Photosynthesis and Photobiology Research Unit, National Institute of Agrobiological Sciences, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan.
Cell. 2012 Dec 7;151(6):1358-69. doi: 10.1016/j.cell.2012.10.048.
Determining the drivers of gene expression patterns is more straightforward in laboratory conditions than in the complex fluctuating environments where organisms typically live. We gathered transcriptome data from the leaves of rice plants in a paddy field along with the corresponding meteorological data and used them to develop statistical models for the endogenous and external influences on gene expression. Our results indicate that the transcriptome dynamics are predominantly governed by endogenous diurnal rhythms, ambient temperature, plant age, and solar radiation. The data revealed diurnal gates for environmental stimuli to influence transcription and pointed to relative influences exerted by circadian and environmental factors on different metabolic genes. The model also generated predictions for the influence of changing temperatures on transcriptome dynamics. We anticipate that our models will help translate the knowledge amassed in laboratories to problems in agriculture and that our approach to deciphering the transcriptome fluctuations in complex environments will be applicable to other organisms.
在实验室条件下，确定基因表达模式的驱动因素比在生物体通常生活的复杂波动环境中更为直接。我们从水田中的水稻叶片中收集转录组数据，并结合相应的气象数据，用于开发内源性和外源性基因表达影响的统计模型。我们的结果表明，转录组动态主要受内源性昼夜节律、环境温度、植物年龄和太阳辐射的控制。数据显示，环境刺激影响转录的昼夜门控，并且表明昼夜节律和环境因素对不同代谢基因的相对影响。该模型还对温度变化对转录组动态的影响进行了预测。我们预计，我们的模型将有助于将实验室中积累的知识转化为农业问题，并且我们解析复杂环境中转录组波动的方法将适用于其他生物体。
