The AtGenExpress hormone and chemical treatment data set: experimental design, data evaluation, model data analysis and data access

Goda, Hideki; Sasaki, Eriko; Akiyama, Kenji; Maruyama‐Nakashita, Akiko; Nakabayashi, Kazumi; Wei-qiang, LI; Ogawa, Masaru; Yamauchi, Yukika; Preston, Jeremy; Aoki, K.; Kiba, Takatoshi; Takatsuto, Suguru; Fujioka, Shozo; Asami, Tadao; Nakano, Takeshi; Kato, Hisashi; Mizuno, Takeshi; Sakakibara, Hitoshi; Yamaguchi, Shinjiro; Nambara, Eiji; Kamiya, Yûji; Takahashi, Hideki; Hirai, Masami Yokota; Sakurai, Tetsuya; Shinozaki, Kazuo; Saito, Kazuki; Yoshida, Shigeo; Shimada, Yukihisa

doi:10.1111/j.1365-313x.2008.03510.x

Cited by 457 publications

(167 citation statements)

References 61 publications

(59 reference statements)

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“…Other genes have been shown experimentally to be responsive to drought or ABA such as LEA4-1 and OEP16-S (At1g32560 and At4g16160; [33,65]; Additional file 1: Figure S2B and Additional file 1: Figure S1A). The gene pairs were also examined for the extent of co-expression using AtGenExpress Visualisation Tool [38-40] which showed that while in some cases the genes showed very similar patterns of expression, there were also cases where the expression patterns of both genes differed significantly in terms of both temporal and spatial patterns and also in terms of their response to various stresses (Additional file 1: Figure S2). Several parameters can be taken into account when assessing if a gene pairs’ products might be directly linked functionally such as the extent of co-expression and the subcellular co-localization of the gene pair products.…”

Section: Resultsmentioning

confidence: 99%

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Bidirectional promoters in seed development and related hormone/stress responses

Kourmpetli

Lee

Hemsley³

et al. 2013

BMC Plant Biol

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BackgroundBidirectional promoters are common in genomes but under-studied experimentally, particularly in plants. We describe a targeted identification and selection of a subset of putative bidirectional promoters to identify genes involved in seed development and to investigate possible coordinated responses of gene pairs to conditions important in seed maturation such as desiccation and ABA-regulation.ResultsWe combined a search for 100–600 bp intergenic regions in the Arabidopsis genome with a cis-element based selection for those containing multiple copies of the G-box motif, CACGTG. One of the putative bidirectional promoters identified also contained a CE3 coupling element 5 bp downstream of one G-box and is identical to that characterized previously in the HVA1 promoter of barley. CE3 elements are significantly under-represented and under-studied in Arabidopsis. We further characterized the pair of genes associated with this promoter and uncovered roles for two small, previously uncharacterized, plant-specific proteins in Arabidopsis seed development and stress responses.ConclusionsUsing bioinformatics we identified putative bidirectional promoters involved in seed development and analysed expression patterns for a pair of plant-specific genes in various tissues and in response to hormones/stress. We also present preliminary functional analysis of these genes that is suggestive of roles in seed development.

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Section: Resultsmentioning

confidence: 99%

“…We used the AtGenExpress Visualisation Tool (AVT; http://jsp.weigelworld.org/expviz/expviz.jsp) to extract gene expression data where indicated using the datasets for development, abiotic stress, hormones and light [38-40]. …”

Section: Methodsmentioning

confidence: 99%

Bidirectional promoters in seed development and related hormone/stress responses

Kourmpetli

Lee

Hemsley³

et al. 2013

BMC Plant Biol

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“…Furthermore, OPDA-triggered signalling involves activation of TGA transcription factors [64]. The upregulation of PPTE, a reference gene for oxylipin signalling [39], might be the consequence of higher OPDA levels after the H-light transfer. The JA-antagonist SA decreased during N !…”

Section: Discussionmentioning

confidence: 99%

Kinetics of retrograde signalling initiation in the high light response of Arabidopsis thaliana

Alsharafa

Vogel

Oelze

et al. 2014

Phil. Trans. R. Soc. B

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High light acclimation depends on retrograde control of nuclear gene expression. Retrograde regulation uses multiple signalling pathways and thus exploits signal patterns. To maximally challenge the acclimation system, Arabidopsis thaliana plants were either adapted to 8 (low light (L-light)) or 80 µmol quanta m −2 s −1 (normal light (N-light)) and subsequently exposed to a 100- and 10-fold light intensity increase, respectively, to high light (H-light, 800 µmol quanta m −2 s −1 ), for up to 6 h. Both L → H- and N → H-light plants efficiently regulated CO 2 assimilation to a constant level without apparent damage and inhibition. This experimental set-up was scrutinized for time-dependent regulation and efficiency of adjustment. Transcriptome profiles revealed that N-light and L-light plants differentially accumulated 2119 transcripts. After 6 h in H-light, only 205 remained differently regulated between the L → H- and N → H-light plants, indicating efficient regulation allowing the plants to reach a similar transcriptome state. Time-dependent analysis of transcripts as markers for signalling pathways, and of metabolites and hormones as possibly involved transmitters, suggests that oxylipins such as oxophytodienoic acid and jasmonic acid, metabolites and redox cues predominantly control the acclimation response, whereas abscisic acid, salicylic acid and auxins play an insignificant or minor role.

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“…Several distinct types of baseline gene expression data exist: tissue, cancer or development profiles (usually absolute expression values), perturbations and diseases (relative values) and time courses and dose responses (absolute or relative values), or a combination of these spatial, temporal and response profiles. Examples of baseline data sets that have been published include the GNF human tissue panel [1], The Cancer Genome Atlas [2], the rat liver and kidney HESI baseline dataset [3], the NOWAC Postgenome Study [4], and the Arabidopsis AtGenExpress datasets for abiotic stress [5], plant development [6], or hormonal and chemical responses [7]. New technological platforms are also frequently assessed by generating data from control samples, resulting in baseline experimental datasets that can subsequently be used as a reference on these platforms.…”

Section: Introductionmentioning

confidence: 99%

ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions

Zimmermann¹,

Bleuler²,

Laule³

et al. 2014

BioData Mining

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Reference datasets are often used to compare, interpret or validate experimental data and analytical methods. In the field of gene expression, several reference datasets have been published. Typically, they consist of individual baseline or spike-in experiments carried out in a single laboratory and representing a particular set of conditions.Here, we describe a new type of standardized datasets representative for the spatial and temporal dimensions of gene expression. They result from integrating expression data from a large number of globally normalized and quality controlled public experiments. Expression data is aggregated by anatomical part or stage of development to yield a representative transcriptome for each category. For example, we created a genome-wide expression dataset representing the FDA tissue panel across 35 tissue types. The proposed datasets were created for human and several model organisms and are publicly available at http://www.expressiondata.org.

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The AtGenExpress hormone and chemical treatment data set: experimental design, data evaluation, model data analysis and data access

Cited by 457 publications

References 61 publications

Bidirectional promoters in seed development and related hormone/stress responses

Bidirectional promoters in seed development and related hormone/stress responses

Kinetics of retrograde signalling initiation in the high light response of Arabidopsis thaliana

ExpressionData - A public resource of high quality curated datasets representing gene expression across anatomy, development and experimental conditions

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