Model integration of circadian- and sleep-wake-driven contributions to rhythmic gene expression reveals distinct regulatory principles

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Maxime Jan, Sonia Jimenez, Charlotte N. Hor, Derk-Jan Dijk, Anne C. Skeldon, Paul Franken
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Abstract

Analyses of gene-expression dynamics in research on circadian rhythms and sleep homeostasis often describe these two processes using separate models. Rhythmically expressed genes are, however, likely to be influenced by both processes. We implemented a driven, damped harmonic oscillator model to estimate the contribution of circadian- and sleep-wake-driven influences on gene expression. The model reliably captured a wide range of dynamics in cortex, liver, and blood transcriptomes taken from mice and humans under various experimental conditions. Sleep-wake-driven factors outweighed circadian factors in driving gene expression in the cortex, whereas the opposite was observed in the liver and blood. Because of tissue- and gene-specific responses, sleep deprivation led to a long-lasting intra- and inter-tissue desynchronization. The model showed that recovery sleep contributed to these long-lasting changes. The results demonstrate that the analyses of the daily rhythms in gene expression must take the complex interactions between circadian and sleep-wake influences into account. A record of this paper’s transparent peer review process is included in the supplemental information.

Abstract Image

昼夜节律和睡眠-觉醒对节律性基因表达贡献的模型整合揭示了不同的调控原理
在有关昼夜节律和睡眠平衡的研究中,对基因表达动态的分析通常使用不同的模型来描述这两个过程。然而,有节律表达的基因很可能同时受到这两个过程的影响。我们采用了一个驱动型阻尼谐振子模型来估计昼夜节律和睡眠-觉醒驱动对基因表达的影响。该模型可靠地捕捉到了小鼠和人类在各种实验条件下大脑皮层、肝脏和血液转录组的各种动态变化。在大脑皮层中,睡眠-觉醒因素对基因表达的影响超过了昼夜节律因素,而在肝脏和血液中则相反。由于组织和基因的特异性反应,睡眠剥夺导致了组织内和组织间的长期不同步。该模型显示,恢复性睡眠促成了这些持久的变化。研究结果表明,对基因表达日节律的分析必须考虑到昼夜节律和睡眠-觉醒之间复杂的相互作用。本文的同行评审过程透明,其记录见补充信息。
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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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