Department of Electrical and Computer Engineering, Texas A&M University, 188 Bizzell St, College Station, 77843, United States.
BMC Plant Biol. 2019 Mar 12;19(1):96. doi: 10.1186/s12870-019-1684-3.
Plants are sessile organisms and are unable to relocate to favorable locations under extreme environmental conditions. Hence they have no choice but to acclimate and eventually adapt to the severe conditions to ensure their survival. As traditional methods of bolstering plant defense against stressful conditions come to their biological limit, we require newer methods that can allow us to strengthen plants' internal defense mechanism. These factors motivated us to look into the genetic networks of plants. The WRKY transcription factors are well known for their role in plant defense against biotic stresses, but recent studies have shed light on their activities against abiotic stresses such as drought. We modeled this network of WRKY transcription factors using Bayesian networks and applied inference algorithm to find the best regulators of drought response. Biologically intervening (activating/inhibiting) these regulators can bolster the defense response of plants against droughts.
We used real world data from the NCBI GEO database and synthetic data generated from dependencies in the Bayesian network to learn the network parameters. These parameters were estimated using both a Bayesian and a frequentist approach. The two sets of parameters were used in a utility-based inference algorithm to determine the best regulator of plant drought response in the WRKY transcription factor network.
Our analysis revealed that activating the transcription factor WRKY18 had the highest likelihood of inducing drought response among all the other elements of the WRKY transcription factor network. Our observation was also supported by biological literature, as WRKY18 is known to regulate drought responsive genes positively. We also found that activating the protein complex WRKY60-60 had the second highest likelihood of inducing drought defense response. Consistent with the existing biological literature, we also found the transcription factor WRKY40 and the protein complex WRKY40-40 to suppress drought response.
植物是固着生物，在极端环境条件下无法迁移到有利位置。因此，它们别无选择，只能适应并最终适应恶劣条件，以确保自身的生存。由于增强植物对胁迫条件的防御的传统方法已经达到其生物学极限，我们需要新的方法来加强植物的内部防御机制。这些因素促使我们研究植物的遗传网络。WRKY 转录因子在植物抵御生物胁迫方面的作用是众所周知的，但最近的研究表明，它们在应对非生物胁迫（如干旱）方面也具有活性。我们使用贝叶斯网络对 WRKY 转录因子网络进行建模，并应用推理算法来寻找干旱响应的最佳调节剂。生物干预（激活/抑制）这些调节剂可以增强植物对干旱的防御反应。
我们使用来自 NCBI GEO 数据库的真实世界数据和贝叶斯网络中的依赖关系生成的合成数据来学习网络参数。这些参数是使用贝叶斯和频率主义方法估计的。两组参数都用于基于效用的推理算法中，以确定 WRKY 转录因子网络中植物干旱响应的最佳调节剂。
我们的分析表明，激活转录因子 WRKY18 在 WRKY 转录因子网络的所有其他元素中诱导干旱响应的可能性最高。我们的观察结果也得到了生物学文献的支持，因为 WRKY18 已知可正向调节干旱响应基因。我们还发现激活蛋白复合物 WRKY60-60 诱导干旱防御反应的可能性第二高。与现有的生物学文献一致，我们还发现转录因子 WRKY40 和蛋白复合物 WRKY40-40 抑制干旱反应。
