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Articulation of three core metabolic processes in Arabidopsis: fatty acid biosynthesis, leucine catabolism and starch metabolism.

Mentzen WI, Peng J, Ransom N, Nikolau BJ, Wurtele ES - BMC Plant Biol. (2008)

Bottom Line: In addition, the co-expression data define a novel hierarchical transcript-level structure associated with catabolism, in which genes performing smaller, more specific tasks appear to be recruited into higher-order modules with a broader catabolic function.Each of these core metabolic pathways is structured as a module of co-expressed transcripts that co-accumulate over a wide range of environmental and genetic perturbations and developmental stages, and represent an expanded set of macromolecules associated with the common task of supporting the functionality of each metabolic pathway.As experimentally demonstrated, co-expression analysis can provide a rich approach towards understanding gene function.

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Affiliation: 1CRS4 Bioinformatics Laboratory, Loc. Piscinamanna, 09010 Pula, CA, Italy. wiesia@crs4.it

ABSTRACT

Background: Elucidating metabolic network structures and functions in multicellular organisms is an emerging goal of functional genomics. We describe the co-expression network of three core metabolic processes in the genetic model plant Arabidopsis thaliana: fatty acid biosynthesis, starch metabolism and amino acid (leucine) catabolism.

Results: These co-expression networks form modules populated by genes coding for enzymes that represent the reactions generally considered to define each pathway. However, the modules also incorporate a wider set of genes that encode transporters, cofactor biosynthetic enzymes, precursor-producing enzymes, and regulatory molecules. We tested experimentally the hypothesis that one of the genes tightly co-expressed with starch metabolism module, a putative kinase AtPERK10, will have a role in this process. Indeed, knockout lines of AtPERK10 have an altered starch accumulation. In addition, the co-expression data define a novel hierarchical transcript-level structure associated with catabolism, in which genes performing smaller, more specific tasks appear to be recruited into higher-order modules with a broader catabolic function.

Conclusion: Each of these core metabolic pathways is structured as a module of co-expressed transcripts that co-accumulate over a wide range of environmental and genetic perturbations and developmental stages, and represent an expanded set of macromolecules associated with the common task of supporting the functionality of each metabolic pathway. As experimentally demonstrated, co-expression analysis can provide a rich approach towards understanding gene function.

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Enrichment of edges joining genes from the same pathway in the graph in Fig. 2B (red arrow), as compared to random graphs (blue histogram). Histogram shows distribution of numbers of links joining genes from the same pathway in each of 10,000 random graphs with the same links structure as the original graph (μ = 111.7; σ = 6.8). Red arrow denotes number of within-pathway links (245) based on expression data (from Fig. 2B graph), blue arrow denotes mean number of within-pathway links (111.7) in randomly obtained graphs. Total number of links in each graph is 444.
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Figure 3: Enrichment of edges joining genes from the same pathway in the graph in Fig. 2B (red arrow), as compared to random graphs (blue histogram). Histogram shows distribution of numbers of links joining genes from the same pathway in each of 10,000 random graphs with the same links structure as the original graph (μ = 111.7; σ = 6.8). Red arrow denotes number of within-pathway links (245) based on expression data (from Fig. 2B graph), blue arrow denotes mean number of within-pathway links (111.7) in randomly obtained graphs. Total number of links in each graph is 444.

Mentions: Publicly available Affymetrix ATH1 chip-transcriptomic datasets comprising of 956 biological samples were used to infer patterns of transcript co-accumulation for the 22,746 Arabidopsis genes that are represented on this chip (see Methods section for details). These data are drawn from 72 experiments from NASCArrays [43] and PLEXdb [44] that represent a wide range of developmental, and environmental and genetic perturbations on Arabidopsis [see Additional file 2]. Data with poor reproducibility were discarded, and the data was normalized to the same mean and range (available at MetaOmGraph [11]). We calculated the values of Pearson pair-wise correlation across these data for the set of 126 selected genes. The results were visualized as a graph, such that genes form the nodes, which are joined by an edge if the value of correlation between them is higher than selected threshold. Using Pearson correlation thresholds of 0.5, 0.6 and 0.7 yields three co-expression networks of 107, 77 and 62 genes, connected by 733, 444, and 204 edges, respectively (Fig. 2). The positioning of the nodes (genes) in these networks was produced by graph-layout software that places highly interconnected nodes close together [45]. Thus, the absolute position of the node on the plot has no meaning, only its relative position versus other nodes: the most closely crowded nodes indicate genes with the highest co-expression. Within each of these co-expression networks the number of correlations between genes from the same metabolic pathway is significantly larger than in randomly generated networks with similar link structure (specifically, in the network at threshold 0.6, the proportion of within-pathway edges is 245/444, versus a mean of 112/444 in randomly rewired networks; this is equal to a difference of ~20 standard deviations; Fig. 3). As the correlation threshold is increased from 0.5 to 0.7, three distinct closely-interconnected clusters emerge, whose member genes closely correspond with the three metabolic pathways that were the focus of this study. We refer to the three closely-interconnected clusters identifiable in Fig. 2B as modules.


