Evidence map›Paper›PMID 24151307›Full record

ArticleJournal of experimental botany2013

Deciphering genetic diversity and inheritance of tomato fruit weight and composition through a systems biology approach.

Laura Pascual, Jiaxin Xu, Benoît Biais, Mickaël Maucourt, Patricia Ballias, Stéphane Bernillon, Catherine Deborde, Daniel Jacob, Aurore Desgroux, Mireille Faurobert and 4 more

Abstract read
In one paragraph

Article in Journal of experimental botany, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. An IBD-based mixed model approach for QTL mapping in multiparental populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    Article
  5. Dissection of complex traits of tomato in the post-genome era.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020
    Review
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Laura PascualINRA, UR1052, Unité de Génétique et Amélioration des Fruits et Légumes, F-84143 Avignon, France.
Jiaxin Xu
Benoît Biais
Mickaël Maucourt
Patricia Ballias
Stéphane Bernillon
Catherine Deborde
Daniel Jacob
Aurore Desgroux
Mireille Faurobert
Jean-Paul Bouchet
Yves Gibon
Annick Moing
Mathilde Causse

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Integrative systems biology proposes new approaches to decipher the variation of phenotypic traits. In an effort to link the genetic variation and the physiological and molecular bases of fruit composition, the proteome (424 protein spots), metabolome (26 compounds), enzymatic profile (26 enzymes), and phenotypes of eight tomato accessions, covering the genetic diversity of the species, and four of their F1 hybrids, were characterized at two fruit developmental stages (cell expansion and orange-red). The contents of metabolites varied among the genetic backgrounds, while enzyme profiles were less variable, particularly at the cell expansion stage. Frequent genotype by stage interactions suggested that the trends observed for one accession at a physiological level may change in another accession. In agreement with this, the inheritance modes varied between crosses and stages. Although additivity was predominant, 40% of the traits were non-additively inherited. Relationships among traits revealed associations between different levels of expression and provided information on several key proteins. Notably, the role of frucktokinase, invertase, and cysteine synthase in the variation of metabolites was highlighted. Several stress-related proteins also appeared related to fruit weight differences. These key proteins might be targets for improving metabolite contents of the fruit. This systems biology approach provides better understanding of networks controlling the genetic variation of tomato fruit composition. In addition, the wide data sets generated provide an ideal framework to develop innovative integrated hypothesis and will be highly valuable for the research community.

Indexed as

Genetic VariationQuantitative Trait, HeritableEnzymesFruitGenotypeLeast-Squares AnalysisMetabolic Networks and PathwaysOrgan SizePlant ProteinsProteomeSolanum lycopersicumSystems BiologyEnzymesPlant ProteinsProteomeFruitmetabolomeproteomesystems biologytomato.

Identifiers

PMID24151307
PMCPMC3871826

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.