Interdependence between histone marks and steps in Pol II transcription [Danko.submission]

ABSTRACT: We trained sensitive machine learning models that decompose maps of primary transcription into ChIP-seq profiles representing 9 distinct histone modifications. We show that transcription measured using precision run-on and sequencing (PRO-seq)  can recover the pattern of active histone modifications at nucleosome resolution and with an accuracy that rivals the correlation between independent ChIP-seq experiments in holdout cell types. To define the nature of the causal relationship between histone modifications and transcription, we perturbed transcription and examined the genomic distribution of four active and one repressive histone modification: H3K4me1, H3K4me3, H3K27ac, H3K36me3, H3K27me3.

ORGANISM(S): Homo sapiens

PROVIDER: GSE163043 | GEO | 2020/12/12

REPOSITORIES: GEO