ArticleThe plant genome2025
Genomic prediction models for morpho-phenological traits in durum wheat based on Vrn, Ppd, and Rht alleles.
Article in The plant genome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Temporal GWAS and QTL mapping of UAV-derived digital canopy height reveals stage-specific genetic effects in bread wheat.Plant phenomics (Washington, D.C.) · 2026Article
- Do modern winter wheat cultivars outperform traditional landraces under cold stress? A large-scale agro-morphological evaluation.BMC plant biology · 2026Article
- Multimodal deep learning improves cross-environment prediction of durum wheat yield components.BMC plant biology · 2026Article
- Multi-trait and multi-environment genomic prediction enhances yield components improvement in durum wheat.Frontiers in plant science · 2026Article
- Genomic prediction models for morpho-phenological traits in durum wheat based on Vrn, Ppd, and Rht alleles.The plant genome · 2025Article
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8 authors.
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Abstract
Genetic variations in vernalization (Vrn), photoperiod (Ppd), and reduced plant height (Rht) genes significantly influence durum wheat adaptability. However, the systematic integration of these functional alleles into genomic prediction (GP) models has been limited. This study identified genetic markers associated with heading date (HD), flowering time (FT), and plant height (PH) via genome-wide association study (GWAS) in 186 durum wheat [Triticum turgidum ssp. durum (Desf.) Husn.] genotypes, including landraces, old cultivars, and modern cultivars, grown in eight sowing × season environments. GWAS confirmed major loci at Rht-B1 (Q.PH.cer-4B), Ppd-A1 (Q.HD.cer-2A), Ppd-B1 (Q.FT.cer-2B.1), and Vrn-A1 (Q.HD.cer-5A), underpinning trait variation. Nineteen distinct allelic combinations (ACs) derived from Vrn-A1, Ppd-A1, Ppd-B1, and Rht-B1 showed strong selection for specific alleles (e.g., Vrn-A1c, Ppd-A1a, and Rht-B1b) in modern cultivars. GP models evaluated prediction accuracy (PA) by incorporating ACs, GWAS-derived markers (M), or both (AC-M) as fixed effects using 4399 SNPs under single (SE) and multi-environment (ME) scenarios. High prediction accuracies were achieved, notably in ME models (PA up to 0.93 for all analyzed traits). Incorporating functional ACs along with markers (AC-M) yielded consistent PA improvements. These results affirm the importance of Vrn, Ppd, and Rht genes and suggest that targeted integration of functional alleles can moderately enhance GP accuracy, potentially improving durum wheat breeding efficiency under varying environmental conditions.
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