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United States Department of Agriculture

Agricultural Research Service

Title: Parallel Expression Profiling of Gene-for-Gene-Specified Responses in Barley-Powdery Mildew Interactions

Authors
item Caldo, Rico - IOWA STATE UNIVERSITY
item Nettleton, Dan - IOWA STATE UNIVERSITY
item Turner, Stacy - IOWA STATE UNIVERSITY
item Dickerson, Julie - IOWA STATE UNIVERSITY
item Wise, Roger

Submitted to: Plant Molecular Biology International Conference Proceedings
Publication Type: Proceedings
Publication Acceptance Date: April 9, 2003
Publication Date: June 10, 2003
Citation: CALDO, R., NETTLETON, D., TURNER, S., DICKERSON, J., WISE, R.P. PARALLEL EXPRESSION PROFILING OF GENE-FOR-GENE-SPECIFIED RESPONSES IN BARLEY-POWDERY MILDEW INTERACTIONS. AVAILABLE FROM: http://www.ispmb2003.com/. PLANT MOLECULAR BIOLOGY INTERNATIONAL CONFERENCE PROCEEDINGS. 2003. Poster S21-51.

Technical Abstract: Host responses to invading pathogens are controlled by complex regulatory pathways and accompanied by the differential expression of many genes. We are utilizing our newly developed 22,786 feature, Affymetrix barley microarray to characterize novel genes regulated during Rar1/Sgt1-dependent and Rar1/Sgt1-independent interactions with Blumeria graminis, as well as genes regulated during powdery mildew induced programmed cell death. Our goal is to identify induced/repressed genes at different time points after pathogen infection to provide a molecular description of the events orchestrating incompatible and compatible barley-powdery mildew interactions. Time course expression profiling is being performed with plants containing the Mla6, Mla13, and Mla1 resistance specificities, in addition to programmed-cell-death mutants derived from the parental line containing Mla6, in response to the powdery mildew isolates 5874 (AvrMla6, virMla13) and K1 (AvrMla13, virMla6). In addition, this project will create an on-line interactive database, BarleyBase, and develop a set of web-accessible tools for the analysis of GeneChip data. BarleyBase will feature "click through" integration of web-base data sets 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 perform meta-analysis of gene expression in response to a particular treatment.

Last Modified: 12/18/2014
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