Gene trees inferred from molecular sequence alignments are typically unrooted, and determining the most credible rooting edge is a classical problem in computational biology. One approach to solve this problem is unrooted reconciliation, where the rooting edge is postulated based on the split of the root from a given species tree. In this paper, we propose a novel variant of the gene tree rooting problem, where the gene tree root is inferred using a phylogenetic network of the species present in the gene tree. To obtain the best rooting, unrooted reconciliation can be applied, where the unrooted gene tree is jointly reconciled with a set of splits inferred from the network. However, the exponential size of the set induced by display trees of the network makes this approach computationally prohibitive. To address this, we propose a broader and easier-to-control set of splits based on the structural properties of the network. We then derive exact mathematical formulas for the rooting problem and propose two general rooting algorithms to handle cases where the input network does not meet the initial requirements. Our experimental study based on simulated gene trees and networks demonstrates that our algorithms infer gene tree rootings correctly or with a small error in most cases.

从分子序列比对推断出的基因树通常是无根的，确定最可信的根边是计算生物学中的一个经典问题。解决这个问题的一种方法是无根协调，其中根边是根据给定物种树的根的分裂来假设的。在本文中，我们提出了基因树生根问题的一种新变体，其中使用基因树中存在的物种的系统发育网络来推断基因树根。为了获得最佳的生根，可以应用无根协调，其中无根基因树与从网络推断的一组分割联合协调。然而，由网络显示树引起的集合的指数大小使得这种方法在计算上令人望而却步。为了解决这个问题，我们根据网络的结构特性提出了一组更广泛且更易于控制的分割。然后，我们推导出求根问题的精确数学公式，并提出两种通用的求根算法来处理输入网络不满足初始要求的情况。我们基于模拟基因树和网络的实验研究表明，我们的算法正确地推断出基因树的根部，或者在大多数情况下推断出的误差很小。