Evidence map›Paper›PMID 32502173›Full record

ArticlePloS one2020

Can metabolic prediction be an alternative to genomic prediction in barley?

Mathias Ruben Gemmer, Chris Richter, Yong Jiang, Thomas Schmutzer, Manish L Raorane, Björn Junker, Klaus Pillen, Andreas Maurer

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

21 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
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  4. Integrating multi-omics and machine learning for disease resistance prediction in legumes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
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  7. Multi-omics assists genomic prediction of maize yield with machine learning approaches.Molecular breeding : new strategies in plant improvement · 2024
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Metabolomic selection for enhanced fruit flavor.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. 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

8 authors at 2 institutions in 1 country.

Mathias Ruben GemmerInstitute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany.
Chris RichterInstitute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany.
Yong JiangDepartment of Breeding Research, Quantitative Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research, Gatersleben, Germany.ORCID 0000-0002-2824-677X
Thomas SchmutzerInstitute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany.ORCID 0000-0003-1073-6719
Manish L RaoraneInstitute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany.
Björn JunkerInstitute of Pharmacy, Martin Luther University Halle-Wittenberg, Halle, Germany.
Klaus PillenInstitute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany.
Andreas MaurerInstitute of Agricultural and Nutritional Sciences, Chair of Plant Breeding, Martin Luther University Halle-Wittenberg, Halle, Germany.ORCID 0000-0002-2916-7475
Martin Luther University Halle-Wittenberg · DELeibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Like other crop species, barley, the fourth most important crop worldwide, suffers from the genetic bottleneck effect, where further improvements in performance through classical breeding methods become difficult. Therefore, indirect selection methods are of great interest. Here, genomic prediction (GP) based on 33,005 SNP markers and, alternatively, metabolic prediction (MP) based on 128 metabolites with sampling at two different time points in one year, were applied to predict multi-year agronomic traits in the nested association mapping (NAM) population HEB-25. We found prediction abilities of up to 0.93 for plant height with SNP markers and of up to 0.61 for flowering time with metabolites. Interestingly, prediction abilities in GP increased after reducing the number of incorporated SNP markers. The estimated effects of GP and MP were highly concordant, indicating MP as an interesting alternative to GP, being able to reflect a stable genotype-specific metabolite profile. In MP, sampling at an early developmental stage outperformed sampling at a later stage. The results confirm the value of GP for future breeding. With MP, an interesting alternative was also applied successfully. However, based on our results, usage of MP alone cannot be recommended in barley. Nevertheless, MP can assist in unravelling physiological pathways for the expression of agronomically important traits.

Indexed as

Genome, PlantMetabolomeBayes TheoremChromosome MappingGenotypeHordeumPhenotypePolymorphism, Single Nucleotide

Identifiers

PMID32502173
PMCPMC7274421
OpenAlexW3034043436

What OpenQuestion holds

Textmetadata
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.