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University of California-San Diego: Dataset Details, ID=GSE23301

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Superfund Research Program

Detection and Models of Toxicant Exposure

Center Director: Robert H. Tukey
Grant Number: P42ES010337
Funding Period: 2000-2023
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Title: Quantitative transcriptomic analysis of abscisic acid-induced and reactive oxygen species-dependent expression changes and proteomic profiling in Arabidopsis suspension cells

Accession Number: GSE23301

Link to Dataset:

Repository: Gene Expression Omnibus (GEO)

Data Type(s): Gene Expression

Experiment Type(s): Expression profiling by array

Organism(s): Arabidopsis thaliana

Summary: Early rapid changes in response to the phytohormone abscisic acid (ABA) have been observed at the transcript level, but little is known how these transcript changes translate to changes in protein abundance under the same conditions. Here we have performed a global quantitative analysis of transcript and protein changes in Arabidopsis suspension cells in response to ABA using microarrays and quantitative proteomics. In summary, 3494 transcripts and 50 proteins were significantly regulated by ABA over a treatment period of 20–24 h. Abscisic acid also caused a rapid and strong increase in production of extracellular reactive oxygen species (ROS) with an average half-rise time of 33 sec. A subset of ABA-regulated transcripts were differentially regulated in the presence of the ROS scavenger dimethylthiourea (DMTU) as compared with ABA alone, suggesting a role for ROS in the regulation of these ABA-induced genes. Transcript changes showed an overall poor correlation to protein changes (r = 0.66). Only a subset of genes was regulated at the transcript and protein level, including known ABA marker genes. We furthermore identified ABA regulation of proteins that function in a branch of glucosinolate catabolism previously not associated with ABA signaling. The discovery of genes that were differentially regulated at the transcript and at the protein level emphasizes the strength of our combined approach. In summary, our dataset not only expands previous studies on gene and protein regulation in response to ABA, but rather uncovers unique aspects of the ABA regulon and gives rise to additional mechanisms regulated by ABA.

Publication(s) associated with this dataset:
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