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ARS Home » Midwest Area » West Lafayette, Indiana » Crop Production and Pest Control Research » Research » Publications at this Location » Publication #151270
Title: ANALYSIS OF THE WHEAT DEFENSE TRANSCRIPTOME

Author
item Scofield, Steven - Steve
item Anderson, Joseph
item Crane, Charles
item Goodwin, Stephen - Steve
item OHM, HERBERT - PURDUE UNIVERSITY
item Williams, Christie
item LORET, TIMOTHY - CURAGEN CORPORATION
item CRASTA, OSWALD - CURAGEN CORPORATION

Submitted to: Wheat Genetics International Symposium Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/9/2003
Publication Date: 9/1/2003
Citation: Scofield, S.R., Anderson, J.M., Crane, C.F., Goodwin, S.B., Ohm, H., Williams, C.E., Loret, T., Crasta, O. 2003. Analysis of the wheat defense transcriptome. Proceedings of the Tenth International Wheat Genetics Symposium, Paestum, Italy. 1:407-410.

Interpretive Summary: Wheat is the preeminent source of protein in the world's diet and increasing yield through improvement in disease resistance is crucial to meeting the civilization's future nutritional needs. Host-plant resistance provides both economically and environmentally sound methods for increasing crop yields; however, this mode of resistance is not available for some important diseases. Our long-term goal is to define the genes that are essential for resistances to a diverse group of economically important pathogens of wheat. The pathogens tested include fungi, Barley and Cereal Yellow Dwarf viruses and Hessian fly. This knowledge will be essential for efforts to engineer improved forms of resistance in wheat. Working under the premise that many of genes encoding essential components of these resistance mechanisms are likely to be up- or down-regulated during the responses, our first step toward this goal is to identify the genes whose expression changes significantly during various resistance responses. To do this, we employed a highly sensitive technology that allows us to monitor changes in global gene expression and does not require any prior knowledge of the sequences of the genes being monitored. This analysis has yielded a list of over 3,500 genes whose expression changes by at least 1.5-fold in one or more of the four plant-pathogen interactions tested. The fact that ~10% of these sequences have not been identified in other analyses of wheat gene expression, despite that fact that over 500,000 sequences have been previously determined, is an indication of the sensitivity of this survey. This work is essential for efforts to genetically engineer wheat with improved disease resistance. Ultimately, the seed industry, growers and consumers would benefit from the development of wheat that can resist a broad spectrum of pathogens without the need for application of pesticides.

Technical Abstract: In an effort to understand the mechanisms of disease resistance in plants and the extent that various pathogens affect different genetic pathways, we analyzed the global changes in gene expression as wheat interacts with a wide-range of pathogens and pests. GeneCalling, an open-architecture gene expression profiling technology that requires no prior knowledge of gene sequence (Curagen Corp.), was employed to characterize the transcriptome of wheat after it was challenged by fungi (Fusarium graminearum and Mycosphaerella graminicola), Barley and Cereal Yellow Dwarf viruses or Hessian fly (Mayetiola destructor). The GeneCalling studies profiled >11,000 cDNA fragments per sample, detecting expression changes differing by at least 1.5 fold between treatments. For example, in the M. graminicola treatments 4,900 sequences were differentially expressed in at least one of 7 timepoints, divided equally between those that were up- (2418) or down- (2482) regulated. Bioinformatics analysis of the >11,000 differentially expressed sequences resulted in assembly of 3,111 previously annotated genes, and an additional group of 398 novel or unannotated sequences. With >500,000 wheat ESTs currently in databases, the fact that our analysis has identified ~10% novel sequences suggests that GeneCalling is very effective in identifying rare mRNAs.