4.8 Article

Learning the distribution of single-cell chromosome conformations in bacteria reveals emergent order across genomic scales

Journal

NATURE COMMUNICATIONS
Volume 12, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-021-22189-x

Keywords

-

Funding

  1. Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [269423233-TRR 174]
  2. DFG fellowship within the Graduate School of Quantitative Biosciences Munich (QBM)

Ask authors/readers for more resources

The study develops a fully data-driven method to extract single-cell 3D chromosome conformations from Hi-C experiments on Caulobacter crescentus, revealing the order and variability of bacterial chromosome organization, such as long-ranged two-point axial correlations on large genomic scales and chromosome extensions correlating with transcriptional and loop extrusion activity on smaller scales. This approach can be extended to other species, providing a general strategy to resolve variability in single-cell chromosomal organization.
The order and variability of bacterial chromosome organization, contained within the distribution of chromosome conformations, are unclear. Here, we develop a fully data-driven maximum entropy approach to extract single-cell 3D chromosome conformations from Hi-C experiments on the model organism Caulobacter crescentus. The predictive power of our model is validated by independent experiments. We find that on large genomic scales, organizational features are predominantly present along the long cell axis: chromosomal loci exhibit striking long-ranged two-point axial correlations, indicating emergent order. This organization is associated with large genomic clusters we term Super Domains (SuDs), whose existence we support with super-resolution microscopy. On smaller genomic scales, our model reveals chromosome extensions that correlate with transcriptional and loop extrusion activity. Finally, we quantify the information contained in chromosome organization that may guide cellular processes. Our approach can be extended to other species, providing a general strategy to resolve variability in single-cell chromosomal organization. The order and variability of bacterial chromosome organization, contained within the distribution of chromosome conformations, are unclear. Here, the authors develop a fully data-driven maximum entropy approach to extract single-cell 3D chromosome conformations from Hi-C experiments on the model organism Caulobacter crescentus.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available