CicerTransDB 1.0: a resource for expression and functional study of chickpea transcription factors
© The Author(s). 2016
Received: 20 July 2016
Accepted: 21 July 2016
Published: 29 July 2016
Transcription factor (TF) databases are major resource for systematic studies of TFs in specific species as well as related family members. Even though there are several publicly available multi-species databases, the information on the amount and diversity of TFs within individual species is fragmented, especially for newly sequenced genomes of non-model species of agricultural significance.
We constructed CicerTransDB (Cicer Transcription Factor Database), the first database of its kind, which would provide a centralized putatively complete list of TFs in a food legume, chickpea. CicerTransDB, available at www.cicertransdb.esy.es, is based on chickpea (Cicer arietinum L.) annotation v 1.0. The database is an outcome of genome-wide domain study and manual classification of TF families. This database not only provides information of the gene, but also gene ontology, domain and motif architecture.
CicerTransDB v 1.0 comprises information of 1124 genes of chickpea and enables the user to not only search, browse and download sequences but also retrieve sequence features. CicerTransDB also provides several single click interfaces, transconnecting to various other databases to ease further analysis. Several webAPI(s) integrated in the database allow end-users direct access of data. A critical comparison of CicerTransDB with PlantTFDB (Plant Transcription Factor Database) revealed 68 novel TFs in the chickpea genome, hitherto unexplored.
Database URL: http://www.cicertransdb.esy.es
Chickpea is one of the most important pulse crops with a diverse array of potential nutritional and health benefits. It is the world’s second most widely grown legume after soybean. Currently, chickpea is grown in over fifty countries covering ~12771 million hectares [Faostat, 2013] and has become a leading crop in many nations across the globe . Chickpea has significant amounts of all the essential amino acids that cannot be synthesized by the human body . Due to its high value in the agro-industries, chickpea has received much research attention, particularly in the areas of improvement in agronomic performances and as a model for basic biological studies. Chickpea is presumed to be of special importance to food security for the developing world wherein, due to its biological nitrogen fixation capability, it is a primary source of human dietary protein .
The genome of chickpea was sequenced and assembled by whole-genome shotgun sequencing . Despite progress in the functional annotation of the genes, analysis platforms for accessing detailed information from the draft sequence are limited. This level of annotation also holds true for transcription factors (TFs). The regulation of gene expression by TFs is crucial to growth and development as well as the physiology of plants. It is now known that TFs weave a complex inter-regulatory network within the cell that influences almost all metabolic processes. TFs recognize specific DNA sequences that are the key components involved in gene regulatory networks, and are therefore of particular interest for functional characterization.
Arabidopsis is the first plant to be completely sequenced, which provides the foundation for identifying a wide range of plant-specific gene functions. Transcription factors of Arabidopsis have been well studied [3–5], which made it possible to identify and study TFs of other sequenced plant species by homology searching and comparative analysis. The available databases provide: (1) a uniform platform to review plant TF families across species; (2) descriptions of each TF family and links to the appropriate literature; and (3) cross-references between the databases by means of orthologous relationships.
The transcription process in eukaryotes is mediated by the general transcription factors (GTFs), the protein factors involved in messenger RNA synthesis [6, 7], which are conserved across species. The cataloguing of plant-specific TFs was initiated with the release of TRANSFAC (Transcription Factor Database) database extensively represented by cis-acting elements and trans-acting factors of Arabidopsis . Currently available plant-specific GTF databases can be exemplified by PlantTFDB (Plant Transcription Factor Database)  and DBD (DNA-binding Domain) , comprising information about TFs from multiple plant species. However, such databases poorly represent the newly sequenced genomes, for example, the TFs of chickpea. Traditional method for prediction of TFs, specifically organism-specific TFs, uses blast homology or pattern-specific (hmm) search on the complete genome. The former method is greatly biased to the seed database used for searching against the genome and therefore, very often lacks discovery of new TFs with novel sequences. The latter method is relatively slow, as the initial seed for domain-specific blast (PSI-BLAST or hmmer) needs seeds of their own, making database generation and maintenance a cumbersome process.
