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用于果蝇整个胚胎中偶数跳动基因调控的细胞分辨率模型。

Cellular resolution models for even skipped regulation in the entire Drosophila embryo.

作者信息

Ilsley Garth R, Fisher Jasmin, Apweiler Rolf, De Pace Angela H, Luscombe Nicholas M

机构信息

European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus , Cambridge , United Kingdom ; Okinawa Institute of Science and Technology Graduate University , Okinawa , Japan.

出版信息

Elife. 2013 Aug 6;2:e00522. doi: 10.7554/eLife.00522.

Abstract

Transcriptional control ensures genes are expressed in the right amounts at the correct times and locations. Understanding quantitatively how regulatory systems convert input signals to appropriate outputs remains a challenge. For the first time, we successfully model even skipped (eve) stripes 2 and 3+7 across the entire fly embryo at cellular resolution. A straightforward statistical relationship explains how transcription factor (TF) concentrations define eve's complex spatial expression, without the need for pairwise interactions or cross-regulatory dynamics. Simulating thousands of TF combinations, we recover known regulators and suggest new candidates. Finally, we accurately predict the intricate effects of perturbations including TF mutations and misexpression. Our approach imposes minimal assumptions about regulatory function; instead we infer underlying mechanisms from models that best fit the data, like the lack of TF-specific thresholds and the positional value of homotypic interactions. Our study provides a general and quantitative method for elucidating the regulation of diverse biological systems. DOI:http://dx.doi.org/10.7554/eLife.00522.001.

摘要

转录调控确保基因在正确的时间和位置以适当的量表达。定量理解调控系统如何将输入信号转化为合适的输出仍然是一个挑战。我们首次成功地以细胞分辨率对整个果蝇胚胎中的偶数条纹2和3 + 7进行建模。一种直接的统计关系解释了转录因子(TF)浓度如何定义偶数条纹的复杂空间表达,而无需成对相互作用或交叉调控动力学。通过模拟数千种TF组合,我们找到了已知的调控因子并提出了新的候选因子。最后,我们准确预测了包括TF突变和错误表达在内的扰动的复杂影响。我们的方法对调控功能的假设最少;相反,我们从最符合数据的模型中推断潜在机制,比如缺乏TF特异性阈值和同型相互作用的位置值。我们的研究提供了一种通用的定量方法来阐明各种生物系统的调控机制。DOI:http://dx.doi.org/10.7554/eLife.00522.001

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d57/3736529/b30e60024a24/elife00522f001.jpg

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