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Comparative cofactor screens reveal the influence of transactivation domains and core promoters on the mechanisms of transcription [Degron ChIP]

GSE256175 Homo sapiens Genome binding/occupancy profiling by high throughput sequencing 9 samples Submitted 2024/03/01 Platform GPL18573
Summary
Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here, we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors required by nine different TFs in human cells. Using this dataset, we associate key TFs with their cofactors, classify cofactors as ubiquitous or specific, discover novel transcriptional co-dependencies and demonstrate that certain TFs use the tail 2 and kinase submodules of Mediator to potentiate transcriptional elongation. By employing a reductionistic and comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF is dependent on a unique combination of cofactors, which influences distinct steps in the transcriptional process. We also extend our screens to nine different core promoters to explore how core promoter elements influence cofactor dependence. Our data suggest that different classes of promoter are constrained by either initiation or pause release, which influences their dynamic range of gene expression and compatibility with specific cofactors. Overall, our comparative cofactor screens uncover the interplay between TFs, cofactors and core promoters and reveal general principles by which they influence transcription. 
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Direct links to NCBI, no account and no request form: the whole study as GSE256175_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 9 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1078372 and SRA study SRP490579. Searching any of these in the dataset finder brings you back here.

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