In this study, we used a quick and accurate method of whole genome cataloguing for generation of chickpea TF database. CicerTransDB is a database of TFs of chickpea discovered by the process of cataloguing domains of chickpea gene-products using domain-specific seeds from pfam. It harbours 1124 chickpea TFs grouped into 47 separate families. The database expands to features like motifs, domains, homologues in PlantTFDB and TAIR, gene ontology, among others which in turn gives the user a better interface for quick research in comparison to general TF databases. The database also takes care of need to analyse information in other databases. Additionally, various databases can be directly queried, for example, InterProScan, PlantCare and many more. Direct blast submission to NCBI and ENA databases has also been facilitated through a single click interface. These tools along with sequence information make CicerTransDB a comprehensive platform to visualize and cross-search chickpea TFs aiding to the study of chickpea signalling geometrically. Furthermore, we developed few short webAPI(s) and several webinterfaces to facilitate advanced users to query the database for information in individual or bulk through single URL or incorporate it into other database pipelines. The CicerTransDB would provide a user-friendly interface for retrieving useful information specific to chickpea, which is otherwise lacking in the existing database systems. Integration of other database through one-click interface adds an example of future database systems for a new dimension of user-friendliness.
Construction and content
This section describes briefly the process of recruiting TFs, making of the database, utility of the CicerTransDB webserver and usage of the webAPI/webinterfaces.
Searching for chickpea TFs and generation of data
The annotation data used in this study was acquired from Chickpea Genome Annotation v 1.0 . Protein sequences were analysed through pfam  in batch mode, and the retrieved data was parsed to tab format using perl scripts. The parsed data was fed into Mariadb for initial local database and queried for specific domains as specified in PlantTFDB , generating the primary list. The primary list thus obtained was manually examined and catalogued into various classes according to the classification system described earlier [9, 12]. Additionally, Tub domain, previously published from our lab , was added to this list finalising the secondary list (Additional file 1: Table S1). This was considered as the final TFlist, which was used as a template for obtaining additional data.
The TFlist was blasted against NCBInr database (updated Dec, 2014) for naming the genes, using blastp program with e-value 1e-03 and max 20 targets . Additionally, custom perl scripts were used to retrieve 1.5 kb upstream promoter sequences from the chickpea genome . The data was analyzed for cis-acting regulatory elements using PLACE database , and the output was converted to SQL table. We also developed a PLACE parser using perl to convert PLACE output into SQL compatible tab format (data not shown). The complete set of protein sequences were analyzed through LocTree 3.0 and LocTree 2.0 [16, 17] programs to predict their localization. Each TF sequence was searched against TAIR  and PlantTFDB for annotation of functions of chickpea TFs, via blastp using e-value 1e-03 and 1e-06, respectively, with identity cutoff of 80 %. The protein homologues were also searched against SwissProt  with an e-value of 1e-03 and cutoff identity of 80 %. The mapped SwissProt ID and TAIR ID were then employed to map Gene Ontology using map tables obtained through Gene Ontology Consortium . The summary information from all these sources would offer a strong knowledge-based foundation for further characterization of chickpea TFs.
Development of database and webserver
The user interface of CicerTransDB was developed on framework of PHP. This enables the use of robust hidden layers which is secured from user, as well as diverse and dynamic front end layout that provides user with variety of information. A schematic diagram of the workflow is shown in Figure S1 of Additional file 2.
Utility and discussion
Search form and diversity of query
Download bulk data
CicerTransDB has the feature for downloading data in bulk which includes both TF sequences and feature tables. The sequences can be downloaded in either fasta, excel or tab delimited text format. The fasta headers are pipe (|) delimited containing information such as location, strand and name. The name is put on fifth position in accordance to NCBI blast convention facilitating parsing programs. The user has the option of downloading all sequences as well as sequences based on particular TF family, chromosome or localization. Furthermore, user can also download features such as accession list, list of motifs, list of domains and list of homologues based on TF family, chromosome or localization in excel as well as tab delimited text format. A short tutorial on the above is included in the wiki section of the database. The wiki section also includes know-how to download bulk data directly through URL.
Data information of individual genes and cross database tools
WebAPI(s) and webinterface(s)
CicerTransDB integrates several APIs and interfaces, the first of which is for individual data that returns the information of accession number in html format. The interface further extends to information regarding fasta sequences, domain and motif details. For example, information of gene Ca_00040 can be obtained at www.cicertransdb.esy.es/data/Ca_00040, and the details of domains and motifs of Ca_00040 can be obtained at http://www.cicertransdb.esy.es/data/domain/Ca_00040 and http://www.cicertransdb.esy.es/data/motif/Ca_00040, respectively. All available features list is detailed in Fig. 3. The users can search and download the batch information using query in URL. A detailed explanation about how to formulate the URL is provided in the website’s wiki section.
