Evolution through segmental duplications and losses: a Super-Reconciliation approach.

IF 1.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Algorithms for Molecular Biology Pub Date : 2020-05-26 eCollection Date: 2020-01-01 DOI:10.1186/s13015-020-00171-4
Mattéo Delabre, Nadia El-Mabrouk, Katharina T Huber, Manuel Lafond, Vincent Moulton, Emmanuel Noutahi, Miguel Sautie Castellanos
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引用次数: 8

Abstract

The classical gene and species tree reconciliation, used to infer the history of gene gain and loss explaining the evolution of gene families, assumes an independent evolution for each family. While this assumption is reasonable for genes that are far apart in the genome, it is not appropriate for genes grouped into syntenic blocks, which are more plausibly the result of a concerted evolution. Here, we introduce the Super-Reconciliation problem which consists in inferring a history of segmental duplication and loss events (involving a set of neighboring genes) leading to a set of present-day syntenies from a single ancestral one. In other words, we extend the traditional Duplication-Loss reconciliation problem of a single gene tree, to a set of trees, accounting for segmental duplications and losses. Existency of a Super-Reconciliation depends on individual gene tree consistency. In addition, ignoring rearrangements implies that existency also depends on gene order consistency. We first show that the problem of reconstructing a most parsimonious Super-Reconciliation, if any, is NP-hard and give an exact exponential-time algorithm to solve it. Alternatively, we show that accounting for rearrangements in the evolutionary model, but still only minimizing segmental duplication and loss events, leads to an exact polynomial-time algorithm. We finally assess time efficiency of the former exponential time algorithm for the Duplication-Loss model on simulated datasets, and give a proof of concept on the opioid receptor genes.

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通过片段复制和损失的进化:一种超级调和方法。
经典的基因和物种树和解理论,用来推断基因获得和丢失的历史,解释基因家族的进化,假设每个家族都是独立的进化。虽然这种假设对于基因组中相距很远的基因来说是合理的,但对于组合在一起的基因来说就不合适了,因为这些基因更可能是协同进化的结果。在这里,我们介绍了超级调和问题,它包括推断片段复制和丢失事件的历史(涉及一组邻近基因),导致一组来自单一祖先的现代共音。换句话说,我们将传统的单基因树的重复-损失协调问题扩展到一组树,考虑片段重复和损失。超级和解的存在取决于个体基因树的一致性。此外,忽略重排意味着存在也依赖于基因顺序的一致性。我们首先证明重建一个最简洁的超级调和问题(如果有的话)是np困难的,并给出了一个精确的指数时间算法来解决它。或者,我们表明,考虑到进化模型中的重排,但仍然只是最小化片段重复和损失事件,导致一个精确的多项式时间算法。最后,我们在模拟数据集上评估了前一种指数时间算法对重复损失模型的时间效率,并给出了阿片受体基因的概念证明。
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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