论文标题
使用统计物理方法解决细菌染色体中的顺序程度
Resolving the degree of order in the bacterial chromosome using a statistical physics approach
论文作者
论文摘要
尽管长期以来人们认为细菌染色体是无定形的,但最近的实验表明组织特征明显。但是,细菌染色体组织的程度尚不清楚。在这里,我们开发了完全数据驱动的最大熵方法,以从实验归一化的HI-C数据中提取单细胞染色体构象的分布。我们将此推断应用于模型生物酸膜菌。在104-105底座的小基因组尺度上,我们的模型揭示了局部染色体延伸的模式,该模式与转录和DNA环挤出活性相关。在较大的基因组尺度上,我们发现染色体结构主要存在沿长细胞轴:染色体基因座不仅具有明确定义的轴向位置,而且由于相互作用的大型新兴基因组群集,它们还具有长期的相关性,称为超级超级域。最后,我们的模型揭示了可以指导细胞过程的染色体结构中包含的信息。我们的方法可以推广到其他物种,提供了一种分析空间染色体组织的原则方法。
While bacterial chromosomes were long thought to be amorphous, recent experiments reveal pronounced organizational features. However, the extent of bacterial chromosome organization remains unclear. Here, we develop a fully data-driven maximum entropy approach to extract the distribution of single-cell chromosome conformations from experimental normalized Hi-C data. We apply this inference to the model organism Caulobacter crescentus. On small genomic scales of 104-105 basepairs, our model reveals a pattern of local chromosome extensions that correlates with transcriptional and DNA loop extrusion activity. On larger genomic scales, we find that chromosome structure is predominantly present along the long cell axis: chromosomal loci not only have well-defined axial positions, they also exhibit long-ranged correlations due interacting large emergent genomic clusters, termed Super Domains. Finally, our model reveals information contained in chromosome structure that can guide cellular processes. Our approach can be generalized to other species, providing a principled way of analyzing spatial chromosome organization.