全基因组关联和预测大麦的表型稳定性
Jeffrey L Neyhart1, Lucia Gutierrez2, Kevin P Smith3
1USDA-ARS Genetic Improvement for Fruits and Vegetables Laboratory, Chatsworth, New Jersey, USA.
The plant genome
|September 27, 2025
概括
了解大麦 (Hordeum vulgare L.) 的遗传可塑性是开发适应气候变化的作物的关键. 基因组预测可以识别稳定的作物品种,减少对广泛的多环境试验的需求.
科学领域:
- 植物遗传学和育种.
- 适应气候变化 适应气候变化
- 农业科学 农业科学
背景情况:
- 气候变化增加了极端的非生物压力,威胁到农作物生产.
- 现型稳定性 (与可塑性相反) 对于作物品种在压力下发展至关重要.
- 了解可塑性的遗传基础有助于选择稳定的作物品种.
研究的目的:
- 确定与大麦特征的平均性能和线性可塑性相关的基因组区域.
- 确定基因组预测可塑性的准确性.
- 评估环境采样对塑性估计和预测的影响.
主要方法:
- 在42个环境中计算了233个大麦线的特征平均值和线性可塑性 (斜率).
- 利用标记-特征关联分析来识别基因组区域.
- 用于对未观察到的种群进行交叉验证和预测,以评估基因组预测的准确性.
主要成果:
- 确定了87个标记-特征关联;许多可塑性的显著SNP与平均性能的SNP重叠.
- 塑性基因组预测的准确性中等 (rMP = 0.260.69).
- 增加环境采样改善了可塑性估计和预测准确性,但适度数量的环境足够了.
结论:
- 表明特征可塑性和平均性能之间有共同的遗传控制.
- 基因组预测可以有效地用于在作物育种中选择可塑性.
- 减少了对资源密集型多环境试验的需求,以培育稳定的作物品种.
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