Evidence map›Paper›PMID 32371453›Full record

ArticleG3 (Bethesda, Md.)2020

Improving Prediction Accuracy Using Multi-allelic Haplotype Prediction and Training Population Optimization in Wheat.

Ahmad H Sallam, Emily Conley, Dzianis Prakapenka, Yang Da, James A Anderson

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Exploring the potential of naked barley to manage deoxynivalenol accumulation from Fusarium head blight.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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  9. Review
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  11. Genomic prediction with haplotype blocks in wheat.Frontiers in plant science · 2023
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. 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

5 authors.

Ahmad H SallamDepartment of Plant Pathology.ORCID 0000-0003-3212-9231
Emily ConleyDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108.
Dzianis PrakapenkaDepartment of Animal Science, and.ORCID 0000-0002-4592-7120
Yang DaDepartment of Animal Science, and.
James A AndersonDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108 ander319@umn.edu.ORCID 0000-0003-4655-6517

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of haplotypes may improve the accuracy of genomic prediction over single SNPs because haplotypes can better capture linkage disequilibrium and genomic similarity in different lines and may capture local high-order allelic interactions. Additionally, prediction accuracy could be improved by portraying population structure in the calibration set. A set of 383 advanced lines and cultivars that represent the diversity of the University of Minnesota wheat breeding program was phenotyped for yield, test weight, and protein content and genotyped using the Illumina 90K SNP Assay. Population structure was confirmed using single SNPs. Haplotype blocks of 5, 10, 15, and 20 adjacent markers were constructed for all chromosomes. A multi-allelic haplotype prediction algorithm was implemented and compared with single SNPs using both

Indexed as

Plant BreedingTriticumGenotypeHaplotypesLinkage DisequilibriumPhenotypePolymorphism, Single Nucleotidegenomic selectionGenPredhaplotype predictionplant breedingquantitative trait lociShared data resourcestraining population optimizationwheat

Identifiers

PMID32371453
PMCPMC7341132

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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.