Evidence map›Paper›PMID 27760136›Full record

ArticlePLoS genetics2016

Combined Use of Genome-Wide Association Data and Correlation Networks Unravels Key Regulators of Primary Metabolism in Arabidopsis thaliana.

Si Wu, Saleh Alseekh, Álvaro Cuadros-Inostroza, Corina M Fusari, Marek Mutwil, Rik Kooke, Joost B Keurentjes, Alisdair R Fernie, Lothar Willmitzer, Yariv Brotman

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% of its field
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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

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  13. Genetic dissection reveals the complex architecture of amino acid composition in soybean seeds.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
  14. Validation of a metabolite-GWAS network forFrontiers in plant science · 2023
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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

10 authors at 3 institutions in 3 countries.

Si WuMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Saleh AlseekhMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Álvaro Cuadros-InostrozaMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Corina M FusariMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.ORCID http://orcid.org/0000-0001-6809-0266
Marek MutwilMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Rik KookeLaboratory of Genetics, Wageningen University, Wageningen, the Netherlands.ORCID http://orcid.org/0000-0002-8161-9811
Joost B KeurentjesLaboratory of Genetics, Wageningen University, Wageningen, the Netherlands.ORCID http://orcid.org/0000-0001-8918-0711
Alisdair R FernieMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Lothar WillmitzerMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.ORCID http://orcid.org/0000-0003-3297-825X
Yariv BrotmanMax Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
Max Planck Institute of Molecular Plant Physiology · DEWageningen University & Research · NLBen-Gurion University of the Negev · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant primary metabolism is a highly coordinated, central, and complex network of biochemical processes regulated at both the genetic and post-translational levels. The genetic basis of this network can be explored by analyzing the metabolic composition of genetically diverse genotypes in a given plant species. Here, we report an integrative strategy combining quantitative genetic mapping and metabolite‒transcript correlation networks to identify functional associations between genes and primary metabolites in Arabidopsis thaliana. Genome-wide association study (GWAS) was used to identify metabolic quantitative trait loci (mQTL). Correlation networks built using metabolite and transcript data derived from a previously published time-course stress study yielded metabolite‒transcript correlations identified by covariation. Finally, results obtained in this study were compared with mQTL previously described. We applied a statistical framework to test and compare the performance of different single methods (network approach and quantitative genetics methods, representing the two orthogonal approaches combined in our strategy) with that of the combined strategy. We show that the combined strategy has improved performance manifested by increased sensitivity and accuracy. This combined strategy allowed the identification of 92 candidate associations between structural genes and primary metabolites, which not only included previously well-characterized gene‒metabolite associations, but also revealed novel associations. Using loss-of-function mutants, we validated two of the novel associations with genes involved in tyrosine degradation and in β-alanine metabolism. In conclusion, we demonstrate that applying our integrative strategy to the largely untapped resource of metabolite-transcript associations can facilitate the discovery of novel metabolite-related genes. This integrative strategy is not limited to A. thaliana, but generally applicable to other plant species.

Indexed as

Arabidopsis ProteinsGenome-Wide Association StudyAlanineArabidopsisChromosome MappingGene Expression Regulation, PlantGenetic VariationGenome, PlantGenotypeQuantitative Trait LociStatistics as TopicTyrosineAlanineArabidopsis ProteinsTyrosine

Identifiers

PMID27760136
PMCPMC5070769
OpenAlexW2534495003

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.