机器人化室内表型化允许基因组预测在现场适应性特征
Jugurta Bouidghaghen1,2, Laurence Moreau3, Katia Beauchêne4
1LEPSE, Univ Montpellier, INRAE, Montpellier, France.
Nature communications
|October 19, 2023
概括
机器人室内表型化可以预测玉米在不同的田间条件下的适应性特征. 这种方法有助于通过在基因型中识别用水策略来培育气候变化弹性.
科学领域:
- 植物育种和遗传学
- 适应气候变化 适应气候变化
- 农业技术 农业技术
背景情况:
- 气候变化需要培育作物性超出产量,专注于适应性特征,如植物结构和口腔导电性.
- 高通量机器人化室内表型化提供了快速繁殖能力,但其现场相关性经常受到质疑.
研究的目的:
- 为了证明玉米的适应性特征可以在各种野外环境中使用室内表型化数据准确地推断.
- 建立一个模型,将室内表型化结果转化为现场条件和不同现场环境之间.
- 评估基因组预测对基于未来气候情景适应性特征的基因型排名的有效性.
主要方法:
- 利用了从机器人化室内表型化中获得的基因型值.
- 嵌入了每个领域特定的环境条件.
- 开发了一种建模方法,将室内数据转换为现场条件,反之亦然.
- 应用基因组预测来对适应性特征的基因型进行排名.
主要成果:
- 在室内测量的玉米适应性特征在不同的田间条件下成功推断出来.
- 环境建模使特征数据在室内和现场设置之间以及跨领域的准确翻译成为可能.
- 适应性特征的基因型值显示室内和现场测量之间的一致性.
- 基因组预测提供了足够的基因型排名,尽管精度因表型变异性而异.
结论:
- 机器人化室内表型是评估玉米适应性特征的相关工具,以评估其现场表现.
- 开发的建模方法可方便对跨环境的特征性能进行准确预测.
- 这种方法有助于识别具有独特用水策略的基因型 (花费者与保守者) 以适应气候的育种.
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