- Open Access
miSolRNA: A tomato micro RNA relational database
- Ariel A Bazzini†1,
- Ramón Asís†1, 2,
- Virginia González3,
- Sebastián Bassi3,
- Mariana Conte1,
- Marcelo Soria4,
- Alisdair R Fernie5,
- Sebastián Asurmendi1 and
- Fernando Carrari1Email author
© Bazzini et al; licensee BioMed Central Ltd. 2010
- Received: 9 August 2010
- Accepted: 8 November 2010
- Published: 8 November 2010
The economic importance of Solanaceae plant species is well documented and tomato has become a model for functional genomics studies. In plants, important processes are regulated by microRNAs (miRNA).
We describe here a data base integrating genetic map positions of miRNA-targeted genes, their expression profiles and their relations with quantitative fruit metabolic loci and yield associated traits. miSolRNA provides a metadata source to facilitate the construction of hypothesis aimed at defining physiological modes of action of regulatory process underlying the metabolism of the tomato fruit.
The MiSolRNA database allows the simple extraction of metadata for the proposal of new hypothesis concerning possible roles of miRNAs in the regulation of tomato fruit metabolism. It permits i) to map miRNAs and their predicted target sites both on expressed (SGN-UNIGENES) and newly annotated sequences (BAC sequences released), ii) to co-locate any predicted miRNA-target interaction with metabolic QTL found in tomato fruits, iii) to retrieve expression data of target genes in tomato fruit along their developmental period and iv) to design further experiments for unresolved questions in complex trait biology based on the use of genetic materials that have been proven to be a useful tools for map-based cloning experiments in Solanaceae plant species.
- Quantitative Trait Locus
- Tomato Fruit
- Tomato Genome
- Putative Target Gene
- miRNA Target Site
The sequencing and annotation of genomes of various organisms alongside the deposition of the resultant information in public domain repositories has lead to the availability of vast data sets. When these data sets are compared with data coming from post-genomic experimentation they can subsequently be exploited in integrative genomics approaches. This is particularly true in plant biology, since a considerable amount of information is now available allowing the linkage of traits to either genomic DNA sequences, ESTs or proteins for a wide range of different plant species (see for example Arabidopsis, ; Solanaceae ; Grasses,; Legumes, ). At the same time experimental data on the regulation of metabolic pathways at the whole genome level has been recently released for a handful of plant species (Arabidopsis, ; tomato, ; legumes,  and barley ). In the case of tomato (Solanum lycopersicum), Schauer et al.,  identified 889 fruit quantitative metabolic loci (QML) and 326 yield-associated loci (YAL) distributed across the tomato genome and studied the hereditability of the fruit metabolome . These combined quantitative trait loci (QTL) were identified using the Solanum pennelli introgression line (ILs) population , that has previously been utilized by several groups to identify a total of more than 2000 QTL . More recently, we focused on a subset of 126 of these QTL and were able to identify a total of 88 metabolism-associated and 39 non-metabolism associated (transport, signaling, protein processing or degradation and DNA/RNA/protein-metabolism) candidate genes co-localizing with these QTL . Moreover, an important observation made from these combined reports is that a large proportion of the QTL were associated with changes in whole plant morphology [9, 10]. However, although these experiments provide strong clues towards elucidating the interactions between genetic, expressional and protein quality aspects underlying developmental shifts during fruit ripening, the exact mechanisms underlying these traits are, as yet, far from clear.
Recent studies have demonstrated that both pattern formation and metabolism in plants involves regulation by microRNAs (miRNAs) of transcription factors  and enzyme-encoding genes [15, 16]. These studies, alongside the demonstration that miRNA319 regulates tomato leaf morphology , suggests that this level of regulation should also be evaluated with respect to the metabolic changes observed in the introgression lines. This prompted us to search for miRNA precursors and their putative target genes in the genomic regions comprising these QTL. To integrate this information here we compiled a non-redundant database of known miRNAs , and screened the Solanaceae Unigene collection  and completed BAC sequences from the tomato genome sequence initiative (Solanaceae Genome Network: http://www.solgenomics.net), for putative target sites. Target sites found in genomic clones were annotated by using two gene prediction softwares (Augustus;  and GenomeThreader; ) and aligned against S. lycopersicom unigenes and Arabidopsis thaliana peptide sequences and finally mapped onto the respective BINs (chromosomal segments) of the IL population using the molecular markers of two genetic maps (Tomato EXPEN2000 and Tomato EXPEN1992, http://www.solgenomics.net). Moreover, the expression profiles obtained from the assessment of tomato fruit development  of the target genes were also integrated. The resultant database, named miSolRNA, is comprised of 16 tables storing information concerning the map positions of miRNA target genes and their expression patterns as well as map positions of genes co-localizing with the previously identified QML. Relations within the whole dataset are searchable by means of the following fields: BIN, miRNA, target and keywords. Retrieved information can be set by the user in the following fields: i) QTL, indicates those metabolites and yield associated traits showing significant variations associated to the genomic regions where a miRNA target was found; ii) target localization, indicates the genetic BIN where the target was localized; iii) hit definition, shows annotations of the Unigene and/or the predicted products for the cases of target found onto genomic regions and iv) alignment, shows the alignments between the miRNA and the target site. Data extraction and conversion was performed by use of Python scripts. The data display was built using a combination of Python, Yaro Middleware on top of Web Server Gateway Interface (WSGI; ), Cheetah template, JQuery and SQLite for persistence.
Meta-analyses proposed here allow the linkage of genomic data with miRNA function, gene expression and metabolite profiling data. Although the resultant computational predictions should be interpreted cautiously prior to experimental confirmation, the rapid accumulation of information concerning sRNAs , necessitates computational, curated, relational databases of such entities in order to facilitate the construction of hypotheses aimed at defining their physiological mode of action.
