Evidence map›Paper›PMID 24518889›Full record

ArticleHeredity2014

Bridging the gap between marker-assisted and genomic selection of heading time and plant height in hybrid wheat.

Y Zhao, M F Mette, M Gowda, C F H Longin, J C Reif

Open access · bronzeAbstract read
In one paragraph

Article in Heredity, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers.

0numbers the graph read from it
0cells of the map it votes in
86citing papers in PubMed
26.6field-weighted citation impact, top 1% 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

86 citing papers in PubMed, 167 citations in OpenAlex.

  1. Evaluating reaction norm and fixed effect models for genomic selection of end-use quality in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  2. Genomic Analysis of Resistance toPathogens (Basel, Switzerland) · 2026
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  3. Targeted expansion of a barley genebank core collection facilitates the discovery of disease resistance loci.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  4. Article
  5. Review
  6. Assessment of genomic prediction capabilities of transcriptome data in a barley multi-parent RIL population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  7. Article
  8. Co-Location of QTL for Vigor and Resistance to Three Diseases inInternational journal of molecular sciences · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. 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
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Hybrid wheat: quantitative genetic parameters and heterosis for quality and rheological traits as well as baking volume.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Review
  19. Capturing Wheat Phenotypes at the Genome Level.Frontiers in plant science · 2022
    Review
  20. Article

26 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 2 countries.

Y ZhaoDepartment of Cytogenetics and Genome Analysis, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
M F MetteDepartment of Cytogenetics and Genome Analysis, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
M GowdaState Plant Breeding Institute, University of Hohenheim, Stuttgart, Germany.
C F H LonginState Plant Breeding Institute, University of Hohenheim, Stuttgart, Germany.
J C ReifDepartment of Cytogenetics and Genome Analysis, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany.
Leibniz Institute of Plant Genetics and Crop Plant Research · DECentro Internacional de Mejoramiento de Maíz Y Trigo · MXUniversity of Hohenheim · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on data from field trials with a large collection of 135 elite winter wheat inbred lines and 1604 F1 hybrids derived from them, we compared the accuracy of prediction of marker-assisted selection and current genomic selection approaches for the model traits heading time and plant height in a cross-validation approach. For heading time, the high accuracy seen with marker-assisted selection severely dropped with genomic selection approaches RR-BLUP (ridge regression best linear unbiased prediction) and BayesCπ, whereas for plant height, accuracy was low with marker-assisted selection as well as RR-BLUP and BayesCπ. Differences in the linkage disequilibrium structure of the functional and single-nucleotide polymorphism markers relevant for the two traits were identified in a simulation study as a likely explanation for the different trends in accuracies of prediction. A new genomic selection approach, weighted best linear unbiased prediction (W-BLUP), designed to treat the effects of known functional markers more appropriately, proved to increase the accuracy of prediction for both traits and thus closes the gap between marker-assisted and genomic selection.

Indexed as

Genome, PlantQuantitative Trait, HeritableSelection, GeneticAllelesBreedingDatasets as TopicGenetic MarkersGenetic VariationGenotypeHybridization, GeneticLinkage DisequilibriumModels, GeneticPhenotypePolymorphism, Single NucleotideQuantitative Trait LociReproducibility of ResultsGenetic Markers

Identifiers

PMID24518889
PMCPMC4023446
OpenAlexW2031742569

What OpenQuestion holds

Textmetadata
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.