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Biology subjects

Asante, Y.

Publications and source records attributed to Asante, Y..

2 recordsLinked to original sources

Rare RNA Polymerase II failure modes mark the cancer-driving genes most affected by epigenetic perturbation

RNA Polymerase II (Pol2) transcribes genes through a complex life cycle (initiation, pausing, elongation, co-transcriptional splicing, termination, and recycling). Chromatin immunoprecipitation of Pol2 before and after chemical perturbation has identified promoter-proximal accumulation (pausing) as a critical step in the transcription genome-wide. However, the full landscape of Pol2 responses has not been well characterized. Here, we introduce a tool for comparing Pol2 Activity State Shifts (compPASS), a computational pipeline which uses data from paired ChIP-based approaches to assign genes to one of eight distinct modes by Pol2 response under different forms of perturbation. In multiple cancer types and drug contexts, we show that compPASS identifies previously undescribed Pol2 failure modes with important implications for gene regulation. By looking past pausing, compPASS exposes Pol2 failure modes (clogging, entry, gain, loss) that are rare but pinpoint the genes most relevant to cancer cell state changes in response to therapy, turning a single paired Pol2 ChIP-seq into a mechanistic map of shifting transcriptional states.

bioinformatics↗

CpG island density predicts CBP/p300 dependency across 3D chromatin clusters

RNA Polymerase II (Pol2) organizes transcription through higher-ordered chromatin clusters that integrate promoter and enhancer interactions to coordinate gene expression. Nevertheless, the features that distinguish unique classes of Pol2-mediated clusters remain to be defined. Here, we identify two distinct classes of Pol2-mediated clusters: one enriched for CpG islands, promoter-promoter interactions, and housekeeping gene expression, and another characterized by high CBP/p300 occupancy, enhancer-promoter looping, and lineage-defining (LD) transcriptional programs. Acute inhibition of CBP/p300 catalytic activity leads to rapid loss of acetylation at enhancers and preferential downregulation of LD genes, resulting in impaired cellular proliferation and activation of apoptotic programs. Integrative machine learning modeling reveals that cluster strength, RNA half-life, and CpG island content as strong predictors of genes sensitive to CBP/p300 inhibition. Together, these findings clarify enhancer-addiction and vulnerability to CBP/p300 inhibition.

cancer biology↗