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Assessing the limits of restraint-based 3D modeling of genomes and genomic domains
Restraint-based modeling of genomes has been recently explored with the advent of Chromosome Conformation Capture (3C-based) experiments. We previously developed a reconstruction method to resolve the 3D architecture of both prokaryotic and eukaryotic genomes using 3C-based data. These models were c...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402535/ https://www.ncbi.nlm.nih.gov/pubmed/25800747 http://dx.doi.org/10.1093/nar/gkv221 |
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author | Trussart, Marie Serra, François Baù, Davide Junier, Ivan Serrano, Luís Marti-Renom, Marc A. |
author_facet | Trussart, Marie Serra, François Baù, Davide Junier, Ivan Serrano, Luís Marti-Renom, Marc A. |
author_sort | Trussart, Marie |
collection | PubMed |
description | Restraint-based modeling of genomes has been recently explored with the advent of Chromosome Conformation Capture (3C-based) experiments. We previously developed a reconstruction method to resolve the 3D architecture of both prokaryotic and eukaryotic genomes using 3C-based data. These models were congruent with fluorescent imaging validation. However, the limits of such methods have not systematically been assessed. Here we propose the first evaluation of a mean-field restraint-based reconstruction of genomes by considering diverse chromosome architectures and different levels of data noise and structural variability. The results show that: first, current scoring functions for 3D reconstruction correlate with the accuracy of the models; second, reconstructed models are robust to noise but sensitive to structural variability; third, the local structure organization of genomes, such as Topologically Associating Domains, results in more accurate models; fourth, to a certain extent, the models capture the intrinsic structural variability in the input matrices and fifth, the accuracy of the models can be a priori predicted by analyzing the properties of the interaction matrices. In summary, our work provides a systematic analysis of the limitations of a mean-field restrain-based method, which could be taken into consideration in further development of methods as well as their applications. |
format | Online Article Text |
id | pubmed-4402535 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44025352015-04-29 Assessing the limits of restraint-based 3D modeling of genomes and genomic domains Trussart, Marie Serra, François Baù, Davide Junier, Ivan Serrano, Luís Marti-Renom, Marc A. Nucleic Acids Res Computational Biology Restraint-based modeling of genomes has been recently explored with the advent of Chromosome Conformation Capture (3C-based) experiments. We previously developed a reconstruction method to resolve the 3D architecture of both prokaryotic and eukaryotic genomes using 3C-based data. These models were congruent with fluorescent imaging validation. However, the limits of such methods have not systematically been assessed. Here we propose the first evaluation of a mean-field restraint-based reconstruction of genomes by considering diverse chromosome architectures and different levels of data noise and structural variability. The results show that: first, current scoring functions for 3D reconstruction correlate with the accuracy of the models; second, reconstructed models are robust to noise but sensitive to structural variability; third, the local structure organization of genomes, such as Topologically Associating Domains, results in more accurate models; fourth, to a certain extent, the models capture the intrinsic structural variability in the input matrices and fifth, the accuracy of the models can be a priori predicted by analyzing the properties of the interaction matrices. In summary, our work provides a systematic analysis of the limitations of a mean-field restrain-based method, which could be taken into consideration in further development of methods as well as their applications. Oxford University Press 2015-04-20 2015-03-23 /pmc/articles/PMC4402535/ /pubmed/25800747 http://dx.doi.org/10.1093/nar/gkv221 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Computational Biology Trussart, Marie Serra, François Baù, Davide Junier, Ivan Serrano, Luís Marti-Renom, Marc A. Assessing the limits of restraint-based 3D modeling of genomes and genomic domains |
title | Assessing the limits of restraint-based 3D modeling of genomes and genomic domains |
title_full | Assessing the limits of restraint-based 3D modeling of genomes and genomic domains |
title_fullStr | Assessing the limits of restraint-based 3D modeling of genomes and genomic domains |
title_full_unstemmed | Assessing the limits of restraint-based 3D modeling of genomes and genomic domains |
title_short | Assessing the limits of restraint-based 3D modeling of genomes and genomic domains |
title_sort | assessing the limits of restraint-based 3d modeling of genomes and genomic domains |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402535/ https://www.ncbi.nlm.nih.gov/pubmed/25800747 http://dx.doi.org/10.1093/nar/gkv221 |
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