Genomewide association of piglet responses to infection with one of two porcine reproductive and respiratory syndrome virus isolates

• Published in: Journal of animal science Vol. 95; no. 1; pp. 16 - 38
• Main Authors: Waide, E H, Tuggle, C K, Serão, N V L, Schroyen, M, Hess, A, Rowland, R R R, Lunney, J K, Plastow, G, Dekkers, J C M
• Format: Journal Article Web Resource
• Language: English
• Published: American Society of Animal Science 01.01.2017
• Subjects: Animals; Bayes Theorem; Genetics & genetic processes; Genome; Genome-Wide Association Study; Genomics; Genotype; Génétique & processus génétiques; Life sciences; Phenotype; Porcine Reproductive and Respiratory Syndrome/genetics/virology; Porcine respiratory and reproductive syndrome virus/classification; Sciences du vivant; Swine; Viral Load
• ISSN: 0021-8812; 1525-3163; 1525-3163
• DOI: 10.2527/jas.2016.0874

Porcine reproductive and respiratory syndrome (PRRS) is a devastating disease in the swine industry. Identification of host genetic factors that enable selection for improved performance during PRRS virus (PRRSV) infection would reduce the impact of this disease on animal welfare and production efficiency. We conducted genomewide association study (GWAS) analyses of data from 13 trials of approximately 200 commercial crossbred nursery-age piglets that were experimentally infected with 1 of 2 type 2 isolates of PRRSV (NVSL 97-7985 [NVSL] and KS2006-72109 [KS06]). Phenotypes analyzed were viral load (VL) in blood during the first 21 d after infection (dpi) and weight gain (WG) from 0 to 42 dpi. We accounted for the previously identified QTL in the region on SSC4 in our models to increase power to identify additional regions. Many regions identified by single-SNP analyses were not identified using Bayes-B, but both analyses identified the same regions on SSC3 and SSC5 to be associated with VL in the KS06 trials and on SSC6 in the NVSL trials ( < 5 × 10); for WG, regions on SSC5 and SSC17 were associated in the NVSL trials ( < 3 × 10). No regions were identified with either method for WG in the KS06 trials. Except for the region on SSC4, which was associated with VL for both isolates (but only with WG for NVSL), identified regions did not overlap between the 2 PRRSV isolate data sets, despite high estimates of the genetic correlation between isolates for traits based on these data. We also identified genomic regions whose associations with VL or WG interacted with either PRRSV isolate or with genotype at the SSC4 QTL. Gene ontology (GO) annotation terms for genes located near moderately associated SNP ( < 0.003) were enriched for multiple immunologically (VL) and metabolism- (WG) related GO terms. The biological relevance of these regions suggests that, although it may increase the number of false positives, the use of single-SNP analyses and a relaxed threshold also increased the identification of true positives. In conclusion, although only the SSC4 QTL was associated with response to both PRRSV isolates, genes near associated SNP were enriched for the same GO terms across PRRSV isolates, suggesting that host responses to these 2 isolates are affected by the actions of many genes that function together in similar biological processes.