Assessing the impact of genomic selection against hip dysplasia in the Labrador Retriever dog - PubMed (original) (raw)

. 2014 Apr;131(2):134-45.

doi: 10.1111/jbg.12056. Epub 2013 Oct 18.

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Free PMC article

Assessing the impact of genomic selection against hip dysplasia in the Labrador Retriever dog

E Sánchez-Molano et al. J Anim Breed Genet. 2014 Apr.

Free PMC article

Abstract

Many purebred dogs exhibit a higher prevalence of inherited diseases compared with non-purebred dogs. One of the most popular breeds in the UK is the Labrador Retriever, which has a high prevalence of hip dysplasia resulting in high costs for surgical operations and impaired animal welfare. Considering the many complications of highly managed populations, mainly due to breeder's conventions and the resulting population structure, is of great importance for the proper development of a strategy against the disease. In this study, we have compared the utilities and performances of both genomic and phenotypic selection against hip dysplasia in a simulated population with the characteristics of the British Veterinary Association and Kennel Club (BV /KC) hip dysplasia scheme. The results confirm the potential benefits of genomic selection by showing a moderate increase of 1.15-fold (assuming a realistic accuracy of r(2) = 0.5) in response to selection due to the higher accuracy (between 0.96- and 1.32-fold, considering 0.35 ≤ r(2) ≤ 0.7) and more than a threefold increase when all the offspring in each litter are tested (between 3.25- and 4.55-fold, again considering 0.35 ≤ r(2) ≤ 0.7).

Keywords: Labrador Retriever; canine hip dysplasia; genomic selection.

© 2013 The Authors Journal of Animal Breeding and Genetics Published by Blackwell Verlag GmbH.

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Figures

Figure 1

Figure 1

Frequency of the number of scored males (circles) and females (crosses) per breeder in the data set. Fitted curve (thin line) corresponds to equation y = 0.84_x_−3.92, fitted by regression.

Figure 2

Figure 2

Age at whelping of sires (black) and dams (white). Scales are given in percentages, and age was rounded to the closest integer.

Figure 3

Figure 3

Cumulative density function observed (crosses) and expected (thin line) for the number of matings per male lifetime in the data set. Expected probability distribution was fitted by regression to y = 0.63_x_−2.01 up to a value of 25 matings, whereas for 26–50 matings, probability was equal to 4 × 10−3, and for 51–200 matings, probability was equal to 2.3 × 10−5.

Figure 4

Figure 4

Cumulative density function observed (crosses) and expected (thin line) for the number of matings per male and year in the data set. Expected probability distribution was fitted by regression to y = 0.63_x_−1.98 up to a value of 11 matings. Expected values were adjusted to reach a maximum cumulative proportion of 1.

Figure 5

Figure 5

Evolution of the genetic progress per year in the overlapping (left) and non-overlapping scheme (right) for genomic selection with _r_2 = 0.5 and testing 33% of each litter.

Figure 6

Figure 6

Annual reduction in the TH median selecting the best 85% for the transformed hip score for three percentages of scored animals per litter (33%, 50% and 100%) under an overlapping generations scheme. The dashed line is classical phenotypic selection, whilst solid lines are genomic selection with _r_2 = 0.99 (squares), _r_2 = 0.7 (triangles) and _r_2 = 0.5 (crosses).

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