Finding local genome rearrangements.

IF 1.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Algorithms for Molecular Biology Pub Date : 2018-05-04 eCollection Date: 2018-01-01 DOI:10.1186/s13015-018-0127-2
Pijus Simonaitis, Krister M Swenson
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引用次数: 6

Abstract

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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寻找局部基因组重排。
背景:基因组重排的双切割和连接(DCJ)模型由于其数学上的简单性和解释改变基因顺序的许多事件的能力而得到了很好的研究。这些研究主要致力于了解将一个基因组转化为另一个基因组的最小长度方案。在本文中,我们寻找的重排方案,最大限度地减少重排的数量,其断点是不可能的,由于一些生物学标准。由于Hi-C实验的出现,一个这样的准则最近变得容易获得,促进了断点区域之间三维空间距离的研究。结果:我们建立了场景所需的最小不可能重排数与在邻接图的某个变换版本上找到最大边不相交循环填充问题之间的联系。这个环节引出了我们的问题的3/2近似和一个精确的整数线性规划公式,我们证明了它是np完全的。我们还介绍了果蝇的实验结果,表明Hi-C数据在用作重排标准时具有信息性。结论:本文提出了一种新的加权DCJ距离问题,该问题在其目标函数中忽略了场景长度。这个问题的解决方案提供了将一个基因序列转化为另一个基因序列所需的不可能移动次数的下界。这个下界有助于研究染色质结构的重排情况,并最终可用于设计具有更一般目标函数的固定参数算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Algorithms for Molecular Biology
Algorithms for Molecular Biology 生物-生化研究方法
CiteScore
2.40
自引率
10.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Algorithms for Molecular Biology publishes articles on novel algorithms for biological sequence and structure analysis, phylogeny reconstruction, and combinatorial algorithms and machine learning. Areas of interest include but are not limited to: algorithms for RNA and protein structure analysis, gene prediction and genome analysis, comparative sequence analysis and alignment, phylogeny, gene expression, machine learning, and combinatorial algorithms. Where appropriate, manuscripts should describe applications to real-world data. However, pure algorithm papers are also welcome if future applications to biological data are to be expected, or if they address complexity or approximation issues of novel computational problems in molecular biology. Articles about novel software tools will be considered for publication if they contain some algorithmically interesting aspects.
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