DeNOPA: decoding nucleosome positions sensitively with sparse ATAC-seq data

Abstract

Abstract As the basal bricks, the dynamics and arrangement of nucleosomes orchestrate the higher architecture of chromatin in a fundamental way, thereby affecting almost all nuclear biology processes. Thanks to its rather simple protocol, assay for transposase-accessible chromatin using sequencing (ATAC)-seq has been rapidly adopted as a major tool for chromatin-accessible profiling at both bulk and single-cell levels; however, to picture the arrangement of nucleosomes per se remains a challenge with ATAC-seq. In the present work, we introduce a novel ATAC-seq analysis toolkit, named decoding nucleosome organization profile based on ATAC-seq data (deNOPA), to predict nucleosome positions. Assessments showed that deNOPA outperformed state-of-the-art tools with ultra-sparse ATAC-seq data, e.g. no more than 0.5 fragment per base pair. The remarkable performance of deNOPA was fueled by the short fragment reads, which compose nearly half of sequenced reads in the ATAC-seq libraries and are commonly discarded by state-of-the-art nucleosome positioning tools. However, we found that the short fragment reads enrich information on nucleosome positions and that the linker regions were predicted by reads from both short and long fragments using Gaussian smoothing. Last, using deNOPA, we showed that the dynamics of nucleosome organization may not directly couple with chromatin accessibility in the cis-regulatory regions when human cells respond to heat shock stimulation. Our deNOPA provides a powerful tool with which to analyze the dynamics of chromatin at nucleosome position level with ultra-sparse ATAC-seq data.