等位基因相关性是基因网络中表达变异性传播障碍与信号响应之间权衡的标志。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Cell Systems Pub Date : 2022-12-21 Epub Date: 2022-11-29 DOI:10.1016/j.cels.2022.10.008
Ryan H Boe, Vinay Ayyappan, Lea Schuh, Arjun Raj
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引用次数: 0

摘要

遗传网络应该对信号做出反应,但要防止自发波动的传播。来自哺乳动物细胞的有限数据表明,噪音传播并不常见,但由于无法直接测量,有关噪音传播的系统性说法一直受到限制。在这里,我们建立了一个等位基因相关性和噪音传递的数学建模框架,表明等位基因相关性和噪音传递在不同的模型参数和网络结构下是一致的。限制噪声传输的代价是对信号无响应,而在有响应的情况下,响应时间和基础噪声传输之间又存在进一步的权衡。对等位基因特异性单细胞 RNA 测序数据的分析表明,编码信号通路上游因子和细胞类型特异性因子的基因比下游因子具有更高的等位基因相关性,这表明它们更容易受到调控。总之,我们的研究结果表明,信号的响应性必然会导致一些噪音的传播,但可以通过换取较慢的响应来尽量减少噪音的传播。补充信息中包含了本文透明的同行评审过程记录。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Allelic correlation is a marker of trade-offs between barriers to transmission of expression variability and signal responsiveness in genetic networks.

Genetic networks should respond to signals but prevent the transmission of spontaneous fluctuations. Limited data from mammalian cells suggest that noise transmission is uncommon, but systematic claims about noise transmission have been limited by the inability to directly measure it. Here, we build a mathematical framework modeling allelic correlation and noise transmission, showing that allelic correlation and noise transmission correspond across model parameters and network architectures. Limiting noise transmission comes with the trade-off of being unresponsive to signals, and within responsive regimes, there is a further trade-off between response time and basal noise transmission. Analysis of allele-specific single-cell RNA-sequencing data revealed that genes encoding upstream factors in signaling pathways and cell-type-specific factors have higher allelic correlation than downstream factors, suggesting they are more subject to regulation. Overall, our findings suggest that some noise transmission must result from signal responsiveness, but it can be minimized by trading off for a slower response. A record of this paper's transparent peer review process is included in the supplemental information.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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