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Genetic and genomic basis of antibody response to porcine reproductive and respiratory syndrome (PRRS) in gilts and sows

Authors :
Graham Plastow
John C. S. Harding
Jack C. M. Dekkers
Benny E. Mote
Stephen Bishop
Philip Willson
Robert Kemp
Nick V. L. Serão
Source :
Genetics Selection Evolution, Genetics Selection Evolution, BioMed Central, 2016, 48 (1), pp.51. ⟨10.1186/s12711-016-0230-0⟩, Genetics, Selection, Evolution : GSE, Serão, N V L, Kemp, R A, Mote, B E, Willson, P, Harding, J C S, Bishop, S C, Plastow, G S & Dekkers, J C M 2016, ' Genetic and genomic basis of antibody response to porcine reproductive and respiratory syndrome (PRRS) in gilts and sows ', Genetics Selection Evolution, vol. 48, no. 1, pp. 51 . https://doi.org/10.1186/s12711-016-0230-0
Publication Year :
2016
Publisher :
HAL CCSD, 2016.

Abstract

Background Our recent research showed that antibody response to porcine reproductive and respiratory syndrome (PRRS), measured as sample-to-positive (S/P) ratio, is highly heritable and has a high genetic correlation with reproductive performance during a PRRS outbreak. Two major quantitative trait loci (QTL) on Sus scrofa chromosome 7 (SSC7; QTLMHC and QTL130) accounted for ~40 % of the genetic variance for S/P. Objectives of this study were to estimate genetic parameters for PRRS S/P in gilts during acclimation, identify regions associated with S/P, and evaluate the accuracy of genomic prediction of S/P across populations with different prevalences of PRRS and using different single nucleotide polymorphism (SNP) sets. Methods Phenotypes and high-density SNP genotypes of female pigs from two datasets were used. The outbreak dataset included 607 animals from one multiplier herd, whereas the gilt acclimation (GA) dataset included data on 2364 replacement gilts from seven breeding companies placed on health-challenged farms. Genomic prediction was evaluated using GA for training and validation, and using GA for training and outbreak for validation. Predictions were based on SNPs across the genome (SNPAll), SNPs in one (SNPMHC and SNP130) or both (SNPSSC7) QTL, or SNPs outside the QTL (SNPRest). Results Heritability of S/P in the GA dataset increased with the proportion of PRRS-positive animals in the herd (from 0.28 to 0.47). Genomic prediction accuracies ranged from low to moderate. Average accuracies were highest when using only the 269 SNPs in both QTL regions (SNPSSC7, with accuracies of 0.39 and 0.31 for outbreak and GA validation datasets, respectively. Average accuracies for SNPALL, SNPMHC, SNP130, and SNPRest were, respectively, 0.26, 0.39, 0.21, and 0.05 for the outbreak, and 0.28, 0.25, 0.22, and 0.12, for the GA validation datasets. Conclusions Moderate genomic prediction accuracies can be obtained for PRRS antibody response using SNPs located within two major QTL on SSC7, while the rest of the genome showed limited predictive ability. Results were obtained using data from multiple genetic sources and farms, which further strengthens these findings. Further research is needed to validate the use of S/P ratio as an indicator trait for reproductive performance during PRRS outbreaks. Electronic supplementary material The online version of this article (doi:10.1186/s12711-016-0230-0) contains supplementary material, which is available to authorized users.

Details

Language :
English
ISSN :
0999193X and 12979686
Database :
OpenAIRE
Journal :
Genetics Selection Evolution, Genetics Selection Evolution, BioMed Central, 2016, 48 (1), pp.51. ⟨10.1186/s12711-016-0230-0⟩, Genetics, Selection, Evolution : GSE, Serão, N V L, Kemp, R A, Mote, B E, Willson, P, Harding, J C S, Bishop, S C, Plastow, G S & Dekkers, J C M 2016, ' Genetic and genomic basis of antibody response to porcine reproductive and respiratory syndrome (PRRS) in gilts and sows ', Genetics Selection Evolution, vol. 48, no. 1, pp. 51 . https://doi.org/10.1186/s12711-016-0230-0
Accession number :
edsair.doi.dedup.....73a97f56de5014bec6935aa1a8baf7b5
Full Text :
https://doi.org/10.1186/s12711-016-0230-0⟩