基因调控网络
生物
拟南芥
计算生物学
转录因子
基因表达调控
基因
染色质
功能(生物学)
基因表达
拟南芥
表型
遗传学
转录调控
突变体
作者
Inge De Clercq,Jan Van de Velde,Xiaopeng Luo,Li Liu,Véronique Storme,Michiel Van Bel,Robin Pottie,Dries Vaneechoutte,Frank Van Breusegem,Klaas Vandepoele
出处
期刊:Nature plants
[Springer Nature]
日期:2021-04-12
卷期号:7 (4): 500-513
被引量:55
标识
DOI:10.1038/s41477-021-00894-1
摘要
Gene regulation is a dynamic process in which transcription factors (TFs) play an important role in controlling spatiotemporal gene expression. To enhance our global understanding of regulatory interactions in Arabidopsis thaliana, different regulatory input networks capturing complementary information about DNA motifs, open chromatin, TF-binding and expression-based regulatory interactions were combined using a supervised learning approach, resulting in an integrated gene regulatory network (iGRN) covering 1,491 TFs and 31,393 target genes (1.7 million interactions). This iGRN outperforms the different input networks to predict known regulatory interactions and has a similar performance to recover functional interactions compared to state-of-the-art experimental methods. The iGRN correctly inferred known functions for 681 TFs and predicted new gene functions for hundreds of unknown TFs. For regulators predicted to be involved in reactive oxygen species (ROS) stress regulation, we confirmed in total 75% of TFs with a function in ROS and/or physiological stress responses. This includes 13 ROS regulators, previously not connected to any ROS or stress function, that were experimentally validated in our ROS-specific phenotypic assays of loss- or gain-of-function lines. In conclusion, the presented iGRN offers a high-quality starting point to enhance our understanding of gene regulation in plants by integrating different experimental data types.
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