在澳大利亚东南部使用基因组预测,考虑基因型与环境相互作用,估计瑞草 (Lolium) 干物质产量
Jiashuai Zhu1,2, Khageswor Giri2, Zibei Lin2
1Faculty of Science, The University of Melbourne, Parkville, VIC, Australia.
Frontiers in plant science
|June 24, 2025
概括
基因组预测与环境相互作用的基因型提高了多年生麦草产量预测准确率24.9%. 这提高了澳大利亚乳制品行业和未来育种计划的品种选择.
科学领域:
- 植物育种 植物育种
- 定量遗传学 是一种定量遗传学.
- 农业科学 农业科学
背景情况:
- 基因组预测 (GP) 对于提高作物和牧场产量至关重要.
- 了解基因型与环境 (G×E) 相互作用对于准确的育种和品种推至关重要.
- 多年生麦草 (Lolium perenne L.) 是澳大利亚的关键料作物,需要优化品种选择.
研究的目的:
- 实施和评估基因组预测,将G×E相互作用纳入澳大利亚东南部多年生麦草的基因组预测.
- 评估72种多年生麦草品种的环境特异性表现和遗传潜力.
- 将G×E增强的GP的预测准确度与行业标准模型进行比较.
主要方法:
- 在最好的线性无偏预测 (BLUP) 框架内利用了多种收获,多地点试验数据和基因组数据.
- 应用空间分析以纠正现场异质性,并进行预测能力评估的Leave-One-Out交叉验证.
- 开发了一个G×E增强的GP模型,并将其与标准的最佳线性无偏估计 (BLUE) 模型进行比较.
主要成果:
- 在澳大利亚确定了两个不同的大型环境:大陆 (AUM) 和塔斯马尼亚 (TAS).
- 与BLUE模型 (CCC:0.434) 相比,G×E增强的GP模型在预测准确度上实现了24.9%的提高 (CCC:0.542).
- 基因组信息提高了预测12.7%,G×E建模增加了10.8%的进一步改进;遗传概率估计也得到了增强.
结论:
- 结合G×E相互作用的基因组预测显著提高了澳大利亚环境中多年生麦草的预测准确度.
- 这些发现为澳大利亚乳制品行业的知情品种选择提供了坚实的框架.
- 这种方法使基因组学为基础的父母选择成为可能,加速了未来的育种计划的进展.
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