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Finding local genome rearrangements

BACKGROUND: The double cut and join (DCJ) model of genome rearrangement is well studied due to its mathematical simplicity and power to account for the many events that transform gene order. These studies have mostly been devoted to the understanding of minimum length scenarios transforming one geno...

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Autores principales: Simonaitis, Pijus, Swenson, Krister M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5934872/
https://www.ncbi.nlm.nih.gov/pubmed/29755580
http://dx.doi.org/10.1186/s13015-018-0127-2
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author Simonaitis, Pijus
Swenson, Krister M.
author_facet Simonaitis, Pijus
Swenson, Krister M.
author_sort Simonaitis, Pijus
collection PubMed
description BACKGROUND: The double cut and join (DCJ) model of genome rearrangement is well studied due to its mathematical simplicity and power to account for the many events that transform gene order. These studies have mostly been devoted to the understanding of minimum length scenarios transforming one genome into another. In this paper we search instead for rearrangement scenarios that minimize the number of rearrangements whose breakpoints are unlikely due to some biological criteria. One such criterion has recently become accessible due to the advent of the Hi-C experiment, facilitating the study of 3D spacial distance between breakpoint regions. RESULTS: We establish a link between the minimum number of unlikely rearrangements required by a scenario and the problem of finding a maximum edge-disjoint cycle packing on a certain transformed version of the adjacency graph. This link leads to a 3/2-approximation as well as an exact integer linear programming formulation for our problem, which we prove to be NP-complete. We also present experimental results on fruit flies, showing that Hi-C data is informative when used as a criterion for rearrangements. CONCLUSIONS: A new variant of the weighted DCJ distance problem is addressed that ignores scenario length in its objective function. A solution to this problem provides a lower bound on the number of unlikely moves necessary when transforming one gene order into another. This lower bound aids in the study of rearrangement scenarios with respect to chromatin structure, and could eventually be used in the design of a fixed parameter algorithm with a more general objective function.
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spelling pubmed-59348722018-05-11 Finding local genome rearrangements Simonaitis, Pijus Swenson, Krister M. Algorithms Mol Biol Research BACKGROUND: The double cut and join (DCJ) model of genome rearrangement is well studied due to its mathematical simplicity and power to account for the many events that transform gene order. These studies have mostly been devoted to the understanding of minimum length scenarios transforming one genome into another. In this paper we search instead for rearrangement scenarios that minimize the number of rearrangements whose breakpoints are unlikely due to some biological criteria. One such criterion has recently become accessible due to the advent of the Hi-C experiment, facilitating the study of 3D spacial distance between breakpoint regions. RESULTS: We establish a link between the minimum number of unlikely rearrangements required by a scenario and the problem of finding a maximum edge-disjoint cycle packing on a certain transformed version of the adjacency graph. This link leads to a 3/2-approximation as well as an exact integer linear programming formulation for our problem, which we prove to be NP-complete. We also present experimental results on fruit flies, showing that Hi-C data is informative when used as a criterion for rearrangements. CONCLUSIONS: A new variant of the weighted DCJ distance problem is addressed that ignores scenario length in its objective function. A solution to this problem provides a lower bound on the number of unlikely moves necessary when transforming one gene order into another. This lower bound aids in the study of rearrangement scenarios with respect to chromatin structure, and could eventually be used in the design of a fixed parameter algorithm with a more general objective function. BioMed Central 2018-05-04 /pmc/articles/PMC5934872/ /pubmed/29755580 http://dx.doi.org/10.1186/s13015-018-0127-2 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Simonaitis, Pijus
Swenson, Krister M.
Finding local genome rearrangements
title Finding local genome rearrangements
title_full Finding local genome rearrangements
title_fullStr Finding local genome rearrangements
title_full_unstemmed Finding local genome rearrangements
title_short Finding local genome rearrangements
title_sort finding local genome rearrangements
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5934872/
https://www.ncbi.nlm.nih.gov/pubmed/29755580
http://dx.doi.org/10.1186/s13015-018-0127-2
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