|TUGGLE, C - IOWA STATE UNIVERSITY
|WANG, Y - IOWA STATE UNIVERSITY
|COUTURE, O - IOWA STATE UNIVERSITY
|QU, L - IOWA STATE UNIVERSITY
|UTHE, J - IOWA STATE, NADC IOWA
|NETTLETON, D - IOWA STATE UNIVERSITY
|DEKKERS, J - IOWA STATE UNIVERSITY
Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 12/15/2007
Publication Date: 8/1/2008
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. 2008. Computational Integration of Structural and Functional Genomics Data Across Species to Develop Information on Porcine Inflammatory Gene Regulatory Pathway. In: Animal Genomics for Animal Health M.-H. Pinard, C. Gay, P.-P. Pastoret, B. Dodet (Eds); In the series Developments in Biologicals (Karger, Basel). 132:105-114.
Interpretive Summary: Animal genome disease researchers aim to identify genes that determine disease resistance and susceptibility. This review highlights the potential of using comparative genomic data across species, integrating structural and functional genome data, to find genes that potentially control disease resistance and susceptibility. The research team at Iowa State Univ., and ARS’s National Animal Disease Center and Beltsville Agricultural Research Center investigated the porcine gut immune response to infection using Affymetrix GeneChip microarrays and gene expression profiling. Pig data was collected from RNA prepared from mesenteric lymph node of swine infected with either the foodborne Salmonella enterica serovar Typhimurium (ST) or the swine specific S. Choleraesuis (SC) for 0, 8, 24, 48 or 504 hours post-inoculation (hpi). Extensive data analyses identified 2,365 differential expressed (DE) genes with statistical evidence between at least two time-points. Studies then focused on using comparative genomic tools, e.g., Comparative Gene Ontology analyses to identify which cell and immune systems are activated or suppressed as a result of ST or SC infections. As expected these studies revealed that a high proportion of annotated DE genes in both infections are involved in immune and defense responses. By using additional statistical tools (hierarchical clustering of expression patterns and annotations) the team identified 28% (22 of 80) of the genes upregulated from 8-24 hpi are known cellular targets of the master regulator gene, NFkB. These expression results were affirmed by further molecular tests [real-time Quantitative Polymerase Chain Reaction (QPCR) analyses] for 90% of tested genes. The analyses then compared the sequences of human genes that were like (orthologous to) the DE porcine genes. Use of another genome program (TFM-Explorer) led to the identification of a set of 71 pig gene promoters that appeared to be significantly over-representated with potential NFkB DNA-binding motifs. Of these 71 genes, 22 were known from previous data to be NFkB target genes; the team now hypothesizes that the remaining 49 genes are actually un-recognized NFkB targets. Thus we have determined that there are several transcription factor motifs that potentially lead to regulation of the porcine DE genes. By integrating these results we will be able to verify putative target genes that are differentially expressed in ST and SC infections. Integration of these results and verification of putative target genes will increase our understanding of the porcine response pathways responding to bacterial infection and of genes that potentially control disease resistance and susceptibility.
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. This research will provide important clues and increase our understanding of the porcine response pathways responding to bacterial infection.