Application of Bayesian causal inference and structural equation model to animal breeding

Optimized breeding goals and management practices for the improvement of target traits requires knowledge regarding any potential functional relationships between them. Fitting a structural equation model (SEM) allows for inferences about the magnitude of causal effects between traits to be made. In recent years, an adaptation of SEM was proposed in the context of quantitative genetics and mixed models. Several studies have since applied the SEM in the context of animal breeding. However, fitting the SEM requires choosing a causal structure with prior biological or temporal knowledge. The inductive causation (IC) algorithm can be used to recover an underlying causal structure from observed associations between traits. The results of the papers, which are introduced in this review, showed that using the IC algorithm to infer a causal structure is a helpful tool for detecting a causal structure without proper prior knowledge or with uncertain relationships between traits. The reports also presented that fitting the SEM could infer the effects of interventions, which are not given by correlations. Hence, information from the SEM provides more insights into and suggestions on breeding strategy than that from a multiple‐trait model, which is the conventional model used for multitrait analysis.     

Technical note: how to use Winbugs to draw inferences in animal models

This paper deals with Bayesian inferences of animal models using Gibbs sampling. First, we suggest a general and efficient method for updating additive genetic effects, in which the computational cost is independent of the pedigree depth and increases linearly only with the size of the pedigree. Second, we show how this approach can be used to draw inferences from a wide range of animal models using the computer package Winbugs. Finally, we illustrate the approach in a simulation study, in which the data are generated and analyzed using Winbugs according to a linear model with i.i.d errors having Student's t distributions. In conclusion, Winbugs can be used to make inferences in small-sized, quantitative, genetic data sets applying a wide range of animal models that are not yet standard in the animal breeding literature.     

Relationship between calving difficulty and fertility traits in first‐parity Iranian Holsteins under standard and recursive models

The main objective of this study was to estimate the genetic and phenotypic relationships between calving difficulty (CD) and fertility traits, including success at first service (SF), number of inseminations to conception (INS), interval from calving to first service (CTFS), interval between first and last service (IFL) and days open (DO), in first‐parity Iranian Holsteins under standard (SMMs) and recursive (RMMs) mixed models. The data analysed in this paper included 29 950 records on CD and fertility traits, collected in the time period from 1995 to 2014 by the Animal Breeding and Improvement Center of Iran. Under all observed SMMs and RMMs, five bivariate sire‐maternal grandsire models (ten bivariate analyses in total) were used for the analyses. Recursive models were applied with a view to consider that CD influences the fertility traits in the subsequent reproductive cycle and the genetic determination of CD and fertility traits by fitting CD as covariate for any of the fertility traits studied. The existence of such cause‐and‐effect is considered in RMMs but not in SMMs. Our results implied a statistically non‐zero magnitude of the causal relationships between CD and all the fertility traits studied, with the former influencing the latter. The causal effects of CD on SF (on the observed scale, %), INS, CTFS, IFL and DO were ?2.23%, 0.10 services, 1.93 days, 3.76 days and 5.61 days, respectively. Direct genetic correlations between CD and the fertility traits under both models were not statistically different from zero (95% HPD interval included zero), except for the correlation between CD and CTFS, which were 0.197 and 0.134 under SMM and RMM, respectively, indicating that genes associated with difficult births also increase intervals between calving and the first insemination afterwards. Comparison of both models by the deviance information criterion (DIC) demonstrated the plausibility of RMMs over SMMs.     

Alternative parameterizations of the multiple-trait random regression model for milk yield and somatic cell score via recursive links between phenotypes

Multiple-trait random regression models with recursive phenotypic link from somatic cell score (SCS) to milk yield on the same test day and with different restrictions on co-variances between these traits were fitted to the first-lactation Canadian Holstein data. Bayesian methods with Gibbs sampling were used to derive inferences about parameters for all models. Bayes factor indicated that the recursive model with uncorrelated environmental effects between traits was the most plausible specification in describing the data. Goodness of fit in terms of a within-trait weighted mean square error and correlation between observed and predicted data was the same for all parameterizations. All recursive models estimated similar negative causal effects from SCS to milk yield (up to -0.4 in 46-115 days in milk in lactation). Estimates of heritabilities, genetic and environmental correlations for the first two regression coefficients (overall level of a trait and lactation persistency) within both traits were similar among models. Genetic correlations between milk and SCS were dependent on the restrictions on genetic co-variances for these traits. Recursive model with uncorrelated system genetic effects between milk and SCS gave estimates of genetic correlations of the opposite sign compared with a regular multiple-trait model. Phenotypic recursion between milk and SCS seemed, however, to be the only source of environmental correlations between these two traits. Rankings of sires for total milk yield in lactation, average daily SCS and persistency for both traits were similar among models. Multiple-trait model with recursive links between milk and SCS and uncorrelated random environmental effects could be an attractive alternative for a regular multiple-trait model in terms of model parsimony and accuracy.     

