A new tool for discovering transcriptional regulators of co-expressed genes predicts gene regulatory networks that mediate ethylene-controlled root development

IF 2.4 Q1 AGRONOMY in silico Plants Pub Date : 2020-01-01 DOI:10.1093/insilicoplants/diaa006
Alexandria F. Harkey, Kira N Sims, G. Muday
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引用次数: 3

Abstract

Gene regulatory networks (GRNs) are defined by a cascade of transcriptional events by which signals, such as hormones or environmental cues, change development. To understand these networks, it is necessary to link specific transcription factors (TFs) to the downstream gene targets whose expression they regulate. Although multiple methods provide information on the targets of a single TF, moving from groups of co-expressed genes to the TF that controls them is more difficult. To facilitate this bottom-up approach, we have developed a web application named TF DEACoN. This application uses a publicly available Arabidopsis thaliana DNA Affinity Purification (DAP-Seq) data set to search for TFs that show enriched binding to groups of co-regulated genes. We used TF DEACoN to examine groups of transcripts regulated by treatment with the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC), using a transcriptional data set performed with high temporal resolution. We demonstrate the utility of this application when co-regulated genes are divided by timing of response or cell-type-specific information, which provides more information on TF/target relationships than when less defined and larger groups of co-regulated genes are used. This approach predicted TFs that may participate in ethylene-modulated root development including the TF NAM (NO APICAL MERISTEM). We used a genetic approach to show that a mutation in NAM reduces the negative regulation of lateral root development by ACC. The combination of filtering and TF DEACoN used here can be applied to any group of co-regulated genes to predict GRNs that control coordinated transcriptional responses.
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一种发现共表达基因转录调控因子的新工具预测了介导乙烯控制的根系发育的基因调控网络
基因调控网络(GRNs)是由一系列转录事件定义的,通过这些事件,激素或环境线索等信号会改变发育。为了理解这些网络,有必要将特定的转录因子(TF)与它们调节表达的下游基因靶点联系起来。尽管多种方法提供了关于单个TF靶点的信息,但从共表达基因组转移到控制它们的TF更为困难。为了促进这种自下而上的方法,我们开发了一个名为TFDEACON的web应用程序。该应用程序使用公开可用的拟南芥DNA亲和纯化(DAP-Seq)数据集来搜索显示与共调节基因组富集结合的转录因子。我们使用TF DEACoN来检测由乙烯前体1-氨基环丙烷-1-羧酸(ACC)处理调节的转录物组,使用高时间分辨率的转录数据集。当共调节基因按反应时间或细胞类型特异性信息划分时,我们证明了这种应用的实用性,这比使用定义较少和较大的共调节基因组时提供了更多关于TF/靶标关系的信息。该方法预测了可能参与乙烯调节根系发育的TF,包括TF NAM(无APICAL MERISTEM)。我们使用遗传学方法表明,NAM的突变减少了ACC对侧根发育的负调控。这里使用的过滤和TF DEACoN的组合可以应用于任何一组共调控基因,以预测控制协调转录反应的GRN。
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来源期刊
in silico Plants
in silico Plants Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
4.70
自引率
9.70%
发文量
21
审稿时长
10 weeks
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