Tompitak Marco, Vaillant Cédric, Schiessel Helmut
Leiden University, Lorentz Institute, Leiden, the Netherlands.
Laboratoire de Physique, Univ Lyon, Ens de Lyon, Univ Claude Bernard, CNRS, Lyon, France.
Biophys J. 2017 Feb 7;112(3):505-511. doi: 10.1016/j.bpj.2016.12.041. Epub 2017 Jan 25.
Sequences that influence nucleosome positioning in promoter regions, and their relation to gene regulation, have been the topic of much research over the last decade. In yeast, significant nucleosome-depleted regions are found, which facilitate transcription. With the arrival of nucleosome positioning maps for the human genome, it was discovered that in our genome, unlike in that of yeast, promoters encode for high nucleosome occupancy. In this work, we look at the genomes of a range of different organisms, to provide a catalog of nucleosome positioning signals in promoters across the tree of life. We utilize a computational model of the nucleosome, based on crystallographic analyses of the structure and elasticity of the nucleosome, to predict the nucleosome positioning signals in promoter regions. To be able to apply our model to large genomic datasets, we introduce an approximative scheme that makes use of the limited range of correlations in nucleosomal sequence preferences to create a computationally efficient approximation of the full biophysical model. Our predictions show that a clear distinction between unicellular and multicellular life is visible in the intrinsically encoded nucleosome affinity. Furthermore, the strength of the nucleosome positioning signals correlates with the complexity of the organism. We conclude that encoding for high nucleosome occupancy, as in the human genome, is in fact a universal feature of multicellular life.
在过去十年中,影响启动子区域核小体定位的序列及其与基因调控的关系一直是众多研究的主题。在酵母中,发现了显著的核小体缺失区域,这些区域促进转录。随着人类基因组核小体定位图谱的出现,人们发现,在我们的基因组中,与酵母基因组不同,启动子编码高核小体占有率。在这项工作中,我们研究了一系列不同生物体的基因组,以提供生命之树中各启动子核小体定位信号的目录。我们利用基于核小体结构和弹性晶体学分析的核小体计算模型,来预测启动子区域的核小体定位信号。为了能够将我们的模型应用于大型基因组数据集,我们引入了一种近似方案,该方案利用核小体序列偏好中有限的相关范围,来创建完整生物物理模型的计算高效近似。我们的预测表明,在内在编码的核小体亲和力方面,单细胞生命和多细胞生命之间存在明显区别。此外,核小体定位信号的强度与生物体的复杂性相关。我们得出结论,如在人类基因组中那样,编码高核小体占有率实际上是多细胞生命的一个普遍特征。