酒精阳性乳产生的原因及其预防措施

在乳制品生产中,原料乳的质量影响最终产品的质量.酒精阳性乳是衡量乳汁质量的一个重要指标,而引起酒精阳性乳的原因很多.作者通过多年的临床经验,并查阅国内外有关资料,结合当地实际,对高酸度和低酸度两种酒精阳性乳的产生原因及综合防治措施进行了分析整理,为全面、深刻、完整地认识酒精阳性乳提供资料并指导实践工作.     

Inferring phenotypic causal structure among farrowing and weaning traits in pigs

Direct selection for litter size or weight at weaning in pigs is often hindered by external interventions such as cross‐fostering. The objective of this study was to infer the causal structure among phenotypes of reproductive traits in pigs to enable subsequent direct selection for these traits. Examined traits included: number born alive (NBA), litter size on day 21 (LS21), and litter weight on day 21 (LW21). The study included 6,240 litters from 1,673 Landrace dams and 5,393 litters from 1,484 Large White dams. The inductive causation (IC) algorithm was used to infer the causal structure, which was then fitted to a structural equation model (SEM) to estimate causal coefficients and genetic parameters. Based on the IC algorithm and temporal and biological information, the causal structure among traits was identified as: NBA → LS21 → LW21 and NBA → LW21. Owing to the causal effect of NBA on LS21 and LW21, the genetic, permanent environmental, and residual variances of LS21 and LW21were much lower in the SEM than in the multiple‐trait model for both breeds. Given the strong effect of NBA on LS21 and LW21, the SEM and causal information might assist with selective breeding for LS21 and LW21 when cross‐fostering occurs.     

Risk factors for bovine respiratory disease in Australian feedlot cattle: Use of a causal diagram-informed approach to estimate effects of animal mixing and movements before feedlot entry

A nationwide longitudinal study was conducted to investigate risk factors for bovine respiratory disease (BRD) in cattle in Australian feedlots. After induction (processing), cattle were placed in feedlot pens (cohorts) and monitored for occurrence of BRD over the first 50 days on feed. Data from a national cattle movement database were used to derive variables describing mixing of animals with cattle from other farms, numbers of animals in groups before arrival at the feedlot, exposure of animals to saleyards before arrival at the feedlot, and the timing and duration of the animal's move to the vicinity of the feedlot. Total and direct effects for each risk factor were estimated using a causal diagram-informed process to determine covariates to include in four-level Bayesian logistic regression models. Mixing, group size and timing of the animal's move to the feedlot were important predictors of BRD. Animals not mixed with cattle from other farms prior to 12 days before induction and then exposed to a high level of mixing (≥4 groups of animals mixed) had the highest risk of developing BRD (OR 3.7) compared to animals mixed at least 4 weeks before induction with less than 4 groups forming the cohort. Animals in groups formed at least 13 days before induction comprising 100 or more (OR 0.5) or 50–99 (OR 0.8) were at reduced risk compared to those in groups of less than 50 cattle. Animals moved to the vicinity of the feedlot at least 27 days before induction were at reduced risk (OR 0.4) compared to cattle undergoing short-haul transportation (<6 h) to the feedlot within a day of induction, while those experiencing longer transportation durations (6 h or more) within a day of induction were at slightly increased risk (OR 1.2). Knowledge of these risk factors could potentially be used to inform management decisions to reduce the risk of BRD in feedlot cattle.     

Statistics and evidence-based veterinary medicine: answers to 21 common statistical questions that arise from reading scientific manuscripts.

Evidence-based veterinary medicine relies critically on the scientific validity of research. A component of validity is the statistical design and subsequent analysis of data collected during the study. Correct statistical design reduces bias and improves generalizability, and correct analysis leads to appropriate inferences. Inference is the art and science of making correct decisions based on data. Because veterinarians are responsible for the medical care of their patents, it is also their responsibility to understand inferences about treatments presented in papers. This article is designed to assist veterinarians with the interpretation and understanding of statistics presented in papers.     

