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Antibody Response During a PRRS Outbreak can be Predicted Using High-Density SNP Genotypes Nick V.L. Serão 1 *, R.A. Kemp 2, B.E. Mote 3, J.C.S. Harding.

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Presentation on theme: "Antibody Response During a PRRS Outbreak can be Predicted Using High-Density SNP Genotypes Nick V.L. Serão 1 *, R.A. Kemp 2, B.E. Mote 3, J.C.S. Harding."— Presentation transcript:

1 Antibody Response During a PRRS Outbreak can be Predicted Using High-Density SNP Genotypes Nick V.L. Serão 1 *, R.A. Kemp 2, B.E. Mote 3, J.C.S. Harding 4, P. Willson 5, S.C. Bishop 6, G.S. Plastow 7, J.C.M. Dekkers 1 G.S. Plastow 7, J.C.M. Dekkers 1 1 Department of Animal Science, Iowa State University, Ames, IA, 2 Genesus Inc., Oakville, Canada, 3 Fast Genetics, Saskatoon, Canada, 4 Department of Large Animal Clinical Sciences, University of Saskatchewan, Saskatoon, Canada, 5 Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Canada, 6 The Roslin Institute and R(D)SVS, University of Edinburgh, Scotland, 7 Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada Nick V.L. Serão 1 *, R.A. Kemp 2, B.E. Mote 3, J.C.S. Harding 4, P. Willson 5, S.C. Bishop 6, G.S. Plastow 7, J.C.M. Dekkers 1 G.S. Plastow 7, J.C.M. Dekkers 1 1 Department of Animal Science, Iowa State University, Ames, IA, 2 Genesus Inc., Oakville, Canada, 3 Fast Genetics, Saskatoon, Canada, 4 Department of Large Animal Clinical Sciences, University of Saskatchewan, Saskatoon, Canada, 5 Canadian Centre for Health and Safety in Agriculture, University of Saskatchewan, Saskatoon, Canada, 6 The Roslin Institute and R(D)SVS, University of Edinburgh, Scotland, 7 Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Canada Motivation PRRS in breeding herds costs over US$ 300 million in the US (Holtkamp et al., 2013). Serão et al. (2014) reported that antibody response ( Ab ) during a PRRS outbreak (measured as Sample-to- positive [ S/P ] ratio): has high heritability (0.45) has high positive genetic correlation with favorable reproductive performance (0.73 with number of piglets born alive) is mainly controlled by two major quantitative trait loci ( QTL ) on chromosome 7 ( Figure 1 ) One of these QTL encompasses the Major Histocompatibility Complex ( MHC ) region; the other is located at ~130 Mb. Objective Evaluate the use of high-density Single Nucleotide Polymorphism ( SNP ) genotypes to predict PRRS Ab response of sows during a PRRS outbreak. SSC Mb 16 % SSC Mb 25 % Major Histocompatibility Complex Figure 1. Manhattan plot from the genome-wide association study for sample-to-positive (S/P) ratio measured at ~46 days in a PRRS outbreak herd. Each data point represents a 1-Mb SNP window (Serão et al. 2014). Materials and Methods Training data set: 1,648 F1 sows (Landrace x Large White): from 17 multiplier herds with high-health status, 6 genetic sources and introduced into 22 commercial farms with historical cases of natural disease challenges; Blood samples collected 40.1±14 days after entry at the farm; Validation data set: PRRS outbreak data on 580 purebred Landrace sows from a commercial multiplier herd (Serao et al. 2014). Blood samples were used to measure S/P ratio and to genotype 38,678 SNPs. Principal component analysis was performed on SNP genotypes to assess population structure (Figure 2). The training dataset was used to estimate the effects of SNPs on S/P ratio using the Bayes-B method in five scenarios: using all SNPs across the genome (ALL_SNP) only SNPs in the two QTL (SSC7_SNP) only SNPs in the MHC QTL (MHC_SNP) only SNPs in the 130 Mb QTL (130Mb_SNP) all SNPs except those located in the two QTL regions (Not7_SNP). Conclusions These results demonstrate that antibody response during a PRRS outbreak can be predicted using genetic markers in the two QTL on SSC7. In addition, the high accuracy of MHC_SNP suggests that the SNP effect estimates are consistent across different Landrace x Large White populations. References Holtkamp et al (2013) Journal of Swine Health and Production, 21: Serão et al. (2014) Journal of Animal Science, 92(7): Results Genomic prediction accuracies are presented in Figure 3. Moderate to high accuracies were observed for all scenarios except Not7_SNP (0.15), indicating that the rest of the genome have little predictive ability for S/P ratio. The highest accuracy was for SSC7_SNP (0.63). Slightly greater accuracy was obtained with MHC_SNP (0.55) compared to using all SNPs (0.49) Lastly, 130Mb_SNP had a moderate accuracy of Acknowledgement Financial support from Genome Canada, the Canadian Swine Health Board, and PigGen Canada is appreciated Figure 2. Plot of the first two principal components (PC), using all genotype data (38,678 SNPs). The validation data set is well discriminated from the validation data set by PC1 and PC2. The number within parenthesis represents the percentage of the total variance accounted for by each PC. Figure 3. Genomic prediction accuracy of Sample-to-Positive (S/P) ratio across the five training scenarios. The value on within parenthesis represents the correlation ( r ) between predicted and S/P ratio pre-adjusted for fixed effects. The value on top of each bar represents the accuracy, which was calculated as r divided by ssqaure-root of heritability. (r = 0.33) (r = 0.42) (r = 0.37) (r = 0.20) (r = 0.10) Number of SNPs: 38, ,489


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