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Nat Commun. 2017 Aug 28;8(1):368. doi: 10.1038/s41467-017-00239-7.
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CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping.CrY2H-seq:一种用于深度覆盖相互作用组图谱绘制的大规模多重检测方法。
Nat Methods. 2017 Aug;14(8):819-825. doi: 10.1038/nmeth.4343. Epub 2017 Jun 26.
3
Reducing DNA context dependence in bacterial promoters.降低细菌启动子中DNA上下文依赖性
PLoS One. 2017 Apr 19;12(4):e0176013. doi: 10.1371/journal.pone.0176013. eCollection 2017.
4
Mechanism of transcription initiation and promoter escape by . RNA polymerase.. RNA 聚合酶转录起始和启动子逃避的机制。
Proc Natl Acad Sci U S A. 2017 Apr 11;114(15):E3032-E3040. doi: 10.1073/pnas.1618675114. Epub 2017 Mar 27.
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Open complex DNA scrunching: A key to transcription start site selection and promoter escape.开放复合物DNA挤压:转录起始位点选择和启动子逃逸的关键。
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Copy number variability of expression plasmids determined by cell sorting and Droplet Digital PCR.通过细胞分选和微滴数字PCR测定表达质粒的拷贝数变异
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Local and global regulation of transcription initiation in bacteria.细菌中转录起始的局部和全局调控。
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8
Hard-Wired Control of Bacterial Processes by Chromosomal Gene Location.染色体基因定位对细菌过程的硬连线控制
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Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay.使用多重报告基因检测直接鉴定数百个表达调控变异体
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10
Interactions between RNA polymerase and the core recognition element are a determinant of transcription start site selection.RNA聚合酶与核心识别元件之间的相互作用是转录起始位点选择的一个决定因素。
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利用基于基因组编码的多重报告基因检测在大肠杆菌中系统性剖析控制 σ70 启动子的序列元件。

Systematic Dissection of Sequence Elements Controlling σ70 Promoters Using a Genomically Encoded Multiplexed Reporter Assay in Escherichia coli.

机构信息

Molecular Biology Interdepartmental Doctoral Program , University of California , Los Angeles , California 90095 , United States.

Department of Molecular, Cell, and Developmental Biology , University of California , Los Angeles , California 90095 , United States.

出版信息

Biochemistry. 2019 Mar 19;58(11):1539-1551. doi: 10.1021/acs.biochem.7b01069. Epub 2018 Dec 21.

DOI:10.1021/acs.biochem.7b01069
PMID:29388765
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6389444/
Abstract

Promoters are the key drivers of gene expression and are largely responsible for the regulation of cellular responses to time and environment. In Escherichia coli, decades of studies have revealed most, if not all, of the sequence elements necessary to encode promoter function. Despite our knowledge of these motifs, it is still not possible to predict the strength and regulation of a promoter from primary sequence alone. Here we develop a novel multiplexed assay to study promoter function in E. coli by building a site-specific genomic recombination-mediated cassette exchange system that allows for the facile construction and testing of large libraries of genetic designs integrated into precise genomic locations. We build and test a library of 10898 σ70 promoter variants consisting of all combinations of a set of eight -35 elements, eight -10 elements, three UP elements, eight spacers, and eight backgrounds. We find that the -35 and -10 sequence elements can explain approximately 74% of the variance in promoter strength within our data set using a simple log-linear statistical model. Simple neural network models explain >95% of the variance in our data set by capturing nonlinear interactions with the spacer, background, and UP elements.

摘要

启动子是基因表达的关键驱动因素,在很大程度上负责调节细胞对时间和环境的反应。在大肠杆菌中,经过几十年的研究,已经揭示了编码启动子功能所需的大多数(如果不是全部)序列元件。尽管我们了解了这些基序,但仍然不可能仅从原始序列预测启动子的强度和调控。在这里,我们通过构建一种基于基因组特异性重组介导盒交换系统的新型多重测定法来研究大肠杆菌中的启动子功能,该系统允许轻松构建和测试精确基因组位置处集成的大量遗传设计文库。我们构建并测试了一个由 10898 个 σ70 启动子变体组成的文库,这些变体由一组八个 -35 元件、八个 -10 元件、三个 UP 元件、八个间隔子和八个背景组成。我们发现,使用简单的对数线性统计模型,-35 和 -10 序列元件可以解释我们数据集内大约 74%的启动子强度变化。简单的神经网络模型通过捕捉与间隔子、背景和 UP 元件的非线性相互作用,解释了我们数据集内 >95%的方差。