We designed a new chromosome map utility based on PHP for making chromosome maps in CicerTransDB. Chromosome map for each TF family is accessible both through website as well as webAPI. The number of TFs and average TF density were calculated for each chromosome, which showed the lowest number of TFs in Ca2 and Ca8, although the average TF density per chromosome was highest on Ca8 (Figure S2 in Additional file 3). We also calculated the number of TFs per chromosome per family (Table S2 in Additional file 4). These data may facilitate in evolutionary studies of genes across related organisms.
CicerTransDB is based on chickpea genome annotation v 1.0. We anticipate that future fine-tuning of the genome annotation and further release of new sequences would exert an extra pressure on release of new versions of CicerTransDB and maintaining data. Our future efforts will focus onto updating the database with new information as it becomes available. Deciphering new families of TFs through data-mining remains difficult, which will be an important task in upcoming versions of the database. CicerTransDB would predict direct binding targets of TFs throughout the chickpea genome.
CicerTransDB is a cross platform database where user can query and view information about TFs of chickpea. It also provides advanced search tools, which can be used to generate diverse information from the database. Furthermore, the data can be queried though webAPI and webinterfaces to get data for individual TF as well as large datasets. Various third-party links have been provided as single-click interface to user for an easy workflow. Altogether, these features make CicerTransDB a unique and comprehensive resource for chickpea TF repertoire. Comparison of CicerTransDB with PlantTFDB revealed 68 unique TFs in chickpea genome, hitherto unexplored. The chromosome distributional analysis revealed that chickpea TFs are disseminated throughout its genome. In spite of having lowest number of TFs, chromosome Ca8 was found to have the highest average TF density among all chromosomes. We strongly believe that CicerTransDB will act as a conceptual framework for future computational and experimental research on the chickpea transcriptional regulatory network from the perspective of the TFs acting on cis-regulatory elements, and provide the necessary acceleration in this area of resaerch.
API, Application programming interface; GTFs, General transcription factors; HTML, HyperText Markup Language; PHP, Hypertext Preprocessor; PSI-BLAST, Position-Specific Iterated BLAST; SQL, Structured Query Language; TF, Transcription factor.
We are thankful to Jasbeer Singh for illustrations and graphical representation in the manuscript.
This work was supported by the National Institute of Plant Genome Research, New Delhi. We thank the Council of Scientific & Industrial Research (CSIR), Govt. of India for providing pre-doctoral fellowship to S.G. and N.V.L., and the National Institute of Plant Genome Research, New Delhi for providing Research Associateship to A.P.
Availability and requirements
CicerTransDB is freely available at http://cicertransdb.esy.es for academic use. Based on our test, CicerTransDB is fully functional with three web browsers: Mozilla Firefox, Internet Explorer, and Safari, and four operating systems: Windows XP, Windows Vista, Linux (Red Hat), and Mac OS. No additional software installation is needed for browsing the database.
