Combinatorial probabilistic chromatin interactions produce transcriptional heterogeneity

组合概率染色质相互作用产生转录异质性

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Abstract

Gene regulation often appears deterministic in the average cell population, but transcription is a probabilistic process at the single-cell level. Although many mechanisms are invoked to account for this behavior, it is difficult to determine how cell-to-cell variation in the interactions of transcription factors with target chromatin impact transcriptional output. Here, we use cells that contain a 200-copy tandem array of promoter or reporter gene units to simultaneously visualize transient interaction, equilibrium or steady-state binding of fluorescent-protein-labeled glucocorticoid receptor with its DNA response elements, the recruitment of diverse coregulators, and transcriptional output at the single-cell level. These regulatory proteins associate with target chromatin via a probabilistic mechanism that produces cell-to-cell variability in binding. The multiple steps of this process are partially independent and differ between individual regulators. The association level of each regulator influences the transcriptional output in individual cells, but this does not account for all transcriptional heterogeneity. Additionally, specific combinatorial interactions of the glucocorticoid receptor and coregulators with response elements regulate transcription at the single-cell level. Like many endogenous genes, the average array transcriptional activity evolves over time. This apparently deterministic average temporal promoter progression involves changes in the probability that specific combinatorial glucocorticoid receptor and coregulator interactions will occur on the response elements in single cells. These data support the emerging ;return-to-template' transcription model, which mechanistically unifies the observed extremely transient interactions between the transcription factor and response elements, cell-to-cell variability in steady-state association of factors with chromatin, and the resulting heterogeneous gene expression between individual cells.

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