Those genomic regions predicted to be targeted by a miRNA were annotated automatically using the Gff3 BAC files information (containing the genome browser information) downloaded from http://www.solgenomics.net ftp site. From these sequence files, the following gene prediction information was extracted: i) gene positions predicted by the Augustus software against tomato EST, potato EST, tomato Unigene and "de novo" hints and ii) gene positions predicted by the Genome threader (http://www.genomethreader.org/) against tomato Unigenes supporting alignments and BLASTX alignments against the TAIR9 Arabidopsis peptides database (TAIR9_pep_20090619, located at http://www.arabidopsis.org/). Following this analysis target sites were scored as positives ("yes") or negatives ("no") when a predicted gene by any August modality was hit. Outputs obtained after the analysis of the annotation by Genome threader and those obtained by BLASTX against the Arabidopsis peptide DB are also retrievable by a single search. Moreover, when the preceding analyses did not recognize a gene, these targeted sequences were used as query in Megablast analyses for putative miRNA precursor searches against those from Arabidopsis and tomato deposited in the miRBase. The Blast parameters were -G = 3, -E = 2, -W = 20, low-complexity sequence filter and an expect value cutoff of 10-50.
Locations of miRNA target sites, detected within fully sequenced BACs, on the genetic map of the Solanum pennellii introgression lines (ILs) were determined by searching for molecular markers of both TOMATO-expen1992 and -expen2000 genetic map into the Gff3 files for each anchored BAC clone. Markers were then located to a genetic BIN at defined position ranges in each map. Unigenes predicted to be targeted by miRNAs were mapped by aligning their sequences against anchored BACs with the following BLASTn parameters: ≥90% identity and ≥95% coverage. This allowed the mapping of the putative miRNAs target sites to specific BINs of the IL map facilitating the comparison of this information with the QML and QTL previously described for fruits on these ILs by Schauer et al. [9, 10]. In addition, expression data of the miRNA targets were extracted from microarray experiments performed across the developmental progression of tomato fruit ripening .
Prediction of secondary structures of the pre-miRNA alleles performed by the RNAfold software (http://rna.tbi.univie.ac.at/; ) showed slightly different values for thermodynamic properties related to structure stability: free energy, minimum free energy (MFE) structure and ensemble diversity . However, mature sequences for miRNA395a and b showed no allelic differences. This was not the case for miRNA395c which exhibited three polymorphic nucleotides including bases previously identified as being important for the miRNA-target recognition . This observation thus suggests that the product of the S. pennellii allele may cleave the target gene mRNA more efficiently (Figure 3). The fact that the expression of ATP-sulfurylase gene is significantly down-regulated in the IL5-1 with respect to S. lycopersicum fruits (J. Giovannoni, personal communication) together with the allelic differences previously mentioned favor the hypothesis that the S. pennellii allele of miRNA395c when introgressed into the domesticated variety leads to an efficient cleavage than the S. lycoperisum orthologue and that these differences could be implicated in the control of a few, if not all, of the QTL mapped on this genomic region.
MiSolRNA database allows the simple extraction of metadata favoring the proposal of new hypotheses about possible roles of miRNAs in the regulation of tomato fruit metabolism. It allows i) the mapping of miRNAs and their predicted target sites both on expressed (SGN-UNIGENES) and newly annotated sequences (BAC sequences released), ii) the co-location of any predicted miRNA-target interaction with metabolic QTL found in tomato fruits, iii) the retrieval of expression data of target genes in tomato fruit across development and iv) the design of further experiments aimed at addressing unresolved questions in complex trait biology. In summary, miSolRNA together with the previously released Tomato small RNAs database (http://ted.bti.cornell.edu/cgi-bin/TFGD/sRNA/home.cgi), provides an insight into putative miRNA target sites within specific regions of the tomato genome and ultimately of individual genes. It also displays how these putative target genes are expressed in fruits and the co-location of these target sites with QTL for fruit metabolism. These relations provide a stepping stone for new hypotheses based on robust genetic, structural genomic, mRNA expression and metabolite profiling data.
MiSolRNA will be updated as the tomato genome sequencing project proceeds and novel sRNAs discovered. Updates will be announced in an associated RSS feed. MiSolRNA is intended as a resource to integrate information on tomato (and other Solanaceae plant species) metabolism and its regulation by miRNAs. Different experimental approaches already in progress in our laboratories at the Instituto de Biotecnología and at the Max-Planck-Institute of Molecular Plant Physiology will be made available through this database. Given that the in-depth analysis and understanding of metabolic regulation at the systems level will require a multidisciplinary effort, we open the database as an informative public resource for researchers focusing on experimental biology and bioinformatics. Wet experiments are under progress and they will ultimately confirm relationships suggested here such as those presented in Figure 3.
miSOLRNA server, source code and database are freely available under the Affero GNU Public License (AGPL) at http://www.misolrna.org.
We appreciate the work of all scientists who contributed information and curation of the Solanaceae genomic resources, especially those deposited to the Solanaceae Genome Network (SGN). We are grateful to the Max-Planck-Institute of Molecular Plant Physiology and the Max-Planck-Society for long-standing and continuous support by a partnership to FC.
Funding: This work was partially supported with grants from Max Planck Society (Germany) to F.C., INTA (Argentina) CONICET (Argentina) and ANPCYT (Argentina) to F.C. and S.A. and under the auspices of the EU SOL Integrated Project FOOD-CT-2006-016214 to F.C. and A.R.F.. F.C., R.A. and S.A. are members of CONICET, Argentina. A.B. held a fellowship from EMBO.
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