Research Repository

Changes of nucleosome positioning and 3D chromatin organization in cell transitions

Clarkson, Chris (2020) Changes of nucleosome positioning and 3D chromatin organization in cell transitions. PhD thesis, Univerisity of Essex.

[img] Text
Thesis_corrections.pdf
Restricted to Repository staff only until 20 March 2023.

Download (8MB) | Request a copy

Abstract

The genome of a eukaryotic cell is stored inside the nucleus in a highly condensed form called chromatin. The basic unit of chromatin is the nucleosome. The positioning of nucleosomes on the DNA determines the accessibility of transcription factors (TFs) and other regulatory molecules. Beyond nucleosome positioning, the higher level of 3D chromatin architecture is constituted by relatively large loops of DNA such as topologically associating domains (TADs) which serve to insulate some loci from the rest of the genome. A major determinant of the chromatin domain boundaries is the architectural protein CTCF that binds to thousands of locations in the genome and changes the chromatin configuration during cell differentiation or cancer development. Chapter 1 of this thesis provides an overview of the field of chromatin folding and a premise of the questions that we later address. Chapter 2 is based on our paper [Clarkson et al. (2019) Nucleic Acids Res. 47, 11181-11196] devoted to CTCF-nucleosome interplay at chromatin boundaries. It reports a new effect: the strength of CTCF binding to DNA is inversely proportional to the average distance between nucleosomes near its binding site. We found that a number of CTCF binding sites that remain bound during the differentiation of mouse embryonic stem cells maintain a relatively short distance between the neighbouring nucleosomes. Furthermore, we observed that CTCF binding sites occur in clusters at TAD boundaries, and proposed a new model of chromatin boundary formation through ordered, asymmetric nucleosome arrays. Chapter 3 documents my work on the connection between nucleosome positioning and chromatin state using machine learning. We developed a general methodology for this task and provided a proof of principle that it can work as a diagnostic tool classifying nucleosome positioning patterns to distinguish samples from peripheral blood of healthy individuals and patients with chronic lymphocytic leukaemia.

Item Type: Thesis (PhD)
Subjects: Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Science and Health > Life Sciences, School of
Depositing User: Christopher Clarkson
Date Deposited: 20 Mar 2020 14:46
Last Modified: 24 Mar 2020 08:28
URI: http://repository.essex.ac.uk/id/eprint/27142

Actions (login required)

View Item View Item