Transcription factors often act in a combinatorial fashion to induce or inhibit the expression of their target genes. Despite their prominent role in enhancing our understanding of gene regulatory system, the TF co-regulatory network on a genome-wide scale is not yet constructed and characterized in Arabidopsis. In this paper, we proposed a simple integrative approach to leverage publicly available information (e.g., TF binding data and gene expression profile) to construct and characterize a genome-scale transcriptional co-regulatory network in Arabidopsis. The biological relevance of the predicted cooperative TFs was verified by analysis of PPI enrichment and functional similarities. Network analysis revealed that the Arabidopsis co-regulatory network has small-world and modular properties, as well as exponential degree distribution and assortative mixing, suggesting an evolutionary model involving sublinear preferential attachment. Analysis also showed a strong positive correlation between the number of interacting TFs and the number of conditions under which a TF is functioning. Clustering analysis identified eight groups of TFs whose target genes were co-expressed under same experimental conditions. Interestingly, many TF-TF interactions are between TFs that share similar binding motifs and belong to the same TF family or TF cluster. Nonetheless, frequent cross-group interaction was also observed, some of which are well known, while most are unreported previously. The approach and findings presented in this paper provide valuable insights into the organizational principle and evolution of co-regulatory networks. Experimental follow-up of predicted TF cooperative pairs as well as comparative studies with co-regulatory networks in different species will provide further mechanistic understanding of transcriptional regulation combinatorics and evolution.