Evidence map›Paper›PMID 24150750›Full record

ArticleeLife2013

Cytoplasmic genetic variation and extensive cytonuclear interactions influence natural variation in the metabolome.

Bindu Joseph, Jason A Corwin, Baohua Li, Suzi Atwell, Daniel J Kliebenstein

Abstract read
In one paragraph

Article in eLife, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

43 citing papers in PubMed.

  1. Article
  2. Article
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  5. A trans-species cytoplasmic polymorphism is associated with seed shape and aridity across multiple species of sunflowers.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  6. Review
  7. OptimizingPlants (Basel, Switzerland) · 2024
    Review
  8. Article
  9. Plant biochemical genetics in the multiomics era.Journal of experimental botany · 2023
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Daniel J. Kliebenstein.The Plant cell · 2018
    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

5 authors.

Bindu JosephDepartment of Plant Sciences, University of California, Davis, Davis, United States.
Jason A Corwin
Baohua Li
Suzi Atwell
Daniel J Kliebenstein

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding genome to phenotype linkages has been greatly enabled by genomic sequencing. However, most genome analysis is typically confined to the nuclear genome. We conducted a metabolomic QTL analysis on a reciprocal RIL population structured to examine how variation in the organelle genomes affects phenotypic variation. This showed that the cytoplasmic variation had effects similar to, if not larger than, the largest individual nuclear locus. Inclusion of cytoplasmic variation into the genetic model greatly increased the explained phenotypic variation. Cytoplasmic genetic variation was a central hub in the epistatic network controlling the plant metabolome. This epistatic influence manifested such that the cytoplasmic background could alter or hide pairwise epistasis between nuclear loci. Thus, cytoplasmic genetic variation plays a central role in controlling natural variation in metabolomic networks. This suggests that cytoplasmic genomes must be included in any future analysis of natural variation. DOI: http://dx.doi.org/10.7554/eLife.00776.001.

Indexed as

Genetic VariationMetabolomicsCell NucleusCytoplasmEpistasis, GeneticGenes, PlantPlant ProteinsPlantsQuantitative Trait LociPlant Proteinsgenomic variationmaternal geneticsorganellar variation

Identifiers

PMID24150750
PMCPMC3791467

What OpenQuestion holds

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LicenceCC BY
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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.