Hasić Damir, Tannier Eric
Department of Mathematics, Faculty of Science, University of Sarajevo, 71000, Sarajevo, Bosnia and Herzegovina.
Inria Grenoble Rhône-Alpes, 38334, Montbonnot, France.
J Math Biol. 2019 May;78(6):1981-2014. doi: 10.1007/s00285-019-01331-w. Epub 2019 Feb 15.
Gene tree/species tree reconciliation is a recent decisive progress in phylogenetic methods, accounting for the possible differences between gene histories and species histories. Reconciliation consists in explaining these differences by gene-scale events such as duplication, loss, transfer, which translates mathematically into a mapping between gene tree nodes and species tree nodes or branches. Gene conversion is a frequent and important evolutionary event, which results in the replacement of a gene by a copy of another from the same species and in the same gene tree. Including this event in reconciliation models has never been attempted because it introduces a dependency between lineages, and standard algorithms based on dynamic programming become ineffective. We propose here a novel mathematical framework including gene conversion as an evolutionary event in gene tree/species tree reconciliation. We describe a randomized algorithm that finds, in polynomial running time, a reconciliation minimizing the number of duplications, losses and conversions in the case when their weights are equal. We show that the space of optimal reconciliations includes an analog of the last common ancestor reconciliation, but is not limited to it. Our algorithm outputs any optimal reconciliation with a non-null probability. We argue that this study opens a research avenue on including gene conversion in reconciliation, and discuss its possible importance in biology.
基因树/物种树的和解是系统发育方法中一项近期取得的决定性进展,它考虑到了基因历史和物种历史之间可能存在的差异。和解在于通过基因层面的事件(如复制、丢失、转移)来解释这些差异,这在数学上转化为基因树节点与物种树节点或分支之间的一种映射。基因转换是一种频繁且重要的进化事件,它导致一个基因被来自同一物种且在同一基因树中的另一个基因的拷贝所取代。在和解模型中纳入这一事件从未被尝试过,因为它引入了谱系之间的依赖性,并且基于动态规划的标准算法变得无效。我们在此提出一个新颖的数学框架,将基因转换作为基因树/物种树和解中的一种进化事件纳入其中。我们描述了一种随机算法,在权重相等的情况下,该算法能在多项式运行时间内找到一个使复制、丢失和转换的数量最小化的和解。我们表明,最优和解的空间包含一个类似于最近共同祖先和解的情况,但并不局限于此。我们的算法以非零概率输出任何最优和解。我们认为这项研究开启了一条关于在和解中纳入基因转换的研究途径,并讨论了其在生物学中可能具有的重要性。