Whole blood response of Pigs to infection with Porcine Reproductive and Respiratory Syndrome Virus (PRRSV)
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ABSTRACT:
ORGANISM(S): Sus scrofa
PROVIDER: GSE41144 | GEO | 2012/09/26
SECONDARY ACCESSION(S): PRJNA175915
REPOSITORIES: GEO
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Project description:Porcine reproductive and respiratory disease (PRRS) is the most important disease in swine industry worldwide. However, strategies such as vaccination and good biosecurity are not consistently successful to eliminate PRRSV. Although some gene expression pathways have been explored recently, host molecular pathways blocked by PRRSV and the protective immune response expressed in pigs resistant to PRRSV are largely unknown. In order to answer these questions, we herein characterize changes in blood gene expression in pigs responding differentially to infection with a well characterized type 2 (North American) PRRSV isolate. Samples are those collected through the PRRS Host Genetics Consortium (PHGC). Samples were those from Tempus tube collected blood of PHGC pigs selected from four response groups according to their serum viral load (0-21 days post infection) and weight gain (0-42 dpi) and characterized as low vs. high viral load and low vs high weight gain . block reference design was used to accommodate samples from 4 treatment groups.
2012-09-26 | E-GEOD-41144 | biostudies-arrayexpress
Project description:One hundred Hampshire by Duroc crossbred pigs (HD) and 100 NE Index line pigs (I) were infected with porcine reproductive and respiratory syndrome virus (PRRSV) and evaluated for resistance/susceptibility. Controls (100/line) were uninfected littermates to infected pigs. Viremia (V), weight change (WTΔ), and rectal temperature at 0, 4, 7, and 14 days post-infection (dpi) were recorded. Lung, bronchial lymph node (BLN), and blood tissue were collected at necropsy (14 dpi). Infected pigs were classified as low or high responders to PRRSV based on the first principal component (PC) from principal component analyses of all variables. Low responders to PRRSV (low PRRSV burden) and their uninfected littermates were assigned to low (L) class. High responders to PRRSV (high PRRSV burden) and their uninfected littermates were assigned to high (H) class. Infected pigs in the L-class had high WTΔ, low V, and few lung lesions; H-class pigs had low WTΔ, high V, and many lung lesions. RNA was extracted from lung and BLN tissue of the seven highest and seven lowest responders per line and from each of their control littermates. A control reference design was used and cDNA from each reference sample tissue was prepared from pooled RNA extracted from two control pigs from each line whose infected littermates had a PC value of 0. Design variables in data analyses were line (I vs HD), class (H vs L), treatment (infected vs uninfected controls), and slide/pig as error.
2008-12-31 | GSE12194 | GEO
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
2015-06-04 | E-GEOD-69513 | biostudies-arrayexpress
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 7 days post infection
2015-06-04 | E-GEOD-69514 | biostudies-arrayexpress
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.
2015-06-04 | GSE69514 | GEO
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.
2015-06-04 | GSE69513 | GEO
Project description:Porcine reproductive and respiratory syndrome (PRRS), caused by PRRS virus (PRRSV), is the most economically important disease in pig populations. Lung damage is one major pathological condition following PRRSV infection, often leading to animal death. In vivo, PRRSV productive infection occurs predominately in alveolar macrophages of the lung. Here, transcriptome profiling of pulmonary alveolar macrophages (PAMs) from Tongcheng piglets pre- and post- infection of highly pathogenic PRRSV has been performed using porcine Affymetrix GeneChip. All animal procedures were performed according to protocols approved by the Biological Studies Animal Care and Use Committee of Hubei Province, China. Piglets used in this study were free from PRRSV, pseudorabies virus (PRV) and porcine circovirus type 2 (PCV2) determined by ELISA test for serum antibodies. Twelve of 5-week-old boars were obtained from three litters (four piglets per litter), and raised in pathogen-free facilities. In order to perform a paired experiment, every four full-sib individuals were divided equally into two groups: one infected group and one control group with 6 piglets in each group. The infected groups were challenged with PRRSV-Wuh2 (3 ml/15 kg, 10-5 TCID50/ml) by intramuscular inoculation. Slaughters were carried out at 0 days post-infection (dpi) for uninfected (control) groups, and at 5 or 7 dpi for infected groups. The PAMs for microarray analysis were collected by bronchoalveolar lavage from three uninfected pigs and three infected pigs at 5 dpi. Total of 6 microarrays have been hybridized in this experiment.
