PlantPAN: Plant promoter analysis navigator, for identifying combinatorial cis-regulatory elements with distance constraint in plant gene groups
© Chang et al; licensee BioMed Central Ltd. 2008
Received: 14 August 2008
Accepted: 26 November 2008
Published: 26 November 2008
The elucidation of transcriptional regulation in plant genes is important area of research for plant scientists, following the mapping of various plant genomes, such as A. thaliana, O. sativa and Z. mays. A variety of bioinformatic servers or databases of plant promoters have been established, although most have been focused only on annotating transcription factor binding sites in a single gene and have neglected some important regulatory elements (tandem repeats and CpG/CpNpG islands) in promoter regions. Additionally, the combinatorial interaction of transcription factors (TFs) is important in regulating the gene group that is associated with the same expression pattern. Therefore, a tool for detecting the co-regulation of transcription factors in a group of gene promoters is required.
This study develops a database-assisted system, PlantPAN (Plant Promoter Analysis Navigator), for recognizing combinatorial cis-regulatory elements with a distance constraint in sets of plant genes. The system collects the plant transcription factor binding profiles from PLACE, TRANSFAC (public release 7.0), AGRIS, and JASPER databases and allows users to input a group of gene IDs or promoter sequences, enabling the co-occurrence of combinatorial transcription factor binding sites (TFBSs) within a defined distance (20 bp to 200 bp) to be identified. Furthermore, the new resource enables other regulatory features in a plant promoter, such as CpG/CpNpG islands and tandem repeats, to be displayed. The regulatory elements in the conserved regions of the promoters across homologous genes are detected and presented.
In addition to providing a user-friendly input/output interface, PlantPAN has numerous advantages in the analysis of a plant promoter. Several case studies have established the effectiveness of PlantPAN. This novel analytical resource is now freely available at http://PlantPAN.mbc.nctu.edu.tw.
The appropriate regulation of gene expression is essential for all cellular processes, in which transcriptional control is primarily concerned with improved survival. In animals and plants, transcription factors are key regulators of gene expression and play a critical role in the life cycle . Investigations on transcription factors (TFs) and their corresponding cis-acting elements in promoters have attracted much attention from researchers of gene regulation. However, defining all functional binding sites within an identified promoter is difficult, and the existence of some additional binding sites should be assumed . Furthermore, studies of various model systems have shown that relatively few transcription factors can establish strikingly complex spatial and temporal patterns of gene expression . Some co-regulatory networks model all significant associations among transcription factors in regulating common target genes . Accordingly, work on the combinatorial interaction of transcription factors (TFs) is important in gene regulation. In a previous study, AthaMap [5, 6] identified the co-localization of transcription factor binding sites and noted that the analysis of gene co-expression is crucial to reconstructing gene regulatory networks for plant scientists. The PathoPlant  web tool enables identification of plant genes co-regulated in plant defense response. Subsequently, common cis-regulatory elements in co-regulated genes are identified by exporting sets of genes to AthaMap. The study describes an effective resource, PlantPAN (Plant Promoter Analysis Navigator), for identifying the co-occurrence of transcription factor binding sites (TFBSs) in a group of gene promoters with distance constraint between two TFBSs, and presents graphically the transcription factor binding sites in specific gene promoter regions of interest. With the advent of microarray technology, Arabidopsis co-expression tool (ACT)  was developed as a tool for analyzing co-expression patterns across selected genes. ATTED-II  provides co-regulated gene relationships based on co-expressed genes deduced from microarray data and predicted cis-regulatory elements in the 200 bp region upstream of the transcription start site. Recently, Chawade et al. proposed putative cold acclimation networks by combining data from microarrays, promoter sequences and known promoter binding sites . Accordingly, the "Gene Group Analysis" function in PlantPAN is useful for discovering co-regulated TFBSs in sets of plant genes and not restricted to a set of co-expressed genes of microarray data.
