Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model

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).Res...

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Main Authors: Papapit Ingkasuwan, Supatcharee Netrphan, Sukon Prasitwattanaseree, Morakot Tanticharoen, Sakarindr Bhumiratana, Asawin Meechai, Jeerayut Chaijaruwanich, Hideki Takahashi, Supapon Cheevadhanarak
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Published: 2018
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/51365
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-513652018-09-04T06:09:11Z Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model Papapit Ingkasuwan Supatcharee Netrphan Sukon Prasitwattanaseree Morakot Tanticharoen Sakarindr Bhumiratana Asawin Meechai Jeerayut Chaijaruwanich Hideki Takahashi Supapon Cheevadhanarak Biochemistry, Genetics and Molecular Biology Computer Science Mathematics 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. © 2012 Ingkasuwan et al.; licensee BioMed Central Ltd. 2018-09-04T06:00:49Z 2018-09-04T06:00:49Z 2012-08-16 Journal 17520509 2-s2.0-84864931487 10.1186/1752-0509-6-100 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84864931487&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/51365
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Biochemistry, Genetics and Molecular Biology
Computer Science
Mathematics
spellingShingle Biochemistry, Genetics and Molecular Biology
Computer Science
Mathematics
Papapit Ingkasuwan
Supatcharee Netrphan
Sukon Prasitwattanaseree
Morakot Tanticharoen
Sakarindr Bhumiratana
Asawin Meechai
Jeerayut Chaijaruwanich
Hideki Takahashi
Supapon Cheevadhanarak
Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
description 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. © 2012 Ingkasuwan et al.; licensee BioMed Central Ltd.
format Journal
author Papapit Ingkasuwan
Supatcharee Netrphan
Sukon Prasitwattanaseree
Morakot Tanticharoen
Sakarindr Bhumiratana
Asawin Meechai
Jeerayut Chaijaruwanich
Hideki Takahashi
Supapon Cheevadhanarak
author_facet Papapit Ingkasuwan
Supatcharee Netrphan
Sukon Prasitwattanaseree
Morakot Tanticharoen
Sakarindr Bhumiratana
Asawin Meechai
Jeerayut Chaijaruwanich
Hideki Takahashi
Supapon Cheevadhanarak
author_sort Papapit Ingkasuwan
title Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
title_short Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
title_full Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
title_fullStr Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
title_full_unstemmed Inferring transcriptional gene regulation network of starch metabolism in Arabidopsis thaliana leaves using graphical Gaussian model
title_sort inferring transcriptional gene regulation network of starch metabolism in arabidopsis thaliana leaves using graphical gaussian model
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84864931487&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/51365
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