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Stochastic Modeling of Expression Kinetics Identifies Messenger Half-Lives and Reveals Sequential Waves of Co-ordinated Transcription and Decay

机译:表达动力学的随机建模可识别信使半衰期并揭示协调转录和衰变的顺序波

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摘要

The transcriptome in a cell is finely regulated by a large number of molecular mechanisms able to control the balance between mRNA production and degradation. Recent experimental findings have evidenced that fine and specific regulation of degradation is needed for proper orchestration of a global cell response to environmental conditions. We developed a computational technique based on stochastic modeling, to infer condition-specific individual mRNA half-lives directly from gene expression time-courses. Predictions from our method were validated by experimentally measured mRNA decay rates during the intraerythrocytic developmental cycle of Plasmodium falciparum. We then applied our methodology to publicly available data on the reproductive and metabolic cycle of budding yeast. Strikingly, our analysis revealed, in all cases, the presence of periodic changes in decay rates of sequentially induced genes and co-ordination strategies between transcription and degradation, thus suggesting a general principle for the proper coordination of transcription and degradation machinery in response to internal and/or external stimuli.
机译:细胞中的转录组受到许多能够控制mRNA产生与降解之间平衡的分子机制的良好调控。最近的实验发现证明,要适当地协调全局细胞对环境条件的响应,就需要对降解进行精细和特定的调节。我们开发了一种基于随机建模的计算技术,可以直接从基因表达时程推断条件特定的个体mRNA半衰期。通过我们在恶性疟原虫的红细胞内发育周期中通过实验测量的mRNA衰减率验证了我们方法的预测。然后,我们将我们的方法应用于关于萌芽酵母的生殖和代谢周期的公开数据。令人惊讶的是,我们的分析显示,在所有情况下,顺序诱导的基因的衰变率周期性变化以及转录和降解之间的协调策略均存在,从而为响应内部结构而适当协调转录和降解机制提出了一般原则。和/或外部刺激。

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