Many databases harbor collections of numerous transcription factors and are useful for the prediction of transcription factor binding sites in the promoter regions of plants. For instance, TRANSFAC [11–13] is a database of transcription factors, including genomic binding sites and DNA-binding profiles. Athena  is a database, which contains 30,067 predicted Arabidopsis promoter sequences and consensus sequences for 105 previously characterized transcription factor binding sites (TFBSs) and provides analysis on over-represented TFBSs occurring in multiple promoters. PlnTFDB  is an integrative plant transcription factor database that provides a web interface to access large (close to complete) sets of transcription factors of several plant species. PLACE  is a database that collects various cis- and trans- acting regulatory DNA elements, described in earlier studies. AGRIS  contains an Arabidopsis thaliana transcription factor database (At TFDB) consisting of approximately 1,770 Arabidopsis TFs and their sequences (protein and DNA) grouped into around 50 families with information on available mutants in the corresponding genes. AGRIS  integrates a variety of tools to determine transcription factors and their putative binding sites on all genes to reconstruct transcriptional regulatory networks in Arabidopsis. JASPAR [18, 19] is an open-access database of annotated, high-quality, matrix-based transcription factor binding site profiles for multicellular eukaryotes. DATF  stores information on 3D structural templates, EST expression, transcription factor binding sites and nuclear location signals (NLSs) of known and predicted Arabidopsis transcription factors. PlantCARE  is a database of plant cis-acting regulatory elements and a portal to tools for the in silico analysis of promoter sequences. AthaMap  contains 103 transcription factors and nearly 10 million putative TFs binding sites mapping cis-regulatory elements in Arabidopsis. Notwithstanding the recent development of the above resources, advances in plant science require a more detailed analysis of plant promoters. For example, CpG islands in the genome are important because of their strong correlation with gene regulation. CpG-rich regions are methylated and are associated with inactive DNA often linked to heterochromatin, gene silencing, and pathogen control [22–25]. In plants, DNA methylation is not only found on the cytosine of CpG islands, but also on CpNpG islands and nonsymmetrical trinucleotides [26–28]. Therefore, methods for identifying CpG/CpNpG islands, which are important sites for DNA methylation that may result in gene silencing, are certainly crucial [26–28]. Recently, CpGProD  and CpG Island Searcher  were developed to identify CpG/CpNpG islands in promoters. Tandem repeats in promoters are also critical as they participate in gene expression regulation as well [31–33]. For instance, a tandem-repeat rsus3 promoter construct displays three fold higher expression level in a GUS reporter gene assay experiment in Oryza sativa . Moreover, in Arabidopsis, gene expression is up-regulated when gene promoters were enriched in GGCCCAWW and AAACCCTA repeat sequence; gene expression is down regulated when gene promoters were enriched with TTATCC motif repeat . For this purpose, Tandem Repeat Finder (TRF)  was developed to identify tandem repeats. PlantPAN annotates not only transcription factor binding sites, but also CpG/CpNpG islands and tandem repeats in plant promoter sequences, to analyze all of these regulatory features simultaneously. Additionally, as the availability of data from multiple eukaryotic genome sequencing projects increases, attention has been focused on comparative genomic approaches. For that reason, PlantPAN also provides an additional special "Cross-Species" analyzing function for discovering the transcription factor binding sites in conserved regions between promoters of homologous genes or two input sequences. Thus, PlantPAN provides an effective resource for versatile analyses and predictions of the transcriptional regulation of genes in plants.
Construction and content
Integrating external databases
Data statistics of PlantPAN.
No. of gene transcripts
No. of promoter sequences
No. of experimental promoter sequences
No. of transcripts containing putative CpG/CpNpG Islands (predicted by CpGProD)
No. of transcripts containing putative tandem repeats (predicted by TRF)
No. of plant transcription factors used in PlantPANb
Identifying cis-regulatory elements
Supported regulatory features in PlantPAN.
Transcriptional Regulatory Features
Integrated Databases or Tools
Promoter sequences and location sites
Containing the information on the TSS and sequence location sites of Arabidopsis genes from the annotations in TAIR.
Containing the information on the TSS and sequence location sites of Oryza genes from the annotations in TIGR.
Containing the information on the 2 kb upstream location sites of Zea genes from the annotations in ZmGDB.
Transcription factor binding sites
Collecting experimentally verified transcription factors, their genomic binding sites and DNA-binding profiles.
A database of nucleotide sequence motifs found in plant cis-acting regulatory DNA elements. Motifs were extracted from previously published reports on genes in vascular plants.
Collecting approximately 1,770 Arabidopsis transcription factors that are grouped into 50 families.
A popular open-access database for matrix models describing DNA-binding preferences for transcription factors and other DNA patterns.
Scanning transcription factor binding sites using transcription factor binding profiles from TRANSFAC and PLACE.
Detecting CpG/CpNpG islands.
Finding the tandem repeat.
Conservation of homologous gene promoter sequences
Searching sequence similarity; it is also used for discovering similar gene promoters and identifying conserved regions in the PlantPAN assistant promoter database.
Utilizing the BLAST algorithm for identifying conserved regions in two sequences.
Co-occurrence transcription factor binding sites in a gene group of gene promoters
Mining the co-occurrence of transcription factor binding sites in a group of gene promoters.
Identifying co-occurrence of TFBSs in a group of gene promoters
where K is the number of background gene promoters used and T is the number of observed gene promoters that are input by users, k is the number of promoters have the combination in the background gene set and t is the number of promoters have the combination in the observed gene set. P-value is calculated for each combination based on the hypermetric equation; smaller the p-value is, more statistically significant the combination is. A smaller p-value of a combination corresponds to greater statistical significance.
