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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 plantpathogen 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 Medicago and Arabidopsis. Made available in DSpace on 2015-08-20T05:51:38Z (GMT). No. of bitstreams: 1 gmb.overall.v35n1s.260271.2012.pdf: 3610777 bytes, checksum: 19b3fafd55033fa219c897e666f6264b (MD5) Previous issue date: 2012-06-18

Plants experience various environmental stresses, but tolerance to these adverse conditions is a very complex phenomenon. The present research aimed to evaluate a set of genes involved in osmotic response, comparing soybean and medicago with the well-described Arabidopsis thaliana model plant. Based on 103 Arabidopsis proteins from 27 categories of osmotic stress response, comparative analyses against Genosoja and Medicago truncatula databases allowed the identification of 1,088 soybean and 1,210 Medicago sequences. The analysis showed a high number of sequences and high diversity, comprising genes from all categories in both organisms. Genes with unknown function were among the most representative, followed by transcription factors, ion transport proteins, water channel, plant defense, protein degradation, cellular structure, organization & biogenesis and senescence. An analysis of sequences with unknown function allowed the annotation of 174 soybean and 217 Medicago sequences, most of them concerning transcription factors. However, for about 30% of the sequences no function could be attributed using in silico procedures. The establishment of a gene set involved in osmotic stress responses in soybean and barrel medic will help to better understand the survival mechanisms for this type of stress condition in legumes. Made available in DSpace on 2015-08-20T05:51:50Z (GMT). No. of bitstreams: 1 gmb.silico.v35n1s.315321.2012.pdf: 1731333 bytes, checksum: 8154bc6ca1244920d367621ab15fe16d (MD5) Previous issue date: 2012-06-19

Physical maps are important tools to uncover general chromosome structure as well as to compare different plant lineages and species, helping to elucidate genome structure, evolution and possibilities regarding synteny and colinearity. The increasing production of sequence data has opened an opportunity to link information from mapping studies to the underlying sequences. Genome browsers are invaluable platforms that provide access to these sequences, including tools for genome analysis, allowing the integration of multivariate information, and thus aiding to explain the emergence of complex genomes. The present work presents a tutorial regarding the use of genome browsers to develop targeted physical mapping, providing also a general overview and examples about the possibilities regarding the use of Fluorescent In Situ Hybridization (FISH) using bacterial artificial chromosomes (BAC), simple sequence repeats (SSR) and rDNA probes, highlighting the potential of such studies for map integration and comparative genetics. As a case study, the available genome of soybean was accessed to show how the physical and in silico distribution of such sequences may be compared at different levels. Such evaluations may also be complemented by the identification of sequences beyond the detection level of cytological methods, here using members of the aquaporin gene family as an example. The proposed approach highlights the complementation power of the combination of molecular cytogenetics and computational approaches for the anchoring of coding or repetitive sequences in plant genomes using available genome browsers, helping in the determination of sequence location, arrangement and number of repeats, and also filling gaps found in computational pseudochromosome assemblies.