Implication of the oep16-1 mutation in a flu-independent, singlet oxygen-regulated cell death pathway in Arabidopsis thaliana

Singlet oxygen is a prominent form of reactive oxygen species in higher plants. It is easily formed from molecular oxygen by triplet–triplet interchange with excited porphyrin species. Evidence has been obtained from studies on the flu mutant of Arabidopsis thaliana of a genetically determined cell death pathway that involves differential changes at the transcriptome level. Here we report on a different cell death pathway that can be deduced from the analysis of oep16 mutants of A. thaliana. Pure lines of four independent OEP16-deficient mutants with different cell death properties were isolated. Two of the mutants overproduced free protochlorophyllide (Pchlide) in the dark because of defects in import of NADPH:Pchlide oxidoreductase A (pPORA) and died after illumination. The other two mutants avoided excess Pchlide accumulation. Using pulse labeling and polysome profiling studies we show that translation is a major site of cell death regulation in flu and oep16 plants. flu plants respond to photooxidative stress triggered by singlet oxygen by reprogramming their translation toward synthesis of key enzymes involved in jasmonic acid synthesis and stress proteins. In contrast, those oep16 mutants that were prone to photooxidative damage were unable to respond in this way. Together, our results show that translation is differentially affected in the flu and oep16 mutants in response to singlet oxygen.

Two Novel Methods For The Determination Of The Number Of Components In Independent Components Analysis Models

Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance.

Independent component analysis for the identification of sources of variation on an industrial nirs application

A Near Infrared Spectroscopy (NIRS) industrial application was developed by the LPF-Tagralia team, and transferred to a Spanish dehydrator company (Agrotécnica Extremeña S.L.) for the classification of dehydrator onion bulbs for breeding purposes. The automated operation of the system has allowed the classification of more than one million onion bulbs during seasons 2004 to 2008 (Table 1). The performance achieved by the original model (R2=0,65; SEC=2,28ºBrix) was enough for qualitative classification thanks to the broad range of variation of the initial population (18ºBrix). Nevertheless, a reduction of the classification performance of the model has been observed with the passing of seasons. One of the reasons put forward is the reduction of the range of variation that naturally occurs during a breeding process, the other is the variations in other parameters than the variable of interest but whose effects would probably be affecting the measurements [1]. This study points to the application of Independent Component Analysis (ICA) on this highly variable dataset coming from a NIRS industrial application for the identification of the different sources of variation present through seasons.

The Agrobacterium vitis T-6b oncoprotein induces auxin-independent cell expansion in tobacco

Among the Agrobacterium T-DNA genes, rolB, rolC, orf13, orf8, lso, 6b and several other genes encode weakly homologous proteins with remarkable effects on plant growth. The 6b oncogene induces tumors and enations. In order to study its properties we have used transgenic tobacco plants that carry a dexamethasone-inducible 6b gene, dex-T-6b. Upon induction, dex-T-6b plants develop a large array of morphological modifications, some of which involve abnormal cell expansion. In the present investigation, dex-T-6b-induced expansion was studied in intact leaves and an in vitro leaf disc system. Although T-6b and indole-3-acetic acid (IAA) both induced expansion and were non-additive, T-6b expression did not increase IAA levels, nor did it induce an IAA-responsive gene. Fusicoccin (FC) is known to stimulate expansion by increasing cell wall plasticity. T-6b- and FC-induced expansion were additive at saturating FC concentrations, indicating that T-6b does not act by a similar mechanism to FC. T-6b expression led to higher leaf osmolality values, in contrast to FC, suggesting that the T-6b gene induces expansion by increasing osmolyte concentrations. Metabolite profiling showed that glucose and fructose played a major role in this increase. We infer that T-6b disrupts the osmoregulatory controls that govern cell expansion during development and wound healing.

Automatic compile-time parallelization of logic programs for restricted, goal-level, independent and-parallelism.

A framework for the automatic parallelization of (constraint) logic programs is proposed and proved correct. Intuitively, the parallelization process replaces conjunctions of literals with parallel expressions. Such expressions trigger at run-time the exploitation of restricted, goal-level, independent and-parallelism. The parallelization process performs two steps. The first one builds a conditional dependency graph (which can be implified using compile-time analysis information), while the second transforms the resulting graph into linear conditional expressions, the parallel expressions of the &-Prolog language. Several heuristic algorithms for the latter ("annotation") process are proposed and proved correct. Algorithms are also given which determine if there is any loss of parallelism in the linearization process with respect to a proposed notion of maximal parallelism. Finally, a system is presented which implements the proposed approach. The performance of the different annotation algorithms is compared experimentally in this system by studying the time spent in parallelization and the effectiveness of the results in terms of speedups.

High-level characteristics of or-and independent and-parallelism in prolog

Although studies of a number of parallel implementations of logic programming languages are now available, their results are difficult to interpret due to the multiplicity of factors involved, the effect of each of which is difficult to sepárate. In this paper we present the results of a high-level simulation study of or- and independent and-parallelism with a wide selection of Prolog programs that aims to determine the intrinsic amount of parallelism, independently of implementation factors, thus facilitating this separation. We expect this study will be instrumental in better understanding and comparing results from actual implementations, as shown by some examples provided in the paper. In addition, the paper examines some of the issues and tradeoffs associated with the combination of and- and or-parallelism and proposes reasonable solutions based on the simulation data obtained.

The &-prolog system: Exploiting independent and-parallelism

The &-Prolog system, a practical implementation of a parallel execution niodel for Prolog exploiting strict and non-strict independent and-parallelism, is described. Both automatic and manual parallelization of programs is supported. This description includes a summary of the system's language and architecture, some details of its execution model (based on the RAP-WAM model), and data on its performance on sequential workstations and shared memory multiprocessors, which is compared to that of current Prolog systems. The results to date show significant speed advantages over state-of-the-art sequential systems.

Strict and non-strict independent and-parallelism in logic programs: Correctness, efficiency, and compile-time conditions.

This paper presents some fundamental properties of independent and-parallelism and extends its applicability by enlarging the class of goals eligible for parallel execution. A simple model of (independent) and-parallel execution is proposed and issues of correctness and efficiency discussed in the light of this model. Two conditions, "strict" and "non-strict" independence, are defined and then proved sufficient to ensure correctness and efñciency of parallel execution: if goals which meet these conditions are executed in parallel the solutions obtained are the same as those produced by standard sequential execution. Also, in absence of failure, the parallel proof procedure does not genérate any additional work (with respect to standard SLD-resolution) while the actual execution time is reduced. Finally, in case of failure of any of the goals no slow down will occur. For strict independence the results are shown to hold independently of whether the parallel goals execute in the same environment or in sepárate environments. In addition, a formal basis is given for the automatic compile-time generation of independent and-parallelism: compile-time conditions to efficiently check goal independence at run-time are proposed and proved sufficient. Also, rules are given for constructing simpler conditions if information regarding the binding context of the goals to be executed in parallel is available to the compiler.