA, and Nova Scotia, Canada, suggest the introduction of the parasite to mainland North America. We screened for A. vasorum in coyotes from across southern Ontario. Additionally, we evaluated the performance of ELISAs for detection of circulating A. vasorum antigen (Ag-ELISA) and antibodies against A. vasorum (Ab-ELISA) designed for use in sera or blood of foxes for use with coyotes in this region. Autopsies were performed on 397 coyotes, and lung tissue extract prepared from each carcass was tested via both ELISAs. The sensitivity and specificity for both tests were estimated in the absence of a gold standard using a 2-test single population Bayesian model; sensitivity and specificity priors were based on the performance of the assays in foxes in Switzerland. Eight coyotes tested positive for A. vasorum antigen; no animal was antibody positive. The estimated sensitivity and specificity of the Ag-ELISA were 90.8% (95% credible interval [CrI]: 83.8–95.6%) and 95.5% (95% CrI: 93.4–97.2%), respectively. For the Ab-ELISA, the estimated sensitivity and specificity were 41.9% (95% CrI: 32.1–51.9%) and 98.0% (95% CrI: 96.3–99.0%), respectively. Based on these findings and negative postmortem data for the same animals, there is insufficient evidence to suggest the presence of A. vasorum in southern Ontario coyotes.