Expression Pattern and Promoter Analysis of a Eucalyptus grandis Germin-like Gene

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Seasonal effects on the relationship between photosynthesis and leaf carbohydrates in orange trees

To understand the effect of summer and winter on the relationships between leaf carbohydrate and photosynthesis in citrus trees growing in subtropical conditions, 'Valencia' orange trees were subjected to external manipulation of their carbohydrate concentration by exposing them to darkness and evaluating the maximal photosynthetic capacity. In addition, the relationships between carbohydrate and photosynthesis in the citrus leaves were studied under natural conditions. Exposing the leaves to dark conditions decreased the carbohydrate concentration and increased photosynthesis in both seasons, which is in accordance with the current model of carbohydrate regulation. Significant negative correlations were found between total non-structural carbohydrates and photosynthesis in both seasons. However, non-reducing sugars were the most important carbohydrate that apparently regulated photosynthesis on a typical summer day, whereas starch was important on a typical winter day. As a novelty, photosynthesis stimulation by carbohydrate consumption was approximately three times higher during the summer, i.e. the growing season. Under subtropical conditions, citrus leaves exhibited relatively high photosynthesis and high carbohydrate levels on the summer day, as well as a high nocturnal consumption of starch and soluble sugars. A positive association was determined between photosynthesis and photoassimilate consumption/exportation, even in leaves showing a high carbohydrate concentration. This paper provides evidence that photosynthesis in citrus leaves is regulated by an increase in sink demand rather than by the absolute carbohydrate concentration in leaves.

Horizontal gene transfer confers fermentative metabolism in the respiratory-deficient plant trypanosomatid Phytomonas serpens

Among trypanosomatids, the genus Phytomonas is the only one specifically adapted to infect plants. These hosts provide a particular habitat with a plentiful supply of carbohydrates. Phytomonas sp. lacks a cytochrome-mediated respiratory chain and Krebs cycle, and ATP production relies predominantly on glycolysis. We have characterised the complete gene encoding a putative pyruvate/indolepyruvate decarboxylase (PDC/IPDC) (548 amino acids) of P. serpens, that displays high amino acid sequence similarity with phytobacteria and Leishmania enzymes. No orthologous PDC/IPDC genes were found in Trypanosoma cruzi or T. brucei. Conservation of the PDC/IPDC gene sequence was verified in 14 Phytomonas isolates. A phylogenetic analysis shows that Phytomonas protein is robustly monophyletic with Leishmania spp. and C. fasciculata enzymes. In the trees this clade appears as a sister group of indolepyruvate decarboxylases of gamma-proteobacteria. This supports the proposition that a horizontal gene transfer event from a donor phytobacteria to a recipient ancestral trypanosome has occurred prior to the separation between Phytomonas. Leishmania and Crithidia. We have measured the PDC activity in P. serpens cell extracts. The enzyme has a Km value for pyruvate of 1.4 mM. The acquisition of a PDC, a key enzyme in alcoholic fermentation, explains earlier observations that ethanol is one of the major end-products of glucose catabolism under aerobic and anaerobic conditions. This represents an alternative and necessary route to reoxidise part of the NADH produced in the highly demanding glycolytic pathway and highlights the importance of this type of event in metabolic adaptation. (C) 2012 Elsevier B.V. All rights reserved.

Automatic Design of Boolean Networks for Modelling Differentiation Trees

Real living cell is a complex system governed by many process which are not yet fully understood: the process of cell differentiation is one of these. In this thesis work we make use of a cell differentiation model to develop gene regulatory networks (Boolean networks) with desired differentiation dynamics. To accomplish this task we have introduced techniques of automatic design and we have performed experiments using various differentiation trees. The results obtained have shown that the developed algorithms, except the Random algorithm, are able to generate Boolean networks with interesting differentiation dynamics. Moreover, we have presented some possible future applications and developments of the cell differentiation model in robotics and in medical research. Understanding the mechanisms involved in biological cells can gives us the possibility to explain some not yet understood dangerous disease, i.e the cancer. Le cellula è un sistema complesso governato da molti processi ancora non pienamente compresi: il differenziamento cellulare è uno di questi. In questa tesi utilizziamo un modello di differenziamento cellulare per sviluppare reti di regolazione genica (reti Booleane) con dinamiche di differenziamento desiderate. Per svolgere questo compito abbiamo introdotto tecniche di progettazione automatica e abbiamo eseguito esperimenti utilizzando vari alberi di differenziamento. I risultati ottenuti hanno mostrato che gli algoritmi sviluppati, eccetto l'algoritmo Random, sono in grado di poter generare reti Booleane con dinamiche di differenziamento interessanti. Inoltre, abbiamo presentato alcune possibili applicazioni e sviluppi futuri del modello di differenziamento in robotica e nella ricerca medica. Capire i meccanismi alla base del funzionamento cellulare può fornirci la possibilità di spiegare patologie ancora oggi non comprese, come il cancro.