2012-06-30 | E-GEOD-22782 | biostudies-arrayexpress
Project description:The aim of this study was to acquire a better understanding of porcine reproductive and respiratory syndrome (PRRS) disease through a deeper knowledge of gene expression changes that occur in pulmonary lymph nodes by comparing PRRS virus (PRRSV), porcine circovirus type 2 (PCV-2), and swine influenza virus (IAV-S) infections. The PRRSV, IAV-S and PCV-2 viral infections followed a clinical course in these domestic pigs typical of experimental infection of young pigs with these viruses. PRRSV isolate SDSU-73 was pathogenic in this study inducing fever, anorexia, listlessness, and dyspnea.
2018-03-03 | GSE111378 | GEO
Project description:Porcine reproductive and respiratory disease (PRRS) is the most important disease in swine industry worldwide. However, strategies such as vaccination and good biosecurity are not consistently successful to eliminate PRRSV. Though some interesting pathways have been tentatively examined recently, host molecular pathways utilized by PRRSV and the protective immune responses in resistant to PRRSV are largely unknown. In order to answer these questions, we herein characterize changes in global gene expressions in multiple tissues [tonsil, tracheobronchial lymph nodes (TBLN), Cranial lung (CR Lung), and distal lung (D Lung)] in response to PRRSV of high and low virulence. Both vaccinated and unvaccinated pigs are used for this study. Based on Ingenuity Pathway Analysis (IPA), molecule bases of some “black boxes” underlying immune responses are further identified. Our results indicate that cross talks among these pathways and immune balances/competition between host and virus are always happened during the pathogenesis of PRRS. connected loop design was used to accommodate samples from 4 treatment groups.
2011-01-15 | E-GEOD-26642 | biostudies-arrayexpress
Project description:Porcine reproductive and respiratory syndrome (PRRS) has been one of the most economically important diseases affecting swine industry worldwide and causes great economic losses each year. PRRS virus (PRRSV) replicates mainly in porcine alveolar macrophages (PAMs) and dendritic cells (DCs) and develops persistent infections, antibody-dependent enhancement (ADE), interstitial pneumonia and immunosuppression. But the molecular mechanisms of PRRSV infection still are poorly understood. Here we reported on the first genome-wide host transcriptional responses to normal PRRSV (N-PRRSV) infection using Solexa/Illumina’s digital gene expression (DGE) system, a tag-based high-throughput transcriptome sequencing method, and analyzed systematically the relationship between pulmonary gene expression profiles after N-PRRSV infection and infection pathology. Our results indicated that N-PRRSV appeared to utilize multiple strategies for its long surviral in infected pigs, including subverting host innate immune response, hijacking host lipid metabolism, inducing an anti-apoptotic and anti-inflammatory state as well as developing ADE. Virus-induced pro-inflammatory cytokines, chemokines, adhesion molecules and inflammatory enzymes production and inflammatory cells, antibodies, complement activation were likely to result in the development of inflammatory responses during N-PRRSV infection processing. N-PRRSV-induced immunosuppression might be mediated by apoptosis of infected cells, which caused depletion of immune cells and induced an anti-inflammatory cytokine response in which they were unable to eradicate the primary infection or developed secondary infection. Our systems analysis will benefit for better understanding the molecular pathogenesis of N-PRRSV infection, developing novel antiviral therapies and identifying genetic components for swine resistance/susceptibility to PRRS.
2010-12-05 | GSE19970 | GEO