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The Genosoja consortium is an initiative to integrate different omics research approaches carried out in Brazil. Basically, the aim of the project is to improve the plant by identifying genes involved in responses against stresses that affect domestic production, like drought stress and Asian Rust fungal disease. To do so, the project generated several types of sequence data using different methodologies, most of them sequenced by next generation sequencers. The initial stage of the project is highly dependent on bioinformatics analysis, providing suitable tools and integrated databases. In this work, we describe the main features of the Genosoja web database, including the pipelines to analyze some kinds of data (ESTs, SuperSAGE, microRNAs, subtractive cDNA libraries), as well as web interfaces to access information about soybean gene annotation and expression.

Plants have the ability to recognize and respond to a multitude of pathogens, resulting in a massive reprogramming of the plant to activate defense responses including Resistance (R) and Pathogenesis-Related (PR) genes. Abiotic stresses can also activate PR genes and enhance pathogen resistance, representing valuable genes for breeding purposes. The present work offers an overview of soybean R and PR genes present in the GENOSOJA (Brazilian Soybean Genome Consortium) platform, regarding their structure, abundance, evolution and role in the plant-pathogen metabolic pathway, as compared with Medicago and Arabidopsis. Searches revealed 3,065 R candidates (756 in Soybean, 1,142 in Medicago and 1,167 in Arabidopsis), and PR candidates matching to 1,261 sequences (310, 585 and 366 for the three species, respectively). The identified transcripts were also evaluated regarding their expression pattern in 65 libraries, showing prevalence in seeds and developing tissues. Upon consulting the SuperSAGE libraries, 1,072 R and 481 PR tags were identified in association with the different libraries. Multiple alignments were generated for Xa21 and PR-2 genes, allowing inferences about their evolution. The results revealed interesting insights regarding the variability and complexity of defense genes in soybean, as compared with Medicago and Arabidopsis.