Delineation of Nitrogen Signaling Networks: Computational Approaches in the Big Data Era
Delineation of Nitrogen Signaling Networks: Computational Approaches in the Big Data Era
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氮信号网络的描绘：大数据时代的计算方法
DOI：
10.1016/j.molp.2019.01.008
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发表时间：
2019
期刊：
影响因子：
27.5
通讯作者：
Yanagisawa Shuichi
中科院分区：
文献类型：
--
作者：
Ueda Yoshiaki;Yanagisawa Shuichi
植物从根际吸收氮素，这是一种必需的大量营养素，因此土壤氮素状况是植物生长和生产力的重要决定因素。植物已经进化出多种机制来诱导氮代谢的调节和广泛的生理过程，以响应氮源供应的变化和含氮化合物内部丰度的变化。这些反应统称为氮反应。先前的研究揭示，NIN样蛋白（NLP）家族转录因子处于由硝酸根离子触发的转录级联的起始（Liu et al.，2017），大多数高等植物物种的主要氮源和氮反应的关键调节剂。然而，在理解全面的氮信号网络方面仍存在很大的差距，通过该网络，输入信号（氮源供应）通过大量基因的调节诱导氮响应。最近的两项研究使用大规模数据集和计算分析来检查这个网络。
Plants absorb nitrogen, an essential macronutrient, from the rhizosphere, and soil nitrogen status is thus an important determinant of plant growth and productivity. Plants have evolved numerous mechanisms to induce modulations of nitrogen metabolism and a wide range of physiological processes in response to changes in nitrogen source supply and variation in the internal abundance of nitrogen-containing compounds. which are collectively referred to as nitrogen responses. Previous investigations revealed that NIN-like protein (NLP) family transcription factors are at the start of transcriptional cascades triggered by nitrate ions (Liu et al., 2017), the major nitrogen source for most higher plant species and a key modulator of nitrogen responses. However, there are still large gaps in understanding the comprehensive nitrogen signaling network, through which input signals (nitrogen source supply) induce nitrogen responses via modulations in large numbers of genes. Two recent studies used largescale datasets and computational analyses to examine this network.