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LIET模型:捕捉RNA聚合酶从装载到终止的动力学过程。

LIET model: capturing the kinetics of RNA polymerase from loading to termination.

作者信息

Stanley Jacob T, Barone Georgia E F, Townsend Hope A, Sigauke Rutendo F, Allen Mary A, Dowell Robin D

机构信息

BioFrontiers Institute, University of Colorado Boulder, Boulder, CO 80303, United States.

Molecular, Cellular and Developmental Biology, University of Colorado Boulder, Boulder, CO 80309, United States.

出版信息

Nucleic Acids Res. 2025 Apr 10;53(7). doi: 10.1093/nar/gkaf246.

Abstract

Transcription by RNA polymerases is an exquisitely regulated step of the central dogma. Transcription is the primary determinant of cell-state, and most cellular perturbations impact transcription by altering polymerase activity. Thus, detecting changes in polymerase activity yields insight into most cellular processes. Nascent run-on sequencing provides a direct readout of polymerase activity, but no tools exist to model all aspects of this activity at genes. We focus on RNA polymerase II-responsible for transcribing protein-coding genes. We present the first model to capture the complete process of gene transcription. For individual genes, this model parameterizes each distinct stage of transcription-loading, initiation, elongation, and termination, hence LIET-in a biologically interpretable Bayesian mixture, which is applied to nascent run-on data. Our improved modeling of loading/initiation demonstrates these stages are characteristically different between sense and antisense strands. Applying LIET to 24 human cell-types, our analysis indicates the position of dissociation (the last step of termination) appears to be highly consistent, indicative of a tightly regulated process. Furthermore, by applying LIET to perturbation experiments, we demonstrate its ability to detect specific changes in pausing (5' end), strand-bias, and dissociation location (3' end)-opening the door to differential assessment of transcription at individual stages of individual genes.

摘要

RNA聚合酶的转录是中心法则中一个受到精确调控的步骤。转录是细胞状态的主要决定因素,大多数细胞扰动通过改变聚合酶活性来影响转录。因此,检测聚合酶活性的变化有助于深入了解大多数细胞过程。新生链延伸测序可直接读出聚合酶活性,但目前尚无工具能够对基因处这种活性的所有方面进行建模。我们聚焦于负责转录蛋白质编码基因的RNA聚合酶II。我们提出了首个能够捕捉基因转录完整过程的模型。对于单个基因,该模型在一个具有生物学可解释性的贝叶斯混合模型中对转录的每个不同阶段——装载、起始、延伸和终止进行参数化,即LIET,并将其应用于新生链延伸数据。我们对装载/起始过程的改进建模表明,有义链和反义链之间这些阶段存在显著差异。将LIET应用于24种人类细胞类型,我们的分析表明解离位置(终止的最后一步)似乎高度一致,这表明该过程受到严格调控。此外,通过将LIET应用于扰动实验,我们证明了它能够检测到暂停(5'端)、链偏向和解离位置(3'端)的特定变化——为在单个基因的各个阶段对转录进行差异评估打开了大门。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c7f/12086695/9f6092105f4f/gkaf246figgra1.jpg

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