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Related Experiment Video

Updated: Jan 18, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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Comprehensive profiling of chromatin occupancy dynamics through the cell cycle.

Yulong Li1, David M MacAlpine2, Alexander J Hartemink1

  • 1Department of Computer Science, Duke University, Durham, NC 27708, United States.

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|January 16, 2026
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Summary

Cell division involves complex chromatin and transcription dynamics. This study reveals transcription-independent chromatin changes and uses a model to predict transcript dynamics during the cell cycle.

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Area of Science:

  • Molecular Biology
  • Genetics
  • Cell Biology

Background:

  • DNA-binding factors establish chromatin context for DNA-templated processes.
  • Previous research focused on external perturbations, lacking cell-cycle specific chromatin dynamics.
  • Understanding cell-cycle chromatin dynamics is crucial for gene regulation.

Purpose of the Study:

  • Investigate the interplay between cell-cycle-regulated chromatin dynamics and transcription.
  • Profile genome-wide chromatin occupancy and transcriptome across cell cycles.
  • Develop a model to predict transcript dynamics using chromatin data.

Main Methods:

  • Utilized Saccharomyces cerevisiae as a model organism.
  • Performed time-series profiling of chromatin occupancy (MNase-seq) and transcriptome (RNA-seq) over two cell cycles.
  • Employed entropy as a measure of nucleosome organization and developed a Gaussian process statistical model.

Main Results:

  • Identified a small subset of cell-cycle-regulated genes with matching protein occupancy and expression dynamics.
  • Discovered widespread, transcription-independent chromatin changes during cell-cycle progression.
  • Observed nucleosome disruption in S phase and re-organization in M phase, with exceptions for highly transcribed mitotic genes.

Conclusions:

  • Chromatin dynamics during the cell cycle are complex and not always directly tied to gene expression.
  • Transcription-independent chromatin reorganization occurs during cell division.
  • The developed model improves prediction of transcript dynamics using chromatin features.