Khodadadi Ehsan, Mehrabi Ali Ashraf, Najafi Ali, Rastad Saber, Masoudi-Nejad Ali
Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Ilam, Ilam, Iran.
Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
Physiol Mol Biol Plants. 2017 Apr;23(2):331-342. doi: 10.1007/s12298-017-0416-0. Epub 2017 Feb 10.
Transcriptional and post-transcriptional regulators including transcription regulator, transcription factor and miRNA are the main endogenous molecular elements which control complex cellular mechanisms such as development, growth and response to biotic and abiotic stresses in a coordinated manner in plants. Utilizing the most recent information on such relationships in a plant species, obtained from high-throughput experimental technologies and advanced computational tools, we can reconstruct its co-regulatory network which consequently sheds light on key regulators involved in its important biological processes. In this article, combined systems biology approaches such as mining the literatures, various databases and network reconstruction, analysis, and visualization tools were employed to infer and visualize the coregulatory relationships between miRNAs and transcriptional regulators in . Using computationally and experimentally verified miRNA-target interactions and constructed co-expression networks on array-based data, 10 coregulatory networks and 10 corresponding subgraphs include FFL motifs were obtained for 10 distinct tissues/conditions. Then PPI subnetworks were extracted for transcripts/genes included in mentioned subgraphs in order to the functional analysis of extracted coregulatory circuits. These proposed coregulatory connections shed light on precisely identifying metabolic pathways key switches, which are demanded for ultimate goals such as genome editing.
转录和转录后调节因子,包括转录调节因子、转录因子和微小RNA(miRNA),是植物中以协调方式控制复杂细胞机制(如发育、生长以及对生物和非生物胁迫的响应)的主要内源性分子元件。利用从高通量实验技术和先进计算工具获得的关于某一植物物种中此类关系的最新信息,我们可以重建其共调控网络,从而揭示参与其重要生物学过程的关键调节因子。在本文中,采用了多种系统生物学方法,如挖掘文献、各种数据库以及网络重建、分析和可视化工具,来推断和可视化植物中miRNA与转录调节因子之间的共调控关系。利用经过计算和实验验证的miRNA-靶标相互作用,并基于阵列数据构建共表达网络,针对10种不同的组织/条件获得了10个共调控网络和10个包含前馈环(FFL)基序的相应子图。然后为上述子图中包含的转录本/基因提取蛋白质-蛋白质相互作用(PPI)子网,以便对提取的共调控回路进行功能分析。这些提出的共调控连接有助于精确识别代谢途径的关键开关,而这些开关是基因组编辑等最终目标所需要的。