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通过相互关联的前馈通路进行噪声传播。

Noise propagation with interlinked feed-forward pathways.

作者信息

Chepyala Surendhar Reddy, Chen Yi-Chen, Yan Ching-Cher Sanders, Lu Chun-Yi David, Wu Yi-Chun, Hsu Chao-Ping

机构信息

Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, Taiwan.

Institute of Chemistry, Academia Sinica, Taipei, Taiwan.

出版信息

Sci Rep. 2016 Mar 31;6:23607. doi: 10.1038/srep23607.

Abstract

Functionally similar pathways are often seen in biological systems, forming feed-forward controls. The robustness in network motifs such as feed-forward loops (FFLs) has been reported previously. In this work, we studied noise propagation in a development network that has multiple interlinked FFLs. A FFL has the potential of asymmetric noise-filtering (i.e., it works at either the "ON" or the "OFF" state in the target gene). With multiple, interlinked FFLs, we show that the propagated noises are largely filtered regardless of the states in the input genes. The noise-filtering property of an interlinked FFL can be largely derived from that of the individual FFLs, and with interlinked FFLs, it is possible to filter noises in both "ON" and "OFF" states in the output. We demonstrated the noise filtering effect in the developmental regulatory network of Caenorhabditis elegans that controls the timing of distal tip cell (DTC) migration. The roles of positive feedback loops involving blmp-1 and the degradation regulation of DRE-1 also studied. Our analyses allow for better inference from network structures to noise-filtering properties, and provide insights into the mechanisms behind the precise DTC migration controls in space and time.

摘要

功能相似的通路在生物系统中经常出现,形成前馈控制。此前已有报道前馈环(FFL)等网络基序中的稳健性。在这项工作中,我们研究了一个具有多个相互连接的FFL的发育网络中的噪声传播。一个FFL具有不对称噪声过滤的潜力(即它在靶基因的“开”或“关”状态下起作用)。通过多个相互连接的FFL,我们表明,无论输入基因的状态如何,传播的噪声在很大程度上都会被过滤掉。相互连接的FFL的噪声过滤特性在很大程度上可以从单个FFL的特性推导出来,并且通过相互连接的FFL,可以在输出的“开”和“关”状态下过滤噪声。我们在秀丽隐杆线虫控制远端末梢细胞(DTC)迁移时间的发育调控网络中证明了噪声过滤效应。还研究了涉及blmp-1的正反馈环的作用以及DRE-1的降解调控。我们的分析有助于从网络结构更好地推断噪声过滤特性,并深入了解DTC在空间和时间上精确迁移控制背后的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cfbe/4814832/254788b53fcc/srep23607-f1.jpg

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