Nucleosome positioning: resources and tools online

This is the author's version which is being continuously updated and not synchronised with the journal version. The final printed version will appear in Briefings in Bioinformatics Abstract Nucleosome positioning is an important process required for proper genome packing and its accessibility to execute the genetic program in a cell-specific, timely manner. In the recent years hundreds of papers have been devoted to the bioinformatics, physics and biology of nucleosome positioning. The purpose of this review is to cover a practical aspect of this field, namely to provide a guide to the multitude of nucleosome positioning resources available online. These include almost 300 experimental datasets of genome-wide nucleosome occupancy profiles determined in different cell types and more than 40 computational tools for the analysis of experimental nucleosome positioning data and prediction of intrinsic nucleosome formation probabilities from the DNA sequence. A manually curated, up to date list of these resources will be maintained at http://generegulation.info. 1 Introduction The nucleosome is the basic unit of chromatin compaction, composed of the histone octamer and 146-147 base pairs (bp) of DNA wrapped around it. Nucleosomes can form at any genomic locations, but some DNA sequences have higher affinity to the histone octamer, mostly due to the differential bending properties of the DNA double helix. In addition, nucleosome positioning is cell type-specific, in a sense that the cells of the same organism sharing the same genome can have different nucleosome locations depending on the cell type and state. Interested readers are directed to a number of recent publications reviewing the biological, physical and bioinformatics aspects of these phenomena, which will be outside of the scope of the current work [1-32]. Here we will omit fundamental scientific questions, and will focus on a very practical aspect of the field: which experimental nucleosome positioning datasets already exist, how to generate your own data, and how to compare these with other experimental datasets and bioinformatically predicted nucleosome positions in a given genome? 1. Available experimental datasets Recent high-throughput genome-wide data with respect to nucleosome positioning come from a number of related techniques, which have in common an idea to cut DNA between nucleosomes and map protected DNA regions. The most frequently used method is MNase-seq (chromatin digestion by micrococcal nuclease followed by deep sequencing) [11, 33-35].