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Formation of correlated chromatin domains at nanoscale dynamic resolution during transcription

Intrinsic dynamics of chromatin contribute to gene regulation. How chromatin mobility responds to genomic processes, and whether this response relies on coordinated chromatin movement is still unclear. Here, we introduce an approach called Dense Flow reConstruction and Correlation (DFCC), to quantif...

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Detalles Bibliográficos
Autores principales: Shaban, Haitham A, Barth, Roman, Bystricky, Kerstin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6061878/
https://www.ncbi.nlm.nih.gov/pubmed/29718294
http://dx.doi.org/10.1093/nar/gky269
Descripción
Sumario:Intrinsic dynamics of chromatin contribute to gene regulation. How chromatin mobility responds to genomic processes, and whether this response relies on coordinated chromatin movement is still unclear. Here, we introduce an approach called Dense Flow reConstruction and Correlation (DFCC), to quantify correlation of chromatin motion with sub-pixel sensitivity at the level of the whole nucleus. DFCC reconstructs dense global flow fields of fluorescent images acquired in real-time. We applied our approach to analyze stochastic movements of DNA and histones, based on direction and magnitude at different time lags in human cells. We observe long-range correlations extending over several μm between coherently moving regions over the entire nucleus. Spatial correlation of global chromatin dynamics was reduced by inhibiting elongation by RNA polymerase II, and abolished in quiescent cells. Furthermore, quantification of spatial smoothness over time intervals up to 30 s points to clear-cut boundaries between distinct regions, while smooth transitions in small (<1 μm) neighborhoods dominate for short time intervals. Rough transitions between regions of coherent motion indicate directed squeezing or stretching of chromatin boundaries, suggestive of changes in local concentrations of actors regulating gene expression. The DFCC approach hence allows characterizing stochastically forming domains of nuclear activity.