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转录-复制相互作用揭示了细菌基因组调控的原理。

Transcription-replication interactions reveal principles of bacterial genome regulation.

作者信息

Pountain Andrew W, Jiang Peien, Yao Tianyou, Homaee Ehsan, Guan Yichao, Podkowik Magdalena, Shopsin Bo, Torres Victor J, Golding Ido, Yanai Itai

机构信息

Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY USA.

Department of Biology, New York University, New York, NY, USA.

出版信息

Res Sq. 2023 Mar 31:rs.3.rs-2724389. doi: 10.21203/rs.3.rs-2724389/v1.

Abstract

Organisms determine the transcription rates of thousands of genes through a few modes of regulation that recur across the genome. These modes interact with a changing cellular environment to yield highly dynamic expression patterns. In bacteria, the relationship between a gene's regulatory architecture and its expression is well understood for individual model gene circuits. However, a broader perspective of these dynamics at the genome-scale is lacking, in part because bacterial transcriptomics have hitherto captured only a static snapshot of expression averaged across millions of cells. As a result, the full diversity of gene expression dynamics and their relation to regulatory architecture remains unknown. Here we present a novel genome-wide classification of regulatory modes based on each gene's transcriptional response to its own replication, which we term the Transcription-Replication Interaction Profile (TRIP). We found that the response to the universal perturbation of chromosomal replication integrates biological regulatory factors with biophysical molecular events on the chromosome to reveal a gene's local regulatory context. While the TRIPs of many genes conform to a gene dosage-dependent pattern, others diverge in distinct ways, including altered timing or amplitude of expression, and this is shaped by factors such as intra-operon position, repression state, or presence on mobile genetic elements. Our transcriptome analysis also simultaneously captures global properties, such as the rates of replication and transcription, as well as the nestedness of replication patterns. This work challenges previous notions of the drivers of expression heterogeneity within a population of cells, and unearths a previously unseen world of gene transcription dynamics.

摘要

生物体通过少数几种在全基因组中反复出现的调控模式来决定数千个基因的转录速率。这些模式与不断变化的细胞环境相互作用,产生高度动态的表达模式。在细菌中,对于单个模型基因回路,基因的调控结构与其表达之间的关系已得到充分理解。然而,目前缺乏对基因组尺度上这些动态变化的更广泛视角,部分原因是细菌转录组学迄今仅捕获了数百万个细胞平均表达水平的静态快照。因此,基因表达动态变化的全部多样性及其与调控结构的关系仍然未知。在此,我们基于每个基因对自身复制的转录反应,提出了一种全新的全基因组调控模式分类方法,我们将其称为转录 - 复制相互作用图谱(TRIP)。我们发现,对染色体复制这一普遍扰动的反应,将生物调控因子与染色体上的生物物理分子事件整合在一起,从而揭示基因的局部调控环境。虽然许多基因的TRIP符合基因剂量依赖性模式,但其他基因则以不同方式出现偏差,包括表达时间或幅度的改变,这是由操纵子内位置、抑制状态或移动遗传元件的存在等因素所塑造的。我们的转录组分析还同时捕获了全局特性,如复制和转录速率,以及复制模式的嵌套性。这项工作挑战了之前关于细胞群体内表达异质性驱动因素的观念,并揭示了一个此前未被发现的基因转录动态变化的世界。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b56f/10081379/42fe205164da/nihpp-rs2724389v1-f0001.jpg

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