Plant Physiology Preview
Published on August 18, 2006; 10.1104/pp.106.080358
OPEN ACCESS ARTICLE
Received March 22, 2006
Accepted August 2, 2006
Transcriptional coordination of the metabolic network in Arabidopsis thaliana
Hairong Wei , Staffan Persson , Tapan Mehta , Vinodh Srinivasasainagendra , Lang Chen , Grier P. Page , Chris Somerville , and Ann Loraine *
Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA
Department of Plant Biology, Carnegie Institution, Stanford, CA 94305, USA
Department of Plant Biology, Carnegie Institution, Stanford, CA 94305, USA; Department of Biological Sciences, Stanford University, Stanford, CA 94305, USA
Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA; Department of Genetics, University of Alabama at Birmingham, AL 35294, USA
* Corresponding author; email: author.aloraine{at}uab.edu.
Patterns of co-expression can reveal networks of functionally-related genes and provide deeper understanding of processes requiring multiple gene products. We performed an analysis of co-expression networks for 1,330 genes from the AraCyc database of metabolic pathways in Arabidopsis. We found that genes associated with the same metabolic pathway are, on average, more highly co-expressed than genes from different pathways. Positively co-expressed genes within the same pathway tend to cluster close together in the pathway structure, while negatively correlated genes typically occupy more distant positions. The distribution of co-expression links per gene is highly skewed, with a small but significant number of genes having numerous co-expression partners but most having fewer than ten. Genes with multiple connections ("hubs") tend to be single-copy genes, while genes with multiple paralogs are co-expressed with fewer genes, on average, than single-copy genes, suggesting that the network expands through gene duplication, followed by weakening of co-expression links involving duplicate nodes. Using a network-analysis algorithm based on co-expression with multiple pathway members (pathway-level co-expression), we identified and prioritized novel candidate pathway members, regulators, and cross-pathway transcriptional control points for over 140 metabolic pathways. To facilitate exploration and analysis of the results, we provide a Web site (http://www.transvar.org/at_coexpress/analysis/web) listing analyzed pathways with links to regression and pathway-level co-expression results. These methods and results will aid in the prioritization of candidates for genetic analysis of metabolism in plants and contribute to the improvement of functional annotation of the Arabidopsis genome.
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