One TFBS which co-occur in a group of gene promoters could be identified in sixth step. Additionally, the fact that target genes with characteristic distances show significantly higher co-expression than those without preferred distances provides evidence for the biological relevance of the observed characteristic distances . Yu et al. found that 75% of the interacting transcription factors were occurred within the characteristic distances which are smaller than 166 bp in yeast . In this work, a distance of 20 to 200 bp between two factors is considered to analyze the co-occurrence of combinatorial TFBSs in gene group. Accordingly, the support and confidence values in co-occurrence analysis and a distance constraint must be set in step six. Following the six-step analysis, step seven (final step) displays the co-occurrence percentage of every pair of combinatorial TFBSs for the input genes. Finally, users can investigate the interested combinations of TFBSs within the defined distance by graphical laid-out.
Identifying TFBSs, tandem repeats, and CpNpG islands in homologous conserved regions
The paralogous and orthologous genes among Arabidopsis and Oryza in the cross-species analysis of promoter sequences of homologous genes, were extracted from Gramene . Following the identification of the paired homologous genes, the sequence alignment search tool, BLAST , was applied to identify conserved regions in promoter sequences. Based on the conservation of homologous promoter sequences, transcription factor binding sites within the conserved regions are identified. Users can input a promoter sequence to search for homologous gene promoters; this capacity diversifies the platform. Additionally, two sequences in FASTA format can be employed to search for conserved regions within the two sequences using BL2SEQ  program. The detection of transcription factor binding sites, tandem repeats, and CpNpG islands in those regions are also displayed. The identified conserved sites are more believable than those non-conserved regions in the analyses of the transcriptional regulation in plant genes.
Graphical visualization and table list
The regulatory features discovered in the promoters are presented graphically or tabulated. A graphical interface is implemented using the GD library of a PHP programming language. Once the analysis has been completed, numerous regulatory characteristics, including transcription factor binding sites, CpG/CpNpG islands, and repeat regions, are shown in an overview. The regulatory features are then presented in more detail if users click the regulatory elements figured in the graph or the label, "View in Table." Moreover, the regulatory elements in the conserved regions and the co-occurrence of cis-regulatory elements are also revealed graphically to improve presentation.
Utility and discussion
Gene group analysis – case study I
In a previous study, Chawade et al.  constructed putative cold regulatory networks by integrating data from co-expressed microarray data, promoter sequences and known promoter binding sites. In a part of this regulatory network, co-expressed cold related genes, At4g17550.1, At1g20450.1, At5g52310.1, At4g37150.1, and At1g20440.1 were all regulated by AP2 following cold treatment for 30 min in microarray data (Fig. 3A). These five gene IDs were used as inputs in the "Gene group analysis" of PlantPAN. Transcription factors from all plant species were chosen to detect TFBSs in promoters. The thresholds of the core and matrix scores in TFBSs scanning and the support and confidence values in the co-occurrence analysis were all set to their default values. In this example, a distance of 100 bp between two factors was used to analyze the co-occurrence of combinatorial TFBSs. Consequently, the six analytic steps identified CBFHV (AP2) in these five promoters (Fig. 3B). This result was confirmed an already known regulatory pathway, as described earlier . Moreover, Chawade et al. predicted that DOF and AP2 could co-regulate At4g37150.1 and At1g20440.1 in this cold regulatory network  (Fig. 3A). Significantly, DOF and AP2 were also identified as combinatorial transcription factors in At4g37150.1 and At1g20440.1 promoters after seven-step analysis in the PlantPAN system (Figs. 3A and 3C). Two pathways were newly predicted: DOF may regulate AT5G52310.1 and At4G17550.1 expression and co-occur with AP2 in a cold regulatory network (Figs. 3A and 3C). Accordingly, this system can be adopted to analyze co-regulation in microarray gene expression databases, such as AtGenExpress  and Genevestigator . The developed PlantPAN system improves our understanding of the transcription regulatory networks of gene regulation in plants.