Articulation of three core metabolic processes in Arabidopsis: fatty acid biosynthesis, leucine catabolism and starch metabolism.

Mentzen WI, Peng J, Ransom N, Nikolau BJ, Wurtele ES - BMC Plant Biol. (2008)

Enrichment of edges joining genes from the same pathway in the graph in Fig. 2B (red arrow), as compared to random graphs (blue histogram). Histogram shows distribution of numbers of links joining genes from the same pathway in each of 10,000 random graphs with the same links structure as the original graph (μ = 111.7; σ = 6.8). Red arrow denotes number of within-pathway links (245) based on expression data (from Fig. 2B graph), blue arrow denotes mean number of within-pathway links (111.7) in randomly obtained graphs. Total number of links in each graph is 444.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2483283&req=5

Figure 3: Enrichment of edges joining genes from the same pathway in the graph in Fig. 2B (red arrow), as compared to random graphs (blue histogram). Histogram shows distribution of numbers of links joining genes from the same pathway in each of 10,000 random graphs with the same links structure as the original graph (μ = 111.7; σ = 6.8). Red arrow denotes number of within-pathway links (245) based on expression data (from Fig. 2B graph), blue arrow denotes mean number of within-pathway links (111.7) in randomly obtained graphs. Total number of links in each graph is 444.
Mentions: Publicly available Affymetrix ATH1 chip-transcriptomic datasets comprising of 956 biological samples were used to infer patterns of transcript co-accumulation for the 22,746 Arabidopsis genes that are represented on this chip (see Methods section for details). These data are drawn from 72 experiments from NASCArrays [43] and PLEXdb [44] that represent a wide range of developmental, and environmental and genetic perturbations on Arabidopsis [see Additional file 2]. Data with poor reproducibility were discarded, and the data was normalized to the same mean and range (available at MetaOmGraph [11]). We calculated the values of Pearson pair-wise correlation across these data for the set of 126 selected genes. The results were visualized as a graph, such that genes form the nodes, which are joined by an edge if the value of correlation between them is higher than selected threshold. Using Pearson correlation thresholds of 0.5, 0.6 and 0.7 yields three co-expression networks of 107, 77 and 62 genes, connected by 733, 444, and 204 edges, respectively (Fig. 2). The positioning of the nodes (genes) in these networks was produced by graph-layout software that places highly interconnected nodes close together [45]. Thus, the absolute position of the node on the plot has no meaning, only its relative position versus other nodes: the most closely crowded nodes indicate genes with the highest co-expression. Within each of these co-expression networks the number of correlations between genes from the same metabolic pathway is significantly larger than in randomly generated networks with similar link structure (specifically, in the network at threshold 0.6, the proportion of within-pathway edges is 245/444, versus a mean of 112/444 in randomly rewired networks; this is equal to a difference of ~20 standard deviations; Fig. 3). As the correlation threshold is increased from 0.5 to 0.7, three distinct closely-interconnected clusters emerge, whose member genes closely correspond with the three metabolic pathways that were the focus of this study. We refer to the three closely-interconnected clusters identifiable in Fig. 2B as modules.

Bottom Line: In addition, the co-expression data define a novel hierarchical transcript-level structure associated with catabolism, in which genes performing smaller, more specific tasks appear to be recruited into higher-order modules with a broader catabolic function.Each of these core metabolic pathways is structured as a module of co-expressed transcripts that co-accumulate over a wide range of environmental and genetic perturbations and developmental stages, and represent an expanded set of macromolecules associated with the common task of supporting the functionality of each metabolic pathway.As experimentally demonstrated, co-expression analysis can provide a rich approach towards understanding gene function.

View Article: PubMed Central - HTML - PubMed

Affiliation: 1CRS4 Bioinformatics Laboratory, Loc. Piscinamanna, 09010 Pula, CA, Italy. wiesia@crs4.it

ABSTRACT

Background: Elucidating metabolic network structures and functions in multicellular organisms is an emerging goal of functional genomics. We describe the co-expression network of three core metabolic processes in the genetic model plant Arabidopsis thaliana: fatty acid biosynthesis, starch metabolism and amino acid (leucine) catabolism.

Results: These co-expression networks form modules populated by genes coding for enzymes that represent the reactions generally considered to define each pathway. However, the modules also incorporate a wider set of genes that encode transporters, cofactor biosynthetic enzymes, precursor-producing enzymes, and regulatory molecules. We tested experimentally the hypothesis that one of the genes tightly co-expressed with starch metabolism module, a putative kinase AtPERK10, will have a role in this process. Indeed, knockout lines of AtPERK10 have an altered starch accumulation. In addition, the co-expression data define a novel hierarchical transcript-level structure associated with catabolism, in which genes performing smaller, more specific tasks appear to be recruited into higher-order modules with a broader catabolic function.

Conclusion: Each of these core metabolic pathways is structured as a module of co-expressed transcripts that co-accumulate over a wide range of environmental and genetic perturbations and developmental stages, and represent an expanded set of macromolecules associated with the common task of supporting the functionality of each metabolic pathway. As experimentally demonstrated, co-expression analysis can provide a rich approach towards understanding gene function.

Show MeSH
Related in: MedlinePlus