5 resultados para microarrays

em Institutional Repository of Leibniz University Hannover


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Understanding of seed ageing, which leads to viability loss during storage, is vital for ex situ plant conservation and agriculture alike. Yet the potential for regulation at the transcriptional level has not been fully investigated. Here, we studied the relationship between seed viability, gene expression and glutathione redox status during artificial ageing of pea (Pisum sativum) seeds. Transcriptome-wide analysis using microarrays was complemented with qRT-PCR analysis of selected genes and a multilevel analysis of the antioxidant glutathione. Partial degradation of DNA and RNA occurred from the onset of artificial ageing at 60% RH and 50 degrees C, and transcriptome profiling showed that the expression of genes associated with programmed cell death, oxidative stress and protein ubiquitination were altered prior to any sign of viability loss. After 25 days of ageing viability started to decline in conjunction with progressively oxidising cellular conditions, as indicated by a shift of the glutathione redox state towards more positive values (>-190 mV). The unravelling of the molecular basis of seed ageing revealed that transcriptome reprogramming is a key component of the ageing process, which influences the progression of programmed cell death and decline in antioxidant capacity that ultimately lead to seed viability loss.

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Background: Expressed Sequence Tags (ESTs) are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings: Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis), expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions: MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants.

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Composite plants consisting of a wild-type shoot and a transgenic root are frequently used for functional genomics in legume research. Although transformation of roots using Agrobacterium rhizogenes leads to morphologically normal roots, the question arises as to whether such roots interact with arbuscular mycorrhizal (AM) fungi in the same way as wild-type roots. To address this question, roots transformed with a vector containing the fluorescence marker DsRed were used to analyse AM in terms of mycorrhization rate, morphology of fungal and plant subcellular structures, as well as transcript and secondary metabolite accumulations. Mycorrhization rate, appearance, and developmental stages of arbuscules were identical in both types of roots. Using Mt16kOLI1Plus microarrays, transcript profiling of mycorrhizal roots showed that 222 and 73 genes exhibited at least a 2-fold induction and less than half of the expression, respectively, most of them described as AM regulated in the same direction in wild-type roots. To verify this, typical AM marker genes were analysed by quantitative reverse transcription-PCR and revealed equal transcript accumulation in transgenic and wild-type roots. Regarding secondary metabolites, several isoflavonoids and apocarotenoids, all known to accumulate in mycorrhizal wild-type roots, have been found to be up-regulated in mycorrhizal in comparison with non-mycorrhizal transgenic roots. This set of data revealed a substantial similarity in mycorrhization of transgenic and wild-type roots of Medicago truncatula, validating the use of composite plants for studying AM-related effects.

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Background: Bio-conjugated nanoparticles are important analytical tools with emerging biological and medical applications. In this context, in situ conjugation of nanoparticles with biomolecules via laser ablation in an aqueous media is a highly promising one-step method for the production of functional nanoparticles resulting in highly efficient conjugation. Increased yields are required, particularly considering the conjugation of cost-intensive biomolecules like RNA aptamers. Results: Using a DNA aptamer directed against streptavidin, in situ conjugation results in nanoparticles with diameters of approximately 9 nm exhibiting a high aptamer surface density (98 aptamers per nanoparticle) and a maximal conjugation efficiency of 40.3%. We have demonstrated the functionality of the aptamer-conjugated nanoparticles using three independent analytical methods, including an agglomeration-based colorimetric assay, and solid-phase assays proving high aptamer activity. To demonstrate the general applicability of the in situ conjugation of gold nanoparticles with aptamers, we have transferred the method to an RNA aptamer directed against prostate-specific membrane antigen (PSMA). Successful detection of PSMA in human prostate cancer tissue was achieved utilizing tissue microarrays. Conclusions: In comparison to the conventional generation of bio-conjugated gold nanoparticles using chemical synthesis and subsequent bio-functionalization, the laser-ablation-based in situ conjugation is a rapid, one-step production method. Due to high conjugation efficiency and productivity, in situ conjugation can be easily used for high throughput generation of gold nanoparticles conjugated with valuable biomolecules like aptamers.

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Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.