P0580 Systems Genetics Approach to Predicting Candidate Genes from Pathways

Brian Sayre , Virginia State University, Petersburg, VA
Glenn Harris , Virginia State University, Petersburg, VA
The power of the model species approach is only fully realized, if the depth of study and information developed can be transferred to problems in other species. The objective of this project was to determine if a systems biology pathway-based approach could predict potential genes in sheep from data generated in model species. Gene data was collected from published QTL regions in cattle, mice, rats, and human. Data from QTL, microarray and SNP analyses were collected for sheep. All gene data were converted to human Entrez Gene IDs and compared to the KEGG pathway database. Selection of pathways from QTL data was based on a selection index that ensured the selected pathways were in all species and a majority of the projects overall and within species.  The common pathways identified in the model species were compared to the gene data from publications in sheep. A total of 14 out of 19 pathways identified in model species were found in either QTL or microarray projects in sheep.  Gene data from the top pathways were used to determine potential candidate genes for identification in sheep.  Comparisons of predicted data to known data sets in sheep was used to identify potential prediction models.  Similarities among species allowed the identification of candidate pathways in a non-model species. Further development of this procedure may transform the way model data is used in order to improve the ability to quickly identify potential candidate genetic markers or genes for selection.