Differential expression and sequence data mining of genes induced during Coffea arabica L-Hemeleia vastatrix L interactions
Geleta Dugassa Barka
Universidade Federal de Vicosa, Brazil
: J Plant Physiol Pathol
Abstract
C ountering the economic hurdle caused by coffee leaf rust disease is most appealing than any time as it has posed a major threat once again on coffee production. Establishing differential expression profiles at different times following pathogen invasion in both innate and acquired immunities unlocks the molecular components of resistance and susceptibility. Suppression subtractive hybridization (SSH) was used to unveil genes differentially over expressed and repressed during incompatible and compatible interactions between coffee and rust fungus. A total of 433 resistance related expressed sequence tags (ESTs) were sequenced; from which 354 were annotated and categorized based on biological function and cell component. We used four databases in searching for significant matches using local alignment tools and evaluated the integration and sharing of sequences among data repositories. The result shows different types and numbers of genes were differentially expressed in both interactions in up-regulated and down regulated libraries. Despite the ever increasing size of databases and homology search tools, the extent of integrity and data sharing between databases was found to be inconsistent. The work enlightens the different types of resistance related genes to be used in resistance development and shows the challenges in homology search and database integration between different sources.
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