A computational pipeline to visualize DNA-protein binding states using dSMF data

STAR Protoc. 2022 Apr 12;3(2):101299. doi: 10.1016/j.xpro.2022.101299. eCollection 2022 Jun 17.

Abstract

Here, we present a pipeline to map states of protein-binding DNA in vivo. Our pipeline infers as well as quantifies cooperative binding. Using dual-enzyme single-molecule footprinting (dSMF) data, we show how our workflow identifies binding states at an enhancer in Drosophila S2 cells. Data from cells lacking endogenous DNA methylation are a prerequisite for this pipeline. For complete details on the use and execution of this protocol, please refer to Rao et al. (2021) and Krebs et al. (2017).

Keywords: Bioinformatics; Genomics; Molecular Biology; Sequence analysis.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • DNA Methylation* / genetics
  • DNA* / genetics
  • Protein Binding
  • Workflow

Substances

  • DNA