Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-23712 - High-throughput sequencing reveals a simple model of nucleosome energetics
Submitted on 18 August 2010, released on 20 August 2010, last updated on 2 June 2014
Escherichia coli, Saccharomyces cerevisiae
We use nucleosome maps obtained by high-throughput sequencing to study sequence specificity of intrinsic histone-DNA interactions. In contrast with previous approaches, we employ an analogy between a classical one-dimensional fluid of finite-size particles in an arbitrary external potential and arrays of DNA-bound histone octamers. We derive an analytical solution to infer free energies of nucleosome formation directly from nucleosome occupancies measured in high-throughput experiments. The sequence-specific part of free energies is then captured by fitting them to a sum of energies assigned to individual nucleotide motifs. We have developed hierarchical models of increasing complexity and spatial resolution, establishing that nucleosome occupancies can be explained by systematic differences in mono- and dinucleotide content between nucleosomal and linker DNA sequences, with periodic dinucleotide distributions and longer sequence motifs playing a secondary role. Furthermore, similar sequence signatures are exhibited by control experiments in which genomic DNA is either sonicated or digested with micrococcal nuclease in the absence of nucleosomes, making it possible that current predictions based on highthroughput nucleosome positioning maps are biased by experimental artifacts. Included are raw (eland) and mapped (wig) reads. The mapped reads are provided in eland and wiggle formats, and the raw reads are included in the eland file. This series includes only Mnase control data. The sonicated control is part of this already published accession, as is a in vitro nucleosome map: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15188 We also studied data (in vitro and in vivo maps as well as a model) from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13622 and from: http://www.ncbi.nlm.nih.gov/sra/?term=SRA001023
ChIP-seq, ChIP-seq by high throughput sequencing
George Locke <email@example.com>, Alexandre V Morozov, Denis Tolkunov, Kevin Struhl, Zarmik Moqtaderi