ArticleBMC genomics2026
Integration and imputation of GBS-derived and DArTseq-derived SNP markers in assessing genetic diversity of bread wheat genotypes.
Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- QTL rich genomic clusters in wheat: a catalogue for resistance toFrontiers in plant science · 2026Review
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6 authors.
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Abstract
backgroundWheat (Triticum aestivum L.) is a globally paramount crop. Iranian landraces serve as a vital resource for enriching wheat gene banks worldwide, and deciphering the diversity in its genotypes is crucial for breeders. Genotyping-by-Sequencing (GBS) and Diversity Array Technology (DArT) are two important platforms for generating single nucleotide polymorphisms (SNP) markers. The integration of molecular marker data from different genotyping platforms is crucial for a comprehensive analysis of genetic variation in wheat germplasm. The aim of this study was to integrate and impute SNP markers derived from GBS and DArTseq platforms, and to employ the dataset for assessing the genetic diversity of Iranian bread wheat genotypes and for detecting selection signatures.
resultsThis study integrated molecular marker data from two genotyping platforms (GBS and DArTseq) through imputation to enable a unified analysis of genetic diversity in bread wheat germplasm. We first imputed missing data for 357 Iranian bread wheat accessions genotyped via GBS. This process more than tripled the number of usable SNP markers obtained through GBS. Subsequently, we imputed markers for the remaining genotypes using a reference set of 90 accessions genotyped with DArTseq technology. These sequential imputation steps yielded a consolidated dataset of 46,876 high-quality GBS-derived SNP and 3,417 high-quality DArTseq-derived SNP markers. The results obtained from the two marker systems demonstrated a high degree of complementarity, effectively distinguishing cultivars from landraces. Furthermore, cluster analysis delineated the genotypes into three distinct groups. Furthermore, these markers were used to identify signatures of natural and artificial selection by detecting high Fst values. Our results showed that the genomic regions under selection, identified by SNPs contain genes involved in regulatory processes related to DNA transcription, cell wall organization, protein phosphorylation, and defense response to biotic stresses. These pathways are particularly significant in the differentiation of populations in response to environmental pressures. In contrast, genes associated with DArTseq-derived SNP markers were mainly involved in more general pathways such as transcription regulation and cell structure processes, which may indicate the lower sensitivity of this system in detecting directional selection. Nevertheless, the identification of distinct selection signatures by DArTseq-derived SNP markers underscores their complementary role in genomic studies.
conclusionsThe presented framework enables effective integration of multi-platform marker data, enhancing genetic diversity assessment and revealing new selection signatures in wheat. The resulting imputed dataset forms a foundational resource for subsequent genome-wide association and genomic selection studies.
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