Mesh-like vascular changes in copper deficiency-induced rat cardiomyopathy

The pathological effects of copper deficiency (COD) are well known. However, the pathogenesis of cardiomyopathy resulting from COD remains unclear. In this study, aimed to elucidate the pathogenesis of COD-induced cardiomyopathy by examining the morphology of the cardiovascular system in copper-deficient rats using histopathology, immunohistochemistry, and scanning and transmission electron microscopy. Changes detected in the myocardium and interstitium were consistent with those reported for COD. Morphological changes included mesh-like changes in the capillary endothelial cells that appear to be a novel finding in COD-induced cardiomyopathy. These changes are hypothesized to result from abnormal vascular remodeling following damage to the basement membrane and due to the mechanical effects of myocardial contractions. Although cardiomyopathy may be associated with microcirculatory disorders arising from these lesions, further investigations are necessary to demonstrate a causal relationship between the pathogenesis of cardiomyopathy and the contribution of these lesions to disease progression.     

Test-day somatic cell score, fat-to-protein ratio and milk yield as indicator traits for sub-clinical mastitis in dairy cattle

Test-day (TD) records of milk, fat-to-protein ratio (F:P) and somatic cell score (SCS) of first-lactation Canadian Holstein cows were analysed by a three-trait finite mixture random regression model, with the purpose of revealing hidden structures in the data owing to putative, sub-clinical mastitis. Different distributions of the data were allowed in 30 intervals of days in milk (DIM), covering the lactation from 5 to 305 days. Bayesian analysis with Gibbs sampling was used for model inferences. Estimated proportion of TD records originated from cows infected with mastitis was 0.66 in DIM from 5 to 15 and averaged 0.2 in the remaining part of lactation. Data from healthy and mastitic cows exhibited markedly different distributions, with respect to both average value and the variance, across all parts of lactation. Heterogeneity of distributions for infected cows was also apparent in different DIM intervals. Cows with mastitis were characterized by smaller milk yield (down to -5 kg) and larger F:P (up to 0.13) and SCS (up to 1.3) compared with healthy contemporaries. Differences in averages between healthy and infected cows for F:P were the most profound at the beginning of lactation, when a dairy cow suffers the strongest energy deficit and is therefore more prone to mammary infection. Residual variances for data from infected cows were substantially larger than for the other mixture components. Fat-to-protein ratio had a significant genetic component, with estimates of heritability that were larger or comparable with milk yield, and was not strongly correlated with milk and SCS on both genetic and environmental scales. Daily milk, F:P and SCS are easily available from milk-recording data for most breeding schemes in dairy cattle. Fat-to-protein ratio can potentially be a valuable addition to SCS and milk yield as an indicator trait for selection against mastitis.     

Immunology and genetics of zoonotic infections involving parasites

Zoonoses involving parasites are both common and important, some causing serious diseases. The abilities of such parasites to pass between humans and a variety of vertebrates facilitates their use as experimental model systems. Much can be learned about the host-parasite relationships of zoonotic infections from laboratory-based studies, particularly where it is possible to make use of defined parasite isolates in a variety of host species or in genetically defined strains of a given host. This review focuses on our current understanding of the immunological influences upon host-parasite interactions involving zoonotic parasites and on how such influences are modified by the genetic variability found in populations of both hosts and parasites. Particular emphasis is given to data arising from work with the intestinal parasitic nematode Trichinella spiralis and other isolates of the genus Trichinella.     

动物模型在荷斯坦牛遗传评定上的应用

本研究应用动物模型ＢＬＵＰ法在微机上评定了北京地区１９６５￣１９９２年间出生的荷斯坦牛４１０８０头，建立了一套荷斯坦牛的动物模型评定系统。迭代求解采用间接解法，在阅读数据文件时进行。对于管理组、公牛与牛场互作、永久环境效应，采用Ｇａｕｓｓ－Ｓｅｉｄｅｌ迭代法，对于动物个体和遗传组效应，采用不完全的Ｊａｃｏｂｉ迭代法。提供预期传递力、父母传递力均数、预期生产力、表型均值等有用的遗传和生产信息。在配备     

Predictive ability of alternative models for genetic analysis of clinical mastitis

Mastitis in cows can be defined as a binary trait, reflecting presence or absence of clinical mastitis (CM), or as a count variable, number of mastitis cases (NCM), within a defined time interval. Many different models have been proposed for genetic analyses of mastitis, and the objective of this study was to evaluate the predictive ability and sire predictions of a set of models for genetic evaluation of CM or NCM. Linear- and threshold liability models for CM, and linear, censored ordinal threshold, and zero-inflated Poisson (ZIP) models for NCM were compared in a cross-validation study. To assess the ability of these models to predict future data, records from 620492 first-lactation Norwegian Red cows, which were daughters of 3064 sires, were evaluated in a fourfold cross-validation scheme. The mean squared error of prediction was used for model comparison. All models but ordinal threshold model equally performed when comparing the overall predictive ability. This result was on average, across sick and healthy cows; however, the models behaved differently for each category of animals. For example, healthy cows were predicted better by the threshold and linear models for binary data and ZIP model, whereas for mastitic cows, the ordinal threshold model was by far the best model. Predicted sire effects and rankings of sires were highly correlated across all models. For practical purposes, the linear models are very competitive with the nonlinear models.     

