Start Date: Jan 01, 2009
End Date: Dec 31, 2012
The assembled team has expertise and recent experience in collecting and analyzing porcine transcriptional profiling data, as well as in developing computational regulatory networks. We will propose to integrate and extend these datasets to specifically build a database containing transcriptional and regulatory factor-chromatin binding data of the inflammatory response to pathogen challenge. We will use the most comprehensive approaches possible, including the Affymetrix Porcine GeneChip' and/or pig long oligo arrays for RNA work, and chromatin immunoprecipitation methods for selected transcription factors to develop regulatory network data. These data will then be analyzed using several computational approaches to find genes and develop an understanding of regulatory networks responsible for differences in outcome after infection, and this new information will be applied to find predictors for not only which swine are more resistant to Salmonella infection and shedding but also optimal health traits. We believe this approach will be successful in both establishing molecular measures of health and disease, predicting Salmonella resistant versus susceptible pigs, and identifying the most promising targets for improving animal health and growth in challenging environments.