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BMC Syst Biol. 2012; 6: 100.
Published online Aug 16, 2012. doi:  10.1186/1752-0509-6-100
PMCID: PMC3490714
Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
Papapit Ingkasuwan,1 Supatcharee Netrphan,2 Sukon Prasitwattanaseree,3 Morakot Tanticharoen,1 Sakarindr Bhumiratana,1 Asawin Meechai,4 Jeerayut Chaijaruwanich,5 Hideki Takahashi,6,7 and Supapon Cheevadhanarakcorresponding author1
1School of Bioresources and Technology, King Mongkut’s University of Technology Thonburi, Bangkok, 10140, Thailand
2National Center for Genetic Engineering and Biotechnology, Pathumthani, 12120, Thailand
3Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand
4Department of Chemical Engineering, Faculty of Engineering, King Mongkut’s University of Technology Thonburi, Bangkok, 10140, Thailand
5Department of Computer Science, Faculty of Science, Chiang Mai University, Chiang Mai, 50200, Thailand
6RIKEN Plant Science Center, Yokohama, 230-0045, Japan
7Department of Biochemistry & Molecular Biology, Michigan State University, 603 Wilson Rd, East Lansing, MI, 48824, USA
corresponding authorCorresponding author.
Papapit Ingkasuwan: papapit_ing/at/yahoo.com; Supatcharee Netrphan: supatchareen/at/biotec.or.th; Sukon Prasitwattanaseree: sprasitwattanaseree/at/gmail.com; Morakot Tanticharoen: morakot.tan/at/kmutt.ac.th; Sakarindr Bhumiratana: sakarindr.bhu/at/kmutt.ac.th; Asawin Meechai: asawin.mee/at/kmutt.ac.th; Jeerayut Chaijaruwanich: jeerayut.c/at/cmu.ac.th; Hideki Takahashi: htakaha/at/msu.edu; Supapon Cheevadhanarak: supapon.che/at/kmutt.ac.th
Received February 23, 2012; Accepted June 20, 2012.
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 β-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.
Keywords: Arabidopsis thaliana, Constans-like, Indeterminate domain 5, Graphical Gaussian model, Starch synthase 4, Transcriptional regulation
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