SG, NC and SC conceived the project. SG and SA designed the study and constructed the database. NVL and AP helped with data analysis. SG, AP and NC discussed the study and wrote the article. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Varshney RK, Song C, Saxena RK, Azam S, Yu S, Sharpe AG, et al. Draft genome sequence of chickpea (Cicer arietinum) provides a resource for trait improvement. Nat Biotechnol. 2013;31:240–6.View ArticlePubMedGoogle Scholar
- Jukanti AK, Gaur PM, Gowda CLL, Chibbar RN. Nutritional quality and health benefits of chickpea (Cicer arietinum L.): a review. Br J Nutr. 2012;108 Suppl:S11-S26.Google Scholar
- Riechmann JL, Heard J, Martin G, Reuber L, Jiang C, Keddie J, et al. Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes. Science. 2000;290:2105–10.View ArticlePubMedGoogle Scholar
- Jakoby M, Weisshaar B, Dröge-Laser W, Vicente-Carbajosa J, Tiedemann J, Kroj T, et al. bZIP transcription factors in Arabidopsis. Trends Plant Sci. 2002;7:106–11.View ArticlePubMedGoogle Scholar
- Ülker B, Somssich IE. WRKY transcription factors: From DNA binding towards biological function. Curr Opin Plant Biol. 2004;7:491–8.View ArticlePubMedGoogle Scholar
- Weinzier R. Mechanisms of gene expression: structure, function and evolution of the basal transcriptional machinery. London: UK Imperial College Press; 1999.View ArticleGoogle Scholar
- Reese JC. Basal transcription factors. Curr Opin Genet Dev. 2003;13:114–8.View ArticlePubMedGoogle Scholar
- Schmutz J, Cannon SB, Schlueter J, Ma J, Mitros T, Nelson W, et al. Genome sequence of the palaeopolyploid soybean. Nature. 2010;463:178–83.View ArticlePubMedGoogle Scholar
- Guo AY, Chen X, Gao G, Zhang H, Zhu QH, Liu XC, et al. PlantTFDB: A comprehensive plant transcription factor database. Nucleic Acids Res. 2008;36:D966–9.View ArticlePubMedGoogle Scholar
- Wilson D, Charoensawan V, Kummerfeld SK, Teichmann SA. DBD - Taxonomically broad transcription factor predictions: New content and functionality. Nucleic Acids Res. 2008;36:D88–92.View ArticlePubMedGoogle Scholar
- Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, et al. The Pfam protein families database. Database. 2014;42:D222–30.Google Scholar
- Jin J, Zhang H, Kong L, Gao G, Luo J. PlantTFDB 3.0: A portal for the functional and evolutionary study of plant transcription factors. Nucleic Acids Res. 2014;42:D1182–7.View ArticlePubMedGoogle Scholar
- Wardhan V, Jahan K, Gupta S, Chennareddy S, Datta A, Chakraborty S, et al. Overexpression of CaTLP1, a putative transcription factor in chickpea (Cicer arietinum L.), promotes stress tolerance. Plant Mol. Biol. 2012;79:479–93.Google Scholar
- Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10:421.View ArticlePubMedPubMed CentralGoogle Scholar
- Higo K, Ugawa Y, Iwamoto M, Korenaga T. Plant cis-acting regulatory DNA elements (PLACE) database: 1999. Nucleic Acids Res. 1999;27:297–300.View ArticlePubMedPubMed CentralGoogle Scholar
- Goldberg T, Hecht M, Hamp T, Karl T, Yachdav G, Ahmed N, et al. LocTree3 prediction of localization. Nucleic Acids Res. 2014;42:W350–5.View ArticlePubMedPubMed CentralGoogle Scholar
- Goldberg T, Hamp T, Rost B. LocTree2 predicts localization for all domains of life. Bioinformatics. 2012;28:i458–65.View ArticlePubMedPubMed CentralGoogle Scholar
- Lamesch P, Berardini TZ, Li D, Swarbreck D, Wilks C, Sasidharan R, et al. The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools. Nucleic Acids Res. 2012;40:D1202–10.View ArticlePubMedGoogle Scholar
- Bairoch A, Apweiler R. The SWISS-PROT protein sequence data bank and its new supplement TREMBL. Nucleic Acids Res. 1996;24:21–5.View ArticlePubMedPubMed CentralGoogle Scholar
- Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.View ArticlePubMedPubMed CentralGoogle Scholar
- Chang WC, Lee TY, Huang HD, Huang HY, Pan RL. PlantPAN: Plant promoter analysis navigator, for identifying combinatorial cis-regulatory elements with distance constraint in plant gene groups. BMC Genomics. 2008;9:561.View ArticlePubMedPubMed CentralGoogle Scholar
- Rombauts S, Déhais P, Van Montagu M, Rouze P. PlantCARE, a plant cis-acting regulatory element database. Nucleic Acids Res. 1999;27:295–6.View ArticlePubMedPubMed CentralGoogle Scholar
- Leinonen R, Akhtar R, Birney E, Bower L, Cerdeno-Tarraga A, Cheng Y, et al. The European Nucleotide Archive. Nucleic Acids Res. 2011;39:D28–31.View ArticlePubMedGoogle Scholar
- Briesemeister S, Rahnenführer J, Kohlbacher O. YLoc-an interpretable web server for predicting subcellular localization. Nucleic Acids Res. 2010;38:W497–502.View ArticlePubMedPubMed CentralGoogle Scholar