Next Article in Journal
Environmental Influences Measured by Epigenetic Clock and Vulnerability Components at Birth Impact Clinical ASD Heterogeneity
Next Article in Special Issue
Identification, Molecular Characterization, and Tissue Expression Profiles of Three Smad Genes from Water Buffalo (Bubalus bubalis)
Previous Article in Journal
Metagenomic Analyses of Plant Growth-Promoting and Carbon-Cycling Genes in Maize Rhizosphere Soils with Distinct Land-Use and Management Histories
Previous Article in Special Issue
A KRT71 Loss-of-Function Variant Results in Inner Root Sheath Dysplasia and Recessive Congenital Hypotrichosis of Hereford Cattle
Article

Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model

1
Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1, Canada
2
Ontario Ministry of Agriculture, Food and Rural Affairs, 6484 Wellington Road 7, Elora, ON N0B 1S0, Canada
*
Author to whom correspondence should be addressed.
Genes 2021, 12(9), 1432; https://doi.org/10.3390/genes12091432
Received: 27 July 2021 / Revised: 19 August 2021 / Accepted: 14 September 2021 / Published: 17 September 2021
(This article belongs to the Special Issue Animal Domestication and Breeding)
Selection based on scrapie genotypes could improve the genetic resistance for scrapie in sheep. However, in practice, few animals are genotyped. The objectives were to define numerical values of scrapie resistance genotypes and adjust for their non-additive genetic effect; evaluate prediction accuracy of ungenotyped animals using linear animal model; and predict and assess selection response based on estimated breeding values (EBV) of ungenotyped animals. The scrapie resistance (SR) was defined by ranking scrapie genotypes from low (0) to high (4) resistance based on genotype risk groups and was also adjusted for non-additive genetic effect of the haplotypes. Genotypes were simulated for 1,671,890 animals from pedigree. The simulated alleles were assigned to scrapie haplotypes in two scenarios of high (SRh) and low (SRl) resistance populations. A sample of 20,000 genotyped animals were used to predict ungenotyped using animal model. Prediction accuracies for ungenotyped animals for SRh and SRl were 0.60 and 0.54, and for allele content were from 0.41 to 0.71, respectively. Response to selection on SRh and SRl increased SR by 0.52 and 0.28, and on allele content from 0.13 to 0.50, respectively. In addition, the selected animals had large proportion of homozygous for the favorable haplotypes. Thus, pre-selection prior to genotyping could reduce genotyping costs for breeding programs. Using a linear animal model to predict SR makes better use of available information for the breeding programs. View Full-Text
Keywords: sheep; scrapie resistance; BLUP; selection response; prediction accuracy sheep; scrapie resistance; BLUP; selection response; prediction accuracy
Show Figures

Figure 1

MDPI and ACS Style

Boareki, M.; Schenkel, F.; Kennedy, D.; Cánovas, A. Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model. Genes 2021, 12, 1432. https://doi.org/10.3390/genes12091432

AMA Style

Boareki M, Schenkel F, Kennedy D, Cánovas A. Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model. Genes. 2021; 12(9):1432. https://doi.org/10.3390/genes12091432

Chicago/Turabian Style

Boareki, Mohammed, Flavio Schenkel, Delma Kennedy, and Angela Cánovas. 2021. "Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model" Genes 12, no. 9: 1432. https://doi.org/10.3390/genes12091432

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop