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      Transcriptome-Wide Mapping of Pea Seed Ageing Reveals a Pivotal Role for Genes Related to Oxidative Stress and Programmed Cell Death


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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°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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          Redox environment of the cell as viewed through the redox state of the glutathione disulfide/glutathione couple.

          Redox state is a term used widely in the research field of free radicals and oxidative stress. Unfortunately, it is used as a general term referring to relative changes that are not well defined or quantitated. In this review we provide a definition for the redox environment of biological fluids, cell organelles, cells, or tissue. We illustrate how the reduction potential of various redox couples can be estimated with the Nernst equation and show how pH and the concentrations of the species comprising different redox couples influence the reduction potential. We discuss how the redox state of the glutathione disulfide-glutathione couple (GSSG/2GSH) can serve as an important indicator of redox environment. There are many redox couples in a cell that work together to maintain the redox environment; the GSSG/2GSH couple is the most abundant redox couple in a cell. Changes of the half-cell reduction potential (E(hc)) of the GSSG/2GSH couple appear to correlate with the biological status of the cell: proliferation E(hc) approximately -240 mV; differentiation E(hc) approximately -200 mV; or apoptosis E(hc) approximately -170 mV. These estimates can be used to more fully understand the redox biochemistry that results from oxidative stress. These are the first steps toward a new quantitative biology, which hopefully will provide a rationale and understanding of the cellular mechanisms associated with cell growth and development, signaling, and reductive or oxidative stress.
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            Normalization of cDNA microarray data.

            Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.
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              Comprehensive algorithm for quantitative real-time polymerase chain reaction.

              Quantitative real-time polymerase chain reactions (qRT-PCR) have become the method of choice for rapid, sensitive, quantitative comparison of RNA transcript abundance. Useful data from this method depend on fitting data to theoretical curves that allow computation of mRNA levels. Calculating accurate mRNA levels requires important parameters such as reaction efficiency and the fractional cycle number at threshold (CT) to be used; however, many algorithms currently in use estimate these important parameters. Here we describe an objective method for quantifying qRT-PCR results using calculations based on the kinetics of individual PCR reactions without the need of the standard curve, independent of any assumptions or subjective judgments which allow direct calculation of efficiency and CT. We use a four-parameter logistic model to fit the raw fluorescence data as a function of PCR cycles to identify the exponential phase of the reaction. Next, we use a three-parameter simple exponent model to fit the exponential phase using an iterative nonlinear regression algorithm. Within the exponential portion of the curve, our technique automatically identifies candidate regression values using the P-value of regression and then uses a weighted average to compute a final efficiency for quantification. For CT determination, we chose the first positive second derivative maximum from the logistic model. This algorithm provides an objective and noise-resistant method for quantification of qRT-PCR results that is independent of the specific equipment used to perform PCR reactions.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                29 October 2013
                : 8
                : 10
                [1 ]Plant Germplasm and Genomics Center, Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, People's Republic of China
                [2 ]Seed Conservation Department, Royal Botanic Gardens, Kew, Ardingly, West Sussex, United Kingdom
                [3 ]Departamento de Fisiología Vegetal, Centro Hispano-Luso de Investigaciones Agrarias (CIALE), Facultad de Biología. Universidad de Salamanca, Salamanca, Spain
                [4 ]Institute for Biology II, Botany/Plant Physiology, Faculty of Biology, Albert-Ludwigs-University Freiburg, Freiburg, Germany
                [5 ]Institute for Plant Genetics, Unit IV – Plant Genomics, Leibniz Universität Hannover, Hannover, Germany
                Queen's University Belfast, United Kingdom
                Author notes

                Competing Interests: The Millennium Seed Bank Project is supported by the Millennium Commission, The Wellcome Trust, Orange Plc and Defra. The authors confirm that the funding from Orange Plc does not alter their adherence to all of the PLOS ONE policies on sharing data and materials.

                Conceived and designed the experiments: IK HC DO OL KG HK GLM. Performed the experiments: HC DO KG. Analyzed the data: LC DO HC KG. Contributed reagents/materials/analysis tools: HK OL GLM. Wrote the paper: LC HC DO KG IK.


                Current address: School of Biological Sciences, Plant Molecular Science and Centre for Systems and Synthetic Biology, Royal Holloway, University of London, Egham, Surrey, United Kingdom


                Current address: Institute of Botany, and Center of Molecular Biosciences, University of Innsbruck, Innsbruck, Austria


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 15
                This work was supported by the Spanish Ministerio de Educación y Ciencia and Junta de Castilla y León [BIO2011-26940, CSD2007-00057(TRANSPLANTA) and SA048A10-2 to O.L.], the German Research Foundation [DFGLe720/7 to G.L.M.], and the Chinese Academy of Sciences [KSCX2-EW-J-24 and Y3221411W1 to H.C.]. The Millennium Seed Bank Project is supported by the Millennium Commission, The Wellcome Trust, Orange Plc. and Defra. The Royal Botanic Gardens, Kew receive grant-in-aid from Defra. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article



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