浅谈优化英语教学模式

成功的英语教学,重要的是看学生学会了多少,在实践中能否自如应用。这就涉及到英语教学模式的优化。本文从四个方面论述优化英语教学模式:一、坚持用英语教英语;二、每课一说,促使学生开口说英语;三、创设英语情景、培养语言交际能力;四、培养良好,和谐的师生情感。     

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy‐tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy‐tail distributions (multivariate Student's t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89 ± 0.90 (4.35, 7.86) and 2.04 ± 0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals.     

Enhanced growth of E. coli in whey from sows with agalactia syndrome

E. coli strains were inoculated into porcine whey samples. Replication rates and the final number of bacteria increased when grown in samples collected from sows affected by the agalactiae syndrome as compared with control samples from healthy ones. The bacteria grew especially well in samples collected on the day of farrowing.The results suggest that milk collected at the very early stages of lactation and from sows affected by agalactia supports growth of E. coli. This might make the mammary glands more sensitive to infections caused by coliform bacteria although the causal relationship remains to be resolved.     

Using Very-Large-Scale Aerial Imagery for Rangeland Monitoring and Assessment: Some Statistical Considerations

The availability of very-large-scale aerial (VLSA) imagery (typically less than 1 cm ground-sampling-distance spatial resolution) and techniques for processing those data into ecosystem indicators has opened the door for routinely using VLSA imagery in rangeland monitoring and assessment. However, for VLSA imagery to provide defensible information for managers, it is crucial to understand the statistical implications of designing and implementing VLSA image studies, including consideration of image scale, sample design limitations, and the need for validation of estimates. A significant advantage of VLSA imaging is that the researcher can specify the scale (i.e., spatial resolution and extent) of the images. VLSA image programs should plan for scales that match monitoring questions, size of landscape elements to be measured, and spatial heterogeneity of the environment. Failure to plan for scale may result in images that are not optimal for answering management questions. Probability-based sampling guards against bias and ensures that inferences can be made to the desired study area. Often collected along flight transects, VLSA imagery lends itself well to certain probability-based sample designs, such as systematic sampling, not often used in field studies. With VLSA image programs, the sample unit can be an entire image or a portion of an image. It is critical to define the sampling unit and understand the relationship between measurements and estimates made from the imagery. Finally, it is important to statistically validate estimates produced from VLSA images at selected locations using quantitative data of the same scale and more precise and accurate than the VLSA image techniques. The extent to which VLSA imagery will be useful as a tool for understanding the status and trend of rangelands depends as much on the ability to build the imagery into robust programs as it does on the ability to quickly and relatively easily collect VLSA images over large landscapes.     

Haematological correlates of phytohaemagglutinin-induced lymphocyte transformation in horses.

The purpose of these investigations was to assemble and compare data which might illustrate a functional relationship between phytohaemagglutinin-induced transformation of equine lymphocytes in vitro and the haematological profiles of the lymphocyte donors. Statistically significant correlation between transformation and a haematological parameter was taken as evidence that both may be part of a common regulatory system. There was no evidence that transformation in vitro was affected by artefactual variation in the cellular composition of the cultures. Transformational behaviour of lymphocytes in autologous plasma showed significant correlation with donors' total leucocyte, neutrophil and T cell count. Different batches of donor plasma varied in ability to support the transformation and this ability was found to correlate significantly with the total leucocyte, eosinophil, lymphocyte and T cell count of the original blood. It is concluded that previously reported variation in transformation ratios of normal equine lymphocytes is attributable to regulatory mechanisms affecting circulating blood as a whole and that helminth parasitism may be among the primary causal agents which modify the mechanism.     

Diet elucidation: Supplementary inferences from mysid feeding appendage morphology

Scanning electron microscope investigations were made of the mandibles, feeding baskets and gut armatures of Mesopodopsis slabberi and Gastrosaccus psammodytes collected in Algoa Bay, southern Africa. Comparison of the structure of the feeding appendages of these two marine mysid species allows dietary inferences supplementing data derived from gut content analyses. Both species occur in abundance in the surf zone off sandy beaches where they contribute significantly to energy transfer through the food web.