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Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo

机译:基于定量扰动的基因表达分析预测果蝇早期胚胎中的增强子活性

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摘要

Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale.>DOI:
机译:增强子构成后生动物调控机制的主要组成部分之一。尽管几项全基因组研究集中在基因组中寻找和定位增强子,但控制其内部结构和顺式调控语法的基本原理仍然难以捉摸。在这里,我们描述了针对果蝇NF-κB同源物Dorsal控制的背腹模式基因调控网络(GRN)的广泛,定量的扰动分析。为了了解转录因子在增强子上的相互作用,我们采用了数学模型的集成,测试了协同作用,抑制和因子效能的影响。在数据集上训练的模型可以正确预测进化上不同的调控区域的活动,从而提供对阻抑物和激活物结合位点之间空间关系的见解。重要的是,模型集的集体预测在新型增强子识别和表征方面是有效的。我们的研究表明,如何有效地结合实验数据集和模型,以提供对全基因组范围内顺式调节信息的定量见解。> DOI:

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