Hashida Yoichi, Kyogoku Daisuke, Tanaka Suguru E, Mori Naoya, Tanabata Takanari, Watanabe Hiroyuki, Nagano Atsushi J
Faculty of Agriculture, Takasaki University of Health and Welfare, Takasaki, Gunma, Japan.
Museum of Nature and Human Activities, Sanda, Hyogo, Japan.
Genome Biol. 2025 Jul 28;26(1):225. doi: 10.1186/s13059-025-03690-8.
Plants in the field respond to seasonal and diel changes in various environmental factors such as irradiance and temperature. We previously developed a statistical model that predicts rice gene expression from the meteorological data and identified the environmental factors regulating each gene. However, since irradiance and temperature-the two most critical environmental factors-are correlated in the field, it remains difficult to distinguish their roles in gene expression regulation.
We show that transcriptome dynamics in the field are predominantly regulated by irradiance, by the modeling involving diel transcriptome data from the 73 controlled conditions where irradiance and temperature are independently varied. The model's prediction performance is substantially high when trained using field and controlled conditions data.
Our results highlight the utility of a systematic sampling approach under controlled environments to understand the mechanism of plant environmental response and to improve transcriptome prediction under field environments.
田间植物会对光照和温度等各种环境因素的季节性和昼夜变化做出反应。我们之前开发了一种统计模型，可根据气象数据预测水稻基因表达，并确定了调控每个基因的环境因素。然而，由于光照和温度这两个最关键的环境因素在田间是相关的，因此仍然难以区分它们在基因表达调控中的作用。
我们通过对73种光照和温度独立变化的受控条件下的昼夜转录组数据进行建模，表明田间转录组动态主要受光照调控。当使用田间和受控条件数据进行训练时，该模型的预测性能相当高。
我们的结果突出了在受控环境下采用系统采样方法对于理解植物环境响应机制以及改善田间环境下转录组预测的实用性。
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