Expression of senescence-enhanced genes in response to oxidative stress

Navabpour, Saeid

doi:10.1093/jxb/erg267

Cited by 243 publications

(152 citation statements)

References 39 publications

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“…7,8 Under normal growth conditions an intricate antioxidative defense system provides adequate guard against ROS, however environmental stress may cause ROS to rise to unfavorable levels causing irreparable cell damage. ROS also accumulate during agedependent leaf senescence, and many SAGs are known to be controlled by changes in cellular ROS levels 9 (see Genevestigator at www.genevestigator.com).…”

Section: H 2 O 2 -Responsive Sennacsmentioning

confidence: 99%

Salt-triggered expression of the ANAC092-dependent senescence regulon inArabidopsis thaliana

Balazadeh

Mueller‐Roeber

2010

Plant Signaling & Behavior

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Section: H 2 O 2 -Responsive Sennacsmentioning

confidence: 99%

Salt-triggered expression of the ANAC092-dependent senescence regulon inArabidopsis thaliana

Balazadeh

Mueller‐Roeber

2010

Plant Signaling & Behavior

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“…Endogenous H 2 O 2 levels in dnd1 mutants are increased from wild-type levels (Mateo et al, 2006). Reactive oxygen species molecules, such as H 2 O 2 , are critical to the PCD/senescence processes of plants (Navabpour et al, 2003;Overmyer et al, 2003;Hung and Kao, 2004;Guo and Crawford, 2005;Zimmermann et al, 2006). Here, we use the dnd1 mutant to evaluate the relationship between leaf Ca 2+ uptake during plant growth and leaf senescence.…”

mentioning

confidence: 99%

Leaf Senescence Signaling: The Ca2+-Conducting Arabidopsis Cyclic Nucleotide Gated Channel2 Acts through Nitric Oxide to Repress Senescence Programming

Smigel

Walker

et al. 2010

Plant Physiology

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Ca 2+ and nitric oxide (NO) are essential components involved in plant senescence signaling cascades. In other signaling pathways, NO generation can be dependent on cytosolic Ca 2+ . The Arabidopsis (Arabidopsis thaliana) mutant dnd1 lacks a plasma membrane-localized cation channel (CNGC2). We recently demonstrated that this channel affects plant response to pathogens through a signaling cascade involving Ca 2+ modulation of NO generation; the pathogen response phenotype of dnd1 can be complemented by application of a NO donor. At present, the interrelationship between Ca 2+ and NO generation in plant cells during leaf senescence remains unclear. Here, we use dnd1 plants to present genetic evidence consistent with the hypothesis that Ca 2+ uptake and NO production play pivotal roles in plant leaf senescence. Leaf Ca 2+ accumulation is reduced in dnd1 leaves compared to the wild type. Early senescence-associated phenotypes (such as loss of chlorophyll, expression level of senescence-associated genes, H 2 O 2 generation, lipid peroxidation, tissue necrosis, and increased salicylic acid levels) were more prominent in dnd1 leaves compared to the wild type. Application of a Ca 2+ channel blocker hastened senescence of detached wild-type leaves maintained in the dark, increasing the rate of chlorophyll loss, expression of a senescence-associated gene, and lipid peroxidation. Pharmacological manipulation of Ca 2+ signaling provides evidence consistent with genetic studies of the relationship between Ca 2+ signaling and senescence with the dnd1 mutant. Basal levels of NO in dnd1 leaf tissue were lower than that in leaves of wild-type plants. Application of a NO donor effectively rescues many dnd1 senescence-related phenotypes. Our work demonstrates that the CNGC2 channel is involved in Ca 2+ uptake during plant development beyond its role in pathogen defense response signaling. Work presented here suggests that this function of CNGC2 may impact downstream basal NO production in addition to its role (also linked to NO signaling) in pathogen defense responses and that this NO generation acts as a negative regulator during plant leaf senescence signaling.

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“…For example, the early light induced protein (ELIP1), one of the genes showing an early stress response pattern (1233), has been described by Adamska [4] as a component of the photo protection mechanism. A mitochondrial glutathione peroxidasea with a 1234 modeled base pattern has been reported by Navabpour et al [11] to be induced by oxidative stress. There was also a relatively high percentage of up-regulated genes involved in transcription, communication and stress-response which are thought to be components of early signalling pathways leading to morphological and physiological adaptations to the new environment.…”

Section: Application To An Arabidopsis Thaliana Light Adaptation Expementioning

confidence: 73%

Modeling Microarray Data: Interpreting and communicating the biological results

Pittelkow

Wilson

2006

Journal of Integrative Bioinformatics

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SummaryVarious statistical models have been proposed for detecting differential gene expression in data from microarray experiments. Given such detection, we are usually interested in describing the differential expression patterns. Due to the large number of genes that are typically analysed in microarray experiments, possibly more than ten thousand, the tasks of interpretation and communication of all the corresponding statistical models pose a considerable challenge, except perhaps in the simplest experiment involving only two groups. A further challenge is to find methods to summarize the resulting models. These challenges increase with experimental complexity. Biologists often wish to sort genes into 'classes' with similar response profiles/patterns. So, in this paper we describe a likelihood approach for assigning genes to these different class patterns for data from a replicated experimental design. The number of potential patterns increases very quickly as the number of combinations in the experimental design increases. In a two group experimental design there are only three patterns required to describe the mean response: up, down and no difference. For a factorial design with three treatments there are 13 different patterns, and with four levels there are 75 potential patterns to be considered, and so on. The approach is applied to the identification of differential response patterns in gene expression from a microarray experiment using RNA extracted from the leaves of Arabidopsis thaliana plants. We compare patterns of response found using additive and multiplicative models. A multiplicative model is more commonly used in the statistical analysis of microarray data because of the variance stabilizing properties of the logarithmic function. Then the error structure of the model is taken to be log-Normal. On the other hand, for the additive model the gene expression value is modeled directly as being from a gamma distribution which successfully accounts for the constant coefficient of variation often observed. Appropriate visualization displays for microarray data are important as a way of communicating the patterns of response amongst the genes. Here we use graphical 'icons' to represent the patterns of up/down and no response and two alternative displays, the Gene-plot and a grid layout to provide rapid overall summaries of the gene expression patterns.

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Expression of senescence-enhanced genes in response to oxidative stress

Cited by 243 publications

References 39 publications

Salt-triggered expression of the ANAC092-dependent senescence regulon inArabidopsis thaliana

Salt-triggered expression of the ANAC092-dependent senescence regulon inArabidopsis thaliana

Leaf Senescence Signaling: The Ca2+-Conducting Arabidopsis Cyclic Nucleotide Gated Channel2 Acts through Nitric Oxide to Repress Senescence Programming

Modeling Microarray Data: Interpreting and communicating the biological results

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