BMC Genomics 2009, 10:415 http://www.biomedcentral.com/1471-2164/10/415 labeled dUTP into the nascent cDNA from the target RNA instead of Cy3 and Cy5 modified nucleotides since it is known to negate any dye bias during the microarray experiment [80-82]. The transcript level for each cDNA was calculated as the average intensity of four data points from duplicate spots of two replicate slides. We used a fold cut off of 2.5 and Students t-test with P-value  0.05 ranking with false discovery rate (FDR) multiple testing corrections to identify differentially expressed genes. A total of 257 differentially expressed unigenes were found to be associated with the early signaling pathway, of which 107 were induced and 150 repressed during incom- patible interaction (see Additional file 6). Further, to iden- tify co-expression kinetics amongst the differentially expressed genes, we applied hierarchical clustering analy- sis to the transcriptome data set that grouped the genes in two clusters based on their positive and negative fold change. Cluster 1 represents repressed genes while cluster 2 comprised of genes induced at 24 h post Fusarium infec- tion. Almost all the 23 functional classes are represented in these two clusters but differed in the type of the repre- sentative genes and their relative abundance (Figure 4). Moreover, the transcriptional response to immune sensi- tivity of genes involved in major biological processes and molecular functions showed different dynamics within repressed vs. induced gene clusters. The detailed expres- sion level has been highlighted in additional file 6. The repressed gene cluster is enriched for genes affecting trans- lation, ribosome structure and biogenesis, while the induced cluster is dominated by genes encoding hypo- thetical proteins, metabolism and miscellaneous groups. Genes involved in metabolism GO category are over-rep- resented in both cluster 1 and 2, but the magnitude of over-representation is higher for cluster 1 than cluster 2. UF, NSH and Miscellaneous categories notably formed a major group of overrepresented genes. Genes involved in translation, ribosome structure and biogenesis form the largest functional category in cluster 1 that includes genes for ribosomal proteins, translation initiation and elongation factors. Several genes encoding proteins involved in post translational modifications and protein turnover, for example, protein disufide isomerase- like protein and ubiquitin were also grouped in cluster 1. Many of these genes have previously been implicated in specific stresses in different organisms [83,84]. In the repressed set of genes other major functional classes included metabolism, hypothetical proteins, cellular redox state and transcription. These include genes encod- ing cytochrome P450, thioredoxin, superoxide dismutase and glutathione-S-transferase that are known to play crit- ical role in plant stress [85-87]. Many carbohydrate metabolism genes like GAPDH, triosephosphate isomer- ase and malate dehydrogenase precursor were downregu- lated. Earlier reports showed altered expression of GAPDH during plant stress [38], however the specific function of this enzyme during stress is not known. More- over GAPDH has also been known to act as an essential component of transcriptional activator complex regulat- ing histone expression [88]. We also observed defense related genes like chitinase 1 and PR10, and secondary metabolism genes like chalcone synthase and isoflavone 3'-hydroxylase to be repressed during Fusarium infection. These genes are known to be associated with pathogen stress [63,64]. In contrary, genes encoding hypothetical proteins, metab- olism and miscellaneous groups form the dominant func- tional class in cluster 2. The induced set of metabolic genes include some carbohydrate metabolism genes like ADH1, FBF, aldolase and pfkB-type carbohydrate kinase family protein of carbohydrate metabolism and oleate desaturase involved in lipid metabolism. The role of these enzymes in plant immunity has not yet been defined and hence will be of great interest in future. Post-translational modification and protein turnover related genes like cystatin, Sec61beta and ubiquitin extension protein were also induced consistent with the notion that damaged or partially denatured proteins need to be degraded to pre- vent the accumulation of protein aggregates. Many such genes are involved in regulating protein metabolism in response to stress [89,90]. Other cell stress induced genes include classical phenylpropanoid pathway genes like chalcone reductase and chalcone--flavonone isomerase 1. Role played by these genes during cell defense is a well known phenomenon [64]. Many signaling related genes like serine/threonine protein kinase, leucine-rich repeat transmembrane protein kinase to name a few were induced attesting their role in plant defense. More than thirty percent of the repressed and induced gene clusters represented NSH and hypothetical proteins those do not have known cellular roles, these can now be annotated as being involved in immune response path- way. Expression analysis of selected ESTs by RNA blot analysis To confirm the differential expression of immune-respon- sive genes, four highly abundant genes in our CaEST data- set showing induced gene expression were selected for RNA blot analysis. The results showed that all four ESTs had a strong induction in root tissue at 24 h post infection and the level of gene expression corroborated to that of microarray analyses (Figure 5, see Additional file 6). The genes encoding alcohol dehydrogenase and pfkB-type kinase, showed a very high expression suggesting that the carbohydrate metabolic pathways are altered in response to vascular wilt. A disease resistance response gene for defense signaling also showed upregulation indicating its role in immune response. The expression level of a fungal Page 11 of 21 (page number not for citation purposes)