# Inferring differential protein binding from time-series chromatin accessibility data

## TL;DR

This paper introduces a new method to analyze how chromatin accessibility changes over time, revealing shifts in protein binding and gene regulation under stress.

## Contribution

DynaCOP is a novel method for identifying differential chromatin occupancy from time-series data using nucleosome-guided difference profiles.

## Key findings

- DynaCOP identifies differentially binding transcription factors and nucleosome changes in yeast under cadmium stress.
- Observed chromatin changes correlate strongly with transcriptional changes in response to stress.
- Time-series MNase-seq data reveal dynamic chromatin occupancy patterns across the yeast genome.

## Abstract

Due to internal and external factors, the epigenomic landscape is constantly changing in ways that are linked to changes in gene expression. Chromatin accessibility data, such as MNase-seq, provide valuable insights into this landscape and have been used to compute chromatin occupancy profiles. Multiple datasets generated over time or under different conditions can thus be used to study dynamic changes in chromatin occupancy across the genome.

Our existing model, RoboCOP, computes a genome-wide chromatin occupancy profile for nucleosomes and hundreds of transcription factors. Here, we present a new method called DynaCOP that takes multiple chromatin occupancy profiles and uses them to generate a series of nucleosome-guided difference profiles. These profiles identify differentially binding transcription factors and reveal changes in nucleosome occupancy and positioning. We apply DynaCOP to chromatin occupancy profiles derived from deeply sequenced time-series MNase-seq data to study differential chromatin occupancy in the yeast genome under cadmium stress. We find strong correlations between the observed chromatin changes and changes in transcription.

https://github.com/HarteminkLab/RoboCOP