具有单基因重复的单切割或连接模型中的距离和中位数问题。

IF 1.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Algorithms for Molecular Biology Pub Date : 2020-05-04 eCollection Date: 2020-01-01 DOI:10.1186/s13015-020-00169-y
Aniket C Mane, Manuel Lafond, Pedro C Feijao, Cedric Chauve
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引用次数: 3

摘要

背景:在基因组重排算法领域,考虑基因复制的模型经常导致一些难题。例如,虽然在大多数无重复模型中计算成对距离是可处理的,但对于考虑重复基因的这些模型的大多数扩展来说,问题是np完全的。此外,涉及两个以上基因组的问题,如基因组中位数和小简约问题,对于大多数无重复模型来说是难以解决的,但也有一些例外,例如单切割或连接(SCJ)模型。结果:在祖先基因组向后代基因组定向进化的背景下,我们引入了SCJ距离的一种变体,该变体解释了重复基因,其中祖先基因与其后代之间的同源关系是已知的。我们的模型包括两种复制机制:单基因串联复制和单基因环状染色体的产生。我们证明了在该模型中,根据SCJ和单基因复制事件计算有向距离和简化的进化场景可以在线性时间内完成。我们还表明,有向中位数问题对于这个距离是可处理的,而根中位数问题是np完全的,我们假设给定的基因组之一是中位数的祖先。我们还描述了一个整数线性规划来解决这个问题。我们在模拟数据上评估了有向距离和根中值算法。结论:我们的研究结果提供了一个简单的基因组重排模型,将SCJ模型扩展到单基因重复,我们证明了可追溯性和硬度结果的混合。对于np完全有根中值问题,我们设计了一个简单的整数线性规划。我们对有向距离和中值问题的这些算法的公开实现允许在大型实例上有效地解决这些问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The distance and median problems in the single-cut-or-join model with single-gene duplications.

The distance and median problems in the single-cut-or-join model with single-gene duplications.

The distance and median problems in the single-cut-or-join model with single-gene duplications.

The distance and median problems in the single-cut-or-join model with single-gene duplications.

Background: In the field of genome rearrangement algorithms, models accounting for gene duplication lead often to hard problems. For example, while computing the pairwise distance is tractable in most duplication-free models, the problem is NP-complete for most extensions of these models accounting for duplicated genes. Moreover, problems involving more than two genomes, such as the genome median and the Small Parsimony problem, are intractable for most duplication-free models, with some exceptions, for example the Single-Cut-or-Join (SCJ) model.

Results: We introduce a variant of the SCJ distance that accounts for duplicated genes, in the context of directed evolution from an ancestral genome to a descendant genome where orthology relations between ancestral genes and their descendant are known. Our model includes two duplication mechanisms: single-gene tandem duplication and the creation of single-gene circular chromosomes. We prove that in this model, computing the directed distance and a parsimonious evolutionary scenario in terms of SCJ and single-gene duplication events can be done in linear time. We also show that the directed median problem is tractable for this distance, while the rooted median problem, where we assume that one of the given genomes is ancestral to the median, is NP-complete. We also describe an Integer Linear Program for solving this problem. We evaluate the directed distance and rooted median algorithms on simulated data.

Conclusion: Our results provide a simple genome rearrangement model, extending the SCJ model to account for single-gene duplications, for which we prove a mix of tractability and hardness results. For the NP-complete rooted median problem, we design a simple Integer Linear Program. Our publicly available implementation of these algorithms for the directed distance and median problems allow to solve efficiently these problems on large instances.

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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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