Computational analysis of nucleosome positioning datasets

Monomer extension (ME) is an established <i>in vitro </i>experimental technique which maps the positions adopted by reconstituted core histone octamers on a defined DNA sequence. It provides quantitative positioning information, at high resolution, over long continuous stretches of DNA s...

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Main Author: Fraser, Ross Macdonald
Published: University of Edinburgh 2006
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Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.651095
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spelling ndltd-bl.uk-oai-ethos.bl.uk-6510952018-05-12T03:19:47ZComputational analysis of nucleosome positioning datasetsFraser, Ross Macdonald2006Monomer extension (ME) is an established <i>in vitro </i>experimental technique which maps the positions adopted by reconstituted core histone octamers on a defined DNA sequence. It provides quantitative positioning information, at high resolution, over long continuous stretches of DNA sequence. This technique has been employed to map several genes: globin genes (8 kbp), the beta-lactoglobulin gene (10 kbp) and various imprinting genes (4 kbp). This study explores and analyses this unique dataset, utilising computational and stochastic techniques, to gain insight into the potential influence of nucleosomal positioning on the structure and function of chromatin. The first section of this thesis expands upon prior analyses, explores general features of the dataset using common bioinformatics tools, and attempts to relate the quantitative positioning information from ME to data from other commonly used competitive reconstitution protocols. Finally, evidence of a correlation between the <i>in vitro </i>ME dataset and <i>in vivo </i>nucleosome positions for the beta-lactoglobulin gene region is presented. The second section presents the development of a novel method for the analysis of ME maps using Monte Carlo simulation methods. The goal was to use the ME datasets to simulate a higher order chromatin fibre, taking advantage of the long-range and quantitative nature of the ME datasets. The Monte Carlo simulations have allowed new insights to be gleaned from the datasets. Analysis of the beta-lactoglobulin positioning map indicates the potential for discrete disruption of nucleosomal organisation, at specific physiological nucleosome densities, over regions found to have unusual chromatin structure <i>in vivo. </i>This suggests a correspondence between the quantitative histone octamer positioning information <i>in vitro </i>and the positioning of nucleosomes <i>in vivo.</i> Taken together, these studies lend weight to the hypothesis that necleosome positioning information encoded within DNA plays a fundamental role in directing chromatin structure <i>in vivo</i>.572.8University of Edinburghhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.651095http://hdl.handle.net/1842/29110Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 572.8
spellingShingle 572.8
Fraser, Ross Macdonald
Computational analysis of nucleosome positioning datasets
description Monomer extension (ME) is an established <i>in vitro </i>experimental technique which maps the positions adopted by reconstituted core histone octamers on a defined DNA sequence. It provides quantitative positioning information, at high resolution, over long continuous stretches of DNA sequence. This technique has been employed to map several genes: globin genes (8 kbp), the beta-lactoglobulin gene (10 kbp) and various imprinting genes (4 kbp). This study explores and analyses this unique dataset, utilising computational and stochastic techniques, to gain insight into the potential influence of nucleosomal positioning on the structure and function of chromatin. The first section of this thesis expands upon prior analyses, explores general features of the dataset using common bioinformatics tools, and attempts to relate the quantitative positioning information from ME to data from other commonly used competitive reconstitution protocols. Finally, evidence of a correlation between the <i>in vitro </i>ME dataset and <i>in vivo </i>nucleosome positions for the beta-lactoglobulin gene region is presented. The second section presents the development of a novel method for the analysis of ME maps using Monte Carlo simulation methods. The goal was to use the ME datasets to simulate a higher order chromatin fibre, taking advantage of the long-range and quantitative nature of the ME datasets. The Monte Carlo simulations have allowed new insights to be gleaned from the datasets. Analysis of the beta-lactoglobulin positioning map indicates the potential for discrete disruption of nucleosomal organisation, at specific physiological nucleosome densities, over regions found to have unusual chromatin structure <i>in vivo. </i>This suggests a correspondence between the quantitative histone octamer positioning information <i>in vitro </i>and the positioning of nucleosomes <i>in vivo.</i> Taken together, these studies lend weight to the hypothesis that necleosome positioning information encoded within DNA plays a fundamental role in directing chromatin structure <i>in vivo</i>.
author Fraser, Ross Macdonald
author_facet Fraser, Ross Macdonald
author_sort Fraser, Ross Macdonald
title Computational analysis of nucleosome positioning datasets
title_short Computational analysis of nucleosome positioning datasets
title_full Computational analysis of nucleosome positioning datasets
title_fullStr Computational analysis of nucleosome positioning datasets
title_full_unstemmed Computational analysis of nucleosome positioning datasets
title_sort computational analysis of nucleosome positioning datasets
publisher University of Edinburgh
publishDate 2006
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.651095
work_keys_str_mv AT fraserrossmacdonald computationalanalysisofnucleosomepositioningdatasets
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