ArticleBiology2024
Genome-Wide Association Study and Genomic Prediction of Soft Wheat End-Use Quality Traits Under Post-Anthesis Heat-Stressed Conditions.
Article in Biology, 2024. 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.
- Evaluating reaction norm and fixed effect models for genomic selection of end-use quality in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Harnessing genomics approaches for heat stress resilience in wheat: from discovery to deployment.Journal of experimental botany · 2026Review
- Mining QTLs and candidate genes in bread wheat associated with kernel hardness through GWAS.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Uncovering the Genetic Basis of Grain Protein Content and Wet Gluten Content in Common Wheat (Plants (Basel, Switzerland) · 2026Article
- Uncover the genetic basis of processing quality related traits in common wheat (Frontiers in plant science · 2026Article
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Authors and funding
9 authors.
Funding
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Abstract
Wheat end-use quality is an important component of a wheat breeding program. Heat stress during grain filling impacts wheat quality traits, making it crucial to understand the genetic basis of wheat quality traits under post-anthesis heat stress. This study aimed to identify the genomic regions associated with wheat quality traits using genome-wide association studies (GWASs) and evaluate the prediction accuracy of different genomic selection (GS) models. A panel of 236 soft red facultative wheat genotypes was evaluated for end-use quality traits across four heat-stressed environments over three years. Significant phenotypic variation was observed across environments for traits such as grain yield (GY), grain protein (GP), grain hardness (GH), and flour yield (AFY). Heritability estimates ranged from 0.52 (GY) to 0.91 (GH). The GWASs revealed 136 significant marker-trait associations (MTAs) across all 21 chromosomes, with several MTAs located within candidate genes involved in stress responses and quality traits. Genomic selection models showed prediction accuracy values up to 0.60, with within-environment prediction outperforming across-environment prediction. These results suggest that integrating GWAS and GS approaches can enhance the selection of wheat quality traits under heat stress, contributing to the development of heat-tolerant varieties.
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