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Quantifying the role of steric constraints in nucleosome positioning

Statistical positioning, the localization of nucleosomes packed against a fixed barrier, is conjectured to explain the array of well-positioned nucleosomes at the 5′ end of genes, but the extent and precise implications of statistical positioning in vivo are unclear. We examine this hypothesis quant...

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Detalles Bibliográficos
Autores principales: Rube, H. Tomas, Song, Jun S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3936764/
https://www.ncbi.nlm.nih.gov/pubmed/24288372
http://dx.doi.org/10.1093/nar/gkt1239
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author Rube, H. Tomas
Song, Jun S.
author_facet Rube, H. Tomas
Song, Jun S.
author_sort Rube, H. Tomas
collection PubMed
description Statistical positioning, the localization of nucleosomes packed against a fixed barrier, is conjectured to explain the array of well-positioned nucleosomes at the 5′ end of genes, but the extent and precise implications of statistical positioning in vivo are unclear. We examine this hypothesis quantitatively and generalize the idea to include moving barriers as well as nucleosomes actively packed against a barrier. Early experiments noted a similarity between the nucleosome profile aligned and averaged across genes and that predicted by statistical positioning; however, we demonstrate that aligning random nucleosomes also generates the same profile, calling the previous interpretation into question. New rigorous results reformulate statistical positioning as predictions on the variance structure of nucleosome locations in individual genes. In particular, a quantity termed the variance gradient, describing the change in variance between adjacent nucleosomes, is tested against recent high-throughput nucleosome sequencing data. Constant variance gradients provide support for generalized statistical positioning in ∼50% of long genes. Genes that deviate from predictions have high nucleosome turnover and cell-to-cell gene expression variability. The observed variance gradient suggests an effective nucleosome size of 158 bp, instead of the commonly perceived 147 bp. Our analyses thus clarify the role of statistical positioning in vivo.
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spelling pubmed-39367642014-03-04 Quantifying the role of steric constraints in nucleosome positioning Rube, H. Tomas Song, Jun S. Nucleic Acids Res Computational Biology Statistical positioning, the localization of nucleosomes packed against a fixed barrier, is conjectured to explain the array of well-positioned nucleosomes at the 5′ end of genes, but the extent and precise implications of statistical positioning in vivo are unclear. We examine this hypothesis quantitatively and generalize the idea to include moving barriers as well as nucleosomes actively packed against a barrier. Early experiments noted a similarity between the nucleosome profile aligned and averaged across genes and that predicted by statistical positioning; however, we demonstrate that aligning random nucleosomes also generates the same profile, calling the previous interpretation into question. New rigorous results reformulate statistical positioning as predictions on the variance structure of nucleosome locations in individual genes. In particular, a quantity termed the variance gradient, describing the change in variance between adjacent nucleosomes, is tested against recent high-throughput nucleosome sequencing data. Constant variance gradients provide support for generalized statistical positioning in ∼50% of long genes. Genes that deviate from predictions have high nucleosome turnover and cell-to-cell gene expression variability. The observed variance gradient suggests an effective nucleosome size of 158 bp, instead of the commonly perceived 147 bp. Our analyses thus clarify the role of statistical positioning in vivo. Oxford University Press 2014-02 2013-11-27 /pmc/articles/PMC3936764/ /pubmed/24288372 http://dx.doi.org/10.1093/nar/gkt1239 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computational Biology
Rube, H. Tomas
Song, Jun S.
Quantifying the role of steric constraints in nucleosome positioning
title Quantifying the role of steric constraints in nucleosome positioning
title_full Quantifying the role of steric constraints in nucleosome positioning
title_fullStr Quantifying the role of steric constraints in nucleosome positioning
title_full_unstemmed Quantifying the role of steric constraints in nucleosome positioning
title_short Quantifying the role of steric constraints in nucleosome positioning
title_sort quantifying the role of steric constraints in nucleosome positioning
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3936764/
https://www.ncbi.nlm.nih.gov/pubmed/24288372
http://dx.doi.org/10.1093/nar/gkt1239
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