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In silico differential display of defense-related expressed sequence tags from sugarcane tissues infected with diazotrophic endophytes

The expression patterns of 277 sugarcane expressed sequence tags (EST)-contigs encoding putative defense-related (DR) proteins were evaluated using the Sugarcane EST database. The DR proteins evaluated included chitinases, beta-1,3-glucanases, phenylalanine ammonia-lyases, chalcone synthases, chalcone isomerases, isoflavone reductases, hydroxyproline-rich glycoproteins, proline-rich glycoproteins, peroxidases, catalases, superoxide dismutases, WRKY-like transcription factors and proteins involved in cell death control. Putative sugarcane WRKY proteins were compared and their phylogenetic relationships determined. A hierarchical clustering approach was used to identify DR ESTs with similar expression profiles in representative cDNA libraries. To identify DR ESTs differentially expressed in sugarcane tissues infected with Gluconacetobacter diazotrophicus or Herbaspirillum rubrisubalbicans, 179 putative DR EST-contigs expressed in non-infected tissues (leaves and roots) and/or infected tissues were selected and arrayed by similarity of their expression profiles. Changes in the expression levels of 124 putative DR EST-contigs, expressed in non-infected tissues, were evaluated in infected tissues. Approximately 42% of these EST-contigs showed no expression in infected tissues, whereas 15% and 3% showed more than 2-fold suppression in tissues infected with G. diazotrophicus or H. rubrisubalbicans, respectively. Approximately 14 and 8% of the DR EST-contigs evaluated showed more than 2-fold induction in tissues infected with G. diazotrophicus or H. rubrisubalbicans, respectively. The differential expression of clusters of DR genes may be important in the establishment of a compatible interaction between sugarcane and diazotrophic endophytes. It is suggested that the hierarchical clustering approach can be used on a genome-wide scale to identify genes likely involved in controlling plant-microorganism interactions.


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