背景:遗传序列的统计方法有助于更深入地了解生物学和结构功能,使用来自信息论和符号序列随机建模的思想。特别是,先前对基因组中CG二核苷酸位置的分析强调了其在DNA甲基化中的表观遗传作用,显示与其他二核苷酸相比不同的分布尾。在本文中,我们将分析扩展到一组选定的高阶生物上的整个CG距离分布。然后,我们将最佳拟合概率密度函数应用于不同复杂性(从细菌到哺乳动物)的大范围生物(>4400),并表征了一些新兴的全局特征。
结果:我们发现,与一组几个分布相比,Gamma分布对于所选子集是最佳的,选择是因为它们的物理意义,或者是因为最近在文献中用于类似研究。这个分布的参数,当应用于我们更大的生物体时,允许突出所考虑的有机体类别的一些生物学相关特征,这也可以用于分类目的。
结论:CG二核苷酸沿基因组定位的统计特性的定量被证实是表征广泛种类生物的有用工具,跨越生物复杂性的整个范围。
BACKGROUND: Statistical approaches to genetic sequences have revealed helpful to gain deeper insight into biological and structural functionalities, using ideas coming from information theory and stochastic modelling of symbolic sequences. In particular, previous analyses on CG dinucleotide position along the genome allowed to highlight its epigenetic role in DNA methylation, showing a different distribution tail as compared to other dinucleotides. In this paper we extend the analysis to the whole CG distance distribution over a selected set of higher-order organisms. Then we apply the best fitting probability density function to a large range of organisms (>4400) of different complexity (from bacteria to mammals) and we characterize some emerging global features.
RESULTS: We find that the Gamma distribution is optimal for the selected subset as compared to a group of several distributions, chosen for their physical meaning or because recently used in literature for similar studies. The parameters of this distribution, when applied to our larger set of organisms, allows to highlight some biologically relavant features for the considered organism classes, that can be useful also for classification purposes.
CONCLUSIONS: The quantification of statistical properties of CG dinucleotide positioning along the genome is confirmed as a useful tool to characterize broad classes of organisms, spanning the whole range of biological complexity.