在小麦中纳入基因表达和基因预测的环境
Jia Liu1,2, Andrew Gock3, Kerrie Ramm1
1Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Canberra, ACT, Australia.
Frontiers in plant science
|May 21, 2025
概括
整合转录组数据增强小麦育种中的基因组选择 (GS),提高了对花期和高度等特征的预测准确度. 将环境共变量与基因组数据相结合,为育种者提供了一个切实可行的替代方案.
科学领域:
- 植物育种 植物育种
- 基因组学就是基因组学.
- 分子生物学分子生物学
背景情况:
- 基因组选择 (GS) 对于作物育种中的遗传收益至关重要.
- 需要新的分子策略来提高GS效率.
- 小麦育种研究的重点是增强GS方法.
研究的目的:
- 探索转录组数据在增强小麦GS中的作用.
- 评估整合多原子数据的预测性能.
- 为了比较不同的建模方法用于遗传优点预测.
主要方法:
- 综合表型和多原子数据 (SNP,转录组) 来自286个小麦系.
- 使用线性 (GBLUP) 和非线性 (RKHS) 回归模型.
- 评估基因组,转录基因组和环境数据的贡献,包括环境相互作用的基因型.
主要成果:
- 转录组数据在受控环境中显示出预测优势.
- 综合SNP,环境和基因型按环境 (GxE) 模型表现良好.
- 在现场条件下,将所有变量结合在一起的模型优越,但转录组贡献下降.
结论:
- 转录组数据的直接包含在小麦育种中为GxE影响的特征提供了预测优势.
- 复杂性和成本限制了用于商业繁殖的转录组数据的当前可行性.
- 将环境共变量与基因组数据相结合,提供了一个实用,有效的替代方案.
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