184 research outputs found

    Global expression profiling in leaves of free-growing aspen

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    <p>Abstract</p> <p>Background</p> <p>Genomic studies are routinely performed on young plants in controlled environments which is very different from natural conditions. In reality plants in temperate countries are exposed to large fluctuations in environmental conditions, in the case of perennials over several years. We have studied gene expression in leaves of a free-growing aspen (<it>Populus tremula</it>) throughout multiple growing seasons</p> <p>Results</p> <p>We show that gene expression during the first month of leaf development was largely determined by a developmental program although leaf expansion, chlorophyll accumulation and the speed of progression through this program was regulated by the temperature. We were also able to define "transcriptional signatures" for four different substages of leaf development. In mature leaves, weather factors were important for gene regulation.</p> <p>Conclusion</p> <p>This study shows that multivariate methods together with high throughput transcriptional methods in the field can provide additional, novel information as to plant status under changing environmental conditions that is impossible to mimic in laboratory conditions. We have generated a dataset that could be used to e.g. identify marker genes for certain developmental stages or treatments, as well as to assess natural variation in gene expression.</p

    K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space

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    <p>Abstract</p> <p>Background</p> <p>Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projections to Latent Structures (K-OPLS) method offers unique properties facilitating separate modelling of predictive variation and structured noise in the feature space. While providing prediction results similar to other kernel-based methods, K-OPLS features enhanced interpretational capabilities; allowing detection of unanticipated systematic variation in the data such as instrumental drift, batch variability or unexpected biological variation.</p> <p>Results</p> <p>We demonstrate an implementation of the K-OPLS algorithm for MATLAB and R, licensed under the GNU GPL and available at <url>http://www.sourceforge.net/projects/kopls/</url>. The package includes essential functionality and documentation for model evaluation (using cross-validation), training and prediction of future samples. Incorporated is also a set of diagnostic tools and plot functions to simplify the visualisation of data, e.g. for detecting trends or for identification of outlying samples. The utility of the software package is demonstrated by means of a metabolic profiling data set from a biological study of hybrid aspen.</p> <p>Conclusion</p> <p>The properties of the K-OPLS method are well suited for analysis of biological data, which in conjunction with the availability of the outlined open-source package provides a comprehensive solution for kernel-based analysis in bioinformatics applications.</p

    A cross-species transcriptomics approach to identify genes involved in leaf development

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    <p>Abstract</p> <p>Background</p> <p>We have made use of publicly available gene expression data to identify transcription factors and transcriptional modules (regulons) associated with leaf development in <it>Populus</it>. Different tissue types were compared to identify genes informative in the discrimination of leaf and non-leaf tissues. Transcriptional modules within this set of genes were identified in a much wider set of microarray data collected from leaves in a number of developmental, biotic, abiotic and transgenic experiments.</p> <p>Results</p> <p>Transcription factors that were over represented in leaf EST libraries and that were useful for discriminating leaves from other tissues were identified, revealing that the C2C2-YABBY, CCAAT-HAP3 and 5, MYB, and ZF-HD families are particularly important in leaves. The expression of transcriptional modules and transcription factors was examined across a number of experiments to select those that were particularly active during the early stages of leaf development. Two transcription factors were found to collocate to previously published Quantitative Trait Loci (QTL) for leaf length. We also found that miRNA family 396 may be important in the control of leaf development, with three members of the family collocating with clusters of leaf development QTL.</p> <p>Conclusion</p> <p>This work provides a set of candidate genes involved in the control and processes of leaf development. This resource can be used for a wide variety of purposes such as informing the selection of candidate genes for association mapping or for the selection of targets for reverse genetics studies to further understanding of the genetic control of leaf size and shape.</p

    Chemometrics in Metabonomics

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    Metabolite Signature during Short-Day Induced Growth Cessation in Populus

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    The photoperiod is an important environmental signal for plants, and influences a wide range of physiological processes. For woody species in northern latitudes, cessation of growth is induced by short photoperiods. In many plant species, short photoperiods stop elongational growth after a few weeks. It is known that plant daylength detection is mediated by Phytochrome A (PHYA) in the woody hybrid aspen species. However, the mechanism of dormancy involving primary metabolism remains unclear. We studied changes in metabolite profiles in hybrid aspen leaves (young, middle, and mature leaves) during short-day-induced growth cessation, using a combination of gas chromatography–time-of-flight mass spectrometry, and multivariate projection methods. Our results indicate that the metabolite profiles in mature source leaves rapidly change when the photoperiod changes. In contrast, the differences in young sink leaves grown under long and short-day conditions are less distinct. We found short daylength induced growth cessation in aspen was associated with rapid changes in the distribution and levels of diverse primary metabolites. In addition, we conducted metabolite profiling of leaves of PHYA overexpressor (PHYAOX) and those of the control to find the discriminative metabolites between PHYAOX and the control under the short-day conditions. The metabolite changes observed in PHYAOX leaves, together with those in the source leaves, identified possible candidates for the metabolite signature (e.g., 2-oxo-glutarate, spermidine, putrescine, 4-amino-butyrate, and tryptophan) during short-day-induced growth cessation in aspen leaves

