Impacts of the feedback loop between sense-antisense RNAs in regulating circadian rhythms.

IF 3.5 2区生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY NPJ Systems Biology and Applications Pub Date : 2024-10-16 DOI:10.1038/s41540-024-00451-4

Koichiro Uriu, Juan P Hernandez-Sanchez, Shihoko Kojima

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Abstract

Antisense transcripts are a unique group of non-coding RNAs and play regulatory roles in a variety of biological processes, including circadian rhythms. Per2AS is an antisense transcript to the sense core clock gene Period2 (Per2) in mouse and its expression is rhythmic and antiphasic to Per2. To understand the impact of Per2AS-Per2 interaction, we developed a new mathematical model that mechanistically described the mutually repressive relationship between Per2 and Per2AS. This mutual repression can regulate both amplitude and period of circadian oscillation by affecting a negative feedback regulation of Per2. Simulations from this model also fit with experimental observations that could not be fully explained by our previous model. Our revised model can not only serve as a foundation to build more detailed models to better understand the impact of Per2AS-Per2 interaction in the future, but also be used to analyze other sense-antisense RNA pairs that mutually repress each other.

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有义-反义 RNA 之间的反馈回路对调节昼夜节律的影响

反义转录本是一类独特的非编码 RNA，在包括昼夜节律在内的多种生物过程中发挥调控作用。Per2AS 是小鼠有义核心时钟基因 Period2（Per2）的反义转录本，其表达与 Per2 具有节律性和反相性。为了了解 Per2AS 与 Per2 相互作用的影响，我们建立了一个新的数学模型，从机理上描述了 Per2 与 Per2AS 之间的相互抑制关系。这种相互抑制可通过影响 Per2 的负反馈调节来调节昼夜节律振荡的振幅和周期。该模型的模拟结果也符合我们之前的模型无法完全解释的实验观察结果。我们修改后的模型不仅可以作为今后建立更详细模型的基础，以更好地理解 Per2AS-Per2 相互作用的影响，还可以用来分析其他相互抑制的有义反义 RNA 对。

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来源期刊

NPJ Systems Biology and Applications Mathematics-Applied Mathematics

CiteScore

5.80

自引率

0.00%

发文量

审稿时长

8 weeks

期刊介绍： npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.