Transcript Profiling in Host - Pathogen Interactions - Wise Laboratory
Using genomic technologies, it is now possible to address research hypotheses in the context of entire developmental or biochemical pathways, gene networks,and chromosomal location of relevant genes and their inferred evolutionary history. Interrogation of an entire transcriptome under a variety of experimental and field conditions has lead to new insights into previously undescribed phenomena. In the area of plant-pathogen interactions, transcript profiling has provided unparalleled perception into the mechanisms underlying gene-for-gene resistance and basal defense, host vs. non-host resistance, biotrophy vs. necrotrophy, or pathogenicity of vascular vs. non-vascular pathogens, among many others. This has facilitated a system-wide approach to unifying themes in the interactions of hosts and pathogens as well as unique features of different pathosystems
Dissection of coexpression networks in barleypowdery mildew interactions: a multi-dimensional approach to understanding parasitism by obligate biotrophs.
Regulation of gene expression in barley-powdery mildew interactions influences the establishment of fungal biotrophy and the development of host resistance. To identify global expression responses to the powdery mildew fungus, Blumeria graminis f. sp. hordei, 468 Barley1 GeneChips were used to profile the expression of 21,439 genes in inoculated vs. noninoculated seedlings at hours 0, 8, 16, 20, 24, and 32 for each of nine variants of genes in the Mla (powdery mildew) resistance signaling pathway, as well as mutants in programmed cell death (NSF Plant Genome Award #0500461). As shown in Fig. 1, we are analyzing these data to build coexpression networks containing genes involved in sugar transport, photosynthesis, WRKY signaling, secretion of PR proteins, signal peptide processing, and abiotic stress signaling. Single cell dsRNAi (TIGS), Virus Induced Gene Silencing (VIGS), transcript based cloning, and proteomics experiments are being used to dissect the various sub-networks and timecourse interactions of disease defense pathways.
The exponential growth of datasets from plants and microbespresent a plethora of opportunities for comparative analysis. New genetical genomics applications will make possible the creation of dense expression polymorphism maps and identification of regulatory regions (see Fig. 2). These resources will promote the understanding of the complex architecture of plant disease defense, which will have long-term value for crop improvement.