Validation of microsatellite markers for routine horse parentage testing

A parallel testing of 4803 routine Quarter Horse parentage cases, using 15 loci of blood group and protein polymorphisms (blood typing) and 11 loci of dinucleotide repeat microsatellites (DNA typing), validated DNA markers for horse pedigree verification. For the 26 loci, taken together, the theoretical effectiveness of detecting incorrect parentage was 99·999%, making it extremely unlikely that false parentage would fail to be recognized. The tests identified incorrect parentage assignment for 95 offspring (2% of cases). Despite fewer loci, DNA typing was as effective as blood typing and, in parentage exclusion cases, provided more systems to substantiate the genetic incompatibility. Five offspring presented potential genetic incompatibilities with their parents in only a single microsatellite system, but the parentage exclusions could not be confirmed with discordant results at additional loci. Two of these five incompatibilities could be explained as consequences of a null allele and three as fragment size increases or decreases (putative mutations). Provided that an exclusion assignment was based on at least two systems of genetic incompatibility, such rare genetic events did not lead to false exclusions. Notwithstanding the near 100% effectiveness estimations for either typing panel alone to identify incorrect parentage, this validation test showed an actual effectiveness of 97·3% for blood typing and 98·2% for DNA typing. The DNA-based test, however, may feasibly achieve higher efficacy than reported here by adding selected systems to the parentage test panel.     

Phenotypic and genetic analysis of reproductive traits in horse populations with different breeding purposes

Reproductive traits have a major influence on the economic effectiveness of horse breeding. However, there is little information available. We evaluated the use of reproductive traits as selection criteria in official breeding programs to increase the reproductive efficiency of breeding studs, analysing 696 690 records from the pedigree data of eight Spanish horse populations, with different breeding purposes. The reproductive parameters studied in both sexes were age at first foaling (AFF), age at last foaling, average reproductive life and generational interval. In the females, the average interval between foaling (AIF) and interval between first and second foaling were also studied. There were clear differences between sexes and breeds, which may be due to management practices, breeding purposes and the status of the populations, rather than to differences in actual physiological conditions. Riding mares were the most precocious (AFF, 1937.64 to 2255.69 days) and had a more intensive reproductive use (AIF, 625.83 to 760.07 days), whereas sires used for meat production were the most precocious males (AFF, 1789.93 to 1999.75 days), although they had a shorter reproductive life (1564.34 to 1797.32 days). Heritabilities (0.02 to 0.42 in females and 0.04 to 0.28 in males) evidenced the genetic component of the reproductive traits, with Sport Horses having the higher average values. These results support the selection by AFF to improve reproductive aspects because of its medium–high heritability and its positive correlations with other important reproductive traits. The inclusion of the AIF is also recommended in sport populations, because this determines the length of the breaks between foaling and conditions the reproductive performance of the dams, as well as their selective intensity, genetic gain and genetic improvement. It is therefore an important economic parameter in breeding studs.     

Bayesian prediction of breeding values for multivariate binary and continuous traits in simulated horse populations using threshold-linear models with Gibbs sampling

