Estimated breeding values for canine hip dysplasia radiographic traits in a cohort of Australian German Shepherd dogs - PubMed (original) (raw)
Estimated breeding values for canine hip dysplasia radiographic traits in a cohort of Australian German Shepherd dogs
Bethany J Wilson et al. PLoS One. 2013.
Abstract
Canine hip dysplasia (CHD) is a serious and common musculoskeletal disease of pedigree dogs and therefore represents both an important welfare concern and an imperative breeding priority. The typical heritability estimates for radiographic CHD traits suggest that the accuracy of breeding dog selection could be substantially improved by the use of estimated breeding values (EBVs) in place of selection based on phenotypes of individuals. The British Veterinary Association/Kennel Club scoring method is a complex measure composed of nine bilateral ordinal traits, intended to evaluate both early and late dysplastic changes. However, the ordinal nature of the traits may represent a technical challenge for calculation of EBVs using linear methods. The purpose of the current study was to calculate EBVs of British Veterinary Association/Kennel Club traits in the Australian population of German Shepherd Dogs, using linear (both as individual traits and a summed phenotype), binary and ordinal methods to determine the optimal method for EBV calculation. Ordinal EBVs correlated well with linear EBVs (r = 0.90-0.99) and somewhat well with EBVs for the sum of the individual traits (r = 0.58-0.92). Correlation of ordinal and binary EBVs varied widely (r = 0.24-0.99) depending on the trait and cut-point considered. The ordinal EBVs have increased accuracy (0.48-0.69) of selection compared with accuracies from individual phenotype-based selection (0.40-0.52). Despite the high correlations between linear and ordinal EBVs, the underlying relationship between EBVs calculated by the two methods was not always linear, leading us to suggest that ordinal models should be used wherever possible. As the population of German Shepherd Dogs which was studied was purportedly under selection for the traits studied, we examined the EBVs for evidence of a genetic trend in these traits and found substantial genetic improvement over time. This study suggests the use of ordinal EBVs could increase the rate of genetic improvement in this population.
Conflict of interest statement
Competing Interests: Please note that co-author Claire Wade is a PLOS ONE Editorial Board member. The authors declare that this does not alter their adherence to all the PLOS ONE policies on sharing data and materials.
Figures
Figure 1. Ordinal estimated breeding values and standard errors from a multi-threshold mixed-model analysis of BVAHTs of a cohort of Australian German Shepherd Dogs.
Figure 2. Relationship between ordinal EBVs and their standard errors.
Animals with phenotypic scores are shown in blue, animals without phenotypic scores are shown in red, NORB = Norberg Angle, SUBL = Subluxation, CrAE = Cranial Acetabular Edge, DAE = Dorsal Acetabular Edge, CrEAR = Cranial Effective Acetabular Rim, AF = Acetabular Fossa, CaAE = Caudal Acetabular Edge, FHNE = Femoral Head and Neck Exostosis, FHR = Femoral Head Remodelling.
Figure 3. Boxplots of EBV accuracies for BVAHTs for a cohort of Australian German Shepherd Dogs.
NORB = Norberg Angle, SUBL = Subluxation, CrAE = Cranial Acetabular Edge, DAE = Dorsal Acetabular Edge, CrEAR = Cranial Effective Acetabular Rim, AF = Acetabular Fossa, CaAE = Caudal Acetabular Edge, FHNE = Femoral Head and Neck Exostosis, FHR = Femoral Head Remodelling.
Figure 4. Correlation between EBVs for nine BVAHTs calculated by ordinal logistic regression.
NORB = Norberg Angle, SUBL = Subluxation, CrAE = Cranial Acetabular Edge, DAE = Dorsal Acetabular Edge, CrEAR = Cranial Effective Acetabular Rim, AF = Acetabular Fossa, CaAE = Caudal Acetabular Edge, FHNE = Femoral Head and Neck Exostosis, FHR = Femoral Head Remodelling.
Figure 5. A- Linear EBVs (x) vs ordinal EBVs (y) for Femoral Head and Neck Exostosis (FHNE; a Group 2 trait) and B- fitted regression values(x) vs standardised residuals(y).
Note that although the correlation is high (0.96) and the relationship on the left appears approximately linear; it is clear from the graph on right that the assumptions of a simple linear regression are not met.
Figure 6. Trend of EBVs by year of birth expressed in terms of their effects on the observed BVAHT scale for a cohort of Australian German Shepherd Dogs born from 1980–2005.
Proprtions for each score are derived from an ordinal model analysis of observed BVAHT scores. Increasing proportions in lower scores represent a genetic improvement over time.
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