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算法:同时进行纠错和根系重建,以解决基因树协调和基因复制问题。

Algorithms: simultaneous error-correction and rooting for gene tree reconciliation and the gene duplication problem.

机构信息

Institute of Informatics, University of Warsaw, Warsaw, 02-097, Poland.

出版信息

BMC Bioinformatics. 2012 Jun 25;13 Suppl 10(Suppl 10):S14. doi: 10.1186/1471-2105-13-S10-S14.

Abstract

BACKGROUND

Evolutionary methods are increasingly challenged by the wealth of fast growing resources of genomic sequence information. Evolutionary events, like gene duplication, loss, and deep coalescence, account more then ever for incongruence between gene trees and the actual species tree. Gene tree reconciliation is addressing this fundamental problem by invoking the minimum number of gene duplication and losses that reconcile a rooted gene tree with a rooted species tree. However, the reconciliation process is highly sensitive to topological error or wrong rooting of the gene tree, a condition that is not met by most gene trees in practice. Thus, despite the promises of gene tree reconciliation, its applicability in practice is severely limited.

RESULTS

We introduce the problem of reconciling unrooted and erroneous gene trees by simultaneously rooting and error-correcting them, and describe an efficient algorithm for this problem. Moreover, we introduce an error-corrected version of the gene duplication problem, a standard application of gene tree reconciliation. We introduce an effective heuristic for our error-corrected version of the gene duplication problem, given that the original version of this problem is NP-hard. Our experimental results suggest that our error-correcting approaches for unrooted input trees can significantly improve on the accuracy of gene tree reconciliation, and the species tree inference under the gene duplication problem. Furthermore, the efficiency of our algorithm for error-correcting reconciliation is capable of handling truly large-scale phylogenetic studies.

CONCLUSIONS

Our presented error-correction approach is a crucial step towards making gene tree reconciliation more robust, and thus to improve on the accuracy of applications that fundamentally rely on gene tree reconciliation, like the inference of gene-duplication supertrees.

摘要

背景

进化方法越来越受到快速增长的基因组序列信息资源的挑战。进化事件,如基因复制、丢失和深度合并,比以往任何时候都更能解释基因树与实际种系树之间的不一致。通过调用使根基因树与根物种树相一致的最少数量的基因复制和丢失,基因树协调解决了这个基本问题。然而,协调过程对基因树的拓扑错误或错误根非常敏感,而在实践中大多数基因树都不符合这种情况。因此,尽管基因树协调有其承诺,但其实用性受到严重限制。

结果

我们通过同时对无根和错误的基因树进行根化和纠错来引入协调无根和错误基因树的问题,并描述了一种解决该问题的有效算法。此外,我们引入了基因复制问题的纠错版本,这是基因树协调的标准应用。对于基因复制问题的原始版本,我们引入了一种有效的启发式方法。我们的实验结果表明,对于无根输入树,我们的纠错方法可以显著提高基因树协调的准确性,以及基因复制问题下的物种树推断。此外,我们的纠错协调算法的效率能够处理真正的大规模系统发育研究。

结论

我们提出的纠错方法是使基因树协调更健壮的关键步骤,从而提高根本依赖基因树协调的应用程序的准确性,例如基因复制超树的推断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7778/3382441/c421e19db990/1471-2105-13-S10-S14-1.jpg

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