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Qualitative network models and genome-wide expression data define carbon/nitrogen-responsive molecular machines in Arabidopsis

Rodrigo A Gutiérrez12, Laurence V Lejay15, Alexis Dean1, Francesca Chiaromonte3, Dennis E Shasha4 and Gloria M Coruzzi1*

Author Affiliations

1 Department of Biology, New York University, Washington Square East, New York, NY 10003, USA

2 Departamento de Genética Molecular y Microbiología, Pontificia Universidad Católica de Chile. Alameda 340. 8331010. Santiago, Chile

3 Department of Statistics, Penn State. 326 Thomas Building, University Park, PA 16802, USA

4 Courant Institute of Mathematical Sciences, New York University. 251 Mercer Street, New York, NY 10012, USA

5 Biochimie et Physiologie Moleculaire des Plantes, INRA, Place Viala, F-34060 Montpellier Cedex 1, France

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Genome Biology 2007, 8:R7  doi:10.1186/gb-2007-8-1-r7

Published: 11 January 2007



Carbon (C) and nitrogen (N) metabolites can regulate gene expression in Arabidopsis thaliana. Here, we use multinetwork analysis of microarray data to identify molecular networks regulated by C and N in the Arabidopsis root system.


We used the Arabidopsis whole genome Affymetrix gene chip to explore global gene expression responses in plants exposed transiently to a matrix of C and N treatments. We used ANOVA analysis to define quantitative models of regulation for all detected genes. Our results suggest that about half of the Arabidopsis transcriptome is regulated by C, N or CN interactions. We found ample evidence for interactions between C and N that include genes involved in metabolic pathways, protein degradation and auxin signaling. To provide a global, yet detailed, view of how the cell molecular network is adjusted in response to the CN treatments, we constructed a qualitative multinetwork model of the Arabidopsis metabolic and regulatory molecular network, including 6,176 genes, 1,459 metabolites and 230,900 interactions among them. We integrated the quantitative models of CN gene regulation with the wiring diagram in the multinetwork, and identified specific interacting genes in biological modules that respond to C, N or CN treatments.


Our results indicate that CN regulation occurs at multiple levels, including potential post-transcriptional control by microRNAs. The network analysis of our systematic dataset of CN treatments indicates that CN sensing is a mechanism that coordinates the global and coordinated regulation of specific sets of molecular machines in the plant cell.