bioRxivBiophysics
Quantifying the large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition of cell cycle
Abstract
Cell cycle, essential for various cellular processes, is known to be precisely regulated by the underlying gene network. Accumulating evidence has revealed that the chromosome, which serves as the scaffold for the gene expressions, undergoes significant structural reorganizations during mitosis. Understanding the mechanism of the cell cycle from the molecular chromosome structural perspective remains a grand challenge. In this study, we applied an integrated approach using a data-driven model combined with a nonequilibrium landscape-switching model to investigate large-scale chromosome structural dynamics during the mitosis-to-G1 phase transition. We generated 3D chromosome structural ensembles for the five critical stages in the process. We observed that the chromosome structural expansion and adaptation of the structural asphericity do not occur synchronously. We attributed this asynchronous adaptation behavior in the chromosome structural geometry to the unique unloading sequence of the two types of condensins. Furthermore, we observed that the coherent motions between the chromosomal loci are primarily enhanced within the topologically associating domains (TADs) as cells progress to the G1 phase, suggesting that TADs can be considered as both structural and dynamical units for organizing the 3D chromosome. Our analysis also reveals that the quantified pathways of chromosome structural reorganizations during the mitosis-to-G1 phase transition exhibit high stochasticity at the single-cell level and show non-linear behaviors in changing TADs and contacts formed at the long-range regions. These features underscore the complex nature of the cell-cycle processes. Our findings, which are consistent with the experiments in many aspects, offer valuable insights into the large-scale chromosome structural dynamics after mitosis and contribute to the molecular-level understanding of the cell-cycle process.
- assay: Hi-C
- research focus: chromatin & epigenetic regulation
- approach: deep learning
- approach: statistical model
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