TRUNCATULIX – a data warehouse for the legume community
© Henckel et al; licensee BioMed Central Ltd. 2009
Received: 27 October 2008
Accepted: 11 February 2009
Published: 11 February 2009
Databases for either sequence, annotation, or microarray experiments data are extremely beneficial to the research community, as they centrally gather information from experiments performed by different scientists. However, data from different sources develop their full capacities only when combined. The idea of a data warehouse directly adresses this problem and solves it by integrating all required data into one single database – hence there are already many data warehouses available to genetics. For the model legume Medicago truncatula, there is currently no such single data warehouse that integrates all freely available gene sequences, the corresponding gene expression data, and annotation information. Thus, we created the data warehouse TRUNCATULIX, an integrative database of Medicago truncatula sequence and expression data.
The TRUNCATULIX data warehouse integrates five public databases for gene sequences, and gene annotations, as well as a database for microarray expression data covering raw data, normalized datasets, and complete expression profiling experiments. It can be accessed via an AJAX-based web interface using a standard web browser. For the first time, users can now quickly search for specific genes and gene expression data in a huge database based on high-quality annotations. The results can be exported as Excel, HTML, or as csv files for further usage.
The integration of sequence, annotation, and gene expression data from several Medicago truncatula databases in TRUNCATULIX provides the legume community with access to data and data mining capability not previously available. TRUNCATULIX is freely available at http://www.cebitec.uni-bielefeld.de/truncatulix/.
Medicago truncatula is a model plant for studying legume biology. Legumes are mainly characterized by their ability to interact with beneficial microbial organisms, leading to the formation of nitrogen-fixing root nodules and to phosphate-acquiring arbuscular mycorriza. Various international research projects are investigating these different symbioses of Medicago truncatula. The arbuscular mycorrhiza (AM) interaction between the host root and the fungal partner is an interesting field of research because more than 80% of land plants depend on an efficient AM for the uptake of nutrients, primarily phosphate. Apart from AM, Medicago truncatula is capable of entering a nitrogen-fixing symbiosis with the soil bacterium Sinorhizobium meliloti. The capacity for symbiotic nitrogen fixation allows legumes such as Medicago truncatula to grow on nitrogen-depleted soils and to develop protein-rich seeds, which are properties exploited in sustainable agriculture [1–5].
In recent years, more and more databases for the storage of microarray expression data (Arrayexpress , PEPR , The Stanford MicroArray Database , PlexDB ), and data from different sequencing projects (EST sequencing(dbEST ), BAC sequencing (GenMapDB ), ultrafast sequencing (Short Read Archive )), have been developed to store the exponentially growing amount of data. However, scientists have to search for the specific information in each and every database separately.
Directly adressing this issue, data warehouses, specially designed databases, offer an approach to store different aspects of a certain data object in an optimized data schema. This provides fast data access and enables return of query results in minimal time [13, 14].
To overcome the problem of distributed data sources in the field of Medicago truncatula research, we created TRUNCATULIX, a data warehouse storing sequence data, annotations, and expression experiments of the model legume Medicago truncatula.
Construction and content
The construction of the TRUNCATULIX data warehouse is divided in three main parts: 1) the database schema, 2) the data integration, 3) and the source data. The following sections outline these three aspects in detail.
The TRUNCATULIX data warehouse is based on the IGetDB data warehouse engine  using Java . It uses MySQL  as the database management system and is based on the Biomart API , while providing additional functionality such as full-text searches and direct access to SQL-functions (e.g. SUM, AVG, ROUND). The primary gene information such as sequence data, start codon, stop codon, length of the encoded open reading frame, name, or gene_id are stored in the main table, whereas data such as gene expression values from different experiments, GO numbers, or KOG categories are stored in extra tables refering to the main table.
High throughput technologies yield vast amounts of data. However, in order to investigate, for example, regulatory pathways, further standard genetics approaches are yet most effective. High throughput data provide an excellent means to reduce the number of possible mutation targets. Such data is found, in general, in different sources and the screening of (most likely) thousands of candidates is, when performed manually, a rather tedious task. On the other hand, if the data was integrated and preprocessed for querying, such a task can be performed in a matter of minutes. As has been shown recently, such data integration strategies saves both time and money .
For the integration and import of data we use the extract, transform and load (ETL) approach commonly used in data warehousing . Sequence and annotation data are extracted from SAMS (cf. next section), and are subsequently transformed and loaded into the TRUNCATULIX database. Expression data is exported from EMMA (cf. Section "Expression data") via an export script that can be initiated by a human curator within the EMMA web interface. During the transformation step, the expression data are linked to the sequence data. This enables the user of TRUNCATULIX to conveniently search across annotation and expression data.
