Ferreira R C, Bosco F, Paiva P B, Briones M R S
Departamento de Microbiologia, Imunologia e Parasitologia, Universidade Federal de São Paulo, São Paulo, SP, Brasil.
Genet Mol Res. 2007 Jul 1;6(2):397-414.
The analysis of transcriptional temporal noise could be an interesting means to study gene expression dynamics and stochasticity in eukaryotes. To study the statistical distributions of temporal noise in the eukaryotic model system Saccharomyces cerevisiae, we analyzed microarray data corresponding to one cell cycle for 6200 genes. We found that the temporal noise follows a lognormal distribution with scale invariance at the genome, chromosomal and sub-chromosomal levels. Correlation of temporal noise with the codon adaptation index suggests that at least 70% of all protein-coding genes are a noise minimization core of the genome. Accordingly, a mathematical model of individual gene expression dynamics was proposed, using an operator theoretical approach, which reveals strict conditions for noise variability and a possible global noise minimization/optimization strategy at the genome level. Our model and data show that minimal noise does not correspond to genes obeying a strictly deterministic dynamics. The natural strategy of minimization consists in equating the mean of the absolute value of the relative variation of the expression level (alpha) with noise (eta). We hypothesize that the temporal noise pattern is an emergent property of the genome and shows how the dynamics of gene expression could be related to chromosomal organization.
转录时间噪声分析可能是研究真核生物基因表达动态和随机性的一种有趣方法。为了研究真核生物模型系统酿酒酵母中时间噪声的统计分布，我们分析了6200个基因一个细胞周期的微阵列数据。我们发现，在基因组、染色体和亚染色体水平上，时间噪声遵循具有尺度不变性的对数正态分布。时间噪声与密码子适应指数的相关性表明，所有蛋白质编码基因中至少70%是基因组的噪声最小化核心。因此，使用算子理论方法提出了个体基因表达动态的数学模型，该模型揭示了噪声变异性的严格条件以及基因组水平上可能的全局噪声最小化/优化策略。我们的模型和数据表明，最小噪声并不对应于遵循严格确定性动态的基因。最小化的自然策略在于使表达水平相对变化绝对值的平均值（α）与噪声（η）相等。我们假设时间噪声模式是基因组的一种涌现特性，并展示了基因表达动态如何与染色体组织相关。
