Project description:The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so, additionally, the effect of the WUR10000125 (WUR) genotype was examined. Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups. three timepoints from 100 animals are hibridized following a blocked reference design; Blood gene expression of pigs 4 days post infection

Project description:The presence of variability in the response of pigs to Porcine Reproductive and Respiratory Syndrome virus (PRRSv) infection, and recent demonstration of significant genetic control of such responses, leads us to believe that selection towards more disease resistant pigs could be a valid strategy to reduce its economic impact on the swine industry. To find underlying molecular differences in PRRS susceptible versus more resistant pigs, 100 animals with extremely different growth rates and viremia levels after PRRSv infection were selected from a total of 600 infected pigs. A microarray experiment was conducted on whole blood RNA samples taken at 0, 4 and 7 days post infection (dpi) from these pigs. From these data, we examined associations of gene expression with weight gain and viral load phenotypes. The single nucleotide polymorphism (SNP) marker WUR10000125 (WUR) on the porcine 60K SNP chip was shown to be associated with viral load and weight gain after PRRSv infection, and so, additionally, the effect of the WUR10000125 (WUR) genotype was examined. Limited information was obtained through linear modeling of blood gene differential expression (DE) that contrasted pigs with extreme phenotypes, for growth or viral load or between animals with different WUR genotype. However, using network-based approaches, molecular pathway differences between extreme phenotypic classes could be identified. Several gene clusters of interest were found when Weighted Gene Co-expression Network Analysis (WGCNA) was applied to 4dpi contrasted with 0dpi data. The expression pattern of one such cluster of genes correlated with weight gain and WUR genotype, contained numerous immune response genes such as cytokines, chemokines, interferon type I stimulated genes, apoptotic genes and genes regulating complement activation. In addition, Partial Correlation and Information Theory (PCIT) identified differentially hubbed (DH) genes between the phenotypically divergent groups. GO enrichment revealed that the target genes of these DH genes are enriched in adaptive immune pathways. There are molecular differences in blood RNA patterns between pigs with extreme phenotypes or with a different WUR genotype in early responses to PRRSv infection, though they can be quite subtle and more difficult to discover with conventional DE expression analyses. Co-expression analyses such as WGCNA and PCIT can be used to reveal network differences between such extreme response groups.

Project description:Porcine reproductive and respiratory syndrome caused by porcine reproductive and respiratory syndrome virus (PRRSV) is an infectious disease characterized by severe reproductive deficiency in pregnant sows, respiratory symptoms in piglets, and high mortality. In this study, we employed Affymetrix microarray chip technology to compare the gene expression profiles of lung tissue samples from Dapulian (DPL) pigs (a Chinese indigenous pig breed) and Duroc×Landrace×Yorkshire (DLY) pigs after infection with PRRSV. During infection with PRRSV, the DLY pigs exhibited the range of clinical features that typify the disease, while the DPL pigs exhibited only mild signs of the disease. The percentage of CD8+ T cells in the DPL pigs was significantly higher than that in the DLY pigs at 21 days post-infection (dpi) (p< 0.05). Interleukin (IL) 1 beta (IL-1β) and IL-2 levels showed significant differences between the DPL and DLY pigs at 0 and 7 dpi (p< 0.01). For IL-10, the DLY pigs had significantly higher values than the DPL pigs at 0 and 7 dpi (p< 0.01). Significant differences were apparent between the DPL and DLY pigs in terms of their tumor necrosis factor-alpha (TNF-α) and interferon (IFN)-gamma (IFN-γ) levels at 0 and 7 dpi (p< 0.01). Microarray data revealed 16 differentially expressed genes in the lung tissue samples from the DLY and DPL pigs (q≤5%), of which LOC100516029 and LOC100523005 were up-regulated in the PRRSV-infected DPL pigs, while the other 14 genes were down-regulated in the PRRSV-infected DPL pigs compared with the PRRSV-infected DLY pigs. The expression levels of 10 of the 16 genes, namely CCDC84, C6ORF52, THYMOSIN, PRVE, HSPCB, CYP2J2, AMPD3, TOR1AIP2, PTGES3, and ACOX3, were validated by real-time quantitative RT-PCR. This study provides a platform for further investigation of the molecular mechanisms underlying the differential immune responses to PRRSV infection in different breeds or lines of pig. We investigated the response of lung tissues from Dapulian (DPL) pigs (a Chinese indigenous pig breed) and Duroc×Landrace×Yorkshire (DLY) pigs infected with porcine reproductive and respiratory syndrome virus (strain JXA1) by using the Affymetrix Porcine Genome Array. Sixteen healthy 30-day-old weaned DPL pigs were selected from the Jiaxiang Dapulian farm, Jining City, China, and 15 healthy 30-day-old weaned DLY pigs were obtained from a commercial farm with high standards of animal health. These pigs were free from PRRSV, porcine circovirus type 2 (PCV2), pseudorabies virus (PRV), and classical swine fever virus (CSFV) as determined by ELISA tests for serum antibodies; the absence of PRRSV was also confirmed by real-time quantitative reverse transcription PCR (qRT-PCR). Pigs were randomly assigned into two groups and reared in separate places: the PRRSV-infected group consisted of 11 DPL and 10 DLY pigs, and the control group consisted of five DPL and five DLY pigs. Infections in the pigs proceeded via inoculation with 2 ml of a viral suspension of PRRSV (at a tissue culture infectious dose of 105) by dripping the solution into the nasal cavity of each pig. The control group was treated with an identical volume of PBS by the same method. Rectal temperatures and clinical examinations on the pigs were recorded daily during the experiment. Anticoagulant-treated blood and untreated blood samples were collected separately at 0, 7, 14, and 21 days post-infection (dpi) from the infected and control groups for assaying CD4+, CD8+, cytokine (interleukin (IL) 1 beta (IL-1β), IL-2, IL-10, interferon (IFN)-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and immunoglobulin G (IgG) protein levels. Lung samples for microarray analysis and real-time qRT-PCR analysis were collected from six infected DLY and DPL pigs (three pigs for each breed) immediately post-slaughter at 28 dpi. Total RNA was isolated from lung tissue samples and purified using an RNeasy Mini kit according to the manufacturer’s protocol. RNA was prepared using the GeneChip (AFF-900623) one cycle target for the labeling and control reagents, and the labeled RNA was hybridized in an Affymetrix Hybridization Oven 640 for sequencing.

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Whole blood microarray analysis of pigs showing extreme phenotypes after a porcine reproductive and respiratory syndrome virus infection [7 dpi]

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