An Arabidopsis gene network based on the graphical Gaussian model

Abstract

We describe a gene network for the Arabidopsis thaliana transcriptome based on a modified graphical Gaussian model (GGM). Through partial correlation (pcor), GGM infers coregulation patterns between gene pairs conditional on the behavior of other genes. Regularized GGM calculated pcor between gene pairs among ∼2000 input genes at a time. Regularized GGM coupled with iterative random samplings of genes was expanded into a network that covered the Arabidopsis genome (22,266 genes). This resulted in a network of 18,625 interactions (edges) among 6760 genes (nodes) with high confidence and connections representing ∼0.01% of all possible edges. When queried for selected genes, locally coherent subnetworks mainly related to metabolic functions, and stress responses emerged. Examples of networks for biochemical pathways, cell wall metabolism, and cold responses are presented. GGM displayed known coregulation pathways as subnetworks and added novel components to known edges. Finally, the network reconciled individual subnetworks in a topology joined at the whole-genome level and provided a general framework that can instruct future studies on plant metabolism and stress responses. The network model is included.

Assembly of an Interactive Correlation Network for the Arabidopsis Genome Using a Novel Heuristic Clustering Algorithm

“…To assess the biological relevance of the partitioned network, we initially compared obtained connections with known biological data through visual inspection. For example, the secondary cell wall cellulose synthase genes CESA4, CESA7, and CESA8 have been used extensively for coexpression analyses (Brown et al, 2005;Persson et al, 2005;Ma et al, 2007). In agreement with these analyses, we obtained genes associated with secondary cell wall synthesis, including IRX6, IRX8, IRX9, IRX12, and several transcription factors that recently have been implicated in secondary cell wall regulation (Zhong and Ye, 2007), in the network vicinity of the three CESA genes (Supplemental Fig.…”

“…Several studies have explored the properties of such network assemblies (Barabási and Oltvai, 2004;Ihmels et al, 2004;Ma et al, 2007;Mentzen and Wurtele, 2008). The distribution of connections in the networks may generally be described by power-law-related relationships (i.e.…”

Life at the extreme: lessons from the genome

“…With regard to this last question, network analysis has already proved to be a good starting place. As has already been demonstrated in Arabidopsis transcriptional network models, the correlated expression of TRGs and genes with assigned functions in response to stresses provides, even without definitive annotations, useful linkages for visualizing co-expression patterns and identifying 'hub' genes that have core roles in regulating pathways [53,54]. Although still limited for extremophiles, RNA-sequencing experiments performed under both transient and chronic stress conditions should, before long, contribute the expression data needed for extending similar networks to non-model - or new model - species.…”

Characterizing gene coexpression modules in Oryza sativa based on a graph-clustering approach

“…Using the graphical Gaussian model, Ma and colleagues (Ma et al 2007) presented a coexpression network in Arabidopsis; it allows the identification of metabolic processes as coherent coexpression modules. Biehl and colleagues (Biehl et al 2005) identified 23 distinct clusters of coexpressed genes known as regulons.…”