Evidence map›Paper›PMID 24850820›Full record

ArticleGenetics2014

Genome properties and prospects of genomic prediction of hybrid performance in a breeding program of maize.

Frank Technow, Tobias A Schrag, Wolfgang Schipprack, Eva Bauer, Henner Simianer, Albrecht E Melchinger

Abstract read
In one paragraph

Article in Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 130 papers.

0numbers the graph read from it
0cells of the map it votes in
130citing 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

130 citing papers in PubMed.

  1. Article
  2. Review
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  5. Article
  6. Improving hybrid breeding efficiency in winter oilseed rape under sparse multi-environment testing.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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  20. Review

70 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

6 authors.

Frank TechnowInstitute of Plant Breeding, Seed Sciences, and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany.
Tobias A SchragInstitute of Plant Breeding, Seed Sciences, and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany.
Wolfgang SchipprackInstitute of Plant Breeding, Seed Sciences, and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany.
Eva BauerPlant Breeding, Technische Universität München, 85354 Freising, Germany.
Henner SimianerDepartment of Animal Sciences, Georg-August-University Goettingen, 37075 Goettingen, Germany.
Albrecht E MelchingerInstitute of Plant Breeding, Seed Sciences, and Population Genetics, University of Hohenheim, 70599 Stuttgart, Germany melchinger@uni-hohenheim.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maize (Zea mays L.) serves as model plant for heterosis research and is the crop where hybrid breeding was pioneered. We analyzed genomic and phenotypic data of 1254 hybrids of a typical maize hybrid breeding program based on the important Dent × Flint heterotic pattern. Our main objectives were to investigate genome properties of the parental lines (e.g., allele frequencies, linkage disequilibrium, and phases) and examine the prospects of genomic prediction of hybrid performance. We found high consistency of linkage phases and large differences in allele frequencies between the Dent and Flint heterotic groups in pericentromeric regions. These results can be explained by the Hill-Robertson effect and support the hypothesis of differential fixation of alleles due to pseudo-overdominance in these regions. In pericentromeric regions we also found indications for consistent marker-QTL linkage between heterotic groups. With prediction methods GBLUP and BayesB, the cross-validation prediction accuracy ranged from 0.75 to 0.92 for grain yield and from 0.59 to 0.95 for grain moisture. The prediction accuracy of untested hybrids was highest, if both parents were parents of other hybrids in the training set, and lowest, if none of them were involved in any training set hybrid. Optimizing the composition of the training set in terms of number of lines and hybrids per line could further increase prediction accuracy. We conclude that genomic prediction facilitates a paradigm shift in hybrid breeding by focusing on the performance of experimental hybrids rather than the performance of parental lines in test crosses.

Indexed as

Genome, PlantBreedingGene FrequencyGenetic MarkersHybridization, GeneticHybrid VigorLinkage DisequilibriumModels, GeneticPhenotypeQuantitative Trait LociZea maysGenetic Markersgenomic predictionGenPred, shared data resourcesheterotic groupshybrid breedinglinkage phasestraining set design

Identifiers

PMID24850820
PMCPMC4125404

What OpenQuestion holds

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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.