|Samac, Deborah - Debby|
Submitted to: North American Alfalfa Improvement Conference
Publication Type: Abstract only
Publication Acceptance Date: 7/29/2002
Publication Date: 7/29/2002
Citation: SAMAC, D.A., PENUELA, S., DANESH, D., YOUNG, N.D., VANDENBOSCH, K. TRANSCRIPTOME ANALYSIS OF PATHOGENIC INTERACTIONS WITH MEDICAGO TRUNCATULA. 38TH NORTH AMERICAN ALFALFA IMPROVEMENT CONFERENCE. 2002. P. 6. Interpretive Summary:
Technical Abstract: The forage legume, Medicago truncatula, is an excellent model for investigating functional genomics of plant-microbe interactions. Glass slide microarrays containing 1152 cDNAs ('kiloclone set') printed in triplicate are being used for hybridization with labeled targets derived from pathogen-infected and uninoculated leaf and root tissues. Comparison of gene expression profiles of M. truncatula "Jemalong A17" interactions with two foliar pathogens (Colletotrichum trifolii and Erysiphe pisi) and one root pathogen (Phytophthora medicaginis) were performed. Cluster analysis revealed subsets of genes that are differentially expressed across tissues and pathogens. In the C. trifolii interaction, 54 genes were up-regulated, 19 genes were up-regulated by infection with E. pisi, and 35 genes were up-regulated by P. medicaginis infection. Hierarchical clustering of pathogen-challenged tissues showed that expression profiles of pathogen-challenged Jemalong A17 with P. medicaginis and C. trifolii were more closely related than to the profile observed with E. pisi. This may reflect the strong hypersensitive reaction observed in the E. pisi-Jemalong A17 interaction. Two-dimensional clustering analysis showed that out of 48 clones representing disease defense response genes, 19 were up-regulated across all experiments. A time course experiment of M. truncatula roots challenged with P. medicaginis showed a number of differentially expressed genes at each time point. At 2 days after inoculation, with the development of the first symptoms, 52 genes were up-regulated, including most of the defense-response genes, and 26 genes were down-regulated, including many known nodulin genes. Several subgroups of unknowns were associated with defense-response genes using self-organizing maps partitioning. These novel genes will be studied further to assign putative functions related to disease response.