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Label-free deep shotgun proteomics reveals protein dynamics during tomato fruit tissues development.

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TLDR
Large-scale shotgun proteomics profiling of tomato fruit across two key tissues and five developmental stages is presented, adding a new dimension to the existing genomic, transcriptomic and metabolomic resources.
Abstract
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 crop plants engaged with global proteome assays. Here, we present large-scale shotgun proteomics profiling of tomato fruit across two key tissues and five developmental stages. A total of 7738 individual protein groups were identified and reliably measured at least in one of the analyzed tissues or stages. The depth of our assay enabled identification of 61 differentially expressed transcription factors, including renowned ripening-related regulators and elements of ethylene signaling. Significantly, we measured proteins involved in 83% of all predicted enzymatic reactions in the tomato metabolic network. Hence, proteins representing almost the complete set of reactions in major metabolic pathways were identified, 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 view of skin and flesh tissues in developing fruit. This study adds a new dimension 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.

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Citations
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Journal ArticleDOI

Trait discovery and editing in tomato

TL;DR: Insight is provided into the major tomato traits and underlying causal genetic variations discovered so far and the existing genetic resources and most recent strategies for trait discovery in tomato and the opportunities offered by CRISPR/Cas9 and their exploitation for trait editing are explored.
Journal ArticleDOI

Putting primary metabolism into perspective to obtain better fruits.

TL;DR: Since high-quality data are a key requirement in modelling, a range of must-have parameters and variables is proposed.
Journal ArticleDOI

Proteomics and metabolomics analysis of tomato fruit at different maturity stages and under salt treatment.

TL;DR: Proteomics and metabolomics used to study the changes in proteins and metabolites in tomato fruits at different ripening stages and the effect of salt treatment on fruit quality showed 2607 and 153 differentially expressed proteins in ripe fruits compared with mature green fruits and in NaCl-treated ripe fruitsCompared with control ripe fruits.
Journal ArticleDOI

The Tomato Translational Landscape Revealed by Transcriptome Assembly and Ribosome Profiling.

TL;DR: The approach provides a high-throughput method to discover unannotated ORFs, elucidates evolutionarily conserved and unique translational features, and identifies regulatory mechanisms hidden in a crop genome.
References
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Journal ArticleDOI

limma powers differential expression analyses for RNA-sequencing and microarray studies

TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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Universal sample preparation method for proteome analysis

TL;DR: A method is described, filter-aided sample preparation (FASP), which combines the advantages of in-gel and in-solution digestion for mass spectrometry–based proteomics and allows single-run analyses of organelles and an unprecedented depth of proteome coverage.
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Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

TL;DR: A statistical model is presented to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST, demonstrating that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides.
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2016 update of the PRIDE database and its related tools

TL;DR: The developments in PRIDE resources and related tools are summarized and a brief update on the resources under development 'PRIDE Cluster' and 'PRide Proteomes', which provide a complementary view and quality-scored information of the peptide and protein identification data available inPRIDE Archive are given.
Journal ArticleDOI

MAPMAN: a user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes

TL;DR: Widespread changes in the expression of genes encoding receptor kinases, transcription factors, components of signalling pathways, proteins involved in post-translational modification and turnover, and proteins involved with the synthesis and sensing of cytokinins, abscisic acid and ethylene revealing large-scale rewiring of the regulatory network is an early response to sugar depletion are revealed.
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