Expression dynamics and genome distribution of osmoprotectants in soybean: identifying important components to face abiotic stress.

BACKGROUND: Despite the importance of osmoprotectants, no previous in silico evaluation of high throughput data is available for higher plants. The present approach aimed at the identification and annotation of osmoprotectant-related sequences applied to short transcripts from a soybean HT-SuperSAGE (High Throughput Super Serial Analysis of Gene Expression; 26-bp tags) database, and also its comparison with other transcriptomic and genomic data available from different sources. METHODS: A curated set of osmoprotectants related sequences was generated using text mining and selected seed sequences for identification of the respective transcripts and proteins in higher plants. To test the efficiency of the seed sequences, these were aligned against four HT-SuperSAGE contrasting libraries generated by our group using soybean tolerant and sensible plants against water deficit, considering only differentially expressed transcripts (p ≤ 0.05). Identified transcripts from soybean and their respective tags were aligned and anchored against the soybean virtual genome. RESULTS: The workflow applied resulted in a set including 1,996 seed sequences that allowed the identification of 36 differentially expressed genes related to the biosynthesis of osmoprotectants [Proline (P5CS: 4, P5CR: 2), Trehalose (TPS1: 9, TPPB: 1), Glycine betaine (BADH: 4) and Myo-inositol (MIPS: 7, INPS1: 8)], also mapped in silico in the soybean genome (25 loci). Another approach considered matches using Arabidopsis full length sequences as seed sequences, and allowed the identification of 124 osmoprotectant-related sequences, matching ~10.500 tags anchored in the soybean virtual chromosomes. Osmoprotectant-related genes appeared clustered in all soybean chromosomes, with higher density in some subterminal regions and synteny among some chromosome pairs. CONCLUSIONS: Soybean presents all searched osmoprotectant categories with some important members differentially expressed among the comparisons considered (drought tolerant or sensible vs. control; tolerant vs. sensible), allowing the identification of interesting candidates for biotechnological inferences. The identified tags aligned to corresponding genes that matched 19 soybean chromosomes. Osmoprotectant-related genes are not regularly distributed in the soybean genome, but clustered in some regions near the chromosome terminals, with some redundant clusters in different chromosomes indicating their involvement in previous duplication and rearrangements events. The seed sequences, transcripts and map represent the first transversal evaluation for osmoprotectant-related genes and may be easily applied to other plants of interest.

Overall picture of expressed Heat Shock Factors in Glycine max, Lotus japonicus and Medicago truncatula.

Heat shock (HS) leads to the activation of molecular mechanisms, known as HS-response, that prevent damage and enhance survival under stress. Plants have a flexible and specialized network of Heat Shock Factors (HSFs), which are transcription factors that induce the expression of heat shock proteins. The present work aimed to identify and characterize the Glycine max HSF repertory in the Soybean Genome Project (GENOSOJA platform), comparing them with other legumes (Medicago truncatula and Lotus japonicus) in view of current knowledge of Arabidopsis thaliana. The HSF characterization in leguminous plants led to the identification of 25, 19 and 21 candidate ESTs in soybean, Lotus and Medicago, respectively. A search in the SuperSAGE libraries revealed 68 tags distributed in seven HSF gene types. From the total number of obtained tags, more than 70% were related to root tissues (water deficit stress libraries vs. controls), indicating their role in abiotic stress responses, since the root is the first tissue to sense and respond to abiotic stress. Moreover, as heat stress is related to the pressure of dryness, a higher HSF expression was expected at the water deficit libraries. On the other hand, expressive HSF candidates were obtained from the library inoculated with Asian Soybean Rust, inferring crosstalk among genes associated with abiotic and biotic stresses. Evolutionary relationships among sequences were consistent with different HSF classes and subclasses. Expression profiling indicated that regulation of specific genes is associated with the stage of plant development and also with stimuli from other abiotic stresses pointing to the maintenance of HSF expression at a basal level in soybean, favoring its activation under heat-stress conditions.

An overall evaluation of the Resistance (R) and Pathogenesis-Related (PR) superfamilies in soybean, as compared with Medicago and Arabidopsis.

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.

In silico identification of known osmotic stress responsive genes from Arabidopsis in soybean and Medicago.

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.

Mining plant genome browsers as a means for efficient connection of physical, genetic and cytogenetic mapping: An example using soybean.

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.

Databank based mining on the track of antimicrobial weapons in plant genomes.

The expressive amount of nucleotide sequences from diverse plant species in databanks enables the use of computational approaches to discovery still unidentified genes and to infer about their function, structure and role in some biological processes. Of special interest are the antimicrobial peptides (AMP), whose functionalities have a very important role in defense against microbial infection in multicellular eukaryotes, being considered less susceptible to bacterial resistance than traditional antibiotics, with potential to develop a new class of therapeutic agents. Recent computational developments have provided various algorithms and resources to profit from the overwhelming information in data banks for biomining such peptides. This review focuses on the computational and bioinformatic approaches so far used for the identification of antimicrobial peptides in plant systems, highlighting alternative means of mining the entire plant peptide space that has recently become available.