在基于反应规范模型的多环境试验中,对玉米谷物产量进行基因组预测和关联映射
Seth A Tolley1, Luiz F Brito2, Diane R Wang1
1Department of Agronomy, Purdue University, West Lafayette, IN, United States.
Frontiers in genetics
|September 18, 2023
概括
在玉米产量方面,基因型与环境相互作用 (GEI) 是一个主要的挑战. 这项研究通过将GEI纳入预测模型进行了改进,提高了跨多种环境中混合性能的基因组预测准确性.
科学领域:
- 植物育种 植物育种
- 遗传学 是一个遗传学.
- 农业科学 农业科学
背景情况:
- 基因型与环境相互作用 (GEI) 通过限制基因型性能预测和与产量相关的基因组区域的识别,显著复杂化了玉米的育种.
- 了解并将GEI纳入预测模型对于提高玉米谷物产量和育种效率至关重要.
研究的目的:
- 通过反应规范模型评估玉米谷物产量的GEI,并预测跨环境梯度的混合性能.
- 进行全基因组关联研究 (GWAS) 和玉米谷物产量的GWAS后分析.
主要方法:
- 从基因组到田间计划中利用了来自86个环境 (位置-年组合) 的2,126个杂交的数据.
- 应用反应规范模型用于GEI评估和基因组预测,与GWAS一起用于产量相关的SNP.
- 分析了跨环境的遗传性,确定了与应激反应相关的显著SNP附近的候选基因.
主要成果:
- 在高产率环境中,由于基因变异性增加,遗传能力更高.
- 与没有GEI的模型相比,采用GEI的基因组预测模型显著提高了预测准确性 (CV0-Predicted EG高达0.80).
- 确定了与玉米谷物产量和应激反应相关的基因组区域和候选基因.
结论:
- GEI显著影响玉米谷物产量,其纳入预测模型可以提高准确性.
- 该研究提供了一种方法,通过基因组预测来提高多环境试验中的混合评估效率.
- 确定的基因组区域为未来的选择提供了目标,以提高玉米产量潜力.
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