Background: The WRKY transcription factor gene family has a very ancient origin and has undergone extensive duplications in the plant kingdom. Several studies have pointed out their involvement in a range of biological processes, revealing that a large number ofWRKYgenes are transcriptionally regulated under conditions of biotic and/or abiotic stress. To investigate the existence ofWRKYco-regulatory networks in plants, a whole gene familyWRKYs expression study was carried out in rice (Oryza sativa). This analysis was extended toArabidopsis thalianataking advantage of an extensive repository of gene expression data.Results: The presented results suggested that 24 members of the riceWRKYgene family (22% of the total) were differentially-regulated in response to at least one of the stress conditions tested. We defined the existence of nine OsWRKYgene clusters comprising both phylogenetically related and unrelated genes that were significantly co-expressed, suggesting that specific sets ofWRKYgenes might act in co-regulatory networks. This hypothesis was tested by Pearson Correlation Coefficient analysis of the ArabidopsisWRKYgene family in a large set of Affymetrix microarray experiments.AtWRKYswere found to belong to two main co-regulatory networks (COR-A, COR-B) and two smaller ones (COR-C and COR-D), all including genes belonging to distinct phylogenetic groups. The COR-A network contained severalAtWRKYgenes known to be involved mostly in response to pathogens, whose physical and/or genetic interaction was experimentally proven. We also showed that specific co-regulatory networks were conserved between the two model species by identifying Arabidopsis orthologs of the co-expressedOsWRKYgenes.Conclusion: In this work we identified sets of co-expressedWRKYgenes in both rice and Arabidopsis that are functionally likely to cooperate in the same signal transduction pathways. We propose that, making use of data from co-regulatory networks, it is possible to highlight novel clusters of plant genes contributing to the same biological processes or signal transduction pathways. Our approach will contribute to unveil gene cooperation pathways not yet identified by classical genetic analyses. This information will open new routes contributing to the dissection of WRKY signal transduction pathways in plants.

Over the years, several studies have been performed to analyse plant–pathogen interactions. Recently, functional genomic strategies, including proteomics and transcriptomics, have contributed to the effort of defining gene and protein function and expression profiles. Using these ‘omic’ approaches, pathogenicity‐ and defence‐related genes and proteins expressed during phytopathogen infections have been identified and enormous datasets have been accumulated. However, the understanding of molecular plant–pathogen interactions is still an intriguing area of investigation. Proteomics has dramatically evolved in the pursuit of large‐scale functional assignment of candidate proteins and, by using this approach, several proteins expressed during phytopathogenic interactions have been identified. In this review, we highlight the proteins expressed during plant–virus, plant–bacterium, plant–fungus and plant–nematode interactions reported in proteomic studies, and discuss these findings considering the advantages and limitations of current proteomic tools.

Background: Rice (Oryza sativa L.) germplasm represents an extraordinary source of genes that control traits of agronomic importance such as drought tolerance. This diversity is the basis for the development of new cultivars better adapted to water restriction conditions, in particular for upland rice, which is grown under rainfall. The analyses of subtractive cDNA libraries and differential protein expression of drought tolerant and susceptible genotypes can contribute to the understanding of the genetic control of water use efficiency in rice. Results: Two subtractive libraries were constructed using cDNA of drought susceptible and tolerant genotypes submitted to stress against cDNA of well-watered plants. In silico analysis revealed 463 reads, which were grouped into 282 clusters. Several genes expressed exclusively in the tolerant or susceptible genotypes were identified. Additionally, proteome analysis of roots from stressed plants was performed and 22 proteins putatively associated to drought tolerance were identified by mass spectrometry. Conclusion: Several genes and proteins involved in drought-response, as well as genes with no described homologs were identified. Genes exclusively expressed in the tolerant genotype were, in general, related to maintenance of turgor and cell integrity. In contrast, in the susceptible genotype, expression of genes involved in protection against cell damage was not detected. Several protein families identified in the proteomic analysis were not detected in the cDNA analysis. There is an indication that the mechanisms of susceptibility to drought in upland rice are similar to those of lowland varieties.

Background: Cultivated peanut (Arachis hypogaea) is one of the most widely grown grain legumes in the world, being valued for its high protein and unsaturated oil contents. Worldwide, the major constraints to peanut production are drought and fungal diseases. Wild Arachis species, which are exclusively South American in origin, have high genetic diversity and have been selected during evolution in a range of environments and biotic stresses, constituting a rich source of allele diversity. Arachis stenosperma harbors resistances to a number of pests, including fungal diseases, whilst A. duranensis has shown improved tolerance to water limited stress. In this study, these species were used for the creation of an extensive databank of wild Arachis transcripts under stress which will constitute a rich source for gene discovery and molecular markers development. Results: Transcriptome analysis of cDNA collections from A. stenosperma challenged with Cercosporidium personatum (Berk. and M.A. Curtis) Deighton , and A. duranensis submitted to gradual water limited stress was conducted using 454 GS FLX Titanium generating a total of 7.4 x 10⁵ raw sequence reads covering 211 Mbp of both genomes. High quality reads were assembled to 7,723 contigs for A. stenosperma and 12,792 for A. duranensis and functional annotation indicated that 95% of the contigs in both species could be appointed to GO annotation categories. A number of transcription factors families and defense related genes were identified in both species. Additionally, the expression of five A. stenosperma Resistance Gene Analogs (RGAs) and four retrotransposon (FIDEL-related) sequences were analyzed by qRT-PCR. This data set was used to design a total of 2,325 EST-SSRs, of which a subset of 584 amplified in both species and 214 were shown to be polymorphic using ePCR. Conclusions: This study comprises one of the largest unigene dataset for wild Arachis species and will help to elucidate genes involved in responses to biological processes such as fungal diseases and water limited stress. Moreover, it will also facilitate basic and applied research on the genetics of peanut through the development of new molecular markers and the study of adaptive variation across the genus.