Medicago truncatula Gene Index 8.0
The Institute for Genomic Research (TIGR – J. Craig Venter Institute since October 2006) clustered and assembled 226,923 high-quality ESTs from over 60 different Medicago truncatula EST-libraries sequenced in laboratories all over the world. Using the clustering software tgicl , the Medicago truncatula Gene Index (MtGI, hosted at the Dana-Farber Cancer Institute – DFCI), was built. The MtGI 8.0 contains 18,612 Tentative Consensus sequences (TCs) and 18,238 singletons (Jan. 2005) . The sequences were imported into the Sequence Analysis and Management System (SAMS) , an annotation software created at the Center for Biotechnology (CeBiTec) in Bielefeld. The SAMS system contains an automatic annotation pipeline (Metanor), which runs several bioinformatics tools for gene annotation (Blast, Interpro, TMHMM) [24–26]. A high quality consensus annotation is created, covering EC numbers , KEGG functions , GO numbers , KOG numbers , putative gene functions, and gene names.
Medicago truncatula Gene Index 9.0
Recently, the J. Craig Venter Institute released a new version of the Medicago truncatula Gene Index, now covering over 70 EST-libraries. The assembly of the 259,642 ESTs led to 29,273 TCs, while 26,696 ESTs remained as singletons. In addition to the previous Gene Index 8.0, TIGR used 25,600 mature transcripts (ETs) from the qcGene Database  for the EST assembly, whereof 11,494 ETs remained as singletons. The new sequences were downloaded from the DFCI websites and imported into SAMS, where a complete automatic annotation was performed.
Medicago genome project
The Medicago Genome Sequence Consortium (MGSC) sequenced the Medicago truncatula genome using a classical BAC sequencing approach [31, 32]. Starting in 2005, they released a assembly of the sequences in October 2007 (release 2.0). This release contains 38,759 coding sequences (CDS) and the same number of translated protein sequences. The CDS's were downloaded from the project website and afterwards imported into SAMS. Using SAMS, a complete automatic annotation was performed.
Affymetrix Medicago GeneChip® probes
Affymetrix  offers a GeneChip® microarray holding probes primarily for genes of Medicago truncatula, but also for the related legume Medicago sativa and their symbiontic Sinorhizobium meliloti. The sequences used by Affymetrix to construct the Medicago Genome GeneChip® were downloaded from the Affymetrix website and imported into SAMS. That way, 61,103 sequences containing the Affymetrix annotations were integrated into SAMS and were automatically re-annotated using the Metanor pipeline.
Medicago truncatula 454 sequencing project
In 2006, Cheung et al. used the pyrosequencing approach to generate 292,465 cDNA reads of Medicago truncatula using a GS20 sequencer . The reads were assembled forming 3,619 sequences. These sequences were downloaded from the project website and imported into SAMS. Using SAMS, a complete automatic annotation was performed.
Sequence data integrated into TRUNCATULIX.
MtGI 8.0 TCs & Singletons
MtGI 9.0 TCs & Singletons
Mt Genome 2.0
Medicago 454 sequencing project
Oligo-microarray expression data
Microarray expression data imported from EMMA into TRUNCATULIX.
Number of microarrays
Number of transformed datasets
Nitrogen-fixing root nodules in Medicago truncatula*
Nod-Factor response in Medicago truncatula roots 
Root endosymbiosis in Medicago truncatula 
Uromyces pathogenesis in Medicago truncatula**
AHL treatment of Medicago truncatula roots***
LMW EPS I treatment of Medicago truncatula roots I****
LMW EPS I treatment of Medicago truncatula roots II****
LMW EPS I treatment of Medicago truncatula roots III****
Nod-factor treatment of Medicago truncatula roots I****
Nod-factor treatment of Medicago truncatula roots II****
Seed development in Medicago truncatula 
Early Salt Stress in Medicago truncatula 
Cold stress in Medicago truncatula*****
Medicago truncatula wild type roots vs. TN1_11 mutant roots after 1 h of salt stress*****
Response to phosphate in Medicago truncatula roots 
GeneChips® expression data
GeneChip data integrated into TRUNCATULIX.
