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Single-molecule chromatin configurations link transcription factor binding to expression in human cells [RNA-seq]

GSE276515 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2024/09/10 Platform GPL21697
Summary
The binding of multiple transcription factors (TFs) to genomic enhancers activates gene expression in mammalian cells. However, the molecular details that link enhancer sequence to TF binding, promoter state, and gene expression levels remain opaque. We applied single-molecule footprinting (SMF) to measure the simultaneous occupancy of TFs, nucleosomes, and components of the transcription machinery on engineered enhancer/promoter constructs with variable numbers of TF binding sites for both a synthetic and an endogenous TF. We find that activation domains enhance a TF’s capacity to compete with nucleosomes for binding to DNA in a BAF-dependent manner, TF binding on nucleosome-free DNA is consistent with independent binding between TFs, and average TF occupancy linearly contributes to promoter activation rates. We also decompose TF strength into separable binding and activation terms, which can be tuned and perturbed independently. Finally, we develop thermodynamic and kinetic models that quantitatively predict both the binding microstates observed at the enhancer and subsequent time-dependent gene expression. This work provides a template for quantitative dissection of distinct contributors to gene activation, including the activity of chromatin remodelers, TF activation domains, chromatin acetylation, TF concentration, TF binding affinity, and TF binding site configuration.
Published in
Single-molecule states link transcription factor binding to gene expression
Doughty BR, Hinks MM, Schaepe JM et al. · Nature 2024 · PMID 39567683 · doi:10.1038/s41586-024-08219-w
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Direct links to NCBI, no account and no request form: the whole study as GSE276515_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1071686 and SRA study SRP487205. Searching any of these in the dataset finder brings you back here.

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