Pig genetic factors influencing response to PRRSV infection

Comparison of host genetic factors influencing pig response to infection with two North American isolates of porcine reproductive and respiratory syndrome virus

By: Hess, Andrew S.; Islam, Zeenath; Hess, Melanie K.; et al.

GENETICS SELECTION EVOLUTION   Volume: 48     Article Number: 43   Published: JUN 20 2016

Background: Porcine reproductive and respiratory syndrome (PRRS) is one of the most important swine diseases in the world and genetic selection of pigs for increased resistance to PRRS is an attractive method to improve the health status of the swine herd. This study compared phenotypic and genetic responses to infection with one of two genetically distinct type 2 PRRS virus (PRRSV) isolates: NVSL-97-7895 (NVSL) and KS-2006-72109 (KS06), and evaluated whether the single nucleotide polymorphism (SNP) WUR10000125 (WUR) on chromosome 4 that was associated with viral load and weight gain under infection with NVSL also has an effect on response to infection across North American PRRSV isolates. Wood's lactation curve was fitted to repeated viremia measurements to derive five curve characteristics that were evaluated.

Results: Infection with NVSL was characterized by reaching a 14 +/- 2 % higher peak viremia (PV) 2.5 +/- 0.6 days earlier (time to peak; TP) than KS06, followed by 36 +/- 1 % faster virus clearance, which occurred 3.9 +/- 0.7 days sooner. Weight gain from 0 to 42 days post-infection (WG) tended to be higher under infection with KS06 than NVSL (3.7 +/- 1.5 kg). Estimates of heritability were moderate for both PRRSV isolates for viral load from 0 to 21 days post-infection (VL) (NVSL: 0.31 +/- 0.06; KS06: 0.51 +/- 0.09) and WG (NVSL: 0.33 +/- 0.06; KS06: 0.31 +/- 0.09). Strong negative genetic correlations were observed between VL and WG for both NVSL (-0.74 +/- 0.10) and KS06 (-0.52 +/- 0.17) infected pigs. Pigs with genotype AB at the WUR SNP had a more desirable phenotype than AA pigs for all traits under infection with NVSL, but only for VL and PV with KS06; effects on other traits were smaller and not significantly different from zero (P > 0.05). Genetic correlations of host response between isolates were strong for VL, WG and PV. Accounting for WUR genotype had little impact on these correlations, suggesting that response to PRRSV infection has a substantial polygenic component that is common between these two isolates.

Conclusions: These results suggest that the KS06 PRRSV isolate is less virulent than NVSL but that genetic selection for increased resistance to either of these genetically distinct isolates is expected to increase resistance to the other isolate.

======================================

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

By: Serao, Nick V. L.; Kemp, Robert A.; Mote, Benny E.; et al.

GENETICS SELECTION EVOLUTION   Volume: 48     Article Number: 51   Published: JUL 14 2016

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; QTL(MHC) and QTL(130)) accounted for similar to 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.