Speciation with gene-flow in eastern North American red oaks (Quercus section Lobatae)

As foundational species, oaks (Quercus : Fagaceae) support the activities of both humans and wildlife. However, many oaks in North America are declining, a crisis exacerbated by the previous disappearance of other hard mast-producing trees. In addition, the economic demands placed on this drought-tolerant group may intensify if climate change extirpates other, relatively mesophytic species. Genetic tools can help address these management challenges. To this end, we developed a suite of 27 microsatellite markers, of which 22 are derived from expressed sequence tags (ESTs). Many of these markers bear significant homology to known genes and may be able to directly assay functional genetic variation. Markers obtained from enriched microsatellite libraries, on the other hand, are typically located in heterochromatic regions and should reflect demographic processes. Considered jointly, genic and genomic microsatellites can elucidate patterns of gene-flow and natural selection, which are fundamental to both an organism's evolutionary ecology and conservation biology. To this end, we employed the developed markers in an FST-based genome scan to detect the signature of divergent selection among the red oaks (Quercus section Lobatae). Three candidate genes with putative roles in stress responses demonstrated patterns of diversity consistent with adaptation to heterogeneous selective pressures. These genes may be important in both local genetic adaptation within species and divergence among them. Next, we used an isolation-with-migration model to quantify levels of gene-flow among four red oaks species during speciation. Both speciation in allopatry and speciation with gene-flow were found to be major drivers of red oak biodiversity. Loci playing a key role in speciation are also likely to be ecologically important within species

Genetic relationships of Aeromonas strains inferred from 16S rRNA, gyrB and rpoB gene sequences

Genetic relationships among bacterial strains belonging to the genus Aeromonas were inferred from 16S rRNA, gyrB and rpoB gene sequences. Twenty-eight type or collection strains of the recognized species or subspecies and 33 Aeromonas strains isolated from human and animal specimens as well as from environmental samples were included in the study. As reported previously, the 16S rRNA gene sequence is highly conserved within the genus Aeromonas, having only limited resolution for this very tight group of species. Analysis of a 1.1 kb gyrB sequence confirmed that this gene has high resolving power, with maximal interspecies divergence of 15.2 %. Similar results were obtained by sequencing only 517 bp of the rpoB gene, which showed maximal interspecies divergence of 13 %. The topologies of the gyrB- and rpoB-derived trees were similar. The results confirm the close relationship of species within the genus Aeromonas and show that a phylogenetic approach including several genes is suitable for improving the complicated taxonomy of the genus.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

CsRAV1: a candidate gene for improving lignocellulosic biomass yield

Fast-growing tree species of Populus spp.,Salix spp. and Eucalyptus spp. are cultivated to produce wood in a short time. Poplars are cultivated with cycles of 15-18 years to obtain saw timber and peeler logs, but when grown as short -rotation coppice(SRC) to produce biomass, planting density increases and rotation is considerably reduced (3-5 years). In this regard, research efforts are focused in the identification of traits and loci that allow the generation of improved SRC biomass-yielding genotypes. Biomass yield is a highly complex trait as it is the combined outcome of many other complex traits, each under separate polygenic control. Among profitable biomass yield-related traits are the amount of sylleptic branching and the length of winter dormancy. In poplar and in a few other Salicaceae species some lateral buds grow out sylleptically, the same season in which they form without the need of an intervening rest period. Sylleptic branching in poplar increases branch number, leaf area and general growth of the tree in its early years, and is a reasonable predictor of coppice yield. On the other hand, the length of winter dormancy determines the extent of the growth period. Our group has characterized the RAV1 gene of Castanea sativa (CsRAV1), encoding a transcription factor of the subfamily RAV (Related to ABI3/VP1). CsRAV1 expression shows a marked seasonal pattern, being higher in autumn and winter both in stems and buds. We generated transgenic lines of the hybrid clone Populus tremulax P. alba INRA 717 1B4 constitutively expressing CsRAV 1. These CsRAV1-expressing poplars develop sylleptic branches only a few weeks after potting. In addition to the sylleptic branching phenotype, these trees show phenological features that could give rise to an extended growth period. We are currently assessing the phenotype and behavior of these transgenic trees in a field trial, and ultimately, we will evaluate the impact on lignocellulosic biomass quality and production.

Characterization of a glycosylase family gene specifically expressed during winter dormancy in woody plants

Winter dormancy is the strategy used by perennial plants to survive the harsh conditions of winter in temperate and cold regions. This complex mechanism is characterized by cessation of the meristems activity, which is accompanied by the budset, the acquisition of a high tolerance to the cold temperatures and, in the case of deciduous trees, by the senescence and leaf abscission. In long-lived forest species, the length of the dormancy period limits the growing season, affecting wood production and quality. A Suppression Subtractive Hybridization (SSH) enriched in genes overexpressed during the process of winter dormancy in chesnut stems identified a DNA glycosylase gene. In order to study its role in the establishment and maintenance of the winter dormancy, a molecular characterization and seasonal expression were performed. Furthermore, we have obtained poplar transgenic plantlets overexpressing the chesnut gene.

