Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process

Greenman, C. D., Cooke, S. L., Marshall, J., Stratton, M. R. and Campbell, P. J. (2016) Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process. Journal of Mathematical Biology, 72 (1). pp. 47-86. ISSN 0303-6812

[thumbnail of Greenman et al]
PDF (Greenman et al) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview


Breakage-Fusion-Bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. The process has parallels with paper folding sequences that arise when a piece of paper is folded several times and then unfolded. Here we adapt such methods to study the breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are 2^(n(n-1)/2) qualitatively distinct evolutions involving n breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the fold positions, to determine evolution likelihoods, and also describe how amplicons become localised. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples.

Item Type: Article
Additional Information: © The Author(s) 2015. This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
Uncontrolled Keywords: sdg 3 - good health and well-being ,/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being
Faculty \ School: Faculty of Science > School of Natural Sciences
Faculty of Science > School of Computing Sciences

UEA Research Groups: Faculty of Science > Research Groups > Computational Biology
Related URLs:
Depositing User: Pure Connector
Date Deposited: 09 Jun 2014 20:34
Last Modified: 01 May 2024 09:30
DOI: 10.1007/s00285-015-0875-2


Downloads per month over past year

Actions (login required)

View Item View Item