Project description:Cell lines derived from Chlorocebus sabaeus kidney were infected with an isolate of PRRSV-1 or PRRSV-2 and RNASeq was performed (this entry) in parallel with ribosome profiling (see related accession numbers). These RNASeq datasets provide information on the transcriptome of PRRSV-infected cells and were used to detect novel viral transcripts and perform differential gene expression analysis on host transcripts. For the PRRSV-1 experiments, MA-104 cells were infected with an isolate based on the Porcilis vaccine strain (KJ127878.1 but with several accumulated mutations, see associated publication) and harvested at 8 hpi after pre-treatment with cycloheximide (CHX). For the PRRSV-2 experiments, MARC-145 cells were infected with SD95-21 PRRSV (KC469618.1), and a mutant thereof (KO2). One group of samples was harvested at 9 hpi after pre-treatment with CHX, and another group of samples was harvested at 3, 6, 9 and 12 hpi by flash-freezing without CHX pre-treatment. For all samples, RNA was extracted, ribosomal RNA was removed using Illumina's RiboZero kit, and remaining RNA was gel purified to select fragments 25-34 nt (PRRSV-1-infected samples, CHX-pre-treated PRRSV-2- or mock-infected samples, and non-CHX-pre-treated PRRSV-2- or mock-infected 9 hpi replicate one samples) or ~50 nt long (all other samples). Fragments were cloned into adapters based on the TruSeq small RNA adapters. For all PRRSV-2-infected (or mock-infected) libraries, adapters with an additional seven random nucleotides at the 5′-end of the 3′-adapter and the 3′-end of the 5′-adapter were used. For PRRSV-1 replicate one, no random nucleotides were present on the adapters, and for PRRSV-1 replicate two, 14 random nucleotides were present at the 5′-end of the 3′-adapter. Libraries were sequenced on the Illumina NextSeq 500 platform as a single-end run. For one NextSeq run, some potyvirus amplicons, indexed using TruSeq small RNA indices 1-48, was spiked in to the pool directly before sequencing, therefore some libraries (noCHX_RNA_9hpi_KO2_1, noCHX_RNA_9hpi_KO2_2, noCHX_RNA_9hpi_mock_1, noCHX_RNA_9hpi_mock_2, noCHX_RNA_9hpi_WT_1, noCHX_RNA_9hpi_WT_2) have a small proportion of potyvirus reads, but this does not represent co-infection in the biological sample and does not affect the conclusions of the study. Note that sample nomeclature (including replicate numbers) is consistent between this and the two related accessions, and RiboSeq libraries are matched with RNASeq libraries, which were prepared from the same lysate.

Project description:Cell lines derived from Chlorocebus sabaeus kidney were infected with an isolate of PRRSV-1 or PRRSV-2 and ribosome profiling was performed (this entry) in parallel with RNASeq (see related accession number). These datasets were used to analyse the viral and host translatome, frameshifting on the viral genome, and putative frameshift-related ribosome pausing events. For the PRRSV-1 experiments, MA-104 cells were infected with an isolate based on the Porcilis vaccine strain (KJ127878.1 but with several accumulated mutations, see associated publication) and harvested at 8 hpi after pre-treatment with cycloheximide (CHX). For the PRRSV-2 experiments, MARC-145 cells were infected with SD95-21 PRRSV (KC469618.1), and a mutant thereof (KO2). One group of samples was harvested at 9 hpi after pre-treatment with CHX, and another group of samples was harvested at 3, 6, 9 and 12 hpi by flash-freezing without CHX pre-treatment. For all samples, RNase I treatment was carried out, following which ribosomes and enclosed RNA were isolated by centrifugation through a sucrose cushion. RNA was extracted, ribosomal RNA was removed using Illumina's RiboZero kit, and remaining RNA was gel purified to select fragments 25-34 nt (PRRSV-1-infected samples, CHX-pre-treated PRRSV-2- or mock-infected samples, and non-CHX-pre-treated PRRSV-2- or mock-infected 9 hpi replicate one samples) or 19-34 nt long (all other samples). Fragments were cloned into adapters based on the TruSeq small RNA adapters. For all PRRSV-2-infected (or mock-infected) libraries, adapters with an additional seven random nucleotides at the 5′-end of the 3′-adapter and the 3′-end of the 5′-adapter were used. For PRRSV-1 replicate one, no random nucleotides were present on the adapters, and for PRRSV-1 replicate two, 14 random nucleotides were present at the 5′-end of the 3′-adapter. Libraries were sequenced on the Illumina NextSeq 500 platform as a single-end run. Non-CHX-pre-treated PRRSV-2-infected 9 hpi replicate two libraries were uploaded under a separate accession number due to differences in the size selection and sequencing protocol - see associated paired-end entry. Note that sample nomeclature (including replicate numbers) is consistent between this and the two related accessions, and RiboSeq libraries are matched with RNASeq libraries, which were prepared from the same lysate. The noCHX_Ribo_9hpi_mock_3 library is deliberately absent as this was a poor quality library.

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. three timepoints from 100 animals are hibridized following a blocked reference design; Blood gene expression of pigs 7 days post infection

Dataset Information

Transcriptional immune response of PRRSV-infected porcine dendritic cells and monocytes to Streptococcus suis infection

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