title: Reconciling the concurrent fast and slow cycling of proteins on gene promoters.
abstract: During gene transcription, proteins appear to cycle on and off some gene promoters with both long (tens of minutes) and short periods (no more than several minutes). The essence of these phenomena still remains unclear. Here, we propose a stochastic model for the state evolution of promoters in terms of DNA-protein interactions. The model associates the characteristics of microscopic molecular interactions with macroscopic measurable quantities. Through theoretical derivation, we reconcile the contradictory viewpoints on the concurrent fast and slow cycling; both the cycling phenomena are further reproduced by fitting simulation results to the experimental data on the pS2 gene. Our results suggest that the fast cycling dictates how the proteins behave on the promoter and that stable binding hardly occurs. Different kinds of proteins rapidly bind/unbind the promoter at distinct transcriptional stages fulfilling specific functions; this feature is essentially manifested as the slow cycling of proteins when detected by chromatin immunoprecipitation assays. Thus, the slow cycling represents neither stable binding of proteins nor external modulation of the fast cycling. This work also reveals the relationship between the essence and measurement of transcriptional dynamics.
authors.affiliation: National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, , Nanjing 210093, People's Republic of China.
authors.forename: Yaolai
authors.initials: Y
authors.lastname: Wang
authors.forename: Feng
authors.initials: F
authors.lastname: Liu
authors.forename: Jun
authors.initials: J
authors.lastname: Li
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
mesh_terms: D001665:Binding Sites; D047369:Chromatin Immunoprecipitation; D008957:Models, Genetic; D011401:Promoter Regions, Genetic; D013269:Stochastic Processes; D014158:Transcription, Genetic / Q000502:physiology*
keywords: pS2 gene; promoter state; promoter–protein interactions; stochastic model; transcriptional dynamics