Literature DB >> 17630278

Natural variation among Arabidopsis thaliana accessions for transcriptome response to exogenous salicylic acid.

Hans van Leeuwen1, Daniel J Kliebenstein, Marilyn A L West, Kyunga Kim, Remco van Poecke, Fumiaki Katagiri, Richard W Michelmore, Rebecca W Doerge, Dina A St Clair.   

Abstract

Little is known about how gene expression variation within a given species controls phenotypic variation under different treatments or environments. Here, we surveyed the transcriptome response of seven diverse Arabidopsis thaliana accessions in response to two treatments: the presence and absence of exogenously applied salicylic acid (SA), an important signaling molecule in plant defense. A factorial experiment was conducted with three biological replicates per accession with and without applications of SA and sampled at three time points posttreatment. Transcript level data from Affymetrix ATH1 microarrays were analyzed on both per-gene and gene-network levels to detect expression level polymorphisms associated with SA response. Significant variation in transcript levels for response to SA was detected among the accessions, with relatively few genes responding similarly across all accessions and time points. Twenty-five of 54 defined gene networks identified from other microarray studies (pathogen-challenged Columbia [Col-0]) showed a significant response to SA in one or more accessions. A comparison of gene-network relationships in our data to the pathogen-challenged Col-0 data demonstrated a higher-order conservation of linkages between defense response gene networks. Cvi-1 and Mt-0 appeared to have globally different SA responsiveness in comparison to the other five accessions. Expression level polymorphisms for SA response were abundant at both individual gene and gene-network levels in the seven accessions, suggesting that natural variation for SA response is prevalent in Arabidopsis.

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Year:  2007        PMID: 17630278      PMCID: PMC1955704          DOI: 10.1105/tpc.107.050641

Source DB:  PubMed          Journal:  Plant Cell        ISSN: 1040-4651            Impact factor:   11.277


  36 in total

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2.  Genomic survey of gene expression diversity in Arabidopsis thaliana.

Authors:  Daniel J Kliebenstein; Marilyn A L West; Hans van Leeuwen; Kyunga Kim; R W Doerge; Richard W Michelmore; Dina A St Clair
Journal:  Genetics       Date:  2005-10-03       Impact factor: 4.562

3.  Global eQTL mapping reveals the complex genetic architecture of transcript-level variation in Arabidopsis.

Authors:  Marilyn A L West; Kyunga Kim; Daniel J Kliebenstein; Hans van Leeuwen; Richard W Michelmore; R W Doerge; Dina A St Clair
Journal:  Genetics       Date:  2006-12-18       Impact factor: 4.562

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-01-18       Impact factor: 11.205

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  44 in total

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Authors:  Michael Bartsch; Paweł Bednarek; Pedro D Vivancos; Bernd Schneider; Edda von Roepenack-Lahaye; Christine H Foyer; Erich Kombrink; Dierk Scheel; Jane E Parker
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2.  Physiological genomics of response to soil drying in diverse Arabidopsis accessions.

Authors:  David L Des Marais; John K McKay; James H Richards; Saunak Sen; Tierney Wayne; Thomas E Juenger
Journal:  Plant Cell       Date:  2012-03-09       Impact factor: 11.277

3.  Natural variation of transcriptional auxin response networks in Arabidopsis thaliana.

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4.  Progress and Promise in using Arabidopsis to Study Adaptation, Divergence, and Speciation.

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Review 5.  Systems biology uncovers the foundation of natural genetic diversity.

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Journal:  Plant Physiol       Date:  2009-11-20       Impact factor: 8.340

6.  Global changes in gene expression, assayed by microarray hybridization and quantitative RT-PCR, during acclimation of three Arabidopsis thaliana accessions to sub-zero temperatures after cold acclimation.

Authors:  Mai Q Le; Majken Pagter; Dirk K Hincha
Journal:  Plant Mol Biol       Date:  2014-10-14       Impact factor: 4.076

7.  Quantitative genetic analysis of salicylic acid perception in Arabidopsis.

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Journal:  Planta       Date:  2011-05-26       Impact factor: 4.116

8.  Network modeling reveals prevalent negative regulatory relationships between signaling sectors in Arabidopsis immune signaling.

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9.  Identifying genotype-by-environment interactions in the metabolism of germinating arabidopsis seeds using generalized genetical genomics.

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