Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Microarray analysis of gene expression from different developmental stages of the tomato fruit

ABSTRACT: The goal of this research was to measure the gene expression levels thoughout 10 stages of tomato fruit development. Whole buds, flowers or fruits were collected at various developmental timepoints. Total RNA was extracted from 10 stages of flower and fruit development. A single technical and biological repeat was performed. cDNA was amplified and labelled using standard Affymetrix protocols.

ORGANISM(S): Solanum lycopersicum

SUBMITTER: Irina Mohorianu

PROVIDER: E-GEOD-22300 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Diverse correlation patterns between microRNAs and their targets during tomato fruit development indicates different modes of microRNA actions.

Lopez-Gomollon Sara S Mohorianu Irina I Szittya Gyorgy G Moulton Vincent V Dalmay Tamas T

Planta 20120826 6

MicroRNAs negatively regulate the accumulation of mRNAs therefore when they are expressed in the same cells their expression profiles show an inverse correlation. We previously described one positively correlated miRNA/target pair, but it is not known how widespread this phenomenon is. Here, we investigated the correlation between the expression profiles of differentially expressed miRNAs and their targets during tomato fruit development using deep sequencing, Northern blot and RT-qPCR. We found ...[more]

PMID: 22922939

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Project description:Gene-to-gene coexpression analysis is a powerful approach to infer function of uncharacterized genes. To perform non-targeted coexpression analysis of tomato genes, we collected a developmental gene expression dataset using various tissues of tomato plant. Expression data are collected from 24 different tissue types including root, hypocotyl, cotyledon, leaf at different stages, and fruit tissues at 4 different ripening stages from 4 different Solanum lycopersicum cultivars. Fruits were separated to the flesh and the peel. These two tissue types indeed showed remarkably different gene expression profiles. We also collected data from 4 different ripening stages (mature green, yellow, orange, and red) to detail the changes during ripening. By using this gene expression dataset, we calculated pair-wise Pearsonâs correlation coefficients, and performed network-based coexpression analysis. The analysis generated a number of coexpression modules, some of which showed an enrichment of genes associated with specific functional categories. This result will be useful in inferring functions of uncharacterized tomato genes, and in prioritizing genes for further experimental analysis. We used Affymetrix GeneChip Tomato genome Arrays to detail the global gene expression change using 24 different tomato tissue types (67 hybridizations). We collected gene expression data from 24 different tomato tissue types using 67 hybridizations. Root, hypocotyl, cotyledon, and leaf were sampled from 3-week-old or 5-weekâold plant of Solanum lycopersicum cultivar Micro-Tom. Fruit tissues were sampled from S. lycopersicum cultivars Micro-Tom, Anthocyanin fruit (Aft, LA1996), Line27859, and Momotaro 8 (Takii, Japan). From Micro-Tom fruit, the peel and the flesh were separately sampled from 4 different ripening stages: mature green (MG, approximately 30 day after anthesis), yellow (Y, approximately 35 days after anthesis), orange (O, approximately 38-40 days after anthesis), and red (R, approximately 45-48 days after anthesis). From fruits of Aft and Line27859, the peel and the flesh were sampled at mature green (MG, approximately 40 days after anthesis) and red (R, approximately 50-55 days after anthesis) stages. From Momotaro 8, the peel and the flesh were sampled at red (R, 50- approximately 50-55 days after anthesis) stages. For each tissue type, 2-4 biological replicates were made in RNA preparation.

Project description:Current innovations in mass-spectrometry-based technologies allow deep coverage of protein expression. Despite its immense value and in contrast to transcriptomics, only a handful of studies in Arabidopsis and especially other plant species engaged with global proteome assays. Here, we present large-scale protein profiling of tomato fruit across two key tissues and five developmental stages. This was accomplished by means of a shotgun proteomic assay comprising prior multi-step peptide fractionation followed by nano flow liquid chromatography coupled with high-resolution mass-spectrometry. A total of 7738 individual proteins were identified and reliably measured at least in one of the analysed tissues or stages. The detection of 115 putative transcription factors (TFs) further demonstrated the depth of our assay since a small number of TF proteins are typically detected in plant proteomics assays. Among this TFs set, 61 were differentially expressed in fruit development including renowned ripening regulators and elements of ethylene signalling. Curiously, we measured more than 80% of the predicted enzymatic reactions in the tomato metabolic network. Hence, proteins representing almost the complete set of reactions in major metabolic pathways were detected including the cytosolic and plastidic isoprenoid and the phenylpropanoid pathways. Furthermore, the data allowed us to discern between protein isoforms according to expression patterns which is most significant in light of the weak transcript-protein expression correspondence. Finally, visualization of changes in protein abundance associated with a particular process provided us with a unique, protein level view of skin and flesh tissues in developing fruit. This study adds a different perspective to the existing genomic, transcriptomic and metabolomic resources. It is therefore likely to promote translational and post-translational research in tomato and additional species which is presently focused on transcription.

Dataset Information

Microarray analysis of gene expression from different developmental stages of the tomato fruit

Publications

Diverse correlation patterns between microRNAs and their targets during tomato fruit development indicates different modes of microRNA actions.

Similar Datasets

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