Simulated data were used to determine the properties of multivariate prediction of breeding values for categorical and continuous traits using phenotypic, molecular genetic and pedigree information by mixed linear-threshold animal models via Gibbs sampling. Simulation parameters were chosen such that the data resembled situations encountered in Warmblood horse populations. Genetic evaluation was performed in the context of the radiographic findings in the equine limbs. The simulated pedigree comprised seven generations and 40 000 animals per generation. The simulated data included additive genetic values, residuals and fixed effects for one continuous trait and liabilities of four binary traits. For one of the binary traits, quantitative trait locus (QTL) effects and genetic markers were simulated, with three different scenarios with respect to recombination rate (r) between genetic markers and QTL and polymorphism information content (PIC) of genetic markers being studied: r = 0.00 and PIC = 0.90 (r0p9), r = 0.01 and PIC = 0.90 (r1p9), and r = 0.00 and PIC = 0.70 (r0p7). For each scenario, 10 replicates were sampled from the simulated horse population, and six different data sets were generated per replicate. Data sets differed in number and distribution of animals with trait records and the availability of genetic marker information. Breeding values were predicted via Gibbs sampling using a Bayesian mixed linear-threshold animal model with residual covariances fixed to zero and a proper prior for the genetic covariance matrix. Relative breeding values were used to investigate expected response to multi- and single-trait selection. In the sires with 10 or more offspring with trait information, correlations between true and predicted breeding values ranged between 0.89 and 0.94 for the continuous traits and between 0.39 and 0.77 for the binary traits. Proportions of successful identification of sires of average, favourable and unfavourable genetic value were 81% to 86% for the continuous trait and 57% to 74% for the binary traits in these sires. Expected decrease of prevalence of the QTL trait was 3% to 12% after multi-trait selection for all binary traits and 9% to 17% after single-trait selection for the QTL trait. The combined use of phenotype and genotype data was superior to the use of phenotype data alone. It was concluded that information on phenotypes and highly informative genetic markers should be used for prediction of breeding values in mixed linear-threshold animal models via Gibbs sampling to achieve maximum reduction in prevalences of binary traits.     

Validation of Bayesian analysis of compartmental kinetic models in medical imaging

IntroductionKinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated.Materials and methodsThe closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach.Results and discussionPosteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P > 0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P < 0.0001).ConclusionsThe results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities.     

Cross-validation analysis for genetic evaluation models for ranking in endurance horses

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider–horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider–horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In conclusion, the Thurstonian approach is recommended for the routine genetic evaluations for ranking in endurance horses.     

On the effectiveness of higher taxonomic ranks for vegetation analysis

The ecological value of employing taxonomic categories other than species to describe vegetation is examined by comparing the results of numerical classification. Using presence data only and an unsophisticated classification method with data from a small area, it is found that the use of generic and subgeneric categories instead of species causes little loss in interpretability. At the family and subfamily levels more sophisticated analyses probably employing quantitative data, are apparently required to achieve similar levels of interpretability. The transformation between categories is shown to be a simple matrix multiplication and some alternative transformations are briefly outlined. It is suggested that the use of different taxonomic categories in a sequence of analyses beginning with the highest category would provide a useful means of planning which could reduce the overall time required for the analysis of large data sets.     

An evaluation of randomization models for nested species subsets analysis

Randomization models, often termed “null” models, have been widely used since the 1970s in studies of species community and biogeographic patterns. More recently they have been used to test for nested species subset patterns (or nestedness) among assemblages of species occupying spatially subdivided habitats, such as island archipelagoes and terrestrial habitat patches. Nestedness occurs when the species occupying small or species-poor sites have a strong tendency to form proper subsets of richer species assemblages. In this paper, we examine the ability of several published simulation models to detect, in an unbiased way, nested subset patterns from a simple matrix of site-by-species presence-absence data. Each approach attempts to build in biological realism by following the assumption that the ecological processes that generated the patterns observed in nature would, if they could be repeated many times over using the same species and landscape configuration, produce islands with the same number of species and species present on the same number of islands as observed. In mathematical terms, the mean marginal totals (column and row sums) of many simulated matrices would match those of the observed matrix. Results of model simulations suggest that the true probability of a species occupying any given site cannot be estimated unambiguously. Nearly all of the models tested were shown to bias simulation matrices toward low levels of nestedness, increasing the probability of a Type I statistical error. Further, desired marginal totals could be obtained only through ad-hoc manipulation of the calculated probabilities. Paradoxically, when such results are achieved, the model is shown to have little statistical power to detect nestedness. This is because nestedness is determined largely by the marginal totals of the matrix themselves, as suggested earlier by Wright and Reeves. We conclude that at the present time, the best null model for nested subset patterns may be one based on equal probabilities of occurrence for all species. Examples of such models are readily available in the literature. Received: 3 February 1997 / Accepted: 21 September 1997     

