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Title: Computational Integration Of Structural And Functional Genomics Data Across Species To Develop Porcine Inflammatory Gene Regulatory Pathway Information

Author
item TUGGLE, C - IOWA STATE U, AMES
item WANG, Y - IOWA STATE U, AMES
item COUTURE, O - IOWA STATE U. AMES
item QU, L - IOWA STATE U, AMES
item UTHE, J - IOWA STATE U, AMES
item Kuhar, Daniel
item Lunney, Joan
item NETTLETON, D - IOWA STATE U, AMES
item DEKKERS, J - IOWA STATE U, AMES
item Bearson, Shawn
item BEARSON,, S M - NADC AMES, IOWA

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 8/15/2007
Publication Date: 10/22/2007
Citation: Tuggle, C.K., Wang, Y.F., Couture, O.P., Qu, L., Uthe, J.J., Kuhar, D.J., Lunney, J.K., Nettleton, D., Dekkers, J.C., Bearson, S.M., Bearson,, S.D. 2007. Computational Integration Of Structural And Functional Genomics Data Across Species To Develop Porcine Inflammatory Gene Regulatory Pathway Information. Proceedings International Symposium on Animal Genomics for Animal Health,OIE, Paris, France, October 2007.p 33.

Interpretive Summary:

Technical Abstract: Comparative integration of structural and functional genomic data across species holds great promise in finding genes controlling disease resistance. We are investigating the porcine gut immune response to infection through gene expression profiling. We have collected porcine Affymetrix GeneChip data from RNA prepared from mesenteric lymph node of swine infected with either Salmonella enterica serovar Typhimurium (ST) or S. Choleraesuis (SC) for 0, 8, 24, 48 or 504 hours post-inoculation (hpi). In total, we identified 2,365 genes with statistical evidence for differential expression (DE; p < 0.01, q < 0.26, fold-change > 2) between at least two time-points. Comparative Gene Ontology analyses revealed that a high proportion of annotated DE genes in both infections are involved in immune and defense responses. Hierarchical clustering of expression patterns and annotations showed that 28% (22 of 80) of the genes upregulated from 8-24 hpi are known NFkB targets. Real-time QPCR analyses confirmed these patterns for 90% of tested genes. We then collected the sequences of human genes orthologous to the DE genes and used TFM-Explorer to identify a set of 71 gene promoters with significant over-representation of NFkB DNA-binding motifs. Twenty-two known NFkB target genes are in this list; we hypothesize the remaining 49 genes are un-recognized NFkB targets. We determined that motifs for several additional transcription factors are over-represented at human orthologous promoters for these DE genes. Integration of these results and verification of putative target genes will increase our understanding of the porcine response pathways responding to bacterial infection.