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Efficient algorithms for the reconciliation problem with gene duplication, horizontal transfer and loss

机译:基因重复,水平转移和丢失的和解问题的高效算法

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Motivation: Gene family evolution is driven by evolutionary events such as speciation, gene duplication, horizontal gene transfer and gene loss, and inferring these events in the evolutionary history of a given gene family is a fundamental problem in comparative and evolutionary genomics with numerous important applications. Solving this problem requires the use of a reconciliation framework, where the input consists of a gene family phylogeny and the corresponding species phylogeny, and the goal is to reconcile the two by postulating speciation, gene duplication, horizontal gene transfer and gene loss events. This reconciliation problem is referred to as duplication-transfer-loss (DTL) reconciliation and has been extensively studied in the literature. Yet, even the fastest existing algorithms for DTL reconciliation are too slow for reconciling large gene families and for use in more sophisticated applications such as gene tree or species tree reconstruction. Results: We present two new algorithms for the DTL reconciliation problem that are dramatically faster than existing algorithms, both asymptotically and in practice. We also extend the standard DTL reconciliation model by considering distance-dependent transfer costs, which allow for more accurate reconciliation and give an efficient algorithm for DTL reconciliation under this extended model. We implemented our new algorithms and demonstrated up to 100 000-fold speed-up over existing methods, using both simulated and biological datasets. This dramatic improvement makes it possible to use DTL reconciliation for performing rigorous evolutionary analyses of large gene families and enables its use in advanced reconciliation-based gene and species tree reconstruction methods.
机译:动机:基因家族的进化受物种,物种复制,水平基因转移和基因丢失等进化事件的驱动,在给定基因家族的进化史中推断这些事件是比较基因组和进化基因组学中的一个基本问题,具有许多重要应用。解决此问题需要使用和解框架,其中输入由基因家族系统发育和相应物种系统发育组成,目标是通过推测物种形成,基因复制,水平基因转移和基因丢失事件来调和两者。此对帐问题称为复制转移损失(DTL)对帐,并且已在文献中进行了广泛研究。但是,即使现有最快的DTL协调算法也无法协调大型基因家族,也无法用于更复杂的应用程序,例如基因树或物种树重建。结果:我们提出了两种新的DTL对帐问题算法,它们在渐近和实践上都比现有算法快得多。我们还考虑了距离相关的传输成本,从而扩展了标准DTL对帐模型,该模型允许更精确的对帐,并在此扩展模型下为DTL对帐提供了有效的算法。我们使用模拟和生物学数据集实施了新算法,并证明了比现有方法快10万倍的速度。这种巨大的改进使得可以使用DTL调节来对大型基因家族进行严格的进化分析,并使其可以用于基于先进和解的基因和物种树重建方法中。

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