Location: Animal Parasitic Diseases LaboratoryTitle: Characterizing differential individual response to Porcine Reproductive and Respiratory Virus infection through statistical and functional analysis of gene expression
|ARCEO, MARIA - Michigan State University|
|ERNST, CATHERINE - Michigan State University|
|RANEY, NANCY - Michigan State University|
|HUANG, TINGHUA - Iowa State University|
|TUGGLE, CHRISTOPHER - Iowa State University|
|ROWLAND, RAYMOND - Kansas State University|
|STEIBEL, JUAN - Michigan State University|
Submitted to: Frontiers in Livestock Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/23/2012
Publication Date: 1/16/2013
Publication URL: http://handle.nal.usda.gov/10113/56721
Citation: Arceo, M., Ernst, C., Lunney, J.K., Choi, I., Raney, N., Huang, T., Tuggle, C.K., Rowland, R.R., Steibel, J. 2013. Characterizing differential individual response to Porcine Reproductive and Respiratory Virus infection through statistical and functional analysis of gene expression. Frontiers in Livestock Genomics. 3:321.
Interpretive Summary: Porcine Respiratory and Reproductive Syndrome (PRRS) is the most economically important disease of pigs worldwide. Our research is aimed at determining whether pigs can be identified that exhibit improved resistance to PRRS virus (PRRSV) infection and good growth despite the infection. The current studies focus on the earliest timepoints, 0, 4 and 7 days post PRRSV infection (dpi). We prepared RNA from whole blood Tempus tube samples from 12 pigs, labeled the cDNA with dyes and hybridized them to a pig specific microarray. Statistical analyses focused on evaluating differentially expressed (DE) transcripts that correlate with significant interactions of weight gain and serum viral level. We identified 491 significant comparisons (FDR = 10%) across all dpi and phenotypic groups. At four and seven days post infection, network and functional analyses were performed to assess if immune related gene sets were enriched for genes differentially expressed across the four phenotypic groups. Overall, our findings of DE genes in blood cells are in agreement with previous reports on PRRSV specific target tissues and cells, such as lung and lung macrophages. Our results verify the importance of our study for using the more accessible blood sampling to reveal the complexity of host response to PRRSV infection. We expect that our more detailed studies will generate further questions on the role of these genes in PRRS responses. We hope to identify unique mechanisms and pathways that PRRS resistant pigs use to overcome the viral infection. Combined with our basic genomic studies we hope to identify informative single-nucleotide polymorphisms (SNPs) that correlate with viral resistance traits. Finally, our global differential expression results were used as pilot data to inform design of future time-course transcription profiling experiments. We evaluated different scenarios of sample sizes and sampling time-points for combinations given a fixed total sampling effort. We concluded the best scenario for future studies consists of sampling at 4 and 7 DPI using about 30 pigs per phenotypic group. Our preliminary results have already identified differential gene expression, molecular networks and biological functions affecting the four phenotypic groups of pigs and the influence of PRRSV infection. Finally, due to the flexible experimental design utilized in this study, the resulting dataset can be merged with future data for increasingly powerful and precise inferences on response to PRRSV infection.
Technical Abstract: We evaluated differences in gene expression in pigs from the Porcine Reproductive and Respiratory Syndrome (PPRS) Host Genetics Consortium initiative showing a range of responses to PRRS virus (PRRSV) infection. Pigs were allocated into four phenotypic groups according to their serum viral level and weight gain. RNA was obtained from blood at seven different days post infection (0, 4, 7, 11, 14, 28, and 42) and hybridized to the 70-mer 20K Pigoligoarray. We used a blocked reference design for the microarray experiment. This allowed us to account for individual biological variation in gene expression, and to assess baseline effects before infection (day zero post infection). Additionally, this design has the flexibility of incorporating future data for differential expression analysis. We focused on evaluating transcripts showing significant interaction of weight gain and serum viral level. We identified 491 significant comparisons (FDR = 10%) across all days post-infection and phenotypic groups and we corroborated the overall trend in direction and level of expression (measured as fold-change) at four days post infection using qPCR (r = 0.91, p = 0.0007). At four and seven days post infection, network and functional analyses were performed to assess if immune related gene sets were enriched for genes differentially expressed across four phenotypic groups. We identified cell death function as being significantly associated (FDR = 5%) with several networks enriched for differentially expressed transcripts. We found the genes interferon, type 1, cluster (IFNA), major histocompatibility complex, class II, DQ alpha 1 (SLA-DQA1), and major histocompatibility complex, class II, DR alpha (SLA-DRA) to be differentially expressed (p = 0.05) between phenotypic groups. Finally, we performed a power analysis to estimate sample size and sampling time-points for future experiments. We concluded the best scenario for investigation of early response to PRRSV infection consists of sampling at 4 and 7 days post-infection using about 30 pigs per phenotypic group, and that a minimum of 20 pigs per group are needed for controlling type I and type II error rate at desirable levels.