Building Nucleosome Positioning Maps: Discovering Hidden Gems

Abstract

Nucleosomes serve as fundamental units of chromatin packaging and play a crucial role as central hubs in epigenetic regulation. Their positions throughout the genome are not random and follow certain patterns, influenced by DNA sequence, histone-DNA interactions, chromatin physical barriers, nucleosome sliding and unwrapping, and chromatin modifications. There are many experimental techniques for identifying nucleosome positions, but these methods often involve a trade-off between achieving high resolution and covering the entire genome. In this regard, computational approaches may offer a fast alternative, with the benefit of aiding experimental analysis by denoising data, refining nucleosome boundaries, and identifying features critical for nucleosome positioning. Moreover, computational predictions enable the integration of nucleosome positioning data with other genomic and epigenomic datasets, providing a more comprehensive view of chromatin organization and gene regulation. In this review, we focus on various nucleosome positioning methods, including experimental techniques of nucleosome boundaries identification and in silico methods of nucleosome positioning data denoising and prediction of nucleosome positioning from the DNA sequence.