Cargando…
Recovering ensembles of chromatin conformations from contact probabilities
The 3D higher order organization of chromatin within the nucleus of eukaryotic cells has so far remained elusive. A wealth of relevant information, however, is increasingly becoming available from chromosome conformation capture (3C) and related experimental techniques, which measure the probabiliti...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3592477/ https://www.ncbi.nlm.nih.gov/pubmed/23143266 http://dx.doi.org/10.1093/nar/gks1029 |
_version_ | 1782262125280886784 |
---|---|
author | Meluzzi, Dario Arya, Gaurav |
author_facet | Meluzzi, Dario Arya, Gaurav |
author_sort | Meluzzi, Dario |
collection | PubMed |
description | The 3D higher order organization of chromatin within the nucleus of eukaryotic cells has so far remained elusive. A wealth of relevant information, however, is increasingly becoming available from chromosome conformation capture (3C) and related experimental techniques, which measure the probabilities of contact between large numbers of genomic sites in fixed cells. Such contact probabilities (CPs) can in principle be used to deduce the 3D spatial organization of chromatin. Here, we propose a computational method to recover an ensemble of chromatin conformations consistent with a set of given CPs. Compared with existing alternatives, this method does not require conversion of CPs to mean spatial distances. Instead, we estimate CPs by simulating a physically realistic, bead-chain polymer model of the 30-nm chromatin fiber. We then use an approach from adaptive filter theory to iteratively adjust the parameters of this polymer model until the estimated CPs match the given CPs. We have validated this method against reference data sets obtained from simulations of test systems with up to 45 beads and 4 loops. With additional testing against experiments and with further algorithmic refinements, our approach could become a valuable tool for researchers examining the higher order organization of chromatin. |
format | Online Article Text |
id | pubmed-3592477 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-35924772013-03-08 Recovering ensembles of chromatin conformations from contact probabilities Meluzzi, Dario Arya, Gaurav Nucleic Acids Res Computational Biology The 3D higher order organization of chromatin within the nucleus of eukaryotic cells has so far remained elusive. A wealth of relevant information, however, is increasingly becoming available from chromosome conformation capture (3C) and related experimental techniques, which measure the probabilities of contact between large numbers of genomic sites in fixed cells. Such contact probabilities (CPs) can in principle be used to deduce the 3D spatial organization of chromatin. Here, we propose a computational method to recover an ensemble of chromatin conformations consistent with a set of given CPs. Compared with existing alternatives, this method does not require conversion of CPs to mean spatial distances. Instead, we estimate CPs by simulating a physically realistic, bead-chain polymer model of the 30-nm chromatin fiber. We then use an approach from adaptive filter theory to iteratively adjust the parameters of this polymer model until the estimated CPs match the given CPs. We have validated this method against reference data sets obtained from simulations of test systems with up to 45 beads and 4 loops. With additional testing against experiments and with further algorithmic refinements, our approach could become a valuable tool for researchers examining the higher order organization of chromatin. Oxford University Press 2013-01 2012-11-10 /pmc/articles/PMC3592477/ /pubmed/23143266 http://dx.doi.org/10.1093/nar/gks1029 Text en © The Author(s) 2012. 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 License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial reuse, 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 Meluzzi, Dario Arya, Gaurav Recovering ensembles of chromatin conformations from contact probabilities |
title | Recovering ensembles of chromatin conformations from contact probabilities |
title_full | Recovering ensembles of chromatin conformations from contact probabilities |
title_fullStr | Recovering ensembles of chromatin conformations from contact probabilities |
title_full_unstemmed | Recovering ensembles of chromatin conformations from contact probabilities |
title_short | Recovering ensembles of chromatin conformations from contact probabilities |
title_sort | recovering ensembles of chromatin conformations from contact probabilities |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3592477/ https://www.ncbi.nlm.nih.gov/pubmed/23143266 http://dx.doi.org/10.1093/nar/gks1029 |
work_keys_str_mv | AT meluzzidario recoveringensemblesofchromatinconformationsfromcontactprobabilities AT aryagaurav recoveringensemblesofchromatinconformationsfromcontactprobabilities |