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Nucleic Acids Res. 2015 Apr 20;43(7):3465-77. doi: 10.1093/nar/gkv221. Epub 2015 Mar 23.

Assessing the limits of restraint-based 3D modeling of genomes and genomic domains.

Author information

1
EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain.
2
Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain Genome Biology Group, Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain.
3
Universitat Pompeu Fabra (UPF), Barcelona, Spain Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain.
4
EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
5
Gene Regulation, Stem Cells and Cancer Program, Centre for Genomic Regulation (CRG), Barcelona, Spain Genome Biology Group, Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain mmarti@pcb.ub.cat.

Abstract

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.

PMID:
25800747
PMCID:
PMC4402535
DOI:
10.1093/nar/gkv221
[Indexed for MEDLINE]
Free PMC Article

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