A temporal switch model for estimating transcriptional activity in gene expression
A temporal switch model for estimating transcriptional activity in gene expression
复制标题
DOI：
10.1093/bioinformatics/btt111
复制
发表时间：
2013-05-01
期刊：
影响因子：
5.8
通讯作者：
Rand, David A.
中科院分区：
文献类型：
--
作者：
Jenkins, Dafyd J.;Finkenstaedt, Baerbel;Rand, David A.
动机：时间序列基因表达数据的分析和机制建模提供的技术，如微阵列，NanoString，逆转录-聚合酶链反应和先进的测序是非常宝贵的发展变化的理解关键的生物过程。我们解决这一问题，提出了一个灵活的动态模型，它applies时间的合成和降解的mRNA，因此，允许转录活性之间切换不同的states.Results：该模型是足够灵活的捕捉各种观察到的转录动态，包括振荡行为，在一种方式，是兼容的要求所施加的质量，时间分辨率和数量的数据。我们发现，在转录活性的开关事件的时间和数量可以估计与贝叶斯可逆跳马尔可夫链蒙特卡罗算法的帮助下，随着单个基因mRNA的稳定性。为了证明的方法，我们专注于模拟野生型行为的选择200昼夜节律基因的模式植物拟南芥。这些结果支持了这样一种观点，即使用一种机制模型来识别转录开关点可能会极大地有助于阐明和理解关键的生物过程，如转录和降解。
Motivation: The analysis and mechanistic modelling of time series gene expression data provided by techniques such as microarrays, NanoString, reverse transcription-polymerase chain reaction and advanced sequencing are invaluable for developing an understanding of the variation in key biological processes. We address this by proposing the estimation of a flexible dynamic model, which decouples temporal synthesis and degradation of mRNA and, hence, allows for transcriptional activity to switch between different states.Results: The model is flexible enough to capture a variety of observed transcriptional dynamics, including oscillatory behaviour, in a way that is compatible with the demands imposed by the quality, time-resolution and quantity of the data. We show that the timing and number of switch events in transcriptional activity can be estimated alongside individual gene mRNA stability with the help of a Bayesian reversible jump Markov chain Monte Carlo algorithm. To demonstrate the methodology, we focus on modelling the wild-type behaviour of a selection of 200 circadian genes of the model plant Arabidopsis thaliana. The results support the idea that using a mechanistic model to identify transcriptional switch points is likely to strongly contribute to efforts in elucidating and understanding key biological processes, such as transcription and degradation.