Evidence map›Paper›PMID 26272883›Full record

ArticlePlant physiology2015

Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights.

Nicole E Soltis, Daniel J Kliebenstein

Abstract read
In one paragraph

Article in Plant physiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Metabolic plasticity and adaptive evolution inFrontiers in plant science · 2025
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  12. SNPeffect: identifying functional roles of SNPs using metabolic networks.The Plant journal : for cell and molecular biology · 2020
    Article
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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

2 authors.

Nicole E SoltisDepartment of Plant Sciences, University of California, Davis, California 95616 (N.E.S., D.J.K.); andDynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark (D.J.K.).
Daniel J KliebensteinDepartment of Plant Sciences, University of California, Davis, California 95616 (N.E.S., D.J.K.); andDynaMo Center of Excellence, University of Copenhagen, DK-1871 Frederiksberg C, Denmark (D.J.K.) kliebenstein@ucdavis.edu.ORCID http://orcid.org/0000-0001-5759-3175

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combining quantitative genetics studies with metabolomics/metabolic profiling platforms, genomics, and transcriptomics is creating significant progress in identifying the causal genes controlling natural variation in metabolite accumulations and profiles. In this review, we discuss key mechanistic and evolutionary insights that are arising from these studies. This includes the potential role of transport and other processes in leading to a separation of the site of mechanistic causation and metabolic consequence. A reilluminated observation is the potential for genomic variation in the organelle to alter phenotypic variation alone and in epistatic interaction with the nuclear genetic variation. These studies are also highlighting new aspects of metabolic pleiotropy both in terms of the breadth of loci altering metabolic variation as well as the potential for broader effects on plant defense regulation of the metabolic variation than has previously been predicted. We also illustrate caveats that can be overlooked when translating quantitative genetics descriptors such as heritability and per-locus r(2) to mechanistic or evolutionary interpretations.

Indexed as

Biological EvolutionEpistasis, GeneticGene Expression Regulation, PlantGenome, PlantGenotypeMetabolomicsPlantsSpecies SpecificityTranscriptome

Identifiers

PMID26272883
PMCPMC4634085

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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.