Evidence map›Paper›PMID 30420469›Full record

ArticleG3 (Bethesda, Md.)2019

Genotype Imputation in Winter Wheat Using First-Generation Haplotype Map SNPs Improves Genome-Wide Association Mapping and Genomic Prediction of Traits.

Moses Nyine, Shichen Wang, Kian Kiani, Katherine Jordan, Shuyu Liu, Patrick Byrne, Scott Haley, Stephen Baenziger, Shiaoman Chao, Robert Bowden and 1 more

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Genotype imputation for soybean nested association mapping population to improve precision of QTL detection.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  8. Article
  9. Multi-stage resistance toFrontiers in plant science · 2022
    Article
  10. Article
  11. Article
  12. The Haplotype-Based Analysis ofFrontiers in plant science · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. 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

11 authors.

Moses NyineDepartment of Plant Pathology, Kansas State University, Manhattan, KS 66506.ORCID 0000-0002-8409-7588
Shichen WangDepartment of Plant Pathology, Kansas State University, Manhattan, KS 66506.ORCID 0000-0003-1441-2252
Kian KianiDepartment of Plant Pathology, Kansas State University, Manhattan, KS 66506.
Katherine JordanDepartment of Plant Pathology, Kansas State University, Manhattan, KS 66506.
Shuyu LiuTexas A&M AgriLife Research, Amarillo, TX 79106.
Patrick ByrneDepartment of Soil & Crop Sciences, Colorado State University, Fort Collins, CO 80523.
Scott HaleyDepartment of Soil & Crop Sciences, Colorado State University, Fort Collins, CO 80523.ORCID 0000-0002-1996-9570
Stephen BaenzigerDepartment of Agronomy and Horticulture, University of Nebraska, Lincoln, NE 68583-0915.ORCID 0000-0002-9109-6954
Shiaoman ChaoUSDA-ARS Cereal Crops Research Unit, Fargo, ND 58102-2765.
Robert BowdenUSDA-ARS Hard Winter Wheat Genetics Research Unit, Kansas State University, Manhattan, KS 66506.ORCID 0000-0001-9419-6574
Eduard AkhunovDepartment of Plant Pathology, Kansas State University, Manhattan, KS 66506 eakhunov@ksu.edu.ORCID 0000-0002-0416-5211

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide single nucleotide polymorphism (SNP) variation allows for the capture of haplotype structure in populations and prediction of unobserved genotypes based on inferred regions of identity-by-descent (IBD). Here we have used a first-generation wheat haplotype map created by targeted re-sequencing of low-copy genomic regions in the reference panel of 62 lines to impute marker genotypes in a diverse panel of winter wheat cultivars from the U.S. Great Plains. The IBD segments between the reference population and winter wheat cultivars were identified based on SNP genotyped using the 90K iSelect wheat array and genotyping by sequencing (GBS). A genome-wide association study and genomic prediction of resistance to stripe rust in winter wheat cultivars showed that an increase in marker density achieved by imputation improved both the power and precision of trait mapping and prediction. The majority of the most significant marker-trait associations belonged to imputed genotypes. With the vast amount of SNP variation data accumulated for wheat in recent years, the presented imputation framework will greatly improve prediction accuracy in breeding populations and increase resolution of trait mapping hence, facilitate cross-referencing of genotype datasets available across different wheat populations.

Indexed as

BasidiomycotaChromosome MappingCold TemperatureDisease ResistanceGenome, PlantGenome-Wide Association StudyGenomicsGenotypeHaplotypesPhenotypePlant BreedingPlant DiseasesPolymorphism, Single NucleotideQuantitative Trait LociSeasonsTriticumGenomic PredictionGenPredGWASImputationShared Data ResourcesSNPWheat HapMap

Identifiers

PMID30420469
PMCPMC6325902

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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.