Number of GeneChip arrays
Mature organs series
Leaf: 4-week old trifolia were harvest without their petioles (but with their petiolule) 
Petiole: Petioles from 4-week old plant 
Stem: Stems of 4-week old plants (without vegetative buds) 
Vegetative Bud: Vegetative buds of 4-week old plants 
Root: 4-week old non-inoculated roots 
Nodule: Nodules from 4-week old plants 
Flower: Fully open flowers were harvest at the day of anthesis 
Pod: Mix of small, medium and physiologically mature pods 
Nodulation development series
Root-0d: Roots at 0 dpi (control for nodule developmental series) 
Nod4d: Nodules at 4 dpi (root lumps with residual roots) 
Nod10d: Developing nodules at 10 dpi 
Nod14d: Mature nodules at 14 dpi 
Seed development series
Seed10d: Developing seeds at early embryogenesis – 10 dap 
Seed12d: Developing seeds at 12 dap (transition between embryogenesis and seed filling) 
Seed16d: Developing seeds at 16 dap (accumulation of storage proteins) 
Seed20d: Developing seeds at 20 dap (seed filling) 
Seed24d: Developing seeds at 24 dap (maturation phase) 
Seed36d: Developing seeds at 36 dap (physiologically mature seeds, desiccation) 
The integrated data (sequence and expression data) is curated before it is imported into TRUNCATULIX. No user is allowed to import any datasets, this is reserved to the curators, but can be done upon request. In case of an update of one of the source databases the integrated data are updated by the curators.
Utility and Discussion
TRUNCATULIX is a relational, integrated database of sequence data, annotation information and microarray expression data, which is specially created to store data of the model legume Medicago truncatula.
The interface for the TRUNCATULIX data warehouse can be accessed via a web browser. It provides a user-friendly interface built with Echo2 .
Consider a query for genes concerning GRAS transcription factors, suggesting that these genes are activated during nodulation [48, 49]. As an example, we search for genes annotated as GRAS transcription factors in microarray experiments covering nodulation with three or more replicates.
For our example, the Annotation Description field is set to "GRAS transcription factor", due to our interest in GRAS genes. This way only genes that are annotated as GRAS transcription factor genes remain for the next filterstep.
In the next step, the user can specify results for the different functional annotation tools, as well as for KOG Categories and Gene Ontology numbers. They remain unused in our example, but more complex queries could use these to filter for specific KOG categories or GO numbers.
The last page shows the possible export options that can be selected for the remaining 35 entries. The previously selected filter criteria are preselected for the export.
After sumbitting the query, the details of the export can be selected as shown before using the complete query dialog (see Figure 4).
With the TRUNCATULIX data warehouse, it is now possible to have a look at the specific gene expressions for the different experiments and to find possibly interesting candidates for further experiments. Our example covers GRAS transcription factors. Some of them having already been reported to be key components of symbiotic signal transduction during nodulation [48, 50, 51].
The TRUNCATULIX data warehouse allows users easy access to sequencing, annotation, and expression research done at many laboratories worldwide.
Combining different data sources for fast searching and filtering is a widely used and common approach to overcome the immense manual work of searching for related data in every available database . Related examples for this technique are GeWare  and the Medicago truncatula Gene Expression Atlas . GeWare is a data warehouse that stores Affymetrix GeneChip® microarray data combined with manually added annotations and data from public databases like GO, Ensembl, LocusLink and NetAffx [28, 53–55]. The GeWare data warehouse focuses on the processing and analysis of microarrays, mostly containing clinical data. Various filter and export options are implemented.
The Medicago truncatula Gene Expression Atlas stores previously processed and analyzed gene expression and annotation data from Affymetrix GeneChip® experiments. The data published is also available on ArrayExpress. The annotation data from Affymetrix is integrated into the data warehouse, but it can only be used for queries, it cannot be exported or viewed. In the same way, the GO numbers, KEGG functions, and the annotations of the genes can be queries. A homology search using Blast offers the opportunity to find genes according to their similarity to the Affymetrix GeneChip® reporter or consensus sequences. The results of a query can be downloaded, but only the names of the reporters and the expression values are listed, the annotations are not shown and cannot be extracted.
A comparison of TRUNCATULIX to other data warehouses
Data Warehouse feature
Medicago truncatula Gene Expression Atlas
number of microarray experiments
number of microarrays mircoarrays
automatic annotation information
searchable, but not visible
blast homology search
As more Medicago trunculata data becomes available from oligo-microarray and Affymetrix GeneChip® experiments, it will be integrated into TRUNCATULIX. Additionally, a homology search using Blast will be implemetend.
We created TRUNCATULIX, a data warehouse that combines data from microarray experiments with sequence data and high quality annotations in the area of Medicago truncatula. TRUNCATULIX is the first data warehouse in the field or Medicago truncatula research that offers the opportunity to search in all publicly available Medicago truncatula sequence data and expression data for different criteria and as a result to get a complete list of sequences, expression data, and annotations. Thus, a researcher can save much time and work finding interesting genes and results of previously conducted expression experiments. As the application uses an AJAX-based web interface, it can be used via a web browser and is platform independent. The results can be exported as Excel, HTML, or as csv files.
Availability and requirements
The TRUNCATULIX data warehouse is freely available at http://www.cebitec.uni-bielefeld.de/truncatulix/.
KH thanks the International NRW Graduate School in Bioinformatics and Genome Research for funding the project. We thank Florian Frugier (ISV, Gif-sur-Yvette) for making available data prior to publication.
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