A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data

<p>Abstract</p> <p>Background</p> <p>Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientific impact and a wide application area. Several standalone applications had been developed in order to analyze microarray data. Two of the most known free analysis software packages are the R-based Bioconductor and dChip. The part of dChip software concerning the calculation and the analysis of gene expression has been modified to permit its execution on both cluster environments (supercomputers) and Grid infrastructures (distributed computing).</p> <p>This work is not aimed at replacing existing tools, but it provides researchers with a method to analyze large datasets without any hardware or software constraints.</p> <p>Results</p> <p>An application able to perform the computation and the analysis of gene expression on large datasets has been developed using algorithms provided by dChip. Different tests have been carried out in order to validate the results and to compare the performances obtained on different infrastructures. Validation tests have been performed using a small dataset related to the comparison of HUVEC (Human Umbilical Vein Endothelial Cells) and Fibroblasts, derived from same donors, treated with IFN-α.</p> <p>Moreover performance tests have been executed just to compare performances on different environments using a large dataset including about 1000 samples related to Breast Cancer patients.</p> <p>Conclusion</p> <p>A Grid-enabled software application for the analysis of large Microarray datasets has been proposed. DChip software has been ported on Linux platform and modified, using appropriate parallelization strategies, to permit its execution on both cluster environments and Grid infrastructures. The added value provided by the use of Grid technologies is the possibility to exploit both computational and data Grid infrastructures to analyze large datasets of distributed data. The software has been validated and performances on cluster and Grid environments have been compared obtaining quite good scalability results.</p

Modulation of ethylene- and heat-controlled hyponastic leaf movement in Arabidopsis thaliana by the plant defence hormones jasmonate and salicylate

Upward leaf movement (hyponastic growth) is adopted by several plant species including Arabidopsis thaliana, as a mechanism to escape adverse growth conditions. Among the signals that trigger hyponastic growth are, the gaseous hormone ethylene, low light intensities, and supra-optimal temperatures (heat). Recent studies indicated that the defence-related phytohormones jasmonic acid (JA) and salicylic acid (SA) synthesized by the plant upon biotic infestation repress low light-induced hyponastic growth. The hyponastic growth response induced by high temperature (heat) treatment and upon application of the gaseous hormone ethylene is highly similar to the response induced by low light. To test if these environmental signals induce hyponastic growth via parallel pathways or converge downstream, we studied here the roles of Methyl-JA (MeJA) and SA on ethylene- and heat-induced hyponastic growth. For this, we used a time-lapse camera setup. Our study includes pharmacological application of MeJA and SA and biological infestation using the JA-inducing caterpillar Pieris rapae as well as mutants lacking JA or SA signalling components. The data demonstrate that MeJA is a positive, and SA, a negative regulator of ethylene-induced hyponastic growth and that both hormones repress the response to heat. Taking previous studies into account, we conclude that SA is the first among many tested components which is repressing hyponastic growth under all tested inductive environmental stimuli. However, since MeJA is a positive regulator of ethylene-induced hyponastic growth and is inhibiting low light- and heat-induced leaf movement, we conclude that defence hormones control hyponastic growth by affecting stimulus-specific signalling pathways

Kinome Profiling Reveals an Interaction Between Jasmonate, Salicylate and Light Control of Hyponastic Petiole Growth in Arabidopsis thaliana

Plants defend themselves against infection by biotic attackers by producing distinct phytohormones. Especially jasmonic acid (JA) and salicylic acid (SA) are well known defense-inducing hormones. Here, the effects of MeJA and SA on the Arabidopsis thaliana kinome were monitored using PepChip arrays containing kinase substrate peptides to analyze posttranslational interactions in MeJA and SA signaling pathways and to test if kinome profiling can provide leads to predict posttranslational events in plant signaling. MeJA and SA mediate differential phosphorylation of substrates for many kinase families. Also some plant specific substrates were differentially phosphorylated, including peptides derived from Phytochrome A, and Photosystem II D protein. This indicates that MeJA and SA mediate cross-talk between defense signaling and light responses. We tested the predicted effects of MeJA and SA using light-mediated upward leaf movement (differential petiole growth also called hyponastic growth). We found that MeJA, infestation by the JA-inducing insect herbivore Pieris rapae, and SA suppressed low light-induced hyponastic growth. MeJA and SA acted in a synergistic fashion via two (partially) divergent signaling routes. This work demonstrates that kinome profiling using PepChip arrays can be a valuable complementary ∼omics tool to give directions towards predicting behavior of organisms after a given stimulus and can be used to obtain leads for physiological relevant phenomena in planta

Molecular and genetic control of plant thermomorphogenesis

Temperature is a major factor governing the distribution and seasonal behaviour of plants. Being sessile, plants are highly responsive to small differences in temperature and adjust their growth and development accordingly. The suite of morphological and architectural changes induced by high ambient temperatures, below the heat-stress range, is collectively called thermomorphogenesis. Understanding the molecular genetic circuitries underlying thermomorphogenesis is particularly relevant in the context of climate change, as this knowledge will be key to rational breeding for thermo-tolerant crop varieties. Until recently, the fundamental mechanisms of temperature perception and signalling remained unknown. Our understanding of temperature signalling is now progressing, mainly by exploiting the model plant Arabidopsis thaliana. The transcription factor PHYTOCHROME INTERACTING FACTOR 4 (PIF4) has emerged as a critical player in regulating phytohormone levels and their activity. To control thermomorphogenesis, multiple regulatory circuits are in place to modulate PIF4 levels, activity and downstream mechanisms. Thermomorphogenesis is integrally governed by various light signalling pathways, the circadian clock, epigenetic mechanisms and chromatin-level regulation. In this Review, we summarize recent progress in the field and discuss how the emerging knowledge in Arabidopsis may be transferred to relevant crop systems

Research tools: Ethylene detection

info:eu-repo/semantics/publishe