Iterative reconstruction of three-dimensional models of human chromosomes from chromosomal contact data.
BACKGROUND
The entire collection of genetic information resides within the chromosomes, which themselves reside within almost every cell nucleus of eukaryotic organisms. Each individual chromosome is found to have its own preferred three-dimensional (3D) structure independent of the other chromosomes. The structure of each chromosome plays vital roles in controlling certain genome operations, including gene interaction and gene regulation. As a result, knowing the structure of chromosomes assists in the understanding of how the genome functions. Fortunately, the 3D structure of chromosomes proves possible to construct through computational methods via contact data recorded from the chromosome. We developed a unique computational approach based on optimization procedures known as adaptation, simulated annealing, and genetic algorithm to construct 3D models of human chromosomes, using chromosomal contact data.


RESULTS
Our models were evaluated using a percentage-based scoring function. Analysis of the scores of the final 3D models demonstrated their effective construction from our computational approach. Specifically, the models resulting from our approach yielded an average score of 80.41%, with a high of 91%, across models for all chromosomes of a normal human B-cell. Comparisons made with other methods affirmed the effectiveness of our strategy. Particularly, juxtaposition with models generated through the publicly available method Markov chain Monte Carlo 5C (MCMC5C) illustrated the outperformance of our approach, as seen through a higher average score for all chromosomes. Our methodology was further validated using two consistency checking techniques known as convergence testing and robustness checking, which both proved successful.


CONCLUSIONS
The pursuit of constructing accurate 3D chromosomal structures is fueled by the benefits revealed by the findings as well as any possible future areas of study that arise. This motivation has led to the development of our computational methodology. The implementation of our approach proved effective in constructing 3D chromosome models and proved consistent with, and more effective than, some other methods thereby achieving our goal of creating a tool to help advance certain research efforts. The source code, test data, test results, and documentation of our method, Gen3D, are available at our sourceforge site at: http://sourceforge.net/projects/gen3d/.
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. jn9qc@mail.missouri.edu.
Jackson
J
Nowotny
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. sa262@mail.missouri.edu.
Sharif
S
Ahmed
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. lxq35@mail.missouri.edu.
Lingfei
L
Xu
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. oeow39@mail.missouri.edu.
Oluwatosin
O
Oluwadare
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. hannahc9596@gmail.com.
Hannah
H
Chen
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. ndhhfb@mail.missouri.edu.
Noelan
N
Hensley
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. tuantrieu@mail.missouri.edu.
Tuan
T
Trieu
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. rcrg4@mail.missouri.edu.
Renzhi
R
Cao
Department of Computer Science, Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. chengji@missouri.edu.
Jianlin
J
Cheng
D001402:B-Lymphocytes; D002877:Chromosomes, Human / Q000235:genetics*; D016678:Genome / Q000235:genetics*; D006801:Humans; D008962:Models, Theoretical; D016415:Sequence Alignment; D013698:Templates, Genetic