植物基因网络的跨调控格局。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2023-06-21 DOI:10.1016/j.cels.2023.05.002
Niklas F C Hummel, Andy Zhou, Baohua Li, Kasey Markel, Izaiah J Ornelas, Patrick M Shih
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引用次数: 0

摘要

转录因子的转录效应结构域在控制基因表达方面起着关键作用;然而,人们对它们的功能性质知之甚少,这阻碍了我们探索基因调控网络这一基本层面的能力。为了绘制复杂真核生物的转录调控图谱,我们系统地鉴定了拟南芥 400 多个转录因子的推测转录效应结构域,以确定它们的转录调控能力。我们证明,转录效应器活性可被整合到基因调控网络中,从而阐明基因表达模式背后的功能动态。我们进一步展示了我们表征的结构域如何增强基因组工程工作,并揭示了植物转录激活因子如何与远缘真核生物共享调控特征。我们的研究结果为在基因组尺度上系统描述转录因子的调控作用提供了一个框架,以便了解生物系统的转录线路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The trans-regulatory landscape of gene networks in plants.

The transcriptional effector domains of transcription factors play a key role in controlling gene expression; however, their functional nature is poorly understood, hampering our ability to explore this fundamental dimension of gene regulatory networks. To map the trans-regulatory landscape in a complex eukaryote, we systematically characterized the putative transcriptional effector domains of over 400 Arabidopsis thaliana transcription factors for their capacity to modulate transcription. We demonstrate that transcriptional effector activity can be integrated into gene regulatory networks capable of elucidating the functional dynamics underlying gene expression patterns. We further show how our characterized domains can enhance genome engineering efforts and reveal how plant transcriptional activators share regulatory features conserved across distantly related eukaryotes. Our results provide a framework to systematically characterize the regulatory role of transcription factors at a genome-scale in order to understand the transcriptional wiring of biological systems.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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