Gene content phylogeny of herpesviruses

Clusters of orthologous groups [COGs; Tatusov, R. L., Koonin, E. V. & Lipman, D. J. (1997) Science 278, 631–637] were identified for a set of 13 completely sequenced herpesviruses. Each COG represented a family of gene products conserved across several herpes genomes. These families were defined without using an arbitrary threshold criterion based on sequence similarity. The COG technique was modified so that variable stringency in COG construction was possible. High stringencies identify a core set of highly conserved genes. Varying COG stringency reveals differences in the degree of conservation between functional classes of genes. The COG data were used to construct whole-genome phylogenetic trees based on gene content. These trees agree well with trees based on other methods and are robust when tested by bootstrap analysis. The COG data also were used to construct a reciprocal tree that clustered genes with similar phylogenetic profiles. This clustering may give clues to genes with related functions or with related histories of acquisition and loss during herpesvirus evolution.

Recursive partitioning for tumor classification with gene expression microarray data

Precise classification of tumors is critically important for cancer diagnosis and treatment. It is also a scientifically challenging task. Recently, efforts have been made to use gene expression profiles to improve the precision of classification, with limited success. Using a published data set for purposes of comparison, we introduce a methodology based on classification trees and demonstrate that it is significantly more accurate for discriminating among distinct colon cancer tissues than other statistical approaches used heretofore. In addition, competing classification trees are displayed, which suggest that different genes may coregulate colon cancers.

Ozone Sensitivity in Hybrid Poplar Is Correlated with a Lack of Defense-Gene Activation1

Ozone is a major gaseous pollutant thought to contribute to forest decline. Although the physiological and morphological responses of forest trees to ozone have been well characterized, little is known about the molecular basis for these responses. Our studies compared the response to ozone of ozone-sensitive and ozone-tolerant clones of hybrid poplar (Populus maximowizii × Populus trichocarpa) at the physiological and molecular levels. Gas-exchange analyses demonstrated clear differences between the ozone-sensitive clone 388 and the ozone-tolerant clone 245. Although ozone induced a decrease in photosynthetic rate and stomatal conductance in both clones, the magnitude of the decrease in stomatal conductance was significantly greater in the ozone-tolerant clone. RNA-blot analysis established that ozone-induced mRNA levels for phenylalanine ammonia-lyase, O-methyltransferase, a pathogenesis-related protein, and a wound-inducible gene were significantly higher in the ozone-tolerant than in the ozone-sensitive plants. Wound- and pathogen-induced levels of these mRNAs were also higher in the ozone-tolerant compared with the ozone-sensitive plants. The different physiological and molecular responses to ozone exposure exhibited by clones 245 and 388 suggest that ozone tolerance involves the activation of salicylic-acid- and jasmonic-acid-mediated signaling pathways, which may be important in triggering defense responses against oxidative stress.

Detection of a major gene for resistance to fusiform rust disease in loblolly pine by genomic mapping.

Genomic mapping has been used to identify a region of the host genome that determines resistance to fusiform rust disease in loblolly pine where no discrete, simply inherited resistance factors had been previously found by conventional genetic analysis over four decades. A resistance locus, behaving as a single dominant gene, was mapped by association with genetic markers, even though the disease phenotype deviated from the expected Mendelian ratio. The complexity of forest pathosystems and the limitations of genetic analysis, based solely on phenotype, had led to an assumption that effective long-term disease resistance in trees should be polygenic. However, our data show that effective long-term resistance can be obtained from a single qualitative resistance gene, despite the presence of virulence in the pathogen population. Therefore, disease resistance in this endemic coevolved forest pathosystem is not exclusively polygenic. Genomic mapping now provides a powerful tool for characterizing the genetic basis of host pathogen interactions in forest trees and other undomesticated, organisms, where conventional genetic analysis often is limited or not feasible.

Seven species of broadleaf deciduous trees for windbreaks : effect of spacing distance and age on their survival and growth at Cheyenne, Wyo. /

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Cambial meristem dormancy in trees involves extensive remodelling of the transcriptome

The establishment of the dormant state in meristems involves considerable physiological and metabolic alterations necessary for surviving unfavourable growth conditions. However, a global molecular analysis of dormancy in meristems has been hampered by the difficulty in isolating meristem cells. We used cryosectioning to isolate purified cambial meristem cells from the woody plant Populus tremula during active growth and dormancy. These samples were used to generate meristem-specific cDNA libraries and for cDNA microarray experiments to define the global transcriptional changes underlying cambial dormancy. The results indicate a significant reduction in the complexity of the cambial transcriptome in the dormant state. Although cell division is terminated in the dormant cambium, the cell cycle machinery appears to be maintained in a skeletal state as suggested by the continued presence of transcripts for several cell cycle regulators. The downregulation of PttPIN1 and PttPIN2 transcripts explains the reduced basipetal polar auxin transport during dormancy. The induction of a member of the SINA family of ubiquitin ligases implicated in auxin signalling indicates a potential mechanism for modulation of auxin sensitivity during cambial dormancy. The metabolic alterations during dormancy are mirrored in the induction of genes involved in starch breakdown and the glyoxysomal cycle. Interestingly, the induction of RGA1 like gene suggests modification of gibberellin signalling in cambial dormancy. The induction of genes such as poplar orthologues of FIE and HAP2 indicates a potential role for these global regulators of transcription in orchestrating extensive changes in gene expression during dormancy.