Selection indices for quality evaluation in wheat breeding

Summary From multilocation trials involving 125 cultivars of wheat of mainly French and European origin four tests — protein content, Pelshenke, modified Zeleny and the mixograph — were used to establish six selection indices. Three of these indices — IW₁, IW₂ and IW₃ — were calculated in order to evaluate the genetic potentiality of the lines for dough strength as given by the Chopin alveograph. The indices IV₁, IV₂ and IV₃ were established to evaluate loaf volume as measured by the French bread-making standard. A quality index IQ was calculated from the allelic effects of the high-molecular-weight (HMW) subunits of glutenin from 195 cultivars assessed by the Chopin alveograph and the Pelshenke test. Comparison of the relative efficiency of each of the six indices to the individual tests revealed the superiority of the indices over one or several technological parameters. The six selection indices and the quality index were compared using 30 very diverse F₄ lines. Their ability to retain the good quality lines is discussed in particular.     

Integration of genomic information into sport horse breeding programs for optimization of accuracy of selection

Reliable selection criteria are required for young riding horses to increase genetic gain by increasing accuracy of selection and decreasing generation intervals. In this study, selection strategies incorporating genomic breeding values (GEBVs) were evaluated. Relevant stages of selection in sport horse breeding programs were analyzed by applying selection index theory. Results in terms of accuracies of indices (r_TI) and relative selection response indicated that information on single nucleotide polymorphism (SNP) genotypes considerably increases the accuracy of breeding values estimated for young horses without own or progeny performance. In a first scenario, the correlation between the breeding value estimated from the SNP genotype and the true breeding value (= accuracy of GEBV) was fixed to a relatively low value of r_mg = 0.5. For a low heritability trait (h² = 0.15), and an index for a young horse based only on information from both parents, additional genomic information doubles r_TI from 0.27 to 0.54. Including the conventional information source ‘own performance’ into the before mentioned index, additional SNP information increases r_TI by 40%. Thus, particularly with regard to traits of low heritability, genomic information can provide a tool for well-founded selection decisions early in life. In a further approach, different sources of breeding values (e.g. GEBV and estimated breeding values (EBVs) from different countries) were combined into an overall index when altering accuracies of EBVs and correlations between traits. In summary, we showed that genomic selection strategies have the potential to contribute to a substantial reduction in generation intervals in horse breeding programs.     

Validation of a system of models for plutonium decorporation therapy

A recently proposed system of models for plutonium decorporation (SPD) was developed using data from an individual occupationally exposed to plutonium via a wound [from United States Transuranium and Uranium Registries (USTUR) Case 0212]. The present study evaluated the SPD using chelation treatment data, urine measurements, and post-mortem plutonium activities in the skeleton and liver from USTUR Case 0269. This individual was occupationally exposed to moderately soluble plutonium via inhalation and extensively treated with chelating agents. The SPD was linked to the International Commission on Radiological Protection (ICRP) Publication 66 Human Respiratory Tract Model (HRTM) and the ICRP Publication 30 Gastrointestinal Tract model to evaluate the goodness-of-fit to the urinary excretion data and the predictions of post-mortem plutonium retention in the skeleton and liver. The goodness-of-fit was also evaluated when the SPD was linked to the ICRP Publication 130 HRTM and the ICRP Publication 100 Human Alimentary Tract Model. The present study showed that the proposed SPD was useful for fitting the entire, chelation-affected and non-affected, urine bioassay data, and for predicting the post-mortem plutonium retention in the skeleton and liver at time of death, 38.5 years after the accident. The results of this work are consistent with the conclusion that Ca-EDTA is less effective than Ca-DTPA for enhancing urinary excretion of plutonium.

     

Validation protocol of models for centre of mass estimation.

