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Identification of cis-regulatory elements in Arabidopsis is a key step to understanding its transcriptional regulation scheme. In this study, the Arabidopsis gene coexpression network was constructed using the ATTED-II data, and thereafter a subgraph-induced approach and clique-finding algorithm were used to extract gene coexpression groups from the gene coexpression network. A total of 23 large coexpression gene groups were obtained, with each consisting of more than 100 highly correlated genes. Four classical tools were used to predict motifs in the promoter regions of coexpressed genes. Consequently, we detected a large number of candidate biologically relevant regulatory elements, and many of them are consistent with known cis-regulatory elements from AGRIS and AthaMap. Experiments on coexpressed groups, including E2Fa target genes, showed that our method had a high probability of returning the real binding motif. Our study provides the basis for future cis-regulatory module analysis and creates a starting point to unravel regulatory networks of Arabidopsis thaliana.

Identification of regulatory relationships between transcription factors (TFs) and their targets is a central problem in post-genomic biology. In this paper, we apply an approach based on the support vector machine (SVM) and gene-expression data to predict the regulatory interactions in Arabidopsis. A set of 125 experimentally validated TF-target interactions and 750 negative regulatory gene pairs are collected as the training data. Their expression profiles data at 79 experimental conditions are fed to the SVM to perform the prediction. Through the jackknife cross-validation test, we find that the overall prediction accuracy of our approach achieves 88.68%. Our approach could help to widen the understanding of Arabidopsis gene regulatory scheme and may offer a cost-effective alternative to construct the gene regulatory network.

Arabidopsis thaliana Protein Interactome Database (AtPID) is an object database that integrates data from several bioinformatics prediction methods and manually collected information from the literature. It contains data relevant to protein-protein interaction, protein subcellular location, ortholog maps, domain attributes and gene regulation. The predicted protein interaction data were obtained from ortholog interactome, microarray profiles, GO annotation, and conserved domain and genome contexts. This database holds 28,062 protein-protein interaction pairs with 23,396 pairs generated from prediction methods. Among the rest 4666 pairs, 3866 pairs of them involving 1875 proteins were manually curated from the literature and 800 pairs were from enzyme complexes in KEGG. In addition, subcellular location information of 5562 proteins is available. AtPID was built via an intuitive query interface that provides easy access to the important features of proteins. Through the incorporation of both experimental and computational methods, AtPID is a rich source of information for system-level understanding of gene function and biological processes in A. thaliana. Public access to the AtPID database is available at http://atpid.biosino.org/.

The Imitation Switch (ISWI) type adenosine triphosphate (ATP)-dependent chromatin remodeling factors are conserved proteins in eukaryotes, and some of them are known to form stable remodeling complexes with members from a family of proteins, termed DDT-domain proteins. Although it is well documented that ISWIs play important roles in different biological processes in many eukaryotic species, the molecular basis for protein interactions in ISWI complexes has not been fully addressed. Here, we report the identification of interaction domains for both ISWI and DDT-domain proteins. By analyzing CHROMATIN REMODELING11 (CHR11) and RINGLET1 (RLT1), an Arabidopsis thaliana ISWI (AtISWI) and AtDDT-domain protein, respectively, we show that the SLIDE domain of CHR11 and the DDT domain together with an adjacent sequence of RLT1 are responsible for their binding. The Arabidopsis genome contains at least 12 genes that encode DDT-domain proteins, which could be grouped into five subfamilies based on the sequence similarity. The SLIDE domain of AtISWI is able to bind members from different AtDDT subfamilies. Moreover, a human ISWI protein SNF2H is capable of binding AtDDT-domain proteins through its SLIDE domain, suggesting that binding to DDT-domain proteins is a conserved biochemical function for the SLIDE domain of ISWIs in eukaryotes.

During their life cycle, flowering plants must experience a transition from vegetative to reproductive growth. Here, we report that double mutations in the Arabidopsis thaliana IMITATION SWITCH (AtISWI) genes, CHROMATIN REMODELING11 (CHR11) and CHR17, and the plant-specific DDT-domain containing genes, RINGLET1 (RLT1) and RLT2, resulted in plants with similar developmental defects, including the dramatically accelerated vegetative-to-reproductive transition. We demonstrated that AtISWI physically interacts with RLTs in preventing plants from activating the vegetative-to-reproductive transition early by regulating several key genes that contribute to flower timing. In particular, AtISWI and RLTs repress FT, SEP1, SEP3, FUL, and SOC1, but promote FLC in the leaf. Furthermore, AtISWI and RLTs may directly repress FT and SEP3 through associating with the FT and SEP3 loci. Our study reveals that AtISWI and RLTs represent a previously unrecognized genetic pathway that is required for the maintenance of the plant vegetative phase.