Evidence map›Paper›PMID 30615624›Full record

ArticlePloS one2019

Imputation accuracy of wheat genotyping-by-sequencing (GBS) data using barley and wheat genome references.

Hadi Alipour, Guihua Bai, Guorong Zhang, Mohammad Reza Bihamta, Valiollah Mohammadi, Seyed Ali Peyghambari

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Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

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29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

  1. Article
  2. A haplotype-layered GWAS identifies a multi-trait grain mold resistance hub on sorghum chromosome 5.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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  14. Wheat Omics: Advancements and Opportunities.Plants (Basel, Switzerland) · 2023
    Review
  15. Interspecific common bean population derived fromFrontiers in plant science · 2023
    Article
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hadi AlipourDepartment of Agronomy, Kansas State University, Manhattan, Kansas, United States of America.ORCID 0000-0003-0086-002X
Guihua BaiUSDA-ARS, Hard Winter Wheat Genetics Research Unit, Manhattan, Kansas, United States of America.
Guorong ZhangDepartment of Agronomy, Kansas State University, Manhattan, Kansas, United States of America.ORCID 0000-0003-1342-8578
Mohammad Reza BihamtaDepartment of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran.
Valiollah MohammadiDepartment of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran.
Seyed Ali PeyghambariDepartment of Agronomy and Plant Breeding, Faculty of Agriculture, University of Tehran, Karaj, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genotyping-by-sequencing (GBS) provides high SNP coverage and has recently emerged as a popular technology for genetic and breeding applications in bread wheat (Triticum aestivum L.) and many other plant species. Although GBS can discover millions of SNPs, a high rate of missing data is a major concern for many applications. Accurate imputation of those missing data can significantly improve the utility of GBS data. This study compared imputation accuracies among four genome references including three wheat references (Chinese Spring survey sequence, W7984, and IWGSC RefSeq v1.0) and one barley reference genome by comparing imputed data derived from low-depth sequencing to actual data from high-depth sequencing. After imputation, the average number of imputed data points was the highest in the B genome (~48.99%). The D genome had the lowest imputed data points (~15.02%) but the highest imputation accuracy. Among the four reference genomes, IWGSC RefSeq v1.0 reference provided the most imputed data points, but the lowest imputation accuracy for the SNPs with < 10% minor allele frequency (MAF). The W7984 reference, however, provided the highest imputation accuracy for the SNPs with < 10% MAF.

Indexed as

Genome, PlantChromosomes, PlantGene FrequencyGenotyping TechniquesHigh-Throughput Nucleotide SequencingHordeumPolymorphism, Single NucleotideReference StandardsTriticum

Identifiers

PMID30615624
PMCPMC6322752

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