ArticleNucleic acids research2026
Comprehensive profiling of chromatin occupancy dynamics through the cell cycle.
Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The occupancy of DNA-binding factors is critical for establishing the chromatin context of DNA-templated processes like transcription and replication. Many studies have investigated relationships between chromatin and transcription in response to genetic and environmental perturbations, but a comprehensive view of the dynamics of chromatin organization and its effect on transcription during the cell-intrinsic process of the cell division cycle has been lacking. In this study, we use the model organism Saccharomyces cerevisiae to investigate the interplay between the cell-cycle-regulated dynamics of chromatin and transcription. In a time series across two consecutive cell cycles, we profile the genome-wide chromatin occupancy landscape with next-generation sequencing of micrococcal-nuclease-digested chromatin while simultaneously profiling the transcriptome with RNA-seq. Surprisingly, among cell-cycle-regulated genes, only a small subset exhibits a change in protein occupancy in their promoter or gene body that strongly mirrors the dynamics of their expression level. However, we separately identify widespread chromatin changes that are not directly linked to cell-cycle-regulated genes, revealing transcription-independent chromatin dynamics during cell-cycle progression. Using entropy as a proxy for nucleosome disorganization, we observe widespread nucleosome disruption in S phase followed by re-organization in M phase, associated with replicative and mitotic activities, respectively. A notable exception is the set of genes expressed in mitosis, which exhibit marked M-phase nucleosome disorganization, likely due to elevated transcription. We develop a Gaussian process statistical model that uses simple features from these chromatin data to improve the prediction of transcript dynamics through the cell cycle. Collectively, our data reveal complex relationships between the dynamics of chromatin occupancy, transcription, and replication during the cell cycle.
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