Shahi Dipendra, Guo Jia, Pradhan Sumit, Avci Muhsin, Bai Guihua, Khan Jahangir, Baik Byung-Kee, Mergoum Mohamed, Babar Md Ali
School of Plant, Environmental and Soil Sciences, Louisiana State Agricultural Center, Baton Rouge, LA 70803, USA.
Inari Agriculture, 1281 Win Hentschel Blvd w1108, West Lafayette, IN 47906, USA.
Biology (Basel). 2024 Nov 22;13(12):962. doi: 10.3390/biology13120962.
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.
小麦的最终用途品质是小麦育种计划的一个重要组成部分。灌浆期的热胁迫会影响小麦品质性状，因此了解花后热胁迫下小麦品质性状的遗传基础至关重要。本研究旨在利用全基因组关联研究（GWAS）鉴定与小麦品质性状相关的基因组区域，并评估不同基因组选择（GS）模型的预测准确性。在三年中的四个热胁迫环境下，对一组236个软红兼性小麦基因型的最终用途品质性状进行了评估。在不同环境中，观察到产量（GY）、籽粒蛋白质（GP）、籽粒硬度（GH）和出粉率（AFY）等性状存在显著的表型变异。遗传力估计值范围从0.52（GY）到0.91（GH）。GWAS在所有21条染色体上共鉴定出136个显著的标记-性状关联（MTA），其中一些MTA位于参与胁迫响应和品质性状的候选基因内。基因组选择模型显示预测准确性值高达0.60，环境内预测优于跨环境预测。这些结果表明，整合GWAS和GS方法可以提高热胁迫下小麦品质性状的选择效率，有助于培育耐热品种。