The estimation of the body centre-of-mass (COM) position requires the modelling of the human body as a system of rigid segments and the measurement of the position of related external anatomical landmarks. Many models for COM position estimation have been proposed with different levels of complexity and, in some cases, specific protocols have been used for model accuracy evaluation. In this paper, we propose a general method for the quantitative assessment of any COM model in relation to a determined set of movements. It consists of an experimental protocol and of a set of comparative indices, which quantify the congruence among the estimated kinematic variables and their expected values. The general applicability of the method is specifically addressed to models' comparison, aiming to support the user in the process of choice and validation of the most suitable model for her/his purposes. In this frame, the results of the analytical comparison among two kinematic models with different levels of complexity are reported.     

A Thurstonian model for quantitative genetic analysis of ranks: a Bayesian approach

A fully Bayesian method for quantitative genetic analysis of data consisting of ranks of, e.g., genotypes, scored at a series of events or experiments is presented. The model postulates a latent structure, with an underlying variable realized for each genotype or individual involved in the event. The rank observed is assumed to reflect the order of the values of the unobserved variables, i.e., the classical Thurstonian model of psychometrics. Parameters driving the Bayesian hierarchical model include effects of covariates, additive genetic effects, permanent environmental deviations, and components of variance. A Markov chain Monte Carlo implementation based on the Gibbs sampler is described, and procedures for inferring the probability of yet to be observed future rankings are outlined. Part of the model is rendered nonparametric by introducing a Dirichlet process prior for the distribution of permanent environmental effects. This can lead to potential identification of clusters of such effects, which, in some competitions such as horse races, may reflect forms of undeclared preferential treatment.     

Validation of biopharmaceutical purification processes for virus clearance evaluation

Any biopharmaceutical product that has involved the use of animal-derived material during the manufacturing process has the potential to be contaminated with animal viruses. To ensure safety of these products, extensive testing is performed on the starting materials, such as the cell banks, and on the raw materials used in manufacture. Additional testing is also performed at various stages of production and, in some cases, on the final product as well. Because of inherent limitations in direct testing methods, the capacity of the downstream purification process to remove/inactivate potential viral contaminants is also studied to give an extra degree of assurance that the final product will be free of infectious viruses.     

Advantage of single-trial models for response to selection in wheat breeding multi-environment trials

An investigation was conducted to evaluate the impact of experimental designs and spatial analyses (single-trial models) of the response to selection for grain yield in the northern grains region of Australia (Queensland and northern New South Wales). Two sets of multi-environment experiments were considered. One set, based on 33 trials conducted from 1994 to 1996, was used to represent the testing system of the wheat breeding program and is referred to as the multi-environment trial (MET). The second set, based on 47 trials conducted from 1986 to 1993, sampled a more diverse set of years and management regimes and was used to represent the target population of environments (TPE). There were 18 genotypes in common between the MET and TPE sets of trials. From indirect selection theory, the phenotypic correlation coefficient between the MET and TPE single-trial adjusted genotype means [r _p(MT)] was used to determine the effect of the single-trial model on the expected indirect response to selection for grain yield in the TPE based on selection in the MET. Five single-trial models were considered: randomised complete block (RCB), incomplete block (IB), spatial analysis (SS), spatial analysis with a measurement error (SSM) and a combination of spatial analysis and experimental design information to identify the preferred (PF) model. Bootstrap-resampling methodology was used to construct multiple MET data sets, ranging in size from 2 to 20 environments per MET sample. The size and environmental composition of the MET and the single-trial model influenced the r _p(MT). On average, the PF model resulted in a higher r _p(MT) than the IB, SS and SSM models, which were in turn superior to the RCB model for MET sizes based on fewer than ten environments. For METs based on ten or more environments, the r _p(MT) was similar for all single-trial models.Communicated by H.C. Becker     

