Evidence map›Paper›PMID 27858103›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2017

Validating the prediction accuracies of marker-assisted and genomic selection of Fusarium head blight resistance in wheat using an independent sample.

Yong Jiang, Albert Wilhelm Schulthess, Bernd Rodemann, Jie Ling, Jörg Plieske, Sonja Kollers, Erhard Ebmeyer, Viktor Korzun, Odile Argillier, Gunther Stiewe and 3 more

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.8field-weighted citation impact, top 5% 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

25 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
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  4. Toward combining qualitative race-specific and quantitative race-nonspecific disease resistance by genomic selection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
  5. Article
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  8. Identification of the major QTLFrontiers in plant science · 2022
    Article
  9. Capturing Wheat Phenotypes at the Genome Level.Frontiers in plant science · 2022
    Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. From markers to genome-based breeding in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019
    Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

13 authors at 2 institutions in 1 country.

Yong JiangDepartment of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
Albert Wilhelm SchulthessDepartment of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
Bernd RodemannJulius Kühn Institute, Brunswick, Germany.
Jie LingDepartment of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
Jörg PlieskeTraitGenetics GmbH, Gatersleben, Germany.
Sonja KollersKWS LOCHOW GMBH, Bergen, Germany.
Erhard EbmeyerKWS LOCHOW GMBH, Bergen, Germany.
Viktor KorzunKWS LOCHOW GMBH, Bergen, Germany.
Odile ArgillierSyngenta France S.A.S., Orgerus, France.
Gunther StieweSyngenta Seeds GmbH, Bad Salzuflen, Germany.
Martin W GanalTraitGenetics GmbH, Gatersleben, Germany.
Marion S RöderDepartment of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany.
Jochen C ReifDepartment of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), 06466, Gatersleben, Germany. reif@ipk-gatersleben.de.
Leibniz Institute of Plant Genetics and Crop Plant Research · DEJulius Kühn-Institut · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

key messageCompared with independent validation, cross-validation simultaneously sampling genotypes and environments provided similar estimates of accuracy for genomic selection, but inflated estimates for marker-assisted selection. Estimates of prediction accuracy of marker-assisted (MAS) and genomic selection (GS) require validations. The main goal of our study was to compare the prediction accuracies of MAS and GS validated in an independent sample with results obtained from fivefold cross-validation using genomic and phenotypic data for Fusarium head blight resistance in wheat. In addition, the applicability of the reliability criterion, a concept originally developed in the context of classic animal breeding and GS, was explored for MAS. We observed that prediction accuracies of MAS were overestimated by 127% using cross-validation sampling genotype and environments in contrast to independent validation. In contrast, prediction accuracies of GS determined in independent samples are similar to those estimated with cross-validation sampling genotype and environments. This can be explained by small population differentiation between the training and validation sets in our study. For European wheat breeding, which is so far characterized by a slow temporal dynamic in allele frequencies, this assumption seems to be realistic. Thus, GS models used to improve European wheat populations are expected to possess a long-lasting validity. Since quantitative trait loci information can be exploited more precisely if the predicted genotype is more related to the training population, the reliability criterion is also a valuable tool to judge the level of prediction accuracy of individual genotypes in MAS.

Indexed as

Chromosome MappingDisease ResistanceFusariumGene FrequencyGenetic MarkersGenomicsGenotypeModels, GeneticPhenotypePlant BreedingPlant DiseasesQuantitative Trait LociReproducibility of ResultsTriticumGenetic Markers

Identifiers

PMID27858103
OpenAlexW2557086510

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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.