Tissue specialization at the metabolite level is perceived during the development of tomato fruit

Moco, Sofia; Capanoglu, Esra; Tikunov, Yury; Bino, R.J.; Boyacıoğlu, Dilek; Hall, Robert D.; Vervoort, Jacques; Vos, Ric C. H. de

doi:10.1093/jxb/erm271

Cited by 182 publications

(198 citation statements)

References 47 publications

Supporting

Mentioning

179

Contrasting

Unclassified

Order By: Relevance

“…2-4), in accordance with the different cell size and shape in these tissues (Fig. 1) and with published results (Moco et al, 2007). Organic acids (malate, citrate, and fumarate) as well as GABA, acidic amino acids (Glu and Asp), and some soluble sugars (Suc and UDP-Glc) were more abundant in locular tissue at the end of the cell expansion period.…”

Section: Discussionsupporting

confidence: 90%

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development

et al. 2009

View full text Add to dashboard Cite

Variations in early fruit development and composition may have major impacts on the taste and the overall quality of ripe tomato (Solanum lycopersicum) fruit. To get insights into the networks involved in these coordinated processes and to identify key regulatory genes, we explored the transcriptional and metabolic changes in expanding tomato fruit tissues using multivariate analysis and gene-metabolite correlation networks. To this end, we demonstrated and took advantage of the existence of clear structural and compositional differences between expanding mesocarp and locular tissue during fruit development (12-35 d postanthesis). Transcriptome and metabolome analyses were carried out with tomato microarrays and analytical methods including proton nuclear magnetic resonance and liquid chromatography-mass spectrometry, respectively. Pairwise comparisons of metabolite contents and gene expression profiles detected up to 37 direct gene-metabolite correlations involving regulatory genes (e.g. the correlations between glutamine, bZIP, and MYB transcription factors). Correlation network analyses revealed the existence of major hub genes correlated with 10 or more regulatory transcripts and embedded in a large regulatory network. This approach proved to be a valuable strategy for identifying specific subsets of genes implicated in key processes of fruit development and metabolism, which are therefore potential targets for genetic improvement of tomato fruit quality.

show abstract

Section: Discussionsupporting

confidence: 90%

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development

et al. 2009

View full text Add to dashboard Cite

show abstract

“…A possible explanation for this disparity is that gene expression is not uniform across the different fruit tissues during ripening. This hypothesis is supported by a study of tissue-specific metabolites during tomato development, where differences in metabolite profiles were detected between specific tissues and at different ripening stages (Moco et al, 2007).…”

Section: Discussionmentioning

confidence: 77%

High-Resolution Mapping of a Fruit Firmness-Related Quantitative Trait Locus in Tomato Reveals Epistatic Interactions Associated with a Complex Combinatorial Locus

Chapman

Bonnet²,

Grivet³

et al. 2012

Plant Physiology

View full text Add to dashboard Cite

Fruit firmness in tomato (Solanum lycopersicum) is determined by a number of factors including cell wall structure, turgor, and cuticle properties. Firmness is a complex polygenic trait involving the coregulation of many genes and has proved especially challenging to unravel. In this study, a quantitative trait locus (QTL) for fruit firmness was mapped to tomato chromosome 2 using the Zamir Solanum pennellii interspecific introgression lines (ILs) and fine-mapped in a population consisting of 7,500 F2 and F3 lines from IL 2-3 and IL 2-4. This firmness QTL contained five distinct subpeaks, Fir s.p. QTL2.1 to Fir s.p. QTL2.5, and an effect on a distal region of IL 2-4 that was nonoverlapping with IL 2-3. All these effects were located within an 8.6-Mb region. Using genetic markers, each subpeak within this combinatorial locus was mapped to a physical location within the genome, and an ethylene response factor (ERF) underlying Fir s.p. QTL2.2 and a region containing three pectin methylesterase (PME) genes underlying Fir s.p. QTL2.5 were nominated as QTL candidate genes. Statistical models used to explain the observed variability between lines indicated that these candidates and the nonoverlapping portion of IL 2-4 were sufficient to account for the majority of the fruit firmness effects. Quantitative reverse transcription-polymerase chain reaction was used to quantify the expression of each candidate gene. ERF showed increased expression associated with soft fruit texture in the mapping population. In contrast, PME expression was tightly linked with firm fruit texture. Analysis of a range of recombinant lines revealed evidence for an epistatic interaction that was associated with this combinatorial locus.

show abstract

“…Information theory has been used for multivariate data generated in a broad scope of biological contexts ranging from plant ecology (23) to microbiome diversity (24), but, to our knowledge, it has never been used to summarize trends in MS-based metabolomics data. Previous studies identified preferential tissue-based redirectionalities in secondary metabolism, for instance, during the maturation of tomato fruits for which the green, turning, and red developmental stages are characterized by rearrangements in pathways related to flavonoids, phenolics, and glycoalkaloids (25). However, to our knowledge, no unbiased metabolomics study, other than a study of the AtMetExpress database (6), has been applied with rigorous statistical analysis to such a broad range of tissues as in the present study.…”

Section: Discussionmentioning

confidence: 93%

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Heiling

Baldwin

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Secondary metabolite diversity is considered an important fitness determinant for plants' biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissuemetabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function.secondary metabolism | mass spectrometry | metabolomics | information theory | Nicotiana attenuata P lants are elegant synthetic chemists making use of their metabolic prowess to produce complex blends of structurally diverse chemicals. Commonly quoted estimates state that plants produce somewhere on the order of 200,000 chemical structures. Secondary metabolites, also referred to as specialized metabolites or natural products, contribute to the largest fraction of this structural diversity. Compared with their counterparts in central metabolism (primary metabolites), secondary metabolite groups have diversified to the extreme in plant lineages, likely as a result of the multiple ecological roles they fulfill (1). The high degree of plasticity of secondary metabolism pathways is consistent with the existence of large families of metabolism-related genes such as cytochrome P450s and UDP-glycosyltransferases in plant genomes that can create structural and chemical modifications almost without limits. The majority of metabolic gene functions remain unknown, however, either because the metabolites that they produce are unknown or signi...

show abstract

Tissue specialization at the metabolite level is perceived during the development of tomato fruit

Cited by 182 publications

References 47 publications

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development

Gene and Metabolite Regulatory Network Analysis of Early Developing Fruit Tissues Highlights New Candidate Genes for the Control of Tomato Fruit Composition and Development

High-Resolution Mapping of a Fruit Firmness-Related Quantitative Trait Locus in Tomato Reveals Epistatic Interactions Associated with a Complex Combinatorial Locus

Illuminating a plant’s tissue-specific metabolic diversity using computational metabolomics and information theory

Contact Info

Product

Resources

About