RT Journal Article
SR Electronic
T1 Retrieving the topology of chromatin domains from deep sequencing data with correlation functions
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 054049
DO 10.1101/054049
A1 Jana Molitor
A1 Jan-Philipp Mallm
A1 Karsten Rippe
A1 Fabian Erdel
YR 2016
UL http://biorxiv.org/content/early/2016/05/18/054049.abstract
AB Epigenetic modifications and other chromatin features partition the genome on multiple length scales to control its biological function. Some of them like DNA methylation target single bases, whereas others such as heterochromatic histone modifications span regions of several megabases. It has now become a routine task to map chromatin marks by deep sequencing. However, the quantitative assessment and comparison of the topology of chromatin domains and their spatial relationships across data sets without a priori assumptions remains challenging, especially if broad domains are involved. Here, we introduce multi-scale correlation evaluation (MCORE), which uses the fluctuation spectrum of mapped sequencing reads to quantify and compare spatial patterns on multiple length scales in a model-independent manner. We used MCORE to dissect the chromatin domain topology of embryonic stem cells and neural cells by integrating sequencing data from chromatin immunoprecipitation, RNA expression, DNA methylation and chromosome interaction experiments. Further, we constructed network models that reflect the relationships among these features on different genomic scales. We anticipate that MCORE will complement current sequencing evaluation schemes and aid in the design and validation of mechanistic models for chromatin signaling.