Gene group analysis – case study II
The development of flowers has attracted widespread interest in recent decades as an excellent model system of plant development. A novel floral induction system was recently used to construct an early Arabidopsis flower development network . Particular transcription factors regulated various co-expressed genes, demonstrating the critical roles of such genes in flower development . Some genes in this gene regulation network are taken as an example to demonstrate the effectiveness of the developed "Gene group analysis" system. Wellmer et al. indicated that AP1 regulated TFL1 (At5g03840.1), LFY (At5g61850.1), FUL (At5g60910.1), AGL24 (At4g24540.1), and PI (At5g20240.1), which participated importantly in flower development (Fig. S3A in additional file 1) . These five gene IDs were input into the "Gene group analysis". Again, transcription factors from all plant species were selected to detect TFBSs in promoters. The thresholds of the core and matrix scores in TFBSs scanning and the support and confidence values in co-occurrence analysis were set to the default values. In this case study, a distance of 100 bp between two factors is considered to analyze the co-occurring TFBSs. Consequently, the six analytic steps identified AP1 in these five promoters (Fig. S3B in additional file 1). This result was confirmed using Wellmer's model . However, the most remarkable utility of the proposed system is not its identification of a single transcription factor that may regulate a group of genes, but the identification of candidates that may co-occur with the finding TF. This information yields the novel transcription factor binding sites or supports the discovery of co-regulated transcription factors. Furthermore, the distance between the two co-occurring transcription factors was regarded as important in regulating transcription. In this example, the C1-motif (CIMOTIFZMBZ2) might co-occur with AP1 in the group of genes within a distance of less than 100 bp (Fig. S3C in additional file 1). The C1-motif has also been demonstrated to be required for anthocyanin pigmentation in the aleuron and scutellum of the plant biological kernels [51, 52]. As a result, the C1-motif might be a new candidate that is involved in the regulation of flower development in plants and might be co-regulated with AP1. Therefore, this system can be utilized to identify novel TFBSs.
Promoter analysis – annotating TFBSs, CpG/CpNpG islands, andtandem repeats
In the annotation of TFBSs, Arabidopsis thaliana rbcS-1A (At1g67090.1) promoter has been defined from -320 bp to -125 bp; a binding site (CTTCCACGTGGCA, from -241 bp to -230 bp) is present for the GBF (G-box binding factor) transcription factor binding. Following the input of the Arabidopsis rbcS-1A gene ID for a search, one GBF binding site was identified between -241 bp and -230 bp (Fig. S4 in additional file 1). The graph is hyperlinked to more details of the transcription factor or TFBSs.
Previous investigations have revealed that the gene expression can be up-regulated when the promoter that contains Up1 (GGCCCAWW) or Up2 (AAACCCTA) repeats . Arabidopsis nucleolar protein (AT4G26600.1) is one of the putative genes whose promoter contains Up1 and Up2 . These repeats were successfully identified by PlantPAN in the At4G26600.1 promoter (Fig. S5 in additional file 1). In the annotation of CpG/CpNpG islands, several methyl-CpG-binding domain (MBD) proteins , which contain CpG/CpNpG islands, were identified; PlantPAN exhibits those at -2342 bp to -1480 bp in the MBD5 (AT3G46580.1) promoter region (Fig. S6 in additional file 1).
Nevertheless, users can input a novel promoter sequence to analyze the above four regulatory features. After the annotation tools were employed, the selected features, such as TFBSs, CpG/CpNpG islands and tandem repeats, were represented in the graph and table (Figs. S4-S6 in additional file 1). The parameters of each annotating tool were set to their default values, as described in Construction and content.
The number of sequenced and annotated plant genomes is rapidly increasing. The PlantPAN database is currently being expanded to cover species other than Arabidopsis, rice and maize. Future versions will include other plant species (wheat, potato, barley and others). Additionally, the transcription factors will be enlarged by taking into account more experimental matrices from different plants. The authors will in the near future be energetically connecting transcription factors to other proteins using protein-protein interaction databases. Furthermore, the plant microarray data will be integrated into "Gene group analysis" of PlantPAN.
PlantPAN provides a "Gene group analysis" function for analyzing the co-occurrence of combinatorial TFBSs with a distance constraint in sets of plant genes. This function extends a good platform to examine the co-expression genes of microarray data in transcriptional regulation networks. Furthermore, the PlantPAN web server not only provides a user-friendly input/output interface, but also offers numerous advantages in plant promoter analysis over currently available tools for annotating plant promoters (Table S1 in additional file 1). PlantPAN supports various important regulatory elements for promoter analysis, such as transcription factor binding sites, CpG/CpNpG islands, and tandem repeat regions. PlantPAN also provides "Cross-Species" analysis for two paralogous or orthologous promoters, allowing the identification of transcription factor binding sites to be refined. Future improved versions of PlantPAN will include more detailed information on gene regulation and transcription factors. The PlantPAN resource will be continuously maintained and updated for upcoming studies.
Availability and requirements
Access to PlantPAN is via a web interface, freely available to all interested users, at http://PlantPAN.mbc.nctu.edu.tw.
List of abbreviations
transcription factor binding sites
transcription start site.
The authors would like to thank the National Science Council of the Republic of China, Taiwan, for financially supporting this research (NSC90-2311-B-007-B30, NSC91-2311-B-007-034, NSC95-2311-B-007-004) to RLP, and (NSC 95-3112-E-009-002, NSC 97-2627-B-009-007, NSC 95-2311-B009-004-MY3) to HDH. Ted Knoy is appreciated for his editorial assistance.
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