    Bit errors in the Kirchhoff-Law–Johnson-Noise secure key exchange

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    Background: Accuracy in malaria diagnosis and staging is vital in order to reduce mortality and post infectious sequelae. Herein we present a metabolomics approach to diagnostic staging of malaria infection, specifically Plasmodium falciparum infection in children. Methods: A group of 421 patients between six months and six years of age with mild and severe states of malaria with age-matched controls were included in the study, 107, 192 and 122 individuals respectively. A multivariate design was used as basis for representative selection of twenty patients in each category. Patient plasma was subjected to Gas Chromatography-Mass Spectrometry analysis and a full metabolite profile was produced from each patient. In addition, a proof-of-concept model was tested in a Plasmodium berghei in-vivo model where metabolic profiles were discernible over time of infection. Results: A two-component principal component analysis (PCA) revealed that the patients could be separated into disease categories according to metabolite profiles, independently of any clinical information. Furthermore, two sub-groups could be identified in the mild malaria cohort who we believe represent patients with divergent prognoses. Conclusion: Metabolite signature profiling could be used both for decision support in disease staging and prognostication

    MASQOT: a method for cDNA microarray spot quality control

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    BACKGROUND: cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more. RESULTS: A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies. CONCLUSION: The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process

    Metabolic profiling of zebrafish embryo development from blastula period to early larval stages

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    The zebrafish embryo is a popular model for drug screening, disease modelling and molecular genetics. In this study, samples were obtained from zebrafish at different developmental stages. The stages that were chosen were 3/4, 4/5, 24, 48, 72 and 96 hours post fertilization (hpf). Each sample included fifty embryos. The samples were analysed using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). Principle component analysis (PCA) was applied to get an overview of the data and orthogonal projection to latent structure discriminant analysis (OPLS-DA) was utilised to discriminate between the developmental stages. In this way, changes in metabolite profiles during vertebrate development could be identified. Using a GC-TOF-MS metabolomics approach it was found that nucleotides and metabolic fuel (glucose) were elevated at early stages of embryogenesis, whereas at later stages amino acids and intermediates in the Krebs cycle were abundant. This agrees with zebrafish developmental biology, as organs such as the liver and pancreas develop at later stages. Thus, metabolomics of zebrafish embryos offers a unique opportunity to investigate large scale changes in metabolic processes during important developmental stages in vertebrate development. In terms of stability of the metabolic profile and viability of the embryos, it was concluded at 72 hpf was a suitable time point for the use of zebrafish as a model system in numerous scientific applications

    Serum metabolite signature predicts the acute onset of diabetes in spontaneously diabetic congenic BB rats

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    The clinical presentation of type 1 diabetes is preceded by a prodrome of beta cell autoimmunity. We probed the short period of subtle metabolic abnormalities, which precede the acute onset of diabetes in the spontaneously diabetic BB rat, by analyzing the serum metabolite profile detected with combined gas chromatography/mass spectrometry (GC/MS) and liquid chromatography/mass spectrometry (LC/MS). We found that the metabolite pattern prior to diabetes included 17 metabolites, which differed between individual diabetes prone (DP) BB rats and their age and sex matched diabetes resistant (DR) littermates. As the metabolite signature at the 40 days of age baseline failed to distinguish DP from DR, there was a brief 10-day period after which the diabetes prediction pattern was observed, that includes fatty acids (e.g. oleamide), phospholipids (e.g. phosphocholines) and amino acids (e.g. isoleucine). It is concluded that distinct changes in the serum metabolite pattern predict type 1 diabetes and precede the appearance of insulitis in spontaneously diabetic BB DP rats. This observation should prove useful to dissect mechanisms of type 1 diabetes

    Перспективы развития логистической деятельности мелких торговых организаций Беларуси

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    Дана оценка логистической деятельности мелких торговых организаций Беларуси и намечены пути ее совершенствования
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