Predictive model of transcriptional elongation control identifies trans regulatory factors from chromatin signatures.

ABSTRACT: Promoter-proximal Polymerase II (Pol II) pausing is a key rate-limiting step for gene expression. DNA and RNA-binding trans-acting factors regulating the extent of pausing have been identified. However, we lack a quantitative model of how interactions of these factors determine pausing, therefore the relative importance of implicated factors is unknown. Moreover, previously unknown regulators might exist. Here we address this gap with a machine learning model that accurately predicts the extent of promoter-proximal Pol II pausing from large-scale genome and transcriptome binding maps and gene annotation and sequence composition features. We demonstrate high accuracy and generalizability of the model by validation on an independent cell line which reveals the model's cell line agnostic char

SUBMITTER: Akcan TS 

PROVIDER: S-EPMC9976927 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature