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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Genotyping Data of 251 Wheat Samples for Population Structure and GWAS Analysis

SNP Genotyping Data of 251 Wheat Samples
Authors: Wang, Shichen; Akhunov, Eduard; Hayden, Matthew;

Genotyping Data of 251 Wheat Samples for Population Structure and GWAS Analysis

Abstract

Title: Genotyping Data of 251 Wheat Samples for Population Structure and GWAS Analysis Description: This dataset encompasses genotyping results for a collection of 251 wheat samples. The genotyping was conducted using the Illumina iSelect 90K SNP array at Trait Genetics, Gatersleben (Germany), using Illumina Inc., San Diego, USA. The SNP dataset underwent rigorous quality filtering. Markers with a minor allele frequency (MAF) below 5% and those with more than 10% missing data were excluded. Following this filtering process, a total of 17,093 high-quality SNP markers were retained for the subsequent GWAS analysis. These data enable research focused on understanding the genetic basis of traits in wheat, investigating population structure within this collection, and identifying genomic regions associated with important agronomic characteristics. Crucially, this high-density genotypic data has served as a valuable resource across multiple research projects, enabling diverse investigations into wheat genetics under various stress conditions (e.g., drought, heat, salinity) and across different field environments. It facilitates a deeper understanding of the genetic basis for traits relevant to crop improvement and adaptation. )This dataset supports the manuscript 'Genome-Wide Association Study Reveals Key SNP Markers for Agro-Physiological Traits in Bread Wheat (Triticum aestivum L.)', currently under peer-review. It's uploaded at the editor's request. Upon publication, the article's DOI will be added to this record for traceability( Keywords: Wheat, Genotyping, SNP, GWAS, Illumina iSelect, Trait Genetics, Data Quality, Data Filtering, Genetic Analysis, Agronomic Traits

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average