Validation of a multi-criteria evaluation model for animal welfare

The aim of this paper was to validate an alternative multi-criteria evaluation system to assess animal welfare on farms based on the Welfare Quality® (WQ) project, using an example of welfare assessment of growing pigs. This alternative methodology aimed to be more transparent for stakeholders and more flexible than the methodology proposed by WQ. The WQ assessment protocol for growing pigs was implemented to collect data in different farms in Schleswig-Holstein, Germany. In total, 44 observations were carried out. The aggregation system proposed in the WQ protocol follows a three-step aggregation process. Measures are aggregated into criteria, criteria into principles and principles into an overall assessment. This study focussed on the first two steps of the aggregation. Multi-attribute utility theory (MAUT) was used to produce a value of welfare for each criterion and principle. The utility functions and the aggregation function were constructed in two separated steps. The MACBETH (Measuring Attractiveness by a Categorical-Based Evaluation Technique) method was used for utility function determination and the Choquet integral (CI) was used as an aggregation operator. The WQ decision-makers’ preferences were fitted in order to construct the utility functions and to determine the CI parameters. The validation of the MAUT model was divided into two steps, first, the results of the model were compared with the results of the WQ project at criteria and principle level, and second, a sensitivity analysis of our model was carried out to demonstrate the relative importance of welfare measures in the different steps of the multi-criteria aggregation process. Using the MAUT, similar results were obtained to those obtained when applying the WQ protocol aggregation methods, both at criteria and principle level. Thus, this model could be implemented to produce an overall assessment of animal welfare in the context of the WQ protocol for growing pigs. Furthermore, this methodology could also be used as a framework in order to produce an overall assessment of welfare for other livestock species. Two main findings are obtained from the sensitivity analysis, first, a limited number of measures had a strong influence on improving or worsening the level of welfare at criteria level and second, the MAUT model was not very sensitive to an improvement in or a worsening of single welfare measures at principle level. The use of weighted sums and the conversion of disease measures into ordinal scores should be reconsidered.     

Bull breeding soundness evaluation in Southern Africa

The motivation for and process leading up to the publication of a new bull breeding soundness certification standard endorsed by the South African Veterinary Association is described. The veterinary certificate of bull breeding soundness and explanatory notes and minimum standards are shown. The first component of the certificate is a declaration by the veterinarian that the bull complies with the minimum standards set for examinations for the selected purpose, these being for use as a natural service sire, as a donor of semen for distribution, and for insurance purposes. This is followed by the details of the bull and owner, and a list of the recommended examinations and tests for the bull with provision for which were performed. Certificates are available in book form with the explanatory notes and minimum standards on the reverse, and a carbon copy which remains in the book.The clarity and ease of completion of the document are regarded as being positive features. Bulls are either classified as breeding sound or not, with no actual parameters indicated on the document and no certificate issued for those which do not meet the set criteria. Contact details of the parties involved are shown on the certificate to allow for communication as a means of avoiding disputes.     

Estimating the annual number of breeding attempts from breeding dates using mixture models

Well-established statistical methods exist to estimate variation in a number of key demographic rates from field data, including life-history transition probabilities and reproductive success per attempt. However, our understanding of the processes underlying population change remains incomplete without knowing the number of reproductive attempts individuals make annually; this is a key demographic rate for which we have no satisfactory method of estimating. Using census data to estimate this parameter from requires disaggregating the overlying temporal distributions of first and subsequent breeding attempts. We describe a Bayesian mixture method to estimate the annual number of reproductive attempts from field data to provide a new tool for demographic inference. We validate our method using comprehensive data on individually-marked song sparrows Melospiza melodia , and then apply it to more typical nest record data collected over 45 years on yellowhammers Emberiza citrinella . We illustrate the utility of our method by testing, and rejecting, the hypothesis that declines in UK yellowhammer populations have occurred concurrently with declines in annual breeding frequency.     

Correction for skin displacement errors in movement analysis of the horse

In movement analysis of the horse, large errors result from movements of the skin with respect to the underlying bones. A generally applicable, two-dimensional, method for correction of these skin-movement errors in kinematic data has been developed. It was tested on a kinematic analysis of the hindlimb in a walking pony. The results indicate that without correction for skin-movement errors, misreadings of up to 15 degrees in the knee angle and 30% in the moment arm of the gastrocnemius muscle can be expected.