Evidence map›Paper›PMID 32488300›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2020

The value of early-stage phenotyping for wheat breeding in the age of genomic selection.

Daniel Borrenpohl, Mao Huang, Eric Olson, Clay Sneller

Abstract read
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In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. The effect of selection on allele frequencies and diversity in wheat (Triticum aestivum).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  2. Article
  3. The effect of cycles of genomic selection on the wheat (T. aestivum) genome.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023
    Article
  4. Article
  5. Article
  6. Article
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

4 authors.

Daniel BorrenpohlDepartment of Horticulture and Crop Science, Ohio Agriculture Research and Development Center, The Ohio State University, 1680 Madison Av, Wooster, OH, 44691, USA.
Mao HuangDepartment of Horticulture and Crop Science, Ohio Agriculture Research and Development Center, The Ohio State University, 1680 Madison Av, Wooster, OH, 44691, USA.
Eric OlsonDepartment of Plant, Soil, and Microbial Science, Michigan State University, 1066 Bogue St, East Lansing, MI, 48824, USA.
Clay SnellerDepartment of Horticulture and Crop Science, Ohio Agriculture Research and Development Center, The Ohio State University, 1680 Madison Av, Wooster, OH, 44691, USA. sneller.5@osu.edu.ORCID http://orcid.org/0000-0003-4195-4743

Funding

Agricultural Research Service 1234567
6 · The paper itself

Abstract

key messageGenomic selection using data from an on-going breeding program can improve gain from selection, relative to phenotypic selection, by significantly increasing the number of lines that can be evaluated. The early stages of phenotyping involve few observations and can be quite inaccurate. Genomic selection (GS) could improve selection accuracy and alter resource allocation. Our objectives were (1) to compare the prediction accuracy of GS and phenotyping in stage-1 and stage-2 field evaluations and (2) to assess the value of stage-1 phenotyping for advancing lines to stage-2 testing. We built training populations from 1769 wheat breeding lines that were genotyped and phenotyped for yield, test weight, Fusarium head blight resistance, heading date, and height. The lines were in cohorts, and analyses were done by cohort. Phenotypes or GS estimated breeding values were used to determine the trait value of stage-1 lines, and these values were correlated with their phenotypes from stage-2 trials. This was repeated for stage-2 to stage-3 trials. The prediction accuracy of GS and phenotypes was similar to each other regardless of the amount (0, 50, 100%) of stage-1 data incorporated in the GS model. Ranking of stage-1 lines by GS predictions that used no stage-1 phenotypic data had marginally lower correspondence to stage-2 phenotypic rankings than rankings of stage-1 lines based on phenotypes. Stage-1 lines ranked high by GS had slightly inferior phenotypes in stage-2 trials than lines ranked high by phenotypes. Cost analysis indicated that replacing stage-1 phenotyping with GS would allow nearly three times more stage-1 candidates to be assessed and provide 0.84-2.23 times greater gain from selection. We conclude that GS can complement or replace phenotyping in early stages of phenotyping.

Indexed as

Selection, GeneticComputer SimulationData AccuracyFusariumGenome, PlantGenomicsGenotypeHigh-Throughput Nucleotide SequencingModels, GeneticPhenotypePlant BreedingPolymorphism, Single NucleotideQuantitative Trait LociRegression AnalysisTriticum

Identifiers

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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.