Plant & Animal Genomes XI Conference

January 11-15, 2003
Town & Country Convention Center
San Diego, CA

Workshop: Barley
            

PARALLEL EXPRESSION ANALYSIS USING BARLEY MICROARRAYS.

¹ USDA-ARS, Department of Plant Pathology and Center for Plant Responses to Environmental Stresses, 351 Bessey Hall, Iowa State University, Ames, IA, 50011-1020, USA

² Department of Plant Pathology, Iowa State University, Ames, IA, 50011-1020, USA

³ Bioinformatics & Computational Biology and Department of Plant Pathology, Iowa State University, Ames, IA, 50011-1020, USA

⁴ Department of Mathematics, Iowa State University, Ames, IA, 50011, USA

⁵ Department of Computer Engineering, Iowa State University, Ames, IA, 50011, USA

In small grain Triticeae crops, the molecular characterization of genes coincident with disease, response to biotic or abiotic stresses, or cellular development has traditionally followed a “one-gene-at-a-time” approach. However, recent advances in microarray technology now allow the parallel investigation of up to 22,500 genes in a single experiment. In 2003, a USDA-IFAFS funded barley GeneChip will be available from Affymetrix. We are using these arrays to monitor plant-pathogen interactions on a global scale. Pairwise expression profiling is being performed with plants containing the Mla6 and Mla13 resistance specificities in response to the powdery mildew isolates 5874 (AvrMla6, virMla13) and K1 (AvrMla13, virMla6). Our objective is to identify genes that induced/repressed during early stages of pathogen challenge to fully elucidate the molecular mechanisms orchestrating incompatible and compatible barley-powdery mildew interactions. In order to effectively utilize up to 500,000 data points per experiment, researchers must be able to easily access, compare, and manipulate the generated data. This project will create an on-line interactive database component, BarleyBase, and develop a set of web-accessible tools for the analysis of Affymetrix GeneChip data. BarleyBase will feature “click through” integration of the data on the web and it will be interoperable with the Gramene comparative mapping resource for grains (http://www.gramene.org/). The web-based analysis tools will enable database users to identify subsets of genes that change expression in response to drought, cold stress, disease, or other treatments.