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Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
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Document Title
Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
Author
Ingkasuwan P, Netrphan S, Prasitwattanaseree S, Tanticharoen M, Bhumiratana S, Meechai A, Chaijaruwanich J, Takahashi H, Cheevadhanarak S
Name from Authors Collection
Affiliations
King Mongkuts University of Technology Thonburi; National Science & Technology Development Agency - Thailand; National Center Genetic Engineering & Biotechnology (BIOTEC); Chiang Mai University; King Mongkuts University of Technology Thonburi; Chiang Mai University; RIKEN; Michigan State University
Type
Article
Source Title
BMC SYSTEMS BIOLOGY
Year
2012
Volume
6
Open Access
gold, Green Published
Publisher
BMC
DOI
10.1186/1752-0509-6-100
Format
Abstract
Background: Starch serves as a temporal storage of carbohydrates in plant leaves during day/night cycles. To study transcriptional regulatory modules of this dynamic metabolic process, we conducted gene regulation network analysis based on small-sample inference of graphical Gaussian model (GGM). Results: Time-series significant analysis was applied for Arabidopsis leaf transcriptome data to obtain a set of genes that are highly regulated under a diurnal cycle. A total of 1,480 diurnally regulated genes included 21 starch metabolic enzymes, 6 clock-associated genes, and 106 transcription factors (TF). A starch-clock-TF gene regulation network comprising 117 nodes and 266 edges was constructed by GGM from these 133 significant genes that are potentially related to the diurnal control of starch metabolism. From this network, we found that beta-amylase 3 (b-amy3: At4g17090), which participates in starch degradation in chloroplast, is the most frequently connected gene (a hub gene). The robustness of gene-to-gene regulatory network was further analyzed by TF binding site prediction and by evaluating global co-expression of TFs and target starch metabolic enzymes. As a result, two TFs, indeterminate domain 5 (AtIDD5: At2g02070) and constans-like (COL: At2g21320), were identified as positive regulators of starch synthase 4 (SS4: At4g18240). The inference model of AtIDD5-dependent positive regulation of SS4 gene expression was experimentally supported by decreased SS4 mRNA accumulation in Atidd5 mutant plants during the light period of both short and long day conditions. COL was also shown to positively control SS4 mRNA accumulation. Furthermore, the knockout of AtIDD5 and COL led to deformation of chloroplast and its contained starch granules. This deformity also affected the number of starch granules per chloroplast, which increased significantly in both knockout mutant lines. Conclusions: In this study, we utilized a systematic approach of microarray analysis to discover the transcriptional regulatory network of starch metabolism in Arabidopsis leaves. With this inference method, the starch regulatory network of Arabidopsis was found to be strongly associated with clock genes and TFs, of which AtIDD5 and COL were evidenced to control SS4 gene expression and starch granule formation in chloroplasts.
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Knowledge Taxonomy Level 1
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Funding Sponsor
Thailand Graduate Institute of Science and Technology (TGIST) [TGIST 01-47-048]; National Center for Genetic Engineering and Biotechnology (BIOTEC) [BT-B-02-PG-B5-4813]; BIOTEC, Thailand; RIKEN Plant Science Center, Japan; Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan; Bio-oriented Technology Research Advancement Institution (BRAIN)
License
CC BY
Rights
Ingkasuwan et al.; licensee BioMed Central Ltd.
Publication Source
WOS